Sequence based characterization of microbial communities in food: The panacea for smart detection of food microbes or dirty deeds done dirt cheap?

Sequence-based methods are a rapid and high-throughput approach to characterize microbial communities in food and food processing facilities. Such methodologies have been widely used for characterisation of microbial communities or for detection of specific microbes the past years. They have partially replaced culture-based approaches, but their limitations are often overlooked. This review briefly outlines advantages and limitations of sequence-based methods, which mainly relate to the limited taxonomic resolution of gene amplicon sequencing, PCR bias that distorts quantitative relationships, the lack of differentiation of dead and viable cells, and the completeness and contamination of metagenomic assembled bins. We also provide a perspective on innovative approaches for smart microbial detection that (i) integrate sequence-based methods and (high throughput) culture-based methodology; (ii) use enrichment culture in combination with nanopore sequencing and live basecalling for rapid detection; (iii) use current ecological concepts and up-to-date bioinformatics tools to identify bacterial strains; and (iv) employ hybrid assembly of metagenomics sequences. The proposed framework for smart microbial detection makes best use of both world – 19 th century microbiological methods and 21 st century sequencing technology, to improve the accuracy, resolution and sensitivity of detection of pathogens, fermentation microbes and spoilage microbes in food. • Sequence-based detection of food microbes is influenced by quantitative biases. • Sequence-based detection of food microbes does not differentiate dead and alive. • Most sequence-based detection methods have a high detection limit. • Amplicon sequencing resolves at the species- or genus level only. • Combining sequencing and culture improves microbial detection.