-
Microbiome Sep 2023Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a cerebral small vessel disease that carries mutations in NOTCH3....
BACKGROUND
Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a cerebral small vessel disease that carries mutations in NOTCH3. The clinical manifestations are influenced by genetic and environmental factors that may include gut microbiome.
RESULTS
We investigated the fecal metagenome, fecal metabolome, serum metabolome, neurotransmitters, and cytokines in a cohort of 24 CADASIL patients with 28 healthy household controls. The integrated-omics study showed CADASIL patients harbored an altered microbiota composition and functions. The abundance of bacterial coenzyme A, thiamin, and flavin-synthesizing pathways was depleted in patients. Neurotransmitter balance, represented by the glutamate/GABA (4-aminobutanoate) ratio, was disrupted in patients, which was consistent with the increased abundance of two major GABA-consuming bacteria, Megasphaera elsdenii and Eubacterium siraeum. Essential inflammatory cytokines were significantly elevated in patients, accompanied by an increased abundance of bacterial virulence gene homologs. The abundance of patient-enriched Fusobacterium varium positively correlated with the levels of IL-1β and IL-6. Random forest classification based on gut microbial species, serum cytokines, and neurotransmitters showed high predictivity for CADASIL with AUC = 0.89. Targeted culturomics and mechanisms study further showed that patient-derived F. varium infection caused systemic inflammation and behavior disorder in Notch3 mice potentially via induction of caspase-8-dependent noncanonical inflammasome activation in macrophages.
CONCLUSION
These findings suggested the potential linkage among the brain-gut-microbe axis in CADASIL. Video Abstract.
Topics: Animals; Mice; CADASIL; Gastrointestinal Microbiome; Mental Disorders; Cytokines; gamma-Aminobutyric Acid
PubMed: 37684694
DOI: 10.1186/s40168-023-01638-3 -
Frontiers in Microbiology 2023Gut microbiota plays an important role in colorectal cancer (CRC) pathogenesis through microbes and their metabolites, while oral pathogens are the major components of...
OBJECTIVE
Gut microbiota plays an important role in colorectal cancer (CRC) pathogenesis through microbes and their metabolites, while oral pathogens are the major components of CRC-associated microbes. Multiple studies have identified gut and fecal microbiome-derived biomarkers for precursors lesions of CRC detection. However, few studies have used salivary samples to predict colorectal polyps. Therefore, in order to find new noninvasive colorectal polyp biomarkers, we searched into the differences in fecal and salivary microbiota between patients with colorectal polyps and healthy controls.
METHODS
In this case-control study, we collected salivary and fecal samples from 33 patients with colorectal polyps (CP) and 22 healthy controls (HC) between May 2021 and November 2022. All samples were sequenced using full-length 16S rRNA sequencing and compared with the Nucleotide Sequence Database. The salivary and fecal microbiota signature of colorectal polyps was established by alpha and beta diversity, Linear discriminant analysis Effect Size (LEfSe) and random forest model analysis. In addition, the possibility of microbiota in identifying colorectal polyps was assessed by Receiver Operating Characteristic Curve (ROC).
RESULTS
In comparison to the HC group, the CP group's microbial diversity increased in saliva and decreased in feces ( < 0.05), but there was no significantly difference in microbiota richness ( > 0.05). The principal coordinate analysis revealed significant differences in β-diversity of salivary and fecal microbiota between the CP and HC groups. Moreover, LEfSe analysis at the species level identified and as the major contributors to the salivary microbiota, and and to the fecal microbiota of patients with polyps. Salivary and fecal bacterial biomarkers showed Area Under ROC Curve of 0.8167 and 0.8051, respectively, which determined the potential of diagnostic markers in distinguishing patients with colorectal polyps from controls, and it increased to 0.8217 when salivary and fecal biomarkers were combined.
CONCLUSION
The composition and diversity of the salivary and fecal microbiota were significantly different in colorectal polyp patients compared to healthy controls, with an increased abundance of harmful bacteria and a decreased abundance of beneficial bacteria. A promising non-invasive tool for the detection of colorectal polyps can be provided by potential biomarkers based on the microbiota of the saliva and feces.
