-
Frontiers in Cellular and Infection... 2022Although the gut microbiota may be involved in obesity onset and progression, the exact association of the gut microbiota in metabolically healthy obesity (MHO) remains...
BACKGROUND
Although the gut microbiota may be involved in obesity onset and progression, the exact association of the gut microbiota in metabolically healthy obesity (MHO) remains largely unknown.
METHODS
An integrated paired-sample metagenomic analysis was conducted to investigate the gut microbial network and biomarkers of microbial species from the MHO and healthy non-obese subjects in the GMrepo database. Further explorations were performed in the MHO mice model using a multiomics analysis to detect changes in the composition and function of the intestinal microbiome and associated metabolites.
RESULTS
In the human study, 314 matched metagenomic data were qualified for the final analysis. We identified seven significantly changed species possibly involved in MHO pathogenesis (MHO-enriched: , ; MHO-depleted: , , ; ; ). In the murine study, we found 79 significantly-changed species which may have possible associations with the MHO phenotype. The depletion of was commonly recognized in the human and murine MHO phenotype. Consistent with the metagenomic data, liquid chromatography-mass spectrometry (LC/MS) revealed significantly changed gut metabolites, which may promote MHO pathogenesis by altering the amino acids and lipid metabolic pathways. In the microbe-metabolites interaction analysis, we identified certain fatty acids (Dodecanedioic acid, Arachidic Acid, Mevalonic acid, etc.) that were significantly correlated with the MHO-enriched or depleted species.
CONCLUSION
This study provides insights into identifying specific microbes and metabolites that may involve in the development of obesity without metabolic disorders. Future modalities for MHO intervention may be further validated by targeting these bacteria and metabolites.
Topics: Humans; Mice; Animals; Gastrointestinal Microbiome; Obesity, Metabolically Benign; Obesity; Metagenomics
PubMed: 36389176
DOI: 10.3389/fcimb.2022.1012028 -
Frontiers in Cellular and Infection... 2021Frailty is a common geriatric syndrome that is diagnosed and staged based mainly on symptoms. We aimed to evaluate frailty-related alterations of the intestinal...
OBJECTIVE
Frailty is a common geriatric syndrome that is diagnosed and staged based mainly on symptoms. We aimed to evaluate frailty-related alterations of the intestinal permeability and profile fecal microbiota of healthy and frail older adults to identify microbial biomarkers of this syndrome.
METHODS
We collected serum and fecal samples from 94 community-dwelling older adults, along with anthropometric, medical, mental health, and lifestyle data. Serum inflammatory cytokines IL-6 and HGMB1 and the intestinal permeability biomarker zonulin were measured using enzyme-linked immunosorbent assays. The 16S rRNA amplicon sequencing method was performed to determine the fecal composition of fecal microbiota. We analyzed the diversity and composition differences of the gut microbiota in the two groups and assessed the relationship between the changes in microbiota structure and clinical biomarkers.
RESULTS
Older adults with frailty showed higher concentrations of IL-6, HGMB1, and zonulin. Although there were no statistically significant differences in the diversity index and evenness indices or species richness of fecal microbiota between the two groups, we found significant microbiota structure differences. Compared with the control group, fecal samples from the frail group had higher levels of , , and and lower levels of the commensal genera , , , , and Spearman's correlation analysis showed that the intergenus interactions were more common in healthy controls than older adults with frailty. /, , , and were positively correlated with IL-6, while , , and were negatively correlated with IL-6. were found to be positively correlated with HGMB1. and were linked to the increased serum level of inflammatory factors and intestinal permeability.
CONCLUSIONS
Frailty is associated with differences in the composition of fecal microbiota. These findings might aid in the development of probiotics or microbial-based therapies for frailty.
Topics: Aged; Feces; Frailty; Gastrointestinal Microbiome; Humans; Microbiota; RNA, Ribosomal, 16S
PubMed: 34485176
DOI: 10.3389/fcimb.2021.696186 -
AMB Express Jun 2023Anal fistula is a common proctological disease, but the thorough mechanisms of the anal fistula formation are still unclear. An increasing number of studies have...
