scholarly journals Longitudinal analysis of serum cytokine levels and gut microbial abundance links IL-17/IL-22 with Clostridia and insulin sensitivity in humans

2020 ◽  
Author(s):  
Ada Admin ◽  
Xin Zhou ◽  
Jethro S. Johnson ◽  
Daniel Spakowicz ◽  
Wenyu Zhou ◽  
...  
Keyword(s):  
Insulin Sensitivity ◽  
Gut Microbiome ◽  
Metabolic Diseases ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Serum Levels ◽  
Discrete Groups ◽  
Cytokine Levels ◽  
Using Data ◽  
Study Participants

Recent studies using mouse models suggest that interaction between the gut microbiome and IL-17/IL-22 producing cells plays a role in the development of metabolic diseases. We investigated this relationship in humans using data from the prediabetes study of the Integrated Human Microbiome Project (iHMP). Specifically, we addressed the hypothesis that early in the onset of metabolic diseases there is a decline in serum levels of IL-17/IL-22, with concomitant changes in the gut microbiome. Clustering iHMP study participants on the basis of longitudinal IL-17/IL-22 profiles identified discrete groups. Individuals distinguished by low levels of IL-17/IL-22 were linked to established markers of metabolic disease, including insulin sensitivity. These individuals also displayed gut microbiome dysbiosis, characterized by decreased diversity, and IL-17/IL-22-related declines in the phylum <i>Firmicutes,</i> class <i>Clostridia</i>, and<i> </i>order <i>Clostridiales.</i> This ancillary analysis of the iHMP data therefore supports a link between the gut microbiome, IL-17/IL-22 and the onset of metabolic diseases. This raises the possibility for novel, microbiome-related therapeutic targets that may effectively alleviate metabolic diseases in humans as they do in animal models.

scholarly journals Longitudinal analysis of serum cytokine levels and gut microbial abundance links IL-17/IL-22 with Clostridia and insulin sensitivity in humans

2020 ◽  
Author(s):  
Ada Admin ◽  
Xin Zhou ◽  
Jethro S. Johnson ◽  
Daniel Spakowicz ◽  
Wenyu Zhou ◽  
...  
Keyword(s):  
Insulin Sensitivity ◽  
Gut Microbiome ◽  
Metabolic Diseases ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Serum Levels ◽  
Discrete Groups ◽  
Cytokine Levels ◽  
Using Data ◽  
Study Participants

Recent studies using mouse models suggest that interaction between the gut microbiome and IL-17/IL-22 producing cells plays a role in the development of metabolic diseases. We investigated this relationship in humans using data from the prediabetes study of the Integrated Human Microbiome Project (iHMP). Specifically, we addressed the hypothesis that early in the onset of metabolic diseases there is a decline in serum levels of IL-17/IL-22, with concomitant changes in the gut microbiome. Clustering iHMP study participants on the basis of longitudinal IL-17/IL-22 profiles identified discrete groups. Individuals distinguished by low levels of IL-17/IL-22 were linked to established markers of metabolic disease, including insulin sensitivity. These individuals also displayed gut microbiome dysbiosis, characterized by decreased diversity, and IL-17/IL-22-related declines in the phylum <i>Firmicutes,</i> class <i>Clostridia</i>, and<i> </i>order <i>Clostridiales.</i> This ancillary analysis of the iHMP data therefore supports a link between the gut microbiome, IL-17/IL-22 and the onset of metabolic diseases. This raises the possibility for novel, microbiome-related therapeutic targets that may effectively alleviate metabolic diseases in humans as they do in animal models.

scholarly journals Circulating Levels of Sclerostin Predict Glycemic Improvement after Sleeve Gastrectomy

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 623
Author(s):  
Federico Carbone ◽  
Elisa Nulli Migliola ◽  
Aldo Bonaventura ◽  
Alessandra Vecchié ◽  
Stefano De Vuono ◽  
...  
Keyword(s):  
Sleeve Gastrectomy ◽  
Insulin Sensitivity ◽  
Metabolic Diseases ◽  
Serum Levels ◽  
Morbidly Obese ◽  
Model Assessment ◽  
Anthropometric Measures ◽  
Baseline Serum ◽  
Peripheral Insulin Sensitivity ◽  
Post Surgery

