Advertisement

Synthetic microbial consortia for biosynthesis and biodegradation: promises and challenges

  • Shun Che
  • Yujie MenEmail author
Metabolic Engineering and Synthetic Biology - Review

Abstract

Functional differentiation and metabolite exchange enable microbial consortia to perform complex metabolic tasks and efficiently cycle the nutrients. Inspired by the cooperative relationships in environmental microbial consortia, synthetic microbial consortia have great promise for studying the microbial interactions in nature and more importantly for various engineering applications. However, challenges coexist with promises, and the potential of consortium-based technologies is far from being fully harnessed. Thorough understanding of the underlying molecular mechanisms of microbial interactions is greatly needed for the rational design and optimization of defined consortia. These knowledge gaps could be potentially filled with the assistance of the ongoing revolution in systems biology and synthetic biology tools. As current fundamental and technical obstacles down the road being removed, we would expect new avenues with synthetic microbial consortia playing important roles in biological and environmental engineering processes such as bioproduction of desired chemicals and fuels, as well as biodegradation of persistent contaminants.

Keywords

Microbial consortia Systems biology Synthetic biology Biosynthesis Biodegradation 

Notes

References

  1. 1.
    Altenbuchner J (2016) Editing of the Bacillus subtilis genome by the CRISPR-Cas9 system. Appl Environ Microbiol 82:5421–5427.  https://doi.org/10.1128/AEM.01453-16 Google Scholar
  2. 2.
    Aschenbrenner IA, Cernava T, Berg G, Grube M (2016) Understanding microbial multi-species symbioses. Front Microbiol.  https://doi.org/10.3389/fmicb.2016.00180 Google Scholar
  3. 3.
    Aulenta F, Gossett JM, Papini MP, Rossetti S, Majone M (2005) Comparative study of methanol, butyrate, and hydrogen as electron donors for long-term dechlorination of tetrachloroethene in mixed anerobic cultures. Biotechnol Bioeng 91:743–753.  https://doi.org/10.1002/bit.20569 Google Scholar
  4. 4.
    Bao Z, Xiao H, Liang J, Zhang L, Xiong X, Sun N, Si T, Zhao H (2015) Homology-integrated CRISPR-Cas (HI-CRISPR) system for one-step multigene disruption in Saccharomyces cerevisiae. Acs Synth Biol 4:585–594.  https://doi.org/10.1021/sb500255k Google Scholar
  5. 5.
    Bassalo MC, Liu RM, Gill RT (2016) Directed evolution and synthetic biology applications to microbial systems. Curr Opin Biotechnol 39:126–133.  https://doi.org/10.1016/j.copbio.2016.03.016 Google Scholar
  6. 6.
    Becker J, Reinefeld J, Stellmacher R, Schafer R, Lange A, Meyer H, Lalk M, Zelder O, von Abendroth G, Schroder H, Haefner S, Wittmann C (2013) Systems-wide analysis and engineering of metabolic pathway fluxes in bio-succinate producing Basfia succiniciproducens. Biotechnol Bioeng 110:3013–3023.  https://doi.org/10.1002/bit.24963 Google Scholar
  7. 7.
    Beliaev AS, Romine MF, Serres M, Bernstein HC, Linggi BE, Markillie LM, Isern NG, Chrisler WB, Kucek LA, Hill EA, Pinchuk GE, Bryant DA, Wiley HS, Fredrickson JK, Konopka A (2014) Inference of interactions in cyanobacterial-heterotrophic co-cultures via transcriptome sequencing. ISME J 8:2243–2255.  https://doi.org/10.1038/ismej.2014.69 Google Scholar
  8. 8.
    Bernstein HC, Carlson RP (2012) Microbial consortia engineering for cellular factories: in vitro to in silico systems. Comput Struct Biotechnol J 3:e201210017.  https://doi.org/10.5936/csbj.201210017 Google Scholar
  9. 9.
    Bernstein HC, Paulson SD, Carlson RP (2012) Synthetic Escherichia coli consortia engineered for syntrophy demonstrate enhanced biomass productivity. J Biotechnol 157:159–166.  https://doi.org/10.1016/j.jbiotec.2011.10.001 Google Scholar
  10. 10.
    Biebl H, Pfennig N (1978) Growth yields of green sulfur bacteria in mixed cultures with sulfur and sulfate reducing bacteria. Arch Microbiol 117:9–16.  https://doi.org/10.1007/Bf00689344 Google Scholar
  11. 11.
    Bikard D, Jiang W, Samai P, Hochschild A, Zhang F, Marraffini LA (2013) Programmable repression and activation of bacterial gene expression using an engineered CRISPR-Cas system. Nucleic Acids Res 41:7429–7437.  https://doi.org/10.1093/nar/gkt520 Google Scholar
  12. 12.
    Bittihn P, Din MO, Tsimring LS, Hasty J (2018) Rational engineering of synthetic microbial systems: from single cells to consortia. Curr Opin Microbiol 45:92–99.  https://doi.org/10.1016/j.mib.2018.02.009 Google Scholar
  13. 13.
    Boaro AA, Kim YM, Konopka AE, Callister SJ, Ahring BK (2014) Integrated ‘omics analysis for studying the microbial community response to a pH perturbation of a cellulose-degrading bioreactor culture. FEMS Microbiol Ecol 90:802–815.  https://doi.org/10.1111/1574-6941.12435 Google Scholar
  14. 14.
    Boetius A, Ravenschlag K, Schubert CJ, Rickert D, Widdel F, Gieseke A, Amann R, Jorgensen BB, Witte U, Pfannkuche O (2000) A marine microbial consortium apparently mediating anaerobic oxidation of methane. Nature 407:623–626.  https://doi.org/10.1038/35036572 Google Scholar
  15. 15.
    Booth IR (1985) Regulation of cytoplasmic pH in bacteria. Microbiol Rev 49:359–378Google Scholar
  16. 16.
