The persistence of heat-resistant Bacillus subtilis spores in dairy products constitutes a critical constraint on product quality and safety. Currently, thermosonication technology demonstrates considerable potential as a novel non-thermal sterilization method for spore inhibition. However, its precise mechanism of action remains unclear. To address this research gap, this study employed an integrated transcriptomic and proteomic approach to systematically investigate the inhibitory mechanism of thermosonication against Bacillus subtilis SN-6. Transcriptomic analysis revealed significant downregulation of multiple spore coat-associated proteins following thermosonication treatment, including six YjcZ family sporulation proteins, YqfC, and SpoVM. Proteomics results revealed that the expression of 13 α/β-type small acid-soluble spore proteins (SASPs), the GerD germination receptor, the SleB enzyme, and the activator protein (RBAM_001820) in the KinB signaling pathway was significantly downregulated. Integrated multi-omics analysis demonstrated that thermosonication exerted multi-level inhibitory effects through regulation of spore-related genes, impacting spore coat formation, spore protein composition, germination capacity, and signal transduction. Furthermore, it also exerts an indirect inhibitory effect on spore by suppressing key metabolic pathways, including uridine nucleotide synthesis, arginine and proline metabolism, and TCA cycle. Finally, RT-qPCR was used to validate the two key genes identified through a multi-omics approach. This study systematically elucidates the dual inhibitory mechanisms of thermosonication against Bacillus subtilis spores through integrated transcriptomic-proteomic analysis, identifying critical genes at the regulatory level and clarifying indirect suppression through metabolic network disruption. These findings provide a theoretical foundation for developing novel control strategies against heat-resistant spores and support the future application of thermosonication technology in the dairy industry.

This study investigated how varying concentrations of exopolysaccharide (EPS) derived from Bacillus velezensis SN-1 (B. velezensis SN-1) affect the characteristics of soy protein isolate (SPI) gels. EPS was extracted and purified, and EPS-SPI composite gels containing different EPS concentrations (0%, 0.5%, 1.0%, 1.5%, and 2.0%, w/v) were prepared. The water-holding capacity, thermal stability, rheological behavior, textural properties, microstructure, and intermolecular forces of the gels were systematically evaluated. The results demonstrated that EPS significantly enhanced moisture retention in composite gels (from 13.25% to 82.41%), improved thermal stability, and increased both storage (G') and loss (G") moduli in a concentration-dependent manner. Thus, EPS strengthened the solid-like behavior and pseudo-plastic fluid characteristics of SPI gels. Microstructural analysis revealed that EPS promoted the formation of a denser and more uniform gel network structure, reduced pore size within the gel, and increased fractal dimensions, contributing to structural reinforcement. Further analysis of molecular interactions demonstrated that gel stability was primarily maintained by hydrophobic interactions, hydrogen bonding, and disulfide bonds, with EPS acting as a cross-linking agent to enhance protein-polysaccharide interactions. Overall, this study provides a theoretical basis for the application of EPS-SPI composite gels in functional food systems, demonstrating that EPS can serve as an effective natural modifier for improving the comprehensive performance of plant protein-based gels.

Advances inst traditional protease hurdles, a new frontier in protease engineering, include the high-efficiency design of tailored variants. A central challenge in modern enzyme engineering is designing highly efficient proteases tailored to specific industrial applications. Artificial intelligence (AI) is now providing powerful solutions to these problems. By integrating established strategies, such as directed evolution and rational design, the capacity of AI to analyze enzyme structures and predict mutational outcomes has substantially enhanced the stability and adaptability of proteases. This synergy extends beyond mere optimization to enable the de novo design of novel proteases. This review provides an overview of the importance of this capability in the food industry as AI-driven design paves the way for safer and more sustainable production methods to meet the demands of precision food production. These innovations collectively represent an important advance toward enhancing the performance and enabling the sustainable production of industrial proteases. The next frontier may involve the deep integration of AI with multi-omics data, a necessary step to expand protease applications and improve the nutritional quality of biotechnology food products. The integration of multi-omics with AI-guided de novo design has expanded protease applications in food biotechnology, addressing the evolving demands of industrial processes while enhancing food quality and nutritional value.

