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.

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, ß-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.

Response of microbial community assembly and succession pattern to abiotic factors during the second round of light-flavor Baijiu fermentation.

The regulation of microbial communities is an important strategy for fermentation management. Dynamic microbiota during the Baijiu fermentation is shaped by a variety of abiotic factors. Therefore, this study aims to investigate the effects of the microbiota of the fermentation starter Daqu on the microbial assembly and the interaction of microbiota succession and abiotic factors during the second round (Ercha) of light-flavor Baijiu fermentation. The results revealed that Streptomyces, Bacillus, Lactobacillus, and Staphylococcus were the dominant bacterial genera in the initial fermentation, while Lactobacillus was dominant during the middle and later stages. Pichia and Saccharomycopsis were the dominant fungal genera during the whole fermentation process. A total of 54 volatile compounds were identified during the fermentation, among which 15 compounds, mainly including ethyl acetate, diethyl azelate, ethyl 2-hydroxyisocaproate, 3-furaldehyde, and ethylidene diacetate, were identified as important flavor metabolites. The SourceTracker software revealed that Daqu contributed 52.3 % of the bacterial community and 38.6 % of the fungal community to the fermentation. Ethanol, moisture, and pH were the major factors regulating the succession of dominant bacteria and fungi during the fermentation. The microbial succession and co-occurrence pattern driven by abiotic factors played a crucial role in shaping flavor profiles. These results provide guidance for controlling the fermentation process by optimizing operational parameters or bioaugmentation with specific microbes.

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.

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.

Insights into the bacterial, fungal, and phage communities and volatile profiles in different types of Daqu.

Daqu has a rich and diverse microbiota, giving them a suitable biotope for phages. However, the absolute abundances of bacteria and fungi, as well as the phage community characteristics in Daqu, remain unclear. In this study, the microbiota absolute abundance, indigenous phage composition and function, and volatile compound profiles of high-temperature Daqu (HTDQ), medium-temperature Daqu (MTDQ), and low-temperature Daqu (LTDQ) were investigated. Absolute microbiota quantification revealed that there were significant variations in microbial composition and absolute abundance across three types of Daqu. The absolute abundances of the top 30 bacterial genera in LTDQ, MTDQ, and HTDQ were 6.0 × 105, 5.3 × 104, 1.4 × 105 copies/ng DNA, while the top 30 fungal genera had 8.5 × 107, 2.1 × 106, and 6.2 × 105 copies/ng DNA, respectively. LTDQ were enriched in Pantoea, Staphylococcus, and Saccharomycopsis; MTDQ were dominated by Saccharopolyspora, Staphylococcus, Saccharomycopsis, and Aspergillus; HTDQ were dominated by Saccharopolyspora, Bacillus, Byssochlamys, and Saccharomycopsis. Volatile profile analysis revealed that LTDQ, MTDQ, and HTDQ comprised 68, 68, and 75 compounds, respectively, with 39 compounds shared by the three types. Fourteen volatile compounds were identified as highly discriminative features among three types of Daqu, which were closely related to Saccharopolyspora, Thermoactinomyces, Kroppenstedtia, Byssochlamys, and Thermomyces. Metaviromics indicated that Genomoviridae, Mimiviridae and Siphoviridae, and Parvoviridae were the dominant viruses in LTDQ, MTDQ, and HTDQ, respectively. The hosts of phages in Daqu mainly included Lactobacillus, Enterobacter, Pantoea, Bacillus, Pediococcus, and Staphylococcus. Phages may prey on numerous microbes living on Daqu via pathways such as genetic information processing, signaling and cellular processes, and replication and repair. This study highlights the use of absolute quantification to avoid misjudgment of differential taxa in comparative microbiome analysis and provides new insights into the phage community and function in Daqu.

