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Article

Prevalence of Colistin-Resistant, Carbapenem-Hydrolyzing Proteobacteria in Hospital Water Bodies and Out-Falls of West Bengal, India

National Institute of Biomedical Genomics, Kalyani 741251, West Bengal, India
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2020, 17(3), 1007; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17031007
Submission received: 4 December 2019 / Revised: 17 January 2020 / Accepted: 22 January 2020 / Published: 5 February 2020
(This article belongs to the Special Issue Water and Health)

Abstract

:
Indiscriminate use of antibiotics has resulted in a catastrophic increase in the levels of antibiotic resistance in India. Hospitals treat critical bacterial infections and thus can serve as reservoirs of multidrug resistant (MDR) bacteria. Hence, this study was conducted to gauge the prevalence patterns of MDR bacteria in hospital wastewater. Water samples collected from 11 hospitals and 4 environmental sources belonging to 5 most-densely populated districts of West Bengal, India were grown on MacConkey and Eosin Methylene Blue agar. A total of 84 (hospital-associated = 70, environmental water sources = 14) isolates were characterized. The predominant species found in water from hospital-associated areas (HAA) were Acinetobacter baumannii (22.9%), Escherichia coli (28.6 %), and Klebsiella pneumoniae (25.7%). Greater than 75% of the HAA isolates were found to be mcr-1 gene negative and colistinresistant. Meropenem non-susceptibility was also high among the HAA isolates at 58.6%, with the presence of the carbapenemase gene and blaNDM in 67.1% of the non-susceptible isolates. Among the three predominant species, significantly higher numbers of E. coli isolates were found to be non-susceptible to meropenem ((80%), p-value = 0.00432) and amikacin (AK (90%), p-value = 0.00037). This study provides evidence for the presence of high numbers of colistin-resistant and carbapenem-hydrolyzing Proteobacteriain hospital wastewater.

Graphical Abstract

1. Introduction

Antimicrobial resistance (AMR) is a global health challenge of the 21st century, and India contributes majorly to it [1,2]. India has a high burden of bacterial diseases, in addition to which, misguided overuse of antibiotics is also rampant [3]. It is one of the three leading consumers of antibiotics among low to middle-income countries across the world, with the highest usage of broad-spectrum penicillins [4]. However, medical practitioners still follow a pattern of usage in human infections, where carbapenems and polymyxins are considered to be last resort antibiotics in treatment. By contrast, in the animal production industry, polymyxins are routinely used as growth promoters [5,6]. Under such contrasting usage practices, both foodborne pathogens and high human usage of antibiotics can impact human health [7]. Hence, an understanding of the bacterial population distribution is imperative for better treatment design.
The use of antimicrobials is the highest in critical care units in hospitals that provide a selective environment for propagation of multidrug resistant (MDR) pathogens. These pathogens can effectively spread within hospital wards through infected medical devices and human contact and are also flushed out of hospitals through sewage [8]. Untreated or inadequately treated hospital wastewater has been reported to have the highest potential of dispersing such MDR pathogens to the community and the environment, where both the use of antimicrobials and antimicrobial pollutants maintain the selection pressure [9,10]. Once dispersed, these MDR pathogens can contribute to the spread of AMR against the commonly prescribed antimicrobials in a two-pronged manner; through multiplication and horizontal transfer of combinations of resistance-conferring genes to environmental isolates [11].
Reports from European countries and from the USA have highlighted the presence of higher proportions of colistin-resistance genes and extended-spectrum β-lactamase or carbapenemase-producing enteric bacteria in hospital effluents in comparison with urban wastewater [12,13]. Along similar lines, neighboring countries, such as Bangladesh and Singapore, have also reported prevalence of blaNDM harboring bacteria in hospital wastewater and water collected from hospital-adjacent areas [14,15]. In the Indian context, reports are few and restricted to one or two hospitals [16,17,18]. So far, the spread of carbapenem-resistant Enterobacteriaceae and New Delhi Metallo-β lactamase-1 (NDM-1) in hospital wastewater out-falls has been explicitly probed only in New Delhi [19,20]. Colistin resistance is increasingly being reported by tertiary care hospitals in India; however, there are no reports on the prevalence rates in hospital wastewater [21].
A comprehensive understanding of the relative role of hospitals in environmental dissemination of AMR is essential for policy interventions to be put in place. Hence, this study was conducted in the fourth-most populous Indian state of West Bengal, and the objectives of this study were to understand: (i) the gram-negative species distribution, ii) antimicrobial resistance profiles, including colistin, and iii) β-lactamase gene carriage, and among the gram-negative bacterial isolates found in water samples collected from hospital wastewater out-falls and/or hospital ponds belonging to five districts, and contrast them with environmental water sources (EWS) in an unbiased manner, without selecting specific isolates resistant to any particular class of antimicrobial.

