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Journal article

Gene-Based Pathogen Detection: Can We Use qPCR to Predict the Outcome of Diagnostic Metagenomics?

From

National Food Institute, Technical University of Denmark1

Research Group for Analytical and Predictive Microbiology, National Food Institute, Technical University of Denmark2

Statens Serum Institut3

In microbial food safety, molecular methods such as quantitative PCR (qPCR) and next-generation sequencing (NGS) of bacterial isolates can potentially be replaced by diagnostic shotgun metagenomics. However, the methods for pre-analytical sample preparation are often optimized for qPCR, and do not necessarily perform equally well for qPCR and sequencing.

The present study investigates, through screening of methods, whether qPCR can be used as an indicator for the optimization of sample preparation for NGS-based shotgun metagenomics with a diagnostic focus. This was used on human fecal samples spiked with 10³ or 10⁶ colony-forming units (CFU)/g Campylobacter jejuni, as well as porcine fecal samples spiked with 10³ or 10⁶ CFU/g Salmonella typhimurium.

DNA was extracted from the samples using variations of two widely used kits. The following quality parameters were measured: DNA concentration, qPCR, DNA fragmentation during library preparation, amount of DNA available for sequencing, amount of sequencing data, distribution of data between samples in a batch, and data insert size; none showed any correlation with the target ratio of the spiking organism detected in sequencing data.

Surprisingly, diagnostic metagenomics can have better detection sensitivity than qPCR for samples spiked with 10³ CFU/g C. jejuni. The study also showed that qPCR and sequencing results may be different due to inhibition in one of the methods. In conclusion, qPCR cannot uncritically be used as an indicator for the optimization of sample preparation for diagnostic metagenomics.

Language: English
Publisher: MDPI
Year: 2017
Pages: 332
ISSN: 20734425
Types: Journal article
DOI: 10.3390/genes8110332
ORCIDs: Andersen, Sandra Christine , Fachmann, Mette Sofie Rousing , Hoorfar, Jeffrey and 0000-0002-6675-2411
Other keywords

Genetics QH426-470

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