scholarly journals A meta-analysis study of the robustness and universality of gut microbiome-metabolome associations

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Efrat Muller ◽  
Yadid M. Algavi ◽  
Elhanan Borenstein
Keyword(s):  
Machine Learning ◽  
Gut Microbiome ◽  
Meta Analysis ◽  
Control Group ◽  
Disease Group ◽  
Human Gut ◽  
Host Health ◽  
Polyamines Metabolism ◽  
Carry Over ◽  
Metabolome Data

Abstract Background Microbiome-metabolome studies of the human gut have been gaining popularity in recent years, mostly due to accumulating evidence of the interplay between gut microbes, metabolites, and host health. Statistical and machine learning-based methods have been widely applied to analyze such paired microbiome-metabolome data, in the hope of identifying metabolites that are governed by the composition of the microbiome. Such metabolites can be likely modulated by microbiome-based interventions, offering a route for promoting gut metabolic health. Yet, to date, it remains unclear whether findings of microbially associated metabolites in any single study carry over to other studies or cohorts, and how robust and universal are microbiome-metabolites links. Results In this study, we addressed this challenge by performing a comprehensive meta-analysis to identify human gut metabolites that can be predicted based on the composition of the gut microbiome across multiple studies. We term such metabolites “robustly well-predicted”. To this end, we processed data from 1733 samples from 10 independent human gut microbiome-metabolome studies, focusing initially on healthy subjects, and implemented a machine learning pipeline to predict metabolite levels in each dataset based on the composition of the microbiome. Comparing the predictability of each metabolite across datasets, we found 97 robustly well-predicted metabolites. These include metabolites involved in important microbial pathways such as bile acid transformations and polyamines metabolism. Importantly, however, other metabolites exhibited large variation in predictability across datasets, suggesting a cohort- or study-specific relationship between the microbiome and the metabolite. Comparing taxonomic contributors to different models, we found that some robustly well-predicted metabolites were predicted by markedly different sets of taxa across datasets, suggesting that some microbially associated metabolites may be governed by different members of the microbiome in different cohorts. We finally examined whether models trained on a control group of a given study successfully predicted the metabolite’s level in the disease group of the same study, identifying several metabolites where the model was not transferable, indicating a shift in microbial metabolism in disease-associated dysbiosis. Conclusions Combined, our findings provide a better understanding of the link between the microbiome and metabolites and allow researchers to put identified microbially associated metabolites within the context of other studies.

scholarly journals Quantitatively Different, yet Qualitatively Alike: A Meta-Analysis of the Mouse Core Gut Microbiome with a View towards the Human Gut Microbiome

PLoS ONE ◽  
2013 ◽  
Vol 8 (5) ◽  
pp. e62578 ◽  
Author(s):  
Lukasz Krych ◽  
Camilla H. F. Hansen ◽  
Axel K. Hansen ◽  
Frans W. J. van den Berg ◽  
Dennis S. Nielsen
Keyword(s):  
Gut Microbiome ◽  
Meta Analysis ◽  
Human Gut ◽  
Human Gut Microbiome

scholarly journals Captivity humanizes the primate microbiome

2016 ◽  
Vol 113 (37) ◽  
pp. 10376-10381 ◽  
Author(s):  
Jonathan B. Clayton ◽  
Pajau Vangay ◽  
Hu Huang ◽  
Tonya Ward ◽  
Benjamin M. Hillmann ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Meta Analysis ◽  
Human Microbiome ◽  
16S Rrna Gene Sequencing ◽  
Modern Human ◽  
Primate Species ◽  
Rrna Gene ◽  
Human Gut ◽  
Dietary Analysis ◽  
Human Gut Microbiome

The primate gastrointestinal tract is home to trillions of bacteria, whose composition is associated with numerous metabolic, autoimmune, and infectious human diseases. Although there is increasing evidence that modern and Westernized societies are associated with dramatic loss of natural human gut microbiome diversity, the causes and consequences of such loss are challenging to study. Here we use nonhuman primates (NHPs) as a model system for studying the effects of emigration and lifestyle disruption on the human gut microbiome. Using 16S rRNA gene sequencing in two model NHP species, we show that although different primate species have distinctive signature microbiota in the wild, in captivity they lose their native microbes and become colonized with Prevotella and Bacteroides, the dominant genera in the modern human gut microbiome. We confirm that captive individuals from eight other NHP species in a different zoo show the same pattern of convergence, and that semicaptive primates housed in a sanctuary represent an intermediate microbiome state between wild and captive. Using deep shotgun sequencing, chemical dietary analysis, and chloroplast relative abundance, we show that decreasing dietary fiber and plant content are associated with the captive primate microbiome. Finally, in a meta-analysis including published human data, we show that captivity has a parallel effect on the NHP gut microbiome to that of Westernization in humans. These results demonstrate that captivity and lifestyle disruption cause primates to lose native microbiota and converge along an axis toward the modern human microbiome.

scholarly journals Is the Gut Microbiome a Target for Adjuvant Treatment of COVID-19?