2. Materials and Methods

2.1. Collection of Samples and Isolation of Gram-Negative Bacteria

Water samples were collected from hospital-associated areas (HAA), which included untreated hospital wastewater from out-falls to community drains and natural water bodies within hospital premises belonging to 11 government-run hospitals from 5 districts of West Bengal with populations ranging from 4,496,694 to 10,009,781 inhabitants [22]. The districts were Howrah, Hoogly, Kolkata, Nadia, and North 24 Paraganas (Table 1). The names of the hospitals have been anonymized to maintain confidentiality. Institutional Ethical Committee Approval (RC/C/29032016) was taken to work on bacterial pathogens. The hospital water bodies were defined as those within the hospital premises with visible sewage pipelines traversing nearby. In parallel, samples from EWS, namely, four ponds/lakes from four of the same five districts, were also collected to serve as controls. These EWS were defined as natural water bodies without direct disposal of hospital effluents and in use by the community for household chores.
Collection was carried out using the procedure described by Lamba et al. [19] with modification. Briefly, samples were collected in triplicate during the month of May 2018 using sterile 50 ml syringes. Particulate matter, if any were allowed to settle by sedimentation, and the pH were measured. After sedimentation, 10 µL of each sample was plated on Mueller Hinton agar (MHA (Himedia labs, Mumbai, India)) within 6–8 h of collection to be grown aerobically at 37 °C for 18 h in an incubator (Thermo Scientific, Waltham, MA, United States) to determine the total colony forming unit (CFU) counts. Simultaneously, specimens were also grown on both MacConkey with bile salts (MC) and Eosin Methylene Blue agar (EMB (Himedia labs) to determine the colony forming units (CFU) of gram-negative bacteria.
Statistical power was calculated with sample size estimates of 6 isolates per hospital and 3 EWS isolates per district, and multiple testing correction was accounted for the significance level of 0.05. The expected differences in proportion of antibiotic non-susceptibility were 59%, which has been reported earlier [14], and a lower cutoff of 48%. This resulted in power values of 0.95 and 0.81, respectively, using the pwr.2p2n test package in R [23]. Accordingly, a total of 2–3 colonies of differing morphologies were isolated at random from both MC and EMB agar plates (Himedia labs) per sample. The colonies were subcultured in Mueller Hinton broth (Himedia labs) in a shaker incubator (Eppendorf, Hamburg, Germany), and 20% DMSO (Himedia labs) stocks were maintained at −80°C until further analyses.

2.2. Species Identification

DNA was isolated from subcultured isolates using the QIAamp DNA isolation kit (Qiagen, Hilden, Germany) and subjected to PCR amplification using the 16S- S-D-Bact-0008-c-S-20/ S-D-Bact-1391-a-A-17 primer pairs (Eurofins Scientific, Bengaluru, India) and Sanger sequencing. Amplicon sequences were queried against the National Center for Biotechnology Information (NCBI) 16S rRNA gene database for species determination.

2.3. Testing of Antimicrobial Susceptibility

The susceptibility profiles were generated using Kirby–Bauer disc diffusion assays, following Clinical & Laboratory Standards Institute (CLSI) guidelines (CLSI, 2017), and the antibiotics tested were aminoglycosides (amikacin (30 μg), gentamicin, (10 μg)), carbapenem (meropenem, (10 μg)), third generation cephalosporin (cefotaxime, (30 μg)), fluoroquinolone (ciprofloxacin, (5 μg)), penicillin+β-lactamase inhibitor (piperacillin/tazobactam, (100/10 μg)), and phenicol (chloramphenicol, (30 μg)) (Himedia labs).

2.4. Testing of Colistin Susceptibility

Colistin susceptibility was tested by the broth microdilution method using colistin sulphate (Himedia labs) and cation-adjusted Mueller Hinton II broth (CAMHB, Himedia labs) without supplementation of polysorbate-80 in polystyrene microtiter plates as per the CLSI- European Committee on Antimicrobial Susceptibility Testing (EUCAST) joint Polymyxin Breakpoints Working Group guidelines [24]. Three twofold dilutions ranging from 2 ug/mL to 8 ug/mL were used. E. coli, ATCC25922 and Pseudomonas aeruginosa, ATCC27853 were used as controls. Those isolates that exhibited growth at ≥4 µg/mL of colistin after 16–18 h, as detected by OD600, were considered to be resistant [25,26]. The assays were done in triplicate and were repeated three times to confirm the findings.

2.5. Genotyping of the β-Lactamase Genes blaCTX-M, blaNDM, blaSHV, blaTEM, and Plasmid-Borne Colistin Resistance Gene mcr-1

The four β-lactamase genes, namely, blaCTX-M, blaNDM, blaSHV, and blaTEM and the mcr-1 gene were amplified using PCR conditions and primer pairs that have been described before [27,28]. The positive controls used were laboratory isolate JNM10.C3 for the β-lactamase genes [27] and the E. coli NCTC13846 strain for the mcr-1 gene amplifications. Sanger sequencing was carried out and the resulting sequences were queried against the Antimicrobial Resistance Database (ARDB) and the Bacterial Isolate Genome Sequence Database (BIGSdb).

2.6. Identification of Metallo-β-Lactamase (MBL) Producers by MBL Etest

All the isolates were tested for Metallo-β-Lactamase (MBL) by Etest (Himedia labs). The isolates were spread on MHA, and MBL Etest strips with meropenem(4–256 µg/mL) and meropenem inhibitior (meropenem-EDTA) (1–64 µg/mL) were applied and incubated for 16–20 h at 37 °C. A ratio of MRP to MRP-EDTA of >8 or a phenotype of no zone inhibition on the MRP coated side with inhibition zone on the MRP-EDTA side were considered to be MBL positive. This was in alignment with the manufacturer’s recommendations.

2.7. Statistical Analyses

Fisher’s exact test was carried out to identify statistically significant differences in species distribution, antimicrobial resistance phenotypes, and resistance genes among groups using the GraphPad Prism version 7.04 (GraphPad Software, La Jolla, CA, USA) [29]. A p-value of <0.05 was considered to be statistically significant. Multiple testing corrections were carried out independently for each hypothesis tested in this study, using the Benjamini–Hochberg method [30,31].

2.8. Availability of Data and Material

The 16S V1-V8, blaCTX, blaSHV, blaTEM, and blaNDM amplicon sequences have been submitted to GenBank, and the accession numbers are MK719774-MK719852, MN200677-MN200711, MN210360-MN210393, MN200712-MN200750, and MN200638-MN200750, respectively.

