Computational meta'omics for microbial community studies

被引:219
作者
Segata, Nicola [1 ]
Boernigen, Daniela [1 ,2 ]
Tickle, Timothy L. [1 ,2 ]
Morgan, Xochitl C. [1 ,2 ]
Garrett, Wendy S. [2 ,3 ,4 ,5 ]
Huttenhower, Curtis [1 ,2 ]
机构
[1] Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA
[2] Broad Inst MIT & Harvard, Cambridge, MA USA
[3] Harvard Univ, Sch Publ Hlth, Dept Immunol & Infect Dis, Boston, MA 02115 USA
[4] Harvard Univ, Sch Med, Dept Med, Boston, MA 02115 USA
[5] Dana Farber Canc Inst, Dept Med Oncol, Boston, MA 02115 USA
基金
美国国家科学基金会;
关键词
meta'omics; microbial communities; microbiome computational models; ACCURATE TAXONOMIC CLASSIFICATION; DE-NOVO ASSEMBLER; SINGLE-CELL; GUT MICROBIOTA; GENE-EXPRESSION; FUNCTIONAL-ANALYSIS; METABOLIC PATHWAYS; GENOMIC FRAGMENTS; HOST INTERACTIONS; READ ALIGNMENT;
D O I
10.1038/msb.2013.22
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Complex microbial communities are an integral part of the Earth's ecosystem and of our bodies in health and disease. In the last two decades, culture-independent approaches have provided new insights into their structure and function, with the exponentially decreasing cost of high-throughput sequencing resulting in broadly available tools for microbial surveys. However, the field remains far from reaching a technological plateau, as both computational techniques and nucleotide sequencing platforms for microbial genomic and transcriptional content continue to improve. Current microbiome analyses are thus starting to adopt multiple and complementary meta'omic approaches, leading to unprecedented opportunities to comprehensively and accurately characterize microbial communities and their interactions with their environments and hosts. This diversity of available assays, analysis methods, and public data is in turn beginning to enable microbiome-based predictive and modeling tools. We thus review here the technological and computational meta'omics approaches that are already available, those that are under active development, their success in biological discovery, and several outstanding challenges.
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页数:15
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