MICOM: Metagenome-Scale Modeling To Infer Metabolic Interactions in the Gut Microbiota

ABSTRACT Compositional changes in the gut microbiota have been associated with a variety of medical conditions such as obesity, Crohn’s disease, and diabetes. However, connecting microbial community composition to ecosystem function remains a challenge. Here, we introduce MICOM, a customizable metabolic model of the human gut microbiome. By using a heuristic optimization approach based on L2 regularization, we were able to obtain a unique set of realistic growth rates that corresponded well with observed replication rates. We integrated adjustable dietary and taxon abundance constraints to generate personalized metabolic models for individual metagenomic samples. We applied MICOM to a balanced cohort of metagenomes from 186 people, including a metabolically healthy population and individuals with type 1 and type 2 diabetes. Model results showed that individual bacterial genera maintained conserved niche structures across humans, while the community-level production of short-chain fatty acids (SCFAs) was heterogeneous and highly individual specific. Model output revealed complex cross-feeding interactions that would be difficult to measure in vivo. Metabolic interaction networks differed somewhat consistently between healthy and diabetic subjects. In particular, MICOM predicted reduced butyrate and propionate production in a diabetic cohort, with restoration of SCFA production profiles found in healthy subjects following metformin treatment. Overall, we found that changes in diet or taxon abundances have highly personalized effects. We believe MICOM can serve as a useful tool for generating mechanistic hypotheses for how diet and microbiome composition influence community function. All methods are implemented in an open-source Python package, which is available at https://github.com/micom-dev/micom. IMPORTANCE The bacterial communities that live within the human gut have been linked to health and disease. However, we are still just beginning to understand how those bacteria interact and what potential interventions to our gut microbiome can make us healthier. Here, we present a mathematical modeling framework (named MICOM) that can recapitulate the growth rates of diverse bacterial species in the gut and can simulate metabolic interactions within microbial communities. We show that MICOM can unravel the ecological rules that shape the microbial landscape in our gut and that a given dietary or probiotic intervention can have widely different effects in different people.

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Phylogenetic barriers to horizontal transfer of antimicrobial peptide resistance genes in the human gut microbiota

10.1101/385831 ◽

2018 ◽

Author(s):

Bálint Kintses ◽

Orsolya Méhi ◽

Eszter Ari ◽

Mónika Számel ◽

Ádám Györkei ◽

...

Keyword(s):

Antibiotic Resistance ◽

Gut Microbiota ◽

Resistance Genes ◽

Gut Microbiome ◽

Horizontal Transfer ◽

Bacterial Species ◽

Antibiotic Resistance Genes ◽

Genetic Exchange ◽

Human Gut ◽

Human Gut Microbiota

AbstractThe human gut microbiota has adapted to the presence of antimicrobial peptides (AMPs) that are ancient components of immune defence. Despite important medical relevance, it has remained unclear whether AMP resistance genes in the gut microbiome are available for genetic exchange between bacterial species. Here we show that AMP- and antibiotic-resistance genes differ in their mobilization patterns and functional compatibilities with new bacterial hosts. First, whereas AMP resistance genes are widespread in the gut microbiome, their rate of horizontal transfer is lower than that of antibiotic resistance genes. Second, gut microbiota culturing and functional metagenomics revealed that AMP resistance genes originating from phylogenetically distant bacteria only have a limited potential to confer resistance inEscherichia coli, an intrinsically susceptible species. Third, the phenotypic impact of acquired AMP resistance genes heavily depends on the genetic background of the recipient bacteria. Taken together, functional compatibility with the new bacterial host emerges as a key factor limiting the genetic exchange of AMP resistance genes. Finally, our results suggest that AMPs induce highly specific changes in the composition of the human microbiota with implications for disease risks.

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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

10.1101/2020.02.13.947515 ◽

2020 ◽

Cited By ~ 1

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.

