UNASSIGNED: Previous observational studies have suggested an association between gut microbiota and diabetic neuropathy (DN). However, confounding factors and reverse causality make the causal relationship between gut microbiota and DN uncertain. We aimed to investigate the interactive causal relationships between the abundance of gut microbiota and DN.
UNASSIGNED: We conducted a Mendelian randomization (MR) analysis to examine the causal relationship between gut microbiota and DN. Genomic data on gut microbiota at the genus level were obtained from the MiBioGen Consortium, including 18,340 individuals of European descent. Data on diabetic polyneuropathy (DPN) were obtained from the FinnGen Consortium, which included 1,048 cases and 374,434 controls, while data on diabetic autonomic neuropathy (DAN) were also obtained from the FinnGen Consortium, including 111 cases and 374,434 controls. Causal effects were primarily estimated using inverse variance weighted (IVW) analysis, supplemented with four validation methods, and additional sensitivity analyses to assess the pleiotropy, heterogeneity, and robustness of instrumental variables.
UNASSIGNED: The IVW analysis indicated that Prevotella 9 had a protective effect on DPN (OR = 0.715, 95% CI: 0.521-0.982, P = 0.038), and Bacteroides also showed a protective effect (OR = 0.602, 95% CI: 0.364-0.996, P = 0.048). On the other hand, Ruminococcus 2 had a promoting effect on DPN (OR = 1.449, 95% CI: 1.008-2.083, P = 0.045). Blautia (OR = 0.161, 95% CI: 0.035-0.733, P = 0.018), Clostridium innocuum group (OR = 3.033, 95% CI: 1.379-6.672, P = 0.006), and Howardella (OR = 2.595, 95% CI: 1.074-6.269, P = 0.034) were causally associated with DAN in the IVW analysis, with no evidence of heterogeneity or pleiotropy. Sensitivity analyses showed no significant pleiotropy or heterogeneity.
UNASSIGNED: Our study identified a causal relationship between gut microbiota and the increased or decreased risk of diabetic neuropathy. These findings underscore the importance of adopting a comprehensive approach that combines gut microbiota modulation with other therapeutic interventions in the management of diabetic neuropathy.

Although the gut microbiota and kynurenine (KYN) metabolism have significant protective effects against ischaemic stroke (IS), the exact mechanism has yet to be fully elucidated. Combined serum metabolomics and 16S rRNA gene sequencing were used to reveal the differences between the gut microbiota and metabolites in rats treated with or without blueberry extract. Faecal microbiota transplantation (FMT) was employed to validate the protective role of the gut microbiota in IS. Furthermore, the interaction between Prevotella and IS was also confirmed in patients. Rats with IS experienced neurological impairments accompanied by an impaired intestinal barrier and disturbed intestinal flora, which further contributed to heightened inflammatory responses. Furthermore, Prevotella played a critical role in IS pathophysiology, and a positive correlation between Prevotella and KYN was detected. The role of KYN metabolism in IS was further demonstrated by the finding that IDO was significantly upregulated and that the use of the IDO inhibitor, attenuated KYN metabolic pathway activity and ameliorated neurological damage in rats with IS. Prevotella intervention also significantly improved stroke symptoms and decreasing KYN levels in rats with IS. FMT showed that the beneficial effects of blueberry extract on IS involve gut bacteria, especially Prevotella, which were confirmed by microbiological analyses conducted on IS patients. Moreover, blueberry extract led to significant changes in kynurenic acid levels and tryptophan and IDO levels through interactions with Prevotella. Our study demonstrates for the first time that blueberry extract could modulate \"intestinal microecology-KYN metabolism\" to improve IS.

