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The American Journal of Clinical... Dec 2022Many studies have investigated the effects of soy isoflavones on weight control, but few have focused on the role of equol, a gut-derived metabolite of daidzein with... (Clinical Trial)
Clinical Trial
BACKGROUND
Many studies have investigated the effects of soy isoflavones on weight control, but few have focused on the role of equol, a gut-derived metabolite of daidzein with greater bioavailability than other soy isoflavones.
OBJECTIVES
This study examined the association of equol production with obesity and explored the mediating roles of equol-related gut microbiota and microbial carnitine metabolites.
METHODS
This 6.6-y prospective study included 2958 Chinese adults (2011 females and 947 males) aged 60.6 ± 6.0 y (mean ± SD) at baseline. Urinary equol and isoflavones were measured using HPLC-tandem MS. BMI, percentage fat mass (%FM), and serum triglycerides (TGs) were assessed every 3 y. Metagenomics sequencing and assessment of carnitine metabolites in feces were performed in a subsample of 897 participants.
RESULTS
Urinary equol, but not daidzein and genistein, was independently and inversely associated with the obesity-related indicators of BMI, %FM, and a biomarker (TGs). Equol producers (EPs) had lower odds of adiposity conditions and a reduced risk of 6.6-y obesity progression than non-EPs among total participants. Gut microbial analyses indicated that EPs had higher microbiome species richness (P = 3.42 × 10-5) and significantly different β-diversity of gut microbiota compared with the non-EP group (P = 0.001), with 20 of 162 species differing significantly. EPs (compared with non-EPs) had higher abundances of Alistipes senegalensis and Coprococcus catus but lower abundances of Ruminococcus gnavus (false discovery rate <0.05). Among the 7 determined fecal acylcarnitine metabolites, palmitoylcarnitine, oleylcarnitine 18:1, and stearylcarnitine were inversely associated with EPs but positively correlated with obesity conditions and progression. Path analyses indicated that the beneficial association between equol and obesity might be mediated by gut microbiota and decreased production of 3 acylcarnitines in feces.
CONCLUSIONS
This study suggests a beneficial association between equol and obesity, mediated by the gut microbiome and acylcarnitines, in adults.This trial was registered at clinicaltrials.gov as NCT03179657.
Topics: Adult; Female; Humans; Male; Adiposity; Carnitine; Equol; Gastrointestinal Microbiome; Isoflavones; Obesity; Prospective Studies; Middle Aged
PubMed: 36095141
DOI: 10.1093/ajcn/nqac252 -
Frontiers in Immunology 2023Adenoid hypertrophy (AH) is a common upper respiratory disorder in children. Disturbances of gut microbiota have been implicated in AH. However, the interplay of...
INTRODUCTION
Adenoid hypertrophy (AH) is a common upper respiratory disorder in children. Disturbances of gut microbiota have been implicated in AH. However, the interplay of alteration of gut microbiome and enlarged adenoids remains elusive.
METHODS
119 AH children and 100 healthy controls were recruited, and microbiome profiling of fecal samples in participants was performed using 16S rRNA gene sequencing. Fecal microbiome transplantation (FMT) was conducted to verify the effects of gut microbiota on immune response in mice.
RESULTS
In AH individuals, only a slight decrease of diversity in bacterial community was found, while significant changes of microbial composition were observed between these two groups. Compared with HCs, decreased abundances of , and genera and increased abundances of , , genera were revealed in AH patients. The abundance of remained stable with age in AH children. Notably, a microbial marker panel of 8 OTUs were identified, which discriminated AH from HC individuals with an area under the curve (AUC) of 0.9851 in the discovery set, and verified in the geographically different validation set, achieving an AUC of 0.9782. Furthermore, transfer of mice with fecal microbiota from AH patients dramatically reduced the proportion of Treg subsets within peripheral blood and nasal-associated lymphoid tissue (NALT) and promoted the expansion of Th2 cells in NALT.
CONCLUSION
These findings highlight the effect of the altered gut microbiota in the AH pathogenesis.
