Profiling the composition and metabolic activities of microbial community in fermented grain for the Chinese strong-flavor Baijiu production by using the metatranscriptome, high-throughput 16S rRNA and ITS gene sequencings

Abstract The composition and function of microbial community analyzed by sequencing 16S rRNA/ITS gene amplicons (DNA level) were compared with those derived by using metatranscriptome sequencing (RNA level) from the same fermented grain (FG) sample, which obtained from the key fermentation time point during the Chinese strong-flavor Baijiu (CSFB) production process. The results showed that the fungi with the highest relative abundance was Saccharomyces (RNA: 83.15%, DNA: 89.74%) at the two levels. The most abundant bacterium was Kroppenstedtia (37.09%) detected only at the DNA level, while it was Streptococcus (93.75%) at the RNA level, indicating that the structures of prokaryotic communities at the two levels were quite different. For the microbial functions, a large proportion of genes of FG microorganisms related to “Metabolism” function were observed both by using PICRUSt2 analysis (DNA level) and metatranscriptome analysis (RNA level), and especially enriched in “Carbohydrate metabolism”. While the proportions of genes involved in some functions were different, such as “Replication and repair”, “Membrane transport” and “Environmental adaptation”, with high proportions of genes involved in at the DNA level when compared those at the RNA level. Furthermore, Saccharomyces cerevisiae was the most active microbe in the top15 pathways, followed by Torulaspora dellbrueckii. During the conversion of starch to ethanol, S. cerevisiae showed high metabolic capacity, and cooperated with other microorganisms to convert pyruvate to acetaldehyde directly or through acetyl-CoA and acetate, and then acetaldehyde to ethanol. As far as we know, this is a first study to profile the microbial community and metabolic features in FG of CSFB by using a combination of DNA- and RNA- based technologies. Our findings could provide useful insights for further understanding the active microbial function, metabolic pathways and fermentation mechanism in the FG ecosystem during CSFB fermentation.