Collaborative Multiple Players to Address Label Sparsity in Quality Prediction of Batch Processes.

For decades, soft sensors have been extensively renowned for their efficiency in real-time tracking of expensive variables for advanced process control. However, despite the diverse efforts lavished on enhancing their models, the issue of label sparsity when modeling the soft sensors has always posed challenges across various processes. In this paper, a fledgling technique, called co-training, is studied for leveraging only a small ratio of labeled data, to hone and formulate a more advantageous framework in soft sensor modeling. Dissimilar to the conventional routine where only two players are employed, we investigate the efficient number of players in batch processes, making a multiple-player learning scheme to assuage the sparsity issue. Meanwhile, a sliding window spanning across both time and batch direction is used to aggregate the samples for prediction, and account for the unique 2D correlations among the general batch process data. Altogether, the forged framework can outperform the other prevalent methods, especially when the ratio of unlabeled data is climbing up, and two case studies are showcased to demonstrate its effectiveness.

Integrative analysis with microbial modelling and machine learning uncovers potential alleviators for ulcerative colitis.

Ulcerative colitis (UC) is a challenging form of inflammatory bowel disease, and its etiology is intricately linked to disturbances in the gut microbiome. To identify the potential alleviators of UC, we employed an integrative analysis combining microbial community modeling with advanced machine learning techniques. Using metagenomics data sourced from the Integrated Human Microbiome Project, we constructed individualized microbiome community models for each participant. Our analysis highlighted a significant decline in both α and ß-diversity of strain-level microbial populations in UC subjects compared to controls. Distinct differences were also observed in the predicted fecal metabolite profiles and strain-to-metabolite contributions between the two groups. Using tree-based machine learning models, we successfully identified specific microbial strains and their associated metabolites as potential alleviators of UC. Notably, our experimental validation using a dextran sulfate sodium-induced UC mouse model demonstrated that the administration of Parabacteroides merdae ATCC 43,184 and N-acetyl-D-mannosamine provided notable relief from colitis symptoms. In summary, our study underscores the potential of an integrative approach to identify novel therapeutic avenues for UC, paving the way for future targeted interventions.

Mannan-oligosaccharides promote gut microecological recovery after antibiotic disturbance.

Antibiotic treatment often causes collateral damage to the gut microbiota, including changes in its diversity and composition. Dietary fiber helps maintain intestinal health, regulate short-chain fatty acids, and promote the recovery of the intestinal microbiome. However, it is currently unknown which specific plant-based dietary fiber is optimal as a dietary supplement for restoring the intestinal microbiota after antibiotic disturbance. Previously, we proposed predictive recovery-associated bacterial species (p-RABs) and identified the most important interventions. This study aimed to identify an optimal form of dietary fiber to recover the gut microbiome after antibiotic treatment. Therefore, we examined the types of dietary fibers associated with p-RABs through a p-RAB-metabolite bilayer network constructed from prior knowledge; we searched for dietary fiber that could provide nutritional support for Akkermansia muciniphila and Bacteroides uniformis. C57BL/6J mice were fed with 500 mg kg-1 of different types of dietary fibers daily for one week after being treated with ampicillin. The results showed that mannan-oligosaccharides could better promote the diversity of intestinal microbial growth, enhance the recovery of most genera, including Akkermansia and Bacteroides, and inhibit certain pathogenic bacteria, such as Proteus, compared to the other fiber types. Furthermore, mannan-oligosaccharides could regulate the levels of short-chain fatty acids, especially butyric acid. Functional predictions showed that starch metabolism, galactose metabolism, and the metabolism of other carbohydrates played key roles in the early recovery process. In conclusion, mannan-oligosaccharides could enhance the recovery of the intestinal microbiome after antibiotic treatment, offering valuable insights for targeted dietary strategies.

Visualizing the Habenula Using 3T High-Resolution MP2RAGE and QSM: A Preliminary Study.

