Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community
Identifieur interne : 000630 ( Pmc/Corpus ); précédent : 000629; suivant : 000631Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community
Auteurs : Zhuofei Xu ; Martin Asser Hansen ; Lars H. Hansen ; Samuel Jacquiod ; S Ren J. S RensenSource :
- PLoS ONE [ 1932-6203 ] ; 2014.
Abstract
As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment) and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function.
Url:
DOI: 10.1371/journal.pone.0093445
PubMed: 24691166
PubMed Central: 3972102
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PMC:3972102Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment) and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function.</p>
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<back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Daniel, R" uniqKey="Daniel R">R Daniel</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Vogel, Tm" uniqKey="Vogel T">TM Vogel</name>
</author>
<author><name sortKey="Simonet, P" uniqKey="Simonet P">P Simonet</name>
</author>
<author><name sortKey="Jansson, Jk" uniqKey="Jansson J">JK Jansson</name>
</author>
<author><name sortKey="Hirsch, Pr" uniqKey="Hirsch P">PR Hirsch</name>
</author>
<author><name sortKey="Tiedje, Jm" uniqKey="Tiedje J">JM Tiedje</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Delmont, To" uniqKey="Delmont T">TO Delmont</name>
</author>
<author><name sortKey="Robe, P" uniqKey="Robe P">P Robe</name>
</author>
<author><name sortKey="Cecillon, S" uniqKey="Cecillon S">S Cecillon</name>
</author>
<author><name sortKey="Clark, Im" uniqKey="Clark I">IM Clark</name>
</author>
<author><name sortKey="Constancias, F" uniqKey="Constancias F">F Constancias</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Torsvik, V" uniqKey="Torsvik V">V Torsvik</name>
</author>
<author><name sortKey=" Vre S, L" uniqKey=" Vre S L">L Øvreås</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Henne, A" uniqKey="Henne A">A Henne</name>
</author>
<author><name sortKey="Daniel, R" uniqKey="Daniel R">R Daniel</name>
</author>
<author><name sortKey="Schmitz, Ra" uniqKey="Schmitz R">RA Schmitz</name>
</author>
<author><name sortKey="Gottschalk, G" uniqKey="Gottschalk G">G Gottschalk</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Rondon, Mr" uniqKey="Rondon M">MR Rondon</name>
</author>
<author><name sortKey="August, Pr" uniqKey="August P">PR August</name>
</author>
<author><name sortKey="Bettermann, Ad" uniqKey="Bettermann A">AD Bettermann</name>
</author>
<author><name sortKey="Brady, Sf" uniqKey="Brady S">SF Brady</name>
</author>
<author><name sortKey="Grossman, Th" uniqKey="Grossman T">TH Grossman</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Fierer, N" uniqKey="Fierer N">N Fierer</name>
</author>
<author><name sortKey="Lauber, Cl" uniqKey="Lauber C">CL Lauber</name>
</author>
<author><name sortKey="Ramirez, Ks" uniqKey="Ramirez K">KS Ramirez</name>
</author>
<author><name sortKey="Zaneveld, J" uniqKey="Zaneveld J">J Zaneveld</name>
</author>
<author><name sortKey="Bradford, Ma" uniqKey="Bradford M">MA Bradford</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Barberan, A" uniqKey="Barberan A">A Barberán</name>
</author>
<author><name sortKey="Bates, St" uniqKey="Bates S">ST Bates</name>
</author>
<author><name sortKey="Casamayor, Eo" uniqKey="Casamayor E">EO Casamayor</name>
</author>
<author><name sortKey="Fierer, N" uniqKey="Fierer N">N Fierer</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="De Angelis, Km" uniqKey="De Angelis K">KM De Angelis</name>
</author>
<author><name sortKey="Gladden, Jm" uniqKey="Gladden J">JM Gladden</name>
</author>
<author><name sortKey="Allgaier, M" uniqKey="Allgaier M">M Allgaier</name>
</author>
<author><name sortKey="Dhaeseleer, P" uniqKey="Dhaeseleer P">P Dhaeseleer</name>
</author>
<author><name sortKey="Fortney, Jl" uniqKey="Fortney J">JL Fortney</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Delmont, To" uniqKey="Delmont T">TO Delmont</name>
</author>
<author><name sortKey="Prestat, E" uniqKey="Prestat E">E Prestat</name>
</author>
<author><name sortKey="Keegan, Kp" uniqKey="Keegan K">KP Keegan</name>
</author>
<author><name sortKey="Faubladier, M" uniqKey="Faubladier M">M Faubladier</name>
</author>
<author><name sortKey="Robe, P" uniqKey="Robe P">P Robe</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Stewart, Fj" uniqKey="Stewart F">FJ Stewart</name>
</author>
<author><name sortKey="Sharma, Ak" uniqKey="Sharma A">AK Sharma</name>
</author>
<author><name sortKey="Bryant, Ja" uniqKey="Bryant J">JA Bryant</name>
</author>
<author><name sortKey="Eppley, Jm" uniqKey="Eppley J">JM Eppley</name>
</author>
<author><name sortKey="Delong, Ef" uniqKey="Delong E">EF DeLong</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Fierer, N" uniqKey="Fierer N">N Fierer</name>
</author>
<author><name sortKey="Leff, Jw" uniqKey="Leff J">JW Leff</name>
</author>
<author><name sortKey="Adams, Bj" uniqKey="Adams B">BJ Adams</name>
</author>
<author><name sortKey="Nielsen, Un" uniqKey="Nielsen U">UN Nielsen</name>
</author>
<author><name sortKey="Bates, St" uniqKey="Bates S">ST Bates</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Yergeau, E" uniqKey="Yergeau E">E Yergeau</name>
</author>
<author><name sortKey="Sanschagrin, S" uniqKey="Sanschagrin S">S Sanschagrin</name>
</author>
<author><name sortKey="Beaumier, D" uniqKey="Beaumier D">D Beaumier</name>
</author>
<author><name sortKey="Greer, Cw" uniqKey="Greer C">CW Greer</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Langille, Mg" uniqKey="Langille M">MG Langille</name>
</author>
<author><name sortKey="Zaneveld, J" uniqKey="Zaneveld J">J Zaneveld</name>
</author>
<author><name sortKey="Caporaso, Jg" uniqKey="Caporaso J">JG Caporaso</name>
</author>
<author><name sortKey="Mcdonald, D" uniqKey="Mcdonald D">D McDonald</name>
</author>
<author><name sortKey="Knights, D" uniqKey="Knights D">D Knights</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Meyer, F" uniqKey="Meyer F">F Meyer</name>
</author>
<author><name sortKey="Paarmann, D" uniqKey="Paarmann D">D Paarmann</name>
</author>
<author><name sortKey="Dsouza, M" uniqKey="Dsouza M">M DSouza</name>
</author>
<author><name sortKey="Olson, R" uniqKey="Olson R">R Olson</name>
</author>
<author><name sortKey="Glass, Em" uniqKey="Glass E">EM Glass</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Markowitz, Vm" uniqKey="Markowitz V">VM Markowitz</name>
</author>
<author><name sortKey="Chen, Im" uniqKey="Chen I">IM Chen</name>
</author>
<author><name sortKey="Chu, K" uniqKey="Chu K">K Chu</name>
</author>
<author><name sortKey="Szeto, E" uniqKey="Szeto E">E Szeto</name>
</author>
<author><name sortKey="Palaniappan, K" uniqKey="Palaniappan K">K Palaniappan</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Sun, S" uniqKey="Sun S">S Sun</name>
</author>
<author><name sortKey="Chen, J" uniqKey="Chen J">J Chen</name>
</author>
<author><name sortKey="Li, W" uniqKey="Li W">W Li</name>
</author>
<author><name sortKey="Altintas, I" uniqKey="Altintas I">I Altintas</name>
</author>
<author><name sortKey="Lin, A" uniqKey="Lin A">A Lin</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Wu, S" uniqKey="Wu S">S Wu</name>
</author>
<author><name sortKey="Zhu, Z" uniqKey="Zhu Z">Z Zhu</name>
</author>
<author><name sortKey="Fu, L" uniqKey="Fu L">L Fu</name>
</author>
<author><name sortKey="Niu, B" uniqKey="Niu B">B Niu</name>
</author>
<author><name sortKey="Li, W" uniqKey="Li W">W Li</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Gevers, D" uniqKey="Gevers D">D Gevers</name>
</author>
<author><name sortKey="Knight, R" uniqKey="Knight R">R Knight</name>
</author>
<author><name sortKey="Petrosino, Jf" uniqKey="Petrosino J">JF Petrosino</name>
</author>
<author><name sortKey="Huang, K" uniqKey="Huang K">K Huang</name>
</author>
<author><name sortKey="Mcguire, Al" uniqKey="Mcguire A">AL McGuire</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Segata, N" uniqKey="Segata N">N Segata</name>
</author>
<author><name sortKey="Boernigen, D" uniqKey="Boernigen D">D Boernigen</name>
</author>
<author><name sortKey="Tickle, Tl" uniqKey="Tickle T">TL Tickle</name>
</author>
<author><name sortKey="Morgan, Xc" uniqKey="Morgan X">XC Morgan</name>
</author>
<author><name sortKey="Garrett, Ws" uniqKey="Garrett W">WS Garrett</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Segata, N" uniqKey="Segata N">N Segata</name>
</author>
<author><name sortKey="Izard, J" uniqKey="Izard J">J Izard</name>
</author>
<author><name sortKey="Waldron, L" uniqKey="Waldron L">L Waldron</name>
</author>
<author><name sortKey="Gevers, D" uniqKey="Gevers D">D Gevers</name>
</author>
<author><name sortKey="Miropolsky, L" uniqKey="Miropolsky L">L Miropolsky</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Faust, K" uniqKey="Faust K">K Faust</name>
</author>
<author><name sortKey="Sathirapongsasuti, Jf" uniqKey="Sathirapongsasuti J">JF Sathirapongsasuti</name>
</author>
<author><name sortKey="Izard, J" uniqKey="Izard J">J Izard</name>
</author>
<author><name sortKey="Segata, N" uniqKey="Segata N">N Segata</name>
</author>
<author><name sortKey="Gevers, D" uniqKey="Gevers D">D Gevers</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Andreote, Fd" uniqKey="Andreote F">FD Andreote</name>
</author>
<author><name sortKey="Jimenez, Dj" uniqKey="Jimenez D">DJ Jiménez</name>
</author>
<author><name sortKey="Chaves, D" uniqKey="Chaves D">D Chaves</name>
</author>
<author><name sortKey="Dias, Ac" uniqKey="Dias A">AC Dias</name>
</author>
<author><name sortKey="Luvizotto, Dm" uniqKey="Luvizotto D">DM Luvizotto</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Segata, N" uniqKey="Segata N">N Segata</name>
</author>
<author><name sortKey="Waldron, L" uniqKey="Waldron L">L Waldron</name>
</author>
<author><name sortKey="Ballarini, A" uniqKey="Ballarini A">A Ballarini</name>
</author>
<author><name sortKey="Narasimhan, V" uniqKey="Narasimhan V">V Narasimhan</name>
</author>
<author><name sortKey="Jousson, O" uniqKey="Jousson O">O Jousson</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Altschul, Sf" uniqKey="Altschul S">SF Altschul</name>
</author>
<author><name sortKey="Gish, W" uniqKey="Gish W">W Gish</name>
</author>
<author><name sortKey="Miller, W" uniqKey="Miller W">W Miller</name>
</author>
<author><name sortKey="Myers, Ew" uniqKey="Myers E">EW Myers</name>
</author>
<author><name sortKey="Lipman, Dj" uniqKey="Lipman D">DJ Lipman</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Bray, Jr" uniqKey="Bray J">JR Bray</name>
</author>
<author><name sortKey="Curtis, Jt" uniqKey="Curtis J">JT Curtis</name>
</author>
</analytic>
</biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct><analytic><author><name sortKey="Abubucker, S" uniqKey="Abubucker S">S Abubucker</name>
</author>
<author><name sortKey="Segata, N" uniqKey="Segata N">N Segata</name>
</author>
<author><name sortKey="Goll, J" uniqKey="Goll J">J Goll</name>
</author>
<author><name sortKey="Schubert, Am" uniqKey="Schubert A">AM Schubert</name>
</author>
<author><name sortKey="Izard, J" uniqKey="Izard J">J Izard</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Kanehisa, M" uniqKey="Kanehisa M">M Kanehisa</name>
</author>
<author><name sortKey="Goto, S" uniqKey="Goto S">S Goto</name>
</author>
<author><name sortKey="Furumichi, M" uniqKey="Furumichi M">M Furumichi</name>
</author>
<author><name sortKey="Tanabe, M" uniqKey="Tanabe M">M Tanabe</name>
</author>
<author><name sortKey="Hirakawa, M" uniqKey="Hirakawa M">M Hirakawa</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Edgar, Rc" uniqKey="Edgar R">RC Edgar</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Ye, Y" uniqKey="Ye Y">Y Ye</name>
</author>
<author><name sortKey="Doak, Tg" uniqKey="Doak T">TG Doak</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Goecks, J" uniqKey="Goecks J">J Goecks</name>
</author>
<author><name sortKey="Nekrutenko, A" uniqKey="Nekrutenko A">A Nekrutenko</name>
</author>
<author><name sortKey="Taylor, J" uniqKey="Taylor J">J Taylor</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Sarkar, Sk" uniqKey="Sarkar S">SK Sarkar</name>
</author>
<author><name sortKey="Chang, Ck" uniqKey="Chang C">CK Chang</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Benjamini, Y" uniqKey="Benjamini Y">Y Benjamini</name>
</author>
<author><name sortKey="Hochberg, Y" uniqKey="Hochberg Y">Y Hochberg</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Smoot, Me" uniqKey="Smoot M">ME Smoot</name>
</author>
<author><name sortKey="Ono, K" uniqKey="Ono K">K Ono</name>
</author>
<author><name sortKey="Ruscheinski, J" uniqKey="Ruscheinski J">J Ruscheinski</name>
</author>
<author><name sortKey="Wang, Pl" uniqKey="Wang P">PL Wang</name>
</author>
<author><name sortKey="Ideker, T" uniqKey="Ideker T">T Ideker</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Qin, J" uniqKey="Qin J">J Qin</name>
</author>
<author><name sortKey="Li, R" uniqKey="Li R">R Li</name>
</author>
<author><name sortKey="Raes, J" uniqKey="Raes J">J Raes</name>
</author>
<author><name sortKey="Arumugam, M" uniqKey="Arumugam M">M Arumugam</name>
</author>
<author><name sortKey="Burgdorf, Ks" uniqKey="Burgdorf K">KS Burgdorf</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Segata, N" uniqKey="Segata N">N Segata</name>
</author>
<author><name sortKey="Haake, Sk" uniqKey="Haake S">SK Haake</name>
</author>
<author><name sortKey="Mannon, P" uniqKey="Mannon P">P Mannon</name>
</author>
<author><name sortKey="Lemon, Kp" uniqKey="Lemon K">KP Lemon</name>
</author>
<author><name sortKey="Waldron, L" uniqKey="Waldron L">L Waldron</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Janssen, Ph" uniqKey="Janssen P">PH Janssen</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Dedysh, Sn" uniqKey="Dedysh S">SN Dedysh</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Dedysh, Sn" uniqKey="Dedysh S">SN Dedysh</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Ojima, Ds" uniqKey="Ojima D">DS Ojima</name>
</author>
<author><name sortKey="Valentine, Dw" uniqKey="Valentine D">DW Valentine</name>
</author>
<author><name sortKey="Mosier, Ar" uniqKey="Mosier A">AR Mosier</name>
</author>
<author><name sortKey="Parton, Wj" uniqKey="Parton W">WJ Parton</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Jang, I" uniqKey="Jang I">I Jang</name>
</author>
<author><name sortKey="Lee, S" uniqKey="Lee S">S Lee</name>
</author>
<author><name sortKey="Hong, Jh" uniqKey="Hong J">JH Hong</name>
</author>
