ABSTRACT
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 Californias 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.
Subject(s)
COVID-19 , Encephalitis, CaliforniaABSTRACT
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.