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MICOM: metagenome-scale modeling to infer metabolic interactions in the gut microbiota

10.1101/361907 ◽

2018 ◽

Cited By ~ 3

Author(s):

Christian Diener ◽

Sean M. Gibbons ◽

Osbaldo Resendis-Antonio

Keyword(s):

Gut Microbiota ◽

Microbial Community Composition ◽

Metabolic Model ◽

Short Chain Fatty Acids ◽

Specific Model ◽

Healthy Population ◽

Optimization Approach ◽

Microbiome Composition ◽

Community Function

AbstractCompositional changes in the gut microbiota have been associated with a variety of medical conditions such as obesity, Crohn’s disease and diabetes. However, connecting microbial community composition to ecosystem function remains a challenge. Here, we introduce MICOM – a customizable metabolic model of the human gut microbiome. By using a heuristic optimization approach based on L2 regularization we were able to obtain a unique set of realistic growth rates that corresponded well with observed replication rates. We integrated adjustable dietary and taxon abundance constraints to generate personalized metabolic models for individual metagenomic samples. We applied MICOM to a balanced cohort of metagenomes from 186 people, including a metabolically healthy population and individuals with type 1 and type 2 diabetes. Model results showed that individual bacterial genera maintained conserved niche structures across humans, while the community-level production of short chain fatty acids (SCFAs) was heterogeneous and highly individual-specific. Model output revealed complex cross-feeding interactions that would be difficult to measurein vivo. Metabolic interaction networks differed somewhat consistently between healthy and diabetic subjects. In particular MICOM predicted reduced butyrate and propionate production in a diabetic cohort, with restoration of SCFA production profiles found in healthy subjects following metformin treatment. Overall, we found that changes in diet or taxon abundances have highly personalized effects. We believe MICOM can serve as a useful tool for generating mechanistic hypotheses for how diet and microbiome composition influence community function. All methods are implemented in the open source Python package, which is available athttps://github.com/micom-dev/micom.

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Substrate use prioritization by a coculture of five species of gut bacteria fed mixtures of arabinoxylan, xyloglucan, β-glucan, and pectin

10.26686/wgtn.12585620.v1 ◽

2020 ◽

Author(s):

Y Liu ◽

AL Heath ◽

B Galland ◽

N Rehrer ◽

L Drummond ◽

...

Keyword(s):

Gut Microbiota ◽

Dietary Fiber ◽

Plant Cell Wall ◽

Bacterial Species ◽

Short Chain ◽

Emergent Properties ◽

Human Gut ◽

Fermentation Products ◽

Plant Polysaccharides ◽

Human Gut Microbiota

© 2020 American Society for Microbiology. Dietary fiber provides growth substrates for bacterial species that belong to the colonic microbiota of humans. The microbiota degrades and ferments substrates, producing characteristic short-chain fatty acid profiles. Dietary fiber contains plant cell wall-associated polysaccharides (hemicelluloses and pectins) that are chemically diverse in composition and structure. Thus, depending on plant sources, dietary fiber daily presents the microbiota with mixtures of plant polysaccharides of various types and complexity. We studied the extent and preferential order in which mixtures of plant polysaccharides (arabinoxylan, xyloglucan, β-glucan, and pectin) were utilized by a coculture of five bacterial species (Bacteroides ovatus, Bifidobacterium longum subspecies longum, Megasphaera elsdenii, Ruminococcus gnavus, and Veillonella parvula). These species are members of the human gut microbiota and have the biochemical capacity, collectively, to degrade and ferment the polysaccharides and produce short-chain fatty acids (SCFAs). B. ovatus utilized glycans in the order β-glucan, pectin, xyloglucan, and arabinoxylan, whereas B. longum subsp. longum utilization was in the order arabinoxylan, arabinan, pectin, and β-glucan. Propionate, as a proportion of total SCFAs, was augmented when polysaccharide mixtures contained galactan, resulting in greater succinate production by B. ovatus and conversion of succinate to propionate by V. parvula. Overall, we derived a synthetic ecological community that carries out SCFA production by the common pathways used by bacterial species for this purpose. Systems like this might be used to predict changes to the emergent properties of the gut ecosystem when diet is altered, with the aim of beneficially affecting human physiology. This study addresses the question as to how bacterial species, characteristic of the human gut microbiota, collectively utilize mixtures of plant polysaccharides such as are found in dietary fiber. Five bacterial species with the capacity to degrade polymers and/or produce acidic fermentation products detectable in human feces were used in the experiments. The bacteria showed preferential use of certain polysaccharides over others for growth, and this influenced their fermentation output qualitatively. These kinds of studies are essential in developing concepts of how the gut microbial community shares habitat resources, directly and indirectly, when presented with mixtures of polysaccharides that are found in human diets. The concepts are required in planning dietary interventions that might correct imbalances in the functioning of the human microbiota so as to support measures to reduce metabolic conditions such as obesity.

