Multidimensional profiling indicates the shifts and functionality of wheat-origin microbiota during high-temperature Daqu incubation

Deciphering layer formation in Red Heart Qu: A comprehensive study of metabolite profile and microbial community influenced by raw materials and environmental factors

Environmental-origin microbiota significantly influences Red Heart Qu (RH_Qu) stratification, but their microbial migration and metabolic mechanisms remain unclear. Using high-throughput sequencing and metabolomics, we divided the stratification of RH_Qu into three temperature-based stages. Phase I features rising temperatures, causing microbial proliferation and a two-layer division. Phase II, characterized by peak temperatures, sees the establishment of thermotolerant species like Bacillus, Thermoactinomyces, Rhodococcus, and Thermoascus, forming four distinct layers and markedly altering metabolite profiles. The Huo Quan (HQ), developing from the Pi Zhang (PZ), is driven by the tyrosine-melanin pathway and increased MRPs (Maillard reaction products). The Hong Xin evolves from the Rang, associated with the phenylalanine-coumarin pathway and QCs (Quinone Compounds) production. Phase III involves the stabilization of the microbial and metabolic profile as temperatures decline. These findings enhance our understanding of RH_Qu stratification and offer guidance for quality control in its fermentation process.

Heterogenetic mechanism in high-temperature Daqu fermentation by traditional craft and mechanical craft: From microbial assembly patterns to metabolism phenotypes

The mechanical process has a widely usage in large-scale high-temperature Daqu (HTD) enterprises, however, the quality of the mechanical HTD is gapped with the HTD by traditional process. Currently, the understanding of the mechanism behind this phenomenon is still over-constrained. To this end, the discrepancies in fermentation parameters, enzymatic characteristics, microbial assembly and succession patterns, metabolic phenotypes were compared between traditional HTD and mechanical HTD in this paper. The results showed that mechanical process altered the temperature ramping procedure, resulting in a delayed appearance of the peak temperature. This alteration shifted the assembly pattern of the initial bacterial community from determinism to stochasticity, while having no impact on the stochastic assembly pattern of the fungal community. Concurrently, mechanical pressing impeded the accumulation of arginase, tetramethylpyrazine, trimethylpyrazine, 2-methoxy-4-vinylphenol, and butyric acid, as the target dissimilarities in metabolism between traditional HTD and mechanical HTD. Pearson correlation analysis combined with the functional prediction further demonstrated that Bacillus, Virgibacillus, Oceanobacillus, Kroppenstedtia, Lactobacillus, and Monascus were mainly contributors to metabolic variances. The Redundancy analysis (RDA) of fermented environmental factors on functional ASVs indicated that high temperature, high acid and low moisture were key positive drivers on the microbial metabolism for the characteristic flavor in HTD. Based on these results, heterogeneous mechanisms between traditional HTD and mechanical HTD were explored, and controllable metabolism targets were as possible strategies to improve the quality of mechanical HTD.

Strategies and Challenges of Microbiota Regulation in Baijiu Brewing

The traditional Chinese Baijiu brewing process utilizes natural inoculation and open fermentation. The microbial composition and abundance in the microecology of Baijiu brewing often exhibit unstable characteristics, which directly results in fluctuations in Baijiu quality. The microbiota plays a crucial role in determining the quality of Baijiu. Analyzing the driving effect of technology and raw materials on microorganisms. Elucidating the source of core microorganisms and interactions between microorganisms, and finally utilizing single or multiple microorganisms to regulate and intensify the Baijiu fermentation process is an important way to achieve high efficiency and stability in the production of Baijiu. This paper provides a systematic review of the composition and sources of microbiota at different brewing stages. It also analyzes the relationship between raw materials, brewing processes, and brewing microbiota, as well as the steps involved in the implementation of brewing microbiota regulation strategies. In addition, this paper considers the feasibility of using Baijiu flavor as a guide for Baijiu brewing regulation by synthesizing the microbiota, and the challenges involved. This paper is a guide for flavor regulation and quality assurance of Baijiu and also suggests new research directions for regulatory strategies for other fermented foods.