BACKGROUND AND PURPOSE: The habenula is a key node in the regulation of emotion-related behavior. Accurate visualization of the habenula and its reliable quantitative analysis is vital for the assessment of psychiatric disorders. To obtain high-contrast habenula images and allow them to be compatible with clinical applications, this preliminary study compared 3T MP2RAGE and quantitative susceptibility mapping with MPRAGE by evaluating the habenula segmentation performance. MATERIALS AND METHODS: Ten healthy volunteers were scanned twice with 3T MPRAGE and MP2RAGE and once with quantitative susceptibility mapping. Image quality and visibility of habenula anatomic features were analyzed by 3 radiologists using a 5-point scale. Contrast assessments of the habenula and thalamus were also performed. The reproducibility of the habenula volume from MPRAGE and MP2RAGE was evaluated by manual segmentation and the Multiple Automatically Generated Template brain segmentation algorithm (MAGeTbrain). T1 values and susceptibility were measured in the whole habenula and habenula geometric subregion using MP2RAGE T1-mapping and quantitative susceptibility mapping. RESULTS: The 3T MP2RAGE and quantitative susceptibility mapping demonstrated clear boundaries and anatomic features of the habenula compared with MPRAGE, with a higher SNR and contrast-to-noise ratio (all P < .05). Additionally, 3T MP2RAGE provided reliable habenula manual and MAGeTbrain segmentation volume estimates with greater reproducibility. T1-mapping derived from MP2RAGE was highly reliable, and susceptibility contrast was highly nonuniform within the habenula. CONCLUSIONS: We identified an optimized sequence combination (3T MP2RAGE combined with quantitative susceptibility mapping) that may be useful for enhancing habenula visualization and yielding more reliable quantitative data.

Interspecific differences and mechanisms of Lactobacillus-derived anti-inflammatory exopolysaccharides.

Accumulating evidence has revealed the anti-inflammatory properties of Lactobacillus-derived exopolysaccharides (EPSs). However, interspecific differences among these Lactobacillus-derived anti-inflammatory EPSs have not been investigated. Cell experiments showed that Limosilactobacillus fermentum, Lacticaseibacillus rhamnosus, and Lactiplantibacillus plantarum-derived EPSs exhibited excellent anti-inflammatory efficacy in vitro. Subsequently, we used Lactobacillus-derived EPSs to treat colitis in mice. There was no significant difference in EPS's repair of the intestinal barrier from the five Lactobacillus species. However, Ligilactobacillus salivarius-derived EPSs and L. plantarum-derived EPSs more potently reduced proinflammatory cytokines (TNF-α, IL-1ß, IL-6, TNF-γ, and IL-17), increasing IL-10 concentrations in the colon. Lactobacillus-derived EPS moieties from five species regulate intestinal bacteria at the strain level. Immunofluorescence staining revealed that owing to the different infiltration and polarization effects of Lactobacillus-derived EPSs on macrophages, the in vitro and in vivo anti-inflammatory effects of Lactobacillus-derived EPSs were inconsistent. The structure-activity relationship showed that Lactobacillus-derived EPSs with high fructose content had excellent anti-inflammatory activity in vivo. The results mentioned above revealed that the anti-inflammatory activity of Lactobacillus-derived EPSs had interspecific variability, and the mechanism of anti-inflammatory action in vitro and in vivo was different.

Effects of Varied Sulfamethazine Dosage and Exposure Durations on Offspring Mice.

The development of antibiotics was a turning point in the history of medicine; however, their misuse and overuse have contributed to the current global epidemic of antibiotic resistance. According to epidemiological studies, early antibiotic exposure increases the risk of immunological and metabolic disorders. This study investigated the effects of exposure to different doses of sulfamethazine (SMZ) on offspring mice and compared the effects of exposure to SMZ on offspring mice in prenatal and early postnatal periods and continuous periods. Furthermore, the effects of SMZ exposure on the gut microbiota of offspring mice were analyzed using metagenome. According to the results, continuous exposure to high-dose SMZ caused weight gain in mice. IL-6, IL-17A, and IL-10 levels in the female offspring significantly increased after high-dose SMZ exposure. In addition, there was a significant gender difference in the impact of SMZ exposure on the gut microbiota of offspring: Continuous high-dose SMZ exposure significantly decreased the relative abundance of Ligilactobacillus murinus, Limosilactobacillus reuteri, Lactobacillus johnsonii, and Bifidobacterium pseudolongum (p < 0.05) in female offspring mice; however, these significant changes were not observed in male offspring mice.