<author><name sortKey="Kang, H" uniqKey="Kang H">H Kang</name>
</author>
</analytic>
</biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct><analytic><author><name sortKey="Lau, E" uniqKey="Lau E">E Lau</name>
</author>
<author><name sortKey="Fisher, Mc" uniqKey="Fisher M">MC Fisher</name>
</author>
<author><name sortKey="Steudler, Pa" uniqKey="Steudler P">PA Steudler</name>
</author>
<author><name sortKey="Cavanaugh, Cm" uniqKey="Cavanaugh C">CM Cavanaugh</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Mulkidjanian, Ay" uniqKey="Mulkidjanian A">AY Mulkidjanian</name>
</author>
<author><name sortKey="Koonin, Ev" uniqKey="Koonin E">EV Koonin</name>
</author>
<author><name sortKey="Makarova, Ks" uniqKey="Makarova K">KS Makarova</name>
</author>
<author><name sortKey="Mekhedov, Sl" uniqKey="Mekhedov S">SL Mekhedov</name>
</author>
<author><name sortKey="Sorokin, A" uniqKey="Sorokin A">A Sorokin</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Empadinhas, N" uniqKey="Empadinhas N">N Empadinhas</name>
</author>
<author><name sortKey="Da Costa, Ms" uniqKey="Da Costa M">MS da Costa</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Kaneko, T" uniqKey="Kaneko T">T Kaneko</name>
</author>
<author><name sortKey="Nakamura, Y" uniqKey="Nakamura Y">Y Nakamura</name>
</author>
<author><name sortKey="Sato, S" uniqKey="Sato S">S Sato</name>
</author>
<author><name sortKey="Minamisawa, K" uniqKey="Minamisawa K">K Minamisawa</name>
</author>
<author><name sortKey="Uchiumi, T" uniqKey="Uchiumi T">T Uchiumi</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Desrosiers, Dc" uniqKey="Desrosiers D">DC Desrosiers</name>
</author>
<author><name sortKey="Sun, Yc" uniqKey="Sun Y">YC Sun</name>
</author>
<author><name sortKey="Zaidi, Aa" uniqKey="Zaidi A">AA Zaidi</name>
</author>
<author><name sortKey="Eggers, Ch" uniqKey="Eggers C">CH Eggers</name>
</author>
<author><name sortKey="Cox, Dl" uniqKey="Cox D">DL Cox</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Wolosiuk, Ra" uniqKey="Wolosiuk R">RA Wolosiuk</name>
</author>
<author><name sortKey="Ballicora, Ma" uniqKey="Ballicora M">MA Ballicora</name>
</author>
<author><name sortKey="Hagelin, K" uniqKey="Hagelin K">K Hagelin</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Maloney, Gs" uniqKey="Maloney G">GS Maloney</name>
</author>
<author><name sortKey="Kochevenko, A" uniqKey="Kochevenko A">A Kochevenko</name>
</author>
<author><name sortKey="Tieman, Dm" uniqKey="Tieman D">DM Tieman</name>
</author>
<author><name sortKey="Tohge, T" uniqKey="Tohge T">T Tohge</name>
</author>
<author><name sortKey="Krieger, U" uniqKey="Krieger U">U Krieger</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Maeda, H" uniqKey="Maeda H">H Maeda</name>
</author>
<author><name sortKey="Dudareva, N" uniqKey="Dudareva N">N Dudareva</name>
</author>
</analytic>
</biblStruct>
</listBibl>
</div1>
</back>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id>
<journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id>
<journal-id journal-id-type="publisher-id">plos</journal-id>
<journal-id journal-id-type="pmc">plosone</journal-id>
<journal-title-group><journal-title>PLoS ONE</journal-title>
</journal-title-group>
<issn pub-type="epub">1932-6203</issn>
<publisher><publisher-name>Public Library of Science</publisher-name>
<publisher-loc>San Francisco, USA</publisher-loc>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">24691166</article-id>
<article-id pub-id-type="pmc">3972102</article-id>
<article-id pub-id-type="publisher-id">PONE-D-13-52103</article-id>
<article-id pub-id-type="doi">10.1371/journal.pone.0093445</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline-v2"><subject>Biology and Life Sciences</subject>
<subj-group><subject>Computational Biology</subject>
<subj-group><subject>Comparative Genomics</subject>
</subj-group>
</subj-group>
<subj-group><subject>Evolutionary Biology</subject>
</subj-group>
<subj-group><subject>Genetics</subject>
<subj-group><subject>Genomics</subject>
<subj-group><subject>Functional Genomics</subject>
<subject>Metagenomics</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v2"><subject>Ecology and Environmental Sciences</subject>
<subj-group><subject>Soil Science</subject>
<subj-group><subject>Soil Ecology</subject>
</subj-group>
</subj-group>
</subj-group>
</article-categories>
<title-group><article-title>Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community</article-title>
<alt-title alt-title-type="running-head">Characterization of Soil Metagenomes</alt-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Xu</surname>
<given-names>Zhuofei</given-names>
</name>
<xref ref-type="aff" rid="aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Hansen</surname>
<given-names>Martin Asser</given-names>
</name>
<xref ref-type="aff" rid="aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Hansen</surname>
<given-names>Lars H.</given-names>
</name>
<xref ref-type="aff" rid="aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Jacquiod</surname>
<given-names>Samuel</given-names>
</name>
<xref ref-type="aff" rid="aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Sørensen</surname>
<given-names>Søren J.</given-names>
</name>
<xref ref-type="aff" rid="aff1"></xref>
<xref ref-type="corresp" rid="cor1"><sup>*</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1"><addr-line>Section of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark</addr-line>
</aff>
<contrib-group><contrib contrib-type="editor"><name><surname>Balestrini</surname>
<given-names>Raffaella</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"></xref>
</contrib>
</contrib-group>
<aff id="edit1"><addr-line>Institute for Plant Protection (IPP), CNR, Italy</addr-line>
</aff>
<author-notes><corresp id="cor1">* E-mail: <email>SJS@bio.ku.dk</email>
</corresp>
<fn fn-type="conflict"><p><bold>Competing Interests: </bold>
The authors have declared that no competing interests exist.</p>
</fn>
<fn fn-type="con"><p>Conceived and designed the experiments: ZX SJS. Performed the experiments: ZX. Analyzed the data: ZX MAH SJ. Contributed reagents/materials/analysis tools: ZX LHH SJS. Wrote the paper: ZX MAH LHH SJ SJS.</p>
</fn>
</author-notes>
<pub-date pub-type="collection"><year>2014</year>
</pub-date>
<pub-date pub-type="epub"><day>1</day>
<month>4</month>
<year>2014</year>
</pub-date>
<volume>9</volume>
<issue>4</issue>
<elocation-id>e93445</elocation-id>
<history><date date-type="received"><day>11</day>
<month>12</month>
<year>2013</year>
</date>
<date date-type="accepted"><day>28</day>
<month>2</month>
<year>2014</year>
</date>
</history>
<permissions><copyright-year>2014</copyright-year>
<copyright-holder>Xu et al</copyright-holder>
<license><license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>
, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<abstract><p>As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment) and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function.</p>
</abstract>
<funding-group><funding-statement>This work was partly funded by the EU ITN project TRAINBIODIVERSE and the Center for Environmental and Agricultural Microbiology (CREAM) funded by The Villum Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement>
</funding-group>
<counts><page-count count="11"></page-count>
</counts>
</article-meta>
</front>
<body><sec id="s1"><title>Introduction</title>
<p>Soil is considered to be the most diverse natural environment on the Earth <xref rid="pone.0093445-Daniel1" ref-type="bibr">[1]</xref>
, <xref rid="pone.0093445-Vogel1" ref-type="bibr">[2]</xref>
. The soil microbial communities harbor thousands of different prokaryotic organisms that contain a substantial number of genetic information, ranging from 2,000 to 18,000 different genomes estimated in one gram of soil <xref rid="pone.0093445-Delmont1" ref-type="bibr">[3]</xref>
. One of the most important issues in the field of soil ecology is to uncover the complex relationships between microbial compositions and functional diversity in soil.</p>
<p>Based on traditional approaches for cultivating and isolating soil microorganisms, early studies have focused on culturable bacteria which only account for less than 1% of soil microbial populations <xref rid="pone.0093445-Torsvik1" ref-type="bibr">[4]</xref>
. These studies have already discovered many novel genes encoding interesting enzymes and antimicrobials in soils via functional screens and clone-based Sanger sequencing <xref rid="pone.0093445-Daniel1" ref-type="bibr">[1]</xref>
, <xref rid="pone.0093445-Henne1" ref-type="bibr">[5]</xref>
, <xref rid="pone.0093445-Rondon1" ref-type="bibr">[6]</xref>
. Due to the recent advent of High-Throughput Sequencing (HTS) technologies, metagenomic sequencing approaches have been applied to investigate characterizations of diverse soil microbial communities, including target sequencing of the phylogenetic marker gene encoding 16S rRNA <xref rid="pone.0093445-Fierer1" ref-type="bibr">[7]</xref>
, <xref rid="pone.0093445-Barbern1" ref-type="bibr">[8]</xref>
and whole-metagenome shotgun sequencing <xref rid="pone.0093445-DeAngelis1" ref-type="bibr">[9]</xref>
–<xref rid="pone.0093445-Yergeau1" ref-type="bibr">[13]</xref>
. However, the majority of 16S rRNA gene-based studies are committed to the interpretation of community composition but poorly focus on the functional and metabolic properties in a microbial community <xref rid="pone.0093445-Langille1" ref-type="bibr">[14]</xref>
. In addition, integrated bioinformatic analyses for microbial community-level taxonomic affiliation, metabolic reconstruction, and interaction network, seems to be less studied for the highly diverse soil ecosystems. Currently, MG-RAST <xref rid="pone.0093445-Meyer1" ref-type="bibr">[15]</xref>
, IMG/M <xref rid="pone.0093445-Markowitz1" ref-type="bibr">[16]</xref>
, and CAMERA <xref rid="pone.0093445-Sun1" ref-type="bibr">[17]</xref>
are the major databases that can support deposition and analysis of metagenomic datasets. Uploading large sequencing data and the subsequent analysis jobs on these web servers sometimes take long waiting time and even weeks. The computational pipelines implemented by these prominent platforms are capable of processing many analysis tasks, but some approaches for special biological inference and graphical visualization still need to be complemented <xref rid="pone.0093445-Wu1" ref-type="bibr">[18]</xref>
.</p>
<p>Recently, together with the rapid development of the Human Microbiome Project, numerous computational tools and methodologies have been developed for effective interpretation and visualization of taxonomic and metabolic profiling of complex microbial communities <xref rid="pone.0093445-Gevers1" ref-type="bibr">[19]</xref>
, <xref rid="pone.0093445-Segata1" ref-type="bibr">[20]</xref>
and could be applied to the analysis of the soil microbiota. Particularly, some outstanding computational techniques that could better explain the complexity and heterogeneity of microbial communities are still less applied in the study of the soil microbiota, e.g. prediction of metagenomic biomarkers and network-based correlation analyses <xref rid="pone.0093445-Segata2" ref-type="bibr">[21]</xref>
, <xref rid="pone.0093445-Faust1" ref-type="bibr">[22]</xref>
. In this study, we aim to explore the characterizations of the soil microbiota through integrating the current state-of-the-art bioinformatics tools. A collection dataset of 33 publicly available soil metagenomes was investigated in a custom metagenomic data mining pipeline for explaining and visualizing microbial compositions and metabolic potential. A full spectrum of metagenomic biomarkers and a network of taxon co-occurrence patterns were inferred to hopefully provide some new insights into the underlying mechanisms of complex ecological relationships in the soil microbial community.</p>
</sec>
<sec sec-type="materials|methods" id="s2"><title>Materials and Methods</title>
<sec id="s2a"><title>Ethics statement</title>
<p>No specific permissions were required for the described field studies. The study locations are not privately owned and the field studies did not involve endangered or protected species.</p>
</sec>
<sec id="s2b"><title>Collection and quality control of metagenomic datasets</title>
<p>Thirty-three metagenomes sampled from five natural soil environments were publicly available and collected in the present study: 14 from grassland, seven from forest soil, nine from desert, two from Arctic soil, and one from mangrove sediment. The metagenomic datasets used can be downloadable according to the list of sequence accession numbers or web links shown in <xref ref-type="supplementary-material" rid="pone.0093445.s003">Table S1</xref>
. All datasets have been produced by whole-metagenome shotgun sequencing using the Roche 454 or Illumina platforms. More reference information about these chosen metagenomes was listed in <xref ref-type="table" rid="pone-0093445-t001">Table 1</xref>
. For the datasets of FASTQ formatted sequence reads without quality control, we performed a quality check of bases by using the package Biopieces (<ext-link ext-link-type="uri" xlink:href="http://www.biopieces.org">http://www.biopieces.org</ext-link>
). Low quality ends per read were trimmed by <italic>trim_seq</italic>
. Trimming progressed until all bases in a 3-bp stretch with minimum quality score of 20. High quality reads were retained if satisfying the following criteria: minimum average quality score of 15 in a sliding window of 20 bp; minimum read length of 50 bp.</p>
<table-wrap id="pone-0093445-t001" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0093445.t001</object-id>
<label>Table 1</label>
<caption><title>Summary of 33 soil metagenomes used in this study.</title>
</caption>
<alternatives><graphic id="pone-0093445-t001-1" xlink:href="pone.0093445.t001"></graphic>
<table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
</colgroup>
<thead><tr><td align="left" rowspan="1" colspan="1">Biome type</td>
<td align="left" rowspan="1" colspan="1">ID</td>
<td align="left" rowspan="1" colspan="1">Sequencer</td>
<td align="left" rowspan="1" colspan="1">Original name</td>
<td align="left" rowspan="1" colspan="1">Location</td>
<td align="left" rowspan="1" colspan="1">Coordinates</td>
<td align="left" rowspan="1" colspan="1">No. of sequences</td>
<td align="left" rowspan="1" colspan="1">No. of bases (Mb)</td>
<td align="left" rowspan="1" colspan="1">Reference</td>
</tr>
</thead>
<tbody><tr><td align="left" rowspan="1" colspan="1">Forest soil</td>