3. Results

3.1. Bacterial Load and Species Distribution

The pH of the water samples varied between 7.44 to 8.56, with a median pH (±standard deviation) of 7.93 (±0.524) (Table 1). The total CFU/ml values (±standard deviation) varied between 1.0 × 103 to 6.0 × 104 (±2.2 × 104) and there were no differences among groups. However, the hospital wastewater out-falls on an average had 10 times higher colony counts on MC (CFU/ml 1.4 × 104 and 1.3 × 103) and EMB agar (CFU/ml 2.4 × 104 and 2.8 × 103) compared to hospital ponds, while the EWS had 100 times lesser colony counts (MC: CFU/ml 1.4 × 104 and 1.0 × 102; EMB: CFU/ml 2.4 × 104 and 2.0 × 102). An average of 2–3 colonies from both EMB and MC agar were randomly selected from 10 hospital wastewater out-falls and 2 ponds, with the exception of W.KL.JN1 water samples, which when plated on MC agar had only 2 colonies. One isolate could not be identified and was removed from further analyses making the total count of isolates to be 70. From EWS, a total of 14 isolates could be obtained. All the isolates were found to belong to the phylum Proteobacteria, and Enterobactericeae was the predominant family (Genbank Accession numbers: MK719774–MK719852). Among the EWS isolates, Serratia marcescens (n = 5, 35.7%) was the dominant species, while A. baumannii (n = 16; 22.9%) and E. coli (n = 20; 28.6%) were found to be in the highest numbers among the HAA isolates. K. pneumoniae isolates were found both in HAA (n = 18; 25.7%) and in EWS (n = 3; 21.4%) (Figure 1A, Table S1).

3.2. Antimicrobial Susceptibility Profiles

Out of the eight antimicrobials tested, cefotaxime had the highest non-susceptibility (intermediate or resistant) in both HAA (98.6%) and EWS isolates (84.6%). This was followed by piperacillin/tazobactam (95.7%) in the HAA isolates. Meropenem non-susceptibility was found in 58.6% of the HAA isolates and in none of the control isolates. One Vogesella perlucida isolate from the control group had to be excluded due to poor growth. The prevalence of resistance to piperacillin/tazobactam, meropenem, ciprofloxacin, gentamicin, and amikacin was significantly higher in hospital isolates (Figure 1B, Table 2). The three EWS K. pneumoniae isolates were found to be susceptible to meropenem, ciprofloxacin, gentamicin and chloramphenicol. However, all three were non-susceptible to cefotaxime, piperacillin/tazobactam, and colistin (Table S1). A total of 53 of the 70 (75.7%) HAA isolates were found to be resistant to colistin. Four out of five naturally resistant EWS S. marcescens isolates tested were also found to be resistant to colistin, further validating the results of the assay. Additionally, four meropenem-susceptible EWS Klebsiella spp. isolates and an Enterobacter. ludwigii isolate were also found to be resistant to colistin (Table S1). There were four HAA isolates resistant to all eight antimicrobials.
Among the HAA isolates, the species-specific distributions of susceptibility profiles were compared among A. baumannii, E. coli, and K. pneumoniae isolates because of high prevalence. All the A. baumannii and K. pneumoniae isolates were found to be non-susceptible to cefotaxime. Above 90%, all the isolates belonging to the three species were also non-susceptible to piperacillin / tazobactam. E coli isolates had the highest percentage of ciprofloxacin (90%), gentamicin (45%), amikacin (90%), and meropenem (80%) non-susceptibility, colistin resistance varied between 70% to 83.3% among the three species, and the K. pneumoniae isolates had the highest resistance (83.3%). However, susceptibility differences for only meropenem and amikacin were found to be statistically significant after multiple testing corrections (Figure 2A, Table 3, Table S1). Further, pairwise comparisons revealed that the frequency of both amikacin and meropenem non-susceptibility were lowest among the A. baumanii isolates and highest among the E. coli isolates, with the effect being more prominent in the case of amikacin (Table S2).

3.3. Carriage of Candidate β-Lactamase and mcr-1 Genes among the Pathogenic HAA A. baumannii, K. pneumoniae, and E. coli Isolates

The genes blaCTX-M, blaSHV, and blaTEM were amplified and sequenced, as described previously [27]. Out of a total of 54 HAA A. baumannii, E. coli, and K. pneumoniae isolates, 55.6% (n = 30) were found to harbor the extended spectrum β-lactamase gene blaCTX-M-15, 61.1% (n = 33) harbored the non-Extended Spectrum Beta-Lactamase(ESBL) gene variant blaTEM-1, while in another three isolates the blaTEM variants could not be resolved. A total of 50% (n = 27) were also found to harbor the blaSHV gene. Sequencing revealed the presence of two ESBL blaSHV gene variants (blaSHV12 (n = 1; 3.7%) and blaSHV27 (n = 8; 29.6%)), along with six non-ESBL variants (blaSHV1 (n = 8; 29.6%), blaSHV33 (n = 3; 11.1%), blaSHV85 (n = 3; 11.1%), blaSHV108 (n = 1; 3.7%), blaSHV123 (n = 1; 3.7%), and blaSHV180 (n = 1; 3.7%)). One blaSHV variant could not be resolved. Among the nine ESBL blaSHV gene variants, four each were found in A. baumannii and K. pneumoniae isolates and one in an E. coli isolate. However, there were no differences in the distributions of resistance phenotypes against cefotaxime and P/T among the three species, and a comparison of β-lactamase gene carriage profiles revealed significantly increased occurrences of the blaCTX-M-15 gene among the A. baumannii isolates and decreased blaSHV gene occurrences among the E. coli isolates (n = 4; 20%) (Figure 2B, Table 4). None of the colistin-resistant HAA isolates were found to harbor the mcr-1 gene (Table S1).

