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1.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329062

ABSTRACT

Monitoring wastewater samples at building-level resolution screens large populations for SARS-CoV-2, prioritizing testing and isolation efforts. Here we perform untargeted metatranscriptomics on virally-enriched wastewater samples from 10 locations on the UC San Diego campus, demonstrating that resulting bacterial taxonomic and functional profiles discriminate SARS-CoV-2 status even without direct detection of viral transcripts. Our proof-of-principle reveals emergent threats through changes in the human microbiome, suggesting new approaches for untargeted wastewater-based epidemiology.

2.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327572

ABSTRACT

Epitopes are short amino acid sequences that define the antigen signature to which an antibody binds. In light of the current pandemic, epitope analysis and prediction is paramount to improving serological testing and developing vaccines. In this paper, we leverage known epitope sequences from SARS-CoV, SARS-CoV-2 and other Coronaviridae and use those known epitopes to identify additional antigen regions in 62k SARS-CoV-2 genomes. Additionally, we present epitope distribution across SARS-CoV-2 genomes, locate the most commonly found epitopes, discuss where epitopes are located on proteins, and how epitopes can be grouped into classes. We also discuss the mutation density of different regions on proteins using a big data approach. We find that there are many conserved epitopes between SARS-CoV-2 and SARS-CoV, with more diverse sequences found in Nucleoprotein and Spike Glycoprotein.

3.
Viruses ; 13(12)2021 12 03.
Article in English | MEDLINE | ID: covidwho-1554806

ABSTRACT

SARS-CoV-2 genomic sequencing efforts have scaled dramatically to address the current global pandemic and aid public health. However, autonomous genome annotation of SARS-CoV-2 genes, proteins, and domains is not readily accomplished by existing methods and results in missing or incorrect sequences. To overcome this limitation, we developed a novel semi-supervised pipeline for automated gene, protein, and functional domain annotation of SARS-CoV-2 genomes that differentiates itself by not relying on the use of a single reference genome and by overcoming atypical genomic traits that challenge traditional bioinformatic methods. We analyzed an initial corpus of 66,000 SARS-CoV-2 genome sequences collected from labs across the world using our method and identified the comprehensive set of known proteins with 98.5% set membership accuracy and 99.1% accuracy in length prediction, compared to proteome references, including Replicase polyprotein 1ab (with its transcriptional slippage site). Compared to other published tools, such as Prokka (base) and VAPiD, we yielded a 6.4- and 1.8-fold increase in protein annotations. Our method generated 13,000,000 gene, protein, and domain sequences-some conserved across time and geography and others representing emerging variants. We observed 3362 non-redundant sequences per protein on average within this corpus and described key D614G and N501Y variants spatiotemporally in the initial genome corpus. For spike glycoprotein domains, we achieved greater than 97.9% sequence identity to references and characterized receptor binding domain variants. We further demonstrated the robustness and extensibility of our method on an additional 4000 variant diverse genomes containing all named variants of concern and interest as of August 2021. In this cohort, we successfully identified all keystone spike glycoprotein mutations in our predicted protein sequences with greater than 99% accuracy as well as demonstrating high accuracy of the protein and domain annotations. This work comprehensively presents the molecular targets to refine biomedical interventions for SARS-CoV-2 with a scalable, high-accuracy method to analyze newly sequenced infections as they arise.


Subject(s)
COVID-19/virology , Genome, Viral , Molecular Sequence Annotation , SARS-CoV-2/genetics , Amino Acid Sequence , Base Sequence , Computational Biology , Humans , Mutation , Protein Binding , Protein Domains , Spike Glycoprotein, Coronavirus/genetics
4.
Pediatrics ; 148(1)2021 07.
Article in English | MEDLINE | ID: covidwho-1533449

ABSTRACT

BACKGROUND AND OBJECTIVES: Depression is common, and suicide rates are increasing. Adolescent depression screening might miss those with unidentified suicide risk. Our primary objective in this study was to compare the magnitude of positive screen results across different approaches. METHODS: From June 2019 to October 2020, 803 mostly Medicaid-enrolled adolescents aged ≥12 years with no recent history of depression or self-harm were screened with the Patient Health Questionnaire-9 Modified for Adolescents (PHQ-9A) and the Ask Suicide-Screening Questions (ASQ) across 12 primary care practices. Two PHQ-9A screening strategies were evaluated: screening for any type of depression or other mental illness (positive on any item) or screening for major depressive disorder (MDD) (total score ≥10). RESULTS: Overall, 56.4% of patients screened positive for any type of depression, 24.7% screened positive for MDD, and 21.1% screened positive for suicide risk. Regardless of PHQ-9A screening strategy, the ASQ identified additional subjects (eg, 2.2% additional cases compared with screening for any type of depression or other mental illness and 8.3% additional cases compared with screening positive for MDD). Of those with ≥6 month follow-up, 22.9% screened positive for any type of depression (n = 205), 35.6% screened positive for MDD (n = 90), and 42.7% with a positive ASQ result (n = 75) had a depression or self-harm diagnosis or an antidepressant prescription. CONCLUSIONS: Suicide risk screening identifies cases not identified by depression screening. In this study, we underscore opportunities and challenges in primary care related to the high prevalence of depression and suicide risk. Research is needed regarding optimal screening strategies and to help clinicians manage the expected number of screening-identified adolescents.


