scholarly journals RNA viromics of Southern California wastewater and detection of SARS-CoV-2 single nucleotide variants.

Author(s):  
Jason A. Rothman ◽  
Theresa B. Loveless ◽  
Joseph Kapcia ◽  
Eric D. Adams ◽  
Joshua A. Steele ◽  
...  

Municipal wastewater provides an integrated sample of a diversity of human-associated microbes across a sewershed, including viruses. Wastewater-based epidemiology (WBE) is a promising strategy to detect pathogens and may serve as an early-warning system for disease outbreaks. Notably, WBE has garnered substantial interest during the COVID-19 pandemic to track disease burden through analyses of SARS-CoV-2 RNA. Throughout the COVID-19 outbreak, tracking SARS-CoV-2 in wastewater has been an important tool for understanding the spread of the virus. Unlike traditional sequencing of SARS-CoV-2 isolated from clinical samples, which adds testing burden to the healthcare system, in this study, metatranscriptomics was used to sequence virus directly from wastewater. Here, we present a study in which we explored RNA viral diversity through sequencing 94 wastewater influent samples across seven treatment plants (WTPs), collected August 2020 – January 2021, representing approximately 16 million people in Southern California. Enriched viral libraries identified a wide diversity of RNA viruses that differed between WTPs and over time, with detected viruses including coronaviruses, influenza A, and noroviruses. Furthermore, single nucleotide variants (SNVs) of SARS-CoV-2 were identified in wastewater and we measured proportions of overall virus and SNVs across several months. We detected several SNVs that are markers for clinically-important SARS-CoV-2 variants, along with SNVs of unknown function, prevalence, or epidemiological consequence. Our study shows the potential of WBE to detect viruses in wastewater and to track the diversity and spread of viral variants in urban and suburban locations, which may aid public health efforts to monitor disease outbreaks. Importance: Wastewater based epidemiology (WBE) can detect pathogens across sewersheds, which represents the collective waste of human populations. As there is a wide diversity of RNA viruses in wastewater, monitoring the presence of these viruses is useful for public health, industry, and ecological studies. Specific to public health, WBE has proven valuable during the COVID-19 pandemic to track the spread of SARS-CoV-2 without adding burden to healthcare systems. In this study, we used metatranscriptomics and RT-ddPCR to assay RNA viruses across Southern California wastewater from August 2020 – January 2021, representing approximately 16 million people from Los Angeles, Orange, and San Diego counties. We found that SARS-CoV-2 quantification in wastewater correlates well with county-wide COVID-19 case data, and that we can detect SARS-CoV-2 single nucleotide variants through sequencing. Likewise, WTPs harbored different viromes, and we detected other human pathogens such as noroviruses and adenoviruses, furthering our understanding of wastewater viral ecology.

2021 ◽  
Author(s):  
Jason A Rothman ◽  
Theresa B Loveless ◽  
Joseph Kapcia ◽  
Eric D Adams ◽  
Joshua A Steele ◽  
...  

Abstract: Municipal wastewater provides an integrated sample of a diversity of human-associated microbes across a sewershed, including viruses. Wastewater-based epidemiology (WBE) is a promising strategy to detect pathogens and may serve as an early-warning system for disease outbreaks. Notably, WBE has garnered substantial interest during the COVID-19 pandemic to track disease burden through analyses of SARS-CoV-2 RNA. Throughout the COVID-19 outbreak, tracking SARS-CoV-2 in wastewater has been an important tool for understanding the spread of the virus. Unlike traditional sequencing of SARS-CoV-2 isolated from clinical samples, which adds testing burden to the healthcare system, in this study, metatranscriptomics was used to sequence virus directly from wastewater. Here, we present a study in which we explored RNA viral diversity through sequencing 94 wastewater influent samples across seven treatment plants (WTPs), collected August 2020 - January 2021, representing approximately 16 million people in Southern California. Enriched viral libraries identified a wide diversity of RNA viruses that differed between WTPs and over time, with detected viruses including coronaviruses, influenza A, and noroviruses. Furthermore, single nucleotide variants (SNVs) of SARS-CoV-2 were identified in wastewater and we measured proportions of overall virus and SNVs across several months. We detected several SNVs that are markers for clinically-important SARS-CoV-2 variants, along with SNVs of unknown function, prevalence, or epidemiological consequence. Our study shows the potential of WBE to detect viruses in wastewater and to track the diversity and spread of viral variants in urban and suburban locations, which may aid public health efforts to monitor disease outbreaks. Importance: Wastewater based epidemiology (WBE) can detect pathogens across sewersheds, which represents the collective waste of human populations. As there is a wide diversity of RNA viruses in wastewater, monitoring the presence of these viruses is useful for public health, industry, and ecological studies. Specific to public health, WBE has proven valuable during the COVID-19 pandemic to track the spread of SARS-CoV-2 without adding burden to healthcare systems. In this study, we used metatranscriptomics and RT-ddPCR to assay RNA viruses across Southern California wastewater from August 2020 - January 2021, representing approximately 16 million people from Los Angeles, Orange, and San Diego counties. We found that SARS-CoV-2 quantification in wastewater correlates well with county-wide COVID-19 case data, and that we can detect SARS-CoV-2 single nucleotide variants through sequencing. Likewise, WTPs harbored different viromes, and we detected other human pathogens such as noroviruses and adenoviruses, furthering our understanding of wastewater viral ecology.


