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      Dietary emulsifiers directly alter human microbiota composition and gene expression ex vivo potentiating intestinal inflammation

      , , , ,
      Gut
      BMJ

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          Abstract

          The intestinal microbiota plays a central role in the development of many chronic inflammatory diseases including IBD and metabolic syndrome. Administration of substances that alter microbiota composition, including the synthetic dietary emulsifiers polysorbate 80 (P80) and carboxymethylcellulose (CMC), can promote such inflammatory disorders. However, that inflammation itself impacts microbiota composition has obfuscated defining the extent to which these compounds or other substances act directly upon the microbiota versus acting on host parameters that promote inflammation, which subsequently reshapes the microbiota.

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          Most cited references38

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          KEGG: kyoto encyclopedia of genes and genomes.

          M Kanehisa (2000)
          KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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            An obesity-associated gut microbiome with increased capacity for energy harvest.

            The worldwide obesity epidemic is stimulating efforts to identify host and environmental factors that affect energy balance. Comparisons of the distal gut microbiota of genetically obese mice and their lean littermates, as well as those of obese and lean human volunteers have revealed that obesity is associated with changes in the relative abundance of the two dominant bacterial divisions, the Bacteroidetes and the Firmicutes. Here we demonstrate through metagenomic and biochemical analyses that these changes affect the metabolic potential of the mouse gut microbiota. Our results indicate that the obese microbiome has an increased capacity to harvest energy from the diet. Furthermore, this trait is transmissible: colonization of germ-free mice with an 'obese microbiota' results in a significantly greater increase in total body fat than colonization with a 'lean microbiota'. These results identify the gut microbiota as an additional contributing factor to the pathophysiology of obesity.
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              Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

              Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community’s functional capabilities. Here we describe PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this ‘predictive metagenomic’ approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.
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                Author and article information

                Journal
                Gut
                Gut
                BMJ
                0017-5749
                1468-3288
                July 11 2017
                August 2017
                August 2017
                March 21 2017
                : 66
                : 8
                : 1414-1427
                Article
                10.1136/gutjnl-2016-313099
                5940336
                28325746
                e8b1de21-7ef2-40d3-8988-7a7dd9d9d07c
                © 2017
                History

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