Antibacterial activity of nonantibiotics is orthogonal to standard antibiotics.

Numerous nonantibiotic drugs have potent antibacterial activity and can adversely affect the human microbiome. The mechanistic underpinning of this toxicity remains largely unknown. We investigated the antibacterial activity of 200 drugs using genetic screens with thousands of barcoded Escherichia coli knockouts. We analyzed 2 million gene-drug interactions underlying drug-specific toxicity. Network-based analysis of drug-drug similarities revealed that antibiotics clustered into modules that are consistent with the mode of action of their established classes, whereas nonantibiotics remained unconnected. Half of the nonantibiotics clustered into separate modules, potentially revealing shared and unexploited targets for new antimicrobials. Analysis of efflux systems revealed that they widely affect antibiotics and nonantibiotics alike, suggesting that the impact of nonantibiotics on antibiotic cross-resistance should be investigated closely in vivo.

Predicting hosts and cross-species transmission of Streptococcus agalactiae by interpretable machine learning.

BACKGROUND: Streptococcus agalactiae, commonly known as Group B Streptococcus (GBS), exhibits a broad host range, manifesting as both a beneficial commensal and an opportunistic pathogen across various species. In humans, it poses significant risks, causing neonatal sepsis and meningitis, along with severe infections in adults. Additionally, it impacts livestock by inducing mastitis in bovines and contributing to epidemic mortality in fish populations. Despite its wide host spectrum, the mechanisms enabling GBS to adapt to specific hosts remain inadequately elucidated. Therefore, the development of a rapid and accurate method differentiates GBS strains associated with particular animal hosts based on genome-wide information holds immense potential. Such a tool would not only bolster the identification and containment efforts during GBS outbreaks but also deepen our comprehension of the bacteria's host adaptations spanning humans, livestock, and other natural animal reservoirs. METHODS AND RESULTS: Here, we developed three machine learning models-random forest (RF), logistic regression (LR), and support vector machine (SVM) based on genome-wide mutation data. These models enabled precise prediction of the host origin of GBS, accurately distinguishing between human, bovine, fish, and pig hosts. Moreover, we conducted an interpretable machine learning using SHapley Additive exPlanations (SHAP) and variant annotation to uncover the most influential genomic features and associated genes for each host. Additionally, by meticulously examining misclassified samples, we gained valuable insights into the dynamics of host transmission and the potential for zoonotic infections. CONCLUSIONS: Our study underscores the effectiveness of random forest (RF) and logistic regression (LR) models based on mutation data for accurately predicting GBS host origins. Additionally, we identify the key features associated with each GBS host, thereby enhancing our understanding of the bacteria's host-specific adaptations.

Global epidemiology of asymptomatic colonisation of methicillin-resistant Staphylococcus aureus in the upper respiratory tract of young children: a systematic review and meta-analysis.

OBJECTIVE: To estimate the global prevalence of asymptomatic colonisation, and determine the associated risk factors, antibiotic resistance and genotypes of methicillin-resistant Staphylococcus aureus (MRSA) in the upper respiratory tract of young children. DESIGN: Four bibliometric databases were searched for publications between 2010 and 2022 according to the protocol registered in PROSPERO. Cross-sectional or cohort studies describing the prevalence of asymptomatic colonisation of S. aureus and MRSA in young children were included. Data extraction and analysis were carried out by two reviewers independently according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement. Pooled prevalence was estimated using a random effects model. SETTING AND STUDIES: We included studies where children without respiratory tract infection or Staphylococcal infection were recruited from the community, children's institutions (ie, nurseries, kindergartens, daycare centres and preschools) and healthcare centre visits and assessed for asymptomatic colonisation with S. aureus and MRSA. MAIN OUTCOME MEASURES: The pooled prevalence of asymptomatic colonisation of S. aureus and MRSA of young children globally. RESULTS: In this systematic review and meta-analysis of 21 416 young children, the pooled global prevalence of asymptomatic S. aureus colonisation was 25.1% (95% CI 21.4 to 28.8) and MRSA colonisation was 3.4% (95% CI 2.8 to 4.1). The clones of MRSA strains included healthcare-associated MRSA, community-associated MRSA and livestock-associated MRSA. CONCLUSION: This study provides evidence of increased MRSA colonisation globally among young children, underlining the critical role of asymptomatic carriers in MRSA transmission and the need for control measures. PROSPERO REGISTRATION NUMBER: CRD 42022328385.

