Comparative Analysis of Microbial Community Diversity and Physicochemical Factors of Nongxiangxing Baijiu Pit Mud at Different Ages and Cellar Locations

Abstract

In this study, high-throughput sequencing technology, linear discriminant analysis effect size (LEfSe) and redundancy analysis (RDA) were used to investigate the structure of prokaryotic and eukaryotic communities, the differential microbial communities, and the relationship between microorganisms and physicochemical factors in pit mud (PM) from cellars of different ages (5, 10 and 20 years) and from different spatial locations of cellars. The results showed that the diversity of both prokaryotic and eukaryotic microorganisms was higher in the five-year-old PM than in the 10- and 20-year-old PM. Among all samples, a total of 37 phyla, 83 classes, 176 orders, 306 families and 629 genera of prokaryotic microorganisms were detected, with five phyla being the dominant ones. Totally 12 phyla, 37 orders, 74 families, 160 families and 282 genera of eukaryotic microorganisms were detected, including three phyla and 15 genera being dominant. LEfSe identified 12 differential prokaryotic genera and 15 differential eukaryotic species, and the differential microbial communities of each sample played an important role in the fermentation process of baijiu. The results of physicochemical analysis showed that the pH of the PM samples varied from 3.66 to 5.20, and the effective phosphorus content of PM was significantly different among locations. RDA analysis showed that Lactobacillus, unclassified_f__Aspergillaceae, and Thermomyces were negatively correlated with moisture, ammonia nitrogen, and effective phosphorus contents, and Methanobacterium, Clostridium_sensu_stricto_12, Caproiciproducens, Methanobrevibacter, Cryptococcus_f__Tremellaceae and Apiotrichum were positively correlated with moisture, pH, ammonia nitrogen, and effective phosphorus. This study provides theoretical support for the establishment of daily PM maintenance as well as high-quality PM domestication and production.

Keywords

• pit mud; high-throughput?sequencing; prokaryotic and eukaryotic microorganisms; physicochemical factors; correlation analysis