High-valence metal sites induced by heterostructure engineering for promoting 5-hydroxymethylfurfural electrooxidation and hydrogen generation.

The electrocatalytic 5-hydroxymethylfurfural (HMF) oxidation reaction coupling with hydrogen evolution reaction (HER) serves as a promising strategy to generate both high-value-added products and clean energy, which is limited by the poor catalytic efficiency of bifunctional electrocatalysts and unclear electrocatalytic mechanism for HMF oxidation reaction. Herein, we fabricate a bifunctional NiSe2-NiMoO4 heterostructure nanowire electrocatalyst for the conversion of HMF to 2,5-furandicarboxylic acid (FDCA) and simultaneous H2 production. As expected, the NiSe2-NiMoO4 exhibits outstanding activity and selectivity toward HMF oxidation reaction. In particular, at a potential of 1.50 V, the yield of FDCA could reach 98 % with a faradaic efficiency of 96.5 %, as well as excellent stability. Density functional theory calculation results demonstrate that the NiSe2-NiMoO4 heterostructure could tune the adsorption energy of HMF, facilitate high-valence active species formation, and enhance electronic conductivity. Furthermore, a two-electrode electrolyzer assembled using NiSe2-NiMoO4 as a bifunctional catalyst requires 1.53 V to acquire a current density of 50 mA cm-2, which is 201 mV lower than that of water electrolysis. This work provides new insights for designing multifunctional catalysts for biomass upgrading coupled with hydrogen evolution.

A gut aging clock using microbiome multi-view profiles is associated with health and frail risk.

Age-related changes in the microbiome have been reported in previous studies; however, direct evidence for their association with frailty is lacking. Here, we introduce biological age based on gut microbiota (gAge), an integrated prediction model that integrates gut microbiota data from different perspectives with potential background factors for aging assessment. Simulation results show that, compared with a single model, the ensemble model can not only significantly improve the prediction accuracy, but also make full use of the data in unpaired samples. From this, we identified markers associated with age development and grouped markers into accelerated aging and mitigated aging according to their effect on the prediction. Importantly, the application of gAge to an elderly cohort with different frailty levels confirmed that gAge and its predictive residuals are closely related to the individual's health status and frailty stage, and age-related markers overlap significantly with disease and frailty characteristics. Furthermore, we applied the gAge prediction model to another independent cohort of the elderly population for aging assessment and found that gAge could effectively represent the aging population. Overall, our study explains the association between the gut microbiota and frailty, providing potential targets for the development of gut microbiota-based targeted intervention strategies for aging.

The therapeutic potential of dietary intervention: based on the mechanism of a tryptophan derivative-indole propionic acid on metabolic disorders.

Tryptophan (TRP) contributes to individual immune homeostasis and good condition via three complex metabolism pathways (5-hydroxytryptamine (5-HT), kynurenine (KP), and gut microbiota pathway). Indole propionic acid (IPA), one of the TRP derivatives of the microbiota pathway, has raised more attention because of its impact on metabolic disorders. Here, we retrospect increasing evidence that TRP metabolites/IPA derived from its proteolysis impact host health and disease. IPA can activate the immune system through aryl hydrocarbon receptor (AHR) and/or Pregnane X receptor (PXR) as a vital mediator among diet-caused host and microbe cross-talk. Different levels of IPA in systemic circulation can predict the risk of NAFLD, T2DM, and CVD. IPA is suggested to alleviate cognitive impairment from oxidative damage, reduce gut inflammation, inhibit lipid accumulation and attenuate the symptoms of NAFLD, putatively enhance the intestinal epithelial barrier, and maintain intestinal homeostasis. Now, we provide a general description of the relationships between IPA and various physiological and pathological processes, which support an opportunity for diet intervention for metabolic diseases.

