scholarly journals Association Between Vaginal Bacterial Microbiota and Vaginal Yeast Colonization

2020 ◽  
Author(s):  
McKenna C Eastment ◽  
Jennifer E Balkus ◽  
Barbra A Richardson ◽  
Sujatha Srinivasan ◽  
Joshua Kimani ◽  
...  
Keyword(s):  
Lower Risk ◽  
Amplicon Sequencing ◽  
Bifidobacterium Bifidum ◽  
Vaginal Infections ◽  
Bacterial Microbiota ◽  
Prevotella Bivia ◽  
Species Type ◽  
Relative Abundances ◽  
Lactobacillus Mucosae

Abstract Background Vaginal yeast is frequently found with Lactobacillus-dominant microbiota. The relationship between vaginal yeast and other bacteria has not been well characterized. Methods These analyses utilized data from the Preventing Vaginal Infections trial. Relative abundance of vaginal bacteria from 16S ribosomal ribonucleic acid gene amplicon sequencing and quantities of 10 vaginal bacteria using taxon-directed polymerase chain reaction assays were compared at visits with and without detection of yeast on microscopy, culture, or both. Results Higher relative abundances of Megasphaera species type 1 (risk ratio [RR], 0.70; 95% confidence interval [CI], 0.52–0.95), Megasphaera species type 2 (RR, 0.81; 95% CI, 0.67–0.98), and Mageeibacillus indolicus (RR, 0.46; 95% CI, 0.25–0.83) were associated with lower risk of detecting yeast. In contrast, higher relative abundances of Bifidobacterium bifidum, Aerococcus christensenii, Lactobacillus mucosae, Streptococcus equinus/infantarius/lutentiensis, Prevotella bivia, Dialister propionicifaciens, and Lactobacillus crispatus/helveticus were associated with yeast detection. Taxon-directed assays confirmed that increasing quantities of both Megasphaera species and M indolicus were associated with lower risk of detecting yeast, whereas increasing quantities of L crispatus were associated with higher risk of detecting yeast. Conclusions Despite an analysis that examined associations between multiple vaginal bacteria and the presence of yeast, only a small number of vaginal bacteria were strongly and significantly associated with the presence or absence of yeast.

Insulin resistance and risk of vascular events, interventions and mortality in type 1 diabetes

2021 ◽  
Author(s):  
Marga A.g. Helmink ◽  
Marieke de Vries ◽  
Frank L.j. Visseren ◽  
Wendela L. de Ranitz ◽  
Harold W. de Valk ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Cardiovascular Disease ◽  
Type 1 Diabetes ◽  
Insulin Sensitivity ◽  
Lower Risk ◽  
Cardiovascular Events ◽  
Additional Risk Factor ◽  
Vascular Events ◽  
All Cause Mortality

Objective: To identify determinants associated with insulin resistance and to assess the association between insulin resistance and cardiovascular events, vascular interventions and mortality in people with type 1 diabetes at high risk of cardiovascular disease . Design: Prospective cohort study. Methods: 195 people with type 1 diabetes from the Secondary Manifestations of ARTerial disease (SMART) cohort were included. Insulin resistance was quantified by the estimated glucose disposal rate (eGDR) with higher eGDR levels indicating higher insulin sensitivity (i.e. lower eGDR levels indicating higher insulin resistance). Linear regression models were used to evaluate determinants associated with eGDR. The effect of eGDR on cardiovascular events, cardiovascular events or vascular interventions (combined endpoint) and on all-cause mortality was analysed using Cox proportional hazards models adjusted for confounders. Results: In 195 individuals (median follow-up 12.9 years, IQR 6.7-17.0), a total of 25 cardiovascular events, 26 vascular interventions and 27 deaths were observed. High eGDR as a marker for preserved insulin sensitivity was independently associated with a lower risk of cardiovascular events (HR 0.75; 95%CI 0.61-0.91), a lower risk of cardiovascular events and vascular interventions (HR 0.74; 95%CI 0.63-0.87), and a lower risk of all-cause mortality (HR 0.81; 95%CI 0.67-0.98). Conclusions: Insulin resistance as measured by eGDR is an additional risk factor for cardiovascular disease in individuals with type 1 diabetes. Modification of insulin resistance by lifestyle interventions or pharmacological treatment could be a viable therapeutic target to lower the risk of cardiovascular disease.

scholarly journals Gut Microbial Signatures for Glycemic Responses of GLP-1 Receptor Agonists in Type 2 Diabetic Patients: A Pilot Study

2022 ◽  
Vol 12 ◽  
Author(s):  
Chih-Yiu Tsai ◽  
Hsiu-Chen Lu ◽  
Yu-Hsien Chou ◽  
Po-Yu Liu ◽  
Hsin-Yun Chen ◽  
...  
Keyword(s):  
Pilot Study ◽  
Amplicon Sequencing ◽  
Forest Tree ◽  
Diabetic Patients ◽  
Linear Regression Models ◽  
Type 2 Diabetic Patients ◽  
16S Rrna Amplicon Sequencing ◽  
Random Forest Tree ◽  
Lactobacillus Mucosae