Categorical Updating in a Bayesian Propensity Problem.

We present three experiments using a novel problem in which participants update their estimates of propensities when faced with an uncertain new instance. We examine this using two different causal structures (common cause/common effect) and two different scenarios (agent-based/mechanical). In the first, participants must update their estimate of the propensity for two warring nations to successfully explode missiles after being told of a new explosion on the border between both nations. In the second, participants must update their estimate of the accuracy of two early warning tests for cancer when they produce conflicting reports about a patient. Across both experiments, we find two modal responses, representing around one-third of participants each. In the first, "Categorical" response, participants update propensity estimates as if they were certain about the single event, for example, certain that one of the nations was responsible for the latest explosion, or certain about which of the two tests is correct. In the second, "No change" response, participants make no update to their propensity estimates at all. Across the three experiments, the theory is developed and tested that these two responses in fact have a single representation of the problem: because the actual outcome is binary (only one of the nations could have launched the missile; the patient either has cancer or not), these participants believe it is incorrect to update propensities in a graded manner. They therefore operate on a "certainty threshold" basis, whereby, if they are certain enough about the single event, they will make the "Categorical" response, and if they are below this threshold, they will make the "No change" response. Ramifications are considered for the "categorical" response in particular, as this approach produces a positive-feedback dynamic similar to that seen in the belief polarization/confirmation bias literature.

Multi-year seabed environmental baseline in deep-sea offshore oil prospective areas established using microbial biodiversity.

Microorganisms are the ocean's first responders to marine pollution events, yet baseline studies rarely focus on microbial communities. Temporal and spatial microbial biodiversity baselines were established using bacterial 16S rRNA gene amplicon sequencing of seafloor sediments in a deep-water oil prospective area along the Scotian Slope off Canada's east coast sampled during 2015-2018. Bacterial diversity was generally similar in space and time, with members of the family Woeseiaceae detected consistently in >1 % relative abundance, similar to seabed sediments in other parts of the world. Anomalous biodiversity results at one site featured lower Woeseiaceae as well as higher levels of bacterial groups specifically associated with cold seeps such as Aminicenantes. This was unexpected given that site selection was based on sediment geochemistry not revealing any petroleum hydrocarbons in these locations. This finding highlights the sensitivity and specificity of microbial DNA sequencing in environmental monitoring. Microbiome assessments like this one represent an important strategy for incorporating microbial biodiversity as a new and useful metric for establishing robust environmental baselines that are necessary for understanding ecosystem responses to marine pollution.

Physical Supporting Devices as Interventions to Reduce Muscular Load of Surgeons in the Operating Room.

INTRODUCTION: Heavy muscle load during operations, caused by static and awkward postures, contributes to the discomfort of surgeons, and imperils surgical quality. We reviewed the supporting devices available to assist surgeons in the operating room and anticipated that physical support devices would help reduce occupational injuries among surgeons and improve surgical performance. METHODS: A systematic literature review was completed. Papers on supporting devices for intraoperative stress reduction were included. Supported body parts and the impact of these devices on the surgeons' performance were extracted from the 21 selected papers. RESULTS: Among the 21 devices introduced, eleven targeted on the upper extremities, 5 targeted on the lower extremities, and 5 were ergonomic chairs. Nine devices were tested in the operating room, 10 in a lab setting with simulated tasks, and 2 were still in development. The data from 7 studies did not show a significant improvement in stress reduction or surgical quality. With 2 devices still in the development phase, the remaining 12 papers showed promising results. DISCUSSION: Although some of the devices were still in testing, most of the research teams believed that physical supporting devices can be useful in reducing muscle load, relieving discomfort, and improving surgical performance intraoperatively.

