Removal efficiency of antibiotic residues, antibiotic resistant bacteria, and genes across parallel secondary settling tank and membrane bioreactor treatment trains in a water reclamation plant.

Antimicrobial resistance is recognized as a potent threat to human health. Wastewater treatment facilities are viewed as hotspots for the spread of antimicrobial resistance. This study provides comprehensive data on the occurrences of 3 different antibiotic resistant opportunistic pathogens (with resistance to up to 5 antibiotics), 13 antibiotic resistant genes and intI1, and 22 different antimicrobial residues in a large water reclamation plant (176 million gallons per day) that runs a conventional Modified Ludzack-Ettinger (MLE) reactor followed by a secondary settling tank (SST) and membrane bioreactor (MBR) in parallel. All the antibiotic resistant bacteria and most of the antibiotic resistance genes were present in the raw influent, ranging from 2.5 × 102-3.7 × 106 CFU/mL and 1.2× 10-1-6.5 × 1010 GCN/mL, respectively. MBR outperformed the SST system in terms of ARB removal as the ARB targets were largely undetected in MBR effluent, with log removals ranging from 2.7 to 6.8, while SST only had log removals ranging from 0.27 to 4.6. Most of the ARG concentrations were found to have significantly higher in SST effluent than MBR permeate, and MBR had significantly higher removal efficiency for most targets (p < 0.05) except for sul1, sul2, blaOXA48, intI1 and 16S rRNA genes (p > 0.05). As for the antibiotic residues (AR), there was no significant removal from the start to the end of the treatment process, although MBR had higher removal efficiencies for azithromycin, chloramphenicol, erythromycin, erythromycin-H2O, lincomycin, sulfamethoxazole and triclosan, compared to the SST system. In conclusion, MBR outperformed SST in terms of ARB and ARGs removal. However low removal efficiencies of most AR targets were apparent.

Assessing the additional health burden of antibiotic resistant Enterobacteriaceae in surface waters through an integrated QMRA and DALY approach.

Antibiotic resistant Enterobacteriaceae pose a significant threat to public health. However, limited studies have evaluated the health risks associated with exposure to antibiotic-resistant bacteria (ARB), especially in natural environments. While quantitative microbial risk assessment (QMRA) assesses microbial risks in terms of the probability of infection, it does not account for the severity of health outcomes. In this study, a QMRA-DALY model was developed to integrate QMRA with health burden (disability-adjusted life years (DALY)) from infections caused by ARB. The model considers uncertainties in probability of infection and health burden assessment using Monte Carlo simulations. The study collected antimicrobial resistance (AMR) surveillance data from surface waters with different land uses. Results revealed water bodies with agricultural land use to be the main AMR hotspots, with the highest additional health burden observed in infections caused by meropenem-resistant E. coli (∆DALY = 0.0105 DALY/event) compared to antibiotic-susceptible E. coli. The estimated ∆DALY for antibiotic-resistant K. pneumoniae was lower than for antibiotic-resistant E. coli (highest ∆DALY = 0.00048 DALY/event). The study highlights the need for better evaluation of AMR associated health burden, and effective measures to mitigate the risks associated with antibiotic-resistant bacteria in natural environments.

Population-based variations of a core resistome revealed by urban sewage metagenome surveillance.

Sewage-based surveillance is widely employed to understand the occurrence and distribution of antimicrobial resistance (AMR) in urban community. However, there are limited studies which investigated the sewage of different sources within community. The present study used metagenomics to decipher the AMR profiles in five sources: local residence's source, animal source, migrant workers' source, clinical source , and urban wastewater treatment plant influent. A core resistome of ARGs was found across all samples, accounting for 81.4%-93.3% of the abundance of total resistome with only 17.3% diversity, irrespective of the sewage sources. Clinically relevant ARGs were identified in the core resistome across all wastewater sources. This included genes conferring resistance to beta-lactams as biomarkers of hospital sewage. The pet center wastewater showed a high abundance of genes encoding resistance to tetracycline, which is a commonly used veterinary antibiotic. The resistome profile of sewage from the migrant workers' dormitories showed a slight variation to that of the local residential population, suggesting possible differences in the human gut resistome of the foreign/migrant population, with biomarkers of genes encoding resistance to fosfomycin, fosmidomycin, kasugamycin, MLS, and polymyxin. The co-localization of ARGs and plasmid, MGEs and integrative and conjugative elements (ICEs) could explain variations in the core resistome, presumably a result of high antibiotic selection pressure. Further analysis showed a specific host-associated resistance pattern, in which core hosts mediated the core resistome profile. The core BMRGs were also co-localized with MGEs/ICEs and carried by core potential bacterial hosts. Local healthy population carried the lowest ARG load (copy number discharged by each person per day) but contributed the highest ARG burden (copy number discharged by the population). This study elucidates population-based variations of a core resistome, and further provides important insights into source tracking and management of AMR in urban environments.

Prevalence and characterization of antibiotic resistant bacteria in raw community sewage from diverse urban communities.