Among the different effects of bariatric surgery, here we focus on bone-derived inflammatory molecules, and in particular, sclerostin; an osteocyte product potentially associated with cardio-metabolic diseases. In 94 morbidly obese patients undergoing laparoscopic sleeve gastrectomy (SG), over-time changes in anthropometric and biochemical measures—including insulin resistance (IR) indexes—were correlated with serum sclerostin levels. Sclerostin was positively associated with anthropometric indexes of obesity, and inversely with IR, namely homeostatic model assessment for peripheral insulin sensitivity (HOMA2%S) (r = −0.218; p = 0.045). Sclerostin emerged as the only significant predictor of HOMA2-%S normalization, independently of demographic and anthropometric variables (OR 1.01 (95% CI 1.00–1.02); p = 0.024). We also identified two distinct patterns of serum sclerostin change: the higher/lower sclerostin levels at baseline, the greater their post-surgical reduction/increase (p < 0.001 for all subgroups). Among those two patterns, especially the post-surgery increase in serum sclerostin was associated with lean mass reduction, without any association with IR indexes. Although counterintuitive, this change was likely dependent on the post-surgical increase in bone turnover. In conclusion, baseline serum levels of sclerostin correlate with anthropometric measures of obesity and IR, and the ability to predict glycemic improvements after SG. Specifically, serum sclerostin was closely associated with peripheral insulin sensitivity (HOMA2-%S), thus supporting the role of skeletal muscle/bone interactions in metabolic diseases.

scholarly journals Gut dysbiosis induces the development of pre-eclampsia through bacterial translocation

Gut ◽  
2020 ◽  
Vol 69 (3) ◽  
pp. 513-522 ◽  
Author(s):  
Xia Chen ◽  
Pan Li ◽  
Mian Liu ◽  
Huimin Zheng ◽  
Yan He ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Metabolic Diseases ◽  
In Situ Hybridisation ◽  
Gut Dysbiosis ◽  
Causative Relationship ◽  
Cytokine Levels ◽  
Rrna Sequencing ◽  
Faecal Microbiome

ObjectivePre-eclampsia (PE) is one of the malignant metabolic diseases that complicate pregnancy. Gut dysbiosis has been identified for causing metabolic diseases, but the role of gut microbiome in the pathogenesis of PE remains unknown.DesignWe performed a case–control study to compare the faecal microbiome of PE and normotensive pregnant women by 16S ribosomal RNA (rRNA) sequencing. To address the causative relationship between gut dysbiosis and PE, we used faecal microbiota transplantation (FMT) in an antibiotic-treated mouse model. Finally, we determined the microbiome translocation and immune responses in human and mouse placental samples by 16S rRNA sequencing, quantitative PCR and in situ hybridisation.ResultsPatients with PE showed reduced bacterial diversity with obvious dysbiosis. Opportunistic pathogens, particularly Fusobacterium and Veillonella, were enriched, whereas beneficial bacteria, including Faecalibacterium and Akkermansia, were markedly depleted in the PE group. The abundances of these discriminative bacteria were correlated with blood pressure (BP), proteinuria, aminotransferase and creatinine levels. On successful colonisation, the gut microbiome from patients with PE triggered a dramatic, increased pregestational BP of recipient mice, which further increased after gestation. In addition, the PE-transplanted group showed increased proteinuria, embryonic resorption and lower fetal and placental weights. Their T regulatory/helper-17 balance in the small intestine and spleen was disturbed with more severe intestinal leakage. In the placenta of both patients with PE and PE-FMT mice, the total bacteria, Fusobacterium, and inflammatory cytokine levels were significantly increased.ConclusionsThis study suggests that the gut microbiome of patients with PE is dysbiotic and contributes to disease pathogenesis.

scholarly journals Changes in circulating adiponectin and tumour necrosis factor-α and their relationship with insulin resistance in periparturient dairy cows

2016 ◽  
Vol 60 (2) ◽  
pp. 163-167 ◽  
Author(s):  
Zafer Mecitoglu ◽  
Sezgin Senturk ◽  
Gulsah Akgul ◽  
Duygu Udum ◽  
Ender Uzabacı ◽  
...  
Keyword(s):  
Insulin Sensitivity ◽  
Dairy Cows ◽  
Negative Correlation ◽  
Serum Levels ◽  
Negative Energy ◽  
Glucose Levels ◽  
Periparturient Period ◽  
Tnf Α ◽  
Using Data ◽  
Factor Α