SituSeq: an offline protocol for rapid and remote Nanopore 16S rRNA amplicon sequence analysis.

Microbiome analysis through 16S rRNA gene sequencing is a crucial tool for understanding the microbial ecology of any habitat or ecosystem. However, workflows require large equipment, stable internet, and extensive computing power such that most of the work is performed far away from sample collection in both space and time. Performing amplicon sequencing and analysis at sample collection would have positive implications in many instances including remote fieldwork and point-of-care medical diagnoses. Here we present SituSeq, an offline and portable workflow for the sequencing and analysis of 16S rRNA gene amplicons using Nanopore sequencing and a standard laptop computer. SituSeq was validated by comparing Nanopore 16S rRNA gene amplicons, Illumina 16S rRNA gene amplicons, and Illumina metagenomes, sequenced using the same environmental DNA. Comparisons revealed consistent community composition, ecological trends, and sequence identity across platforms. Correlation between the abundance of taxa in each taxonomic level in Illumina and Nanopore data sets was high (Pearson's r > 0.9), and over 70% of Illumina 16S rRNA gene sequences matched a Nanopore sequence with greater than 97% sequence identity. On board a research vessel on the open ocean, SituSeq was used to analyze amplicon sequences from deep sea sediments less than 2 h after sequencing, and 8 h after sample collection. The rapidly available results informed decisions about subsequent sampling in near real-time while the offshore expedition was still underway. SituSeq is a portable and user-friendly workflow that helps to bring the power of microbial genomics and diagnostics to many more researchers and situations.

Alterations in faecal microbiome and resistome in Chinese international travellers: a metagenomic analysis.

BACKGROUND: International travel increases the risk of acquisition of antibiotic-resistant bacteria and antibiotic resistance genes (ARGs). Previous studies have characterized the changes in the gut microbiome and resistome of Western travellers; however, information on non-Western populations and the effects of travel-related risk factors on the gut microbiome and resistome remains limited. METHODS: We conducted a prospective observational study on a cohort of 90 healthy Chinese adult residents of Hong Kong. We characterized the microbiome and resistome in stools collected from the subjects before and after travelling to diverse international locations using shotgun metagenomic sequencing and examined their associations with travel-related variables. RESULTS: Our results showed that travel neither significantly changed the taxonomic composition of the faecal microbiota nor altered the alpha (Shannon) or beta diversity of the faecal microbiome or resistome. However, travel significantly increased the number of ARGs. Ten ARGs, including aadA, TEM, mgrB, mphA, qnrS9 and tetR, were significantly enriched in relative abundance after travel, eight of which were detected in metagenomic bins belonging to Escherichia/Shigella flexneri in the post-trip samples. In sum, 30 ARGs significantly increased in prevalence after travel, with the largest changes observed in tetD and a few qnrS variants (qnrS9, qnrS and qnrS8). We found that travel to low- or middle-income countries, or Africa or Southeast Asia, increased the number of ARG subtypes, whereas travel to low- or middle-income countries and the use of alcohol-based hand sanitizer (ABHS) or doxycycline as antimalarial prophylaxis during travel resulted in increased changes in the beta diversity of the faecal resistome. CONCLUSIONS: Our study highlights travel to low- or middle-income countries, Africa or Southeast Asia, a long travel duration, or the use of ABHS or doxycycline as antimalarial prophylaxis as important risk factors for the acquisition/enrichment of ARGs during international travel.

Evolved bacterial resistance to the chemotherapy gemcitabine modulates its efficacy in co-cultured cancer cells.