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

Wheat-origin microbiota is a critical factor in the assembly of the microbial community during high-temperature Daqu incubation. However, the succession and functional mechanisms of these microbial communities in Daqu are still unclear. This study investigated the shifts in microbiota diversity from the wheat to the end of incubation by the third generation Pacific Biosciences (PacBio) single-molecule, real-time (SMRT) sequencing technology. Results indicated that Staphylococcus, Pantoea, Alternaria, and Mycosphaerella were the dominant genera of wheat-origin microbiota while Bacillus and Thermoascus were the most predominant bacterial and fungal genera of Daqu microbiota, respectively. Metabolite detection revealed that volatile organic compounds (VOCs) changed obviously in different incubation stages and the 7th day to the 15th day of incubation was the critical period for the formation of VOCs. The content of non-VOCs, especially sugars, increased steeply in the first four days of incubation. The network analysis between microbes and metabolites showed that Thermoactinomyces and Staphylococcus had opposite correlations with most non-VOCs. Alternaria and Mycosphaerella had strong positive correlations with fructose. As key functional fungal genera in wheat-origin microbiota, Mycosphaerella, Aspergillus, and Alternaria participated in multiple metabolic pathways (gluconeogenesis I, sucrose degradation III, pentose phosphate pathway, 5-aminoimidazole ribonucleotide biosynthesis I, methyl ketone biosynthesis, and GDP-mannose biosynthesis) at the early stage of incubation, which played an important role in the formation of flavors and succession of microbiota. This work highlighted the shifts and functionality of wheat-origin microbiota in Daqu incubation, which can be a guideline to stabilize Daqu quality by wheat-origin microbiota control.

Comparative study on inhibitory effects of ferulic acid and p-coumaric acid on Salmonella Enteritidis biofilm formation.

Biofilm cells exhibit higher resistance than their planktonic counterparts to commonly used disinfectants in food industry. Phenolic acids are promising substitute offering less selective pressure than traditional antibiotics. This study aims to evaluate the inhibitory effects of ferulic acid (FA) and p-coumaric acid (p-CA) on Salmonella Enteritidis biofilm formation and explore the underlying inhibitory mechanisms. The minimal inhibitory concentration (MIC) of FA and p-CA were 1.0 and 0.5 mg/ml, respectively. The sub-inhibitory concentration (1/8 MIC) significantly decreased biofilm formation without growth inhibitory effects. The biomass and extracellular polymeric substances (EPS) of S. Enteritidis biofilm as well as the bacterial swimming and chemotaxis abilities were significantly decreased when exposed to sub-MIC concentrations of FA and p-CA. These two phenolic acids showed high affinity to proteins involved in flagella motility and repressed the S. Enteritidis biofilm formation-related gene expressions. Furthermore, these two phenolic acids maintained high antibiofilm efficiency in simulated food processing conditions. This study provided valuable information of multiple phenotypic and molecular responses of S. Enteritidis to these two phenolic acids.

Characteristics of the microbiota and metabolic profile of high-temperature Daqu with different grades.

The superior grade Daqu (S_Daqu) and normal grade Daqu (N_Daqu) have obvious differences in flavor, fracture surface, appearance, etc., which can be accurately grouped by well-trained panel based on their sensory properties. However, the differences in microbial community diversity and metabolites between the S_Daqu and N_Daqu were still unclear. The culture-dependent method, the third generation Pacific Biosciences (PacBio) single-molecule, real-time (SMRT) sequencing technology, and nuclear magnetic resonance (NMR) were combined to show the characteristics in microorganisms and metabolites. Results showed that the fungal counts were higher in N_Daqu while the richness of bacterial communities was higher in S_Daqu (P < 0.05). Lentibacillus, Burkholderia, Saccharopolyspora, Thermoascus, and Rasamsonia were the dominant genera of S_Daqu while Staphylococcus, Scopulibacillus, and Chromocleista were the dominant genera in N_Daqu. The content of differential acids, amino acids, and alcohols including fumarate, glucuronate, glycine, 4-carboxyglutamate, and myo-inositol in S_Daqu was higher than that in N_Daqu by 1H NMR coupled with multivariate statistical analysis. The network analysis regarding microbes and metabolites suggested that Saccharopolyspora showed a strong positive correlation with 4-carboxyglutamate while Thermoascus and Chromocleista were highly negatively correlated with alanine and isobutyrate, respectively. Linear Discriminant Analysis (LDA) Effect Size (LEfSe) revealed that Macrococcus and Caulobacter were regarded as bacterial biomarkers in the S_Daqu while Chromocleista was the key fungal genera in N_Daqu. Functionality prediction indicated that the bacteria in S_Daqu were largely involved in more metabolic activities including biosynthesis, degradation, detoxification, and generation of precursor metabolite and energy.

Unraveling the microbial compositions, metabolic functions, and antibacterial properties of Huangshui, a byproduct of Baijiu fermentation.