OBJECTIVE: Epigallocatechin-3-gallate (EGCG), a catechin abundant in green tea, exhibits antibacterial activity. In this study, the antimicrobial effects of EGCG on periodontal disease-associated bacteria (Porphyromonas gingivalis, Prevotella intermedia, Prevotella nigrescens, Fusobacterium nucleatum, and Fusobacterium periodontium) were evaluated and compared with its effects on Streptococcus mutans, a caries-associated bacterium.
RESULTS: Treatment with 2 mg/ml EGCG for 4 h killed all periodontal disease-associated bacteria, whereas it only reduced the viable count of S. mutans by about 40 %. Regarding growth, the periodontal disease-associated bacteria were more susceptible to EGCG than S. mutans, based on the growth inhibition ring test. As for metabolism, the 50 % inhibitory concentration (IC50) of EGCG for bacterial metabolic activity was lower for periodontal disease-associated bacteria (0.32-0.65 mg/ml) than for S. mutans (1.14 mg/ml). Furthermore, these IC50 values were negatively correlated with the growth inhibition ring (r = -0.73 to -0.86). EGCG induced bacterial aggregation at the following concentrations: P. gingivalis (>0.125 mg/ml), F. periodonticum (>0.5 mg/ml), F. nucleatum (>1 mg/ml), and P. nigrescens (>2 mg/ml). S. mutans aggregated at an EGCG concentration of > 1 mg/ml.
CONCLUSIONS: EGCG may help to prevent periodontal disease by killing bacteria, inhibiting bacterial growth by suppressing bacterial metabolic activity, and removing bacteria through aggregation.

Gaining a comprehensive understanding of the role played by the oral microbiome in moderate to severe plaque psoriasis and its potential implications for disease management and development holds significant importance. With the objective of exploring correlations between the oral microbiota and severe psoriasis, this study involved 72 severe psoriasis patients and 16 healthy individuals, whose clinical manifestations and living habits were carefully recorded. Cutting-edge techniques such as 16S rRNA gene sequencing and bioinformatics analysis were employed to compare the microbial flora, investigating dynamic changes among severe plaque psoriasis patients, psoriatic arthritis patients and healthy individuals. The findings revealed noteworthy patterns including increased levels of Aggregatibacter in the psoriatic arthritis group, accompanied by a decrease in the level of Prevotella. Moreover, the enrichment o Capnocytandophaga (P = 0.009), Campylobacter (P = 0.0022), and Acetobacter (P = 0.0292) was notably more substantial in the psoriasis group compared to the control group, whereas certain bacterial species such as Bacteroides (P = 0.0049), Muribaculaceae (P = 0.0048) demonstrated decreased enrichment. Additionally, the psoriatic arthritis group exhibited significantly higher levels of Ralstonia, Bifidobacterium and Micromonospora. Based on these findings, it can be inferred that individuals with lower levels of Prevotella and higher levels of Corynebacterium may be more susceptible to psoriasis exacerbation.

BACKGROUND: Obesity is prevalent in type 1 diabetes (T1D) and is problematic with higher risk for diabetes complications. It is unknown to what extent gut microbiome changes are associated with obesity and T1D.
OBJECTIVE: To describe the gut microbiome and microbial metabolite changes associated with obesity in T1D. We hypothesized significant gut microbial and metabolite differences in lean T1D youth (BMI: 5-<85%) vs. those with obesity (BMI: ≥95%).
METHODS: We analyzed stool samples for gut microbial (using metagenomic shotgun sequencing) and short-chain fatty acid (SCFA) differences in lean (n=27) and obese (n=21) T1D youth in a pilot study. The mean±SD age was 15.3±2.2yrs, A1c 7.8±1.3%, diabetes duration 5.1±4.4yrs, 42.0% females, and 94.0% were White.
RESULTS: Bacterial community composition showed between sample diversity differences (β-diversity) by BMI group (p=0.013). There was a higher ratio of Prevotella to Bacteroides in the obese group (p=0.0058). There was a differential distribution of significantly abundant taxa in either the lean or obese groups, including increased relative abundance of Prevotella copri, among other taxa in the obese group. Functional profiling showed an upregulation of branched chain amino acid (BCAA) biosynthesis in the obese group and upregulation of BCAA degradation, tyrosine metabolism and secondary bile acid biosynthesis in the lean group. Stool SCFAs were higher in the obese versus the lean group (p<0.05 for all).
CONCLUSIONS: Our findings identify a gut microbiome and microbial metabolite signature associated with obesity in T1D. These findings could help identify gut microbiome targeted therapies to manage obesity in T1D.

