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Explicet: graphical user interface software for metadata-driven management, analysis and visualization of microbiome data

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TLDR
The subject of this manuscript, the graphical user interface-based Explicet software package, fills a previously unmet need for a robust, yet intuitive means of integrating the outputs of the software pipelines with user-specified metadata and then visualizing the combined data.
Abstract
Summary: Studies of the human microbiome, and microbial community ecology in general, have blossomed of late and are now a burgeoning source of exciting research findings. Along with the advent of next-generation sequencing platforms, which have dramatically increased the scope of microbiome-related projects, several high-performance sequence analysis pipelines (e.g. QIIME, MOTHUR, VAMPS) are now available to investigators for microbiome analysis. The subject of our manuscript, the graphical user interface-based Explicet software package, fills a previously unmet need for a robust, yet intuitive means of integrating the outputs of the software pipelines with user-specified metadata and then visualizing the combined data. Availability and Implementation: Explicet is implemented in C++ via the Qt framework and supported in native code on all major operating systems (Windows, Macintosh, Linux). The source code, documents and tutorials are freely available under an open-source license at www.explicet.org. Contact: ude.revnedcu@knarf.leinad

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An altered intestinal mucosal microbiome in HIV-1 infection is associated with mucosal and systemic immune activation and endotoxemia

TL;DR: Observations suggest that an important relationship exists between altered mucosal bacterial communities and intestinal inflammation during chronic HIV-1 infection, as well as with levels of systemic T-cell activation, inflammation, and microbial translocation.
Journal ArticleDOI

Alterations in Intestinal Microbiota Correlate With Susceptibility to Type 1 Diabetes

TL;DR: Results from a study performed in subjects with islet autoimmunity living in the U.S. suggest that altered intestinal microbiota may be associated with disease susceptibility.
Journal ArticleDOI

Comparative Evaluation of Four Bacteria-Specific Primer Pairs for 16S rRNA Gene Surveys.

TL;DR: Insilico evaluation of four bacterial primers for characterizing complex microbial communities in explosives contaminated and non-contaminated forest soil and by in silico evaluation against the current SILVA123 database suggests the high utility of primer pair 341f/785r for soil and plant-associated bacterial microbiome studies.
Journal ArticleDOI

Intermittent hypoxia alters gut microbiota diversity in a mouse model of sleep apnoea

TL;DR: Faecal microbiota composition and diversity are altered as a result of intermittent hypoxia realistically mimicking OSA, suggesting the possibility that physiological interplays between host and gut microbiota could be deregulated in OSA.
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The gut microbiota in infants of obese mothers increases inflammation and susceptibility to NAFLD.

TL;DR: Functional evidence is provided supporting a causative role of maternal obesity-associated infant dysbiosis in childhood obesity and NAFLD by showing that maternal Obesity-shaped infant gut microbiome induces macrophage dysfunction, inflammation, and diet-induced metabolic disease in germ-free mice.
References
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Journal ArticleDOI

Topographical and temporal diversity of the human skin microbiome.

TL;DR: This topographical and temporal survey of body sites from 10 healthy human individuals sampled over time provides a baseline for studies that examine the role of bacterial communities in disease states and the microbial interdependencies required to maintain healthy skin.
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Sex Differences in the Gut Microbiome Drive Hormone-Dependent Regulation of Autoimmunity

TL;DR: It is demonstrated that early-life microbial exposures determine sex hormone levels and modify progression to autoimmunity in the nonobese diabetic (NOD) mouse model of type 1 diabetes (T1D), and Colonization by commensal microbes elevated serum testosterone and protected NOD males from T1D.
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Using QIIME to Analyze 16S rRNA Gene Sequences from Microbial Communities

TL;DR: The following protocols describe how to install QIIME on a single computer and use it to analyze microbial 16S sequence data from nine distinct microbial communities.
Journal ArticleDOI

BARCRAWL and BARTAB: software tools for the design and implementation of barcoded primers for highly multiplexed DNA sequencing

TL;DR: The functions implemented by barcrawl and bartab are described and a proof-of-concept case study of both programs in which barcoded rRNA primers were designed and validated by high-throughput sequencing are presented.
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