characterization of dickeya dianthicola and pectobacterium
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Characterization of Dickeya dianthicola and Pectobacterium Characterization of Dickeya dianthicola and Pectobacterium
parmentieri Causing Blackleg and Soft Rot on Potato parmentieri Causing Blackleg and Soft Rot on Potato
Tongling Ge University of Maine, [email protected]
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CHARACTERIZATION OF DICKEYA DIANTHICOLA AND PECTOBACTERIUM
PARMENTIERI CAUSING BLACKLEG AND SOFT ROT ON POTATO
By
Tongling Ge
B.S. Shandong Agricultural University, China 2014
M.S. China Agricultural University, China 2016
A DISSERTATION
Submitted in Partial Fulfillment of the
Requirements for the Degree of
Doctor of Philosophy
(in Ecology and Environmental Sciences)
The Graduate School
The University of Maine
May 2021
Advisory Committee:
Jianjun Hao, Associate Professor of Plant Pathology, School of Food and Agriculture, Advisor
Robert P. Larkin, Research Plant Pathologist (USDA-ARS)
Gregory Porter, Professor of Crop Ecology and Management, School of Food and Agriculture
Seanna L. Annis, Associate Professor of Mycology, School of Biology and Ecology
Ek Han Tan, Assistant Professor of Plant Genetics, School of Biology and Ecology
Copyright 2021 Tongling Ge
CHARACTERIZATION OF DICKEYA DIANTHICOLA AND PECTOBACTERIUM
PARMENTIERI CAUSING BLACKLEG AND SOFT ROT ON POTATO
By Tongling Ge
Dissertation Advisor: Dr. Jianjun Hao
An Abstract of the Dissertation Presented
in Partial Fulfillment of the Requirements for the
Degree of Doctor of Philosophy
(in Ecology and Environmental Sciences)
May 2021
Potato blackleg and soft rot (PBSR), which can be caused by Dickeya spp. and
Pectobacterium spp., is a serious problem worldwide. The recent outbreak of PBSR in the
Northeastern USA, caused primarily by D. dianthicola, has resulted in significant economic
losses since 2015. This seedborne disease is highly associated with and therefore spread by seed
tuber distribution. To understand how the outbreak occurred and where the pathogen originated,
a total of 1204 potato samples were collected from 11 northeastern states from 2015 to 2020. All
the samples were processed for bacterial isolation and DNA extraction. Dickeya dianthicola and
P. parmentieri were detected using conventional polymerase chain reaction (PCR). Dickeya
dianthicola and P. parmentieri were found in 38.1% and 53.3% of the samples, respectively, and
20.6% of samples contained both D. dianthicola and P. parmentieri. Seventeen isolates of D.
dianthicola were obtained from the samples and classified into three genotypes (Type I, II, III).
Results based on 258 samples showed that Maine mainly had Type I but no Type III, while Type
II appeared to be distributed throughout the Northeastern USA. By pan-genomic analysis, D.
dianthicola strains collected worldwide were classified into eight distinguished clades. Type I
strains had an extraordinarily high homogeneity and distinct discrimination from other countries,
indicating a single-strain population. Virulence-related systems, such as plant cell-wall degrading
enzymes, flagellar and chemotaxis related features, two-component regulatory system, and type
I/II/III secretion systems were highly conserved, but type IV/VI secretion systems varied, in
which type I strain had an additional set T4SS cluster, implying more aggressiveness and
virulence. Thus, the PBSR outbreak was proposed to be associated with a new strain derived by
mutation.
Bacterial communities were analyzed on the samples using Illumina sequencing targeting
on the V3-V4 region of 16S rRNA gene. Genera Dickeya or Pectobacterium prevailed in the
microbial community when they each existed alone, while Dickeya surpassed Pectobacterium
when they coexisted. Among the pathogen complex, D. dianthicola was the only species in the
Dickeya genus, while species varied in the Pectobacterium genus, with P. parmentieri, P.
polaris, P. carotovora subsp. carotovora, P. carotovora subsp. odoriferum being the most
prevalent presumptive species. Isolates of the four presumptive species and P. c. subsp.
brasiliensis were identified by sequencing the gapA gene and were confirmed to be pathogenic
on potatoes. Thus, PBSR was caused by intergeneric or intrageneric species of Dickeya and
Pectobacterium that contribute collectively to the disease complex. To further investigate the
relationship between the two bacterial species and their interaction, field trials were established.
Three varieties of potato seed pieces were inoculated with bacterial suspensions of D.
dianthicola and planted in the field. Two-year results showed that there was a significant linear
correlation (P < 0.01) between relative yield loss and percentage of inoculated seed pieces.
Furthermore, D. dianthicola was more virulent than P. parmentieri in the field, but the co-
inoculation of the two species resulted in increased disease severity compared to single-species
inoculation with either pathogen.
iii
DEDICATION
Back in the summer of 2016, I opened a new chapter at the University of Maine
(UMaine), with the beginning of a one-year work exchange in Dr. Hao’s lab. However, I stayed
here for five years as I gradually got into the spirit of life and research at UMaine. It was unlikely
to happen without the support and encouragement from my parents Ensheng Ge, Xiu’e Wang,
and my husband Shenghua Zhou. Their sacrifices allowed me to concentrate on my study and
research. The best possession that my parents gave to me was the instruction of being steadfast in
my work, which contributed so much toward conducting my research. I will cherish this
personality trait though my whole life. I also appreciate the patient waiting and ‘virtual
accompany’ of my husband. If I had any success, I would give half of the credit to him. We were
pursuing our dreams in both ends of the earth and never give up our relationship to each other. I
am looking forward to the new life when we reunite.
I love you all, as always!
iv
ACKNOWLEGEMENTS
The first to be acknowledged is my former advisor Dr. Laixin Luo who supported me to
go to Maine. I would like to express the deepest appreciation to my advisor Dr. Jianjun Hao for
having me in his program. My life has changed since and I am constantly improving myself both
in academia and personal growth because of his patience, support, and guidance. A special
“thank you” goes to Dr. Steven B. Johnson for his all-time and all-way support, constant
encouragement and expert guidance. The project would not have been possible without the
precious samples he provided and managed. Being a thesis committee member, Dr. Robert
Larkin has contributed to this project in multiple ways including experimental design,
manuscript revision and additional efforts in technical support. I sincerely thank my other
committee members Dr. Gregory Porter, Dr. Seanna Annis, Dr. Ek Han Tan and Dr. John Singer,
for their encouragement, advice and patience throughout my graduate study. Although it’s
unfortunate that Dr. Singer could not witness my defense, I feel his inspiration is still in me. I
have received a great deal of support and assistance from members of Hao lab, Dr. Helen Jiang,
Nayara Marangoni, Alice Chesley, Fatemeh Ekbataniamiri, Andrea Hain, Kedi Li and Sylvia
Zhang. I appreciate their wonderful collaboration and friendship. Special thanks also go to
Elbridge Giggie, the most experienced and respected field technician in supporting my project. I
would like to thank Bradly Libby who helped in my greenhouse work. I am thankful that Patty
Singer has provided me a great amount of support in DNA sequencing. With a special mention to
Lihua Yang, I am very appreciative for ‘Mom’-like care, which made my life much easier and
happier without being homesick. I would never forget my special friend Val Kinerson who has
unselfishly offered me English lessons for years. A very special gratitude goes out to Maine
Potato Board, USDA-ARS, and USDA-NIFA-SCRI for providing the funding for my study.
v
TABLE OF CONTENTS
DEDICATION.............................................................................................................................. iii
ACKNOWLEGEMENTS ........................................................................................................... iv
LIST OF TABLES ....................................................................................................................... ix
LIST OF FIGURES ..................................................................................................................... xi
CHAPTER 1 .................................................................................................................................. 1
LITERATURE REVIEW ............................................................................................................ 1
1.1 Potato ..................................................................................................................................... 1
1.1.1 Potato production ............................................................................................................ 1
1.1.2 Biology and physiology of potato growth ...................................................................... 2
1.2 Potato diseases....................................................................................................................... 3
1.3 Blackleg and soft rot of potato .............................................................................................. 6
1.3.1 Disease symptoms .......................................................................................................... 6
1.3.2 Disease cycle .................................................................................................................. 7
1.3.3 The occurrence of PBSR worldwide and outbreaks in the US ....................................... 9
1.3.4 The pathogens of PBSR ................................................................................................ 10
1.3.4.1 Taxonomy of PBSR pathogens .............................................................................. 10
1.3.4.2 Host range .............................................................................................................. 13
1.3.4.3 Pathogenesis of PBSR pathogens .......................................................................... 16
1.3.5 Management of PBSR .................................................................................................. 18
1.3.5.1 Exclusion................................................................................................................ 18
1.3.5.2 Resistant varieties .................................................................................................. 19
1.3.5.3 Protection ............................................................................................................... 20
1.4 Microbiomes........................................................................................................................ 21
1.4.1 Plant microbiome .......................................................................................................... 22
1.4.2 Plant pathobiome .......................................................................................................... 23
1.4.3 Microbial interactions ................................................................................................... 24
1.4.3.1 Competition and coexistence ................................................................................. 25
vi
1.4.3.2 Cooperation and synergism.................................................................................... 26
1.4.4 Sequencing-based methods for studying microbiomes ................................................ 27
1.5 Objectives ............................................................................................................................ 29
CHAPTER 2 ................................................................................................................................ 31
GENOTYPING DICKEYA DIANTHICOLA CAUSING POTATO BLACKLEG AND
SOFT ROT ASSOCIATED WITH INOCULUM GEOGRAPHY IN THE UNITED
STATES ....................................................................................................................................... 31
ABSTRACT .............................................................................................................................. 31
2.1 INTRODUCTION ............................................................................................................... 32
2.2 MATERIALS AND METHODS ........................................................................................ 34
2.2.1 Sample collection ......................................................................................................... 34
2.2.2 Pathogen isolation......................................................................................................... 35
2.2.3 Pathogen detection and identification........................................................................... 36
2.2.4 Fingerprinting analysis ................................................................................................. 36
2.2.5 Primer design for genotyping ....................................................................................... 37
2.2.6 Phylogenetic analysis ................................................................................................... 37
2.3 RESULTS............................................................................................................................ 38
2.3.1 Disease detection and pathogen isolation ..................................................................... 38
2.3.2 Genotyping by fingerprinting and DNA sequencing of D. dianthicola ....................... 40
2.3.3 Identification of genotypes of D. dianthicola ............................................................... 46
2.4 DISCUSSION ..................................................................................................................... 51
CHAPTER 3 ................................................................................................................................ 55
PANGENOMIC ANALYSIS OF DICKEYA DIANTHICOLA STRAINS REVEALS THE
OUTBREAK OF BLACKLEG AND SOFT ROT ON POTATO IN USA ........................... 55
ABSTRACT .............................................................................................................................. 55
3.1 INTRODUCTION ............................................................................................................... 56
3.2 MATERIALS AND METHODS ........................................................................................ 59
vii
3.2.1 Bacterial strains ............................................................................................................ 59
3.2.2 Whole genome sequencing (WGS) and assembly ........................................................ 61
3.2.3 Genome annotation ....................................................................................................... 61
3.2.4 Pangenome analysis ...................................................................................................... 61
3.2.5 Comparison among USA strains of D. dianthicola genomes ....................................... 62
3.3 RESULTS............................................................................................................................ 63
3.3.1 Genomic assemblies ..................................................................................................... 63
3.3.2 Pangenome.................................................................................................................... 65
3.3.3 SNPs-based phylogeny ................................................................................................. 67
3.3.4 Analyses of USA strains ............................................................................................... 69
3.4 DISCUSSION ..................................................................................................................... 75
CHAPTER 4 ................................................................................................................................ 80
PATHOGEN COMPLEX AND MICROBIAL ASSOCIATION OF POTATO
BLACKLEG AND SOFT ROT IN NORTHEASTERN AMERICA .................................... 80
ABSTRACT .............................................................................................................................. 80
4.1 INTRODUCTION ............................................................................................................... 81
4.2 MATERIALS AND METHODS ........................................................................................ 83
4.2.1. Disease samples ........................................................................................................... 83
4.2.2 Metagenomic sequencing ............................................................................................. 84
4.2.3 Bacterial isolation and identification ............................................................................ 84
4.2.4 Bacterial isolation and identification ............................................................................ 85
4.2.5 Pathogenicity assay....................................................................................................... 86
4.2.6 Bacterial growth on CVP medium ................................................................................ 87
4.3 RESULTS............................................................................................................................ 88
4.3.1 Bacterial communities associated with PBSR .............................................................. 88
4.3.2 Distribution of Dickeya and Pectobacterium spp. ........................................................ 91
4.3.3 Presumptive bacterial species in genera Dickeya and Pectobacterium ........................ 94
4.3.4 Pathogenicity and growth of Pectobacterium spp. ....................................................... 97
4.4 DISCUSSION ................................................................................................................... 102
viii
CHAPTER 5 .............................................................................................................................. 105
INTERACTION BETWEEN DICKEYA DIANTHICOLA AND PECTOBACTERIUM
PARMENTIERI IN POTATO INFECTION OF POTATO UNDER FIELD CONDITIONS
..................................................................................................................................................... 105
ABSTRACT ............................................................................................................................ 105
5.1 INTRODUCTION ............................................................................................................. 106
5.2 MATERIALS AND METHODS ...................................................................................... 108
5.2.1 Frequency and distribution of Dickeya dianthicola and Pectobacterium parmentieri in
naturally infected potato ...................................................................................................... 108
5.2.2 Tuber inoculation using vacuum infiltration .............................................................. 109
5.2.3 Effects of bacterial inoculation on potato growth ...................................................... 109
5.2.4 Interaction between D. dianthicola and P. parmentieri in potato infection ............... 110
5.2.5 Statistical analysis....................................................................................................... 111
5.3 RESULTS.......................................................................................................................... 111
5.3.1 Frequency and distribution of Dickeya dianthicola and Pectobacterium parmentieri in
naturally infected potato ...................................................................................................... 111
5.3.2 Effects of bacterial inoculation on potato growth ...................................................... 113
5.3.3 Interaction between D. dianthicola and P. parmentieri in potato infection ............... 113
5.4 DISCUSSION ................................................................................................................... 118
DISSERTATION SUMMARY ................................................................................................ 122
REFERENCES .......................................................................................................................... 124
BIOGRAPHY OF THE AUTHOR ......................................................................................... 152
ix
LIST OF TABLES
Table 1-1. Development of etiology and taxonomy of blackleg and soft rot bacteria. ................. 12
Table 1-2. Confirmed hosts of Dickeya spp. and Pectobacterium spp. causing blackleg and soft
rot of potato. .................................................................................................................................. 15
Table 2-1. Detection of Dickeya dianthicola in potato samples collected from Northeastern US,
and a smaller amount from Midwestern and Southern regions. ................................................... 39
Table 2-2. Dickeya dianthicola isolates obtained in this study. .................................................. 40
Table 2-3. Dickeya dianthicola strains retrieved from NCBI database. ....................................... 42
Table 2-4. Primers (F: forward; R: reversed) used for genotypic analysis of Dickeya dianthicola.
....................................................................................................................................................... 46
Table 2-5. Genotype detection of Dickeya dianthicola strains using polymerase chain reaction
with primers Trac_4, Anti_1, and DIA-A. .................................................................................... 48
Table 3-1. Dickeya dianthicola strains used in this study. ........................................................... 60
Table 3-2. Genome statistics of Dickeya dianthicola strains. ....................................................... 64
Table 4-1. Bacterial detection in potato samples using polymerase chain reaction (PCR) with
primers pelADE targeting on Dickeya spp. and PEC targeting on both Dickeya and
Pectobacterium spp. ...................................................................................................................... 83
Table 4-2. Dickeya and Pectobacterium spp. strains used for pathogen-bacteria interactions. .... 88
Table 4-3. Relative abundance (%) of shared and exclusive genera of bacteria in four groups (D,
DP, P, and N) of potato samples showing symptoms of blackleg and soft rot. ............................ 92
Table 4-4. Relative abundance (%) of shared and exclusive genera of bacteria in four groups (D,
DP, P, and N) of potato samples showing symptoms of blackleg and soft rot. ............................ 95
x
Table 4-5. Cavity diameter (cm) of bacterial species belonging to genera Dickeya and
Pectobacterium estimated by measuring the colony diameter on crystal violet pectate agar plates
incubated at 28 C in darkness for 24 and 48 hours. .................................................................. 101
Table 5-1. Detection of Dickeya and Pectobacterium spp. in symptomatic potato stems or tubers
using polymerase chain reaction (PCR). ..................................................................................... 112
Table 5-2. Chi-square test on tissue distribution of Dickeya dianthicola (DDi) and
Pectobacterium parmentieri (PPa) on potato tissues showing blackleg and soft rot symptoms. 112
Table 5-3. Effects of infection level of seed pieces with Dickeya dianthicola on yield and
emergence of potato in 2020. ...................................................................................................... 114
Table 5-4. Effects of seed tuber inoculation with Dickeya dianthicola (DDi), Pectobacterium
parmentieri (PPa) and non-inoculated (NI) on emergence and yield of potato varieties in years
2018 and 2019. ............................................................................................................................ 118
xi
LIST OF FIGURES
Figure 1-1. Potato production in the United States (USDA 2019). ................................................ 2
Figure 1-2. Symptoms of blackleg and soft rot of potato.. ............................................................. 7
Figure 1-3. Flowchart of the chapters. .......................................................................................... 30
Figure 2-1. Gel electrophoresis of BOX PCR on Dickeya dianthicola strains ............................. 43
Figure 2-2. Phylogenetic tree using maximum-likelihood analysis on Dickeya dianthicola strains
collected in this study.................................................................................................................... 44
Figure 2-3. Phylogenetic tree using maximum-likelihood analysis on Dickeya dianthicola strains
collected in this study and NCBI .................................................................................................. 45
Figure 2-4. Multiple genome analysis of Dickeya dianthicola strains using MAUVE for
identifying a region for primer design. ......................................................................................... 47
Figure 2-5. Genotypic distribution of Dickeya dianthicola in the Northeastern United States from
2015 to 2019. ................................................................................................................................ 50
Figure 3-1. Pangenome statistics of 32 Dickeya dianthicola strains. ........................................... 66
Figure 3-2. Geographic and phylogenetic relationship of Dickeya dianthicola strains used in this
study. ............................................................................................................................................. 68
Figure 3-3. Whole genome alignment and comparison of orthologous genes from clades I, II and
III of Dickeya dianthicola from USA. .......................................................................................... 70
Figure 3-4. BLAST Ring Image Generator (BRIG) analysis of genomes of Dickeya dianthicola
strains clustered in clades I, II and III against reference strain ME23. ......................................... 71
Figure 3-5. Schematic map of type IV secretion system in clades I, II and III of Dickeya
dianthicola from USA................................................................................................................... 73
xii
Figure 3-6. Schematic map of type VI secretion system in clades I, II and III of Dickeya
dianthicola .................................................................................................................................... 74
Figure 4-1. Number of operational taxonomic unit (OTU) and Shannon evenness index of
bacterial community in potato tissues. .......................................................................................... 90
Figure 4-3. Relative abundances of Dickeya and Pectobacterium spp. by geographic locations or
states (A and C) and sample groups (B and D) of PBSR. ............................................................ 93
Figure 4-4. Phylogenetic tree constructed based on partial sequences the gapA gene (850 bp)
using maximum-likelihood algorithm with strains of Pectobacterium spp., including P.
carotovora subsp. odoriferum (PCO), P. polaris (PPO), P. parmentieri (PPA), P. carotovora
subsp. carotovora (PCC), and P. carotovora subsp. brasiliensis (PCB) ...................................... 98
Figure 4-5. Pathogenicity test of Pectobacterium spp. Species include P. carotovora subsp.
brasiliensis (PCB), P. carotovora subsp. odoriferum (PCO), P. parmentieri (PPA), and P.
polaris (PPO) on potato ‘Lamoka’ stems ..................................................................................... 99
Figure 4-6. Pathogenicity test of Pectobacterium spp. Species include P. carotovora subsp.
brasiliensis (PCB), P. carotovora subsp. odoriferum (PCO), P. parmentieri (PPA), and P.
polaris (PPO) on potato ‘Lamoka’ tubers. .................................................................................. 100
Figure 5-1. Regression analysis between relative emergence loss/relative yield loss and infection
percentage of potato. ................................................................................................................... 115
Figure 5-2. Disease progress of blackleg in potato ‘Lamoka’, ‘Atlantic’ and ‘Shepody’ grown
from seed pieces inoculated with either Dickeya dianthicola (DDi), Pectobacterium parmentieri
(PPa), or DDi + PPa under field conditions in 2018 (upper panels) and 2019 (bottom panels).
Non-inoculated (NI) plants were used for control. ..................................................................... 116
1
CHAPTER 1
LITERATURE REVIEW
1.1 Potato
1.1.1 Potato production
Potato (Solanum tuberosum L.) is the most important vegetable crop in the world,
ranking number four as a main food crop, following rice (Oryza sativa L.), wheat (Triticum
aestivum L.) and corn (Zea mays L.), feeding a big part of the global population (Johnson 2008).
Potato originated from the Andes Mountains of South America (Salaman and Burton 1985), and
was introduced to Europe with Spain being the first entry port as early as 1576 (Brown 1993). In
1719, potato was brought to the United States of America (USA) from Ireland and was first
grown in New Hampshire (Brown 1993). Due to its adaptation to temperate growing conditions,
potatoes have been grown in over 100 countries throughout the world (Hijmans 2001). The
popularity and importance of potato as a food crop is because it produces greater nutrition on
smaller amounts of land than most other crops, and has high food value, therefore can be used as
a staple food (F. A. O. 2008).
USA is the fifth largest potato producer in the world, following China, India, Russia, and
Ukraine (Hijmans 2001). As in many other countries, potato is the top vegetable crop in the US,
and its importance has been documented by the US Department of Agriculture since 1866. There
are three growing seasons for potato nationwide in USA, depending on the location, including
spring, summer and fall, with the usual time of harvest being January to June, July to mid-
September, and August to November respectively (USDA 2019). According to the latest potato
report, 92% of the total production or 90% of the harvested area in 2018 came from the fall
season, and the total potato production totaled 450 million cwt, with harvested area of 1.01
2
million acres (USDA 2019). Production from the spring and summer seasons each make up 4%
of the total (USDA 2019).
Idaho and Washington are the top two US states in potato production and harvested area,
and together produce half of the total US potato crop (Figure 1.1). Potato production in the state
of Maine ranked the 10th in 2018, while the harvested area ranked 6th (Figure 1.1). Maine has
48,500 acres of harvested potato with total production of 15 million cwt, 67% of which is used
for processing, 22% for seed and 11% for table stock (NASS 2018).
Figure 1-1. Potato production in the United States (USDA 2019).
1.1.2 Biology and physiology of potato growth
A potato crop goes through several stages, including sprout development, vegetative
growth, tuber initiation, tuber bulking, and tuber maturation (Dean 1994; Thornton 2020).
Potato tubers are dormant due to hormonal control, after first being harvested, and it takes
several weeks or months to break the dormancy. Under favorable environmental conditions (e.g.,
0
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3
soil temperature above 64 F), potato tubers are ready to sprout and grow once they break
dormancy. Lenticels on the surface of potato tubers provide pathways for gas exchange with the
outside, and the activities of lenticels are affected by soil water content (Adams 1975b;
Wigginton 1973). Lenticels enlarge in soil with high water content, which favors entry of some
opportunistic pathogens (Adams 1975a; Adams and Lapwood 1978). Mother (seed) tubers
provide nutrition for initial growth before the young plants have a well-established root system
(Davies 1984). Any seed-borne pathogens can be transported to plants during this period.
Elongation of stems and growth of leaves, along with a well-established root system constitute a
sophisticated system of nutrition exchange and maintain healthy plant establishment. Under
appropriate growing conditions, daughter tubers start to initiate from the tips of stolon and
rapidly bulk. Interruption of the leaf canopy (damage caused by foliar diseases), which produce
photosynthate, can result in reduced tuber growth rates (Tekalign and Hammes 2005). Excessive
irrigation and inappropriate nutrient management can also affect tuber growth, resulting in
greater susceptibility to tuber diseases (Ojala et al. 1990). Tubers are close to mature as potato
vines die. During tuber maturation, skin or periderm thickens and hardens, which can block entry
of pathogens to the tuber (Singh et al. 2020). Properly matured tubers also have greater
resistance to pathogens in storage. However, tubers will have higher respiration rates when they
are over mature, and then are more susceptible to decay in storage (Marquez-Villavicencio et al.
2011).
1.2 Potato diseases
The growth of potatoes can be affected by various environmental factors, such as
temperature, soil type, water, cultivar, as well as all kinds of disease. Under certain conditions,
potato tubers serve as a nutritive source for many pathogens. There are at least 80 pests and
4
diseases caused by insects, nematodes, viruses, bacteria, fungi and oomycetes, which can affect
all parts of a potato plant, especially harvested tubers that are the most economically important
parts (Fiers et al. 2012).
Tuber diseases can directly cause economic losses by reducing yield and quality of
tubers. Tuber diseases include viral diseases such as net necrosis caused by potato leafroll virus
(PLRV), dry rot caused by the fungal pathogen Fusarium spp., soft rot caused by
Pectobacterium spp. and Dickeya spp. and ring rot caused by Clavibacter michiganensis subsp.
sepedonicus, as well as Pythium leak and pink rot caused by Pythium spp. and Phytophthora
erythroseptica respectively (Gudmestad et al. 2007; van der Wolf and De Boer 2007). These
pathogens are responsible for significant losses in the field as well as storage problems. Although
common scab caused by Streptomyces scabies and powdery scab caused by Spongospora
subterranea have little or no influence on total yield, they can severely blemish the tuber
periderm, detract for tuber appearance, and drastically reduce the value in the fresh market (Dees
and Wanner 2012; Harrison et al. 1997). More importantly, S. subterranea is a vector for potato
mop top virus (PMTV) (Jones and Harrison 1969).
Foliar diseases affect potato production by disturbing photosynthesis and reducing plant
growth (Waggoner and Berger 1987). Foliar diseases mainly show up from the tuber initiation to
harvest stages. One example of a foliar disease is late blight (Phytophthora infestans), which is
best known for causing the Irish Potato Famine, resulting in the starvation deaths of one million
people and at least another one million people had to leave their homeland (Donnelly 2002;
Zwankhuizen et al. 1998). Late blight starts with small pale to dark green spots and spreads to
entire leaflets, eventually killing the entire plant when not controlled (Zwankhuizen et al. 1998).
In addition, other foliar diseases can also be constraints to production. For example, early blight
5
(Alternaria solani), white mold (Sclerotinia sclerotiorum) and grey mold (Botrytis cinerea)
cause discoloration and concentric or irregular rings on the leaf surface, which affect potato
production (Stevenson et al. 2001).
Stem and vascular diseases include stem canker/black scurf (Rhizoctonia solani), white
mold (Sclerotinia sclerotiorum), early dying/Verticillium wilt (Verticillium spp.) and blackleg
(Pectobacterium spp. and Dickeya spp.) (Stevenson et al. 2001). Stem canker is the most
common fungal disease of potatoes. Besides canker symptoms on stems, R. solani can produce
black sclerotia on the tuber surface (black scurf) reducing the value in the fresh market (Fiers et
al. 2012). Stem lesions of white mold begin when stems are in contact with soil containing
surviving pathogen spores. White mold can girdle potato stems and cause vine wilt or death.
Pectobacterium spp. and Dickeya spp. can colonize host xylem interrupting the transportation of
water and dissolved minerals (De Boer and Rubio 2004). Once the community population of
Pectobacterium spp. and Dickeya spp. reaches a certain level, these bacteria will secrete pectic
enzymes to degrade cell wall structure and cause the whole plant to collapse (Põllumaa et al.
2012).
Disease establishment requires a susceptible host, an available pathogen, and favorable
environmental conditions (Scholthof 2007). Pathogens causing diseases on potatoes may
originate from seed pieces, plant debris in soil, weed hosts, or even contaminated machinery like
seed cutters or storage conditions (Stevenson et al. 2001). Many fungal or oomycetes pathogens
produce survival structures to remain in the soil throughout the non-growing season. These
include oospores of Phytophthora spp., sclerotia of Rhizoctonia and Verticillium spp., spore balls
of Spongospora subterranea, and chlamydospores of Fusarium spp. Pathogens surviving on/in
seed tubers can infect plants systemically and transmit to daughter tubers, which are called seed-
6
borne pathogens. Bacterial diseases, such as ring rot, blackleg and soft rot are common seed-
borne potato diseases. Survival structures will serve as a primary inoculum and start the disease
cycle when reaching a susceptible plant under favorable conditions. In the growing season,
disease can transmit from infected plants to healthy ones by wind, rain, insects, and irrigation
water (Binyam 2014; Radcliffe and Ragsdale 2002; Scholthof 2007).
1.3 Blackleg and soft rot of potato
1.3.1 Disease symptoms
Blackleg and soft rot of potato (PBSR) are named based on symptoms on different tissues
of potato. Blackleg is a consequence of decayed stems, while soft rot is a symptom shown on
tubers both prior- and post-harvest (Perombelon and Kelman 1980). PBSR is primarily a seed-
borne disease. Seed tubers carrying the pathogens may be decayed at an earlier stage in the field
and result in missed emergence, which is often termed as pre-emergence blackleg or blanking
(Figure 1-2). Successfully emerged seedlings from infected seed pieces could be characterized
by blackened decay on the basal stem with length ranging from less than one inch up to the entire
stem, followed by rapid wilting and yellowing of leaves (Perombelon and Kelman 1980).
Blackleg symptoms can develop during any stage of plant development. The stolon attachment
site of tubers produced from blackleg-infected plants may be first blackened and decayed, and
the entire tuber may decay as the disease progresses under moist conditions or may remain intact
until conditions favorable for disease development return. Internal soft rotted tissues are wet and
mushy, cream to tan-colored with a black border between the diseased and healthy tissues
(Figure 1-2). Symptoms of tuber soft rot can also become sunken, dry and hard under dry
conditions. In seed potato production, the disease can cause important losses mainly due to
downgrading and rejection of seed lots in certification schemes. The extent of losses varies
7
widely from country to country and is influenced by the climate as well as the conditions of
growth and storage.
Figure 1-2. Symptoms of blackleg and soft rot of potato. Symptoms include low emergence in
the field (left panel), blackleg on stems (middle), and soft rot on tuber (right).
1.3.2 Disease cycle
It is now generally accepted that PBSR can be caused by seed-borne bacteria, such as D.
dianthicola and P. atroseptica, also soil-borne bacteria, such as D. solani and P. carotovora
(Parkinson et al. 2015; Perombelon and Kelman 1980). Therefore, PBSR can be initiated from
multiple sources. Soil-borne bacteria can survive in soil for a long time and penetrate seed tubers
through natural openings or wounds. Seed tubers harboring the soil-borne and seed-borne
bacteria play a critical role in the disease cycle (Ansermet et al. 2016; De Boer and Rubio 2004).
When a contaminated or infected seed potato is planted, symptoms will develop or not
depending on weather conditions. If pathogens are confined to the lenticels, decay of the seed
tuber occurs first and may cause non-emergence in the field. Pathogens can also move through
the vascular tissue directly into the growing plant, which will form blackleg and collapse the
stem if bacterial populations become great enough. However, when conditions are favorable for
the growth of the potato plant, no disease may occur even when blackleg-causing bacteria are
8
present. Whether diseases show up during growth or not, daughter tubers generated from the
contaminated mother tubers may carry blackleg bacteria. In storage, the contaminated tubers may
decay or remain symptomless. Then the disease cycle starts again if the symptomless but
contaminated tubers are used for planting in the following season (De Boer and Rubio 2004).
PBSR pathogens are believed to be dormant when present in potato tubers under stressed
environmental conditions, such as low storage temperature. One dormant status, called the viable
but non-culturable state (VBNC), has been described for more than 80 bacterium species (Pinto
et al. 2015). Bacteria can convert to a VBNC state when nutrient starved or in a stressed
environment, caused by chemicals, nutrient stress, temperature, etc. Cells converted to VBNC
state underwent a non-recoverable stage of existence, but still remain viable (Xu et al. 1982).
Although the VBNC state cannot be detected by conventional culture techniques because of the
non-culturability, they do take up nutrients, produce new biomass and maintain active
metabolism (Mederma et al. 1992). Furthermore, cells in VBNC state can still be pathogenic
after release from stress or when triggered by some compounds (Pinto et al. 2015).
The disease cycle of these pathogens is facilitated by their epiphytic and saprophytic
survival for extended periods of time in the phyllosphere, rhizosphere, soil, and plant debris. The
soft rot bacteria cannot survive over winter in soil, with the length of survival restricted to 1
week to 6 months, depending on environmental conditions such as soil temperature, moisture
and pH (Czajkowski et al. 2011; Perombelon and Kelman 1980). However, soft rot bacteria can
survive longer on plants, such as weeds and volunteers (Czajkowski et al. 2011). Although some
of the PBSR pathogens, such as Dickeya zeae, D. dadantii and D. aquatica have been frequently
isolated from surface water in the US and Europe (Cother et al. 1992; Duprey et al. 2019;
Ekbataniamiri 2020; Parkinson et al. 2014), indicating a long-time survival, their low titer may
9
not allow a direct infection of potato plants in fields. In other words, it is not proven that
blackleg bacteria can be spread through soil or water between multiple cropping seasons.
1.3.3 The occurrence of PBSR worldwide and outbreaks in the US
PBSR, especially caused by Dickeya dianthicola and D. solani, have emerged in
European countries in the past decades and severely affected local potato industries (Toth et al.
2011; van der Wolf et al. 2014). Dickeya dianthicola was first detected causing stunting and
slow wilting of Dianthus in the early 1950s in Denmark, then in the Netherlands and the UK
(Hellmers 1958; Parkinson et al. 2015). The presence of D. dianthicola strains has been reported
on potato or ornamental plants in more than 10 countries, including USA, UK, Belgium, France,
Morocco, Netherlands, Pakistan, Switzerland, Israel, Serbia etc. (Jiang et al. 2016; Marković et
al. 2020; Nasaruddin et al. 2019; Oulghazi et al. 2017; Rosenzweig et al. 2016; Sarfraz et al.
2018; Toth et al. 2011).
