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Influence of Wastewater Treatment Plants in Antibiotic-resistant Enterococcus with focus on Vancomycin
Resistance
Miguel Ângelo Alves Oliveira
Thesis to obtain the Master of Science Degree in
Microbiology
Supervisors: Doctor Ricardo Jaime Pereira Rosário dos Santos Professor Arsénio do Carmo Sales Mendes Fialho
Examination Committee
Chairperson: Professor Jorge Humberto Gomes Leitão
Supervisor: Doctor Ricardo Jaime Pereira Rosário dos Santos Member of the Committee: Professor Helena Maria Rodrigues Vasconcelos Pinheiro
October 2018
II
Acknowledgements
Está finalmente concluída mais uma etapa da minha vida, a Dissertação de Mestrado. É certo que
não foi um percurso fácil e, como todos os desafios (quero vê-la nessa perspetiva), teve os seus altos
e baixos. Mas esta caminhada não foi feita sozinho. Foi com a companhia dos meus pais, amigos,
familiares, professores e colegas, com quem me cruzei ao longo destes anos, que fui capaz de a findar.
A todos eles, o meu obrigado.
Não quero começar esta lista de agradecimentos sem falar dos meus pais. Para eles, um obrigado
não chega e palavras seriam escassas para agradecer tudo o que fizeram por mim. A eles, por
acreditarem em mim, e me fazerem perceber que a frase “Estuda, que para ti é!” tem muito sentido, o
meu mais sincero e amado obrigado. Aos meus restantes familiares, um obrigado por toda a paciência
e confiança depositada em mim para acabar este trabalho.
Não podia deixar de agradecer aos meus amigos, que tanto me ouviram reclamar ao longo deste
ano (e de toda a vida, vamos ser sinceros!).
É claro que este trabalho não podia ser feito sem o contributo do meu orientador, Doutor Ricardo
Santos. Agradeço-lhe por me ter aceite no seu laboratório, por me ter orientado nas indecisões deste
percurso, e por me ter providenciado todas as ferramentas ao seu alcance para que este trabalho fosse
concluído. A todo o pessoal do Laboratório de Análises do Técnico (LAIST), em especial à Filipa
Macieira, um gigante obrigado por toda a ajuda e conselhos neste percurso. Agradeço também ao
Professor Arsénio Fialho por ter aceitado o convite de ser meu coorientador.
É provável que me esqueça de alguém. Quem me conhece, sabe que pode acontecer. Por isso, se
não estás aqui mencionado, mas sabes que és ou foste importante para mim ao longo deste desafio
este parágrafo é para ti. Obrigado!
III
Abstract
The presence of antibiotic-resistant bacteria in the environment is a substantial public health concern.
Usually, this topic is focused on clinical isolates and not so often in bacteria present in aquatic systems.
The treatments applied in wastewater treatment plants (WWTPs) are not effective in the removal of
antibiotic-resistant bacteria and antibiotic resistance genes, being possible to find them on final effluents,
for example. In this work were collected samples from different treatments applied in 3 WWTPs, in
Portugal. Culture-based techniques to detect and isolate faecal Enterococcus were performed. The
identification of E. faecium and E. faecalis was done using specific primers for each one of them through
conventional polymerase chain reaction (PCR). Antibiotic resistance profiles of isolates were evaluated
through the disk diffusion test, in accordance with the recommendations of the Clinical and Laboratory
Standards Institute (CLSI) guidelines. Detection of specific resistance genes (vanA and vanB) was also
accomplished. According to the results, E. faecium was the most common isolate identified, as usually
reported. It was not confirmed any selection by the treatments of a specific species. In the overall
analysis was confirmed the positive selection of tetracycline resistance phenotype. Additionally, it was
demonstrated that more than half of the isolates with vancomycin resistance were associated with E.
faecalis species (p-value < 0.001). It was also possible to verify that the treatments positively select
multiantibiotic-resistant bacteria (MAR), being demonstrated an increasing trend throughout the
treatments (p-value = 0.028). However, this selection was not related to any of the species identified.
Based on the results obtained, a continuous monitorization of aquatic environments is imperative to
perform an adequate risk assessment related to antibiotic resistance.
Key words: antibiotics, antibiotic resistance, Enterococcus faecium, Enterococcus faecalis,
WWTP, multiantibiotic-resistant Enterococcus.
IV
Resumo
A presença de bactérias resistentes a antibióticos no ambiente constitui um grande problema de
saúde pública. Normalmente, este tópico é focado em isolados clínicos e não tão frequentemente, em
bactérias presentes nos sistemas aquáticos. Os tratamentos aplicados nas ETARs parecem não ser
completamente eficazes, sendo possível encontrar nestes sistemas, bactérias resistentes a antibióticos
e genes de resistência (mesmo nos efluentes finais). Neste trabalho foram colhidas amostras em
diferentes fases dos tratamentos de 3 ETARs em Portugal. Foram usados métodos culturais para
deteção e isolamento dos Enterococcus fecais, tendo sendo a identificação de E. faecium e E. faecalis
realizada por polymerase chain reaction (PCR convencional). Os perfis de resistência aos antibióticos
foram avaliados através do teste de difusão em disco, de acordo com as recomendações das diretrizes
CLSI. A deteção de genes de resistência específicos (vanA e vanB) também foi realizada por PCR. E.
faecium foi o isolado mais prevalente neste trabalho, como descrito na literatura. Em nenhuma ETAR
foi confirmada a seleção de uma espécie em particular, ao longo dos tratamentos. Verificou-se na
análise global uma seleção positiva do fenótipo resistente à tetraciclina. Adicionalmente, foi
demonstrado que mais da metade dos isolados com resistência à vancomicina estavam associados à
espécie E. faecalis (p-valor < 0,001). Também foi possível verificar que os tratamentos selecionavam
positivamente bactérias multirresistentes, tendo sido demonstrado um aumento de (multirresistência)
MAR ao longo dos tratamentos (p-valor = 0,028). No entanto, esta seleção não está associada com
nenhuma das espécies identificadas. Com base nos resultados obtidos, é imperativo uma
monitorização contínua dos ambientes aquáticos, com vista a uma adequada avaliação de risco
relacionada à resistência a antibióticos.
Palavras-chave: antibióticos, resistência a antibióticos, Enterococcus faecium, Enterococcus
faecalis, ETAR, Enterococcus multiantibiótico-resistentes.
V
List of Contents
Acknowledgements ................................................................................................................................ II
Abstract ................................................................................................................................................. III
Resumo ................................................................................................................................................ IV
List of Abbreviations ............................................................................................................................ VII
List of Figures ..................................................................................................................................... VIII
List of Tables ......................................................................................................................................... X
1. Introduction ..................................................................................................................................... 1
1.1. Antimicrobial substances ........................................................................................................ 1
1.2. Description of Enterococcus Genus........................................................................................ 2
1.3. Antibiotic Resistance in Enterococcus Genus ........................................................................ 3
1.3.1. General Aspects ............................................................................................................. 3
1.3.2. VanA and VanB Operons ................................................................................................ 7
1.3.3. Epidemiology and Characterization of Vancomycin-Resistant Enterococcus ................. 8
1.4. Antibiotic Resistance in Wastewater Treatment Plants........................................................... 9
1.5. Aims of the Study.................................................................................................................. 12
2. Materials and methods .................................................................................................................. 13
2.1. Sampling Collection .............................................................................................................. 13
2.2. Detection and Isolation of Faecal Enterococci by Conventional Culture Method .................. 13
2.3. DNA Extraction and Enterococcus Genotyping .................................................................... 13
2.4. Antimicrobial Susceptibility Testing....................................................................................... 14
2.5. Detection of vanA and vanB Genes by PCR ........................................................................ 15
2.6. Data Analysis ........................................................................................................................ 16
3. Results and Discussion ................................................................................................................. 17
3.1. Prevalence of Enterococcus Species in the WWTPs............................................................ 17
3.2. Differences in Enterococcus Species Prevalence in the Treatments Applied in WWTPs ..... 19
3.2.1. Background ................................................................................................................... 19
3.2.2. Species Prevalence in the Treatments Applied in WWTP A ......................................... 20
3.2.3. Species Prevalence in the Treatments Applied in WWTP B ......................................... 21
3.2.4. Species Prevalence in the Treatments Applied in WWTP C and Natural Receptors .... 21
VI
3.2.5. Overall Analysis of the Species Prevalence in the Treatments Applied in WWTPs ...... 22
3.3. Prevalence of Antibiotic-resistant Enterococcus in WWTPs ................................................. 23
3.3.1. Background ................................................................................................................... 23
3.3.2. Antibiotic-specific Resistance in the Treatments Applied in WWTP A .......................... 24
3.3.3. Antibiotic-specific Resistance in the Treatments Applied in WWTP B .......................... 26
3.3.4. Antibiotic-specific Resistance in the Treatments Applied in WWTP C and Natural
Receptors ..................................................................................................................................... 27
3.3.5. Overall Analysis of the Antibiotic-specific Resistance in the Treatments Applied in
WWTPs ...................................................................................................................................... 28
3.4. The Resistance of the Species to Vancomycin in the WWTPs ............................................. 30
3.4.1. The Occurrence of Vancomycin-resistance Genes in Raw Water Samples and VRE
Confirmed Isolates by Disk Diffusion Method ................................................................................ 32
3.5. Multiresistance in the Treatments of the WWTPs ................................................................. 33
3.5.1. Background ................................................................................................................... 33
3.5.2. Multiresistance in WWTP A .......................................................................................... 33
3.5.3. Multiresistance in WWTP B .......................................................................................... 34
3.5.4. Multiresistance in WWTP C and Natural Receptors...................................................... 35
3.5.5. Overall Analysis of Multiresistance in WWTPs ............................................................. 36
3.6. Analysis of the Multiresistance in the Treatments and the Species Identified in the WWTPs ...
.............................................................................................................................................. 37
3.6.1. MAR vs Species Identified in WWTP A......................................................................... 37
3.6.2. MAR vs Species Identified in WWTP B......................................................................... 38
3.6.3. MAR vs Species Identified in WWTP C and Natural Receptors .................................... 38
3.6.4. Overall Analysis MAR vs Species Identified in the WWTPs.......................................... 39
4. Conclusion .................................................................................................................................... 41
5. References .................................................................................................................................... 42
Appendix .............................................................................................................................................. 51
VII
List of Abbreviations
AFLP – Amplified Fragment Length Polymorphism
AMP – Ampicillin
AR – Antibiotic resistant
ARB – Antibiotic-resistant Bacteria
ARG – Antibiotic Resistance Genes
BEA – Bile Esculin Azide Agar
C – Chloramphenicol
CDC – Centers for Disease Control and Prevention
CIP – Ciprofloxacin
CLABSIs – Central Line–associated Bloodstream Infections
CLSI – Clinical and Laboratory Standards Institute
CRISPR – Clustered Regularly Interspaced Short Palindromic Repeats
GIT – Gastrointestinal Tract
GM – Gentamicin
HAIs – Healthcare-associated Infections
HGT – Horizontal Gene Transfer
LNZ – Linezolid
MAR – Multiantibiotic resistance
MLST – Multilocus Sequence Typing
PCR – Polymerase Chain Reaction
PFGE – Pulse-Field Gel Electrophoresis
SBA – Slanetz and Bartley Agar
TET – Tetracycline
TSA – Tryptic Soy Agar
TTC – Triphenyl Tetrazolium Chloride
UV – Ultraviolet
VAN – Vancomycin
VRE – Vancomycin-resistant Enterococcus
WGS – Whole Genome Sequence
WHO – World Health Organization
WWTPs – Wastewater Treatment Plants
VIII
List of Figures
Figure 1 - Representation of mechanisms responsible for the spread of antibiotic resistance genes. A –
Conjugation is the transfer of plasmids through direct contact between two bacteria; B – Transformation
is the uptake of naked DNA from the environment; C – Transduction is the transfer of DNA mediated by
bacteriophages being this transference possible between bacteria from different taxonomic groups. D –
Gene transfer agents are bacteriophages like particles that transfer only small regions of the bacteria
DNA without the transfer of phage structural genes. Adapted from Von Wintersdorff et al. 2016. ......... 4
Figure 2 - Mode of action and organization of vanA and vanB operons. The open arrows represent
coding sequences and indicate the direction of transcription. It is possible two observe that a two-
component regulatory system regulates the genes of the operon. When glycopeptides are present, VanS
phosphorylated on a specific histidine residue and the phosphate group is subsequently transfer to the
response regulator, VanR. This system is transcribed by a specific promotor (PR) whereas the remaining
genes are transcribed by a second promoter (PH). The vanH gene encodes a dehydrogenase, vanA a
ligase and vanY and vanX genes encode a peptidase. There are slight differences between these two
operons. The 2-component regulatory system of vanB is quite different comparing to vanA. Moreover,
vanB operon has an additional protein, VanW, and there is no gene related to vanZ. Adapted from Arthur
& Quintiliani R. 2001, and Gilmore et al. 2014. ....................................................................................... 8
Figure 3 - Summary of potential pathways for ARB, ARG, and antibiotics to enter the environment
through water sources. Wastewater from diverse sources can enter in the WWTPs where the number
of bacteria is reduced. However, in these treatments can occur the selection of antibiotic-resistant
bacteria that are discharged into the environment. Through drinking or recreational waters, and food
these bacteria can colonize humans and cause infections. Adapted from Mcconnell 2016. ................ 12
Figure 4 - PCR for identification of different Enterococcus spp. PCR products were loaded on 2.5 %
agarose gel. 100 bp DNA ladder (lane 1), E. faecium isolates (lanes 3-6), E. faecium (positive control –
lane 7) and negative control (lane 8). ................................................................................................... 17
Figure 5 - PCR for identification of different enterococcal spp. PCR products were loaded on 2.5%
agarose gel. 100 bp DNA ladder (lane 1), E. faecalis isolates (lanes 2, 4, 6 and 7), E. faecalis (positive
control – lane 8) and negative control (lane 9). .................................................................................... 18
Figure 6 - Species prevalence in the WWTPs studied and the global prevalence. .............................. 19
Figure 7 - Species prevalence in the treatments applied in WWTP A. ................................................ 20
Figure 8 - Species prevalence in the treatments applied in WWTP B. ................................................ 21
Figure 9 - Species prevalence in the treatments applied in WWTP C and Natural Receptors............. 22
Figure 10 - Species prevalence in the treatments applied in the WWTPs. .......................................... 23
Figure 11 - Resistance to each one of the antibiotics in the treatments applied in WWTP A............... 25
Figure 12- Resistance to each one of the antibiotics in the treatments applied in WWTP B................ 27
Figure 13 - Resistance to each one of the antibiotics in the treatments applied in WWTP C and Natural
Receptors. ............................................................................................................................................ 28
Figure 14 - Resistance to each one of the antibiotics in the treatments applied in the WWTPs. ......... 29
Figure 15 - Distribution of vancomycin-resistance for species Enterococcus in each one of the WWTPs.