    Bozinovski D, Taubert M, Kleinsteuber S, Richnow HH, von Bergen M, Vogt C, Seifert J (2014) Metaproteogenomic analysis of a sulfate-reducing enrichment culture reveals genomic organization of key enzymes in the m-xylene degradation pathway and metabolic activity of proteobacteria. Syst Appl Microbiol 37:488–501.  https://doi.org/10.1016/j.syapm.2014.07.005 Google Scholar
  17. 17.
    Brenner K, You L, Arnold FH (2008) Engineering microbial consortia: a new frontier in synthetic biology. Trends Biotechnol 26:483–489.  https://doi.org/10.1016/j.tibtech.2008.05.004 Google Scholar
  18. 18.
    Brethauer S, Studer MH (2014) Consolidated bioprocessing of lignocellulose by a microbial consortium. Energy Environ Sci 7:1446–1453.  https://doi.org/10.1039/c3ee41753k Google Scholar
  19. 19.
    Bruder MR, Pyne ME, Moo-Young M, Chung DA, Chou CP (2016) Extending CRISPR-Cas9 technology from genome editing to transcriptional engineering in the genus Clostridium. Appl Environ Microbiol 82:6109–6119.  https://doi.org/10.1128/AEM.02128-16 Google Scholar
  20. 20.
    Burmolle M, Webb JS, Rao D, Hansen LH, Sorensen SJ, Kjelleberg S (2006) Enhanced biofilm formation and increased resistance to antimicrobial agents and bacterial invasion are caused by synergistic interactions in multispecies biofilms. Appl Environ Microbiol 72:3916–3923.  https://doi.org/10.1128/Aem.03022-05 Google Scholar
  21. 21.
    Chandra Mohana N, Yashavantha Rao HC, Rakshith D, Mithun PR, Nuthan BR, Satish S (2018) Omics based approach for biodiscovery of microbial natural products in antibiotic resistance era. J Genet Eng Biotechnol 16:1–8.  https://doi.org/10.1016/j.jgeb.2018.01.006 Google Scholar
  22. 22.
    Cherubini F (2010) The biorefinery concept: using biomass instead of oil for producing energy and chemicals. Energ Convers Manag 51:1412–1421.  https://doi.org/10.1016/j.enconman.2010.01.015 Google Scholar
  23. 23.
    Chignell JF, Park S, Lacerda CMR, De Long SK, Reardon KF (2018) Label-free proteomics of a defined, binary co-culture reveals diversity of competitive responses between members of a model soil microbial system. Microbiol Ecol 75:701–719.  https://doi.org/10.1007/s00248-017-1072-1 Google Scholar
  24. 24.
    Chou HH, Keasling JD (2013) Programming adaptive control to evolve increased metabolite production. Nat Commun.  https://doi.org/10.1038/ncomms3595 Google Scholar
  25. 25.
    Chuang JS (2012) Engineering multicellular traits in synthetic microbial populations. Curr Opin Chem Biol 16:370–378.  https://doi.org/10.1016/j.cbpa.2012.04.002 Google Scholar
  26. 26.
    Cobb RE, Chao R, Zhao HM (2013) Directed evolution: past, present, and future. AIChE J 59:1432–1440.  https://doi.org/10.1002/aic.13995 Google Scholar
  27. 27.
    Cobb RE, Sun N, Zhao HM (2013) Directed evolution as a powerful synthetic biology tool. Methods 60:81–90.  https://doi.org/10.1016/j.ymeth.2012.03.009 Google Scholar
  28. 28.
    Cobb RE, Wang Y, Zhao H (2015) High-efficiency multiplex genome editing of Streptomyces species using an engineered CRISPR/Cas system. Acs Synth Biol 4:723–728.  https://doi.org/10.1021/sb500351f Google Scholar
  29. 29.
    De Mey M, De Maeseneire S, Soetaert W, Vandamme E (2007) Minimizing acetate formation in E. coli fermentations. J Ind Microbiol Biot 34:689–700.  https://doi.org/10.1007/s10295-007-0244-2 Google Scholar
  30. 30.
    De Roy K, Marzorati M, Van den Abbeele P, Van de Wiele T, Boon N (2014) Synthetic microbial ecosystems: an exciting tool to understand and apply microbial communities. Environ Microbiol 16:1472–1481.  https://doi.org/10.1111/1462-2920.12343 Google Scholar
  31. 31.
    Dekas AE, Chadwick GL, Bowles MW, Joye SB, Orphan VJ (2014) Spatial distribution of nitrogen fixation in methane seep sediment and the role of the ANME archaea. Environ Microbiol 16:3012–3029.  https://doi.org/10.1111/1462-2920.12247 Google Scholar
  32. 32.
    Dekas AE, Connon SA, Chadwick GL, Trembath-Reichert E, Orphan VJ (2016) Activity and interactions of methane seep microorganisms assessed by parallel transcription and FISH-NanoSIMS analyses. ISME J 10:678–692.  https://doi.org/10.1038/ismej.2015.145 Google Scholar
  33. 33.
    Ettwig KF, Butler MK, Le Paslier D, Pelletier E, Mangenot S, Kuypers MMM, Schreiber F, Dutilh BE, Zedelius J, de Beer D, Gloerich J, Wessels HJCT, van Alen T, Luesken F, Wu ML, van de Pas-Schoonen KT, den Camp HJMO, Janssen-Megens EM, Francoijs KJ, Stunnenberg H, Weissenbach J, Jetten MSM, Strous M (2010) Nitrite-driven anaerobic methane oxidation by oxygenic bacteria. Nature 464:543–548.  https://doi.org/10.1038/nature08883 Google Scholar
  34. 34.
    Falkowski PG, Fenchel T, Delong EF (2008) The microbial engines that drive Earth’s biogeochemical cycles. Science 320:1034–1039.  https://doi.org/10.1126/science.1153213 PubMedGoogle Scholar
  35. 35.