In 2013 and 2014, problems of low potato emergence were observed in Maine fields by
Dr. Steven B. Johnson and his colleagues. In the following years, potato plants with blackened
and decayed stems were recorded in the field, along with severe tuber decay in storage (Johnson
2016). Similar situations also happened in other eastern states in the U.S., including New York,
New Jersey, Massachusetts, Pennsylvania, Virginia (Charkowski 2018; Ma et al. 2018; Patel et
al. 2019). Twenty-four states in the U.S. have now been identified with PBSR symptoms.
Dickeya dianthicola was identified as the predominant bacterial pathogen in the outbreak
(Jiang et al. 2016). Pectobacterium parmentieri was later detected in the diseased potato stems
and tubers (Ge et al. 2018b). As a seed-borne disease, related pathogens are believed to be
distributed and spread through seed transportation. Spread of contaminated seed potatoes from
Maine, as the biggest potato seed producer for the northeastern area, was considered to be
10
responsible for the outbreak. Tracing and analysis of the geographically distributed pathogens
could help explain the inoculum of the outbreak. Furthermore, it was also believed that D.
dianthicola was present in seed potatoes and farms in the affected states for at least a few years.
Abundant rainfall in 2013 and 2014 spread the pathogen, but cool temperatures caused dormancy
or latency. Warmer temperatures in 2015 resulted in the significant disease outbreak on
commercial farms (Johnson 2016).
Pectobacterium species are typical soil inhabitants and are well adapted to living as
saprophytes in the soil until a host plant is nearby. Therefore, Pectobacterium spp. always exist
in rot samples as secondary invaders associated with other major pathogens (Charkowski 2018).
Increasingly diversified Dickeya and Pectobacterium likely result from the evolution of gene
repertoires, differences in pathogenicity, and the presence or absence of different virulence
factors (Duprey et al. 2019).
1.3.4 The pathogens of PBSR
1.3.4.1 Taxonomy of PBSR pathogens
PBSR can be caused by multiple species belonging to the closely related Dickeya and
Pectobacterium species (Charkowski 2018; Czajkowski et al. 2011; De Boer and Rubio 2004).
The bacteria are Gram-negative, non-sporing, and facultative anaerobes. They are characterized
by producing large quantities of extracellular pectic enzymes which can macerate plant tissues
along with a wide range of other plant cell wall-degrading enzymes (PCWDEs) (Collmer and
Keen 1986).
PBSR was initially recognized to be caused by several species in the genus Erwinia,
including E. carotovora subsp. carotovora, E. carotovora subsp. atroseptica and E.
chrysanthemi (Perombelon and Kelman 1980). These species were called soft rot Erwinia
11
because they share the ability of producing large quantities of pectic enzymes, which
distinguished these species from other Erwinia species. Since 1981, E. carotovora was further
differentiated into three subspecies, including E. carotovora subsp. betavasculorum isolated
from vascular necrosis of sugar beet in 1981, E. carotovora subsp. wasabiae isolated from
wasabi samples in 1987, and E. carotovora subsp. odoriferum from slimy rot witloof chicory in
1992 (Gallois et al. 1992; Goto and Matsumoto 1987; Thomson et al. 1981). In 1998, by
analyzing the 16S rRNA gene, Hauben et al. proposed to place the above six into one cluster, and
reassigned them into genus Pectobacterium (Hauben et al. 1998). Later on, the three subspecies
of P. carotovora, P. carotovora subsp. betavasculorum, P. carotovora subsp. wasabiae, P.
carotovora subsp. atroseptica were then elevated to species level, which are P. betavasculorum,
P. wasabiae, P. atroseptica now (Gardan et al. 2003). Up to then, soft rot Erwinia included P.
carotovora subsp. carotovora, P. carotovora subsp. odoriferum, P. atroseptica, P. chrysanthemi,
P. betavasculorum, P. wasabiae. In 2004, a new species, P. carotovora subsp. brasiliensis was
isolated from potato in Brazil (Duarte et al. 2004). Pectobacterium wasabiae isolated from
potato plants was renamed as P. parmentieri based on whole genome analysis in 2016 (Khayi et
al. 2016). New species P. polaris was isolated from potato in 2017 (Dees et al. 2017). Currently,
soft rot bacteria include P. carotovora subsp. carotovora, P. carotovora subsp. odoriferum, P.
carotovora subsp. brasiliensis, P. atroseptica, P. chrysanthemi, P. betavasculorum, P.
parmentieri and P. polaris (Table 1-1). However, the Pectobacterium complex also contains far
more than the discussed species.
In 1998, P. chrysanthemi was divided into six pathovars (Lelliott and Dickey 1984;
Young et al. 1978), which were then transferred into a new genus Dickeya, including D.
chrysanthemi, D. paradisiaca, D. dadantii, D. dianthicola, D. dieffenbachiae and D. zeae based
12
Table 1-1. Development of etiology and taxonomy of blackleg and soft rot bacteria.
Before
1981
1981 1987 1992 1998 2003 2004 2005 2012 2014 2016 2017 Conclusion
Erwinia chrysanthemi
Brenneria paradisiaca Dickeya paradisiaca D. paradisiaca
Dick
eya sp
p.
Pectobacterium chrysanthemi
D. chrysanthemi D. chrysanthemi
D. zeae D. zeae
D. dadantii D. dadantii subsp. dadantii D. dadantii
D.
diffenbachiae
D. dadantii subsp. diffenbachiae
D. dianthicola D. dianthicola
D. solani
D. solani
D. aquatica D. aquatica
D. fangzhongdai D. fangzhongdai
E. carotovora subsp. atroseptica
P. carotovora
subsp.
atroseptica
P. atroseptica
P. atroseptica
Pecto
ba
cterium
spp
.
E. carotovora subsp. carotovora P. carotovora subsp. carotovora P. carotovora
subsp.
carotovora
E. carotovora subsp.
betavasculorum
P. carotovora
subsp.
betavasculoru
m
P. betavasculorum P.
betavasculorum
E. carotovora subsp.
wasabiae
P. carotovora
subsp.
wasabiae
P. wasabiae P. parmentieri
P. wasabiae
P. parmentieri
E. carotovora
subsp.
odoriferum
P. carotovora subsp. odoriferum P. carotovora
subsp. odoriferum
P. carotovora subsp. brasiliensis P. carotovora
subsp.
brasiliensis
P.
polaris
P. polaris
13
on 16S rRNA gene-based phylogenetic analyses in 2005 (Samson et al. 2005). The above six
Dickeya spp. were then reduced to five by dividing D. dadantii into two subspecies and placing
all strains in D. dieffenbachiae as a subspecies within D. dadantii (D. dadantii subsp. dadantii
and D. dadantii subsp. dieffenbachiae) (Brady et al. 2012). More recently, three additional
Dickeya species have been described: D. solani, isolated from potatoes in Europe and hyacinth
(Sławiak et al. 2009; van der Wolf et al. 2014), D. aquatica from freshwater rivers
(Ekbataniamiri 2020; Parkinson et al. 2014), and D. fangzhongdai from pear trees displaying
symptoms of bleeding canker in China (Tian et al. 2016). So far, the species in genus Dickeya
include D. chrysanthemi, D. dadantii, D. dianthicola, D. solani, D. zeae, D. aquatica, D.
paradisiaca and D. fangzhongdai (Table 1-1).
1.3.4.2 Host range
Host range and host specificity of pathogens are conventionally determined by their
serological and temperature characteristics, which reflects their geographic distribution (Ma et al.
2007). Dickeya spp. and Pectobacterium spp. are considered as broad-host-range pathogens, with
the exceptions of P. atroseptica and D. solani that are restricted mostly to potatoes, and D.
paradisiaca which is restricted only to plantain (Table 1-2). Most Dickeya spp. infect a wide
range of crops in tropical and subtropical regions, as well as greenhouse crops grown in
temperate regions. Since potato is widely cultivated in various regions, Dickeya spp. have
become important in potato production. Dickeya dianthicola is a serious pathogen that is known
to occur in many countries such as Australia, European countries, Israel, and the U.S. and others,
and has resulted in significant yield losses to potato crops (Charkowski 2018).
14
In addition to potatoes, D. dianthicola can also infect other crops and ornamentals, such
as carnation, lily, chrysanthemum, dahlia, hyacinth, dianthus, chicory and globe artichoke.
Dickeya zeae causes maize stalk rot, rice foot rot and banana soft rot diseases in many countries
and regions (Nassar et al. 1994; Pu et al. 2012; Samson et al. 2005; Sinha and Prasad 1977;
Zhang et al. 2014). Dickeya zeae has not been found and isolated from potatoes in the U.S.,
although isolation from irrigation water and inoculation tests have shown that D. zeae can be
pathogenic to potatoes (Ekbataniamiri 2020). Dickeya dadantii causes soft rot on many crops and
ornamentals as well as potato (Ngadze et al. 2010). Pathogenicity of D. aquatica has been
confirmed on cucumber, tomato and potato under high concentration, indicating that it is a
potential pathogen of potato. However, D. aquatica is much more pathogen to aquatic
charophyte hosts due to the lack of xylanases and xylose (Duprey et al. 2019). Since D. aquatica
was only isolated from surface water near irrigation ponds with very low concentrations, it may
not result in potato infection in the field. As the newest Dickeya species, D. fangzhongdai was
first reported on pear trees and later was isolated from decayed onions, phalaenopsis and
poinsettia (Alič et al. 2018).
In contrast to Dickeya spp., Pectobacterium spp. have a wide distribution in both the
temperate and tropical zones and are pathogenic to a much wider range of crops. For example, P.
carotovora subsp. carotovora has a wide host range including potato, cabbage, carrot, celery,
cucumber, maize, and hyacinth (Ma et al. 2007). Pectobacterium carotovora subsp. brasiliensis
was first found in Brazil, and later in New Zealand, Canada, and South Africa to be pathogenic
to multiple hosts, including cucumber, sugar beet, cabbage, Chinese cabbage, tomato, pepper,
potato, eggplant, nepenthes and zucchini (Duarte et al. 2004). Pectobacterium odoriferum was
first isolated from chicory with odorous smell, and then also found in multiple crops, including
15
leek, celery, parsley, carrot, onion, and potato (Gallois et al. 1992; Ma et al. 2007).
Pectobacterium parmentieri can infect potato, horseradish, carrot, cabbage, maize, sugar beet,
and calla lily (Khayi et al. 2016). Pectobacterium betavasculorum was viewed as a pathogen
restricted to sugar beet, but later was isolated from sunflower and artichoke (Gardan et al. 2003).
Table 1-2. Confirmed hosts of Dickeya spp. and Pectobacterium spp. causing blackleg and soft
rot of potato.
Species Host
D. solani Potato
D. paradisiaca Plantain
D. zeae Maize, rice, banana
D. chrysanthemi Chrysanthemum, dendranthema, grandiflorum, dianthus caryophyllus, potato,
etc.
D. dianthicola Carnation, lily, chrysanthemum, dahlia, hyacinth, dianthus chicory, globe
artichoke, potato, etc.
D. dadantii Pepper, eggplant, tomato, tobacco, sweet potato, broccoli, radishes, celery,
carrot, sugar cane, sorghum, rice, pineapple, urn plant, onion, orchids, tulip,
chicory, chrysanthemums, carnations, hyacinths, etc.
P. atroseptica Potato
P. polaris Potato
D. aquatica No host, but can be pathogenic to many crops
D. fangzhongdai Onion, pear trees, phalaenopsis, poinsettia
P. betavasculorum Sugar beet, sunflower, artichoke
P. carotovora
subsp. odoriferum
Chicory, leek, celery, parsley, carrot, onion, potato
P. parmentieri Carrot, cabbage, maize, sugar beet, calla lily, horseradish, potato etc.
P. carotovora
subsp. brasiliensis
Cucumber, sugar beet, cabbage, tomato, pepper, eggplant, nepenthes, zucchini,
potato
P. carotovora
subsp.
carotovora
Arum, cabbage, carrot, celery, cotton, cucumber, cyclamen, delphinium,
hyacinth, maize, sugar cane, tobacco, potato
16
1.3.4.3 Pathogenesis of PBSR pathogens
Disease establishment of PBSR starts with the entry of the bacteria into the host tissue
through a natural opening or wound. Under favorable conditions, bacteria multiply to a high titer.
In order to infect host plants, pathogenic bacteria translocate various chemicals on/in host
through different secretion systems. Secreted chemicals included adhesins, effectors, biofilm-
related chemicals, pectinolytic enzymes, and quorum-sensing signals. There are six types of
secretion systems that are more or less related to the pathogenicity of soft rot bacteria.
Bacteria firstly attach to the plant surface with the formation of a biofilm by secreting
adhesins such as extracellular polysaccharides (Yousef and Espinosa-Urgel 2007). The adhesion
is governed by some genes in association with the type I secretion system (T1SS) gene cluster.
For example, the hecA gene in D. dadantii encodes adhesin of the hemagglutinin (Rojas et al.
2002). In P. atroseptica, genes encoding the components of the T1SS were identified along with
the gene encoding a multirepeat adhesin protein (MRP) (Pérez‐Mendoza et al. 2011). Through
T1SS, cytoplasmic proteins of various sizes, such as the adhesins, are secreted directly from the
cytoplasm across the inner and outer membranes in a periplasm-independent manner (Tseng et
al. 2009).
After attaching to the plant surface, the plant cell wall is the first structural barrier that
soft rot bacteria must overcome during infection. To overcome this barrier, soft rot bacteria
produce multiple PCWDEs, including pectin methylesterases, pectate lyases, pectin lyases,
pectin acetylesterases, and poly-galacturonases, most of which are translocated from bacterial
cells through the type II secretion system (T2SS) (Charkowski et al. 2012; Salmond 1994; Toth
et al. 2006).
17
Effector proteins translocated from bacterial cells to host plants play an important role in
their virulence. Effectors that define the outcome of host-pathogen interaction are secreted by the
type III secretion system (T3SS) directly into host cells. Once inside host cells, effectors
manipulate host defenses and promote bacterial growth. The utilization of T3SS has been found
in D. dadantii, P. carotovora, P. atroseptica, and D. zeae (Bell et al. 2002; Ham et al. 1998; Li
et al. 2012; Rantakari et al. 2001; Yang et al. 2002). However, not all Pectobacterium spp.
require the same secretion system. For example, T3SS is absent in P. parmentieri. In addition to
the well-known type I, II, and III secretion systems, the function of type IV, V and VI secretion
systems are also believed to support the infection process by soft rot bacteria (Bell et al. 2004;
Glasner et al. 2008; Li et al. 2012; Toth et al. 2003).
Genomic studies of P. atroseptica, P. carotovora subsp. brasiliensis, and D. zeae have
revealed the existence of a type IV secretion system (T4SS) (Glasner et al. 2008; Li et al. 2012;
Mattinen et al. 2008), but the full function in virulence has yet to be identified. The putative
T4SS gene virB4 only has been found to affect the lesion development by P. atroseptica on
potato stems (Bell et al. 2004). Knowledge of the biological function of the type V secretion
system (T5SS) and type VI secretion system (T6SS) in soft rot bacteria is still limited.
Quorum sensing (QS) is an intercellular signaling mechanism allowing bacterial cells to
sense the population density and then modulate cellular behaviors when the population reaches a
certain threshold. Activities associated with QS include production of virulence factors,
formation of biofilms, control of motility, and biosynthesis of secondary metabolites (Decho et
al. 2010; von Bodman et al. 2003). Novel biocontrol strategies based on the disruption of
bacterial communication through QS are being developed. In the soft rot bacteria, QS is largely
dependent on N-acylhomoserine lactone- (AHL-) type signaling molecules, followed by
18
autoinducer-2 (AI-2) (Põllumaa et al. 2012). Pectobacterium and Dickeya spp. are quite different
in that AHL-mediated QS plays an important role in virulence of P. carotovora and P.
atroseptica but is less obvious in the virulence of D. dadantii (Chatterjee et al. 2010; Ham et al.
2004).
1.3.5 Management of PBSR
An integrative strategy, combining the use of certified seed tubers, hygienic practices
during harvesting and grading, and avoidance of PBSR introduction during planting and in
storage, has been partially effective, but has not resulted in a broad eradication of the PBSR in
the potato production chain (Perombelon and Kelman 1980; Toth et al. 2011). Management
approaches, including exclusion, use of resistant varieties, and protection through chemical and
biological control, have been developed and implemented with varying degrees of success.
1.3.5.1 Exclusion
Exclusion strategies are often regulatory and involve the use of seed certification,
quarantine, and plant inspection to prevent disease spread. Seed certification schemes are widely
used to manage PBSR and have been partially successful. This method involves sampling
representative tubers from seed lots, testing tuber tissues for pathogens and estimating blackleg
risk assessment (Perombelon 2000). However, latent infection of progeny tubers from
symptomless plants can easily escape diagnosis, which may increase the risk of exclusion failure.
Minitubers grown in a controlled pathogen-free environment are used to obtain pathogen-free
seed (Farran and Mingo-Castel 2006; Rolot and Seutin 1999). Avoidance of wounding at any
steps during harvesting and grading is important to reduce the risks of introducing bacteria
through wounds.
19
Potato plants in a seed production system are usually subjected to field inspections twice
during the growing season. During field inspections, removal of diseased plants, including
daughter tubers contribute to reducing PBSR inoculum. Moreover, removal of decayed tubers
during harvesting and grading can also reduce the spreading and smearing of the bacteria in the
seed lots (Elphinstone and Pérombelon 1986). Spreading of the causal agents across plants or
fields can be controlled by sanitation procedures in storage facilities, as well as on cutters or
other equipment (Pérombelon et al. 1979).
1.3.5.2 Resistant varieties
It is challenging to breed a highly resistant potato variety due to limitations of available
germplasm. Breeding for resistant varieties has so far had relatively little success. No hybrid
lines that are immune to PBSR have been commercialized to date (Czajkowski et al. 2011).
Screening for resistance is not straightforward, as cultivar resistance or susceptibility to PBSR is
not always measurable. Moreover, the extremely complicated pathogen community capable of
causing PBSR makes the target of breeding much more difficult. Some white-skined potato
varieties such as ‘Shepody’ and ‘Atlantic’ show a good level of PBSR tolerance (Ge et al.
2020a). It is also encouraging that the newly released variety ‘Caribou Russet’ bred by the
University of Maine breeding program has shown good resistance against PBSR (Ekbataniamiri
2020).
Physiological features, such as mature tubers with a well-developed periderm will reduce
risk of wounding. Using true seeds, derived from sexual crosses which are believed to be free
from blackleg and soft rot bacteria, can be an alternative way to reduce the incidence of
infections (Chujoy and Cabello 2007). A high calcium content in crops is often positively related
20
to increased resistance against bacterial diseases, including potato blackleg (McGuire and
Kelman 1984; Pagel and Heitefuss 1989).
1.3.5.3 Protection
Physical, chemical, and biological controls can be considered in protecting potatoes from
PBSR. Physical factors involve hot water, steam, dry hot air and ultraviolet and solar radiation
(Bartz and Kelman 1985; Bdliya and Haruna 2007; Ranganna et al. 1997; Robinson and Foster
1987; Shirsat et al. 1991). These methods have been widely used for several decades. However,
their limitations are the inability to kill plant pathogenic bacteria located deep inside the tubers or
plant xylem without negative effects on plant growth. Also, bulky seed tubers prepared for each
growing season result in substantial operational costs and the difficulty of expanding for large-
scale use (Czajkowski et al. 2011).
Chemical control strategies are usually used based on the eradication of the pathogen
and/or the creation of unfavorable environmental conditions (e.g. low or high pH, etc.) to inhibit
disease development (Czajkowski et al. 2013a). Chemical treatments applied on seed tubers are
the most efficient way to control PBSR. However, extensive use of antibiotics is no longer
allowed for large-scale field applications due to the high risk of development of antibiotic
resistance in bacterial pathogens. Some chemicals have indirect effects by enhancing plant
growth or altering plant physiology. For example, salicylic acid can induce the systemic acquired
resistance defense mechanism, which has been effective at reducing infection symptoms caused
by D. solani in tissue-culture-grown potato plants (Czajkowski et al. 2015a). Reduction of PBSR
causal agents by physical and chemical treatments is only partially effective and is still in
experimental development (Czajkowski et al. 2011; van der Wolf and De Boer 2007).
21
Biological agents have been studied for PBSR control. Pseudomonas spp., including P.
putida and P. fluorescens are frequently tested as biological agents (Des Essarts et al. 2016;
Kastelein et al. 1999). Some other bacteria have been also studied (Czajkowski et al. 2012;
Garge and Nerurkar 2017). Bacteriophages have been tested for the control of bacterial plant
diseases for more than 30 years, such as the control of Agrobacterium tumefaciens, Xanthomonas
campestris pv. pruni, X. oryzae etc. (Jones et al. 2007). The advantages of bacteriophages over
other biocontrol agents include specificity to their bacterial hosts and non-pathogenicity for
humans and animals (Jones et al. 2007). Bacteriophages were isolated and used to infect Erwinia
and Dickeya spp., which can infect bacterial host effectively (Czajkowski 2016; Czajkowski et
al. 2015b; Czajkowski et al. 2014; Smolarska et al. 2018; Soleimani-Delfan et al. 2015).
Unfortunately, no commercial biocontrol products are currently available for the control of
PBSR.
1.4 Microbiomes
The microbiome is defined as a characteristic microbial community occupying a
reasonable well-defined habitat which has distinct physio-chemical properties (Berg et al. 2020).
A microbial community is a multi-species assemblage, in which microorganisms share a
common living space in natural environments, such as soil, water, and animal or plant host, and
interact with each other. In agroecosystems, soil microbial communities can influence the
physiology and development of associated plants (Mendes et al. 2013). Plant microbiota
comprise all microorganisms in/on plants, which is also called the plant microbiome and is
comprised of all microbial genomes. Plant-associated microbiota includes diverse microbes such
as archaea, bacteria, fungi, nematodes, and protists, and the micro biota is a key determinant of
plant health and productivity (Berendsen et al. 2012; Compant et al. 2019; Turner et al. 2013).
22
1.4.1 Plant microbiome
The rhizosphere (roots and underground parts), phyllosphere (plant aerial surfaces) and
endosphere (internal tissues) are the most investigated microbial reservoirs on plants. The nature
of plant-associated microbiota is plant genotype dependent. The rhizosphere is a region of rich
microbial diversity, which is influenced by deposition of plant exudates, mainly dominated by
the bacterial phyla Acidobacteria, Verrucomicrobia, Bacteroidetes, Proteobacteria,
Planctomycetes and Actinobacteria (Fierer 2017; Kent and Triplett 2002). Dominant microbes
may be diverse as the structure of plant-associated microbiota in rhizosphere is largely plant
genotype dependent (Chaparro et al. 2014; Hartmann et al. 2009; Ladygina and Hedlund 2010;
Reinhold-Hurek et al. 2015). Microbes in the rhizosphere can obtain carbon sources from root
exudates, sloughed root cells or the release of mucilage. The root exudates, in particular, contain
a variety of compounds and are key determinants of rhizosphere microbiome structure (Bertin et
al. 2003). In addition to root exudates, microbes in the rhizosphere can degrade sloughed root
cells and mucilage and obtain a large amount of material, such as plant cell wall polymers
(cellulose or pectin), as food source, (Dennis et al. 2010). In contrast to the rhizosphere, the
phyllosphere niche is relatively nutrient poor and easily subjected to extremes of temperature,
radiation and moisture.
Microbial inhabitants of the rhizosphere and phyllosphere are considered as epiphytes.
Microbes residing within plant tissues (the endosphere) whether in leaves, roots or stems, are
referred to as endophytes. Endophytes are thought to be a sub-population of the rhizosphere
microbiome, partially because not all microorganisms from the rhizosphere can enter plants
(Compant et al. 2010). Endophytes are generally non-pathogenic, but they also include latent
23
pathogens that can cause disease under certain environmental circumstances and/or with certain
host genotypes (James and Olivares 1998; Monteiro et al. 2012).
Microbial communities and their interactions with plant hosts are of high significance to
plant health. Plant hosts and the associated microorganisms mutually influence their lifestyles.
Plant hosts provide nutrient sources and niche space for microbial growth, while microbes in
these niches can establish beneficial, neutral or detrimental (pathogenic) associations with their
host plants. Microorganisms benefit plant health with a wide range of effects, including disease
suppression, priming of the plant immune system through microbe-associated molecular patterns
(MAMPs) or pathogen-associated molecular patterns (PAMPs). They can also increase nutrient
acquisition, tolerance to abiotic stresses, adaptation to environmental variation, or the
establishment of mycorrhizal associations (Garbaye 1994; Haney et al. 2015; Mendes et al.
2011; Ritpitakphong et al. 2016; Rolli et al. 2015; Van der Ent et al. 2009; Van Der Heijden et
al. 2016; Zamioudis et al. 2015).
1.4.2 Plant pathobiome
Within the context of microbial community interactions, pathobiome is defined by
Vayssier-Taussat et al. (2014) to represent the pathogenic agent integrated within its biotic
environment. In this case, “pathobiome” has been proposed to replace “pathogens”, indicating a
leveraged understanding of plant diseases from “one microbe-one disease” to “multi-microbes-
one disease” (Vayssier-Taussat et al. 2014). Pathobiome plays a direct role of triggering or
influencing disease progression by establishing multiple interactions with other microorganisms
within plant microbiota. Such microbial consortia represent the pathogenic agent integrated
within its biotic environment and make disease establishment/development much more complex
(Mina et al. 2020). Pathobiome can be viewed as an approach to study plant diseases by looking
24
at more factors though it may not replace one-pathogen for one disease, because non-pathogenic
microbes can be considered as one kind of environmental factor.
Currently in plant pathology, the role and interactions of pathobiome have been focused
on disease establishment or development, rather than being focused on a single species of
disease-causing agent. The latter overlooks the crucial biotic complexity encountered in plant
hosts. This microflora is usually a ubiquitous constituent of the plant host. This microbiota can
cooperate with pathogens via specific pathways, such as quorum sensing signal sharing,
metabolic sharing/complementarity, resulting in a mutualistic interaction (Egland et al. 2004;
Kim et al. 2008). The mutualistic interactions between pathogens and other microorganisms can
result in a more aggressive disease when co-inoculations are made compared with single
inoculations (da Silva et al. 2014).
1.4.3 Microbial interactions
Microbiome is an important component of plant health. Microorganisms have various
interactions, which are essential to maintain the stability and functioning of microbial
communities, including plant pathogens (Singer 2010). The prevalence of multiple infections in
the field indicates that the extent of complex interactions, known as co-infection, can be
significant in some disease systems (Tollenaere et al. 2016).
Co-infection has become of particular interest since it tends to alter the course of disease
and the overall virulence of multiple pathogens (Tollenaere et al. 2016). Before co-infection was
studied, host-pathogen interaction was the only well-studied key interaction when investigating
disease development or other topics (Brown 2015), while pathogen-pathogen interaction, and
host-multiple-pathogen interactions have been less studied. Here, pathogen-pathogen interactions
will be reviewed in detail, and can be classified into three types: 1) competition, in which
25
competing pathogens exclude competitors from resource-dense niches by physical or chemical
approaches; 2) cooperation, whereby pathogens benefit from each other by sharing or
exchanging substances essential for pathogenesis or survival; 3) coexistence, whereby pathogens
can stably coexist through niche specialization (Abdullah et al. 2017).
1.4.3.1 Competition and coexistence
Theoretically, in a defined space with sufficient nutrients, many microbes including
pathogens can stably coexist (Monod 1949). Because host resources are limited, pathogens often
enter into fierce competition, fundamentally for growth- and fitness-limiting resources (West et
al. 2006). The limited resources, such as nutrients, can be utilized by one pathogen and then
other pathogens sharing the similar nutritional requirements will be restricted. However, some
species may dominate within a space of suboptimal nutrition. Competition under such conditions
may result in the selection for more virulent species, or conversely, all associated pathogens may
suffer from insufficient resources (Rankin et al. 2007). In addition to competing for resources,
more aggressive forms of competition between pathogens include direct chemical exclusion,
such as secreting toxins to prevent competitors’ growth (Mousa et al. 2015), or mechanical
aggression, like forming multilayer physical barriers or special structure to limit the growth or
infection of competitors (Mousa et al. 2016). Competition can also happen indirectly by
mediating the plant defense system against other pathogens (Na and Gijzen 2016).
To avoid or reduce the severity of the competition, negotiation among pathogens can
occur. Niche specializations in space and time enable pathogen species to coexist stably when
localized in different tissues of the host, or by arriving at different time intervals (Fitt et al.
2006).
26
1.4.3.2 Cooperation and synergism
Besides competition and peaceful coexistence, plant pathogens may also cooperate to
enhance their pathogenicity. This relationship has been determined in many pathosystems, such
as biophysical transport, in which bacteria are transported by Didymella bryoniae resulting in co-
infection of Styrian oil pumpkin (Grube et al. 2011). Scanning electronic microscopy (SEM) or
confocal microscopy combined with fluorescence labeled microbes can visually demonstrate the
spatial distribution or interaction, such as clear niche specialization or adherence (Murray et al.
2014).
Microbes not only interact through direct contact. cooperation crossing kingdoms can
also occur through biochemical means. An example is Rhizopus microsporus causing rice blight
which owes its pathogenicity to phytotoxins secreted by its endosymbiont Burkholderia sp.
(Partida-Martinez and Hertweck 2005). QS is also one example of bacterial cooperation in which
a group of bacteria share the extracellular signals to regulate certain processes together (Cook et
al. 2013). Therefore, QS signals (AHLs, AI-2) are important chemical factors for synergy during
infection (Armbruster et al. 2010; Duan et al. 2003). Between closely related species,
complementation of growth substrates is a common strategy and prominent when resources are
deficient (Hoek et al. 2016). Certain microbes are only host destructive when they cooperate with
other independent pathogens, such as the endophytes which are considered as nonpathogenic or
only causing nonvisible symptoms (Partida-Martinez and Heil 2011). Complex dynamics
involving other microbes may alter the properties of endophytes.
Plant diseases can be the result of multispecies with synergistic disease effects. In many
cases, plants may not show severe disease symptoms when infected by a single microbe
(pathogen), but are subjected to severe symptoms when co-infected by multiple microbial
27
species due to synergistic interaction (Lamichhane and Venturi 2015). Such synergistic
interactions in plants may be of crucial importance for the understanding of microbial
pathogenesis and evolution. This increases the complexity of the disease and has to be taken into
consideration in the development of more effective control strategies (Lamichhane and Venturi
2015). Tomato pith necrosis is caused by at least eight bacterial species Pseudomonas cichorii,
P. corrugata, P. viridiflava, P. mediterranea, P. fluorescens, Pectobacterium atroseptica,
Pectobacterium carotovora, and Dickeya chrysanthemi (Alivizatos 1985; Dhanvantari and Dirks
1987; Goumans and Chatzaki 1998; Malathrakis and Goumas 1987; Paula Wilkie and Dye
1974; Saygili et al. 2008; Scarlett et al. 1978). Disease severity is greatly enhanced when co-
infection of multiple bacterial species occurs (Kůdela et al. 2011; Moura et al. 2004).
1.4.4 Sequencing-based methods for studying microbiomes
Historically, microbiomes have been studied using culture-based techniques, which allow
researchers to isolate and characterize microbes for biological studies of microorganisms. But it
has limitations because the majority of microorganisms are not culturable (Steen et al. 2019).
Due to the complexity of polymicrobial disease, their study has been somewhat overlooked when
only using the culture-based techniques. In recent decades, culture-independent techniques have
been extensively applied to explore microbiomes and disease complex. Sequencing has
facilitated the study of microbiome and pathobiome as well as the underlying mechanisms of
plant diseases (Lamichhane and Venturi 2015).
Metagenomics allow the identification of microbes in situ. At the microbiome level,
huge datasets (e.g., metagenomics and metabolomics) are often generated using homogenized,
whole-tissue samples, by sequencing the variable regions of the ubiquitous genes. For example,
16S ribosomal RNA (rRNA) and internal transcribed space (ITS) have been universally used for
28
a high-resolution (species- and strain- level) taxonomic identification of all members in a
specific microbiome (Chakravorty et al. 2007; Schoch et al. 2012).
Sequencing technologies have evolved rapidly over the last 40 years. Since Sanger
sequencing technology was invented as the first generation, we have moved to the third
generation sequencing (Sanger and Coulson 1975; Sanger et al. 1977). Sanger sequencing has
the read-length ability of up to 1000 base pair (bp) with accuracy as high as 99.999% (Shendure
and Ji 2008). To enhance the capacity and speed, next generation sequencing (NGS) was
developed, which is symbolized by Roche’s 454 technology, Illumina’s Solexa, HiSeq
technology, and ABI’s Solid technology (Mardis 2008). NGS produces short reads ranging from
75 to 300 bp, but it allows us to genotype hundreds to thousands of samples in a single
experiment (Mardis 2017; Shendure and Ji 2008). Moreover, the tremendously low cost and
shortened sequencing NGS makes possible the analyses of tens of thousands of microbial
identities in a microbiome (Guttman et al. 2014). Metagenomic information from hypervariable
regions in the 16S/18S ribosomal RNA (rRNA) amplicons for bacteria or ribosomal internal
transcribed spacer (ITS) for fungi are so far preferred in microbiome research (Hiergeist et al.
2015). Many pipelines have emerged to compute the large data sets of NGS, with the commonly
used pipelines as quantitative insights into microbial ecology (QIIME) and Mothur (López-
García et al. 2018). In NGS, operating taxonomic units (OTUs) and amplicon sequence variant
(ASV) approaches are standard to determine the taxonomic origin of microbial sequences
(Callahan et al. 2017).
The third-generation sequencing, also known as long-read sequencing is the latest DNA
sequencing method that produces substantially longer reads than the NGS technique (Bleidorn
2016). The relatively long reads allow sequencing near-complete viral or small bacterial
29
genomes with an accuracy of as high as 97 to 99% (Greninger et al. 2015). The sequencing
platform includes the PacBio SMRT (Single Molecule Real Time) and the Oxford Nanopore
(Weirather et al. 2017). The main advantage for the third-generation sequencing technologies in
metagenomics is the speed of sequencing and length of reads in comparison to NGS, but high
error rates need to be overcome in future improvement (Petersen et al. 2019). Combining NGS
and third generation sequencing have been frequently used for accurate and complete whole
genome sequencing. For example, long read sequencing by Oxford nanopore can be polished
with short reads by Illumina sequencing (Bouchez et al. 2018; Kranz et al. 2017).
