Evidence map›Paper›PMID 41822221›Full record

ArticleFrontiers in veterinary science2026

Diagnostic sensitivity and specificity of metagenomic sequencing and qPCR for detection of viruses associated with bovine respiratory disease estimated using Bayesian latent class models.

Emmanuel Donbraye, Lianne McLeod, Zhijian Chai, Stacey R Lacoste, E Luke McCarthy, Janet E Hill, Nathan E N Erickson, Matthew G Links, Simon J G Otto, Yanyun Huang and 1 more

Abstract read
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Article in Frontiers in veterinary science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Emmanuel DonbrayeDepartment of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
Lianne McLeodDepartment of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
Zhijian ChaiDepartment of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
Stacey R LacosteDepartment of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
E Luke McCarthyDepartment of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, SK, Canada.
Janet E HillDepartment of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
Nathan E N EricksonDepartment of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
Matthew G LinksDepartment of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, SK, Canada.
Simon J G OttoHEAT-AMR (Human-Environment-Animal Transdisciplinary AMR) Research Group, School of Public Health, University of Alberta, Edmonton, AB, Canada.
Yanyun HuangPrairie Diagnostic Services Inc., Saskatoon, SK, Canada.
Cheryl L WaldnerDepartment of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Very few studies have examined the diagnostic sensitivity and specificity of currently available laboratory tests for detecting respiratory pathogens in cattle, and even fewer have examined test performance on samples from animals before the onset of clinical disease. Methods: In this study, Bayesian latent class modeling (BLCM) was used to assess diagnostic test performance in the absence of a gold standard on nasal swabs collected from 19 western Canadian feedlots. Viruses associated with bovine respiratory disease (BRD) were identified using qPCR from a commercial diagnostic laboratory from 760 nasal swabs collected from fall-placed calves (FPC) and yearlings (YRL) at and shortly after feedlot arrival. Using BLCM, the qPCR results were compared to previously reported matching nanopore metagenomic sequencing data for these same samples. Based on BLCM, test sensitivities and specificities were estimated for the detection of bovine coronavirus (BCoV), bovine herpesvirus type 1 (BoHV-1), bovine parainfluenza virus type 3 (BPIV-3), bovine respiratory syncytial virus (BRSV), and influenza D virus (IDV). Estimates informed by BLCM were not available for the detection of bovine viral diarrheal virus (BVDV) because qPCR did not detect this virus in any samples. Results: Diagnostic sensitivity of qPCR was higher than metagenomic sequencing for detecting BCoV (qPCR 0.90, 95% CrI 0.81-0.99; sequencing 0.35, 95% CrI 0.25-0.46) and BoHV-1 (qPCR 0.39, 95% CrI 0.19-0.99; sequencing 0.04, 95% CrI 0.01-0.15). However, the estimated diagnostic sensitivity of metagenomic sequencing was higher than qPCR for identifying BRSV (qPCR 0.32, 95% CrI 0.22-0.43; sequencing 0.60, 95% CrI 0.44-0.77). No significant difference among sensitivities was noted for the detection of BPIV-3 (qPCR 0.42, 95% CrI 0.21-0.66; sequencing 0.52, 95% CrI 0.19-0.87) and IDV (qPCR 0.65, 95% CrI 0.53-0.79; sequencing 0.60, 95% CrI 0.48-0.73). Diagnostic specificity was comparable for most viruses, except for BCoV, where metagenomic sequencing (BCoV 0.91, 95% CrI 0.88-0.95) outperformed qPCR (BCoV 0.59, 95% CrI 0.51-0.68). The specificity and sensitivity for detection of BRD-associated bacteria from the same metagenomic data were also similar to those estimated for culture and qPCR results for the same samples. Discussion: Estimated test sensitivities of both nanopore metagenomic sequencing and qPCR for the detection of BRD viruses of interest in nasal swab samples were moderate to very low for most viruses. While the tests varied in their ability to detect individual viruses, data from this study suggest nanopore metagenomic sequencing offers a potential alternative for diagnostic laboratories to identify three of six important BRD viruses as well as bacteria associated with BRD.

Indexed as

Bayesian latent class modelsbovine respiratory bacteriabovine respiratory diseasebovine respiratory viruseslong-read metagenomic sequencingqPCR

Identifiers

PMID41822221
PMCPMC12976743

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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.