3.4. Distribution of the blaNDM Gene and MBL Production among All the Isolates

The blaNDM gene was not detected in all the meropenem non-susceptible isolates. A total of 55.7% (n = 39) HAA and 46.2% (n = 6) EWS isolates were found to be producing MBL, and a fraction of 68.9% (n = 31) harbored the blaNDM gene. The blaNDM gene was detected in a total of 19 (79.2%) meropenem resistant isolates and 13 (76.5%) intermediate isolates. However, there were 15 meropenem sensitive isolates that were found to be blaNDM positive, of which 46.7% (n = 7) were identified to be A. baumannii. The blaNDM gene subtypes identified were blaNDM-1 (n = 19; 45.2%), blaNDM-2 (n = 6; 14.3%), and blaNDM-5 (n = 17; 40.5%). Subtyping could not be carried out for six isolates, which had low band intensities. A species-specific clustering of blaNDM gene variants was also observed. The K. pneumoniae isolates harbored more blaNDM-1 variants (80%) in comparison with the E. coli isolates, which predominantly harbored the blaNDM-5 variant (90.9%).

3.5. Colistin Resistance Among the Carbapenem-Hydrolyzing HAA Isolates

Given that carbapenem non-susceptible bacterial infections are often treated with colistin, the distributions of colistin resistance among meropenem susceptible and non-susceptible HAA isolates were compared. When both carbapenem-hydrolyzing, as well as the susceptible HAA isolates, harboring the blaNDM gene were taken together (n = 56), a significantly higher (83.9%; p-value = 0.0033, Fisher’s exact test) number of colistin resistant isolates were observed in comparison with those isolates which neither exhibited meropenem non-susceptibility nor harbored the blaNDM gene (n = 14; 42.9%).

4. Discussion

Across the globe, infections associated with contaminated drinking water kills approximately 1800 children under the age of five every day [32]. It has also been reported by a number of countries that pathogenic microorganisms released in hospital wastewater contribute majorly to this contamination [33,34]. The WHO recommendation for hospital wastewater treatment entails three rounds of treatments, ending in disinfection of pathogens [35]. In spite of that, reports on the presence of MDR pathogens in hospital wastewater has been published by a number of countries [14,36,37], and there are a few reports from India as well [19,20]. Further, persistence of antibiotic-resistant bacteria in treated sewage water is also increasingly being reported because of the increase in pathogen loads within expanding communities and cities [38]. Thus, it has become imperative to understand and monitor antibiotic concentrations and pathogen loads in hospital sewage for appropriate water treatment before it is released to the environment or used for irrigation.
The present study was undertaken in one of the most populated states of India [39] and the findings highlight the presence of WHO priority pathogens, namely, carbapenem non-susceptible A. baumannii and carbapenem non-susceptible, ESBL-producing E. coli and K. pneumoniae. Mirroring these findings, earlier reports on patient blood cultures collected from all over India have also shown high levels of resistance to aminoglycosides and third generation cephalosporins among A. baumannii, E. coli, and K. pneumoniae isolates [40]. However, in this study, it was observed that amikacin and meropenem non-susceptibility were the highest among E. coli isolates, which was in contrast to a 2018 report from New Delhi that had highlighted the presence of higher numbers of carbapenem-resistance in A. baumannii and K. pneumoniae isolates collected from small and large hospital wastewater out-falls, respectively [19].
In recent years, to tackle the rapid increase in prevalence of carbapenem-resistant isolates in human infections, the use of the relatively toxic polymyxins has become more frequent, and multiple studies from various parts of the world have also confirmed the parallel increase in dissemination of colistin-resistant isolates in wastewater and water bodies [41,42,43,44,45]. Regardless of an increase in polymyxin sales in India between 2000–2015 [4], data on dissemination has been lacking. The high prevalence of colistin resistance (85.37%) observed in this study among the meropenem non-susceptible HAA isolates abundantly resonates the after effects of such usage practices. However, the absence of the mcr-1 gene among the colistin-resistant isolates warrants further investigation to identify the resistance determinants.
The presence of the blaNDM gene in 78.05% of the meropenem non-susceptible isolates in the present study is indicative of the presence of other carbapenemase genes. Additionally, the observed blaNDM variant types and frequencies were also distinct from the previous studies [16,19]. Interestingly, a total of 21.4% of the meropenem-sensitive isolates were both MBL-producers and harbored the blaNDM gene, which requires further analyses of gene copy number variations among the isolates. The CTX-M-15 variant, prevalently found in the Enterobactericeae family and known to be a dominant variant in India, was also found to be the predominant ESBL among the HAA A. baumannii, K. pneumoniae, and E. coli isolates in this study [46]. Further, it was interesting to note that all the E. coli isolates harboring the blaCTX-M-15 gene were also non-susceptible to ciprofloxacin, a second generation fluoroquinone, which is a known characteristic of the sequence type (ST) 131 clone [47]. However, a 2017 report using whole genome sequences of extraintestinal pathogenic isolates have indicated the spread of the CTX-M-15 gene variant to other STs as well [48]. Hence, further analyses for accurate clonal characterization will be necessary to identify the ST clones included in this study. Similarly, high CTX-M-15 carriage rates among the A. baumannii isolates, as observed in this study, have been reported earlier among clinical A. baumannii isolates [49], although the rise in dissemination might be attributed to the excessive use of third generation cephalosporins.

5. Conclusions

Taken together, this study, in spite of a modest sample size and single season collection, provides evidence for the presence of large proportions of colistin-resistant and carbapenem-hydrolyzing human pathogens enlisted in the WHO priority list for the dearth of therapeutic options. Given the presence of overcrowding in the populated districts included in the study and warm climatic conditions, the spread of such pathogens and human exposure can have serious consequences. Wider implications of these findings are yet to be seen. However, the spread of nosocomial pathogens to the environment may also result in the transfer of antimicrobial resistance genes to environmental isolates, which can further worsen the present scenario. Hence, it is imperative that hospital wastewater be monitored and treated adequately by hospitals before being released to common treatment plants.

Supplementary Materials

The following are available online at https://0-www-mdpi-com.brum.beds.ac.uk/1660-4601/17/3/1007/s1, Table S1: Characteristics of all the isolates included in the study. Table S2: Differences in the distribution of amikacin and meropenem non-susceptibility among HAA A. baumannii (n = 16), E. coli (n = 20), and K. pneumoniae (n = 18) isolates (Post-hoc tests).