Subject(s)
Depression/epidemiology , Mass Screening/methods , Primary Health Care/methods , Suicide/statistics & numerical data , Adolescent , Antidepressive Agents/therapeutic use , COVID-19/epidemiology , COVID-19/psychology , Child , Depression/diagnosis , Depression/drug therapy , Depressive Disorder, Major/diagnosis , Depressive Disorder, Major/drug therapy , Depressive Disorder, Major/epidemiology , Female , Humans , Loneliness , Male , Mental Disorders/diagnosis , Mental Disorders/epidemiology , Pandemics , Risk Factors , SARS-CoV-2 , Social Isolation , Suicide/prevention & control , Young Adult
5.
Microbiome ; 9(1): 132, 2021 06 08.
Article in English | MEDLINE | ID: covidwho-1262519

ABSTRACT

BACKGROUND: SARS-CoV-2 is an RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Viruses exist in complex microbial environments, and recent studies have revealed both synergistic and antagonistic effects of specific bacterial taxa on viral prevalence and infectivity. We set out to test whether specific bacterial communities predict SARS-CoV-2 occurrence in a hospital setting. METHODS: We collected 972 samples from hospitalized patients with COVID-19, their health care providers, and hospital surfaces before, during, and after admission. We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and used these bacterial profiles to classify SARS-CoV-2 RNA detection with a random forest model. RESULTS: Sixteen percent of surfaces from COVID-19 patient rooms had detectable SARS-CoV-2 RNA, although infectivity was not assessed. The highest prevalence was in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples more closely resembled the patient microbiome compared to floor samples, SARS-CoV-2 RNA was detected less often in bed rail samples (11%). SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity in both human and surface samples and higher biomass in floor samples. 16S microbial community profiles enabled high classifier accuracy for SARS-CoV-2 status in not only nares, but also forehead, stool, and floor samples. Across these distinct microbial profiles, a single amplicon sequence variant from the genus Rothia strongly predicted SARS-CoV-2 presence across sample types, with greater prevalence in positive surface and human samples, even when compared to samples from patients in other intensive care units prior to the COVID-19 pandemic. CONCLUSIONS: These results contextualize the vast diversity of microbial niches where SARS-CoV-2 RNA is detected and identify specific bacterial taxa that associate with the viral RNA prevalence both in the host and hospital environment. Video Abstract.


Subject(s)
COVID-19 , SARS-CoV-2 , Hospitals , Humans , Pandemics , Phylogeny , RNA, Ribosomal, 16S/genetics , RNA, Viral/genetics
6.
Sci Rep ; 11(1): 8988, 2021 04 26.
Article in English | MEDLINE | ID: covidwho-1203449

ABSTRACT

Rapid tests for active SARS-CoV-2 infections rely on reverse transcription polymerase chain reaction (RT-PCR). RT-PCR uses reverse transcription of RNA into complementary DNA (cDNA) and amplification of specific DNA (primer and probe) targets using polymerase chain reaction (PCR). The technology makes rapid and specific identification of the virus possible based on sequence homology of nucleic acid sequence and is much faster than tissue culture or animal cell models. However the technique can lose sensitivity over time as the virus evolves and the target sequences diverge from the selective primer sequences. Different primer sequences have been adopted in different geographic regions. As we rely on these existing RT-PCR primers to track and manage the spread of the Coronavirus, it is imperative to understand how SARS-CoV-2 mutations, over time and geographically, diverge from existing primers used today. In this study, we analyze the performance of the SARS-CoV-2 primers in use today by measuring the number of mismatches between primer sequence and genome targets over time and spatially. We find that there is a growing number of mismatches, an increase by 2% per month, as well as a high specificity of virus based on geographic location.


Subject(s)
DNA Primers/genetics , DNA Probes/genetics , Reverse Transcriptase Polymerase Chain Reaction/methods , SARS-CoV-2/genetics , Genome, Viral , Mutation
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