Anal fistula is a common proctological disease, but the thorough mechanisms of the anal fistula formation are still unclear. An increasing number of studies have revealed the crucial role of gut microbiota in intestinal diseases. We used 16S rRNA gene sequencing to analyze the intestinal microbiome in order to determine whether there are differences in the microbiome between anal fistula patients and healthy individuals. The microbiome samples were extracted by repeatedly wiping the rectal wall with intestinal swab. Before this operation, the whole intestine of all participants was irrigated and the score of the Boston bowel preparation scale reached 9. The biodiversity of gut microbiome of rectum revealed significant difference between anal fistula patients and healthy individuals. 36 discriminative taxa were identified by LEfSe analysis between two groups. At the phylum level, Synergistetes was enriched in anal fistula patients, while Proteobacteria was higher in healthy individuals. We also found that at the genus level, Blautia, Faecalibacterium, Ruminococcus, Coprococcus, Bacteroides, Clostridium, Megamonas and Anaerotruncus were highly enriched in anal fistula patients, while the microbiome of healthy individuals was enriched with Peptoniphilus and Corynebacterium. Spearman correlations showed the extensive and close association among genera and species. Finally, a diagnostic prediction model was constructed by random forest classifier, and the area under curve (AUC) reached 0.990. This study gave an important hint for analyzing gut microbiome of rectum in anal fistula patient.Keypoints.We use the 16S rRNA gene sequencing to test the microbiome samples extracted from the intestinal swab. This is the first study to explore the gut microbiome of rectum using this workflow. We also found the distinct gut microbiome of rectum differences between anal fistula patients and healthy individuals.
PubMed: 37301777
DOI: 10.1186/s13568-023-01560-9 -
Nutrients Apr 2023The etiology of systemic lupus erythematosus (SLE) remains unclear, with both genetic and environmental factors potentially contributing. This study aimed to explore the...
The etiology of systemic lupus erythematosus (SLE) remains unclear, with both genetic and environmental factors potentially contributing. This study aimed to explore the relationship among gut microbiota (GM), intestinal permeability, and food intake with inflammatory markers in inactive SLE patients. A total of 22 women with inactive SLE and 20 healthy volunteers were enrolled, and dietary intake was assessed through 24-h dietary recalls. Plasma zonulin was used to evaluate intestinal permeability, while GM was determined by 16S rRNA sequencing. Regression models were used to analyze laboratory markers of lupus disease (C3 and C4 complement and C-reactive protein). Our results showed that the genus Megamonas was significantly enriched in the iSLE group ( < 0.001), with Megamonas funiformis associated with all evaluated laboratory tests ( < 0.05). Plasma zonulin was associated with C3 levels ( = 0.016), and sodium intake was negatively associated with C3 and C4 levels ( < 0.05). A combined model incorporating variables from each group (GM, intestinal permeability, and food intake) demonstrated a significant association with C3 complement levels ( < 0.01). These findings suggest that increased Megamonas funiformis abundance, elevated plasma zonulin, and higher sodium intake may contribute to reduced C3 complement levels in women with inactive SLE.
Topics: Humans; Female; Complement C3; RNA, Ribosomal, 16S; Lupus Erythematosus, Systemic; Sodium, Dietary
PubMed: 37111218
DOI: 10.3390/nu15081999 -
Atherosclerosis May 2024Metabolic associated fatty liver disease (MAFLD) is a novel concept proposed in 2020, which is more practical for identifying patients with fatty liver disease with high...
BACKGROUND
Metabolic associated fatty liver disease (MAFLD) is a novel concept proposed in 2020, which is more practical for identifying patients with fatty liver disease with high risk of disease progression. Fatty liver is a driver for extrahepatic complications, particularly cardiovascular diseases (CVD). Although the risk of CVD in MAFLD could be predicted by carotid ultrasound test, a very early stage prediction method before the formation of pathological damage is still lacking.
METHODS
Stool microbiomes and plasma metabolites were compared across 196 well-characterized participants encompassing normal controls, simple MAFLD patients, MAFLD patients with carotid artery pathological changes, and MAFLD patients with diagnosed coronary artery disease (CAD). 16S rDNA sequencing data and untargeted metabolomic profiles were interrogatively analyzed using differential abundance analysis and random forest (RF) machine learning algorithm to identify discriminatory gut microbiomes and metabolomic.
RESULTS
Characteristic microbial changes in MAFLD patients with CVD risk were represented by the increase of Clostridia and Firmicutes-to-Bacteroidetes ratios. Faecalibacterium was negatively correlated with mean-intima-media thickness (IMT), TC, and TG. Megamonas, Bacteroides, Parabacteroides, and Escherichia were positively correlated with the exacerbation of pathological indexes. MAFLD patients with CVD risk were characterized by the decrease of lithocholic acid taurine conjugate, and the increase of ethylvanillin propylene glycol acetal, both of which had close relationship with Ruminococcus and Gemmiger. Biotin l-sulfoxide had positive correlation with mean-IMT, TG, and weight. The general auxin pesticide beta-naphthoxyacetic acid and the food additive glucosyl steviol were both positively correlated with the increase of mean-IMT. The model combining the metabolite signatures with 9 clinical parameters accurately distinguished MAFLD with CVD risk in the proband and validation cohort. It was found that citral was the most important discriminative metabolite marker, which was validated by both in vitro and in vivo experiments.
CONCLUSIONS
Simple MAFLD patients and MAFLD patients with CVD risk had divergent gut microbes and plasma metabolites. The predictive model based on metabolites and 9 clinical parameters could effectively discriminate MAFLD patients with CVD risk at a very early stage.