1.5 Objectives
Because potato is the most important vegetable in USA, as well as in the world, the
impact of diseases, such as PBSR is substantial. The outbreak has caused huge yield and
economic losses to the growers in multiple states. Maine as a major seed producer in the
northeastern region has been heavily affected by the outbreak of the seedborne PBSR since 2015.
We have found that D. dianthicola is the primary pathogen in the PBSR outbreak, but that many
Pectobacterium spp. have also been involved. Thus, this research project focused on these
bacterial species. To understand PBSR outbreak, I was interested in how the disease initiated,
what factors affected the disease epidemic, and eventually how to prevent and control PBSR in
the future. As such, I had the following questions and hypotheses.
1). What is the origin of bacterial pathogen D. dianthicola causing the outbreak? The
hypothesis was that D. dianthicola was clonal and that the outbreak was caused by
dispersal of infected seed tubers.
30
2). How do D. dianthicola strains causing this outbreak differ to known strains from those
other countries? The outbreak was caused by endemic D. dianthicola strains, which could
well adapt to the northeastern environmental conditions.
3). Was D. dianthicola the only causal agent of the outbreak or were multiple bacteria
involved? Potato plants exposed to multiple species of bacteria that are potentially causal
agents of PBSR.
4). How do these pathogen complexes perform during disease development? Multiple species
of causal agents have advantages in pathogen infection and disease development.
With the above questions raised, my dissertation was arranged as shown in Figure 1-3.
Figure 1-3. Flowchart of the chapters.
31
CHAPTER 2
GENOTYPING DICKEYA DIANTHICOLA CAUSING POTATO BLACKLEG AND
SOFT ROT ASSOCIATED WITH INOCULUM GEOGRAPHY IN THE UNITED
STATES
This chapter has been previously published in Plant Disease:
Ge, T.L., Jiang, H.H., Johnson, S.B., Larkin, R.P., Charkowski, A.O., Secor, G., and Hao, J.J. (2020)
Genotyping Dickeya dianthicola causing potato blackleg and soft rot associated with inoculum geography
in the United States. Plant Disease. DOI: 10.1094/PDIS-10-20-2138-RE.
ABSTRACT
An outbreak of blackleg and soft rot of potato, caused primarily by the bacterial pathogen
Dickeya dianthicola, has resulted in significant economic losses in the Northeastern United
States since 2015. The spread of this seedborne disease is highly associated with seed
distribution, therefore the pathogen likely spread with seed tubers. To describe the blackleg
epidemic and track inoculum origins, a total of 1183 potato samples were collected from 11
northeastern states from 2015 to 2019. Of these samples, 39.8% tested positive for D.
dianthicola. Seventeen isolates of Dickeya dianthicola were recovered from these samples and
the genetic diversity of these isolates was examined. Fingerprinting with BOX-PCR and
phylogenetic analysis based on 16S rDNA and gapA sequences indicated that D. dianthicola
isolates were divided into three genotypes, denoted Type I, II, and III. Ninety five percent of
samples from Maine were Type I. Type II was found in Maine only in 2015 and 2018. Type II
was present throughout the five years in some states at a lower percentage than Type I. Type III
was found in Pennsylvania, New Jersey and Massachusetts, but not in Maine. Therefore, Type I
appears to be associated with Maine, but Type II appeared to be distributed throughout the
32
Northeastern United States. The Type II and rarer Type III strain were closer to the D.
dianthicola type strain isolated from the United Kingdom. This work provides evidence that the
outbreak of blackleg of potato in the Northeastern United States was caused by multiple strains
of D. dianthicola. The geographic origins of these strains remain unknown.
2.1 INTRODUCTION
The bacterial disease blackleg and soft rot of potato (Solanum tuberosum) is caused by
multiple species of Dickeya and Pectobacterium (Toth et al. 2011). Both genera are broad host
range pathogens and Dickeya infects plants in at least 35% of plant orders (Perombelon and
Kelman 1980). At least seven species of Dickeya, including D. dianthicola, D. zeae, D. solani,
D. chrysanthemi, D. dadantii, D. aquatica, and D. paradisiaca, cause similar decay symptoms in
plants, although with different levels of aggressiveness (Brady et al. 2012; Samson et al. 2005;
van der Wolf et al. 2014). Dickeya dianthicola (syn. Erwinia chrysanthemi) was described for
the first time as a soft-rotting-causative agent of potato tubers in 1980 (Cother et al. 1992), and
later recognized as a blackleg-causing agent in Europe (Toth et al. 2011).
An outbreak of blackleg in potato started in Maine and many other states in the
Northeastern region in 2015 (Hao et al. 2016; Jiang et al. 2016; Johnson 2016; Ma et al. 2018;
Patel et al. 2019; Rosenzweig et al. 2016). Symptoms included non-emergence after planting,
blackened and rotted stems and wilting canopy during the growing season, and decayed and
rotten potato tubers in storage (Johnson 2017). Severe losses caused by the outbreak were
mainly associated with the bacterial pathogen D. dianthicola (Hao et al. 2016; Johnson 2016;
Ma et al. 2019). Pectobacterium species were frequently present as part of a pathogen complex.
It is now generally believed that potato blackleg caused by Dickeya and Pectobacterium are
predominately tuber-borne diseases, therefore infected seed tubers play an important role in the
33
disease cycle and elimination of infected seed tuber lots can aid in disease management
(Pérombelon 1992). Planting contaminated seed can cause stand loss or stem infection. However,
symptoms may not occur even when conditions are favorable, which allows the pathogen to
spread asymptomatically as seed tubers are produced, and results in larger outbreaks in
subsequent years (Pérombelon 1992). In storage, the contaminated tubers can develop soft rot
symptoms or remain symptomless. The disease cycle continues if the symptomless but
contaminated tubers are used for planting (Pérombelon 1992).
Application of genotypic approaches have made separation of bacteria species more
precise. Fingerprinting methods based on the widespread distribution of repetitive DNA elements
in genomes have been widely used as a tool to increase the taxonomic resolution at the species
level (Lanoot et al. 2004; Versalovic et al. 1991). Other methods, such as phylogenetic analysis
of 16S ribosomal RNA (rRNA), genes containing hypervariable regions, or other central
metabolism genes, can also be used to determine taxonomic relationships among different
bacteria species and strains (Van de Peer et al. 1996). Single nucleotide polymorphism (SNP)
analysis reveals a relatively high variation in gene gapA (coding for the glyceraldehyde-3-
phosphate dehydrogenase A) among Dickeya and Pectobacterium spp.(Cigna et al. 2017). A
high level of strain discrimination has been detected using variable number tandem repeat
analysis among D. dianthicola strains isolated from multiple hosts, including Dianthus
caryophyllus, and Dahlia sp. and potato (Parkinson et al. 2015).
Although potatoes are grown in most U.S. states, only a few states produce large amounts
of seed potatoes. These seed potatoes are subject to certification protocols that include multiple
inspections throughout the growing season and in storage and a postharvest test (Frost et al.
2013; Powelson 2007). This system results in high quality seed potatoes, but if new pathogens
34
enter the system, it also can allow for swift dissemination of new diseases across the U. S. Maine
is a major source of potato seed to the Eastern states. At the beginning of the Dickeya outbreak in
2014, seed potato certification programs in the Northeastern U. S. (New York and Maine) did not
test seed potatoes for blackleg pathogens, but evidence indicates tight connection between seed
contamination and field disease development as blackleg is a seedborne disease. However, no
solid data were available in determining where the inoculum originated from except observing
the geographic incidence of disease (Johnson, 2016). Since then, testing has become routine.
The purpose of the study was to understand the origin of the primary inoculum causing
the blackleg outbreak in the Northeastern U. S. and to determine if the pathogen was clonal and
of a single origin, likely in one of the seed potatoes producing states, or if multiple D.
dianthicola taxa were present and if this pathogen was likely endemic to the Northeastern U. S.
For the present study, analyses included the BOX-PCR technique, and phylogenetic analysis of
16S rRNA and central metabolism genes to conduct a genotypic classification of D. dianthicola
strains isolated from various geographical locations to address this question.
2.2 MATERIALS AND METHODS
2.2.1 Sample collection
Symptomatic potato stems and tubers were collected from 2015 to 2019 during the
growing season as well as from storage, resulting in 1,183 samples collected. Samples were
primarily collected from commercial potato production fields by growers, consultants, or
vegetable pathologists, then directly shipped to our lab for diagnostic analyses. Each sample
represented an individual potato plant in one field. These samples were predominantly from
Maine (epidemic center), with the rest being from the eastern states of the US, including
35
Massachusetts, Pennsylvania, New York, Rhode Island, New Jersey, Virginia, North Carolina,
Maryland, Florida, Delaware and Michigan (Table 2-1).
2.2.2 Pathogen isolation
Bacterial isolates were obtained from blackened or rotted potato stems, decayed tubers, or
healthy-appearing tubers. Stem samples of potato were surface disinfected with 10% bleach
(6.25% NaOCl) for three minutes and rinsed in sterile water for three minutes. Approximately
two-centimeter segments were cut from potato stems near the transition between healthy and
diseased tissues. Five milliliters of sterile water were added to a sterile container, and then the
tissue segments were submerged, and held in the water for 5 min to allow the bacteria to release
from the tissue. To isolate bacteria from dormant tubers, a peel around the circumference of the
stem end of the tuber was submerged in sterile water in Ziploc bags. The bags were sealed after
air removal and incubated at 28 C for 48 hours.
Tissue saps derived from the above preparations were streaked on a crystal violate
pectate (CVP) plate (Hélias et al. 2012). The plates were incubated at 28 C over 24 hours.
Preliminary tests showed that D. dianthicola colonies formed later and did not grow as large as
other enterobacteria on CVP. Therefore, only small colonies that formed in cavities in CVP were
transferred to new CVP plates for isolation. Purified cultures were then transferred to tryptic soy
broth (TSB) and incubated at 28C overnight.
Pathogenicity assay was conducted with all the isolates by tuber inoculation. Four tubers
of potato ‘Lamoka’ were used per bacterial isolate as four replicates. An aliquot of 10 L of
bacterial suspension in tryptic soy broth (106 CFU/ml) was added to a pre-poked hole on the
tuber and sealed with Parafilm. The liquid medium without bacteria was used for control. The
36
treated tubers were incubated at 23 1 C for 3 days before disease was evaluated. Disease was
evaluated by measuring the length and width of a lesion from a dissected tuber.
2.2.3 Pathogen detection and identification
Genomic DNA was extracted from the stem- or tuber-derived sap using the FastDNA
SPIN Kit (MP Biomedical, Santa Ana, CA, USA). Genomic DNA was extracted from the pure
cultures for pathogen identification using the QiAamp DNA Mini Kit (QIAGEN, Germany).
DNA concentration was measured with NanoDrop 2000 (Thermo Fisher Scientific, Wilminton,
DE, USA) and adjusted to 10 ng/L. Polymerase chain reaction (PCR) was performed using
Dickeya-specific (genus level) primers pelADE (Nassar et al. 1996) and D. dianthicola-specific
primers DIA-A (Pritchard et al. 2013). PCR was performed in a 25 L total volume reaction
containing 17.9 L of sterile water, 5 L of 5x PCR buffer, with MgCl2 at a final concentration
of 0.25 mM dNTPs, 0.1 M of each pair of primers, 0.5 U GoTaq DNA Polymerase and 1 L of
DNA. The PCR reagents were purchased from Promega (Madison, MI). Primers were
synthesized in Integrated DNA Technologies (www.idtdna.com/pages).
2.2.4 Fingerprinting analysis
BOX-A1R-based repetitive extragenic palindromic-PCR (BOX-PCR) was used to
analyze genotypes of the bacterial isolates. The BOX element (BOX1A) was amplified using the
BOXA1R primer 5′-CTACGGCAAGGCGACGCTGACG-3′ (Koeuth et al. 1995). PCR
amplifications were performed as described above, except using 0.2 M of the primer. The
thermal cycler was programmed for an initial denaturation of 7 min at 95°C, followed by 30
cycles of 1 min at 94°C, 1 min at 53°C and 8 min at 65°C, with a final elongation of 15 min at
65°C. PCR amplicons were examined by electrophoresis of 6 L aliquots mixed with 2 L of
10 gel green (Biotium, Fremont, CA) through 1.5% agarose gels in TAE buffer.
37
2.2.5 Primer design for genotyping
Whole genome sequences of Dickeya dianthicola strain RNS04.9 (accession number:
CP017638.1) and strain ME23 (CP031560.1) were downloaded from the NCBI GenBank
(https://www.nlm.nih.gov/). Synteny analysis was performed using the MAUVE software
(Darling et al. 2004). Based on the genome comparison, strain-specific genes were selected to
design primers. Chromosome regions (ME23: TraC_4 1576824-1577768, RNS04.9: DDI_1427
1444469-1446052) was used for primer design using integrated DNA technologies. Primers
Anti_1 is specific to RNS04.9 which generates a 434-base-pair (bp) product, while primers
TraC_4 is specific to ME23 which generates a 418 bp product (Table 2-4). The two new
designed primers were tested for optimal annealing temperature by using gradient PCR, and
55C was determined for both pairs of primers. The specification of the two new pairs of primers
were validated by running PCR with strains in Type I and Type III. All the blackleg samples that
were DIA-A positive were re-analyzed using the new primer pairs Anti_1 and TraC_4. Number
of each genotype in each state was shown with the reanalyzed PCR results using the software
Tableau 10.2 (Tableau, Seattle, WA, USA).
2.2.6 Phylogenetic analysis
Segments of the 16S rRNA gene and segments of partial three central metabolism genes
(dnaX, recA and gapA) were amplified using PCR with primer pairs 27F/1492R, dnaXf/dnaXr,
recAf/recAr and gapA-7F/gapA-938R, respectively (Table 2-2). Amplicons generated by PCR
were purified using UltraClean 15 DNA purification kit (MO BIO, Carlsbad, CA). Amplicons
generated from dnaX, recA and gapA genes were directly sequenced using the corresponding
primer pairs. Amplicons generated from 16S rDNA were sequenced with four primers 519R,
907R, 1492R and 907F to guarantee the sequencing quality. Sequence data of gapA from 16
38
additional D. dianthicola were obtained from NCBI GenBank (Table 2-3). Phylogenetic analysis
of 16S rDNA and gapA was performed among the strains isolated in this study using MEGA7
(Kumar et al. 2016). While only gapA was used for phylogenetic analysis for comparison among
worldwide strains. A maximum likelihood phylogenetic tree was constructed with 500 bootstrap
replicates.
2.3 RESULTS
2.3.1 Disease detection and pathogen isolation
A total of 1183 samples of diseased potato plants with typical blackleg symptoms were
collected from 11 northeastern states in US. Most of the samples (680) came from Maine, where
disease incidence was higher than other states. Among these samples, 42%, 52%, 19% and 27%
diseased samples collected from 2015, 2016, 2017 and 2018 were D. dianthicola positive, but no
D. dianthicola was found in 2019 samples (Table 2-1). Representative states where a large
number of samples (>100) were collected included Pennsylvania and Massachusetts, where D.
dianthicola was detected in 39% and 46% of the total samples from each state, respectively.
Compared to Maine, the number of samples collected from Delaware, New Jersey, New York,
Rhode Island and Virginia were lower, which ranged from 12 to 69, while percent of D.
dianthicola positive samples ranged from 29% to 53%. The total number of samples received
each year declined from 512 to 61 in the years 2015 to 2019. This is likely due to greatly
increased testing by seed potato growers and buyers that resulted in elimination of infected seed
lots from the potato industry during the course of this study.
D. dianthicola grows slower than species in the closely related genus Pectobacterium and
Pectobacterium is often present in samples with Dickeya. As a result, isolation of D. dianthicola
was challenging and D. dianthicola isolates were recovered from only a small percentage of
39
samples that tested positive for Dickeya. In total, seventeen isolates of D. dianthicola were
obtained from plant samples collected between 2015 and 2016 (Table 2-2). Results of
pathogenicity assay showed that no differences were found among all isolates of D. dianthicola.
Table 2-1. Detection of Dickeya dianthicola in potato samples collected from Northeastern US,
and a smaller amount from Midwestern and Southern regions.
State 2019 2018 2017 2016 2015 Total
Delaware - - 1 (1) 7 (5) 4 (3) 12 (9)
Maine 7 x (0 y) 34 (9) 43 (8) 144 (77) 452 (170) 680 (264)
Maryland - - - 2 (2) - 2 (2)
Massachusetts 12 (4) 12 (0) 18 (12) 65 (32) 3 (3) 110 (51)
Michigan - - 9 (1) - - 9 (1)
New Jersey - - 25 (3) 33 (10) 11 (7) 69 (20)
New York 3 (0) 1 (0) 1 (0) 19 (10) 6 (5) 30 (15)
North Carolina - - - 6 (1) - 6 (1)
Pennsylvania 34 (8) 34 (5) 54 (27) 34 (10) 36 (24) 192 (74)
Rhode Island - - 18 (3) 25 (15) - 43 (18)
Virginia 5 (1) 1 (0) 13 (7) 11 (8) - 30 (16)
Total 61 (13) 82 (14) 182 (62) 346 (170) 512 (212) 1183
(471)
“-“: no sample available.
x total number of samples collected.
y the number of samples showing D. dianthicola positive.
40
Table 2-2. Dickeya dianthicola isolates obtained in this study.
Genotype Bacterial
Strain
State Plant tissue Target
gene
GenBank
Accession No.
Target
gene
GenBank
Accession No.
Type I ME30 Maine Potato stem 16S rRNA MN732907 gapA MN735191
Type I 16ME21T Maine Potato tuber 16S rRNA MN732910 gapA MN735196
Type I 16ME22T Maine Potato tuber 16S rRNA MN732909 gapA MN735195
Type I 16SBJ16 Maine Potato stem 16S rRNA MN732908 gapA MN735190
Type I 16LI01 New York Potato stem 16S rRNA MN732913 gapA MN735202
Type I 16LI02 New York Potato stem 16S rRNA MN732914 gapA MN735201
Type I 16LI04 New York Potato stem 16S rRNA MN732905 gapA MN735200
Type I 16JP03 Virginia Potato stem 16S rRNA MN732915 gapA MN735189
Type I 16JP05 Virginia Potato stem 16S rRNA MN732916 gapA MN735187
Type I 16MA08CT Massachusetts Potato tuber 16S rRNA MN732912 gapA MN735199
Type I 16MA15T Massachusetts Potato tuber 16S rRNA MN732906 gapA MN735198
Type I PA24 Pennsylvania Potato stem 16S rRNA MN732917 gapA MN735188
Type I 16MB01 New Jersey Potato stem 16S rRNA MN732920 gapA MN735192
Type II 16PA07 Pennsylvania Potato stem 16S rRNA MN732911 gapA MN735197
Type II 59W Maine Water 16S rRNA MN732921 gapA MN735203
Type II 16NJ11 New Jersey Potato stem 16S rRNA MN732919 gapA MN735194
Type III 16NJ12 New Jersey Potato stem 16S rRNA MN732918 gapA MN735193
2.3.2 Genotyping by fingerprinting and DNA sequencing of D. dianthicola
Three unique genomic fingerprint patterns were discriminated with BOX-PCR (Figure 2-
1, Table 2-2). The fingerprint patterns separated the 17 examined D. dianthicola strains into
three genotypes, which were designated as Type I, II and III.
Following BOX-PCR fingerprinting, D. dianthicola strains were further analyzed with
Sanger sequencing of 27F/1492R PCR amplicons, which covered nearly the whole region of 16S
rDNA. PCR amplification yielded products of approximately 1,500 bp when visualized on
agarose gels. According to the published whole genomes of D. dianthicola, there are seven
copies of 16S rRNA gene. Sanger sequencing reactions produced chromatograms with
overlapping peaks at some nucleotide sites as expected due to 16S rRNA polymorphisms. Both
in strain ME23 (CP031560.1) and RNS04.9 (CP017638.1), 20 out of 1535 bp nucleotide sites
were shown same polymorphisms within the seven copies, while another 11 sites of
polymorphisms were only present in strain RNS04,9 and another 3 sites only present in strain
ME23 (data was not shown here). Seven copies of 16S rRNA genes in strains collected in this
41
study were separated by sequence alignment with seven copies of 16s rRNA genes from
annotated genomes (CP031560.1 and CP017638.1). The allele with the highest variability was
selected for phylogenetic analysis. Dickeya dianthicola strains ME23 and RNS04.9 were used as
references, and D. dadantii 3937, D. solani IPO2222 and Erwinia amylovora CFBP1430 were
used as outgroups.
There were three single nucleotide polymorphisms (SNPs) in the region of gapA having
850 bp in length. Both dnaX and recA sequences were 100% identical among all isolates.
Therefore, sequences of 16S rRNA and gapA were used to genotype the strains. Strains in Type I
were grouped together by phylogenetic analysis of sequences of both 16S rRNA and gapA. Type
II and III were not separated by phylogenetic analysis, which may be a result of the higher
similarity between these two genotypes (Figure 2-2).
Because 16S rDNA sequences were not available for some D. dianthicola strains in
NCBI, gapA was again reanalyzed by adding more strains from countries out of USA, including
UK, France, Belgium, Morocco, Pakistan, Switzerland (Table 2-3). To confine the results to
country-to-country comparison, specific geographic information of American states was not
included here. The type I Dickeya dianthicola isolates from USA were clustered together in a
group that did not include strains from Europe or Africa. The four Type II and Type III isolates
were clustered with D. dianthicola strains isolated from other countries (Figure 2-3).
42
Table 2-3. Dickeya dianthicola strains retrieved from NCBI database.
NCBI reference
strain Country Isolated from
Collection
Year
GenBank
Accession No.
ME23 USA Potato 2015 CP031560.1
DE440 USA Potato 2016 PJJB01000011.1
WV516 USA Potato 2016 PJJC01000019.1
Ddi1 USA Potato No record Unknown
CFBP2015 France Potato 1975 VZQG01000010.1
SS70 Pakistan Potato 2017 QESZ01000027.1
CFBP1888 France Potato 1978 VZQE01000002.1
RNS 11-47-1-1A France Potato 2011 VYSC01000033.1
CFBP2982 France Potato 1988 VZQF01000020.1
S4.16.03.P2.4 Morocco Potato 2016 QZDN01000072.1
MIE34 Switzerland Potato 2013 VZQH01000012.1
S4.16.03.LID Morocco Potato 2016 QZDO01000064.1
GBBC2039 Belgium Potato No record CM001838.1
IPO980 Netherlands Potato No record CM002023.1
NCPPB3534 Netherlands Potato 1987 CM001840.1
NCPPB453 UK Dianthus caryophyllus 1957 CM001841.1
RNS04.9 France Potato 2004 CP017638.1
43
Figure 2-1. Gel electrophoresis of BOX PCR on Dickeya dianthicola strains. Most strains were isolated from potato tissues in 2016,
except ME30 and PA24 were isolated in 2015, and 59W was isolated from irrigation water in 2017. Strains were separated into three
types by DNA band patterns of BOX PCR.
44
Figure 2-2. Phylogenetic tree using maximum-likelihood analysis on Dickeya dianthicola strains
collected in this study, reference strains (IPO2222, 3939, ME23 and RNS04.9) and Erwinia
amylovora CFBP1430 (outgroup) obtained from the GenBank. The tree was constructed based
on integrated sequences of partial sequences the gapA (850 bp) and 16S rDNA (1440 bp).
Numbers next to the branching points indicate the relative support from 500 bootstrap replicates,
with only scores above 60 are shown. The number (0.010) of the scale represents the percentage
(1%) of genetic variation for the length of the scale.
45
Figure 2-3. Phylogenetic tree using maximum-likelihood analysis on Dickeya dianthicola strains
collected in this study and NCBI, representing seven countries, including USA, UK, France,
Belgium, Morocco, Pakistan, Switzerland. Labels in the phylogenetic tree were made up by
domestic location and strain ID. Dickeya dadantii 3937, D. solani IPO222 and Erwinia
amylovora CFBP1430 were referred as outgroup strains. The tree was constructed based on
integrated sequences of partial sequences the gapA (850 bp). Numbers next to the branching
points indicate the relative support from 500 bootstrap replicates, with only scores above60 are
shown. The number (0.020) of the scale represents the percentage (2%) of genetic variation for
the length of the scale.
46
2.3.3 Identification of genotypes of D. dianthicola
Reference strain ME23 was assigned as Type I, while reference strain RNS04.9 was
assigned as Type III by the phylogenetic analysis of 16S rRNA and gapA genes. By aligning the
whole-genome sequences of reference strains ME23 and RNS04.9, gene traC_4 producing DNA
primase TraC was selected as a strain-specific region for ME23, while DDI_1427 producing
antirestriction protein was selected as a unique region of RNS04.9 (Figure 2-4). Two pairs of
primers specific to Type I (Trac_4) and III (Anti_1) were designed accordingly (Table 2-4).
Table 2-4. Primers (F: forward; R: reversed) used for genotypic analysis of Dickeya dianthicola.
Primer Sequence (5’-3’) Target Annealing
Tm (C)
References
pelADE F: GATCAGAAAGCCCGCAGCCAGAT
R: CTGTGGCCGATCAGGATGGTTTTGTCGTGC
Dickeya spp. 58 (Nassar et al. 1996)
TraC_4 F: ACGGCACGACAGTGATTT
R: AACTCGGCGATCAACTCTTC
Type I D.
dianthicola
55 This study
Anti_1 F: CGCATCGTAGAGAAAGGTCAA
R: GACTGAGGTTCAGGCAGTTTAG
Type III D.
dianthicola
55 This study
DIA-A F: GGCCGCCTGAATACTACATT
R: TGGTATCTCTACGCCCATCA
Type I, II and III
D. dianthicola
55 (Pritchard et al. 2013)
gapA 7-F: ATCAAAGTAGGTATCAACGG
938-R: TCRTACCARGAAACCAGTT
gapA 54 (Cigna et al. 2017)
16S
rRNA
27F: AGAGTTTGATCCTGGCTCAG
519R: GWATTACCGCGGCKGCTG
907R: CCGTCAATTCMTTTRAGTTT
1492R: GGTTACCTTGTTACGACTT
16S rDNA 59 (Frank et al. 2008;
Mao et al. 2012)
Primer pairs Trac_4 (Type I specific) and Anti_1 (Type III specific) were confirmed by
PCR amplification of all 17 strains. The results were consistent with the fingerprinting results
(Table 2- 5, Figure 2-1). All Type I strains showed positive results with Trac_4, while Type III
strains showed positive result with Anti_1. Sufficient genomic data were lacked to construct
primers that could identify Type II strains. Therefore, an exclusive method was used to
determine if samples were likely infected with Type II strains which might be a heterogeneous
47
Type II group. To be specific, strains or samples that were DIA-A positive, Trac_4 negative and
Anti_1 negative were classified into Type II.
Figure 2-4. Multiple genome analysis of Dickeya dianthicola strains using MAUVE for
identifying a region for primer design. A: Pairwise alignment of genomes of D. dianthicola
strains ME23 (on the top) and RNS04.9 (on the bottom). The red boxes represent a homologous
region between the genomes that are internally free from genomic rearrangement. B: Zoomed-in
image of the regions in the red boxes in panel A, which was used for primer design.
48
Table 2-5. Genotype detection of Dickeya dianthicola strains using polymerase chain reaction
with primers Trac_4, Anti_1, and DIA-A.
Genotype Strain Trac_4 Anti_1 DIA-A
Type I ME23 (reference) Not available Not available Not available
Type I ME30 + - +
Type I 16ME21T + - +
Type I 16ME22T + - +
Type I 16SBJ16 + - +
Type I 16LI01 + - +
Type I 16LI02 + - +
Type I 16LI04 + - +
Type I 16JP03 + - +
Type I 16JP05 + - +
Type I 16MA08CT + - +
Type I 16MA15T + - +
Type I PA24 + - +
Type I 16MB01 + - +
Type II 16PA07 - - +
Type II 59W - - +
Type II 16NJ11 - - +
Type III 16NJ12 - + +
Type III RNS04.9 (reference) Not available Not available Not available
After validation of the primers Trac_4 and Anti_1, samples collected from 2015 to 2019
were re-analyzed using DIA-A, Trac_4 and Anti_1. Out of the 471 samples that were positive
for D. dianthicola confirmed by PCR with the DIA-A primers, since DNAs of many samples
were progressively degraded, 256 DNA samples showing a high quality were selected and
further analyzed using Trac_4 and Anti_1. Of 71 samples collected in Maine in 2015 and re-
analyzed, Type I D. dianthicola was detected in 67 (94%) of the samples. The remaining 4
samples appeared to be infected with Type II or a yet to be described type. No samples from
Maine in 2015 were Type III (Figure 2-5). Re-analyzed samples collected after 2015, including
106 in 2016, 53 in 2017, 13 in 2018 and 13 in 2019, represented all the listed northeastern states,
although the majority was from 2016 and 2017. Samples from New York, Rhode Island and
49
Delaware in 2016 and 2017 were all associated only with Type I D. dianthicola. Samples from
2018 and 2019 in those states were not analyzed because of the quality of DNA obtained from
the sample was insufficient. Although Type I was predominant in Pennsylvania, New Jersey and
Virginia samples, there were 10% to 33% Type II (or a yet-to-be described type) D. dianthicola
detected in samples from these states from 2016 to 2019. Type III was first observed in samples
in 2016, comprising 33% and 40% of the positive samples in Pennsylvania and New Jersey,
respectively. All samples collected from Massachusetts in 2016 and 2017 contained Type I D.
dianthicola, while all four positive samples collected in 2019 were Type III. Overall, Type I D.
dianthicola was the predominant genotype through the five years, comprising 95% of positive
samples in Maine, and 83% of the samples from all other states. The type II genotype or another
uncharacterized genotype was continuously present in at least one state every year through the
five years, but at relatively lower percentages than Type I. Type III was only detected in 2016 in
Pennsylvania and New Jersey, and 2019 in Massachusetts (Figure 2-5).
50
Figure 2-5. Genotypic distribution of Dickeya dianthicola in the Northeastern United States
from 2015 to 2019. Total of 256 isolates were used for analysis. Each pie represents a state of
sampling of the year, with the size of pie being the number of samples, and the number
associated with each color being a sample size of a specific genotype. Genotypes included blue
circle: Type I, orange circle: Type II, and green circle: Type III.
51
2.4 DISCUSSION
The 2015 blackleg epidemic was first observed in potato crops planted with seed potatoes
originating in Maine (Johnson, 2016; 2017). As such, it was suspected that the original
contamination in other states initiated from Maine. Initial results suggested multiple origins for
this outbreak since a strain isolated from potatoes in Wisconsin and Texas in 2016 is genetically
distinct from a strain isolated in Maine (Ma et al. 2019; Nasaruddin et al. 2019). The Maine
hypothesis was based on the fact that blackleg is a tuber borne disease, that Maine is the primary
seed potato supplier to states in the Northeastern U. S., and that at least some of the infected
crops in these states had been planted with seed potatoes from Maine. The outbreak led to
comprehensive testing of seed potatoes for Dickeya in Maine and a large reduction in losses due
to this pathogen within just a few years. This affected the current study by reducing the number
of samples that could be collected, and also demonstrated the efficacy that pathogen testing in
seed potato certification has in disease management.
In this study that blackleg disease in this outbreak was not caused by a single genotype of
D. dianthicola strain, although it is not clear whether these strains all came from the same
location. This contrasts with the D. solani outbreak in Europe and the Middle East, which was
caused by a single genotype that was probably a recent introduction to the potato industry
(Parkinson et al. 2015). By fingerprinting with BOX PCR, three D. dianthicola genotypes were
identified, namely Type I, II and III. Although they were discriminated in different groups, there
were no differences of pathogenicity and virulence among the groups. As expected, these types
were strongly related to geographic locations. The vast majority of samples collected from
Maine, and most of the samples from other states, had Type I D. dianthicola. This result is
expected if contaminated seed tubers from Maine were subsequently planted in other states.
52
However, from these results, it was not clear if the states outside Maine had D. dianthicola
before or during the outbreak. Genome-wide analysis will be performed in the following work to
assist on further investigation of D. dianthicola causing potato blackleg in USA and other
countries that export agricultural products to USA.
Interestingly, a small portion of samples showed Type II D. dianthicola. In Maine, Type
II was only found in few samples in 2015 and 2018, but not 2016 and 2017. This showed a
chronic disconnection and random distribution. In contrast, Type II was consistently detected
every year outside Maine. I hypothesize that Type I was likely associated with Maine seed
origination, but Type II may have been indigenous across all examined states or that Type II also
initiated from Maine but was more adaptive in the southern region outside Maine. More
importantly, Type III D. dianthicola was found in Pennsylvania, New Jersey and Massachusetts,
but never detected in Maine isolates. Information on where the seed potatoes originated from
was lacked for these samples, but our data suggests that the Type III strain may have spread from
another seed potato producing state or province since it has yet to be found in Maine. Dickeya
dianthicola has been reported in Wisconsin, which also exports seed to states on the east coast,
and strains from Wisconsin differ from those in Maine (Nasaruddin et al. 2019). Dickeya
chrysanthemi was also recently reported in potato, showing that additional Dickeya species are
present in the potato production system and suggesting that other species could cause future
epidemics (McNally et al. 2018).
I suspect that the pathogen has occurred in most potato growing areas at low inoculum
levels in either potato or in alternate hosts. Although D. dianthicola is a seedborne pathogen, it
does survive up to 6 months in soil and it can become established in surface water (Pérombelon
1992). In addition, the pathogen can be harbored and transported by other plants, such as weeds
53
and ornamentals and it can initiate an epidemic by spreading from other plant species (Parkinson
et al. 2015). Dickeya is well-known for causing asymptomatic infections that lead to severe
outbreaks when environmental conditions change. The weather conditions in 2014, which had
exceptional levels of rainfall, could have exacerbated this outbreak. Predicted climate change
effects, including warmer temperatures and more severe rain events will provide conditions
favorable to D. dianthicola, so the potato industry is likely to see future epidemics of this
pathogen.
Unlike some other important plant pathogens, there is no suggested center of origin for
soft rot Pectobacteriaceae. These data that were present here show that D. dianthicola strains in
the United States are more diverse than those reported from Europe or Africa. The Type I strain
was not found in collections other than in isolates from the United States, although the limited
number of strains available from other locations does not allow us to determine whether it is
present on other continents. The Type II and Type III strains were found in the United States,
Europe, and Africa. There has been no legal potato import from Europe or Africa into the United
States since 1913 and exports of potato from the United States to Europe or Africa are
uncommon. This suggests that Type II and Type III strains have either been long established in
all three regions or that they were spread by other hosts, such as ornamental plants. A large
number of ornamentals are imported annually from Europe and Africa into the United States and
from the United States throughout the world, providing an invasion route for D. dianthicola in
either direction (Wocial 2013).