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Fruits and their impact on the gut microbiota, gut motility and constipation

Food & Function ◽

10.1039/d1fo01125a ◽

2021 ◽

Vol 12 (19) ◽

pp. 8850-8866

Author(s):

Zoi Katsirma ◽

Eirini Dimidi ◽

Ana Rodriguez-Mateos ◽

Kevin Whelan

Keyword(s):

Gut Microbiota ◽

Gut Microbiome ◽

Nutrient Content ◽

Mechanisms Of Action ◽

Human Gut ◽

Gut Motility ◽

Gut Function

A summary of the mechanisms of action by which fruit products confer effects on the human gut function, motility and the gut microbiome, as well as an exploration of the effects of processing on the active nutrient content and efficacy of fruits.

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Distinct composition and metabolic functions of human gut microbiota are associated with cachexia in lung cancer patients

The ISME Journal ◽

10.1038/s41396-021-00998-8 ◽

2021 ◽

Author(s):

Yueqiong Ni ◽

Zoltan Lohinai ◽

Yoshitaro Heshiki ◽

Balazs Dome ◽

Judit Moldvay ◽

...

Keyword(s):

Lung Cancer ◽

Gut Microbiota ◽

Cancer Patients ◽

Gut Microbiome ◽

Human Gut ◽

Microbial Composition ◽

Shotgun Metagenomics ◽

Lung Cancer Patients ◽

Microbial Species ◽

Functional Pathways

AbstractCachexia is associated with decreased survival in cancer patients and has a prevalence of up to 80%. The etiology of cachexia is poorly understood, and limited treatment options exist. Here, we investigated the role of the human gut microbiome in cachexia by integrating shotgun metagenomics and plasma metabolomics of 31 lung cancer patients. The cachexia group showed significant differences in the gut microbial composition, functional pathways of the metagenome, and the related plasma metabolites compared to non-cachectic patients. Branched-chain amino acids (BCAAs), methylhistamine, and vitamins were significantly depleted in the plasma of cachexia patients, which was also reflected in the depletion of relevant gut microbiota functional pathways. The enrichment of BCAAs and 3-oxocholic acid in non-cachectic patients were positively correlated with gut microbial species Prevotella copri and Lactobacillus gasseri, respectively. Furthermore, the gut microbiota capacity for lipopolysaccharides biosynthesis was significantly enriched in cachectic patients. The involvement of the gut microbiome in cachexia was further observed in a high-performance machine learning model using solely gut microbial features. Our study demonstrates the links between cachectic host metabolism and specific gut microbial species and functions in a clinical setting, suggesting that the gut microbiota could have an influence on cachexia with possible therapeutic applications.

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Adopting seasonal regimen (Ritucharya) to modulate the seasonal variation in gut microbiome

Journal of Ethnic Foods ◽

10.1186/s42779-021-00078-4 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Deepthi. R ◽

Vandana Rani M ◽

Delvin T. Robin ◽

Anusree Dileep

Keyword(s):

Public Health ◽

Gut Microbiota ◽

Gut Microbiome ◽

Health Management ◽

Disease Process ◽

The Body ◽

Leaky Gut ◽

Human Gut ◽

Extrinsic Factors ◽

Application Prospects

AbstractThe science of Ayurveda with its strong and unique fundamentals holds its domain forever amidst all scientific and medical advancements. The concept of Shadkriyakala (the different phases of disease formation) holds relevance in preventive medicine and public health management as it provides ample chance to halt the disease process at each stage by timely intervention. In this review, we would like to bring to the limelight the relevance of Ritucharya (seasonal regimen) in primary prevention by modulating the gut microbiota. The modern gut microbiome researches now help us to better explore the Ayurveda theories of Agni (digestive fire) and Ama (metabolic toxins) preached centuries back. Ayurveda firmly proclaims that no disease ever arises without the derangement of Agni (digestive fire). The whole preventive and treatment methodology in Ayurveda focuses upon the modulation and management of “Agni” (digestive fire). When the functioning of Agni is deranged, Ama (metabolic toxin) is produced and it vitiates the doshas which spread throughout the body and manifest as varied diseases. A biomedical perspective of our reviews suggests that dysbiosis of microbial flora can cause a leaky gut by which the toxins of deranged digestive metabolism enter the bloodstream. Consequently, an inflammatory response occurs within the body which expresses out as diseases opportunistically. We meticulously reviewed the influence of extrinsic factors namely diet and climate on human gut microbiota, and our analysis emphasises the application prospects of Ritucharya (seasonal regimen), in regulating the dynamic host-microbe interaction.

