-
Frontiers in Cellular and Infection... 2022Aging is now the most profound risk factor for almost all non-communicable diseases. Studies have shown that probiotics play a specific role in fighting aging. We used...
Aging is now the most profound risk factor for almost all non-communicable diseases. Studies have shown that probiotics play a specific role in fighting aging. We used metagenomic sequencing to study the changes in gut microbes in different age groups and found that aging had the most significant effect on subjects' gut microbe structure. Our study divided the subjects (n=614) into two groups by using 50 years as the age cut-off point for the grouping. Compared with the younger group, several species with altered abundance and specific functional pathways were found in the older group. At the species level, the abundance of , , , , , and were increased in older individuals. They were positively correlated to the pathways responsible for lipopolysaccharide (LPS) biosynthesis and the degradation of short-chain fatty acids (SCFAs). On the contrary, the levels of , , and were decreased in the older group, which negatively correlated with the above pathways (p-value<0.05). Functional prediction revealed 92 metabolic pathways enriched in the older group significantly higher than those in the younger group (p-value<0.05), especially pathways related to LPS biosynthesis and the degradation of SCFAs. Additionally, we established a simple non-invasive model of aging, nine species (, , , , , , , , and ) were selected to construct the model. The area under the receiver operating curve (AUC) of the model implied that supplemented probiotics might influence aging. We discuss the features of the aging microbiota that make it more amenable to pre-and probiotic interventions. We speculate these metabolic pathways of gut microbiota can be associated with the immune status and inflammation of older adults. Health interventions that promote a diverse microbiome could influence the health of older adults.
Topics: Aged; Bacteroides; Bacteroides fragilis; Bacteroidetes; Bifidobacterium longum; Clostridiales; Escherichia coli; Feces; Firmicutes; Gastrointestinal Microbiome; Humans; Lipopolysaccharides
PubMed: 35959379
DOI: 10.3389/fcimb.2022.877914 -
Microbiology Resource Announcements Dec 2021Here, we report the complete genome sequence of Megamonas funiformis strain 1CBH44, which was isolated from the feces of a healthy Japanese person. The genome consists...
Here, we report the complete genome sequence of Megamonas funiformis strain 1CBH44, which was isolated from the feces of a healthy Japanese person. The genome consists of a circular chromosome (2,310,709 bp, with a GC content of 31.5%) and possesses 2,170 putative protein-coding genes, 18 rRNA genes, and 54 tRNA genes.
PubMed: 34854722
DOI: 10.1128/MRA.00785-21 -
Biomedicine & Pharmacotherapy =... Jan 2022Metformin modifies the gut microbiome in type 2 diabetes and gastrointestinal tolerance to metformin could be mediated by the gut microbiome.
OBJECTIVE
Metformin modifies the gut microbiome in type 2 diabetes and gastrointestinal tolerance to metformin could be mediated by the gut microbiome.
METHODS
We enrolled 35 patients with type 2 diabetes not receiving treatment with metformin due to suspected gastrointestinal intolerance. Metformin was reintroduced at 425 mg, increasing 425 mg every two weeks until reaching 1700 mg per day. According to the occurrence of metformin-related gastrointestinal symptoms, patients were classified into three groups: early intolerance, non-tolerant, and tolerant. Gut microbiota was profiled with 16 S rRNA. This sequencing aimed to determine the differences in the baseline gut microbiota in all groups and prospectively in the tolerant and non-tolerant groups.
RESULTS
The classification resulted in 15 early intolerant, 10 tolerant, and 10 non-tolerant subjects. Early tolerance was characterized by a higher abundance of Subdoligranulum; while Veillonella and Serratia were higher in the non-tolerant group. The tolerant group showed enrichment of Megamonas, Megamonas rupellensis, and Phascolarctobacterium spp; Ruminococcus gnavus was lower in the longitudinal analysis. At the end point Prevotellaceae, Prevotella stercorea, Megamonas funiformis, Bacteroides xylanisolvens, and Blautia producta had a higher relative abundance in the tolerant group compared to the non-tolerant group. Subdoligranulum, Ruminococcus torques_1, Phascolarctobacterium faecium, and Eubacterium were higher in the non-tolerant group. The PICRUSt analysis showed a lower activity of the amino acid biosynthesis pathways and a higher sugar degradation pathway in the intolerant groups.
CONCLUSIONS
Gut microbiota of subjects with gastrointestinal intolerance depicted taxonomic and functional differences compared to tolerant patients, and this changed differently after metformin administration.
Topics: Aged; Diabetes Mellitus, Type 2; Female; Follow-Up Studies; Gastrointestinal Microbiome; Humans; Hypoglycemic Agents; Male; Metformin; Middle Aged; Prospective Studies
PubMed: 34844104
DOI: 10.1016/j.biopha.2021.112448 -
Annals of Palliative Medicine Oct 2021Type 2 diabetes mellitus (T2DM) is a major social and public health problem which may be induced by intestinal flora imbalance through inflammatory response, and the...