Microbial communities, functional, and flavor differences among three different-colored high-temperature Daqu: A comprehensive metagenomic, physicochemical, and electronic sensory analysis

High-temperature Daqu (HTD) is the starter for producing sauce-flavor Baijiu, with different-colored Daqu (white, yellow, and black) reflecting variations in fermentation chamber conditions, chemical reactions, and associated microbiota. Understanding the relationship between Daqu characteristics and flavor/taste is challenging yet vital for improving Baijiu fermentation. This study utilized metagenomic sequencing, physicochemical analysis, and electronic sensory evaluation to compare three different-colored HTD and their roles in fermentation. Fungi and bacteria dominated the HTD-associated microbiota, with fungi increasing as the fermentation temperature rose. The major fungal genera were Aspergillus (40.17%) and Kroppenstedtia (21.16%), with Aspergillus chevalieri (25.65%) and Kroppenstedtia eburnean (21.07%) as prevalent species. Microbial communities, functionality, and physicochemical properties, particularly taste and flavor, were color-specific in HTD. Interestingly, the microbial communities in different-colored HTDs demonstrated robust functional complementarity. White Daqu exhibited non-significantly higher α-diversity compared to the other two Daqu. It played a crucial role in breaking down substrates such as starch, proteins, hyaluronic acid, and glucan, contributing to flavor precursor synthesis. Yellow Daqu, which experienced intermediate temperature and humidity, demonstrated good esterification capacity and a milder taste profile. Black Daqu efficiently broke down raw materials, especially complex polysaccharides, but had inferior flavor and taste. Notably, large within-group variations in physicochemical quality and microbial composition were observed, highlighting limitations in color-based HTD quality assessment. Water content in HTD was associated with Daqu flavor, implicating its crucial role. This study revealed the complementary roles of the three HTD types in sauce-flavor Baijiu fermentation, providing valuable insights for product enhancement.

Pediococcus spp.-mediated competition interaction within Daqu microbiota determines the temperature formation and metabolic profiles

Fermented microbiota is critical to the formation of microenvironment and metabolic profiles in spontaneous fermentation. Microorganisms generate a diverse array of metabolites concurrent with the release of heat energy. In the case of Daqu fermentation, the peak temperature exceeded 60°C, forming a typical high-temperature fermentation system known as high-temperature Daqu. However, microorganisms that cause the quality variation in Daqu and how they affect the functional microbiota and microenvironment in the fermentation process are not yet clear. This study adopted high-throughput sequencing and monitored the dynamic fluctuations of metabolites and environmental factors to identify the pivotal microorganism responsible for the alterations in interaction patterns of functional keystone taxa and quality decline in the fermentation system of different operational areas during the in situ fermentation process that had been mainly attributed to operational taxonomic unit (OTU)_22 (Pediococcus acidilactici). Additionally, we used isothermal microcalorimetry, plate inhibition experiments, and in vitro simulation fermentation experiments to explore the impact of Pediococcus spp. on heat generation, microorganisms, and metabolite profiles. Results showed the heat peak generated by Pediococcus spp. was significantly lower than that of Bacillus spp., filamentous fungi, and yeast. In addition, the preferential growth of P. acidilactici strain AA3 would obviously affect other strains to colonize through competition, and its metabolites made a significant impact on filamentous fungi. The addition of P. acidilactici strain AA3 in simulated fermentation would cause the loss of pyrazines and acids in metabolites. These evidences showed that the overgrowth of Pediococcus spp. greatly influenced the formation of high temperatures and compounds in solid-state fermentation systems. Our work illustrated the vital impact of interaction variability mediated by Pediococcus spp. for microbial assembly and metabolites, as well as in forming temperature. These results emphasized the functional role of Daqu microbiota in metabolites and heat production and the importance of cooperation in improving the fermentation quality.IMPORTANCEThe stable and high-quality saccharifying and fermenting starter in traditional solid-state fermentation was the prerequisite for liquor brewing. An imbalance of microbial homeostasis in fermentation can adversely impact production quality. Identification of such critical microorganisms and verifying their associations with other fermentation parameters pose a challenge in a traditional fermentation environment. To enhance the quality of spontaneous fermented products, strategies such as bioaugmentation or the control of harmful microorganisms would be employed. This work started with the differences in high-temperature Daqu metabolites to explore a series of functional microorganisms that could potentially contribute to product disparities, and found that the differences in interactions facilitated directly or indirectly by Pediococcus spp. seriously affected the development of microbial communities and metabolites, as well as the formation of the microenvironment. This study not only identified functional microbiota in Daqu that affected fermentation quality, but also demonstrated how microorganisms interact to affect the fermentation system, which would provide guidance for microbial supervision in the actual production process. Besides, the application of isothermal microcalorimetry in this study was helpful for us to understand the heat production capacity of microorganisms and their adaptability to the environment. This study presented a commendable framework for improving and controlling the quality of traditional fermentation and inspired further investigations in similar systems.

