Lactic acid bacteria in the brewing of traditional Daqu liquor

Deciphering the core microbes and their interactions in spontaneous Baijiu fermentation: A comprehensive review

The spontaneous Baijiu fermentation system harbors a complex microbiome that is highly dynamic in time and space and varies depending on the Jiuqu starters and environmental factors. The intricate microbiota presents in the fermentation environment is responsible for carrying out various reactions. These reactions necessitate the interaction among the core microbes to influence the community function, ultimately shaping the distinct Baijiu styles through the process of spontaneous fermentation. Numerous studies have been conducted to enhance our understanding of the diversity, succession, and function of microbial communities with the aim of improving fermentation manipulation. However, a comprehensive and critical assessment of the core microbes and their interaction remains one of the significant challenges in the Baijiu fermentation industry. This paper focuses on the fermentation properties of core microbes. We discuss the state of the art of microbial traceability, highlighting the crucial role of environmental and starter microbiota in the Baijiu brewing microbiome. Also, we discuss the various interactions between microbes in the Baijiu production system and propose a potential conceptual framework that involves constructing predictive network models to simplify and quantify microbial interactions using co-culture models. This approach offers effective strategies for understanding the core microbes and their interactions, thus beneficial for the management of microbiota and the regulation of interactions in Baijiu fermentation processes.

Identifying Variables Influencing Traditional Food Solid-State Fermentation by Statistical Modeling

Solid-state fermentation is widely used in traditional food production, but most of the complex processes involved were designed and are carried out without a scientific basis. Often, mathematical models can be established to describe mass and heat transfer with the assistance of chemical engineering tools. However, due to the complex nature of solid-state fermentation, mathematical models alone cannot explain the many dynamic changes that occur during these processes. For example, it is hard to identify the most important variables influencing product yield and quality fluctuations. Here, using solid-state fermentation of Chinese liquor as a case study, we established statistical models to correlate the final liquor yield with available industrial data, including the starting content of starch, water and acid; starting temperature; and substrate temperature profiles throughout the process. Models based on starting concentrations and temperature profiles gave unsatisfactory yield predictions. Although the most obvious factor is the starting month, ambient temperature is unlikely to be the direct driver of differences. A lactic-acid-inhibition model indicates that lactic acid from lactic acid bacteria is likely the reason for the reduction in yield between April and December. Further integrated study strategies are necessary to confirm the most crucial variables from both microbiological and engineering perspectives. Our findings can facilitate better understanding and improvement of complex solid-state fermentations.

Exploring the regulated effects of solid-state fortified Jiuqu and liquid-state fortified agent on Chinese Baijiu brewing

Zaopei is the direct source of Chinese liquor (Baijiu). Adding functional strains to Zaopei is a potential strategy to regulate Baijiu brewing, mainly including the two ways of solid-state fortified Jiuqu (SFJ) and liquid-state fortified agent (LFA). Here, to explore their regulated details, the response patterns of Zaopei microecosystem and the changes in the product features were comprehensively investigated. The results showed that SFJ more positively changed the physicochemical properties of Zaopei and improved its ester content, from 978.57 mg/kg to 1078.63 mg/kg over the fermentation of 30 days, while LFA decreased the content of esters, alcohols, and acids. Microbial analysis revealed that SFJ significantly increased Saccharomycopsis and Aspergillus from the start of fermentation and induced a positive interaction cluster driven by the added functional Paenibacillus, while LFA exhibited a community structure near that of the original microecosystem and led to a simpler network with the reduced microbial nodes and correlations. Metabolism analysis found that both SFJ and LFA weakened the flavor-producing metabolism by suppressing some key enzyme pathways, such as EC 3.2.1.51, EC 4.2.1.47, EC 1.1.1.27, EC 1.1.1.22, EC 1.5.1.10, EC 1.14.11.12. As a result, SFJ improved the raw liquor yield by 28.5 % and endowed the final product with a more fragrant aroma, mainly through ethyl (E)-cinnamate, ethyl isovalerate, ethyl phenacetate with the higher odor activity values, while LFA promoted the yield by 13.2 % and resulted in a purer and less intense aroma through the aroma-active β-damascenone, ethyl heptoate, ethyl phenacetate. These results facilitated the regulated mechanism of SFJ and LFA on Baijiu brewing and indicated that the used functional strains in this study could be applicated in SFJ way for the further industrial-scale application.