    Faust K, Raes J (2012) Microbial interactions: from networks to models. Nat Rev Microbiol 10:538–550.  https://doi.org/10.1038/nrmicro2832 Google Scholar
  36. 36.
    Freeborn RA, West KA, Bhupathiraju VK, Chauhan S, Rahm BG, Richardson RE, Alvarez-Cohen L (2005) Phylogenetic analysis of TCE-dechlorinating consortia enriched on a variety of electron donors. Environ Sci Technol 39:8358–8368.  https://doi.org/10.1021/es048003p Google Scholar
  37. 37.
    Fu N, Peiris P, Markham J, Bavor J (2009) A novel co-culture process with Zymomonas mobilis and Pichia stipitis for efficient ethanol production on glucose/xylose mixtures. Enzyme Microb Tech 45:210–217.  https://doi.org/10.1016/j.enzmictec.2009.04.006 Google Scholar
  38. 38.
    Garst A, Lynch M, Evans R, Gill RT (2013) Strategies for the multiplex mapping of genes to traits. Microb Cell Fact 12:99.  https://doi.org/10.1186/1475-2859-12-99 Google Scholar
  39. 39.
    Garst AD, Bassalo MC, Pines G, Lynch SA, Halweg-Edwards AL, Liu RM, Liang LY, Wang ZW, Zeitoun R, Alexander WG, Gill RT (2017) Genome-wide mapping of mutations at single-nucleotide resolution for protein, metabolic and genome engineering. Nat Biotechnol 35:48–55.  https://doi.org/10.1038/nbt.3718 Google Scholar
  40. 40.
    Gebreselassie NA, Antoniewicz MR (2015) 13C-metabolic flux analysis of co-cultures: a novel approach. Metab Eng 31:132–139.  https://doi.org/10.1016/j.ymben.2015.07.005 Google Scholar
  41. 41.
    Ghosh A, Nilmeier J, Weaver D, Adams PD, Keasling JD, Mukhopadhyay A, Petzold CJ, Martin HG (2014) A peptide-based method for 13C metabolic flux analysis in microbial communities. PLoS Comput Biol 10:e1003827.  https://doi.org/10.1371/journal.pcbi.1003827 Google Scholar
  42. 42.
    Gieseke A, Bjerrum L, Wagner M, Amann R (2003) Structure and activity of multiple nitrifying bacterial populations co-existing in a biofilm. Environ Microbiol 5:355–369.  https://doi.org/10.1046/j.1462-2920.2003.00423.x Google Scholar
  43. 43.
    Gomaa AA, Klumpe HE, Luo ML, Selle K, Barrangou R, Beisel CL (2014) Programmable removal of bacterial strains by use of genome-targeting CRISPR-Cas systems. Mbio 5:e00913–e00928.  https://doi.org/10.1128/mBio.00928-13 Google Scholar
  44. 44.
    Gouveia L, Oliveira AC (2009) Microalgae as a raw material for biofuels production. J Ind Microbiol Biot 36:269–274.  https://doi.org/10.1007/s10295-008-0495-6 Google Scholar
  45. 45.
    Gujer W, Zehnder AJB (1983) Conversion processes in anaerobic-digestion. Water Sci Technol 15:127–167.  https://doi.org/10.2166/wst.1983.0164 Google Scholar
  46. 46.
    Gupta RM, Musunuru K (2014) Expanding the genetic editing tool kit: ZFNs, TALENs, and CRISPR-Cas9. J Clin Invest 124:4154–4161.  https://doi.org/10.1172/Jci72992 Google Scholar
  47. 47.
    Haagensen JA, Hansen SK, Christensen BB, Pamp SJ, Molin S (2015) Development of spatial distribution patterns by biofilm cells. Appl Environ Microbiol 81:6120–6128.  https://doi.org/10.1128/AEM.01614-15 Google Scholar
  48. 48.
    Hanemaaijer M, Roling WF, Olivier BG, Khandelwal RA, Teusink B, Bruggeman FJ (2015) Systems modeling approaches for microbial community studies: from metagenomics to inference of the community structure. Front Microbiol 6:213.  https://doi.org/10.3389/fmicb.2015.00213 Google Scholar
  49. 49.
    Hanson RS, Hanson TE (1996) Methanotrophic bacteria. Microbiol Rev 60:439–471Google Scholar
  50. 50.
    Haroon MF, Hu SH, Shi Y, Imelfort M, Keller J, Hugenholtz P, Yuan ZG, Tyson GW (2013) Anaerobic oxidation of methane coupled to nitrate reduction in a novel archaeal lineage. Nature 500:567–570.  https://doi.org/10.1038/nature12375 Google Scholar
  51. 51.
    Hatzenpichler R, Connon SA, Goudeau D, Malmstrom RR, Woyke T, Orphan VJ (2016) Visualizing in situ translational activity for identifying and sorting slow-growing archaeal-bacterial consortia. Proc Natl Acad Sci USA.  https://doi.org/10.1073/pnas.1603757113 Google Scholar
  52. 52.
    Hays SG, Patrick WG, Ziesack M, Oxman N, Silver PA (2015) Better together: engineering and application of microbial symbioses. Curr Opin Biotechnol 36:40–49.  https://doi.org/10.1016/j.copbio.2015.08.008 Google Scholar
  53. 53.
    Hill DT, Bolte JP (1989) Digester stress as related to iso-butyric and iso-valeric acids. Biol Waste 28:33–37.  https://doi.org/10.1016/0269-7483(89)90047-5 Google Scholar
  54. 54.
    Hu SH, Zeng RJ, Haroon MF, Keller J, Lant PA, Tyson GW, Yuan ZG (2015) A laboratory investigation of interactions between denitrifying anaerobic methane oxidation (DAMO) and anammox processes in anoxic environments. Sci Rep-UK.  https://doi.org/10.1038/srep08706 Google Scholar
  55. 55.
