Electrochemically Induced Ru/CoOOH Synergistic Catalyst as Bifunctional Electrode Materials for Alkaline Overall Water Splitting.

Efficient and affordable price bifunctional electrocatalysts based on transition metal oxides for oxygen and hydrogen evolution reactions have a balanced efficiency, but it remains a significant challenge to control their activity and durability. Herein, a trace Ru (0.74 wt.%) decorated ultrathin CoOOH nanosheets (≈4 nm) supported on the surface of nickel foam (Ru/CoOOH@NF) is rationally designed via an electrochemically induced strategy to effectively drive the electrolysis of alkaline overall water splitting. The as-synthesized Ru/CoOOH@NF electrocatalysts integrate the advantages of a large number of different HER (Ru nanoclusters) and OER (CoOOH nanosheets) active sites as well as strong in-suit structure stability, thereby exhibiting exceptional catalytic activity. In particular, the ultra-low overpotential of the HER (36 mV) and the OER (264 mV) are implemented to achieve 10 mA cm-2. Experimental and theoretical calculations also reveal that Ru/CoOOH@NF possesses high intrinsic conductivity, which facilitates electron release from H2O and H-OH bond breakage and accelerates electron/mass transfer by regulating the charge distribution. This work provides a new avenue for the rational design of low-cost and high-activity bifunctional electrocatalysts for large-scale water-splitting technology and expects to help contribute to the creation of various hybrid electrocatalysts.

Rapid detection of Saccharomyces cerevisiae with boronic acid-decorated multivariate metal-organic frameworks and aptamers.

Liquor brewing is a classic solid-substrate fermentation process with a unique brewing microbiome. As one of the most common fungi, Saccharomyces cerevisiae ferments saccharides and has been extensively applied in brewing production. Here, we present the facile fabrication of a selective, sensitive, and integrated fluorescent biosensor for S. cerevisiae detection. The proposed biosensor used aptamer-modified magnetic beads to specifically capture S. cerevisiae, and the enriched fungi were recognized and detected with boronic acid-decorated multivariate metal-organic frameworks. The biosensor allows rapid quantification of S. cerevisiae in the range of 10-106 CFU mL-1, showing excellent specificity and repeatability, and maintaining stable biosensing performance in long-term storage. The analytical ability of the proposed biosensor was successfully verified in distilled yeast and fermented grain samples spiked with S. cerevisiae.

Fusion data from FT-IR and MALDI-TOF MS result in more accurate classification of specific microbiota.

Microbes are usually present as a specific microbiota, and their classification remains a challenge. MALDI-TOF MS is particularly successful in library-based microbial identification at the species level as it analyzes the molecular weight of peptides and ribosomal proteins. FT-IR allows more accurate classification of bacteria at the subspecies level due to the high sensitivity, specificity and repeatability of FT-IR signals from bacteria, which is not achievable with MALDI-TOF MS. Previous studies have shown that more accurate identification results can be obtained by the fusion of FT-IR and MALDI-TOF MS spectral data. Here, we constructed 20 groups of model microbiota samples and used FT-IR, MALDI-TOF MS, and their fusion data to classify them. Hierarchical clustering analysis (HCA) showed that the classification accuracy of FT-IR, MALDI-TOF MS, and the fusion data was 85%, 90%, and 100%, respectively. These results indicate that both FT-IR and MALDI-TOF MS can effectively classify specific microbiota, and the fusion of their spectral data could improve the classification accuracy. The FT-IR and MALDI-TOF MS data fusion strategy may be a promising technology for specific microbiota classification.

Non-gene-editing microbiome engineering of spontaneous food fermentation microbiota-Limitation control, design control, and integration.

