www.fems-microbiology.org

FEMS Microbiology Reviews 29 (2005) 393–409

Genomic features of lactic acid bacteria effectingbioprocessing and health

Todd R. Klaenhammer a,b,*, Rodolphe Barrangou a,b, B. Logan Buck a,M. Andrea Azcarate-Peril a, Eric Altermann a

a Departments of Food Science and Microbiology, North Carolina State University, Box 7624, Raleigh, NC 27695-7624, United Statesb Functional Genomics Program, Southeast Dairy Foods Research Center, Raleigh, NC 27695, United States

Received 24 March 2005; accepted 27 April 2005

First published online 28 August 2005

Abstract

The lactic acid bacteria are a functionally related group of organisms known primarily for their bioprocessing roles in food and

beverages. More recently, selected members of the lactic acid bacteria have been implicated in a number of probiotic roles that

impact general health and well-being. Genomic analyses of multiple members of the lactic acid bacteria, at the genus, species,

and strain level, have now elucidated many genetic features that direct their fermentative and probiotic roles. This information

is providing an important platform for understanding core mechanisms that control and regulate bacterial growth, survival, signal-

ing, and fermentative processes and, in some cases, potentially underlying probiotic activities within complex microbial and host

ecosystems.

� 2005 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved.

Keywords: Lactic acid bacteria; Genomics; Bioprocessing; Probiotics; Comparative genomics; Functional genomics

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393

2. Genome characteristics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 394

3. Comparative genomics of lactobacilli. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399

4. Functional genomic analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401

5. Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 406

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 406

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 406

1. Introduction

Lactic acid bacteria (LAB) are a heterogeneous fam-

ily of microorganisms that can ferment a variety of

0168-6445/$22.00 � 2005 Federation of European Microbiological Societies

doi:10.1016/j.femsre.2005.04.007

* Corresponding author. Tel.: +1 919 515 2972; fax: +1 919 513 0014.

E-mail address: klaenhammer@ncsu.edu (T.R. Klaenhammer).

nutrients [1] primarily into lactic acid. They are mainly

Gram-positive, anaerobic bacteria, non-sporulating,

and acid tolerant. Biochemically, LAB include both

homofermenters and heterofermenters. The former pro-

duce primarily lactic acid, while the latter yield also a

variety of fermentation by-products, including lacticacid, acetic acid, ethanol, carbon dioxide and formic

. Published by Elsevier B.V. All rights reserved.

394 T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409

acid [2,3]. Although their primary contribution centers

on rapid acid production and acidification of food prod-

ucts, they also contribute to flavor, texture and nutrition

[3]. LAB are found naturally in a variety of environmen-

tal habitats, including dairy, meat, vegetable, cereal and

plant environments, where fermentation can occur. His-torically, the traditional roles for many LAB have been

as starter cultures to drive food and dairy fermentations,

leading to their widespread human consumption and

generally recognized as safe (GRAS) status.

It was nearly 100 years ago that Russian scientist,

Elie Metchnikoff, then at the Pasteur Institute, proposed

that lactic bacteria in fermented milk could promote the

development of a healthy intestinal microbiota. Specifi-cally, the Nobel-laureate developed a theory that lactic-

acid bacteria in the digestive tract could prolong life by

preventing putrefaction. Since that time, it has been rec-

ognized that some LAB and the high G + C content

Gram-positive bifidobacteria are also found naturally

within human and animal cavities, including the gastro-

intestinal tract (Lactobacillus acidophilus, Lactobacillus

gasseri, Lactobacillus johnsonii, Lactobacillus plantarum,Streptococcus agalactiae, Enterococcus faecalis), the oral

cavity (Streptococcus mutans, Bifidobacterium longum),

and the vaginal cavity (B. longum, S. agalactiae, Lacto-

bacillus crispatus) [4–6]. LAB are considered to be

important components of the normal intestinal microbi-

ota, which contribute to a variety of functions including

intestinal integrity, immunomodulation, and pathogen

resistance. Selected groups of Lactobacillus and Bifido-

bacterium are used widely as probiotics primarily in

dairy products and dietary supplements [5,7,8].

Defined most recently as ‘‘live microorganisms which,

when administered in adequate amounts, confer a health

benefit on the host’’ [9], probiotic cultures have been

found useful in the maintenance of gastrointestinal

(GI) health including the treatment of diarrheal diseases

and preservation of intestinal integrity and mobility. Re-cent evidence from in vitro systems, animal models, and

clinical studies suggests that LAB can enhance both spe-

cific and non-specific immune responses, possibly by

activating macrophages, altering cytokine expression,

increasing natural killer cell activity, and/or increasing

levels of immunoglobulins [5,10,11]. However, the mech-

anisms through which these LAB function as immuno-

modulators are not characterized and specific reactionscan be highly variable among different strains.

In the recent past, substantial progress has been

achieved in microbial genomics, particularly in genome

sequencing. To date, over 229 complete microbial gen-

omes (prokaryotes and archaea) have been published

(NCBI website, www.ncbi.nlm.nih.gov/genomes/MI-

CROBES/complete.html), covering a wide diversity of

taxonomic groups. Early microbial genome analysesindicate that genomic content reflects an organism�smetabolism, physiology, biosynthetic capabilities, and

adaptability to varying conditions and environments.

In the case of the LAB, genome analysis is revolutioniz-

ing our view of their metabolic processes, bioprocessing

capabilities and potential roles in health and well-being.

2. Genome characteristics

The published genome sequences of the lactic acid

bacteria and bifidobacteria include Lactococcus lactis

[12], S. mutans [13], S. pneumoniae [14], S. agalactiae

[15], S. pyogenes [16], S. thermophilus [17], B. longum

[18], L. plantarum [19], L. johnsonii [20] and L. acidoph-

ilus [21]. The 11 draft genomes represented by the LacticAcid Bacteria Genomics Consortium [22,23] have re-

cently been completed (unpublished results). The LAB

analyzed were Lactobacillus brevis, L. casei, L. gasseri,

Lc. cremoris, Leuconostoc mesenteroides, Oenococcus

oeni, Pediococcus pentosaceus, and S. thermophilus. For

the LAB and bifidobacteria, probiotic organisms, and

other related industrial microbes, genome features are

presented in Table 1.LAB and bifidobacteria are Gram-positive bacteria

with low and high GC content, respectively, with small

genomes ranging in size between 1.8 and 3.3 Mb (Table

1). For those species where complete genomes are pub-

lished and annotated, a broad picture emerges of con-

served and varying biosynthetic and metabolic

capabilities. Glycolysis enzymes are uniformly repre-

sented among members of the LAB. A recent transcrip-tional analysis of global gene expression by L.