Dysbiosis of the vaginal microbiome poses a serious risk for sexual human immunodeficiency virus type 1 (HIV-1) transmission. Prevotella spp are abundant during vaginal dysbiosis and associated with enhanced HIV-1 susceptibility; however, underlying mechanisms remain unclear. Here, we investigated the direct effect of vaginal bacteria on HIV-1 susceptibility of vaginal CD4+ T cells. Notably, pre-exposure to Prevotella timonensis enhanced HIV-1 uptake by vaginal T cells, leading to increased viral fusion and enhanced virus production. Pre-exposure to antiretroviral inhibitors abolished P timonensis-enhanced infection. Our study shows that the vaginal microbiome directly affects mucosal CD4+ T-cell susceptibility, emphasizing importance of vaginal dysbiosis diagnosis and treatment.

SARS-CoV-2, a severe respiratory disease primarily targeting the lungs, was the leading cause of death worldwide during the pandemic. Understanding the interplay between the oral microbiome and inflammatory cytokines during acute infection is crucial for elucidating host immune responses. This study aimed to explore the relationship between the oral microbiome and cytokines in COVID-19 patients, particularly those with and without sputum production. Saliva and blood samples from 50 COVID-19 patients were subjected to 16S ribosomal RNA gene sequencing for oral microbiome analysis, and 65 saliva and serum cytokines were assessed using Luminex multiplex analysis. The Mann-Whitney test was used to compare cytokine levels between individuals with and without sputum production. Logistic regression machine learning models were employed to evaluate the predictive capability of oral microbiome, salivary, and blood biomarkers for sputum production. Significant differences were observed in the membership (Jaccard dissimilarity: p = 0.016) and abundance (PhILR dissimilarity: p = 0.048; metagenomeSeq) of salivary microbial communities between patients with and without sputum production. Seven bacterial genera, including Prevotella, Streptococcus, Actinomyces, Atopobium, Filifactor, Leptotrichia, and Selenomonas, were more prevalent in patients with sputum production (p<0.05, Fisher\'s exact test). Nine genera, including Prevotella, Megasphaera, Stomatobaculum, Selenomonas, Leptotrichia, Veillonella, Actinomyces, Atopobium, and Corynebacteria, were significantly more abundant in the sputum-producing group, while Lachnoanaerobaculum was more prevalent in the non-sputum-producing group (p<0.05, ANCOM-BC). Positive correlations were found between salivary IFN-gamma and Eotaxin2/CCL24 with sputum production, while negative correlations were noted with serum MCP3/CCL7, MIG/CXCL9, IL1 beta, and SCF (p<0.05, Mann-Whitney test). The machine learning model using only oral bacteria input outperformed the model that included all data: blood and saliva biomarkers, as well as clinical and demographic variables, in predicting sputum production in COVID-19 subjects. The performance metrics were as follows, comparing the model with only bacteria input versus the model with all input variables: precision (95% vs. 75%), recall (100% vs. 50%), F1-score (98% vs. 60%), and accuracy (82% vs. 66%).

