NetCooperate: A network-based tool for inferring host-microbe and microbe-microbe cooperation

BMC Bioinformatics

Volumn 16, Issue 1, 2015, Pages

  Levy, Roie ^a   Carr, Rogan ^a   Kreimer, Anat ^b,c   Freilich, Shiri ^d   Borenstein, Elhanan ^a,e,f  

^a UNIVERSITY OF WASHINGTON   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d VOLCANI CENTER   (Israel)

^e University of Washington   (United States)

^f SANTA FE INSTITUTE   (United States)

Author keywords

Community assembly; Metabolic networks; Microbial ecology; Reverse ecology; Species interactions; Systems biology

Indexed keywords

BACTERIA; BIOSYNTHESIS; COMPLEX NETWORKS; ECOLOGY; ECOSYSTEMS; ELECTRIC NETWORK TOPOLOGY; GRAPH THEORY; METABOLISM; OPEN SOURCE SOFTWARE; SOCIAL NETWORKING (ONLINE); TOPOLOGY; WEBSITES;

COMMUNITY ASSEMBLY; METABOLIC NETWORK; MICROBIAL ECOLOGY; SPECIES INTERACTIONS; SYSTEMS BIOLOGY;

MICROORGANISMS;

ANIMAL; BACTERIUM; BIOLOGICAL MODEL; BIOLOGY; CLASSIFICATION; COMPUTER PROGRAM; GENETICS; HOST PARASITE INTERACTION; HUMAN; INTERNET; METABOLISM; ORGANISMAL INTERACTION; PROCEDURES;

ANIMALS; BACTERIA; COMPUTATIONAL BIOLOGY; HOST-PARASITE INTERACTIONS; HUMANS; INTERNET; METABOLIC NETWORKS AND PATHWAYS; MICROBIAL INTERACTIONS; MODELS, BIOLOGICAL; SOFTWARE;

EID: 84938918346     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-015-0588-y     Document Type: Article

References (36)

