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Fast Evaluation of Viral Emerging Risks (Fever)

A computational tool for biosurveillance, diagnostics, and mutation typing of emerging viral pathogens

Bibliographic Data

ID19594775
AuthorsZachary R Stromberg (0000-0002-1137-1128, Los Alamos National Laboratory), James Theiler (0000-0003-1888-3684, Los Alamos National Laboratory), Brian Foley (0000-0002-1086-0296, Los Alamos National Laboratory), Adán Myers y Gutiérrez (0000-0002-3457-1632, Los Alamos National Laboratory), Attelia Hollander (0000-0002-6347-8074, Los Alamos National Laboratory), Samantha J Courtney (0000-0001-9277-2937, Los Alamos National Laboratory), Jason Gans (0000-0002-7151-3108, Los Alamos National Laboratory), Alina Deshpande (0000-0003-4541-4410, Los Alamos National Laboratory), Ebany J Martinez-Finley (0000-0002-2639-9107, Presbyterian Healthcare Services), Jason Mitchell (0000-0002-2091-0509, Presbyterian Healthcare Services), Harshini Mukundan (0000-0002-0931-0545, Los Alamos National Laboratory), Karina Yusim (Los Alamos National Laboratory), Jessica Z Kubicek-Sutherland (0000-0001-6215-4871, Los Alamos National Laboratory, corresponding author)
EditorsPriyanka Baloni
Year2022
Volume2
Issue2
Pagese0000207
Publication date2022-02-24
Open AccessYes
TypeARTICLE
VenuePLOS Global Public Health (JOURNAL)
Journal identifiersISSN: 2767-3375 • E-ISSN: 2767-3375
PublisherPublic Library of Science (PLoS) (PUBLISHER)
DOI10.1371/journal.pgph.0000207
PMID36962401
OpenAlexW4226025148
LanguageEN
References cited71

Viral pathogens can rapidly evolve, adapt to novel hosts, and evade human immunity. The early detection of emerging viral pathogens through biosurveillance coupled with rapid and accurate diagnostics are required to mitigate global pandemics. However, RNA viruses can mutate rapidly, hampering biosurveillance and diagnostic efforts. Here, we present a novel computational approach called FEVER (Fast Evaluation of Viral Emerging Risks) to design assays that simultaneously accomplish: 1) broad-coverage biosurveillance of an entire group of viruses, 2) accurate diagnosis of an outbreak strain, and 3) mutation typing to detect variants of public health importance. We demonstrate the application of FEVER to generate assays to simultaneously 1) detect sarbecoviruses for biosurveillance; 2) diagnose infections specifically caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); and 3) perform rapid mutation typing of the D614G SARS-CoV-2 spike variant associated with increased pathogen transmissibility. These FEVER assays had a high in silico recall (predicted positive) up to 99.7% of 525,708 SARS-CoV-2 sequences analyzed and displayed sensitivities and specificities as high as 92.4% and 100% respectively when validated in 100 clinical samples. The D614G SARS-CoV-2 spike mutation PCR test was able to identify the single nucleotide identity at position 23,403 in the viral genome of 96.6% SARS-CoV-2 positive samples without the need for sequencing. This study demonstrates the utility of FEVER to design assays for biosurveillance, diagnostics, and mutation typing to rapidly detect, track, and mitigate future outbreaks and pandemics caused by emerging viruses

Biology · Computational biology · Disease · Gene · In silico · Outbreak · Pandemic · Typing · Medicine · SARS-CoV-2 and COVID-19 Research · SARS-CoV-2 detection and testing · Viral Infections and Outbreaks Research · Genetics · Virology

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