2021 ◽  
Author(s):  
Clare L Fasching ◽  
Venice Servellita ◽  
Bridget McKay ◽  
Vaishnavi Nagesh ◽  
James P Broughton ◽  
...  

Laboratory tests for the accurate and rapid identification of SARS-CoV-2 variants have the potential to guide the treatment of COVID-19 patients and inform infection control and public health surveillance efforts. Here we present the development and validation of a COVID-19 variant DETECTR assay incorporating loop-mediated isothermal amplification (LAMP) followed by CRISPR-Cas12 based identification of single nucleotide polymorphism (SNP) mutations in the SARS-CoV-2 spike (S) gene. This assay targets the L452R, E484K, and N501Y mutations associated with nearly all circulating viral lineages. In a comparison of three different Cas12 enzymes, only the newly identified enzyme CasDx1 was able to accurately identify all three targeted SNP mutations. We developed a data analysis pipeline for CRISPR-based SNP identification using the assay from 91 clinical samples (Ct < 30), yielding an overall SNP concordance and agreement with SARS-CoV-2 lineage classification of 100% compared to viral whole-genome sequencing. These findings highlight the potential utility of CRISPR-based mutation detection for clinical and public health diagnostics.


2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Robert Fragoza ◽  
Jishnu Das ◽  
Shayne D. Wierbowski ◽  
Jin Liang ◽  
Tina N. Tran ◽  
...  

Abstract Each human genome carries tens of thousands of coding variants. The extent to which this variation is functional and the mechanisms by which they exert their influence remains largely unexplored. To address this gap, we leverage the ExAC database of 60,706 human exomes to investigate experimentally the impact of 2009 missense single nucleotide variants (SNVs) across 2185 protein-protein interactions, generating interaction profiles for 4797 SNV-interaction pairs, of which 421 SNVs segregate at > 1% allele frequency in human populations. We find that interaction-disruptive SNVs are prevalent at both rare and common allele frequencies. Furthermore, these results suggest that 10.5% of missense variants carried per individual are disruptive, a higher proportion than previously reported; this indicates that each individual’s genetic makeup may be significantly more complex than expected. Finally, we demonstrate that candidate disease-associated mutations can be identified through shared interaction perturbations between variants of interest and known disease mutations.


2021 ◽  
Author(s):  
Justin Landis ◽  
Razia Moorad ◽  
Linda J. Pluta ◽  
Carolina Caro-Vegas ◽  
Ryan P. McNamara ◽  
...  

Variants of concern (VOC) in SARS-CoV-2 refer to viral genomes that differ significantly from the ancestor virus and that show the potential for higher transmissibility and/or worse clinical progression. VOC have the potential to disrupt ongoing public health measures and vaccine efforts. Yet, little is known regarding how frequently different viral variants emerge and under what circumstances. We report a longitudinal study to determine the degree of SARS-CoV-2 sequence evolution in 94 COVID-19 cases and to estimate the frequency at which highly diverse variants emerge. 2 cases accumulated 9 single-nucleotide variants (SNVs) over a two-week period and 1 case accumulated 23 SNVs over a three-week period, including three non-synonymous mutations in the Spike protein (D138H, E554D, D614G). We estimate that in 2% of COVID cases, viral variants with multiple mutations, including in the Spike glycoprotein, can become the dominant strains in as little as one month of persistent in patient virus replication. This suggests the continued local emergence of VOC independent of travel patterns. Surveillance by sequencing for (i) viremic COVID-19 patients, (ii) patients suspected of re-infection, and (iii) patients with diminished immune function may offer broad public health benefits.