<td align="left" rowspan="1" colspan="1">F1</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">NA</td>
<td align="left" rowspan="1" colspan="1">Puerto Rican</td>
<td align="left" rowspan="1" colspan="1">18°18′N, 65°50′W</td>
<td align="left" rowspan="1" colspan="1">782,404</td>
<td align="left" rowspan="1" colspan="1">322</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-DeAngelis1" ref-type="bibr">[9]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Forest soil</td>
<td align="left" rowspan="1" colspan="1">F2</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">NA</td>
<td align="left" rowspan="1" colspan="1">Massachusetts, USA</td>
<td align="left" rowspan="1" colspan="1">42°54′N, 72°18′W</td>
<td align="left" rowspan="1" colspan="1">1,439,445</td>
<td align="left" rowspan="1" colspan="1">742</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Stewart1" ref-type="bibr">[11]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Forest soil</td>
<td align="left" rowspan="1" colspan="1">F3</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">AR3</td>
<td align="left" rowspan="1" colspan="1">Misiones, Argentina</td>
<td align="left" rowspan="1" colspan="1">26°44′S, 54°41′W</td>
<td align="left" rowspan="1" colspan="1">5,235,352</td>
<td align="left" rowspan="1" colspan="1">524</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Forest soil</td>
<td align="left" rowspan="1" colspan="1">F4</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">PE6</td>
<td align="left" rowspan="1" colspan="1">Manu National Park, Peru</td>
<td align="left" rowspan="1" colspan="1">12°38′S, 71°14′W</td>
<td align="left" rowspan="1" colspan="1">9,206,662</td>
<td align="left" rowspan="1" colspan="1">921</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Forest soil</td>
<td align="left" rowspan="1" colspan="1">F5</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">BZ1</td>
<td align="left" rowspan="1" colspan="1">Bonanza Creek, Alaska, USA</td>
<td align="left" rowspan="1" colspan="1">64°48′N, 148°15′W</td>
<td align="left" rowspan="1" colspan="1">6,543,903</td>
<td align="left" rowspan="1" colspan="1">654</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Forest soil</td>
<td align="left" rowspan="1" colspan="1">F6</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">CL1</td>
<td align="left" rowspan="1" colspan="1">South Carolina, USA</td>
<td align="left" rowspan="1" colspan="1">34°37′N, 81°40′W</td>
<td align="left" rowspan="1" colspan="1">6,402,940</td>
<td align="left" rowspan="1" colspan="1">640</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Forest soil</td>
<td align="left" rowspan="1" colspan="1">F7</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">DF1</td>
<td align="left" rowspan="1" colspan="1">North Carolina, USA</td>
<td align="left" rowspan="1" colspan="1">35°58′N, 79°5′W</td>
<td align="left" rowspan="1" colspan="1">3,890,044</td>
<td align="left" rowspan="1" colspan="1">389</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Arctic soil</td>
<td align="left" rowspan="1" colspan="1">A1</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">Control</td>
<td align="left" rowspan="1" colspan="1">Alert, Canada</td>
<td align="left" rowspan="1" colspan="1">82°31′N, 62°17′W</td>
<td align="left" rowspan="1" colspan="1">495,998</td>
<td align="left" rowspan="1" colspan="1">254</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Yergeau1" ref-type="bibr">[13]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Arctic soil</td>
<td align="left" rowspan="1" colspan="1">A2</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">TL1</td>
<td align="left" rowspan="1" colspan="1">Toolik Lake LTER, Alaska, USA</td>
<td align="left" rowspan="1" colspan="1">68°38′N, 149°35′W</td>
<td align="left" rowspan="1" colspan="1">6,011,971</td>
<td align="left" rowspan="1" colspan="1">601</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G1</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">F1</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">976,268</td>
<td align="left" rowspan="1" colspan="1">358</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G2</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">F2a</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">1,094,883</td>
<td align="left" rowspan="1" colspan="1">471</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G3</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">F2b</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">890,966</td>
<td align="left" rowspan="1" colspan="1">321</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G4</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">F3</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">754,829</td>
<td align="left" rowspan="1" colspan="1">311</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G5</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">F4</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">946,839</td>
<td align="left" rowspan="1" colspan="1">391</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G6</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">F5</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">754,135</td>
<td align="left" rowspan="1" colspan="1">256</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G7</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">F6</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">782,342</td>
<td align="left" rowspan="1" colspan="1">306</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G8</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">J1</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">1,130,719</td>
<td align="left" rowspan="1" colspan="1">466</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G9</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">J1a</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">1,137,813</td>
<td align="left" rowspan="1" colspan="1">433</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G10</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">J1b</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">919,406</td>
<td align="left" rowspan="1" colspan="1">343</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G11</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">J1rhizo</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">1,025,699</td>
<td align="left" rowspan="1" colspan="1">369</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G12</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">J4</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">1,135,084</td>
<td align="left" rowspan="1" colspan="1">506</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G13</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">J7</td>
<td align="left" rowspan="1" colspan="1">Hertfordshire, UK</td>
<td align="left" rowspan="1" colspan="1">51°48′N, 0°14′E</td>
<td align="left" rowspan="1" colspan="1">938,860</td>
<td align="left" rowspan="1" colspan="1">339</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Delmont2" ref-type="bibr">[10]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">G14</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">KP1</td>
<td align="left" rowspan="1" colspan="1">Kansas, USA</td>
<td align="left" rowspan="1" colspan="1">39°6′N, 96°36′W</td>
<td align="left" rowspan="1" colspan="1">5,348,832</td>
<td align="left" rowspan="1" colspan="1">535</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Desert</td>
<td align="left" rowspan="1" colspan="1">D1</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">EB017</td>
<td align="left" rowspan="1" colspan="1">Garwood Valley, Antarctica</td>
<td align="left" rowspan="1" colspan="1">78°2′S, 163°52′E</td>
<td align="left" rowspan="1" colspan="1">7,947,086</td>
<td align="left" rowspan="1" colspan="1">795</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Desert</td>
<td align="left" rowspan="1" colspan="1">D2</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">EB019</td>
<td align="left" rowspan="1" colspan="1">Lake Bonney Valley, Antarctica</td>
<td align="left" rowspan="1" colspan="1">77°44′S, 162°18′E</td>
<td align="left" rowspan="1" colspan="1">5,454,640</td>
<td align="left" rowspan="1" colspan="1">545</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Desert</td>
<td align="left" rowspan="1" colspan="1">D3</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">EB020</td>
<td align="left" rowspan="1" colspan="1">Lake Fryxell Valley, Antarctica</td>
<td align="left" rowspan="1" colspan="1">77°36′S, 163°15′E</td>
<td align="left" rowspan="1" colspan="1">9,446,684</td>
<td align="left" rowspan="1" colspan="1">945</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Desert</td>
<td align="left" rowspan="1" colspan="1">D4</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">EB021</td>
<td align="left" rowspan="1" colspan="1">Lake Hoare Valley, Antarctica</td>
<td align="left" rowspan="1" colspan="1">77°38′S, 162°53′E</td>
<td align="left" rowspan="1" colspan="1">6,543,681</td>
<td align="left" rowspan="1" colspan="1">654</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Desert</td>
<td align="left" rowspan="1" colspan="1">D5</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">EB024</td>
<td align="left" rowspan="1" colspan="1">Wright Valley, Antarctica</td>
<td align="left" rowspan="1" colspan="1">77°32′S, 161°42′E</td>
<td align="left" rowspan="1" colspan="1">10,863,646</td>
<td align="left" rowspan="1" colspan="1">1,086</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Desert</td>
<td align="left" rowspan="1" colspan="1">D6</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">EB026</td>
<td align="left" rowspan="1" colspan="1">Lake Bonney Valley, Antarctica</td>
<td align="left" rowspan="1" colspan="1">77°44′S, 162°19′E</td>
<td align="left" rowspan="1" colspan="1">5,951,684</td>
<td align="left" rowspan="1" colspan="1">595</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Desert</td>
<td align="left" rowspan="1" colspan="1">D7</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">MD3</td>
<td align="left" rowspan="1" colspan="1">Mojave Desert, California, USA</td>
<td align="left" rowspan="1" colspan="1">34°54′N, 115°39′W</td>
<td align="left" rowspan="1" colspan="1">5,899,497</td>
<td align="left" rowspan="1" colspan="1">590</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Desert</td>
<td align="left" rowspan="1" colspan="1">D8</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">SF2</td>
<td align="left" rowspan="1" colspan="1">Chihuahuan Desert, New Mexico, USA</td>
<td align="left" rowspan="1" colspan="1">35°23′N, 105°56′W</td>
<td align="left" rowspan="1" colspan="1">6,805,456</td>
<td align="left" rowspan="1" colspan="1">681</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Desert</td>
<td align="left" rowspan="1" colspan="1">D9</td>
<td align="left" rowspan="1" colspan="1">Illumina</td>
<td align="left" rowspan="1" colspan="1">SV1</td>
<td align="left" rowspan="1" colspan="1">Chihuahuan Desert, New Mexico, USA</td>
<td align="left" rowspan="1" colspan="1">34°20′N, 106°44′W</td>
<td align="left" rowspan="1" colspan="1">11,122,546</td>
<td align="left" rowspan="1" colspan="1">1,112</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Mangrove sediment</td>
<td align="left" rowspan="1" colspan="1">M1</td>
<td align="left" rowspan="1" colspan="1">454</td>
<td align="left" rowspan="1" colspan="1">NA</td>
<td align="left" rowspan="1" colspan="1">Bertioga, Brazil</td>
<td align="left" rowspan="1" colspan="1">23°53′S, 46°12′W</td>
<td align="left" rowspan="1" colspan="1">913,752</td>
<td align="left" rowspan="1" colspan="1">216</td>
<td align="left" rowspan="1" colspan="1"><xref rid="pone.0093445-Andreote1" ref-type="bibr">[23]</xref>
</td>
</tr>
</tbody>
</table>
</alternatives>
</table-wrap>
</sec>
<sec id="s2c"><title>Estimation of microbial composition</title>
<p>MetaPhlAn v1.7 <xref rid="pone.0093445-Segata3" ref-type="bibr">[24]</xref>
and BLAST v2.2.22 <xref rid="pone.0093445-Altschul1" ref-type="bibr">[25]</xref>
were employed for profiling the taxonomic clades in the metagenomic datasets. Briefly, metagenomic reads were firstly mapped to the MetaPhlAn reference database composed of unique clade-specific marker genes using BLASTN. The non-default parameters used for BLASTN sequencing similarity searching were as follows: E-value cutoff of 1e-10, word size of 12, and minimum alignment length of 75 nt. Relative abundance scores at all taxonomic levels from the domain level to the species level were then estimated by MetaPhlAn. In the text, mean values of abundances were shown for the mentioned taxon. To assess the compositional similarity among soil samples from different microbial communities, the Bray-Curtis measure of beta diversity <xref rid="pone.0093445-Bray1" ref-type="bibr">[26]</xref>
was employed to compare all pairwise taxonomic abundances between each sample-pair using a R function <italic>vegdist</italic>
in the package vegan <xref rid="pone.0093445-Oksanen1" ref-type="bibr">[27]</xref>
. The permutation-based multivariate analysis of variance (PERMANOVA) and 2D stress value were then estimated. Based on the resultant Bray-Curtis similarity distance matrix, non-metric multidimensional scaling (NMDS) was adopted to visualize the dispersion of community structure. Multivariate analysis was carried out using vegan <xref rid="pone.0093445-Oksanen1" ref-type="bibr">[27]</xref>
and R (<ext-link ext-link-type="uri" xlink:href="http://www.R-project.org">http://www.R-project.org</ext-link>
) <xref rid="pone.0093445-R1" ref-type="bibr">[28]</xref>
.</p>
</sec>
<sec id="s2d"><title>Metabolic reconstruction of metagenomes</title>
<p>Metabolic reconstruction was carried out using the HUMAnN methodology designed for the functional analyses of meta'omics <xref rid="pone.0093445-Abubucker1" ref-type="bibr">[29]</xref>
. High quality reads were initially mapped to the characterized protein functional database KEGG Orthology v54 <xref rid="pone.0093445-Kanehisa1" ref-type="bibr">[30]</xref>
using the accelerated translated BLAST program USEARCH v6.0.307 <xref rid="pone.0093445-Edgar1" ref-type="bibr">[31]</xref>
. The cutoff E-value was set to 1e-6 and best hits were then used to estimate relative abundances of KEGG orthologous (KO) gene families by HUMAnN v0.98. Base on the resulting KO information, MinPath was used to calculate the coverage and relative abundances of KEGG modules that are manually defined functional units <xref rid="pone.0093445-Ye1" ref-type="bibr">[32]</xref>
