Applied Microbiology and Biotechnology

, Volume 102, Issue 11, pp 4615–4627 | Cite as

Evolutionary engineering of industrial microorganisms-strategies and applications

  • Zhengming Zhu
  • Juan ZhangEmail author
  • Xiaomei Ji
  • Zhen Fang
  • Zhimeng WuEmail author
  • Jian Chen
  • Guocheng Du


Microbial cells have been widely used in the industry to obtain various biochemical products, and evolutionary engineering is a common method in biological research to improve their traits, such as high environmental tolerance and improvement of product yield. To obtain better integrate functions of microbial cells, evolutionary engineering combined with other biotechnologies have attracted more attention in recent years. Classical laboratory evolution has been proven effective to letting more beneficial mutations occur in different genes but also has some inherent limitations such as a long evolutionary period and uncontrolled mutation frequencies. However, recent studies showed that some new strategies may gradually overcome these limitations. In this review, we summarize the evolutionary strategies commonly used in industrial microorganisms and discuss the combination of evolutionary engineering with other biotechnologies such as systems biology and inverse metabolic engineering. Finally, we prospect the importance and application prospect of evolutionary engineering as a powerful tool especially in optimization of industrial microbial cell factories.


Evolutionary engineering Industrial microorganisms Evolutionary strategies Systems biology Inverse metabolic engineering 



This work was supported by the National Natural Science Foundation of China (31470160), the project of Integration of Industry, Education and Research of Jiangsu Province, China (BY2016022-39), the grant from Pioneer Innovative Research Team of Dezhou, Program for Changjiang Scholars and Innovative Research Team in University (No. IRT_15R26), the Program of Introducing Talents of Discipline to Universities (No. 111-2-06), and the Open Project of Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University(KLIB-KF201706).

Compliance with ethical standards

This article does not contain any studies with human participants or animals performed by any of the authors.

Conflict of interest

The authors declare that they have no competing interests.


  1. Agresti JJ, Antipov E, Abate AR, Ahn K, Rowat AC, Baret JC, Marquez M, Klibanov AM, Griffiths AD, Weitz DA (2010) Ultrahigh-throughput screening in drop-based microfluidics for directed evolution. Proc Natl Acad Sci 107(9):4004–4009. PubMedPubMedCentralCrossRefGoogle Scholar
  2. Almario MP, Reyes LH, Kao KC (2013) Evolutionary engineering of Saccharomyces cerevisiae for enhanced tolerance to hydrolysates of lignocellulosic biomass. Biotechnol Bioeng 110(10):2616–2623. PubMedCrossRefGoogle Scholar
  3. Alper H, Stephanopoulos G (2007) Global transcription machinery engineering: a new approach for improving cellular phenotype. Metab Eng 9(3):258–267. PubMedCrossRefGoogle Scholar
  4. Alper H, Moxley J, Nevoigt E, Fink GR, Stephanopoulos G (2006) Engineering yeast transcription machinery for improved ethanol tolerance and production. Science 314(5805):1565–1568. PubMedCrossRefGoogle Scholar
  5. Baek SH, Kwon EY, Bae SJ, Cho BR, Kim SY, Hahn JS (2017) Improvement of D-lactic acid production in Saccharomyces cerevisiae under acidic conditions by evolutionary and rational metabolic engineering. Biotechnol J 12(10):7. CrossRefGoogle Scholar