PubMed: 37655344
DOI: 10.3389/fmicb.2023.1182346 -
Microbiome Nov 2023The mechanism of microbiota assembly is one of the main problems in microbiome research, which is also the primary theoretical basis for precise manipulation of...
BACKGROUND
The mechanism of microbiota assembly is one of the main problems in microbiome research, which is also the primary theoretical basis for precise manipulation of microbial communities. Bacterial quorum sensing (QS), as the most common means for bacteria to exchange information and interactions, is characterized by universality, specificity, and regulatory power, which therefore may influence the assembly processes of human microbiota. However, the regulating role of QS in microbiota assembly is rarely reported. In this study, we developed an optimized in vitro oral biofilm microbiota assembling (OBMA) model to simulate the time-series assembly of oral biofilm microbiota (OBM), by which to excavate the QS network and its regulating power in the process.
RESULTS
By using the optimized OBMA model, we were able to restore the assembly process of OBM and generate time-series OBM metagenomes of each day. We discovered a total of 2291 QS protein homologues related to 21 QS pathways. Most of these pathways were newly reported and sequentially enriched during OBM assembling. These QS pathways formed a comprehensive longitudinal QS network that included successively enriched QS hubs, such as Streptococcus, Veillonella-Megasphaera group, and Prevotella-Fusobacteria group, for information delivery. Bidirectional cross-talk among the QS hubs was found to play critical role in the directional turnover of microbiota structure, which in turn, influenced the assembly process. Subsequent QS-interfering experiments accurately predicted and experimentally verified the directional shaping power of the longitudinal QS network in the assembly process. As a result, the QS-interfered OBM exhibited delayed and fragile maturity with prolonged membership of Streptococcus and impeded membership of Prevotella and Fusobacterium.
CONCLUSION
Our results revealed an unprecedented longitudinal QS network during OBM assembly and experimentally verified its power in predicting and manipulating the assembling process. Our work provides a new perspective to uncover underlying mechanism in natural complex microbiota assembling and a theoretical basis for ultimately precisely manipulating human microbiota through intervention in the QS network. Video Abstract.
Topics: Humans; Quorum Sensing; Bacterial Proteins; Bacteria; Biofilms; Streptococcus; Microbiota
PubMed: 37926838
DOI: 10.1186/s40168-023-01699-4 -
Frontiers in Cellular and Infection... 2023Immunoglobulin G4 (IgG4) is a member of the human immunoglobulin G (IgG) subclass, a protein involved in immunity to pathogens and the body's resistance system....
INTRODUCTION
Immunoglobulin G4 (IgG4) is a member of the human immunoglobulin G (IgG) subclass, a protein involved in immunity to pathogens and the body's resistance system. IgG4-related diseases (IgG4-RD) are intractable diseases in which IgG4 levels in the blood are elevated, causing inflammation in organs such as the liver, pancreas, and salivary glands. IgG4-RD are known to be more prevalent in males than in females, but the etiology remains to be elucidated. This study was conducted to investigate the relationship between gut microbiota (GM) and serum IgG4 levels in the general population.
METHODS
In this study, the relationship between IgG4 levels and GM evaluated in male and female groups of the general population using causal inference. The study included 191 men and 207 women aged 40 years or older from Shika-machi, Ishikawa. GM DNA was analyzed for the 16S rRNA gene sequence using next-generation sequencing. Participants were bifurcated into high and low IgG4 groups, depending on median serum IgG4 levels.
RESULTS
ANCOVA, Tukey's HSD, linear discriminant analysis effect size, least absolute shrinkage and selection operator logistic regression model, and correlation analysis revealed that , , , and group were associated with IgG4 levels in women, while , group, , 1, and were associated with IgG4 levels in men. Linear non-Gaussian acyclic model indicated three genera, , group, and , and showed a presumed causal association with IgG4 levels in women.
DISCUSSION
This differential impact of the GM on IgG4 levels based on sex is a novel and intriguing finding.