Author Contributions

T.B. and M.C. contributed equally to this work. Conceptualization, B.B.; data curation, T.B. and M.C.; formal analysis, T.B. and M.C.; funding acquisition, B.B.; investigation, T.B., M.C., and B.B.; methodology, T.B. and M.C.; project administration, B.B.; resources, B.B.; supervision, B.B.; writing—original draft, T.B. and M.C.; writing—review and editing, B.B. All authors approved the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Ramanujan fellowship, funded by the Department of Science and Technology, Government of India, awarded to B.B and Intramural funding.

Acknowledgments

The authors acknowledge Anjan Dasgupta (Department of Biochemistry, Calcutta University) for his valuable suggestions and Samsiddhi Bhattacharjee (National Institute of Biomedical Genomics) for providing inputs on study design and statistical analyses.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Toner, E.; Adalja, A.; Gronvall, G.K.; Cicero, A.; Inglesby, T.V. Antimicrobial resistance is a global health emergency. Health Secur. 2015, 13, 153–155. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Gandra, S.; Tseng, K.K.; Arora, A.; Bhowmik, B.; Robinson, M.L.; Panigrahi, B.; Laxminarayan, R.; Klein, E.Y. The mortality burden of multidrug-resistant pathogens in India: A retrospective observational study. Clin. Inf. Dis. 2018, 69, 563–570. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. WHO. Multi-Country Survey Reveals Widespread Public Misunderstanding About Antibiotic Resistance; WHO Media Centre: Geneva, Switzerland, 2015; Available online: https://www.who.int/news-room/detail/16-11-2015-who-multi-country-survey-reveals-widespread-public-misunderstanding-about-antibiotic-resistance (accessed on 10 January 2019).
  4. Klein, E.Y.; Van Boeckel, T.P.; Martinez, E.M.; Pant, S.; Gandra, S.; Levin, S.A.; Goossens, H.; Laxminarayan, R. Global increase and geographic convergence in antibiotic consumption between 2000 and 2015. Proc. Natl. Acad. Sci. USA 2018, 115, E3463–E3470. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Thomas, R.; Velaphi, S.; Ellis, S.; Walker, A.S.; Standing, J.F.; Heath, P.; Sharland, M.; Dona, D. The use of polymyxins to treat carbapenem resistant infections in neonates and children. Expert Opin. Pharmacother. 2019, 20, 415–422. [Google Scholar] [CrossRef]
  6. Davies, M.; Walsh, T.R. A colistin crisis in India. Lancet Infect. Dis. 2018, 18, 256–257. [Google Scholar] [CrossRef]
  7. Ghafur, A.; Shankar, C.; GnanaSoundari, P.; Venkatesan, M.; Mani, D.; Thirunarayanan, M.A.; Veeraraghavan, B. Detection of chromosomal and plasmid-mediated mechanisms of colistin resistance in Escherichia coli and Klebsiella pneumoniae from Indian food samples. J. Glob. Antimicrob. Resist. 2019, 16, 48–52. [Google Scholar] [CrossRef]
  8. Cornejo-Juárez, P.; Vilar-Compte, D.; Pérez-Jiménez, C.; Ñamendys-Silva, S.A.; Sandoval-Hernández, S.; Volkow-Fernández, P. The impact of hospital-acquired infections with multidrug-resistant bacteria in an oncology intensive care unit. Int. J. Infect. Dis. 2015, 31, 31–34. [Google Scholar] [CrossRef] [Green Version]
  9. Sharpe, M. High on pollution: Drugs as environmental contaminants. J. Environ. Monit. 2003, 5, 42N–46N. [Google Scholar]
  10. Pandey, P.K.; Kass, P.H.; Soupir, M.L.; Biswas, S.; Singh, V.P. Contamination of water resources by pathogenic bacteria. AMB Express 2014, 4, 51. [Google Scholar] [CrossRef] [Green Version]
  11. Von Wintersdorff, C.J.; Penders, J.; van Niekerk, J.M.; Mills, N.D.; Majumder, S.; van Alphen, L.B.; Savelkoul, P.H.; Wolffs, P.F. Dissemination of Antimicrobial Resistance in Microbial Ecosystems through Horizontal Gene Transfer. Front. Microbiol. 2016, 7, 173. [Google Scholar] [CrossRef] [Green Version]
  12. Initiatives for Addressing Antimicrobial Resistance in the Environment: Current Situation and Challenges. 2018. Available online: https://wellcome.ac.uk/sites/default/files/antimicrobial-resistance-environment-report.pdf (accessed on 14 January 2020).
  13. Hembach, N.; Schmid, F.; Alexander, J.; Hiller, C.; Rogall, E.T.; Schwartz, T. Occurrence of the mcr-1 Colistin Resistance Gene and other Clinically Relevant Antibiotic Resistance Genes in Microbial Populations at Different Municipal Wastewater Treatment Plants in Germany. Front. Microbiol. 2017, 8, 1282. [Google Scholar] [CrossRef] [PubMed]
  14. Islam, M.A.; Islam, M.; Hasan, R.; Hossain, M.I.; Nabi, A.; Rahman, M.; Goessens, W.H.F.; Endtz, H.P.; Boehm, A.B.; Faruque, S.M. Environmental Spread of New Delhi Metallo-β-Lactamase-1-Producing Multidrug-Resistant Bacteria in Dhaka, Bangladesh. Appl. Environ. Microbiol. 2017, 83, 15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Le, T.-H.; Ng, C.; Chen, H.; Yi, X.Z.; Koh, T.H.; Barkham, T.M.S.; Zhou, Z.; Gin, K.Y.-H. Occurrences and Characterization of Antibiotic-Resistant Bacteria and Genetic Determinants of Hospital Wastewater in a Tropical Country. Antimicrob. Agents. Chemother. 2016, 60, 7449–7456. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Parvez, S.; Khan, A.U. Hospital sewage water: A reservoir for variants of New Delhi metallo-β-lactamase (NDM) and extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae. Int. J. Antimicrob. Agents 2018, 51, 82–88. [Google Scholar] [CrossRef]
