Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach

MicrobiologyOpen

Volumn 5, Issue 1, 2016, Pages 106-117

  Bordron, Philippe ^a   Latorre, Mauricio ^a   Cortés, Maria Paz ^a   González, Mauricio ^a   Thiele, Sven ^b   Siegel, Anne ^c,d   Maass, Alejandro ^a   Eveillard, Damien ^e  

^a UNIVERSITY OF CHILE   (Chile)

^b MAX PLANCK INSTITUTE FOR DYNAMICS OF COMPLEX TECHNICAL SYSTEMS   (Germany)

^c CAMPUS DE BEAULIEU   (France)

^d INRIA   (France)

^e UNIVERSITÉ DE NANTES   (France)

Author keywords

Environmental microbiology; In silico analysis; Metabolic pathways; Molecular microbial ecology

Indexed keywords

ACIDIPHILIUM; ACIDIPHILIUM CRYPTUM; ACIDITHIOBACILLUS FERROOXIDANS; ACIDITHIOBACILLUS THIOOXIDANS; ARTICLE; BACTERIAL GENE; BACTERIAL GENETICS; BACTERIAL GENOME; BACTERIAL METABOLISM; BACTERIAL STRAIN; BIOLEACHING; CATALYSIS; CONTROLLED STUDY; COPPER METABOLISM; ENVIRONMENTAL FACTOR; GENOME ANALYSIS; GENOMICS; HORIZONTAL GENE TRANSFER; KNOWLEDGE; LEPTOSPIRILLUM FERRIPHILUM; METAGENOMICS; MICROBIAL COMMUNITY; NONHUMAN; ORGANISMAL INTERACTION; PRIORITY JOURNAL; SULFOBACILLUS THERMOSULFIDOOXIDANS; ACIDITHIOBACILLUS; CLOSTRIDIALES; ECOSYSTEM; GENETICS; METABOLISM;

BACTERIAL DNA; COPPER;

ACIDIPHILIUM; ACIDITHIOBACILLUS; CLOSTRIDIALES; COPPER; DNA, BACTERIAL; ECOSYSTEM; GENOME, BACTERIAL; METABOLIC NETWORKS AND PATHWAYS; METAGENOMICS;

EID: 84951320206     PISSN: None     EISSN: 20458827     Source Type: Journal    
DOI: 10.1002/mbo3.315     Document Type: Article

References (56)

