Longitudinal metatranscriptomic sequencing of Southern California wastewater representing 16 million people from August 2020–21 reveals widespread transcription of antibiotic resistance genes

Rothman, Jason A.; Saghir, Andrew; Chung, Seung-Ah; Boyajian, Nicholas; Dinh, Thao; Kim, Jin-Woo; Oval, Jordan; Sharavanan, Vivek; York, Courtney; Zimmer‐Faust, Amity G.; Langlois, Kylie; Steele, Joshua A.; Griffith, John F.; Whiteson, Katrine

doi:10.1016/j.watres.2022.119421

Cited by 7 publications

(5 citation statements)

References 76 publications

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“…We previously reported the sample collection and handling procedure in Rothman et al 2021 (17) and Rothman et al 2022 (42). Briefly, we collected 317 1-liter 24-hour composite influent wastewater samples by autosampler at eight WTPs across Southern California between April 2020 -August 2021 (Table 1).…”

Section: Sample Collection and Handlingmentioning

confidence: 99%

“…We used two separate RNA extraction and library preparation protocols for the samples in this study. For one set (N = 269), we used a protocol based on Crits-Christoph 2021 (25) and Rothman 2021 (17), and as the samples' RNA was extracted for both this study and Rothman et al 2022 (42), we refer to that paper for detailed RNA extraction methods. Briefly, samples were pasteurized at 65 °C for 90 minutes in a water bath, filtered through 0.22-µM sterile filters (VWR, Radnor, PA), then centrifugated at 3000 xg with 10-kDa filters (MilliporeSigma, Burlington, MA) and RNA was extracted with an Invitrogen PureLink RNA Mini Kit plus DNase (Invitrogen, Waltham, MA).…”

Section: Wastewater Sample Rna Extractionmentioning

confidence: 99%

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Longitudinal sequencing and variant detection of SARS-CoV-2 across Southern California wastewater from April 2020 – August 2021

Rothman

Saghir

Zimmer‐Faust

et al. 2023

Preprint

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Wastewater based epidemiology (WBE) is a useful method to detect pathogen prevalence and may serve to effectively monitor diseases at a broad scale. WBE has been used throughout the COVID-19 pandemic to track localized and population-level disease burden through the quantification of SARS-CoV-2 RNA present in wastewater. Aside from case load estimation, WBE is being used to assay viral genomic diversity and the emergence of potential SARS-CoV-2 variants. Here, we present a study in which we sequenced RNA extracted from sewage influent samples obtained from eight wastewater treatment plants representing 16 million people in Southern California over April 2020 - August 2021. We sequenced SARS-CoV-2 with two methods: Illumina Respiratory Virus Enrichment and metatranscriptomic sequencing (N = 269), and QIAseq SARS-CoV-2 tiled amplicon sequencing (N = 95). We were able to classify SARS-CoV-2 reads into lineages and sublineages that approximated several named variants across a full year, and we identified a diversity of single nucleotide variants (SNVs) of which many are putatively novel SNVs, and SNVs of unknown potential function and prevalence. Through our retrospective study, we also show that several sublineages of SARS-CoV-2 were detected in wastewater up to several months before clinical detection, which may assist in the prediction of future Variants of Concern. Lastly, we show that sublineage diversity was similar between wastewater treatment plants across Southern California, and that diversity changed by sampling month indicating that WBE is effective across megaregions. As the COVID-19 pandemic moves to new phases, and additional SARS-CoV-2 variants emerge, the ongoing monitoring of wastewater is important to understand local and population-level dynamics of the virus. Our study shows the potential of WBE to detect SARS-CoV-2 variants throughout Southern California's wastewater and track the diversity of viral SNVs and strains in urban and suburban locations. These results will aid in our ability to monitor the evolutionary potential of SARS-CoV-2 and help understand circulating SNVs to further combat COVID-19.

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Section: Sample Collection and Handlingmentioning

confidence: 99%

Section: Wastewater Sample Rna Extractionmentioning

confidence: 99%

Longitudinal sequencing and variant detection of SARS-CoV-2 across Southern California wastewater from April 2020 – August 2021

Rothman

Saghir

Zimmer‐Faust

et al. 2023

Preprint

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show abstract

“…Wastewater-based epidemiology (WBE) refers to the specific detection and tracking of substances 1 , chemicals 2 , genes 3 , 4 , or pathogens 5 in municipal sewage or sludge to assess population health or disease risk. During the COVID-19 pandemic, the WBE field underwent significant reinvestment 6 , wherein PCR-based detection of SARS-CoV-2 was used as a proxy for community infection levels, and amplicon sequencing facilitated the resolution of SARS-CoV-2 variants well before clinical detection 7 – 9 .…”