Huangshui (HS) is a byproduct of Chinese Baijiu production that has tremendous potential to become a high-value product in the food industry. This study comprehensively analyzed the commonalities and differences in physicochemical properties, microbial structures, metabolomes, flavor profiles, and antibacterial properties among sources of HS. The HS samples were extracted from three different pits in three different workshops within an industrial Baijiu distillery. Lactobacillus was the dominant genus of bacteria in all of them, while Kazachstania, Aspergillus, and Pichia were the dominant genera of fungi. A total of 45 volatile compounds, including ethyl hexanoate, hexanoic acid, and 1-butanol, were detected in the HS by headspace solid-phase microextraction coupled with gas chromatography mass spectrometry, suggesting HS could be used to flavor liquor. Untargeted metabolomic analysis yielded 224 nonvolatile metabolites that were common in all HS samples. These metabolites included organic acids, carbohydrates, benzenoids, nucleic acids, and fatty acids, which are mainly involved in amino acid and sugar metabolism. While the compositions of the microbiome and metabolome among HS samples were affected by workshop factors, there were essentially no differences in the bactericidal properties of the HS samples among workshops. HS exhibited potent antibacterial activities against Escherichia coli and Staphylococcus aureus, and HS was effective in inactivating mature biofilms formed on polystyrene microplates, as confirmed by scanning electron micrographs. Our results provided a theoretical basis to increase the economic value of HS for applications in the food industry.

Characterization and comparison of the bacterial community on environmental surfaces through a fresh-cut vegetables processing line in China.

Zoning is typically adopted by food manufacturers and classified into three different zones including Zone 1 (food contact surface), Zone 2 (proximity to food and food contact surfaces) and Zone 3 (remote surfaces from processing). In this study, environmental surfaces belonging to these three zones were sampled during food processing in a fresh-cut vegetables (FVs) processing facility located in Beijing, China. Bacterial loads in terms of aerobic plate count and coliform count were evaluated by culture-dependent techniques. The profile and diversity of bacterial community in these three zones were investigated by high-throughput sequencing. Zone 1 showed similar microbiota and predominated by Pseudomonas and Acinetobacter, while the predominant genera on Zone 2 or 3 were quite varied among different processing steps. The SourceTracker analysis showed that most of the bacteria (above 80%) on surfaces were from unknown sources, while sorting and disinfection & cleaning steps contributed equally to the bacterial community of cutting areas. Microbial association network analysis revealed strong positive interactions of Comamonas and Janthinobacterium with Myroides and Serratia, respectively, whereas Pseudomonas showed no significant correlation with other genera. The function of microbial communities was predicted based on BugBase 16S rRNA database, and the results indicated that the proportions of potential biofilm-forming bacteria were above 70% in all samples, and species of Pseudomonas, Comamonas, Chryseobacterium and Janthinobacterium were opportunistic pathogens or spoilage bacteria. This study evaluated the bacteria risks including bacterial load, composition, as well as potential bacterial interaction, function and microbial transfer on food processing surfaces, which will facilitate our better understanding on the cross-contaminations and preventions of harmful microorganism in FVs processing industry.

Reduced neutralization of SARS-CoV-2 B.1.617 variant by convalescent and vaccinated sera.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The Spike protein that mediates coronavirus entry into host cells is a major target for COVID-19 vaccines and antibody therapeutics. However, multiple variants of SARS-CoV-2 have emerged, which may potentially compromise vaccine effectiveness. Using a pseudovirus-based assay, we evaluated SARS-CoV-2 cell entry mediated by the viral Spike B.1.617 and B.1.1.7 variants. We also compared the neutralization ability of monoclonal antibodies from convalescent sera and neutralizing antibodies (NAbs) elicited by CoronaVac (inactivated vaccine) and ZF2001 (RBD-subunit vaccine) against B.1.617 and B.1.1.7 variants. Our results showed that, compared to D614G and B.1.1.7 variants, B.1.617 shows enhanced viral entry and membrane fusion, as well as more resistant to antibody neutralization. These findings have important implications for understanding viral infectivity and for immunization policy against SARS-CoV-2 variants.

Understanding the Shifts of Microbial Community and Metabolite Profile From Wheat to Mature Daqu.

