Proficiency Testing of Metagenomics-Based Detection of Food-Borne Pathogens Using a Complex Artificial Sequencing Dataset

Abstract

Metagenomics-based high-throughput sequencing (HTS) enables comprehensive detection of all species comprised in a sample with a single assay and is becoming a standard method for outbreak investigation. However, unlike real-time PCR or serological assays, HTS datasets generated for pathogen detection do not easily provide yes/no answers. Rather, results of the taxonomic read assignment need to be assessed by trained personnel to gain information thereof. Proficiency tests are important instruments of validation, harmonization, and standardization. Within the European Union funded project COMPARE [COllaborative Management Platform for detection and Analyses of (Re-) emerging and foodborne outbreaks in Europe], we conducted a proficiency test to scrutinize the ability to assess diagnostic metagenomics data. An artificial dataset resembling shotgun sequencing of RNA from a sample of contaminated trout was provided to 12 participants with the request to provide a table with per-read taxonomic assignments at species level and a report with a summary and assessment of their findings, considering different categories like pathogen, background, or contaminations. Analysis of the read assignment tables showed that the software used reliably classified the reads taxonomically overall. However, usage of incomplete reference databases or inappropriate data pre-processing caused difficulties. From the combination of the participants’ reports with their read assignments, we conclude that, although most species were detected, a number of important taxa were not or not correctly categorized. This implies that knowledge of and awareness for potentially dangerous species and contaminations need to be improved, hence, capacity building for the interpretation of diagnostic metagenomics datasets is necessary.

Metagenomic sequencing determines complete infectious bronchitis virus (avian Gammacoronavirus) vaccine strain genomes and associated viromes in chicken clinical samples

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Campylobacter Species, Microbiological Source Tracking and Risk Assessment of Bacterial pathogens

“…Therefore, to detect species pertinent to risk assessment, it is indispensable to target pathogens, thence effortlessly removing trivial data for risk assessment. Doing this will no doubt minimize one of the major challenges of metagenomic studies, the difficulties associated with data analysis 96 .…”

High Throughput Sequencing for the Detection and Characterization of RNA Viruses

“…Most virus specific pipelines rely on k-mer frequency classification, sometimes with protein alignment based verification (Zhao et al, 2013 ; Roux et al, 2015 ; Ren et al, 2017 ; Alam and Chowdhury, 2020 ; Nayfach et al, 2020 ). However as Höper et al ( 2020 ) demonstrated bioinformatic pipelines require further harmonization and standardization for diagnostic application. A comprehensive review on bioinformatic processing of viral sequencing data is required and the current pandemic (COVID-19) has placed our knowledge gaps and ability to interpret sequence data, front, and center.…”