1. Baker, B. J., and J. F. Banfield 2003. Microbial communities in acid mine drainage. FEMS Microbiol. Ecol. 44:139-152.
2. Barreto, M., R. Quatrini, S. Bueno, S. Arriagada, and J. Valdés 2003. Aspects of the predicted physiology of Acidithiobacillus ferrooxidans deduced from an analysis of its partial genome sequence. Hydrometallurgy 71:97-105.
3. Bordron, P., D. Eveillard, and I. Rusu 2011. Integrated analysis of the gene neighbouring impact on bacterial metabolic networks. IET Syst. Biol. 5:261-268.
4. Borenstein, E., M. Kupiec, M. W. Feldman, and E. Ruppin 2008. Large-scale reconstruction and phylogenetic analysis of metabolic environments. Proc. Natl Acad. Sci. USA 105:14482-14487.
5. Boyer, F., A. Morgat, L. Labarre, J. Pothier, and A. Viari 2005. Syntons, metabolons and interactons: an exact graph-theoretical approach for exploring neighbourhood between genomic and functional data. Bioinformatics 21:4209-4215.
6. Brown, M. V., G. K. Philip, J. A. Bunge, M. C. Smith, A. Bissett, F. M. Lauro, et al. 2009. Microbial community structure in the North Pacific ocean. ISME J. 3:1374-1386.
7. Caspi, R., T. Altman, K. Dreher, C. A. Fulcher, P. Subhraveti, I. M. Keseler, et al. 2012. The metacyc database of metabolic pathways and enzymes and the biocyc collection of pathway/genome databases. Nucleic Acids Res. 40:D742-D753.
8. Chaffron, S., H. Rehrauer, J. Pernthaler, and C. von Mering 2010. A global network of coexisting microbes from environmental and whole-genome sequence data. Genome Res. 20:947-959.
9. Christian, N., P. May, S. Kempa, T. Handorf, and O. Ebenhoeh 2009. An integrative approach towards completing genome-scale metabolic networks. Mol. BioSyst. 5:1889-1903.
10. Croes, D., F. Couche, S. J. Wodak, and J. van Helden 2005. Metabolic pathfinding: inferring relevant pathways in biochemical networks. Nucleic Acids Res. 33:W326-W330.
11. DeLong, E. F. 2005. Microbial community genomics in the ocean. Nat. Rev. Microbiol. 3:459-469.
12. Drobner, E., H. Huber, G. Wächtershäuser, D. Rose, and K. O. Stetter 1990. Pyrite formation linked with hydrogen evolution under anaerobic conditions. Nature 346:742-744.
13. Faust, K., and J. Raes 2012. Microbial interactions: from networks to models. Nat. Rev. Microbiol. 10:538-550.
14. Faust, K., J. F. Sathirapongsasuti, J. Izard, N. Segata, D. Gevers, J. Raes, et al. 2012. Microbial co-occurrence relationships in the human microbiome. PLoS Comput. Biol. 8:e1002606.
15. Guimera, R., and L. A. N. Amaral 2005. Functional cartography of complex metabolic networks. Nature 433:895-900.
16. Hingamp, P., N. Grimsley, S. G. Acinas, C. Clerissi, L. Subirana, J. Poulain, et al. 2013. Exploring nucleo-cytoplasmic large DNA viruses in tara oceans microbial metagenomes. ISME J. 7:1678-1695.
17. Karp, P. D., S. M. Paley, M. Krummenacker, M. Latendresse, J. M. Dale, T. J. Lee, et al. 2010. Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology. Brief Bioinform. 11:40-79.
18. Karsenti, E., S. G. Acinas, P. Bork, C. Bowler, C. de Vargas, J. Raes, et al. 2011. A holistic approach to marine eco-systems biology. PLoS Biol. 9:e1001177.
19. Kitano, H. 2004. Biological robustness. Nat. Rev. Genet. 5:826-837.
20. Klitgord, N., and D. Segrè 2011. Ecosystems biology of microbial metabolism. Curr. Opin. Biotechnol. 22:541-546.
21. Lapierre, P., and J. P. Gogarten 2009. Estimating the size of the bacterial pan-genome. Trends Genet. 25:107-110.
22. Larhlimi, A., S. Blachon, J. Selbig, and Z. Nikoloski 2011. Robustness of metabolic networks: a review of existing definitions. BioSystems 106:1-8.
23. Latorre, M., N. Ehrenfeld, M. P. Cortés, D. Travisany, M. Budinich, A. Aravena, et al. 2015. Global transcriptional responses of Acidithiobacillus ferrooxidans Wenelen under different sulfide minerals. Bioresour. Technol. 200:29-34.
24. Levican, G., J. A. Ugalde, N. Ehrenfeld, A. Maass, and P. Parada 2008. Comparative genomic analysis of carbon and nitrogen assimilation mechanisms in three indigenous bioleaching bacteria: predictions and validations. BMC Genom. 9:581.
25. Liberal, R., and J. W. Pinney 2013. Simple topological properties predict functional misannotations in a metabolic network. Bioinformatics 29:i154-i161.
26. Magnuson, T. S., M. W. Swenson, A. J. Paszczynski, L. A. Deobald, D. Kerk, and D. E. Cummings 2010. Proteogenomic and functional analysis of chromate reduction in Acidiphilium cryptum JF-5, an Fe(III)-respiring acidophile. Biometals 23:1129-1138.
27. Mao, F., P. Dam, J. Chou, V. Olman, and Y. Xu 2009. DOOR: a database for prokaryotic operons. Nucleic Acids Res. 37:D459-D463.
28. McCloskey, D., B. Ø. Palsson, and A. M. Feist 2013. Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli. Mol. Syst. Biol. 9:661.
29. Meyer, F., A. Goesmann, A. C. McHardy, D. Bartels, T. Bekel, J. Clausen, et al. 2003. GenDB - an open source genome annotation system for prokaryote genomes. Nucleic Acids Res. 31:2187-2195.
30. Mi, S., J. Song, J. Lin, Y. Che, H. Zheng, and J. Lin 2011. Complete genome of Leptospirillum ferriphilum ML-04 provides insight into its physiology and environmental adaptation. J. Microbiol. 49:890-901.