Recent Advances in Habenula Imaging Technology: A Comprehensive Review.

The habenula (Hb) is involved in many natural human behaviors, and the relevance of its alterations in size and neural activity to several psychiatric disorders and addictive behaviors has been presumed and investigated in recent years using magnetic resonance imaging (MRI). Although the Hb is small, an increasing number of studies have overcome the difficulties in MRI. Conventional structural-based imaging also has great defects in observing the Hb contrast with adjacent structures. In addition, more and more attention should be paid to the Hb's functional, structural, and quantitative imaging studies. Several advanced MRI methods have recently been employed in clinical studies to explore the Hb and its involvement in psychiatric diseases. This review summarizes the anatomy and function of the human Hb; moreover, it focuses on exploring the human Hb with noninvasive MRI approaches, highlighting strategies to overcome the poor contrast with adjacent structures and the need for multiparametric MRI to develop imaging markers for diagnosis and treatment follow-up. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

PCSK9 Inhibitors in Multi-Branch Lesions in Coronary Artery Disease with Substandard Lipid-Lowering Effects.

Objective: This study was carried out to evaluate the clinical efficacy of proprotein convertase chymotrypsin 9 (PCSK9) inhibitors in multi-branch lesions in coronary artery disease with substandard lipid-lowering effects. Methods: This retrospective study collected the clinical data of 100 patients with multiple coronary artery diseases admitted to our hospital between May 2020 and August 2022 for analysis. The eligible patients were assigned to either a PCSK9 inhibitor group or a control group at a ratio of 1:1 by their dosing regimens, with 50 cases in each group. Outcome measures for the clinical efficacy of PCSK9 inhibitors included lipid levels, low-density lipoprotein cholesterol (LDL-C) changes, serum concentrations of coronary artery disease-related inflammatory factors, improvement of angina questionnaire scores, adverse reactions, and major cardiovascular adverse events. Results: PCSK9 inhibitors resulted in significantly lower serum concentrations of total cholesterol (TC), LDL-C, and ApoB and higher high-density lipoprotein cholesterol (HDL-C) levels versus conventional lipid-lowering medication (P < .05). The two arms exhibited similar serum concentrations of triglyceride (TG) and ApoA1 after treatment (P > .05). With LDL-C<1.4 mmol/L as the cut-off for desirable blood lipid levels, 47 (94%) patients reached the standard after in the PCSK9 inhibitors group, while no eligible cases were reported in the control group (P < .05). PCSK9 inhibitors provided a marked reduction in the serum concentrations of high-sensitivity C-reactive protein in the patients. Patients had higher angina stability (AS), angina flare (AF), physical limitation (PL), and treatment satisfaction (TS) scores after PCSK9 inhibitor administration versus after conventional medication (P < .05). PCSK9 inhibitors were associated with a significantly lower incidence of adverse cardiovascular events (10%) versus conventional medication (42%) (P < .05). Conclusion: PCSK9 inhibitors significantly improve the LDL-C concentrations of patients with multiple lesions of coronary artery disease who have failed to meet lipid-lowering targets, this enables physicians to more effectively manage patients' cholesterol levels, consequently reducing their cardiovascular risk. Moreover, these inhibitors have the potential to enhance patients' quality of life by alleviating relieve angina symptoms. These findings offer valuable insights into managing multi-branch coronary artery disease.

Multi-omics analysis reveals genes and metabolites involved in Bifidobacterium pseudocatenulatum biofilm formation.