Drug metabolism by the microbiome can influence anticancer treatment success. We previously suggested that chemotherapies with antimicrobial activity can select for adaptations in bacterial drug metabolism that can inadvertently influence the host's chemoresistance. We demonstrated that evolved resistance against fluoropyrimidine chemotherapy lowered its efficacy in worms feeding on drug-evolved bacteria (Rosener et al., 2020). Here, we examine a model system that captures local interactions that can occur in the tumor microenvironment. Gammaproteobacteria-colonizing pancreatic tumors can degrade the nucleoside-analog chemotherapy gemcitabine and, in doing so, can increase the tumor's chemoresistance. Using a genetic screen in Escherichia coli, we mapped all loss-of-function mutations conferring gemcitabine resistance. Surprisingly, we infer that one third of top resistance mutations increase or decrease bacterial drug breakdown and therefore can either lower or raise the gemcitabine load in the local environment. Experiments in three E. coli strains revealed that evolved adaptation converged to inactivation of the nucleoside permease NupC, an adaptation that increased the drug burden on co-cultured cancer cells. The two studies provide complementary insights on the potential impact of microbiome adaptation to chemotherapy by showing that bacteria-drug interactions can have local and systemic influence on drug activity.

Rapid SARS-CoV-2 Variants Enzymatic Detection (SAVED) by CRISPR-Cas12a.

The continuous and rapid surge of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with high transmissibility and evading neutralization is alarming, necessitating expeditious detection of the variants concerned. Here, we report the development of rapid SARS-CoV-2 variants enzymatic detection (SAVED) based on CRISPR-Cas12a targeting of previously crucial variants, including Alpha, Beta, Gamma, Delta, Lambda, Mu, Kappa, and currently circulating variant of concern (VOC) Omicron and its subvariants BA.1, BA.2, BA.3, BA.4, and BA.5. SAVED is inexpensive (US$3.23 per reaction) and instrument-free. SAVED results can be read out by fluorescence reader and tube visualization under UV/blue light, and it is stable for 1 h, enabling high-throughput screening and point-of-care testing. We validated SAVED performance on clinical samples with 100% specificity in all samples and 100% sensitivity for the current pandemic Omicron variant samples having a threshold cycle (CT) value of ≤34.9. We utilized chimeric CRISPR RNA (crRNA) and short crRNA (15-nucleotide [nt] to 17-nt spacer) to achieve single nucleotide polymorphism (SNP) genotyping, which is necessary for variant differentiation and is a challenge to accomplish using CRISPR-Cas12a technology. We propose a scheme that can be used for discriminating variants effortlessly and allows for modifications to incorporate newer upcoming variants as the mutation site of these variants may reappear in future variants. IMPORTANCE Rapid differentiation and detection tests that can directly identify SARS-CoV-2 variants must be developed in order to meet the demands of public health or clinical decisions. This will allow for the prompt treatment or isolation of infected people and the implementation of various quarantine measures for those exposed. We report the development of the rapid SARS-CoV-2 variants enzymatic detection (SAVED) method based on CRISPR-Cas12a that targets previously significant variants like Alpha, Beta, Gamma, Delta, Lambda, Mu, and Kappa as well as the VOC Omicron and its subvariants BA.1, BA.2, BA.3, BA.4, and BA.5 that are currently circulating. SAVED uses no sophisticated instruments and is reasonably priced ($3.23 per reaction). As the mutation location of these variations may reoccur in subsequent variants, we offer a system that can be applied for variant discrimination with ease and allows for adjustments to integrate newer incoming variants.

Rapid pathogen identification and phenotypic antimicrobial susceptibility directly from urine specimens.