. Circular cladograms representing microbial taxonomic compositions and metabolic modules were implemented by using a standalone graphical tool GraPhlAn v0.9.5 (<ext-link ext-link-type="uri" xlink:href="http://huttenhower.sph.harvard.edu/GraPhlAn">http://huttenhower.sph.harvard.edu/GraPhlAn</ext-link>
).</p>
</sec>
<sec id="s2e"><title>Detection of metagenomic biomarkers</title>
<p>In order to further test whether some taxa/metabolic modules are significantly overrepresented in the individual soil habitat, statistical analyses were performed according to the inferred relative abundances. Differentially abundant features were identified by the approach of the linear discriminant analysis (LDA) effect size (LEfSe) and could be used as metagenomic biomarkers <xref rid="pone.0093445-Segata2" ref-type="bibr">[21]</xref>
. As the sample size is not very large in this test, the significance threshold of the alpha parameter for the Krushkal-Wallis (KW) test among classes was set to 0.01 and the cut-off logarithmic LDA score was 2.0. These analyses were performed through the Galaxy server <xref rid="pone.0093445-Goecks1" ref-type="bibr">[33]</xref>
. Additionally, a non-parametric test of Spearman rank correlation between the relative abundances of each KO entry and taxonomic unit was employed to estimate co-variation of community composition and functional features using the R function <italic>cor.test</italic>
.</p>
</sec>
<sec id="s2f"><title>Detection of microbial interactions</title>
<p>A recently developed computational methodology was used to investigate microbial co-occurrence and co-exclusion relationships within and between soil sites <xref rid="pone.0093445-Faust1" ref-type="bibr">[22]</xref>
. The microbial network of significant co-occurrence and co-exclusion interactions was built by a Cytoscape plugin CoNet 1.0b2 (<ext-link ext-link-type="uri" xlink:href="http://psbweb05.psb.ugent.be/conet/">http://psbweb05.psb.ugent.be/conet/</ext-link>
). The taxonomic abundances estimated by MetaPhlAn were used to prepare an input matrix consisting of data from three sites (grasslands, deserts, and forest soils). The analysis was carried out with the non-default parameters listed below: 50 initial top and bottom edges; four similarity measures (Spearman, Pearson, Kullbackleibler, and Bray Curtis); edgeScores for the randomization routine; 1000 permutations and bootstraps. The resulting networks were merged based on the Simes method <xref rid="pone.0093445-Sarkar1" ref-type="bibr">[34]</xref>
and Benjamini-Hochberg false discovery rate (FDR) correction <xref rid="pone.0093445-Benjamini1" ref-type="bibr">[35]</xref>
. The FDR cutoff was set to 0.05. The ensemble co-occurrence network was visualized by Cytoscape 2.8 <xref rid="pone.0093445-Smoot1" ref-type="bibr">[36]</xref>
.</p>
</sec>
</sec>
<sec id="s3"><title>Results and Discussion</title>
<sec id="s3a"><title>General characterization of soil community composition</title>
<p>To explore comprehensive characterizations of taxonomic compositions in the soil microbiota, 33 metagenomes sampled from five soil habitats (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment) were included in this analysis (<xref ref-type="table" rid="pone-0093445-t001">Table 1</xref>
). Based on the assessment by MetaPhlAn, a total of 63 clades (11 phyla and 53 genera) were identified at ≥0.5% abundance in at least one sample (<xref ref-type="supplementary-material" rid="pone.0093445.s004">Table S2</xref>
). Proteobacteria was the most dominated phylum in the microbial community of soil, ≥70% abundance detected in all soil sites except for the microbiota in the desert samples (<xref ref-type="fig" rid="pone-0093445-g001">Figure 1A</xref>
). In desert, both phyla Proteobacteria and Actinobacteria exhibit almost identical abundance: 30% for Proteobacteria and 29% for Actinobacteria. In addition, Firmicutes and Bacteroidetes, which are the two major phyla dominating the human microbiome <xref rid="pone.0093445-Qin1" ref-type="bibr">[37]</xref>
, <xref rid="pone.0093445-Segata4" ref-type="bibr">[38]</xref>
, were not frequently present in the soil microbial communities. Particularly, bacterial species within the Firmicutes rarely occurred in soil. As the taxonomic distribution of environmental metagenomic sequences are greatly affected by distinct reference databases <xref rid="pone.0093445-Andreote1" ref-type="bibr">[23]</xref>
, the 16S amplicon approach should provide more accurate taxonomic profiling than metagenome shotgun sequencing <xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
. Previous amplicon surveys of 16S rRNA gene have pointed out that bacterial phyla Acidobacteria, Actinobacteria, Bacteroidetes, Proteobacteria, and Verrucomicorbia are often abundant and ubiquitous in soil <xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
, <xref rid="pone.0093445-Janssen1" ref-type="bibr">[39]</xref>
. Although the clade-specific marker gene database in MetaPhlAn has successfully validated the composition of the human microbiome <xref rid="pone.0093445-Segata3" ref-type="bibr">[24]</xref>
, it still needs to be updated with more genomes sequenced recently from various environments.</p>
<fig id="pone-0093445-g001" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0093445.g001</object-id>
<label>Figure 1</label>
<caption><title>Taxonomic distribution of the soil microbial communities.</title>
<p>A) Distribution at the phylum level; B) Distribution at the family level. Labels show the taxonomic units with average relative abundance >2% in at least one of five soil habitats: desert, forest soil, grassland, Arctic soil, and mangrove sediment.</p>
</caption>
<graphic xlink:href="pone.0093445.g001"></graphic>
</fig>
<p>At the family level, several families were observed to be evidently more prevalent in and specific to one soil habitat or closely related habitats (<xref ref-type="fig" rid="pone-0093445-g001">Figure 1B</xref>
). For instance, the family <italic>Methylocystaceae</italic>
was dominated and almost equally present in both sites of forest soil (16.4% abundance) and grassland (17.1%) comparing with the other three soil habitats. Additionally, among five soil habitats, both families <italic>Ectothiorhodospiraceae</italic>
(37.0%) and <italic>Desulfobulbaceae</italic>
(30.8%) were found to be extremely abundant in the microbiota of mangrove sediment. The enrichment of these families could be reasonably explained by the selective pressures acting on certain ecological sites. For example, organisms within <italic>Methylocystaceae</italic>
are usually methanotrophs that can metabolize methane as their only carbon source and involved in methane oxidation <xref rid="pone.0093445-Dedysh1" ref-type="bibr">[40]</xref>
, <xref rid="pone.0093445-Dedysh2" ref-type="bibr">[41]</xref>
. The DNA-level evidence identified herein may support the oxidation of methane observed in forest soil and grasslands <xref rid="pone.0093445-Ojima1" ref-type="bibr">[42]</xref>
, <xref rid="pone.0093445-Jang1" ref-type="bibr">[43]</xref>
. In addition, the microbiota of mangrove sediments is known to be sampled from anaerobic and hyperhaline seawater <xref rid="pone.0093445-Andreote1" ref-type="bibr">[23]</xref>
. The corresponding environmental features should be beneficial for the dominance of <italic>Ectothiorhodospiraceae</italic>
and <italic>Desulfobulbaceae</italic>
in this particular habitat. The former comprises the most halophilic eubacteria <xref rid="pone.0093445-Imhoff1" ref-type="bibr">[44]</xref>
and bacteria in the latter family are strictly anaerobe sulphate reducers <xref rid="pone.0093445-Kuever1" ref-type="bibr">[45]</xref>
. However, it is worth mentioning that taxonomic profiling of individual metagenome is visually distinguished from those of the other metagenomes within the same soil habitat (<xref ref-type="supplementary-material" rid="pone.0093445.s001">Figure S1</xref>
). This is probably because publicly available soil metagenomes were generated by different research groups and varied in sampling strategies as well as sequencing methods. Thus, analysis of more soil metagenomes newly sequenced or coming soon is still required to statistically support the findings of soil biodiversity in the present study.</p>
</sec>
<sec id="s3b"><title>Structure similarity and taxonomic biomarkers of soil microbial communities</title>
<p>For a glimpse of structural similarity of soil microbial communities, ecological dissimilarity indices Bray-Curtis similarity scores were inferred and summarized in <xref ref-type="table" rid="pone-0093445-t002">Table 2</xref>
. The PERMANOVA test demonstrated that taxonomic compositions of microbial communities were significantly varied among soil habitats (<italic>p</italic>
= 0.001). Meanwhile, the NMDS plot in <xref ref-type="fig" rid="pone-0093445-g002">Figure 2</xref>
further illustrated the compositional similarity among 33 samples from five soil sites. These results demonstrated that the microbiota from the same soil habitat should be more similar to each other. The community structure similarity is also influenced by varied geographical locations. E.g., the soil samples from grasslands were intensively clustered together and the corresponding similarity score (Bray-Curtis index 0.80±0.07) is indeed the highest among all inter- or intra-group comparisons (<xref ref-type="table" rid="pone-0093445-t002">Table 2</xref>
). On the contrary, the Bray-Curtis similarity score between nine desert samples is the lowest (0.58±0.16) among all intra-group comparisons, perhaps due to their sampling environments: three samples from hot deserts but the remaining ones from cold deserts <xref rid="pone.0093445-Fierer2" ref-type="bibr">[12]</xref>
. Likewise, A2 sampled from the edge of the Arctic Circle is distant from A1 from high Arctic soil (<xref ref-type="table" rid="pone-0093445-t001">Table 1</xref>
). In addition, it was observed that the distances of most samples between forest soil and grasslands were closely clustered (<xref ref-type="fig" rid="pone-0093445-g002">Figure 2</xref>
) and the Bray-Curtis similarity score was consistently high (0.76±0.07). Whereas, the microbiota from two extreme conditions, desert and mangrove soil, respectively, exhibited the greatest compositional dissimilarity (0.37±0.07) among all inter-group comparisons.</p>
<fig id="pone-0093445-g002" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0093445.g002</object-id>
<label>Figure 2</label>
<caption><title>A nonmetric multidimensional scaling (NMDS) plot showing diversity of soil ecosystems.</title>
<p>A Bray-Curtis distance similarity matrix was calculated based on the pairwise taxonomic profiles of 33 soil samples and used to generate NMDS coordinates of each sample. The distance linking two samples is shorter, indicating higher similarity between these samples. Samples from five soil sites were illustrated by different symbols and colors.</p>
</caption>
<graphic xlink:href="pone.0093445.g002"></graphic>
</fig>
<table-wrap id="pone-0093445-t002" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0093445.t002</object-id>
<label>Table 2</label>
<caption><title>Community structure similarity of the soil metagenomes within a habitat or between habitat pair.</title>
</caption>
<alternatives><graphic id="pone-0093445-t002-2" xlink:href="pone.0093445.t002"></graphic>
<table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
</colgroup>
<thead><tr><td align="left" rowspan="1" colspan="1">Biome type</td>
<td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1">Forest soil</td>
<td align="left" rowspan="1" colspan="1">Arctic soil</td>
<td align="left" rowspan="1" colspan="1">Desert</td>
<td align="left" rowspan="1" colspan="1">Mangrove soil</td>
</tr>
</thead>
<tbody><tr><td align="left" rowspan="1" colspan="1">Grassland</td>
<td align="left" rowspan="1" colspan="1"><bold>0.80±0.07</bold>
</td>
<td align="left" rowspan="1" colspan="1">0.76±0.07</td>
<td align="left" rowspan="1" colspan="1">0.68±0.09</td>
<td align="left" rowspan="1" colspan="1">0.50±0.12</td>
<td align="left" rowspan="1" colspan="1">0.45±0.02</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Forest soil</td>
<td align="left" rowspan="1" colspan="1">0.76±0.07</td>
<td align="left" rowspan="1" colspan="1"><bold>0.77</bold>
±<bold>0.05</bold>
</td>
<td align="left" rowspan="1" colspan="1">0.68±0.10</td>
<td align="left" rowspan="1" colspan="1">0.48±0.12</td>
<td align="left" rowspan="1" colspan="1">0.45±0.05</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Arctic soil</td>
<td align="left" rowspan="1" colspan="1">0.68±0.09</td>
<td align="left" rowspan="1" colspan="1">0.68±0.10</td>
<td align="left" rowspan="1" colspan="1">NA</td>
<td align="left" rowspan="1" colspan="1">0.45±0.11</td>
<td align="left" rowspan="1" colspan="1">0.52±0.15</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Desert</td>
<td align="left" rowspan="1" colspan="1">0.50±0.12</td>
<td align="left" rowspan="1" colspan="1">0.48±0.12</td>
<td align="left" rowspan="1" colspan="1">0.45±0.11</td>
<td align="left" rowspan="1" colspan="1"><bold>0.58</bold>
±<bold>0.16</bold>
</td>
<td align="left" rowspan="1" colspan="1">0.37±0.07</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Mangrove soil</td>
<td align="left" rowspan="1" colspan="1">0.45±0.02</td>
<td align="left" rowspan="1" colspan="1">0.45±0.05</td>
<td align="left" rowspan="1" colspan="1">0.52±0.15</td>
<td align="left" rowspan="1" colspan="1">0.37±0.07</td>
<td align="left" rowspan="1" colspan="1">NA</td>
</tr>
</tbody>
</table>
</alternatives>
<table-wrap-foot><fn id="nt101"><label></label>
<p>Mean and standard deviation of Bray-cutis similarities of all pairwise samples between any pair of soil habitats were shown herein. The number of sample combination less than 2 was denoted by NA.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>To further investigate the taxonomic distribution and differentially abundant clades of diverse soil ecosystems, we compared the abundances of microbial compositions at each taxonomic level. <xref ref-type="fig" rid="pone-0093445-g003">Figure 3A</xref>
shows a cladogram visualizing all detected microbial compositions (≥0.5% abundance) from domain to species, respectively. Based on the inferred taxonomic profiling of all samples, a statistical strategy for discovering metagenomic biomarkers was carried out by LEfSe and determined 46 differentially abundant taxa (<xref ref-type="supplementary-material" rid="pone.0093445.s004">Table S2</xref>