............................................................................................................................................................. 31
IX
Figure 16 – Percentages of resistance for vancomycin in each species of Enterococcus. .................. 32
Figure 17 – Proportion of MAR in the treatments applied in WWTP A. ............................................... 34
Figure 18 - Proportion of MAR in the treatments applied in WWTP B. ................................................ 35
Figure 19 - Proportion of MAR in the treatments applied in WWTP C and Natural Receptors. ........... 35
Figure 20 – Proportion of MAR in the treatments applied in WWTPs. ................................................. 36
Figure 21 - Distribution of multiresistant species throughout the treatment of the WWTP A................ 37
Figure 22 - Distribution of multiresistant species throughout the treatment of the WWTP B................ 38
Figure 23 - Distribution of multiresistant species throughout the treatment of the WWTP C and Natural
Receptors. ............................................................................................................................................ 39
Figure 24 - Distribution of multiresistant species throughout the treatments in the WWTPs................ 40
X
List of Tables
Table 1 – Differences between the nine operons that confer resistance to glycopeptides. The main
differences rely on the type of resistance, occurrence of conjugation, the mobile elements, type of
expression, the location of the operon, the modified target, and the mainly species where the operon is
found. ..................................................................................................................................................... 6
Table 2 - Primers specifications (sequence and size of PCR product) used for identification of
Enterococcus faecalis (ddl E. faecalis) and Enterococcus faecium (ddl E. faecium). ...................................... 14
Table 3 - Antimicrobial compounds used in this study and susceptibility values established by CLSI
(2017). .................................................................................................................................................. 15
Table 4 - Primers specifications (sequence and size of PCR product) used for detection of vanA and
vanB genes. ......................................................................................................................................... 16
Table 5 – Species prevalence in each one of the WWTPs studied and all of them. ............................ 18
Table 6 – Species prevalence and p-value in the treatments applied in WWTP A. .............................. 20
Table 7 - Species prevalence and p-value in the treatments applied in WWTP B. .............................. 21
Table 8 - Species prevalence and p-value in the treatments applied in WWTP C and Natural Receptors.
............................................................................................................................................................. 22
Table 9 - Species prevalence and p-value in the treatments applied in the WWTPs. .......................... 23
Table 10- Comparison of antibiotic resistance (%) in WWTP A and respective p-values. ................... 25
Table 11 - Comparison of antibiotic resistance (%) in WWTP B and respective p-values. .................. 26
Table 12 - Comparison of antibiotic resistance (%) in WWTP C and Natural Receptors and respective
p-values. ............................................................................................................................................... 28
Table 13 - Comparison of antibiotic resistance (%) in WWTPs and respective p-values. .................... 29
Table 14 – Prevalence of vancomycin-resistance (%) for species of Enterococcus in each one of the
WWTPs and p-value associated. ......................................................................................................... 31
Table 15 - Percentage and p-value of the comparison of the multiresistance in WWTP A. ................. 34
Table 16 - Percentage and p-value of the comparison of the multiresistance in WWTP B. ................. 34
Table 17 - Percentage and p-value of the comparison of the multiresistance in WWTP C and Natural
Receptors. ............................................................................................................................................ 35
Table 18 - Percentage and p-value of the comparison of the multiresistance in the WWTPs. ............. 36
Table 19 - Percentage and p-value of the comparison of the multiresistance of the species in WWTP A.
............................................................................................................................................................. 37
Table 20 - Percentage and p-value of the comparison of the multiresistance of the species in WWTP B.
............................................................................................................................................................. 38
Table 21 - Percentage and p-value of the comparison of the multiresistance of the species in WWTP C
treatments and in Natural Receptors. ................................................................................................... 39
Table 22 - Percentage and p-value of the comparison of the multiresistance of the species in WWTPs
............................................................................................................................................................. 40
Table 23 - Antibiotics classification according to how they attack bacteria and their chemical shape. It is
also enumerated some example (s). .................................................................................................... 51
XI
Table 24 – Characterization of the isolates collected from WWTP A. It is possible to distinguish 4
different types of treatment: Influent, Disinfection, Effluent and Reused water. All the isolates were
identified using PCR and cultured-based techniques. In Zone Diameter (mm) section it is possible to
distinguish the 7 antibiotics used, and the diameter of the inhibition zones. According to these
measurements, the isolates were sorted as susceptible (green), intermediate (orange), and resistant
(red). ..................................................................................................................................................... 52
Table 25 - Characterization of the isolates collected from WWTP B. It is possible to distinguish 3 different
types of treatment: Influent, Disinfection, and Reused water. All the isolates were identified using PCR
and cultured-based techniques. In Zone Diameter (mm) section it is possible to distinguish the 7
antibiotics used and the diameter of the inhibition zones. According to these measurements, the isolates
were sorted as susceptible (green), intermediate (orange), and resistant (red). .................................. 54
Table 26 - Characterization of the isolates collected from WWTP C. It is possible to distinguish 3 different
types of treatment: Filtration, Disinfection, Effluent, and two Natural Receptors. All the isolates were
identified using PCR and cultured-based techniques. In Zone Diameter (mm) section it is possible to
distinguish the 7 antibiotics used and the diameter of the inhibition zones. According to these
measurements, the isolates were sorted as susceptible (green), intermediate (orange), and resistant
(red). ..................................................................................................................................................... 56
1
1. Introduction
1.1. Antimicrobial substances
Antimicrobial substances were one of the major and most significant discoveries in Medicine,
decreasing human mortality and morbidity significantly around the world. Among these
antimicrobial substances, the antibiotics were the most successful form of antimicrobial therapy
developed. Nowadays, modern medicine depends on their effectiveness to treat and prevent
various infections (Banin, Hughes, & Kuipers, 2017; Björkman & Andersson, 2000).
The first effective antibacterial agent named sulphonamide was developed in the 1930s.
However, the discovery of antibiotics began in 1928 with the microbiologist Alexander Fleming
who discovered a mold (now called Penicillium notatum) that was efficient killing Staphylococcus
aureus. The substance produced by the fungus, the penicillin, was efficient against not only S.
aureus but also against a broad range of bacteria. The first clinical use of penicillin dated 1941,
in London, and since then it is widely used in the treatment of several infections. In the following
years, the large diversity of antibiotics was discovered giving rise to a period known as “The
antibiotic era”. The discovery of antibiotics continued until the 1960s. During this period, most of
the antibiotic classes used today were discovered (Guilfoile, 2007; Santos-Beneit, Ordóñez-
Robles, & Martín, 2017) (Annex 1, Table 23).
Unavoidably some bacteria started to shown antibiotic resistance, being this fact documented
as early as the beginning of the antibiotic era (Kon & Rai, 2013). Although natural-resistant
bacteria and resistance genes to antibiotics always existed, anthropogenic activities increased
the antibiotic resistance. It has increased significantly due to overconsumption and imprudent use
in human therapeutics, veterinary medicine, animal husbandry, aquaculture, food technology and
agriculture. It is also due to the constant evolution and spread of mobile genetic resistance
elements (Bouki et al. 2013; Rizzo et al. 2013; Sidrach-Cardona et al. 2014; Rafraf et al. 2016,
Banin et al. 2017).
According to the World Health Organization (WHO) the gradual emergence of antibiotic-
resistant bacteria (ARB) population is a massive concern for public health around the world,
restricting treatment options for bacterial infections and thus reducing clinical efficacy, while
increasing treatment costs and mortality (Banin et al., 2017; Björkman & Andersson, 2000).
This situation is very alarming since antibiotic-resistant bacteria are not confined to one
environment, and their spread became much more frequent and dangerous. Antibiotics used as
growth promoters in farms or aquaculture, and in human medicine are commonly excreted in the
active form namely in the urine or/and feces. In humans, antibiotics such as β-lactams (except for
ceftriaxone), aminoglycosides, quinolones, nitrofurantoin, sulphonamides, and glycopeptides are
excreted in the urine. Macrolides, tetracyclines and fusidic acid, for instance, are actively excreted
in feces. On the other hand, fosfomycin, rifampicin, and ceftriaxone are excreted in both ways
(Martínez, 2008; Singer, Shaw, Rhodes, & Hart, 2016). After excretion, antibiotics usually go to
2
the sewage system and enter wastewater treatment plants (WWTPs) ending up, eventually, in
the natural environment (Singer et al., 2016). In environments like these, antibiotics can exert
selective pressions by killing the susceptible population and maintaining the resistant-ones.
The number of antibiotic-resistant bacteria present in these environments is increasing
considerably. A group of bacteria that has been raising an epidemiological and antimicrobial
concern is Enterococci (Holzapfel & Wood, 2014; Oravcova et al., 2017; Yang et al., 2015). The
species of Enterococci group have tremendous genome plasticity and therefore can harbour a
wide variety of transposons and plasmids that are crucial in the acquisition of antibiotic resistance
genes (ARGs) and virulence factors (Cetinkaya, Falk, & Mayhall, 2000; Jett, Huycke, & Gilmore,
1994; O’Driscoll & Crank, 2015).
1.2. Description of Enterococcus Genus
The establishment of the Enterococcus genus was made in 1984 by Scleifer and Kilpper-Bälz
using DNA-DNA and DNA-rDNA hybridization. These experiments were relevant to differentiate
this genus from other phenotypically similar, such as Streptococcus and Lactococcus. This
separation was confirmed by 16s rRNA oligonucleotide cataloguing by Ludwig et al, in 1985. Until
now, 54 species and 2 subspecies are recognized being Enterococcus faecalis the type species
(Bergey, 2009; Cetinkaya et al., 2000; Holzapfel & Wood, 2014).
Enterococcal bacteria have ovoid shape and can occur singly, in pairs, short chains, or can be
arranged in groups. They are gram-positive facultative anaerobes (with a preference for
anaerobic conditions), non-sporeforming, typically catalase negative, and possess group D
antigen of Lancefield typing. Most species have their optimal growth between 35 - 37 ºC but many
species can grow between 10 ºC - 45 ºC (Holzapfel & Wood, 2014). Colonies are regular and
circular up to 5 mm in diameter. Although enterococci have complex nutritional requirements,
such as the presence of amino acids, B vitamins, purine and pyrimidine bases, this group of
bacteria can grow on commonly used bacteriological media (Slanetz-Bartley agar - SBA, for
example). In anaerobic conditions, through the Embden-Meyerhof-Parnas pathway, the bacteria
produce L-lactic acid from glucose (homofermentative formation); under aerobic conditions,
glucose is converted to acetic acid, acetoin, and CO2. Their DNA G+C content ranges from 37 to
45 mol % (Bergey, 2009).
These microorganisms occur in a broad range of different ecological environments such as
surface waters, wastewaters, recreational waters, on plants, soils, and in the gastrointestinal tract
(GIT) of warm-blooded animals (Holzapfel & Wood, 2014).
These microorganisms can cause spoilage, deteriorating the food or, on the other hand, can
play an important role in ripening and aroma development in fermented food products, like
cheeses and sausages. Thus, an association between enterococci and food can be detrimental
or valuable. These bacteria can act as human probiotics and be used to treat diarrhoeal disease
caused by antibiotic-associated diarrhea bacteria or food-borne pathogens such as the species
Enterococcus faecalis and Enterococcus faecium (Holzapfel & Wood, 2014).
3
Since E. faecalis and E. faecium constitute a large proportion of the natural microflora of the
intestinal tract of warm-blooded animals their presence can be useful in the identification of fecal
pollution from human and animal sources (Holzapfel & Wood, 2014; Scott, Jenkins, Lukasik, &
Rose, 2005; Taučer-Kapteijn, Hoogenboezem, Heiliegers, de Bolster, & Medema, 2016). After
fecal elimination to the environment, enterococci can be found in waters, being recurrently used
as indicators for bacteriological water quality in fresh and saline waters.
Despite their widespread distribution enterococci can cause community-acquired and
nosocomial infections. The first enterococcal infection was described in 1899 (William Maccallum
and Thomas Hastings, 1899) – infective endocarditis – and after that was shown that enterococci
could cause a range of infections. Nowadays, is estimated that E. faecalis and E. faecium are
responsible for 80 % to 90 % of human enterococcal infections (Cetinkaya et al., 2000;
Hammerum et al., 2017; Rathnayake, Hargreaves, & Huygens, 2011). However, infections by
other enterococcal species have been described (Lozano et al., 2016). Enterococci can be
etiological agents of the urinary tract, surgical wounds, endocarditis, bacteremia, neonatal, intra-
abdominal and pelvic infections (Jett et al., 1994; Oravcova et al., 2017; Rosenberg Goldstein et
al., 2014).
In 2016, the Centers for Disease Control and Prevention’s (CDC) National Healthcare Safety
Network reported the antimicrobial resistance patterns for healthcare-associated infections (HAIs)
that occurred in 2011 – 2014. According to this report, and citing the article: “ If all Enterococcus
species were analysed at the genus-level, this group would be considered the second most
common pathogen across all HAI types, and the single most common pathogen among central
line–associated bloodstream infections (CLABSIs)” (Weiner et al., 2016).
1.3. Antibiotic Resistance in Enterococcus Genus
1.3.1. General Aspects
Enterococcus are noted to contain multiple antibiotic-resistant capabilities, which contributes
to their persistence during the infection process and subsequent treatment.
The antibiotic resistance present in bacteria can be intrinsic or acquired. Intrinsic resistance
occurs without a prior exposure of the bacteria to the antimicrobial compound. This type of
resistance is due to the presence of resistance genes located on the chromosome, being
transmitted vertically to bacteria progeny. Intrinsic resistance mechanisms include: cell wall and
membrane impermeability to the drug, absence of target receptors for the antibiotic, existence of
efflux pumps or antimicrobial compound alteration (Amábile-Cuevas, 2016; Clark, Teixeira,
Facklam, & Tenover, 1998; Miller, M, & Arias, 2014).
Enterococcus are intrinsic-resistant to fluoroquinolones, lincosamides, trimethoprim-
sulfamethoxazole, moderate level to aminoglycosides and β-lactams. Some species such as
Enterococcus gallinarum, Enterococcus casseliflavus, and Enterococcus flavescens have a
constitutive resistance gene, the vanC, that confers intrinsic resistance to low levels of
4
vancomycin (Hollenbeck & Rice, 2012; Lozano et al., 2016; Madigan, Martinko, Bender, Buckley,
& Stahl, 2014).
The acquisition of resistance to antibiotics is a process much more sophisticated. Two main
mechanisms lead to a formation of a drug-resistant bacteria: mutations and horizontal gene
transfer (HGT). Between them, HGT is considered the most important factor in the current
pandemic of resistance (Davies & Davies, 2010; Kon & Rai, 2013), being conjugation,
transformation, transduction, and gene transfer agents the most prevalent mechanisms to the
spread of antibiotic resistance genes (ARG) (Amábile-Cuevas, 2016; Von Wintersdorff et al.,
2016) (Figure 1). Enterococcus can develop resistant to chloramphenicol, lincosamides,
macrolides, streptogramins, tetracyclines, quinolones, glycopeptides as well as high-level
resistance to aminoglycosides, and β-lactams (Hollenbeck & Rice, 2012; Lozano et al., 2016;
Madigan et al., 2014).
Among the acquired resistances, the resistance to glycopeptides has been thoroughly studied.
Glycopeptides, such as vancomycin or teicoplanin, are used in clinical practice and represent a
class of antibiotics of last resort for the treatment of severe infections caused by gram-positive
bacteria (L. Guardabassi & Dalsgaard, 2004). Enterococcus that possess resistance to
vancomycin are called Vancomycin-resistant Enterococcus (VRE). According to CDC this
Figure 1 - Representation of mechanisms responsible for the spread of antibiotic resistance
genes. A – Conjugation is the transfer of plasmids through direct contact between two bacteria;
B – Transformation is the uptake of naked DNA from the environment; C – Transduction is the
transfer of DNA mediated by bacteriophages being this transference possible between bacteria
from different taxonomic groups. D – Gene transfer agents are bacteriophages like particles that
transfer only small regions of the bacteria DNA without the transfer of phage structural genes.