Topics: Child; Humans; Animals; Mice; Gastrointestinal Microbiome; Adenoids; RNA, Ribosomal, 16S; Microbiota; Hypertrophy; Bacteroides
PubMed: 38090578
DOI: 10.3389/fimmu.2023.1277351 -
BMC Cancer Jul 2023Colorectal cancer (CRC) is a heterogeneous disease, with subtypes that have different clinical behaviours and subsequent prognoses. There is a growing body of evidence...
BACKGROUND
Colorectal cancer (CRC) is a heterogeneous disease, with subtypes that have different clinical behaviours and subsequent prognoses. There is a growing body of evidence suggesting that right-sided colorectal cancer (RCC) and left-sided colorectal cancer (LCC) also differ in treatment success and patient outcomes. Biomarkers that differentiate between RCC and LCC are not well-established. Here, we apply random forest (RF) machine learning methods to identify genomic or microbial biomarkers that differentiate RCC and LCC.
METHODS
RNA-seq expression data for 58,677 coding and non-coding human genes and count data for 28,557 human unmapped reads were obtained from 308 patient CRC tumour samples. We created three RF models for datasets of human genes-only, microbes-only, and genes-and-microbes combined. We used a permutation test to identify features of significant importance. Finally, we used differential expression (DE) and paired Wilcoxon-rank sum tests to associate features with a particular side.
RESULTS
RF model accuracy scores were 90%, 70%, and 87% with area under curve (AUC) of 0.9, 0.76, and 0.89 for the human genomic, microbial, and combined feature sets, respectively. 15 features were identified as significant in the model of genes-only, 54 microbes in the model of microbes-only, and 28 genes and 18 microbes in the model with genes-and-microbes combined. PRAC1 expression was the most important feature for differentiating RCC and LCC in the genes-only model, with HOXB13, SPAG16, HOXC4, and RNLS also playing a role. Ruminococcus gnavus and Clostridium acetireducens were the most important in the microbial-only model. MYOM3, HOXC4, Coprococcus eutactus, PRAC1, lncRNA AC012531.25, Ruminococcus gnavus, RNLS, HOXC6, SPAG16 and Fusobacterium nucleatum were most important in the combined model.
CONCLUSIONS
Many of the identified genes and microbes among all models have previously established associations with CRC. However, the ability of RF models to account for inter-feature relationships within the underlying decision trees may yield a more sensitive and biologically interconnected set of genomic and microbial biomarkers.
Topics: Colorectal Neoplasms; Humans; Random Forest; Machine Learning; Microbiota; Genetic Markers; Male; Female; Adult; Middle Aged; Aged; Aged, 80 and over
PubMed: 37434131
DOI: 10.1186/s12885-023-10848-9 -
Gut Microbes Jul 2016We previously identified and characterized an intramolecular trans-sialidase (IT-sialidase) in the gut symbiont Ruminococcus gnavus ATCC 29149, which is associated to...
We previously identified and characterized an intramolecular trans-sialidase (IT-sialidase) in the gut symbiont Ruminococcus gnavus ATCC 29149, which is associated to the ability of the strain to grow on mucins. In this work we have obtained and analyzed the draft genome sequence of another R. gnavus mucin-degrader, ATCC 35913, isolated from a healthy individual. Transcriptomics analyses of both ATCC 29149 and ATCC 35913 strains confirmed that the strategy utilized by R. gnavus for mucin-degradation is focused on the utilization of terminal mucin glycans. R. gnavus ATCC 35913 also encodes a predicted IT-sialidase and harbors a Nan cluster dedicated to sialic acid utilization. We showed that the Nan cluster was upregulated when the strains were grown in presence of mucin. In addition we demonstrated that both R. gnavus strains were able to grow on 2,7-anyhydro-Neu5Ac, the IT-sialidase transglycosylation product, as a sole carbon source. Taken together these data further support the hypothesis that IT-sialidase expressing gut microbes, provide commensal bacteria such as R. gnavus with a nutritional competitive advantage, by accessing and transforming a source of nutrient to their own benefit.