  17. Chandran, S.P.; Diwan, V.; Tamhankar, A.J.; Joseph, B.V.; Rosales-Klintz, S.; Mundayoor, S.; Lundborg, C.S.; Macaden, R. Detection of carbapenem resistance genes and cephalosporin, and quinolone resistance genes along with oqxAB gene in Escherichia coli in hospital wastewater: A matter of concern. J. Appl. Microbiol. 2014, 117, 984–995. [Google Scholar] [CrossRef]
  18. Marathe, N.P.; Berglund, F.; Razavi, M.; Pal, C.; Dröge, J.; Samant, S.; Kristiansson, E.; Joakim Larsson, D.G. Sewage effluent from an Indian hospital harbors novel carbapenemases and integron-borne antibiotic resistance genes. Microbiome 2019, 7, 97. [Google Scholar] [CrossRef] [Green Version]
  19. Lamba, M.; Graham, D.W.; Ahammad, S.Z. Hospital Wastewater Releases of Carbapenem-Resistance Pathogens and Genes in Urban India. Environ. Sci. Technol. 2017, 51, 13906–13912. [Google Scholar] [CrossRef] [Green Version]
  20. Lamba, M.; Gupta, S.; Shukla, R.; Graham, D.W.; Sreekrishnan, T.R.; Ahammad, S.Z. Carbapenem resistance exposures via wastewaters across New Delhi. Environ. Int. 2018, 119, 302–308. [Google Scholar] [CrossRef]
  21. Jain, S. Emergence of Colistin Resistance among Gram Negative Bacteria in Urinary Tract Infections from Super Specialty Hospital of North India. Int. J. Infect. Dis. 2018, 73, 133. [Google Scholar] [CrossRef]
  22. Population Census 2011. Available online: https://www.census2011.co.in/census/state/districtlist/west+bengal.html (accessed on 2 February 2019).
  23. Champely, S. Pwr: Basic Functions for Power Analysis. R Package Version 1.2-2. 2018. Available online: https://CRAN.R-project.org/package=pwr (accessed on 19 August 2019).
  24. CLSI-EUCAST Guidelines. 2016. Available online: http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/General_documents/Recommendations_for_MIC_determination_of_colistin_March_2016.pdf (accessed on 5 January 2018).
  25. Clinical and Laboratory Standards Institute. Performance Standards for Antimicrobial Susceptibility Testing; 23rd informational supplement; CLSI M100-S27; Clinical and Laboratory Standards Institute: Wayne, PA, USA, 2017. [Google Scholar]
  26. Hindler, J.A.; Humphries, R.M. Colistin MIC variability by method for contemporary clinical isolates of multidrug-resistant Gram-negative bacilli. J. Clin. Microbiol. 2013, 51, 1678–1684. [Google Scholar] [CrossRef] [Green Version]
  27. Bhattacharjee, B.; Bardhan, T.; Chakraborty, M.; Basu, M. Resistance profiles and resistome mapping of multidrug resistant carbapenem-hydrolyzing Klebsiella pneumoniae strains isolated from the nares of preterm neonates. Int. J. Antimicrob. Agents 2019, 53, 535–537. [Google Scholar] [CrossRef] [PubMed]
  28. Rebelo, A.R.; Bortolaia, V.; Kjeldgaard, J.S.; Pedersen, S.K.; Leekitcharoenphon, P.; Hansen, I.M.; Guerra, B.; Malorny, B.; Borowiak, M.; Hammerl, J.A.; et al. Multiplex PCR for detection of plasmid-mediated colistin resistance determinants, mcr-1, mcr-2, mcr-3, mcr-4 and mcr-5 for surveillance purposes. Eurosurveillance 2018, 23. [Google Scholar] [CrossRef] [PubMed]
  29. Yang, S.; Xu, H.; Sun, J.; Sun, S. Shifting trends and age distribution of ESKAPEEc resistance in bloodstream infection, Southwest China, 2012–2017. Antimicrob. Resist. Infect. Control 2019, 8, 61. [Google Scholar] [CrossRef] [Green Version]
  30. Bhattacharjee, B.; Mandal, N.R.; Roy, S.; Sengupta, S. Characterization of sequence variations within HPV16 isolates among Indian women: Prediction of causal role of rare non-synonymous variations within intact isolates in cervical cancer pathogenesis. Virology 2008, 377, 143–150. [Google Scholar] [CrossRef]
  31. Benjamini, Y.; Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. 1995, 57, 289–300. [Google Scholar] [CrossRef]
  32. UNICEF. Children Dying Daily Because of Unsafe Water Supplies and Poor Sanitation and Hygiene; UNICEF: New York, NY, USA, 2013; Available online: https://www.unicef.org/media/media_68359.html (accessed on 5 January 2019).
  33. Khan, S.; Siddique, R.; Nabi, G.; Li, Q.; Hou, H.; Ali, I. Investigation of Sewage and Drinking Water in Major Healthcare Centres for Bacterial and Viral Pathogens. Hydrol. Curr. Res. 2017, 8, 272. [Google Scholar] [CrossRef]
  34. Szekeres, E.; Baricz, A.; Chiriac, C.M.; Farkas, A.; Opris, O.; Soranm, M.L.; Andrei, A.S.; Rudi, K.; Balcázar, J.L.; Dragos, N.; et al. Abundance of antibiotics, antibiotic resistance genes and bacterial community composition in wastewater effluents from different Romanian hospitals. Environ. Pollut. 2017, 225, 304–315. [Google Scholar] [CrossRef]