Adapted from Von Wintersdorff et al. 2016.
5
bacteria group is one of the most dangerous in terms of antibiotic resistance epidemiology (CDC,
2013), evidencing the importance of monitorization of these microorganisms.
Glycopeptides antibiotics act inhibiting the cell wall synthesis by binding with high affinity to a
specific peptidoglycan precursor (d-ala-d-ala terminus of Lipid II) (Courvalin, 2006).
The glycopeptide resistance is usually due to the presence of operons that encode enzymes
for synthesis of low-affinity precursors, in which the C-terminal d-Ala residue in lipid II is replaced
by D-Lac or D-Ser. The resistance is also due to the elimination of high-affinity precursors that
are naturally produced by the hosts. Until now nine operons have been described (Hollenbeck &
Rice, 2012; Oravcova et al., 2017; Yang et al., 2015). In the Table below (Table 1) is possible to
identify several characteristics of the nine operons that confer glycopeptide resistance (Taučer-
Kapteijn et al., 2016). So far, vanA and vanB operons are the most common in human
vancomycin-resistant enterococcal infections.
6
Table 1 – Differences between the nine operons that confer resistance to glycopeptides. The main differences rely on the type of resistance, occurrence
of conjugation, the mobile elements, type of expression, the location of the operon, the modified target, and the mainly species where the operon is found.
VanA VanB VanD VanG VanC
VanL VanE VanN VanM C1 C2/C3
MIC (µg/mL)
Vancomycin 64-1000 4-1000 64-128 ≤ 16 2-32 8 8-32 16 > 256
Teicoplanin 16-521 0,5-1 4-64 Sensitive 0,5-1 ≤ 0,5 0,5 ≤ 0,5 96
Type of resistance Acquired Acquired Acquired Acquired Intrinsic Acquired Acquired Acquired Acquired
Conjugation Positive Positive Negative Positive Negative Negative Negative Positive Positive
Mobile element Tn1546 Tn1547 or
Tn1549 - - - - - - -
Expression Inducible Inducible Constitutive or inducible
Inducible Constitutive Inducible Inducible Constitutive Inducible
Location Plasmid or
chromosome Plasmid or
chromosome Plasmid or
chromosome Chromosome Chromosome Chromosome Chromosome
Plasmid or chromosome
Plasmid or chromosome
Modified target d-Ala-d-Lac d-Ala-d-Lac d-Ala-d-Lac d-Ala-d-Ser d-Ala-d-Ser d-Ala-d-Ser d-Ala-d-Ser d-Ala-d-Ser d-Ala-d-Lac
Mainly species E. faecalis
and E. faecium
E. faecalis and
E. faecium
E. faecalis and
E. faecium E. faecalis
E. gallinarum
E. casseliflavus
E. faecalis E. faecalis E. faecium E. faecium
Reference
(Arthur et al. 1993;
Guardabassi and
Dalsgaard 2004;
O’Driscoll and Crank
2015)
(Garnier et al. 2000)
(Perichon, Reynolds,
and Courvalin
1997)
(McKessar et al. 2000)
(Clark et al. 1998) (Boyd et al.
2008) (Fines et al.
1999) (Lebreton et
al. 2011) (Xu et al.
2010)
7
1.3.2. VanA and VanB Operons
The VanA phenotype is characterized by resistance to both vancomycin and teicoplanin. The
expression of VanA phenotype is due to the presence of Tn1546, 11kb - transposon carried by a
self-transferable plasmid or in some cases by the host chromosome as part of larger conjugative
elements (M.-C. Kim, Cha, Ryu, & Woo, 2017).
The vanR and vanS genes encode two proteins (VanR and VanS) that constitute a 2-
component regulatory system that modulates transcription of the resistance gene cluster. VanS
detects the presence of glycopeptide, and after that, the cytoplasmic domain of the protein
catalyses ATP-dependent autophosphorylation on a specific histidine residue and transfers the
phosphate group to an aspartate residue of VanR present in the effector domain. The VanS
sensor can modulate the phosphorylation level on the VanR regulator, meaning that when
glycopeptides are absent, the sensor acts as a phosphatase and when in the presence of
glycopeptide acts as a kinase which leads to the activation of resistance genes (Arthur &
Quintiliani Richard., 2001; Courvalin, 2006). This regulatory apparatus is transcribed by a specific
promoter (PR), while the remaining genes are transcribed by a second promoter (PH) (Ahmed &
Baptiste, 2017).
In the operon contains a gene that encodes a dehydrogenase (VanH) which reduces pyruvate
to d-Lac and with the assistance of VanA ligase is produce de dipeptide d-Ala-d-Lac. This
molecule replaces the d-Ala-d-Ala dipeptide during the peptidoglycan synthesis and therefore
decrease the affinity of the molecule for glycopeptides (Arthur et al. 1993; Courvalin 2006).
The interaction of vancomycin with its target is prevented by the removal of the susceptible
precursors that terminate in d-Ala (high-affinity precursors produced by the host). In order to
eliminate those molecules, the VanX D,D-dipeptidase hydrolyses the d-Ala-d-Ala dipeptide
synthesized by chromosomal D-Ala-D-Ala ligase (Ddl), and the VanY D,D-carboxypeptidase
removes the C-terminal d-Ala residue of late peptidoglycan precursors when elimination of d-Ala-
d-Ala by VanX is not complete (Arthur et al., 1993; L. Guardabassi & Dalsgaard, 2004).
The VanB phenotype is characterized by resistance only to vancomycin. The expression of
VanB phenotype is due to the presence of a smaller VanB transposon (Tn1549) which can
transpose replicatively into plasmids or due to a larger transposon (Tn1547) which can excise
from the chromosome, circularize, and transfer to Gram-positive bacteria by conjugation (Garnier,
Taourit, Glaser, Courvalin, & Galimand, 2000).
The genetic backbone of vanB cluster is identical to vanA. However, some differences are
worth noting. The vanB cluster is only induced by vancomycin resulting in slight differences in the
overall regulatory system. Moreover, the cluster has an additional VanW protein (which function
is unknown), and there is no gene related to vanZ (Ahmed & Baptiste, 2017; Courvalin, 2006;
Garnier et al., 2000) (Figure 2).
Based on sequence differences, the vanB gene cluster is divided into 3 subtypes: vanB1,
vanB2, and vanB3. There is no correlation between the vanB subtype, and the level of resistance
to vancomycin (Courvalin, 2006).
8
1.3.3. Epidemiology and Characterization of Vancomycin-Resistant
Enterococcus
The emergence of VRE followed a worst-case scenario in the epidemiologic problematic of
antibiotic-resistant bacteria (Willems et al., 2005): firstly reported in Europe by 1986 and in the
United States by 1987 (M.-C. Kim et al., 2017; Levine, 2006), VRE now represents one of the
most common pathogens in health-care-associated infections (Armin et al., 2017; Weiner et al.,
2016).
In Europe, the misuse of avoparcin (a glycopeptide antibiotic) as a growth promotor in farm
animals was the most probable source of VRE. However, in the US avoparcin was never
approved. For this reason, the appearance of VRE was associated with the overuse of
vancomycin in hospital facilities (O’Driscoll & Crank, 2015). E. faecium is the most common isolate
Figure 2 - Mode of action and organization of vanA and vanB operons. The open arrows
represent coding sequences and indicate the direction of transcription. It is possible two observe
that a two-component regulatory system regulates the genes of the operon. When glycopeptides
are present, VanS phosphorylated on a specific histidine residue and the phosphate group is
subsequently transfer to the response regulator, VanR. This system is transcribed by a specific
promotor (PR) whereas the remaining genes are transcribed by a second promoter (PH). The
vanH gene encodes a dehydrogenase, vanA a ligase and vanY and vanX genes encode a
peptidase. There are slight differences between these two operons. The 2-component regulatory
system of vanB is quite different comparing to vanA. Moreover, vanB operon has an additional
protein, VanW, and there is no gene related to vanZ. Adapted from Arthur & Quintiliani R. 2001,
and Gilmore et al. 2014.
9
found in hospitals, being the main clinical reservoir of vanA and vanB genes in Europe, Southwest
Asia, and Northern and Latin America. These isolates are rarely found in the community contrary
to E. faecalis, the most common isolate in the community, farm animals and food products
(Ahmed & Baptiste, 2017).
According to recent surveillance data, an increase of vancomycin-resistant E. faecium was
observed in almost half of the reporting countries between 2012 and 2015. However, in Europe
this increment was not observed, indicating changes in the epidemiology of the bacterium
(European Centre for Disease Prevention and Control, 2016).
The public health concern about this microorganism is not only related to the ability to cause
severe infections but also with the propensity to acquire and transfer mobile resistance genes
(Guzman Prieto et al., 2016). VRE can transfer resistance genetic elements to methicillin-resistant
Staphylococcus aureus (MRSA), for example, a very pathogenic organism in health care settings
(M.-C. Kim et al., 2017; Levine, 2006; Rosenberg Goldstein et al., 2014).
Colonisation and infection of VRE are associated with long periods of hospitalization, intensive
antibiotic use, proximity to patients previously colonized or infected, immunosuppressed,
transplant, and severe comorbid conditions (Remschmidt et al. 2017). VRE are commonly
multidrug-resistant and so the treatment options for VRE-infections are limited. Some new
antibiotics including quinupristin-dalfopristin, linezolid, tigecycline, and daptomycin have been
used to treat these infections. However, for each one of these, resistance has already been
reported (Leavis, Bonten, & Willems, 2006).
To study the dissemination of VRE clones in and between hospitals, in farm animals and
healthy humans a vast number of molecular epidemiological studies have been performed, using
techniques such as amplified fragment length polymorphism (AFLP), multilocus sequence locus
(MLST), pulse-field gel electrophoresis (PFGE), Clustered Regularly Interspaced Short
Palindromic Repeats (CRISPR) analysis, and whole genome sequence (WGS) (Ahmed &
Baptiste, 2017; Guzman Prieto et al., 2016; Lytsy, Engstrand, Gustafsson, & Kaden, 2017).
VRE are not confined to hospitals and in 1993 was recovered from wastewater samples the
first vancomycin-resistant E. faecium (Iversen et al., 2004) and in the previous years in many
other sources, such as broilers, foods, rivers’ water, and food products confirming the spread of
this microorganism to natural and non-natural environments (Ahmed & Baptiste, 2017; Lozano et
al., 2016).
1.4. Antibiotic Resistance in Wastewater Treatment Plants
To decrease the use pressure on freshwater resources several countries – including Portugal
– are reusing treated municipal wastewater for non-potable purposes, such as landscape and
crop irrigation, groundwater recharge, and snowmaking (USEPA, 2004). This reclaimed water
needs to be treated based on specific water quality criteria. Also, the sludges that result from the
treatments’ process can be spread upon agricultural soil to fertilize and/or improve soils (Carey
et al. 2016; Oliveira et al. 2016; Singer et al. 2016).
10
The wastewaters from homes, industries, farms, and hospitals can contain antibiotics and
other pollutants (heavy metals and biocides, for instance), ARB, and ARG, especially if the waste
is from hospital settings (Bouki, Venieri, & Diamadopoulos, 2013). Water constitutes not only a
way of dispersal of antibiotic-resistant bacteria among human and animal populations but also
the route by which resistance genes are introduced in water and soil bacterial communities. In
these systems, non-pathogenic bacteria could serve as a reservoir of resistance genes.
Antibiotics, disinfectants, and heavy metals that are released into water exert selective activities,
as well as ecological damage in water communities, resulting in antibiotic resistance (Baquero,
Martínez, & Cantón, 2008).
Several studies have shown that WWTPs are a source and a reservoir of ARG and ARB.
WWTPs have appropriate conditions such as high nutrient concentration, sub-inhibitory antibiotic
concentration, close contact between bacteria, optimal pH, and temperature, that allow the growth
of ARB and the maintenance of ARG (Bouki et al., 2013; Rizzo et al., 2013; Rosenberg Goldstein
et al., 2014; Sidrach-Cardona, Hijosa-Valsero, Marti, Balcázar, & Becares, 2014). The antibiotics
are, in general, detected in WWTP at low concentrations. However, these low concentrations
have associated the development, maintenance and spread ARG and ARB in the environment.
These conditions exert a selective pressure that provides an ideal setting for HGT (Fiorentino et
al., 2015; Heß & Gallert, 2016; Rizzo et al., 2013). HGT allows the transfer of genetic elements
between bacteria, being critical to the spreading of resistance, principally in a mixed bacterial
population, as what happens in activated sludge of sewage treatment plants (Da Costa, Loureiro,
& Matos, 2013; Rafraf et al., 2016; Sidrach-Cardona et al., 2014).
WWTPs can have three different treatment types: preliminary and primary, secondary, and
tertiary. In the first one, oils, sands, and coarse solids are removed by physical operations (bar
screens or settling tanks). In secondary treatment, to remove organic matter and nutrients,
biological and chemical processes can be used. The biological process relies on aerobic and/or
anaerobic microorganisms, being the activated sludge (floc) method the most used. Other
treatments can be applied such as sand filtration, adsorption, membranes, or advanced oxidation
process (Rizzo et al., 2013). Some WWTPs have an additional treatment where the compounds
that were not eliminated in previous ones, such as nitrogen or phosphorous, are removed.
An additional result of these treatments is the reduction of the number of bacteria, assuring
the elimination of pathogenic bacteria which may be responsible for dysentery, typhoid, and
gastroenteritis diseases, for example (Bouki, Venieri, and Diamadopoulos 2013; Oliveira et al.
2016; Da Silva et al. 2006).
After these treatments’ disinfection processes are also used to improve the effluent
biosecurity. The most used disinfection process in WWTPs is ultraviolet (UV) radiation, but
chlorination (as chlorine gas or hypochlorite) can also be applied. Chlorine reacts strongly with
lipids of the membrane leading to oxidation of the germ cells, alteration of the cell permeability,
inhibition of enzymatic activity and damage in nucleic acids (Rizzo et al., 2013). In EUA, for
example, it is the most used disinfection process because it is widely applicable and has moderate
11
costs. However, during this process, some by-products can be generated, and that can be a public
health and an environmental problem. To balance these problems, some WWTPs have adopted
UV light as the most appropriate treatment option, and its use has increased over the past few
decades (Bouki et al., 2013). With UV light it is possible to destroy nucleic acids and disrupt DNA,
which inhibits cell functions (Rizzo et al., 2013).
Generally, the treatments reduce the number of bacteria between 1 and 3 logs in the incoming
water (Sidrach-Cardona et al., 2014). However, ARB and ARG may persist even after these
processes (Rizzo et al., 2013). The amount of ARG, ARB, metals, and biocide in the final effluent
and sludge is variable. These variations are related with the WWTP catchment characteristics,
the types of the treatments applied, or the presence of hospital wastewaters (Singer et al., 2016).
WWTP effluents can be released into rivers, estuaries, river outlets or streams. The receiving
surface waters represent a significant fraction of public drinking water, and standard treatment
processes in WWTPs may not be effective in removing or inactivating the ARB and ARG (Rafraf
et al., 2016). That means from those ecosystems, resistant bacteria can return to humans directly,
by drinking water (Morris et al., 2012) or recreational ones, but also indirectly by eating
vegeTables, meat or fish (L. Ben Said et al., 2016; Ben et al., 2017; Da Costa et al., 2013; Lozano
et al., 2016; Oravcova et al., 2017; Taučer-Kapteijn et al., 2016).