Non-gene-editing microbiome engineering (NgeME) is the rational design and control of natural microbial consortia to perform desired functions. Traditional NgeME approaches use selected environmental variables to force natural microbial consortia to perform the desired functions. Spontaneous food fermentation, the oldest kind of traditional NgeME, transforms foods into various fermented products using natural microbial networks. In traditional NgeME, spontaneous food fermentation microbiotas (SFFMs) are typically formed and controlled manually by the establishment of limiting factors in small batches with little mechanization. However, limitation control generally leads to trade-offs between efficiency and the quality of fermentation. Modern NgeME approaches based on synthetic microbial ecology have been developed using designed microbial communities to explore assembly mechanisms and target functional enhancement of SFFMs. This has greatly improved our understanding of microbiota control, but such approaches still have shortcomings compared to traditional NgeME. Here, we comprehensively describe research on mechanisms and control strategies for SFFMs based on traditional and modern NgeME. We discuss the ecological and engineering principles of the two approaches to enhance the understanding of how best to control SFFM. We also review recent applied and theoretical research on modern NgeME and propose an integrated in vitro synthetic microbiota model to bridge gaps between limitation control and design control for SFFM.

Improving flavor metabolism of Saccharomyces cerevisiae by mixed culture with Bacillus licheniformis for Chinese Maotai-flavor liquor making.

Microbial interactions could impact the metabolic behavior of microbes involved in food fermentation, and therefore they are important for improving food quality. This study investigated the effect of Bacillus licheniformis, the dominant bacteria in the fermentation process of Chinese Maotai-flavor liquor, on the metabolic activity of Saccharomyces cerevisiae. Results indicated that S. cerevisiae inhibited the growth of B. licheniformis in all mixed culture systems and final viable cell count was lower than 20 cfu/mL. Although growth of S. cerevisiae was barely influenced by B. licheniformis, its metabolism was changed as initial inoculation ratio varied. The maximum ethanol productions were observed in S. cerevisiae and B. licheniformis at 10(6):10(7) and 10(6):10(8) ratios and have increased by 16.8 % compared with single culture of S. cerevisiae. According to flavor compounds, the culture ratio 10(6):10(6) showed the highest level of total concentrations of all different kinds of flavor compounds. Correlation analyses showed that 12 flavor compounds, including 4 fatty acids and their 2 corresponding esters, 1 terpene, and 5 aromatic compounds, that could only be produced by S. cerevisiae were significantly correlated with the initial inoculation amount of B. licheniformis. These metabolic changes in S. cerevisiae were not only a benefit for liquor aroma, but may also be related to its inhibition effect in mixed culture. This study could help to reveal the microbial interactions in Chinese liquor fermentation and provide guidance for optimal arrangement of mixed culture fermentation systems.

Allosteric mechanism of synergistic effect in α- and ß-amylase mixtures.

Alpha-amylase and beta-amylase coexist as mixtures in industrial production, and the two amylases have active synergistic effects when they approach each other. These effects are due to enhanced enzyme binding affinity for the substrate and the rate of particle hydrolysis. Here, we report the allosteric mechanism of this synergistic effect in α- and ß-amylase mixtures. The assay showed higher activity after mixing α- and ß-amylase. Molecular docking showed that α- and ß-amylase create a stable dual-enzyme complex with high binding energy, and that complex formation does not affect the exposure of respective active sites. ß-Amylase is specifically bound to the B domain of α-amylase, and the dynamic plasticity of the B domain makes it move spatially, and this adjustment leads to a more open conformation in the active site of α-amylase. Because the enzymes binding make the complex more stable, the degree to which the relative activity of the dual-enzyme complex is inhibited is significantly reduced. After enzyme hydrolysis, the products maltose and glucose accumulate and produce competitive inhibition, which explains the relative activity decrease of the later-stage dual-enzyme cooperation. Structural characterization by FT-IR and CD spectroscopy did not reveal significant changes in respective secondary structures after enzyme binding.

Enzyme-integrated metal-organic framework platform for cascade detection of α-amylase.