  6. Bailey JE, Sburlati A, Hatzimanikatis V, Lee K, Renner WA, Tsai PS (2002) Inverse metabolic engineering: a strategy for directed genetic engineering of useful phenotypes. Biotechnol Bioeng 79(5):568–579. PubMedCrossRefGoogle Scholar
  7. Basak S, Geng HF, Jiang RR (2014) Rewiring global regulator cAMP receptor protein (CRP) to improve E. coli tolerance towards low pH. J Biotechnol 173:68–75. PubMedCrossRefGoogle Scholar
  8. Biot-Pelletier D, Martin VJJ (2014) Evolutionary engineering by genome shuffling. Appl Microbiol Biotechnol 98(9):3877–3887. PubMedCrossRefGoogle Scholar
  9. Blaby IK, Lyons BJ, Wroclawska-Hughes E, Phillips GCF, Pyle TP, Chamberlin SG, Benner SA, Lyons TJ, de Crecy-Lagard V, de Crecy E (2012) Experimental evolution of a facultative thermophile from a mesophilic ancestor. Appl Environ Microbiol 78(1):144–155. PubMedPubMedCentralCrossRefGoogle Scholar
  10. Buchenauer A, Hofmann MC, Funke M, Buchs J, Mokwa W, Schnakenberg U (2009) Micro-bioreactors for fed-batch fermentations with integrated online monitoring and microfluidic devices. Biosens Bioelectron 24(5):1411–1416. PubMedCrossRefGoogle Scholar
  11. Cao X, Hou L, Lu M, Wang C, Zeng B (2010) Genome shuffling of Zygosaccharomyces rouxii to accelerate and enhance the flavour formation of soy sauce. J Sci Food Agric 90(2):281–285. PubMedCrossRefGoogle Scholar
  12. Cao XH, Song Q, Wang CL, Hou LH (2012) Genome shuffling of Hansenula anomala to improve flavour formation of soy sauce. World J Microbiol Biotechnol 28(5):1857–1862. PubMedCrossRefGoogle Scholar
  13. Chao R, Liang J, Tasan I, Si T, Ju LY, Zhao HM (2017) Fully automated one-step synthesis of single-transcript TALEN pairs using a biological foundry. ACS Synth Biol 6(4):678–685. PubMedPubMedCentralCrossRefGoogle Scholar
  14. Chen J, Shen J, Hellgren LI, Jensen PR, Solem C (2015) Adaptation of Lactococcus lactis to high growth temperature leads to a dramatic increase in acidification rate. Sci Rep 5(14):199. CrossRefGoogle Scholar
  15. Chong HQ, Huang L, Yeow JW, Wang I, Zhang HF, Song H, Jiang RR (2013) Improving ethanol tolerance of Escherichia coli by rewiring its global regulator cAMP receptor protein (CRP). PLoS One 8(2):9. CrossRefGoogle Scholar
  16. Chou HH, Keasling JD (2013) Programming adaptive control to evolve increased metabolite production. Nat Commun 4:8. CrossRefGoogle Scholar
  17. de Gérando HM, Fayolle-Guichard F, Rudant L, Millah S, Monot F, Ferreira NL, López-Contreras A (2016) Improving isopropanol tolerance and production of Clostridium beijerinckii DSM 6423 by random mutagenesis and genome shuffling. Appl Microbiol Biotechnol 100(12):5427–5436. PubMedPubMedCentralCrossRefGoogle Scholar
  18. Dhar R, Sagesser R, Weikert C, Yuan J, Wagner A (2011) Adaptation of Saccharomyces cerevisiae to saline stress through laboratory evolution. J Evol Biol 24(5):1135–1153. PubMedCrossRefGoogle Scholar
  19. Dhar R, Sägesser R, Weikert C, Wagner A (2013) Yeast adapts to a changing stressful environment by evolving cross-protection and anticipatory gene regulation. Mol Biol Evol 30(3):573–588. PubMedCrossRefGoogle Scholar
  20. Dragosits M, Mattanovich D (2013) Adaptive laboratory evolution - principles and applications for biotechnology. Microb Cell Factories 12:64. CrossRefGoogle Scholar
  21. Durot M, Bourguignon PY, Schachter V (2009) Genome-scale models of bacterial metabolism: reconstruction and applications. FEMS Microbiol Rev 33(1):164–190. PubMedCrossRefGoogle Scholar