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Interaction between Host MicroRNAs and the Gut Microbiota in Colorectal Cancer

mSystems ◽

10.1128/msystems.00205-17 ◽

2018 ◽

Vol 3 (3) ◽

Cited By ~ 35

Author(s):

Ce Yuan ◽

Michael B. Burns ◽

Subbaya Subramanian ◽

Ran Blekhman

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Gut Microbiota ◽

Mirna Expression ◽

Gut Microbiome ◽

Noncoding Rna ◽

Microbial Community Composition ◽

Host Cells ◽

Microbiome Composition ◽

Small Noncoding Rna

ABSTRACT Although variation in gut microbiome composition has been linked with colorectal cancer (CRC), the factors that mediate the interactions between CRC tumors and the microbiome are poorly understood. MicroRNAs (miRNAs) are known to regulate CRC progression and are associated with patient survival outcomes. In addition, recent studies suggested that host miRNAs can also regulate bacterial growth and influence the composition of the gut microbiome. Here, we investigated the association between miRNA expression and microbiome composition in human CRC tumor and normal tissues. We identified 76 miRNAs as differentially expressed (DE) in tissue from CRC tumors and normal tissue, including the known oncogenic miRNAs miR-182, miR-503, and mir-17~92 cluster. These DE miRNAs were correlated with the relative abundances of several bacterial taxa, including Firmicutes , Bacteroidetes , and Proteobacteria . Bacteria correlated with DE miRNAs were enriched with distinct predicted metabolic categories. Additionally, we found that miRNAs that correlated with CRC-associated bacteria are predicted to regulate targets that are relevant for host-microbiome interactions and highlight a possible role for miRNA-driven glycan production in the recruitment of pathogenic microbial taxa. Our work characterized a global relationship between microbial community composition and miRNA expression in human CRC tissues. IMPORTANCE Recent studies have found an association between colorectal cancer (CRC) and the gut microbiota. One potential mechanism by which the microbiota can influence host physiology is through affecting gene expression in host cells. MicroRNAs (miRNAs) are small noncoding RNA molecules that can regulate gene expression and have important roles in cancer development. Here, we investigated the link between the gut microbiota and the expression of miRNA in CRC. We found that dozens of miRNAs are differentially regulated in CRC tumors and adjacent normal colon and that these miRNAs are correlated with the abundance of microbes in the tumor microenvironment. Moreover, we found that microbes that have been previously associated with CRC are correlated with miRNAs that regulate genes related to interactions with microbes. Notably, these miRNAs likely regulate glycan production, which is important for the recruitment of pathogenic microbial taxa to the tumor. This work provides a first systems-level map of the association between microbes and host miRNAs in the context of CRC and provides targets for further experimental validation and potential interventions.

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TrpNet: Understanding Tryptophan Metabolism across Gut Microbiome

Metabolites ◽

10.3390/metabo12010010 ◽

2021 ◽

Vol 12 (1) ◽

pp. 10

Author(s):

Yao Lu ◽

Jasmine Chong ◽

Shiqian Shen ◽

Joey-Bahige Chammas ◽

Lorraine Chalifour ◽

...

Keyword(s):

Metabolic Pathway ◽

Gut Microbiome ◽

Bacterial Species ◽

Tryptophan Metabolism ◽

Indole Derivatives ◽

Human Gut ◽

Animal Development ◽

Tryptophan Metabolites ◽

Bayesian Logistic Regression ◽

Human And Mouse

Crosstalk between the gut microbiome and the host plays an important role in animal development and health. Small compounds are key mediators in this host–gut microbiome dialogue. For instance, tryptophan metabolites, generated by biotransformation of tryptophan through complex host–microbiome co-metabolism can trigger immune, metabolic, and neuronal effects at local and distant sites. However, the origin of tryptophan metabolites and the underlying tryptophan metabolic pathway(s) are not well characterized in the current literature. A large number of the microbial contributors of tryptophan metabolism remain unknown, and there is a growing interest in predicting tryptophan metabolites for a given microbiome. Here, we introduce TrpNet, a comprehensive database and analytics platform dedicated to tryptophan metabolism within the context of host (human and mouse) and gut microbiome interactions. TrpNet contains data on tryptophan metabolism involving 130 reactions, 108 metabolites and 91 enzymes across 1246 human gut bacterial species and 88 mouse gut bacterial species. Users can browse, search, and highlight the tryptophan metabolic pathway, as well as predict tryptophan metabolites on the basis of a given taxonomy profile using a Bayesian logistic regression model. We validated our approach using two gut microbiome metabolomics studies and demonstrated that TrpNet was able to better predict alterations in in indole derivatives compared to other established methods.

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