Fermentation offers a promising route to enhance the bioactivity of medicinal plants, yet traditional processes often rely on complex, undefined microbiota that limit reproducibility and yield. Here, using a microbiome-guided approach, we develop a defined fermentation system for Platycodon grandiflorus (PG) aimed at the targeted enrichment of its key bioactive saponins, particularly platycodin D (PD). Metagenomic analysis of naturally fermented PG pickle revealed a Firmicutes-dominated community (>65%) with Weissella and Enterococcus as core genera. Targeting beta D glucosidase-a key enzyme for platycoside activation-we isolated 141 microbial strains and identified Leuconostoc mesenteroides ZS W3 4-4 as the top performer in monobacterial fermentation. This defined starter initially increased total saponins content to 57.76 +/- 3.52 mg/g in static fermentation, a 41.3% gain over natural fermentation, and elevated PD by 26.25%. We further integrated ultrasound assistance to optimize the fermentation process parameters, which ultimately raised total saponins content to a maximum of 60.4 +/- 1.1mg/g-a 4.92% improvement over the static pure-culture fermentation and a 47.9% increase compared to natural fermentation. This progression demonstrates a stepwise enhancement from strain screening to process optimization. The strain maintained stable productivity over five passages (P > 0.05), demonstrating robust process controllability. Our study elucidates the role of L. mesenteroides in platycoside transformation and establishes a scalable, microbiome-informed strategy for fermenting PG. This work provides a defined microbial starter and a tunable fermentation platform to support the standardized, high-value production of traditional fermented medicinal foods.

As consumers increasingly pursue foods with superior quality and enriched flavor, fermented products have attracted considerable attention due to their unique sensory properties and nutritional advantages. Aroma-producing yeasts, as pivotal microbial catalysts in fermentation processes, are widely utilized in the production of a broad range of fermented foods, including alcoholic beverages, fermented dough-based products, and fermented soybean products. This review synthesizes recent research progress on aroma-producing yeasts in fermented foods, beginning with a systematic overview of their taxonomic classification and key biological characteristics. The primary aroma-active metabolites synthesized by these yeasts are esters and alcohols, which play a decisive role in determining the flavor profiles of fermented food products. Next, the mechanisms underlying aroma biosynthesis in these yeasts are elaborated. By regulating metabolic pathways, these yeasts synthesize a diverse array of aromatic metabolites, which in turn impart unique sensory attributes to fermented foods. In-depth exploration of these mechanisms not only facilitates the clarification of the functional roles of aroma-producing yeasts during fermentation but also establishes a solid theoretical foundation for further optimizing the flavor quality of fermented products. Lastly, the current application status of aroma-producing yeasts in fermented food manufacturing is summarized. This review offers valuable insights and guidance for the innovative development of the fermented food industry, while concurrently promoting in-depth research and expanded industrial application of aroma-producing yeasts in the field of food science and technology.