  22. Fang MY, Jin LH, Zhang C, Tan YY, Jiang PX, Ge N, Li HP, Xing XH (2013) Rapid mutation of spirulina platensis by a new mutagenesis system of atmospheric and room temperature plasmas (ARTP) and generation of a mutant library with diverse phenotypes. PLoS One 8(10):12. CrossRefGoogle Scholar
  23. Feist AM, Herrgard MJ, Thiele I, Reed JL, Palsson BO (2009) Reconstruction of biochemical networks in microorganisms. Nat Rev Microbiol 7(2):129–143. PubMedCrossRefGoogle Scholar
  24. Fletcher E, Feizi A, Bisschops MMM, Hallstrom BM, Khoomrung S, Siewers V, Nielsen J (2017) Evolutionary engineering reveals divergent paths when yeast is adapted to different acidic environments. Metab Eng 39:19–28. PubMedCrossRefGoogle Scholar
  25. Fong SS, Joyce AR, Palsson BO (2005) Parallel adaptive evolution cultures of Escherichia coli lead to convergent growth phenotypes with different gene expression states. Genome Res 15(10):1365–1372. PubMedPubMedCentralCrossRefGoogle Scholar
  26. Fu RY, Bongers RS, van Swam II, Chen J, Molenaar D, Kleerebezem M, Hugenholtz J, Li Y (2006) Introducing glutathione biosynthetic capability into Lactococcus lactis subsp cremoris NZ9000 improves the oxidative-stress resistance of the host. Metab Eng 8(6):662–671. PubMedCrossRefGoogle Scholar
  27. Furusawa C, Horinouchi T, Hirasawa T, Shimizu H (2013) Systems metabolic engineering: the creation of microbial cell factories by rational metabolic design and evolution. Future Trends Biotechnol 13:1–23. CrossRefGoogle Scholar
  28. Gao X, Jiang L, Zhu LY, Xu Q, Xu X, Huang H (2016) Tailoring of global transcription sigma D factor by random mutagenesis to improve Escherichia coli tolerance towards low-pHs. J Biotechnol 224:55–63. PubMedCrossRefGoogle Scholar
  29. Ge XD, Hanson M, Shen H, Kostov Y, Brorson KA, Frey DD, Moreira AR, Rao G (2006) Validation of an optical sensor-based high-throughput bioreactor system for mammalian cell culture. J Biotechnol 122(3):293–306. PubMedCrossRefGoogle Scholar
  30. Gong ZW, Nielsen J, Zhou YJJ (2017) Engineering robustness of microbial cell factories. Biotechnol J 12(10):9. CrossRefGoogle Scholar
  31. Gonzalez A, Bell G (2013) Evolutionary rescue and adaptation to abrupt environmental change depends upon the history of stress. Philos Trans R Soc B-Biol Sci 368(1610):6. CrossRefGoogle Scholar
  32. Gonzalez-Ramos D, de Vries ARG, Grijseels SS, van Berkum MC, Swinnen S, van den Broek M, Nevoigt E, Daran JMG, Pronk JT, van Maris AJA (2016) A new laboratory evolution approach to select for constitutive acetic acid tolerance in Saccharomyces cerevisiae and identification of causal mutations. Biotechnol Biofuels 9(1):173. PubMedPubMedCentralCrossRefGoogle Scholar
  33. Gresham D, Dunham MJ (2014) The enduring utility of continuous culturing in experimental evolution. Genomics 104(6:399–405. CrossRefGoogle Scholar
  34. Gresham D, Hong J (2015) The functional basis of adaptive evolution in chemostats. FEMS Microbiol Rev 39(1):2–16. PubMedCrossRefGoogle Scholar
  35. Groisman A, Lobo C, Cho HJ, Campbell JK, Dufour YS, Stevens AM, Levchenko A (2005) A microfluidic chemostat for experiments with bacterial and yeast cells. Nat Methods 2(9):685–689. PubMedCrossRefGoogle Scholar
  36. Guan N, Shin H-d, Chen RR, Li J, Liu L, Du G, Chen J (2014) Understanding of how Propionibacterium acidipropionici respond to propionic acid stress at the level of proteomics. Sci Rep 4.