AbstractIntroduction: The aim of the study was to investigate changes in the serum levels of adiponectin and TNF-α, as well as insulin sensitivity, and to elucidate the possible relationship among the parameters and negative energy balance during the periparturient period of dairy cows.Material and Methods: Thirty primiparous Holstein dairy cows were selected for the study. Blood samples were collected from each cow seven days before the expected calving date, on the calving day, and 7, 14, and 21 days after calving. Blood non-esterified fatty acids (NEFA), β-hydroxybutyric acid (BHBA), glucose, insulin, adiponectin, and TNF- α levels were measured. Revised Quantitative Insulin Sensitivity Check Index (rQUICKI) was calculated using data on NEFA, insulin, and glucose concentrations.Results: When compared to prepartum levels, serum concentration of adiponectin significantly increased on day 21 postpartum. The rQUICKI increased and NEFA levels decreased on day 7 after parturition. Insulin and glucose levels decreased on days 7, 14, and 21 postpartum when compared with prepartum levels. BHBA levels decreased on day 21 and TNF- α concentration also decreased on days 7, 14, and 21 postpartum. Adiponectin levels positively correlated with NEFA during the preparturient period. Negative correlation was detected between adiponectin and rQUICKI on calving day and on 14th day after parturition. TNF- α concentration positively correlated with glucose levels on day 7 prepartum and on 21st day postpartum and with rQUICKI on 21st day postpartum. Negative correlation was detected between adiponectin level and insulin sensitivity.Conclusion: Based on the results of the study, we concluded that adiponectin could possibly increase insulin sensitivity when blood NEFA concentrations are elevated.

scholarly journals G2S: a new deep learning tool for predicting stool microbiome structure from oral microbiome data

2020 ◽  
Author(s):  
Simone Rampelli ◽  
Marco Candela ◽  
Elena Biagi ◽  
Patrizia Brigidi ◽  
Silvia Turroni
Keyword(s):  
Deep Learning ◽  
Gut Microbiome ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Oral Microbiome ◽  
The Family ◽  
Family Level ◽  
Microbial Metagenomics ◽  
Real Composition ◽  
Microbiome Data

Abstract Background Deep learning methodologies have revolutionized prediction in many fields and show the potential to do the same in microbial metagenomics. However, deep learning is still unexplored in the field of microbiology, with only a few software designed to work with microbiome data. In the frame of meta-community theory, we foresee new perspectives for the development and application of deep learning algorithms in microbiology, with a great potential in the field of human microbiome. Results G2S is a bioinformatic tool for the taxonomic prediction of the human stool microbiome directly from oral microbiome data of the same individual. The tool uses a deep convolutional neural network trained on data of the Human Microbiome Project, allowing to infer the stool microbiome at the family level more accurately than other approaches. G2S was validated on already characterized oral and fecal sample pairs, and then applied to ancient microbiome data from dental calculi, to derive putative intestinal components in medieval subjects. Conclusions G2S infers the family-level taxonomic configuration of the stool microbiome mirroring the real composition with exceptional performance. G2S can be used with modern samples, allowing to predict the eubiotic/dysbiotic state of the gut microbiome when fecal sampling is missing, and especially with ancient samples, as a unique opportunity in the field of paleomicrobiology to recover data related to ancient gut microbiome configurations.

scholarly journals HLA-A alleles including HLA-A29 affect the composition of the gut microbiome: a potential clue to the pathogenesis of birdshot retinochoroidopathy

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Peter R. Sternes ◽  
Tammy M. Martin ◽  
Michael Paley ◽  
Sarah Diamond ◽  
Mark J. Asquith ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Bacterial Species ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Eye Disease ◽  
Intestinal Biopsy ◽  
Healthy Individuals ◽  
Sequencing Data ◽  
Immune Mediated ◽  
Bacterial Profiling

Abstract Birdshot retinochoroidopathy occurs exclusively in individuals who are HLA-A29 positive. The mechanism to account for this association is unknown. The gut microbiome has been causally implicated in many immune-mediated diseases. We hypothesized that HLA-A29 would affect the composition of the gut microbiome, leading to a dysbiosis and immune-mediated eye disease. Fecal and intestinal biopsy samples were obtained from 107 healthy individuals from Portland, Oregon environs, 10 of whom were HLA-A29 positive, undergoing routine colonoscopy. Bacterial profiling was achieved via 16S rRNA metabarcoding. Publicly available whole meta-genome sequencing data from the Human Microbiome Project (HMP), consisting of 298 healthy controls mostly of US origin, were also interrogated. PERMANOVA and sparse partial least squares discriminant analysis (sPLSDA) demonstrated that subjects who were HLA-A29 positive differed in bacterial species composition (beta diversity) compared to HLA-A29 negative subjects in both the Portland (p = 0.019) and HMP cohorts (p = 0.0002). The Portland and HMP cohorts evidenced different subsets of bacterial species associated with HLA-A29 status, likely due to differences in the metagenomic techniques employed. The functional composition of the HMP cohort did not differ overall (p = 0.14) between HLA-A29 positive and negative subjects, although some distinct pathways such as heparan sulfate biosynthesis showed differences. As we and others have shown for various HLA alleles, the HLA allotype impacts the composition of the microbiome. We hypothesize that HLA-A29 may predispose chorioretinitis via an altered gut microbiome.

scholarly journals Gut Microbial Protein Expression in Response to Dietary Patterns in a Controlled Feeding Study: A Metaproteomic Approach