31. Nuñez, P.A., H. Romero, M.D. Farber, and E.P.C. Rocha 2013. Natural selection for operons depends on genome size. Genome Biol Evol, 5:2242-2254.
32. Orphan, V. J. 2009. Methods for unveiling cryptic microbial partnerships in nature. Curr. Opin. Microbiol. 12:231-237.
33. Patel, P. V., T. A. Gianoulis, R. D. Bjornson, K. Y. Yip, D. M. Engelman, and M. B. Gerstein 2010. Analysis of membrane proteins in metagenomics: networks of correlated environmental features and protein families. Genome Res. 20:960-971.
34. Quatrini, R., C. Appia-Ayme, Y. Denis, E. Jedlicki, D. S. Holmes, and V. Bonnefoy 2009. Extending the models for iron and sulfur oxidation in the extreme acidophile Acidithiobacillus ferrooxidans. BMC Genom. 10:394.
35. Raes, J., I. Letunic, T. Yamada, L. J. Jensen, and P. Bork 2011. Toward molecular trait-based ecology through integration of biogeochemical, geographical and metagenomic data. Mol. Syst. Biol. 7:473.
36. Ranjard, L., S. Dequiedt, N. Chemidlin Prévost-Bouré, J. Thioulouse, N. P. A. Saby, M. Lelievre, et al. 2013. Turnover of soil bacterial diversity driven by wide-scale environmental heterogeneity. Nat. Commun. 4:1434.
37. Ravasz, E., A. L. Somera, D. A. Mongru, Z. N. Oltvai, and A.-L. Barabási 2002. Hierarchical organization of modularity in metabolic networks. Science 297:1551-1555.
38. Roesch, L. F. W., R. R. Fulthorpe, A. Riva, G. Casella, A. K. M. Hadwin, A. D. Kent, et al. 2007. Pyrosequencing enumerates and contrasts soil microbial diversity. ISME J. 1:283-290.
39. Ruan, Q., D. Dutta, M. S. Schwalbach, J. A. Steele, J. A. Fuhrman, and F. Sun 2006. Local similarity analysis reveals unique associations among marine bacterioplankton species and environmental factors. Bioinformatics 22:2532-2538.
40. Ruan, J., A. K. Dean, and W. Zhang 2010. A general co-expression network-based approach to gene expression analysis: comparison and applications. BMC Syst. Biol. 4:8.
41. Segata, N., D. Boernigen, T. L. Tickle, X. C. Morgan, W. S. Garrett, and C. Huttenhower 2013. Computational meta'omics for microbial community studies. Mol. Syst. Biol. 9:666.
42. Taboada, B., R. Ciria, C. E. Martinez-Guerrero, and E. Merino 2012. ProOpDB: Prokaryotic Operon DataBase. Nucleic Acids Res. 40:D627-D631.
43. Travisany, D., A. Di Genova, A. Sepúlveda, R. A. Bobadilla-Fazzini, P. Parada, and A. Maass 2012. Draft genome sequence of the Sulfobacillus thermosulfidooxidans Cutipay strain, an indigenous bacterium isolated from a naturally extreme mining environment in Northern Chile. J. Bacteriol. 194:6327-6328.
44. Tzamali, E., P. Poirazi, I. G. Tollis, and M. Reczko 2011. A computational exploration of bacterial metabolic diversity identifying metabolic interactions and growth-efficient strain communities. BMC Syst. Biol. 5:167.
45. Valdés, J., F. Veloso, E. Jedlicki, and D. Holmes 2003. Metabolic reconstruction of sulfur assimilation in the extremophile Acidithiobacillus ferrooxidans based on genome analysis. BMC Genom. 4:51.
46. Valdés, J., I. Pedroso, R. Quatrini, R.J. Dodson, H. Tettelin, R. Blake, et al. 2008. Acidithiobacillus ferrooxidans metabolism: from genome sequence to industrial applications. BMC Genom. 9:597.
47. Valdés, J., J. P. Cárdenas, R. Quatrini, M. Esparza, H. Osorio, F. Duarte, et al. 2010. Comparative genomics begins to unravel the ecophysiology of bioleaching. Hydrometallurgy 104:471-476.
48. Valdés, J., F. Ossandon, F. Quatrini, M. Dopson, and D. S. Holmes 2011. Draft genome sequence of the extremely acidophilic biomining bacterium Acidithiobacillus thiooxidans ATCC 19377 provides insights into the evolution of the Acidithiobacillus genus. J. Bacteriol. 193:7003-7004.
49. de Vargas, C., S. Audic, N. Henry, J. Decelle, F. Mahé, R. Logares, et al. 2015. Ocean plankton. Eukaryotic plankton diversity in the sunlit ocean. Science 348:1261605.
50. Wächtershäuser, G. 2000. Origin of life. Life as we don't know it. Science 289:1307-1308.
51. Yin, H., L. Cao, M. Xie, Q. Chen, G. Qiu, and J. Zhou 2008. Bacterial diversity based on 16S rRNA and gyrB genes at Yinshan mine, China. Syst. Appl. Microbiol. 31:302-311.
52. Yus, E., T. Maier, K. Michalodimitrakis, V. van Noort, T. Yamada, W. H. Chen, et al. 2009. Impact of genome reduction on bacterial metabolism and its regulation. Science 326:1263-1268.
53. Zaneveld, J. R. R., L. W. Parfrey, W. Van Treuren, C. Lozupone, J. C. Clemente, D. Knights, et al. 2011. Combined phylogenetic and genomic approaches for the high-throughput study of microbial habitat adaptation. Trends Microbiol. 19:472-482.
54. Zelezniak, A., S. Andrejev, O. Ponomarova, D. R. Mende, P. Bork, and K. R. Patil 2015. Metabolic dependencies drive species co-occurrence in diverse microbial communities. Proc. Natl Acad. Sci. USA. doi:10.1073/pnas.1421834112.
55. Zengler, K., and B. Ø. Palsson 2012. A road map for the development of community systems (CoSy) biology. Nat. Rev. Microbiol. 10:366-372.
56. Zomorrodi, A. R., M. M. Islam, and C. D. Maranas 2014. d-OptCom: dynamic multi-level and multi-objective metabolic modeling of microbial communities. ACS Synth. Biol. 3:247-257.