  37. Guan N, Li J, Shin H-d, Wu J, Du G, Shi Z, Liu L, Chen J (2015) Comparative metabolomics analysis of the key metabolic nodes in propionic acid synthesis in Propionibacterium acidipropionici. Metabolomics 11(5):1106–1116. CrossRefGoogle Scholar
  38. Guan N, Li J, Shin H, Du G, Chen J, Liu L (2016) Metabolic engineering of acid resistance elements to improve acid resistance and propionic acid production of Propionibacterium jensenii. Biotechnol Bioeng 113(6):1294–1304. PubMedCrossRefGoogle Scholar
  39. Harden MM, He A, Creamer K, Clark MW, Hamdallah I, Martinez KA, Kresslein RL, Bush SP, Slonczewski JL (2015) Acid-adapted strains of Escherichia coli K-12 obtained by experimental evolution. Appl Environ Microbiol 81(6):1932–1941. PubMedPubMedCentralCrossRefGoogle Scholar
  40. Heinemann M, Sauer U (2010) Systems biology of microbial metabolism. Curr Opin Microbiol 13(3):337–343. PubMedCrossRefGoogle Scholar
  41. Herzenberg LA, Sweet RG, Herzenberg LA (1976) Fluorescence-activated cell sorting. Sci Am 234(3):108–117. PubMedCrossRefGoogle Scholar
  42. Hou LH (2010) Improved production of ethanol by novel genome shuffling in Saccharomyces cerevisiae. Appl Biochem Biotechnol 160(4):1084–1093. PubMedCrossRefGoogle Scholar
  43. Hua XF, Wang J, Wu ZJ, Zhang HX, Li HP, Xing XH, Liu Z (2010) A salt tolerant Enterobacter cloacae mutant for bioaugmentation of petroleum- and salt-contaminated soil. Biochem Eng J 49(2):201–206. CrossRefGoogle Scholar
  44. Jakociunas T, Jensen MK, Keasling JD (2016) CRISPR/Cas9 advances engineering of microbial cell factories. Metab Eng 34:44–59. PubMedCrossRefGoogle Scholar
  45. Jansen MLA, Diderich JA, Mashego M, Hassane A, de Winde JH, Daran-Lapujade P, Pronk JT (2005) Prolonged selection in aerobic, glucose-limited chemostat cultures of Saccharomyces cerevisiae causes a partial loss of glycolytic capacity. Microbiol-Sgm 151:1657–1669. CrossRefGoogle Scholar
  46. Jezequel N, Lagomarsino MC, Heslot F, Thomen P (2013) Long-term diversity and genome adaptation of acinetobacter baylyi in a minimal-medium chemostat. Genome Biol Evol 5(1):87–97. PubMedCrossRefGoogle Scholar
  47. Jiang LY, Chen SG, Zhang YY, Liu JZ (2013) Metabolic evolution of Corynebacterium glutamicum for increased production of L-ornithine. BMC Biotechnol 13:11. CrossRefGoogle Scholar
  48. Jiang Y, Chen B, Duan CL, Sun BB, Yang JJ, Yang S (2015) Multigene editing in the Escherichia coli genome via the CRISPR-Cas9 system. Appl Environ Microbiol 81(7):2506–2514. PubMedPubMedCentralCrossRefGoogle Scholar
  49. Jiang YY, Ren FZ, Liu SL, Zhao L, Guo HY, Hou CY (2016) Enhanced acid tolerance in Bifidobacterium longum by adaptive evolution: comparison of the genes between the acid-resistant variant and wild-type strain. J Microbiol Biotechnol 26(3):452–460. PubMedCrossRefGoogle Scholar
  50. Ju SY, Kim JH, Lee PC (2016) Long-term adaptive evolution of Leuconostoc mesenteroides for enhancement of lactic acid tolerance and production. Biotechnol Biofuels 9:12. CrossRefGoogle Scholar
  51. Kao KC, Sherlock G (2008) Molecular characterization of clonal interference during adaptive evolution in asexual populations of Saccharomyces cerevisiae. Nat Genet 40(12):1499–1504. PubMedPubMedCentralCrossRefGoogle Scholar
  52. Kato Y, Ho SH, Vavricka CJ, Chang JS, Hasunuma T, Kondo A (2017) Evolutionary engineering of salt-resistant Chlamydomonas sp strains reveals salinity stress-activated starch-to-lipid biosynthesis switching. Bioresour Technol 245:1484–1490. PubMedCrossRefGoogle Scholar
  53. Kildegaard KR, Hallstrom BM, Blicher TH, Sonnenschein N, Jensen NB, Sherstyk S, Harrison SJ, Maury J, Herrgard MJ, Juncker AS, Forster J, Nielsen J, Borodina I (2014) Evolution reveals a glutathione-dependent mechanism of 3-hydroxypropionic acid tolerance. Metab Eng 26:57–66. PubMedCrossRefGoogle Scholar
  54. Klein-Marcuschamer D, Stephanopoulos G (2010) Method for designing and optimizing random-search libraries for strain improvement. Appl Environ Microbiol 76(16):5541–5546. PubMedPubMedCentralCrossRefGoogle Scholar
  55. Knorr B, Schlieker H, Hohmann HP, Weuster-Botz D (2007) Scale-down and parallel operation of the riboflavin production process with Bacillus subtilis. Biochem Eng J 33(3):263–274. CrossRefGoogle Scholar
  56. Koch H, Jeschke A, Becks L (2016) Use of ddPCR in experimental evolution studies. Methods Ecol Evol 7(3):340–351. CrossRefGoogle Scholar
  57. Kodym A, Afza R (2003) Physical and chemical mutagenesis. Methods Mol Biol 236:189–204. PubMedCrossRefGoogle Scholar
  58. Lee SY, Mattanovich D, Villaverde A (2012) Systems metabolic engineering, industrial biotechnology and microbial cell factories. Microb Cell Factories 11:3. CrossRefGoogle Scholar
  59. Lee JY, Seo J, Kim ES, Lee HS, Kim P (2013) Adaptive evolution of Corynebacterium glutamicum resistant to oxidative stress and its global gene expression profiling. Biotechnol Lett 35(5):709–717. PubMedCrossRefGoogle Scholar
  60. Lee SH, Kim MS, Lee JH, Kim TW, Bae SS, Lee SM, Jung HC, Yang TJ, Choi AR, Cho YJ, Lee JH, Kwon KK, Lee HS, Kang SG (2016) Adaptive engineering of a hyperthermophilic archaeon on CO and discovering the underlying mechanism by multi-omics analysis. Sci Rep 6.
