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Nature Communications Apr 2024The etiopathogenesis of diverticulitis, among the most common gastrointestinal diagnoses, remains largely unknown. By leveraging stool collected within a large...
The etiopathogenesis of diverticulitis, among the most common gastrointestinal diagnoses, remains largely unknown. By leveraging stool collected within a large prospective cohort, we performed shotgun metagenomic sequencing and untargeted metabolomics profiling among 121 women diagnosed with diverticulitis requiring antibiotics or hospitalizations (cases), matched to 121 women without diverticulitis (controls) according to age and race. Overall microbial community structure and metabolomic profiles differed in diverticulitis cases compared to controls, including enrichment of pro-inflammatory Ruminococcus gnavus, 1,7-dimethyluric acid, and histidine-related metabolites, and depletion of butyrate-producing bacteria and anti-inflammatory ceramides. Through integrated multi-omic analysis, we detected covarying microbial and metabolic features, such as Bilophila wadsworthia and bile acids, specific to diverticulitis. Additionally, we observed that microbial composition modulated the protective association between a prudent fiber-rich diet and diverticulitis. Our findings offer insights into the perturbations in inflammation-related microbial and metabolic signatures associated with diverticulitis, supporting the potential of microbial-based diagnostics and therapeutic targets.
Topics: Humans; Female; Gastrointestinal Microbiome; Middle Aged; Diverticulitis; Feces; Aged; Prospective Studies; Bilophila; Metabolomics; Case-Control Studies; Clostridiales; Bile Acids and Salts; Adult; Dietary Fiber; Metabolome; Metagenomics
PubMed: 38684664
DOI: 10.1038/s41467-024-47859-4 -
Microbiology Spectrum Aug 2023Many studies have suggested that gut microbiota dysbiosis may be one of the pathogenesis factors of diabetes mellitus (DM), while it is not clear whether it is involved...
Many studies have suggested that gut microbiota dysbiosis may be one of the pathogenesis factors of diabetes mellitus (DM), while it is not clear whether it is involved in the development of diabetic kidney diseases (DKD). The objective of this study was to determine bacterial taxa biomarkers during the progression of DKD by investigating bacterial compositional changes in early and late DKD. 16S rRNA gene sequencing was performed on fecal samples, including the diabetes mellitus (DM), DNa (early DKD), and DNb (late DKD) groups. Taxonomic annotation of microbial composition was performed. Samples were sequenced on the Illumina NovaSeq platform. At the genus level, we found counts of , , and were significantly elevated both in the DNa group (0.0001, 0.0007, and 0.0174, respectively) and the DNb group (0.0001, 0.0012, and 0.0003, respectively) compared with those in the DM group. Only the level of was significantly decreased in the DNa group than the DM group and in the DNb group than the DNa group. Counts of , were significantly decreased in the DNa group compared with those in the DM group (0.001 and 0.006, respectively) and in the DNb group compared with those in the DM group (0.0001 and 0.003, respectively). Levels of , and were positively correlated with an estimated glomerular filtration rate (eGFR), but negatively correlated with microalbuminuria (MAU), 24 h urinary protein quantity (24hUP), and serum creatinine (Scr). Moreover, the areas under the curve (AUCs) of and were 83.33% and 80.77%, respectively, for the DM and DNa cohorts, respectively. Notably, the largest AUC for DNa and DNb cohorts was also that of at 83.60%. Gut microbiota dysbiosis was found in the early and late stages of DKD, especially in the early stage. may be the most promising intestinal bacteria biomarker that can help distinguish different stages of DKD. It is not clear as to whether gut microbiota dysbiosis is involved in the progression of DKD. This study may be the first to explore gut microbiota compositional changes in diabetes, early-DKD, and late DKD. We identify different gut microbial characteristics during different stages of DKD. Gut microbiota dysbiosis is found in the early and late stages of DKD. may be the most promising intestinal bacteria biomarker that can help distinguish different stages of DKD, although further studies are warranted to illustrate these mechanisms.
