An Adaptive Laboratory Evolution Method to Accelerate Autotrophic Metabolism

  • Tian ZhangEmail author
  • Pier-Luc Tremblay
Part of the Methods in Molecular Biology book series (MIMB, volume 1671)


Adaptive laboratory evolution (ALE) is an approach enabling the development of novel characteristics in microbial strains via the application of a constant selection pressure. This method is also an efficient tool to acquire insights on molecular mechanisms responsible for specific phenotypes. ALE experiments have mainly been conducted with heterotrophic microbes to study, for instance, cell metabolism with different multicarbon substrates, tolerance to solvents, pH variation, and high temperature. Here, we describe employing an ALE method to generate Sporomusa ovata strains growing faster autotrophically and reducing CO2 into acetate more efficiently. Strains developed via this ALE method were also used to gain knowledge on the autotrophic metabolism of S. ovata as well as other acetogenic bacteria.

Key words

Adaptive laboratory evolution Autotroph Acetogen CO2 fixation Sporomusa ovata Methanol Microbial electrosynthesis 


  1. 1.
    Elena SF, Lenski RE (2003) Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation. Nat Rev Genet 4:457–469. doi: 10.1038/nrg1088 CrossRefPubMedGoogle Scholar
  2. 2.
    Dragosits M, Mattanovich D (2013) Adaptive laboratory evolution – principles and applications for biotechnology. Microb Cell Factories 12:64. doi: 10.1186/1475-2859-12-64 CrossRefGoogle Scholar
  3. 3.
    Patzschke A, Steiger MG, Holz C et al (2015) Enhanced glutathione production by evolutionary engineering of Saccharomyces cerevisiae strains. Biotechnol J 10:1719–1726. doi: 10.1002/biot.201400809 CrossRefPubMedGoogle Scholar
  4. 4.
    Zambanini T, Sarikaya E, Kleineberg W et al (2016) Efficient malic acid production from glycerol with Ustilago trichophora TZ1. Biotechnol Biofuels 9:67. doi: 10.1186/s13068-016-0483-4 CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Hu B, Yang Y-M, Beck DAC et al (2016) Comprehensive molecular characterization of Methylobacterium extorquens AM1 adapted for 1-butanol tolerance. Biotechnol Biofuels 9:84. doi: 10.1186/s13068-016-0497-y CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Horinouchi T, Tamaoka K, Furusawa C et al (2010) Transcriptome analysis of parallel-evolved Escherichia coli strains under ethanol stress. BMC Genomics 11:579. doi: 10.1186/1471-2164-11-579 CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Atsumi S, Wu T-Y, Machado IMP et al (2010) Evolution, genomic analysis, and reconstruction of isobutanol tolerance in Escherichia coli. Mol Syst Biol 6:449. doi: 10.1038/msb.2010.98 CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Reyes LH, Almario MP, Winkler J et al (2012) Visualizing evolution in real time to determine the molecular mechanisms of n-butanol tolerance in Escherichia coli. Metab Eng 14:579–590. doi: 10.1016/j.ymben.2012.05.002 CrossRefPubMedGoogle Scholar
  9. 9.
    Oide S, Gunji W, Moteki Y et al (2015) Adaptive laboratory evolution conferred cross-tolerance to thermal and solvent stress to Corynebacterium glutamicum. Appl Environ Microbiol. doi: 10.1128/AEM.03973-14
  10. 10.
    Tremblay P-L, Summers ZM, Glaven RH et al (2011) A c-type cytochrome and a transcriptional regulator responsible for enhanced extracellular electron transfer in Geobacter sulfurreducens revealed by adaptive evolution. Environ Microbiol 13:13–23. doi: 10.1111/j.1462-2920.2010.02302.x CrossRefPubMedGoogle Scholar
  11. 11.