Wheat-originated microbes play an important role in shaping the quality of high-temperature Daqu which is commonly used as a starter for producing sauce-flavor Baijiu. However, the shifts of microbiota from raw material to fresh Daqu and then to mature Daqu remain unclear. Hence, in the present study, the inner and outer of fresh and mature Daqu were collected to explore the correlation between microbiota and metabolites as well as the source of the microbiota in Daqu. Results indicated that the activities of amylase and protease between the inner and outer of fresh Daqu varied significantly while both parts became similar after maturation. The predominant bacteria shifted from Saccharopolyspora (outer) and Staphylococcus (inner) to Kroppenstedtia (both outer and inner), while the predominant fungi shifted from Thermoascus (both outer and inner) to Byssochlamys (outer) and Fusarium (inner). A combining analysis of headspace solid-phase micro extraction-gas chromatography-mass spectrometry, headspace gas chromatography-ion mobility spectrometry, and nuclear magnetic resonance was employed to detect the metabolites. The network analysis was conducted to perform the relationships between microbes and metabolites. The results showed that the bacteria, especially Saccharopolyspora, Bacillus, and Acinetobacter, had a strong correlation with the productions of esters, amino acids and their derivatives, and sugars and their derivatives, while most fungi such as Thermoascus, were negatively correlated with the phenylalanine, trimethylamine n-oxide, and isovalerate. SourceTracker analysis indicated that wheat was the important source of the Daqu microbiota, especially, the microorganisms in the inner of Daqu might be the drivers of the microbial succession during maturation. This study provided a comprehensive exploration to understand the microbial sources and shifts in high-temperature Daqu during maturation.

Reduced neutralization of SARS-CoV-2 B.1.617 variant by inactivated and RBD-subunit vaccine

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The Spike protein that mediates coronavirus entry into host cells is a major target for COVID-19 vaccines and antibody therapeutics. However, multiple variants of SARS-CoV-2 have emerged, which may potentially compromise vaccine effectiveness. Using a pseudovirus-based assay, we evaluated SARS-CoV-2 cell entry mediated by the viral Spike B.1.617 and B.1.1.7 variants. We also compared the neutralization ability of monoclonal antibodies from convalescent sera and neutralizing antibodies (NAbs) elicited by CoronaVac (inactivated vaccine) and ZF2001 (RBD-subunit vaccine) against B.1.617 and B.1.1.7 variants. Our results showed that, compared to D614G and B.1.1.7 variants, B.1.617 shows enhanced viral entry and membrane fusion, as well as more resistant to antibody neutralization. These findings have important implications for understanding viral infectivity and for immunization policy against SARS-CoV-2 variants.

Immune memory in convalescent patients with asymptomatic or mild COVID-19.

It is important to evaluate the durability of the protective immune response elicited by primary infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we systematically evaluated the SARS-CoV-2-specific memory B cell and T cell responses in healthy controls and individuals recovered from asymptomatic or symptomatic infection approximately 6 months prior. Comparatively low frequencies of memory B cells specific for the receptor-binding domain (RBD) of spike glycoprotein (S) persisted in the peripheral blood of individuals who recovered from infection (median 0.62%, interquartile range 0.48-0.69). The SARS-CoV-2 RBD-specific memory B cell response was detected in 2 of 13 individuals who recovered from asymptomatic infection and 10 of 20 individuals who recovered from symptomatic infection. T cell responses induced by S, membrane (M), and nucleocapsid (N) peptide libraries from SARS-CoV-2 were observed in individuals recovered from coronavirus disease 2019 (COVID-19), and cross-reactive T cell responses to SARS-CoV-2 were also detected in healthy controls.

Emerging SARS-CoV-2 variants reduce neutralization sensitivity to convalescent sera and monoclonal antibodies

SARS-CoV-2 Spike-specific antibodies contribute the majority of the neutralizing activity in most convalescent human sera. Two SARS-CoV-2 variants, N501Y.V1 (also known as B.1.1.7 lineage or VOC-202012/01) and N501Y.V2 (B.1.351 lineage), reported from the United Kingdom and South Africa, contain several mutations in the receptor binding domain of Spike and are of particular concern. To address the infectivity and neutralization escape phenotypes potentially caused by these mutations, we used SARS-CoV-2 pseudovirus system to compare the viral infectivity, as well as the neutralization activities of convalescent sera and monoclonal antibodies (mAbs) against SARS-CoV-2 variants. Our results showed that N501Y Variant 1 and Variant 2 increase viral infectivity compared to the reference strain (wild-type, WT) in vitro. At 8 months after symptom onset, 17 serum samples of 20 participants (85%) retaining titers of ID50 >40 against WT pseudovirus, whereas the NAb titers of 8 samples (40%) and 18 samples (90%) decreased below the threshold against N501Y.V1 and N501Y.V2, respectively. In addition, both N501Y Variant 1 and Variant 2 reduced neutralization sensitivity to most (6/8) mAbs tested, while N501Y.V2 even abrogated neutralizing activity of two mAbs. Taken together the results suggest that N501Y.V1 and N501Y.V2 reduce neutralization sensitivity to some convalescent sera and mAbs.