LWT · 2024 · 20 citations · 26 references
AgricultureEnologyMicrobiologyMetabolomicsMicrobial MetabolismWine MicrobiologyMetabolomics In Wine FermentationMicrobial Ecology Of WineMicrobial Metabolites In WineNon-saccharomyces YeastsWine FermentationWine Fermentation Microbiology16S Ribosomal Ribonucleic Acid (Rrna) SequencingMetagenomics Of Wine MicrobiotaPrimary MetabolitesSaccharomyces Cerevisiae MetabolomicsSpontaneous FermentationWine Fermentation MicrobiotaWine YeastsYeast Metabolites
Emphasize on natural wines has gained prominence in the wine industry. However, there is a lack of research on natural wines that are fermented relying solely on grape skin-resident microorganisms. The microbes in spontaneous and inoculated fermentation must were analyzed utilizing 16S ITS rRNA sequencing, metabolomics, and metagenomics. The upregulated primary metabolites involved in Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathways suggesting that the stress resistance of Saccharomyces was more robust and complex during spontaneous fermentation. Gene functional analysis indicated that Saccharomyces and non- Saccharomyces yeasts play crucial roles in carbohydrate metabolism, and their functions are complementary. The non- Saccharomyces yeasts contributed positively to the overall characteristics of the spontaneous wine. An analysis of the correlations between the dominant microorganisms and metabolites proved that more abundant strains participated in the fermentation of spontaneous wines and had a positive effect on the fermentation process of the wines.
26
Fast gapped-read alignment with Bowtie 2
Ben Langmead, Steven L. Salzberg · Nature Methods · 2012 · 61.1K citations
UPARSE: highly accurate OTU sequences from microbial amplicon reads
R. C. Edgar · Nature Methods · 2013 · 17.3K citations
UCHIME improves sensitivity and speed of chimera detection
R. C. Edgar, Brian J. Haas, José C. Clemente et al. · Bioinformatics · 2011 · 15.5K citations · Full text
Life Sciences, Biology, Microbiology +17
CD-HIT: accelerated for clustering the next-generation sequencing data
LiMin Fu, Beifang Niu, Zhengwei Zhu et al. · Bioinformatics · 2012 · 11.8K citations · Full text
Life Sciences, Bioinformatics, High-performance Computing +12