Alcoholic liver disease represents a considerable public health challenge globally. Its development is driven by multiple mechanisms, including oxidative stress, inflammatory responses, and dysbiosis of intestinal microbiota. Recent studies have indicated that functional foods may effectively mitigate alcoholic liver injury, owing to their natural active constituents and favorable safety profiles. This study aimed to evaluate the protective effects of Lactiplantibacillus plantarum WW-fermented Pueraria lobata (FLP) against alcoholic liver injury. Single-factor experiments and response surface methodology were employed to optimize the fermentation conditions of strain WW for processing Pueraria lobata, determining the optimal process parameters. Furthermore, fermentation significantly increased the flavonoid content of FLP, and its antioxidant capacity was also significantly enhanced accordingly. Molecular docking analysis further revealed that puerarin, the main active component, binds stably to the Keap1 protein. Animal studies demonstrated that FLP intervention markedly alleviates alcohol-induced liver damage, restores the liver's capacity for alcohol metabolism, diminishes lipid accumulation, and attenuates oxidative stress within the liver. Additionally, FLP upregulates the expression of ZO-1, MUC2, and LGR5 in the colon, thereby enhancing intestinal barrier function and repair capacity, which subsequently reduces serum lipopolysaccharide levels and inflammatory factors. FLP effectively modulates intestinal microbiota composition and increases beneficial bacteria abundance, leading to restored intestinal levels of SCFAs and upregulation of Gpr43 gene expression. This short-chain fatty acids (SCFAs)-GPR43 signaling consequently activates the hepatic AMPK/mTOR pathway, thereby inducing protective autophagy. This study confirms that probiotic-fermented Pueraria lobata overcomes the limitations of single interventions, offering a novel synergistic strategy for treating alcoholic liver disease.

Background Research on biomimetic taste sensors is shifting from traditional chemical analysis tools toward simulators of human perception. Although conventional instrumental detection can distinguish between different taste compounds, its static detection mode lacks a direct connection to human taste perception, making it difficult to replicate the actual taste perception process. Scope and Methods By summarizing the technological evolution of biomimetic taste sensors and reviewing the limitations of existing sensors, this paper proposes a forward-looking conceptual framework. Future research could involve fixing the five taste receptors in hydrogels according to their sensitivity zones and utilizing deep learning to establish a transmembrane mapping model linking sensor signals to neural activity in the human brain. This model would be used to validate the reliability of sensor output signals and to develop models with adaptive adjustment capabilities. Key Findings and Conclusions The innovative biomimetic strategy proposed in this review aims to construct biomimetic taste sensors that more closely align with human taste perception. It advances the transformation of biomimetic taste sensors from simple chemical analysis instruments to platforms that more closely approximate human taste perception, providing a direction for food flavor research, taste interaction, and the development of novel sensory evaluation systems.

Sheep whey protein, a valuable resource for bioactive peptide production, is prone to contamination or often discarded, generating resource waste. This study explored novel milk-derived antimicrobial peptides (AMPs) for sheep milk preservation by evaluating the antimicrobial effects of whey protein hydrolyzed by four proteases. It utilized single-factor experiments and response surface methodology, combined with computer simulations and wet-lab validation. The results revealed that the hydrolysate obtained from neutral protease exhibited the strongest antimicrobial activity. Subsequently, 394 peptide sequences were identified from the 1-3 kDa fraction of the neutral protease hydrolysate via ultrafiltration centrifugation and Liquid Chromatography-Tandem Mass Spectrometry. Through various bioinformatics analyses, machine learning, and AlphaFold3, three candidate peptides-LKAWSVARLSQKFPKA, TLSQLTKLGKPFK, and KKQTALVELLKHKPK-were selected for further evaluation. 200 ns molecular dynamics simulations and gmx_mmpbsa calculations revealed LKAWSVARLSQKFPKA exhibited superior membrane-binding ability and stable alpha-helix structure in the environments of Staphylococcus aureus and Escherichia coli than the other two peptides. The wet-lab experiments showed that it also disrupted bacterial membranes and caused intracellular leakage, demonstrating excellent antimicrobial activity and stability against Staphylococcus aureus and Escherichia coli, along with low hemolytic toxicity. Additionally, LKAWSVARLSQKFPKA at minimum inhibitory concentrations of 32 mu g/mL and 128 mu g/mL respectively effectively inhibited the growth of Staphylococcus aureus and Escherichia coli in sheep milk. Overall, these findings provided a theoretical basis for the application of sheep whey protein and the development of novel milk-derived AMPs.

