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.
Highlights
Approaches for the investigation of food-borne outbreaks regarding pathogen characterization, source attribution and risk assessment need to be precise, fast and independent from slow and biased cultivation techniques
Metagenomics-based highthroughput sequencing (HTS) is becoming a standard method for outbreak investigations of non-culturable, difficult-to-culture or slow-growing microorganisms (Koutsoumanis et al, 2019) yet protocols and analysis pipelines need to be standardized for routine use
The aim of the present proficiency test was in particular to test the interpretation of results obtained from metagenomics sequencing datasets based on the software analysis performed by the participants
Summary
Approaches for the investigation of food-borne outbreaks regarding pathogen characterization, source attribution and risk assessment need to be precise, fast and independent from slow and biased cultivation techniques. Problems with the analysis and the diagnostic assessment of HTS datasets may occur in several sample processing steps including sequencing, and during bioinformatics analysis. Beside the contamination of a sample during sampling and sample processing, microbial DNA can be introduced within the reagents during the preparation of sequencing libraries (Salter et al, 2014). The interpreter of data should be aware of possible false-positives detected due to contaminated genomes and insufficiently curated databases (e.g., Kirstahler et al, 2018). All these points are very important when interpreting metagenomic datasets in search for possible pathogens that may be less abundant in terms of sequencing reads. The remaining eight participants provided both the requested summary table and an assessment of the reported results. Three participants (P4, P8, and P11; Figure 1) reported classifications for the majority of the reads and only in these cases the overall composition resembled the actual one (Figure 1)
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