Irrigation water has been investigated as one of the dispersal media of D. dianthicola
(Elphinstone et al. 2014). D. dianthicola isolated from river water in the United Kingdom has
helped explain the cross-infection between potato and ornamental hosts (Elphinstone et al. 2014).
54
The only D. dianthicola strain, 59W, isolated from water in Maine belonged to Type II. Type II
D. dianthicola was consistently distributed in the southern states, like Pennsylvania, New Jersey
and Virginia, but not in Maine. This suggests that either the seed potatoes originated in a state
where Type II is more prevalent or that this strain is more aggressive in southern states than it is
in Maine, possibly because it is better adapted to higher temperature.
In conclusion, the outbreak of blackleg of potato in the Northeastern United States was
caused by multiple strains of D. dianthicola, which have most likely existed in various potato
production areas for many years. Contaminated potato seed tubers have exacerbated the disease
epidemics in multiple ways, but the disease may also have been enhanced by recent changes in
weather conditions. In managing the disease, certified seed and pathogen testing are always keys
to reduce primary infection, but the change of environmental factors should be considered in
disease forecasting.
55
CHAPTER 3
PANGENOMIC ANALYSIS OF DICKEYA DIANTHICOLA STRAINS REVEALS THE
OUTBREAK OF BLACKLEG AND SOFT ROT ON POTATO IN USA
ABSTRACT
Dickeya dianthicola has caused an outbreak of blackleg and soft rot of potato in the
eastern half of the United States since 2015. To investigate genetic diversity of the pathogen, a
comparative analysis was conducted on genomes of D. dianthicola strains. Whole genomes of 16
strains from the US outbreak were fully assembled and compared to 16 reference genomes
retrieved from the NCBI GenBank. Among the 32 strains, eight distinct clades were
distinguished based on phylogenomic analysis. The outbreak strains were grouped into three
clades, with the majority of the strains in clade I. Clade I strains were unique and homogeneous,
suggesting a recent incursion of this strain into potato production from alternative hosts or
environmental sources. Pangenome of the 32 strains contained 6693 genes, 3377 of which were
core genes. By screening primary protein subunits associated with virulence from all USA
strains, it was found that virulence-related gene clusters, such as plant cell wall degrading
enzyme genes, flagellar and chemotaxis related genes, two-component regulatory genes, and
type I/II/III secretion system genes were highly conserved but type IV and type VI secretion
system genes varied. The virulent clade I strains encoded two clusters of type IV secretion
systems, while clade II and III strains encoded only one cluster. Clade I and II strains encoded
one more VgrG/PAAR spike protein than clade III. Thus, it was predicted that the presence of
additional virulence-related genes may have enabled the unique clade I strain to become the
predominant source of the US outbreak.
56
3.1 INTRODUCTION
The Pectobacteriaceae pathogens Dickeya and Pectobacterium are pectolytic bacteria
that cause blackleg and soft rot (BSR) on potato. These pathogens also infect numerous other
economically important vegetables, grain and ornamental crops (Adeolu et al. 2016; Dees et al.
2017; Duarte et al. 2004; Ekbataniamiri 2020; Gardan et al. 2003; Khayi et al. 2016; Ma et al.
2007; Parkinson et al. 2014; Perombelon and Kelman 1980; Samson et al. 2005; Sławiak et al.
2009; Tian et al. 2016; van der Wolf et al. 2014).
Dickeya dianthicola has been reported in more than 10 countries in the regions of North
America, Europe, North Africa, and the Middle East on potato, vegetable or ornamental plants
(Jiang et al. 2016; Marković et al. 2020; Nasaruddin et al. 2019; Oulghazi et al. 2017; Patel et al.
2019; Rosenzweig et al. 2016; Sarfraz et al. 2018; Toth et al. 2011). Dickeya dianthicola and D.
solani have emerged in European countries in the past decades and have severely affected the
European potato industries (Toth et al. 2011; van der Wolf et al. 2014). Dickeya dianthicola was
first detected causing stunting and slow wilting of Dianthus in the early 1950s in Denmark, then
in the Netherlands and UK (Hellmers 1958; Parkinson et al. 2015). Although D. solani has not
been found in the United States, D. dianthicola has caused an outbreak in the northeast U.S.
since 2015 (Jiang et al. 2016; Johnson 2016; Ma et al. 2018). Recently, Ge et al. (2020b) have
discovered that strains collected from outbreak samples can be divided into three distinct
genotypes, with one predominant genotype. Furthermore, D. dianthicola populations from
multiple hosts in European regions can be divided into additional genotypes (Parkinson et al.
2015).
Dickeya is a pectinolytic genus that produces large quantities of secreted plant cell wall
degrading enzymes (PCWDE) that are required for pathogenicity and that contribute to bacterial
57
growth in plants (Salmond 1994). The PCWDE and other pathogenesis- and survival-related
proteins or effectors are secreted or transported to the target cells via various secretion systems
(Russell et al. 2014; Wallden et al. 2010). For example, PCWDEs are secreted through the type
II secretion system (T2SS) under the control of quorum sensing (QS) system (Charkowski et al.
2012; Salmond 1994; Toth et al. 2006). Type III secretion system (T3SS) contributes to
pathogenesis of some pectinolytic bacteria, including D. dadantii, P. carotovora, P. atroseptica,
and D. zeae (Bell et al. 2002; Ham et al. 1998; Li et al. 2012; Rantakari et al. 2001; Yang et al.
2002). Other genes/gene clusters related to pathogenicity include genes required for flagella
motility and chemotaxis, iron acquisition, polysaccharides and biofilm synthesis, quorum
sensing, and CRISPR-Cas systems (Blin et al. 2020; Li et al. 2018; Motyka-Pomagruk et al.
2020).
Type IV secretion system (T4SS) promotes genetic exchange and/or effector
translocation with consequent impacts on virulence and genome plasticity. The T4SS is
classified into three main types: conjugative, DNA release and uptake, and effector-delivery
(Alvarez-Martinez and Christie 2009). The conjugative and DNA release and uptake systems
play important role in horizontal gene transfer, which allows prokaryotes to adapt to their
environment, and is a powerful driver in the acquisition of novel functions by bacterial
pathogens (Cascales and Christie 2003). In Gram-negative bacteria, the structure of T4SS is
composed of 12 protein subunits (virB1-virB11 and virD4). In general, DNA or effectors are
recruited by APTase analogues (consist of VirB, VirB11, and VirD4), then translocated between
extracellular space and the cytoplasm through the translocation channel (contains VirB6-VirB10)
and the pilus (composed of VirB2 and VirB5) (Chandran et al. 2009; Fronzes et al. 2009;
Wallden et al. 2010).
58
The Type VI secretion system (T6SS) is involved in mediating antagonistic or synergistic
communications against adjacent eukaryotes or bacteria (Russell et al. 2014; Wallden et al.
2010). The T6SS apparatus is a tubular structure consisting of a sheath of TssB and TssC, which
surround a tube built from stacked hexameric rings of the haemolysin co-regulated protein (Hcp)
(Brunet et al. 2014; Bönemann et al. 2009). The apparatus assembles on a baseplate complex
(TssE, TssF, TssG, TssK) and is attached to the cell envelope by the membrane complex (TssJ,
TssM, TssL). The trimer VgrG spike protein sits at the tip of the Hcp tube, which is sometimes
capped with a pointed PAAR (Proline-Alanine-Alanine-aRginine) domain-containing protein
(Bönemann et al. 2009). VgrG or VgrG/PAAR spike facilitates the secretion of substrates (or
effectors) to adjacent bacterial or eukaryotic cells by penetrating of the membrane of the
neighboring cell. In addition to VgrG or VgrG/PAAR spike, substrates of T6SS can also directly
bind within the pore of an Hcp hexamer and are secreted together as a substrate-Hcp complex
(Silverman et al. 2013). All characterized bacterial-targeting T6SS proteins function as toxins,
either by killing or preventing the growth of target cells. Transcriptome and comparative
genomic analyses conducted by Bellieny-Rabelo et al. found the T6SS associated with a
toxin/immunity pair in Pectobacterium strains (Bellieny-Rabelo et al. 2019).
Whole genome sequence (WGS) is a powerful tool for describing bacterial species
evolution and pangenome (Medini et al. 2005). Genes in the pangenome that are shared by all
members of the taxa are the core-genome, while genes observed in a subset of strains are
considered as the dispensable genome and genes present just in a single strain form a unique
genome (Lapierre and Gogarten 2009). From the genome-related research, genomic diversity and
evolution of the taxa of interest can be described by analyzing their pangenome. Putative genetic
59
differences can be screened out from dispensable or unique genomes to explain the differences in
virulence, morphology or other survival-related characteristics.
In this study, I reveal genetic variations of D. dianthicola and examine the variations
found in recent outbreak strains compared to each other and to previously collected strains in
order to describe biodiversity and emergence of new strains of D. dianthicola. Specific
objectives were to compare putative biological functions required for virulence or interbacterial
competition and to determine if D. dianthicola strains causing the current potato blackleg
outbreak in the United States differ from previously collected strains.
3.2 MATERIALS AND METHODS
3.2.1 Bacterial strains
A total of 32 D. dianthicola strains were analyzed, including 19 from USA and 13 from
elsewhere in the world (Table 3-1). Among the strains from USA, 16 were isolated from potato
(Ge et al. 2020b) and were whole-genome sequenced. Genome sequence data of three additional
strains from USA, one strain from Pakistan, two from Morocco, and 10 from Europe were
retrieved from the NCBI database (https://www.ncbi.nlm.nih.gov/genbank/).
60
Table 3-1. Dickeya dianthicola strains used in this study.
Strain name Assembly number Source Country USA State Year Host
ME23 GCA_003403135.1 NCBI a USA Maine 2015 Potato
DE440 GCA_002906725.1 NCBI USA Delaware 2016 Potato
WV516 GCA_002906735.1 NCBI USA West Virginia 2016 Potato
CFBP2015 GCA_009873535.1 NCBI France NA b 1975 Potato
SS70 GCA_003121805.1 NCBI Pakistan NA 2017 Potato
CFBP1888 GCA_009873515.1 NCBI France NA 1978 Potato
RNS 11-47-1-1A GCA_009874325.1 NCBI France NA 2011 Potato
CFBP2982 GCA_009873565.1 NCBI France NA 1988 Potato
S4.16.03.P2.4 GCA_003595075.1 NCBI Morocco NA 2016 Potato
MIE34 GCA_009874285.1 NCBI Switzerland NA 2013 Potato
S4.16.03.LID GCA_003595005.1 NCBI Morocco NA 2016 Potato
GBBC 2039 GCA_000365365.1 NCBI Belgium NA NR c Potato
IPO980 GCA_000430955.1 NCBI Netherlands NA NR Potato
NCPPB 3534 GCA_000365405.2 NCBI Netherlands NA 1987 Potato
NCPPB 453 GCA_000365305.1 NCBI UK NA 1957 Carnation
RNS04.9 GCA_002706485.1 NCBI France NA 2004 Potato
PA24 CP069595 This study USA Pennsylvania 2015 Potato
ME30 CP060830 This study USA Maine 2015 Potato
16SBJ16 CP069596 This study USA Maine 2016 Potato
16PA07 CP060833 This study USA Pennsylvania 2016 Potato
16NJ12 CP060832 This study USA New Jersey 2016 Potato
16NJ11 CP060829 This study USA New Jersey 2016 Potato
16ME21T CP069598 This study USA Maine 2016 Potato
16ME22T CP069597 This study USA Maine 2016 Potato
16MB01 CP069599 This study USA New Jersey 2016 Potato
16MA15T CP069600 This study USA Massachusetts 2016 Potato
16LI04 CP069601 This study USA New York 2016 Potato
16LI02 CP069602 This study USA New York 2016 Potato
16LI01 CP069603 This study USA New York 2016 Potato
16JP05 CP069604 This study USA Virginia 2016 Potato
16JP03 CP069605 This study USA Virginia 2016 Potato
59W CP060831 This study USA Maine 2016 water
a NCBI: National Center for Biotechnology Information. b NA: not available. c NR: not recorded.
61
3.2.2 Whole genome sequencing (WGS) and assembly
Bacterial DNA was extracted and prepared using the QIAamp DNA Mini Kit (QIAGEN,
Hilden, Germany) according to the manufacturer’s instructions. WGS was performed with index-
tagged libraries for each strain by paired-end sequencing at the CD Genomic (New York, USA)
on an Illumina HiSeq (Illumina Inc., San Diego, California, United States). The coverage was
greater than 100. Short reads were assembled using the Geneious Primer 2020.2.2 software
(Biomatters, Ltd., San Diego, CA, USA) by mapping to the reference genome of strain ME23
(CP031560). Draft genomes were then finished after closing gaps using the abundant pair
relationships of short reads through GapCloser (Luo et al. 2012). Raw reads used for gap-closing
were filtered by removing low quality, adapters and duplications with the use of FASTP (Chen et
al. 2018).
3.2.3 Genome annotation
Additional genome sequences of three USA strains and 13 non-USA reference strains
were downloaded from the NCBI genome database in a FASTA format. The reference genomes
along with the newly sequenced genomes were evaluated using the quality assessment tool
QUAST (Mikheenko et al. 2018). Gene features of the 32 genomes were then predicted using
Prokka v1.12 (Seemann 2014) using default settings. The newly assembled genome sequences
were deposited in the BioProject at NCBI with accession number PRJNA659753.
3.2.4 Pangenome analysis
Following the annotation using Prokka, pangenome analysis of all 32 strains were
performed using the Roary software package with its default settings (Page et al. 2015). Files
created by Roary were used for generating pan and core genome curves in R (Team 2013). Lists
62
containing all the predicted gene clusters that generated from Roary were uploaded to eggnog-
Mapper2 to identify the cluster of orthologs groups (COG) on the basis of an all-against-all
sequence comparison of the proteins (Huerta-Cepas et al. 2019). Subtyping of the 32 strains was
performed using RxAML (Huerta-Cepas et al. 2019) to identify single-nucleotide
polymorphisms (SNP) in the core genomes and to reconstruct a parsimony phylogenomic tree.
Phylogenetic trees were visualized using the online tool iTOL (Letunic and Bork 2019).
3.2.5 Comparison among USA strains of D. dianthicola genomes
Dickeya dianthicola strains from USA were clustered into clades I, II and III. Whole
genome comparison of strains in the three clades were computed with the use of the BLAST
Ring Image Generator (BRIG) v0.95 (Alikhan et al. 2011) to illustrate the similarity among the
genomes. Complete genome sequence of strain ME23 was used as the reference genome for
analysis. Similarity was determined using BLASTn.
To predict the genetic determinants for pathogenesis or survival related differences,
genomes from each clade were evaluated on the evolutionary distance using the Mauve software
(Darling et al. 2004). A set of common genes and a set of unique genes among the three clades
were analyzed using files generated from Roary. Venn diagrams were created using VennPainter
(Lin et al. 2016). The comparative analysis of the secretion system, two-component regulatory
systems, flagellar and chemotaxis, and PCWDEs were conducted using GenBank files generated
by Prokka, and diagrams were drawn using Illustrator for Biological Sequences (IBS) (Liu et al.
2015).
63
3.3 RESULTS
3.3.1 Genomic assemblies
Thirty-two genomes of D. dianthicola were used for comparative analysis, with 16 USA
strains being sequenced in this study (Table 3-1). Of the 16 genomes from USA strains, 12 were
assembled into one scaffold, and four were assembled into 6 to 12 scaffolds with no consecutive
gap longer than 10 bases (Table 3-2). The average size of the assembled genome was 4.88 Mb
with the range from 4,775,037 bp (16NJ12) to 4,909,063 bp (16MB01) (Table 3-2). In
measuring the quality of assembled genomes, N50 (minimum length of contigs in which 50% of
the genome are covered) ranged from 752,789 (16NJ12) to 4,909,063 (16MB01) (Table 3-2).
The calculated GC content fell within the range of 55.72 to 55.99 % (Table 3-2). An average of
4,279 predicted protein sequences (CDS) were annotated for each genome, ranging from 4,151
(16NJ12) to 4,388 (RNS-11-47-1-1A) (Table 3-2). For all 16 strains, the quantity of the
annotated rRNA were 22 and number of tRNA ranged from 72-81, which were nearly identical
to the two complete genomes ME23 (CP031560.1) and RNS04.9 (CP017638.1) (Table 3-2).
Intact sequences of rRNA indicated that the assembling pipeline was of good quality.
Except the two complete genomes ME23 and RNS04.9, the number of scaffolds present in the
remaining 14 reference genomes obtained from NCBI database was considerably higher (11-
108) than in the drafted genomes of the 16 USA strains newly obtained for this study (Table 3-
2). Another quality metric of reference assembly, the N50, was relatively lower for these strains.
Moreover, a significantly higher variation (55.60-56.32) in the %GC was observed among the
reference genomes than the newly sequenced ones (Table 3-2). To compare all 32 genomes, the
16 retrieved reference genomes were also annotated with same Prokka-based pipeline. The stated
quantities of tRNA (39-77) were often lower in the reference genomes, while the number of
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rRNA was 1 to 17 in contrast to 22 detected in herein reported newly sequenced genomes (Table
3-2).
Table 3-2. Genome statistics of Dickeya dianthicola strains.
Strain
No. of
scaffolds
Genome
size (bp) N50
%GC CDS rRNA
repeat
region tRNA tmRNA
ME23 1 4,909,058 4,909,058 55.72 4317 22 3 76 2
DE440 55 4,867,975 246,586 55.72 4321 8 3 68 2
WV516 103 4,906,266 214,389 55.60 4318 6 3 66 2
CFBP2015 55 4,785,831 107,754 55.74 4207 1 3 63 2
SS70 62 4,797,592 177,218 55.94 4217 5 3 61 2
CFBP1888 67 4,844,898 161,968 55.73 4276 1 5 64 2
RNS-11-47-1-1A 78 4,948,067 145,496 55.77 4388 1 4 61 2
CFBP2982 90 4,704,394 94,450 55.86 4171 1 1 62 2
S4.16.03.P2.4 101 4,865,147 92,028 55.67 4306 1 3 39 2
MIE34 94 4,677,677 89,071 55.90 4118 1 2 64 2
S4.16.03.LID 108 4,863,939 71,707 55.68 4300 1 3 39 2
GBBC2039 32 4,798,242 4,649,420 56.32 4235 4 6 59 2
IPO980 27 4,840,931 4,662,278 55.69 4227 5 5 66 2
NCPPB3534 100 4,867,392 4,775,960 55.71 4248 17 4 76 2
NCPPB453 11 4,676,060 462,956 55.99 4101 4 9 64 2
RNS04.9 1 4,720,132 4,720,132 55.96 4110 22 4 77 2
PA24 1 4,909,043 4,909,043 55.72 4318 22 3 76 2
ME30 1 4,909,051 4,909,051 55.73 4306 22 3 76 2
16SBJ16 1 4,909,059 4,909,059 55.72 4318 22 3 76 2
16PA07 9 4,800,845 1,060,962 55.99 4175 22 3 79 2
16NJ12 12 4,775,037 752,789 55.97 4151 22 4 81 3
16NJ11 7 4,813,906 1,130,583 55.97 4173 22 4 80 2
16ME21T 1 4,909,059 4,909,059 55.72 4318 22 3 76 2
16ME22T 1 4,909,042 4,909,042 55.72 4318 22 3 76 2
16MB01 1 4,909,063 4,909,063 55.72 4317 22 3 76 2
16MA15T 1 4,909,059 4,909,059 55.72 4317 22 3 76 2
16LI04 1 4,909,059 4,909,059 55.72 4318 22 3 76 2
16LI02 1 4,909,059 4,909,059 55.72 4318 22 3 76 2
16LI01 1 4,909,059 4,909,059 55.72 4317 22 3 76 2
16JP05 1 4,909,059 4,909,059 55.72 4318 22 3 76 2
16JP03 1 4,909,059 4,909,059 55.72 4318 22 3 76 2
59W 6 4,860,981 1,340,508 55.96 4209 22 3 72 2
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3.3.2 Pangenome
Gene accumulation curves showed that the pangenome plateaued at 6,693 genes, and core
genome kept at 3,205 genes, reflecting a stable core and an almost closed pangenome (Figure 3-
1A). The pangenome of the 32 D. dianthicola strains comprised 6693 CDSs, including 3205 core
genes (genes present in more than 31 strains), 172 soft core genes (genes present in more than 30
and less than 31 strains), 1288 shell genes (genes present in more than 4 and less than 30 strains),
and 2028 cloud genes (genes present in less than 4 strains) (Figure 3-1B).
By combining core and soft-core genes into one core category, genes in clades I, II and
III were sorted into COG; the outcomes of the attribution are depicted in Figure 3-1C. When
sorting the annotated genes into COG, 22.8% were categorized as unknown function which was
excluded from the graphical representation of the COG categories. The most abundant categories
in the core genome were genes involved in storage housekeeping functions, such as transcription
and translation (8.6%, 5.5%), and different metabolism categories (inorganic ion transport and
metabolism 10.5%, amino acid metabolism and transport 9.8%, energy production and
conversion 7.8%). The shell genomes had a larger portion of genes associated with mobile
genetic elements (MGE) such as transposons and bacteriophages (transcription (11.0%),
replication, recombination and repair (16.3%)), which was also the most enriched category
amongst the cloud genomes (11.6%, 19.4% respectively). Genes involved in functions other than
the above two were considerably more prevalent in the core gene pool, compared to the shell and
cloud genes.
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Figure 3-1. Pangenome statistics of 32 Dickeya dianthicola strains. (A) Pangenome curve
generated by plotting the number of genomes (X axis) and number of conserved genes (dotted
line) or total genes (solid line) (Y axis). (B) Size and distribution of genes within subgroups
including core (in blue color) and soft-core genes (in orange) shared by more than 30 strains,
shell genes (in grey) shared by 5 to 30 strains and cloud genes (in yellow) found in less than 5
strains. (C) Percentage of each cluster of orthologs group that distributed in core (in blue), shell
(in grey) and cloud genes (in yellow), Cluster of orthologs groups include a: metabolism, b:
storage and processing, and c: cellular processes and signaling.
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3.3.3 SNPs-based phylogeny
The 32 strains were classified into eight clades (I-VIII) using phylogenetic reconstruction
based on SNPs (Figure 3-2). Lineages of D. dianthicola contained differential levels of
observable diversity. Particularly, there was a distinct distribution of USA strains into three
different clades (I, II, III), which was consistent in matching the three genotypes described by Ge
et al. (2020b). Clade I consisted of the majority of strains from USA (n = 15), while the
remaining four of the USA strains were clustered into clade II and III. Strains from European
countries were more diversified into five clades (III, IV, V, VI and VIII). One strain from Asia
(Pakistan) was solely clustered in clade VII. One strain from the USA was clustered with two
European strains, and two strains from Africa (Morocco) were also clustered with two different
European strains. Two strains out of the 32 were isolated from non-potato sources, with one in
clade II and one in clade III.
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Figure 3-2. Geographic and phylogenetic relationship of Dickeya dianthicola strains used in this
study. (A) Pie chart showing the geographic origin of Dickeya dianthicola strains included in this
study. Strains are colored based on country of origin, USA in orange, Belgium in aquamarine,
France in purple, Morocco in neon green, the Netherlands in yellow, Pakistan in vivid blue,
Switzerland in Emerald green, and the UK in purple in Irish. (B) Phylogenetic tree of 32 strains
established based on single nucleotide polymorphisms (SNPs) of the core genome, with color
codes indicating the country of origin described in (A). Fifteen out of 19 strains from the USA
were clustered within clade I. Three strains from the USA were clustered within clade II. One
strain from USA was clustered with two other European strain into clade III. Two strains out of
the 32 were isolated from non-potato sources, with one in clade II and one in clade III.
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3.3.4 Analyses of USA strains
To identify the region of interest in clades I, II and III containing USA strains of D.
dianthicola, one strain from each clade was selected for comparative analysis. Strains with high
integrity genomes (ME23, 16PA01, RNS04.9), each with 3760 conserved genes were selected as
representative. Clade I by strain ME23 shared 116 genes with clade II strain 16PA07 genome
and shared 50 genes with clade III strain RNS04.9 genome (Figure 3-3). Furthermore, 391
unique genes were present in the genome of ME23.
Similarities among the genomes was illustrated by comparing genomic nucleotide
sequences using BLAST. Genomic nucleotide sequences of strains were compared using
BLASTn to reference strain ME23. Graphical output of BRIG analysis displayed an overview of
identity and the major features related with virulence. The features included secretion systems,
two-component regulatory systems, PCWDE and flagella motility and chemotaxis (Figure 3-4).
Genomes of D. dianthicola in clade I possessed nearly identical genomic structures to that of
ME23, while multiple regions of substantial variation were observed in genomes of strains in
clade II and III (Figure 3-4). By combining the results from COG clusters, shell and cloud genes
were associated with bacteriophage or transposon-elements.
70
Figure 3-3. Whole genome alignment and comparison of orthologous genes from clades I, II and III of Dickeya dianthicola from
USA. (A) Mauve progressive alignment of RNS04.9 (clade III) genome, 16PA07 (clade II) genome, and ME23 (clade I) genome. (B)
Venn diagram showing the number of clusters of orthologous genes shared and unique among clades I, II and III.
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Figure 3-4. BLAST Ring Image Generator (BRIG) analysis of genomes of Dickeya dianthicola
strains clustered in clades I, II and III against reference strain ME23. Reference features related
with virulence were labeled in the outermost layer, including secretion system in red, with types
I, II, III, IV and VI, two-component regulatory system in light blue, plant cell wall degrade
enzymes (PCWDE) and flagellar and chemotaxis related coding sequences (CDS) in black.
72
Screening for PCWDE showed that all strains shared a set of extracellular enzymes with
same number of copies, including pectate lyase, pectate disaccharidelyase, pectinesterase,
polysaccharide lyase, rhamnogalacturonate lyase, and cellulase family glycosylhydrolase. In
addition, D. dianthicola strains in clades I, II, and III all contained conserved T1SS, T2SS and
T3SS gene clusters, which are used by many Gram-negative pathogenic bacteria in transporting
effectors or some other proteins. Flagellar- and chemotaxis-related genes were also conserved.
The T4SS and T6SS gene clusters differed among the three clades of USA strains. Two
clusters of T4SS system, containing 18 core components were found in clade I, while only one
cluster of T4SS system was found in clade II, consisting of 8 core components, and one cluster in
clade III, consisting of 9 core components (Figure 3-5). The T4SS DNA binding domain
containing protein was encoded downstream of the T4SS system cluster 1 in all clades. Twelve
core T6SS components were highly conserved in all three clades (Figure 3-6). Four VgrG, three
PAAR and four hcp genes were found in clade I and clade II, while only three VgrG, two PAAR
and three hcp genes were discovered in clade III (Figure3-6). Additionally, there was one
additional VgrG/PAAR spike genes in clade I and clade II with Type II Toxin-antitoxin system
(CcdA/CcdB) upstream of this cluster (Figure 3-6).
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Figure 3-5. Schematic map of type IV secretion system in clades I, II and III of Dickeya dianthicola from USA. Arrows indicate
putative transcriptional units with directions. Long distant intervals were disconnected by cut lines. T4SS components depicted in blue
color and hypothetical proteins depicted in grey color. T4SS components include two clusters (cluster 1: virB1/ virB2/ virB3/ virB5/
virB6/ virB8/ virB9/ virB11; cluster 2: virB1/ virB2/ virB3/ virB5/ virB6/ virB8/ virB9/ virB10/ virB11). Both cluster 1 and cluster 2
were found in clade I, while clade II had cluster 1 only, and clade III had cluster2 only. T4SS DNA binding domain containing protein
(coded by DDILJCIA_01468, AGKNFJGG_01395, EAMBJKPE_01341) were found in all three clades.
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Figure 3-6. Schematic map of type VI secretion system in clades I, II and III of Dickeya dianthicola, including T6SS components
(coded by tssA/ tssB/ tssC/ tssE/ tssF/ tssG/ tssJ/ tssK/ tssL /tssH and tssM) in light blue color, PAAR in green, VgrG in vivid blue, hcp
in red, T6SS-related rshB loci in red octagon, and hypothetical proteins coding genes in grey color. Arrows indicate directions of
transcription.
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3.4 DISCUSSION
The newly sequenced genomes in this study were assembled by mapping to the reference
genome ME23 with Geneious Primer 2020.2.2, which has an intuitive interface equipped with
essential genomic tools for data analysis. De novo assembling through SOAPdenovo2 (Luo et al.
2012) was utilized to compare with the Geneious Primer. After closing the gaps generated during
the GapCloser assembly, longer and more complete sequences were obtained from Geneious
Primer plus GapCloser. Therefore, I took the advantage of the Geneious Primer for assembling
and GapCloser for gap closing, then switched to other tools for further analysis. In view of a high
demand of genomic sequences and the significant threat of D. dianthicola to potato production in
USA (Charkowski 2018; Hao et al. 2016; Johnson 2016), whole genomes of D. dianthicola
strains isolated during the blackleg outbreak and from representative regions in the USA were
sequenced. Through the above workflow, the 16 D. dianthicola genomes that were re-sequenced
and assembled in this study, 12 have been nearly closed to a full chromosome, and the remaining
4 contained only 6 to 12 scaffolds. Furthermore, they contained a complete number of rRNA.
Shortly after the start of the recent D. dianthicola outbreak in the United States, multiple
D. dianthicola genotypes were identified (Ge et al. 2020b). The extent of genetic variability in
this important pathogen needed to be clarified to understand disease epidemiology and pathogen
evolution and to aid in disease management. Therefore, pangenomic analyses of 32 D.
dianthicola strains were completed to obtain a comprehensive representation of the D.
dianthicola core- (3377 proteins) and pangenomes (6693 proteins). The number and the
representativeness of the genomes affect the status of pangenomes of a certain species (Rouli et
al. 2015). In a closed pangenome, new coding capabilities will not be discovered with the
continuous adding of new genomes (Bosi et al. 2015). Importantly, the number of sequences in
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this study was representative for the geographic origins and are sufficient for a nearly closed
pangenome of D. dianthicola. Attribution of the genes from the studied D. dianthicola
pangenome to functional COG categories showed overrepresentation of transcription-associated
groups and MGE in the cloud and shell pangenome parts. In this context, MGE promote bacterial
evolution through horizontal gene transfer, which frequently function through bacterial secretion
systems (Gyles & Boerlin 2014; Rodríguez-Beltrán et al. 2020).
PBSR can be caused by a number of bacterial species, but each particular outbreak of this
disease is typically caused by one predominant genotype probably due in part to contamination
and spread of that genotype in one or a few widely used seed potato sources. In the United
States, seed potatoes from a small number of sources in the northeastern quarter of the United
States appeared to be important during the early stages of the outbreak. In Europe, D. dianthicola
was isolated from potato in 1970s (Parkinson et al. 2009; Toth et al. 2011), and became a
predominant species, until it was supplanted by D. solani (Blin et al. 2020; Parkinson et al. 2009;
Patel et al. 2019; Sarfraz et al. 2018; Toth et al. 2011). The predominant species must have
highly competitive traits in fitness and pathogenicity. Dickeya solani has some advantages over
D. dianthicola. Dickeya solani is more efficient and effective in infecting and rotting potato
tubers, giving it a higher level of fitness and quick proliferation in infected tissues, primarily due
to a higher gene expression of pectate lyases and balanced frequencies of two alleles in the
VfmB protein involved in quorum sensing (Blin et al. 2020), as well as a quick colonization
(Toth et al. 2011).
Dickeya solani emerged as a potato pathogen recently and was quickly spread from seed
potato fields in the Netherlands throughout Europe, the Middle East, Africa, and China through
the seed trade (Chen et al. 2015; Toth et al. 2011). Currently, D. solani isolates in potato are
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highly homogeneous, reflecting its recent emergence (Motyka-Pomagruk et al. 2020). Dickeya
dianthicola strains from potato show a stark contrast to D. solani. By comparing genomes of all
available D. dianthicola strains, it was found that it appears to have a clonal distribution across at
least three continents, reflecting ecological evolution and possible interference by trade of
agricultural products (Carvajal-Yepes et al. 2019; Shahbandeh 2020).
An exceptionally high level of distinction was found among the eight clades of D.
dianthicola genomes through a SNP analysis of the core genomes. The predominant USA strains
were distinct from the European strains (Ge et al. 2020b; Parkinson et al. 2015). Clade III was
found in other countries, but clade I and II were unique to USA and clade I had extraordinarily
high homogeneity within the collected bacterial isolates. Interestingly, three genotypes identified
from our previous work consistently fall into three clades (I, II, and III) obtained in this study,
namely the former genotypes I, II, and III corresponded to clades I, II, and III, respectively.
Clade I was a predominant population in the US outbreak as previously reported (Ge et al.
2020b; Parkinson et al. 2015). The characteristic genome of clade I possibly enables D.
dianthicola to be more efficient in adapting to the ecological niches, such as capabilities for
temperature adaption, competition or survival.
The homogeneity and predominance of the clade I population indicated the outbreak of
PBSR in the United States was primarily caused by one strain. The primary pathogenicity genes
in D. dianthicola, such as the PCWDE and quorum-sensing genes, are conserved. Some genes
that may contribute to virulence differ among clades. For example, Clade I encode two copies of
the T4SS, whereas clades II and III only encode one copy and the clades differed in the secreted
proteins associated with the T6SS. Either or both of the T4SS and T6SS differences may affect
strain fitness. It is possible from pangenomic analysis that clade I strains have pathogenic
78
advantages over other clades. However, these differences do not fully explain clade I strains as
being predominant over others, so further experimental studies should be conducted. One
supporting evidence from previous studies (Ge et al. 2020b) is that clade I (or genotype I)
consistently showed up in Maine every year in the five years of data collection, while clade II
only showed up in 2015 as a small subset in Maine and disappeared since then.
Clade I and II strains possessed an additional VgrG/PAAR spike genes than clade III
strain, with Type II Toxin-antitoxin system (CcdA/CcdB) upstream of the VgrG/PAAR genes,
although whether the adjacent toxin can be secreted by T6SS and act on neighboring cells
remains unknown. According to other studies, rhsB gene (coding for deoxyribonuclease RhsB) is
delivered into target cells in a VgrG-dependent process in D. dadantii, and also closely
associated with VgrG spike in D. dianthicola (Bellieny-Rabelo et al. 2019; Koskiniemi et al.
