Dataset Information

Microbial diversity of extreme habitats in human homes.

ABSTRACT: High-throughput sequencing techniques have opened up the world of microbial diversity to scientists, and a flurry of studies in the most remote and extreme habitats on earth have begun to elucidate the key roles of microbes in ecosystems with extreme conditions. These same environmental extremes can also be found closer to humans, even in our homes. Here, we used high-throughput sequencing techniques to assess bacterial and archaeal diversity in the extreme environments inside human homes (e.g., dishwashers, hot water heaters, washing machine bleach reservoirs, etc.). We focused on habitats in the home with extreme temperature, pH, and chemical environmental conditions. We found a lower diversity of microbes in these extreme home environments compared to less extreme habitats in the home. However, we were nonetheless able to detect sequences from a relatively diverse array of bacteria and archaea. Habitats with extreme temperatures alone appeared to be able to support a greater diversity of microbes than habitats with extreme pH or extreme chemical environments alone. Microbial diversity was lowest when habitats had both extreme temperature and one of these other extremes. In habitats with both extreme temperatures and extreme pH, taxa with known associations with extreme conditions dominated. Our findings highlight the importance of examining interactive effects of multiple environmental extremes on microbial communities. Inasmuch as taxa from extreme environments can be both beneficial and harmful to humans, our findings also suggest future work to understand both the threats and opportunities posed by the life in these habitats.

SUBMITTER: Savage AM

PROVIDER: S-EPMC5028791 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Microbial diversity of extreme habitats in human homes.

Savage Amy M AM Hills Justin J Driscoll Katherine K Fergus Daniel J DJ Grunden Amy M AM Dunn Robert R RR

PeerJ 20160913

High-throughput sequencing techniques have opened up the world of microbial diversity to scientists, and a flurry of studies in the most remote and extreme habitats on earth have begun to elucidate the key roles of microbes in ecosystems with extreme conditions. These same environmental extremes can also be found closer to humans, even in our homes. Here, we used high-throughput sequencing techniques to assess bacterial and archaeal diversity in the extreme environments inside human homes (e.g., ...[more]

PMID: 27672493

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Project description:Background Human mesenchymal cells are culprit factors in vascular (patho)physiology and are hallmarked by phenotypic and functional heterogeneity. At present, they are subdivided by classic umbrella terms, such as "fibroblasts," "myofibroblasts," "smooth muscle cells," "fibrocytes," "mesangial cells," and "pericytes." However, a discriminative marker-based subclassification has to date not been established. Methods and Results As a first effort toward a classification scheme, a systematic literature search was performed to identify the most commonly used phenotypical and functional protein markers for characterizing and classifying vascular mesenchymal cell subpopulation(s). We next applied immunohistochemistry and immunofluorescence to inventory the expression pattern of identified markers on human aorta specimens representing early, intermediate, and end stages of human atherosclerotic disease. Included markers comprise markers for mesenchymal lineage (vimentin, FSP-1 [fibroblast-specific protein-1]/S100A4, cluster of differentiation (CD) 90/thymocyte differentiation antigen 1, and FAP [fibroblast activation protein]), contractile/non-contractile phenotype (α-smooth muscle actin, smooth muscle myosin heavy chain, and nonmuscle myosin heavy chain), and auxiliary contractile markers (h1-Calponin, h-Caldesmon, Desmin, SM22α [smooth muscle protein 22α], non-muscle myosin heavy chain, smooth muscle myosin heavy chain, Smoothelin-B, α-Tropomyosin, and Telokin) or adhesion proteins (Paxillin and Vinculin). Vimentin classified as the most inclusive lineage marker. Subset markers did not separate along classic lines of smooth muscle cell, myofibroblast, or fibroblast, but showed clear temporal and spatial diversity. Strong indications were found for presence of stem cells/Endothelial-to-Mesenchymal cell Transition and fibrocytes in specific aspects of the human atherosclerotic process. Conclusions This systematic evaluation shows a highly diverse and dynamic landscape for the human vascular mesenchymal cell population that is not captured by the classic nomenclature. Our observations stress the need for a consensus multiparameter subclass designation along the lines of the cluster of differentiation classification for leucocytes.

Project description:BackgroundThe human habitat is a host where microbial species evolve, function, and continue to evolve. Elucidating how microbial communities respond to human habitats is a fundamental and critical task, as establishing baselines of human microbiome is essential in understanding its role in human disease and health. Recent studies on healthy human microbiome focus on particular body habitats, assuming that microbiome develop similar structural patterns to perform similar ecosystem function under same environmental conditions. However, current studies usually overlook a complex and interconnected landscape of human microbiome and limit the ability in particular body habitats with learning models of specific criterion. Therefore, these methods could not capture the real-world underlying microbial patterns effectively.ResultsTo obtain a comprehensive view, we propose a novel ensemble clustering framework to mine the structure of microbial community pattern on large-scale metagenomic data. Particularly, we first build a microbial similarity network via integrating 1920 metagenomic samples from three body habitats of healthy adults. Then a novel symmetric Nonnegative Matrix Factorization (NMF) based ensemble model is proposed and applied onto the network to detect clustering pattern. Extensive experiments are conducted to evaluate the effectiveness of our model on deriving microbial community with respect to body habitat and host gender. From clustering results, we observed that body habitat exhibits a strong bound but non-unique microbial structural pattern. Meanwhile, human microbiome reveals different degree of structural variations over body habitat and host gender.ConclusionsIn summary, our ensemble clustering framework could efficiently explore integrated clustering results to accurately identify microbial communities, and provide a comprehensive view for a set of microbial communities. The clustering results indicate that structure of human microbiome is varied systematically across body habitats and host genders. Such trends depict an integrated biography of microbial communities, which offer a new insight towards uncovering pathogenic model of human microbiome.

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Microbial diversity of extreme habitats in human homes.

Publications

Microbial diversity of extreme habitats in human homes.

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