Rapid detection of human and animal respiratory viruses using Microbe Finder (MiFi®)

TL;DR

The MiFi® software enables rapid and accurate detection of multiple respiratory viruses in human and animal clinical samples using metagenomic sequencing.

Contribution

MiFi® provides a user-friendly, strain-specific, and scalable tool for detecting respiratory viruses without requiring advanced bioinformatics skills.

Findings

In silico validation showed 100% specificity and detection limits as low as 0.0010% of total reads.

Clinical testing matched PCR performance for HRSV, IAV, IBV, BRSV, and CDV.

Internal controls ensured reliable detection without interference.

Abstract

Rapid and accurate detection of respiratory pathogens is essential for timely diagnosis, effective treatment, and outbreak monitoring in both human and veterinary medicine. We evaluated the Microbe Finder (MiFi®) software for detection of nine RNA viruses of human and veterinary clinical importance. Species specific signature sequences in the different pathogen genomes were identified, and specific electronic probe sets were curated using the MiFi® software. Analytical specificity and sensitivity were evaluated through simulated metagenomes and public sequence databases, respectively. Host-specific internal control probes were designed to ensure diagnostic reliability and quality control. Diagnostic performance was assessed using Oxford Nanopore sequence data from clinical nasal swab samples. In silico validation showed 100% specificity across 83 datasets and limits of detection as low as 0.0010% of total reads (10 reads per 106) for some targets. Internal controls generated stable background signals without interfering with pathogen detection. In vivo testing of 44 clinical samples matched PCR performance for Human respiratory syncytial virus (HRSV), Influenza B virus (IBV), Influenza A virus (IAV), Bovine respiratory syncytial virus (BRSV), and Canine distemper virus (CDV). These findings demonstrate that the MiFi® software enables rapid, multiplex, and strain-specific detection of respiratory viruses in metagenomic sequence data without the need for advanced bioinformatics expertise. The approach supports scalable use in clinical laboratories, veterinary diagnostics for surveillance and triage, offering a valuable tool for improving respiratory pathogen detection across diverse settings.

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