acidophilus during growth on eight different carbohy-

drates revealed that genes of the glycolytic pathway were

among the most highly expressed genes within the gen-

ome [25] (Fig. 1). Since LAB recover their primary en-

ergy via glycolysis, it seems likely that this is a

universal feature. Genome analyses have shown that lac-

tobacilli, bifidobacteria, streptococci, and lactococcipossess broad saccharolytic potentials, which reflect

the nutrient diversity provided by the range of environ-

ments they inhabit [13,14,18–21]. Analysis of the L.

plantarum genome revealed many transporters, particu-

larly PTS (phosphotransferase system) transporters

(25) correlating with the organism�s broad capacity to

metabolize varied carbohydrates from different environ-

ments [19]. In particular, a ‘‘lifestyle adaptation island’’was defined over a 213 kb region that harbored genes in-

volved in sugar transport and metabolism. Similarly, the

diversity of transporters in S. mutans and S. pneumoniae

has been associated with an increased ability to utilize

nutrient sources present in their environments, namely

the oral cavity and respiratory tract [13,14]. Analysis

of the L. johnsonii [20], L. acidophilus [21], and L. gasseri

genomes further substantiate these observations show-ing a preponderance of PTS transporters, and only 2

to 3 ABC (ATP-binding cassette) transporters identified

Table 1

Genomes of lactic acid bacteria and other industrially used species

Genus Species Strain Size (Mbp) %GC Status Reference

Bifidobacterium longum NCC2705 2.3 60.1 Ca [18]

longum DJ010A 2.4 59 IPb JGIc

Brevibacterium linens BL2/ATCC9174 4.4 60.9 IP JGI

Enterococcus faecalis V583 3.2 37.5 C [24]

Lactobacillus acidophilus NCFM 2.0 34.7 C [21]

gasseri ATCC333323 1.8 35.1 IP JGI

johnsonii NCC533 2.0 34.6 C [20]

plantarum WCFS1 3.3 44.5 C [19]

casei ATCC334 2.5 41.1 IP JGI

casei BL23 2.6 4.6 IP [23]

rhamnosus HN001 2.4 46.4 IP Lubbers et al. (unpublished)

helveticus CNRZ32 2.4 37.1 IP Steele et al. (unpublished)

helveticus CM4 2.0 37 C Shinoda (unpublished)

sakei 23K 1.9 41.2 C [23]

delbrueckii ATCCBAA365 2.3 45.7 IP JGI

delbrueckii ATCC11842 2.3 50 IP [23]

delbrueckii DN-100107 2.1 IP [23]

reuteri IP JGI

salivarius UCC118 IP [23]

brevis ATCC367 2.0 43.1 IP JGI

Lactococcus lactis ssp. lactis IL1403 2.3 35.4 C [12]

lactis ssp. cremoris SK11 2.3 30.9 IP JGI

lactis spp. cremoris MG1363 2.6 37.1 IP [23]

Leuconostoc mesenteroides ATCC8293 2.0 37.4 IP JGI

Oenococcus oeni ATCCBAA331 1.8 37.5 IP JGI

oeni IOEB84.13 1.8 37.9 IP [23]

Pediococcus pentosaceus ATCC25745 2.0 37.0 IP JGI

Propionibacterium freudenreichii ATCC6207 2.6 67.4 IP [23]

Streptococcus agalactiae 2603V/R 2.2 35.7 C [15]

mutans UA159 2.0 36.8 C [13]

pneumoniae TIGR4 2.2 39.7 C [14]

pyogenes M1 1.9 38.5 C [16]

thermophilus LMD9 1.8 36.8 IP JGI

thermophilus LMG18311 1.9 39 C [17]

thermophilus CNRZ1066 1.8 39 C [17]

Adapted from [22,23,25].a C, complete.b IP, in progress.c JGI, Joint Genome Institute.

T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409 395

for maltose and complex carbohydrates like fructooligo-

saccharide and raffinose (Table 2). An overview of the

carbohydrate transporters found in L. acidophilus is

shown in Fig. 2, where PTS systems were predominant

and lactose and galactose were predicted to be trans-

ported by a galactoside permease [25]. A recent analysis

of 9 LAB genomes for transporter capabilities revealed

that 13–17 % of their total genes encoded transport pro-teins (Lorca, G.L., Zlotopolski, V., Tran, C., Winnen,

B., Hvorup, R.N., Nguyen, E., Huang, L.-W., and

Saier, M.H., unpublished). This proportion was larger

than observed for most bacteria. Interestingly, amino

acid uptake systems predominated over sugar and pep-

tide uptake systems.

Although amino acid biosynthetic pathways are com-

plete in L. lactis, they are deficient in varying levels in

most other LAB. L. plantarum is missing only a few syn-

thetic pathways including those for branched chain

amino acid synthesis [19], whereas species of the

‘‘L. acidophilus complex’’ (L. gasseri, L. johnsonii and

L. acidophilus) [27] are largely deficient in amino acid

biosynthetic capacity [20,21]. Compensating for thesedeficiencies, the lactobacilli generally encode a large

number of peptidases, amino acid permeases, and multi-

ple oligo-peptide transporters that could support effi-

cient processing and recovery of amino acids from

nutritionally rich environmental sources. However, of

the intestinal lactobacilli (including comparisons with

Fig. 1. Hierarchical clustering analyses of gene expression patterns (left panel). The expression of 1889 genes (vertically) after growth on eight

carbohydrates (horizontally) is shown colorimetrically. Least squares means, representing overall gene expression level corrected for systematic and

random errors low = blue, high = red; hierarchical clustering of least squares means allows visualization of the relative expression levels of all genes

within each treatment. Lanes from left to right are fructooligosaccharides; fructose; galactose; glucose; lactose; raffinose; sucrose; and trehalose.

Microarrays were carried out using PCR products of predicted ORFs [26]. Expression of glycolysis genes (right panel). In a whole genome array, the

global transcription responses during growth on eight different carbohydrates are denoted for D-lactate dehydrogenase (D-LDH, La55),

phosphyglycerate mutase (PGM, La185), L-lactate dehydrogenase (L-LDH, La271), glyceraldehyde 3-phosphate dehydrogenase (GPDH, La698),

phosphoglycerate kinase (PGK La699), glucose 6-phosphate isomerase (GPI, La752), 2-phosphoglycerate dehydratase (PGDH, La889),

phosphofructokinase (PFK, La956), pyruvate kinase (PK, La957), fructose-biphosphate aldolase (FBPA,La1599). Expression: low

high [25].

396 T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409

L. gasseri and L. plantarum), only L. acidophilus and

L. johnsonii were found to encode the cell wall-associ-

ated proteinase, PrtP. Interestingly, the gene predicted

to encode the maturation protein, PrtM, was found in

all these Lactobacillus genomes.