2020 ◽  
Vol 8 (3) ◽  
pp. 379
Author(s):  
Sheng Pan ◽  
Meredith A. J. Hullar ◽  
Lisa A. Lai ◽  
Hong Peng ◽  
Damon H. May ◽  
...  
Keyword(s):  
Protein Expression ◽  
Dietary Patterns ◽  
Gut Microbiome ◽  
Dietary Intervention ◽  
Glycemic Load ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Microbial Metabolism ◽  
Microbial Protein ◽  
Bacterial Enzymes

Although the gut microbiome has been associated with dietary patterns linked to health, microbial metabolism is not well characterized. This ancillary study was a proof of principle analysis for a novel application of metaproteomics to study microbial protein expression in a controlled dietary intervention. We measured the response of the microbiome to diet in a randomized crossover dietary intervention of a whole-grain, low glycemic load diet (WG) and a refined-grain, high glycemic load diet (RG). Total proteins in stools from 9 participants at the end of each diet period (n = 18) were analyzed by LC MS/MS and proteins were identified using the Human Microbiome Project (HMP) human gut microbiome database and UniProt human protein databases. T-tests, controlling for false discovery rate (FDR) <10%, were used to compare the Gene Ontology (GO) biological processes and bacterial enzymes between the two interventions. Using shotgun proteomics, more than 53,000 unique peptides were identified including microbial (89%) and human peptides (11%). Forty-eight bacterial enzymes were statistically different between the diets, including those implicated in SCFA production and degradation of fatty acids. Enzymes associated with degradation of human mucin were significantly enriched in the RG diet. These results illustrate that the metaproteomic approach is a valuable tool to study the microbial metabolism of diets that may influence host health.

scholarly journals Human and rat gut microbiome composition is maintained following sleep restriction

2017 ◽  
Vol 114 (8) ◽  
pp. E1564-E1571 ◽  
Author(s):  
Shirley L. Zhang ◽  
Lei Bai ◽  
Namni Goel ◽  
Aubrey Bailey ◽  
Christopher J. Jang ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Metabolic Diseases ◽  
Human Microbiome ◽  
Modern Society ◽  
Sleep Restriction ◽  
Medical Problems ◽  
Fecal Microbiome ◽  
Microbiome Composition ◽  
Operational Taxonomic Units ◽  
Obesity And Diabetes

Insufficient sleep increasingly characterizes modern society, contributing to a host of serious medical problems. Loss of sleep is associated with metabolic diseases such as obesity and diabetes, cardiovascular disorders, and neurological and cognitive impairments. Shifts in gut microbiome composition have also been associated with the same pathologies; therefore, we hypothesized that sleep restriction may perturb the gut microbiome to contribute to a disease state. In this study, we examined the fecal microbiome by using a cross-species approach in both rat and human studies of sleep restriction. We used DNA from hypervariable regions (V1-V2) of 16S bacteria rRNA to define operational taxonomic units (OTUs) of the microbiome. Although the OTU richness of the microbiome is decreased by sleep restriction in rats, major microbial populations are not altered. Only a single OTU, TM7-3a, was found to increase with sleep restriction of rats. In the human microbiome, we find no overt changes in the richness or composition induced by sleep restriction. Together, these results suggest that the microbiome is largely resistant to changes during sleep restriction.

scholarly journals Expression-Based Inference of Human Microbiome Metabolic Flux Patterns in Health and Disease

2020 ◽  
Author(s):  
Yiping Wang ◽  
Zhenglong Gu
Keyword(s):  
Metabolic Disease ◽  
Gut Microbiome ◽  
Metabolic Flux ◽  
Metabolic Diseases ◽  
Human Microbiome ◽  
Metagenomic Sequencing ◽  
Metabolic Cooperation ◽  
Human Host ◽  
Compositional Stability ◽  
Constraint Based Modeling

1AbstractMetagenomic sequencing has revealed that the composition of the gut microbiome is linked to several major metabolic diseases, including obesity, type 2 diabetes (T2D), and inflammatory bowel disease (IBD). However, the exact mechanistic link between the gut microbiome and human host phenotypes is unclear. Here we used constraint-based modeling of the gut microbiome, using a gene-expression based algorithm called FALCON, to simulate metabolic flux differences in the microbiome of controls vs. metabolic disease patients. We discovered that several major pathways, previously shown to be important in human host metabolism, have significantly different flux between the two groups. We also modeled metabolic cooperation and competition between pairs of species in the microbiome, and use this to determine the compositional stability of the microbiome. We find that that the microbiome is generally unstable across controls as well as metabolic microbiomes, and metabolic disease microbiomes even more unstable than controls.

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