As one of the most important industrial enzymes, α-amylase is widely used in food processing, such as starch sugar and fermentation, bringing high added value to industry of more than a trillion dollars. We developed a multi-enzyme system (Glu&Gox@Cu-MOF-74) prepared by embedding α-glucosidase (Glu) and glucose oxidase (Gox) into the biomimetic metal-organic framework Cu-MOF-74 using in situ encapsulation within 15 min at room temperature for efficient and sensitive detection of α-amylase activity. Benefitting from the remarkable peroxidase-mimicking property and rigid skeleton of Cu-MOF-74, the biocatalytic platform exhibited excellent cascade activity and tolerance in various extremely harsh environments compared to natural enzymes. On this basis, a cascade biocatalytic platform was constructed for the detection of α-amylase activity with wide linear range (5-100 U/L) and low limit of detection (1.45 U/L). The colorimetric cascade scheme is important for the sensitive and selective determination of α-amylase in complex fermentation samples, and the detection time is short (∼0.5 h). This work provides new ideas for the detection of α-amylase based on the cascade amplification method.

Integration of multienzyme co-immobilization and biomimetic catalysis in magnetic metal-organic framework nanoflowers for α-amylase detection in fermentation samples.

Multiple enzymes induce biological cascade catalysis is essential in nature and industrial production. However, the shortcomings of enzymes, including unsatisfactory stability, reusability, and sensitivity in harsh microenvironment, have restricted their broader use. Here, we report a facile method for fabricating a cascade system by combining the benefits of immobilized enzymes and biomimetic catalysis based on magnetic metal-organic framework nanoflowers (mMOFNFs). mMOFNFs prepared through the layered double hydroxide-derived strategy exhibited remarkable peroxidase-like activity and accessible amino interface, enabling it to serve not only as a reliable carrier for α-glucosidase and glucose oxidase fixation, but also as a nanozyme participating in cascade. On this basis, a colorimetric biosensor of excellent sensitivity and selectivity for α-amylase detection was constructed with a wide range (2-225 U L-1), low detection limit (2.48 U L-1), and rapid operation (30 min). This work provides a versatile strategy for establishing multi-enzyme cascade systems and rapid analysis of α-amylase.

Oxygen influences spatial heterogeneity and microbial succession dynamics during Baijiu stacking process.

The spontaneous solid-state stacking process (SSSP) of Baijiu is an environmentally friendly and cost-effective process for enriching and assembling environmental microorganisms to guarantee the subsequent fermentation efficiency. In this study, how SSSP create spatial heterogeneity of stacking piles were found through spatiotemporal sampling. The degree of difficulty in oxygen exchange categorizes the stacking pile into depleted (≤4%), transitional (4 %-17 %), and enriched (≥17 %) oxygen-defined layers. This results in variation in succession rates (Vdepleted > Vtransitional > Venriched), which accelerates spatial heterogeneity during SSSP. As a dominant species (65 %-99 %) in depleted and transitional layers, Acetilactobacillus jinshanensis can rapidly reduce oxygen disturbance by upregulating poxL and catE, that sustains spatial heterogeneity. The findings demonstrated the value of oxygen control in shaping spatial heterogeneity during SSSP processes, which can create specific functional microbiome. Adding spatial heterogeneity management will help achieve more precise control of such solid-state fermentation systems.

High-sensitivity profiling of dipeptides in sauce-flavor Baijiu Daqu by chemical derivatization and ultrahigh-performance liquid chromatography coupled with high-resolution mass spectrometry.

Dipeptides in sauce-flavor Baijiu Daqu are protein degradation products during the fermentation of Daqu, which are believed to play a crucial role in the flavor and quality of Baijiu. Herein, we integrated dansyl chloride derivatization with ultrahigh-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) for comprehensively profiling dipeptides in Daqu. The derivatization efficiency was higher than 99.1 % for all 17 dipeptide standards under the optimized derivatization conditions. In total, 118 dipeptides were detected in Daqu. The method was validated and the analytical characteristics including the linearity (spanned across 2-4 orders of magnitude), precision (1.2-19.9 %), limit of detection (varied from 1.1 to 53.4 pmol/mL) and the stability (3.6-15.8 %) are satisfactory. The usefulness of the method was examined by studying the distribution characteristics of dipeptides in Daqu under different production conditions. The present method provides an effective and robust strategy for comprehensively analyzing dipeptide compounds in complex biological samples.

