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Modeling microbial communities from atrazine contaminated soils promotes the development of biostimulation solutions

The ISME Journal (2018) | Download Citation


Microbial communities play a vital role in biogeochemical cycles, allowing the biodegradation of a wide range of pollutants. The composition of the community and the interactions between its members affect degradation rate and determine the identity of the final products. Here, we demonstrate the application of sequencing technologies and metabolic modeling approaches towards enhancing biodegradation of atrazine—a herbicide causing environmental pollution. Treatment of agriculture soil with atrazine is shown to induce significant changes in community structure and functional performances. Genome-scale metabolic models were constructed for Arthrobacter, the atrazine degrader, and four other non-atrazine degrading species whose relative abundance in soil was changed following exposure to the herbicide. By modeling community function we show that consortia including the direct degrader and non-degrader differentially abundant species perform better than Arthrobacter alone. Simulations predict that growth/degradation enhancement is derived by metabolic exchanges between community members. Based on simulations we designed endogenous consortia optimized for enhanced degradation whose performances were validated in vitro and biostimulation strategies that were tested in pot experiments. Overall, our analysis demonstrates that understanding community function in its wider context, beyond the single direct degrader perspective, promotes the design of biostimulation strategies.

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  1. 1.

    Hansen SK, Rainey PB, Haagensen JAJ, Molin S. Evolution of species interactions in a biofilm community. Nature. 2007;445:533–6.

  2. 2.

    Fuhrman JA. Microbial community structure and its functional implications. Nature. 2009;459:193–9.

  3. 3.

    Großkopf T, Soyer OS. Synthetic microbial communities. Curr Opin Microbiol. 2014;18:72–7.

  4. 4.

    Falkowski PG, Fenchel T, Delong EF. The microbial engines that drive Earth’s biogeochemical cycles. Science. 2008;320:1034–9.

  5. 5.

    Li X, Li P, Lin X, Zhang C, Li Q, Gong Z. Biodegradation of aged polycyclic aromatic hydrocarbons (PAHs) by microbial consortia in soil and slurry phases. J Hazard Mater. 2008;150:21–26.

  6. 6.

    Bacosa HP, Suto K, Inoue C. Bacterial community dynamics during the preferential degradation of aromatic hydrocarbons by a microbial consortium. Int Biodeterior Biodegrad. 2012;74:109–15.

  7. 7.

    Keller AH, Kleinsteuber S, Vogt C. Anaerobic benzene mineralization by nitrate-reducing and sulfate-reducing microbial consortia enriched from the same site: comparison of community composition and degradation characteristics. Microb Ecol. 2018;75:941–53.

  8. 8.

    Fu H, Zhang JJ, Xu Y, Chao HJ, Zhou NY. Simultaneous biodegradation of three mononitrophenol isomers by a tailor-made microbial consortium immobilized in sequential batch reactors. Lett Appl Microbiol. 2017;64:203–9.

  9. 9.

    Roh SW, Kim K-H, Nam Y-D, Chang H-W, Park E-J, Bae J-W. Investigation of archaeal and bacterial diversity in fermented seafood using barcoded pyrosequencing. ISME J. 2010;4:1–16.

  10. 10.

    Ercolini D. High-throughput sequencing and metagenomics: moving forward in the culture-independent analysis of food microbial ecology. Appl Environ Microbiol. 2013;79:3148–55.

  11. 11.

    Walter J, Ley R. The human gut microbiome: ecology and recent evolutionary changes. Annu Rev Microbiol. 2011;65:411–29.

  12. 12.

    Huttenhower C, Gevers D, Knight R, Abubucker S, Badger JH, Chinwalla AT, et al. Structure, function and diversity of the healthy human microbiome. Nature. 2012;486:207–14.

  13. 13.

    Adams GO, Fufeyin PT, Okoro SE, Ehinomen I. Bioremediation, biostimulation and bioaugmention: a review. Int J Environ Bioremediation Biodegrad. 2015;3:28–39.

  14. 14.