2013), but their functions need to be further confirmed. Nonetheless, the differences of T4SS and
T6SS might partially explain why clade I population was dominant in the PBSR outbreak and
these gene clusters are important targets for future fitness and pathogenicity studies (Ge et al.
2020b).
Currently, there is no enough evidence to explain how the clade I strain emerged and
caused the outbreak of PBSR. Since it had additional copies of secretion system or pathogenicity
related factors, it might be a variant from clade II or other clades by horizontal gene transfer
(Arber 2014; De la Cruz & Davies 2000). Although clade I of D. dianthicola has been
predominant in the outbreak, it does not mean we should ignore the other clades. Since other
clades are present in the environment, additional outbreaks with these strains could occur and
therefore screening protocols need to be able to detect all clades. Dickeya dianthicola has a wide
host range and the clades not currently detected in the United States could enter through trade in
79
ornamental plants or seed and could have a large impact on agricultural production (Toth et al.
2011).
In summary, genomic constructions and compositions determine the distribution and
dominance of a unique strain of Dickeya dianthicola that was the cause of the recent PBSR
outbreak in the northeastern USA in recent years. I infer that the presence of additional copies of
virulence-related genes allowed clade I (or Type I as previously described by Ge et al. 2020b)
population to be predominant over the other strains. This can be a foundation in understanding
the epidemic of PBSR in potato production.
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CHAPTER 4
PATHOGEN COMPLEX AND MICROBIAL ASSOCIATION OF POTATO
BLACKLEG AND SOFT ROT IN NORTHEASTERN AMERICA
ABSTRACT
Potato blackleg and soft rot (PBSR) which can be caused by multiple bacterial species
has become a serious problem in the Northeastern US since 2015. The aim of this study was to
examine the taxa of causal agents and their microbial associations. Potato plants showing
blackleg symptoms were collected from northeastern states. Bacteria were isolated from plant
samples. Polymerase chain reaction (PCR) was conducted with primers specific to Dickeya or
Pectobacterium spp. Illumina sequencing was conducted on the V3-V4 region of 16S rDNA
from the samples, which were analyzed for bacterial communities based on operational
taxonomic units. Samples were divided into four groups: D: samples containing Dickeya only; P:
Pectobacterium only; DP: both Dickeya and Pectobacterium; and N: neither of the two genera.
Pectobacteriaceae was the predominate family in sample groups D, P, and DP. Genera Dickeya
and Pectobacterium prevailed in the microbial community when they each existed alone, while
Dickeya surpassed Pectobacterium when they coexisted. Pseudomonas, Acinetobacter, and
Providencia were always associated with potato samples as endophytes. Among the pathogens,
D. dianthicola was the only species present within the Dickeya genus, while species varied
within Pectobacterium genus, with P. parmentieri, P. polaris, P. carotovora subsp. carotovora,
P. carotovora subsp. odoriferum being the most prevalent presumptive species. Isolates of the
four presumptive species and P. carotovora subsp. brasiliensis were identified by sequencing the
gapA and confirmed to be pathogenic on potatoes. Thus, PBSR was caused by intergeneric or
81
intrageneric species of Dickeya and Pectobacterium that contribute collectively to the disease
complex.
4.1 INTRODUCTION
Potato (Solanum tuberosum) is the third most important food crop in the US, and its total
production is estimated at 25.2 million US tons per year (U.S. Department of Agriculture 2019).
Production has been threatened by blackleg and soft rot (BSR) of potato in northeastern U.S.
since the 2015 outbreak, resulting in millions of dollars lost to the potato industry (Charkowski
2018). Although multiple bacterial species cause PBSR, Dickeya dianthicola has been identified
as the most prevalent species causing PBSR in the region (Hao et al. 2016; Jiang et al. 2016;
Johnson 2016; Ma et al. 2018; Patel et al. 2019). It is believed the bacterium may contaminate
and stay in/on dormant tubers during storage periods and cause field symptoms when these
tubers are planted.
Besides D. dianthicola, other species in genera Dickeya, such as D. chrysanthemi, D.
solani, and D. dadantii have been found potato samples and confirmed to be pathogenic to potato
(McNally et al. 2018; Ngadze et al. 2010; van der Wolf et al. 2014). Dickeya zeae and D.
aquatica were isolated from an irrigation pond adjunct to a potato field, but never found in
potato samples (Parkinson et al. 2014). Species in the genus of Pectobacterium are soil
inhabitants, which are well adapted to survive as saprophytes in the soil until a host plant is
reachable (Aizawa 2014). Owing to their existence in soil and wide host range, Pectobacterium
spp. cause soft rot diseases on potato and a wide range of vegetable crops, including carrot,
cabbage, maize, and sugar beet (Ma et al. 2007). Pectobacterium carotovora, in the family of
Pectobacteriaceae, is a diverse species consisting of P. carotovora subsp. carotovora, P.
carotovora subsp. odoriferum and P. carotovora subsp. brasiliensis, which are all causal agents
82
of PBSR (Duarte et al. 2004; Gallois et al. 1992; Gardan et al. 2003; Zhang et al. 2016). In
addition, P. parmentieri (formerly P. wasabiae) from potato, which was once classified within P.
wasabiae from Japanese horseradish (Goto and Matsumoto 1987; Khayi et al. 2016), has been
found in potato plants and other crops all over the world (Baghaee-Ravari et al. 2011; De Boer
et al. 2012; Ma et al. 2007; Ngadze et al. 2012; Pitman et al. 2008; Rahmanifar et al. 2012).
Pectobacterium atrosepticum (formerly P. carotovora subsp. atrosepticum) causes blackleg in
the field and soft rot of tubers during storage (Pérombelon and van der Wolf 2002), which is very
host specific to potato. These bacteria, however, may live in the rhizosphere of cultivated plants
and weeds without causing disease. One newly named bacterium, P. polaris, was always
associated with PBSR, but requires a wound on plants or high concentration of pathogen to cause
disease (Dees et al. 2017). The distribution of these species within the genus Pectobacterium
vary, depending on geographical location of samples.
With such diversified species and their distribution, regardless of whether they are soil
inhabitants or invaders, potato plants may be exposed to multiple species of bacteria that are
potentially causal agents of PBSR. How these bacteria interact in plant infection needs further
investigation. In this study, the interested subject was the microbes associated with PBSR that
occurred in the US outbreak. If multiple species of Dickeya and Pectobacterium can cause
PBSR, was PBSR outbreak in the US caused by a single species or multiple species? Therefore,
the objectives of this study were to analyze the structure of bacterial communities in potato
disease samples in circumstances with or without the presence of PBSR pathogens and
characterize the associated pathogenic bacterial species.
83
4.2 MATERIALS AND METHODS
4.2.1. Disease samples
Potato stems and tubers showing PBSR symptoms were collected from fields in most of
the Northeastern US states from 2015 to 2020, where PBSR outbreak occurred. DNA was
extracted using FastDNA SPIN Kit (MP Biomedical, Santa Ana, CA, USA). Disease was
confirmed by PCR with primer pairs pelADE targeting on Dickeya spp. and PEC targeting on
both Dickeya and Pectobacterium spp. (Ge et al. 2020b). Potato samples collected in 2015 to
2017 have been described in previous studies and were used in this study for microbial analysis
and pathogen isolation. Seventy-six samples, including 73 with PBSR symptoms and 3 without
PBSR symptoms, were randomly subsampled for microbial analysis. In the 73 symptomatic
samples, 61 tested positive for Dickeya spp. and possibly positive for Pectobacterium spp. and
12 only Pectobacterium spp. positive. The three non-BSR-symptomatic samples were Dickeya
and Pectobacterium negative (Table 4-1).
Table 4-1. Bacterial detection in potato samples using polymerase chain reaction (PCR) with
primers pelADE targeting on Dickeya spp. and PEC targeting on both Dickeya and
Pectobacterium spp.
State State
code
Total
samples
Dickeya
+ z
Dickeya
-
Pectobacterium
+
Pectobacterium
-
Maine ME 16 12 2 14 2
Massachusetts MA 11 11 0 11 0
Pennsylvania PA 10 8 1 9 1
Rhode Island RI 9 7 2 9 0
New Jersey NJ 10 9 1 10 0
New York NY 5 4 1 5 0
Virginia VA 5 4 1 5 0
Michigan MI 4 1 3 4 0
Delaware DE 5 5 0 5 0
Florida FL 1 0 1 1 0
Total 76 61 12 73 3 z “+” indicate a positive PCR reaction and “-” indicates a negative reaction.
84
4.2.2 Metagenomic sequencing
Concentration of DNA from the 76 samples was adjusted to 10 ng/l and submitted to
Michigan State University Genomic Core Facility (East Lansing, MI, USA) for metagenomic
sequencing in 2018 spring. Illumina compatible amplicon libraries of the V3-V4 hypervariable
region of the 16S rRNA gene were amplified using barcoded Illumina compatible primer pair
b341/806r (Caporaso et al. 2012; Juck et al. 2000). This generated a PCR amplicon
encompassing both the V3 and V4 regions. Sequencing was performed in a 2x250 bp paired end
format using a 500 cycle v2 reagent cartridge on Illumina MiSeq platform (Illumina Inc., San
Diego, CA, USA). The raw reads are deposited in the NCBI Sequence Read Archive (SRA) and
can be found with BioProject accession no PRJNA664821.
For community analysis, 1% relative abundance (RA) was used as a cut-off point. Any
species with RA > 1% were counted, otherwise was considered as negative. By combining PCR
assay and RA values, the samples were classified into four groups, which included group N: no
Dickeya nor Pectobacterium spp.; group P: containing Pectobacterium spp.; group D: containing
Dickeya spp.; and group DP: containing both Dickeya and Pectobacterium spp.
4.2.3 Bacterial isolation and identification
Sequencing analysis with QIIME. The standard operating pipeline QIIME was used to
process and analyze Illumina sequencing data (Bolyen et al. 2019). Generated sequences were
modified by trimming off primers and adapters. The quality of the sequences in FASTQ format
was analyzed after pooling all forward or reverse sequences. Overlapping paired-end reads were
denoised and stitched together. Operational taxonomic unit (OTU) was used to classify bacteria.
Alpha diversity, referring to the diversity within a sample, was expressed by the species richness
and species diversity. Observed OTUs in certain sampling depth was analyzed to express the
85
species richness. Shannon diversity index was also calculated, which measures both species
richness and inequality between species abundances. Significance of observed OTUs and
Shannon diversity index among the four groups were analyzed using Kruskal-Wallis H test at
= 0.05. The 341f/805r region of 16S rRNA gene in Silva 132 QIIME-compatible database was
used for reference. Abundance in levels kingdom, phylum, class, order, family and genus was
calculated. RA was used to describe the percent composition of each OTU.
Sequencing data processing with MOTHUR. The MOTHUR software pack (version
1.39.5) was used only for the analysis at species level by analyzing OTUs (Schloss et al. 2009).
Sequences were processed according to the MiSeq SOP (https://mothur.org/wiki/miseq_sop/),
including reducing sequences and PCR errors, finding unique sequences, aligning sequences to
the reference alignment (reference database: silva.bacteria.fasta), and assessing error rates.
FASTA format of sequences of each OTU were printed out, and the output was BLASTed to 16S
rRNA database which was downloaded from NCBI using Python (Rossum 1995). Parameters
were applied to filter out five hits with the top five scores. The hit with the top score was
designated as the final species in excel. Only sequences of Dickeya spp. or Pectobacterium spp.
were selected for analysis with RA.
4.2.4 Bacterial isolation and identification
Potato stems showing PBSR symptoms were cut from the base and dipped into sterile
water for 5 min to let bacteria discharge. A portion of tissue was cut from symptomatic tubers
and ground in a 50 mL centrifuge tube containing sterile water. Bacteria were isolated by
streaking the sap onto crystal violate pectate (CVP) plates (Hélias et al. 2012), and incubated at
28 C for 24 hours in darkness. Purified colonies formed in cavities on the plates were
86
transferred to tryptic soy broth (TSB) and incubated at 28 C overnight. Bacterial cells in TSB
were mixed with glycerol and stored at -80C.
Isolated bacteria were revived from -80C freezer by streaking on tryptic soy agar (TSA)
plates. Pure-cultured colonies were transferred to TSB and incubated at 28C overnight. One
milliliter of cell suspension was used for DNA extraction with QIAamp DNA Mini Kit
(QIAGEN, Germantown, MD, USA). DNA concentration was measured with NanoDrop 2000
(Thermo-Fisher, Waltham, MA USA) and adjusted to 10 ng/L. Metabolism gene gapA (coding
for protein glyceraldehyde-3-phosphate dehydrogenase A) was amplified by PCR using primer
pair gapA-7F/gapA-938R (Cigna et al. 2017). The thermal cycler was programmed for an initial
denaturation of 5 min at 94°C, followed by 40 cycles of 30 sec at 94°C, 30 sec at 54°C and 30
sec at 72°C, with a final elongation of 10 min at 72°C. Amplicons from PCR were cleaned using
UltraClean 15 DNA purification kit (MO BIO, Carlsbad, CA, USA), and then sequenced. The
sequences are deposited in NCBI Genbank; study accession numbers are MW027689 –
MW027797. Phylogenetic analysis was performed using MEGA7 software (Kumar et al. 2016).
The maximum likelihood phylogenetic tree was constructed with 500 bootstrap replicates.
4.2.5 Pathogenicity assay
The pathogenicity of Pectobacterium isolates was conducted using potato ‘Lamoka’ with
two inoculation methods. In the first method, washed potato tubers were stabbed to a depth of 1
cm with a pipette tip. Ten microliters of bacterial suspension at ~109 CFU/ml in TSB was
transferred into the hole which was sealed with Parafilm. Inoculated tubers were incubated at
room temperature (23ºC ± 2) for 5 days. Then the tubers were cut through the inoculation point.
Width and length of the lesion were measured and lesion size (width length) was calculated.
Ten P. parmentieri isolates, 11 P. carotovora subsp. brasiliensis isolates, 41 P. carotovora
87
subsp. odoriferum isolates and 33 P. Polaris isolates were selected for pathogenicity test on
tubers. Each isolate was randomly assigned to 4 tubers as replicates. The second method
consisted of stem injection. Four isolates of each species were randomly selected for
pathogenicity test on stems. Potato tubers were planted in potting mix in a plastic pot and
maintained at 25°C (day) and 15°C (night) in a greenhouse. Six-week-old potato stems were
injected with 100 l of 108 CFU/ml bacterial suspension at 2 cm above the soil line using a
syringe. Four stems were used for each isolate. The wound was sealed with Parafilm. Symptoms
were visually inspected. Both trials were arranged using completely randomized design with four
replicates. Three weeks after inoculation, stems were cut along the stem for disease evaluation.
For both tuber and stem inoculation assay, TSB was used as a negative control. This experiment
was conducted twice. Means of lesion sizes were compared by Tukey HSD multiple range test at
= 0.05 using the SAS software (SAS Institute Inc. 2015, Cary, NC, USA).
4.2.6 Bacterial growth on CVP medium
To compare the growth of Pectobacterium and Dickeya spp., 9 standard strains were
selected for this experiment (Table 4-2). Bacterial cultures of each strain from -80C freezer
were revived as described. After incubation in TSB overnight, bacterial concentration was
approximately 109 CFU/ml. Cell suspension was prepared with three concentrations including
109, 106 and 102 CFU/ml. Ten microliters of cell suspension of each concentration were
transferred onto CVP plates and incubated at 28C. Each isolate was replicated three times on
two plates with six replicates in total. Diameter of cavity was measured at 12, 24, 36 and 48 h
after incubation. The experiment was conducted twice.
88
Table 4-2. Dickeya and Pectobacterium spp. strains used for pathogen-bacteria interactions.
Pathogen Isolate Source
D. dianthicola ME30 University of Maine
P. parmentieri ME175 University of Maine
D. zeae 1686 A. Charkowski, Colorado State University
D. dadantii 3937 A. Charkowski, Colorado State University
D. solani IPO2222 A. Charkowski, Colorado State University
P. carotovora subsp.
brasiliensis
16MA04 University of Maine
P. carotovora subsp.
odoriferum
16MA30 University of Maine
P. polaris 16MA27 University of Maine
P. atroseptica ATCC33260 A. Charkowski, Colorado State University
4.3 RESULTS
4.3.1 Bacterial communities associated with PBSR
To understand the microbial community within PBSR, DNA of 76 samples were
analyzed for microbiome based on OTUs at 99% sequence similarity. After removing low-
quality and non-specific reads, a total of 10,362,620 reads were obtained from the 76 potato
samples from ten states, ranging from 57,643 to 207,222 per sample, with the median of
134,792. The number of reads was normalized to the smallest number of reads for alpha diversity
comparisons. Shannon diversity and observed OTUs (Figure 4-1) demonstrated that sample
group D had significantly (P < 0.05) lower bacterial diversity and evenness than groups N, P and
DP. Bacterial communities within sample groups DP, D and P were dominated by the family
Pectobacteriaceae, with RA of 45.9%, 58.4% and 45.8% accordingly (Figure 4-2A). At genus
level, Dickeya (RA = 52.9%) and Pectobacterium (RA = 36.0%) respectively dominated in
groups D and P (Figure 4-2B). Comparing to groups D and P, RA of Dickeya (22.0%) was much
higher than Pectobacterium (8.9%) in group DP.
89
Figure 4-1. Number of operational taxonomic unit (OTU) and Shannon evenness index of
bacterial community in potato tissues. Significance among groups was analyzed using Kruskal-
Wallis H test ( = 0.05). N: no Dickeya nor Pectobacterium spp.; P: containing Pectobacterium
spp.; D: containing Dickeya spp.; DP: containing both Dickeya and Pectobacterium spp.
90
Figure 4-2. Relative abundances of bacteria in potato samples at family level (A) and genus
level (B). Taxa with relative abundance < 0.001 were excluded). Samples were grouped
according to polymerase chain reaction (PCR). N: no Dickeya nor Pectobacterium spp.; P:
containing Pectobacterium spp.; D: containing Dickeya spp.; DP: containing both Dickeya and
Pectobacterium spp.
91
Genera including Acinetobacter, Pseudomonas, Providencia, Stenotrophomonas,
Sphingobacterium and others were found in samples containing either Dickeya/ Pectobacterium
or not (Table 4-3). Arthrobacter, Kouboulia, Sporosarcina and Anaerosinus were only found in
the group N which comprised lower levels of Dickeya and Pectobacterium (Table 4-3). With the
exception of Dickeya and Pectobacterium, a few genera were only detected in sample groups
comprising higher levels of Dickeya and Pectobacterium (DP, D, P), including Pantoea, Delftia,
Flavobacterium, Serratia, Ralstonia and Aliidiomarina (Table 4-3).
4.3.2 Distribution of Dickeya and Pectobacterium spp.
As causal agents of PBSR, genera Genera Dickeya and Pectobacterium were retrieved
and analyzed individually, as they are causal agents of PBSR. The 76 samples were also grouped
by location (state). States showed a significant difference in RA of Dickeya and Pectobacterium
(Figure 4-3A, C). States with samples containing Dickeya spp. were New York, Massachusetts,
New Jersey and Pennsylvania, and the highest RA for each state was 98.4%, 91.5% 96.6% and
94.8%, respectively. In Michigan, five samples showed extremely low RA of Dickeya (<0.4%),
but a wide range in RA of Pectobacterium (<76.0%). Sixteen samples from Maine and nine
samples from Rhode Island contained lower RA of Dickeya with lower range of RA, which
showed similar distribution on Pectobacterium. The highest RA of Dickeya was 78.7% in group
DP and 98.3% in group D. Meanwhile, the highest RA of Pectobacterium was 39.2% in group
DP and 88.1% in group P. RA of both Dickeya and Pectobacterium was substantially reduced
when they co-existed (Figure 4-2B, D).
92
Table 4-3. Relative abundance (%) of shared and exclusive genera of bacteria in four groups (D,
DP, P, and N) of potato samples showing symptoms of blackleg and soft rot.
Genus DPy (n = 22) D (n =22) P (n = 22) N (n = 10)
Ax
Acinetobacter 13.2 4.8 9.7 14.1
Providencia 7.8 1.5 2.8 12.6
Pseudomonas 13.8 18.1 11.2 22.0
Sphingobacterium 1.8 2.7 1.6 1.2
Stenotrophomonas 1.9 3.3 2.6 2.0
Unassigned 6.2 4.1 6.5 8.1
Comamonas 3.9 0.0 2.4 2.5
Myroides 1.8 0.0 1.3 3.0
Alcaligenes 0.0 0.0 1.9 5.1
Citrobacter 0.0 1.6 0.0 1.6
B
Anaerosinus 0.0 0.0 0.0 1.8
Arthrobacter 0.0 0.0 0.0 2.2
Koukoulia 0.0 0.0 0.0 2.0
Lachnoclostridium 5 0.0 0.0 0.0 1.4
Morganella 0.0 0.0 0.0 1.4
Paenalcaligenes 0.0 0.0 0.0 1.1
Enterobacter 0.0 0.0 0.0 1.4
Raoultella 0.0 0.0 0.0 1.1
Sporosarcina 0.0 0.0 0.0 1.8
C
Delftia 1.8 1.0 0.0 0.0
Dickeya 22.0 52.9 0.0 0.0
Flavobacterium 1.6 0.0 0.0 0.0
Pantoea 2.7 0.0 3.0 0.0
Pectobacterium 8.9 0.0 36.0 0.0
Serratia 1.5 0.0 0.0 0.0
Ralstonia 0.0 0.0 1.5 0.0
Aliidiomarina 0.0 0.0 1.5 0.0 x A, B and C were determined by the presence in types of samples N, DP, D or P. Group A contains the
genus only found in all samples; group B contains the genus only found in sample N; group C contains
the genus only found in sample DP, D, or P. y DP: containing both Dickeya and Pectobacterium spp.; D:
containing Dickeya spp.; P: containing Pectobacterium spp.; N: no Dickeya nor Pectobacterium spp.
93
Figure 4-3. Relative abundances of Dickeya and Pectobacterium spp. by geographic locations or
states (A and C) and sample groups (B and D) of PBSR. Samples were grouped (x-axis)
according to polymerase chain reaction (PCR) results. N: no Dickeya nor Pectobacterium spp.;
P: containing Pectobacterium spp.; D: containing Dickeya spp.; DP: containing both Dickeya and
Pectobacterium spp.
DE MA ME NJ PA RI VA NY FL MI
Rel
ativ
eab
und
ance
0
0.2
0.4
0.6
0.8
1
1.2
Dickeya
DP D P None
Rel
ativ
eab
und
ance
0
0.2
0.4
0.6
0.8
1
1.2
Dickeya
DE MA ME NJ PA RI VA NY FL MI
Rel
ativ
eab
un
dan
ce
0
0.2
0.4
0.6
0.8
1
1.2
Pectobacterium
DP D P None
Rel
ativ
eab
un
dan
ce
0
0.2
0.4
0.6
0.8
1
1.2
Pectobacterium
A B
C D
DP (n=22) D (n=22) P (n=22) N (n=10)
DP (n=22) D (n=22) P (n=22) N (n=10)
94
4.3.3 Presumptive bacterial species in genera Dickeya and Pectobacterium
To better understand the species community associated with PBSR, processed sequences
of each OTU from metagenomic sequencing were BLASTed into NCBI database of 16S rRNA
gene. Length of trimmed sequences ranged from 261 nt to 432 nt, with a mean of 423 nt.
Samples in group N were excluded here. All the species present in the alignment results with the
highest bit score (identical similarity) are included (Table 4-4). Due to a small fragment of 16S
rRNA gene sequence used in the blast, limited variable regions among species resulted in more
than one alignment with the highest bits score from one sequence. Percent composition of each
species relative to the total reads of Dickeya and Pectobacterium was calculated (Table 4-4).
Dickeya dadantii and D. dianthicola were the two species with almost same identical similarity
in V3-V4 region, resulting in same percentage of composition. However, only D. dianthicola
was detected by PCR and confirmed to be pathogenic to potato, while D. dadantii was not
detected in another study (Ge et al. 2020b). Compared to Dickeya spp., species community in
Pectobacterium were more complicated and differed greatly in each sample. Overall, P.
parmentieri, P. polaris, P. carotovora subsp. carotovora, P. carotovora subsp. odoriferum, were
the most prevalent species which were viewed as the presumptive causal agent of PBSR.
Pectobacterium carorovorum subsp. actinidiae, P. aroideanum, P. atrosepticum and P.
carotovora subsp. brasiliensis were found in few samples. Samples in group DP showed both
high percentage of Dickeya and Pectobacterium species.
95
Table 4-4. Relative abundance (%) of shared and exclusive genera of bacteria in four groups (D,
DP, P, and N) of potato samples showing symptoms of blackleg and soft rot.
Groupy Ddaz Ddi Par Pat Pca Pcb Pcc Pco Ppa Ppo
P (n = 22)
0 0 0 0 0 0 0 0 98 99
0 0 0 1 0 1 57 63 41 41
1 0 0 0 0 0 0 0 98 98
1 1 1 32 2 32 63 64 33 3
1 1 1 2 1 5 35 37 60 59
1 1 0 0 0 0 0 0 97 97
1 1 51 1 43 1 2 2 3 3
1 1 1 1 0 1 6 16 69 82
1 1 0 1 2 0 1 2 93 94
2 2 2 1 70 1 25 26 2 2
4 4 0 1 0 0 3 4 90 91
0 0 1 0 0 1 97 98 1 1
1 0 1 0 0 1 91 93 7 7
1 1 1 0 0 1 94 95 3 3
2 1 12 0 16 1 36 38 35 36
2 2 18 1 6 3 60 61 11 12
2 2 0 1 0 0 25 26 71 71
4 4 3 0 13 6 71 72 3 3
4 4 1 1 3 2 82 84 9 9
4 4 2 3 1 2 2 2 88 86
15 14 1 1 1 1 8 9 72 72
30 30 1 2 1 3 31 60 8 6
DP (n = 22)
17 16 1 1 1 2 77 78 3 3
17 16 22 1 33 29 14 14 14 15
20 20 2 2 1 2 4 10 63 61
20 20 1 1 1 1 17 39 37 37
22 22 1 0 1 0 29 62 14 15
26 26 1 0 71 0 0 0 2 2
33 32 1 1 1 2 43 44 19 19
38 38 9 1 25 1 16 16 9 9
40 40 0 1 1 1 1 1 45 53
40 40 0 0 0 0 0 0 54 55
42 42 1 1 1 1 54 54 1 1
48 47 0 1 0 0 0 0 42 43
55 55 0 1 1 1 19 38 4 4
56 56 0 0 0 0 0 0 38 38
59 59 0 1 0 0 10 10 26 26
72 71 0 1 0 1 23 24 3 3
79 78 0 0 1 0 1 3 8 17
96
Groupy Ddaz Ddi Par Pat Pca Pcb Pcc Pco Ppa Ppo
80 80 0 0 0 0 0 1 17 17
88 88 0 0 0 0 5 9 2 2
89 88 1 1 0 1 3 6 3 2
94 94 0 0 1 0 0 0 3 3
96 95 0 0 1 0 2 3 0 0
D (n = 22)
96 96 0 1 0 1 1 1 2 1
97 97 0 1 0 0 0 1 2 2
98 97 0 0 0 0 0 1 1 1
99 99 0 0 0 0 0 0 0 0
99 99 0 0 0 0 0 0 0 0
99 99 0 0 0 0 0 0 0 0
99 99 0 0 0 0 0 0 0 0
99 99 0 0 0 0 0 0 0 0
94 94 0 0 0 1 0 1 1 1
95 94 0 0 0 1 0 0 2 2
95 94 0 0 0 1 2 2 1 1
95 95 0 0 0 0 1 1 1 1
96 95 0 1 0 1 1 1 1 1
97 97 0 0 0 0 0 1 1 1
98 97 0 0 0 0 1 1 1 1
98 98 0 0 0 0 0 1 1 1
99 98 0 0 0 0 0 0 0 0
81 81 9 0 1 1 2 3 4 4
82 82 1 2 0 3 9 9 4 2
87 86 1 1 2 1 4 4 4 4
73 72 1 6 3 10 8 11 14 8
92 91 0 1 0 1 2 2 3 3
x Values of relative abundance were calculated as the percentage of reads related to each species on the total number
of reads related to genus Dickeya and Pectobacterium. y Bacterial groups include P containing Pectobacterium spp.,
D containing Dickeya spp., and DP containing both Dickeya and Pectobacterium spp. z Presumptive species in
genera Dickeya and Pectobacterium by blasting all V3-V4 sequences against the NCBI 16S rRNA database,
including D. dadantii (Dda), D. dianthicola (Ddi), P. aroidearum (Par), P. carotovora subsp. actinidiae (Pca), P.
carotovora subsp. brasiliensis (Pcb), P. carotovora subsp. carotovora (Pcc), P. carotovora subsp. odoriferum (Pco),
P. parmentieri (Ppa), and P. polaris (Ppo).
97
4.3.4 Pathogenicity and growth of Pectobacterium spp.
Pectobacterium species were preliminarily confirmed to present in the PBSR samples by
metagenomic analysis. To confirm the presence of these presumptive species, Pectobacterium
species were isolated as many as possible and 110 pure cultures were obtained. Phylogenetic
analysis of the gapA gene showed that all isolates were classified into five Pectobacterium
species that were associated with PBSR in Northeastern US, including P. parmentieri, P.
carotovora subsp. carotovora, P. carotovora subsp. brasiliensis, P. carotovora subsp.
odoriferum and P. Polaris (Figure 4-4). Pectobacterium carotovora subsp. carotovora was
excluded for pathogenicity test as only one isolate was obtained.
Results from stem injection assay showed that P. carotovora subsp. brasiliensis and P.
parmentieri caused the stem to be completely rotted and collapsed (Figure 4-5). However,
symptoms caused by P. polaris and P. carotovora subsp. odoriferum caused mild or non-obvious
symptoms outside stems, but internal degradation only observed after dissection (Figure 4-5).
This difference might be related with the ability of pectic enzyme secretion and pectate
degradation. Results from tuber inoculation assay showed that all isolates of Pectobacterium
species could cause soft rot on potato tubers (Figure 4-6A). There was no significant difference
of pathogenicity among species (Figure 4-6B).
98
Figure 4-4. Phylogenetic tree constructed based on partial sequences the gapA gene (850 bp)
using maximum-likelihood algorithm with strains of Pectobacterium spp., including P.
carotovora subsp. odoriferum (PCO), P. polaris (PPO), P. parmentieri (PPA), P. carotovora
subsp. carotovora (PCC), and P. carotovora subsp. brasiliensis (PCB), which were collected in
years 2015 (n = 37), 2016 (n = 51), and 2017 (n = 22). Reference strains (3-2, BC S7,
NBIO1006, BZA12, 67, IFB5485) and Escherichia coli O83:H1 (outgroup) were obtained from
the GenBank. Numbers next to the branching points indicate the relative support from 500
bootstrap replicates (only scores above 50 are shown). Colors in outer layer represent the five
Pectobacterium spp, and colors (legend) highlighted the sample ID in the middle layer represent
location (state) of potato samples.
99
Figure 4-5. Pathogenicity test of Pectobacterium spp. Species include P. carotovora subsp.
brasiliensis (PCB), P. carotovora subsp. odoriferum (PCO), P. parmentieri (PPA), and P.
polaris (PPO) on potato ‘Lamoka’ stems. Bacterial inoculum (100 l of 109 CFU/ml) was
injected using a syringe on a stem at around 5 cm from soil line and incubated in a greenhouse at
25C (day) and 15C (night). Symptoms included stem collapse (PCB and PPA), blackened
vascular (PCO and PPO).
100
Figure 4-6. Pathogenicity test of Pectobacterium spp. Species include P. carotovora subsp.
brasiliensis (PCB), P. carotovora subsp. odoriferum (PCO), P. parmentieri (PPA), and P.
polaris (PPO) on potato ‘Lamoka’ tubers. Potato tubers were inoculated adding 10 l bacterial
suspension at ~108 CFU/ml into a poked hole on a tuber, sealed with Parafilm, and were
incubated at 22C for 3 days. A) Decayed tissue was observed on inoculation point; B): Lesion
size was measured as width and length of a tuber dissected through the inoculation point. Filled
boxes represent range of lesion area (width length) and error bars represent standard deviation.
101
In forming cavities on CVP plates, P. polaris, P. carotovora subsp. odoriferum, P.
carotovora subsp. brasiliensis showed cavities in less than 24 h, while P. parmentieri and P.
atroseptica required longer than 24 h. Dickeya dianthicola and D. solani required around 48 h,
while other Dickeya species formed cavities within 24 h (Table 4-5). Furthermore, cavity sizes
of P. polaris, P. carotovora subsp. odoriferum, P. carotovora subsp. brasiliensis were
significantly larger than that of D. dianthicola and P. atroseptica under any concentration and
time point (Table 4-5).
Table 4-5. Cavity diameter (cm) of bacterial species belonging to genera Dickeya and
Pectobacterium estimated by measuring the colony diameter on crystal violet pectate agar plates
incubated at 28 C in darkness for 24 and 48 hours.
Pathoge
n
24 h 48 h
109
CFU/mL
106
CFU/mL
102
CFU/mL
109
CFU/mL
106
CFU/mL
102
CFU/mL
PCBx 1.66 a 1.28 a 1.14 a 2.63 a 2.60 a 2.45 a
PPO 1.48 abcd 1.21 ab 0.94 ab 2.23 ab 2.23 b 2.05 ab
DZE 1.55 ab 1.21 ab 1.06 a 2.15 b 2.05 bc 1.85 bc
DDA 1.50 abc 1.23 a 0.60 bc 1.99 b 1.95 bc 1.59 cd
PPA 1.36 bcd 0.65 d 0.50 c 2.10 b 1.85 c 1.33 de
PCO 1.28 d 1.03 c 1.01 a 2.08 b 1.89 bc 1.68 bcd
DSO 1.32 cd 1.08 bc 0.78 abc 1.93 b 1.73 c 1.98 bc
DDI 0.60 e 0.50 e 0.50 c 1.23 c 0.65 d 0.90 ef
PAT 0.64 e 0.49 e 0.53 c 1.35 c 0.54 d 0.50 f x Abbreviation of full name of pathogens, PCB: P. carotovora subsp. brasiliensis, PPO: P. polaris, DZA: D.
zeae, DDA: D. dadantii, PPA: P. parmentieri, PCO: P. carotovora subsp. odoriferum, DSO: Dickeya solani,
DDI: D. dianthicola, PAT: P. atrosepticum.