Spatiotemporal accumulation differences of volatile compounds and bacteria metabolizing pickle like odor compounds during stacking fermentation of Maotai-flavor baijiu.

Pickle like odor (PLO) is undesirable in Maotai-flavor baijiu; however, its formation mechanism is unclear. Furthermore, there is a lack of understanding of the spatiotemporal accumulation of volatile compounds (including PLO compounds, PLOC) and of the microorganisms responsible for the production of PLOC during stacking fermentation. In this study, we analyzed the spatiotemporal distribution differences of 132 volatile compounds in piled fermented grains. PLOC (n = 5) were higher in pile surface than in pile center, reaching their highest levels at 6th and 5th rounds, respectively. The microorganisms in pile center were more conducive to the formation of alcohols, while those in the pile surface more promoted the synthesis of esters. Rhodococcus and Zygosaccharomyces promoted the formation of PLOC. Acetobacter was negatively correlated with the content of sulfur compounds by promoting their conversion into non-volatile sulfur compounds, thereby reducing the content of PLOC. This study provides information on the spatiotemporal differences of volatile compounds (especially PLOC) in piled fermented grains and identified the microorganisms that produce PLOC.

Rapid and ultrasensitive activity detection of α-amylase based on γ-cyclodextrin crosslinked metal-organic framework nanozyme.

α-Amylase plays a significant part in fermentation and the food industry, as this enzyme effectively regulates the content of different sugars in brewing systems and affects the yield and quality of alcoholic beverages. Nevertheless, current strategies suffer from unsatisfactory sensitivity and are time-consuming or are indirect methods which demand the assistance of tool enzymes or inhibitors. Therefore, they are unsuitable for the low bioactivity and non-invasive detection of α-amylase in fermentation samples. Rapid, sensitive, facile, and direct detection method of this protein remains challenging in actual applications. In this work, a nanozyme-based α-amylase assay was constructed. The colorimetric assay used the interaction between α-amylase and γ-cyclodextrin (γ-CD) which crosslinks MOF-919-NH2. The determination mechanism bases on the hydrolysis of γ-CD by α-amylase, resulting in increased peroxidase-like bioactivity of the released MOF nanozyme. The detection limit was 0.12 U L-1 with a wide linear range (0-200 U L-1) and excellent selectivity. Additionally, the proposed detection method was successfully utilized in distilled yeasts to verify analytical capability in fermentation samples. The exploration of this nanozyme-based assay not only provides a convenient and effective strategy for enzyme activity determination in food industry, but also has promotion significance in clinical diagnosis and pharmaceutical production.

The differences in carbohydrate utilization ability between six rounds of Sauce-flavor Daqu.

Sauce-flavor Daqu is an important source of fermentation power in baijiu brewing. Revealing carbohydrate metabolism will help to explore the underlying reasons for the difference in fermentation performance of Daqu. In this study, metagenomic and metaproteomic technologies were performed to explore the carbohydrate metabolism network and its active functional microorganisms of Sauce-flavor Daqu. The sugar profile was analyzed using LC-MS to confirm the metabolic network. The results showed that 23 fungi and 5 bacteria were involved in carbohydrate metabolism. Starch metabolism, cellulose metabolism, and glucan metabolism were the main metabolic pathways, in which fungi especially Aspergillus were more involved than bacteria. Among these active microorganisms, Saccharomycopsis fibuligera, Aspergillus oryzae, Monascus purpureus, Byssochlamys spectabilis, Lichtheimia ramosa, Thermomyces lanuginosus, and Thermoascus aurantiacus were significant functional microorganisms with the ability to produce multiple enzymes. Lichtheimia ramosa, Lichtheimia corymbifera and Kroppenstedtia eburnea were biomarkers of Daqu in the first round, granting it a better liquefaction ability. ß-amylase derived from wheat also played an important role in starch degradation, and the synergistic effect with α-amylase endowed Daqu with higher liquefaction power in the first two rounds. The results of this study are of great significance for the analysis of the mechanism of Daqu fermentation and provide a reliable theoretical basis for strengthening the fermentation performance of Daqu.