For the LAB, their genomes are collectively of low

GC content and relatively small. Those species with

the smallest genomes can be highly auxotrophic anddeficient in a number of biosynthetic pathways, corre-

sponding to their apparent adaptation to nutritionally

rich environments [20,21]. For the lactobacilli, a sum-

mary of biosynthetic pathways (amino acids, nucleo-

tides, fatty acids and vitamins) illustrated that L.

gasseri and L. johnsonii exhibit the fewest metabolic bio-

synthetic pathways (6–8), whereas L. acidophilus shows

a higher number at 14 pathways (K. Makarova, E. Koo-nin and LABGC, unpublished data). In contrast,

L. plantarum encodes a more complete complement of

biosynthetic pathways (22), supporting its more diverse

metabolic capabilities. In this regard, a direct compari-

son of metabolic pathways via Kyoto Encyclopedia of

Genes and Genomes (KEGG) between L. plantarum

and L. johnsonii by Boekhorst et al. [28] highlighted

the biosynthetic deficiencies in L. johnsonii and ex-

panded capacity of L. plantarum.

In the current analysis of the complete LAB gen-

omes, it has been suggested that evolution to nutrition-ally rich environments (e.g., milk, human GI tract) has

promoted genome simplification and degradation for

some species. Notably, in the recent genome analysis

of two S. thermophilus strains, Bolotin et al. [17] found

that 10% of the genes were pseudogenes and non-func-

tional due to frameshifts, nonsense mutation, deletion,

or truncation. Evidence for genome decay was particu-

larly noted for genes involved in carbohydrate metab-olism, uptake and fermentation. In contrast, a specific

symporter for lactose was found in S. thermophilus

that was absent from other pathogenic streptococci.

Table 2

Carbohydrate utilization profiles and predicted transporters for lactobacilli with complete genomes (from [25])

Type Sugar Fermentation

Laca Lplb Ljoc Lgad

Pentoses Arabinose Yese

Ribose Yes

Ribulose

Xylose

Xylulose

Hexoses Fructose PTSf PTS PTS PTS

Galactose GPHg Yes Yes Yes

Glucose PTS Yes Yes Yes

Mannose PTS PTS PTS PTS

Disaccharides Cellobiose PTS PTS PTS

Gentiobiose PTS PTS Yes

Lactose GPH Yes PTS PTS

Maltose ABCh Yes ABC ABC

Melibiose PTS Yes Yes

Sucrose PTS PTS Yes

Trehalose PTS Yes Yes Yes

Turanose Yes

Oligosaccharides FOS ABC Yes

Melezitose Yes

Raffinose ABC Yes PTS

Sugar alcohols Galactitol PTS

Glycerol

Mannitol PTS

Sorbitol PTS

Deoxysugars Fucose

Rhamnose Yes

Modified Sugars Amygdalin Yes PTS Yes Yes

Arbutin PTS PTS Yes

Esculin PTS Yes Yes

Gluconate PTS

Malate

N-acetylglucosamine PTS PTS PTS PTS

Salicin PTS PTS Yes Yes

a Lactobacillus acidophilus.b Lactobacillus plantarum.c Lactobacillus johnsonii.d Lactobacillus gasseri.e Determined by fermentation patterns obtained from API50CHO (BioMerieux, Durham, NC).f PTS, phosphoenolpyruvate phosphortransferase system transporter.g GPH, galactoside pentose hexuronide permease.h ABC, ATP-binding cassette transporter.

T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409 397

It was suggested that evolution of S. thermophilus to

milk resulted in genome degradation of many genes

(including any pathogenic genes) that were despensible

as this organism evolved to this specialized environ-

ment [17]. Interestingly, evidence was also presented

for horizontal gene transfer between S. thermophilus

and other organisms co-occupying the dairy environ-

ment. A 17 kb region was identified that containedmultiple copies of IS1191 and a mosaic of fragments

with over 90% identity to L. bulgaricus and L. lactis.

Among them was a unique copy of metC that allows

methionine biosynthesis, which is a rare amino acid

in milk.

For L. lactis, considerable evidence has demonstrated

that members of this species have aquired plasmid DNA

elements encoding critical functions for growth and

competition in a milk environment, such as lactose

metabolism, proteolytic activity, bacteriocin production,

exopolysaccharide production and resistance to bacte-

riophages [29]. In addition, it is also apparent that hor-

izontal gene transfer has introduced important functionsto the genomes of a number of LAB that are expected to