  61. Leemhuis H, Kelly RM, Dijkhuizen L (2009) Directed evolution of enzymes: library screening strategies. IUBMB Life 61(3):222–228. PubMedCrossRefGoogle Scholar
  62. Li W, Chen G, Gu L, Zeng W, Liang Z (2014) Genome shuffling of Aspergillus niger for improving transglycosylation activity. Appl Biochem Biotechnol 172(1):50–61. PubMedCrossRefGoogle Scholar
  63. Li HM, Xue F, Wang WJ, Chen BZ (2015a) Genome shuffling of Lactobacillus brevis for enhanced production of thymidine phosphorylase. Biotechnol Bioprocess Eng 20(2):333–340. CrossRefGoogle Scholar
  64. Li Y, Lin Z, Huang C, Zhang Y, Wang Z, Tang YJ, Chen T, Zhao X (2015b) Metabolic engineering of Escherichia coli using CRISPR-Cas9 meditated genome editing. Metab Eng 31:13–21. PubMedCrossRefGoogle Scholar
  65. Liu W, Jiang R (2015) Combinatorial and high-throughput screening approaches for strain engineering. Appl Microbiol Biotechnol 99(5):2093–2104. PubMedCrossRefGoogle Scholar
  66. Liu JJ, Ding WT, Zhang GC, Wang JY (2011) Improving ethanol fermentation performance of Saccharomyces cerevisiae in very high-gravity fermentation through chemical mutagenesis and meiotic recombination. Appl Microbiol Biotechnol 91(4):1239–1246. PubMedCrossRefGoogle Scholar
  67. Long Q, Liu XX, Yang YK, Li L, Harvey L, McNeil B, Bai ZG (2014) The development and application of high throughput cultivation technology in bioprocess development. J Biotechnol 192:323–338. PubMedCrossRefGoogle Scholar
  68. Luan GD, Bao GH, Lin Z, Li Y, Chen ZG, Li Y, Cai Z (2015) Comparative genome analysis of a thermotolerant Escherichia coli obtained by genome replication engineering assisted continuous evolution (GREACE) and its parent strain provides new understanding of microbial heat tolerance. New Biotechnol 32(6):732–738. CrossRefGoogle Scholar
  69. Ma JF, Wu MK, Zhang CQ, He AY, Kong XP, Li GL, Wei C, Jiang M (2016) Coupled ARTP and ALE strategy to improve anaerobic cell growth and succinic acid production by Escherichia coli. J Chem Technol Biotechnol 91(3):711–717. CrossRefGoogle Scholar
  70. Mahr R, Frunzke J (2016) Transcription factor-based biosensors in biotechnology: current state and future prospects. Appl Microbiol Biotechnol 100(1):79–90. PubMedCrossRefGoogle Scholar
  71. Mahr R, Gatgens C, Gatgens J, Polen T, Kalinowski J, Frunzke J (2015) Biosensor-driven adaptive laboratory evolution of L-valine production in Corynebacterium glutamicum. Metab Eng 32:184–194. PubMedCrossRefGoogle Scholar
  72. Margolles A, Sanchez B (2012) Selection of a Bifidobacterium animalis subsp lactis strain with a decreased ability to produce acetic acid. Appl Environ Microbiol 78(9):3338–3342. PubMedPubMedCentralCrossRefGoogle Scholar
  73. Mukhopadhyay A (2015) Tolerance engineering in bacteria for the production of advanced biofuels and chemicals. Trends Microbiol 23(8):498–508. PubMedCrossRefGoogle Scholar
  74. Mundhada H, Seoane JM, Schneider K, Koza A, Christensen HB, Klein T, Phaneuf PV, Herrgard M, Feist AM, Nielsen AT (2017) Increased production of L-serine in Escherichia coil through adaptive laboratory evolution. Metab Eng 39:141–150. PubMedCrossRefGoogle Scholar