    Jacques RJS, Okeke BC, Bento FM, Teixeira AS, Peralba MCR, Camargo FAO (2008) Microbial consortium bioaugmentation of a polycyclic aromatic hydrocarbons contaminated soil. Bioresour Technol 99:2637–2643.  https://doi.org/10.1016/j.biortech.2007.04.047 Google Scholar
  56. 56.
    Jagmann N, Philipp B (2014) Reprint of Design of synthetic microbial communities for biotechnological production processes. J Biotechnol 192:293–301.  https://doi.org/10.1016/j.jbiotec.2014.11.005 Google Scholar
  57. 57.
    Jehmlich N, Schmidt F, von Bergen M, Richnow HH, Vogt C (2008) Protein-based stable isotope probing (Protein-SIP) reveals active species within anoxic mixed cultures. ISME J 2:1122–1133.  https://doi.org/10.1038/ismej.2008.64 Google Scholar
  58. 58.
    Jia X, Liu C, Song H, Ding M, Du J, Ma Q, Yuan Y (2016) Design, analysis and application of synthetic microbial consortia. Synth Syst Biotechnol 1:109–117.  https://doi.org/10.1016/j.synbio.2016.02.001 Google Scholar
  59. 59.
    Jiang W, Bikard D, Cox D, Zhang F, Marraffini LA (2013) RNA-guided editing of bacterial genomes using CRISPR-Cas systems. Nat Biotechnol 31:233–239.  https://doi.org/10.1038/nbt.2508 Google Scholar
  60. 60.
    Johns NI, Blazejewski T, Gomes ALC, Wang HH (2016) Principles for designing synthetic microbial communities. Curr Opin Microbiol 31:146–153.  https://doi.org/10.1016/j.mib.2016.03.010 Google Scholar
  61. 61.
    Jones JA, Vernacchio VR, Collins SM, Shirke AN, Xiu Y, Englaender JA, Cress BF, McCutcheon CC, Linhardt RJ, Gross RA, Koffas MAG (2017) Complete biosynthesis of anthocyanins using E. coli polycultures. Mbio.  https://doi.org/10.1128/mbio.00621-17 Google Scholar
  62. 62.
    Jones JA, Vernacchio VR, Sinkoe AL, Collins SM, Ibrahim MHA, Lachance DM, Hahn J, Koffas MAG (2016) Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids. Metab Eng 35:55–63.  https://doi.org/10.1016/j.ymben.2016.01.006 Google Scholar
  63. 63.
    Kato S, Haruta S, Cui ZJ, Ishii M, Igarashi Y (2008) Network relationships of bacteria in a stable mixed culture. Microb Ecol 56:403–411.  https://doi.org/10.1007/s00248-007-9357-4 Google Scholar
  64. 64.
    Kawaguchi H, Hasunuma T, Ogino C, Kondo A (2016) Bioprocessing of bio-based chemicals produced from lignocellulosic feedstocks. Curr Opin Biotechnol 42:30–39.  https://doi.org/10.1016/j.copbio.2016.02.031 Google Scholar
  65. 65.
    Ke XB, Angel R, Lu YH, Conrad R (2013) Niche differentiation of ammonia oxidizers and nitrite oxidizers in rice paddy soil. Environ Microbiol 15:2275–2292.  https://doi.org/10.1111/1462-2920.12098 Google Scholar
  66. 66.
    Klitgord N, Segre D (2011) Ecosystems biology of microbial metabolism. Curr Opin Biotechnol 22:541–546.  https://doi.org/10.1016/j.copbio.2011.04.018 Google Scholar
  67. 67.
    Knittel K, Boetius A (2009) Anaerobic oxidation of methane: progress with an unknown process. Annu Rev Microbiol 63:311–334.  https://doi.org/10.1146/annurev.micro.61.080706.093130 Google Scholar
  68. 68.
    Kong W, Meldgin DR, Collins JJ, Lu T (2018) Designing microbial consortia with defined social interactions. Nat Chem Biol 14:821–829.  https://doi.org/10.1038/s41589-018-0091-7 Google Scholar
  69. 69.
    Kong XX, Jiang JL, Qiao B, Liu H, Cheng JS, Yuan YJ (2019) The biodegradation of cefuroxime, cefotaxime and cefpirome by the synthetic consortium with probiotic Bacillus clausii and investigation of their potential biodegradation pathways. Sci Total Environ 651:271–280.  https://doi.org/10.1016/j.scitotenv.2018.09.187 Google Scholar
  70. 70.
    Kuenen JG (2008) Anammox bacteria: from discovery to application. Nat Rev Microbiol 6:320–326.  https://doi.org/10.1038/nrmicro1857 Google Scholar
  71. 71.
    Kylilis N, Tuza ZA, Stan GB, Polizzi KM (2018) Tools for engineering coordinated system behaviour in synthetic microbial consortia. Nat Commun 9:2677.  https://doi.org/10.1038/s41467-018-05046-2 Google Scholar
  72. 72.
    LaPara TM, Zakharova T, Nakatsu CH, Konopka A (2002) Functional and structural adaptations of bacterial communities growing on particulate substrates under stringent nutrient limitation. Microb Ecol 44:317–326.  https://doi.org/10.1007/s00248-002-1046-8 Google Scholar
  73. 73.
    Lee J, Saddler JN, Um Y, Woo HM (2016) Adaptive evolution and metabolic engineering of a cellobiose- and xylose- negative Corynebacterium glutamicum that co-utilizes cellobiose and xylose. Microb Cell Fact 15:20.  https://doi.org/10.1186/s12934-016-0420-z Google Scholar
  74. 74.