Analysis of the differences in physicochemical properties, volatile compounds, and microbial community structure of pit mud in different time spaces

Pit mud (PM) is among the key factors determining the quality of Nongxiangxing baijiu, a Chinese liquor. Microorganisms present inside PM are crucial for the unique taste and flavor of this liquor. In this study, headspace solid-phase microextraction was used in combination with gas chromatography and high-throughput sequencing to determine the volatile compounds and microbial community structure of 10- and 40-year PM samples from different spaces. The basic physicochemical properties of the PM were also determined. LEfSe and RDA were used to systematically study the PM in different time spaces. The physicochemical properties and ester content of the 40-year PM were higher than those of the 10-year PM, but the spatial distribution of the two years PM samples exhibited no consistency, except in terms of pH, available phosphorus content, and ester content. In all samples, 29 phyla, 276 families, and 540 genera of bacteria, including four dominant phyla and 20 dominant genera, as well as eight phyla, 24 families, and 34 genera of archaea, including four dominant phyla and seven dominant genera, were identified. The LEfSe analysis yielded 18 differential bacteria and five differential archaea. According to the RDA, the physicochemical properties and ethyl caproate, ethyl octanoate, hexanoic acid, and octanoic acid positively correlated with the differential microorganisms of the 40-year PM, whereas negatively correlated with the differential microorganisms of the 10-year PM. Thus, we inferred that Caproiciproducens, norank_f__Caloramatoraceae, and Methanobrevibacter play a dominant and indispensable role in the PM. This study systematically unveils the differences that affect the quality of PM in different time spaces and offers a theoretical basis for improving the declining PM, promoting PM aging, maintaining cellars, and cultivating an artificial PM at a later stage.

Comparison of the Correlations of Microbial Community and Volatile Compounds between Pit-Mud and Fermented Grains of Compound-Flavor Baijiu

The microbial composition and volatile components of fermented grains (FG) and pit mud (PM) are crucial for the quality and flavor of compound-flavor baijiu (CFB). The physicochemical indices, culturable microorganisms, microbial communities, and volatile components of FG and PM were analyzed and correlated in our research. Considering FG and PM, amplicon sequencing was used to analyze the microbial community and the volatile components were detected by headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME). For FG, redundancy analysis and correlation perfume Circos were used to clarify the correlations between the dominant microbial community and volatile components. The results showed that Aspergillus, Pichia, and Rhizopus were the main fungal microflora in FG and PM, whereas Lactobacillus and Bacillus were the dominant bacteria in FG, and Methanosarcina and Clostridium sensu stricto 12 were the dominant bacteria in the PM. The microbial community and volatile compounds in the CB sampled from the bottom layers of the FG were greatly affected by those in the PM. There were 32 common volatile components in CB and PM. For FG, most of the volatile components were highly correlated with Lactobacillus, Bacillus, Aspergillus, Pichia, and Monascus, which includes alcohols, acids and esters. This study reveals correlations between microbial composition, volatile components, and the interplay of FG and PM, which are conducive to optimizing the fermentation process and improving the quality of CFB base.

MALDI-TOF MS Is an Effective Technique To Classify Specific Microbiota

MALDI-TOF MS is well-recognized for single microbial identification and widely used in research and clinical fields due to its specificity, speed of analysis, and low cost of consumables. Multiple commercial platforms have been developed and approved by the U.S. Food and Drug Administration. Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) has been used for microbial identification. However, microbes can present as a specific microbiota, and detection and classification remain a challenge. Here, we constructed several specific microbiotas and tried to classify them using MALDI-TOF MS. Different concentrations of nine bacterial strains (belonging to eight genera) constituted 20 specific microbiotas. Using MALDI-TOF MS, the overlap spectrum of each microbiota (MS spectra of nine bacterial strains with component percentages) could be classified by hierarchical clustering analysis (HCA). However, the real MS spectrum of a specific microbiota was different than that of the overlap spectrum of component bacteria. The MS spectra of specific microbiota showed excellent repeatability and were easier to classify by HCA, with an accuracy close to 90%. These results indicate that the widely used MALDI-TOF MS identification method for individual bacteria can be expanded to classification of microbiota. IMPORTANCE MALDI-TOF MS can be used to classify specific model microbiota. The actual MS spectrum of the model microbiota was not a simple superposition of every single bacterium in a certain proportion but had a specific spectral fingerprint. The specificity of this fingerprint can enhance the accuracy of microbiota classification.