Topics: Bacterial Proteins; Genome, Bacterial; Glycoproteins; Mucins; Neuraminidase; Ruminococcus
PubMed: 27223845
DOI: 10.1080/19490976.2016.1186334 -
Biomolecules Oct 2021Adhesion to the digestive mucosa is considered a key factor for bacterial persistence within the gut. In this study, we show that E1 can express the gene, which...
Adhesion to the digestive mucosa is considered a key factor for bacterial persistence within the gut. In this study, we show that E1 can express the gene, which encodes an adhesin of the MSCRAMMs family, only when it colonizes the gut. The RadA N-terminal region contains an all-β bacterial Ig-like domain known to interact with collagens. We observed that it preferentially binds human immunoglobulins (IgA and IgG) and intestinal mucins. Using deglycosylated substrates, we also showed that the RadA N-terminal region recognizes two different types of motifs, the protein backbone of human IgG and the glycan structure of mucins. Finally, competition assays with lectins and free monosaccharides identified Galactose and N-Acetyl-Galactosamine motifs as specific targets for the binding of RadA to mucins and the surface of human epithelial cells.
Topics: Clostridiales; Mucins; Polysaccharides; Symbiosis
PubMed: 34827611
DOI: 10.3390/biom11111613 -
Proceedings of the National Academy of... May 2021Active inflammatory bowel disease (IBD) often coincides with increases of , a gut microbe found in nearly everyone. It was not known how, or if, this correlation...
Active inflammatory bowel disease (IBD) often coincides with increases of , a gut microbe found in nearly everyone. It was not known how, or if, this correlation contributed to disease. We investigated clinical isolates of to identify molecular mechanisms that would link to inflammation. Here, we show that only some isolates of produce a capsular polysaccharide that promotes a tolerogenic immune response, whereas isolates lacking functional capsule biosynthetic genes elicit robust proinflammatory responses in vitro. Germ-free mice colonized with an isolate of lacking a capsule show increased measures of gut inflammation compared to those colonized with an encapsulated isolate in vivo. These observations in the context of our earlier identification of an inflammatory cell-wall polysaccharide reveal how some strains of could drive the inflammatory responses that characterize IBD.
Topics: Adult; Animals; Anti-Bacterial Agents; Bacterial Capsules; Cells, Cultured; Child; Clostridiales; Cytokines; Female; Gastrointestinal Microbiome; Humans; Ileum; Immunity; Inflammatory Bowel Diseases; Mice, Inbred C57BL; Multigene Family; Phylogeny; Polysaccharides; Mice
PubMed: 33972416
DOI: 10.1073/pnas.2007595118 -
Nature Communications Dec 2017Ruminococcus gnavus is a human gut symbiont wherein the ability to degrade mucins is mediated by an intramolecular trans-sialidase (RgNanH). RgNanH comprises a GH33...
Ruminococcus gnavus is a human gut symbiont wherein the ability to degrade mucins is mediated by an intramolecular trans-sialidase (RgNanH). RgNanH comprises a GH33 catalytic domain and a sialic acid-binding carbohydrate-binding module (CBM40). Here we used glycan arrays, STD NMR, X-ray crystallography, mutagenesis and binding assays to determine the structure and function of RgNanH_CBM40 (RgCBM40). RgCBM40 displays the canonical CBM40 β-sandwich fold and broad specificity towards sialoglycans with millimolar binding affinity towards α2,3- or α2,6-sialyllactose. RgCBM40 binds to mucus produced by goblet cells and to purified mucins, providing direct evidence for a CBM40 as a novel bacterial mucus adhesin. Bioinformatics data show that RgCBM40 canonical type domains are widespread among Firmicutes. Furthermore, binding of R. gnavus ATCC 29149 to intestinal mucus is sialic acid mediated. Together, this study reveals novel features of CBMs which may contribute to the biogeography of symbiotic bacteria in the gut.