Multidimensional analysis of wheat original crucial endogenous enzymes driving microbial communities metabolism during high-temperature Daqu fermentation

Knowledge of the metabolism of functional enzymes is the key to accelerate the transformation and utilization of raw materials during high temperature Daqu (HTD) manufacturing. However, the metabolic contribution of raw materials-wheat is always neglected. In this research, the relationship between the metabolism of wheat and microorganisms was investigated using physicochemical and sequencing analysis method. Results showed that the process of Daqu generation was divided into three stages based on temperature. In the early stage, a positive correlation was found between Monascus, Rhizopus and glucoamylase metabolism (r > 0.8, p < 0.05). Meanwhile, the glucoamylase metabolism in wheat occupied 63.8 % of the total matrix at the day 4. In the middle to later stages, the wheat metabolism of proteases, α-amylases and lipases in gradually reached their peak. Additionally, Lactobacillus and α-amylases presented a positive correlation (r > 0.7, p < 0.05), and the α-amylases metabolism in wheat occupied 22.18 % of the total matrix during the same time period. More importantly, the changes of enzyme activity metabolic pathway in wheat and microorganism were reflected by respiratory entropy (RQ). Overall, these results guide the choice of substrate during Daqu production.

Airborne microorganisms and key environmental factors shaping their community patterns in the core production area of the Maotai-flavor Baijiu

Airborne microorganisms are important parts of the Moutai-flavor Baijiu brewing microbial community, which directly affects the quality of Baijiu. However, environmental factors usually shape airborne microbiomes in different distilleries, even in the different production areas of the same distillery. Unfortunately, current understanding of environmental factors shaping airborne microbiomes in distilleries is very limited. To bridge this gap, we compared airborne microbiomes in the Moutai-flavor Baijiu core production areas of different distilleries in the Chishui River Basin and systematically investigated the key environmental factors that shape the airborne microbiomes. The top abundant bacterial communities are mainly affiliated to the phyla Actinobacteriota, Firmicutes, and Proteobacteri, whereas Ascomycota and Basidiomycota are the predominant fungal communities. The Random Forest analysis indicated that the biomarkers in three distilleries are Saccharomonospora and Bacillus, Thermoactinomyces, Oceanobacillus, and Methylobacterium, which are the core functional flora contributing to the production of Daqu. The correlation and network analyses showed that the distillery age and environmental temperature have a strong regulatory effect on airborne microbiomes, suggesting that the fermentation environment has a domesticating effect on air microbiomes. Our findings will greatly help us understand the relationship between airborne microbiomes and environmental factors in distilleries and support the production of the high-quality Moutai-flavor Baijiu.