BackgroundsGlucagon-like peptide-1 receptor agonist (GLP-1 RA) is probably one of more effective antidiabetic agents in treatment of type 2 diabetes mellitus (T2D). However, the heterogenicity in responses to GLP-1 RA may be potentially related to gut microbiota, although no human evidence has been published. This pilot study aims to identify microbial signatures associated with glycemic responses to GLP-1 RA.Materials and MethodsMicrobial compositions of 52 patients with T2D receiving GLP-1 RA were determined by 16S rRNA amplicon sequencing. Bacterial biodiversity was compared between responders versus non-responders. Pearson’s correlation and random forest tree algorithm were used to identify microbial features of glycemic responses in T2D patients and multivariable linear regression models were used to validate clinical relevance.ResultsBeta diversity significantly differed between GLP-1 RA responders (n = 34) and non-responders (n = 18) (ADONIS, P = 0.004). The top 17 features associated with glycohemoglobin reduction had a 0.96 diagnostic ability, based on area under the ROC curve: Bacteroides dorei and Roseburia inulinivorans, the two microbes having immunomodulation effects, along with Lachnoclostridium sp. and Butyricicoccus sp., were positively correlated with glycemic reduction; Prevotella copri, the microbe related to insulin resistance, together with Ruminococcaceae sp., Bacteroidales sp., Eubacterium coprostanoligenes sp., Dialister succinatiphilus, Alistipes obesi, Mitsuokella spp., Butyricimonas virosa, Moryella sp., and Lactobacillus mucosae had negative correlation. Furthermore, Bacteroides dorei, Lachnoclostridium sp. and Mitsuokella multacida were significant after adjusting for baseline glycohemoglobin and C-peptide concentrations, two clinical confounders.ConclusionsUnique gut microbial signatures are associated with glycemic responses to GLP-RA treatment and reflect degrees of dysbiosis in T2D patients.

scholarly journals Gut microbiota composition is associated with narcolepsy type 1

2020 ◽  
Vol 7 (6) ◽  
pp. e896
Author(s):  
Alexandre Lecomte ◽  
Lucie Barateau ◽  
Pedro Pereira ◽  
Lars Paulin ◽  
Petri Auvinen ◽  
...  
Keyword(s):  
Community Structure ◽  
Gut Microbiota ◽  
Bacterial Communities ◽  
Beta Diversity ◽  
Alpha Diversity ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Differential Abundance ◽  
Alpha And Beta Diversity

ObjectiveTo test the hypothesis that narcolepsy type 1 (NT1) is related to the gut microbiota, we compared the microbiota bacterial communities of patients with NT1 and control subjects.MethodsThirty-five patients with NT1 (51.43% women, mean age 38.29 ± 19.98 years) and 41 controls (57.14% women, mean age 36.14 ± 12.68 years) were included. Stool samples were collected, and the fecal microbiota bacterial communities were compared between patients and controls using the well-standardized 16S rRNA gene amplicon sequencing approach. We studied alpha and beta diversity and differential abundance analysis between patients and controls, and between subgroups of patients with NT1.ResultsWe found no between-group differences for alpha diversity, but we discovered in NT1 a link with NT1 disease duration. We highlighted differences in the global bacterial community structure as assessed by beta diversity metrics even after adjustments for potential confounders as body mass index (BMI), often increased in NT1. Our results revealed differential abundance of several operational taxonomic units within Bacteroidetes, Bacteroides, and Flavonifractor between patients and controls, but not after adjusting for BMI.ConclusionWe provide evidence of gut microbial community structure alterations in NT1. However, further larger and longitudinal multiomics studies are required to replicate and elucidate the relationship between the gut microbiota, immunity dysregulation and NT1.

scholarly journals The Rising Incidence of Type 1 Diabetes Is Accounted for by Cases With Lower-Risk Human Leukocyte Antigen Genotypes

Diabetes Care ◽  
2008 ◽  
Vol 31 (8) ◽  
pp. 1546-1549 ◽  
Author(s):  
S. Fourlanos ◽  
M. D. Varney ◽  
B. D. Tait ◽  
G. Morahan ◽  
M. C. Honeyman ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Human Leukocyte Antigen ◽  
Lower Risk ◽  
Human Leukocyte ◽  
Leukocyte Antigen ◽  
Rising Incidence

scholarly journals Accurate identification and quantification of commensal microbiota bound by host immunoglobulins

2020 ◽  
Author(s):  
Matthew A. Jackson ◽  
Claire Pearson ◽  
Nicholas E. Ilott ◽  
Kelsey E. Huus ◽  
Ahmed N. Hegazy ◽  
...  
Keyword(s):  
Immunoglobulin A ◽  
Amplicon Sequencing ◽  
Positive Control ◽  
Published Data ◽  
Case Control Studies ◽  
Scoring Method ◽  
Accurate Identification ◽  
Relative Abundances ◽  
Identification And Quantification