Topics: Adhesins, Bacterial; Animals; Catalytic Domain; Cell Line; Colon; Computational Biology; Crystallography, X-Ray; Glycoproteins; Goblet Cells; Humans; Lactose; Mice, Inbred C57BL; Mucins; Mutagenesis, Site-Directed; N-Acetylneuraminic Acid; Neuraminidase; Protein Binding; Ruminococcus; Substrate Specificity; Symbiosis
PubMed: 29259165
DOI: 10.1038/s41467-017-02109-8 -
The Journal of Nutrition Apr 2023Diet, a key component of type 1 diabetes (T1D) management, modulates the intestinal microbiota and its metabolically active byproducts-including SCFA-through... (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND
Diet, a key component of type 1 diabetes (T1D) management, modulates the intestinal microbiota and its metabolically active byproducts-including SCFA-through fermentation of dietary carbohydrates such as fiber. However, the diet-microbiome relationship remains largely unexplored in longstanding T1D.
OBJECTIVES
We evaluated whether increased carbohydrate intake, including fiber, is associated with increased SCFA-producing gut microbes, SCFA, and intestinal microbial diversity among young adults with longstanding T1D and overweight or obesity.
METHODS
Young adult men and women with T1D for ≥1 y, aged 19-30 y, and BMI of 27.0-39.9 kg/m at baseline provided stool samples at baseline and 3, 6, and 9 mo of a randomized dietary weight loss trial. Diet was assessed by 1-2 24-h recalls. The abundance of SCFA-producing microbes was measured using 16S rRNA gene sequencing. GC-MS measured fecal SCFA (acetate, butyrate, propionate, and total) concentrations. Adjusted and Bonferroni-corrected generalized estimating equations modeled associations of dietary fiber (total, soluble, and pectins) and carbohydrate (available carbohydrate, and fructose) with microbiome-related outcomes. Primary analyses were restricted to data collected before COVID-19 interruptions.
RESULTS
Fiber (total and soluble) and carbohydrates (available and fructose) were positively associated with total SCFA and acetate concentrations (n = 40 participants, 52 visits). Each 10 g/d of total and soluble fiber intake was associated with an additional 8.8 μmol/g (95% CI: 4.5, 12.8 μmol/g; P = 0.006) and 24.0 μmol/g (95% CI: 12.9, 35.1 μmol/g; P = 0.003) of fecal acetate, respectively. Available carbohydrate intake was positively associated with SCFA producers Roseburia and Ruminococcus gnavus. All diet variables except pectin were inversely associated with normalized abundance of Bacteroides and Alistipes. Fructose was inversely associated with Akkermansia abundance.
CONCLUSIONS
In young adults with longstanding T1D, fiber and carbohydrate intake were associated positively with fecal SCFA but had variable associations with SCFA-producing gut microbes. Controlled feeding studies should determine whether gut microbes and SCFA can be directly manipulated in T1D.
Topics: Female; Humans; Male; Young Adult; Acetates; COVID-19; Diabetes Mellitus, Type 1; Dietary Fiber; Eating; Fatty Acids, Volatile; Feces; Fructose; Gastrointestinal Microbiome; Obesity; Overweight; RNA, Ribosomal, 16S
PubMed: 36841667
DOI: 10.1016/j.tjnut.2022.12.017 -
Applied Microbiology and Biotechnology Dec 2024Altered gut microbiota has been connected to hepatocellular carcinoma (HCC) occurrence and advancement. This study was conducted to identify a gut microbiota signature...