BACKGROUND: Recently, there has been an increase in the number of studies focusing on the association between the gut microbiome and obesity or inflammatory diseases, especially in adults. However, there is a lack of studies investigating the association between gut microbiome and gastrointestinal (GI) diseases in adolescents.
METHODS: We obtained 16S rRNA-seq datasets for gut microbiome analysis from 202 adolescents, comprising ulcerative colitis (UC), Crohn\'s disease (CD), obesity (Ob), and healthy controls (HC). We utilized Quantitative Insights Into Microbial Ecology (QIIME) and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) to acquire Operational Taxonomic Units (OTUs). Subsequently, we analyzed Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology (KO) terms and pathway enrichment for the identified OTUs.
RESULTS: In this study, we investigated the difference between the gut microbiomes in adolescents with GI diseases and those in healthy adolescents using 202 samples of 16S rRNA sequencing data. The distribution of the six main gut microbiota (i.e., unclassified Dorea, unclassified Lachnospiraceae, unclassified Ruminococcus, Faecalibacterium prausnitzii, Prevotella copri, unclassified Sutterella) was different based on the status of obesity and inflammatory diseases. Dysbiosis was observed within Lachnospiraceae in adolescents with inflammatory diseases (i.e., UC and CD), and in adolescents with obesity within Prevotella and Sutterella. More specifically, our results showed that the relative abundance of Faecalibacterium prausnitzii and unclassified Lachnospiraceae was more than 10% and 8% higher, respectively, in the UC group compared to the CD, Ob, and HC groups. Additionally, the Ob group had over 20% and over 3% higher levels of Prevotella copri and unclassified Sutterella, respectively, compared to the UC, CD, and HC groups. Also, inspecting associations between the six specific microbiota and KO terms, we found that the six microbiota -relating KO terms were associated with NOD-like receptor signaling. These six taxa differences may affect the immune system and inflammatory response by affecting NOD-like receptor signaling in the host during critical adolescence.
CONCLUSIONS: In this study, we discovered that dysbiosis of the microbial community had varying degrees of influence on the inflammatory and immune response pathways in adolescents with inflammatory diseases and obesity.

UNASSIGNED: Numerous bacteria are involved in the etiology of bacterial vaginosis (BV). Yet, current tests only focus on a select few. We therefore designed a new test targeting 22 BV-relevant species.
UNASSIGNED: Using 946 stored vaginal samples, a new qPCR test that quantitatively identifies 22 bacterial species was designed. The distribution and relative abundance of each species, α- and β-diversities, correlation, and species co-existence were determined per sample. A diagnostic index was modeled from the data, trained, and tested to classify samples into BV-positive, BV-negative, or transitional BV.
UNASSIGNED: The qPCR test identified all 22 targeted species with 95 - 100% sensitivity and specificity within 8 hours (from sample reception). Across most samples, Lactobacillus iners, Lactobacillus crispatus, Lactobacillus jensenii, Gardnerella vaginalis, Fannyhessea (Atopobium) vaginae, Prevotella bivia, and Megasphaera sp. type 1 were relatively abundant. BVAB-1 was more abundant and distributed than BVAB-2 and BVAB-3. No Mycoplasma genitalium was found. The inter-sample similarity was very low, and correlations existed between key species, which were used to model, train, and test a diagnostic index: MDL-BV index. The MDL-BV index, using both species and relative abundance markers, classified samples into three vaginal microbiome states. Testing this index on our samples, 491 were BV-positive, 318 were BV-negative, and 137 were transitional BV. Although important differences in BV status were observed between different age groups, races, and pregnancy status, they were statistically insignificant.
UNASSIGNED: Using a diverse and large number of vaginal samples from different races and age groups, including pregnant women, the new qRT-PCR test and MDL-BV index efficiently diagnosed BV within 8 hours (from sample reception), using 22 BV-associated species.

Microorganisms in the rumen play a crucial role in determining the most efficient utilization rate of nutrients. Among these microorganisms, Prevotella stands out as one of the most representative bacteria within the rumen biological system. Prevotella is a common strict anaerobic bacterium that is found in the gastrointestinal tract of livestock. Prevotella plays a crucial role in breaking down and metabolizing complex nutrients like cellulose and protein during food digestion. Moreover, it is capable of working together with other bacteria in the body\'s digestive system. Several studies have shown a strong correlation between the abundance of Prevotella and livestock growth performance. This paper provides a comprehensive review of the current research on the function, mechanisms, and applications of Prevotella in the gastrointestinal tract. The insights provided in this review could serve as a theoretical basis for accurately classifying Prevotella, further investigating its effects and potential mechanisms on livestock growth performance, and exploring its practical applications.