). Among these differentially abundant taxa, 10 and 12 were found to be family- and genus-level biomarkers, respectively (<xref ref-type="fig" rid="pone-0093445-g003">Figure 3A</xref>
). These detected taxonomic biomarkers could be used as candidate indicators to distinguish at least one microbial community of five individual soil habitats. E.g., two families <italic>Beijerinckiaceae</italic>
and <italic>Methylocystaceae</italic>
that consist of methanotrophic taxa <xref rid="pone.0093445-Lau1" ref-type="bibr">[46]</xref>
were detected to be family-level biomarkers (<italic>P</italic>
value <0.01) that were most abundant in the forest soil and grassland, respectively. The abundances of both families were found to be significantly decreased in desert and mangrove sediment (<xref ref-type="fig" rid="pone-0093445-g003">Figure 3B</xref>
). The abundance differences of these methanotrophs might be positively associated with the expected capability of methane oxidation among distinct soil ecosystems. Although the organisms within the <italic>Alphaproteobacteria</italic>
class were most differentially abundant in the grassland community, a genus-level biomarker within <italic>Alphaproteobacteria</italic>
was specially enriched in the communities of forest soil and Arctic soil, respectively (<xref ref-type="fig" rid="pone-0093445-g003">Figure 3A</xref>
). Intriguingly, the desert community had two phylum-level markers, Cyanobacteria and Chloroflexi, both of which showed the highest abundance in deserts comparing with other soil sites (<xref ref-type="fig" rid="pone-0093445-g003">Figure 3A</xref>
). Bacteria in both phyla can produce their energy through photosynthesis <xref rid="pone.0093445-Mulkidjanian1" ref-type="bibr">[47]</xref>
. It was worth noting that the family Oscillatoriaceae within Cyanobacteria was significantly enriched in the desert microbial community (<xref ref-type="fig" rid="pone-0093445-g003">Figure 3B</xref>
). The enrichment of these bacterial groups should be consistent with the following environmental features of deserts: extreme arid, strong light, and poor nutrient conditions. In addition, six species were found to be differentially abundant, some of which were uniquely present in the individual soil habitat. E.g., <italic>Rubrobacter xylanophilus</italic>
only occurs in the microbiota of deserts. <italic>R. xylanophilus</italic>
is the most thermophilic actinobacterium known and bears extreme tolerance to desiccation <xref rid="pone.0093445-Empadinhas1" ref-type="bibr">[48]</xref>
. <italic>Bradyrhizobium japonicum</italic>
, an agriculturally important species of legume-root nodulating <xref rid="pone.0093445-Kaneko1" ref-type="bibr">[49]</xref>
, was found to be the most abundant in grassland and second in forest soil.</p>
<fig id="pone-0093445-g003" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0093445.g003</object-id>
<label>Figure 3</label>
<caption><title>Taxonomic composition of soil microbial community based on the metagenomes from five soil habitats.</title>
<p>A) Taxonomic cladogram showing all detected taxa (relative abundance ≥0.5%) in at least one sample. Taxonomic clades with more than five samples ≥0.5% abundance were used as inputs for LEfSe. Seven rings of the cladogram stand for domain (innermost), phylum, class, order, family, genus, and species (outermost), respectively. Enlarged circles in color are the differentially abundant taxa identified to be metagenomic biomarkers and the circle color is corresponding to the individual soil habitat in which the taxon is the most abundant among 5 soil ecosystems (Green for forest soil, red for grassland, purple for Arctic soil, blue for mangrove sediment, and orange for desert). B) The histograms of relative abundances of family-level biomarkers in each sample. Bacterial families significantly differential among all pairwise comparisons were illustrated. The average abundance of each family in the individual soil habitat was denoted by the horizontal line.</p>
</caption>
<graphic xlink:href="pone.0093445.g003"></graphic>
</fig>
</sec>
<sec id="s3c"><title>Metabolic potential and functional biomarkers of soil microbial communities</title>
<p>Besides microbial composition, metabolic potential of soil microbial communities was also investigated. In this study, we focused on the KEGG modules that are tight functional units composed of approximately 5 to 20 genes and beneficial for biological interpretation of metagenomes <xref rid="pone.0093445-Abubucker1" ref-type="bibr">[29]</xref>
, <xref rid="pone.0093445-Kanehisa1" ref-type="bibr">[30]</xref>
, <xref rid="pone.0093445-Segata4" ref-type="bibr">[38]</xref>
. To further enhance the performance of statistical inference on the functional analysis, two soil sites with limited samples (two samples from Arctic soil and one sample from mangrove sediment) were excluded. After translated BLAST searching against the database of KO gene families, we found an average of ∼33.6% of reads mapped to at least one KO entry (<xref ref-type="supplementary-material" rid="pone.0093445.s005">Table S3</xref>
). Based on the metabolic reconstruction of 30 metagenomic datasets using HUMAnN, <xref ref-type="fig" rid="pone-0093445-g004">Figure 4</xref>
shows 119 functional modules detected in the microbial communities of grasslands, forest soils, and deserts (<xref ref-type="supplementary-material" rid="pone.0093445.s006">Table S4</xref>
). Of these functional modules, we found 20 core metabolic modules that were almost entirely present at >90% coverage in all soil metagenomes tested (<xref ref-type="table" rid="pone-0093445-t003">Table 3</xref>
). Some of these core modules were essential for basic life activities of prokaryotic cells in soil, such as central carbon metabolism (M00002-3, M00007, M00009, M00011-12), nucleotide and amino acid metabolism (M00016, M00018, M00048, M00115, M00125), translation (M00178, M00359-360), and ATP synthesis (M00144). In addition, all the remaining core modules were involved in certain transport systems, three (M00207, M00222, M00239) of which are also detected in the core modules of the human microbiome <xref rid="pone.0093445-Abubucker1" ref-type="bibr">[29]</xref>
. On the other hand, three functional modules (M00026, M00133, M00319) were differentially covered among three soil sites (<xref ref-type="fig" rid="pone-0093445-g004">Figure 4</xref>
; <xref ref-type="supplementary-material" rid="pone.0093445.s007">Table S5</xref>
). It was worth noting that structural complex module manganese/zinc/iron transport system (M00319) was completely present only in the deserts but appeared to be absent in both grasslands and forest soils. It indicates that deserts microbiota is well-equipped with metal acquisition systems that play potential roles in the maintenance of metal homeostasis <xref rid="pone.0093445-Desrosiers1" ref-type="bibr">[50]</xref>
.</p>
<fig id="pone-0093445-g004" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0093445.g004</object-id>
<label>Figure 4</label>
<caption><title>Metagenome-level metabolic reconstruction of the soil microbial community.</title>
<p>KEGG BRITE hierarchical structures that are illustrated by the innermost four rings were used to cluster metabolic modules. The outermost ring composed of circles denotes KEGG functional modules detected in at least one of 30 metagenomes from three soil sites. Differentially abundant modules were inferred by LEfSe and illustrated by the enlarged circles in distinct colors: green stands for the modules most abundant in the forest soil, red for the grassland, and orange for the desert. The outermost rectangles denote core and differentially covered modules among three soil sites: ≥90% coverage stands for presence and ≤10% coverage for absence.</p>
</caption>
<graphic xlink:href="pone.0093445.g004"></graphic>
</fig>
<table-wrap id="pone-0093445-t003" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0093445.t003</object-id>
<label>Table 3</label>
<caption><title>Core metabolic modules shared by grasslands, deserts, and forest soils.</title>
</caption>
<alternatives><graphic id="pone-0093445-t003-3" xlink:href="pone.0093445.t003"></graphic>
<table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col>
<col align="center" span="1"></col>
</colgroup>
<thead><tr><td align="left" rowspan="1" colspan="1">Module ID</td>
<td align="left" rowspan="1" colspan="1">Definition of modules in KEGG</td>
</tr>
</thead>
<tbody><tr><td align="left" rowspan="1" colspan="1">M00002</td>
<td align="left" rowspan="1" colspan="1">Glycolysis, core module involving three-carbon compounds</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00003</td>
<td align="left" rowspan="1" colspan="1">Gluconeogenesis, oxaloacetate = > fructose-6P</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00007</td>
<td align="left" rowspan="1" colspan="1">Pentose phosphate pathway, non-oxidative phase, fructose 6P = > ribose 5P</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00009</td>
<td align="left" rowspan="1" colspan="1">Citrate cycle (TCA cycle, Krebs cycle)</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00011</td>
<td align="left" rowspan="1" colspan="1">Citrate cycle, second carbon oxidation</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00012</td>
<td align="left" rowspan="1" colspan="1">Glyoxylate cycle</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00016</td>
<td align="left" rowspan="1" colspan="1">Lysine biosynthesis, aspartate = > lysine</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00018</td>
<td align="left" rowspan="1" colspan="1">Threonine biosynthesis, apartate = > homoserine = > threonine</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00048</td>
<td align="left" rowspan="1" colspan="1">Inosine monophosphate biosynthesis, PRPP + glutamine = > IMP</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00115</td>
<td align="left" rowspan="1" colspan="1">NAD biosynthesis, aspartate = > NAD</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00125</td>
<td align="left" rowspan="1" colspan="1">Riboflavin biosynthesis, GTP = > riboflavin/FMN/FAD</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00144</td>
<td align="left" rowspan="1" colspan="1">Complex I (NADH dehydrogenase), NADH dehydrogenase I</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00178</td>
<td align="left" rowspan="1" colspan="1">Ribosome, bacteria</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00185</td>
<td align="left" rowspan="1" colspan="1">Sulfate transport system</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00207</td>
<td align="left" rowspan="1" colspan="1">Multiple sugar transport system</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00222</td>
<td align="left" rowspan="1" colspan="1">Phosphate transport system</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00237</td>
<td align="left" rowspan="1" colspan="1">Branched-chain amino acid transport system</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00239</td>
<td align="left" rowspan="1" colspan="1">Peptides/nickel transport system</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00359</td>
<td align="left" rowspan="1" colspan="1">Aminoacyl-tRNA biosynthesis, eukaryotes</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">M00360</td>
<td align="left" rowspan="1" colspan="1">Aminoacyl-tRNA biosynthesis, prokaryotes</td>
</tr>
</tbody>
</table>
</alternatives>
</table-wrap>
<p>Furthermore, 33 functional modules were detected to be differentially abundant in at least one of three soil sites (<xref ref-type="fig" rid="pone-0093445-g004">Figure 4</xref>
and <xref ref-type="supplementary-material" rid="pone.0093445.s006">Table S4</xref>
). Interestingly, two thirds of these modules were significantly enriched in the microbiota of deserts in comparison to the microbiota of grasslands and forest soils. Of them, three metabolic modules (M00165-167) are involved in the reductive pentose phosphate cycle (Benson-Calvin cycle), which is the main pathway for the conversion of atmospheric CO<sub>2</sub>
to organic compounds <xref rid="pone.0093445-Wolosiuk1" ref-type="bibr">[51]</xref>
. It was worth noting that these overrepresented modules involved in carbon fixation might be consistent with high abundance of photosynthetic organisms Cyanobacteria present in the microbiota of desert. Additionally, eight structural complex modules detected to be functional biomarkers in deserts are responsible for the transport of metallic cation (M00317, M00319), mineral and organic ion (M00321, M00299), saccharide and polyol (M00201, M00199), glutamate (M00233), and urea (M00323). On the other hand, we found that two metabolic modules (M00022: Shikimate pathway and M00237: Branched chain amino acid transport system) were significantly overrepresented in grasslands and forest soils comparing with plant-free deserts (<xref ref-type="fig" rid="pone-0093445-g004">Figure 4</xref>
and <xref ref-type="supplementary-material" rid="pone.0093445.s006">Table S4</xref>
). Both modules are associated with plant-derived metabolites <xref rid="pone.0093445-Maloney1" ref-type="bibr">[52]</xref>
, <xref rid="pone.0093445-Maeda1" ref-type="bibr">[53]</xref>
. These results showed that some modular metabolic activities are likely to be associated with the individual soil ecosystem. However, more metagenome samples from different sites are needed for accurately statistical validation of these characterized modules as promising biomarkers for diverse soil communities.</p>
</sec>
<sec id="s3d"><title>Correlation between microbial compositions and functions</title>
<p>Similar to the approach presented by Segata et al. <xref rid="pone.0093445-Segata4" ref-type="bibr">[38]</xref>
, we assessed the correlations between microbial compositional and functional enrichment. The results showed that some significant associations between taxonomic clades and functional gene families were detected in the soil microbial communities (Spearman non-parametric test; Benjamini-Hochberg corrected <italic>p</italic>
-value <0.01) (<xref ref-type="supplementary-material" rid="pone.0093445.s002">Figure S2</xref>
). Notably, several taxonomic biomarkers possessed by individual microbial community mentioned above were further confirmed by the related strong associations between gene families and taxonomic clades. E.g. the gene <italic>petA</italic>
