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      Emergence of microbial diversity due to cross-feeding interactions in a spatial model of gut microbial metabolism

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          Abstract

          Background

          The human gut contains approximately 10 14 bacteria, belonging to hundreds of different species. Together, these microbial species form a complex food web that can break down nutrient sources that our own digestive enzymes cannot handle, including complex polysaccharides, producing short chain fatty acids and additional metabolites, e.g., vitamin K. Microbial diversity is important for colonic health: Changes in the composition of the microbiota have been associated with inflammatory bowel disease, diabetes, obesity and Crohn’s disease, and make the microbiota more vulnerable to infestation by harmful species, e.g., Clostridium difficile. To get a grip on the controlling factors of microbial diversity in the gut, we here propose a multi-scale, spatiotemporal dynamic flux-balance analysis model to study the emergence of metabolic diversity in a spatial gut-like, tubular environment. The model features genome-scale metabolic models (GEM) of microbial populations, resource sharing via extracellular metabolites, and spatial population dynamics and evolution.

          Results

          In this model, cross-feeding interactions emerge readily, despite the species’ ability to metabolize sugars autonomously. Interestingly, the community requires cross-feeding for producing a realistic set of short-chain fatty acids from an input of glucose, If we let the composition of the microbial subpopulations change during invasion of adjacent space, a complex and stratified microbiota evolves, with subspecies specializing on cross-feeding interactions via a mechanism of compensated trait loss. The microbial diversity and stratification collapse if the flux through the gut is enhanced to mimic diarrhea.

          Conclusions

          In conclusion, this in silico model is a helpful tool in systems biology to predict and explain the controlling factors of microbial diversity in the gut. It can be extended to include, e.g., complex nutrient sources, and host-microbiota interactions via the intestinal wall.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12918-017-0430-4) contains supplementary material, which is available to authorized users.

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          Most cited references45

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          Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0.

          Over the past decade, a growing community of researchers has emerged around the use of constraint-based reconstruction and analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a substantial update of this in silico toolbox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include (i) network gap filling, (ii) (13)C analysis, (iii) metabolic engineering, (iv) omics-guided analysis and (v) visualization. As with the first version, the COBRA Toolbox reads and writes systems biology markup language-formatted models. In version 2.0, we improved performance, usability and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the toolbox and validate results. This toolbox lowers the barrier of entry to use powerful COBRA methods.
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            The Black Queen Hypothesis: Evolution of Dependencies through Adaptive Gene Loss

            ABSTRACT Reductive genomic evolution, driven by genetic drift, is common in endosymbiotic bacteria. Genome reduction is less common in free-living organisms, but it has occurred in the numerically dominant open-ocean bacterioplankton Prochlorococcus and “Candidatus Pelagibacter,” and in these cases the reduction appears to be driven by natural selection rather than drift. Gene loss in free-living organisms may leave them dependent on cooccurring microbes for lost metabolic functions. We present the Black Queen Hypothesis (BQH), a novel theory of reductive evolution that explains how selection leads to such dependencies; its name refers to the queen of spades in the game Hearts, where the usual strategy is to avoid taking this card. Gene loss can provide a selective advantage by conserving an organism’s limiting resources, provided the gene’s function is dispensable. Many vital genetic functions are leaky, thereby unavoidably producing public goods that are available to the entire community. Such leaky functions are thus dispensable for individuals, provided they are not lost entirely from the community. The BQH predicts that the loss of a costly, leaky function is selectively favored at the individual level and will proceed until the production of public goods is just sufficient to support the equilibrium community; at that point, the benefit of any further loss would be offset by the cost. Evolution in accordance with the BQH thus generates “beneficiaries” of reduced genomic content that are dependent on leaky “helpers,” and it may explain the observed nonuniversality of prototrophy, stress resistance, and other cellular functions in the microbial world.
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              Gut-derived short-chain fatty acids are vividly assimilated into host carbohydrates and lipids.

              Acetate, propionate, and butyrate are the main short-chain fatty acids (SCFAs) that arise from the fermentation of fibers by the colonic microbiota. While many studies focus on the regulatory role of SCFAs, their quantitative role as a catabolic or anabolic substrate for the host has received relatively little attention. To investigate this aspect, we infused conscious mice with physiological quantities of stable isotopes [1-(13)C]acetate, [2-(13)C]propionate, or [2,4-(13)C2]butyrate directly in the cecum, which is the natural production site in mice, and analyzed their interconversion by the microbiota as well as their metabolism by the host. Cecal interconversion, pointing to microbial cross-feeding, was high between acetate and butyrate, low between butyrate and propionate, and almost absent between acetate and propionate. As much as 62% of infused propionate was used in whole body glucose production, in line with its role as gluconeogenic substrate. Conversely, glucose synthesis from propionate accounted for 69% of total glucose production. The synthesis of palmitate and cholesterol in the liver was high from cecal acetate (2.8 and 0.7%, respectively) and butyrate (2.7 and 0.9%, respectively) as substrates, but low or absent from propionate (0.6 and 0.0%, respectively). Label incorporation due to chain elongation of stearate was approximately eightfold higher than de novo synthesis of stearate. Microarray data suggested that SCFAs exert a mild regulatory effect on the expression of genes involved in hepatic metabolic pathways during the 6-h infusion period. Altogether, gut-derived acetate, propionate, and butyrate play important roles as substrates for glucose, cholesterol, and lipid metabolism.
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                Author and article information

                Contributors
                milanvanhoek@gmail.com
                merks@cwi.nl
                Journal
                BMC Syst Biol
                BMC Syst Biol
                BMC Systems Biology
                BioMed Central (London )
                1752-0509
                16 May 2017
                16 May 2017
                2017
                : 11
                : 56
                Affiliations
                [1 ]ISNI 0000 0004 0369 4183, GRID grid.6054.7, Life Sciences Group, , Centrum Wiskunde & Informatica, ; Science Park 123, Amsterdam, 1098 XG The Netherlands
                [2 ]ISNI 0000 0001 2312 1970, GRID grid.5132.5, Mathematical Institute, , Leiden University, ; Niels Bohrweg 1, Leiden, 2333 CA The Netherlands
                Author information
                http://orcid.org/0000-0002-6152-687X
                Article
                430
                10.1186/s12918-017-0430-4
                5434578
                28511646
                121208d9-e651-4117-a504-8d3072f843e1
                © The Author(s) 2017

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 21 June 2016
                : 26 April 2017
                Funding
                Funded by: NWO
                Award ID: Netherlands Genomics Initiative/Netherlands Consortium for Systems Biology
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Quantitative & Systems biology
                flux-balance analysis with molecular crowding,dynamic multi-species metabolic modeling,intestinal microbiota,multiscale modeling,compensated trait loss,microbial communities

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