Topics: Humans; Gastrointestinal Microbiome; Male; Female; Middle Aged; Feces; Metabolomics; Cardiovascular Diseases; Biomarkers; Risk Assessment; Case-Control Studies; Aged; Predictive Value of Tests; Bacteria; Heart Disease Risk Factors; Adult; Non-alcoholic Fatty Liver Disease; Machine Learning; Carotid Intima-Media Thickness
PubMed: 38581738
DOI: 10.1016/j.atherosclerosis.2024.117526 -
Polish Journal of Microbiology Jun 2022To explore the role of gut microbiota in Graves' disease (GD) and Hashimoto's thyroiditis (HT). Seventy fecal samples were collected, including 27 patients with GD, 27...
To explore the role of gut microbiota in Graves' disease (GD) and Hashimoto's thyroiditis (HT). Seventy fecal samples were collected, including 27 patients with GD, 27 with HT, and 16 samples from healthy volunteers. Chemiluminescence was used to detect thyroid function and autoantibodies (FT3, FT4, TSH, TRAb, TGAb, and TPOAb); thyroid ultrasound and 16S sequencing were used to analyze the bacteria in fecal samples; KEGG (Kyoto Encyclopedia of Genes and Genomes) and COG (Clusters of Orthologous Groups) were used to analyze the functional prediction and pathogenesis. The overall structure of gut microbiota in the GD and HT groups was significantly different from the healthy control group. Proteobacteria and Actinobacteria contents were the highest in the HT group. Compared to the control group, the GD and HT groups had a higher abundance of Erysipelotrichia, Cyanobacteria, and _2 and lower levels of and . Further analysis of KEGG found that the "ABC transporter" metabolic pathway was highly correlated with the occurrence of GD and HT. COG analysis showed that the GD and HT groups were enriched in carbohydrate transport and metabolism compared to the healthy control group but not in amino acid transport and metabolism. Our data suggested that , , and could be used as potential markers to distinguish GD and HT from the healthy population and that "ABC transporter" metabolic pathway may be involved in the pathogenesis of GD and HT.
Topics: Autoantibodies; Feces; Gastrointestinal Microbiome; Graves Disease; Hashimoto Disease; Humans
PubMed: 35675824
DOI: 10.33073/pjm-2022-016 -
PloS One 2021Obesity is the cause of cardiovascular diseases and other diseases, leading to increased medical costs, and causing a great burden to individuals, families and society....
BACKGROUND
Obesity is the cause of cardiovascular diseases and other diseases, leading to increased medical costs, and causing a great burden to individuals, families and society. The prevalence of obesity is increasing and has become a global health problem. There is growing evidence that gut microbiota plays an important role in obesity. In this article, we revealed the differences in the gut microbiota between 21 people with obesity and 21 control subjects, and predicted the functional potential changes by 16S rRNA sequencing of the fecal bacteria of the subjects.
METHODS
The raw sequencing data of 21 healthy Beijing volunteers was downloaded from Microbial Genome Database System. Microbial 16S rRNA genes of 21 adults with obesity were sequenced on an Illumina MiSeq instrument and analyzed by using bioinformatics and statistical methods.
RESULTS
The diversity of gut microbiota in people with obesity decreased significantly. There were significant differences in gut microbiota between the Obesity and Control group at different levels. At the phylum level, Firmicutes, Bacteroidetes, Actinobacteria and Fusobacteria are significantly different between the Obesity and Control group. In people with obesity, the ratio of Firmicutes/Bacteroidetes decreased significantly. At the genus level, there were significant differences among the 16 major genera, of which four genera Prevotella, Megamonas, Fusobacterium and Blautia increased significantly in people with obesity, while the remaining 12 genera, Faecalibacterium, Lachnospiracea_incertae_sedis, Gemmiger and Clostridium XlVa, etc. decreased significantly. At the species level, nine species including Bacteroides uniformis and Prevotella copri had significant differences. Compared with the control group, subjects with obesity were abnormalities in 57 pathways, mainly in Carbohydrate metabolism and Lipid metabolism.
CONCLUSIONS
Overall, our study revealed differences in the gut microbiota between people with obesity and control subjects, providing novel target for the treatment of individuals with obesity.
Topics: Adult; Bacteroides; Dysbiosis; Gastrointestinal Microbiome; Humans; Male; Prevotella; RNA, Ribosomal, 16S
PubMed: 34375351
DOI: 10.1371/journal.pone.0255446 -
Scientific Reports Jun 2021This study was aimed to evaluate the differences in the composition of gut microbiota, tryptophan metabolites and short-chain fatty acids in feces between volunteers who...