Topics: Humans; Male; Female; Gastrointestinal Microbiome; Immunoglobulin G4-Related Disease; RNA, Ribosomal, 16S; Salivary Glands; Immunoglobulin G
PubMed: 37908763
DOI: 10.3389/fcimb.2023.1272398 -
Trends in Microbiology May 2024Maintaining a healthy cervicovaginal microbiome (CVM) is vital for women's wellbeing; it is dependent primarily on Lactobacillus dominance. Microbiome imbalances, driven...
Maintaining a healthy cervicovaginal microbiome (CVM) is vital for women's wellbeing; it is dependent primarily on Lactobacillus dominance. Microbiome imbalances, driven by Megasphaera species, contribute to infections and disease. Comprehensive research into Megasphaera biology and interventions is crucial for personalized women's healthcare, and additional efforts are required to mitigate the risks posed by cervicovaginal dysbiosis.
PubMed: 38777699
DOI: 10.1016/j.tim.2024.04.015 -
Journal of Translational Medicine Aug 2023For many years, the role of the microbiome in tumor progression, particularly the tumor microbiome, was largely overlooked. The connection between the tumor microbiome...
Weighted gene coexpression network analysis and machine learning reveal oncogenome associated microbiome plays an important role in tumor immunity and prognosis in pan-cancer.
BACKGROUND
For many years, the role of the microbiome in tumor progression, particularly the tumor microbiome, was largely overlooked. The connection between the tumor microbiome and the tumor genome still requires further investigation.
METHODS
The TCGA microbiome and genome data were obtained from Haziza et al.'s article and UCSC Xena database, respectively. Separate WGCNA networks were constructed for the tumor microbiome and genomic data after filtering the datasets. Correlation analysis between the microbial and mRNA modules was conducted to identify oncogenome associated microbiome module (OAM) modules, with three microbial modules selected for each tumor type. Reactome analysis was used to enrich biological processes. Machine learning techniques were implemented to explore the tumor type-specific enrichment and prognostic value of OAM, as well as the ability of the tumor microbiome to differentiate TP53 mutations.
RESULTS
We constructed a total of 182 tumor microbiome and 570 mRNA WGCNA modules. Our results show that there is a correlation between tumor microbiome and tumor genome. Gene enrichment analysis results suggest that the genes in the mRNA module with the highest correlation with the tumor microbiome group are mainly enriched in infection, transcriptional regulation by TP53 and antigen presentation. The correlation analysis of OAM with CD8+ T cells or TAM1 cells suggests the existence of many microbiota that may be involved in tumor immune suppression or promotion, such as Williamsia in breast cancer, Biostraticola in stomach cancer, Megasphaera in cervical cancer and Lottiidibacillus in ovarian cancer. In addition, the results show that the microbiome-genome prognostic model has good predictive value for short-term prognosis. The analysis of tumor TP53 mutations shows that tumor microbiota has a certain ability to distinguish TP53 mutations, with an AUROC value of 0.755. The tumor microbiota with high importance scores are Corallococcus, Bacillus and Saezia. Finally, we identified a potential anti-cancer microbiota, Tissierella, which has been shown to be associated with improved prognosis in tumors including breast cancer, lung adenocarcinoma and gastric cancer.
CONCLUSION
There is an association between the tumor microbiome and the tumor genome, and the existence of this association is not accidental and could change the landscape of tumor research.
Topics: Female; Humans; Prognosis; Gene Regulatory Networks; Breast Neoplasms; Ovarian Neoplasms; RNA, Messenger
PubMed: 37573394
DOI: 10.1186/s12967-023-04411-0 -
Frontiers in Cellular and Infection... 2023Cerebral small vessel disease (CSVD) is a cluster of microvascular disorders with unclear pathological mechanisms. The microbiota-gut-brain axis is an essential...
BACKGROUND
Cerebral small vessel disease (CSVD) is a cluster of microvascular disorders with unclear pathological mechanisms. The microbiota-gut-brain axis is an essential regulatory mechanism between gut microbes and their host. Therefore, the compositional and functional gut microbiota alterations lead to cerebrovascular disease pathogenesis. The current study aims to determine the alteration and clinical value of the gut microbiota in CSVD patients.
METHODS
Sixty-four CSVD patients and 18 matched healthy controls (HCs) were included in our study. All the participants underwent neuropsychological tests, and the multi-modal magnetic resonance imaging depicted the changes in brain structure and function. Plasma samples were collected, and the fecal samples were analyzed with 16S rRNA gene sequencing.