Integrated multi-omics approaches to understand microbiome assembly in Jiuqu, a mixed-culture starter

The use of Jiuqu as a saccharifying and fermenting starter in the production of fermented foods is a very old biotechnological process that can be traced back to ancient times. Jiuqu harbors a hub of microbial communities, in which prokaryotes and eukaryotes cohabit, interact, and communicate. However, the spontaneous fermentation based on empirical processing hardly guarantees the stable assembly of the microbiome and a standardized quality of Jiuqu. This review describes the state of the art, limitations, and challenges towards the application of traditional and omics-based technology to study the Jiuqu microbiome and highlights the need for integrating meta-omics data. In addition, we review the varieties of Jiuqu and their production processes, with particular attention to factors shaping the microbiota of Jiuqu. Then, the potentials of integrated omics approaches used in Jiuqu research are examined in order to understand the assembly of the microbiome and improve the quality of the products. A variety of different approaches, including molecular and mass spectrometry-based techniques, have led to scientific advances in the analysis of the complex ecosystem of Jiuqu. To date, the extensive research on Jiuqu has mainly focused on the microbial community diversity, flavor profiles, and biochemical characteristics. An integrative approach to large-scale omics datasets and cultivated microbiota has great potential for understanding the interrelation of the Jiuqu microbiome. Further research on the Jiuqu microbiome may explain the inherent property of compositional stability and stable performance of a complex microbiota coping with environmental perturbations and provide important insights to reconstruct synthetic microbiota and develop modern intelligent manufacturing procedures for Jiuqu.

Analysis of Bacterial Diversity in Different Types of Daqu and Fermented Grains From Danquan Distillery

Bacterial communities in high-temperature Daqu and fermented grains are important for brewing Jiang-flavor Baijiu such as Danquan Baijiu. Daqu is a saccharifying and fermenting agent, which has a significant impact on the flavor of Baijiu. However, bacterial communities in three different types of samples from the Danquan distillery (dqjq_ck, dqjqcp, and dqjp3) were still unclear, which limited further development of Danquan Baijiu. “dqjq_ck” and “dqjqcp” indicate high-temperature Daqu at days 45 and 135, respectively. “dqjp3” indicates fermented grains. In this study, the bacterial communities of three samples were analyzed by Illumina Miseq high-throughput sequencing. The bacterial communities of three samples primarily composed of thermophilic bacteria and bacteria with stress resistance. The most abundant species in dqjq_ck, dqjqcp, and dqjp3 were Comamonas, Bacillus, and unclassified Lactobacillales, respectively. The main bacteria included Bacillus, Comamonas, Myroides, Paenibacillus, Acetobacter, Kroppenstedtia, Staphylococcus, Saccharopolyspora, Planifilum, Lactobacillus, Acinetobacter, Oceanobacillus, Enterococcus, Thermoactinomyces, Lactococcus, Streptomyces, Saccharomonospora, Tepidimicrobium, Anaerosalibacter, unclassified_Lactobacillales, unclassified_Thermoactinomycetaceae_1, unclassified_Bacillaceae_2, unclassified_Bacillales, unclassified_Microbacteriaceae, unclassified_Rhodobacteraceae, unclassified_Actinopolysporineae, and unclassified_Flavobacteriaceae in three samples (percentage was more than 1% in one of three samples). In our study, the succession of microbiota in three samples representing three important stages of Danquan Baijiu brewing was revealed. This article lays a good foundation for understanding the fermentation mechanism and screening some excellent indigenous bacteria to improve the quality of Danquan Baijiu in future.

The amino acids, bacterial communities, and their correlations in Wuliangye-flavour liquor production

With the enhancement of people’s awareness of drinking health, the health factors in Wuliangye-flavour liquor is worth our attention. Bacterial communities in 4 layers of Zaopei from the same fermentation pit and amino acids as major health factors in 4 liquors directly related Zaopeis were investigated by Illumina MiSeq sequencing and liquid chromatography mass spectrometry, respectively. Results indicated that 18 amino acids were detected and 8 dominant bacteria (genus level) were observed. Meanwhile, total amino acids, 11 amino acids (Glu, Asp, Val, etc), bacterial diversity, and the percentages of Lactobacillus and Pseudomonas increased with the increase of Zaopei’s depth; 5 amino acids (Pro, Ser, Phe, etc) and the percentages of Pediococcus and Bacteroides first increased and then decreased with the increase of Zaopei’s depth. Moreover, 11 amino acids were significantly (P < 0.01) and strongly (|ρ| > 0.8) positively correlated with Lactobacillus and Pseudomonas numbers.

