Microbiomes Associated With Foods From Plant and Animal Sources

Abstract

Food microbiome composition impacts food safety and quality. The resident microbiota of many food products is influenced throughout the farm to fork continuum by farming practices, environmental factors, and food manufacturing and processing procedures. Currently, most food microbiology studies rely on culture-dependent methods to identify bacteria. However, advances in high-throughput DNA sequencing technologies have enabled the use of targeted 16S rRNA gene sequencing to profile complex microbial communities including non-culturable members. In this study we used 16S rRNA gene sequencing to assess the microbiome profiles of plant and animal derived foods collected at two points in the manufacturing process; post-harvest/pre-retail (cilantro) and retail (cilantro, masala spice mixes, cucumbers, mung bean sprouts, and smoked salmon). Our findings revealed microbiome profiles, unique to each food, that were influenced by the moisture content (dry spices, fresh produce), packaging methods, such as modified atmospheric packaging (mung bean sprouts and smoked salmon), and manufacturing stage (cilantro prior to retail and at retail). The masala spice mixes and cucumbers were comprised mainly of Proteobacteria, Firmicutes, and Actinobacteria. Cilantro microbiome profiles consisted mainly of Proteobacteria, followed by Bacteroidetes, and low levels of Firmicutes and Actinobacteria. The two brands of mung bean sprouts and the three smoked salmon samples differed from one another in their microbiome composition, each predominated by either by Firmicutes or Proteobacteria. These data demonstrate diverse and highly variable resident microbial communities across food products, which is informative in the context of food safety, and spoilage where indigenous bacteria could hamper pathogen detection, and limit shelf life.

Keywords: 16S rRna; food; metagenomics; microbiome; produce; seafood; spices.

FIGURE 1

Principal coordinates analysis reveals clustering by commodity type. Each food is circled and squares indicate garam masala (brown), MDARD cilantro CIL4Z (light blue), and retail cilantro CILSB (dark blue).

FIGURE 2

Unsupervised hierarchical clustering of the top 25 families across all samples. Values reflect proportional abundances. 1 = cilantro, 2 = Mung bean sprouts, 3 = Smoked Salmon, 4 = Masala spice mixes, 5 = Cucumbers.

FIGURE 3

Genus level proportional abundances (≥1%) of masala spice mixes. Two replicates of each spice mixture were sequenced.

FIGURE 4

Genus level average proportional abundances (≥1%) of MDARD and retail cilantro samples. Proportional abundances were average for six replicates of MDARD samples CIL27A, CIL27B, CIl27C, CIL28A, CIL28C, and CIL28D and three replicates of MDARD sample CIL4Z. The proportional abundances for the retail cilantro samples CILSB1 thru CILSB18 were averaged.

FIGURE 5

Genus level proportional abundances (≥1%) of seven cucumber samples.

FIGURE 6

Genus level proportional abundances (≥1%) of three replicates of mung bean sprout brand A (SPA) and nine replicates of mung bean sprout B (SPB).

FIGURE 7

Genus level proportional abundances (≥1%) of three smoked salmon samples. Two replicates of each sample were sequenced.