Evaluating the Diagnostic Performance of Long-Read Metagenomic Sequencing Compared to Culture and Antimicrobial Susceptibility Testing for Detection of Bovine Respiratory Bacteria and Indicators of Antimicrobial Resistance.
Jennifer N Abi Younes, Lianne McLeod, Simon J G Otto, Zhijian Chai, Stacey Lacoste, E Luke McCarthy, Matthew G Links, Emily K Herman, Paul Stothard, Sheryl P Gow, John R Campbell, Cheryl L Waldner
Abstract
Open AccessBackground/Objectives: Long-read metagenomic sequencing can detect bacteria and antimicrobial resistance genes (ARGs) from bovine respiratory samples, providing an alternative to culture and antimicrobial susceptibility testing (C/S). This study applied Bayesian latent class models (BLCMs) to estimate the sensitivity (Se) and specificity (Sp) of long-read metagenomic sequencing compared to C/S for detecting Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni, as well as associated macrolide and tetracycline resistance potential. Methods: Deep nasopharyngeal swabs were collected from fall-placed feedlot calves at arrival, 13, and 36 days on feed across two years and two metaphylaxis protocols. Samples underwent C/S and long-read metagenomic sequencing. BLCMs were used to estimate Se and Sp for the detection of bacteria and potential for antimicrobial resistance (AMR). Results: Se and Sp for detecting respiratory bacteria by metagenomics were not significantly different than culture, with four exceptions. For the 2020 samples, Se for M. haemolytica was lower than culture, and Sp for H. somni was lower, while in both 2020 and 2021 samples, Se for P. multocida was higher for metagenomics than culture. The estimated Se and Sp of metagenomics for the detection of msrE-mphE, EstT, and tet(H) within bacterial reads were either not significantly different or were lower than AST, with Sp > 95% with one exception. Conclusions: This study provided BLCM-based estimates of clinical Se and Sp of metagenomics and C/S without assuming a gold standard in a large pen research setting. These findings demonstrate the potential of long-read metagenomics to support bovine respiratory disease diagnostics, AMR surveillance, and antimicrobial stewardship in feedlot cattle.