The quantification of Escherichia coli and Enterococcus is recommended to evaluate the
microbiological quality of the effluent in WWTPs in order to avoid public health issues (Oliveira et
al. 2016; Rizzo et al. 2013).
Previous studies detected VRE at different stages of the WWTPs, including the final effluent,
suggesting that WWTPs could be partially responsible for the spread of VRE into environments
and human communities (Bessa, Barbosa-Vasconcelos, Mendes, Vaz-Pires, & Da Costa, 2014;
Di Cesare et al., 2014; Rosenberg Goldstein et al., 2014).
In Europe, was suggested that colonisation with VRE mainly occurs in the community (by the
contact with contaminated environments such as waters), and that is related with the spread of
these microorganisms into the environment. The transmission of resistant-bacteria to people and
animals with contact with these environments lead to an increase of human/animal reservoir of
VRE, constituting a major public health concern (McDonald, Kuehnert, Tenover, & Jarvis, 1997;
Novais, Coque, Ferreira, Sousa, & Peixe, 2005).
So, the knowledge about the nature and number of resistant bacteria that are disseminating
is crucial to implement new or different strategies to control the transmission of those within
hospitals or the community.
12
Figure 3 - Summary of potential pathways for ARB, ARG, and antibiotics to enter the environment
through water sources. Wastewater from diverse sources can enter in the WWTPs where the
number of bacteria is reduced. However, in these treatments can occur the selection of antibiotic-
resistant bacteria that are discharged into the environment. Through drinking or recreational
waters, and food these bacteria can colonize humans and cause infections. Adapted from
Mcconnell 2016.
1.5. Aims of the Study
The main aim of this study is to assess the possible correlation between antibiotic resistance
and wastewater treatment processes to infer the possibility of antibiotic or multiantibiotic-resistant
bacteria being positively selected by WWTP treatments. Alongside with this study it will be
possible to understand if one of the species identified (E. faecium or E. faecalis) is more resistant
to the treatments applied in the WWTPs or if they are equally affected by the treatments.
Additionally, it will be possible to analyse an association between the species identified and the
resistance to the antibiotics tested, focusing on vancomycin resistance. The detection of
multiantibiotic-resistant bacteria in final processes of the treatment of wastewaters and natural
receptors (rivers) can reveal the necessity of new or other strategies to eliminate these bacteria.
Waste from households, hospitals, farms potentially contain ARB, ARGs, and
antibiotics.
WWTPs (potential transfer of ARGs between bacteria
or selection of ARB, incomplete removal of
ARB, ARGs, and antibiotics).
Environment (rivers, lakes) - movement of ARB,
ARGs, and antibiotics.
Through drinking water systems, recreational
water, and food ARB can colonize humans.
13
2. Materials and methods
2.1. Sampling Collection
This work was performed in three different WWTPs (A, B, and C). In each one of the stages
of the water treatments applied, 500 mL of water were collected in sterile bottles. Subsequently
were taken to the laboratory at 5 ± 3 ºC within 8 h of collection. In WWTP A, samples were
collected at Influent, Disinfection Process, Effluent, and Reused water. In WWTP B at Influent,
Disinfection Process, and Reused water, and in WWTP C were collected a Filtration (tertiary
treatment), Disinfection, Effluent, and two environmental water receptors (a river, named as
Natural Receptor 1 and 2). The samples of Natural Receptor 2 were collected on downstream of
Natural Receptor 1. In all the WWTPs the disinfection process was UV radiation.
In terms of size characteristics, WWTP A is the biggest receiving waters from around 760 000
habitants, and WWTP C the smallest receiving waters from 28 000 habitants. On the other and
WWTP B receives waters from 211 000 habitants.
2.2. Detection and Isolation of Faecal Enterococci by
Conventional Culture Method
Detection and isolation of intestinal enterococci was performed according to International
Standards (ISO) 7899-2:2000.
The samples were diluted and filtered through a 0.45 μm-pore size membrane (GE
Healthcare’s Life Sciences, Germany). The membrane was then placed into Slanetz and Bartley
Agar (SBA) (Oxoid, UK). Plates were then incubated at 37 ºC for 48 h. After incubation, all
colonies which showed red, maroon, or pink colour were considered as presumptive faecal
enterococci. This medium is selective because it contains sodium azide that inhibits the growth
of Gram-negative bacteria and it contains 0.1% of triphenyltetrazolium chloride (TTC), an indicator
that it is reduced inside the cells, turning presumptive enterococci coloured. Membranes that
showed presumptive positive colonies were transferred, using sterile forceps, onto a plate of Bile-
Esculin-Azide Agar (BEA) (BioKar Diagnostics, Beauvais, France) and incubated at 44 ºC for 2
h. All the colonies that showed a tan to black colour in the surrounding medium were considered
faecal enterococci.
From the total colonies that were confirmed as faecal enterococci, in each one of the samples,
only five colonies were selected and planted into Tryptic Soy Agar (TSA). From the samples that
was impossible to isolate five colonies the number of colonies confirmed was planted into TSA.
2.3. DNA Extraction and Enterococcus Genotyping
To identify the intestinal enterococci species, DNA from the isolates was extracted and PCR
were performed.
DNA extraction was performed using the GenoLyse Kit (Hain Lifescience BMGH, Germany),
following the manufacturer’s protocol. Briefly, an amount of the culture was resuspended in 50 μL
14
of lysis reagent mixed. After that an incubation for 5 min at 95 ºC in a heating block (Grant
Instruments, United Kingdom) was performed. Then, the same volume of neutralization reagent
(50 μL) was added and mixed by pipetting. Extracted DNA was stored at 4 ºC for 24 h or at -
80 ºC for longer periods.
The primers used for the amplification of ddl genes present in Enterococcus faecalis (ddl E.
faecalis) and Enterococcus faecium (ddl E. faecium) are displayed in the Table 2.
Table 2 - Primers specifications (sequence and size of PCR product) used for identification of
Enterococcus faecalis (ddl E. faecalis) and Enterococcus faecium (ddl E. faecium).
The PCR mixture was composed of 12.5 μL of Master Mix Thermo Scientific Maxima Hot Start
Green PCR Master Mix (Thermo Fisher Scientific, USA), 1 μL of each primer, 5.5 μL of water,
and 5 μL of sample, reaching a final volume of 25 μL.
PCR conditions were 94 ºC for 2 min for the first cycle; 94 ºC for 1 min, 54 ºC for 1 min, and
72 ºC for 1 min for the 30 cycles; and 72 ºC for 10 min for the last cycle. The amplification step
was performed in an Applied Biosystems Veriti thermal cycler (Thermo Fisher Scientific, USA).
PCR products were resolved by electrophoresis on a 2.5 % gel (Seakem LE Agarose, Lonza,
USA) at 65 V. For this procedure, 8 μL of each PCR product and 2 μL of Loading Buffer were
used. In the first well of the agarose gel was added a 100 bp DNA Molecular Weight Marker (New
England Biolabs Inc., England). In all the runs were used positive and negative controls to assure
the quality of the assay. The positive control was accomplished with the addiction of 5 μL of
bacterial suspension to the mix initially prepared (12.5 μL of Master Mix Thermo Scientific Maxima
Hot Start Green PCR Master Mix (Thermo Fisher Scientific, USA), 1 μL of each primer, 5.5 μL of
water). In negative control instead of bacterial suspension was added to the mix initially prepared
5 μL of water. The gel then was transferred to a container with ethidium bromide (Sigma-Aldrich,
USA) where it stayed for 15 min. After that, the gel was observed in a transilluminator (UVITEC,
UK) and the bands identified.
2.4. Antimicrobial Susceptibility Testing
Antimicrobial susceptibility testing was performed on all confirmed Enterococcus isolates. The
isolates that grown overnight in TSA were transferred, with the help of a sterile loop, to Eppendorfs
Amplified gene
Oligodeoxynucleotide Reference
Pair Sequence
(5’-3’)
Size of
PCR
product
(bp) (Dutka-Malen et
al., 1995)
ddl E. faecalis E1 +ATCAAGTACAGTTAGTCT
941 E2 -ACGATTCAAAGCTAACTG
ddl E. faecium F1 +GCAAGGCTTCTTAGAGA
550 F2 - CATCGTGTAAGCTAACTTC
15
with 1 mL of demineralized water to achieve a 0.5 on McFarland scale (standard turbidity). Then,
the bacterial suspension was spread onto Mueller Hinton II Agar (BD, USA).
The disk diffusion method determined antimicrobial resistance patterns, according to the
Clinical and Laboratory Standards Institute (CLSI, 2017). Enterococcus isolates were tested for
their sensitivity to 7 antimicrobial agents: ampicillin (AMP, 10 µg), vancomycin (VAN, 30 µg),
tetracycline (TET, 30 µg), gentamicin (GN, 120 µg), chloramphenicol (C, 30 µg), ciprofloxacin
(CIP, 5 µg) and linezolid (30 µg), all supplied by BD, USA. Plates were incubated overnight at
37°C. After incubation, the diameters of antibiotic inhibition of growth were measured and
recorded as susceptible (S), intermediary (I) or resistant (R). The standards value for each one of
the antibiotics is summarized in the Table 3.
Table 3 - Antimicrobial compounds used in this study and susceptibility values established by
CLSI (2017).
Antimicrobial
agent Disk content
Interpretive Categories and Zone Diameter
Breakpoints (nearest whole mm)
S I R
Ampicillin 10 µg > 17 - ≤ 16
Ciprofloxacin 5 µg ≥ 21 16-20 ≤ 15
Chloramphenicol 30 µg ≥ 18 13-17 ≤ 12
Linezolid 30 µg ≥ 23 21-22 ≤ 20
Vancomycin 30 µg ≥ 17 15-16 ≤ 14
Gentamicin 120 µg ≥ 10 7-9 ≤ 6
Tetracycline 30 µg ≥ 19 15-18 ≤ 14
2.5. Detection of vanA and vanB Genes by PCR
The detection of these two genes was performed in two stages of the experience: with the raw
sample, and in all confirmed vancomycin-resistant Enterococcus by antimicrobial susceptibility
tests.
For the DNA extraction of the raw sample, 1 mL of water sample was concentrated by
centrifugation (12000 rpm, for 10 min) in a benchtop centrifuge (Eppendorf, Germany). The pellet
was used for the DNA extraction, using GenoLyse Kit (Hain Lifescience BMGH, Germany), as
previously described.
The extraction of all confirmed vancomycin-resistant Enterococcus was also made with this
protocol.
For vanA and vanB detection were performed PCRs using specific primers for those genes.
The information about the primers is synthesized in Table 4.
16
Table 4 - Primers specifications (sequence and size of PCR product) used for detection of vanA
and vanB genes.
Amplified gene
Oligodeoxynucleotide Reference
Pair Sequence
(5’-3’)
Size of PCR
product (bp) (Dutka-Malen et
al., 1995)
vanA A1 +GGGAAAACGACAATTGC
732 A2 - GTACAATGCGGCCGTTA
vanB B1 +ATGGGAAGCCGATAGTC
635 B2 -GATTTCGTTCCTCGACC
2.6. Data Analysis
For statistical purposes, an isolate was considered antibiotic-resistant (AR) if it was resistant
to at least one antibiotic and was considered multiantibiotic-resistant (MAR) if it was resistant to
at least two antibiotics. Additionally, isolates showing intermediate resistance to the antimicrobial
compounds tested were considered as resistant.
Statistical analysis was performed on Statistical Package for Social Science (SPSS) software,
version 24 (2017), and Excel 2013. The statistical techniques applied were percentage
frequencies (prevalence) and difference-of-proportion tests. In the choice of statistical techniques,
namely, the proportional difference test, was considered the characteristics of the variables under
study, and the recommendations presented by (Maroco, 2007), (Pestana & Gageiro, 2005) and
(Zar J. H. 1974).
17
3. Results and Discussion
3.1. Prevalence of Enterococcus Species in the WWTPs
Enteric bacteria from human and animal feces, like Enterococcus, can be found in WWTPs
and in natural surface waters. Some of the species can simultaneously be members of intestinal
flora and important clinical isolates, such as E. faecium and E. faecalis. For that reason, in this
work only these two species were identified.
The results of genotyping step (section 2.3) are summarized in the Figures 4 and 5. The
isolates to which were not detected any bands were considered as Enterococcus spp.
In Figure 4 is possible to identify bands around 550 bp, which corresponds to the ddl gene of
E. faecium. On the other hand, in Figure 5, it is possible to identify bands around 941 bp, which
corresponds to the ddl gene of E. faecalis.
1 2 3 4 5 6 7 8
500 bp -
600 bp -
- 550 bp
100 bp -
Figure 4 - PCR for identification of different Enterococcus spp. PCR products
were loaded on 2.5 % agarose gel. 100 bp DNA ladder (lane 1), E. faecium
isolates (lanes 3-6), E. faecium (positive control – lane 7) and negative
control (lane 8).
18
From the culture-based method were obtained 186 Enterococcus isolates, being identified
10.8 % (n = 20) as Enterococcus faecalis, 52.7 % (n = 98) as Enterococcus faecium, and the
remnants 36.6 % (n = 68) were not identified to the species level, being identified as Enterococcus
spp. In the Table 5 and Figure 6, are represented the prevalence of the species in each one of
the WWTPs analysed.
Table 5 – Species prevalence in each one of the WWTPs studied and all of them.
WWTP Species (%)
A B C All
E. faecalis 15.2 5.1 10.9 10.8
E. faecium 54.3 46.2 54.5 52.7
Enterococcus spp 30.4 48.7 34.7 36.6
100 bp -
1 2 3 4 5 6 7 8 9
900 bp -
1000 bp -
- 941 bp
Figure 5 - PCR for identification of different enterococcal spp. PCR products
were loaded on 2.5% agarose gel. 100 bp DNA ladder (lane 1), E. faecalis
isolates (lanes 2, 4, 6 and 7), E. faecalis (positive control – lane 8) and
negative control (lane 9).
19
The abundance of enterococci in human and animal feces, the ease with which they are
cultured, and their correlation with human health make them essential tools for assessing water
quality around the world (Byappanahalli, Nevers, Korajkic, Staley, & Harwood, 2012). For that
reason, besides quantification of fecal enterococci, it is important to determine the Enterococcus
species present in waters to assess potential contamination sources. E. faecium is the most
frequently reported enterococcal species in sewage and other environmental samples, followed
by E. faecalis and E. hirae (Blanch et al., 2003; Talebi et al., 2007; Vilanova, Manero, Cerdà-
Cuéllar, & Blanch, 2004).
The observed distribution of enterococci species corroborates with the findings of
aforementioned studies, being E. faecium the most common specimen found in these sampling
points, with exception of WWTP B.
3.2. Differences in Enterococcus Species Prevalence in the
Treatments Applied in WWTPs
3.2.1. Background
When enterococci are released from gastrointestinal tract into secondary habitats via
households’ wastewater, hospital, and community homes, they are exposed to biotic and abiotic
(temperature, pH, competition) stressors. These stressors usually lead to a decline in the
population over time (Byappanahalli et al., 2012; Łuczkiewicz, Jankowska, Fudala-Ksiazek, &
Olańczuk-Neyman, 2010).