  75. Oide S, Gunji W, Moteki Y, Yamamoto S, Suda M, Jojima T, Yukawa H, Inui M (2015) Thermal and solvent stress cross-tolerance conferred to Corynebacterium glutamicum by adaptive laboratory evolution. Appl Environ Microbiol 81(7):2284–2298. PubMedPubMedCentralCrossRefGoogle Scholar
  76. Ojo EO, Auta H, Baganz F, Lye GJ (2015) Design and parallelisation of a miniature photobioreactor platform for microalgal culture evaluation and optimisation. Biochem Eng J 103:93–102. CrossRefGoogle Scholar
  77. Palomino MM, Allievi MC, Grundling A, Sanchez-Rivas C, Ruzal SM (2013) Osmotic stress adaptation in Lactobacillus casei BL23 leads to structural changes in the cell wall polymer lipoteichoic acid. Microbiol-Sgm 159:2416–2426. CrossRefGoogle Scholar
  78. Park KS, Lee DK, Lee H, Lee Y, Jang YS, Kim YH, Yang HY, Lee SI, Seol W, Kim JS (2003) Phenotypic alteration of eukaryotic cells using randomized libraries of artificial transcription factors. Nat Biotechnol 21(10):1208–1214. PubMedCrossRefGoogle Scholar
  79. Park JH, Lee SY, Kim TY, Kim HU (2008) Application of systems biology for bioprocess development. Trends Biotechnol 26(8):404–412. PubMedCrossRefGoogle Scholar
  80. Patnaik R, Louie S, Gavrilovic V, Perry K, Stemmer WPC, Ryan CM, del Cardayre S (2002) Genome shuffling of Lactobacillus for improved acid tolerance. Nat Biotechnol 20(7):707–712. PubMedCrossRefGoogle Scholar
  81. Peabody GL, Winkler J, Kao KC (2014) Tools for developing tolerance to toxic chemicals in microbial systems and perspectives on moving the field forward and into the industrial setting. Curr Opin Chem Eng 6:9–17. CrossRefGoogle Scholar
  82. Pinheiro LB, Coleman VA, Hindson CM, Herrmann J, Hindson BJ, Bhat S, Emslie KR (2011) Evaluation of a droplet digital polymerase chain reaction format for DNA copy number quantification. Anal Chem 84(2):1003–1011. PubMedPubMedCentralCrossRefGoogle Scholar
  83. Portnoy VA, Bezdan D, Zengler K (2011) Adaptive laboratory evolution - harnessing the power of biology for metabolic engineering. Curr Opin Biotechnol 22(4):590–594. PubMedCrossRefGoogle Scholar
  84. Qi LS, Larson MH, Gilbert LA, Doudna JA, Weissman JS, Arkin AP, Lim WA (2013) Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 152(5):1173–1183. PubMedPubMedCentralCrossRefGoogle Scholar
  85. Qi F, Kitahara Y, Wang ZT, Zhao XB, Du W, Liu DH (2014) Novel mutant strains of Rhodosporidium toruloides by plasma mutagenesis approach and their tolerance for inhibitors in lignocellulosic hydrolyzate. J Chem Technol Biotechnol 89(5):735–742. CrossRefGoogle Scholar
  86. Quan S, Ray JCJ, Kwota Z, Duong T, Balazsi G, Cooper TF, Monds RD (2012) Adaptive evolution of the lactose utilization network in experimentally evolved populations of Escherichia coli. PLoS Genet 8(1):18. CrossRefGoogle Scholar
  87. Radek A, Tenhaef N, Muller MF, Brusseler C, Wiechert W, Marienhagen J, Polen T, Noack S (2017) Miniaturized and automated adaptive laboratory evolution: evolving Corynebacterium glutamicum towards an improved D-xylose utilization. Bioresour Technol 245:1377–1385. PubMedCrossRefGoogle Scholar
  88. Raman S, Rogers JK, Taylor ND, Church GM (2014) Evolution-guided optimization of biosynthetic pathways. Proc Natl Acad Sci 111(50):17803–17808. PubMedPubMedCentralCrossRefGoogle Scholar