Implementing effective antimicrobial therapy close to the onset of infection lowers morbidity and mortality and attenuates the spread of antimicrobial resistance. Current antimicrobial susceptibility testing (AST) methods, however, require several days to determine optimal therapies. We present technology and an automated platform that identify (ID) Urinary Tract Infection pathogens in 45 min and provide phenotypic AST results in less than 5 h from urine specimens without colony isolation. The ID and AST tests count cells fluorescently labeled with specific rRNA probes using non-magnified digital imaging. The ID test detected five pathogens at ≤ 7,000 CFU/mL and had a linear range of ~ 4 orders of magnitude. For contrived specimens, AST tests gave 93.1% categorical agreement with 1.3% Very Major Errors (VME), 0.3% Major Errors (ME), and 6.3% minor Errors (mE) compared to the broth microdilution (BMD) reference method. For clinical specimens, the ID test had 98.6% agreement and the AST test had 92.3% categorical agreement with 4.2% mE, 3.4% ME and 4.0% VME compared to BMD. Data presented demonstrates that direct-from-specimen AST tests can accurately determine antimicrobial susceptibility/resistance for each pathogen in a specimen containing two pathogens. The method is robust to urine matrix effects and off-target commensal and contaminating bacteria.

Metabolic responses of thermophilic endospores to sudden heat-induced perturbation in marine sediment samples.

Microbially mediated processes in a given habitat tend to be catalyzed by abundant populations that are ecologically adapted to exploit specific environmental characteristics. Typically, metabolic activities of rare populations are limited but may be stimulated in response to acute environmental stressors. Community responses to sudden changes in temperature and pressure can include suppression and activation of different populations, but these dynamics remain poorly understood. The permanently cold ocean floor hosts countless low-abundance microbes including endospores of thermophilic bacteria. Incubating sediments at high temperature resuscitates viable spores, causing the proliferation of bacterial populations. This presents a tractable system for investigating changes in a microbiome's community structure in response to dramatic environmental perturbations. Incubating permanently cold Arctic fjord sediments at 50°C for 216 h with and without volatile fatty acid amendment provoked major changes in community structure. Germination of thermophilic spores from the sediment rare biosphere was tracked using mass spectrometry-based metabolomics, radiotracer-based sulfate reduction rate measurements, and high-throughput 16S rRNA gene sequencing. Comparing community similarity at different intervals of the incubations showed distinct temporal shifts in microbial populations, depending on organic substrate amendment. Metabolite patterns indicated that amino acids and other sediment-derived organics were decomposed by fermentative Clostridia within the first 12-48 h. This fueled early and late phases of exponential increases in sulfate reduction, highlighting the cross-feeding of volatile fatty acids as electron donors for different sulfate-reducing Desulfotomaculia populations. The succession of germinated endospores triggered by sudden exposure to high temperature and controlled by nutrient availability offers a model for understanding the ecological response of dormant microbial communities following major environmental perturbations.

Geological processes mediate a microbial dispersal loop in the deep biosphere.

The deep biosphere is the largest microbial habitat on Earth and features abundant bacterial endospores. Whereas dormancy and survival at theoretical energy minima are hallmarks of microbial physiology in the subsurface, ecological processes such as dispersal and selection in the deep biosphere remain poorly understood. We investigated the biogeography of dispersing bacteria in the deep sea where upward hydrocarbon seepage was confirmed by acoustic imagery and geochemistry. Thermophilic endospores in the permanently cold seabed correlated with underlying seep conduits reveal geofluid-facilitated cell migration pathways originating in deep petroleum-bearing sediments. Endospore genomes highlight adaptations to life in anoxic petroleum systems and bear close resemblance to oil reservoir microbiomes globally. Upon transport out of the subsurface, viable thermophilic endospores reenter the geosphere by sediment burial, enabling germination and environmental selection at depth where new petroleum systems establish. This microbial dispersal loop circulates living biomass in and out of the deep biosphere.

Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population.

