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Identification of clinically relevant multi-drug resistant ESKAPEE isolates from hospital wastewater surveillance in Thailand
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IntroductionWastewater surveillance has recently emerged as a promising method for AMR surveillance, but few studies have directly compared wastewater surveillance samples with clinical isolates and the clinical significance of wastewater surveillance for AMR bacteria is still unclear.MethodsWe carried out monthly surveillance of hospital wastewater and surrounding community water at a tertiary hospital in Chonburi, Thailand from March to December 2024 and compared our findings with clinical isolates collected at the same hospital during the same period. For each wastewater sample, we isolated ESKAPEE pathogens, identified species by mass spectrometry, performed antimicrobial susceptibility testing (AST), followed by PCR testing of AMR genes and whole genome sequencing (WGS) on a subset of wastewater isolates and compared our results to clinical isolates.ResultsWe obtained 2,735 AMR isolates from untreated hospital wastewater, of which 1,550 were ESKAPEE pathogens including: Klebsiella pneumoniae (35.8%), Enterobacter spp. (397, 25.6%), Escherichia coli (24.9%), Enterococcus faecium (10.1%), Acinetobacter baumannii (2.7%), and Pseudomonas aeruginosa (0.8%). Based on AST data, we found that 85% K. pneumoniae isolates, 43% A. baumannii isolates, and 98% E. coli isolates, 62% Enterobacter spp. isolates, and 26% E. faecium isolates were classified as multi-drug resistant. We carried out hierarchical clustering of the AST data for a subset of 416 wastewater isolates along with 743 clinical isolates and found significant overlap in AST profiles of wastewater and clinical isolates. Using the clustering data, we selected a subset of 52 wastewater isolates with similar AST profiles to clinical isolates for WGS and identified 19 wastewater isolates that were highly genetically related (≤10 different alleles by cgMLST) to a clinical isolate, including 9 isolates with zero different alleles from closely related clinical isolates.ConclusionOur results show that surveillance of untreated hospital wastewater is capable of identifying ESKAPEE that share similar drug resistance profiles, AMR genes, and clonal lineages found in the clinical isolates over the same time period. To our knowledge, this is one of the first studies to demonstrate a high level of genetic-relatedness between hospital wastewater and clinical isolates and demonstrate the clinical relevance of bacterial wastewater surveillance for MDR ESKAPEE pathogens.
Frontiers Media SA
Sidhartha Chaudhury
Wilawan Oransathit
Dutsadee Peerapongpaisarn
Wirote Oransathit
Chatchadaporn Thamnurak
Chantida Pradipol
Kirakarn Kirativanich
Sirigade Ruekit
Tanit Boonsiri
Yutthana Thanyathada
Anjali P. Sapre
Katelyn V. Bartlett
Melissa J. Martin
Paphavee Lertsethtakarn
Pattaraporn Vanachayangkul
Jeffrey R. Livezey
Daniel M. Boudreaux
Nattaya Ruamsap
Title: Identification of clinically relevant multi-drug resistant ESKAPEE isolates from hospital wastewater surveillance in Thailand
Description:
IntroductionWastewater surveillance has recently emerged as a promising method for AMR surveillance, but few studies have directly compared wastewater surveillance samples with clinical isolates and the clinical significance of wastewater surveillance for AMR bacteria is still unclear.
MethodsWe carried out monthly surveillance of hospital wastewater and surrounding community water at a tertiary hospital in Chonburi, Thailand from March to December 2024 and compared our findings with clinical isolates collected at the same hospital during the same period.
For each wastewater sample, we isolated ESKAPEE pathogens, identified species by mass spectrometry, performed antimicrobial susceptibility testing (AST), followed by PCR testing of AMR genes and whole genome sequencing (WGS) on a subset of wastewater isolates and compared our results to clinical isolates.
ResultsWe obtained 2,735 AMR isolates from untreated hospital wastewater, of which 1,550 were ESKAPEE pathogens including: Klebsiella pneumoniae (35.
8%), Enterobacter spp.
(397, 25.
6%), Escherichia coli (24.
9%), Enterococcus faecium (10.
1%), Acinetobacter baumannii (2.
7%), and Pseudomonas aeruginosa (0.
8%).
Based on AST data, we found that 85% K.
pneumoniae isolates, 43% A.
baumannii isolates, and 98% E.
coli isolates, 62% Enterobacter spp.
isolates, and 26% E.
faecium isolates were classified as multi-drug resistant.
We carried out hierarchical clustering of the AST data for a subset of 416 wastewater isolates along with 743 clinical isolates and found significant overlap in AST profiles of wastewater and clinical isolates.
Using the clustering data, we selected a subset of 52 wastewater isolates with similar AST profiles to clinical isolates for WGS and identified 19 wastewater isolates that were highly genetically related (≤10 different alleles by cgMLST) to a clinical isolate, including 9 isolates with zero different alleles from closely related clinical isolates.
ConclusionOur results show that surveillance of untreated hospital wastewater is capable of identifying ESKAPEE that share similar drug resistance profiles, AMR genes, and clonal lineages found in the clinical isolates over the same time period.
To our knowledge, this is one of the first studies to demonstrate a high level of genetic-relatedness between hospital wastewater and clinical isolates and demonstrate the clinical relevance of bacterial wastewater surveillance for MDR ESKAPEE pathogens.
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