Topics: Diabetic Nephropathies; Humans; Male; Female; Middle Aged; Gastrointestinal Microbiome; Clostridiales; Biomarkers; Diabetes Mellitus; Bacteria; Feces; Kidney Failure, Chronic
PubMed: 37341590
DOI: 10.1128/spectrum.00382-23 -
Alimentary Pharmacology & Therapeutics Oct 2023Faecal microbiota transplantation (FMT) has been shown to improve symptoms in a proportion of patients with irritable bowel syndrome (IBS).
BACKGROUND
Faecal microbiota transplantation (FMT) has been shown to improve symptoms in a proportion of patients with irritable bowel syndrome (IBS).
AIM
We performed a randomised trial to assess the efficacy of FMT in patients with IBS.
METHODS
We randomised 56 patients with diarrhoea-predominant IBS 1:1 to FMT or placebo via the duodenal route at baseline and week 4. The primary outcome was > 50 points decrease in IBS severity scoring system (IBS-SSS) score at week 12. Secondary outcomes were improvement in bloating and change in gut microbiota at week 12. After 12-week follow-up, those in the placebo group were assigned to receive open-label FMT.
RESULTS
At week 12, 57.1% in the FMT group and 46.4% in the placebo group achieved the primary endpoint (p = 0.42). More patients receiving FMT than placebo had improvement in bloating (72% vs 30%; p = 0.005). In an open-label extension, 65.2% and 82.4% of patients achieved, respectively, the primary endpoint and improvement in bloating. Faecal microbiome of patients in the FMT group showed a reduction in bacteria like Ruminococcus gnavus and enrichment of bacteria such as Lawsonibacter at week 12, while no change in the placebo group. Functional analyses showed that the hydrogen sulphide-producing pathway decreased in patients who had FMT (p < 0.05) accompanied by a reduction in contributing bacteria. There were no serious adverse events related to FMT.
CONCLUSION
FMT performed twice at an interval of four weeks did not significantly reduce IBS-SSS score. However, more patients had improvement in abdominal bloating, which was associated with a reduction in hydrogen sulphide-producing bacteria. (ClinicalTrials.gov NCT03125564).
Topics: Humans; Irritable Bowel Syndrome; Fecal Microbiota Transplantation; Hydrogen Sulfide; Diarrhea; Feces; Treatment Outcome
PubMed: 37667968
DOI: 10.1111/apt.17703 -
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 -
Nature Communications Nov 2023The early-life gut microbiome development has long-term health impacts and can be influenced by factors such as infant diet. Human milk oligosaccharides (HMOs), an...
The early-life gut microbiome development has long-term health impacts and can be influenced by factors such as infant diet. Human milk oligosaccharides (HMOs), an essential component of breast milk that can only be metabolized by some beneficial gut microorganisms, ensure proper gut microbiome establishment and infant development. However, how HMOs are metabolized by gut microbiomes is not fully elucidated. Isolate studies have revealed the genetic basis for HMO metabolism, but they exclude the possibility of HMO assimilation via synergistic interactions involving multiple organisms. Here, we investigate microbiome responses to 2'-fucosyllactose (2'FL), a prevalent HMO and a common infant formula additive, by establishing individualized microbiomes using fecal samples from three infants as the inocula. Bifidobacterium breve, a prominent member of infant microbiomes, typically cannot metabolize 2'FL. Using metagenomic data, we predict that extracellular fucosidases encoded by co-existing members such as Ruminococcus gnavus initiate 2'FL breakdown, thus critical for B. breve's growth. Using both targeted co-cultures and by supplementation of R. gnavus into one microbiome, we show that R. gnavus can promote extensive growth of B. breve through the release of lactose from 2'FL. Overall, microbiome cultivation combined with genome-resolved metagenomics demonstrates that HMO utilization can vary with an individual's microbiome.