promote their competition in these environments. Genes

encoding sugar transporters and carbohydrate hydro-

lases can represent a large portion of strain-specific

genes that have been acquired by horizontal gene trans-

MELIBIOSE

MELIBIOSE-6P

GLUCOSE

GLUCOSE-6P

EC2.7.1.2 La1433

AMYGDALIN

SALICIN

ARBUTIN

N-ACETYL-GLUCOSAMINE

MANNOSE

MANNOSE-6P

MALTOSE

MALTOSE

CELLOBIOSE

CELLOBIOSE-6P

GENTIOBIOSE

GENTIOBIOSE-6P

AMYGDALIN-6P

SALICIN-6P

ARBUTIN-6P

N-ACETYLGLUCOSAMINE-6P

SUCROSE

SUCROSE-6P

FRUCTOSE

FRUCTOSE-1P

TREHALOSE

TREHALOSE-6P

GLUCOSE

FRUCTOSE

FRUCTOSE-6P GLUCOSE-6P GLUCOSE-6P GLUCOSE-6P GALACTOSE-6P GLUCOSE-6P FRUCTOSE1,6P2

GLUCOSE GLUCOSE GLUCOSE GLUCOSE FRUCTOSE

GLUCOSE-6PPRUNASIN

GLUCOSE-6P

GLUCOSE-6P

GLUCOSAMINE-6P

GLUCOSE-6P

GLUCOSE-6PGLUCOSE

FOS

RAFFINOSE

FOS

RAFFINOSE

FRUCTOSE

GALACTOSESUCROSE

GLUCOSEFRUCTOSE

3.2.1.22 La1438

2.4.1.7 La1437

3.2.1.26 La505

3.2.1.93 La10142.7.1.56 La1778

3.2.1.86 La874

3.5.1.25 La144

3.2.1.21 La1366 3.2.1.21 La1365 2.4.1.8 La1870 5.4.2.6 La1869

5.3.1.8 La745

3.2.1.117

GLUCOSE

EC 3.2.1.118

3.2.1.86 La885

2.6.1.16 La462

3.2.1.86 La1706

LACTOSE

GALACTOSEUDP-GLUCOSE

UDP-GALACTOSE GALACTOSE-1P

LACTOSE 3.2.1.23 La1467

GLUCOSEGALACTOSE

GALACTOSE2.7.1.6 La1459

GLUCOSE-1P

GLUCOSE-6P

GLUCOSE-6P

2.7.7.10La1458

5.1.3.2 La1469

2.7.7.9 La1719

5.4.2.2 La687

3.2.1.26 La400

2.7.1.4 La16

La889

FRUCTOSE-6P

FRUCTOSE-1,6P2

GLYCERALDEHYDE-3P

GLYCERALDEHYDE-1,3P2

GLYCERATE-3P

GLYCERATE-2P

PHOSPHOENOLPYRUVATE

PYRUVATE

La956

La185

La271 L-LDHLa55 D-LDH

La752

La1599

La698

La699

La957

2.7.1.11

4.1.2.13

1.2.1.12

2.7.2.3

5.4.2.1

4.2.1.11

2.7.1.40

1.1.1.27

5.3.1.9

SUBSTRATE SUBSTRATE-P

IIC IIB IIA

LACTATE

Fig. 2. Transporters and pathways predicted for carbohydrate utilization by Lactobacillus acidophilus. The diagram shows transporters, hydrolases

and glycolysis enzymes, as predicted by the putative genome annotation. Gene and enzyme numbers are indicated for each enzymatic reaction. For

transporters, red indicates a putative PTS transporter; green, a putative ABC transporter; and yellow, a galactoside permease. For sugars, identical

compounds share the same color (from [21] with permission).

398 T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409

fer. It has been suggested previously that selected genes

involved in sugar transport, catabolic properties, and

exopolysaccharide synthesis in L. plantarum [19] have

been acquired via horizontal gene transfer, as part of

the adaptation process of this organism to a diverse

number of environments (e.g., plants, cereals, GI tract).

Evidence supporting horizontal gene transfer for these

regions include their grouped position near the originof replication, lowered GC content (41.5% versus

44.5%; Fig. 5), and high variability as to the presence

or absense of these genes among different strains of L.

plantarum [19,23]. The accumulating evidence suggests

that evolution of the LAB to nutritionally complex envi-

ronments has been driven by two major processes; first,

gene degradation and loss of dispensible functions from

ancestral types [17], and second, gene acquisition viahorizontal gene transfer and duplication of important

capabilities [17,19–21, D.A. Mills, K. Makarova, and

E. Koonin, and LABGC, unpublished data].

In addition, there are numerous examples of gene

duplications and multiple copies of related genes pre-

dicted to direct important functions in the genomes of

the sequenced LABs. Examples include PTS transport-

ers, b- and phospho-b galactosidases, lactic dehydrogen-ases, peptidases, and oligopeptide and amino acid

transporters [19–21]. Also notable are the multiple cop-

ies of homologs for mucus-binding (Mub) proteins

found in L. gasseri (7), L. acidophilus (5), L. johnsonii

(4), and L. plantarum (4). First discovered in L. reuteri,

Tuomola et al. [30] reported a 358-kDa surface protein

able to bind to mucin glycoproteins. The predicted

Mub proteins, now revealed in the genomes of many

intestinal lactobacilli, are unusually large proteins rang-

ing in size from 1000 to 4300 amino acids and often rep-resent the largest open reading frames (ORFs) in the

genome. While similar in their large size and the pres-

ence of multiple repeats (4–6) of �20 aa sequences

[20], their amino acid identity is relatively low at 24–

38%, indicating considerable sequence variability within

surface proteins presumed to serve important and simi-

lar roles in mucus binding. In this regard, Altermann

et al. [21] found that 6.6% of unclassified COGs (clustersof orthologous groups) in the L. acidophilus genome

were represented in five distinct regions (Fig. 3, COG re-

gions I, II, III, IV, V). All the genes within these regions

were predicted to be involved with host recognition or

epithelial adherence; including mucus binding, fibronectin

binding, and other cell surface associated type proteins.

A region was identified in L. johnsonii that contained a

mub gene within a predicted nine-gene operon that in-cluded a large serine rich protein with homology to a

Streptococcus fimbrial adhesin. This unique region in

Fig. 3. Genome atlas of L. acidophilus NCFM. The atlas represents a circular view of the complete genome sequence of L. acidophilus NCFM. The

right-hand legend describes the single circles in the top-down-outermost-innermost direction. The circle was created using Genewiz [73] and in house

developed softwares [21]. Circle 1, Intermost, GC-Skew. Circle 2, COG classification. Predicted ORFs were analyzed using the COG database and

grouped into the four major categories. 1, Information storage and processing; 2, Cellular processes and signaling; 3, Metabolism; 4, Poorly

characterized; and 5, ORFs with uncharacterized COGs or no COG assignment. Circle 3, ORF orientation. ORFs in sense orientation (ORF+) are

shown in blue; ORFs oriented in anti-sense direction (ORF�) in red. Circle 4, Blast similarities. Deduced amino-acid sequences compared against the

non-redundant (nr) database using gapped BlastP. Regions in blue represent unique proteins in NCFM, whereas highly conserved features are shown

in red. The degree of color saturation corresponds to the level of similarity. Circle 5, G + C content deviation. Deviations from the average GC-

content are shown in either green (low GC spike) or orange (high GC spike). A boxfilter was applied to visualize contiguous regions of low or high

deviations. Circle 6, Ribosomal machinery. tRNAs, rRNAs and ribosomal proteins are shown as green, cyan, or red lines, respectively. Clusters of

thereof are represented as colored boxes to maintain readability. Circle 7, Mobile elements. Predicted transposases are shown as light purple, phage-

related Integrases as orange dots. Circle 8, Stress response. Genes involved in general stress response, including chaperones, and genes involved in

heat shock, DNA repair, and pH regulation, are shown in dark purple. Circle 9, Peptide and amino acid utilization. Proteases and peptidases are

shown in green, non-sugar-related transporters in light blue dots. Circle 10, Outermost Two-component regulators (2CRS). Each 2CRS is represented

as brown dots, consisting of a response-regulator and a histidine-kinase. In circles 7–10 each full dot represents one predicted ORF and clusters of

ORFs are represented by stacked dots. Selected features representing single ORFs and ORF cluster are shown outside of circle 10 with bars

indicating their absolute size. Origin and terminus of DNA replication are identified in green and red, respectively. Other features are: SlpA and B (S-

layer proteins), CdpA (Cell division protein), sugar utilization (Sucrose, FOS, Trehalose, Raffinose), LacE (PTS-sugar transporter), BshA and B (Bile

salt hydrolases), Mub-909 to Mub-1709 (mucus-binding proteins, numbers correspond to the La-number scheme), FbpA (fibronectin-binding

protein), Cfa (Cyclopropane fatty acid synthase), Fibronectin_binding (fibronectin-binding protein cluster), EPS_cluster (Exopolysaccharides),

Lactacin_B (bacteriocin), pauLA-I to pauLA-III (potential autonomous units), and prLA-I and prLA-II (phage remnants).