In this paper, 21 strains of Bifidobacteria were isolated and identified from healthy breast milk samples, and the strain with the best activity was selected by spleen lymphocyte proliferation assay, drug sensitivity, haemolysis, bacteriostatic activity, and adhesion capacity evaluation. After identification by 16S rRNA, the lyophilisation technique was optimised and lyophilised microcapsules were prepared. The results showed that the bacterium was Bifidobacterium animalis subsp. lactis, named BA-9. B. lactis BA-9 was safe, with a hydrophobicity of 36.24%, a self-agglutination rate of 77.4%, and could significantly reduce NO activity in RAW264.7 cells, with in vitro Anti-inflammatory potential. Sodium alginate and carrageenan were prepared as a 1:1 composite wall with the addition of a composite lyoprotectant (11.25% skimmed milk powder, 4.93% xylooligosaccharides and 2.74% glycerol). The activity of B. lactis BA-9 microcapsules with the addition of lyophilisation protectant after lyophilisation decreased by only 1.3 lg CFU/g after simulated gastrointestinal fluid digestion. The survival rate of B. lactis BA-9 microcapsules could reach up to 90.03% for 28 days of storage at 4 ℃, which effectively enhanced the stability of storage. This study provides a research basis for the screening of Bifidobacterium bifidum with immuno-anti-inflammatory regulatory activities and the development and application of its lyophilised carrier.

Chicken, a perishable meat, is highly susceptible to bacterial contamination during distribution. Reuterin, a broad-spectrum antimicrobial metabolite produced by Lactobacillus reuteri, holds promise as an antimicrobial agent in active food packaging. In this study, a high reuterin-producing Lactobacillus reuteri strain (LR17), was isolated from the feces of breastfed infants. The key gene cluster responsible for reuterin biosynthesis was identified through whole-genome sequencing. The culture conditions were optimized using response surface methodology, achieving a reuterin yield of 204.54 mM, a 35.5% increase compared to pre-optimization levels. Confocal laser scanning microscopy revealed reuterin exerts antimicrobial effects by disrupting bacterial cell membranes. Based on this, chitosan-gelatin (CS-Gel) composite films incorporating varying concentrations of reuterin (0%, 1%, 2%, and 4%) were prepared. The microstructure and mechanical properties of these films were characterized. CS-Gel films containing 2% reuterin (CS-Gel-2 R) exhibited the optimal performance, with a tensile strength of 21.11 MPa (54.3% increase) and elongation at break of 48.87% (21.2% increase). Additionally, CS-Gel-2 R inhibited microbial growth in chicken breast during cold storage, improving antimicrobial activity by 16.23% and controlling physicochemical indicators, extending shelf life. Sensory evaluation confirmed that the CS-Gel-2 R group showed better storage quality than the control and polyethylene film groups, with a delay of at least 2 days in spoilage. In conclusion, reuterin-loaded CS-Gel composite films offer a promising natural solution for cold storage preservation of chicken breast, with potential applications in active food packaging.

Fermented dairy products are significant in the market due to their high nutritional value and unique flavor. However, they have more opportunities for improvement to meet the urgent demand for functional dairy products. As a novel prebiotic, sea buckthorn is widely used as a beneficial ingredient. In this review, we not only discuss its positive effects on the gut microbiota but also clarify its antioxidant and anti-inflammatory properties. Significantly, the unique benefits of sea buckthorn in enhancing the nutritional value of fermented dairy products, improving their physical properties, and enhancing the vitality of probiotics are also demonstrated. Furthermore, we point out the current limitations of sea buckthorn and recommend further research into sea buckthorn bioactive components to stimulate the production of functional dairy products.