AbstractBackgroundIdentifying which taxa are targeted by immunoglobulins can uncover important host-microbe interactions. Immunoglobulin binding of commensal taxa can be assayed by sorting bound bacteria from samples and using amplicon sequencing to determine their taxonomy, a technique most widely applied to study Immunoglobulin A (IgA-Seq). Previous experiments have scored taxon binding in IgA-Seq datasets by comparing abundances in the IgA bound and unbound sorted fractions. However, as these are relative abundances, such scores are influenced by the levels of the other taxa present and represent an abstract combination of these effects. Diversity in the practical approaches of prior studies also warrants benchmarking of the individual stages involved. Here, we provide a detailed description of the design strategy for an optimised IgA-Seq protocol. Combined with a novel scoring method for IgA-Seq datasets that accounts for the aforementioned effects, this platform enables accurate identification and quantification of commensal gut microbiota targeted by host immunoglobulins.ResultsUsing germ-free and Rag1−/− mice as negative controls, and a strain-specific IgA antibody as a positive control, we determine optimal reagents and fluorescence activated cell sorting (FACS) parameters for IgA-Seq. Using simulated IgA-Seq data, we show that existing IgA-Seq scoring methods are influenced by pre-sort relative abundances. This has consequences for the interpretation of case-control studies where there are inherent differences in microbiota composition between groups. We show that these effects can be addressed using a novel scoring approach based on posterior probabilities. Finally, we demonstrate the utility of both the IgA-Seq protocol and probability-based scores by examining both novel and published data from in vivo disease models.ConclusionsWe provide a detailed IgA-Seq protocol to accurately isolate IgA-bound taxa from intestinal samples. Using simulated and experimental data, we demonstrate novel probability-based scores that adjust for the compositional nature of relative abundance data to accurately quantify taxon-level IgA binding. All scoring approaches are made available in the IgAScores R package. These methods should improve the generation and interpretation of IgA-Seq datasets and could be applied to study other immunoglobulins and sample types.

scholarly journals Glyphosate and its formulations Roundup Bioflow and RangerPro alter bacterial and fungal community composition in the rat caecum microbiome

2021 ◽  
Author(s):  
Robin Mesnage ◽  
Simona Panzacchi ◽  
Emma Bourne ◽  
Charles A Mein ◽  
Melissa Perry ◽  
...  
Keyword(s):  
Bacterial Diversity ◽  
Gut Microbiome ◽  
Amplicon Sequencing ◽  
Dependent Manner ◽  
Fungal Community Composition ◽  
Potential Health ◽  
Opportunistic Fungi ◽  
Microbiome Composition ◽  
Bacterial Microbiota ◽  
Multigenerational Effects

The potential health consequences of glyphosate-induced gut microbiome alterations have become a matter of intense debate. As part of a multifaceted study investigating toxicity, carcinogenicity and multigenerational effects of glyphosate and its commercial herbicide formulations, we assessed changes in bacterial and fungal populations in the caecum microbiota of rats exposed prenatally until adulthood (13 weeks after weaning) to three doses of glyphosate (0.5, 5, 50 mg/kg body weight/day), or to the formulated herbicide products Roundup Bioflow and RangerPro at the same glyphosate-equivalent doses. Caecum bacterial microbiota were evaluated by 16S rRNA sequencing whilst the fungal population was determined by ITS2 amplicon sequencing. Results showed that both fungal and bacterial diversity were affected by the Roundup formulations in a dose-dependent manner, whilst glyphosate alone significantly altered only bacterial diversity. At taxa level, a reduction in Bacteroidota abundance, marked by alterations in the levels of Alloprevotella, Prevotella and Prevotellaceae UCG-003, was concomitant to increased levels of Firmicutes (e.g., Romboutsia, Dubosiella, Eubacterium brachy group or Christensenellaceae) and Actinobacteria (e.g., Enterorhabdus, Adlercreutzia, or Asaccharobacter). Treponema and Mycoplasma also had their levels reduced by the pesticide treatments. Analysis of fungal composition indicated that the abundance of the rat gut commensal Ascomycota Kazachstania was reduced while the abundance of Gibberella, Penicillium, Claviceps, Cornuvesica, Candida, Trichoderma and Sarocladium were increased by exposure to the Roundup formulations, but not to glyphosate. Altogether, our data suggest that glyphosate and its Roundup RangerPro and Bioflow caused profound changes in caecum microbiome composition by affecting the fitness of major commensals, which in turn reduced competition and allowed opportunistic fungi to grow in the gut, in particular in animals exposed to the herbicide formulations. This further indicates that changes in gut microbiome composition might influence the long-term toxicity, carcinogenicity and multigenerational effects of glyphosate-based herbicides.

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