Wastewater-based epidemiology (WBE) is an emerging surveillance tool that has been used to monitor the ongoing COVID-19 pandemic by tracking SARS-CoV-2 RNA shed into wastewater. WBE was performed to monitor the occurrence and spread of SARS-CoV-2 from three wastewater treatment plants (WWTP) and six neighborhoods in the city of Calgary, Canada (population 1.44 million). A total of 222 WWTP and 192 neighborhood samples were collected from June 2020 to May 2021, encompassing the end of the first-wave (June 2020), the second-wave (November end to December 2020) and the third-wave of the COVID-19 pandemic (mid-April to May 2021). Flow-weighted 24-hour composite samples were processed to extract RNA that was then analyzed for two SARS-CoV-2-specific regions of the nucleocapsid gene, N1 and N2, using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Using this approach SARS-CoV-2 RNA was detected in 98.06% (406/414) of wastewater samples. SARS-CoV-2 RNA abundance was compared to clinically diagnosed COVID-19 cases organized by the three-digit postal code of affected individuals' primary residences, enabling correlation analysis at neighborhood, WWTP and city-wide scales. Strong correlations were observed between N1 & N2 gene signals in wastewater and new daily cases for WWTPs and neighborhoods. Similarly, when flow rates at Calgary's three WWTPs were used to normalize observed concentrations of SARS-CoV-2 RNA and combine them into a city-wide signal, this was strongly correlated with regionally diagnosed COVID-19 cases and clinical test percent positivity rate. Linked census data demonstrated disproportionate SARS-CoV-2 in wastewater from areas of the city with lower socioeconomic status and more racialized communities. WBE across a range of urban scales was demonstrated to be an effective mechanism of COVID-19 surveillance.

Colonization of Group B Streptococcus in Pregnant Women and Their Neonates from a Sri Lankan Hospital.

We investigated the molecular epidemiology of Streptococcus agalactiae (Group B Streptococcus, GBS) from carriage in a cohort of pregnant mothers and their respective newborns in a Teaching Hospital in Sri Lanka. GBS vaginal carriage was assessed on pregnant mothers at pre-delivery (n = 250), post-delivery (n = 130), and from peri-rectal swabs of neonates (n = 159) in a prospective study. All colonizing, non-duplicate GBS isolates (n = 60) were analyzed for antimicrobial susceptibilities, capsular serotyping, and whole-genome sequencing (WGS). The percentage of GBS carriage in mothers in the pre-delivery and post-delivery cohorts were 11.2% (n = 28) and 19.2% (n = 25), respectively, and 4.4% (n = 7) in neonates. GBS isolates predominantly belonged to serotype VI (17/60, 28.3%). The isolates spanned across 12 sequence types (STs), with ST1 (24/60, 40%) being the most predominant ST. Concomitant resistance to erythromycin, tetracyclines, and gentamicin was observed in eight strains (13.3%). WGS revealed the presence of antimicrobial resistance genes including ermA (5/60), mefA (1/60), msrD (1/60), and tetLMO (2/60, 28/60, and 1/60, respectively) among 60 strains. The study provides insight into the diversity of vaccine targets of GBS since serotype VI is yet to be covered in the vaccine development program.

Prevalence and Characteristics of Streptococcus agalactiae from Freshwater Fish and Pork in Hong Kong Wet Markets.

We report the antimicrobial resistance of 191 fish and 61 pork Group B Streptococcus (GBS) procured from Hong Kong wet markets. Two-hundred-and-fifty-two GBS strains were isolated from 992 freshwater fish and 361 pig offal during 2016-2019. The strains were isolated from homogenised samples and plated on selective media, followed by identification through MALDI-TOF-MS. Molecular characterisation, an antibiotic susceptibility test, and biofilm formation were performed on the strains. The isolation rates of the fish GBS and pig GBS were 19.3% (191 strains from 992 freshwater fish) and 16.9% (61 strains from 361 pig organs), respectively. The fish GBS was predominantly serotype Ia, ST7, while pig GBS was serotype III, ST651 (45 strains). An antibiotic susceptibility test revealed that the fish GBS were mostly antibiotic-sensitive, while the pig GBS were multidrug-resistant. A biofilm formation experiment showed that over 71% of fish GBS and all pig GBS had moderate biofilm formation ability. In general, the prevalence rate of GBS in animals and the multidrug resistance phenotype presented in the strains raise concerns about its zoonotic potential and effects on public health.