T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409 399

L. johnsonii [20] was positioned within a common locus

that has now been found in L. acidophilus, L. gasseri,

and L. plantarum (Fig. 4; E. Altermann and T.R. Klaen-

hammer, unpublished data).

3. Comparative genomics of lactobacilli

In spite of the explosion of genomic information on

microorganisms, complete genomes of beneficial com-

mensals, symbionts, and probionts are just now becom-

ing available [31]. Comparison of the similarities and

differences within these groups is expected to provide

an important view of gene content, organization, and

regulation that contributes to both gut and probioticfunctionality [22,31]. A recent comparative analysis be-

tween the complete genomes of L. plantarum and L.

johnsonii revealed striking differences in gene content

and synteny in the genome, prompting a conclusion that

these two species are only marginally more related to

Fig. 4. Map (not drawn to scale) of surrounding genes of the possible L. johnsonii fimbriae operon LJ0388 to LJ0394 (middle panel, from [20]) and its

comparison to the syntenic regions in L. gasseri (upper panel) and L. acidophilus (lower panel). Predicted open reading frames (ORFs) are shown as

arrows, the black line represents the genome. ORFs are grouped into colored clusters, according to their location, their functionality, or their degree

of homology. Homologous genes are connected by light colored parallelograms between the genome lines. Genes with no syntenic homology are

shown in grey. Gene clusters in different shades of green represent putative insertion events in L. johnsonii and L. acidophilus. The dark green cluster

(L. johnsonii) represents an ABC transporter and a putative sugar phosphatase. The mobile element (tranposase) adjacent to this insertion is shown in

orange (L. johnsonii and L. gasseri). The light green cluster (L. johnsonii) shows the possible fimbriae operon and the green cluster in L. acidophilus

indicates the potential autonomous unit pauLA-II [21], harboring a potential DNA modification system (methylase) and other phage-related

proteins.

Fig. 5. Circular plot of genome diversity found in 20 L. plantarum

strains isolated from different environments, using the method of

DNA–DNA hybridization to L. plantarum WCFS1 microarrays (D.

Molenaar, R.J. Siezen, M. Kleerebezem, unpublished). From outside

to inside: ring 1, base deviation index (BDI), from low (red) via

intermediate (yellow) to high (green); ring 2, DNA variability, from

low (present in all 20 strains) to high (absent in 1–19 strains compared

to WCFS1); ring 3, gene clusters for plantaricin biosynthesis, non-

ribosomal peptide biosynthesis (NRPS), prophages, polysaccharide

biosynthesis, nitrate respiration and sugar metabolism; ring 4, GC%.

This picture was generated with the Microbial Genome Viewer

(www.cmbi.kun.nl/MGV) (from [23], reprinted with permission).

400 T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409

each other than to other Gram-positive bacteria [28].

Nevertheless, 70% of the proteins in L. johnsonii still

had homologs (defined by a Blast score of <1E � 10)

in the larger L. plantarum genome. Unique proteins

found in these two genomes, when compared against

the published and draft genomes of the LAB, were pri-

marily unknown proteins and prophage-related ORFs

[28]. While whole genome comparisons with draft and

incomplete genomes for LAB-specific genes are useful,

some inaccuracies should be expected because gaps inthe draft sequences are likely to contain important

information.

Complete genomes are now published or available for

four Lactobacillus species (acidophilus, gasseri, johnsonii

and plantarum). Whole genome comparison over these

species (Fig. 6) substantiates the lack of synteny among

L. plantarum and the other three lactobacilli. In con-

trast, L. johnsonii and L. acidophilus show extensive con-servation of gene content and order over the length of

the genome. L. gasseri and L. johnsonii are even more

strikingly similar across the length of the genome, except

for two apparent chromosomal inversion events in L.

gasseri resulting in a reversal of gene order when com-

pared to the other two closely related species. A compar-

ison of ORFs between L. gasseri and L. johnsonii

revealed that 83–85% of the proteins had homologs inboth genomes [28]. Overall, the comparisons demon-

strate a high degree of gene synteny in the three species

that have been collectively referred to as members of the

L. acidophilus complex. Differentiation of these three

species, particularly L. gasseri and L. johnsonii, has been

historically difficult using traditional or molecular taxo-

nomic tools [27,32].

In an effort to distinguish between L. gasseri and L.

johnsonii strains, the translated genomic sequences of

three Lactobacillus strains were compared to find genes

unique to L. gasseri ATCC 33323, which do not occur

in L. acidophilus NCFM or L. johnsonii NCC533. Four-

teen unique genes were found in L. gasseri, which were

also not found in the NCBI non-redundant database.

Using specific primers designed for each of these unique

ORFs, L. gasseri specific amplicons could be generatedfrom all the L. gasseri strains evaluated (Table 3). Nota-

bly, primer pairs 4 and 11 appeared unique to the L. gas-

Fig. 6. Multiple whole genome comparison on protein level. The finished and annotated genomes of L. gasseri (top line), L. johnsonii (second line), L.

acidophilus NCFM (third line), and L. plantarum (bottom line) were analyzed using a bidirectional BlastP algorithm. Deduced amino acid sequences

from predicted open reading frames (ORFs) were compared to the respective partner-ORFeome using the standalone Blast provided by NCBI.

Translating these results into a compatible format, visualization of the comparison was realized using the Artemis Comparison Tool (ACT, Sanger

Center). Basepair positions are indicated for each genome in the white centerline. ORFs are shown above and below this line, indicating their length

and orientation on the respective genome. Degrees of similarity and positional relationships are indicated by the red and blue bars. Red bars show the

same chromosomal orientation, blue bars indicate opposite ones. The level of similarity is shown by color shading. The higher the similarity, the more

intense the color of the bars. The overall cutoff-value was 1e � 70. Only BlastP hits with a more significant e-value are displayed.

T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409 401

seri species. Although too few L. johnsonii strains were

analyzed to support a definitive conclusion, this genome

comparison suggests that species-specific genes are pres-

ent and the two species can be differentiated (E. Alter-mann, E. Durmaz and T. Klaenhammer, unpublished).

Conserved genes found between closely related spe-

cies can also provide important clues to function and

importance. Whole genome comparison between L. aci-

dophilus, L. gasseri and L. johnsonii revealed a highly

conserved region harboring a cluster of genes predicted

to encode a cell surface exopolysaccharide (EPS) (Fig.