Section: Introductionmentioning

confidence: 99%

“…These studies have seen mixed success, not been applied at scale, and the extent to which the levels of virus sequences corresponded to community infection levels is unclear. In any case, even the most prevalent wastewater viruses, e.g., human astroviruses and rotaviruses, comprise a very small fraction of the total biomatter in wastewater, especially compared to other microorganisms, such as bacteria 4 , 17 , 21 , 22 .…”

Section: Introductionmentioning

confidence: 99%

Wastewater sequencing reveals community and variant dynamics of the collective human virome

Tisza,

Javornik Cregeen,

Avadhanula

et al. 2023

Nat Commun

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Wastewater is a discarded human by-product, but its analysis may help us understand the health of populations. Epidemiologists first analyzed wastewater to track outbreaks of poliovirus decades ago, but so-called wastewater-based epidemiology was reinvigorated to monitor SARS-CoV-2 levels while bypassing the difficulties and pit falls of individual testing. Current approaches overlook the activity of most human viruses and preclude a deeper understanding of human virome community dynamics. Here, we conduct a comprehensive sequencing-based analysis of 363 longitudinal wastewater samples from ten distinct sites in two major cities. Critical to detection is the use of a viral probe capture set targeting thousands of viral species or variants. Over 450 distinct pathogenic viruses from 28 viral families are observed, most of which have never been detected in such samples. Sequencing reads of established pathogens and emerging viruses correlate to clinical data sets of SARS-CoV-2, influenza virus, and monkeypox viruses, outlining the public health utility of this approach. Viral communities are tightly organized by space and time. Finally, the most abundant human viruses yield sequence variant information consistent with regional spread and evolution. We reveal the viral landscape of human wastewater and its potential to improve our understanding of outbreaks, transmission, and its effects on overall population health.

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“…[11] Recently, WBE has been extended for tracking selected bacterial (Salmonella) and fungal (Candida auris) infections, [12,13] as well as to track the emergence and spread of antimicrobial-resistant (AMR) bacteria within communities. [14][15][16] The ability to broadly and accurately monitor bacterial pathogens at a population level and to address outbreaks before they rise to the level of pandemics could be critical to public health.…”

mentioning

confidence: 99%

Bacterial Wastewater-Based Epidemiology Using Surface-Enhanced Raman Spectroscopy and Machine Learning

Herndon,

Zhang,

Safir

et al. 2024

Preprint

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Wastewater-based epidemiology (WBE) is a powerful tool for monitoring community disease occurrence, but current methods for bacterial detection suffer from limited scalability, the need for a priori knowledge of the target organism, and the high degree of genetic similarity between different strains of the same species. Here, we show that surface-enhanced Raman spectroscopy (SERS) can be a scalable, label-free method for detection of bacteria in wastewater. We preferentially enhance Raman signal from bacteria in wastewater using positively-charged plasmonic gold nanorods (AuNRs) that electrostatically bind to the bacterial surface. Transmission cryoelectron microscopy (cryoEM) confirms that AuNRs bind selectively to bacteria in this wastewater matrix. We spike the bacterial species Staphylococcus epidermidis, Staphylococcus aureus, Serratia marcescens, and Escerichia coli and AuNRs into filter-sterilized wastewater, varying the AuNR concentration to achieve maximum signal across all pathogens. We then collect 540 spectra from each species, and train a machine learning (ML) model to identify bacterial species in wastewater. For bacterial concentrations of 10^9 cells/mL, we achieve an accuracy exceeding 85%. We also demonstrate that this system is effective at environmentally-realistic bacterial concentrations, with a limit of bacterial detection of 10^4 cells/mL. These results are a key first step toward a label-free, high-throughput platform for bacterial WBE.

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Longitudinal metatranscriptomic sequencing of Southern California wastewater representing 16 million people from August 2020–21 reveals widespread transcription of antibiotic resistance genes

Cited by 7 publications

References 76 publications

Longitudinal sequencing and variant detection of SARS-CoV-2 across Southern California wastewater from April 2020 – August 2021

Longitudinal sequencing and variant detection of SARS-CoV-2 across Southern California wastewater from April 2020 – August 2021

Wastewater sequencing reveals community and variant dynamics of the collective human virome

Bacterial Wastewater-Based Epidemiology Using Surface-Enhanced Raman Spectroscopy and Machine Learning

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