  35. WHO. Collection and Disposal of Wastewater. Available online: https://www.who.int/water_sanitation_health/medicalwaste/130to134.pdf (accessed on 3 June 2019).
  36. Wang, Q.; Wang, P.; Yang, Q. Occurrence and diversity of antibiotic resistance in untreated hospital wastewater. Sci. Total Environ. 2018, 621, 990–999. [Google Scholar] [CrossRef]
  37. Gomi, R.; Matsuda, T.; Matsumura, Y.; Yamamoto, M.; Tanaka, M.; Ichiyama, S.; Yoneda, M. Occurrence of Clinically Important Lineages, Including the Sequence Type 131 C1-M27 Subclone, among Extended-Spectrum-β-Lactamase-Producing Escherichia coli in Wastewater. Antimicrob. Agents Chemother. 2017, 61, e00564-17. [Google Scholar] [CrossRef] [Green Version]
  38. Al-Gheethi, A.A.; Efaq, A.N.; Bala, J.D.; Norli, I.; Abdel-Monem, M.O.; Ab Kadir, M.O. Removal of pathogenic bacteria from sewage-treated effluent and biosolids for agricultural purposes. Appl. Water Sci. 2018, 8, 74. [Google Scholar] [CrossRef] [Green Version]
  39. Population of West Bengal 2018. Available online: http://indiapopulation2018.in/population-of-west-bengal-2018.html (accessed on 5 January 2019).
  40. Gandra, S.; Mojica, N.; Klein, E.Y.; Ashok, A.; Nerurkar, V.; Kumari, M.; Ramesh, U.; Dey, S.; Vadwai, V.; Das, B.R.; et al. Trends in antibiotic resistance among major bacterial pathogens isolated from blood cultures tested at a large private laboratory network in India, 2008–2014. Int. J. Infect. Dis. 2016, 50, 75–82. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  41. Büchler, A.C.; Gehringer, C.; Widmer, A.F.; Egli, A.; Tschudin-Sutter, S. Risk factors for colistin-resistant Enterobacteriaceae in a low-endemicity setting for carbapenem resistance—A matched case–control study. Eurosurveillance 2018, 23, 30. [Google Scholar] [CrossRef] [PubMed]
  42. Ovejero, C.M.; Delgado-Blas, J.F.; Calero-Caceres, W.; Muniesa, M.; Gonzalez-Zorn, B. Spread of mcr-1-carrying Enterobacteriaceae in sewage water from Spain. J. Antimicrob. Chemother. 2017, 72, 1050–1053. [Google Scholar] [CrossRef] [PubMed]
  43. Seruga Music, M.; Hrenovic, J.; Goic-Barisic, I.; Hunjak, B.; Skoricm, D.; Ivankovic, T. Emission of extensively-drug-resistant Acinetobacter baumannii from hospital settings to the natural environment. J. Hosp. Infect. 2017, 96, 323–327. [Google Scholar] [CrossRef]
  44. Tuo, H.; Yang, Y.; Tao, X.; Liu, D.; Li, Y.; Xie, X.; Li, P.; Gu, J.; Kong, L.; Xiang, R.; et al. The Prevalence of Colistin Resistant Strains and Antibiotic Resistance Gene Profiles in Funan River, China. Front Microbiol. 2018, 9, 3094. [Google Scholar] [CrossRef] [Green Version]
  45. Chen, K.; Chi Chan, E.W.; Xie, M.; Ye, L.; Dong, N.; Chen, S. Widespread distribution of mcr-1-bearing bacteria in the ecosystem, 2015 to 2016. Eurosurveillance 2017, 22, 39. [Google Scholar] [CrossRef] [Green Version]
  46. Bevan, E.R.; Jones, A.M.; Hawkey, P.M. Global epidemiology of CTX-M β-lactamases: Temporal and geographical shifts in genotype. J. Antimicrob. Chemother. 2017, 72, 2145–2155. [Google Scholar] [CrossRef] [Green Version]
  47. Nicolas-Chanoine, M.H.; Bertrand, X.; Madec, J.Y. Escherichia coli ST131, an intriguing clonal group. Clin. Microbiol. Rev. 2014, 27, 543–574. [Google Scholar] [CrossRef] [Green Version]
  48. Shaik, S.; Ranjan, A.; Tiwari, K.; Hussain, A.; Nandanwar, N.; Kumar, N.; Jadhav, S.; Semmler, T.; Baddam, R.; Islam, M.A.; et al. Comparative Genomic Analysis of Globally Dominant ST131 Clone with Other Epidemiologically Successful Extraintestinal Pathogenic Escherichia coli (ExPEC) Lineages. MBio 2017, 8, e01596-17. [Google Scholar] [CrossRef] [Green Version]
  49. Shakil, S.; Khan, A.U. Detection of CTX-M-15-producing and carbapenem-resistant Acinetobacter baumannii strains from urine from an Indian hospital. J. Chemother. 2010, 22, 324–327. [Google Scholar] [CrossRef]
Figure 1. Differences in the distribution of bacteria between water samples collected from hospital-associated areas (HAA) and environmental water sources (EWS). (A) Species distribution percentages of isolates. (B) Antimicrobial resistance profiles for the antimicrobials tested. The asterisks indicate the statistically significant differences, and the p-values (Fisher’s exact test) are mentioned above.
Figure 1. Differences in the distribution of bacteria between water samples collected from hospital-associated areas (HAA) and environmental water sources (EWS). (A) Species distribution percentages of isolates. (B) Antimicrobial resistance profiles for the antimicrobials tested. The asterisks indicate the statistically significant differences, and the p-values (Fisher’s exact test) are mentioned above.
Ijerph 17 01007 g001