    Lee PK, Men Y, Wang S, He J, Alvarez-Cohen L (2015) Development of a fluorescence-activated cell sorting method coupled with whole genome amplification to analyze minority and trace Dehalococcoides genomes in microbial communities. Environ Sci Technol 49:1585–1593.  https://doi.org/10.1021/es503888y Google Scholar
  75. 75.
    Lian J, Bao Z, Hu S, Zhao H (2018) Engineered CRISPR/Cas9 system for multiplex genome engineering of polyploid industrial yeast strains. Biotechnol Bioeng.  https://doi.org/10.1002/bit.26569 Google Scholar
  76. 76.
    Liang J, Bai Y, Men Y, Qu J (2017) Microbe-microbe interactions trigger Mn(II)-oxidizing gene expression. ISME J 11:67–77.  https://doi.org/10.1038/ismej.2016.106 Google Scholar
  77. 77.
    Lozanovski A, Lindner JP, Bos U (2014) Environmental evaluation and comparison of selected industrial scale biomethane production facilities across Europe. Int J Life Cycle Ass 19:1823–1832.  https://doi.org/10.1007/s11367-014-0791-5 Google Scholar
  78. 78.
    Luesken FA, Sanchez J, van Alen TA, Sanabria J, Op den Camp HJM, Jetten MSM, Kartal B (2011) Simultaneous nitrite-dependent anaerobic methane and ammonium oxidation processes. Appl Environ Microbiol 77:6802–6807.  https://doi.org/10.1128/Aem.05539-11 Google Scholar
  79. 79.
    Ma Q, Zhou J, Zhang W, Meng X, Sun J, Yuan YJ (2011) Integrated proteomic and metabolomic analysis of an artificial microbial community for two-step production of vitamin C. PLoS One 6:e26108.  https://doi.org/10.1371/journal.pone.0026108 Google Scholar
  80. 80.
    Maixner F, Noguera DR, Anneser B, Stoecker K, Wegl G, Wagner M, Daims H (2006) Nitrite concentration influences the population structure of Nitrospira-like bacteria. Environ Microbiol 8:1487–1495.  https://doi.org/10.1111/j.1462-2920.2006.01033.x Google Scholar
  81. 81.
    Mao X, Oremland RS, Liu T, Gushgari S, Landers AA, Baesman SM, Alvarez-Cohen L (2017) Acetylene fuels TCE reductive dechlorination by defined Dehalococcoides/Pelobacter consortia. Environ Sci Technol 51:2366–2372.  https://doi.org/10.1021/acs.est.6b05770 Google Scholar
  82. 82.
    Mao XW, Stenuit B, Polasko A, Alvarez-Cohen L (2015) Efficient metabolic exchange and electron transfer within a syntrophic trichloroethene-degrading coculture of Dehalococcoides mccartyi 195 and Syntrophomonas wolfei. Appl Environ Microbiol 81:2015–2024.  https://doi.org/10.1128/Aem.03464-14 Google Scholar
  83. 83.
    McGlynn SE, Chadwick GL, Kempes CP, Orphan VJ (2015) Single cell activity reveals direct electron transfer in methanotrophic consortia. Nature 526:531-U146.  https://doi.org/10.1038/nature15512 Google Scholar
  84. 84.
    McInerney MJ, Sieber JR, Gunsalus RP (2009) Syntrophy in anaerobic global carbon cycles. Curr Opin Biotechnol 20:623–632.  https://doi.org/10.1016/j.copbio.2009.10.001 Google Scholar
  85. 85.
    Men Y, Feil H, Verberkmoes NC, Shah MB, Johnson DR, Lee PK, West KA, Zinder SH, Andersen GL, Alvarez-Cohen L (2012) Sustainable syntrophic growth of Dehalococcoides ethenogenes strain 195 with Desulfovibrio vulgaris Hildenborough and Methanobacterium congolense: global transcriptomic and proteomic analyses. ISME J 6:410–421.  https://doi.org/10.1038/ismej.2011.111 Google Scholar
  86. 86.
    Men Y, Seth EC, Yi S, Allen RH, Taga ME, Alvarez-Cohen L (2014) Sustainable growth of Dehalococcoides mccartyi 195 by corrinoid salvaging and remodeling in defined lactate-fermenting consortia. Appl Environ Microbiol 80:2133–2141.  https://doi.org/10.1128/AEM.03477-13 Google Scholar
  87. 87.
    Men Y, Yu K, Baelum J, Gao Y, Tremblay J, Prestat E, Stenuit B, Tringe SG, Jansson J, Zhang T, Alvarez-Cohen L (2017) Metagenomic and metatranscriptomic analyses reveal structure and dynamics of a dechlorinating community containing Dehalococcoides mccartyi and corrinoid-providing microorganisms under cobalamin-limited condition. Appl Environ Microbiol.  https://doi.org/10.1128/aem.03508-16 Google Scholar
  88. 88.
    Meyer B, Kuehl JV, Price MN, Ray J, Deutschbauer AM, Arkin AP, Stahl DA (2014) The energy-conserving electron transfer system used by Desulfovibrio alaskensis strain G20 during pyruvate fermentation involves reduction of endogenously formed fumarate and cytoplasmic and membrane-bound complexes, Hdr-Flox and Rnf. Environ Microbiol 16:3463–3486.  https://doi.org/10.1111/1462-2920.12405 Google Scholar
  89. 89.
    Miller JC, Tan S, Qiao G, Barlow KA, Wang J, Xia DF, Meng X, Paschon DE, Leung E, Hinkley SJ, Dulay GP, Hua KL, Ankoudinova I, Cost GJ, Urnov FD, Zhang HS, Holmes MC, Zhang L, Gregory PD, Rebar EJ (2011) A TALE nuclease architecture for efficient genome editing. Nat Biotechnol 29:143–148.  https://doi.org/10.1038/nbt.1755 Google Scholar
  90. 90.