Altered gut microbiota has been connected to hepatocellular carcinoma (HCC) occurrence and advancement. This study was conducted to identify a gut microbiota signature in differentiating between viral-related HCC (Viral-HCC) and non-hepatitis B-, non-hepatitis C-related HCC (NBNC-HCC). Fecal specimens were obtained from 16 healthy controls, 33 patients with viral-HCC (17 and 16 cases with hepatitis B virus (HBV) and hepatitis C virus (HCV) infection, respectively), and 18 patients with NBNC-HCC. Compositions of fecal microbiota were assessed by 16S rRNA sequencing. Bioinformatic analysis was performed by the DADA2 pipeline in the R program. Significantly different genera from the top 50 relative abundance were used to classify between subgroups of HCC by the Random Forest algorithm. Our data demonstrated that the HCC group had a significantly decreased alpha-diversity and changed microbial composition in comparison with healthy controls. Within the top 50 relative abundance, there were 11 genera including Faecalibacterium, Agathobacter, and Coprococcus that were significantly enhanced in Viral-HCC, while 5 genera such as Bacteroides, Streptococcus, Ruminococcus gnavus group, Parabacteroides, and Erysipelatoclostridium were enhanced in NBNC-HCC. Compared to Viral-HCC, the NBNC-HCC subgroup significantly reduced various short-chain fatty acid-producing bacteria, as well as declined fecal butyrate but elevated plasma surrogate markers of microbial translocation. Based on the machine learning algorithm, a high diagnostic accuracy to classify HCC subgroups was achieved with an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.94. Collectively, these data revealed that gut dysbiosis was distinct according to etiological factors of HCC, which might play an essential role in hepatocarcinogenesis. These findings underscore the possible use of a gut microbiota signature for the diagnosis and therapeutic approaches regarding different subgroups of HCC. KEY POINTS: • Gut dysbiosis is connected to hepatocarcinogenesis and can be used as a novel biomarker. • Gut microbiota composition is significantly altered in different etiological factors of HCC. • Microbiota-based signature can accurately distinguish between Viral-HCC and NBNC-HCC.
Topics: Humans; Carcinoma, Hepatocellular; Gastrointestinal Microbiome; Dysbiosis; RNA, Ribosomal, 16S; Liver Neoplasms; Carcinogenesis
PubMed: 38183473
DOI: 10.1007/s00253-023-12845-1 -
Frontiers in Immunology 2024Previous research has partially revealed distinct gut microbiota in ankylosing spondylitis (AS). In this study, we performed non-targeted fecal metabolomics in AS in...
OBJECTIVE
Previous research has partially revealed distinct gut microbiota in ankylosing spondylitis (AS). In this study, we performed non-targeted fecal metabolomics in AS in order to discover the microbiome-metabolome interface in AS. Based on prospective cohort studies, we further explored the impact of the tumor necrosis factor inhibitor (TNFi) on the gut microbiota and metabolites in AS.
METHODS
To further understand the gut microbiota and metabolites in AS, along with the influence of TNFi, we initiated a prospective cohort study. Fecal samples were collected from 29 patients with AS before and after TNFi therapy and 31 healthy controls. Metagenomic and metabolomic experiments were performed on the fecal samples; moreover, validation experiments were conducted based on the association between the microbiota and metabolites.
RESULTS
A total of 7,703 species were annotated using the metagenomic sequencing system and by profiling the microbial community taxonomic composition, while 50,046 metabolites were identified using metabolite profiling. Differential microbials and metabolites were discovered between patients with AS and healthy controls. Moreover, TNFi was confirmed to partially restore the gut microbiota and the metabolites. Multi-omics analysis of the microbiota and metabolites was performed to determine the associations between the differential microbes and metabolites, identifying compounds such as oxypurinol and biotin, which were correlated with the inhibition of the pathogenic bacteria and the promotion of the probiotic bacteria . Through experimental studies, the relationship between microbes and metabolites was further confirmed, and the impact of these two types of microbes on the enterocytes and the inflammatory cytokine interleukin-18 (IL-18) was explored.
CONCLUSION
In summary, multi-omics exploration elucidated the impact of TNFi on the gut microbiota and metabolites and proposed a novel therapeutic perspective: supplementation of compounds to inhibit potential pathogenic bacteria and to promote potential probiotics, therefore controlling inflammation in AS.
Topics: Humans; Spondylitis, Ankylosing; Gastrointestinal Microbiome; Probiotics; Male; Female; Metabolome; Adult; Feces; Metagenomics; Middle Aged; Prospective Studies; Metabolomics; Bacteria; Tumor Necrosis Factor Inhibitors
PubMed: 38711505
DOI: 10.3389/fimmu.2024.1369116