Topics: Female; Child; Humans; Infant; Bifidobacterium; Trisaccharides; Milk, Human; Oligosaccharides; Microbiota
PubMed: 37973815
DOI: 10.1038/s41467-023-43279-y -
Scientific Reports Nov 2023To investigate the gut microbiota distribution and its functions in children with avoidant/restrictive food intake disorder (ARFID). A total of 135 children were...
To investigate the gut microbiota distribution and its functions in children with avoidant/restrictive food intake disorder (ARFID). A total of 135 children were enrolled in the study, including 102 children with ARFID and 33 healthy children. Fecal samples were analyzed to explore differences in gut microbiota composition and diversity and functional differences between the ARFID and healthy control (HC) groups via 16S rDNA and metagenomic sequencing. The gut microbiota composition and diversity in children with ARFID were different from those in heathy children, but there is no difference in the composition and diversity of gut microbiota between children at the age of 3-6 and 7-12 with ARFID. At the phylum level, the most abundant microbes in the two groups identified by 16S rDNA and metagenomic sequencing were the same. At the genus level, the abundance of Bacteroides was higher in the ARFID group (P > 0.05); however, different from the result of 16SrDNA sequencing, metagenomic sequencing showed that the abundance of Bacteroides in the ARFID group was significantly higher than that in the HC group (P = 0.041). At the species level, Escherichia coli, Streptococcus thermophilus and Lachnospira eligens were the most abundant taxa in the ARFID group, and Prevotella copri, Bifidobacterium pseudocatenulatum, and Ruminococcus gnavus were the top three microbial taxa in the HC group; there were no statistically significant differences between the abundance of these microbial taxa in the two groups. LefSe analysis indicated a greater abundance of the order Enterobacterales and its corresponding family Enterobacteriaceae, the family Bacteroidaceae and corresponding genus Bacteroides, the species Bacteroides vulgatus in ARFID group, while the abundance of the phylum Actinobacteriota and its corresponding class Actinobacteria , the order Bifidobacteriales and corresponding family Bifidobacteriaceae, the genus Bifidobacterium were enriched in the HC group. There were no statistically significant differences in the Chao1, Shannon and Simpson indices between the Y1 and Y2 groups (P = 0.1, P = 0.06, P = 0.06). At the phylum level, Bacillota, Bacteroidota, Proteobacteria and Actinobacteriota were the most abundant taxa in both groups, but there were no statistically significant differences among the abundance of these bacteria (P = 0.958, P = 0.456, P = 0.473, P = 0.065). At the genus level, Faecalibacterium was more abundant in the Y2 group than in the Y1 group, and the difference was statistically significant (P = 0.037). The KEGG annotation results showed no significant difference in gut microbiota function between children with ARFID and healthy children; however, GT26 was significantly enriched in children with ARFID based on the CAZy database. The most abundant antibiotic resistance genes in the ARFID group were the vanT, tetQ, adeF, ermF genes, and the abundance of macrolide resistance genes in the ARFID group was significantly higher than that in the HC group (P = 0.041). Compared with healthy children, children with ARFID have a different distribution of the gut microbiota and functional genes. This indicates that the gut microbiome might play an important role in the pathogenesis of ARFID.Clinical trial registration: ChiCTR2300074759.
Topics: Humans; Child; Anti-Bacterial Agents; Avoidant Restrictive Food Intake Disorder; Drug Resistance, Bacterial; Macrolides; Microbiota; Bacteria; Actinobacteria; Eating; RNA, Ribosomal, 16S
PubMed: 37985845
DOI: 10.1038/s41598-023-47760-y -
The Journal of Clinical Endocrinology... May 2024Cushing syndrome (CS) is a severe endocrine disease characterized by excessive secretion of cortisol with multiple metabolic disorders. While gut microbial dysbiosis...