Diversity of microbiota, microbial functions, and flavor in different types of low-temperature Daqu

Light-flavor Baijiu is made from grain materials using a combination of three types of low-temperature Daqu (Hongxin, Houhuo, and Qingcha). This study comprehensively examined the microbial structure, microbial functions, and flavor characteristics of the three types of low-temperature Daqu using high-throughput sequencing and electronic senses, and it further clarified the relationship between the microbiota and flavor in low-temperature Daqu. The results showed that Hongxin had the highest bacterial richness and diversity, while Houhuo had the lowest. Both fungal richness and diversity were significantly higher in Qingcha than in Hongxin and Houhuo. The differences in peak temperature during Daqu-making led to significant differences in the structure of microbial communities, microbial functions, and flavor quality in the three types of low-temperature Daqu, and could be leveraged for screening and enriching functional microorganisms for Baijiu-making. Co-exclusion patterns between lactic acid bacteria and Bacillus in low-temperature Daqu resulted in a negative correlation between amino acid transport metabolism and carbohydrate transport metabolism. The different types of low-temperature Daqu had distinct flavor profiles, and the differences in the taste profiles were more significant. Dominated by Thermoactinomyces and Lactobacillus, and together with Saccharopolyspora, Bacillus, Streptomyces, Saccharomycopsis, and Thermoascus, they formed the core microbiota that influencing the flavor of low-temperature Daqu. The bacteria mainly influenced the taste of low-temperature Daqu, whereas the fungi mainly influenced the aroma. Each type of low-temperature Daqu contributed to the flavor of light-flavor Baijiu: Hongxin could elevate the levels of aromatic compounds, Houhuo could regulate the bitterness and sourness, and Qingcha could inhibit the generation of sulfur organic compounds. The results of the present study enrich and refine our knowledge of low-temperature Daqu, promoting the further evolution of traditional brewing methods.

The Fungal Communities and Flavor Profiles in Different Types of High-Temperature Daqu as Revealed by High-Throughput Sequencing and Electronic Senses

Polymicrobial co-fermentation is among the distinct character of high-temperature Daqu. However, fungal communities in the three types of high-temperature Daqu, namely, white high-temperature Daqu, black high-temperature Daqu, and yellow high-temperature Daqu, are yet to be characterized. In this study, the fungal diversity, taste, and aroma profiles in the three types of high-temperature Daqu were investigated by Illumina MiSeq high-throughput sequencing, electronic tongue, and electronic nose, respectively. Ascomycota and Basidiomycota were detected as the absolute dominant fungal phylum in all types of high-temperature Daqu samples, whereas Thermomyces, Thermoascus, Aspergillus, Rasamsonia, Byssochlamys, and Trichomonascus were identified as the dominant fungal genera. The fungal communities of the three types of high-temperature Daqu differed significantly (p < 0.05), and Thermomyces, Thermoascus, and Monascus could serve as the biomarkers in white high-temperature Daqu, black high-temperature Daqu, and yellow high-temperature Daqu, respectively. The three types of high-temperature Daqu had an extremely significant difference (p < 0.01) in flavor: white high-temperature Daqu was characterized by sourness, bitterness, astringency, richness, methane, alcohols, ketones, nitrogen oxides, and sulfur organic compounds; black high-temperature Daqu was characterized by aftertaste-A, aftertaste-B, methane-aliph, hydrogen, and aromatic compounds; and yellow high-temperature Daqu was characterized by saltiness, umami, methane, alcohols, ketones, nitrogen oxides, and sulfur organic compounds. The fungal communities in the three types of high-temperature Daqu were significantly correlated with taste but not with aroma, and the aroma of high-temperature Daqu was mainly influenced by the dominant fungal genera including Trichomonascus, Aspergillus, Thermoascus, and Thermomyces. The result of the present study enriched and refined our knowledge of high-temperature Daqu, which had positive implications for the development of traditional brewing technique.

Analysis of microbial diversity and functional differences in different types of high-temperature Daqu

Bacterial communities that enrich in high-temperature Daqu are important for the Chinese maotai-flavor liquor brewing process. However, the bacterial communities in three different types of high-temperature Daqu (white Daqu, black Daqu, and yellow Daqu) are still undercharacterized. In this study, the bacterial diversity of three different types of high-temperature Daqu was investigated using Illumina MiSeq high-throughput sequencing. The bacterial community of high-temperature Daqu is mainly composed of thermophilic bacteria, and seven bacterial phyla along with 262 bacterial genera were identified in all 30 high-temperature Daqu samples. Firmicutes, Actinobacteria, Proteobacteria, and Acidobacteria were the dominant bacterial phyla in high-temperature Daqu samples, while Thermoactinomyces, Staphylococcus, Lentibacillus, Bacillus, Kroppenstedtia, Saccharopolyspora, Streptomyces, and Brevibacterium were the dominant bacterial genera. The bacterial community structure of three different types of high-temperature Daqu was significantly different (p < .05). In addition, the results of microbiome phenotype prediction by BugBase and bacterial functional potential prediction using PICRUSt show that bacteria from different types of high-temperature Daqu have similar functions as well as phenotypes, and bacteria in high-temperature Daqu have vigorous metabolism in the transport and decomposition of amino acids and carbohydrates. These results offer a reference for the comprehensive understanding of bacterial diversity of high-temperature Daqu.