To address the issues of poor stability and degradation of antimicrobial peptides in food preservation and pharmaceutical applications, liposome encapsulation technology was employed to enhance the stability and bioavailability of antimicrobial peptide W1. The antimicrobial peptide W1 was extracted and purified from Bacillus subtilis SNBS-3 using ammonium sulfate precipitation, Sephadex-G25 gel chromatography, and high-performance liquid chromatography (HPLC). Its molecular sequence was identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Subsequently, W1-loaded liposomes were prepared using the film dispersion method, and optimal preparation conditions were determined through single-factor experiments and response surface methodology. The physicochemical properties of the liposomes were evaluated through particle size, Zeta potential, encapsulation efficiency, and microscopic structural analysis. The stability and antibacterial activity of the liposomes were tested under different temperature, pH, and enzyme treatment conditions. Additionally, cell experiments assessed the cytotoxicity of W1 liposomes on human liver cells (LO2). The results indicated that a highly active fraction was obtained by Sephadex-G25 purification, further purified by HPLC to obtain the core antibacterial peak, and the antimicrobial peptide W1 sequence was identified as IGLFGGAGVGK by LC-MS/MS. The optimal preparation conditions were determined to be a mass ratio of soybean phosphatidylethanolamine (SPE) to β-sitosterol of 5.94:1, a mass ratio of SPE to W1 of 5.18:1, and an ultrasonication time of 6.75 minutes. Under these conditions, W1-loaded liposomes were obtained with a particle size of 105.88±6.35 nm and an encapsulation efficiency of 68.2%±1.5%. Good physicochemical stability was exhibited by the resulting liposomes. Antibacterial tests revealed that the minimum inhibitory concentration (MIC) of W1 liposomes against Staphylococcus aureus was 32 mg/mL. Cytotoxicity assays demonstrated that W1 liposomes maintained LO2 cell viability above 90% at concentrations below 512 mg/mL (P>0.05), indicating favorable biocompatibility. These findings suggest that liposomal encapsulation significantly enhances the stability and antimicrobial efficacy of W1, providing a promising strategy for its application in the food and pharmaceutical industries.

Polysaccharides are recognized as the primary functional components of Angelica sinensis. While a significant correlation between structural characteristics and biological activities of polysaccharides is established, this relationship for A. sinensis polysaccharides remains largely elucidated. In this study, we isolated a hydrosoluble low-molecular-weight polysaccharide from A. sinensis, designated as ASP-4. We subsequently characterized its structure and determined its biological activities. Structural analysis revealed that ASP-4 possessed a molecular weight of 23.18 kDa and was rich in uronic acids, with glucose and mannose as its principal constituent monosaccharides. Scanning electron microscope (SEM) imaging demonstrated that ASP-4 presented as amorphous aggregates with irregular circular lamellae and discernible pores. Further detailed structural elucidation indicated that the backbone of ASP-4 primarily comprised →4)-α-d-Glcp-(1→ and α-d-Glcp-(1→ units, with side chains predominantly composed of α-d-Manp-(1→ units. In terms of biological activities, ASP-4 was found to increase SOD, CAT and GPx activities, decrease MDA content, ameliorate nuclear damage and apoptosis, and suppress caspase-9 and caspase-3 activities in HepG2 cells. Furthermore, ASP-4 significantly inhibited the secretion of tumor necrosis factor-α (TNF-α) and stimulated the secretion of interleukin-10 (IL-10) in RAW 264.7 cells (p < 0.05). Immunoblotting analysis indicated that ASP-4 dose-dependently inhibited the expression of inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2) signaling pathways at the cellular level. It also attenuated the phosphorylation of p65 and NF-κB inhibitor-α (IκB-α), thereby improving acute inflammatory infiltration. This study supported a structure-activity hypothesis for A. sinensis polysaccharide. Our findings open a new avenue for the utilization of medicinal and edible plant and provide a potential bioactivity exploitation for its polysaccharide.