    Zomorrodi AR, Segrè D. Synthetic ecology of microbes: mathematical models and applications. J Mol Biol. 2016;428:837–61.

  15. 15.

    Bento FM, Camargo FAO, Okeke BC, Frankenberger WT. Comparative bioremediation of soils contaminated with diesel oil by natural attenuation, biostimulation and bioaugmentation. Bioresour Technol. 2005;96:1049–55.

  16. 16.

    Mrozik A, Piotrowska-Seget Z. Bioaugmentation as a strategy for cleaning up of soils contaminated with aromatic compounds. Microbiol Res. 2010;165:363–75.

  17. 17.

    Widder S, Allen RJ, Pfeiffer T, Curtis TP, Wiuf C, Sloan WT, et al. Challenges in microbial ecology: building predictive understanding of community function and dynamics. ISME J. 2016;10:2557–68.

  18. 18.

    Ofaim S, Ofek-Lalzar M, Sela N, Jinag J, Kashi Y, Minz D, et al. Analysis of microbial functions in the rhizosphere using a metabolic-network based framework for metagenomics interpretation. Front Microbiol. 2017;8:1606.

  19. 19.

    Nagarajan H, Embree M, Rotaru A-E, Shrestha PM, Feist AM, Palsson BØ, et al. Characterization and modelling of interspecies electron transfer mechanisms and microbial community dynamics of a syntrophic association. Nat Commun. 2013;4:ncomms 3809.

  20. 20.

    Zelezniak A, Andrejev S, Ponomarova O, Mende DR, Bork P, Patil KR. Metabolic dependencies drive species co-occurrence in diverse microbial communities. Proc Natl Acad Sci USA. 2015;112:6449–54.

  21. 21.

    Opatovsky I, Santos-Garcia D, Ruan Z, Lahav T, Ofaim S, Mouton L, et al. Modeling trophic dependencies and exchanges among insects’ bacterial symbionts in a host-simulated environment. BMC Genom. 2018;19:402.

  22. 22.

    Freilich S, Zarecki R, Eilam O, Segal ES, Henry CS, Kupiec M, et al. Competitive and cooperative metabolic interactions in bacterial communities. Nat Commun. 2011;2:589.

  23. 23.

    Zhuang K, Izallalen M, Mouser P, Richter H, Risso C, Mahadevan R, et al. Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments. ISME J. 2011;5:305–16.

  24. 24.

    Jablonowski ND, Köppchen S, Hofmann D, Schäffer A, Burauel P. Persistence of 14C-labeled atrazine and its residues in a field lysimeter soil after 22 years. Environ Pollut. 2009;157:2126–31.

  25. 25.

    Chiaia-Hernandez AC, Keller A, Wächter D, Steinlin C, Camenzuli L, Hollender J, et al. Long-term persistence of pesticides and TPs in archived agricultural soil samples and comparison with pesticide application. Environ Sci Technol. 2017;51:10642–51.

  26. 26.

    Tappe W, Groeneweg J, Jantsch B. Diffuse atrazine pollution in German aquifers. Biodegradation. 2002;13:3–10.

  27. 27.

    Mahía J, Martín A, Díaz-Raviña M. Extractable atrazine and its metabolites in agricultural soils from the temperate humid zone. Environ Geochem Health. 2008;30:147–52.

  28. 28.

    Murphy MB, Hecker M, Coady KK, Tompsett AR, Jones PD, Du Preez LH, et al. Atrazine concentrations, gonadal gross morphology and histology in ranid frogs collected in Michigan agricultural areas. Aquat Toxicol. 2006;76:230–45.

  29. 29.

    Dalton R. Frogs put in the gender blender by America’s favourite herbicide. Nature. 2002;416:665–6.

  30. 30.

    Hayes TB, Khoury V, Narayan A, Nazir M, Park A, Brown T, et al. Atrazine induces complete feminization and chemical castration in male African clawed frogs (Xenopus laevis). Proc Natl Acad Sci USA. 2010;107:4612–7.

  31. 31.

