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Cancer Medicine Sep 2023Aging is one of the factors leading to cancer. Gut microbiota is related to aging and colorectal cancer (CRC).
BACKGROUND
Aging is one of the factors leading to cancer. Gut microbiota is related to aging and colorectal cancer (CRC).
METHODS
A total of 11 metagenomic data sets related to CRC were collected from the R package curated Metagenomic Data. After batch effect correction, healthy individuals and CRC samples were divided into three age groups. Ggplot2 and Microbiota Process packages were used for visual description of species composition and PCA in healthy individuals and CRC samples. LEfSe analysis was performed for species relative abundance data in healthy/CRC groups according to age. Spearman correlation coefficient of age-differentiated bacteria in healthy individuals and CRC samples was calculated separately. Finally, the age prediction model and CRC risk prediction model were constructed based on the age-differentiated bacteria.
RESULTS
The structure and composition of the gut microbiota were significantly different among the three groups. For example, the abundance of Bacteroides vulgatus in the old group was lower than that in the other two groups, the abundance of Bacteroides fragilis increased with aging. In addition, seven species of bacteria whose abundance increases with aging were screened out. Furthermore, the abundance of pathogenic bacteria (Escherichia_coli, Butyricimonas_virosa, Ruminococcus_bicirculans, Bacteroides_fragilis and Streptococcus_vestibularis) increased with aging in CRCs. The abundance of probiotics (Eubacterium_eligens) decreased with aging in CRCs. The age prediction model for healthy individuals based on the 80 age-related differential bacteria and model of CRC patients based on the 58 age-related differential bacteria performed well, with AUC of 0.79 and 0.71, respectively. The AUC of CRC risk prediction model based on 45 disease differential bacteria was 0.83. After removing the intersection between the disease-differentiated bacteria and the age-differentiated bacteria from the healthy samples, the AUC of CRC risk prediction model based on remaining 31 bacteria was 0.8. CRC risk prediction models for each of the three age groups showed no significant difference in accuracy (young: AUC=0.82, middle: AUC=0.83, old: AUC=0.85).
CONCLUSION
Age as a factor affecting microbial composition should be considered in the application of gut microbiota to predict the risk of CRC.
Topics: Humans; Gastrointestinal Microbiome; Colorectal Neoplasms; Bacteria; Microbiota; Aging
PubMed: 37548332
DOI: 10.1002/cam4.6414 -
Microbial Genomics Jul 2023is prevalent in the intestines of humans and animals, and ambiguities have been reported regarding its relations with the development of diseases and host well-being....
is prevalent in the intestines of humans and animals, and ambiguities have been reported regarding its relations with the development of diseases and host well-being. We postulate the ambiguities of its function in different cases may be attributed to strain-level variability of genomic features of . We performed comparative genomic and pathogenicity prediction analysis on 152 filtered high-quality genomes, including 4 genomes of strains isolated from healthy adults in this study. The mean G+C content of genomes of was 42.73±0.33 mol%, and the mean genome size was 3.46±0.34 Mbp. Genome-wide evolutionary analysis revealed genomes were divided into three major phylogenetic clusters. Pan-core genome analysis revealed that there was a total of 28 072 predicted genes, and the core genes, soft-core genes, shell genes and cloud genes accounted for 3.74 % (1051/28 072), 1.75 % (491/28 072), 9.88 % (2774/28 072) and 84.63 % (23 756/28 072) of the total genes, respectively. The small proportion of core genes reflected the wide divergence among strains. We found certain coding sequences with determined health benefits (such as vitamin production and arsenic detoxification), whilst some had an implication of health adversity (such as sulfide dehydrogenase subunits). The functions of the majority of core genes were unknown. The most widespread genes functioning in antibiotic resistance and virulence are (tetracycline-resistance gene, present in 75 strains) and (capsular polysaccharide biosynthesis protein Cps4J encoding gene, detected in 3 genomes), respectively. Our results revealed genomic divergence and the existence of certain safety-relevant factors of . This study provides new insights for understanding the genomic features and health relevance of , and raises concerns regarding predicted prevalent pathogenicity and antibiotic resistance among most of the strains.