2020 ◽  
Author(s):  
Ping Song ◽  
Sherry X. Chen ◽  
Yan Helen Yan ◽  
Alessandro Pinto ◽  
Lauren Y. Cheng ◽  
...  

DNA sequence variants with low allele frequencies below 1% are difficult to detect and quantitate by sequencing, due to the intrinsic error of sequencing-by-synthesis (NGS). Unique molecular identifier barcodes can in principle help NGS detect mutations down to 0.1% variant allele frequency (VAF), but require extremely high sequencing depths of over 25,000x, rendering high sensitivity mutation detection out of reach for most research and clinical samples. Here, we present the multiplex blocker displacement amplification (mBDA) method to selectively enrich DNA variants by an average of 300-fold in highly multiplexed NGS settings. On a 80-plex human single nucleotide polymorphism panel, mBDA achieves a 0.019% VAF limit of detection for single nucleotide variants, using only 250x sequencing depth, and detects human cell line contamination down to 0.07%. Using this technology, we constructed a 16-plex melanoma NGS panel covering 145 actionable mutations across 9 genes, and applied it to 19 fresh/frozen tumor biopsy tissue samples with high tumor fractions. We found low VAF mutations (0.2% to 5%) in 37% of the samples (7/19, 95% confidence interval 19%-58%). These results suggest that tumor heterogeneity could be significantly more pervasive than previously recognized, and can contribute significantly to acquired drug resistance to targeted therapies. We also validate mBDA panels on clinical cell-free DNA samples from lung cancer patients.


2018 ◽  
Author(s):  
Laurits Skov ◽  
Ruoyun Hui ◽  
Asger Hobolth ◽  
Aylwyn Scally ◽  
Mikkel Heide Schierup ◽  
...  

AbstractHuman populations out of Africa have experienced at least two bouts of introgression from archaic humans, from Neanderthals and Denisovans. In Papuans there is prior evidence of both these introgressions. Here we present a new approach to detect segments of individual genomes of archaic origin without using an archaic reference genome. The approach is based on a hidden Markov model that identifies genomic regions with a high density of single nucleotide variants (SNVs) not seen in unadmixed populations. We show using simulations that this provides a powerful approach to identifying segments of archaic introgression with a small rate of false detection. Furthermore our approach is able to accurately infer admixture proportions and divergence time of human and archaic populations.We apply the model to detect archaic introgression in 89 Papuans and show how the identified segments can be assigned to likely Neanderthal or Denisovan origin. We report more Denisovan admixture than previous studies and directly find a shift in size distribution of fragments of Neanderthal and Denisovan origin that is compatible with a difference in admixture time. Furthermore, we identify small amounts of Denisova ancestry in West Eurasians, South East Asians and South Asians.


Author(s):  
Mohd. Azhar ◽  
Rhythm Phutela ◽  
Manoj Kumar ◽  
Asgar Hussain Ansari ◽  
Riya Rauthan ◽  
...  

Rapid detection of pathogenic sequences or variants in DNA and RNA through a point-of-care diagnostic approach is valuable for accelerated clinical prognosis as has been witnessed during the recent COVID-19 outbreak. Traditional methods relying on qPCR or sequencing are difficult to implement in settings with limited resources necessitating the development of accurate alternative testing strategies that perform robustly. Here, we present FnCas9 Editor Linked Uniform Detection Assay (FELUDA) that employs a direct Cas9 based enzymatic readout for detecting nucleotide sequences and identifying nucleobase identity without the requirement of trans-cleavage activity of reporter molecules. We demonstrate that FELUDA is 100% accurate in detecting single nucleotide variants (SNVs) including heterozygous carriers of a mutation and present a simple design strategy in the form of a web-tool, JATAYU, for its implementation. FELUDA is semi quantitative, can be adapted to multiple signal detection platforms and can be quickly designed and deployed for versatile applications such as infectious disease outbreaks like COVID-19. Using a lateral flow readout within 1h, FELUDA shows 100% sensitivity and 97% specificity across all range of viral loads in clinical samples. In combination with RT-RPA and a smartphone application True Outcome Predicted via Strip Evaluation (TOPSE), we present a prototype for FELUDA for CoV-2 detection at home.


