25 research outputs found

    Combined Aggregated Functional Traits.

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    <p>The gene association patterns in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005252#pcbi.1005252.g001" target="_blank">Fig 1</a> correspond to stable structures, representing different ways to fulfill the metabolic function of interest at the ecosystem level. At the bottom of each box, vectors <i>h</i><sub>1</sub>, <i>h</i><sub>2</sub> and <i>h</i><sub>3</sub> represent functional markers abundances. We call these vectors Combined Aggregated Functional Traits (CAFTs). They should be found in all samples, possibly in varying proportions. Sample 1 is decomposed as <i>A</i><sub>1</sub> = 3<i>h</i><sub>1</sub> + 2<i>h</i><sub>2</sub> + <i>h</i><sub>3</sub> and sample <i>n</i> as <i>A</i><sub><i>n</i></sub> = <i>h</i><sub>1</sub> + 2<i>h</i><sub>2</sub> + 3<i>h</i><sub>3</sub>.</p

    Constraints on the functional markers associated to the production and consumption of intracellular metabolites in the catabolic pathway from simple sugars to SCFA and methane.

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    <p>Constraints on the functional markers associated to the production and consumption of intracellular metabolites in the catabolic pathway from simple sugars to SCFA and methane.</p

    Hierarchical structure underlying metagenomic data.

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    <p>We consider a metabolic process in a microbial ecosystem involving a substrate U, metabolites V, X, Y, Z, T and the set of reactions U → V, V → X, X → Y, V → Z and U → T + X, respectively catalyzed by proteins synthesized by genes in KEGG Orthology (KO) groups <b>a</b>, <b>b</b>, <b>c</b>, <b>d</b> and <b>e</b>. Gene counts stem from an underlying hierarchical organization. Genes are associated within bacterial genomes (solid black lines) and through ecosystem level association patterns (green, red and blue ticked lines). In this example, the green and blue boxes can be interpreted as trophic chains corresponding to two distinct pathways for substrate degradation. The red box can be interpreted as an alternative to the green one, involving different bacterial groups, depending on the host diet or life history. Note that the red box involves (possibly several) species harbouring two copies of gene <b>a</b> in their genomes.</p

    An example of CAFT.

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    <p>The first 61 coordinates of the functional marker frequency vector given by the first line of <i>H</i>*, associated to simple sugar fermentation, is represented on the reaction graph. The color scale represents percentages of the maximum coordinate among the 61 (reaction 7). The reactions form coherent pathways. The 25 coordinates associated with hydrolysis are presented in the table on the right. The numbers indicate GH families the color are scaled as percentages of the maximum coordinate among the 25 (<i>GH</i>13).</p

    Fiber digestion in the human gut: analysis of <i>W</i>*.

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    <p><b>(A)</b> For each biological sample, the total abundances in the 4 CAFTs (row sums of <i>W</i>* <i>H</i>*) is displayed as a function of the proportion of the 86 fiber digestion reactions in the metagenome (row sums of <i>A</i>). <b>(B)</b> For each sample, the vector of distances to the other samples is computed from the rows of <i>A</i> and of <i>W</i>* respectively; the histogram of Pearson correlations between theses two distance vectors for the 1408 biological samples is displayed.</p

    Reaction graph of the biological catabolic pathway from simple sugars to SCFA and methane.

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    <p>The nodes of the graph are the 43 selected metabolites, red nodes correspond to the 18 extracellular metabolites and blue nodes are the 25 extracellular, their full names and status are given in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005252#pcbi.1005252.t003" target="_blank">Table 3</a>. The 61 edges of the graph correspond to the 61 selected functional markers listed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005252#pcbi.1005252.t002" target="_blank">Table 2</a> with their associated reaction. More details can be found in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005252#pcbi.1005252.s007" target="_blank">S1 Table</a>.</p

    Binning and Hybrid assembly of synthetic microbial communities

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    Shotgun metagenomic sequencing is a common approach for studying the taxonomic diversity and metabolic potential of complex microbial communities. Current methods primarily use second generation short read sequencing, yet advances in third generation long read technologies provide opportunities to overcome some of the limitations of short read sequencing. Here, we compared seven platforms, encompassing second generation sequencers (Illumina HiSeq300, MGI DNBSEQ-G400 and DNBSEQ-T7, ThermoFisher Ion GeneStudio S5 and Ion Proton P1) and third generation sequencers (Oxford Nanopore Technologies MinION R9 and Pacific Biosciences Sequel II). We constructed three uneven synthetic microbial communities composed of up to 87 genomic microbial strains DNAs per mock, spanning 29 bacterial and archaeal phyla, and representing the most complex and diverse synthetic communities used for sequencing technology comparisons. Our results demonstrate that third generation sequencing have advantages over second generation platforms in analyzing complex microbial communities, but require careful sequencing library preparation for optimal quantitative metagenomic analysis. Our sequencing data also provides a valuable resource for testing and benchmarking bioinformatics software for metagenomics. </p
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