Topics: Adult; Animals; Humans; Ruminococcus; Phylogeny; Clostridiales; Genomics
PubMed: 37486746
DOI: 10.1099/mgen.0.001071 -
Gastroenterology Jun 2024Chronic visceral pain is one of the most common reasons for patients with gastrointestinal disorders, such as inflammatory bowel disease or disorders of brain-gut... (Review)
Review
Chronic visceral pain is one of the most common reasons for patients with gastrointestinal disorders, such as inflammatory bowel disease or disorders of brain-gut interaction, to seek medical attention. It represents a substantial burden to patients and is associated with anxiety, depression, reductions in quality of life, and impaired social functioning, as well as increased direct and indirect health care costs to society. Unfortunately, the diagnosis and treatment of chronic visceral pain is difficult, in part because our understanding of the underlying pathophysiologic basis is incomplete. In this review, we highlight recent advances in peripheral pain signaling and specific physiologic and pathophysiologic preclinical mechanisms that result in the sensitization of peripheral pain pathways. We focus on preclinical mechanisms that have been translated into treatment approaches and summarize the current evidence base for directing treatment toward these mechanisms of chronic visceral pain derived from clinical trials. The effective management of chronic visceral pain remains of critical importance for the quality of life of suffers. A deeper understanding of peripheral pain mechanisms is necessary and may provide the basis for novel therapeutic interventions.
Topics: Humans; Visceral Pain; Chronic Pain; Animals; Quality of Life; Signal Transduction
PubMed: 38325759
DOI: 10.1053/j.gastro.2024.01.045 -
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 -
BMC Genomics Jul 2023Snub-nosed monkeys are highly endangered primates and their population continues to decline with the habitat fragmentation. Artificial feeding and breeding is an...
BACKGROUND
Snub-nosed monkeys are highly endangered primates and their population continues to decline with the habitat fragmentation. Artificial feeding and breeding is an important auxiliary conservation strategy. Studies have shown that changes and imbalances in the gut microbiota often cause gastrointestinal problems in captive snub-nosed monkeys. Here, we compare the gut microbiota composition, diversity, and predicted metabolic function of three endangered species of snub-nosed monkeys (Rhinopithecus bieti, R. brelichi, and R. roxellana) under the same captive conditions to further our understanding of the microbiota of these endangered primates and inform captive conservation strategies. 16 S rRNA gene sequencing was performed on fecal samples from 15 individuals (R. bieti N = 5, R. brelichi N = 5, R. roxellana N = 5).
RESULTS
The results showed that the three Rhinopithecus species shared 24.70% of their amplicon sequence variants (ASVs), indicating that the composition of the gut microbiota varied among the three Rhinopithecus species. The phyla Firmicutes and Bacteroidetes represented 69.74% and 18.45% of the core microbiota. In particular, analysis of microbiota diversity and predicted metabolic function revealed a profound impact of host species on the gut microbiota. At the genus level, significant enrichment of cellulolytic genera including Rikenellaceae RC9 gut group, Ruminococcus, Christensenellaceae R7 group, UCG 004 from Erysipelatoclostridiaceae, and UCG 002 and UCG 005 from Oscillospiraceae, and carbohydrate metabolism including propionate and butyrate metabolic pathways in the gut of R. bieti indicated that R. bieti potentially has a stronger ability to use plant fibers as energy substances. Bacteroides, unclassified Muribaculaceae, Treponema, and unclassified Eubacterium coprostanoligenes group were significantly enriched in R. brelichi. Prevotella 9, unclassified Lachnospiraceae, and unclassified UCG 010 from Oscillospirales UCG 010 were significantly enriched in R. roxellana. Among the predicted secondary metabolic pathways, the glycan biosynthesis and metabolism had significantly higher relative abundance in the gut of R. brelichi and R. roxellana than in the gut of R. bieti. The above results suggest that different Rhinopithecus species may have different strategies for carbohydrate metabolism. The Principal coordinate analysis (PCoA) and Unweighted pair-group method with arithmetic mean (UPGMA) clustering tree revealed fewer differences between the gut microbiota of R. brelichi and R. roxellana. Correspondingly, no differences were detected in the relative abundances of functional genes between the two Rhinopithecus species.
CONCLUSION
Taken together, the study highlights that host species have an effect on the composition and function of the gut microbiota of snub-nosed monkeys. Therefore, the host species should be considered when developing nutritional strategies and investigating the effects of niche on the gut microbiota of snub-nosed monkeys.
Topics: Animals; Presbytini; Colobinae; Gastrointestinal Microbiome; Plant Breeding; Carbohydrate Metabolism; Bacteroidetes; China
PubMed: 37452294
DOI: 10.1186/s12864-023-09440-z -
BMC Pediatrics Sep 2023Children diagnosed with autism spectrum disorder (ASD) frequently suffer from persistent gastrointestinal symptoms, such as constipation and diarrhea. Various studies...
BACKGROUND
Children diagnosed with autism spectrum disorder (ASD) frequently suffer from persistent gastrointestinal symptoms, such as constipation and diarrhea. Various studies have highlighted differences in gut microbiota composition between individuals with ASD and healthy controls of similar ages. However, it's essential to recognize that these disparities may be influenced by cultural practices, dietary habits, and environmental factors.