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4.4 DISCUSSION
PBSR is a complex disease that can potentially be caused by more than one species of
bacteria. Dickeya dianthicola has been frequently and almost exclusively reported to be a
predominant causal agent of PBSR during the recent outbreak. In this study, PCR and
metagenomic approaches were employed to analyze pathogen composition and microbiota
associated with PBSR. It has been found that in a majority of plant samples, D. dianthicola was
the only species in the genus Dickeya. However, PBSR was not only caused by D. dianthicola
but caused or accompanied by several Pectobacterium spp. and maybe other potential pathogenic
bacteria. Therefore, PBSR could be a complex.
Dickeya and Pectobacterium are within the family Pectobacteriaceae. Thus, it was not
surprising that Pectobacteriaceae were the most abundant bacteria in the samples from diseased
plants, and that Dickeya spp. or Pectobacterium spp. was the most abundant genera present.
From our observations, it was found that Dickeya was more aggressive than Pectobacterium in
potato infection, and when they coexisted in potato tissues, PBSR was more severe than when
they occurred individually. This synergistic phenomenon was confirmed by subsequent
experimentation (chapter 5). Bacteria in families Pseudomonadaceae, Moraxellaceae and
Comamonadaceae, or the genera Pseudomonas and Acinetobacter were also common in many of
the potato samples, but their potential roles in disease development are not clear.
Plants are a driving force for the composition and diversity of microbiomes. Soils,
particularly rhizospheric soils provide unique environments for diversified endophytes and
epiphytes (Hardoim et al. 2015; Mendes et al. 2013; Hartmann et al. 2008; Buchholz et al. 2019).
In addition, PBSR pathogens may have strong associations and interactions with these
microorganisms. Comparing taxa in the four groups, genera such as Acinetobacter,
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Pseudomonas, Providencia, Stenotrophomonas and more were found in all four groups, which
might be endophytes in rhizosphere or phyllosphere that spread systemically via the xylem.
Arthrobacter, Sporosarcina and Anaerosinus were also commonly found in soil, but were only
detected in samples without Dickeya or Pectobacterium. Interestingly, several genera, such as
Alcaligenes, Pantoea and Ralstonia with very low level of abundance were only present in
diseased samples along with the pathogens Dickeya spp and Pectobacterium spp. These bacteria
may share common substrate with Dickeya spp. Pantoea and Ralstonia are worthy of further
investigation on their association with PBSR, since they were reported as unconventional or
important plant pathogens (Hayward 1991; Coutinho & Venter, 2009).
The results from conventional PCR and next generation sequencing were consistent in
diagnostic results, with few exceptions. For example, in samples that were detected by PCR as
Dickeya spp. or Pectobacterium spp. positive, exhibited higher relative abundance for Dickeya
and Pectobacterium spp. by next generation sequencing. Limitations for most 16S-sequence-
based microbiome studies are that they are short reads and do not give a fine resolution for
classification at species level. In this study, V3-V4 regions were used, which contain the most
variable regions and made the final sequence length of around 435 nt. A longer fragment favors
the analysis at species level. However, there was still a high similarity among species within
genera Dickeya or Pectobacterium, thus species-level results in this study were presumptive.
Dickeya dianthicola and D. dadantii were the two species that could not be clearly distinguished.
As such, using PCR, D. dianthicola has been detected in all samples with species-specific
primers to confirm its presence and isolated from a small percentage of samples, while D.
dadantii and D. chrysanthemi were not detected in the samples by PCR (chapter 2). This may be
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the reason why D. dianthicola has been reported as the primary causal agent in the northeastern
region, which was based on bacterial isolation and PCR detection.
Species in genera Dickeya and Pectobacterium were persistently reported worldwide but
without coexistence. In this study, it was proved that Dickeya and Pectobacterium existed
together and played important roles in causing PBSR. Pectobacterium within samples contained
multiple presumptive species, including P. parmentieri, P. polaris, P. carotovora subsp.
odoriferum, P. carotovora subsp. carotovora and P. carotovora subsp. brasiliensis. Dickeya.
dianthicola, P. parmentieri and P. carotovora subsp. brasiliensis resulted in complete collapse of
potato stems, so that they were regarded as the most aggressive pathogens to potato stems and
tubers (Figure 5, Ge et al. 2021). As most of Pectobacterium spp. are soil inhabitants, their
presence may not necessarily mean that they are pathogens. With such a rich community of
pathogenic bacteria, the severe soft rot in potato storage can be readily explained. The
importance of interacted and molecular behavior within a bacterial community has been
highlighted in recent research, and a metabolic complementarity is required for a stable bacterial
consortium (Egland et al. 2004; Kim et al. 2008).
In conclusion, D. dianthicola, P. parmentieri, P. carotovora subsp. brasiliensis, P.
carotovora subsp. odoriferum, and P. polaris were frequently found in the disease complex of
PBSR. The existence of D. dianthicola restricted the growth of Pectobacterium spp. to some
extent. In addition, appearance of the above pathogens reduced the microbial diversity in potato
plants.
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CHAPTER 5
INTERACTION BETWEEN DICKEYA DIANTHICOLA AND PECTOBACTERIUM
PARMENTIERI IN POTATO INFECTION OF POTATO UNDER FIELD CONDITIONS
This chapter has been published in Microorganisms:
Ge, T.L., Ekbataniamiri, F., Johnson, S.B., Larkin, R.P., and Hao, J.J. Interaction between Dickeya
dianthicola and Pectobacterium parmentieri in potato infection under field conditions. Microorganisms
2021, 9, 316.
ABSTRACT
Dickeya and Pectobacterium spp. both cause blackleg and soft rot of potato, which can be
a yield-reducing factor for potato production. The purpose of this study was to examine the
interaction between these two bacterial genera causing potato infection, and subsequent disease
development and yield responses under field conditions. Analysis of 883 potato samples
collected in the Northeastern USA using polymerase chain reaction determined that Dickeya
dianthicola and P. parmentieri were found in 38.1% and 53.3% of all samples, respectively, and
that 20.6% of samples contained both D. dianthicola and P. parmentieri. To further investigate
the relationship between the two bacterial species and their interaction, field trials were
established. Potato seed pieces of ‘Russet Burbank’, ‘Lamoka’, and ‘Atlantic’ were inoculated
with bacterial suspensions of D. dianthicola at 107 colony-forming units (CFU)/ml using a
vacuum-infiltration method, air dried, and then planted in the field. Two-year results showed that
there was a high correlation (P < 0.01) between relative yield loss and percentage of inoculated
seed pieces. In a secondary field trial conducted in 2018 and 2019, seed pieces of potato
‘Shepody’, ‘Lamoka’ and ‘Atlantic’ were inoculated with D. dianthicola, P. parmentieri, or
mixtures of both species, and then planted. In 2019, disease severity index as measured by the
most sensitive variety ‘Lamoka’ was 16.2 with D. dianthicola inoculation, 10.4 with P.
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parmentieri, 25.4 with inoculation with both bacteria. Two-year data had a similar trend. Thus,
D. dianthicola was more virulent than P. parmentieri, but the co-inoculation of the two species
resulted in increased disease severity compared to single-species inoculation with either
pathogen.
5.1 INTRODUCTION
Blackleg and soft rot (BSR) of potato (Solanum tuberosum) are caused by many bacterial
species in the genera Dickeya and Pectobacterium. The predominant species of bacteria
responsible for the disease varies depending on geographical location. For example,
Pectobacterium atroseptica was dominant in Europe before 1970, but Dickeya dianthicola and
followed by D. solani have become dominant in some European countries in recent decades
(Toth et al. 2011; van der Wolf et al. 2014). An outbreak of PBSR in the Northeastern USA was
caused by D. dianthicola in 2015 and the following years, while D. chrysanthemi was found in
the central USA, and Pectobacterium spp. were found everywhere in the USA (Hao et al. 2016;
Jiang et al. 2016; Johnson 2016; Ma et al. 2018; McNally et al. 2017, 2018; Patel et al. 2019).
Symptoms of PBSR were expressed as rot and blackened stems (blackleg), wilting plants and
decayed tubers (soft rot), which has threatened potato production, resulting in millions of dollars
lost by the potato industry (Johnson 2016)
BSR caused by a pathogen complex adds an additional layer of difficulty in the
development of effective control measures. One plant may be infected by more than one
pathogen (Fitt et al. 2006; Lamichhane and Venturi 2015). Such a complex disease structure is
determined on the interactions between pathogen species, host plant, biotic and abiotic
environmental factors (Dung et al. 2014; Fitt et al. 2006; Hibbing et al. 2010; Mazzaglia et al.
2012; Short et al. 2014).
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It is now generally believed that D. dianthicola is primarily a seed-borne pathogen, and
most Pectobacterium spp. are soil inhabitants but can be seed borne as well. Therefore, stored
tubers are the most important source in harboring bacterial pathogens and initiating disease.
Pathogens surviving in soil can colonize roots then penetrate and move into the xylem
(Czajkowski et al. 2009). Some studies indicate that P. parmentieri is less virulent than P.
carotovora, owing to the lack of Type III secretion system (T3SS) (Kim et al. 2009; Nykyri et
al. 2012). However, I have demonstrated that P. parmentieri isolates are highly pathogenic on
both tubers and stems of potato (Ge et al. 2018b).
In the USA PBSR outbreak that happened in 2015 and following years, Dickeya
dianthicola was determined to be the predominant pathogen involved, based on its primary and
predominant detection and isolation from field samples. However, the detection frequency of this
species progressively declined in the following years. In contrast, some Pectobacterium spp.
were found on postharvest tubers and later identified in symptomatic potato plants in increasing
amounts in subsequent years. Common species of PBSR causal agents included P. parmentieri,
P. polaris, P. carotovora subsp. carotovora, P. c. subsp. oderiferium, and other Pectobacterium
spp. (Ge et al. 2018a; Ge et al. 2018b; Jiang et al. 2016; Ma et al. 2018). The above species
were classified as one species, Erwinia carotovora before 1981, but were further differentiated
into several subspecies soon afterwards (Gardan et al. 2003; Perombelon and Kelman 1980;
Samson et al. 2005). In addition, P. parmentieri extended its distribution beyond the
Northeastern USA causing blackleg and soft rot of potato (Dung et al. 2012).
Whether the co-existence of Dickeya and Pectobacterium spp. has advantages for
pathogen infection is a key subject that impacts both biological studies and disease management.
Our questions were: Is the predominance of bacterial species influenced by environmental
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factors or bacterial virulence? Is there an enhanced response when both species co-occur in the
same infected region? The aims of this study were to understand how bacterial infection affected
potato growth and the corresponding yield responses. Specifically, I wanted to determine how
multiple species of pathogens interact, and how they affect disease development and yield
responses.
5.2 MATERIALS AND METHODS
5.2.1 Frequency and distribution of Dickeya dianthicola and Pectobacterium parmentieri in
naturally infected potato
From 2015 to 2020, symptomatic potato stems and tubers showing PBSR were collected
from fields in most of the northeastern states by growers, consultants, or plant pathologists. All
samples were processed and assayed at the University of Maine. Segments of diseased stem
tissue or peels of tubers were obtained from the samples. Bacteria were extracted from the tissue
sap by incubating them in sterile distilled water (Ge et al. 2020b). Genomic DNA was extracted
from the stem- or tuber-derived sap using the FastDNA SPIN Kit (MP Biomedical, Santa Ana,
CA, USA). Concentration of DNA was estimated using NanoDrop 2000c spectrophotometer
(Thermo Fisher Scientific Inc, Wilmington, DE, USA), and diluted to 10 ng/µL for polymerase
chain reaction (PCR). A total of 883 DNA samples were selected and amplified by polymerase
chain reaction (PCR) with primer pairs of PW7011 specific for P. parmentieri, and DIA-A
specific to D. dianthicola (Kim et al. 2012; Pritchard et al. 2013). PCR amplifications were
performed in a 25 L total volume reaction system containing 17.9 L of sterile water, 5 L of
5x PCR buffer, with MgCl2 at a final concentration of 0.25 mM dNTPs, 0.1 M of each pair of
primers, 0.5 U GoTaq DNA Polymerase and 1 L of DNA. All PCR reagents were from
Promega Corporation (Madison, MI). The thermal cycler for primer DIA-A was programmed for
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an initial denaturation of 5 min at 94°C, followed by 35 cycles of 1 min at 94°C, 30 s at 53°C
and 1 min at 72°C, with a final elongation of 10 min at 72°C, while the annealing temperature of
primer PW7011 was set at 67°C for 30 s.
5.2.2 Tuber inoculation using vacuum infiltration
Dickeya dianthicola strain ME30 and P. parmentieri strain ME175 were cultured on
crystal violate pectate (CVP) plates at 28 C for 48 h. The culture was transferred to tryptic soy
broth (TSB) and incubated on an incubator shaker overnight at 28 C and 120 rpm. The chamber
was disinfected with 10% bleach every time after inoculation of each treatment. At planting
inoculation, the prepared bacterial culture was diluted with non-autoclaved tap water and
adjusted to 107 CFU/mL as working inoculum. Well-suberized seed pieces were washed and
submerged into the bacteria suspension in a vacuum chamber (BVV10GL, BEST VALUE
VACS, USA) and tightly sealed. The chamber was held between -60 to -80 kPa for 15 min
(Czajkowski et al. 2010; Ge et al. 2020a). A control was set up by treating seed pieces with tap
water (pathogen free) as ‘non-inoculated’ through the same procedure in the vacuum chamber.
The treated tubers were air dried and planted one week after inoculation.
5.2.3 Effects of bacterial inoculation on potato growth
Field studies were conducted in 2020 at Presque Isle, Maine. A randomized complete
random block design (RCBD) was used with four replicate blocks. Potato varieties ‘Lamoka’,
‘Atlantic’, and ‘Russet Burbank’ were inoculated with D. dianthicola strain ME30 using the
vacuum-infiltration method as described above. For each variety, 50 tubers were planted on May
2020, and each treatment contained a mixture of bacteria-inoculated and bacteria-free tubers at
different percentages, including 0, 10%, 20%, 40% and 80%, which were arranged in a RCBD.
Fertilizer (N:P:K = 14:14:14) was applied at time of planting at a rate of 1,100 lb/A. Nuprid 2SC
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(a.i. 21.4% imidacloprid) was also applied at time of planting at 20 oz/A to control insects. Plant
stand was evaluated on 13 July 2020. Plants were visually inspected for the development of
PBSR symptoms. Disease severity was evaluated weekly or every other week after symptoms
appeared and rated from 0 to 5 with 0 being healthy and 5 being dead plants. Potato vines were
killed with two applications of Reglone at 1.5 pt/A. Potatoes were harvested on 2 October 2020.
Total yield was measured.
5.2.4 Interaction between D. dianthicola and P. parmentieri in potato infection
Field studies were performed in 2018 and repeated in 2019 in Presque Isle, Maine.
Dickeya dianthicola strain ME30 and P. parmentieri strain ME175 were used. Seed pieces of
potato cultivars ‘Lamoka’, ‘Atlantic’, and ‘Shepody’ were inoculated with either ME30, ME175,
or a mixture of both bacterial species using the vacuum-infiltration method as described above.
For the co-inoculation, cell suspension of strains ME30 and ME175 were mixed together at a 1:1
ratio with the final concentration of 107 CFU/mL, which was used for vacuum infiltration. The
treated tubers were air dried for at least one week before planting. A RCBD was used with four
replications in the field. Thirty seed pieces were planted in each plot on 25 May 2018 and 28
May 2019. Field management was as described in the above trial. Emergence was assessed as the
number of emerged plants per plot on 2 July 2018 and 1 July 2019. Plants were visually
inspected for the development of blackleg symptoms using a 0 to 5 disease severity scale as
described above. Disease incidence was calculated as DSD = number of symptomatic stems /
total number of stems. Disease severity index (DSI) was calculated as DSI = [sum (disease scale
frequency × score of disease scale)] / [(total number of stems) × (maximal disease severity
index)] × 100. Potatoes were harvested on 5 September 2018 and 19 September 2019. Total yield
was measured.
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5.2.5 Statistical analysis
Statistical analysis was conducted using the SAS statistical program (SAS university
edition, Red Hat (64-bit) version, SAS Institute Inc., Cary, NC, USA). Categorical variables
were analyzed using a chi-square test. Numerical variables, including emergence, disease
incidence, disease severity index and yield were analyzed using the ANOVA procedure with
Tukey’s multiple range test at a significance level α = 0.05. Relative emergence loss and relative
yield loss (Y) were regressed against percentage of seed infection (X) using linear regression
equation Y = b0 + b1X. Relative emergence loss was expressed as (noninfected plot stand count –
Infected plot stand count) / noninfected plot stand count. Relative yield loss = (yield in
noninfected plot – yield in infected plot / yield in noninfected plot).
5.3 RESULTS
5.3.1 Frequency and distribution of Dickeya dianthicola and Pectobacterium parmentieri in
naturally infected potato
Potato samples collected from fields were assayed using PCR to detect both Dickeya and
Pectobacterium spp. Out of the 883 samples, 761 were from potato stems, and 122 were from
potato tubers. Primers DIA-A specific to D. dianthicola and PW7011 specific to P. parmentieri
were used in the detection. Through the six years, 38.1% of samples contained D. dianthicola
and 53.3% of samples contained P. parmentieri. Furthermore, 20.6% of samples contained both
D. dianthicola and P. parmentieri, and 29.2% of samples neither contained D. dianthicola nor P,
parmentieri (Table 5-1). Chi square test showed that the percentage of D. dianthicola positive
stem samples (40.3%) was significantly (P < 0.001) higher than in tubers (23.8%), whereas the
percentage of P. parmentieri positive stems samples (51.8%) was significantly (P < 0.01) lower
than on tubers (63.1%) (Table 5-2).
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There was a trend that the percentage of samples infected by P. parmentieri increased
during the years, from 30.4% in 2015 to 95.3% in 2020 (Table 5-1). The percentage of total
samples infected by D. dianthicola declined from 41.7% to 9.5% through the six years (Table 5-
1).
Table 5-1. Detection of Dickeya and Pectobacterium spp. in symptomatic potato stems or tubers
using polymerase chain reaction (PCR).
Year
Number of
samples
D. dianthicola
(%)
P. parmentieri
(%)
D. dianthicola + P.
parmentieri (%)
2015 319 133 (41.7) 97 (30.4) 39 (12.2)
2016 230 114 (49.6) 134 (58.3) 72 (31.3)
2017 171 60 (35.1) 132 (77.2) 50 (29.2)
2018 81 14 (17.3) 45 (55.6) 9 (11.1)
2019 61 13 (21.3) 43 (70.5) 10 (16.4)
2020 21 2 (9.5) 20 (95.3) 2 (9.5)
Total 883 336 (38.1) 471 (53.3) 182 (20.6)
Table 5-2. Chi-square test on tissue distribution of Dickeya dianthicola (DDi) and
Pectobacterium parmentieri (PPa) on potato tissues showing blackleg and soft rot symptoms.
Number (percentage) of sample
Stem
(observed)
Tuber
(observed) Tuber (expected)a Chi-Sq df P value
DDi positive 307 (40.3%) 29 (23.8%) 49 (40.3%) 13.64 1 < 0.001
DDi negative 454 (59.7%) 93 (76.2%) 73 (59.7%)
Total 761 122 122
PPa positive 394 (51.8%) 77 (63.1%) 63 (51.8%) 6.43 1 < 0.01
PPa negative 367 (48.2%) 45 (36.9%) 59 (48.2%)
Total 761 122 122
a The number of tuber samples showing pathogen (DDi/PPa) positive or negative with the
assumption that there was no association between pathogen and tissue.
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5.3.2 Effects of bacterial inoculation on potato growth
Extremely dry growing conditions in 2020 resulted in an unexpectedly low emergence,
with the non-inoculated treatment having an emergence rate of 33%, 56% and 67% on ‘Lamoka’,
‘Atlantic’, and ‘Russet Burbank’ respectively (Table 5-3). Potato varieties showed different
responses in yield and emergence to bacterial inoculation (Table 5-3). The responses were
evaluated with regression models. Relative emergence loss and inoculation had a linear
relationship with coefficient (r2) of 0.44 on ‘Lamoka’, 0.62 on ‘Atlantic’ and 0.36 on ‘Russet
Burbank’, while yield loss and inoculation on ‘Lamoka’ and ‘Atlantic’ showed linear
relationships with r2 of 0.44 and 0.55, respectively (Figure 5-1). The level of disease
susceptibility was estimated by the slope of the regression equation between relative emergence
loss and inoculation. Slope of the regression equation between relative emergence loss and
inoculation was ‘Lamoka’ (0.687), ‘Atlantic’ (0.475), and ’Russet Burbank’ (0.332) (Figure 5-
1). ‘Lamoka’ was the most susceptible variety, the 100% inoculated seed treatment resulted in
68.7% emergence loss and 68.1% yield loss (Figure 5-1). For the tolerant variety ‘Russet
Burbank’, yield was not significantly affected by bacterial inoculation because emergence was
not significantly reduced (Figure 5-1).
5.3.3 Interaction between D. dianthicola and P. parmentieri in potato infection
Three potato varieties had different responses when inoculated with either D. dianthicola,
P. parmentieri, or mixture of both bacterial species, with ‘Lamoka’ being the most susceptible
variety. ‘Atlantic’ and ‘Shepody’ were less susceptible. This result was consistent in both years.
For example, in 2019, disease symptoms with inoculation of the bacterial mixture
appeared on ‘Lamoka’ at 49 days post planting with the disease severity index of 5.7, while the
disease severity indices of ‘Atlantic’ and ‘Shepody’ at 49 days post planting were 0.75 and 1.6
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respectively (Figure 5-2). At the end of the growing season, disease severity index of ‘Lamoka’
was 25.4, while ‘Atlantic’ and ‘Shepody’ showed relatively lower disease severity indices of 7.0
and 7.1, respectively (Figure 5-2).
Table 5-3. Effects of infection level of seed pieces with Dickeya dianthicola on yield and
emergence of potato in 2020.
Variety infected seeds
(%)
Total yield
(cwt/A)
Emergence
(%)
Total yield/plant
(cwt/A)
Lamoka 0 100.7 33.0 6.8
10 69.1 20.0 6.7
10 77.4 28.6 6.0
40 63.8 18.0 7.1
80 34.7 13.0 6.3
Atlantic 0 148.2 56.0 5.3
10 151.2 44.6 6.7
20 131.0 46.0 5.7
40 136.8 41.6 6.7
80 104.2 31.0 6.7
Russet
Burbank
0 171.3 67.0 5.2
10 148.9 67.6 4.4
20 154.7 65.0 4.8
40 191.0 62.6 6.2
80 162.7 49.0 6.6
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Figure 5-1. Regression analysis between relative emergence loss/relative yield loss and infection
percentage of potato. 1) (left panels) regression models between relative emergence loss (Y) and
infection percentage (X) of potato ‘Lamoka’ (Y = 0.687X+0.062, r2 = 0.44, P = 0.0017),
‘Atlantic’ (Y = 0.475X+0.073, r2 = 0.62, P < 0.0001), ‘Russet Burbank’ (Y = 0.332X-0.038, r2 =
0.36, P = 0.0056) seed pieces inoculated with Dickeya dianthicola; 2) (right panels) regression
models between relative yield loss (Y) and infection percentage (X) of potato ‘Lamoka’ (Y =
0.681X+0.095, r2 = 0.44, P = 0.0014), ‘Atlantic’ (Y = 0.374X-0.019, r2 = 0.55, P = 0.0002),
‘Russet Burbank’ (r2 = 0.02, P = 0.5850) seed pieces inoculated with Dickeya dianthicola.
Predicted data and confident intervals (CI) were shown as the dash lines and orange curves,
respectively, 2020.
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Figure 5-2. Disease progress of blackleg in potato ‘Lamoka’, ‘Atlantic’ and ‘Shepody’ grown
from seed pieces inoculated with either Dickeya dianthicola (DDi), Pectobacterium parmentieri
(PPa), or DDi + PPa under field conditions in 2018 (upper panels) and 2019 (bottom panels).
Non-inoculated (NI) plants were used for control.
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Dickeya dianthicola was more aggressive than P. parmentieri in the field. For example,
in the season of 2019 and on the most susceptible variety ‘Lamoka’, symptoms were first
observed with inoculation of D. dianthicola. The disease severity index was 6.7 for D.
dianthicola inoculation but 0.7 for P. parmentieri (Figure 5-2). Furthermore, by the end of the
season, disease severity index of ‘Lamoka’ caused by D. dianthicola was 16.2 higher than that
caused by P. parmentieri (10.4) (Figure 5-2). However, the mixture of both bacteria showed the
highest disease level, with disease severity index being 25.4 (Figure 5-2). Thus, the mixture of
two bacterial species had advantages in plant infection. The responses of ‘Shepody’ and
‘Atlantic’ were similar to ‘Lamoka’ for the infection by either single or mixture of bacterial
species, although the difference among treatments was not significant (P > 0.05), because both
varieties were less susceptible to blackleg (Figure 5-2). At early growing stages of potato, a
higher disease incidence was observed with D. dianthicola inoculation compared to the treatment
with P. parmentieri inoculation. While inoculation with the mixture of bacterial species started
with disease level slightly lower than that of D. dianthicola, but soon surpassed it. Although not
statistically significant, the disease severity index of treatments in 2018 showed a trend that D.
dianthicola inoculation was higher than P. parmentieri inoculation regardless of potato variety
(Figure 5-2).
All bacterial inoculations significantly reduced potato yield compared to the non-
inoculated treatment in 2019, yield differences in the 2018 trial were not significant (Table 5-4).
The treatment with a mixture of bacterial species did not show a significant difference compared
to D. dianthicola inoculation (Table 5-3). Thus, D. dianthicola was a key to cause higher yield
loss when potatoes were either infected solely by D. dianthicola or coinfected by D. dianthicola
and P. parmentieri.
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Table 5-4. Effects of seed tuber inoculation with Dickeya dianthicola (DDi), Pectobacterium
parmentieri (PPa) and non-inoculated (NI) on emergence and yield of potato varieties in years
2018 and 2019.
Variety Inoculation 2018 2019
Emergence
(%)
Total yield
(cwt/A)
Emergence
(%)
Total yield
(cwt/A)
Lamoka NI 95 118.3 98.3 166.2 ax
DDi 95.0 100.4 85.0 120.8 b
PPa 93.3 117.9 90.8 152.7 b
DDi & PPa 96.7 123.2 89.2 120.4 b
Atlantic NI 96.7 129.8 85.8 147.8 a
DDi 86.7 124.4 76.7 113.6 b
PPa 83.3 131.8 84.2 121.6 b
DDi & PPa 86.7 97.8 82.5 122.0 b
Shepody NI 96.7 127.0 95.0 188.8 a
DDi 96.7 101.4 86.7 138.6 b
PPa 96.7 157.8 87.5 145.9 b
DDi & PPa 91.7 111.2 90.8 136.6 b xMean values followed by different letters were significantly different (P < 0.05).
5.4 DISCUSSION
Dickeya dianthicola was found to be the predominant species causing PBSR during the
outbreak happened in 2015 in the Northeastern USA. There was a trend that the number of
samples infected by P. parmentieri increased during the years, while the percentage of total
samples infected by D. dianthicola declined through the six years. Pectobacterium parmentieri
turned to be another problem along with D. dianthicola, which was persistently detected as the
predominant pathogen in the following years. Furthermore, D. dianthicola was more likely a
pathogen associated with stems, and P. parmentieri was highly associated with potato tubers.
At least 20.6% of infected potato plants contained both D. dianthicola and P. parmentieri
in this study. In addition, several other Pectobacterium spp. have also frequently been found in
119
naturally infected seed potatoes. It seemed that the coexistence of multiple bacterial species is
common in blackleg, forming a pathogen complex. Since D. dianthicola was consistently
isolated as the predominant species, it is believed that D. dianthicola was the primary pathogen
that aggressively caused disease in the field. Many Pectobacterium spp. can survive well in soil
or they are soil inhabitants. Since they are weak pathogens, they may not cause infection.
However, their availability in fields allows them to follow the initiation of infection by Dickeya
spp. thus disease severity increased.
It is possible that D. dianthicola, compared to P. parmentieri, has more virulence-related
factors in plant infection, such as enzymes to degrade pectin and cellulose (Barras et al. 1994), or
secretion systems to transfer virulence effectors (Charkowski et al. 2012; Kim et al. 2009).
Regarding pathogenicity, D. dianthicola might have advantages over P. parmentieri owing to the
lack of T3SS in P. parmentieri (Kim et al. 2009; Nykyri et al. 2012), as T3SS contributes to the
virulence of bacteria during the early stages of infection (Ham et al. 2004; Rantakari et al.
2001). Studies have reported that D. dadantii exhibited a high number of pectinase-related
enzymes that would enhance the degradation of pectin (Dittoe et al. 2020), and Dickeya spp.
possess complex regulatory networks in order to express virulence genes (Reverchon et al.
2016). However, detailed studies about virulence-related mechanisms have not been established
for D. dianthicola.
Our two-year data supports that D. dianthicola causes a higher level of PBSR severity
than P. parmentieri, and that inoculation with both bacterial species did increase PBSR severity
later during the growing season (Figure 5-2). This suggested that D. dianthicola should be
considered the primary pathogen in disease control. Meanwhile, due to the wide distribution of
P. parmentieri, it is possible that both bacterial species co-existed in the environment and co-
120
infect or -damage potato plants. This could be a consequence of synergy between the two
bacterial species. In production, if D. dianthicola is eliminated, the less-aggressive P.
parmentieri would cause less impact on potato growth and yield. More importantly, it would
remove the complex of co-infection with two or more bacteria. Therefore, it is necessary to
further investigate how Dickeya spp. and Pectobacterium spp. interact with each other inside
potato plants in increasing disease severity.
Competition, cooperation, and coexistence are major means of interactions of bacteria
that co-exist in a same niche (Abdullah et al. 2017). Although no coexistence has been reported
of D. solani and D. dianthicola in fields, D. solani could outcompete D. dianthicola in co-
inoculated plants (Czajkowski et al. 2013b). In this study, there was no antagonistic effect
between D. dianthicola and P. parmentieri when they coexisted but aggravated the disease
epidemic at a higher level.
Surprisingly, even though D. dianthicola or a mixture of the two bacterial species caused
higher disease than the sole infection by P. parmentieri, the total yield did not show a significant
difference (Table 5-4). It was interpreted that yield is constrained by early infection with stand
loss, but less affected by late disease progress. Furthermore, among the three bacterial
treatments, P. parmentieri had less impact on yield compared to the other two. This implied that
D. dianthicola was more aggressive or virulent than P. parmentieri.
Yield losses of potato caused by artificial inoculation of D. dianthicola were evaluated in
this study. There was a high correlation of percentage of seed inoculation/contamination with
lack of emergence, as well as with yield reduction. This was because yield per area of field was
highly correlated with plant emergence or total number of plants. PBSR showed up in the
growing season at a low level and most of the plants survived. Therefore, low percent in-season
121
disease did not significantly affect potato yield. In addition to disease severity, yield is also
dependent on weather conditions, such as precipitation and soil temperature, soil properties,
pathogen aggressiveness, and the ability of the crop to compensate for stand loss. Based on our
results, ‘Lamoka’ was the most susceptible variety to PBSR, while ‘Russet Burbank’ was more
tolerant, ‘Atlantic’ and ‘Shepody’ were moderate. Such information may be incorporated in
breeding a program for BRS resistance.
In conclusion, tuber contamination with either D. dianthicola or P. parmentieri caused
direct stand loss that translated to yield losses, and the percent of tuber infection was negatively
correlated with emergence. When a single species of pathogen infected potato, D. dianthicola
caused more symptoms than P. parmentieri. However, co-infection of the two species showed
even higher disease severity of PBSR, and a synergistic effect of bacterial species in plant
infection.
122
DISSERTATION SUMMARY
This research was conducted on potato blackleg and soft rot (PBSR) and its recent
outbreak in the northeastern U.S. and attempted to address four key questions related to
understanding the pathogen, disease, and the outbreak. These questions were: 1) What was the
origin and cause of the outbreak? 2) What are the genetic characteristics of the pathogen
population responsible for the outbreak compared to those occurring throughout the world? 3)
Were multiple bacteria species involved in outbreak infections? And 4) How do multiple bacteria
species in a pathogen complex interact and affect disease development and yield? By analyzing
thousands of diseased potatoes samples collected from the Northeastern states using molecular
and genetic tools, a clear image has been drawn of the outbreak. The disease epidemic was solely
caused by domestic USA strains of Dickeya dianthicola, which contained three genotypes.
Genotype I was the predominant population and its incursion into potato production could be the
main reason for the PBSR outbreak. It was found at a high percentage in Dickeya positive
samples in all states every year for the five years of sample collection and was distinctly different
from all known genotypes from other parts of the world. By analyzing the whole genome of the
bacteria, genotype I was confirmed to have genetic advantages by having extra copies of types
IV and VI secretion systems, which are highly correlated to bacterial pathogenesis and virulence.
This genetic arrangement might have enhanced the genotype I strain allowing in to become more
competitive. Genotype III was mostly common in the more southerly states. It was a causal agent
of PBSR but not a reason for the outbreak since it was not observed in Maine where much of the
region’s potato seed is produced. Seed was the primary carrier of PBSR pathogens for long-
distance movement.
123
PBSR can be a complex as many other bacteria were involved. This was discovered
using high throughput DNA sequencing. At least four species of Pectobacterium have been
retrieved from symptomatic potato tissues and confirmed to be virulent to potato. More
importantly, D. dianthicola and P. parmentieri showed a synergy in plant infection. The trend of
the stem-associated pathogen D. dianthicola declining and the tuber-related pathogen P.
parmentieri increasing in the past 5 years may indicate another challenge to potato production,
which should be addressed in the future. This work has provided answers to the fundamental
questions surrounding the origin and pathogens involved in the recent outbreak of PBSR, as well
as insight into more effective management of these diseases. Thus, this work significantly
contributed to the productivity and sustainability of potato production, the most important
vegetable crop in the world.
124
REFERENCES
Abdullah, A. S., Moffat, C. S., Lopez-Ruiz, F. J., Gibberd, M. R., Hamblin, J., and Zerihun, A.
