Evidence map›Paper›PMID 35982656›Full record

ArticlebioRxiv : the preprint server for biology2022

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

Jason A Rothman, Andrew Saghir, Seung-Ah Chung, Nicholas Boyajian, Thao Dinh, Jinwoo Kim, Jordan Oval, Vivek Sharavanan, Courtney York, Amity G Zimmer-Faust and 4 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 2 institutions in 1 country.

Jason A RothmanDepartment of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA.
Andrew SaghirDepartment of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA.
Seung-Ah ChungGenomics High-Throughput Facility, Department of Biological Chemistry, University of California, Irvine, Irvine, CA, USA.
Nicholas BoyajianDepartment of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA.
Thao DinhDepartment of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA.
Jinwoo KimDepartment of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA.
Jordan OvalDepartment of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA.
Vivek SharavananDepartment of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA.
Courtney YorkDepartment of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA.
Amity G Zimmer-FaustSouthern California Coastal Water Research Project, Costa Mesa, CA, USA.
Kylie LangloisSouthern California Coastal Water Research Project, Costa Mesa, CA, USA.
Joshua A SteeleSouthern California Coastal Water Research Project, Costa Mesa, CA, USA.
John F GriffithSouthern California Coastal Water Research Project, Costa Mesa, CA, USA.
Katrine L WhitesonDepartment of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA.
University of California, Irvine · USSouthern California Coastal Water Research Project · US

Funding

Univ.of Calif., Irvine Cancer Center Support GrantP30CA062203 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI Melanie Funes · 1994 to 2026
$57.9M
PacBio RS Single Molecule, Real-Time (SMRT) DNA SequencerS10OD010794 · OD · UNIVERSITY OF CALIFORNIA-IRVINE · PI SANDMEYER, SUZANNE · 2012 to 2012
$600k
High-Throughput DNA SequencerS10OD021718 · OD · UNIVERSITY OF CALIFORNIA-IRVINE · PI SANDMEYER, SUZANNE · 2016 to 2016
$600k
High Throughput DNA SequencerS10RR025496 · NCRR · UNIVERSITY OF CALIFORNIA-IRVINE · PI SANDMEYER, SUZANNE · 2009 to 2009
$500k
NCI NIH HHS P30 CA062203NCRR NIH HHS S10 RR025496NIH HHS S10 OD010794NIH HHS S10 OD021718
6 · The paper itself

Abstract

Municipal wastewater provides a representative sample of human fecal waste across a catchment area and contains a wide diversity of microbes. Sequencing wastewater samples provides information about human-associated and medically-important microbial populations, and may be useful to assay disease prevalence and antimicrobial resistance (AMR). Here, we present a study in which we used untargeted metatranscriptomic sequencing on RNA extracted from 275 sewage influent samples obtained from eight wastewater treatment plants (WTPs) representing approximately 16 million people in Southern California between August 2020 - August 2021. We characterized bacterial and viral transcripts, assessed metabolic pathway activity, and identified over 2,000 AMR genes/variants across all samples. Because we did not deplete ribosomal RNA, we have a unique window into AMR carried as ribosomal mutants. We show that AMR diversity varied between WTPs and that the relative abundance of many individual AMR genes/variants increased over time and may be connected to antibiotic use during the COVID-19 pandemic. Similarly, we detected transcripts mapping to human pathogenic bacteria and viruses suggesting RNA sequencing is a powerful tool for wastewater-based epidemiology and that there are geographical signatures to microbial transcription. We captured the transcription of gene pathways common to bacterial cell processes, including central carbon metabolism, nucleotide synthesis/salvage, and amino acid biosynthesis. We also posit that due to the ubiquity of many viruses and bacteria in wastewater, new biological targets for microbial water quality assessment can be developed. To the best of our knowledge, our study provides the most complete longitudinal metatranscriptomic analysis of a large population's wastewater to date and demonstrates our ability to monitor the presence and activity of microbes in complex samples. By sequencing RNA, we can track the relative abundance of expressed AMR genes/variants and metabolic pathways, increasing our understanding of AMR activity across large human populations and sewer sheds.

Indexed as

antimicrobial resistanceenvironmental microbiologymetatranscriptomicsmicrobial ecologyWastewater

Identifiers

PMID35982656
PMCPMC9387120
OpenAlexW4289856283

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.