METHODS
In this study, we collected fecal samples from both children diagnosed with ASD (n = 42) and healthy individuals (n = 41) residing in the southeastern coastal region of China. Subsequently, 16 S rRNA gene sequencing and advanced bioinformatics analyses were conducted to investigate the distinctive features of gut microbial communities within each group.
RESULTS
The ASD group consisted of 28 males and 14 females, with a median age of 5.8 years, while the control group included 25 males and 16 females, with a median age of 6.8 years. Among the 83 sequenced fecal samples, a total of 1031 operational taxonomic units (OTUs) were identified. These included 122 unique OTUs specific to the control group and 285 unique OTUs specific to the ASD group. Analyses of α-diversity and β-diversity unveiled significant differences in the abundance and composition of gut microbiota between the two groups. It was found that the dominant bacterial taxa in healthy individuals were UBA1819, Flavonifractor, and Bradyrhizobium. In contrast, the ASD group exhibited a prevalence of Streptococcus, Ruminococcus, and Ruminiclostridium. Further analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Clusters of Orthologous Groups (COG) showed significant differences in the metabolic functionalities of the gut microbiota between the two groups. Notably, the metabolic pathway related to alpha-linolenic acid (ALA) in the gut microbiota of the ASD group was notably diminished compared to the control group. Conversely, the ASD group demonstrated significantly elevated levels of metabolic pathways involving uncharacterized conserved proteins, aminoglycoside phosphotransferase, and inorganic pyrophosphatase compared to the control group.
CONCLUSIONS
Overall, these results confirm that there are significant differences in the gut microbiota structure between children with ASD and healthy controls in the southeast coastal region of China. This underscores the critical significance of delving into clinical interventions capable of mitigating the gastrointestinal and psychological symptoms encountered by children with ASD. A particularly encouraging path for such interventions lies in the realm of fecal microbiota transplantation, a prospect that merits deeper inquiry.
Topics: Female; Male; Child; Humans; Child, Preschool; Gastrointestinal Microbiome; Autism Spectrum Disorder; Microbiota; Anxiety; Constipation
PubMed: 37730588
DOI: 10.1186/s12887-023-04292-8 -
Scientific Reports Aug 2023A bidirectional communication exists between the brain and the gut, in which the gut microbiota influences cognitive function and vice-versa. Gut dysbiosis has been...
A bidirectional communication exists between the brain and the gut, in which the gut microbiota influences cognitive function and vice-versa. Gut dysbiosis has been linked to several diseases, including Alzheimer's disease and related dementias (ADRD). However, the relationship between gut dysbiosis and markers of cerebral small vessel disease (cSVD), a major contributor to ADRD, is unknown. In this cross-sectional study, we examined the connection between the gut microbiome, cognitive, and neuroimaging markers of cSVD in the Framingham Heart Study (FHS). Markers of cSVD included white matter hyperintensities (WMH), peak width of skeletonized mean diffusivity (PSMD), and executive function (EF), estimated as the difference between the trail-making tests B and A. We included 972 FHS participants with MRI scans, neurocognitive measures, and stool samples and quantified the gut microbiota composition using 16S rRNA sequencing. We used multivariable association and differential abundance analyses adjusting for age, sex, BMI, and education level to estimate the association between gut microbiota and WMH, PSMD, and EF measures. Our results suggest an increased abundance of Pseudobutyrivibrio and Ruminococcus genera was associated with lower WMH and PSMD (p values < 0.001), as well as better executive function (p values < 0.01). In addition, in both differential and multivariable analyses, we found that the gram-negative bacterium Barnesiella intestinihominis was strongly associated with markers indicating a higher cSVD burden. Finally, functional analyses using PICRUSt implicated various KEGG pathways, including microbial quorum sensing, AMP/GMP-activated protein kinase, phenylpyruvate, and β-hydroxybutyrate production previously associated with cognitive performance and dementia. Our study provides important insights into the association between the gut microbiome and cSVD, but further studies are needed to replicate the findings.
Topics: Humans; Cross-Sectional Studies; Dysbiosis; RNA, Ribosomal, 16S; Bacteria; AMP-Activated Protein Kinases; Cerebral Small Vessel Diseases
PubMed: 37604954
DOI: 10.1038/s41598-023-40872-5 -
Gut Microbes Dec 2023The gut microbiome is involved in the bi-directional relationship of the gut - brain axis. As most studies of this relationship are small and do not account for use of...