RESULTS
Based on the alpha diversity analysis, the CSVD group had significantly decreased Shannon and enhanced Simpson compared to the HC group. At the genus level, there was a significant increase in the relative abundances of Parasutterella, Anaeroglobus, Megasphaera, Akkermansia, Collinsella, and Veillonella in the CSVD group. Moreover, these genera with significant differences in CSVD patients revealed significant correlations with cognitive assessments, plasma levels of the blood-brain barrier-/inflammation-related indexes, and structural/functional magnetic resonance imaging changes. Functional prediction demonstrated that lipoic acid metabolism was significantly higher in CSVD patients than HCs. Additionally, a composite biomarker depending on six gut microbiota at the genus level displayed an area under the curve of 0.834 to distinguish CSVD patients from HCs using the least absolute shrinkage and selection operator (LASSO) algorithm.
CONCLUSION
The evident changes in gut microbiota composition in CSVD patients were correlated with clinical features and pathological changes of CSVD. Combining these gut microbiota using the LASSO algorithm helped identify CSVD accurately.
Topics: Humans; Gastrointestinal Microbiome; RNA, Ribosomal, 16S; Brain; Magnetic Resonance Imaging; Cerebral Small Vessel Diseases
PubMed: 37496806
DOI: 10.3389/fcimb.2023.1231541 -
Molecular Neurobiology Nov 2023Depression is one of the complications in patients with polycystic ovary syndrome (PCOS) that leads to considerable mental health. Accumulating evidence suggests that...
Depression is one of the complications in patients with polycystic ovary syndrome (PCOS) that leads to considerable mental health. Accumulating evidence suggests that human gut microbiomes are associated with the progression of PCOS and depression. However, whether microbiota influences depression development in PCOS patients is still uncharacterized. In this study, we employed metagenomic sequencing and transcriptome sequencing (RNA-seq) to profile the composition of the fecal microbiota and gene expression of peripheral blood mononuclear cells in depressed women with PCOS (PCOS-DP, n = 27) in comparison to mentally healthy women with PCOS (PCOS, n = 18) and compared with healthy control (HC, n = 27) and patients with major depressive disorder (MDD, n = 29). Gut microbiota assessment revealed distinct patterns in the relative abundance in the PCOS-DP compared to HC, MDD, and PCOS groups. Several gut microbes exhibited uniquely and significantly higher abundance in the PCOS-DP compared to PCOS patients, inducing EC Ruminococcus torques, Coprococcus comes, Megasphaera elsdenii, Acidaminococcus intestini, and Barnesiella viscericola. Bacteroides eggerthii was a potential gut microbial biomarker for the PCOS-DP. RNA-seq profiling identified that 35 and 37 genes were significantly elevated and downregulated in the PCOS-DP, respectively. The enhanced differential expressed genes (DEGs) in the PCOS-DP were enriched in pathways involved in signal transduction and endocrine and metabolic diseases, whereas several lipid metabolism pathways were downregulated. Intriguingly, genes correlated with the gut microbiota were found to be significantly enriched in pathways of neurodegenerative diseases and the immune system, suggesting that changes in the microbiota may have a systemic impact on the expression of neurodegenerative diseases and immune genes. Gut microbe-related DEGs of CREB3L3 and CCDC173 were possible molecular biomarkers and therapeutic targets of women with PCOS-DP. Our multi-omics data indicate shifts in the gut microbiome and host gene regulation in PCOS patients with depression, which is of possible etiological and diagnostic importance.
PubMed: 37995075
DOI: 10.1007/s12035-023-03744-7 -
Journal of the Science of Food and... Oct 2023Mycoplasma hyorhinis is a prevalent respiratory pathogen in swine, causing significant economic loss to pig producers. There is growing evidence that respiratory...
BACKGROUND
Mycoplasma hyorhinis is a prevalent respiratory pathogen in swine, causing significant economic loss to pig producers. There is growing evidence that respiratory pathogen infections have a large impact on intestinal microecology. To study the effect of M. hyorhinis infection on gut microbial composition and metabolome profile, pigs were infected with M. hyorhinis. Metagenomic sequencing analysis was performed of fecal samples and a liquid chromatography/tandem mass spectrometry (LC-MS/MS) analysis of gut digesta was made.