Biologics ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 285-299
Author(s):  
Kai Hilpert
Keyword(s):  
Clinical Trials ◽  
Gut Microbiome ◽  
Transmembrane Protein ◽  
Meta Analysis ◽  
Gastrointestinal Symptoms ◽  
Control Group ◽  
Intestinal Damage ◽  
Pilot Studies ◽  
Mucosal Integrity ◽  
Probiotic Treatment

High expression of the transmembrane protein angiotensin I converting enzyme 2 (ACE2), more than 100-times higher as in the lung, and transmembrane serine protease 2 (TMPRSS2) in the gastrointestinal tract leads to infection with SARS-CoV-2. According to meta-analysis data, 9.8–20% of COVID-19 patients experience gastrointestinal symptoms, where diarrhoea is the most frequent, and about 50% shed viruses with high titre through their faeces, where a first faecal transmission was reported. Furthermore, gut inflammation, intestinal damage, and weakening of the gut mucosal integrity that leads to increased permeability has been shown in different studies for COVID-19 patients. This can lead to increased inflammation and bacteraemia. Low mucosal integrity combined with low intestinal damage is a good predictor for disease progression and submission to the intensive care unit (ICU). Several pilot studies have shown that the gut microbiome of COVID-19 patients is changed, microbial richness and diversity were lower, and opportunistic pathogens that can cause bacteraemia were enriched compared to a healthy control group. In a large proportion of these patients, dysbiosis was not resolved at discharge from the hospital and one study showed dysbiosis is still present after 3 months post COVID-19. Consequently, there might be a link between dysbiosis of the gut microbiome in COVID-19 patients and chronic COVID-19 syndrome (CCS). Various clinical trials are investigating the benefit of probiotics for acute COVID-19 patients, the majority of which have not reported results yet. However, two clinical trials have shown that a certain combination of probiotics is beneficial and safe for acute COVID-19 patients. Mortality was 11% for the probiotic treatment group, and 22% for the control group. Furthermore, for the probiotic group, symptoms cleared faster, and an 8-fold decreased risk of developing a respiratory failure was calculated. In conclusion, evidence is arising that inflammation, increased permeability, and microbiome dysbiosis in the gut occur in COVID-19 patients and thus provide new targets for adjuvant treatments of acute and chronic COVID-19. More research in this area is needed.

scholarly journals Machine Learning Uncovers Adverse Drug Effects on Intestinal Bacteria

Pharmaceutics ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1026
Author(s):  
Laura E. McCoubrey ◽  
Moe Elbadawi ◽  
Mine Orlu ◽  
Simon Gaisford ◽  
Abdul W. Basit
Keyword(s):  
Machine Learning ◽  
Drug Development ◽  
Gut Microbiome ◽  
Drug Effects ◽  
Intestinal Bacteria ◽  
Clinical Settings ◽  
Adverse Drug Effects ◽  
Bacterial Strains ◽  
Human Gut ◽  
Microbiome Composition

The human gut microbiome, composed of trillions of microorganisms, plays an essential role in human health. Many factors shape gut microbiome composition over the life span, including changes to diet, lifestyle, and medication use. Though not routinely tested during drug development, drugs can exert profound effects on the gut microbiome, potentially altering its functions and promoting disease. This study develops a machine learning (ML) model to predict whether drugs will impair the growth of 40 gut bacterial strains. Trained on over 18,600 drug–bacteria interactions, 13 distinct ML models are built and compared, including tree-based, ensemble, and artificial neural network techniques. Following hyperparameter tuning and multi-metric evaluation, a lead ML model is selected: a tuned extra trees algorithm with performances of AUROC: 0.857 (±0.014), recall: 0.587 (±0.063), precision: 0.800 (±0.053), and f1: 0.666 (±0.042). This model can be used by the pharmaceutical industry during drug development and could even be adapted for use in clinical settings.

scholarly journals Rice Bran and Quercetin Produce a Positive Synergistic Effect on Human Gut Microbiota, Elevate the Level of Propionate, and Reduce the Population of Enterobacteriaceae family when Determined using a Bioreactor Model

2020 ◽  
Author(s):  
Sudeep Ghimire ◽  
Supapit Wongkuna ◽  
Ranjini Sankaranarayanan ◽  
Elizabeth P. Ryan ◽  
G. Jayarama Bhat ◽  
...  
Keyword(s):  
Synergistic Effect ◽  
Gut Microbiota ◽  
Rice Bran ◽  
Gut Microbiome ◽  
Bacterial Species ◽  
Human Gut ◽  
Food Ingredients ◽  
Microbiome Composition ◽  
Human Gut Microbiota ◽  
Host Health