Soybean paste has been a prominent condiment in East Asia for millennia. Nonetheless, the current methodologies for comprehensively assessing the quality of commercially available soybean paste through sensory evaluation or traditional instruments present significant challenges. In this study, contemporary detection techniques and machine learning methodologies were employed to quantitatively characterize and evaluate the overall quality of soybean paste. Sensory evaluations were conducted on 33 varieties of commercial soybean paste using three types of sensors: a colorimeter, an electronic nose (E-nose), and an electronic tongue (E-tongue) for detection purposes. Subsequently, machine learning models, including support vector regression (SVR), random forest, extreme gradient boosting, Bayesian ridge regression, ridge regression, k-nearest neighbors, and artificial neural network, were developed based on the sensory evaluation data to characterize and assess the overall quality of the soybean paste. The findings from both sensory evaluations and sensor detection indicated notable differences between the various soybean pastes. Soybean pastes can be distinguished using three sensors. The quantitative characterization model informed by the sensor data revealed that the SVR model exhibited the highest coefficient of determination (R2) of 0.999 8 for the training set and 0.997 0 for the prediction set, which was close to the ideal value of 1. Additionally, the root mean square error for the prediction set was the lowest at 0.535 9. These results suggest that SVR demonstrates superior performance in cross-validation and testing, aligning closely with human sensory perceptions, thereby establishing it as the most effective predictive model. This study underscores the potential of integrating sensor data with modern machine learning techniques to supplement traditional sensory evaluations for comprehensive characterization and assessment of soybean paste quality. The outcomes of this study offer significant insights and guidance for the advancement of the soybean paste industry and the enhancement of soybean paste quality.

Bacillus subtilis is known for its high protease production, but its ability to form emulsion gels remains underexplored. In this study, a high-protease-yielding strain, B. subtilis SNBS-3, was screened and used to ferment soy protein isolate (SPI)-based emulsion gels. The gel properties and their efficacy as fat replacers in beef meatballs were evaluated. The results demonstrated that At 12 h of fermentation, the emulsion gel achieved maximum water holding capacity (87.6%) and turbidity, with minimum free sulfhydryl content (2.15 mu mol/g). Hydrophobic interactions and hydrogen bonds dominated the intermolecular forces. The gel exhibited shear-thinning behavior and frequency-dependent solid-like characteristics (G'>G''). FT-IR and CD analyses revealed a transition from alpha-helices to beta-sheets, with beta-sheet content increasing by 4.8% and alpha-helix decreasing by 2.7%. Fat replacement with varying gel concentrations indicated that the addition of 15% emulsion gel yielded the best texture (chewiness 512 g), significantly reduced cooking loss (12.4%), and achieved the highest sensory score (28.7). These findings provide a novel approach for the industrial production of low-fat foods without compromising sensory quality.

The color of soybean paste is a crucial sensory attribute for evaluating its quality, with light-colored and color-stable products being more favored in the market. The microbial community plays a significant role in determining color variations in soybean paste; however, the key strains and underlying mechanisms remain unclear. In this study, two lactic acid bacteria strains were isolated from light-colored soybean paste, and their combined application significantly improved the color of fermented soybean paste. Mechanistic investigations revealed that on the one hand, the lactic acid bacteria consumed reducing sugars, thereby decreasing the substrates available for Maillard and caramelization reactions and ultimately inhibiting non-enzymatic browning. On the other hand, the lactic acid bacteria decomposed proteins to produce antioxidant peptides capable of chelating metal ions and scavenging free radicals, thereby suppressing enzymatic browning. This dual-pathway mechanism elucidates how lactic acid bacteria regulate the color of soybean paste and provides theoretical support for the development of anti-browning fermentation agents and targeted color control strategies.

Food spoilage poses a significant challenge to the global food industry, as traditional chemical preservatives carry health risks. In contrast, bacteriocins produced by lactic acid bacteria (LAB) represent a natural, efficient, and non-toxic antimicrobial substance, offering potential as alternatives to chemical preservatives. The traditional methods for discovering bacteriocins rely on pure culture screening and low-throughput sequencing, which encounter bottlenecks such as insufficient coverage of uncultured strains, low screening efficiency, and significant errors in activity prediction. Additionally, natural bacteriocins generally face issues of low yield and poor stability, which limit their industrial application. In recent years, artificial intelligence (AI) technologies, including machine learning (ML) and deep learning (DL), have significantly enhanced the efficiency and accuracy of discovering LAB bacteriocins through precise predictions, intelligent screening, and rational design of microbiome data. This article presents various algorithm models (such as SVM, CNN, Transformer, etc.) and tool applications (such as BAGEL4, BPAGS), systematically reviewing the latest advancements of AI in strain identification and screening, bacteriocin selection, and molecular design of bacteriocins. We discuss the critical role of AI in optimizing fermentation media production, simulating purification processes, and modifying high-yield strains, thereby facilitating the transition of bacteriocins from laboratory research to industrial applications. Moreover, this review highlights current challenges, including data scarcity and model interpretability. Looking ahead, the integration of multi-omics data and generative AI technologies holds promise for the intelligent design and efficient development of bacteriocins, thereby facilitating their widespread application in food preservation.