Bacterial biofilm is an emerging form of life that involves cell populations living embedded in a self-produced matrix of extracellular polymeric substances (EPS). Currently, little is known about the molecular mechanisms of Bifidobacterium biofilm formation. We used the Bifidobacterium biofilm fermentation system to preparation of biofilms on wheat fibers, and multi-omics analysis of both B. pseudocatenulatum biofilms and planktonic cells were performed to identify genes and metabolites involved in biofilm formation. The average diameter of wheat fibers was around 50 µm, while the diameter of particle in wheat fibers culture of B. pseudocatenulatum was over 260 µm at 22 h with 78.96% biofilm formation rate (BR), and the field emission scanning electron microscopy (FESEM) results showed that biofilm cells on the surface of wheat fibers secreted EPS. Transcriptomic analysis indicated that genes associated with stress response (groS, mntH, nth, pdtaR, pstA, pstC, radA, rbpA, whiB, ybjG), quorum sensing (dppC, livM, luxS, sapF), polysaccharide metabolic process (rfbX, galE, zwf, opcA, glgC, glgP, gtfA) may be involved in biofilm formation. In addition, 17 weighted gene co-expression network analysis (WGCNA) modules were identified and two of them positively correlated to BR. Metabolomic analysis indicated that amino acids and amides; organic acids, alcohols and esters; and sugar (trehalose-6-phosphate, uridine diphosphategalactose, uridine diphosphate-N-acetylglucosamine) were main metabolites during biofilm formation. These results indicate that stress response, quorum sensing (QS), and EPS production are essential during B. pseudocatenulatum biofilm formation.

IMOVNN: incomplete multi-omics data integration variational neural networks for gut microbiome disease prediction and biomarker identification.

The gut microbiome has been regarded as one of the fundamental determinants regulating human health, and multi-omics data profiling has been increasingly utilized to bolster the deep understanding of this complex system. However, stemming from cost or other constraints, the integration of multi-omics often suffers from incomplete views, which poses a great challenge for the comprehensive analysis. In this work, a novel deep model named Incomplete Multi-Omics Variational Neural Networks (IMOVNN) is proposed for incomplete data integration, disease prediction application and biomarker identification. Benefiting from the information bottleneck and the marginal-to-joint distribution integration mechanism, the IMOVNN can learn the marginal latent representation of each individual omics and the joint latent representation for better disease prediction. Moreover, owing to the feature-selective layer predicated upon the concrete distribution, the model is interpretable and can identify the most relevant features. Experiments on inflammatory bowel disease multi-omics datasets demonstrate that our method outperforms several state-of-the-art methods for disease prediction. In addition, IMOVNN has identified significant biomarkers from multi-omics data sources.

Clostridium butyricum Strain CCFM1299 Reduces Obesity via Increasing Energy Expenditure and Modulating Host Bile Acid Metabolism.

Clostridium butyricum is a butyrate-producing microorganism which has beneficial effects on various diseases, including obesity. In our previous study, the anti-obesity Clostridium butyricum strain CCFM1299 (C20_1_1) was selected, but its anti-obesity mechanism was not clarified. Herein, CCFM1299 was orally administrated to high-fat-diet-treated C57BL/6J mice for 12 weeks to uncover the way the strain alleviates obesity. The results indicated that CCFM1299 alleviated obesity through increasing the energy expenditure and increasing the expression of genes related to thermogenesis in brown adipose tissue (BAT). Moreover, strain CCFM1299 could also affect the expression of immune-related genes in epididymal white adipose tissue (eWAT). This immunomodulatory effect might be achieved through its influence on the complement system, as the expression of the complement factor D (CFD) gene decreased significantly. From the view of metabolites, CCFM1299 administration increased the levels of ursodeoxycholic acid (UDCA) in feces and taurohyodeoxycholic acid (THDCA) in serum. Together, the anti-obesity potential of CCFM1299 might be attributed to the increase in energy consumption, the regulation of immune-related gene expression in eWAT, and the alteration of bile acid metabolism in the host. These provided new insights into the potential application of anti-obesity microbial preparations and postbiotics.

Weight Loss Promotion in Individuals with Obesity through Gut Microbiota Alterations with a Multiphase Modified Ketogenic Diet.

