1 微生物群落結(jié)構(gòu)分析

Meta-Mesh工作中心的微生物群落分析基于元基因組分析軟件 Parallel-META[1]，并提供可配置的分析參數(shù)。Parallel-META[1]由本文作者開發(fā)，使用HMM(Hidden Markov Model)[2]提取16S rRNA和18S rRNA的生物標記基因片段，然后將其映射到 GreenGenes[3]、RDP[4]、Silva[5]及 Oral Core[6]，數(shù)據(jù)庫中進行物種識別、注釋、進化分析，并使用MetaSee[7]引擎進行分析數(shù)據(jù)的可視化。所有提供的可配置參數(shù)如表S1所示。

2 樣本搜索

Meta-Mesh工作中心的樣本搜索基于元基因組數(shù)據(jù)引擎Meta-Storms[8]來搜索與待查詢樣本群落結(jié)構(gòu)相似的數(shù)據(jù)庫樣本。根據(jù)Meta-Storms[8]的 p-value測試我們建議大于等于 85%的相似度即可認為兩個樣本有著非常明顯相似的結(jié)構(gòu)。

表S2 樣本搜索的可配置參數(shù)Table S2 Configurable parameters of sample search

3 Meta-Mesh系統(tǒng)登錄

Meta-Mesh系統(tǒng)中我們創(chuàng)建了系統(tǒng)共用帳號用來進行登錄操作，登錄用戶名為“metamesh”，密碼是“metamesh”。在此帳號下，名 為 “Human_associate_habitat”的 工 作 平 臺（Workshop）即為正文部分所使用的人體微生物群落應用案例。其中保存了所有的原始數(shù)據(jù)、群落結(jié)構(gòu)分析結(jié)、樣本搜索以及樣本比較的計算結(jié)果。

表S3 案例中數(shù)據(jù)庫匹配樣本的項目來源詳細信息Table S3 Details of projects of matched samples in Meta-Mesh database for case studies

表S4 案例中數(shù)據(jù)庫匹配樣本的項目來源分布Table S4 Matched samples number of each project in Meta-Mesh database of case studies

表 S5 案例樣本的數(shù)據(jù)庫搜索結(jié)果匹配詳細信息(斜體所標注的匹配樣本來源表示與案例中搜索樣本來源相同，即正確匹配)Table S5 Details of search results of case studies. Hit sources marked in italic font indicate matched samples from the same source with the queries, which also means the correct hitsA. Dataset MO(query samples from male oral cavity)

B. Dataset FO (query samples form female oral cavity)

C. Dataset MG (query samples from male gut)

D. Dataset FG (query samples from female gut)

E. Datasets MS (query samples form male palm skin)

F. Dataset FS (query samples from female palm skin)

表S6 案例中樣本的平均識別率Table S6 Overall average rate of correct identification of case studies

[1]Su X, Xu J, Ning K. Parallel-META： efficient metagenomic data analysis based on high-performance computation.BMC Systems Biology, 2012, 6(Suppl 1)： S16.

[2]Mukherjee S, Mitra S. Hidden Markov Models,grammars, and biology： a tutorial.J Bioinform Comput Biol, 2005, 3(2)： 491–526.

[3]DeSantis, TZ, Hugenholtz P, Larsen N, et al.Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB.Appl Environ Microbiol, 2006, 72(7)： 5069–5072.

[4]Cole JR, Wang Q, Cardenas E, et al. The Ribosomal Database Project： improved alignments and new tools for rRNA analysis.Nucleic Acids Res, 2009, 37(Database issue)： D141–145.

[5]Pruesse E, Quast C, Knittel K, et al. SILVA： a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB.Nucleic Acids Res, 2007,35(21)： 7188–7196.

[6]Griffen, AL, Beall CJ, Firestone ND, et al. CORE：a phylogenetically-curated 16S rDNA database of the core oral microbiome.PLoS ONE, 2011, 6(4)：e19051.

[7]Song B, Su X, Xu J, et al.MetaSee： An Interactive and Extendable Visualization Toolbox for Metagenomic Sample Analysis and Comparison.PLoS ONE, 2012, 7(11)： e48998.

[8]Su X, Xu J, Ning K. Meta-Storms： Efficient Search for Similar Microbial Communities Based on a Novel Indexing Scheme and Similarity Score for Metagenomic Data.Bioinformatics, 2012, 28(19)：2493–2501..

[9]Caporaso JG, Lauber CL, Walters WA, et al.Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample.Proceedings of the National Academy of Sciences of the United States of America, 2011, 108： 4516–4522.

[10]Costello EK, Lauber CL, Hamady M, et al.Bacterial community variation in human body habitats across space and time.Science, 2009,326(5960)： 1694–1697.

[11]Turnbaugh, PJ, Hamady M, Yatsunenko T, et al. A core gut microbiome in obese and lean twins.Nature, 2009, 457(7228)： 480–484.

[12]Yatsunenko T, Rey FE, Manary MJ, et al. Human gut microbiome viewed across age and geography.Nature, 2012, 486(7402)： 222–227.

[13]Gill SR, Pop M, Deboy RT, et al. Metagenomic analysis of the human distal gut microbiome.Science, 2006, 312(5778)： 1355–1359.

[14]McNulty NP, Yatsunenko T, Hsiao A, et al. The impact of a consortium of fermented milk strains on the gut microbiome of gnotobiotic mice and monozygotic twins.Sci Transl Med, 2011, 3(106)：106ra106.

[15]Dominguez-Bello MG, Costello EK, Contreras M,et al. Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns.Proc Natl Acad Sci USA, 2010, 107(26)： 11971–11975.

[16]Fierer N, Hamady M, Lauber CL, et al. The influence of sex, handedness, and washing on the diversity of hand surface bacteria.Proc Natl Acad Sci USA, 2008, 105(46)： 17994–17999.

[17]Jones RT, Knight R, and Martin AP. Bacterial communities of disease vectors sampled across time, space, and species.ISME J, 2010, 4(2)：223–231.

[18]Sim K, Cox MJ, Wopereis H, et al. Improved detection of bifidobacteria with optimised 16S rRNA-gene based pyrosequencing.PLoS ONE,2012, 7(3)： e32543.