There are some studies where the prevalence of Enterococcus in WWTP was determined, but
in none of them was stablished any relationship between the treatments applied in the plants and
the prevalence of the species. In fact, in 2010, Łuczkiewicz studied the prevalence of E. faecium,
E. hirae and E. faecalis in raw and treated wastewater (Northern Poland) and it was verified that
0
10
20
30
40
50
60
A B C All
Pre
vale
nce
(%
)
WWTP
E. faecalis E. faecium Enterococcus spp
Figure 6 - Species prevalence in the WWTPs studied and the global prevalence.
20
the relative proportion of E. faecium was the same in these two sampling points, whereas the
proportion of E. hirae decreased and the proportion of E. faecalis increased. However, a
relationship between the treatments and the species was not made.
In this study, it was possible to infer if there were any associations between the species studied
and the treatments applied in the WWTPs. Foremost of my knowledge this is the first study to
demonstrate these differences.
3.2.2. Species Prevalence in the Treatments Applied in WWTP A
In WWTP A, the percentage of isolates identified as E. faecalis ranged from 0.0 %
(Disinfection) to 27.3 % (Reused Water). The E. faecium species presented prevalence that
ranged from a minimum of 36.4 % to 90.0 % in Reused Water and Disinfection, respectively.
Enterococcus spp presented higher incidence in Influent (37.5 %) and lowered in Disinfection
(10.0 %) (Table 6, Figure 7).
Table 6 – Species prevalence and p-value in the treatments applied in WWTP A.
The difference-of-proportions test revealed that, in WWTP A, none of the differences observed
were considered as statistically significant (p-value > 0.050), i.e. there is no evidence that, in this
WWTP, the treatments influenced the species present.
Treatment Species (%)
Influent Disinfection Effluent Reused Water
p-value
E. faecalis 12.5 0.0 22.2 27.3 0.325
E. faecium 50.0 90.0 44.4 36.4 0.071
Enterococcus spp 37.5 10.0 33.3 36.4 0.463
0
10
20
30
40
50
60
70
80
90
100
Influent Disinfection Effluent Reused Water
Pre
vale
nce
(%
)
Treatment
E. faecalis E. faecium Enterococcus spp
Figure 7 - Species prevalence in the treatments applied in WWTP A.
21
3.2.3. Species Prevalence in the Treatments Applied in WWTP B
For WWTP B, it was observed that the percentage of isolates identified as E. faecalis ranged
from 0.0% in Reused Water to 10.0 % in other treatments (Influent and Disinfection). E. faecium
showed prevalence between 30.0 % and 52.6 % in Disinfection and Reused Water, respectively.
For Enterococcus spp it was observed percentages between 40.0 % in Influent, and 60.0 % in
Disinfection (Table 7, Figure 8).
Also, in this WWTP, there was no evidence that the prevalence of the three species was
associated with treatments applied (p-value > 0.050).
Table 7 - Species prevalence and p-value in the treatments applied in WWTP B.
3.2.4. Species Prevalence in the Treatments Applied in WWTP C and Natural
Receptors
In WWTP C and Natural Receptors, the prevalence of E. faecalis ranged from 0.0 % in Effluent
to 15.8 % in Disinfection. Percentages of isolates between 31.6 % in Natural Receptor 1 and 78.9
% in Disinfection were recorded for E. faecium. And, finally, Enterococcus spp was identified with
the lowest percentage in the isolates in Disinfection (5.3 %) and the highest in Natural Receptor
2 (55.6 %) (Table 8, Figure 9).
The difference-of-proportions test revealed statistically significant differences in E. faecium (p-
value = 0.031) and Enterococcus spp (p-value = 0.015). Thus, it is possible to affirm that, in this
WWTP, the prevalence of these two species is associated with the type of the treatments.
Treatment Species (%)
Influent Disinfection Reused Water
p-value
E. faecalis 10.0 10.0 0.0 0.367
E. faecium 50.0 30.0 52.6 0.489
Enterococcus spp 40.0 60.0 47.4 0.661
0
10
20
30
40
50
60
70
Influent Disinfection Reused Water
Pre
vale
nce
(%
)
Treatment
E. faecalis E. faecium
Figure 8 - Species prevalence in the treatments applied in WWTP B.
22
Table 8 - Species prevalence and p-value in the treatments applied in WWTP C and Natural Receptors.
Treatment Species (%)
Filtration Disinfection Effluent Natural
Receptor 1
Natural Receptor
2 p-value
E. faecalis 16.7 15.8 0.0 15.8 11.1 0.246
E. faecium 54.2 78.9 60.0 31.6 33.3 0.031 Enterococcus spp 29.2 5.3 40.0 52.6 55.6 0.015
Giving the nature of the results, to increase the accuracy of the assay and to avoid bias, an
overall analysis in all the studies was made. With this strategy, it was possible to evaluate the
association of the treatments ignoring the “WWTP” variable, revealing a complete scenario of
what happens to Enterococcus population during the water treatments. This way, the confidence
in the results will be increased confirming or denying the conclusion obtain for the specific WWTP.
3.2.5. Overall Analysis of the Species Prevalence in the Treatments Applied
in WWTPs
The same study was carried out for the set of three WWTPs allowing to obtain the results
presented in the Table 9 which are represented in the Figure 10.
It was verified that E. faecalis prevalence was between 5.1 % and 16.7 % in the Effluent and
Filtration treatments, respectively. E. faecium isolates were found to be less prevalent in Natural
Receptor 1 (31.6 %) and more commonplace in the treatment Disinfection (69.2 %). For
Enterococcus spp, the percentages of isolates were between 20.5 % in Disinfection and 55.6 %
in Natural Receptor 2.
The differences observed in the percentage of each one of the species isolates were not
considered statistically significant (p-value > 0.050), and for that reason, it was possible to
conclude that the treatments were not associated with the species distribution.
0
10
20
30
40
50
60
70
80
90
Filtration Disinfection Effluent Natural Receptor1
Natural Receptor2
Pre
vale
nce
(%
)
Treatment
E. faecalis E. faecium Enterococcus spp
Figure 9 - Species prevalence in the treatments applied in WWTP C and Natural Receptors.
23
Table 9 - Species prevalence and p-value in the treatments applied in the WWTPs.
In most of the treatments, E. faecium isolates were the ones that showed a higher prevalence,
as also verified in each of the WWTPs studied. Their presence in every sampling and sewage
treatment plant indicate the capability of this microorganism to survive and resist throughout the
treatment.
3.3. Prevalence of Antibiotic-resistant Enterococcus in WWTPs
3.3.1. Background
The presence of antibiotic-resistant bacteria is a substantial public health concern. Usually,
this topic is focused on antibiotic resistance in human clinical isolates and not so often in bacteria
present in aquatic systems. In the environmental risk assessment, it is important to have in
attention the continuous input of resistant-bacteria versus unceasing input of antimicrobial agents,
which their concentrations in waters, such as in wastewaters is significantly lower than therapeutic
uses. However, it is thought that these low concentrations are responsible for the selection of
antibiotic-resistant bacteria, affecting the growth of susceptible ones (Gullberg et al., 2011; S. Kim
& Aga, 2007; Łuczkiewicz et al., 2010).
Most studies on the occurrence of antibiotic-resistant bacteria in WWTPs have been made
using coliforms, such as E. coli. In the past years, several works have been conducted to study
other microorganisms in these environments, such as Acinetobacter (Luca Guardabassi, Wong,
& Dalsgaard, 2002), Staphylococcus aureus (Gómez et al., 2016; M. Ben Said et al., 2017),
Treatment Species (%)
Influent Filtration Disinfection Effluent Natural
Receptor 1
Natural Receptor
2
Reused Water
p-value
E. faecalis 11.5 16.7 10.3 5.1 15.8 11.1 10,0 0.844
E. faecium 50.0 54.2 69.2 56.4 31.6 33.3 46,7 0.134
Enterococcus spp
38.5 29.2 20.5 38.5 52.6 55.6 43,3 0.168
0
10
20
30
40
50
60
70
80
Influent Filtration Disinfection Effluent NaturalReceptor 1
NaturalReceptor 2
Reused Water
Pre
vale
nce
(%
)
Treatment
E. faecalis E. faecium Enterococcus spp
Figure 10 - Species prevalence in the treatments applied in the WWTPs.
24
Pseudomonas aeruginosa (Slekovec et al., 2012) and Enterococcus (Anderson, Turner, & Lewis,
1997; Martins da Costa, Vaz-Pires, & Bernardo, 2006).
When pathogenic Enterococcus are present in aquatic environments and, the water is used
for drinking, recreational activities, or irrigation a possible scenario of disease may occur. This
scenario worsens if these pathogenic bacteria present in waters are antibiotic-resistant (Servais
& Passerat 2009). It is generally assumed that hospital effluents are the main source for the input
of antibiotics and ARB into municipal sewers and natural environments (Kümmerer, 2004;
Martinez, 2009). Nevertheless, it is possible to detect resistant bacteria in municipal wastewaters.
Due to the domestic use of antibiotics, taken as prophylactic therapy, and their misuse, their
release is much higher when compared to hospital effluents (Kümmerer, 2004). Thus, the
community is responsible for the main input of ARB into sewage. On the other hand, hospital
effluents profoundly affect the presence of multiantibiotic-resistant bacteria. Quantitatively,
hospital wastewaters are the main source for the spread into aquatic environments of
multiantibiotic-resistant bacteria (Servais & Passerat, 2009).
In 2009, Servais and Passerat concluded that depending on the main source of faecal
contamination the levels of AR can vary greatly, being municipal and hospital wastewaters, the
places were these percentages are higher whereas non-point sources from agricultures areas
and from forest areas were the places where AR and MAR prevalence was lower.
An additional problem is introduced which regards these pathogenic antibiotic-resistant enteric
bacteria. Some of these faecal bacteria might be able to transmit the genes responsible for the
resistance to a specific antibiotic autochthonous bacterium through lateral transfer, when
plasmids or transposons carry these genes. Actual work supports the thesis of horizontal genes
transfer under wastewater treatment plants. Some conditions, like high density of cells (in
activated sludges, for example), are regarded as factors promoting the growth and dissemination
of resistance among bacteria (Łuczkiewicz et al., 2010). The information available regarding the
presence of ARB and their possible interaction, in terms of changes in resistance genes,
emphasises the importance of the control and monitorization of susceptible environments, such
as WWTPs.
In the next section the results referring to percentage of resistant isolates (ignoring the species
identified) for each of one the antibiotics studied throughout the treatments applied in the WWTPs
will be presented.
3.3.2. Antibiotic-specific Resistance in the Treatments Applied in WWTP A
The data presented in Table 10 and illustrated in Figure 11 demonstrate the percentage of
resistant isolates for each of one the antibiotics throughout the treatments applied in WWTP A.
As it turns out the percentage of AMP resistance lies between 10.0 % (Disinfection) and 33.3 %
(Effluent). For CIP, there was a decrease in the rate of resistance throughout the WWTP
treatments, with the highest value in Influent (100.0 %) and the lowest in Reused Water (81.8 %).
25
For C, resistance values were found between 12.5 % in Influent and 55.6 % in Effluent. For
LNZ, resistance percentages were observed between 45.5 % in Reused Water and 77.8 % in
Effluent. The proportion of TET-resistant isolates is lower in Disinfection (40.0 %) and higher in
Effluent (66.7 %). The same situation was observed in VAN resistance, with the percentages of
isolates resistant to this antibiotic between 20.0 % and 55.6 %. Relative to GM, no resistance was
observed in all treatments of this WWTP, except in Influent where the percentage was 6.3 %.
The application of difference-of-proportion test revealed a p-value higher than 0.050, so none
of the differences observed in the percentages of resistant isolates among WWTP A treatments
can be considered statistically significant.
Table 10- Comparison of antibiotic resistance (%) in WWTP A and respective p-values.
Treatment Antibiotic
Influent Disinfection Effluent Reused Water
p-value
Ampicillin (AMP) 18.8 10.0 33.3 18.2 0.640
Ciprofloxacin (CIP) 100.0 90.0 88.9 81.8 0.414
Chloraphenicol (C) 12.5 40.0 55.6 27.3 0.133
Linezolid (LNZ) 56.3 50.0 77.8 45.5 0.498
Tetracycline (TET) 43.8 40.0 66.7 63.6 0.496
Vancomycin (VAN) 25.0 20.0 55.6 36.4 0.338
Gentamicin (GM) 6.3 0.0 0.0 0.0 0.590
0
10
20
30
40
50
60
70
80
90
100
Influent Disinfection Effluent Reused Water
Res
ista
nt
(%)
Treatment
AMP CIP C LNZ TET VAN GM
Figure 11 - Resistance to each one of the antibiotics in the treatments applied in WWTP A.
26
3.3.3. Antibiotic-specific Resistance in the Treatments Applied in WWTP B
A similar study was carried out for WWTP B with the results summarised in the Figure 12. The
percentage of resistance to AMP in this WWTP showed an increase throughout the treatment
process, i.e., it was lower in Influent (10.0 %) and higher in Reused Water (21.1 %). The
percentage value of isolates resistant to CIP tended to remain almost constant throughout the
three treatments, varying their values between 80.0 % and 89.5 %. The percentage of C-resistant
isolates was increased during the treatment process, with the lowest value for Influent (20.0 %)
and the highest for Reused Water (63.2 %). The resistance to LNZ was the only situation in which
there was a statistically significant difference (p-value = 0.020), with the percentage of resistance
being the lowest in Disinfection (30.0 %) and highest in the Reused Water (78.9 %). For TET
resistance, the proportion of resistant isolates was lower in Reused Water (26.3 %) and higher in
Disinfection (60.0 %). The rates of VAN resistant were between 20.0 % in Influent and 47.2 % in
Reused Water. Finally, it was found that in this WWTP no isolates were resistant to GM.
Table 11 - Comparison of antibiotic resistance (%) in WWTP B and respective p-values.
Treatment Antibiotic
Influent Disinfection Reused Water
p-value
Ampicillin (AMP) 10.0 20.0 21.1 0.748
Ciprofloxacin (CIP) 80.0 80.0 89.5 0.715
Chloraphenicol (C) 20.0 40.0 63.2 0.077
Linezolid (LNZ) 40.0 30.0 78.9 0.020
Tetracycline (TET) 30.0 60.0 26.3 0.180
Vancomycin (VAN) 20.0 40.0 47.4 0.352
Gentamicin (GM) 0.0 0.0 0.0 1.000
27
3.3.4. Antibiotic-specific Resistance in the Treatments Applied in WWTP C
and Natural Receptors
For WWTP C and respective Natural Receptors, the data presented in Table 12, which are
illustrated in Figure 13 demonstrates that the percentage of isolates resistant to AMP ranged from
0.0 % in Natural Receptor 2 to 36.8 % in Natural Receptor 1. For the CIP antibiotic, percentages
of resistance were between 66.7 %, in Natural Receptor 1, and 90.0 % in Effluent. Resistance to
antibiotic C showed a behaviour almost opposite to that observed for CIP, that is, the lowest
percentage of Effluent resistant (30.0 %) and the highest in Natural Receptor 1 (57.9 %).
Concerning the antibiotic LNZ, it was observed that the percentage of resistance was very similar
in the various treatments, with values between 44.4 % in Natural Receptor 1 and 57.9 % in
Disinfection. Resistance to TET varied between 22.2 % in Natural Receptor 1 and 75.0 % in
Filtration. It was verified that the percentage of isolates resistant to VAN was between 21.1 % and
44.4 in the treatments Disinfection and Natural Receptor 2, respectively. Resistance to the GM
antibiotic was null in all treatments except for the Effluent where it was 3.3 %.