(K02634) encoding apocytochrome f protein involved in photosynthesis was positively associated with the members of Cyanobacteria (Spearman test; <italic>q</italic>
-value <0.001), one of the earliest prokaryotic organisms which can carry out oxygenic photosynthesis on Earth <xref rid="pone.0093445-Mulkidjanian1" ref-type="bibr">[47]</xref>
. In addition, a significantly positive correlation (Spearman test; <italic>q</italic>
-value <0.001) between methanotrophs <italic>Methylocystaceae</italic>
and the gene <italic>mcl</italic>
(K08691) coding for malyl-CoA lyase was observed in the microbial community of grassland. The enrichment of protein Mcl involved in both pathways of methane metabolism and carbon fixation, should be consistent with the featured metabolic activities of these methanotrophs.</p>
</sec>
<sec id="s3e"><title>Soil microbial interaction network</title>
<p>To further decipher complex ecological relationships in the individual soil microbial community, microbial association networks were inferred based on the estimated taxonomic profiling. In this case, we intended to focus on the microbial associations within the single soil habitat, i.e. forest soil, grassland, and desert. The resultant metagenome-wide networks comprised 126 significant associations among 66 phylotypes at or above the genus level (Benjamini-Hochberg corrected <italic>p</italic>
-value <0.05) (<xref ref-type="fig" rid="pone-0093445-g005">Figure 5</xref>
). Of these significant phylotype correlations, 54% was detected to be co-present and the remaining was mutually excluded. Interestingly, we found that three quarters (∼74%) of co-occurrence patterns were constituted by the taxa within the same phyla; whereas nearly all co-exclusion patterns (∼90%) consisted of the taxa from the distinct phyla. The evidence presented herein can again support the previous notion that phylotypes with closely evolutionary relationships usually tend to co-occur <xref rid="pone.0093445-Barbern1" ref-type="bibr">[8]</xref>
. E.g., three families (<italic>Bifidobacteriaceae</italic>
, <italic>Mycobacteriaceae</italic>
, and <italic>Frankiaceae</italic>
) belonging to the same class Actinobacteria showed pairwise positive correlation in the microbiota of desert (<xref ref-type="fig" rid="pone-0093445-g005">Figure 5</xref>
). Similar taxon co-occurrence pattern was also found between <italic>Bifidobacteriaceae</italic>
and <italic>Frankiaceae</italic>
in the microbiota of grassland. Additionally, two genera within the family <italic>Bradyrhizobiaceae</italic>
co-occurred in the grassland community: one is nitrogen-fixing bacteria <italic>Nitrobacter</italic>
and the other is phototrophic bacteria <italic>Rhodopseudomonas</italic>
. On the other hand, those mutually excluded bacteria were found to be evolutionarily unrelated. E.g., <italic>Sphingobacteriaceae</italic>
belonging to the Bacteroidetes were negatively associated with <italic>Desulfovibrionaceae</italic>
from the Proteobacteria and <italic>Rubrobacteraceae</italic>
from the Actinobacteria in the microbiota of desert (<xref ref-type="fig" rid="pone-0093445-g005">Figure 5</xref>
). Although most phylotype associations in the network lack empirical evidence to support their natural presence, it provides some promising targets at least to shed light on the complex cooperative or competitive mechanisms among soil microorganisms.</p>
<fig id="pone-0093445-g005" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0093445.g005</object-id>
<label>Figure 5</label>
<caption><title>A global microbial interaction network of the soil microbial community.</title>
<p>The network captured all significant associations (multiple corrected <italic>p</italic>
-value <0.05) among the abundances of phylotypes at or above the genus level in the soil microbial community within and across the three soil sites. Phylotypes were illustrated by nodes (light blue for grasslands, blue for forest soils, and yellow for deserts) and edges denote significant correlations between phylotypes: positive correlation colored in green means co-occurrence whereas negative correlation in red means mutual exclusion. The border of nodes was colored according to taxonomic affiliations at the class level.</p>
</caption>
<graphic xlink:href="pone.0093445.g005"></graphic>
</fig>
</sec>
</sec>
<sec id="s4"><title>Conclusions</title>
<p>In this study, comparative metagenomic characterizations of divergent soil microbial communities were described in details by an integrated bioinformatics analysis pipeline. Complicated phylogenetic and metabolic networks with a spectrum of taxonomic and functional biomarkers were comprehensively illustrated at the metagenome level for soil. Cooperative or competitive associations among microbes from diverse soil ecosystems were also inferred to understand complex microbial interactions in the soil metagenome. This study provides new insights into the relation between soil biodiversity and ecosystem function, and provides applicable analysis and visualization approaches for studying soil microbial communities.</p>
</sec>
<sec sec-type="supplementary-material" id="s5"><title>Supporting Information</title>
<supplementary-material content-type="local-data" id="pone.0093445.s001"><label>Figure S1</label>
<caption><p><bold>Taxonomic distribution of 33 metagenomes from soil microbial communities.</bold>
A) Distribution at the phylum level; B) Distribution at the family level. Labels show the taxonomic units with average relative abundance >2% in at least one of 33 samples.</p>
<p>(TIF)</p>
</caption>
<media xlink:href="pone.0093445.s001.tif"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
<supplementary-material content-type="local-data" id="pone.0093445.s002"><label>Figure S2</label>
<caption><p><bold>Co-variation of bacterial clades and KEGG orthologous gene families in the desert microbiome.</bold>
The spearman non-parametric correlation of each KEGG gene family against each taxonomic clade was assessed. After multiple testing corrections based on the Benjamini-Hochberg procedure, a network of significant correlations between gene families and taxonomic clades was shown herein (q-value <0.01). Ellipses denote taxa and rectangles stand for KEGG gene families. The edge linking taxonomic clade and gene family indicates that strong correlation was detected in the individual microbial community: green for forest soil, red for grassland, and orange for desert.</p>
<p>(TIF)</p>
</caption>
<media xlink:href="pone.0093445.s002.tif"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
<supplementary-material content-type="local-data" id="pone.0093445.s003"><label>Table S1</label>
<caption><p>Sequence data accession numbers and/or web links of soil metagenomes used in this study.</p>
<p>(XLSX)</p>
</caption>
<media xlink:href="pone.0093445.s003.xlsx"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
<supplementary-material content-type="local-data" id="pone.0093445.s004"><label>Table S2</label>
<caption><p>Taxonomic profiling of the soil metagenomes estimated in this study. Relative abundances of taxa were inferred by MetaPhlAn. Differentially abundant clades among five soil habitats were detected by LEfSe and labeled by the soil site with the highest LDA score among pairwise comparisons of all sites. According to the non-strict and strict statistical strategy, 46 taxonomic biomarkers were detected to be significantly differential in at least one of five soil habitats.</p>
<p>(XLSX)</p>
</caption>
<media xlink:href="pone.0093445.s004.xlsx"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
<supplementary-material content-type="local-data" id="pone.0093445.s005"><label>Table S3</label>
<caption><p>The proportion of reads mapped to MetaPhlAn clade-specific marker genes and KEGG orthologous gene families.</p>
<p>(XLSX)</p>
</caption>
<media xlink:href="pone.0093445.s005.xlsx"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
<supplementary-material content-type="local-data" id="pone.0093445.s006"><label>Table S4</label>
<caption><p>Estimated values for relative abundances of KEGG functional modules in the soil microbial community. Differentially abundant modules were detected by LEfSe and labeled by the soil habitat with the highest LDA score among pairwise comparisons of all habitats.</p>
<p>(XLSX)</p>
</caption>
<media xlink:href="pone.0093445.s006.xlsx"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
<supplementary-material content-type="local-data" id="pone.0093445.s007"><label>Table S5</label>
<caption><p>Estimated values represented by percentage of the coverage of KEGG functional modules in the soil microbial community. The presence/absence of modules was defined as follows: the median of coverage estimates of the samples per site >0.9 stands for presence; the median <0.1 for absence.</p>
<p>(XLSX)</p>
</caption>
<media xlink:href="pone.0093445.s007.xlsx"><caption><p>Click here for additional data file.</p>
</caption>
</media>
</supplementary-material>
</sec>
</body>
<back><ref-list><title>References</title>
<ref id="pone.0093445-Daniel1"><label>1</label>
<mixed-citation publication-type="journal"><name><surname>Daniel</surname>
<given-names>R</given-names>
</name>
(<year>2005</year>
) <article-title>The metagenomics of soil</article-title>
. <source>Nat Rev Microbiol</source>
<volume>3</volume>
: <fpage>470</fpage>
–<lpage>478</lpage>
<pub-id pub-id-type="pmid">15931165</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Vogel1"><label>2</label>
<mixed-citation publication-type="journal"><name><surname>Vogel</surname>
<given-names>TM</given-names>
</name>
, <name><surname>Simonet</surname>
<given-names>P</given-names>
</name>
, <name><surname>Jansson</surname>
<given-names>JK</given-names>
</name>
, <name><surname>Hirsch</surname>
<given-names>PR</given-names>
</name>
, <name><surname>Tiedje</surname>
<given-names>JM</given-names>
</name>
, <etal>et al</etal>
(<year>2009</year>
) <article-title>TerraGenome: a consortium for the sequencing of a soil metagenome</article-title>
. <source>Nat Rev Microbiol</source>
<volume>7</volume>
: <fpage>252</fpage>
</mixed-citation>
</ref>
<ref id="pone.0093445-Delmont1"><label>3</label>
<mixed-citation publication-type="journal"><name><surname>Delmont</surname>
<given-names>TO</given-names>
</name>
, <name><surname>Robe</surname>
<given-names>P</given-names>
</name>
, <name><surname>Cecillon</surname>
<given-names>S</given-names>
</name>
, <name><surname>Clark</surname>
<given-names>IM</given-names>
</name>
, <name><surname>Constancias</surname>
<given-names>F</given-names>
</name>
, <etal>et al</etal>
(<year>2011</year>
) <article-title>Accessing the soil metagenome for studies of microbial diversity</article-title>
. <source>Appl Environ Microbiol</source>
<volume>77</volume>
: <fpage>1315</fpage>
–<lpage>1324</lpage>
<pub-id pub-id-type="pmid">21183646</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Torsvik1"><label>4</label>
<mixed-citation publication-type="journal"><name><surname>Torsvik</surname>
<given-names>V</given-names>
</name>
, <name><surname>Øvreås</surname>
<given-names>L</given-names>
</name>
(<year>2002</year>
) <article-title>Microbial diversity and function in soil: from genes to ecosystems</article-title>
. <source>Curr Opin Microbiol</source>
<volume>5</volume>
: <fpage>240</fpage>
–<lpage>245</lpage>
<pub-id pub-id-type="pmid">12057676</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Henne1"><label>5</label>
<mixed-citation publication-type="journal"><name><surname>Henne</surname>
<given-names>A</given-names>
</name>
, <name><surname>Daniel</surname>
<given-names>R</given-names>
</name>
, <name><surname>Schmitz</surname>
<given-names>RA</given-names>
</name>
, <name><surname>Gottschalk</surname>
<given-names>G</given-names>
</name>
(<year>1999</year>
) <article-title>Construction of environmental DNA libraries in <italic>Escherichia coli</italic>
and screening for the presence of genes conferring utilization of 4-hydroxybutyrate</article-title>
. <source>Appl Environ Microbiol</source>
<volume>65</volume>
: <fpage>3901</fpage>
–<lpage>3907</lpage>
<pub-id pub-id-type="pmid">10473393</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Rondon1"><label>6</label>
<mixed-citation publication-type="journal"><name><surname>Rondon</surname>
<given-names>MR</given-names>
</name>
, <name><surname>August</surname>
<given-names>PR</given-names>
</name>
, <name><surname>Bettermann</surname>
<given-names>AD</given-names>
</name>
, <name><surname>Brady</surname>
<given-names>SF</given-names>
</name>
, <name><surname>Grossman</surname>
<given-names>TH</given-names>
</name>
, <etal>et al</etal>
(<year>2000</year>
) <article-title>Cloning the soil metagenome: a strategy for accessing the genetic and functional diversity of uncultured microorganisms</article-title>
. <source>Appl Environ Microbiol</source>
<volume>66</volume>
: <fpage>2541</fpage>
–<lpage>2547</lpage>
<pub-id pub-id-type="pmid">10831436</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Fierer1"><label>7</label>
<mixed-citation publication-type="journal"><name><surname>Fierer</surname>
<given-names>N</given-names>
</name>
, <name><surname>Lauber</surname>
<given-names>CL</given-names>
</name>
, <name><surname>Ramirez</surname>
<given-names>KS</given-names>
</name>
, <name><surname>Zaneveld</surname>
<given-names>J</given-names>
</name>
, <name><surname>Bradford</surname>
<given-names>MA</given-names>
</name>
, <etal>et al</etal>
(<year>2012</year>
) <article-title>Comparative metagenomic, phylogenetic and physiological analyses of soil microbial communities across nitrogen gradients</article-title>
. <source>ISME J</source>
<volume>6</volume>
: <fpage>1007</fpage>
–<lpage>1017</lpage>
<pub-id pub-id-type="pmid">22134642</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Barbern1"><label>8</label>
<mixed-citation publication-type="journal"><name><surname>Barberán</surname>
<given-names>A</given-names>
</name>
, <name><surname>Bates</surname>
<given-names>ST</given-names>
</name>
, <name><surname>Casamayor</surname>
<given-names>EO</given-names>
</name>
, <name><surname>Fierer</surname>
<given-names>N</given-names>
</name>
(<year>2012</year>
) <article-title>Using network analysis to explore co-occurrence patterns in soil microbial communities. ISME J</article-title>
. <volume>6</volume>
: <fpage>343</fpage>
–<lpage>351</lpage>
</mixed-citation>
</ref>
<ref id="pone.0093445-DeAngelis1"><label>9</label>
<mixed-citation publication-type="journal"><name><surname>De Angelis</surname>
<given-names>KM</given-names>