Bifidobacterium adolescentis (B. adolescentis), a dominant probiotic in the gut of infants and healthy adults, exerts protective effects on immune development and disease prevention. However, the intervention capability of B. adolescentis against different pathogenic bacteria remains unclear. In this study, we verified that B. adolescentis FS2-3 showed inhibitory effects against five common pathogenic bacteria, including Shigella dysenteriae CMCC 51,252, Klebsiella pneumoniae NCTC 13,440, Pseudomonas aeruginosa CMCC 10,104, Salmonella enteritidis CMCC 50,746, and Campylobacter jejuni CICC 22,936. To improve its intestinal colonization efficiency, we constructed double-layered multinucleated microcapsules (probiotic microcapsules) of B. adolescentis FS2-3 and evaluated their effects on bacterial enteritis induced by five representative foodborne pathogens. The in vitro experiments showed that the survival rate of B. adolescentis FS2-3 in the microcapsules was increased by 5.76 times compared with the unencapsulated strain. Additionally, the probiotic microcapsules significantly reduced intestinal tissue damage and inflammation in all enteritis mice, especially in Salmonella-infected mice. Specifically, the probiotic microcapsules reversed the abnormal bacterial composition by promoting the colonization of beneficial bacteria Bifidobacterium, Alloprevotella, and Lachnospiraceae. Furthermore, the probiotic microcapsules inhibited the overexpression of TLR-4 and reduced the expression of inflammatory mediators, including IL-1β, NF-κB, and TNF-α. These findings provide new insights into the application of probiotic microcapsules in the treatment of enteritis. The microcapsule increased the survival rate of internal B. adolescentis FS2-3 by 5.76 times. B. adolescentis FS2-3 microcapsules alleviated enteritis, particularly Salmonella-infected enteritis. B. adolescentis FS2-3 microcapsules suppressed TLR-4 overexpression and alleviated intestinal inflammatory conditions.

The distinctive flavor profile of traditional sour beer is primarily driven by lactic acid bacteria (LAB). However, the precise flavor characteristics of sour beer produced by LAB bioacidification remain poorly understood. To address this gap in the literature, six ethanol- and hop-resistant LAB strains were systematically isolated and screened for their acidification capabilities during beer production. Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME/GC-MS), complemented by multivariate statistical analyses, was used to characterize the flavor compounds of LAB-bioacidified sour beer, sour beer acidified by direct lactic acid addition, and commercially available sour beer. The results revealed that LAB-bioacidified beer exhibited a richer diversity and abundance of flavor compounds than the other groups, notably containing abundant esters that contributed to its distinctive fruity aroma. Among the isolated strains, Lactiplantibacillus plantarum (L. plantarum) A1 produced the highest total concentration of flavor compounds. Integrated orthogonal partial least squares-discriminant analysis (OPLS-DA) and random forest (RF) analyses identified phenethyl alcohol as a critical flavor marker that differentiates beer types and is particularly abundant in beers bioacidified with L. plantarum A1. Kinetic analysis revealed that efficient phenylalanine uptake drove amplification of the Ehrlich pathway, leading to enhanced phenethyl alcohol formation in strain A1. The findings of this study offer theoretical insights into the industrial production of sour beer and underscore the pivotal role of LAB strains in flavor formation.