BACKGROUND
Type 2 diabetes mellitus (T2DM) is a major social and public health problem which may be induced by intestinal flora imbalance through inflammatory response, and the specific mechanism remains unclear. In this study, we aim to explore the interaction network of intestinal flora and cell inflammation in T2DM.
METHODS
This a case-control study. Patients with T2DM was the case group and healthy people as control. The differences of cytokine expression levels between patients with T2DM and healthy controls were assessed by using flow cytometry. The diversity and abundance of intestinal flora were evaluated by using 16S rRNA three-generation full-length sequencing technology.
RESULTS
A total of 29 patients with T2DM and 28 healthy controls were included for analysis. Compared with the healthy control group, the expression levels of plasma cytokine interleukin-2 (IL-2) (P=0.0000006), IL-6 (P=0.000193), tumor necrosis factor α (TNF-α) (P=0.016), interferon-γ (IFN-γ) (P=0.000036) and interleukin-17 (IL-17) (P=0.004) were significantly up-regulated in T2DM patients, and the abundance of Megamonas_funiformis (P=0.0016) and Escherichia (P=0.049) in the intestine were significantly increased. In contrast, the abundance of Bacteroides_stercoris (P=0.0068), Bacteroides_uniformis (P=0.033), and Phascolarctobacterium_faecium (P=0.033) were decreased in T2DM patients. Further, differentially expressed Escherichia had a positive correlation with IFN-γ (r=0.73) by Pearson correlation analysis.
CONCLUSIONS
The interaction network between the intestinal bacteria Escherichia and the cytokine IFN-γ may drive inflammation in visceral adipose tissue (VAT), indicating insulin signal transduction can be inhibited in adipocytes to induce insulin resistance.
Topics: Case-Control Studies; Diabetes Mellitus, Type 2; Escherichia; Humans; Interferon-gamma; Intestines; RNA, Ribosomal, 16S
PubMed: 34763485
DOI: 10.21037/apm-21-2318 -
BMC Medicine Jul 2021Myasthenia gravis (MG) is an acquired immune-mediated disorder of the neuromuscular junction that causes fluctuating skeletal muscle weakness and fatigue. Pediatric MG...
BACKGROUND
Myasthenia gravis (MG) is an acquired immune-mediated disorder of the neuromuscular junction that causes fluctuating skeletal muscle weakness and fatigue. Pediatric MG and adult MG have many different characteristics, and current MG diagnostic methods for children are not quite fit. Previous studies indicate that alterations in the gut microbiota may be associated with adult MG. However, it has not been determined whether the gut microbiota are altered in pediatric MG patients.
METHODS
Our study recruited 53 pediatric MG patients and 46 age- and gender-matched healthy controls (HC). We sequenced the fecal samples of recruited individuals using whole-genome shotgun sequencing and analyzed the data with in-house bioinformatics pipeline.
RESULTS
We built an MG disease classifier based on the abundance of five species, Fusobacterium mortiferum, Prevotella stercorea, Prevotella copri, Megamonas funiformis, and Megamonas hypermegale. The classifier obtained 94% area under the curve (AUC) in cross-validation and 84% AUC in the independent validation cohort. Gut microbiome analysis revealed the presence of human adenovirus F/D in 10 MG patients. Significantly different pathways and gene families between MG patients and HC belonged to P. copri, Clostridium bartlettii, and Bacteroides massiliensis. Based on functional annotation, we found that the gut microbiome affects the production of short-chain fatty acids (SCFAs), and we confirmed the decrease in SCFA levels in pediatric MG patients via serum tests.
CONCLUSIONS
The study indicated that altered fecal microbiota might play vital roles in pediatric MG's pathogenesis by reducing SCFAs. The microbial markers might serve as novel diagnostic methods for pediatric MG.
Topics: Adult; Bacteroides; Child; Clostridiales; Feces; Firmicutes; Fusobacterium; Gastrointestinal Microbiome; Humans; Metagenome; Myasthenia Gravis; Prevotella; RNA, Ribosomal, 16S
PubMed: 34233671
DOI: 10.1186/s12916-021-02034-0 -
Frontiers in Oncology 2020Although increasing evidences showed a correlation between cholecystectomy and the prevalence rate of colorectal cancer (CRC), and shed light on gut microbiota in...
Although increasing evidences showed a correlation between cholecystectomy and the prevalence rate of colorectal cancer (CRC), and shed light on gut microbiota in colorectal pathogenesis, only a few studies focused on microbial alterations after cholecystectomy, and its sequent role in carcinogenesis and progression of CRC has not been reported. Thus, we aimed to investigate the bacterial alterations and tried to clarify their clinical significance. 104 subjects were enrolled and divided into post-cholecystectomy patients (PC, = 52) and healthy controls (HC, = 52). To investigate the bacterial role in carcinogenesis, PC patients were further separated into preCA_CRC (patients with precancerous lesions and/or CRC, = 9) and non-CA (patients without precancerous lesions and CRC, = 43) based on the histopathology. Qualified stool samples were collected for 16S rRNA gene sequencing to analyze the bacterial profile. Our data showed noteworthy compositional and abundant alterations of bacterial microbiota in PC patients, characterized as , and remarkably increased; , and significantly decreased. Additionally, the duration after cholecystectomy was the critical factor that affected bacterial composition. Machine learning-based analysis showed a pivotal role of in discriminating PC from HC subjects and involving in the progression of CRC. The bacterial dysbiosis may associate with CRC in PC patients, and the duration after cholecystectomy was highlighted as an important factor. Altered bacterial microbiota was likely to play a pivotal role in related-disease in the long-term follow-up of PC patients.