The occurrence of obesity and related metabolic disorders is rising, necessitating effective long-term weight management strategies. With growing interest in the potential role of gut microbes due to their association with responses to different weight loss diets, understanding the mechanisms underlying the interactions between diet, gut microbiota, and weight loss remains a challenge. This study aimed to investigate the potential impact of a multiphase dietary protocol, incorporating an improved ketogenic diet (MDP-i-KD), on weight loss and the gut microbiota. Using metagenomic sequencing, we comprehensively analyzed the taxonomic and functional composition of the gut microbiota in 13 participants before and after a 12-week MDP-i-KD intervention. The results revealed a significant reduction in BMI (9.2% weight loss) among obese participants following the MDP-i-KD intervention. Machine learning analysis identified seven key microbial species highly correlated with MDP-i-KD, with Parabacteroides distasonis exhibiting the highest response. Additionally, the co-occurrence network of the gut microbiota in post-weight-loss participants demonstrated a healthier state. Notably, metabolic pathways related to nucleotide biosynthesis, aromatic amino acid synthesis, and starch degradation were enriched in pre-intervention participants and positively correlated with BMI. Furthermore, species associated with obesity, such as Blautia obeum and Ruminococcus torques, played pivotal roles in regulating these metabolic activities. In conclusion, the MDP-i-KD intervention may assist in weight management by modulating the composition and metabolic functions of the gut microbiota. Parabacteroides distasonis, Blautia obeum, and Ruminococcus torques could be key targets for gut microbiota-based obesity interventions.

Bifidobacterium longum subsp. infantis as widespread bacteriocin gene clusters carrier stands out among the Bifidobacterium.

Bifidobacterium is the dominant genus, particularly in the intestinal tract niche of healthy breast-fed infants, and many of these strains have been proven to elicit positive effects on infant development. In addition to its effective antimicrobial activity against detrimental microorganisms, it helps to improve the intestinal microbiota balance. The isolation and identification of bacteriocins from Bifidobacterium have been limited since the mid-1980s, leading to an underestimation of its ability for bacteriocin production. Here, we employed a silicon-based search strategy to mine 354 putative bacteriocin gene clusters (BGCs), most of which have never been reported, from the genomes of 759 Bifidobacterium strains distributed across 9 species. Consistent with previous reports, most Bifidobacterium strains did not carry or carry only a single BGC; however, Bifidobacterium longum subsp. infantis, in contrast to other Bifidobacterium species, carried numerous BGCs, including lanthipeptides, lasso peptides, thiopeptides, and class IId bacteriocins. The antimicrobial activity of the crude bacteriocins and transcription analysis confirmed its potential for bacteriocin biosynthesis. Additionally, we investigated the association of bacteriocins with the phylogenetic positions of their homologs from other genera and niches. In conclusion, this study re-examines a few Bifidobacterium species traditionally regarded as a poor source of bacteriocins. These bacteriocin genes impart a competitive advantage to Bifidobacterium in colonizing the infant intestinal tract. IMPORTANCE Development of the human gut microbiota commences from birth, with bifidobacteria being among the first colonizers of the newborn intestinal tract and dominating it for a considerable period. To date, the genetic basis for the successful adaptation of bifidobacteria to this particular niche remains unclear since studies have mainly focused on glycoside hydrolase and adhesion-related genes. Bacteriocins are competitive factors that help producers maintain colonization advantages without destroying the niche balance; however, they have rarely been reported in Bifidobacterium. The advancement in sequencing methods and bacteriocin databases enables the use of a silicon-based search strategy for the comprehensive and rapid re-evaluation of the bacteriocin distribution of Bifidobacterium. Our study revealed that B. infantis carries abundant bacteriocin biosynthetic gene clusters for the first time, presenting new evidence regarding the competitive interactions of Bifidobacterium in the infant intestinal tract.

Uncovering Predictive Factors and Interventions for Restoring Microecological Diversity after Antibiotic Disturbance.