7). The cluster of genes was oriented similarly in L. aci-

dophilus and L. johnsonii, and inverted in the L. gasseri

genome as a result of the chromosomal rearrangement.

Transcriptional analysis revealed that the eps genes were

expressed by L. acidophilus during log phase growth on

most of the eight carbohydrates examined [25]. Also

apparent was a large region of inverted synteny between

L. gasseri and L. johnsonii, at its downstream end (not

shown). No gene synteny was found outside this low-GC region in L. acidophilus. Detailed in silico analyses

revealed that for all three genomes, the low GC-content

region harbors the EPS cluster. The variable EPS cores

are embedded between the conserved regions and bear

little or no similarities between each other. Each EPS

cluster is bordered downstream by a transposase gene,

followed by a low-GC spike (not shown). It is significantthat this closely related group of intestinal lactobacilli

have conserved this cluster and potentially the ability

to produce an EPS layer.

4. Functional genomic analysis

Whole genome sequencing, genome data mining, andcomparative genomics provide insights into genetic con-

tent, differences and similarities, and offer important

clues into possible gene functions, both essential and un-

ique. Thus far, genomic analyses of LAB have revealed a

number of interesting features that are generally consid-

ered to be important to the roles of these organisms in

bioprocessing or health. Among those considered poten-

tially important to probiotic functions in the LAB are:adherence/attachment factors such as fimbrae [18,20],

mucus-binding proteins [20,21], fibronectin-binding pro-

teins [21], EPS clusters [19–21], and mannose-specific

Table 3

PCR amplicons generated in Lactobacillus species using L. gasseri-specific primers

Lactobacillus species Primer set/strain 1 2 3 4 5 6 7 8 9 10 11 12 13 14

gasseri 11089 * * * * *

ATCC19992 (ADH)a * * * * * ** *

FR2 * * * * * * *

JG141 * * * * * *

AM1 * * * * *

SD10 * * * * * *

WD19 * * * * * *

SK12 * * * ** *

RF81 * * * * *

RF14 * * * * *

ML3 * * * *

ML1a * * * * * * * * * *

ATCC33323 * * * * * * * * * * * * * *

johnsonii ATCC33200 *

12600 * * *

ATCC11506

acidophilus NCFM

ATCC4356

Primer set 4:

4 28 5 0-AGCTGAGTATTATCAATCATTAATCCCT-3 0

4 28 5 0-AATAATGAACAAGAATACATTGTTGGAA-3 0

Primer set 11:

11 28 5 0-TTAAATTTGTTAAAGCCAGACTTACTGA-3 0

11 28 5 0-AATTATGCTGTCTAAATTCTTTTCTTCC-3 0

a Designates strains that could not be distinguished by 16S rRNA sequencing and were thus initially classified as ‘‘L. gasseri/L. johnsonii’’.* Indicates a reproducible PCR product.

** The PCR product was 1.2 kb, all other products from this primer pair were 0.3 kb.

Fig. 7. Organization of the exopolysaccharide (EPS) gene cluster conserved between L. gasseri, L. johnsonii, and L. acidophilus. The complete

genomes of L. gasseri, L. johnsonii, and L. acidophilus were subjected to bidirectional BlastP analysis and results were visualized using ACT. Cut-off

e-values for displayed degrees of similarity were 1e � 10. Also shown in the right panel are the expression profiles of the EPS gene cluster (vertical)

during growth under eight different carbohydrates (horizontal). Low expression, green; high expression, red [25].

402 T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409

T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409 403

adhesion proteins [33]; prophage-encoded proteins sus-

pected of imparting probiotic properties via lysogenic

conversion [34,35]; bacteriocins [36,19–21]; two compo-

nent regulatory systems and signaling pathways

[21,26,37]; stress and acid tolerance factors [38,19–21];

and bile salt hydrolases [39,20]. As the list of genomicfeatures in LAB expands, the need to characterize or

confirm genes important in bioprocessing and health

will increase exponentially. Within this list are also

groups of unknown or unclassified proteins (�25–40%

of the ORFs defined), many of which are highly or dif-

ferentially expressed [25] and are also likely to contrib-

ute important functions or features to LAB.

One powerful strategy to identify potentially signifi-cant genes impacting probiotic functionality is the ‘‘in

vivo expression technology’’ (IVET) that has been em-

ployed in both L. reuteri [40] and L. plantarum [41].

The approach allows the identification of promoter ele-

ments that are expressed during in vivo transit of probi-

otic cultures, and secondarily reveals the corresponding

genes driven by these promoters. A total of 75 inducible

genes have thus far been identified by these strategiesand included groups encoding nutrient acquisition,

intermediate or cofactor biosynthesis, and stress re-

sponses [31]. Two of these same genes were again recov-

ered in screening an alr-complementation library in L.

plantarum for bile-inducible promoter elements [42].

The bile responsive elements identified in both studies

[41,42] were linked to genes encoding an integral mem-

brane protein and an argininosuccinate synthase. Bothgenes were subsequently shown to be induced, in situ,

using a reverse transcriptase-PCR of RNA isolated from

the intestine of mice fed L. plantarum WCFS1. In addi-

tion, four extracellular proteins were induced in L. plan-

tarum which were considered candidates for interaction

with host tissues [42]. Among the genes induced, a sub-

stantial number were shared by both L. plantarum and

various pathogenic bacteria, prompting de Vos et al.[31] to speculate that common gene categories identified

by the IVET strategies were obviously important in sur-

vival of L. plantarum in the host GI-tract environment,

rather than virulence.

Functional genomic analysis to identify or confirm

gene function is vital to our understanding of cellular

physiology, metabolic pathways, sensing, signaling,

and elucidating mechanisms that underly probiotic func-tions. Instrumental in this process are genetic and

molecular tools that can be used for gene cloning,

expression, complementation and inactivation. It was

20 years ago when Kok et al. [43] constructed one of

the first cloning and shuttle vectors for LAB, based on

the lactococcal replicon pWV01. Genetic accessibility

via electroporation was first reported in 1987 by Chassy

and Flickinger [44] and then widely expanded to variousGram-positive bacteria in 1988 [45]. Since then a pleth-

oria of vectors, expression systems, and integration vec-

tors have been constructed and used for genetic

characterization of most LAB. In terms of functional

genomics, notable among these have been the tempera-

ture-sensitive integration vectors pGhost [46], pSA3

[47], and the two plasmid-pORI28 system [48,49]. While

effective in lactococci and some lactobacilli [50], theiruse in some thermophilic-probiotic lactobacilli was ham-

