Application of high-throughput pyrosequencing in the analysis of microbiota of food commodities procured from small and large retail outlets in a U.S. metropolitan area - A pilot study

Food Res Int. 2018 Mar;105:29-40. doi: 10.1016/j.foodres.2017.10.057. Epub 2017 Oct 31.

Abstract

With the advent of high-throughput sequencing technologies, it is possible to comprehensively analyze the microbial community of foods without culturing them in the laboratory. The estimation of all microbes inhabiting a food commodity (food microbiota) therefore may shed light on the microbial quality and safety of foods. In this study, we utilized high-throughput pyrosequencing of 16S rRNA genes as well as traditional microbiological methods to evaluate the bacterial diversity and the predicted metabolic pathways associated with the bacterial communities of selected foods (romaine lettuce, cabbage, deli meat, and chicken legs, total 200 samples) procured from small and large retail outlets located in Memphis-Shelby County, Tennessee, USA. For high-throughput sequencing, microbial genomic DNA was directly extracted from the food products and subjected to genetic sequencing. Aerobic plate count of all food samples was also performed. Foods from small stores (such as corner stores) were found to contain higher bacterial counts as compared to large stores (such as supermarkets). High-throughput pyrosequencing in tandem with bioinformatics analyses revealed a comprehensive picture of the bacterial ecology of foods at different taxonomic levels. Firmicutes and Proteobacteria were the most abundant phyla across all products. At the genus level, Enterobacter and Pantoea in vegetables, and Bacillus and Aeromonas in animal products were found to be the most abundant. The bacterial predicted metabolic pathways such as inosine-5'-phosphate biosynthesis I, methylglyoxal (MG) degradation pathways, urea cycle, dTDP-l-rhamnose biosynthesis I, and mevalonate pathway I differed in foods procured from small stores as compared to large groceries or supermarkets. The results from this study revealed that the bacterial ecology (both in terms of numbers and types of bacteria) of food commodities might differ based on the vending outlet type (large vs. small) of retail stores. The overall estimation bacterial communities in foods by high-throughput sequencing method may be useful to identify potential taxa responsible for food spoilage. Moreover, the data from pyrosequencing of 16S rRNA genes can also be applied to infer major metabolic pathways in bacteria inhabiting different foods. This may reflect the role of these pathways in food-bacteria interaction and adaptation.

Keywords: Bacteria; Food microbiome; Food microbiota; Metagenomics; Retail food.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Aeromonas / isolation & purification
  • Bacillus / isolation & purification
  • Computational Biology
  • DNA, Bacterial / genetics
  • DNA, Bacterial / isolation & purification*
  • Enterobacter / isolation & purification
  • Firmicutes / isolation & purification
  • Food Microbiology*
  • High-Throughput Nucleotide Sequencing*
  • Meat Products / microbiology
  • Microbiota*
  • Pantoea / isolation & purification
  • Pilot Projects
  • Proteobacteria / isolation & purification
  • RNA, Ribosomal, 16S / genetics
  • RNA, Ribosomal, 16S / isolation & purification
  • Sequence Analysis, DNA
  • Tennessee
  • Vegetables / microbiology

Substances

  • DNA, Bacterial
  • RNA, Ribosomal, 16S