2017. Host–multi-pathogen warfare: pathogen interactions in co-infected plants. Frontiers
in Plant Science 8:1806.
Adams, M. J. 1975a. Potato tuber lenticels: susceptibility to infection by Erwinia carotovora var.
atroseptica and Phytophthora infestans. Annals of Applied Biology 79:275-282.
Adams, M. J. 1975b. Potato tuber lenticels: development and structure. Annals of Applied
Biology 79:265-273.
Adams, M. J., and Lapwood, D. H. 1978. Studies on the lenticel development, surface microflora
and infection by common scab (Streptomyces scabies) of potato tubers growing in wet
and dry soils. Annals of Applied Biology 90:335-343.
Adeolu, M., Alnajar, S., Naushad, S., and Gupta, R. S. 2016. Genome-based phylogeny and
taxonomy of the ‘Enterobacteriales’: proposal for Enterobacterales ord. nov. divided
into the families Enterobacteriaceae, Erwiniaceae fam. nov., Pectobacteriaceae fam.
nov., Yersiniaceae fam. nov., Hafniaceae fam. nov., Morganellaceae fam. nov., and
Budviciaceae fam. nov. International Journal of Systematic and Evolutionary
Microbiology 66:5575-5599.
Aizawa, S.-I. 2014. Flagellar World: electron microscopic images of bacterial flagella and
related surface structures. Elsevier.
Alikhan, N.-F., Petty, N. K., Zakour, N. L. B., and Beatson, S. A. 2011. BLAST Ring Image
Generator (BRIG): simple prokaryote genome comparisons. BMC Genomics 12:402.
Alivizatos, A. S. 1985. Bacterial wilt of tomato in Greece caused by Erwinia chrysanthemi. Plant
Pathology 34:638-639.
Alič, Š., Van Gijsegem, F., Pedron, J., Ravnikar, M., and Dreo, T. 2018. Diversity within the
novel Dickeya fangzhongdai sp., isolated from infected orchids, water and pears. Plant
Pathology 67:1612-1620.
Alvarez-Martinez, C. E., and Christie, P. J. 2009. Biological diversity of prokaryotic type IV
secretion systems. Microbiology and Molecular Biology Reviews 73:775-808.
125
Ansermet, M., Schaerer, S., Kellenberger, I., Tallant, M., and Dupuis, B. 2016. Influence of
seed-borne and soil-carried inocula of Dickeya spp. on potato plant transpiration and
symptom expression. European Journal of Plant Pathology 145:459-467.
Arber, W. 2014. Horizontal gene transfer among bacteria and its role in biological evolution.
Life 4:217-224.
Armbruster, C. E., Hong, W., Pang, B., Weimer, K. E. D., Juneau, R. A., Turner, J., and Swords,
W. E. 2010. Indirect pathogenicity of Haemophilus influenzae and Moraxella catarrhalis
in polymicrobial otitis media occurs via interspecies quorum signaling. MBio 1:e00102-
10.
Baghaee-Ravari, S., Rahimian, H., Shams-Bakhsh, M., Lopez-Solanilla, E., Antúnez-Lamas, M.,
and Rodríguez-Palenzuela, P. 2011. Characterization of Pectobacterium species from
Iran using biochemical and molecular methods. European Journal of Plant Pathology
129:413-425.
Barras, F., van Gijsegem, F., and Chatterjee, A. K. 1994. Extracellular enzymes and
pathogenesis of soft-rot Erwinia. Annual Review of Phytopathology 32:201-234.
Bartz, J. A., and Kelman, A. 1985. Effect of air-drying on soft rot potential of potato tubers
inoculated by immersion in suspensions of Erwinia carotovora. Plant Disease 69:128-
131.
Bdliya, B. S., and Haruna, H. U. 2007. Efficacy of solar heat in the control of bacterial soft rot of
potato tubers caused by Erwinia carotovora ssp. carotovora. Journal of Plant Protection
Research 47:11-18.
Bell, K. S., Avrova, A. O., Holeva, M. C., Cardle, L., Morris, W., De Jong, W., Toth, I. K.,
Waugh, R., Bryan, G. J., and Birch, P. R. J. 2002. Sample sequencing of a selected region
of the genome of Erwinia carotovora subsp. atroseptica reveals candidate
phytopathogenicity genes and allows comparison with Escherichia coli The GenBank
accession numbers for the 424 sequences determined in this work are BH614193 to
BH614616. Microbiology 148:1367-1378.
Bell, K. S., Sebaihia, M., Pritchard, L., Holden, M. T. G., Hyman, L. J., Holeva, M. C.,
Thomson, N. R., Bentley, S. D., Churcher, L. J. C., and Mungall, K. 2004. Genome
sequence of the enterobacterial phytopathogen Erwinia carotovora subsp. atroseptica and
characterization of virulence factors. Proceedings of the National Academy of Sciences
101:11105-11110.
126
Bellieny-Rabelo, D., Tanui, C. K., Miguel, N., Kwenda, S., Shyntum, D. Y., and Moleleki, L. N.
2019. Transcriptome and comparative genomics analyses reveal new functional insights
on key determinants of pathogenesis and interbacterial competition in Pectobacterium
and Dickeya spp. Applied and Environmental Microbiology 85.
Berendsen, R. L., Pieterse, C. M. J., and Bakker, P. A. H. M. 2012. The rhizosphere microbiome
and plant health. Trends in Plant Science 17:478-486.
Berg, G., Rybakova, D., Fischer, D., Cernava, T., Vergès, M.-C. C., Charles, T., Chen, X.,
Cocolin, L., Eversole, K., and Corral, G. H. 2020. Microbiome definition re-visited: old
concepts and new challenges. Microbiome 8:1-22.
Bertin, C., Yang, X., and Weston, L. A. 2003. The role of root exudates and allelochemicals in
the rhizosphere. Plant and Soil 256:67-83.
Binyam, T. 2014. Late blight of potato (Phytophthora infestans) biology, economic importance
and its management approaches. Journal of Biology, Agriculture and Healthcare 4:215-
225.
Bleidorn, C. 2016. Third generation sequencing: technology and its potential impact on
evolutionary biodiversity research. Systematics and Biodiversity 14:1-8.
Blin, P., Robic, K., Khayi, S., Cigna, J., Munier, E., Dewaegeneire, P., Laurent, A., Jaszczyszyn,
Y., Hong, K. W., and Chan, K. G. 2020. Pattern and causes of the establishment of the
invasive bacterial potato pathogen Dickeya solani and of the maintenance of the resident
pathogen D. dianthicola. Molecular Ecology 30:608-624.
Bolyen, E., Rideout, J. R., Dillon, M. R., Bokulich, N. A., Abnet, C. C., Al-Ghalith, G. A.,
Alexander, H., Alm, E. J., Arumugam, M., and Asnicar, F. 2019. Reproducible,
interactive, scalable and extensible microbiome data science using QIIME 2. Nature
Biotechnology 37:852-857.
Bosi, E., Fani, R., and Fondi, M. 2015. Defining orthologs and pangenome size metrics. Pages
191-202 in: Bacterial Pangenomics. Springer.
Bouchez, V., Baines, S. L., Guillot, S., and Brisse, S. 2018. Complete genome sequences of
Bordetella pertussis clinical isolate FR5810 and reference strain Tohama from combined
Oxford Nanopore and Illumina sequencing. Microbiology Resource Announcements 7.
127
Brady, C. L., Cleenwerck, I., Denman, S., Venter, S. N., Rodriguez-Palenzuela, P., Coutinho, T.
A., and De Vos, P. 2012. Proposal to reclassify Brenneria quercina (Hildebrand and
Schroth 1967) Hauben et al. 1999 into a new genus, Lonsdalea gen. nov., as Lonsdalea
quercina comb. nov., descriptions of Lonsdalea quercina subsp quercina comb. nov.,
Lonsdalea quercina subsp iberica subsp nov and Lonsdalea quercina subsp britannica
subsp nov., emendation of the description of the genus Brenneria, reclassification of
Dickeya dieffenbachiae as Dickeya dadantii subsp dieffenbachiae comb. nov., and
emendation of the description of Dickeya dadantii. International Journal of Systematic
and Evolutionary Microbiology 62:1592-1602.
Brown, C. R. 1993. Origin and history of the potato. American Potato Journal 70:363-373.
Brown, J. K. M. 2015. Durable resistance of crops to disease: a Darwinian perspective. Annual
Review of Phytopathology 53:513-539.
Callahan, B. J., McMurdie, P. J., and Holmes, S. P. 2017. Exact sequence variants should replace
operational taxonomic units in marker-gene data analysis. The ISME Journal 11:2639-
2643.
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Huntley, J., Fierer, N., Owens,
S. M., Betley, J., Fraser, L., and Bauer, M. 2012. Ultra-high-throughput microbial
community analysis on the Illumina HiSeq and MiSeq platforms. The ISME Journal
6:1621-1624.
Carvajal-Yepes, M., Cardwell, K., Nelson, A., Garrett, K. A., Giovani, B., Saunders, D. G. O.,
Kamoun, S., Legg, J. P., Verdier, V., and Lessel, J. 2019. A global surveillance system
for crop diseases. Science 364:1237-1239.
Cascales, E., and Christie, P. J. 2003. The versatile bacterial type IV secretion systems. Nature
Reviews Microbiology 1:137-149.
Chakravorty, S., Helb, D., Burday, M., Connell, N., and Alland, D. 2007. A detailed analysis of
16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria. Journal of
Microbiological Methods 69:330-339.
Chandran, V., Fronzes, R., Duquerroy, S., Cronin, N., Navaza, J., and Waksman, G. 2009.
Structure of the outer membrane complex of a type IV secretion system. Nature
462:1011-1015.
128
Chaparro, J. M., Badri, D. V., and Vivanco, J. M. 2014. Rhizosphere microbiome assemblage is
affected by plant development. The ISME Journal 8:790-803.
Charkowski, A., Blanco, C., Condemine, G., Expert, D., Franza, T., Hayes, C., Hugouvieux-
Cotte-Pattat, N., Solanilla, E. L., Low, D., and Moleleki, L. 2012. The role of secretion
systems and small molecules in soft-rot Enterobacteriaceae pathogenicity. Annual
Review of Phytopathology 50:425-449.
Charkowski, A. O. 2018. The changing face of bacterial soft-rot diseases. Annual Review of
Phytopathology 56:269-288.
Chatterjee, A., Cui, Y., Chakrabarty, P., and Chatterjee, A. K. 2010. Regulation of motility in
Erwinia carotovora subsp. carotovora: quorum-sensing signal controls FlhDC, the global
regulator of flagellar and exoprotein genes, by modulating the production of RsmA, an
RNA-binding protein. Molecular Plant-Microbe Interactions 23:1316-1323.
Chen, X. F., Zhang, H. L., & Chen, J. (2015). First report of Dickeya solani causing soft rot in
imported bulbs of Hyacinthus orientalis in China. Plant disease 99, 155.
Chen, S., Zhou, Y., Chen, Y., and Gu, J. 2018. fastp: an ultra-fast all-in-one FASTQ
preprocessor. Bioinformatics 34:i884-i890.
Chujoy, E., and Cabello, R. 2007. The canon of potato science: 29. True potato seed (TPS).
Potato Research 50:323-325.
Cigna, J., Dewaegeneire, P., Beury, A., Gobert, V., and Faure, D. 2017. A gapA PCR-
sequencing assay for identifying the Dickeya and Pectobacterium potato pathogens. Plant
Disease 101:1278-1282.
Collmer, A., and Keen, N. T. 1986. The role of pectic enzymes in plant pathogenesis. Annual
Review of Phytopathology 24:383-409.
Compant, S., Clément, C., and Sessitsch, A. 2010. Plant growth-promoting bacteria in the rhizo-
and endosphere of plants: their role, colonization, mechanisms involved and prospects for
utilization. Soil Biology and Biochemistry 42:669-678.
Compant, S., Samad, A., Faist, H., and Sessitsch, A. 2019. A review on the plant microbiome:
Ecology, functions, and emerging trends in microbial application. Journal of Advanced
Research 19:29-37.
129
Cook, L. C., LaSarre, B., and Federle, M. J. 2013. Interspecies communication among
commensal and pathogenic streptococci. MBio 4.
Cother, E. J., Bradley, J. K., Gillings, M. R., and Fahy, P. C. 1992. Characterization of Erwinia
chrysanthemi biovars in alpine water sources by biochemical properties, GLC fatty acid
analysis and genomic DNA fingerprinting. Journal of Applied Bacteriology 73:99-107.
Czajkowski, R. 2016. Bacteriophages of soft rot Enterobacteriaceae—a minireview. FEMS
Microbiology Letters 363.
Czajkowski, R., Grabe, G. J., and van der Wolf, J. M. 2009. Distribution of Dickeya spp. and
Pectobacterium carotovorum subsp. carotovorum in naturally infected seed potatoes.
European Journal of Plant Pathology 125:263-275.
Czajkowski, R., De Boer, W. J., and Van der Wolf, J. M. 2013a. Chemical disinfectants can
reduce potato blackleg caused by ‘Dickeya solani’. European Journal of Plant Pathology
136:419-432.
Czajkowski, R., Ozymko, Z., and Lojkowska, E. 2014. Isolation and characterization of novel
soilborne lytic bacteriophages infecting Dickeya spp. biovar 3 (‘D. solani’). Plant
Pathology 63:758-772.
Czajkowski, R., de Boer, W. J., Velvis, H., and van der Wolf, J. M. 2010. Systemic colonization
of potato plants by a soilborne, green fluorescent protein-tagged strain of Dickeya sp.
biovar 3. Phytopathology 100:134-142.
Czajkowski, R., Perombelon, M. C. M., van Veen, J. A., and van der Wolf, J. M. 2011. Control
of blackleg and tuber soft rot of potato caused by Pectobacterium and Dickeya species: a
review. Plant Pathology 60:999-1013.
Czajkowski, R., De Boer, W. J., Van Veen, J. A., and Van der Wolf, J. M. 2012. Studies on the
interaction between the biocontrol agent, Serratia plymuthica A30, and blackleg‐causing
Dickeya sp.(biovar 3) in potato (Solanum tuberosum). Plant Pathology 61:677-688.
Czajkowski, R., van der Wolf, J. M., Krolicka, A., Ozymko, Z., Narajczyk, M., Kaczynska, N.,
and Lojkowska, E. 2015a. Salicylic acid can reduce infection symptoms caused by
Dickeya solani in tissue culture grown potato (Solanum tuberosum L.) plants. European
Journal of Plant Pathology 141:545-558.
130
Czajkowski, R., De Boer, W. J., Van der Zouwen, P. S., Kastelein, P., Jafra, S., De Haan, E. G.,
Van den Bovenkamp, G. W., and Van der Wolf, J. M. 2013b. Virulence of ‘Dickeya
solani’and Dickeya dianthicola biovar‐1 and‐7 strains on potato (Solanum tuberosum).
Plant Pathology 62:597-610.
Czajkowski, R., Ozymko, Z., de Jager, V., Siwinska, J., Smolarska, A., Ossowicki, A.,
Narajczyk, M., and Lojkowska, E. 2015b. Genomic, proteomic and morphological
characterization of two novel broad host lytic bacteriophages ΦPD10. 3 and ΦPD23. 1
infecting pectinolytic Pectobacterium spp. and Dickeya spp. PLoS One 10:e0119812.
da Silva, D. P., Castañeda-Ojeda, M. P., Moretti, C., Buonaurio, R., Ramos, C., and Venturi, V.
2014. Bacterial multispecies studies and microbiome analysis of a plant disease.
Microbiology 160:556-566.
Darling, A. C. E., Mau, B., Blattner, F. R., and Perna, N. T. 2004. Mauve: multiple alignment of
conserved genomic sequence with rearrangements. Genome Research 14:1394-1403.
Davies, H. V. 1984. Mother tuber reserves as factors limiting potato sprout growth. Potato
Research 27:209-218.
De Boer, S. H., and Rubio, I. 2004. Blackleg of potato. The Plant Health Instructor.
De Boer, S. H., Li, X., and Ward, L. J. 2012. Pectobacterium spp. associated with bacterial stem
rot syndrome of potato in Canada. Phytopathology 102:937-947.
De la Cruz, F., and Davies, J. 2000. Horizontal gene transfer and the origin of species: lessons
from bacteria. Trends in Microbiology 8:128-133.
Dean, B. B. 1994. Managing the Potato Production System: 0734. CRC Press.
Decho, A. W., Norman, R. S., and Visscher, P. T. 2010. Quorum sensing in natural
environments: emerging views from microbial mats. Trends in Microbiology 18:73-80.
Dees, M. W., and Wanner, L. A. 2012. In search of better management of potato common scab.
Potato Research 55:249-268.
131
Dees, M. W., Lysøe, E., Rossmann, S., Perminow, J., and Brurberg, M. B. 2017. Pectobacterium
polaris sp. nov., isolated from potato (Solanum tuberosum). International Journal of
Systematic and Evolutionary Microbiology 67:5222-5229.
Dennis, P. G., Miller, A. J., and Hirsch, P. R. 2010. Are root exudates more important than other
sources of rhizodeposits in structuring rhizosphere bacterial communities? FEMS
Microbiology Ecology 72:313-327.
Des Essarts, Y. R., Cigna, J., Quêtu-Laurent, A., Caron, A., Munier, E., Beury-Cirou, A., Hélias,
V., and Faure, D. 2016. Biocontrol of the potato blackleg and soft rot diseases caused by
Dickeya dianthicola. Applied and Environmental Microbiology 82:268-278.
Dhanvantari, B. N., and Dirks, V. A. 1987. Bacterial stem rot of greenhouse tomato: etiology,
spatial distribution, and the effect of high humidity. Phytopathology 77:1457-1463.
Dittoe, D. K., Barabote, R. D., Rothrock, M. J., and Ricke, S. C. 2020. Assessment of a Potential
Role of Dickeya dadantii DSM 18020 as a Pectinase Producer for Utilization in Poultry
Diets Based on in silico Analyses. Frontiers in Microbiology 11:751.
Donnelly, J. S. 2002. Great Irish potato famine. The History Press.
Duan, K., Dammel, C., Stein, J., Rabin, H., and Surette, M. G. 2003. Modulation of
Pseudomonas aeruginosa gene expression by host microflora through interspecies
communication. Molecular Microbiology 50:1477-1491.
Duarte, V., De Boer, S. H., Ward, L. J., and De Oliveira, A. M. R. 2004. Characterization of
atypical Erwinia carotovora strains causing blackleg of potato in Brazil. Journal of
Applied Microbiology 96:535-545.
Dung, J. K. S., Johnson, D. A., and Schroeder, B. K. 2012. First report of Pectobacterium
wasabiae causing aerial stem rot of potato in Washington State. Plant Disease 96:1819-
1819.
Dung, J. K. S., Johnson, D. A., and Schroeder, B. K. 2014. Role of co‐infection by
Pectobacterium and Verticillium dahliae in the development of early dying and aerial
stem rot of Russet Burbank potato. Plant Pathology 63:299-307.
Duprey, A., Taib, N., Leonard, S., Garin, T., Flandrois, J. P., Nasser, W., Brochier‐Armanet, C.,
and Reverchon, S. 2019. The phytopathogenic nature of Dickeya aquatica 174/2 and the
132
dynamic early evolution of Dickeya pathogenicity. Environmental Microbiology
21:2809-2835.
Egland, P. G., Palmer, R. J., and Kolenbrander, P. E. 2004. Interspecies communication in
Streptococcus gordonii–Veillonella atypica biofilms: signaling in flow conditions
requires juxtaposition. Proceedings of the National Academy of Sciences 101:16917-
16922.
Ekbataniamiri, F. 2020. Potato Resistance and Surface Water Associated with Blackleg and Soft
Rot. The University of Maine, Orono.
Elphinstone, J. G., and Pérombelon, M. C. M. 1986. Contamination of potatoes by Erwinia
carotovora during grading. Plant Pathology 35:25-33.
Elphinstone, J. G., Parkinson, N. M., Saddler, G. S., Cahill, G., Kelly, R., Pritchard, L.,
Humphris, S., and Toth, I. 2014. Biology and control of Dickeya spp. affecting potato in
the UK. Proceedings of the Dundee conference Crop Protection in Northern Britain:235-
241.
F. A. O., T. 2008. International Year of the Potato: FAO Factsheets. Markets Division.
Farran, I., and Mingo-Castel, A. M. 2006. Potato minituber production using aeroponics: effect
of plant density and harvesting intervals. American Journal of Potato Research 83:47-53.
Fierer, N. 2017. Embracing the unknown: disentangling the complexities of the soil microbiome.
Nature Reviews Microbiology 15:579-590.
Fiers, M., Edel-Hermann, V., Chatot, C., Le Hingrat, Y., Alabouvette, C., and Steinberg, C.
2012. Potato soil-borne diseases. A review. Agronomy for Sustainable Development
32:93-132.
Fitt, B. D. L., Huang, Y.-J., Bosch, F. v. d., and West, J. S. 2006. Coexistence of related
pathogen species on arable crops in space and time. Annual Review of Phytopathology
44:163-182.
Frank, J. A., Reich, C. I., Sharma, S., Weisbaum, J. S., Wilson, B. A., and Olsen, G. J. 2008.
Critical evaluation of two primers commonly used for amplification of bacterial 16S
rRNA genes. Applied and Environmental Microbiology 74:2461-2470.
133
Fronzes, R., Schäfer, E., Wang, L., Saibil, H. R., Orlova, E. V., and Waksman, G. 2009.
Structure of a type IV secretion system core complex. Science 323:266-268.
Gallois, A., Samson, R., Ageron, E., and Grimont, P. A. D. 1992. Erwinia carotovora subsp.
odorifera subsp. nov., associated with odorous soft rot of chicory (Cichorium intybus L.).
International Journal of Systematic and Evolutionary Microbiology 42:582-588.
Garbaye, J. 1994. Tansley review no. 76 helper bacteria: a new dimension to the mycorrhizal
symbiosis. New Phytologist 128:197-210.
Gardan, L., Gouy, C., Christen, R., and Samson, R. 2003. Elevation of three subspecies of
Pectobacterium carotovorum to species level: Pectobacterium atrosepticum sp. nov.,
Pectobacterium betavasculorum sp. nov. and Pectobacterium wasabiae sp. nov.
International Journal of Systematic and Evolutionary Microbiology 53:381-391.
Garge, S. S., and Nerurkar, A. S. 2017. Evaluation of quorum quenching Bacillus spp. for their
biocontrol traits against Pectobacterium carotovorum subsp. carotovorum causing soft
rot. Biocatalysis and Agricultural Biotechnology 9:48-57.
Ge, T., Marangoni, N. F., Hao, J., Johnson, S., and Larkin, R. P. 2018a. Isolation and
Identification of Bacteria Causing Blackleg and Soft Rot of Potato in Northeastern US.
Phytopathology 108:62.
Ge, T., Johnson, S., Larkin, R. P., Charkowski, A. O., and Hao, J. 2020a. Pathogen synergism of
blackleg disease on potato. Plant Health 2020 Online.
Ge, T., Jiang, H., Johnson, S. B., Larkin, R., Charkowski, A. O., Secor, G., and Hao, J. 2020b.
Genotyping Dickeya dianthicola causing potato blackleg and soft rot outbreak associated
with inoculum geography in the United States. Plant Disease.
https://doi.org/10.1094/PDIS-10-20-2138-RE
Ge, T., Jiang, H., Hao, J., and Johnson, S. B. 2018b. First report of Pectobacterium parmentieri
causing bacterial soft rot and blackleg on potato in Maine. Plant Disease 102:437.
Glasner, J. D., Marquez-Villavicencio, M., Kim, H. S., Jahn, C. E., Ma, B., Biehl, B. S.,
Rissman, A. I., Mole, B., Yi, X., and Yang, C. H. 2008. Niche-specificity and the
variable fraction of the Pectobacterium pan-genome. Molecular Plant-Microbe
Interactions 21:1549-1560.
134
Goto, M., and Matsumoto, K. 1987. Erwinia carotovora subsp. wasabiae subsp. nov. isolated
from diseased rhizomes and fibrous roots of Japanese horseradish (Eutrema wasabi
Maxim.). International Journal of Systematic and Evolutionary Microbiology 37:130-135.
Goumans, D. E., and Chatzaki, A. K. 1998. Characterization and host range evaluation of
Pseudomonas viridiflava from melon, blite, tomato, chrysanthemum and eggplant.
European Journal of Plant Pathology 104:181-188.
Greninger, A. L., Naccache, S. N., Federman, S., Yu, G., Mbala, P., Bres, V., Stryke, D.,
Bouquet, J., Somasekar, S., and Linnen, J. M. 2015. Rapid metagenomic identification of
viral pathogens in clinical samples by real-time nanopore sequencing analysis. Genome
Medicine 7:99.
Grube, M., Fürnkranz, M., Zitzenbacher, S., Huss, H., and Berg, G. 2011. Emerging multi-
pathogen disease caused by Didymella bryoniae and pathogenic bacteria on Styrian oil
pumpkin. European Journal of Plant Pathology 131:539.
Gudmestad, N. C., Taylor, R. J., and Pasche, J. S. 2007. Management of soilborne diseases of
potato. Australasian Plant Pathology 36:109-115.
Guttman, D. S., McHardy, A. C., and Schulze-Lefert, P. 2014. Microbial genome-enabled
insights into plant–microorganism interactions. Nature Reviews Genetics 15:797-813.
Gyles, C., and Boerlin, P. 2014. Horizontally transferred genetic elements and their role in
pathogenesis of bacterial disease. Veterinary Pathology 51:328-340.
Ham, J. H., Bauer, D. W., Fouts, D. E., and Collmer, A. 1998. A cloned Erwinia chrysanthemi
Hrp (type III protein secretion) system functions in Escherichia coli to deliver
Pseudomonas syringae Avr signals to plant cells and to secrete Avr proteins in culture.
Proceedings of the National Academy of Sciences 95:10206-10211.
Ham, J. H., Cui, Y., Alfano, J. R., Rodríguez-Palenzuela, P., Rojas, C. M., Chatterjee, A. K., and
Collmer, A. 2004. Analysis of Erwinia chrysanthemi EC16 pelE∷ uidA, pelL∷ uidA, and
hrpN∷ uidA mutants reveals strain-specific atypical regulation of the Hrp type III
secretion system. Molecular Plant-Microbe Interactions 17:184-194.
Haney, C. H., Samuel, B. S., Bush, J., and Ausubel, F. M. 2015. Associations with rhizosphere
bacteria can confer an adaptive advantage to plants. Nature Plants 1:1-9.
135
Hao, J., Jiang, H., and Johnson, S. 2016. Detection and characterization of Dickeya species in the
outbreak of blackleg disease of potato in Maine. Phytopathology 106:2.
Harrison, J. G., Searle, R. J., and Williams, N. A. 1997. Powdery scab disease of potato-a
review. Plant Pathology 46:1-25.
Hartmann, A., Schmid, M., Van Tuinen, D., and Berg, G. 2009. Plant-driven selection of
microbes. Plant and Soil 321:235-257.
Hauben, L., Moore, E. R. B., Vauterin, L., Steenackers, M., Mergaert, J., Verdonck, L., and
Swings, J. 1998. Phylogenetic position of phytopathogens within the Enterobacteriaceae.
Systematic and Applied Microbiology 21:384-397.
Hellmers, E. 1958. Four wilt diseases of perpetual-flowering Carnations in Denmark. Dansk
Botanisk Arkiv 18.
Hibbing, M. E., Fuqua, C., Parsek, M. R., and Peterson, S. B. 2010. Bacterial competition:
surviving and thriving in the microbial jungle. Nature Reviews Microbiology 8:15-25.
Hiergeist, A., Gläsner, J., Reischl, U., and Gessner, A. 2015. Analyses of intestinal microbiota:
culture versus sequencing. ILAR journal 56:228-240.
Hijmans, R. J. 2001. Global distribution of the potato crop. American journal of potato research
78:403-412.
Hoek, T. A., Axelrod, K., Biancalani, T., Yurtsev, E. A., Liu, J., and Gore, J. 2016. Resource
availability modulates the cooperative and competitive nature of a microbial cross-
feeding mutualism. PLoS Biology 14:e1002540.
Huerta-Cepas, J., Szklarczyk, D., Heller, D., Hernández-Plaza, A., Forslund, S. K., Cook, H.,
Mende, D. R., Letunic, I., Rattei, T., and Jensen, L. J. 2019. eggNOG 5.0: a hierarchical,
functionally and phylogenetically annotated orthology resource based on 5090 organisms
and 2502 viruses. Nucleic Acids Research 47:D309-D314.
Hélias, V., Hamon, P., Huchet, E., Wolf, J. V. D., and Andrivon, D. 2012. Two new effective
semiselective crystal violet pectate media for isolation of Pectobacterium and Dickeya.
Plant Pathology 61:339-345.
136
James, E. K., and Olivares, F. L. 1998. Infection and colonization of sugar cane and other
graminaceous plants by endophytic diazotrophs. Critical Reviews in Plant Sciences
17:77-119.
Jiang, H. H., Hao, J. J., Johnson, S. B., Brueggeman, R. S., and Secor, G. 2016. First report of
Dickeya dianthicola causing blackleg and bacterial soft rot on potato in Maine. Plant
Disease 100:2320-2320.
Johnson, D. A. 2008. Potato health management. American Phytopathological Society (APS
Press).
Johnson, S. 2016. Dickeya, a new potato pathogen in Maine and elsewhere. Phytopathology
106:3.
Johnson, S. B. 2017. Novel Approach for Identification of Potato Seed Lots Suspected to be
Effected by Dickeya. Plant Pathology Journal 16:96-100.
Jones, J. B., Jackson, L. E., Balogh, B., Obradovic, A., Iriarte, F. B., and Momol, M. T. 2007.
Bacteriophages for plant disease control. Annual Review of Phytopathology 45:245-262.
Jones, R. A. C., and Harrison, B. D. 1969. The behaviour of potato mop‐top virus in soil, and
evidence for its transmission by Spongospora subterranea (Wallr.) Lagerh. Annals of
Applied Biology 63:1-17.
Juck, D., Charles, T., Whyte, L. G., and Greer, C. W. 2000. Polyphasic microbial community
analysis of petroleum hydrocarbon-contaminated soils from two northern Canadian
communities. FEMS Microbiology Ecology 33:241-249.
Kastelein, P., Schepel, E. G., Mulder, A., Turkensteen, L. J., and Van Vuurde, J. W. L. 1999.
Preliminary selection of antagonists of Erwinia carotovora subsp. atroseptica (Van Hall)
Dye for application during green crop lifting of seed potato tubers. Potato Research
42:161-171.
Kent, A. D., and Triplett, E. W. 2002. Microbial communities and their interactions in soil and
rhizosphere ecosystems. Annual Reviews in Microbiology 56:211-236.
Khayi, S., Cigna, J., Chong, T. M., Quêtu-Laurent, A., Chan, K.-G., Hélias, V., and Faure, D.
2016. Transfer of the potato plant isolates of Pectobacterium wasabiae to Pectobacterium
137
parmentieri sp. nov. International Journal of Systematic and Evolutionary Microbiology
66:5379-5383.
Kim, H.-S., Ma, B., Perna, N. T., and Charkowski, A. O. 2009. Phylogeny and virulence of
naturally occurring type III secretion system-deficient Pectobacterium strains. Applied
and Environmental Microbiology 75:4539-4549.
Kim, H. J., Boedicker, J. Q., Choi, J. W., and Ismagilov, R. F. 2008. Defined spatial structure
stabilizes a synthetic multispecies bacterial community. Proceedings of the National
Academy of Sciences 105:18188-18193.
Kim, M. H., Cho, M. S., Kim, B. K., Choi, H. J., Hahn, J. H., Kim, C., Kang, M. J., Kim, S. H.,
and Park, D. S. 2012. Quantitative real-time polymerase chain reaction assay for
detection of Pectobacterium wasabiae using YD repeat protein gene-based primers. Plant
Disease 96:253-257.
Koeuth, T., Versalovic, J., and Lupski, J. R. 1995. Differential subsequence conservation of
interspersed repetitive Streptococcus pneumoniae BOX elements in diverse bacteria.
Genome Research 5:408-418.
Koskiniemi, S., Lamoureux, J. G., Nikolakakis, K. C., de Roodenbeke, C. t. K., Kaplan, M. D.,
Low, D. A., and Hayes, C. S. 2013. Rhs proteins from diverse bacteria mediate
intercellular competition. Proceedings of the National Academy of Sciences 110:7032-
7037.
Kranz, A., Vogel, A., Degner, U., Kiefler, I., Bott, M., Usadel, B., and Polen, T. 2017. High
precision genome sequencing of engineered Gluconobacter oxydans 621H by combining
long nanopore and short accurate Illumina reads. Journal of Biotechnology 258:197-205.
Kumar, S., Stecher, G., and Tamura, K. 2016. MEGA7: molecular evolutionary genetics analysis
version 7.0 for bigger datasets. Molecular Biology and Evolution 33:1870-1874.
Kůdela, V., Krejzar, V., and PáNkoVá, I. 2011. Pseudomonas corrugata and Pseudomonas
marginalis associated with the collapse of tomato plants in rockwool slab hydroponic
culture. Plant Protection Science 46:1-11.
Ladygina, N., and Hedlund, K. 2010. Plant species influence microbial diversity and carbon
allocation in the rhizosphere. Soil Biology and Biochemistry 42:162-168.
138
Lamichhane, J. R., and Venturi, V. 2015. Synergisms between microbial pathogens in plant
disease complexes: a growing trend. Frontiers in Plant Science 6:385.
Lanoot, B., Vancanneyt, M., Dawyndt, P., Cnockaert, M., Zhang, J., Huang, Y., Liu, Z., and
Swings, J. 2004. BOX-PCR fingerprinting as a powerful tool to reveal synonymous
names in the genus Streptomyces. Emended descriptions are proposed for the species
Streptomyces cinereorectus, S. fradiae, S. tricolor, S. colombiensis, S. filamentosus, S.
vinaceus and S. phaeopurpureus. Systematic and Applied Microbiology 27:84-92.
Lapierre, P., and Gogarten, J. P. 2009. Estimating the size of the bacterial pan-genome. Trends in
Genetics 25:107-110.
Lelliott, R. A., and Dickey, R. S. 1984. Genus VII, Erwinia spp.
Letunic, I., and Bork, P. 2019. Interactive Tree Of Life (iTOL) v4: recent updates and new
developments. Nucleic Acids Research 47:W256-W259.