Rapid detection of six Oceanobacillus species in Daqu starter using single-cell Raman spectroscopy combined with machine learning

Many traditional fermented foods and beverages industries around the world request the addition of multi-species starter cultures. However, the microbial community in starter cultures is subject to fluctuations due to their exposure to an open environment during fermentation. A rapid detection approach to identify the microbial composition of starter culture is essential to ensure the quality of the final products. Here, we applied single-cell Raman spectroscopy (SCRS) combined with machine learning to monitor Oceanobacillus species in Daqu starter, which plays crucial roles in the process of Chinese baijiu. First, a total of six Oceanobacillus species (O. caeni, O. kimchii, O. iheyensis, O. sojae, O. oncorhynchi subsp. Oncorhynchi and O. profundus) were detected in 44 Daqu samples by amplicon sequencing and isolated by pure culture. Then, we created a reference database of these Oceanobacillus strains which correlated their taxonomic data and single-cell Raman spectra (SCRS). Based on the SCRS dataset, five machine-learning algorithms were used to classify Oceanobacillus strains, among which support vector machine (SVM) showed the highest rate of accuracy. For validation of SVM-based model, we employed a synthetic microbial community composed of varying proportions of Oceanobacillus species and demonstrated a remarkable accuracy, with a mean error was less than 1% between the predicted result and the expected value. The relative abundance of six different Oceanobacillus species during Daqu fermentation was predicted within 60 min using this method, and the reliability of the method was proved by correlating the Raman spectrum with the amplicon sequencing profiles by partial least squares regression. Our study provides a rapid, non-destructive and label-free approach for rapid identification of Oceanobacillus species in Daqu starter culture, contributing to real-time monitoring of fermentation process and ensuring high-quality products.

Unraveling symbiotic microbial communities, metabolomics and volatilomics profiles of kombucha from diverse regions in China

Kombucha is a natural fermented beverage (mixed system). This study aimed to unravel the signatures of kombucha in China to achieve tailor-made microbial consortium. Here, biochemical parameters, microbiome, metabolite production and volatile profile were comprehensively compared and characterized across four regions (AH, HN, SD, SX), both commonalities and distinctions were highlighted. The findings revealed that yeast species yeast Starmerella, Zygosaccharomyces, Dekkera, Pichia and bacterium Komagataeibacter, Gluconobacter were the most common microbes. Additionally, the composition, distribution and stability of microbial composition in liquid phase were superior to those in biofilm. The species diversity, differences, marker and association were analyzed across four areas. Metabolite profiles revealed a total of 163 bioactive compounds (23 flavonoids, 13 phenols), and 68 differential metabolites were screened and identified. Moreover, the metabolic pathways of phenylpropanoids biosynthesis were closely linked with the highest number of metabolites, followed by flavonoid biosynthesis. Sixty-five volatile compounds (23 esters) were identified. Finally, the correlation analysis among the microbial composition and volatile and functional metabolites showed that Komagataeibacter, Gluconolactone, Zygosacchaaromycess, Starmerella and Dekkera seemed closely related to bioactive compounds, especially Komagataeibacter displayed positive correlations with 1-hexadecanol, 5-keto-D-gluconate, L-malic acid, 6-aminohexanoate, Starmerella contributed greatly to gluconolactone, thymidine, anabasine, 2-isopropylmalic acid. Additionally, Candida was related to β-damascenone and α-terpineol, and Arachnomyces and Butyricicoccus showed the consistency of associations with specific esters and alcohols. These findings provided crucial information for creating a stable synthetic microbial community structure, shedding light on fostering stable kombucha and related functional beverages.

