Metagenomic and metatranscriptomic analysis of the microbial community in Swiss-type Maasdam cheese during ripening

Abstract

In Swiss-type cheeses, characteristic nut-like and sweet flavor develops during the cheese ripening due to the metabolic activities of cheese microbiota. Temperature changes during warm and cold room ripening, and duration of ripening can significantly change the gene expression of the cheese microbiota, which can affect the flavor formation. In this study, a metagenomic and metatranscriptomic analysis of Swiss-type Maasdam cheese was performed on samples obtained during ripening in the warm and cold rooms. We reconstructed four different bacterial genomes (Lactococcus lactis, Lactobacillus rhamnosus, Lactobacillus helveticus, and Propionibacterium freudenreichii subsp. shermanii strain JS) from the Maasdam cheese to near completeness. Based on the DNA and RNA mean coverage, Lc. lactis strongly dominated (~80-90%) within the cheese microbial community. Genome annotation showed the potential for the presence of several flavor forming pathways in these species, such as production of methanethiol, free fatty acids, acetoin, diacetyl, acetate, ethanol, and propionate. Using the metatranscriptomic data, we showed that, with the exception of Lc. lactis, the central metabolism of the microbiota was downregulated during cold room ripening suggesting that fewer flavor compounds such as acetoin and propionate were produced. In contrast, Lc. lactis genes related to the central metabolism, including the vitamin biosynthesis and homolactic fermentation, were upregulated during cold room ripening.

RETRACTED ARTICLE: Metagenomics for taxonomy profiling: tools and approaches

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Long-read based de novo assembly of low-complexity metagenome samples results in finished genomes and reveals insights into strain diversity and an active phage system

“…However, for a higher resolution assessment of the entire functional potential of microbial communities, whole metagenome shotgun (WMGS) sequencing approaches provide important advantages. They allow researchers to go beyond sequencing and classifying individual genes of species by also covering plasmids, prophages and lytic phages [2, 3], which harbor additional functions and play important roles in shaping microbial communities. Moreover, through the analysis of methylation profiles, one can link extrachromosomal genetic elements (e.g., plasmids) to their respective host species [4, 5].…”

Shotgun Metagenomics of a Water Kefir Fermentation Ecosystem Reveals a Novel Oenococcus Species

“…Shotgun metagenomic sequencing is witnessing an increased use to unravel the composition of microbial ecosystems involved in food fermentations. So far, it has been employed to investigate the spontaneous fermentation processes of kimchi (Jung et al, 2011), cocoa (Illeghems et al, 2012), puer tea (Lyu et al, 2013; Li et al, 2018), wine (Sternes et al, 2017), sausage (Ferrocino et al, 2018), and beer (Smukowski Heil et al, 2018), as well as of the ecosystem composition of various cheeses (Wolfe et al, 2014; Dugat-Bony et al, 2015; Escobar-Zepeda et al, 2016; Duru et al, 2018), milk kefirs (Nalbantoglu et al, 2014; Walsh et al, 2016, 2018), withered Corvina grapes (Salvetti et al, 2016), an Indian rice wine starter culture (Bora et al, 2016), cereal vinegar (Wu et al, 2017), and a fermented dairy beverage nunu (Walsh et al, 2017). As opposed to amplicon sequencing, shotgun metagenomic sequencing data can further be used to infer potential metabolic functions encoded by the genomes of the members of the ecosystem under study through the assembly of the metagenomic sequence reads followed by gene prediction (De Filippo et al, 2012; Prakash and Taylor, 2012), as has been employed in the cases of cocoa bean fermentation (Illeghems et al, 2015), Mexican ripened cheese (Escobar-Zepeda et al, 2016), cereal vinegar (Wu et al, 2017), sausage fermentation (Ferrocino et al, 2018), and puer tea fermentation (Li et al, 2018).…”

“…As opposed to amplicon sequencing, shotgun metagenomic sequencing data can further be used to infer potential metabolic functions encoded by the genomes of the members of the ecosystem under study through the assembly of the metagenomic sequence reads followed by gene prediction (De Filippo et al, 2012; Prakash and Taylor, 2012), as has been employed in the cases of cocoa bean fermentation (Illeghems et al, 2015), Mexican ripened cheese (Escobar-Zepeda et al, 2016), cereal vinegar (Wu et al, 2017), sausage fermentation (Ferrocino et al, 2018), and puer tea fermentation (Li et al, 2018). Finally, shotgun metagenomic sequencing analysis of fermented food samples allows the discovery of whole genomes of microorganisms that were not cultured before (Duru et al, 2018; Smukowski Heil et al, 2018).…”