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.

Allosteric regulation of α-amylase induced by ligands binding.

The conformational changes in α-amylase induced by different ligands, including metal ions, substrates, and aromatic compounds in liquor production, were systematically studied using spectroscopy. Fluorescence acrylamide quenching analysis showed that the interaction with active metal cations (K+, Na+, and Ca2+) led to higher exposure of the active sites in α-amylase. In contrast, interactions with substrates (soluble starch, amylose, amylopectin, wheat starch, and dextrin) reduced the degree of exposure of active sites, and the conformation of the enzyme became more rigid and compact. Although the interaction with inhibitory metal cations (Mg2+, Zn2+) and aromatic compounds generated in the brewing process (guaiacol, eugenol, thymol, and vanillin) increased the exposure of active site with a relatively low amplitude, it reduced the enzymatic activity. This finding may be due to the overall structure of the enzyme becoming looser. Structural stability showed that the active cations and substrates increased the stability of the secondary structure of the α-amylase backbone, whereas the inhibitory cations and aromatic compounds reduced the stability of the backbone but increased the compact of domain A and B. Enzymatic assays and molecular docking experiments strongly supported these conclusions. The experimental results may provide a valuable reference for controlling related conditions and improving production efficiency.

Protocol for bacterial typing using Fourier transform infrared spectroscopy.

The Fourier transform infrared (FT-IR) signals obtained from bacterial samples are specific and reproducible, making FT-IR an efficient tool for bacterial typing at a subspecies level. However, the typing accuracy could be affected by many factors, including sample preparation and spectral acquisition. Here, we present a unified protocol for bacterial typing based on FT-IR spectroscopy. We describe sample preparation from bacterial culture and FT-IR spectrum collection. We then detail FT-IR spectrum preprocessing and multivariate analysis of spectral data for bacterial typing.

Profiling and annotation of carbonyl compounds in Baijiu Daqu by chlorine isotope labeling-assisted ultrahigh-performance liquid chromatography-high resolution mass spectrometry.

Carbonyl compounds are among the most important flavor substances that affect the taste of Baijiu. However, high coverage analysis of carbonyl compounds is obstructed due to the poor ionization efficiency of these compounds. Here we report a chlorine isotope labeling-assisted ultrahigh-performance liquid chromatography-high resolution mass spectrometry-based method (CIL-UHPLCHRMS) for profiling and annotation of carbonyl compounds in sauce flavored-Baijiu Daqu. 4-Chloro-2-hydrazinylpyridine was demonstrated to be a good labeling reagent that could achieve highly sensitive profiling and high-coverage screening of carbonyl compounds in the absence of heavy isotope labeling reagents. In the analysis of eight carbonyl standards representing different carbonyl categories, l-(-)-fucose, 2-carboxybenzaldehyde, 2-hydroxyacetophenone and heptan-2-one could be ionized only after labeling and MS signals were significantly increased for other 4 standards with an enhancement factor ranging from 181-fold for 3-methoxysalicylaldehyde to 3141-fold for tridecan-2-one. The annotation was achieved based on multidimensional information including MS1, predicted tR, in silico MS/MS and manually annotated fragments. In total, 487 carbonyl compounds were detected in Baijiu Daqu, among which, 314 (64.5%) of them were positively or putatively identified. The outcome of the linearity (with a linear range of 2, 3 orders of magnitude), precision (less than 10%), and limit of detection (varied from 0.07 to 0.10 nM) indicated that the method was adequate for profiling carbonyl compounds in complex biological samples. The established method was successfully applied to study carbonyl compounds in Baijiu Daqu with different colors and different seasons. Taken collectively, the present work provides an effective, simple and economic strategy for comprehensive analysis of carbonyl compounds in complex matrix samples.