AbstractDiet is one of the prominent determinants of gut microbiota composition significantly impacting human health. Recent studies with dietary supplements such as rice bran and quercetin have been shown to provide a beneficial impact on the host by positively influencing the gut microbiota. However, the specific bacterial species impacted when rice bran or quercetin is present in the diet is not well understood. Therefore, in this study, we used a minibioreactor array system as a model to determine the effect of quercetin and rice bran individually, as well as in combination, on gut microbiota without the confounding host factors. We found that rice bran exerts higher shift in gut microbiome composition when compared to quercetin. At the species level, Acidaminococcus intestini was the only significantly enriched taxa when quercetin was supplemented, while 15 species were enriched in rice bran supplementation and 13 were enriched when quercetin and rice bran were supplemented in combination. When comparing the short chain fatty acid production, quercetin supplementation significantly enriched isobutyrate production while propionate dominated the quercetin and rice bran combined group. Higher levels of propionate were highly correlated to the lower abundance of the potentially pathogenic Enterobacteriaceae family. These findings suggest that the combination of rice bran and quercetin serve to enrich beneficial bacteria and reduce potential opportunistic pathogens. However, further in vivo studies are necessary to determine the synergistic effect of rice bran and quercetin on host health and immunity.ImportanceRice bran and quercetin are dietary components that shape host health by interacting with the gut microbiome. Both these substrates have been reported to provide nutritional and immunological benefits individually. However, considering the complexity of the human diet, it is useful to determine how the combination of food ingredients such as rice bran and quercetin influences the human gut microbiota. Our study provides insights into how these ingredients influence microbiome composition alone and in combination in vitro. This will allow us to identify which species in the gut microbiome are responsible for biotransformation of these dietary ingredients.. Such information is helpful for the development of synbiotics to improve gut health and immunity.

scholarly journals Establishing What Constitutes a Healthy Human Gut Microbiome: State of the Science, Regulatory Considerations, and Future Directions

2019 ◽  
Vol 149 (11) ◽  
pp. 1882-1895 ◽  
Author(s):  
Michael I McBurney ◽  
Cindy Davis ◽  
Claire M Fraser ◽  
Barbara O Schneeman ◽  
Curtis Huttenhower ◽  
...  
Keyword(s):  
Human Health ◽  
Gut Microbiome ◽  
Interindividual Variation ◽  
Sufficient Evidence ◽  
Human Gut ◽  
Future Studies ◽  
Human Gut Microbiome ◽  
Host Health ◽  
Short And Long Term

ABSTRACTOn December 17, 2018, the North American branch of the International Life Sciences Institute (ILSI North America) convened a workshop “Can We Begin to Define a Healthy Gut Microbiome Through Quantifiable Characteristics?” with >40 invited academic, government, and industry experts in Washington, DC. The workshop objectives were to 1) develop a collective expert assessment of the state of the evidence on the human gut microbiome and associated human health benefits, 2) see if there was sufficient evidence to establish measurable gut microbiome characteristics that could serve as indicators of “health,” 3) identify short- and long-term research needs to fully characterize healthy gut microbiome–host relationships, and 4) publish the findings. Conclusions were as follows: 1) mechanistic links of specific changes in gut microbiome structure with function or markers of human health are not yet established; 2) it is not established if dysbiosis is a cause, consequence, or both of changes in human gut epithelial function and disease; 3) microbiome communities are highly individualized, show a high degree of interindividual variation to perturbation, and tend to be stable over years; 4) the complexity of microbiome-host interactions requires a comprehensive, multidisciplinary research agenda to elucidate relationships between gut microbiome and host health; 5) biomarkers and/or surrogate indicators of host function and pathogenic processes based on the microbiome need to be determined and validated, along with normal ranges, using approaches similar to those used to establish biomarkers and/or surrogate indicators based on host metabolic phenotypes; 6) future studies measuring responses to an exposure or intervention need to combine validated microbiome-related biomarkers and/or surrogate indicators with multiomics characterization of the microbiome; and 7) because static genetic sampling misses important short- and long-term microbiome-related dynamic changes to host health, future studies must be powered to account for inter- and intraindividual variation and should use repeated measures within individuals.

scholarly journals Meta-analysis of the human gut microbiome from urbanized and pre-agricultural populations

2017 ◽  
Vol 19 (4) ◽  
pp. 1379-1390 ◽  
Author(s):  
Leonardo Mancabelli ◽  
Christian Milani ◽  
Gabriele Andrea Lugli ◽  
Francesca Turroni ◽  
Chiara Ferrario ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Meta Analysis ◽  
Human Gut ◽  
Human Gut Microbiome
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