    Hénault-Ethier L. Backgrounder: atrazine: banned in Europe, common in Canada. Canada: equiterre; 2016.

  32. 32.

    de Souza ML, Newcombe D, Alvey S, Crowley DE, Hay A, Sadowsky MJ, et al. Molecular basis of a bacterial consortium: interspecies catabolism of atrazine. Appl Environ Microbiol. 1998;64:178–84.

  33. 33.

    Smith D, Alvey S, Crowley DE. Cooperative catabolic pathways within an atrazine-degrading enrichment culture isolated from soil. FEMS Microbiol Ecol. 2005;53:265–75.

  34. 34.

    Yang C, Li Y, Zhang K, Wang X, Ma C, Tang H, et al. Atrazine degradation by a simple consortium of Klebsiella sp. A1 and Comamonas sp. A2 in nitrogen enriched medium. Biodegradation. 2010;21:97–105.

  35. 35.

    Onofri A, Carbonell EA, Piepho H-P, Mortimer AM, Cousens RD. Current statistical issues in weed research. Weed Res. 2010;50:5–24.

  36. 36.

    Jettner RJ, Walker SR, Churchett JD, Blamey FPC, Adkins SW, Bell K. Plant sensitivity to atrazine and chlorsulfuron residues in a soil-free system. Weed Res. 1999;39:287–95.

  37. 37.

    Eizenberg H, Goldwasser Y, Achdary G, Hershenhorn J. The potential of sulfosulfuron to control troublesome weeds in tomato. Weed Technol. 2003;17:133–7.

  38. 38.

    Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics. 2011;27:2194–2200.

  39. 39.

    Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA. 2011;108(Suppl 1):4516–22.

  40. 40.

    Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7:335–6.

  41. 41.

    Hammer Ø, Harper DAT, Ryan PD. PAST: paleontological statistics software package for education and data analysis. Palaeontol Electron. 2001;4:9.

  42. 42.

    Henry CS, DeJongh M, Best AA, Frybarger PM, Linsay B, Stevens RL. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol. 2010;28:977–82.

  43. 43.

    Meyer F, Paarmann D, D’Souza M, Olson R, Glass E, Kubal M, et al. The metagenomics RAST server – a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinforma. 2008;9:386.

  44. 44.

    Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M. Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res. 2014;42:D199–D205.

  45. 45.

    Apweiler R, Bairoch A, Wu CH, Barker WC, Boeckmann B, Ferro S, et al. UniProt: the universal protein knowledgebase. Nucleic Acids Res. 2004;32:D115–9.

  46. 46.

    Nordberg H, Cantor M, Dusheyko S, Hua S, Poliakov A, Shabalov I, et al. The genome portal of the Department of Energy Joint Genome Institute: 2014 updates. Nucleic Acids Res. 2014;42:D26–D31.

  47. 47.

    Jiang J, Pan Y, Hu S, Zhang X, Hu B, Huang H, et al. Halomonas songnenensis sp. nov., a moderately halophilic bacterium isolated from saline and alkaline soils. Int J Syst Evol Microbiol. 2014;64:1662–9.

  48. 48.

    Liu WY, Zeng J, Wang L, Dou YT, Yang SS. Halobacillus dabanensis sp. nov. and Halobacillus aidingensis sp. nov., isolated from salt lakes in Xinjiang, China. Int J Syst Evol Microbiol. 2005;55:1991–6.

  49. 49.

    Ma C, Zhuang L, Zhou SG, Yang GQ, Yuan Y, Xu RX. Alkaline extracellular reduction: isolation and characterization of an alkaliphilic and halotolerant bacterium, Bacillus pseudofirmus MC02. J Appl Microbiol. 2012;112:883–91.

  50. 50.

    Srinivas TNR, Anil Kumar P, Madhu S, Sunil B, Sharma TVRS, Shivaji S. Cesiribacter andamanensis gen. nov., sp. nov., isolated from a soil sample from a mud volcano. Int J Syst Evol Microbiol. 2011;61:1521–7.