1. Ruppin E, Papin JA, de Figueiredo LF, Schuster S. Metabolic reconstruction, constraint-based analysis and game theory to probe genome-scale metabolic networks. Curr Opin Biotechnol. 2010;21:502-10.
2. Segrè D, Vitkup D, Church GM. Analysis of optimality in natural and perturbed metabolic networks. Proc Natl Acad Sci U S A. 2002;99:15112-7.
3. Shlomi T, Berkman O, Ruppin E. Regulatory on/off minimization of metabolic flux changes after genetic perturbations. Proc Natl Acad Sci U S A. 2005;102:7695-700.
4. Bauer AL, Jackson TL, Jiang Y, Rohlf T. Receptor cross-talk in angiogenesis: mapping environmental cues to cell phenotype using a stochastic, Boolean signaling network model. J Theor Biol. 2010;264:838-46.
5. Neph S, Stergachis AB, Reynolds A, Sandstrom R, Borenstein E, Stamatoyannopoulos JA. Circuitry and dynamics of human transcription factor regulatory networks. Cell. 2012;150:1274-86.
6. Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, Alon U. Network motifs: simple building blocks of complex networks. Science. 2002;298:824-7.
7. Parter M, Kashtan N, Alon U. Environmental variability and modularity of bacterial metabolic networks. BMC Evol Biol. 2007;7:169.
8. Kreimer A, Borenstein E, Gophna U, Ruppin E. The evolution of modularity in bacterial metabolic networks. Proc Natl Acad Sci U S A. 2008;105:6976-81.
9. Levy R, Borenstein E. Reverse ecology: from systems to environments and back. Adv Exp Med Biol. 2012;751:329-45.
10. Borenstein E, Kupiec M, Feldman MW, Ruppin E. Large-scale reconstruction and phylogenetic analysis of metabolic environments. Proc Natl Acad Sci U S A. 2008;105:14482-7.
11. Janga SC, Babu MM. Network-based approaches for linking metabolism with environment. Genome Biol. 2008;9:239.
12. Röling WFM, Ferrer M, Golyshin PN. Systems approaches to microbial communities and their functioning. Curr Opin Biotechnol. 2010;21:532-8.
13. Hansen EE, Lozupone CA, Rey FE, Wu M, Guruge JL, Narra A, et al. Pan-genome of the dominant human gut-associated archaeon, Methanobrevibacter smithii, studied in twins. Proc Natl Acad Sci U S A. 2011;108:4599-606.
14. Carr R, Borenstein E. NetSeed: a network-based reverse-ecology tool for calculating the metabolic interface of an organism with its environment. Bioinformatics. 2012;28:734-5.
15. Freilich S, Kreimer A, Borenstein E, Yosef N, Sharan R, Gophna U, et al. Metabolic-network-driven analysis of bacterial ecological strategies. Genome Biol. 2009;10:R61.
16. Freilich S, Kreimer A, Meilijson I, Gophna U, Sharan R, Ruppin E. The large-scale organization of the bacterial network of ecological co-occurrence interactions. Nucleic Acids Res. 2010;38:3857-68.
17. Kreimer A, Doron-Faigenboim A, Borenstein E, Freilich S. NetCmpt: a network-based tool for calculating the metabolic competition between bacterial species. Bioinformatics. 2012;28:2195-7.
18. Levy R, Borenstein E. Metabolic modeling of species interaction in the human microbiome elucidates community-level assembly rules. Proc Natl Acad Sci U S A. 2013;110:12804-9.
19. Chiu HH-C, Levy R, Borenstein E. Emergent biosynthetic capacity in simple microbial communities. PLoS Comput Biol. 2014;10:e1003695.
20. Ebenhöh O, Handorf T, Heinrich R. A cross species comparison of metabolic network functions. Genome Inform. 2005;16:203-13.
21. Handorf T, Ebenhöh O, Heinrich R. Expanding metabolic networks: scopes of compounds, robustness, and evolution. J Mol Evol. 2005;61:498-512.
22. Basler G, Nikoloski Z, Ebenhöh O, Handorf T. Biosynthetic potentials from species-specific metabolic networks. Genome Inform. 2008;20:135-48.
23. Christian N, Handorf T, Ebenhöh O. Metabolic synergy: increasing biosynthetic capabilities by network cooperation. Genome Inform. 2007;18:320-9.
24. Borenstein E, Feldman MW. Topological signatures of species interactions in metabolic networks. J Comput Biol. 2009;16:191-200.
25. Klitgord N, Segrè D. Environments that induce synthetic microbial ecosystems. PLoS Comput Biol. 2010;6:e1001002.
26. Kanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 2000;28:27-30.
27. Levy R, Borenstein E. Metagenomic. systems biology and metabolic modeling of the human microbiome. Gut Microbes 2014;5(2):265-270.
28. Papp B, Notebaart RA, Pál C. Systems-biology approaches for predicting genomic evolution. Nat Rev Genet. 2011;12:591-602.
29. Faust K, Sathirapongsasuti JF, Izard J, Segata N, Gevers D, Raes J, et al. Microbial co-occurrence relationships in the human microbiome. PLoS Comput Biol. 2012;8:e1002606.
30. Kolenbrander PE. Multispecies communities: interspecies interactions influence growth on saliva as sole nutritional source. Int J Oral Sci. 2011;3:49-54.
31. Varma A, Palsson BO. Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110. Appl Environ Microbiol. 1994;60:3724-31.
32. Arifuzzaman M, Maeda M, Itoh A, Nishikata K, Takita C, Saito R, et al. Large-scale identification of protein-protein interaction of Escherichia coli K-12. Genome Res. 2006;16:686-91.
33. Faith JJ, Hayete B, Thaden JT, Mogno I, Wierzbowski J, Cottarel G, et al. Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biol. 2007;5:e8.
34. Fadda A, Fierro AC, Lemmens K, Monsieurs P, Engelen K, Marchal K. Inferring the transcriptional network of Bacillus subtilis. Mol Biosyst. 2009;5:1840-52.
35. Chaffron S, Rehrauer H, Pernthaler J, von Mering C. A global network of coexisting microbes from environmental and whole-genome sequence data. Genome Res. 2010;20:947-59.
36. Smillie CS, Smith MB, Friedman J, Cordero OX, David LA, Alm EJ. Ecology drives a global network of gene exchange connecting the human microbiome. Nature. 2011;480:241-4.