Microbial communities and their correlation with flavor compound formation during the mechanized production of light-flavor Baijiu

Light-flavor Baijiu fermentation is a typical spontaneous solid-state fermentation process fueled by a variety of microorganisms. Mechanized processes have been increasingly employed in Baijiu production to replace traditional manual operation processes, however, the microbiological and physicochemical dynamics in mechanized processes remain largely unknown. Here, we investigated the microbial community succession and flavor compound formation during a whole mechanized fermentation process of light-flavor Baijiu using the conventional dilution plating method, PacBio single-molecule real-time (SMRT) sequencing and headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry. The results showed that largely different fungal and bacterial communities were involved in the soaking and fermentation processes. A clear succession from Pantoea agglomerans to Bacillus (B.) smithii and B. coagulans in dominant bacterial species and from Cladosporium exasperatum to Saccharomyces cerevisiae and Lichtheimia ramosa in dominant fungal species occurred in the soaking processes. In the fermentation process, the most dominant bacterial species was shifted from Pantoea agglomerans to Lactobacillus (La.) acetotolerans and the most dominant fungal species were shifted from Lichtheimia ramose and Rhizopus arrhizus to Saccharomyces cerevisiae. The bacterial and fungal species positively associated with acidity and the formation of ethanol and different flavor compounds were specified. The microbial species exhibited strong co-occurrence or co-exclusion relationships were also identified. The results are helpful for the improvement of mechanized fermentation process of light-flavor Baijiu production.

Exploring the Successions in Microbial Community and Flavor of Daqu during Fermentation Produced by Different Pressing Patterns

Daqu can be divided into artificially pressed daqu (A-Daqu) and mechanically pressed daqu (M-Daqu) based on pressing patterns. Here, we compared the discrepancies in physicochemical properties, volatile metabolites, and microbiota features between A-Daqu and M-Daqu during fermentation and further investigated the factors causing those differences. A-Daqu microbiota was characterized by six genera (e.g., Bacillus and Thermoactinomyces), while five genera (e.g., Bacillus and Thermomyces) dominated in M-Daqu. The flavor compounds analysis revealed that no obvious difference was observed in the type of esters between the two types of daqu, and M-Daqu was enriched with more alcohols. The factors related to differences between the two types of daqu were five genera (e.g., Hyphopichia). The functional prediction of microbial communities revealed that the functional discrepancies between the two types of daqu were mainly related to ethanol metabolism and 2,3-butanediol metabolism. This study provided a theoretical basis for understanding the heterogeneity of daqu due to the different pressing patterns.

Microbial Community Variations and Bioconversion Improvements during Soybean-Based Fermentation by Kefir Grains

Soybeans possess unexpected flavors and are difficult to be absorbed by the gastrointestinal tract. Kefir grain fermentation provides diverse strains and bioactive compounds, which may enhance flavor and bioaccessibility. Third-generation sequencing was applied to analyze the microbial diversity in milk and soybean kefir grains in this study. In both types of kefir grains, the most common bacterial genus was Lactobacillus, and their fungal communities were dominated by Kazachstania. Lactobacillus kefiranofaciens was the most abundant species in kefir grains, while Lactobacillus kefiri showed a higher proportion in soybean kefir grains. In addition, the quantification of free amino acids and volatile flavor compounds in soybean solution and soybean kefir have shown the increased content of glutamic acid and a decreased amount of unpleasant beany flavor compounds, demonstrating that the nutritive value and sensory properties of soybean can be improved by kefir grain fermentation. Finally, the bioconversion of isoflavones during fermentation and in vitro digestion was evaluated, suggesting that fermentation is beneficial for aglycone formation and absorption. To conclude, kefir fermentation is proposed to change the microbial structure of kefir grains, promote the nutritional value of soybean-based fermented products, and provide possible solutions for the development of soybean products.

Functional microorganisms in Baijiu Daqu: Research progress and fortification strategy for application

Daqu is a saccharifying and fermenting starter in the production of Chinese Baijiu; its quality directly affects the quality of Baijiu. The production of Daqu is highly environment-dependent, and after long-term natural domestication, it is rich in a wide variety of microorganisms with a stable composition, which provide complex and diverse enzymes and flavor (precursor) substances and microbiota for Jiupei (Fermented grains) fermentation. However, inoculation with a relatively stable microbial community can lead to a certain upper limit or deficiencies of the physicochemical properties (e.g., saccharification capacity, esterification capacity) of the Daqu and affect the functional expression and aroma formation of the Daqu. Targeted improvement of this problem can be proposed by selecting functional microorganisms to fortify the production of Daqu. This review introduced the isolation, screening, identification and functional characteristics of culture-dependent functional microorganisms in Baijiu-brewing, the core functional microbiota community of Daqu, and the related research progress of functional microorganisms fortified Daqu, and summarized the fortifying strategies of functional microorganisms, aiming to further deepen the application of functional microorganisms fortification in Daqu fermentation and provide ideas for the flavor regulation and quality control of Baijiu.