  51. 51.

    Orth JD, Thiele I, Palsson BØ. What is flux balance analysis? Nat Biotechnol. 2010;28:245–8.

  52. 52.

    Thiele I, Palsson BØ. A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat Protoc. 2010;5:93–121.

  53. 53.

    Schellenberger J, Que R, Fleming RMT, Thiele I, Orth JD, Feist AM, et al. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nat Protoc. 2011;6:1290–307.

  54. 54.

    Harcombe WR, Riehl WJ, Dukovski I, Granger BR, Betts A, Lang AH, et al. Metabolic resource allocation in individual microbes determines ecosystem interactions and spatial dynamics. Cell Rep. 2014;7:1104–15.

  55. 55.

    Wintermute EH, Silver PA. Emergent cooperation in microbial metabolism. Mol Syst Biol. 2010;6:407.

  56. 56.

    Johns NI, Blazejewski T, Gomes AL, Wang HH. Principles for designing synthetic microbial communities. Curr Opin Microbiol. 2016;31:146–53.

  57. 57.

    Sheth RU, Cabral V, Chen SP, Wang HH. Manipulating bacterial communities by in situ microbiome engineering. Trends Genet. 2016;32:189–200.

  58. 58.

    Huang X, He J, Yan X, Hong Q, Chen K, He Q, et al. Microbial catabolism of chemical herbicides: microbial resources, metabolic pathways and catabolic genes. Pestic Biochem Physiol. 2017;143:272–97.

  59. 59.

    Kato S, Haruta S, Cui ZJ, Ishii M, Igarashi Y. Stable coexistence of five bacterial strains as a cellulose-degrading community. Appl Environ Microbiol. 2005;71:7099–106.

  60. 60.

    Lawrence D, Fiegna F, Behrends V, Bundy JG, Phillimore AB, Bell T, et al. Species interactions alter evolutionary responses to a novel environment Ellner SP (ed). PLoS Biol. 2012;10:e1001330.

  61. 61.

    Chen K, Huang L, Xu C, Liu X, He J, Zinder SH, et al. Molecular characterization of the enzymes involved in the degradation of a brominated aromatic herbicide. Mol Microbiol. 2013;89:1121–39.

  62. 62.

    Muller EEL, Faust K, Widder S, Herold M, Martínez Arbas S, Wilmes P. Using metabolic networks to resolve ecological properties of microbiomes. Curr Opin Syst Biol. 2018;8:73–80.

  63. 63.

    Zeidan AA, Rådström P, van Niel EW. Stable coexistence of two Caldicellulosiruptor species in a de novo constructed hydrogen-producing co-culture. Microb Cell Fact. 2010;9:102.

  64. 64.

    Ponomarova O, Patil KR. Metabolic interactions in microbial communities: untangling the Gordian knot. Curr Opin Microbiol. 2015;27:37–44.

  65. 65.

    Embree M, Nagarajan H, Movahedi N, Chitsaz H, Zengler K. Single-cell genome and metatranscriptome sequencing reveal metabolic interactions of an alkane-degrading methanogenic community. ISME J. 2014;8:757–67.

  66. 66.

    Strong LC, Rosendahl C, Johnson G, Sadowsky MJ, Wackett LP. Arthrobacter aurescens TC1 metabolizes diverse s-triazine ring compounds. Appl Environ Microbiol. 2002;68:5973–80.

  67. 67.

    Abdelhafid R, Houot S, Barriuso E. Dependence of atrazine degradation on C and N availability in adapted and non-adapted soils. Soil Biol Biochem. 2000;32:389–401.

  68. 68.

    Langille MG, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes JA, et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol. 2013;31:814–21.

  69. 69.

    Friedman N, Shriker E, Gold B, Durman T, Zarecki R, Ruppin E, et al. Diet-induced changes of redox potential underlie compositional shifts in the rumen archaeal community. Environ Microbiol. 2017;19:174–84.

  70. 70.