    Minty JJ, Singer ME, Scholz SA, Bae CH, Ahn JH, Foster CE, Liao JC, Lin XN (2013) Design and characterization of synthetic fungal–bacterial consortia for direct production of isobutanol from cellulosic biomass. Proc Natl Acad Sci USA 110:14592–14597.  https://doi.org/10.1073/pnas.1218447110 Google Scholar
  91. 91.
    Moore RL (1981) The biology of hyphomicrobium and other prosthecate, budding bacteria. Annu Rev Microbiol 35:567–594.  https://doi.org/10.1146/annurev.mi.35.100181.003031 Google Scholar
  92. 92.
    Morris BE, Henneberger R, Huber H, Moissl-Eichinger C (2013) Microbial syntrophy: interaction for the common good. FEMS Microbiol Rev 37:384–406.  https://doi.org/10.1111/1574-6976.12019 Google Scholar
  93. 93.
    Mukherjee M, Ray A, Post AF, McKay RM, Bullerjahn GS (2016) Identification, enumeration and diversity of nitrifying planktonic archaea and bacteria in trophic end members of the Laurentian Great Lakes. J Great Lakes Res 42:39–49.  https://doi.org/10.1016/j.jglr.2015.11.007 Google Scholar
  94. 94.
    Nagaraju S, Davies NK, Walker DJ, Kopke M, Simpson SD (2016) Genome editing of Clostridium autoethanogenum using CRISPR/Cas9. Biotechnol Biofuels 9:219.  https://doi.org/10.1186/s13068-016-0638-3 Google Scholar
  95. 95.
    Nagasaki A, Kato Y, Meguro K, Yamagishi A, Nakamura C, Uyeda TQP (2018) A genome editing vector that enables easy selection and identification of knockout cells. Plasmid 98:37–44.  https://doi.org/10.1016/j.plasmid.2018.08.005 Google Scholar
  96. 96.
    Nemudryi AA, Valetdinova KR, Medvedev SP, Zakian SM (2014) TALEN and CRISPR/Cas genome editing systems: tools of discovery. Acta Nat 6:19–40Google Scholar
  97. 97.
    Olson DG, McBride JE, Shaw AJ, Lynd LR (2012) Recent progress in consolidated bioprocessing. Curr Opin Biotechnol 23:396–405.  https://doi.org/10.1016/j.copbio.2011.11.026 Google Scholar
  98. 98.
    Parkin GF, Lynch NA, Kuo WC, Vankeuren EL, Bhattacharya SK (1990) Interaction between sulfate reducers and methanogens fed acetate and propionate. Res J Water Pollut Control Fed 62:780–788Google Scholar
  99. 99.
    Pawar S (2014) Caldicellulosiruptor saccharolyticus: an ideal hydrogen producer?. Lund University, LundGoogle Scholar
  100. 100.
    Peng YZ, Zhu GB (2006) Biological nitrogen removal with nitrification and denitrification via nitrite pathway. Appl Microbiol Biotechnol 73:15–26.  https://doi.org/10.1007/s00253-006-0534-z Google Scholar
  101. 101.
    Perez-Garcia O, Lear G, Singhal N (2016) Metabolic metwork modeling of microbial interactions in natural and engineered environmental systems. Front Microbiol 7:673.  https://doi.org/10.3389/fmicb.2016.00673 Google Scholar
  102. 102.
    Port F, Chen HM, Lee T, Bullock SL (2014) Optimized CRISPR/Cas tools for efficient germline and somatic genome engineering in Drosophila. Proc Natl Acad Sci USA 111:E2967–E2976.  https://doi.org/10.1073/pnas.1405500111 Google Scholar
  103. 103.
    Raes J, Bork P (2008) Molecular eco-systems biology: towards an understanding of community function. Nat Rev Microbiol 6:693–699.  https://doi.org/10.1038/nrmicro1935 Google Scholar
  104. 104.
    Rawle RA, Hamerly T, Tripet BP, Giannone RJ, Wurch L, Hettich RL, Podar M, Copie V, Bothner B (2017) Multi-omics analysis provides insight to the Ignicoccus hospitalis-Nanoarchaeum equitans association. Biochim Biophys Acta Gen Subj 1861:2218–2227.  https://doi.org/10.1016/j.bbagen.2017.06.001 Google Scholar
  105. 105.
    Reis MAM, Almeida JS, Lemos PC, Carrondo MJT (1992) Effect of hydrogen-sulfide on growth of sulfate reducing bacteria. Biotechnol Bioeng 40:593–600.  https://doi.org/10.1002/bit.260400506 Google Scholar
  106. 106.
    Rochfort S (2005) Metabolomics reviewed: a new “Omics” platform technology for systems biology and implications for natural products research. J Nat Prod 68:1813–1820.  https://doi.org/10.1021/np050255w Google Scholar
  107. 107.
    Roe AJ, O’Byrne C, McLaggan D, Booth IR (2002) Inhibition of Escherichia coli growth by acetic acid: a problem with methionine biosynthesis and homocysteine toxicity. Microbiology 148:2215–2222.  https://doi.org/10.1099/00221287-148-7-2215 Google Scholar
  108. 108.
    Russell JB, DiezGonzalez F (1998) The effects of fermentation acids on bacterial growth. Adv Microb Physiol 39:205–234.  https://doi.org/10.1016/S0065-2911(08)60017-X Google Scholar
  109. 109.
    Sabra W, Dietz D, Tjahjasari D, Zeng AP (2010) Biosystems analysis and engineering of microbial consortia for industrial biotechnology. Eng Life Sci 10:407–421.  https://doi.org/10.1002/elsc.201000111 Google Scholar
  110. 110.
    Scheller S, Yu H, Chadwick GL, McGlynn SE, Orphan VJ (2016) Artificial electron acceptors decouple archaeal methane oxidation from sulfate reduction. Science 351:703–707.  https://doi.org/10.1126/science.aad7154 Google Scholar
  111. 111.