Figure 2. Differences in antimicrobial phenotype and β-lactamase gene carriage among the three dominant species found in HAA, namely, A. baumannii, K. pneumoniae, and E. coli. (A) Species-specific non-susceptibility profiles against the eight antimicrobials tested. (B) β-lactamase gene carriage differences. The asterisks indicate the statistically significant differences and the p-values (Fisher’s exact test) are mentioned above.
Figure 2. Differences in antimicrobial phenotype and β-lactamase gene carriage among the three dominant species found in HAA, namely, A. baumannii, K. pneumoniae, and E. coli. (A) Species-specific non-susceptibility profiles against the eight antimicrobials tested. (B) β-lactamase gene carriage differences. The asterisks indicate the statistically significant differences and the p-values (Fisher’s exact test) are mentioned above.
Ijerph 17 01007 g002
Table 1. Description of the water samples included in this study.
Table 1. Description of the water samples included in this study.
Location IDWater SourceDistrict
(City/Town)
Date of CollectionpH
W.KL.JN1Hospital wastewater outfallNadia (Kalyani)2.5.20188.12
W.KL.GH1Hospital wastewater outfallNadia (Kalyani)2.5.20187.92
W.CGR.SD1Hospital wastewater outfallHoogly (Chandannagar)8.5.20188.44
W.CNS.ISH1Hospital wastewater outfallHoogly (Chinsurah)8.5.20187.88
W.HWH.DH1Hospital wastewater outfallHowrah11.5.20187.53
W.B.ES1Hospital wastewater outfallHowrah (Belur)11.5.20187.91
W.KOL.MC1Hospital wastewater outfallKolkata16.5.20187.93
W.KOL.NR1Hospital wastewater outfallKolkata16.5.20187.85
W.KOL.NRP1Hospital PondKolkata16.5.20189.54
W.KH.SDP1Hospital PondNorth 24 Parganas16.5.20188.15
W.KH.ES1Hospital wastewater outfallNorth 24 Parganas16.5.20187.44
W.KD.BH1Hospital wastewater outfallNorth 24 Parganas16.5.20187.39
W.BNG.PWPondNorth 24 Parganas (Bonhoogly)21.5.20188.19
W.KL.L1LakeNadia (Kalyani)2.5.20187.87
W.CGR.P1PondHoogly (Chandannagar)8.5.20188.53
W.B.P1PondHowrah (Chandmari)11.5.20188.56
Table 2. Differences in the antimicrobial non-susceptibilities between HAA (n = 70) and EWS (n = 13) bacterial isolates.
Table 2. Differences in the antimicrobial non-susceptibilities between HAA (n = 70) and EWS (n = 13) bacterial isolates.
AntimicrobialsHAA Isolates (%) EWS Isolates (%)p-ValueFalse Discovery Rate (FDR) of 0.05
Cefotaxime 69 (98.6)11 (84.6)0.06250.0429
Piperacillin/Tazobactam67 (95.7)8 (61.5)0.0019 *0.0286
Meropenem41 (58.6)0 (0)0.0001 *0.0071
Ciprofloxacin45 (64.3)1 (7.7)0.0002 *0.0143
Gentamicin19 (27.1)0 (0)0.0332 *0.0357
Amikacin45 (64.3)2 (15.4)0.0016 *0.0214
Chloramphenicol14 (20)0 (0)0.11170.0500
* Statistically significant p-values are highlighted in bold.
Table 3. Differences in the antimicrobial non-susceptibilities between HAA A. baumannii (n = 16), E. coli (n = 20), and K. pneumoniae (n = 18) isolates.
Table 3. Differences in the antimicrobial non-susceptibilities between HAA A. baumannii (n = 16), E. coli (n = 20), and K. pneumoniae (n = 18) isolates.
AntimicrobialsA. baumannii (%)E. coli (%)K. pneumoniae (%)p-ValueFDR of 0.05
Cefotaxime 16 (100)19 (95)18 (100)1.000000.0438
Piperacillin/Tazobactam15 (93.8)19 (95)17 (94.4)1.000000.0500
Meropenem4 (25)16 (80)10 (55.6)0.00432 *0.0125
Ciprofloxacin9 (56.3)18 (90)10 (55.6)0.033370.0188
Gentamicin2 (12.5)9 (45)4 (22.2)0.078080.0313
Amikacin4 (25)18 (90)11 (61.1)0.00037 *0.0063
Chloramphenicol7 (43.8)3 (15)2 (11.1)0.062270.0250
Colistin12 (75)14 (70)15 (83.3)0.668410.0375
* Statistically significant p-values are highlighted in bold.
Table 4. Differences in β-lactamase gene carriage.
Table 4. Differences in β-lactamase gene carriage.
β-Lactamase GenesA. baumannii (%)E. coli (%)K. pneumoniae (%)p-ValueFDR of 0.05
blaCTX-M-1514 (87.5)8 (40)8 (44.4)0.00878 *0.0333
blaTEM13 (81.3)15 (75)8 (44.4)0.045960.0500
blaSHV9 (56.3)4 (20)15 (83.3)0.00045 *0.0167
* Statistically significant p-values are highlighted in bold.

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Bardhan, T.; Chakraborty, M.; Bhattacharjee, B. Prevalence of Colistin-Resistant, Carbapenem-Hydrolyzing Proteobacteria in Hospital Water Bodies and Out-Falls of West Bengal, India. Int. J. Environ. Res. Public Health 2020, 17, 1007. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17031007

AMA Style

Bardhan T, Chakraborty M, Bhattacharjee B. Prevalence of Colistin-Resistant, Carbapenem-Hydrolyzing Proteobacteria in Hospital Water Bodies and Out-Falls of West Bengal, India. International Journal of Environmental Research and Public Health. 2020; 17(3):1007. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17031007

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Bardhan, Taniya, Madhurima Chakraborty, and Bornali Bhattacharjee. 2020. "Prevalence of Colistin-Resistant, Carbapenem-Hydrolyzing Proteobacteria in Hospital Water Bodies and Out-Falls of West Bengal, India" International Journal of Environmental Research and Public Health 17, no. 3: 1007. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17031007

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