Community sewage is a useful medium for antimicrobial resistance (AMR) surveillance of populations residing in urban dwellings as it provides the resolution of tracking sources of AMR from different waste streams within a community. Antibiotic resistance profiles of 4 opportunistic pathogens were compared from 3 sewage sources: raw community sewage from 2 housing estates, a foreign workers dormitory and a pet centre. Sewage was collected from receiving manholes and a culture-based method was used to quantify opportunistic pathogens Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Enterococcus spp. K. pneumoniae was the most prevalent opportunistic pathogen detected while P. aeruginosa was the least abundant across the sample. A total of 892 bacterial isolates were selected for antibiotic susceptibility testing using the VITEKⓇ 2 Compact System (bioMérieux, Singapore). E. coli isolated from the pet centre exhibited higher resistance towards all 16 antibiotics tested, and P. aeruginosa showed at least 75% resistance towards the classes of antibiotics, except for carbapenems, aminoglycosides and quinolones (below 30%). For K. pneumoniae, resistance towards the classes of antibiotics was below 10%, except for penicillin and nitrofurans. Enterococcus spp. had high resistance towards gentamicin and clindamycin (both almost 100%), while resistance towards vancomycin was below 18% for all 4 locations. Multidrug resistant (MDR) P. aeruginosa and Enterococcus spp. showed the highest prevalence with percentages above 96%. MDR E. coli and MDR K. pneumoniae was lower, ranging between 9% to 54% and 8% to 23% respectively. Highest prevalence of MDR E. coli and K. pneumoniae were detected in the pet centre, with a percentage of 54% and 23% respectively. These results show that wastewater based surveillance is not only a useful method of understanding emerging trends of AMR across the community but also provides the resolution of capturing AMR data from key sewage sources based on population demographics. This information could provide a basis for devising better control measures to mitigate the spread of MDR.

A new modelling framework for assessing the relative burden of antimicrobial resistance in aquatic environments.

The infections caused by antibiotic resistant bacteria (ARB) can lead to higher medical costs, prolonged hospital stays, and increased mortality compared to bacteria that are susceptible to antibiotics. Challenges exist in quantifying the potential risk/burden associated with antimicrobial resistance (AMR) as there is a lack of dose-response models available for pathogens which are resistant to antibiotics, in addition to the fact that very little is known regarding the health risks posed by antibiotic resistant genes (ARG). In this paper, we proposed a new modelling framework to evaluate the relative burden of AMR in natural aquatic environments. With this framework, an AMR burden score for each sample was calculated based on burden coefficients assigned for each ARB and ARG, as well as weighted burdens for the separate ARBs and ARGs components. The method developed in this study was applied to assess the relative burden of AMR in local aquatic environments with different land uses at different seasons. The collected filed data were used to verify the applicability of the proposed relative burden assessment method. Through the established method, the spatial and temporal hotspots of AMR were identified, which could provide useful information to agencies for better control and management of AMR emergence in natural aquatic environments.

Metagenomic and Resistome Analysis of a Full-Scale Municipal Wastewater Treatment Plant in Singapore Containing Membrane Bioreactors.

Reclaimed water provides a water supply alternative to address problems of scarcity in urbanized cities with high living densities and limited natural water resources. In this study, wastewater metagenomes from 6 stages of a wastewater treatment plant (WWTP) integrating conventional and membrane bioreactor (MBR) treatment were evaluated for diversity of antibiotic resistance genes (ARGs) and bacteria, and relative abundance of class 1 integron integrases (intl1). ARGs confering resistance to 12 classes of antibiotics (ARG types) persisted through the treatment stages, which included genes that confer resistance to aminoglycoside [aadA, aph(6)-I, aph(3')-I, aac(6')-I, aac(6')-II, ant(2″)-I], beta-lactams [class A, class C, class D beta-lactamases (bla OXA)], chloramphenicol (acetyltransferase, exporters, floR, cmIA), fosmidomycin (rosAB), macrolide-lincosamide-streptogramin (macAB, ereA, ermFB), multidrug resistance (subunits of transporters), polymyxin (arnA), quinolone (qnrS), rifamycin (arr), sulfonamide (sul1, sul2), and tetracycline (tetM, tetG, tetE, tet36, tet39, tetR, tet43, tetQ, tetX). Although the ARG subtypes in sludge and MBR effluents reduced in diversity relative to the influent, clinically relevant beta lactamases (i.e., bla KPC, bla OXA) were detected, casting light on other potential point sources of ARG dissemination within the wastewater treatment process. To gain a deeper insight into the types of bacteria that may survive the MBR removal process, genome bins were recovered from metagenomic data of MBR effluents. A total of 101 close to complete draft genomes were assembled and annotated to reveal a variety of bacteria bearing metal resistance genes and ARGs in the MBR effluent. Three bins in particular were affiliated to Mycobacterium smegmatis, Acinetobacter Iwoffii, and Flavobacterium psychrophila, and carried aquired ARGs aac(2')-Ib, bla OXA-278, and tet36 respectively. In terms of indicator organisms, cumulative log removal values (LRV) of Escherichia coli, Enterococci, and P. aeruginosa from influent to conventional treated effluent was lower (0-2.4), compared to MBR effluent (5.3-7.4). We conclude that MBR is an effective treatment method for reducing fecal indicators and ARGs; however, incomplete removal of P. aeruginosa in MBR treated effluents (<8 MPN/100 mL) and the presence of ARGs and intl1 underscores the need to establish if further treatment should be applied prior to reuse.

Microbial water quality and the detection of multidrug resistant E. coli and antibiotic resistance genes in aquaculture sites of Singapore.

Poor microbial water quality jeopardizes the health and safety of food produced by aquaculture farms. Three fish farms and transect sites in Singapore were assessed for microbial water quality and antimicrobial resistance determinants. Of the 33 multidrug resistant E. coli isolated from surface waters of the Johor Straits, 81.8% were ESBL producers. The relative abundance of sul1, qnrA and intI1 genes were higher in sediments than surface waters. Among the surface water samples, higher concentrations (10-1-101) of beta-lactamases (blaSHV, blaOXA, blaCTX-M) were detected in the transect sites. This study highlights a potential antimicrobial resistance transmission chain from environmental waters, to animal carriers and humans.