RevEcoR: an R package for the reverse ecology analysis of microbiomes

BackgroundAll species live in complex ecosystems. The structure and complexity of a microbial community reflects not only diversity and function, but also the environment in which it occurs. However, traditional ecological methods can only be applied on a small scale and for relatively well-understood biological systems. Recently, a graph-theory-based algorithm called the reverse ecology approach has been developed that can analyze the metabolic networks of all the species in a microbial community, and predict the metabolic interface between species and their environment.ResultsHere, we present RevEcoR, an R package and a Shiny Web application that implements the reverse ecology algorithm for determining microbe–microbe interactions in microbial communities. This software allows users to obtain large-scale ecological insights into species’ ecology directly from high-throughput metagenomic data. The software has great potential for facilitating the study of microbiomes.ConclusionsRevEcoR is open source software for the study of microbial community ecology. The RevEcoR R package is freely available under the GNU General Public License v. 2.0 at http://cran.r-project.org/web/packages/RevEcoR/ with the vignette and typical usage examples, and the interactive Shiny web application is available at http://yiluheihei.shinyapps.io/shiny-RevEcoR, or can be installed locally with the source code accessed from https://github.com/yiluheihei/shiny-RevEcoR.

[1]  Gábor Csárdi,et al.  The igraph software package for complex network research , 2006 .

[2]  Jj Allaire,et al.  Web Application Framework for R , 2016 .

[3]  I-Min A. Chen,et al.  IMG/M 4 version of the integrated metagenome comparative analysis system , 2013, Nucleic Acids Res..

[4]  P. Bork,et al.  A human gut microbial gene catalogue established by metagenomic sequencing , 2010, Nature.

[5]  Anat Kreimer,et al.  NetCooperate: a network-based tool for inferring host-microbe and microbe-microbe cooperation , 2015, BMC Bioinformatics.

[6]  N. Mantel.  The detection of disease clustering and a generalized regression approach. , 1967, Cancer research.

[7]  Robert K. Colwell,et al.  A new statistical approach for assessing similarity of species composition with incidence and abundance data , 2004 .

[8]  H. Wickham.  Simple, Consistent Wrappers for Common String Operations , 2015 .

[9]  Robert E. Tarjan,et al.  Depth-First Search and Linear Graph Algorithms , 1972, SIAM J. Comput..

[10]  J. Izard,et al.  The Human Oral Microbiome , 2010, Journal of bacteriology.

[11]  E. Borenstein,et al.  Metabolic modeling of species interaction in the human microbiome elucidates community-level assembly rules , 2013, Proceedings of the National Academy of Sciences.

[12]  Elhanan Borenstein,et al.  NetSeed: a network-based reverse-ecology tool for calculating the metabolic interface of an organism with its environment , 2012, Bioinform..

[13]  Hadley Wickham,et al.  The Split-Apply-Combine Strategy for Data Analysis , 2011 .

[14]  M. Feldman,et al.  Large-scale reconstruction and phylogenetic analysis of metabolic environments , 2008, Proceedings of the National Academy of Sciences.

[15]  P. Kolenbrander,et al.  Mutualism versus Independence: Strategies of Mixed-Species Oral Biofilms In Vitro Using Saliva as the Sole Nutrient Source , 2001, Infection and Immunity.

[16]  Minoru Kanehisa,et al.  KEGG as a reference resource for gene and protein annotation , 2015, Nucleic Acids Res..

[17]  P. Stenström,et al.  Introduction , 2006, J. Parallel Distributed Comput..

[18]  K. Schleifer,et al.  Phylogenetic identification and in situ detection of individual microbial cells without cultivation. , 1995, Microbiological reviews.

[19]  Elhanan Borenstein,et al.  Metagenomic systems biology and metabolic modeling of the human microbiome , 2014, Gut microbes.

[20]  Nikos Kyrpides,et al.  The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification , 2014, Nucleic Acids Res..

[21]  Elhanan Borenstein,et al.  Reverse Ecology: from systems to environments and back. , 2012, Advances in experimental medicine and biology.

[22]  Philip Hugenholtz,et al.  Impact of Culture-Independent Studies on the Emerging Phylogenetic View of Bacterial Diversity , 1998, Journal of bacteriology.

[23]  P. Kolenbrander,et al.  Mutualistic Biofilm Communities Develop with Porphyromonas gingivalis and Initial, Early, and Late Colonizers of Enamel , 2009, Journal of bacteriology.