pered because the vectors were genetically unstable at

optimal growth temperatures (e.g., 37–40 �C). The

pORI28 system was expanded for use in thermophilic

lactobacilli by using the pGK12-derivative, pTRK699

as the helper plasmid [51]. This helper plasmid was rela-

tively stable at optimum growth/transformation temper-

atures from 37 to 40 �C, but could be readilydestabilized at 42 �C in species of the L. acidophilus com-

plex. This pORI28-pTRK669 system has been markedly

effective in targeting integration events and creating gene

replacements in a variety of probiotic lactobacilli. An

alternative integration system, avoiding potential repli-

cation problems, was introduced in 1997 by van Kran-

enburg et al. [52]. Based on the well-described

plasmids pUC18 and pUC19 [53], derivatives harboringdesired antibiotic resistance cassettes and regions of

chromosomal homologies, were constructed in the repli-

cative host Escherichia coli. Subsequent transformation

into non-replicative target hosts of lactococci [52] and

lactobacilli [54] forced crossover events within the re-

gions of homology. Double-crossover events occurring

under non-selective growth conditions, functionally

inactivating selected target genes. As a result, a numberof gene regions suspected to encode probiotic features

have been characterized and functionally linked to

important phenotypes.

At this point, few predicted gene functions have been

confirmed by a functional genomic analysis. Table 4 lists

those genes to date that have been functionally analyzed

or modified by targeted insertional mutagenesis in pro-

biotic lactobacilli. First among these was the ldhD genein L. johnsonii [55]. Upon gene replacement of ldhD with

a deleted version, the derivative produced exclusively

L-LDH. This form is considered safer, albeit arguably

[60], for use in infant probiotic applications. This was

the first example of directed genetic engineering de-

signed for an improvement of a health target in a probi-

otic culture. More recently, genes implicated in an acid

tolerance response of L. acidophilus were investigatedby a functional genomic approach. Azcarate-Peril

et al. [38] identified four gene loci putatively involved

in acid resistance by gene sequence similarity. Inser-

tional mutagenesis in these regions (see Table 4) created

acid sensitive derivatives confirming their participation

in the acid tolerance of L. acidophilus. Notably, how-

ever, treatment of these mutants at pH 5.5 for 1 h at

37 �C, prior to challenge at pH 3.5, resulted in totalrecovery of acid tolerance to pH conditions that were

previously lethal. Therefore, the organism is capable of

Table 4

Gene and gene regions functionally analyzed from probiotic lactobacilli

Organism Gene Predicted function Mutant phenotype

Metabolism

L. johnsonii D-ldh Lactate dehydrogenase D-Lactate deficient [55]

L. gasseri gusA Beta-glucuronidase Gus-negative [56]

L. acidophilus lacL Beta-galactosidase Lactose-negative [51]

msmE ABC-transporter FOS-deficient [57]

brfA Beta-fructosidase FOS-negative [57]

treB PTS-transporter Trehalose-negative, cryosensitive Duong et al. (unpublished)

treC Trehalase Trehalose-negative, cryosensitive Doung et al. (unpublished)

Surface

L. acidophilus cdpA S-layer/proteinase Cell division deficient, filamentous cells [58]

slpA S-layer Sodium chloride sensitive, ethanol sensitive,

bile resistant

Altermann et al. (unpublished)

fbp Fibronectin-binding protein Reduced adherence to Caco-2 cells Buck et al. (unpublished)

mub Mucin-binding protein Reduced adherence to Caco-2 cells Buck et al. (unpublished)

LBA1633 R-28 homology/adherence No effect on adherence to Caco-2 cells Buck et al. (unpublished)

LBA1634 R-28 homology/adherence No effect on adherence to Caco-2 cells Buck et al. (unpublished)

L. plantarum lp-0373 Mannose-specific adhesin No effect on agglutination ability [33]

msa Mannose-specific adhesin Loss of agglutination ability [33]

lp-2018 D-Alanylation of techoic acid Loss of polyglycerol phosphate polymers in LT;

altered pro-inflammatory cytokines secreted

by PMBCs,

and protective to IBD in colitis model

[59]

Other

L. acidophilus gadC Amino acid antiporter Acid sensitivity [38]

LBA867 Transcriptional regulator Acid sensitivity [38]

LBA995 Amino acid permease Acid sensitivity [38]

LBA996 Ornithine decarboxylase Acid sensitivity [38]

LBA1796 Bacteriocin ABC transporter Loss of lactacin B production Dobson et al. (unpublished)

LBA1272 Cyclopropane FA synthase Loss of membrane dihydrosterculic acid,

acid sensitivity

Courtney et al. (unpublished)

LBA1524HK Histidine kinase of 2CRS Acid sensitivity, ethanol sensitivity,

reduced growth in milk

[26]

bsh A Bile salt hydrolase Inability to hydrolyze bile salts conjugated

to chenodeoxycholic acid

[39]

bsh B Bile salt hydrolase Inability to hydrolyze biles salts conjugated

to taurine

[39]

LBA1430HK Histidine kinase, 2CRS Bile sensitivity Pfeiler et al. (unpublished)

404 T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409

orchestrating an acid tolerance response that appears

capable of overcoming any single mechanism that may

participate in acid resistance [38]. In addition, one

two-component regulatory system (2CRS), a primary

mechanism involved in environmental sensing and sig-

nal transduction, was also identified and insertionally

inactivated in L. acidophilus [26]. This mutant exhibited

lower resistance to acid and ethanol in log phase cells,and poor growth in milk. A whole-genome microarray

revealed that the expression of approximately 80 genes

was affected by the 2CRS mutation; including two oligo-

peptide-transport systems present in the L. acidophilus

genome, other components of the proteolytic enzyme

system, and a LuxS homolog suspected of participating

in synthesis of the AI-2 signaling molecule.

Nearly 30 genes (Table 4) have thus far been inacti-vated to reveal important phenotypic changes in proper-

ties suspected to be important to the functionality of

probiotic lactobacilli. Among them are genetic loci

linked to bile salt hydrolase activity [61,39], and various

potential adhesions (mucus-binding proteins, fibronec-

tin-binding protein) that contribute to the adherence

ability to intestinal epithelial cells (Caco-2) in vitro cells

(B.L. Buck, E. Altermann, and T.R. Klaenhammer,

unpublished data), and mannose-specific receptors, dis-played on the surface of yeast cells [33]. In the later case,

the mannose specific adhesion (msa) exhibited a number

of characteristic adhesion domains including a spacer re-

gion, a Mub protein-type domain, and a LPxTG cell

wall binding motif. Various studies have implicated

the roles of S-layer proteins and mucus-binding proteins

in adherence of probiotic lactobacilli to intestinal tissues

and mucin directly [62,63]. However, the recent compar-ative studies using parental and isogenic mutants are the

T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409 405

first to seek clear evidence of the specific contributions

of these cell surface proteins to adherence mechanisms,

within the context of the whole bacterium.