2020 ◽  
Vol 6 (50) ◽  
pp. eabd9230
Author(s):  
Yuta Suzuki ◽  
Eugene W. Myers ◽  
Shinichi Morishita

Our understanding of centromere sequence variation across human populations is limited by its extremely long nested repeat structures called higher-order repeats that are challenging to sequence. Here, we analyzed chromosomes 11, 17, and X using long-read sequencing data for 36 individuals from diverse populations including a Han Chinese trio and 21 Japanese. We revealed substantial structural diversity with many previously unidentified variant higher-order repeats specific to individuals characterizing rapid, haplotype-specific evolution of human centromeric arrays, while frequent single-nucleotide variants are largely conserved. We found a characteristic pattern shared among prevalent variants in human and chimpanzee. Our findings pave the way for studying sequence evolution in human and primate centromeres.


2019 ◽  
Vol 85 (10) ◽  
Author(s):  
Sabrina Diemert ◽  
Tao Yan

ABSTRACT Municipal wastewater includes human waste that contains both commensal and pathogenic enteric microorganisms, and this collective community microbiome can be monitored for community diseases. In a previous study, we assessed the salmonellosis disease burden using municipal wastewater from Honolulu, Hawaii, which was monitored over a 54-week period. During that time, a strain of Salmonella enterica serovar Paratyphi B variant L(+) tartrate(+) (also known as Salmonella enterica serovar Paratyphi B variant Java) was identified; this strain was detected simultaneously with a clinically reported outbreak, and pulsed-field gel electrophoresis patterns were identical for clinical and municipal wastewater isolates. Months after the outbreak subsided, the same pulsotype was detected as the dominant pulsotype in municipal wastewater samples, with no corresponding clinical cases reported. Using genomic characterization (including core single-nucleotide polymorphism alignment, core genome multilocus sequence typing, and screening for virulence and antibiotic resistance genes), all S. Java municipal wastewater isolates were determined to be clonal, indicating a resurgence of the original outbreak strain. This demonstrates the feasibility and utility of municipal wastewater surveillance for determining enteric disease outbreaks that may be missed by traditional clinical surveillance methods. IMPORTANCE Underdetection of microbial infectious disease outbreaks in human communities carries enormous health costs and is an ongoing problem in public health monitoring (which relies almost exclusively on data from health clinics). Surveillance of municipal wastewater for community-level monitoring of infectious disease burdens has the potential to fill this information gap, due to its easy access to the mixed community microbiome. In the present study, the genomes of 21 S. Java isolates (collected from municipal wastewater in Honolulu) were analyzed; results showed that the same Salmonella strain that caused a known salmonellosis clinical outbreak in spring 2010 remerged as the most dominant strain in municipal wastewater in spring 2011, indicating a new outbreak that was not detected by health clinics. Our results show that wastewater monitoring holds great promise to inform the field of public health regarding outbreak status within communities.


2020 ◽  
Author(s):  
Jameson D. Voss ◽  
Martin Skarzynski ◽  
Erin M. McAuley ◽  
Ezekiel J. Maier ◽  
Thomas Gibbons ◽  
...  

AbstractIntroductionThe coronavirus disease 2019 (COVID-19) pandemic is a global public health emergency causing a disparate burden of death and disability around the world. The molecular characteristics of the virus that predict better or worse outcome are largely still being discovered.MethodsWe downloaded 155,958 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from GISAID and evaluated whether variants improved prediction of reported severity beyond age and region. We also evaluated specific variants to determine the magnitude of association with severity and the frequency of these variants among the genomes.ResultsLogistic regression models that included viral genomic variants outperformed other models (AUC=0.91 as compared with 0.68 for age and gender alone; p<0.001). Among individual variants, we found 17 single nucleotide variants in SARS-CoV-2 have more than two-fold greater odds of being associated with higher severity and 67 variants associated with ≤ 0.5 times the odds of severity. The median frequency of associated variants was 0.15% (interquartile range 0.09%-0.45%). Altogether 85% of genomes had at least one variant associated with patient outcome.ConclusionNumerous SARS-CoV-2 variants have two-fold or greater association with odds of mild or severe outcome and collectively, these variants are common. In addition to comprehensive mitigation efforts, public health measures should be prioritized to control the more severe manifestations of COVID-19 and the transmission chains linked to these severe cases.


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