This study was aimed to evaluate the differences in the composition of gut microbiota, tryptophan metabolites and short-chain fatty acids in feces between volunteers who frequently ate chicken and who frequently ate pork. Twenty male chicken-eaters and 20 male pork-eaters of 18 and 30 years old were recruited to collect feces samples for analyses of gut microbiota composition, short-chain fatty acids and tryptophan metabolites. Chicken-eaters had more diverse gut microbiota and higher abundance of Prevotella 9, Dialister, Faecalibacterium, Megamonas, and Prevotella 2. However, pork-eaters had higher relative abundance of Bacteroides, Faecalibacterium, Roseburia, Dialister, and Ruminococcus 2. In addition, chicken-eaters had high contents of skatole and indole in feces than pork-eaters, as well as higher contents of total short chain fatty acids, in particular for acetic acid, propionic acid, and branched chain fatty acids. The Spearman's correlation analysis revealed that the abundance of Prevotella 2 and Prevotella 9 was positively correlated with levels of fecal skatole, indole and short-chain fatty acids. Thus, intake of chicken diet may increase the risk of skatole- and indole-induced diseases by altering gut microbiota.
Topics: Adolescent; Adult; Animals; Bacteria; Chickens; Diet; Fatty Acids, Volatile; Feces; Feeding Behavior; Gastrointestinal Microbiome; Humans; Male; Meat; Pork Meat; RNA, Ribosomal, 16S; Swine; Tryptophan; Young Adult
PubMed: 34099832
DOI: 10.1038/s41598-021-91429-3 -
Frontiers in Cellular and Infection... 2022There is a growing body of evidence highlighting the significant role of gut microbiota in various pathologies. We performed a systematic review to review the different... (Review)
Review
There is a growing body of evidence highlighting the significant role of gut microbiota in various pathologies. We performed a systematic review to review the different microbiota involved in neuropsychiatric diseases. 50 studies (23 studies for autism spectrum disorders, 18 for major depression, and 9 for schizophrenia), representing 2,137 patients and 2,844 controls. Concerning the microbiota, the genera were the ones detected with the most frequent variation of their relatives abundance. We also assess the overlap between the different pathologies. This study provides new insights into the complex relationship between the brain and the gut and the implications in neuropsychiatric pathologies. The identification of unique signatures in neuropsychiatric diseases suggests new possibilities in targeted anti or probiotic treatment.
Topics: Autism Spectrum Disorder; Brain; Gastrointestinal Microbiome; Humans; Microbiota; Probiotics
PubMed: 35360098
DOI: 10.3389/fcimb.2022.831666 -
PloS One 2022Although some human studies have reported gut microbiome changes in individuals with Alzheimer's disease (AD) dementia or mild cognitive impairment (MCI), gut microbiome...
BACKGROUND
Although some human studies have reported gut microbiome changes in individuals with Alzheimer's disease (AD) dementia or mild cognitive impairment (MCI), gut microbiome alterations in preclinical AD, i.e., cerebral amyloidosis without cognitive impairment, is largely unknown.
OBJECTIVE
We aimed to identify gut microbial alterations associated with preclinical AD by comparing cognitively normal (CN) older adults with cerebral Aβ deposition (Aβ+ CN) and those without cerebral Aβ deposition (Aβ- CN).
METHODS
Seventy-eight CN older participants (18 Aβ+ CN and 60 Aβ- CN) were included, and all participants underwent clinical assessment and Pittsburg compound B-positron emission tomography. The V3-V4 region of the 16S rRNA gene of genomic DNA extracted from feces was amplified and sequenced to establish the microbial community.
RESULTS
Generalized linear model analysis revealed that the genera Megamonas (B = 3.399, q<0.001), Serratia (B = 3.044, q = 0.005), Leptotrichia (B = 5.862, q = 0.024) and Clostridium (family Clostridiaceae) (B = 0.788, q = 0.034) were more abundant in the Aβ+ CN group than the Aβ- CN group. In contrast, genera CF231 (B = -3.237, q< 0.001), Victivallis (B = -3.447, q = 0.004) Enterococcus (B = -2.044, q = 0.042), Mitsuokella (B = -2.119, q = 0.042) and Clostridium (family Erysipelotrichaceae) (B = -2.222, q = 0.043) were decreased in Aβ+ CN compared to Aβ- CN. Notably, the classification model including the differently abundant genera could effectively distinguish Aβ+ CN from Aβ- CN (AUC = 0.823).
CONCLUSION
Our findings suggest that specific alterations of gut bacterial taxa are related to preclinical AD, which means these changes may precede cognitive decline. Therefore, examining changes in the microbiome may be helpful in preclinical AD screening.
Topics: Humans; Animals; Aged; Gastrointestinal Microbiome; Alzheimer Disease; RNA, Ribosomal, 16S; Tomography, X-Ray Computed; Cognitive Dysfunction
PubMed: 36445883
DOI: 10.1371/journal.pone.0278276