In this WWTP, there were statistically significant differences in resistance to antibiotics AMP
(p-value = 0.023) and TET (p-value = 0.002). This fact allowed to state that, for WWTP C, the
resistance to these two antibiotics was significantly affected by the treatments. In order to confirm
this information an overall analysis was made (section 3.3.5).
0
10
20
30
40
50
60
70
80
90
100
Influent Disinfection Reused Water
Res
ista
nt
(%)
Treatment
AMP CIP C LNZ TET VAN GM
Figure 12- Resistance to each one of the antibiotics in the treatments applied in WWTP B.
28
Table 12 - Comparison of antibiotic resistance (%) in WWTP C and Natural Receptors and respective p-values.
Treatment Antibiotic
Filtration Disinfection Effluent Natural
Receptor 1
Natural Receptor
2 p-value
Ampicillin (AMP) 12.5 10.5 6.7 36.8 0.0 0.023
Ciprofloxacin (CIP) 91.7 100.0 90.0 94.7 66.7 0.065
Chloraphenicol (C) 33.3 31.6 30.0 57.9 33.3 0.327
Linezolid (LNZ) 45.8 57.9 50.0 47.4 44.4 0.939
Tetracycline (TET) 75.0 36.8 56.7 84.2 22.2 0.002
Vancomycin (VAN) 25.0 21.1 23.3 26.3 44.4 0.742
Gentamicin (GM) 0.0 0.0 3.3 0.0 0.0 0.664
3.3.5. Overall Analysis of the Antibiotic-specific Resistance in the Treatments
Applied in WWTPs
The same study was developed, considering the set of the three WWTPs, having obtained the
results presented in Table 13 and illustrated in Figure 14. As can be seen, the percentage of
AMP-resistant isolates ranged from a minimum of 0.0 % in Natural Receptor 1 to 36.8 % in Natural
Receptor 2. For CIP, resistance percentages ranged from 66.7 % in Natural Receptor 2 and 94.7
% in Natural Receptor 1. In the antibiotic C, percentages of resistance were registered between
15.4 % and 57.9 % in the Influent and Natural Receptor 1 treatments, respectively. The rate of
isolates resistant to the antibiotic LNZ showed a small variation in the various treatments, with a
minimum value of 44.4 % in Natural Receptor 2 and 56.4 % in Effluent. The percentage of TET-
resistant isolates was between 22.2 % (Natural Receptor 2) and 84.2 % (Natural Receptor 1).
The observed differences were statistically significant (p-value = 0.001), indicating that this
antibiotic is significantly associated with the type of treatment. For the VAN antibiotic resistance
0
10
20
30
40
50
60
70
80
90
100
Filtration Disinfection Effluent Natural Receptor1
Natural Receptor2
Res
ista
nt
(%)
Treatment
AMP CIP C LNZ TET VAN GM
Figure 13 - Resistance to each one of the antibiotics in the treatments applied in WWTP C and Natural Receptors.
29
percentages were observed between 23.1 % and 44.4 % for Influent and Natural Receptor 2,
respectively. For the GM antibiotic, very low percentages of resistant isolates were found, with
values ranging from 0.0 % to 3.8 %.
Table 13 - Comparison of antibiotic resistance (%) in WWTPs and respective p-values.
The previous results highlight the necessity to assure the quality control of the various
treatments applied in WWTPs to avoid possible disease scenarios in the future.
It was found that in each WWTP studied individual and in the overall analysis, the percentage
of resistant isolates was higher to the CIP antibiotic in all treatments. CIP showed higher levels
of resistance compared to previous reports (Łuczkiewicz et al. 2010; Martins da Costa et al. 2006;
Moore et al. 2008). Although the results sound alarming, it is important to have in consideration
that (as stated in section 2.6) all the intermediate-resistant phenotypes were considered as
resistant to the antibiotic. In case of CIP antibiotic, most of the isolates showed an intermediate-
resistant phenotype and not resistant.
The overall analysis showed that tetracycline resistance was the phenotype positively selected
by the treatments, having been observed an apparent increase of resistance over the treatments.
Tetracycline is one of the most used antibiotics in human and animal medicine and it is also used
as a growth promoter. This antibiotic has a hydrophilic character allowing it to be found ad persist
Treatment Antibiótico
Influent Filtration Disinfe-
ction Effluent
Natural Receptor
1
Natural Receptor
2
Reused Water
p-value
Ampicillin (AMP) 15.4 12.5 12.8 12.8 36.8 0.0 20,0 0.176
Ciprofloxacin (CIP) 92.3 91.7 92.3 89.7 94.7 66.7 86,7 0.358
Chloraphenicol (C) 15.4 33.3 35.9 35.9 57.9 33.3 50,0 0.083
Linezolid (LNZ) 50.0 45.8 48.7 56.4 47.4 44.4 66,7 0.703
Tetracycline (TET) 38.5 75.0 43.6 59.0 84.2 22.2 40,0 0.001
Vancomycin (VAN) 23.1 25.0 25.6 30.8 26.3 44.4 43,3 0.571
Gentamicin (GM) 3.8 0.0 0.0 2.6 0.0 0.0 0,0 0.676
0
10
20
30
40
50
60
70
80
90
100
Influent Filtration Disinfection Effluent NaturalReceptor 1
NaturalReceptor 2
ReusedWater
Resis
tan
t (%
)
Treatement
AMP CIP C LNZ TET VAN GM
Figure 14 - Resistance to each one of the antibiotics in the treatments applied in the WWTPs.
30
in aquatic environments, such as WWTPs. Tetracycline presence in waters can exert a selective
pressure in bacteria that possess the resistance gene for this antibiotic, leading to the expression
of not only the gene associated with this resistance but additionally, the expression of other genes
that confer the ability to resist to the treatments applied in WWTPs (Daghrir & Drogui, 2013). Up
to now, wastewater treatment plants are not capable of removing the tetracycline antibiotic
effectively (Tehrani & Gilbride, 2018).
It is known that antibiotic resistance determinants can be present in replicons that contain
other selectable markers as heavy metal resistance, production of siderophores or resistance to
other pollutants. Thus, biocides and detergents, which are commonly found in WWTPs can select
resistant strains as the consequence of the presence of those genes or the presence of MDR
determinants (Alonso, Sánchez, & Martínez, 2001). Resistance to tetracycline, for example, can
be coded for more than 40 determinants (Tehrani & Gilbride, 2018). This can be an ecological
advantage to the bacteria leading to the colonisation of environmental habitat and the spread of
these antibiotic-resistant bacteria.
Thus, the results obtained corroborate with findings elsewhere mentioned, proving that the
prevalence of tetracycline-resistants’ increases over the treatments.
3.4. The Resistance of the Species to Vancomycin in the WWTPs
Vancomycin-resistant enterococci are both medical and public health issues associated with
severe multidrug-resistant infections and persistent colonisation. The release of these bacteria to
the environments is hazardous since animals or humans in contact with them can act as
reservoirs and later transmit them into susceptible individuals. For that reason, it is imperative to
monitor their presence and study their epidemiology.
In this work the association between the resistance of the species to the vancomycin was
analysed in each WWTP and the global, being the results presented in Table 14 and Figures 15
and 16.
In WWTP A, the percentage of isolates resistant to that antibiotic was lower for Enterococcus
spp (21.4 %) and higher for E. faecalis (85.7 %). The differences between these percentages
were statistically significant (p-value = 0.005). For that reason, is possible to assume that an
association, in WWTP A, between resistance to vancomycin and the species identified was
established. The analysis of the multiples percentages of resistance allowed the detection of an
association between the species E. faecalis and the vancomycin antibiotic.
For WWTP B, resistance percentages were observed between 36.8 % in Enterococcus spp
and 50.0 % in E. faecalis. The differences showed were not statistically significant, i.e. in this
WWTP, there was no association between the studied species and the antibiotic.
In WWTP C, there were proportions of isolates resistant to vancomycin between 14.5 % in E.
faecium and 54.5 % in E. faecalis. Since there is a statistically significant difference between the
percentages of resistance (p-value = 0.008), we can state a significant association between
resistance to the VAN and the species identified.
31
The study developed for the three WWTPs allowed to obtain the percentages of resistance to
the antibiotic between 21.4 % in E. faecium and 65.0 % in E. faecalis. Since there was a
statistically significant difference between these percentages (p-value < 0.001), a significant
association between vancomycin resistance and the species studied was confirmed. Once again,
there was identified an association between E. faecalis and vancomycin.
Table 14 – Prevalence of vancomycin-resistance (%) for species of Enterococcus in each one of the WWTPs and p-value associated.
Species WWTP
E. faecalis E. faecium Enterococcus spp p-value
A 85.7 24.0 21.4 0.005 B 50.0 38.9 36.8 0.935 C 54.5 14.5 34.3 0.008
Global 65.0 21.4 32.4 <0.001
0
10
20
30
40
50
60
70
80
90
E. faecalis E. faecium Enterococcus spp
VA
N-R
esis
tan
t (%
)
Species
WWTP A WWTP B WWTP C
Figure 15 - Distribution of vancomycin-resistance for species Enterococcus in each one of the WWTPs.
32
The obtained results met our expectations since E. faecalis resistant to vancomycin are the
most common isolates found in the community, farm animals and food products (Ahmed &
Baptiste, 2017), in contrary to VREfaecium.
3.4.1. The Occurrence of Vancomycin-resistance Genes in Raw Water
Samples and VRE Confirmed Isolates by Disk Diffusion Method
PCR is an universal method widely used in detection and typing of bacterial systems (Belkum
et al., 2007). In this work, this technique was performed for the detection of two genotypes of
vancomycin resistance (vanA and vanB genes).
After PCR, none of the raw water samples presented vanA and/or vanB genes. Additionally,
neither one of the VRE isolates were detected the previously mentioned genes. Although these
results agree with each other, they are not conclusive about the possible existence of
glycopeptide-resistance genes in the WWTPs studied. The results obtained do not corroborate
previous studies where these genes were detected after all of the treatment processes at sewage
treatment plants and in some cases with very high concentration levels (Furukawaa, Hashimotoa,
& Mekatab, 2015; Kühn et al., 2005; Schwartz, Thomas; Kohnen, Wolfgang; Jansen, Brend; Obst,
2003).
The glycopeptide resistance in enterococci is both phenotypically and genotypically
heterogeneous (Fines, Perichon, Reynolds, Sahm, & Courvalin, 1999; Perichon, Reynolds, &
Courvalin, 1997). These differences could be due to the different ecological origins of the van
clusters (Guzman Prieto et al., 2016), being this a possible explanation for the absence of the
vanA and vanB genes in the WWTPs analysed. Furthermore, a previous study, conducted in
Portugal, detected 17 VRE isolates in a WWTP in which 9 of them were vanC1/vanC2-containing
Enterococcus gallinarum/casseliflavus (Araújo et al., 2010). In this study vanC1/vanC2 genes
0
10
20
30
40
50
60
70
E. faecalis E. faecium Enterococcus spp
VA
N-
Res
ista
nt
(%)
Species
Figure 16 – Percentages of resistance for vancomycin in each species of Enterococcus.
33
showed higher prevalence than vanA and vanB genes. So, the absence of the latter ones could
be related with the characteristics of the bacterial community at those specific geographical areas,
for instances. Additionally, the low concentration amount that could be present in the sample did
not allow the detection of those genes.
As stated in the introduction the vanA genotype is the most frequent in Europe (Werner et al.,
2008) having significant importance in the pathogenicity of the enterococci. Although, the genes
associated with this resistance were not found, VRE isolates were detected by the disk diffusion
method. For that reason, the continuous monitorization of ARB and ARG in the environment to
implement it is imperative new or different strategies to control the dissemination of those within
hospitals or the community.
3.5. Multiresistance in the Treatments of the WWTPs
3.5.1. Background
The antibiotics used in prevention or treatment of human and animal infections and the ones
that are used as growth promoters of livestock are partially metabolized, being discharged after
their action, with excreta to sewage or directly to natural environments. These compounds can
modify the dynamics and the physiology of environmental microbiota, leading to changes in their
composition such as the selection of resistant mutants in susceptible species, or the possibility of
HGT between bacteria. The modifications are associated with the presence of sub-inhibitory
concentrations of antibiotics, that trigger specific transactional responses in bacteria (Martinez
2009; Yim et al. 2017).
However, in WWTPs are applied treatments that help in the reduction or complete elimination
of antibiotics and ARB. Nonetheless, some authors suggest that the susceptible population to
antibiotics and the resistant population are not equally affected by the treatments (Sharma et al.
2016; Guardabassi et al. 2002). It is often assumed that antibiotic resistance confers a metabolic
burden to ARB. Thus, the presence of these genes can confer ecological disadvantages leading
to the decrease of antibiotic-resistant-bacteria comparing to non-resistant-bacteria. Oppositely to
what was stated above, there are some cases where a presence of resistance genes enhances
the persistence of resistant strains because the genes don’t have a fitness cost for bacteria
(Björkman & Andersson 2000).
For that reason, it was hypothesized that MAR might be associated with the treatments applied
in WWTPs, being this theory studied in this work and the results presented in the following section.
3.5.2. Multiresistance in WWTP A
The analysis of the data presented in Table 15 and in the Figure 17 show the evaluation in the
proportions of multiresistance observed in each treatment of WWTP A. The percentage of MAR
was between 62.5 % in the Influent and 88.9 % in the Effluent.
There was an apparent increase of MAR throughout the treatments, but the differences were
not statistically significant (p-value > 0.050). This fact allows to state that, in this WWTP, MAR
were not associated with the studied treatments.
34
Table 15 - Percentage and p-value of the comparison of the multiresistance in WWTP A.
3.5.3. Multiresistance in WWTP B
A similar situation for WWTP B was identified, i.e. the percentage of MAR tended to increase
throughout the treatments of this WWTP, with values ranging between 70.0 % in Influent and 89.5
% in Reused Water. Once again, the differences were not statistically relevant (p-value > 0.050),
and so there is no evidence that the MAR ratio is associated with the applied treatments.
Table 16 - Percentage and p-value of the comparison of the multiresistance in WWTP B.
Treatment Influent Disinfection Reused Water
p-value
MAR (%) 70.0 80.0 89.5 0.422
Treatment Influent Disinfection Effluent Reused Water
p-value
MAR (%) 62.5 70.0 88.9 81.8 0.464
0
10
20
30
40
50
60
70
80
90
100
Influent Disinfection Effluent Reused Water
MA
R (
%)
Treatment
Figure 17 – Proportion of MAR in the treatments applied in WWTP A.
35
3.5.4. Multiresistance in WWTP C and Natural Receptors
For WWTP C and Natural Receptors, the percentage of MAR was between 44.4 % in Natural
Receptor 2 and 89.5 % in Disinfection and in Natural Receptor 1. In this WWTP the observed
differences were statistically significant (p-value = 0.009). In conclusion, the proportion of MAR is
related to treatment applied.
Table 17 - Percentage and p-value of the comparison of the multiresistance in WWTP C and Natural Receptors.
Treatment Filtration Disinfection Effluent Natural
Receptor 1
Natural Receptor
2 p-value
MAR (%) 87.5 89.5 63.3 89.5 44.4 0.009
0
10
20
30
40
50
60
70
80
90
100
Influent Disinfection Reused Water
MA
R (
%)
Treatment
Figure 18 - Proportion of MAR in the treatments applied in WWTP B.