The gut microbiome is involved in the bi-directional relationship of the gut - brain axis. As most studies of this relationship are small and do not account for use of psychotropic drugs (PTDs), we explored the relations of the gut microbiome with several internalizing disorders, while adjusting for PTDs and other relevant medications, in 7,656 Lifelines participants from the Northern Netherlands (5,522 controls and 491 participants with at least one internalizing disorder). Disorders included dysthymia, major depressive disorder (MDD), any depressive disorder (AnyDep: dysthymia or MDD), generalized anxiety disorder (GAD) and any anxiety disorder (AnyAnx: GAD, social phobia and panic disorder). Compared to controls, 17 species were associated with depressive disorders and 3 were associated with anxiety disorders. Around 90% of these associations remained significant (FDR <0.05) after adjustment for PTD use, suggesting that the disorders, not PTD use, drove these associations. Negative associations were observed for the butyrate-producing bacteria in participants with AnyDep and for in AnyAnx participants, along with many others. Tryptophan and glutamate synthesis modules and the 3,4-Dihydroxyphenylacetic acid synthesis module (related to dopamine metabolism) were negatively associated with MDD and/or dysthymia. After additional adjustment for functional gastrointestinal disorders and irritable bowel syndrome, these relations remained either statistically (FDR <0.05) or nominally ( < 0.05) significant. Overall, multiple bacterial species and functional modules were associated with internalizing disorders, including gut - brain relevant components, while associations to PTD use were moderate. These findings suggest that internalizing disorders rather than PTDs are associated with gut microbiome differences relative to controls.
Topics: Humans; Depressive Disorder, Major; Depression; Gastrointestinal Microbiome; Anxiety Disorders; Anxiety; Psychotropic Drugs
PubMed: 38017662
DOI: 10.1080/19490976.2023.2281360 -
Nature Communications Oct 2023DddA-derived cytosine base editors (DdCBEs) greatly facilitated the basic and therapeutic research of mitochondrial DNA mutation diseases. Here we devise a saturated...
DddA-derived cytosine base editors (DdCBEs) greatly facilitated the basic and therapeutic research of mitochondrial DNA mutation diseases. Here we devise a saturated spacer library and successfully identify seven DddA homologs by performing high-throughput sequencing based screen. DddAs of Streptomyces sp. BK438 and Lachnospiraceae bacterium sunii NSJ-8 display high deaminase activity with a strong GC context preference, and DddA of Ruminococcus sp. AF17-6 is highly compatible to AC context. We also find that different split sites result in wide divergence on off-target activity and context preference of DdCBEs derived from these DddA homologs. Additionally, we demonstrate the orthogonality between DddA and DddI, and successfully minimize the nuclear off-target editing by co-expressing corresponding nuclear-localized DddI. The current study presents a comprehensive and unbiased strategy for screening and characterizing dsDNA cytidine deaminases, and expands the toolbox for mtDNA editing, providing additional insights for optimizing dsDNA base editors.
Topics: Gene Editing; Mitochondria; Mutation; DNA, Mitochondrial; Cytidine Deaminase; CRISPR-Cas Systems; Cytosine
PubMed: 37857619
DOI: 10.1038/s41467-023-42359-3 -
BMC Microbiology Apr 2024Obesity is a metabolic disorder closely associated with profound alterations in gut microbial composition. However, the dynamics of species composition and functional... (Meta-Analysis)
Meta-Analysis
Obesity is a metabolic disorder closely associated with profound alterations in gut microbial composition. However, the dynamics of species composition and functional changes in the gut microbiome in obesity remain to be comprehensively investigated. In this study, we conducted a meta-analysis of metagenomic sequencing data from both obese and non-obese individuals across multiple cohorts, totaling 1351 fecal metagenomes. Our results demonstrate a significant decrease in both the richness and diversity of the gut bacteriome and virome in obese patients. We identified 38 bacterial species including Eubacterium sp. CAG:274, Ruminococcus gnavus, Eubacterium eligens and Akkermansia muciniphila, and 1 archaeal species, Methanobrevibacter smithii, that were significantly altered in obesity. Additionally, we observed altered abundance of five viral families: Mesyanzhinovviridae, Chaseviridae, Salasmaviridae, Drexlerviridae, and Casjensviridae. Functional analysis of the gut microbiome indicated distinct signatures associated to obesity and identified Ruminococcus gnavus as the primary driver for function enrichment in obesity, and Methanobrevibacter smithii, Akkermansia muciniphila, Ruminococcus bicirculans, and Eubacterium siraeum as functional drivers in the healthy control group. Additionally, our results suggest that antibiotic resistance genes and bacterial virulence factors may influence the development of obesity. Finally, we demonstrated that gut vOTUs achieved a diagnostic accuracy with an optimal area under the curve of 0.766 for distinguishing obesity from healthy controls. Our findings offer comprehensive and generalizable insights into the gut bacteriome and virome features associated with obesity, with the potential to guide the development of microbiome-based diagnostics.
Topics: Humans; Gastrointestinal Microbiome; Metagenome; Obesity; Bacteria; Feces; Clostridiales; Akkermansia
PubMed: 38580930
DOI: 10.1186/s12866-024-03278-5