In a recent study by B.L. Buck, E.A. Altermann and

T.R. Klaenhammer (unpublished), mutants of L. aci-

dophilus were constructed by targeted inactivation ofgenes suspected to encode surface proteins potentially

mediating adherence to mucus or the intestinal epithe-

lium. Analysis of the adhesive properties of these mu-

tants to intestinal Caco-2 epithelial cells, in vitro,

revealed that two streptococcal R28 homolog mutants,

LBA1633 and LBA1634, did not show reproducible de-

creases in adhesion. SlpA�, a surface-layer mutant,

showed the highest decrease in adhesion while fibronec-tin-binding protein (FbpA) and mucus-binding protein

(Mub) mutants showed significant decreases in adhesion

compared to the control (Fig. 8). Interestingly, it was

also observed that treatment of the bacterial cells under

a specific set of environmental conditions could result in

an explosive increase of adherence ability, for both the

parent and the five individual gene knockout mutants

(Fig. 8, inset panels; B.L. Buck and T.R. Klaenhammer,unpublished observations). Therefore, additional factors

are involved, inducible in both the parent and adher-

ence-deficient mutants that can significantly elevate the

capacity of L. acidophilus to adhere in this model sys-

Fig. 8. Relative adhesion of L. acidophilus NCFM mutant strains to Caco-

monolayers in 17 microscopic fields. Each experiment was done in duplicate

tested: W+, L. acidophilus containing a plasmid integration in the b-galactosida fibronectin-binding protein; SlpA-, integration in gene encoding a surface la

protein; and 1633� and 1634�, integration into individual tandem genes h

pyogenes [64]. Inset photos show Gram stained L. acidophilus NCFM adherin

adherence ability (B.L. Buck and T.R. Klaenhammer, unpublished).

tem. These genetic regions and their potential adhesion

and signaling factors are currently being identified by

microarray analysis and investigated by functional

genomic approaches.

Of significant interest is the recent report of Grang-

ette et al. [59], showing that the presence or absence ofteichoic acids on the cell surface of L. plantarum can af-

fect the cytokine expression pattern by peripheral blood

mononuclear cells (PBMCs) and monocytes. The dlt op-

eron, responsible for D-alanylation of teichoic acids, was

disrupted to lead to a substantial reduction in the con-

centration of polyglycerol phosphate polymers (with

D-Ala) in the techoic acids of the bacterial cell wall.

Notably, this change in the chemical composition corre-lated with a reduced secretion of pro-inflamatory cyto-

kines produced by PBMCs, and increased secretion of

the anti-inflammatory cytokine IL-10, when exposed

to the Dlt-mutant. Use of the Dlt-mutant in a murine

colitis model was also found to be protective against

TNBS-induced colitis. This result provides further evi-

dence that LAB communicate with PBMCs and, for

the first time, provides evidence that LAB may induceproinflamatory or anti-inflammatory reponses based

on their cell wall composition in teichoic acids [59],

and perhaps in the display of cell surface bound proteins

or polysaccharides, as well. In this regard, a number of

2 monolayers. Adhesion is expressed as total cells adhering to Caco-2

and replicated at least three times. The following mutant strains were

ase gene used as parental control; FbpA-, integration in gene encoding

yer protein; Mub-, an integration in the gene encoding a mucus-binding

omologous to a gene encoding an epithelial cell-binding protein in S.

g to Caco-2 cells before (A) and after (B) cell treatment that promotes

406 T.R. Klaenhammer et al. / FEMS Microbiology Reviews 29 (2005) 393–409

reports have already shown that different strains and

species of lactobacilli, and other commensal bacteria,

can modulate cytokine expression by both human and

murine antigen presenting (dendritic) cells [65–68].

Overall the results suggest that variations in bacterial

strains and species can direct immunological responsestoward pro- or anti-inflammatory responses. Based on

the results of Grangette et al. [59], the direction of these

responses could reflect the chemical composition and

architecture of the Gram-positive cell wall. Considering

the field�s current position, having a number of complete

probiotic genomes (L. acidophilus, L. gasseri, L. johnso-

nii, and L. plantarum) and the capability to carry out

functional genomic analyses on these organisms, thecourse to understanding the interactions of signaling

molecules with immune cells will be both challenging

and exciting in the years ahead.

5. Concluding remarks

Today�s exciting discoveries based on gene contentand predicted function follow closely behind the explo-

sion of DNA sequence information on microbial gen-

omes. Genomic and comparative genomic analyses are

revealing key gene regions in LAB worthy of continued

investigation for their potential roles in both bioprocess-

ing and health.Microarray analysis of LAB cultures, and

various mutant derivatives thereof, promises to reveal

genetic networks that orchestrate complex microbial re-sponses to a variety of conditions that are critical to

growth, metabolic activity, survival, communication,

signaling, and probiotic functionality. Across the LAB,

genome sequences have already provided information

on genetic content that establishes platforms for meta-

bolic [69] and nutrient engineering [70], understanding

mechanisms of probiotic action [38,59,71], and providing

platforms to engineer LAB for delivery of biotherapeu-tics [72]. The future, armed with genome information

and genetic tools, is an exciting one. It is the first time

in the history of this field that the promising potential

of these beneficial organisms can be mechanistically

investigated, understood, and inevitably expanded for

the benefit of humankind.

Acknowledgments

The substantial contributions of many individuals

participating in this work in our laboratory and as col-

laborators are gratefully acknowledged. Support for

the LAB genetics and Functional Genomics programs

has been provided through the North Carolina Agricul-

tural Research Service, the North Carolina Dairy Foun-dation, Danisco, Inc., Dairy Management, Inc., the

Southeast Dairy Foods Research Center, the California

Dairy Research Foundation, the NIH Biotechnology

Program, GAANN Fellowships in Biotechnology,

IGERT Genomics Fellowships, and the USDA Na-

tional Research Initiative Competitive Grants Program.

Our special gratitude is expressed to Evelyn Durmaz,

Rosemary Sanozky-Dawes, and Edwina Kleeman formany years of laboratory management and excellent re-

search, to the US Department of Energy Joint Genome

Institute for draft sequencing, the members of the U.S.

Lactic Acid Bacteria Genomics Consortium (LABGC)

for genome information and analysis, and to Fidelity

Systems, Inc., for sequencing efforts to close and com-

plete selected genomes used in these analyses. Thanks

are also extended to A. Mercenier, W. de Vos, T. Shi-noda, M. Saier, D.A. Mills, K. Makarova, and E. Koo-

nin for providing data and/or preprints prior to

publication.

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