Bacteria-induced amino acid metabolism involved in appearance characteristics of high-temperature Daqu

BACKGROUND

Significant changes occurd in Daqu bricks on the 15th day of incubation, and brick color (yellow, brown, or dark) is generally used as a standard for quality evaluation by experienced workers. This study aimed to explore the basis behind the phenomenon through multi-omics studies. The physicochemical properties of different high-temperature Daqu were compared. Furthermore, PacBio sequencing and the ultra-high-performance liquid chromatographic-Q-exactive-mass spectrometric approach were employed to analyze the differences in the microbiome and metabolome among different Daqu samples.

RESULTS

Bacillus was the biomarker of yellow Daqu, Thermoactinomyces and Thermoascus were the key genera in brown Daqu, and Burkholderiales, Sphingomonas, and Ralstonia were biomarkers in dark Daqu. The physicochemical characteristics (especially the color values) of different high-temperature Daqu showed strong correlations with the bacterial alpha diversity and the relative abundance of dominant bacterial genera. Amino acid metabolism pathways including tryptophan metabolism, β-alanine metabolism, and arginine biosynthesis were the key factors resulting in the characteristic differences where Bacillus, Burkholderia, Ralstonia, and Sphingomonas were pivotal bacterial genera. The relative abundance of Bacillus had a positive correlation with the content of 3-hydroxykynurenamine, l-glutamic acid, and pantothenic acid, while it showed a negative correlation with indoleacetic acid, l-tryptophan, N-acetylserotonin, l-histidine, l-aspartic acid, phosphatidylserine, 5-methoxyindoleacetate, and L-serine. Burkholderia, Ralstonia, and Sphingomonas had the opposite effects.

CONCLUSION

Microbes play different roles in amino acid metabolism pathways, producing different metabolites, contributing to the differences in Daqu appearance and quality. © 2022 Society of Chemical Industry.

Microbial characteristics and metabolite profiles of high-temperature Daqu in different maturation stages

The maturation period of high-temperature Daqu (HTD) is usually 3-6 months, and the characteristics of HTD at different maturation stages were different. In this study, the microbial characteristics and metabolite profiles of HTD at different maturation stages were revealed with the combination of physicochemical detection, the third generation Pacific Biosciences (PacBio) single-molecule, real-time (SMRT) sequencing technology, gas chromatography-mass spectrometry (GC-MS), and gas chromatography-ion mobility spectrometry (GC-IMS). Results showed that HTD matured for 6 months (Mix_m6) had higher saccharification power but less culturable thermotolerant bacteria and fungi than HTD matured for 3 months (Mix_m3). The average relative abundances of Thermoactinomyces, Paenibacillus, and Rasamsonia in Mix_m3 were higher than that in Mix_m6, while the average relative abundances of Bacillus, Pseudomonas, Thermoascus increased obviously with the prolongation of the maturation period. Streptomyces and Thermoactinomyces were biomarkers in Mix_m3, while Burkholderia and Pseudomonas were regarded as biomarkers in Mix_m6. Differences in microbiota structure led to different enrichment of metabolic pathways in HTD at different maturation stages, resulting in different flavor profiles, especially in ethyl acetate, 1-octen-3-one, (E)-3-Hexen-1, 2,3,5-trimethy-6-ethylpyrazine, pyrazine, tetramethyl content. The microbiota and metabolite characteristics of HTD comprehensively reflected the HTD quality in different maturation stages, which provided a reference for determining the optimal maturation time.