Antibiotic treatment can lead to a loss of diversity of gut microbiota and may adversely affect gut microbiota composition and host health. Previous studies have indicated that the recovery of gut microbes from antibiotic-induced disruption may be guided by specific microbial species. We expect to predict recovery or non-recovery using these crucial species or other indices after antibiotic treatment only when the gut microbiota changes. This study focused on this prediction problem using a novel ensemble learning framework to identify a set of common and reasonably predictive recovery-associated bacterial species (p-RABs), enabling us to predict the host microbiome recovery status under broad-spectrum antibiotic treatment. Our findings also propose other predictive indicators, suggesting that higher taxonomic and functional diversity may correlate with an increased likelihood of successful recovery. Furthermore, to explore the validity of p-RABs, we performed a metabolic support analysis and identified Akkermansia muciniphila and Bacteroides uniformis as potential key supporting species for reconstruction interventions. Experimental results from a C57BL/6J male mouse model demonstrated the effectiveness of p-RABs in facilitating intestinal microbial reconstitution. Thus, we proved the reliability of the new p-RABs and validated a practical intervention scheme for gut microbiota reconstruction under antibiotic disturbance.

Multiomics reveals the mechanism of B. longum in promoting the formation of mixed-species biofilms.

It has been found previously that Bifidobacterium longum, Bacteroides ovatus, Enterococcus faecalis, and Lactobacillus gasseri can form a biofilm better when co-cultured in vitro and B. longum is the core biofilm-formation-promoting strain in this community. B. longum is part of the core microbiota in the gut and is widely recognized as a probiotic. Therefore, it is necessary to explore its role in mixed-species biofilms through transcriptomics and metabolomics. Metabolomics showed that the increase in amino acid and purine content could promote biofilm formation. In transcriptomic analysis, many genes related to carbohydrate metabolism, amino acid metabolism, and environmental tolerance of B. longum were up-regulated. Combined with the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Ontology (GO) analysis, the differentially expressed genes (DEGs) of B. longum in mixed-species biofilms were mainly correlated to "quorum sensing (QS)", "ABC transporters", "biosynthesis of amino acids", "microbial metabolism in different environments", "carbohydrate metabolism" and "two-component system". In addition, the rpl and rps gene families, which function in the metabolism of organic substances and the biosynthesis of amino acids, were the core DEGs according to the analysis of the protein-protein interaction (PPI) network. Finally, by combining metabolomics and quorum sensing mechanisms, it was found that the metabolism of autoinducer peptides (proliylglycine and glycylleucine), N-acyl homoserine lactone (N-(3-oxo hydroxy) homoserine lactone), and AI-2 can promote the formation of biofilms, both mono- and mixed-species biofilms composed of B. longum. Our research enabled us to understand the critical role of B. longum in mixed-species biofilms and the interactions between biofilm metabolism and gut health. In addition, the generated knowledge will be of great significance for us to develop biofilm products with beneficial functions in future.

Lactiplantibacillus pentoses CCFM1227 Produces Desaminotyrosine to Protect against Influenza Virus H1N1 Infection through the Type I Interferon in Mice.

Microbiota-derived desaminotyrosine (DAT) protects the host from influenza by modulating the type I interferon (IFN) response. The aim of this study was to investigate the antivirus effects of a DAT-producing bacteria strain. A comparative genomics analysis and UHPLC Q-Exactive MS were used to search for potential strains and confirm their ability to produce DAT, respectively. The anti-influenza functions of the DAT producer were evaluated using an antibiotic-treated mouse model by orally administering the specific strain before viral infection. The results showed the Lactiplantibacillus pentosus CCFM1227 contained the phy gene and produced DAT by degrading phloretin. In vivo, L. pentosus CCFM1227 re-inoculation increased the DAT level in feces, and protected from influenza through inhibiting viral replication and alleviating lung immunopathology. Furthermore, CCFM1227-derived DAT was positively correlated with the IFN-ß level in the lung. The transcriptome results showed that CCFM1227 activated gene expression in the context of the defense response to the virus, and the response to interferon-beta. Moreover, CCFM1227 treatment upregulated the expression of MHC-I family genes, which regulate the adaptive immune response. In conclusion, L. pentosus CCFM1227 exerted antiviral effects by producing DAT in the gut, and this may provide a potential solution for creating effective antiviral probiotics.