    Tremblay P-L, Höglund D, Koza A et al (2015) Adaptation of the autotrophic acetogen Sporomusa ovata to methanol accelerates the conversion of CO2 to organic products. Sci Rep 5:16168. doi: 10.1038/srep16168 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    LaCroix RA, Sandberg TE, O’Brien EJ et al (2015) Use of adaptive laboratory evolution to discover key mutations enabling rapid growth of Escherichia coli K-12 MG1655 on glucose minimal medium. Appl Environ Microbiol 81:17–30. doi: 10.1128/AEM.02246-14 CrossRefPubMedGoogle Scholar
  13. 13.
    Möller B, Oßmer R, Howard BH et al (1984) Sporomusa, a new genus of gram-negative anaerobic bacteria including Sporomusa sphaeroides spec. nov. and Sporomusa ovata spec. nov. Arch Microbiol 139:388–396. doi: 10.1007/BF00408385 CrossRefGoogle Scholar
  14. 14.
    Poehlein A, Gottschalk G, Daniel R (2013) First insights into the genome of the Gram-negative, endospore-forming organism Sporomusa ovata strain H1 DSM 2662. Genome Announc 1:e00734–e00713. doi: 10.1128/genomeA.00734-13 PubMedPubMedCentralGoogle Scholar
  15. 15.
    Drake HL, Gößner AS, Daniel SL (2008) Old acetogens, new light. Ann N Y Acad Sci 1125:100–128. doi: 10.1196/annals.1419.016 CrossRefPubMedGoogle Scholar
  16. 16.
    Nevin KP, Woodard TL, Franks AE et al (2010) Microbial electrosynthesis: feeding microbes electricity to convert carbon dioxide and water to multicarbon extracellular organic compounds. mBio 1:e00103–e00110. doi: 10.1128/mBio.00103-10 CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Tremblay P-L, Zhang T (2015) Electrifying microbes for the production of chemicals. Front Microbiol 6:201. doi: 10.3389/fmicb.2015.00201 PubMedPubMedCentralGoogle Scholar
  18. 18.
    Chen L, Tremblay P-L, Mohanty S et al (2016) Electrosynthesis of acetate from CO2 by a highly structured biofilm assembled with reduced graphene oxide–tetraethylene pentamine. J Mater Chem A 4:8395–8401. doi: 10.1039/C6TA02036D CrossRefGoogle Scholar
  19. 19.
    Aryal N, Halder A, Tremblay P-L et al (2016) Enhanced microbial electrosynthesis with three-dimensional graphene functionalized cathodes fabricated via solvothermal synthesis. Electrochim Acta 217:117–122. doi: 10.1016/j.electacta.2016.09.063 CrossRefGoogle Scholar
  20. 20.
    Schrader J, Schilling M, Holtmann D et al (2009) Methanol-based industrial biotechnology: current status and future perspectives of methylotrophic bacteria. Trends Biotechnol 27:107–115. doi: 10.1016/j.tibtech.2008.10.009 CrossRefPubMedGoogle Scholar
  21. 21.
    Patterson JA, Ricke SC (2015) Effect of ethanol and methanol on growth of ruminal bacteria Selenomonas ruminantium and Butyrivibrio fibrisolvens. J Environ Sci Health B 50:62–67. doi: 10.1080/03601234.2015.965639 CrossRefPubMedGoogle Scholar
  22. 22.
    Nicolaou SA, Gaida SM, Papoutsakis ET (2010) A comparative view of metabolite and substrate stress and tolerance in microbial bioprocessing: from biofuels and chemicals, to biocatalysis and bioremediation. Metab Eng 12:307–331. doi: 10.1016/j.ymben.2010.03.004 CrossRefPubMedGoogle Scholar
  23. 23.
    McClure R, Balasubramanian D, Sun Y et al (2013) Computational analysis of bacterial RNA-Seq data. Nucleic Acids Res 41:e140. doi: 10.1093/nar/gkt444 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2018

Authors and Affiliations

  1. 1.School of Chemistry, Chemical Engineering and Life ScienceWuhan University of TechnologyWuhanPeople’s Republic of China
  2. 2.The Novo Nordisk Foundation Center for BiosustainablityTechnical University of DenmarkHørsholmDenmark

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