</name>
, <name><surname>Gladden</surname>
<given-names>JM</given-names>
</name>
, <name><surname>Allgaier</surname>
<given-names>M</given-names>
</name>
, <name><surname>Dhaeseleer</surname>
<given-names>P</given-names>
</name>
, <name><surname>Fortney</surname>
<given-names>JL</given-names>
</name>
, <etal>et al</etal>
(<year>2010</year>
) <article-title>Strategies for enhancing the effectiveness of metagenomic based enzyme discovery in lignocellulolytic microbial communities</article-title>
. <source>Bioenerg Res</source>
<volume>3</volume>
: <fpage>146</fpage>
–<lpage>158</lpage>
</mixed-citation>
</ref>
<ref id="pone.0093445-Delmont2"><label>10</label>
<mixed-citation publication-type="journal"><name><surname>Delmont</surname>
<given-names>TO</given-names>
</name>
, <name><surname>Prestat</surname>
<given-names>E</given-names>
</name>
, <name><surname>Keegan</surname>
<given-names>KP</given-names>
</name>
, <name><surname>Faubladier</surname>
<given-names>M</given-names>
</name>
, <name><surname>Robe</surname>
<given-names>P</given-names>
</name>
, <etal>et al</etal>
(<year>2012</year>
) <article-title>Structure, fluctuation and magnitude of a natural grassland soil metagenome</article-title>
. <source>ISME J</source>
<volume>6</volume>
: <fpage>1677</fpage>
–<lpage>1687</lpage>
<pub-id pub-id-type="pmid">22297556</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Stewart1"><label>11</label>
<mixed-citation publication-type="journal"><name><surname>Stewart</surname>
<given-names>FJ</given-names>
</name>
, <name><surname>Sharma</surname>
<given-names>AK</given-names>
</name>
, <name><surname>Bryant</surname>
<given-names>JA</given-names>
</name>
, <name><surname>Eppley</surname>
<given-names>JM</given-names>
</name>
, <name><surname>DeLong</surname>
<given-names>EF</given-names>
</name>
(<year>2011</year>
) <article-title>Community transcriptomics reveals universal patterns of protein sequence conservation in natural microbial communities</article-title>
. <source>Genome Biol</source>
<volume>12</volume>
: <fpage>R26</fpage>
<pub-id pub-id-type="pmid">21426537</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Fierer2"><label>12</label>
<mixed-citation publication-type="journal"><name><surname>Fierer</surname>
<given-names>N</given-names>
</name>
, <name><surname>Leff</surname>
<given-names>JW</given-names>
</name>
, <name><surname>Adams</surname>
<given-names>BJ</given-names>
</name>
, <name><surname>Nielsen</surname>
<given-names>UN</given-names>
</name>
, <name><surname>Bates</surname>
<given-names>ST</given-names>
</name>
, <etal>et al</etal>
(<year>2012</year>
) <article-title>Cross-biome metagenomic analyses of soil microbial communities and their functional attributes</article-title>
. <source>Proc Natl Acad Sci U S A</source>
<volume>109</volume>
: <fpage>21390</fpage>
–<lpage>21395</lpage>
<pub-id pub-id-type="pmid">23236140</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Yergeau1"><label>13</label>
<mixed-citation publication-type="journal"><name><surname>Yergeau</surname>
<given-names>E</given-names>
</name>
, <name><surname>Sanschagrin</surname>
<given-names>S</given-names>
</name>
, <name><surname>Beaumier</surname>
<given-names>D</given-names>
</name>
, <name><surname>Greer</surname>
<given-names>CW</given-names>
</name>
(<year>2012</year>
) <article-title>Metagenomic analysis of the bioremediation of diesel-contaminated Canadian high arctic soils. PLoS One</article-title>
. <volume>7</volume>
: <fpage>e30058</fpage>
</mixed-citation>
</ref>
<ref id="pone.0093445-Langille1"><label>14</label>
<mixed-citation publication-type="journal"><name><surname>Langille</surname>
<given-names>MG</given-names>
</name>
, <name><surname>Zaneveld</surname>
<given-names>J</given-names>
</name>
, <name><surname>Caporaso</surname>
<given-names>JG</given-names>
</name>
, <name><surname>McDonald</surname>
<given-names>D</given-names>
</name>
, <name><surname>Knights</surname>
<given-names>D</given-names>
</name>
, <etal>et al</etal>
(<year>2013</year>
) <article-title>Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences</article-title>
. <source>Nat Biotechnol</source>
<volume>31</volume>
: <fpage>814</fpage>
–<lpage>821</lpage>
<pub-id pub-id-type="pmid">23975157</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Meyer1"><label>15</label>
<mixed-citation publication-type="journal"><name><surname>Meyer</surname>
<given-names>F</given-names>
</name>
, <name><surname>Paarmann</surname>
<given-names>D</given-names>
</name>
, <name><surname>DSouza</surname>
<given-names>M</given-names>
</name>
, <name><surname>Olson</surname>
<given-names>R</given-names>
</name>
, <name><surname>Glass</surname>
<given-names>EM</given-names>
</name>
, <etal>et al</etal>
(<year>2008</year>
) <article-title>The metagenomics RAST server - a public resource for the automatic phylogenetic and functional analysis of metagenomes</article-title>
. <source>BMC Bioinformatics</source>
<volume>9</volume>
: <fpage>386</fpage>
<pub-id pub-id-type="pmid">18803844</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Markowitz1"><label>16</label>
<mixed-citation publication-type="journal"><name><surname>Markowitz</surname>
<given-names>VM</given-names>
</name>
, <name><surname>Chen</surname>
<given-names>IM</given-names>
</name>
, <name><surname>Chu</surname>
<given-names>K</given-names>
</name>
, <name><surname>Szeto</surname>
<given-names>E</given-names>
</name>
, <name><surname>Palaniappan</surname>
<given-names>K</given-names>
</name>
, <etal>et al</etal>
(<year>2012</year>
) <article-title>IMG/M: the integrated metagenome data management and comparative analysis system</article-title>
. <source>Nucleic Acids Res</source>
<volume>40</volume>
: <fpage>D123</fpage>
–<lpage>129</lpage>
<pub-id pub-id-type="pmid">22086953</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Sun1"><label>17</label>
<mixed-citation publication-type="journal"><name><surname>Sun</surname>
<given-names>S</given-names>
</name>
, <name><surname>Chen</surname>
<given-names>J</given-names>
</name>
, <name><surname>Li</surname>
<given-names>W</given-names>
</name>
, <name><surname>Altintas</surname>
<given-names>I</given-names>
</name>
, <name><surname>Lin</surname>
<given-names>A</given-names>
</name>
, <etal>et al</etal>
(<year>2011</year>
) <article-title>Community cyberinfrastructure for Advanced Microbial Ecology Research and Analysis: the CAMERA resource</article-title>
. <source>Nucleic Acids Res</source>
<volume>39</volume>
: <fpage>D546</fpage>
–<lpage>551</lpage>
<pub-id pub-id-type="pmid">21045053</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Wu1"><label>18</label>
<mixed-citation publication-type="journal"><name><surname>Wu</surname>
<given-names>S</given-names>
</name>
, <name><surname>Zhu</surname>
<given-names>Z</given-names>
</name>
, <name><surname>Fu</surname>
<given-names>L</given-names>
</name>
, <name><surname>Niu</surname>
<given-names>B</given-names>
</name>
, <name><surname>Li</surname>
<given-names>W</given-names>
</name>
(<year>2011</year>
) <article-title>WebMGA: a customizable web server for fast metagenomic sequence analysis</article-title>
. <source>BMC Genomics</source>
<volume>12</volume>
: <fpage>444</fpage>
<pub-id pub-id-type="pmid">21899761</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Gevers1"><label>19</label>
<mixed-citation publication-type="journal"><name><surname>Gevers</surname>
<given-names>D</given-names>
</name>
, <name><surname>Knight</surname>
<given-names>R</given-names>
</name>
, <name><surname>Petrosino</surname>
<given-names>JF</given-names>
</name>
, <name><surname>Huang</surname>
<given-names>K</given-names>
</name>
, <name><surname>McGuire</surname>
<given-names>AL</given-names>
</name>
, <etal>et al</etal>
(<year>2012</year>
) <article-title>The Human Microbiome Project: a community resource for the healthy human microbiome</article-title>
. <source>PLoS Biol</source>
<volume>10</volume>
: <fpage>e1001377</fpage>
<pub-id pub-id-type="pmid">22904687</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Segata1"><label>20</label>
<mixed-citation publication-type="journal"><name><surname>Segata</surname>
<given-names>N</given-names>
</name>
, <name><surname>Boernigen</surname>
<given-names>D</given-names>
</name>
, <name><surname>Tickle</surname>
<given-names>TL</given-names>
</name>
, <name><surname>Morgan</surname>
<given-names>XC</given-names>
</name>
, <name><surname>Garrett</surname>
<given-names>WS</given-names>
</name>
, <etal>et al</etal>
(<year>2013</year>
) <article-title>Computational meta'omics for microbial community studies</article-title>
. <source>Mol Syst Biol</source>
<volume>9</volume>
: <fpage>666</fpage>
<pub-id pub-id-type="pmid">23670539</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Segata2"><label>21</label>
<mixed-citation publication-type="journal"><name><surname>Segata</surname>
<given-names>N</given-names>
</name>
, <name><surname>Izard</surname>
<given-names>J</given-names>
</name>
, <name><surname>Waldron</surname>
<given-names>L</given-names>
</name>
, <name><surname>Gevers</surname>
<given-names>D</given-names>
</name>
, <name><surname>Miropolsky</surname>
<given-names>L</given-names>
</name>
, <etal>et al</etal>
(<year>2011</year>
) <article-title>Metagenomic biomarker discovery and explanation</article-title>
. <source>Genome Biol</source>
<volume>12</volume>
: <fpage>R60</fpage>
<pub-id pub-id-type="pmid">21702898</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Faust1"><label>22</label>
<mixed-citation publication-type="journal"><name><surname>Faust</surname>
<given-names>K</given-names>
</name>
, <name><surname>Sathirapongsasuti</surname>
<given-names>JF</given-names>
</name>
, <name><surname>Izard</surname>
<given-names>J</given-names>
</name>
, <name><surname>Segata</surname>
<given-names>N</given-names>
</name>
, <name><surname>Gevers</surname>
<given-names>D</given-names>
</name>
, <etal>et al</etal>
(<year>2012</year>
) <article-title>Microbial co-occurrence relationships in the human microbiome</article-title>
. <source>PLoS Comput Biol</source>
<volume>8</volume>
: <fpage>e1002606</fpage>
<pub-id pub-id-type="pmid">22807668</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Andreote1"><label>23</label>
<mixed-citation publication-type="journal"><name><surname>Andreote</surname>
<given-names>FD</given-names>
</name>
, <name><surname>Jiménez</surname>
<given-names>DJ</given-names>
</name>
, <name><surname>Chaves</surname>
<given-names>D</given-names>
</name>
, <name><surname>Dias</surname>
<given-names>AC</given-names>
</name>
, <name><surname>Luvizotto</surname>
<given-names>DM</given-names>
</name>
, <etal>et al</etal>
(<year>2012</year>
) <article-title>The microbiome of Brazilian mangrove sediments as revealed by metagenomics</article-title>
. <source>PLoS One</source>
<volume>7</volume>
: <fpage>e38600</fpage>
<pub-id pub-id-type="pmid">22737213</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Segata3"><label>24</label>
<mixed-citation publication-type="journal"><name><surname>Segata</surname>
<given-names>N</given-names>
</name>
, <name><surname>Waldron</surname>
<given-names>L</given-names>
</name>
, <name><surname>Ballarini</surname>
<given-names>A</given-names>
</name>
, <name><surname>Narasimhan</surname>
<given-names>V</given-names>
</name>
, <name><surname>Jousson</surname>
<given-names>O</given-names>
</name>
, <etal>et al</etal>
(<year>2012</year>
) <article-title>Metagenomic microbial community profiling using unique clade-specific marker genes</article-title>
. <source>Nat Methods</source>
<volume>9</volume>
: <fpage>811</fpage>
–<lpage>814</lpage>
<pub-id pub-id-type="pmid">22688413</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Altschul1"><label>25</label>
<mixed-citation publication-type="journal"><name><surname>Altschul</surname>
<given-names>SF</given-names>
</name>
, <name><surname>Gish</surname>
<given-names>W</given-names>
</name>
, <name><surname>Miller</surname>
<given-names>W</given-names>
</name>
, <name><surname>Myers</surname>
<given-names>EW</given-names>
</name>
, <name><surname>Lipman</surname>
<given-names>DJ</given-names>
</name>
(<year>1990</year>
) <article-title>Basic local alignment search tool</article-title>
. <source>J Mol Biol</source>
<volume>215</volume>
: <fpage>403</fpage>
–<lpage>410</lpage>
<pub-id pub-id-type="pmid">2231712</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Bray1"><label>26</label>
<mixed-citation publication-type="journal"><name><surname>Bray</surname>
<given-names>JR</given-names>
</name>
, <name><surname>Curtis</surname>
<given-names>JT</given-names>
</name>
(<year>1957</year>
) <article-title>An ordination of the upland forest communities of southern Wisconsin</article-title>
. <source>Ecol Monographs</source>
<volume>27</volume>
: <fpage>325</fpage>
–<lpage>349</lpage>
</mixed-citation>
</ref>
<ref id="pone.0093445-Oksanen1"><label>27</label>
<mixed-citation publication-type="other">Oksanen J (2011) Multivariate analysis of ecological communities in R: vegan tutorial. URL: <ext-link ext-link-type="uri" xlink:href="http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf">http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf</ext-link>
</mixed-citation>
</ref>
<ref id="pone.0093445-R1"><label>28</label>
<mixed-citation publication-type="other">R Development Core Team (2007) R: A language and environment for statistical computing [<ext-link ext-link-type="uri" xlink:href="http://www.R-project.org">http://www.R-project.org</ext-link>
].R Foundation for Statistical Computing, Vienna, Austria.</mixed-citation>
</ref>
<ref id="pone.0093445-Abubucker1"><label>29</label>
<mixed-citation publication-type="journal"><name><surname>Abubucker</surname>
<given-names>S</given-names>
</name>
, <name><surname>Segata</surname>
<given-names>N</given-names>
</name>
, <name><surname>Goll</surname>
<given-names>J</given-names>
</name>
, <name><surname>Schubert</surname>
<given-names>AM</given-names>
</name>
, <name><surname>Izard</surname>
<given-names>J</given-names>
</name>
, <etal>et al</etal>
(<year>2012</year>
) <article-title>Metabolic reconstruction for metagenomic data and its application to the human microbiome</article-title>
. <source>PLoS Comput Biol</source>
<volume>8</volume>
: <fpage>e1002358</fpage>
<pub-id pub-id-type="pmid">22719234</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Kanehisa1"><label>30</label>
<mixed-citation publication-type="journal"><name><surname>Kanehisa</surname>
<given-names>M</given-names>
</name>