Analysis of environmental driving factors on Core Functional Community during Daqu fermentation.

Sauce-flavor Daqu determines the quality of Baijiu because its core functional community (CFC) can produce abundant enzymes and aroma. However, complex environmental factors make it difficult to accurately control the fermentation quality of Daqu. In this study, we constructed a functional gene database to identify CFC based on multi-omics technology and explore controllable environmental factors of CFC to improve the quality of Daqu. The results showed that the CFC is mainly composed of 7 bacterial and 4 fungal genera, including Kroppenstedtia, Thermoactinomyces, Bacillus, Acinetobacter, Brevibacterium, Saccharopolyspora, Ochrobactrum, Aspergillus, Byssochlamys, Thermoascus, and Thermomyces. Most of them are thermostable microorganisms that can provide the power of fermentation and saccharification (α-amylase, glucoamylase, and protease). In CFC, Acinetobacter and Saccharopolyspora were strongly positively correlated with typical flavor substances, while fungi were negatively correlated, particularly with furans. Therefore, the bacterial genera contributed more to the significant flavors. The CFC was significantly influenced by high temperature and total titrate acid based on RDA. In addition, high-temperature conditions were also strongly positively correlated with flavors that can be quickly produced at high temperatures, such as 2-Furancarboxaldehyde, 2-Furanmethanol, and Tetramethylpyrazine. As a controllable factor, the temperature can be adjusted to improve the quality of Daqu directionally, which will provide theoretical guidance for the production of high-quality Daqu.

Quantitative metaproteomics reveals composition and metabolism characteristics of microbial communities in Chinese liquor fermentation starters.

Introduction: Daqu, the Chinese liquor fermentation starter, contains complex microbial communities that are important for the yield, quality, and unique flavor of produced liquor. However, the composition and metabolism of microbial communities in the different types of high-temperature Daqu (i.e., white, yellow, and black Daqu) have not been well understood. Methods: Herein, we used quantitative metaproteomics based on data-independent acquisition (DIA) mass spectrometry to analyze a total of 90 samples of white, yellow, and black Daqu collected in spring, summer, and autumn, revealing the taxonomic and metabolic profiles of different types of Daqu across seasons. Results: Taxonomic composition differences were explored across types of Daqu and seasons, where the under-fermented white Daqu showed the higher microbial diversity and seasonal stability. It was demonstrated that yellow Daqu had higher abundance of saccharifying enzymes for raw material degradation. In addition, considerable seasonal variation of microbial protein abundance was discovered in the over-fermented black Daqu, suggesting elevated carbohydrate and amino acid metabolism in autumn black Daqu. Discussion: We expect that this study will facilitate the understanding of the key microbes and their metabolism in the traditional fermentation process of Chinese liquor production.

Microbial Community Succession and Its Environment Driving Factors During Initial Fermentation of Maotai-Flavor Baijiu.

The microbial composition and environmental factors can take a great influence on community succession during the solid-state fermentation (SSF) of Maotai-flavor Baijiu. In this paper, high-throughput sequencing was used to reveal the dominant microorganisms and the evolution process of microbial community structure in the initial fermentation of Maotai-flavor Baijiu. The correlation analysis was carried out for the relationship between physicochemical factors and fermented microbes. The results showed that microorganisms were obviously enriched and the diversity of bacteria and fungi showed a downward trend during the heap fermentation process of Maotai-flavor Baijiu. However, the diversity of fungi in the pit fermentation process increased. Generally, Lactobacillus, Pichia, and Saccharomyces were the dominant microorganisms in the initial fermentation of Maotai-flavor Baijiu. According to the redundancy analysis, we found that reducing sugar was the key driving factor for microbial succession in the heap fermentation, while acidity, alcohol, and temperature were the main driving forces in pit fermentation. This study revealed the microbial succession and its related environmental factors in the initial fermentation of Maotai-flavor Baijiu, which will enrich our knowledge of the mechanism of solid-state liquor fermentation.