PubMed: 32903396
DOI: 10.3389/fonc.2020.01418 -
Microbiology Resource Announcements Apr 2020We announce the complete genome sequence of JCM 14723 (YIT 11815). The genome consists of a circular chromosome (2,522,577 bp, 31.5% G+C content) and a plasmid of...
We announce the complete genome sequence of JCM 14723 (YIT 11815). The genome consists of a circular chromosome (2,522,577 bp, 31.5% G+C content) and a plasmid of 46,189 bp (29.4% G+C content). The genome was predicted to contain 6 rRNA operons, 53 tRNA genes, and 2,440 protein-coding sequences.
PubMed: 32299874
DOI: 10.1128/MRA.00142-20 -
Frontiers in Neuroscience 2019Multiple system atrophy (MSA) is a fatal neurodegenerative disease, and the pathogenesis is still quite challenging. Emerging evidence has shown that the...
Multiple system atrophy (MSA) is a fatal neurodegenerative disease, and the pathogenesis is still quite challenging. Emerging evidence has shown that the brain-gut-microbiota axis served a pivotal role in neurological diseases; however, researches utilizing metagenomic sequencing to analyze the alteration in gut microbiota of MSA patients were quite rare. Here, we carried out metagenomic sequencing in feces of 15 MSA patients and 15 healthy controls, to characterize the alterations in gut microbial composition and function of MSA patients in mainland China. The results showed that gut microbial community of MSA patients was significantly different from healthy controls, characterized by increased genus and species , , , , and , while decreased genera , , , and and species , , , , , and . Further, functional analysis based on the KEGG database revealed aberrant functional pathways in fecal microbiome of MSA patients. In conclusion, our findings provided evidence for dysbiosis in gut microbiota of Chinese MSA cohorts and helped develop new testable hypotheses on pathophysiology of MSA.
PubMed: 31680836
DOI: 10.3389/fnins.2019.01102 -
Genome Announcements Jan 2018In this article, we present the draft genome sequence of strain Marseille-P3344, isolated from a human fecal sample. The genome described here is composed of...
In this article, we present the draft genome sequence of strain Marseille-P3344, isolated from a human fecal sample. The genome described here is composed of 2,464,704 nucleotides, with 2,230 protein-coding genes and 76 RNA genes.
PubMed: 29326224
DOI: 10.1128/genomeA.01459-17 -
Journal of Microbiology and... Aug 2014The fecal microbiotas were investigated in 13 healthy Thai subjects using polymerase chain reaction denaturing gradient gel electrophoresis (PCR-DGGE). Among the 186 DNA... (Comparative Study)
Comparative Study
The fecal microbiotas were investigated in 13 healthy Thai subjects using polymerase chain reaction denaturing gradient gel electrophoresis (PCR-DGGE). Among the 186 DNA bands detected on the polyacrylamide gel, 37 bands were identified as representing 11 species: Bacteroides thetaiotaomicron, Bacteroides ovatus, Bacteroides uniformis, Bacteroides vulgatus, Clostridium colicanis, Eubacterium eligenes, E. rectale, Faecalibacterium prausnitzii, Megamonas funiformis, Prevotella copri, and Roseburia intestinalis, belonging mainly to the groups of Bacteroides, Prevotella, Clostridium, and F. prausnitzii. A dendrogram of the PCR-DGGE divided the subjects; vegetarians and non-vegetarians. The fecal microbiotas were also analyzed using a quantitative real-time PCR focused on Bacteroides, Bifidobacterium, Enterobacteriaceae, Clostrium coccoides-Eubacterium rectale, C. leptum, Lactobacillus, and Prevotella. The nonvegetarian and vegetarian subjects were found to have significant differences in the high abundance of the Bacteroides and Prevotella genera, respectively. No significant differences were found in the counts of Bifidabacterium, Enterobacteriaceae, C. coccoides-E. rectale group, C. leptum group, and Lactobacillus. Therefore, these findings on the microbiota of healthy Thais consuming different diets could provide helpful data for predicting the health of South East Asians with similar diets.
Topics: Asian People; Bacteria; Biota; Denaturing Gradient Gel Electrophoresis; Diet, Vegetarian; Feces; Humans; Real-Time Polymerase Chain Reaction
PubMed: 24743571
DOI: 10.4014/jmb.1310.10043