    Magnúsdóttir S, Heinken A, Kutt L, Ravcheev DA, Bauer E, Noronha A, et al. Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota. Nat Biotechnol. 2017;35:81–89.

  71. 71.

    Aßhauer KP, Wemheuer B, Daniel R, Meinicke P. Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data. Bioinformatics. 2015;31:2882–4.

  72. 72.

    Anantharaman K, Brown CT, Hug LA, Sharon I, Castelle CJ, Probst AJ, et al. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat Commun. 2016;7:13219.

  73. 73.

    Udaondo Z, Molina L, Segura A, Duque E, Ramos JL. Analysis of the core genome and pangenome of P seudomonas putida. Environ Microbiol. 2016;18:3268–83.

  74. 74.

    Garcia-Garcera M, Touchon M, Brisse S, Rocha EPC. Metagenomic assessment of the interplay between the environment and the genetic diversification of Acinetobacter. Environ Microbiol. 2017;19:5010–24.

  75. 75.

    Herbold CW, Lehtovirta-Morley LE, Jung M-Y, Jehmlich N, Hausmann B, Han P, et al. Ammonia-oxidising archaea living at low pH: Insights from comparative genomics. Environ Microbiol. 2017;19:4939–52.

  76. 76.

    Latendresse M, Krummenacker M, Trupp M, Karp PD. Construction and completion of flux balance models from pathway databases. Bioinformatics. 2012;28:388–96.

  77. 77.

    Agren R, Liu L, Shoaie S, Vongsangnak W, Nookaew I, Nielsen J. The RAVEN toolbox and its use for generating a genome-scale metabolic model for Penicillium chrysogenum. PLoS Comput Biol. 2013;9:e1002980.

  78. 78.

    Machado D, Andrejev S, Tramontano M, Patil KR. Fast automated reconstruction of genome-scale metabolic models for microbial species and communities. Nucleic Acids Res. 2018;46:7542–53.

  79. 79.

    El Amrani A, Dumas AS, Wick LY, Yergeau E, Berthomé R. “Omics” insights into PAH degradation toward improved green remediation biotechnologies. Environ Sci Technol. 2015;49:11281–91.

  80. 80.

    Daliri EB, Wei S, Oh DH, Lee BH. The human microbiome and metabolomics: current concepts and applications. Crit Rev Food Sci Nutr. 2017;57:3565–76.

  81. 81.

    Parmar KM, Gaikwad SL, Dhakephalkar PK, Kothari R, Singh RP. Intriguing interaction of bacteriophage-host association: an understanding in the era of omics. Front Microbiol. 2017;8:559.

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This work was supported by grants from National Key Research and Development Program (2016YFD0800203), the NSFC-ISF joint program (31461143009), Israel Science Foundation Grant no. 1416/14, and the Science Foundation of Jiangsu Province, China (BK20150670).

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Author notes

  1. These authors contributed equally: Xihui Xu and Raphy Zarecki.


  1. Department of Microbiology, Key Lab of Microbiology for Agricultural Environment, Ministry of Agriculture, College of Life Sciences, Nanjing Agricultural University, Nanjing, 210095, China

    • Xihui Xu
    • , Xiaowei Liu
    • , Chen Chen
    • , Shunli Hu
    •  & Jiandong Jiang
  2. Newe Ya’ar Research Center, Agricultural Research Organization, P.O. Box 1021, Ramat Yishay, 30095, Israel

    • Xihui Xu
    • , Raphy Zarecki
    • , Shlomit Medina
    • , Shany Ofaim
    • , Dan Brom
    • , Hanan Eizenberg
    •  & Shiri Freilich
  3. Faculty of Biotechnology and Food Engineering, Technion-Israel Institute of Technology, Haifa, Israel

    • Shany Ofaim
  4. Department of Environmental Hydrology and Microbiology, The Zuckerberg Institute for Water Research, Ben-Gurion University of the Negev, Sede-Boqer Campus, Sede-Boqer, 8499000, Israel

    • Daniella Gat
    • , Seema Porob
    •  & Zeev Ronen


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