Li, B., Shi, Y., Ibrahim, M., Liu, H., Shan, C., Wang, Y., Kube, M., Xie, G.-L., and Sun, G.
2012. Genome sequence of the rice pathogen Dickeya zeae strain ZJU1202. Journal of
Bacteriology 4452-4453.
Li, X., Ma, Y., Liang, S., Tian, Y., Yin, S., Xie, S., and Xie, H. 2018. Comparative genomics of
84 Pectobacterium genomes reveals the variations related to a pathogenic lifestyle. BMC
Genomics 19:889.
Lin, G., Chai, J., Yuan, S., Mai, C., Cai, L., Murphy, R. W., Zhou, W., and Luo, J. 2016.
VennPainter: a tool for the comparison and identification of candidate genes based on
venn diagrams. PLoS One 11:e0154315.
Liu, W., Xie, Y., Ma, J., Luo, X., Nie, P., Zuo, Z., Lahrmann, U., Zhao, Q., Zheng, Y., and Zhao,
Y. 2015. IBS: an illustrator for the presentation and visualization of biological sequences.
Bioinformatics 31:3359-3361.
Luo, R., Liu, B., Xie, Y., Li, Z., Huang, W., Yuan, J., He, G., Chen, Y., Pan, Q., and Liu, Y.
2012. SOAPdenovo2: an empirically improved memory-efficient short-read de novo
assembler. Gigascience 1:2047-2217X.
López-García, A., Pineda-Quiroga, C., Atxaerandio, R., Pérez, A., Hernández, I., García-
Rodríguez, A., and González-Recio, O. 2018. Comparison of Mothur and QIIME for the
139
analysis of rumen microbiota composition based on 16S rRNA amplicon sequences.
Frontiers in Microbiology 9:3010.
Ma, B., Hibbing, M. E., Kim, H.-S., Reedy, R. M., Yedidia, I., Breuer, J., Breuer, J., Glasner, J.
D., Perna, N. T., and Kelman, A. 2007. Host range and molecular phylogenies of the soft
rot enterobacterial genera Pectobacterium and Dickeya. Phytopathology 97:1150-1163.
Ma, X., Schloop, A., Swingle, B., and Perry, K. L. 2018. Pectobacterium and Dickeya
responsible for potato blackleg disease in New York State in 2016. Plant disease
102:1834-1840.
Ma, X., Perna, N. T., Glasner, J. D., Hao, J., Johnson, S., Nasaruddin, A. S., Charkowski, A. O.,
Wu, S., Fei, Z., and Perry, K. L. 2019. Complete Genome Sequence of Dickeya
dianthicola ME23, a Pathogen Causing Blackleg and Soft Rot Diseases of Potato.
Microbiol Resource Announcment 8:e01526-01518.
Malathrakis, N. E., and Goumas, D. E. 1987. Bacterial soft rot of tomato in plastic greenhouses
in Crete. Annals of applied Biology 111:115-123.
Mao, D.-P., Zhou, Q., Chen, C.-Y., and Quan, Z.-X. 2012. Coverage evaluation of universal
bacterial primers using the metagenomic datasets. BMC microbiology 12:66.
Mardis, E. R. 2008. Next-generation DNA sequencing methods. Annu. Rev. Genomics Human
Genetics 9:387-402.
Mardis, E. R. 2017. DNA sequencing technologies: 2006–2016. Nature protocols 12:213.
Marković, S., Stanković, S., Jelušić, A., Ilicic, R., Kosovac, A., Poštić, D., and Popović, T. 2020.
Occurrence and Identification of Pectobacterium carotovorum subsp. brasiliensis and
Dickeya dianthicola causing blackleg in some potato fields in Serbia. Plant Disease.
PDIS-05.
Marquez-Villavicencio, M. d. P., Groves, R. L., and Charkowski, A. O. 2011. Soft rot disease
severity is affected by potato physiology and Pectobacterium taxa. Plant Disease 95:232-
241.
Mattinen, L., Somervuo, P., Nykyri, J., Nissinen, R., Kouvonen, P., Corthals, G., Auvinen, P.,
Aittamaa, M., Valkonen, J. P. T., and Pirhonen, M. 2008. Microarray profiling of host-
140
extract-induced genes and characterization of the type VI secretion cluster in the potato
pathogen Pectobacterium atrosepticum. Microbiology 154:2387-2396.
Mazzaglia, A., Studholme, D. J., Taratufolo, M. C., Cai, R., Almeida, N. F., Goodman, T.,
Guttman, D. S., Vinatzer, B. A., and Balestra, G. M. 2012. Pseudomonas syringae pv.
actinidiae (PSA) isolates from recent bacterial canker of kiwifruit outbreaks belong to the
same genetic lineage. PloS One 7: e36518.
McGuire, R. G., and Kelman, A. 1984. Reduced severity of Erwinia soft rot in potato tubers with
increased calcium content. Phytopathology 74:1250-1256.
McNally, R. R., Curland, R. D., Webster, B. T., Robinson, A. P., and Ishimaru, C. A. 2017. First
report of blackleg and tuber soft rot of potato caused by Pectobacterium parmentieri in
Minnesota and North Dakota. Plant Disease 101:2144.
McNally, R. R., Curland, R. D., Webster, B. T., Robinson, A. P., and Ishimaru, C. A. 2018. First
report of stem rot on potato caused by Dickeya chrysanthemi in Minnesota. Plant Disease
102:238.
Mederma, G. J., Schets, F. M., Van de Giessen, A. W., and Havelaar, A. H. 1992. Lack of
colonization of 1 day old chicks by viable, non‐culturable Campylobacter jejuni. Journal
of Applied Bacteriology 72:512-516.
Medini, D., Donati, C., Tettelin, H., Masignani, V., and Rappuoli, R. 2005. The microbial pan-
genome. Current Opinion in Genetics & Development 15:589-594.
Mendes, R., Garbeva, P., and Raaijmakers, J. M. 2013. The rhizosphere microbiome:
significance of plant beneficial, plant pathogenic, and human pathogenic microorganisms.
FEMS Microbiology Reviews 37:634-663.
Mendes, R., Kruijt, M., De Bruijn, I., Dekkers, E., van der Voort, M., Schneider, J. H. M.,
Piceno, Y. M., DeSantis, T. Z., Andersen, G. L., and Bakker, P. A. H. M. 2011.
Deciphering the rhizosphere microbiome for disease-suppressive bacteria. Science
332:1097-1100.
Mikheenko, A., Prjibelski, A., Saveliev, V., Antipov, D., and Gurevich, A. 2018. Versatile
genome assembly evaluation with QUAST-LG. Bioinformatics 34:i142-i150.
141
Mina, D., Pereira, J. A., Lino-Neto, T., and Baptista, P. 2020. Impact of plant genotype and plant
habitat in shaping bacterial pathobiome: a comparative study in olive tree. Scientific
Reports 10:1-11.
Monod, J. 1949. The growth of bacterial cultures. Annual Review of Microbiology 3:371-394.
Monteiro, R. A., Balsanelli, E., Wassem, R., Marin, A. M., Brusamarello-Santos, L. C. C.,
Schmidt, M. A., Tadra-Sfeir, M. Z., Pankievicz, V. C. S., Cruz, L. M., and Chubatsu, L.
S. 2012. Herbaspirillum-plant interactions: microscopical, histological and molecular
aspects. Plant and Soil 356:175-196.
Motyka-Pomagruk, A., Zoledowska, S., Misztak, A. E., Sledz, W., Mengoni, A., and Lojkowska,
E. 2020. Comparative genomics and pangenome-oriented studies reveal high
homogeneity of the agronomically relevant enterobacterial plant pathogen Dickeya
solani. BMC Genomics 21:1-18.
Moura, M. L., Jacques, M. A., Brito, L. M., Mourão, I. M., and Duclos, J. 2004. Tomato pith
necrosis (TPN) caused by P. corrugata and P. mediterranea: severity of damages and
crop loss assessment. I International Symposium on Tomato Diseases 695:365-372.
Mousa, W. K., Shearer, C., Limay-Rios, V., Ettinger, C. L., Eisen, J. A., and Raizada, M. N.
2016. Root-hair endophyte stacking in finger millet creates a physicochemical barrier to
trap the fungal pathogen Fusarium graminearum. Nature Microbiology 1:1-12.
Mousa, W. K., Schwan, A., Davidson, J., Strange, P., Liu, H., Zhou, T., Auzanneau, F.-I., and
Raizada, M. N. 2015. An endophytic fungus isolated from finger millet (Eleusine
coracana) produces anti-fungal natural products. Frontiers in Microbiology 6:1157.
Murray, J. L., Connell, J. L., Stacy, A., Turner, K. H., and Whiteley, M. 2014. Mechanisms of
synergy in polymicrobial infections. Journal of Microbiology 52:188-199.
Na, R., and Gijzen, M. 2016. Escaping host immunity: new tricks for plant pathogens. PLoS
Pathogens 12:e1005631.
Nasaruddin, A. S., Charkowski, A. O., Babler, B. N., Perna, N. T., and Glasner, J. D. 2019. First
report of Dickeya dianthicola causing blackleg on potato in Texas. Plant Disease
103:2121.
NASS. 2018. Maine potato size and grade report. New England Field Office.
142
Nassar, A., Bertheau, Y., Dervin, C., Narcy, J.-P., and Lemattre, M. 1994. Ribotyping of Erwinia
chrysanthemi strains in relation to their pathogenic and geographic distribution. Applied
and Environmental Microbiology 60:3781-3789.
Nassar, A., Darrasse, A., Lemattre, M., Kotoujansky, A., Dervin, C., Vedel, R., and Bertheau, Y.
1996. Characterization of Erwinia chrysanthemi by pectinolytic isozyme polymorphism
and restriction fragment length polymorphism analysis of PCR-amplified fragments of
pel genes. Applied and Environment Microbiology 62:2228-2235.
Ngadze, E., Coutinho, T. A., and Van der Waals, J. E. 2010. First report of soft rot of potatoes
caused by Dickeya dadantii in Zimbabwe. Plant Disease 94:1263-1263.
Ngadze, E., Brady, C. L., Coutinho, T. A., and Van der Waals, J. E. 2012. Pectinolytic bacteria
associated with potato soft rot and blackleg in South Africa and Zimbabwe. European
Journal of Plant Pathology 134:533-549.
Nykyri, J., Niemi, O., Koskinen, P., Nokso-Koivisto, J., Pasanen, M., Broberg, M., Plyusnin, I.,
Törönen, P., Holm, L., and Pirhonen, M. 2012. Revised phylogeny and novel horizontally
acquired virulence determinants of the model soft rot phytopathogen Pectobacterium
wasabiae SCC3193. PLoS Pathogens 8: e1003013.
Ojala, J. C., Stark, J. C., and Kleinkopf, G. E. 1990. Influence of irrigation and nitrogen
management on potato yield and quality. American Potato Journal 67:29-43.
Oulghazi, S., Khayi, S., Lafkih, N., Massaoudi, Y., El Karkouri, A., El Hassouni, M., Faure, D.,
and Moumni, M. 2017. First report of Dickeya dianthicola causing blackleg disease on
potato in Morocco. Plant Disease 101:1671.
Page, A. J., Cummins, C. A., Hunt, M., Wong, V. K., Reuter, S., Holden, M. T. G., Fookes, M.,
Falush, D., Keane, J. A., and Parkhill, J. 2015. Roary: rapid large-scale prokaryote pan
genome analysis. Bioinformatics 31:3691-3693.
Pagel, W., and Heitefuss, R. 1989. Calcium content and cell wall polygalacturonans in potato
tubers of cultivars with different susceptibilities to Erwinia carotovora subsp.
atroseptica. Physiological and Molecular Plant Pathology 35:11-21.
Parkinson, N., DeVos, P., Pirhonen, M., and Elphinstone, J. 2014. Dickeya aquatica sp. nov.,
isolated from waterways. International Journal of Systematic and Evolutionary
Microbiology 64:2264-2266.
143
Parkinson, N., Pritchard, L., Bryant, R., Toth, I., and Elphinstone, J. 2015. Epidemiology of
Dickeya dianthicola and Dickeya solani in ornamental hosts and potato studied using
variable number tandem repeat analysis. European Journal of Plant Pathology 141:63-70.
Parkinson, N., Stead, D., Bew, J., Heeney, J., Tsror, L., and Elphinstone, J. 2009. Dickeya
species relatedness and clade structure determined by comparison of recA sequences.
International Journal of Systematic and Evolutionary Microbiology 59:2388-2393.
Partida-Martinez, L. P., and Hertweck, C. 2005. Pathogenic fungus harbours endosymbiotic
bacteria for toxin production. Nature 437:884-888.
Partida-Martinez, L. P. P., and Heil, M. 2011. The microbe-free plant: fact or artifact? Frontiers
in Plant Science 2:100.
Patel, N., Baldwin, A. C., Patel, R. D., Kobayashi, D. Y., and Wyenandt, C. A. 2019. First report
of Dickeya dianthicola causing blackleg and soft rot on potato (Solanum tuberosum) in
New Jersey, USA. Plant Disease 103:146.
Paula Wilkie, J., and Dye, D. W. 1974. Pseudomonas cichorii causing tomato and celery
diseases in New Zealand. New Zealand Journal of Agricultural Research 17:123-130.
Perombelon, M. C. M. 2000. Blackleg risk potential of seed potatoes determined by
quantification of tuber contamination by the causal agent and Erwinia carotovora subsp.
atroseptica: a critical review. EPPO Bulletin 30:413-420.
Perombelon, M. C. M., and Kelman, A. 1980. Ecology of the soft rot erwinias. Annual Review
of Phytopathology 18:361-387.
Perombelon, M. C. M., and Van Der Wolf, J. M. 2002. Methods for the detection and
quantification of Erwinia carotovora subsp. atroseptica (Pectobacterium carotovorum
subsp. atrosepticum) on potatoes: a laboratory manual. Scottish Crop Research Institute
Annual Report 10.
Petersen, L. M., Martin, I. W., Moschetti, W. E., Kershaw, C. M., and Tsongalis, G. J. 2019.
Third-generation sequencing in the clinical laboratory: exploring the advantages and
challenges of nanopore sequencing. Journal of Clinical Microbiology 58.
Pinto, D., Santos, M. A., and Chambel, L. 2015. Thirty years of viable but nonculturable state
research: unsolved molecular mechanisms. Critical Reviews in Microbiology 41:61-76.
144
Pitman, A. R., Wright, P. J., Galbraith, M. D., and Harrow, S. A. 2008. Biochemical and genetic
diversity of pectolytic enterobacteria causing soft rot disease of potatoes in New Zealand.
Australasian Plant Pathology 37:559-568.
Pritchard, L., Humphris, S., Saddler, G. S., Parkinson, N. M., Bertrand, V., Elphinstone, J. G.,
and Toth, I. K. 2013. Detection of phytopathogens of the genus Dickeya using a PCR
primer prediction pipeline for draft bacterial genome sequences. Plant Pathology 62:587-
596.
Pu, X. M., Zhou, J. N., Lin, B. R., and Shen, H. F. 2012. First report of bacterial foot rot of rice
caused by a Dickeya zeae in China. Plant Disease 96:1818.
Pérez‐Mendoza, D., Coulthurst, S. J., Humphris, S., Campbell, E., Welch, M., Toth, I. K., and
Salmond, G. P. C. 2011. A multi‐repeat adhesin of the phytopathogen, Pectobacterium
atrosepticum, is secreted by a Type I pathway and is subject to complex regulation
involving a non‐canonical diguanylate cyclase. Molecular Microbiology 82:719-733.
Pérombelon, M. C. M. 1992. Potato blackleg: epidemiology, host-pathogen interaction and
control. Netherlands Journal of Plant Pathology 98:135-146.
Pérombelon, M. C. M., Fox, R. A., and Lowe, R. 1979. Dispersion of Erwinia carotovora in
aerosols produced by the pulverization of potato haulm prior to harvest.
Phytopathologische Zeitschrift 94:249-260.
Põllumaa, L., Alamäe, T., and Mäe, A. 2012. Quorum sensing and expression of virulence in
pectobacteria. Sensors 12:3327-3349.
Radcliffe, E. B., and Ragsdale, D. W. 2002. Aphid-transmitted potato viruses: the importance of
understanding vector biology. American Journal of Potato Research 79:353-386.
Rahmanifar, B., Hasanzadeh, N., Razmi, J., and Ghasemi, A. 2012. Genetic diversity of Iranian
potato soft rot bacteria based on polymerase chain reaction-restriction fragment length
polymorphism (PCR-RFLP) analysis. African Journal of Biotechnology 11:1314-1320.
Ranganna, B., Kushalappa, A. C., and Raghavan, G. S. V. 1997. Ultraviolet irradiance to control
dry rot and soft rot of potato in storage. Canadian Journal of Plant Pathology 19:30-35.
Rankin, D. J., Bargum, K., and Kokko, H. 2007. The tragedy of the commons in evolutionary
biology. Trends in Ecology & Evolution 22:643-651.
145
Rantakari, A., Virtaharju, O., Vähämiko, S., Taira, S., Palva, E. T., Saarilahti, H. T., and
Romantschuk, M. 2001. Type III secretion contributes to the pathogenesis of the soft-rot
pathogen Erwinia carotovora: partial characterization of the hrp gene cluster. Molecular
Plant-Microbe Interactions 14:962-968.
Reinhold-Hurek, B., Bünger, W., Burbano, C. S., Sabale, M., and Hurek, T. 2015. Roots shaping
their microbiome: global hotspots for microbial activity. Annual Review of
Phytopathology 53:403-424.
Reverchon, S., Muskhelisvili, G., and Nasser, W. 2016. Virulence program of a bacterial plant
pathogen: the Dickeya model. Pages 51-92 in: Progress in molecular biology and
translational science. Elsevier 142.
Ritpitakphong, U., Falquet, L., Vimoltust, A., Berger, A., Métraux, J. P., and L'Haridon, F. 2016.
The microbiome of the leaf surface of Arabidopsis protects against a fungal pathogen.
New Phytologist 210:1033-1043.
Robinson, K., and Foster, G. 1987. Control of potato blackleg by tuber pasteurisation: the
determination of time-temperature combinations for the inactivation of pectolytic
erwinia. Potato Research 30:121-125.
Rodríguez-Beltrán, J., Sørum, V., Toll-Riera, M., de la Vega, C., Peña-Miller, R., and San
Millán, Á. 2020. Genetic dominance governs the evolution and spread of mobile genetic
elements in bacteria. Proceedings of the National Academy of Sciences 117:15755-
15762.
Rojas, C. M., Ham, J. H., Deng, W.-L., Doyle, J. J., and Collmer, A. 2002. HecA, a member of a
class of adhesins produced by diverse pathogenic bacteria, contributes to the attachment,
aggregation, epidermal cell killing, and virulence phenotypes of Erwinia chrysanthemi
EC16 on Nicotiana clevelandii seedlings. Proceedings of the National Academy of
Sciences 99:13142-13147.
Rolli, E., Marasco, R., Vigani, G., Ettoumi, B., Mapelli, F., Deangelis, M. L., Gandolfi, C.,
Casati, E., Previtali, F., and Gerbino, R. 2015. Improved plant resistance to drought is
promoted by the root‐associated microbiome as a water stress‐dependent trait.
Environmental Microbiology 17:316-331.
Rolot, J. L., and Seutin, H. 1999. Soilless production of potato minitubers using a hydroponic
technique. Potato Research 42:457-469.
146
Rosenzweig, N., Steere, L., Kirk, W. W., Mambetova, S., Long, C., Schafer, R., Dangi, S., and
Byrne, J. 2016. First report of Dickeya dianthicola and Pectobacterium wasabiae causing
aerial stem rot of potato in Michigan, USA. New Disease Report 33:2044-0588.
Rossum, G. 1995. Python reference manual.
Rouli, L., Merhej, V., Fournier, P. E., and Raoult, D. 2015. The bacterial pangenome as a new
tool for analysing pathogenic bacteria. New Microbes and New Infections 7:72-85.
Russell, A. B., Peterson, S. B., and Mougous, J. D. 2014. Type VI secretion system effectors:
poisons with a purpose. Nature Reviews Microbiology 12:137-148.
Salaman, R. N., and Burton, W. G. 1985. The history and social influence of the potato.
Cambridge University Press.
Salmond, G. P. C. 1994. Secretion of extracellular virulence factors by plant pathogenic bacteria.
Annual Review of Phytopathology 32:181-200.
Samson, R., Legendre, J. B., Christen, R., Fischer-Le Saux, M., Achouak, W., and Gardan, L.
2005. Transfer of Pectobacterium chrysanthemi (Burkholder et al. 1953) Brenner et al.
1973 and Brenneria paradisiaca to the genus Dickeya gen. nov as Dickeya chrysanthemi
comb. nov and Dickeya paradisiaca comb. nov and delineation of four novel species,
Dickeya dadantii sp nov., Dickeya dianthicola sp nov., Dickeya dieffenbachiae sp nov
and Dickeya zeae sp nov. International Journal of Systematic and Evolutionary
Microbiology 55:1415-1427.
Sanger, F., and Coulson, A. R. 1975. A rapid method for determining sequences in DNA by
primed synthesis with DNA polymerase. Journal of Molecular Biology 94:441-448.
Sanger, F., Nicklen, S., and Coulson, A. R. 1977. DNA sequencing with chain-terminating
inhibitors. Proceedings of the National Academy of Sciences 74:5463-5467.
Sarfraz, S., Riaz, K., Oulghazi, S., Cigna, J., Alam, M. W., Dessaux, Y., and Faure, D. 2018.
First report of Dickeya dianthicola causing blackleg disease on potato plants in Pakistan.
Plant Disease 102: 2027-2028.
Saygili, H., Aysan, Y., Ustun, N., Mirik, M., and Sahin, F. 2008. Tomato pith necrosis disease
caused by Pseudomonas species in Turkey. Pages 357-366 in: Pseudomonas syringae
Pathovars and Related Pathogens–Identification, Epidemiology and Genomics. Springer.
147
Scarlett, C. M., Fletcher, J. T., Roberts, P., and Lelliott, R. A. 1978. Tomato pith necrosis caused
by Pseudomonas corrugata n. sp. Annals of Applied Biology 88:105-114.
Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B.,
Lesniewski, R. A., Oakley, B. B., Parks, D. H., and Robinson, C. J. 2009. Introducing
mothur: open-source, platform-independent, community-supported software for
describing and comparing microbial communities. Applied and Environment
Microbiology. 75:7537-7541.
Schoch, C. L., Seifert, K. A., Huhndorf, S., Robert, V., Spouge, J. L., Levesque, C. A., Chen, W.,
and Fungal Barcoding, C. 2012. Nuclear ribosomal internal transcribed spacer (ITS)
region as a universal DNA barcode marker for Fungi. Proceedings of the National
Academy of Sciences 109:6241-6246.
Scholthof, K.-B. G. 2007. The disease triangle: pathogens, the environment and society. Nature
Reviews Microbiology 5:152-156.
Seemann, T. 2014. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30:2068-2069.
Shahbandeh, M. 2020. Trade value of potatoes to the United States from 2015 to 2019. Retrieved
from https://www.statista.com/statistics/816722/us-imports-and-exports-of-potatoes/
Shendure, J., and Ji, H. 2008. Next-generation DNA sequencing. Nature Biotechnology 26:1135-
1145.
Shirsat, S. G., Thomas, P., and Nair, P. M. 1991. Evaluation of treatments with hot water,
chemicals and ventilated containers to reduce microbial spoilage in irradiated potatoes.
Potato research 34:227-231.
Short, F. L., Murdoch, S. L., and Ryan, R. P. 2014. Polybacterial human disease: the ills of social
networking. Trends in Microbiology 22:508-516.
Singer, M. 2010. Pathogen-pathogen interaction: a syndemic model of complex biosocial
processes in disease. Virulence 1:10-18.
Singh, B., Bhardwaj, V., Kaur, K., Kukreja, S., and Goutam, U. 2020. Potato Periderm is the first
layer of defence against biotic and abiotic stresses: a review. Potato Research:1-16.
148
Sinha, S. K., and Prasad, M. 1977. Bacterial stalk rot of maize, its symptoms and host-range.
Zentralblatt für Bakteriologie, Parasitenkunde, Infektionskrankheiten und Hygiene.
Zweite Naturwissenschaftliche Abteilung: Allgemeine, Landwirtschaftliche und
Technische Mikrobiologie 132:81-88.
Smolarska, A., Rabalski, L., Narajczyk, M., and Czajkowski, R. 2018. Isolation and phenotypic
and morphological characterization of the first Podoviridae lytic bacteriophages ϕA38
and ϕA41 infecting Pectobacterium parmentieri (former Pectobacterium wasabiae).
European Journal of Plant Pathology 150:413-425.
Soleimani-Delfan, A., Etemadifar, Z., Emtiazi, G., and Bouzari, M. 2015. Isolation of Dickeya
dadantii strains from potato disease and biocontrol by their bacteriophages. Brazilian
Journal of Microbiology 46:791-797.
Steen, A. D., Crits-Christoph, A., Carini, P., DeAngelis, K. M., Fierer, N., Lloyd, K. G., and
Thrash, J. C. 2019. High proportions of bacteria and archaea across most biomes remain
uncultured. The ISME journal 13:3126-3130.
Stevenson, W. R., Loria, R., Franc, G. D., and Weingartner, D. P. 2001. Compendium of potato
diseases. Microbiology Socity for General.
Sławiak, M., van Beckhoven, J. R. C. M., Speksnijder, A. G. C. L., Czajkowski, R., Grabe, G.,
and van der Wolf, J. M. 2009. Biochemical and genetical analysis reveal a new clade of
biovar 3 Dickeya spp. strains isolated from potato in Europe. European Journal of Plant
Pathology 125:245-261.
Team, R. C. 2013. R: A language and environment for statistical computing. Vienna, Austria.
Tekalign, T., and Hammes, P. S. 2005. Growth and productivity of potato as influenced by
cultivar and reproductive growth: II. Growth analysis, tuber yield and quality. Scientia
Horticulturae 105:29-44.
Thomson, S. V., Hildebrand, D. C., and Schroth, M. N. 1981. Identification and nutritional
differentiation of the Erwinia sugar beet pathogen from members of Erwinia carotovora
and Erwinia chrysanthemi. Phytopathology 71:1037-1042.
Thornton, M. 2020. Potato growth and development. Potato Production Systems. Springer: 19-
33.
149
Tian, Y., Zhao, Y., Yuan, X., Yi, J., Fan, J., Xu, Z., Hu, B., De Boer, S. H., and Li, X. 2016.
Dickeya fangzhongdai sp. nov., a plant-pathogenic bacterium isolated from pear trees
(Pyrus pyrifolia). International Journal of Systematic and Evolutionary Microbiology
66:2831-2835.
Tollenaere, C., Susi, H., and Laine, A.-L. 2016. Evolutionary and epidemiological implications
of multiple infection in plants. Trends in Plant Science 21:80-90.
Toth, I. K., Pritchard, L., and Birch, P. R. J. 2006. Comparative genomics reveals what makes an
enterobacterial plant pathogen. Annual Review of Phytopathology. 44:305-336.
Toth, I. K., Bell, K. S., Holeva, M. C., and Birch, P. R. J. 2003. Soft rot erwinia: from genes to
genomes. Molecular Plant Pathology 4:17-30.
Toth, I. K., van der Wolf, J. M., Saddler, G., Lojkowska, E., Helias, V., Pirhonen, M., Tsror, L.,
and Elphinstone, J. G. 2011. Dickeya species: an emerging problem for potato production
in Europe. Plant Pathology (Oxford) 60:385-399.
Tseng, T.-T., Tyler, B. M., and Setubal, J. C. 2009. Protein secretion systems in bacterial-host
associations, and their description in the Gene Ontology. BMC Microbiology 9:1-9.
Turner, T. R., James, E. K., and Poole, P. S. 2013. The plant microbiome. Genome Biology 14:1-
10.
USDA. 2019. Potato 2018 summary.
Van de Peer, Y., Chapelle, S., and De Wachter, R. 1996. A quantitative map of nucleotide
substitution rates in bacterial rRNA. Nucleic Acids Research 24:3381-3391.
Van der Ent, S., Van Hulten, M., Pozo, M. J., Czechowski, T., Udvardi, M. K., Pieterse, C. M. J.,
and Ton, J. 2009. Priming of plant innate immunity by rhizobacteria and β‐aminobutyric
acid: differences and similarities in regulation. New Phytologist 183:419-431.
Van Der Heijden, M. G. A., De Bruin, S., Luckerhoff, L., Van Logtestijn, R. S. P., and
Schlaeppi, K. 2016. A widespread plant-fungal-bacterial symbiosis promotes plant
biodiversity, plant nutrition and seedling recruitment. The ISME Journal 10:389-399.
150
van der Wolf, J. M., and De Boer, S. H. 2007. Bacterial pathogens of potato. Potato Biology and
Biotechnology. Elsevier: 595-617
van der Wolf, J. M., Nijhuis, E. H., Kowalewska, M. J., Saddler, G. S., Parkinson, N.,
Elphinstone, J. G., Pritchard, L., Toth, I. K., Lojkowska, E., Potrykus, M., Waleron, M.,
de Vos, P., Cleenwerck, I., Pirhonen, M., Garlant, L., Helias, V., Pothier, J. F., Pflueger,
V., Duffy, B., Tsror, L., and Manulis, S. 2014. Dickeya solani sp nov., a pectinolytic
plant-pathogenic bacterium isolated from potato (Solanum tuberosum). International
Journal of Systematic and Evolutionary Microbiology 64:768-774.
Vayssier-Taussat, M., Albina, E., Citti, C., Cosson, J. F., Jacques, M.-A., Lebrun, M.-H., Le
Loir, Y., Ogliastro, M., Petit, M.-A., and Roumagnac, P. 2014. Shifting the paradigm
from pathogens to pathobiome: new concepts in the light of meta-omics. Frontiers in
Cellular and Infection Microbiology 4:29.
Versalovic, J., Koeuth, T., and Lupski, R. 1991. Distribution of repetitive DNA sequences in
eubacteria and application to finerpriting of bacterial enomes. Nucleic Acids Research
19:6823-6831.
von Bodman, S. B., Bauer, W. D., and Coplin, D. L. 2003. Quorum sensing in plant-pathogenic
bacteria. Annual Review of Phytopathology 41:455-482.
Waggoner, P. E., and Berger, R. D. 1987. Defoliation, disease, and growth. Phytopathology
77:393-398.
Wallden, K., Rivera‐Calzada, A., and Waksman, G. 2010. Microreview: Type IV secretion
systems: versatility and diversity in function. Cellular Microbiology 12:1203-1212.
Weirather, J. L., de Cesare, M., Wang, Y., Piazza, P., Sebastiano, V., Wang, X.-J., Buck, D., and
Au, K. F. 2017. Comprehensive comparison of Pacific Biosciences and Oxford Nanopore
Technologies and their applications to transcriptome analysis. F1000Research 6.
West, S. A., Griffin, A. S., Gardner, A., and Diggle, S. P. 2006. Social evolution theory for
microorganisms. Nature Reviews Microbiology 4:597-607.
Wigginton, M. J. 1973. Diffusion of oxygen through lenticels in potato tuber. Potato Research
16:85-87.
151
Xu, H.-S., Roberts, N., Singleton, F. L., Attwell, R. W., Grimes, D. J., and Colwell, R. R. 1982.
Survival and viability of nonculturable Escherichia coli and Vibrio cholerae in the
estuarine and marine environment. Microbial Ecology 8:313-323.
Yang, C.-H., Gavilanes-Ruiz, M., Okinaka, Y., Vedel, R., Berthuy, I., Boccara, M., Chen, J. W.-
T., Perna, N. T., and Keen, N. T. 2002. hrp genes of Erwinia chrysanthemi 3937 are
important virulence factors. Molecular Plant-Microbe Interactions 15:472-480.
Young, J. M., Dye, D. W., Bradbury, J. F., Panagopoulos, C. G., and Robbs, C. F. 1978. A
proposed nomenclature and classification for plant pathogenic bacteria. New Zealand
Journal of Agricultural Research 21:153-177.
Yousef, F., and Espinosa-Urgel, M. 2007. In silico analysis of large microbial surface proteins.
Research in Microbiology 158:545-550.
Zamioudis, C., Korteland, J., Van Pelt, J. A., van Hamersveld, M., Dombrowski, N., Bai, Y.,
Hanson, J., Van Verk, M. C., Ling, H. Q., and Schulze‐Lefert, P. 2015. Rhizobacterial
volatiles and photosynthesis‐related signals coordinate MYB 72 expression in
Arabidopsis roots during onset of induced systemic resistance and iron‐deficiency
responses. The Plant Journal 84:309-322.
Zhang, J., Shen, H., Pu, X., Lin, B., and Hu, J. 2014. Identification of Dickeya zeae as a causal
agent of bacterial soft rot in banana in China. Plant Disease 98:436-442.
Zhang, Y., Fan, Q., and Loria, R. 2016. A re-evaluation of the taxonomy of phytopathogenic
genera Dickeya and Pectobacterium using whole-genome sequencing data. Systematic
and Applied Microbiology 39:252-259.
Zwankhuizen, M. J., Govers, F., and Zadoks, J. C. 1998. Development of potato late blight
epidemics: Disease foci, disease gradients, and infection sources. Phytopathology 88:754-
763.
152
BIOGRAPHY OF THE AUTHOR
Tongling Ge was born in Heze, Shandong, China on November 13, 1992. She graduated from
Dingtao No.1 High School in 2010. She attended Shandong Agricultural University in 2010 and
graduated in June 2014 with a Bachelor of Science degree in Agronomy. She enrolled in the
Department of Plant Pathology at China Agricultural University in the fall of 2014 and graduated
in June 2016 with a master’s degree in Plant Protection. From July 2016 to June 2017, she
worked in Dr. Hao’s Lab at the University of Maine as a Research Assistant. She continued at
the University of Maine seeking a Ph.D. degree in the program of Ecology and Environmental
Sciences in the fall of 2017. During her Ph.D. program, she won two travel awards for research
conferences and one research award. She contributed six talks and abstracts to American
Phytopathological Society annual meetings and other research conferences. Tongling has three
publications in Plant Disease Journal and 14 in Plant Disease Management Reports as first
author. She also has two publications in peer-reviewed journals and 16 in Plant Disease
Management Reports as a co-author. She is a candidate for the Doctor of Philosophy degree in
Ecology and Environmental Sciences from the University of Maine in May 2021.