CONTEXT
Cushing syndrome (CS) is a severe endocrine disease characterized by excessive secretion of cortisol with multiple metabolic disorders. While gut microbial dysbiosis plays a vital role in metabolic disorders, the role of gut microbiota in CS remains unclear.
OBJECTIVE
The objective of this work is to examine the alteration of gut microbiota in patients with CS.
METHODS
We performed shotgun metagenomic sequencing of fecal samples from 78 patients with CS and 78 healthy controls matched for age and body mass index. Furthermore, we verify the cortisol degradation capacity of Ruminococcus gnavus in vitro and identify the potential metabolite by LC-MC/MS.
RESULTS
We observed significant differences in microbial composition between CS and controls in both sexes, with CS showing reduced Bacteroidetes (Bacteroides vulgatus) and elevated Firmicutes (Erysipelotrichaceae_bacterium_6_1_45) and Proteobacteria (Enterobacter cloacae). Despite distinct causes of hypercortisolism in ACTH-dependent and ACTH-independent CS, we found no significant differences in metabolic profiles or gut microbiota between the 2 subgroups. Furthermore, we identified a group of gut species, including R. gnavus, that were positively correlated with cortisol levels in CS. These bacteria were found to harbor cortisol-degrading desAB genes and were consistently enriched in CS. Moreover, we demonstrated the efficient capacity of R. gnavus to degrade cortisol to 11-oxygenated androgens in vitro.
CONCLUSION
This study provides evidence of gut microbial dysbiosis in patients with CS and identifies a group of CS-enriched bacteria capable of degrading cortisol. These findings highlight the potential role of gut microbiota in regulating host steroid hormone levels, and consequently host health.
Topics: Humans; Dysbiosis; Male; Female; Gastrointestinal Microbiome; Cushing Syndrome; Hydrocortisone; Middle Aged; Adult; Feces; Case-Control Studies; Clostridiales
PubMed: 38157274
DOI: 10.1210/clinem/dgad766 -
Frontiers in Cellular and Infection... 2023Low diversity gut dysbiosis can take different forms depending on the disease context. In this study, we used shotgun metagenomic sequencing and gas chromatography-mass...
INTRODUCTION
Low diversity gut dysbiosis can take different forms depending on the disease context. In this study, we used shotgun metagenomic sequencing and gas chromatography-mass spectrometry (GC-MS) to compared the metagenomic and metabolomic profiles of diarrheal cancer and inflammatory bowel disease (IBD) patients and defined the additive effect of infection (CDI) on intestinal dysbiosis.
RESULTS
The study cohort consisted of 138 case-mix cancer patients, 43 IBD patients, and 45 healthy control individuals. Thirty-three patients were also infected with . In the control group, three well-known enterotypes were identified, while the other groups presented with an additional -driven enterotype. Bacterial diversity was significantly lower in all groups than in healthy controls, while the highest level of bacterial species richness was observed in cancer patients. Fifty-six bacterial species had abundance levels that differentiated diarrheal patient groups from the control group. Of these species, 52 and 4 (, , , and ) were under-represented and over-represented, respectively, in all diarrheal patient groups. The relative abundances of propionate and butyrate were significantly lower in fecal samples from IBD and CDI patients than in control samples. Isobutyrate, propanate, and butyrate concentrations were lower in cancer, IBD, and CDI samples, respectively. Glycine and valine amino acids were over- represented in diarrheal patients.
CONCLUSION
Our data indicate that different external and internal factors drive comparable profiles of low diversity dysbiosis. While diarrheal-related low diversity dysbiosis may be a consequence of systemic cancer therapy, a similar phenotype is observed in cases of moderate to severe IBD, and in both cases, dysbiosis is exacerbated by incidence of CDI.
Topics: Humans; Clostridioides difficile; Dysbiosis; Clostridium Infections; Inflammatory Bowel Diseases; Diarrhea; Bacteria; Butyrates; Neoplasms
PubMed: 37577378
DOI: 10.3389/fcimb.2023.1190910 -
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