, <name><surname>Goto</surname>
<given-names>S</given-names>
</name>
, <name><surname>Furumichi</surname>
<given-names>M</given-names>
</name>
, <name><surname>Tanabe</surname>
<given-names>M</given-names>
</name>
, <name><surname>Hirakawa</surname>
<given-names>M</given-names>
</name>
(<year>2010</year>
) <article-title>KEGG for representation and analysis of molecular networks involving diseases and drugs</article-title>
. <source>Nucleic Acids Res</source>
<volume>38</volume>
: <fpage>D355</fpage>
–<lpage>360</lpage>
<pub-id pub-id-type="pmid">19880382</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Edgar1"><label>31</label>
<mixed-citation publication-type="journal"><name><surname>Edgar</surname>
<given-names>RC</given-names>
</name>
(<year>2010</year>
) <article-title>Search and clustering orders of magnitude faster than BLAST</article-title>
. <source>Bioinformatics</source>
<volume>26</volume>
: <fpage>2460</fpage>
–<lpage>2461</lpage>
<pub-id pub-id-type="pmid">20709691</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Ye1"><label>32</label>
<mixed-citation publication-type="journal"><name><surname>Ye</surname>
<given-names>Y</given-names>
</name>
, <name><surname>Doak</surname>
<given-names>TG</given-names>
</name>
(<year>2009</year>
) <article-title>A parsimony approach to biological pathway reconstruction/inference for genomes and metagenomes</article-title>
. <source>PLoS Comput Biol</source>
<volume>5</volume>
: <fpage>e1000465</fpage>
<pub-id pub-id-type="pmid">19680427</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Goecks1"><label>33</label>
<mixed-citation publication-type="journal"><name><surname>Goecks</surname>
<given-names>J</given-names>
</name>
, <name><surname>Nekrutenko</surname>
<given-names>A</given-names>
</name>
, <name><surname>Taylor</surname>
<given-names>J</given-names>
</name>
(<year>2010</year>
) <collab>Galaxy Team</collab>
(<year>2010</year>
) <article-title>Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences</article-title>
. <source>Genome Biol</source>
<volume>11</volume>
: <fpage>R86</fpage>
<pub-id pub-id-type="pmid">20738864</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Sarkar1"><label>34</label>
<mixed-citation publication-type="journal"><name><surname>Sarkar</surname>
<given-names>SK</given-names>
</name>
, <name><surname>Chang</surname>
<given-names>CK</given-names>
</name>
(<year>1997</year>
) <article-title>The Simes method for multiple hypothesis testing with positively dependent test statistics</article-title>
. <source>J Am Stat Assoc</source>
<volume>92</volume>
: <fpage>1601</fpage>
–<lpage>1608</lpage>
</mixed-citation>
</ref>
<ref id="pone.0093445-Benjamini1"><label>35</label>
<mixed-citation publication-type="journal"><name><surname>Benjamini</surname>
<given-names>Y</given-names>
</name>
, <name><surname>Hochberg</surname>
<given-names>Y</given-names>
</name>
(<year>1995</year>
) <article-title>Controlling the false discovery rate: a practical and powerful approach to multiple testing</article-title>
. <source>J Royal Statis Soc B</source>
<volume>57</volume>
: <fpage>289</fpage>
–<lpage>300</lpage>
</mixed-citation>
</ref>
<ref id="pone.0093445-Smoot1"><label>36</label>
<mixed-citation publication-type="journal"><name><surname>Smoot</surname>
<given-names>ME</given-names>
</name>
, <name><surname>Ono</surname>
<given-names>K</given-names>
</name>
, <name><surname>Ruscheinski</surname>
<given-names>J</given-names>
</name>
, <name><surname>Wang</surname>
<given-names>PL</given-names>
</name>
, <name><surname>Ideker</surname>
<given-names>T</given-names>
</name>
(<year>2011</year>
) <article-title>Cytoscape 2.8: new features for data integration and network visualization</article-title>
. <source>Bioinformatics</source>
<volume>27</volume>
: <fpage>431</fpage>
–<lpage>432</lpage>
<pub-id pub-id-type="pmid">21149340</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Qin1"><label>37</label>
<mixed-citation publication-type="journal"><name><surname>Qin</surname>
<given-names>J</given-names>
</name>
, <name><surname>Li</surname>
<given-names>R</given-names>
</name>
, <name><surname>Raes</surname>
<given-names>J</given-names>
</name>
, <name><surname>Arumugam</surname>
<given-names>M</given-names>
</name>
, <name><surname>Burgdorf</surname>
<given-names>KS</given-names>
</name>
, <etal>et al</etal>
(<year>2010</year>
) <article-title>A human gut microbial gene catalogue established by metagenomic sequencing</article-title>
. <source>Nature</source>
<volume>464</volume>
: <fpage>59</fpage>
–<lpage>65</lpage>
<pub-id pub-id-type="pmid">20203603</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Segata4"><label>38</label>
<mixed-citation publication-type="journal"><name><surname>Segata</surname>
<given-names>N</given-names>
</name>
, <name><surname>Haake</surname>
<given-names>SK</given-names>
</name>
, <name><surname>Mannon</surname>
<given-names>P</given-names>
</name>
, <name><surname>Lemon</surname>
<given-names>KP</given-names>
</name>
, <name><surname>Waldron</surname>
<given-names>L</given-names>
</name>
, <etal>et al</etal>
(<year>2012</year>
) <article-title>Composition of the adult digestive tract bacterial microbiome based on seven mouth surfaces, tonsils, throat and stool samples</article-title>
. <source>Genome Biol</source>
<volume>13</volume>
: <fpage>R42</fpage>
<pub-id pub-id-type="pmid">22698087</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Janssen1"><label>39</label>
<mixed-citation publication-type="journal"><name><surname>Janssen</surname>
<given-names>PH</given-names>
</name>
(<year>2006</year>
) <article-title>Identifying the dominant soil bacterial taxa in libraries of 16S rRNA and 16S rRNA genes</article-title>
. <source>Appl Environ Microbiol</source>
<volume>72</volume>
: <fpage>1719</fpage>
–<lpage>1728</lpage>
<pub-id pub-id-type="pmid">16517615</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Dedysh1"><label>40</label>
<mixed-citation publication-type="journal"><name><surname>Dedysh</surname>
<given-names>SN</given-names>
</name>
(<year>2009</year>
) <article-title>Exploring methanotrophs diversity in acidic northern wetlands: molecular and cultivation-based studies</article-title>
. <source>Microbiology</source>
<volume>78</volume>
: <fpage>655</fpage>
–<lpage>669</lpage>
</mixed-citation>
</ref>
<ref id="pone.0093445-Dedysh2"><label>41</label>
<mixed-citation publication-type="journal"><name><surname>Dedysh</surname>
<given-names>SN</given-names>
</name>
(<year>2011</year>
) <article-title>Cultivating uncultured bacteria from northern wetlands: knowledge gained and remaining gaps</article-title>
. <source>Front Microbiol</source>
<volume>2</volume>
: <fpage>184</fpage>
<pub-id pub-id-type="pmid">21954394</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Ojima1"><label>42</label>
<mixed-citation publication-type="journal"><name><surname>Ojima</surname>
<given-names>DS</given-names>
</name>
, <name><surname>Valentine</surname>
<given-names>DW</given-names>
</name>
, <name><surname>Mosier</surname>
<given-names>AR</given-names>
</name>
, <name><surname>Parton</surname>
<given-names>WJ</given-names>
</name>
(<year>1993</year>
) <collab>Schimel</collab>
(<year>1993</year>
) <article-title>Effect of land use change on methane oxidation in temperate forest and grassland soils</article-title>
. <source>Chemosphere</source>
<volume>26</volume>
: <fpage>675</fpage>
–<lpage>685</lpage>
</mixed-citation>
</ref>
<ref id="pone.0093445-Jang1"><label>43</label>
<mixed-citation publication-type="journal"><name><surname>Jang</surname>
<given-names>I</given-names>
</name>
, <name><surname>Lee</surname>
<given-names>S</given-names>
</name>
, <name><surname>Hong</surname>
<given-names>JH</given-names>
</name>
, <name><surname>Kang</surname>
<given-names>H</given-names>
</name>
(<year>2006</year>
) <article-title>Methane oxidation rates in forest soils and their controlling variables, a review and a case study in Korea</article-title>
. <source>Ecol Res</source>
<volume>21</volume>
: <fpage>849</fpage>
–<lpage>854</lpage>
</mixed-citation>
</ref>
<ref id="pone.0093445-Imhoff1"><label>44</label>
<mixed-citation publication-type="other">Imhoff JF (2005) Family II. <italic>Ectothiorhodospiracea</italic>
e. In: Brenner DJ, Krieg NR, Staley JT, Garrity GM, editors. <italic>Bergey</italic>
'<italic>s manual of systematic bacteriology</italic>
, 2<sup>nd</sup>
Springer, New York, NY. pp. 41–52.</mixed-citation>
</ref>
<ref id="pone.0093445-Kuever1"><label>45</label>
<mixed-citation publication-type="other">Kuever J, Rainey FA, Widdel F (2005) Family II. <italic>Desulfobulbaceae</italic>
fam. nov. In: Brenner DJ, Krieg NR, Staley JT, Garrity GM, editors. p.<italic>Bergey</italic>
'<italic>s manual of systematic bacteriology</italic>
, 2<sup>nd</sup>
New York: Springer, p.988.</mixed-citation>
</ref>
<ref id="pone.0093445-Lau1"><label>46</label>
<mixed-citation publication-type="journal"><name><surname>Lau</surname>
<given-names>E</given-names>
</name>
, <name><surname>Fisher</surname>
<given-names>MC</given-names>
</name>
, <name><surname>Steudler</surname>
<given-names>PA</given-names>
</name>
, <name><surname>Cavanaugh</surname>
<given-names>CM</given-names>
</name>
(<year>2013</year>
) <article-title>The methanol dehydrogenase gene, mxaF, as a functional and phylogenetic marker for proteobacterial methanotrophs in natural environments</article-title>
. <source>PLoS One</source>
<volume>8</volume>
: <fpage>e56993</fpage>
<pub-id pub-id-type="pmid">23451130</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Mulkidjanian1"><label>47</label>
<mixed-citation publication-type="journal"><name><surname>Mulkidjanian</surname>
<given-names>AY</given-names>
</name>
, <name><surname>Koonin</surname>
<given-names>EV</given-names>
</name>
, <name><surname>Makarova</surname>
<given-names>KS</given-names>
</name>
, <name><surname>Mekhedov</surname>
<given-names>SL</given-names>
</name>
, <name><surname>Sorokin</surname>
<given-names>A</given-names>
</name>
, <etal>et al</etal>
(<year>2006</year>
) <article-title>The cyanobacterial genome core and the origin of photosynthesis</article-title>
. <source>Proc Natl Acad Sci U S A</source>
<volume>103</volume>
: <fpage>13126</fpage>
–<lpage>13131</lpage>
<pub-id pub-id-type="pmid">16924101</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Empadinhas1"><label>48</label>
<mixed-citation publication-type="journal"><name><surname>Empadinhas</surname>
<given-names>N</given-names>
</name>
, <name><surname>da Costa</surname>
<given-names>MS</given-names>
</name>
(<year>2011</year>
) <article-title>Diversity, biological roles and biosynthetic pathways for sugar-glycerate containing compatible solutes in bacteria and archaea</article-title>
. <source>Environ Microbiol</source>
<volume>13</volume>
: <fpage>2056</fpage>
–<lpage>2077</lpage>
<pub-id pub-id-type="pmid">21176052</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Kaneko1"><label>49</label>
<mixed-citation publication-type="journal"><name><surname>Kaneko</surname>
<given-names>T</given-names>
</name>
, <name><surname>Nakamura</surname>
<given-names>Y</given-names>
</name>
, <name><surname>Sato</surname>
<given-names>S</given-names>
</name>
, <name><surname>Minamisawa</surname>
<given-names>K</given-names>
</name>
, <name><surname>Uchiumi</surname>
<given-names>T</given-names>
</name>
, <etal>et al</etal>
(<year>2002</year>
) <article-title>Complete genomic sequence of nitrogen-fixing symbiotic bacterium <italic>Bradyrhizobium japonicum</italic>
USDA110</article-title>
. <source>DNA Res</source>
<volume>9</volume>
: <fpage>189</fpage>
–<lpage>197</lpage>
<pub-id pub-id-type="pmid">12597275</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Desrosiers1"><label>50</label>
<mixed-citation publication-type="journal"><name><surname>Desrosiers</surname>
<given-names>DC</given-names>
</name>
, <name><surname>Sun</surname>
<given-names>YC</given-names>
</name>
, <name><surname>Zaidi</surname>
<given-names>AA</given-names>
</name>
, <name><surname>Eggers</surname>
<given-names>CH</given-names>
</name>
, <name><surname>Cox</surname>
<given-names>DL</given-names>
</name>
, <etal>et al</etal>
(<year>2007</year>
) <article-title>The general transition metal (Tro) and Zn2+ (Znu) transporters in Treponema pallidum: analysis of metal specificities and expression profiles</article-title>
. <source>Mol Microbiol</source>
<volume>65</volume>
: <fpage>137</fpage>
–<lpage>152</lpage>
<pub-id pub-id-type="pmid">17581125</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Wolosiuk1"><label>51</label>
<mixed-citation publication-type="journal"><name><surname>Wolosiuk</surname>
<given-names>RA</given-names>
</name>
, <name><surname>Ballicora</surname>
<given-names>MA</given-names>
</name>
, <name><surname>Hagelin</surname>
<given-names>K</given-names>
</name>
(<year>1993</year>
) <article-title>The reductive pentose phosphate cycle for photosynthetic CO2 assimilation: enzyme modulation</article-title>
. <source>FASEB J</source>
<volume>7</volume>
: <fpage>622</fpage>
–<lpage>637</lpage>
<pub-id pub-id-type="pmid">8500687</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Maloney1"><label>52</label>
<mixed-citation publication-type="journal"><name><surname>Maloney</surname>
<given-names>GS</given-names>
</name>
, <name><surname>Kochevenko</surname>
<given-names>A</given-names>
</name>
, <name><surname>Tieman</surname>
<given-names>DM</given-names>
</name>
, <name><surname>Tohge</surname>
<given-names>T</given-names>
</name>
, <name><surname>Krieger</surname>
<given-names>U</given-names>
</name>
, <etal>et al</etal>
(<year>2010</year>
) <article-title>Characterization of the branched-chain amino acid aminotransferase enzyme family in tomato</article-title>
. <source>Plant Physiol</source>
<volume>153</volume>
: <fpage>925</fpage>
–<lpage>936</lpage>
<pub-id pub-id-type="pmid">20435740</pub-id>
</mixed-citation>
</ref>
<ref id="pone.0093445-Maeda1"><label>53</label>
<mixed-citation publication-type="journal"><name><surname>Maeda</surname>
<given-names>H</given-names>
</name>
, <name><surname>Dudareva</surname>
<given-names>N</given-names>
</name>
(<year>2012</year>
) <article-title>The Shikimate pathway and aromatic amino acid biosynthesis in plants</article-title>
. <source>Annu Rev Plant Biol</source>
<volume>63</volume>
: <fpage>73</fpage>
–<lpage>105</lpage>
<pub-id pub-id-type="pmid">22554242</pub-id>
</mixed-citation>
</ref>
</ref-list>
</back>
</pmc>
</record>
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