    Schink B (2002) Synergistic interactions in the microbial world. Antonie Van Leeuwenhoek 81:257–261.  https://doi.org/10.1023/A:1020579004534 Google Scholar
  112. 112.
    Schink B, Stams AJM (2006) Syntrophism among prokaryotes. Prokaryotes 2(3):309–335.  https://doi.org/10.1007/0-387-30742-7_11 Google Scholar
  113. 113.
    Schwartz C, Cheng J-F, Evans R, Schwartz CA, Wagner JM, Anglin S, Beitz A, Pan W, Lonardi S, Blenner M, Alper HS, Yoshikuni Y, Wheeldon I (2018) Validating genome-wide CRISPR-Cas9 function in the non-conventional yeast Yarrowia lipolytica. BioRxiv.  https://doi.org/10.1101/358630 Google Scholar
  114. 114.
    Scott SR, Hasty J (2016) Quorum sensing communication modules for microbial consortia. Acs Synth Biol 5:969–977.  https://doi.org/10.1021/acssynbio.5b00286 Google Scholar
  115. 115.
    Shahab RL, Luterbacher JS, Brethauer S, Studer MH (2018) Consolidated bioprocessing of lignocellulosic biomass to lactic acid by a synthetic fungal–bacterial consortium. Biotechnol Bioeng 115:1207–1215.  https://doi.org/10.1002/bit.26541 Google Scholar
  116. 116.
    Shong J, Collins CH (2013) Engineering the esaR promoter for tunable quorum sensing- dependent gene expression. Acs Synth Biol 2:568–575.  https://doi.org/10.1021/sb4000433 Google Scholar
  117. 117.
    Shong J, Diaz MRJ, Collins CH (2012) Towards synthetic microbial consortia for bioprocessing. Curr Opin Biotechnol 23:798–802.  https://doi.org/10.1016/j.copbio.2012.02.001 Google Scholar
  118. 118.
    Shong J, Huang YM, Bystroff C, Collins CH (2013) Directed evolution of the quorum-sensing regulator EsaR for increased signal sensitivity. ACS Chem Biol 8:789–795.  https://doi.org/10.1021/cb3006402 Google Scholar
  119. 119.
    Sieber JR, McInerney MJ, Gunsalus RP (2012) Genomic insights into syntrophy: the paradigm for anaerobic metabolic cooperation. Annu Rev Microbiol 66:429–452.  https://doi.org/10.1146/annurev-micro-090110-102844 Google Scholar
  120. 120.
    Skennerton CT, Chourey K, Iyer R, Hettich RL, Tyson GW, Orphan VJ (2017) Methane-fueled syntrophy through extracellular electron transfer: uncovering the genomic traits conserved within diverse bacterial partners of anaerobic methanotrophic archaea. Mbio.  https://doi.org/10.1128/mbio.01561-17 Google Scholar
  121. 121.
    Stahl DA, de la Torre JR (2012) Physiology and diversity of ammonia-oxidizing archaea. Annu Rev Microbiol 66:83–101.  https://doi.org/10.1146/annurev-micro-092611-150128 Google Scholar
  122. 122.
    Tang X, He LY, Tao XQ, Dang Z, Guo CL, Lu GN, Yi XY (2010) Construction of an artificial microalgal-bacterial consortium that efficiently degrades crude oil. J Hazard Mater 181:1158–1162.  https://doi.org/10.1016/j.jhazmat.2010.05.033 Google Scholar
  123. 123.
    Teague BP, Weiss R (2015) Synthetic communities, the sum of parts. Science 349:924–925.  https://doi.org/10.1126/science.aad0876 Google Scholar
  124. 124.
    Urnov FD, Rebar EJ, Holmes MC, Zhang HS, Gregory PD (2010) Genome editing with engineered zinc finger nucleases. Nat Rev Genet 11:636–646.  https://doi.org/10.1038/nrg2842 Google Scholar
  125. 125.
    Valdez-Vazquez I, Perez-Rangel M, Tapia A, Buitron G, Molina C, Hernandez G, Amaya-Delgado L (2015) Hydrogen and butanol production from native wheat straw by synthetic microbial consortia integrated by species of Enterococcus and Clostridium. Fuel 159:214–222.  https://doi.org/10.1016/j.fuel.2015.06.052 Google Scholar
  126. 126.
    Vandenberg L, Lentz CP (1971) Anaerobic digestion of pear waste - laboratory equipment design and preliminary results. Can Inst F Sci Tec J 4:159–165.  https://doi.org/10.1016/S0008-3860(71)74222-6 Google Scholar
  127. 127.
    VerBerkmoes NC, Denef VJ, Hettich RL, Banfield JF (2009) Functional analysis of natural microbial consortia using community proteomics. Nat Rev Microbiol 7:196–205.  https://doi.org/10.1038/nrmicro2080 Google Scholar
  128. 128.
    Waite AJ, Shou W (2012) Adaptation to a new environment allows cooperators to purge cheaters stochastically. Proc Natl Acad Sci USA 109:19079–19086.  https://doi.org/10.1073/pnas.1210190109 Google Scholar
  129. 129.
    Wang EX, Ding MZ, Ma Q, Dong XT, Yuan YJ (2016) Reorganization of a synthetic microbial consortium for one-step vitamin C fermentation. Microb Cell Fact 15:21.  https://doi.org/10.1186/s12934-016-0418-6 Google Scholar
  130. 130.
    Wang M, Keeley R, Zalivina N, Halfhide T, Scott K, Zhang Q, van der Steen P, Ergas SJ (2018) Advances in algal-prokaryotic wastewater treatment: a review of nitrogen transformations, reactor configurations and molecular tools. J Environ Manag 217:845–857.  https://doi.org/10.1016/j.jenvman.2018.04.021 Google Scholar
  131. 131.