0
10
20
30
40
50
60
70
80
90
100
Filtration Disinfection Effluent Natural Receptor 1 Natural Receptor 2
MA
R (
%)
Treatment
Figure 19 - Proportion of MAR in the treatments applied in WWTP C and Natural Receptors.
36
3.5.5. Overall Analysis of Multiresistance in WWTPs
In the overall analysis, were observed percentages of MAR ranging from 44.4 % in Natural
Receptor 1 to 87.5 % in Filtration. The difference-of-proportions test revealed that the differences
observed were statistically significant (p-value = 0.028). For that reason, it was possible to
conclude that the percentages of MAR were associated with the treatments performed.
Table 18 - Percentage and p-value of the comparison of the multiresistance in the WWTPs.
Treatment Influent Filtration Disinfection Effluent Natural
Receptor 1
Natural Receptor
2
Reused Water
p-value
MAR (%) 65.4 87.5 82.1 69.2 89.5 44.4 86.7 0.028
Taking into consideration that the value of MAR increased over the treatments it was possible
to identify a positive selection of these organisms in WWTPs.
As discussed in the previous sections, many of the resistance genes are found in mobile
genetic determinants that carry resistance to other antibiotics and/or metals. It was found that
bacteria with a single resistance gene to tetracycline are more likely to have resistance to multiple
antibiotics (Tehrani & Gilbride, 2018). The information suggests that this specific resistance could
be acquired as a cassette containing several determinants that promote resistance to different
antibiotics simultaneously. In the end, it seems that the data complements itself, being the positive
selection of TET-resistant Enterococcus in agreement with the increase of MAR throughout the
treatments applied.
The data showed a worrisome scenario where similar WWTPs may act as selectors of MAR,
leading to the spread of these organisms into environmental waters. For that reason, the
monitorization and control of WWTPs are mandatory to assure the public health safety.
0
10
20
30
40
50
60
70
80
90
100
Influent Filtration Disinfection Effluent NaturalReceptor 1
NaturalReceptor 2
Reused Water
MA
R (
%)
Treatment
Figure 20 – Proportion of MAR in the treatments applied in WWTPs.
37
3.6. Analysis of the Multiresistance in the Treatments and the Species
Identified in the WWTPs
A positive selection of multiantibiotic-resistant Enterococcus was confirmed between the
treatments applied in the WWTPs. To establish an association between the multiresistance and
the two species studied, a study identical to the ones previously showed was performed.
3.6.1. MAR vs Species Identified in WWTP A
After the analysis of the results, referring to WWTP A (Table 19 and Figure 21), it is possible
to verify that in the Influent the MAR presented values of 66.7 % for Enterococcus spp and 100.0
% in E. faecalis. In Disinfection, the species E. faecalis was not identified and the percentages of
MAR in the remaining two species varied between 0.0 % in Enterococcus spp and 77.8 % in E.
faecium. In Effluent, the MAR ratio was lower for the species Enterococcus spp (66.7 %) and
higher for the other two species, E. faecalis and E. faecium, both with 100.0 %. For Reused Water
a similar situation was observed, the lowest percentage of MAR was registered for Enterococcus
spp (50.0 %) and the highest occurred in the species E. faecalis and E. faecium (100.0 %).
There was no evidence that, in WWTP A, an association between the MAR observed in the
treatments and the species identified (p-value > 0.050) existed.
Table 19 - Percentage and p-value of the comparison of the multiresistance of the species in WWTP A.
*n.d. – not determined
Species Treatment (MAR)
E. faecalis E.
faecium Enterococcus
spp p-value
Influent 100.0 50.0 66.7 0.411
Disinfection n.d. * 77.8 0.0 0.107
Effluent 100.0 100.0 66.7 0.325
Reused Water 100.0 100.0 50.0 0.118
0
10
20
30
40
50
60
70
80
90
100
E. faecalis E. faecium Enterococcus spp
MA
R (
%)
Species
Influent Disinfection Effluent Reused Water
Figure 21 - Distribution of multiresistant species throughout the treatment of the WWTP A.
38
* n.d. – not determined
3.6.2. MAR vs Species Identified in WWTP B
In WWTP B, it was found that the percentages of MAR in Influent were 0.0 % for E. faecalis
species and 100.0 % for Enterococcus spp. The prevalence of MAR in Disinfection presented
lower percentage in Enterococcus spp (66.7 %) and higher in E. faecalis and E. faecium (both
with 100.0 %). In Reused Water E. faecalis was not identified and the percentages of MAR in the
other two species ranged from 88.9 % for Enterococcus spp and 90.0 % for E. faecium.
Also, in this WWTP there were no statistically significant differences detected (p-value >
0.050), so it was concluded that the data did not show a significant association between
treatments and species regarding MAR.
Table 20 - Percentage and p-value of the comparison of the multiresistance of the species in WWTP B.
Species Treatment (MAR)
E. faecalis E. faecium Enterococcus
spp p-value
Influent 0.0 60.0 100.0 0.117
Disinfection 100.0 100.0 66.7 0.435
Reused Water n.d. * 90.0 88.9 0.937
3.6.3. MAR vs Species Identified in WWTP C and Natural Receptors
In WWTP C and respective Natural Receptors, the percentage of MAR in the Filtration process
was lower for E. faecium (84.6 %) and higher for E. faecalis (100.0 %). In Disinfection,
percentages of MAR varied between 86.7 % in E. faecium and 100.0 % in E. faecalis and
Enterococcus spp. In Effluent the species E. faecalis were not identified and the percentages of
MAR in the remaining two species were 58.3 % and 66.7 % for Enterococcus spp and E. faecium,
respectively. For Natural Receptor 1, percentages of MAR between 83.3 % for E. faecium and
0
10
20
30
40
50
60
70
80
90
100
E. faecalis E. faecium Enterococcus spp
MA
R (
%)
Species
Influent Disinfection Reused Water
Figure 22 - Distribution of multiresistant species throughout the treatment of the WWTP B
39
* n.d. – not determined
100.0 % for E. faecalis were recorded. Finally, in the Natural Receptor 2, the percentages of MAR
varied between 0.0 % in E. faecalis and E. faecium, and 80.0 % in Enterococcus spp.
In none of the treatment’s differences statistically significant (p-value > 0.050) were observed
and so, as in the other two WWTPs, it was possible to conclude that the data did not reveal any
association between treatment and species concerning MAR.
Table 21 - Percentage and p-value of the comparison of the multiresistance of the species in WWTP C treatments and in Natural Receptors.
Species Treatment (MAR)
E. faecalis E. faecium Enterococcus spp p-value
Filtration 100.0 84.6 85.7 0.708 Disinfection 100.0 86.7 100.0 0.742
Effluent n.d.* 66.7 58.3 0.643 Natural Receptor 1 100.0 83.3 90.0 0.742 Natural Receptor 2 0.0 0.0 80.0 0.056
3.6.4. Overall Analysis MAR vs Species Identified in the WWTPs
The same study was developed for all the three WWTPs, revealing that in the Influent
treatment the percentages of MAR ranged from 53.8 % in E. faecium to 80.0 % in Enterococcus
spp. In the Filtration process a lower ratio of MAR to E faecium (84.6 %) and higher for E. faecalis
(100.0 %) was observed. In the Disinfection stage, the percentage values of MAR ranged between
62.5 % in Enterococcus spp and 100.0 % in E. faecalis. A similar situation was observed in the
Effluent, in which the lowest percentage of MAR occurred in Enterococcus spp (60.0 %) and the
highest was recorded for E. faecalis (100.0 %). In the Natural Receptor 1, MAR percentages
between 83.3 % in E. faecium species and 100.0 % in E. faecalis were observed. For Natural
Receptor 2, percentage values were 0.0 % in E. faecalis and E. faecium, and 80.0 % in
0
10
20
30
40
50
60
70
80
90
100
E. faecalis E. faecium Enterococcus spp
MA
R (
%)
Species
Filtration Disinfection Effluent Natural Receptor 1 Natural Receptor 2
Figure 23 - Distribution of multiresistant species throughout the treatment of the WWTP C and Natural Receptors.
40
Enterococcus spp. In the Reused Water, MAR percentages were 76.9 % for Enterococcus spp
and 100.0 % for E. faecalis.
Having in consideration all the treatments applied, it was found that overall, the proportion of
MAR was lower for Enterococcus spp (75.0 %) and higher for E. faecalis (90.0 %).
Table 22 - Percentage and p-value of the comparison of the multiresistance of the species in WWTPs
Species Treatment (MAR)
E. faecalis E. faecium Enterococcus spp p-value
Influent 66.7 53.8 80.0 0.425
Filtration 100.0 84.6 85.7 0.708
Disinfection 100.0 85.2 62.5 0.209
Effluent 100.0 72.7 60.0 0.446
Natural Receptor 1 100.0 83.3 90.0 0.742
Natural Receptor 2 0.0 0.0 80.0 0.056
Reused Water 100.0 92.9 76.9 0.369
All 90.0 76.5 75.0 0.353
Neither one of the WWTPs studied individually or as a group presented differences statistically
significant (p-value > 0.050). This fact allowed to state, again, that the data did not show the
existence of a statistical association between the proportions of MAR and the studied species.
0
10
20
30
40
50
60
70
80
90
100
E. faecalis E. faecium Enterococcus spp
MA
R (
%)
Species
Influent Filtration Disinfection Effluent
Natural Receptor 1 Natural Receptor 2 Reused Water All
Figure 24 - Distribution of multiresistant species throughout the treatments in the WWTPs.
41
4. Conclusion
The antibiotic-resistant enterococci group were investigated in three different WWTPs in
Lisbon, Portugal. Seven different antibiotics were tested in isolates from different treatments
applied in all the WWTPs studied. The identification at the species level for Enterococcus faecium
and Enterococcus faecalis, using the PCR method, was also performed. With this work was
possible to infer some conclusions about the effects of treatments of the WWTPs in Enterococcus
antibiotic-resistant population.
As expected, E. faecium was the most prevalent species identified in WWTPs, with prevalence
ranging 53 %. It was also showed that the treatments did not select a specific species since it
was not demonstrated differences considered statistically significant in the overall analysis.
The treatments applied in WWTPs are responsible for the dissemination of some antibiotic
phenotypes. As confirmed in the overall analysis the treatments positively select the tetracycline-
resistance phenotype.
Although there was no detection of van genes, it was possible to detected vancomycin-
resistant Enterococcus using antimicrobial susceptibility tests. Additionally, the results showed
that the resistance to this antibiotic is associated with E. faecalis. The results obtained are with in
agreement with previous studies where Vancomycin-resistant E. faecalis were more common in
the community than E. faecium.
Finally, was verified that the treatments positively select multiantibiotic-resistant bacteria,
being demonstrated a trend for the increase of MAR throughout the treatments. However, the
selection of MAR is not related with the species of the microorganisms.
Taking in consideration the results obtained it is essential to keep monitoring the presence
and abundance of antibiotic-resistant bacteria in the WWTPs (to see the efficacy of the
treatments) and natural receptors (such as water environments) because there are many gaps in
matters related to antibiotic resistance.
To conclude it is challenging for a country or organization to address the emergence and
adequately expansion of antibiotic resistance. Active surveillance is the key to control and
understand the spread of resistant-capabilities. The long-term consequences of the spread of
antibiotics and resistance genes cannot be predicted without quantitative analysis over right
timescales. The antimicrobial resistance surveillance system should be able to track and identify
antibiotic resistance trends over long-term timescales (Masterton, 2000). Later, with the data
obtained it should be possible to create databases for physicians and scientists. This data would
be helpful for healthcare professionals and to assist governments in crisis scenarios. In that way,
this work reinforces the need to control and prevent the spread of resistant-bacteria and endorses
the need for more surveillance programmes integrated longitudinally as part of national,
international, and institutional studies.
42
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51
Appendix
Table 23 - Antibiotics classification according to how they attack bacteria and their chemical
shape. It is also enumerated some example (s).
Antibiotics class
Example (s) How they
attack bacteria
Chemical shape
Cell wall synthesis inhibition
β-lactams
Penicillins
Natural penicillins:
Penicillin G, Penicillin V
Penicillinase-resistant
penicillins:
Methicillin, Nafcillin, Oxacillin, Dicloxacillin
Broad-spectrum:
Ampicillin, amoxicillin
Extended-spectrum:
Ticarcillin, Piperacillin, Mezlocillin, Carbenicillin
Cephalosporins
First-Generation:
Cefazolin, Cephalexin, Cefadroxil,
Cephalothin
Second-Generation:
Cefuroxime, Cefoxitin, Cefotetan,
Cefmetazole
Third-Generation:
Ceftriaxone, Cefotaxime, Ceftazidime,
Cefdinir
Fourth-Generation:
Cefepime
Fifth-Generation:
Ceftaroline, Ceftobiprole
Carbapenems: Imipenem, Meropenem, Doripenem, Ertapenem
Monobactams: Aztreonam
Glycopeptides Vancomycin, Teicoplanin
Polypeptides Bacitracin
Protein synthesis inhibition
Aminoglycosides Gentamicin, Streptomycin, Kanamycin
Tetracyclines Tetracycline
Chloramphenicol Chloramphenicol
Macrolides Erythromycin; Clarithromycin
Lincosamides Clindamycin
Oxazolidinones Linezolid
Streptogramins Quinupristin, Dalfopristin
Nucleic acid synthesis inhibition
Fluoroquinolones Ciprofloxacin
Rifamycins Rifampin
52
Wastewater Treatment Plant A
Table 24 – Characterization of the isolates collected from WWTP A. It is possible to distinguish 4
different types of treatment: Influent, Disinfection, Effluent and Reused water. All the isolates were
identified using PCR and cultured-based techniques. In Zone Diameter (mm) section it is possible
to distinguish the 7 antibiotics used, and the diameter of the inhibition zones. According to these
measurements, the isolates were sorted as susceptible (green), intermediate (orange), and
resistant (red).