RESULTS
Pigs infected with M. hyorhinis had enriched Sutterella and Mailhella, and depleted Dechloromonas, Succinatimonas, Campylobacter, Blastocystis, Treponema, and Megasphaera. The pigs infected with M. hyorhinis also had greater abundances of bacterium_0_1xD8_71, Ruminococcus_sp__CAG_353, Firmicutes_bacterium_CAG_194, Firmicutes_bacterium_CAG_534, bacterium_1xD42_87, and lower abundances of Chlamydia_suis, Megasphaera_elsdenii, Treponema_porcinum, Bacteroides_sp__CAG_1060, Faecalibacterium_prausnitzii. Metabolomic analysis revealed that some lipids and lipid-like molecules increased in the small intestine, whereas most lipids and lipid-like molecule metabolites decreased in the large intestine. These altered metabolites induce changes in intestinal sphingolipid metabolism, amino acid metabolism, and thiamine metabolism.
CONCLUSION
These findings demonstrate that infection with M. hyorhinis can alter the gut microbial composition and metabolite structure in pigs, which may further affect amino acid metabolism and lipid metabolism in the intestine. © 2023 Society of Chemical Industry.
Topics: Swine; Animals; Mycoplasma hyorhinis; Mycoplasma Infections; Gastrointestinal Microbiome; Swine Diseases; Chromatography, Liquid; Tandem Mass Spectrometry; Metabolome; Amino Acids; Lipids
PubMed: 37145100
DOI: 10.1002/jsfa.12690 -
Scientific Reports Nov 2023Crohn's disease (CD) is a chronic inflammatory bowel disease. An imbalanced microbiome (dysbiosis) can predispose to many diseases including CD. The role of oral...
Crohn's disease (CD) is a chronic inflammatory bowel disease. An imbalanced microbiome (dysbiosis) can predispose to many diseases including CD. The role of oral dysbiosis in CD is poorly understood. We aimed to explore microbiome signature and dysbiosis of the salivary microbiome in CD patients, and correlate microbiota changes to the level of inflammation. Saliva samples were collected from healthy controls (HC) and CD patients (n = 40 per group). Salivary microbiome was analyzed by sequencing the entire 16S rRNA gene. Inflammatory biomarkers (C-reactive protein and calprotectin) were measured and correlated with microbiome diversity. Five dominant species were significantly enriched in CD, namely Veillonella dispar, Megasphaera stantonii, Prevotella jejuni, Dolosigranulum pigrum and Lactobacillus backii. Oral health had a significant impact on the microbiome since various significant features were cariogenic as Streptococcus mutans or periopathogenic such as Fusobacterium periodonticum. Furthermore, disease activity, duration and frequency of relapses impacted the oral microbiota. Treatment with monoclonal antibodies led to the emergence of a unique species called Simonsiella muelleri. Combining immunomodulatory agents with monoclonal antibodies significantly increased multiple pathogenic species such as Salmonella enterica, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa. Loss of diversity in CD was shown by multiple diversity indices. There was a significant negative correlation between gut inflammatory biomarkers (particularly calprotectin) and α-diversity, suggesting more inflammation associated with diversity loss in CD. Salivary dysbiosis was evident in CD patients, with unique microbiota signatures and perturbed species that can serve as disease biomarkers or potential targets for microbiota modulation. The interplay of various factors collectively contributed to dysbiosis, although each factor probably had a unique effect on the microbiome. The emergence of pathogenic bacteria in the oral cavity of CD patients is alarming since they can disturb gut homeostasis and induce inflammation by swallowing, or hematogenous spread of microbiota, their metabolites, or generated inflammatory mediators.
Topics: Humans; Crohn Disease; Dysbiosis; RNA, Ribosomal, 16S; Gastrointestinal Microbiome; Microbiota; Inflammation; Biomarkers; Antibodies, Monoclonal; Leukocyte L1 Antigen Complex
PubMed: 37932491
DOI: 10.1038/s41598-023-46714-8