    Weber W, Baba M, Fussenegger M (2007) Synthetic ecosystems based on airborne inter- and intrakingdom communication. Proc Natl Acad Sci USA 104:10435–10440.  https://doi.org/10.1073/pnas.0701382104 Google Scholar
  132. 132.
    Wen ZQ, Minton NP, Zhang Y, Li Q, Liu JL, Jiang Y, Yang S (2017) Enhanced solvent production by metabolic engineering of a twin-clostridial consortium. Metab Eng 39:38–48.  https://doi.org/10.1016/j.ymben.2016.10.013 Google Scholar
  133. 133.
    West SA, Griffin AS, Gardner A, Diggle SP (2006) Social evolution theory for microorganisms. Nat Rev Microbiol 4:597–607.  https://doi.org/10.1038/nrmicro1461 Google Scholar
  134. 134.
    Woyke T, Teeling H, Ivanova NN, Huntemann M, Richter M, Gloeckner FO, Boffelli D, Anderson IJ, Barry KW, Shapiro HJ, Szeto E, Kyrpides NC, Mussmann M, Amann R, Bergin C, Ruehland C, Rubin EM, Dubilier N (2006) Symbiosis insights through metagenomic analysis of a microbial consortium. Nature 443:950–955.  https://doi.org/10.1038/nature05192 Google Scholar
  135. 135.
    Wu G, Yan Q, Jones JA, Tang YJ, Fong SS, Koffas MAG (2016) Metabolic burden: cornerstones in synthetic biology and metabolic engineering applications. Trends Biotechnol 34:652–664.  https://doi.org/10.1016/j.tibtech.2016.02.010 Google Scholar
  136. 136.
    Wyman CE (2007) What is (and is not) vital to advancing cellulosic ethanol. Trends Biotechnol 25:153–157.  https://doi.org/10.1016/j.tibtech.2007.02.009 Google Scholar
  137. 137.
    Xia WW, Zhang CX, Zeng XW, Feng YZ, Weng JH, Lin XG, Zhu JG, Xiong ZQ, Xu J, Cai ZC, Jia ZJ (2011) Autotrophic growth of nitrifying community in an agricultural soil. ISME J 5:1226–1236.  https://doi.org/10.1038/ismej.2011.5 Google Scholar
  138. 138.
    Xie GJ, Cai C, Hu SH, Yuan ZG (2017) Complete nirogen removal from synthetic anaerobic sludge digestion liquor through integrating anammox and denitrifying anaerobic methane oxidation in a membrane biofilm reactor. Environ Sci Technol 51:819–827.  https://doi.org/10.1021/acs.est.6b04500 Google Scholar
  139. 139.
    Xu T, Li Y, Van Nostrand JD, He Z, Zhou J (2014) Cas9-based tools for targeted genome editing and transcriptional control. Appl Environ Microbiol 80:1544–1552.  https://doi.org/10.1128/AEM.03786-13 Google Scholar
  140. 140.
    Xu T, Li YC, Shi Z, Hemme CL, Li Y, Zhu YH, Van Nostrand JD, He ZL, Zhou JZ (2015) Efficient genome editing in Clostridium cellulolyticum via CRISPR-Cas9 nickase. Appl Environ Microbiol 81:4423–4431.  https://doi.org/10.1128/Aem.00873-15 Google Scholar
  141. 141.
    Yan J, Ritalahti KM, Wagner DD, Loffler FE (2012) Unexpected specificity of interspecies cobamide transfer from Geobacter spp. to organohalide-respiring Dehalococcoides mccartyi strains. Appl Environ Microbiol 78:6630–6636.  https://doi.org/10.1128/AEM.01535-12 Google Scholar
  142. 142.
    Youk H, Lim WA (2014) Secreting and sensing the same molecule allows cells to achieve versatile social behaviors. Science 343:1242782.  https://doi.org/10.1126/science.1242782 Google Scholar
  143. 143.
    Yu K, Yi S, Li B, Guo F, Peng XX, Wang ZP, Wu Y, Alvarez-Cohen L, Zhang T (2019) An integrated meta-omics approach reveals substrates involved in synergistic interactions in a bisphenol A (BPA)-degrading microbial community. Microbiome.  https://doi.org/10.1186/s40168-019-0634-5 Google Scholar
  144. 144.
    Zampieri M, Sekar K, Zamboni N, Sauer U (2017) Frontiers of high-throughput metabolomics. Curr Opin Chem Biol 36:15–23.  https://doi.org/10.1016/j.cbpa.2016.12.006 Google Scholar
  145. 145.
    Zhou K, Qiao KJ, Edgar S, Stephanopoulos G (2015) Distributing a metabolic pathway among a microbial consortium enhances production of natural products. Nat Biotechnol 33:377-U157.  https://doi.org/10.1038/nbt.3095 Google Scholar
  146. 146.
    Zhou YZ, Pope PB, Li SC, Wen B, Tan FJ, Cheng S, Chen J, Yang JL, Liu F, Lei XJ, Su QQ, Zhou C, Zhao J, Dong XZ, Jin T, Zhou X, Yang S, Zhang GY, Yang HM, Wang J, Yang RF, Eijsink VGH, Wang J (2014) Omics-based interpretation of synergism in a soil-derived cellulose-degrading microbial community. Sci Rep UK.  https://doi.org/10.1038/srep05288 Google Scholar
  147. 147.
    Zuroff TR, Curtis WR (2012) Developing symbiotic consortia for lignocellulosic biofuel production. Appl Microbiol Biotechnol 93:1423–1435.  https://doi.org/10.1007/s00253-011-3762-9 Google Scholar

Copyright information

© Society for Industrial Microbiology and Biotechnology 2019

Authors and Affiliations

  1. 1.Department of Civil and Environmental EngineeringUniversity of Illinois Urbana-ChampaignUrbanaUSA
  2. 2.Institute for Genomic BiologyUniversity of Illinois Urbana-ChampaignUrbanaUSA

Personalised recommendations