Zone Diameter (mm)
Isolate AMP CIP C LNZ TET VAN GM Treatment
Species’ Identification
LAIST_001 22 18 14 22 20 16 16 Influent E. faecalis
LAIST_002 22 14 14 20 0 14 16 Influent E. faecalis
LAIST_003 16 14 20 18 0 20 20 Influent E. faecium
LAIST_004 18 14 20 22 26 20 20 Influent E. faecium
LAIST_005 0 16 26 18 0 24 20 Influent E. faecium
LAIST_006 26 20 26 24 26 20 20 Influent E. faecium
LAIST_007 20 18 20 22 0 16 0 Influent E. faecium
LAIST_008 24 16 20 26 24 20 26 Influent E. faecium
LAIST_009 24 14 21 24 22 20 20 Influent E. faecium
LAIST_010 18 16 20 24 24 22 22 Influent E. faecium
LAIST_011 10 12 18 22 0 18 22 Influent Enterecoccus spp
LAIST_012 20 14 22 24 22 18 20 Influent Enterecoccus spp
LAIST_013 18 18 18 28 0 20 14 Influent Enterecoccus spp
LAIST_014 24 14 18 22 0 14 16 Influent Enterecoccus spp
LAIST_015 22 18 18 24 26 24 22 Influent Enterecoccus spp
LAIST_016 26 16 18 16 20 22 18 Influent Enterecoccus spp
LAIST_017 20 12 18 24 0 18 20 Desinfection E. faecium
LAIST_018 14 16 18 26 0 18 20 Desinfection E. faecium
LAIST_019 20 12 20 24 22 18 18 Desinfection E. faecium
LAIST_020 18 12 14 20 0 16 18 Desinfection E. faecium
LAIST_021 18 12 18 20 22 18 16 Desinfection E. faecium
LAIST_022 20 14 14 20 20 20 18 Desinfection E. faecium
LAIST_023 18 12 18 20 22 18 16 Desinfection E. faecium
LAIST_024 18 20 16 18 16 16 16 Desinfection E. faecium
LAIST_025 24 16 18 24 20 18 18 Desinfection E. faecium
LAIST_026 26 24 16 24 22 22 16 Desinfection Enterecoccus spp
LAIST_027 0 16 10 20 0 14 14 Effluent E. faecalis
LAIST_028 16 12 16 20 0 20 20 Effluent E. faecalis
LAIST_029 26 20 16 24 20 16 16 Effluent E. faecium
LAIST_030 24 14 16 18 22 16 16 Effluent E. faecium
LAIST_031 24 24 18 20 0 24 20 Effluent E. faecium
53
Zone Diameter (mm)
Isolate AMP CIP C LNZ TET VAN GM Treatment
Species’ Identification
LAIST_032 24 16 18 20 0 16 18 Effluent E. faecium
LAIST_033 16 12 16 20 0 18 18 Effluent Enterecoccus spp
LAIST_034 20 16 18 20 0 16 18 Effluent Enterecoccus spp
LAIST_035 28 14 20 28 30 20 20 Effluent Enterecoccus spp
LAIST_036 26 18 18 24 0 16 22 Reused Water E. faecalis
LAIST_037 24 14 18 28 0 16 20 Reused Water E. faecalis
LAIST_038 26 18 16 24 18 14 16 Reused Water E. faecalis
LAIST_039 16 18 18 22 26 20 24 Reused Water E. faecium
LAIST_040 18 20 18 18 20 20 22 Reused Water E. faecium
LAIST_041 26 12 20 26 18 26 24 Reused Water E. faecium
LAIST_042 16 14 18 22 0 18 18 Reused Water E. faecium
LAIST_043 26 16 18 24 0 16 16 Reused Water Enterecoccus spp
LAIST_044 26 24 12 24 28 22 22 Reused Water Enterecoccus spp
LAIST_045 20 26 20 20 20 18 18 Reused Water Enterecoccus spp
LAIST_046 22 14 14 18 16 20 20 Reused Water Enterecoccus spp
54
Wastewater Treatment Plant B
Table 25 - Characterization of the isolates collected from WWTP B. It is possible to distinguish 3
different types of treatment: Influent, Disinfection, and Reused water. All the isolates were
identified using PCR and cultured-based techniques. In Zone Diameter (mm) section it is possible
to distinguish the 7 antibiotics used and the diameter of the inhibition zones. According to these
measurements, the isolates were sorted as susceptible (green), intermediate (orange), and
resistant (red).
Zone Diameter (mm)
Isolate AMP CIP C LNZ TET VAN GM Treatment
Species’ Identification
LAIST_047 20 18 18 26 26 20 20 Influent E. faecalis
LAIST_048 12 16 18 22 20 18 20 Influent E. faecium
LAIST_049 20 22 18 26 30 20 18 Influent E. faecium
LAIST_050 20 22 26 20 20 20 20 Influent E. faecium
LAIST_051 18 16 18 24 24 16 16 Influent E. faecium
LAIST_052 24 20 14 30 20 20 20 Influent E. faecium
LAIST_053 30 18 18 20 20 18 18 Influent Enterococcus spp
LAIST_054 28 14 18 18 18 20 16 Influent Enterococcus spp
LAIST_055 22 14 18 30 0 16 18 Influent Enterococcus spp
LAIST_056 20 14 16 32 16 20 20 Influent Enterococcus spp
LAIST_057 22 12 14 20 0 16 18 Desinfection E. faecalis
LAIST_058 12 20 18 30 22 22 22 Desinfection E. faecium
LAIST_059 14 12 20 30 20 20 20 Desinfection E. faecium
LAIST_060 26 16 22 26 0 20 24 Desinfection E. faecium
LAIST_061 18 18 14 26 0 18 18 Desinfection Enterococcus spp
LAIST_062 18 22 20 30 20 18 20 Desinfection Enterococcus spp
LAIST_063 36 18 16 12 0 16 14 Desinfection Enterococcus spp
LAIST_064 26 20 18 24 26 16 14 Desinfection Enterococcus spp
LAIST_065 36 26 22 26 16 26 16 Desinfection Enterococcus spp
LAIST_066 24 16 14 22 18 16 14 Desinfection Enterococcus spp
LAIST_067 30 20 20 20 22 18 22 Reused Water E. faecium
LAIST_068 18 22 14 18 24 14 18 Reused Water E. faecium
LAIST_069 20 12 16 22 18 18 18 Reused Water E. faecium
LAIST_070 26 12 20 26 28 20 22 Reused Water E. faecium
LAIST_071 16 0 16 18 26 18 20 Reused Water E. faecium
LAIST_072 20 18 12 18 16 16 20 Reused Water E. faecium
LAIST_073 22 18 14 20 0 14 14 Reused Water E. faecium
LAIST_074 20 12 16 22 20 16 16 Reused Water E. faecium
LAIST_075 20 18 16 18 20 16 20 Reused Water E. faecium
LAIST_076 16 12 16 18 20 0 20 Reused Water E. faecium
LAIST_077 26 20 20 20 26 18 18 Reused Water Enterococcus spp
55
Zone Diameter (mm)
Isolate AMP CIP C LNZ TET VAN GM Treatment
Species’ Identification
LAIST_078 20 18 18 20 0 16 26 Reused Water Enterococcus spp
LAIST_079 26 24 20 20 20 28 20 Reused Water Enterococcus spp
LAIST_080 12 12 12 24 22 18 20 Reused Water Enterococcus spp
LAIST_081 24 20 24 16 26 24 26 Reused Water Enterococcus spp
LAIST_082 16 14 16 24 20 16 20 Reused Water Enterococcus spp
LAIST_083 34 16 16 18 26 20 20 Reused Water Enterococcus spp
LAIST_084 22 16 20 24 0 16 16 Reused Water Enterococcus spp
LAIST_085 28 18 16 16 20 20 14 Reused Water Enterococcus spp
56
Wastewater Treatment Plant C and Natural Receptors
Table 26 - Characterization of the isolates collected from WWTP C. It is possible to distinguish 3
different types of treatment: Filtration, Disinfection, Effluent, and two Natural Receptors. All the
isolates were identified using PCR and cultured-based techniques. In Zone Diameter (mm)
section it is possible to distinguish the 7 antibiotics used and the diameter of the inhibition zones.
According to these measurements, the isolates were sorted as susceptible (green), intermediate
(orange), and resistant (red).
Zone Diameter (mm)
Isolate AMP CIP C LNZ TET VAN GM Treatment
Species’ Identification
LAIST_086 26 24 16 24 12 18 20 Filtration E. faecalis
LAIST_087 26 18 20 20 0 14 22 Filtration E. faecalis
LAIST_088 34 22 20 22 0 22 16 Filtration E. faecalis
LAIST_089 26 0 18 18 0 14 16 Filtration E. faecalis
LAIST_090 22 16 22 26 22 22 22 Filtration E. faecium
LAIST_091 18 12 16 22 14 18 16 Filtration E. faecium
LAIST_092 20 14 18 20 16 18 20 Filtration E. faecium
LAIST_093 16 14 16 18 0 20 16 Filtration E. faecium
LAIST_094 18 16 16 16 0 16 14 Filtration E. faecium
LAIST_095 24 16 18 20 24 16 16 Filtration E. faecium
LAIST_096 34 16 24 26 0 20 20 Filtration E. faecium
LAIST_097 22 16 18 26 0 16 16 Filtration E. faecium
LAIST_098 24 20 14 32 20 18 20 Filtration E. faecium
LAIST_099 16 16 20 26 14 18 20 Filtration E. faecium
LAIST_100 20 14 16 26 0 18 18 Filtration E. faecium
LAIST_101 32 18 18 18 22 22 14 Filtration E. faecium
LAIST_102 24 20 16 20 0 16 16 Filtration E. faecium
LAIST_103 20 14 22 26 26 18 20 Filtration Enterococcus spp
LAIST_104 24 16 22 24 10 20 20 Filtration Enterococcus spp
LAIST_105 20 12 20 24 0 18 18 Filtration Enterococcus spp
LAIST_106 0 14 12 20 0 20 18 Filtration Enterococcus spp
LAIST_107 28 20 24 26 0 22 22 Filtration Enterococcus spp
LAIST_108 22 16 20 24 20 20 20 Filtration Enterococcus spp
LAIST_109 26 18 18 28 18 22 18 Filtration Enterococcus spp
LAIST_110 26 18 1 18 20 16 18 Desinfection E. faecalis
LAIST_111 22 16 20 30 26 16 18 Desinfection E. faecalis
LAIST_112 20 18 16 20 20 18 12 Desinfection E. faecalis
LAIST_113 26 18 20 20 20 22 18 Desinfection E. faecium
LAIST_114 24 16 18 20 0 20 24 Desinfection E. faecium
LAIST_115 26 18 14 18 20 16 18 Desinfection E. faecium
LAIST_116 20 18 20 30 24 22 20 Desinfection E. faecium
LAIST_117 20 18 20 30 24 22 20 Desinfection E. faecium
57
Zone Diameter (mm)
Isolate AMP CIP C LNZ TET VAN GM Treatment
Species’ Identification
LAIST_118 16 18 18 22 24 20 22 Desinfection E. faecium
LAIST_119 14 18 16 30 18 18 22 Desinfection E. faecium
LAIST_120 26 16 18 18 20 18 24 Desinfection E. faecium
LAIST_121 26 18 20 18 22 24 22 Desinfection E. faecium
LAIST_122 18 14 16 28 0 20 20 Desinfection E. faecium
LAIST_123 18 16 20 20 0 18 16 Desinfection E. faecium
LAIST_124 22 16 18 24 16 18 18 Desinfection E. faecium
LAIST_125 24 20 14 24 20 16 18 Desinfection E. faecium
LAIST_126 18 12 24 24 0 22 20 Desinfection E. faecium
LAIST_127 26 20 20 20 26 22 22 Desinfection E. faecium
LAIST_128 24 16 20 22 0 18 22 Desinfection Enterococcus spp
LAIST_129 18 16 18 18 0 18 18 Effluent E. faecium
LAIST_130 18 16 18 22 14 18 16 Effluent E. faecium
LAIST_131 18 14 18 24 14 20 20 Effluent E. faecium
LAIST_132 26 14 20 20 18 26 26 Effluent E. faecium
LAIST_133 18 12 20 24 0 18 18 Effluent E. faecium
LAIST_134 18 16 12 20 0 16 16 Effluent E. faecium
LAIST_135 20 20 24 20 0 18 18 Effluent E. faecium
LAIST_136 24 18 18 24 0 16 22 Effluent E. faecium
LAIST_137 18 20 16 18 16 18 14 Effluent E. faecium
LAIST_138 24 22 18 22 29 26 16 Effluent E. faecium
LAIST_139 28 14 20 28 22 26 20 Effluent E. faecium
LAIST_140 34 16 16 22 0 18 18 Effluent E. faecium
LAIST_141 28 16 18 24 26 18 18 Effluent E. faecium
LAIST_142 26 20 20 26 26 20 24 Effluent E. faecium
LAIST_143 26 16 24 16 0 22 18 Effluent E. faecium
LAIST_144 28 14 20 28 22 26 20 Effluent E. faecium
LAIST_145 34 16 16 22 0 18 18 Effluent E. faecium
LAIST_146 28 16 18 24 26 18 18 Effluent E. faecium
LAIST_147 26 20 20 26 26 20 24 Effluent Enterococcus spp
LAIST_148 26 16 24 16 0 22 18 Effluent Enterococcus spp
LAIST_149 18 16 18 26 24 18 20 Effluent Enterococcus spp
LAIST_150 26 16 18 24 20 16 16 Effluent Enterococcus spp
LAIST_151 24 14 14 18 18 16 16 Effluent Enterococcus spp
LAIST_152 20 18 22 24 24 24 22 Effluent Enterococcus spp
LAIST_153 18 14 16 18 16 16 12 Effluent Enterococcus spp
LAIST_154 16 16 16 26 20 16 16 Effluent Enterococcus spp
LAIST_155 12 12 16 28 0 18 16 Effluent Enterococcus spp
LAIST_156 18 12 18 28 26 18 18 Effluent Enterococcus spp
LAIST_157 18 26 18 22 24 22 18 Effluent Enterococcus spp
58
Zone Diameter (mm)
Isolate AMP CIP C LNZ TET VAN GM Treatment
Species’ Identification
LAIST_158 18 22 14 20 0 14 0 Effluent Enterococcus spp
LAIST_159 16 0 17 20 0 16 20 Natural Receptor 1 E. faecalis
LAIST_160 26 20 16 16 18 18 16 Natural Receptor 1 E. faecalis
LAIST_161 18 14 14 18 18 14 16 Natural Receptor 1 E. faecalis
LAIST_162 20 12 0 20 0 18 16 Natural Receptor 1 E. faecium
LAIST_163 18 18 18 24 22 20 16 Natural Receptor 1 E. faecium
LAIST_164 16 18 14 20 18 16 20 Natural Receptor 1 E. faecium
LAIST_165 16 0 18 24 0 18 16 Natural Receptor 1 E. faecium
LAIST_166 16 0 18 24 0 18 28 Natural Receptor 1 E. faecium
LAIST_167 16 20 14 18 0 18 16 Natural Receptor 1 E. faecium
LAIST_168 20 18 22 22 0 22 22 Natural Receptor 1 Enterococcus spp
LAIST_169 18 22 18 24 18 18 20 Natural Receptor 1 Enterococcus spp
LAIST_170 18 16 0 24 0 18 18 Natural Receptor 1 Enterococcus spp
LAIST_171 16 0 16 24 0 16 16 Natural Receptor 1 Enterococcus spp
LAIST_172 26 18 16 24 20 20 18 Natural Receptor 1 Enterococcus spp
LAIST_173 18 16 0 26 0 18 16 Natural Receptor 1 Enterococcus spp
LAIST_174 16 0 16 30 0 16 18 Natural Receptor 1 Enterococcus spp
LAIST_175 26 18 16 32 20 20 16 Natural Receptor 1 Enterococcus spp
LAIST_176 26 18 18 20 0 18 14 Natural Receptor 1 Enterococcus spp
LAIST_177 26 18 20 16 0 20 16 Natural Receptor 1 Enterococcus spp
LAIST_178 26 24 24 18 22 20 18 Natural Receptor 2 E. faecalis
LAIST_179 18 28 24 28 28 18 20 Natural Receptor 2 E. faecium
LAIST_180 18 14 26 26 32 24 18 Natural Receptor 2 E. faecium
LAIST_181 20 0 20 26 26 18 20 Natural Receptor 2 E. faecium
LAIST_182 20 0 0 18 20 16 16 Natural Receptor 2 Enterococcus spp
LAIST_183 26 22 20 26 22 20 24 Natural Receptor 2 Enterococcus spp
LAIST_184 22 18 18 22 18 16 18 Natural Receptor 2 Enterococcus spp
LAIST_185 30 14 16 20 18 16 20 Natural Receptor 2 Enterococcus spp
LAIST_186 22 18 16 32 20 16 18 Natural Receptor 2 Enterococcus spp
59