Longitudinal Genomic Characterization of Carbapenemase-producing Enterobacteriaceae (CPE) Reveals Changing Pattern of CPE Isolated in Hong Kong Hospitals.

An active, territory-wide, CPE surveillance program implemented from 2011 showed increasing levels of carbapenemase-producing Enterobacteriaceae (CPE) isolates from patients in Hong Kong hospitals. The molecular epidemiology of 567 CPE from patients of three of seven public hospital clusters in Hong Kong are described. During a 7-year period, the incidence of CPE isolation increased from 0.05 to 9.6/100 000 patient-days. The carbapenemase genes identified were polyclonal, including blaKPC, blaNDM and blaIMP, which were mainly associated with hospitalization overseas in previous years. However, increasing CPE isolation from patients without hospitalization overseas occurred in 2015, with blaNDM (52.6%) predominant followed by blaIMP (30.0%). Escherichia coli (46.4%) and Klebsiella spp. (38.3%) were the dominant species. Whole-genome sequencing was performed on 169 representative isolates with a combination of short and long reads using Illumina and Nanopore technology. Two distinct lineages of blaKPC-2-positive Klebsiella pneumoniae (ST11 and ST258) were identified with ST11 carrying yersiniabactin gene ybt-9 on ICEKp3. ST131 E. coli producing IMP-4 was present throughout the study period. The blaNDM and blaIMP genes were mainly carried in IncX3 and IncN-ST7 plasmids, respectively. blaOXA-48-like gene was carried in the IncX3 plasmid in E. coli and in the ColKP3 plasmid in K. pneumoniae. A lineage of K. pneumoniae with blaNDM-1 plus blaOXA-232 in distinct plasmids of IncF1B/IncHI1B was identified and associated with prior hospitalization overseas. This study highlights the threat of multiple types of CPE, with the predominance of blaNDM and blaIMP among CPE in our hospitals. Enhanced containment strategies are needed to mitigate the trend of rapidly rising CPE in healthcare settings.

A multicenter study investigating SARS-CoV-2 in tertiary-care hospital wastewater. viral burden correlates with increasing hospitalized cases as well as hospital-associated transmissions and outbreaks.

SARS-CoV-2 has been detected in wastewater and its abundance correlated with community COVID-19 cases, hospitalizations and deaths. We sought to use wastewater-based detection of SARS-CoV-2 to assess the epidemiology of SARS-CoV-2 in hospitals. Between August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totaling > 2100 dedicated inpatient beds) were collected. Hospital-1 and Hospital-2 could be captured with a single sampling point whereas Hospital-3 required three separate monitoring sites. Wastewater samples were concentrated and cleaned using the 4S-silica column method and assessed for SARS-CoV-2 gene-targets (N1, N2 and E) and controls using RT-qPCR. Wastewater SARS-CoV-2 as measured by quantification cycle (Cq), genome copies and genomes normalized to the fecal biomarker PMMoV were compared to the total daily number of patients hospitalized with active COVID-19, confirmed cases of hospital-acquired infection, and the occurrence of unit-specific outbreaks. Of 165 wastewater samples collected, 159 (96%) were assayable. The N1-gene from SARS-CoV-2 was detected in 64.1% of samples, N2 in 49.7% and E in 10%. N1 and N2 in wastewater increased over time both in terms of the amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations at those sites with single monitoring points (Pearson's r = 0.679, P < 0.0001, Pearson's r = 0.799, P < 0.0001, respectively). Despite increasing hospitalizations through the study period, nosocomial-acquired cases of COVID-19 (Pearson's r = 0.389, P < 0.001) and unit-specific outbreaks were discernable with significant increases in detectable SARS-CoV-2 N1-RNA (median 112 copies/ml) versus outbreak-free periods (0 copies/ml; P < 0.0001). Wastewater-based monitoring of SARS-CoV-2 represents a promising tool for SARS-CoV-2 passive surveillance and case identification, containment, and mitigation in acute- care medical facilities.