Bacterial Communities and Prediction of Microbial Metabolic Pathway in Rice Wine Koji From Different Regions in China

Environmental Factors Affecting the Diversity and Composition of Environmental Microorganisms in the Shaoxing Rice Wine Producing Area

Shaoxing rice wine is a notable exemplar of Chinese rice wine. Its superior quality is strongly correlated with the indigenous natural environment. The results indicated that Firmicutes (75%), Actinobacteria (15%), Proteobacteria (5%), and Bacteroidetes (3%) comprised the prevailing bacterial groups. Among the main bacterial genera, Lactobacillus was the most abundant, accounting for 49.4%, followed by Lactococcus (11.9%), Saccharopolyspora (13.1%), Leuconostoc (4.1%), and Thermoactinomyces (1.1%). The dominant fungal phyla were Ascomycota and Zygomycota. Among the dominant genera, Saccharomyces (59.3%) prevailed as the most abundant, followed by Saccharomycopsis (10.7%), Aspergillus (7.1%), Thermomyces (6.2%), Rhizopus (4.9%), Rhizomucor (2.2%), and Mucor (1.3%). The findings demonstrate that the structure of the bacterial and fungal communities remains stable in the environment, with their diversity strongly influenced by climatic conditions. The continuous fluctuations in environmental factors, such as temperature, air pressure, humidity, rainfall, and light, significantly impact the composition and diversity of microbial populations, particularly the dominant bacterial community.

Research Progress on Flavor and Quality of Chinese Rice Wine in the Brewing Process

Chinese rice wine (CRW) is a traditional and unique alcoholic beverage in China, favored by many consumers for its rich aroma, unique taste, and complex ingredients. Its flavor is primarily composed of volatile and nonvolatile compounds. These flavor compounds are partly derived from grains and starters (Qu), while the other part is produced by microbial metabolism and chemical reactions during the brewing process. Additionally, ethyl carbamate (EC) in CRW, a hazardous chemical, necessitates controlling its concentration during brewing. In recent years, numerous new brewing techniques for CRW have emerged. Therefore, this paper aims to collect aroma descriptions and thresholds of flavor compounds in CRW, summarize the relationship between the brewing process of CRW and flavor formation, outline methods for reducing the concentration of EC in the brewing process of CRW, and summarize the four stages (pretreatment of grains, fermentation, sterilization, and aging process) of new techniques. Furthermore, we will compare the advantages and disadvantages of different approaches, with the expectation of providing a valuable reference for improving the quality of CRW.

Microbial Communities and Correlation between Microbiota and Volatile Compounds in Fermentation Starters of Chinese Sweet Rice Wine from Different Regions

Chinese sweet rice wines (CSRW) are traditional, regionally distinct alcoholic beverages that are generally brewed with glutinous rice and fermentation starters. This study aimed to characterize microbial communities and volatile compounds of CSRW starters and explore correlations between them. The major volatiles in starters include 1-heptanol, 1-octanol, 2-nonanol, phenylethyl alcohol, 2-nonanone, acetophenone, and benzaldehyde. Microbiological analysis based on high-throughput sequencing (HTS) technology demonstrated that starter bacterial communities are dominated by Weissella, Pediococcus, and Lactobacillus, while Saccharomycopsis and Rhizopus predominate in fungal communities. Carbohydrate and amino acid metabolism are the most active metabolic pathways in starters. Spearman correlation analysis revealed that 15 important volatile compounds including alcohols, acids, aldehydes and esters were significantly positively correlated with nine microbial genera (|r| > 0.7, p < 0.05), including five bacterial genera (i.e., Weissella, Pediococcus, Lactobacillus, Bacillus, and Nocardiopsis) and four fungal genera (i.e., Saccharomycopsis, Rhizopus, Wickerhamomyces, and Cyberlindnera), spanning 19 distinct relationships and these microorganisms were considered the core functional microorganisms in CSRW starters. The most important positive correlations detected between phenylethyl alcohol and Weissella or Saccharomycopsis and between 2-nonanol and Pediococcus. This study can serve as a reference to guide the development of defined starter cultures for improving the aromatic quality of CSRW.

Impact of Aging Microbiome on Metabolic Profile of Natural Aging Huangjiu through Machine Learning

Aging is a time-consuming step in the manufacturing of fermented alcoholic beverages. Natural-aging huangjiu sealed in pottery jars was taken as an example to investigate the changes of physiochemical indexes during aging and to quantify intercorrelations between aging-related factors and metabolites through machine learning methods. Machine learning models provided significant predictions for 86% of metabolites. Physiochemical indexes well reflected the metabolic profile, and total acid was the most important index that needed to be controlled. For aging-related factors, several aging biomarkers of huangjiu were also well predicted. Feature attribution analysis showed aging year was the most powerful predictive factor, and several microbial species were significantly associated with aging biomarkers. Some of the correlations, mostly connected to environmental microorganisms, were newly found, showing considerable microbial influence on aging. Overall, our results reveal the potential determinants that affect the metabolic profile of aged huangjiu, paving the way for a systematical understanding of changes in metabolites of fermented alcoholic beverages.

Predictive Microbial Community and Functional Gene Expression Profiles in Pineapple Peel Fermentation Using 16S rRNA Gene Sequences

Pineapple peel (PP) is a by-product with the potential to be used as a raw material for functional beverages. Traditional PP fermentation has so far paid little attention to the microbial community and its role in the fermentation process. As a result, the current research looked into the microbial communities and their roles during PP fermentation. A metagenomic approach based on the 16S rRNA sequencing data was used to assess the microbial communities. Subsequent analysis was performed using PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states) to analyze the microbial functions in the fermentation system. The microecology of the fermentation process in three samples was predominated by Firmicutes. Furthermore, the well-known probiotic genera Weissella, Lactobacillus, and Lactococcus were found to be predominating in the gumer, promic, and control samples, respectively. It was obvious that microenvironmental differences have an effect on the microbial composition of PP fermentation. Moreover, functional prediction revealed that carbohydrate metabolism was the most prevalent metabolic pathway during the fermentation process. Additionally, it was discovered that all of the bacteria found in the samples played significant roles in carbohydrate, amino acid, vitamin, and co-factor metabolism, which can be inferred to result in the production of beneficial metabolites.