AbstractFood fermentation processes are an interesting example of microbial
ecosystems. Metagenomics and metatranscriptomics are culture-independent
approaches for studying microbial ecosystems that rely on high-throughput
DNA and RNA sequencing, respectively. In this PhD study, omics
methodologies were used to explore the microbial diversity of food
fermentation processes of different complexities and to gain insight into the
possible roles of the microorganisms present, extending our knowledge of
food fermentation ecosystems.
The complete genome of a candidate sourdough starter culture strain,
Lactobacillus fermentum IMDO 130101, was sequenced and annotated. A
species-wide comparative genomics analysis shed light on traits potentially
relevant to sourdough fermentations in this bacterial species, opening up new
avenues in sourdough starter culture strain research.
Metagenomics of two cheese brines from commercial manufacturers in
Flanders revealed a major microbial group consisting of halophilic and
halotolerant species, and a minor microbial group of cheese ingredientassociated microorganisms. The former group likely grows in these extreme
environments and the knowledge gained can be used to assess its impact on
Metagenomics of a water kefir fermentation process showed a restricted
microbial diversity and the reconstruction of a metagenome-assembled
genome revealed a novel Oenococcus species. The assignment of metabolic
functions to microbial species revealed indications of cross-feeding.
Finally, the application of omics and metabolite target analysis on Costa Rican
cocoa bean fermentation processes revealed microbial species from 82 genera
and a decreasing trend in microbial diversity along the fermentation. The
yeasts, lactic acid bacteria, and acetic acid bacteria typical for cocoa bean
fermentation processes were also found and assigned to dedicated metabolic
activities, some of which have so far been unreported. For pectin degradation,
a possible complementary role of distinct microbial species was discovered.
Overall, this PhD study demonstrated a variety of ways of omics data analysis
in terms of microbial composition and functional potential, resulting in the
discovery of microbial ecosystem members and functional traits not revealed
before using more conventional methodologies.
|Date of Award||13 Jul 2020|