  89. Reyes LH, Almario MP, Winkler J, Orozco MM, Kao KC (2012) Visualizing evolution in real time to determine the molecular mechanisms of n-butanol tolerance in Escherichia coli. Metab Eng 14(5):579–590. PubMedCrossRefGoogle Scholar
  90. Reyes LH, Gomez JM, Kao KC (2014) Improving carotenoids production in yeast via adaptive laboratory evolution. Metab Eng 21:26–33. PubMedCrossRefGoogle Scholar
  91. Royce LA, Yoon JM, Chen YX, Rickenbach E, Shanks JV, Jarboe LR (2015) Evolution for exogenous octanoic acid tolerance improves carboxylic acid production and membrane integrity. Metab Eng 29:180–188. PubMedCrossRefGoogle Scholar
  92. Rudolph B, Gebendorfer KM, Buchner J, Winter J (2010) Evolution of Escherichia coli for growth at high temperatures. J Biol Chem 285(25):19029–19034. PubMedPubMedCentralCrossRefGoogle Scholar
  93. Sanchez RG, Karhumaa K, Fonseca C, Nogue VS, Almeida JRM, Larsson CU, Bengtsson O, Bettiga M, Hahn-Hagerdal B, Gorwa-Grauslund MF (2010) Improved xylose and arabinose utilization by an industrial recombinant Saccharomyces cerevisiae strain using evolutionary engineering. Biotechnol Biofuels 3:11. CrossRefGoogle Scholar
  94. Santoro SW, Schultz PG (2002) Directed evolution of the site specificity of Cre recombinase. Proc Natl Acad Sci 99(7):4185–4190. PubMedPubMedCentralCrossRefGoogle Scholar
  95. Satomura A, Katsuyama Y, Miura N, Kuroda K, Tomio A, Bamba T, Fukusaki E, Ueda M (2013) Acquisition of thermotolerant yeast Saccharomyces cerevisiae by breeding via stepwise adaptation. Biotechnol Prog 29(5):1116–1123. PubMedCrossRefGoogle Scholar
  96. Shi DJ, Wang CL, Wang KM (2009) Genome shuffling to improve thermotolerance, ethanol tolerance and ethanol productivity of Saccharomyces cerevisiae. J Ind Microbiol Biotechnol 36(1):139–147. PubMedCrossRefGoogle Scholar
  97. Shi F, Tan J, Chu J, Wang YH, Zhuang YP, Zhang SL (2015) A qualitative and quantitative high-throughput assay for screening of gluconate high-yield strains by Aspergillus niger. J Microbiol Methods 109:134–139. PubMedCrossRefGoogle Scholar
  98. Si T, Chao R, Min YH, Wu YY, Ren W, Zhao HM (2017) Automated multiplex genome-scale engineering in yeast. Nat Commun 8:12. CrossRefGoogle Scholar
  99. Sun XM, Ren LJ, Ji XJ, Chen SL, Guo DS, Huang H (2016) Adaptive evolution of Schizochytrium sp by continuous high oxygen stimulations to enhance docosahexaenoic acid synthesis. Bioresour Technol 211:374–381. PubMedCrossRefGoogle Scholar
  100. Utrilla J, Licona-Cassani C, Marcellin E, Gosset G, Nielsen LK, Martinez A (2012) Engineering and adaptive evolution of Escherichia coli for D-lactate fermentation reveals GatC as a xylose transporter. Metab Eng 14(5):469–476. PubMedCrossRefGoogle Scholar
  101. Vogelstein B, Kinzler KW (1999) Digital PCR. Proc Natl Acad Sci 96(16):9236–9241. PubMedPubMedCentralCrossRefGoogle Scholar
  102. Wan NW, Liu ZQ, Xue F, Huang K, Tang LJ, Zheng YG (2015) An efficient high-throughput screening assay for rapid directed evolution of halohydrin dehalogenase for preparation of beta-substituted alcohols. Appl Microbiol Biotechnol 99(9):4019–4029. PubMedCrossRefGoogle Scholar
  103. Wang LY, Huang ZL, Li G, Zhao HX, Xing XH, Sun WT, Li HP, Gou ZX, Bao CY (2010) Novel mutation breeding method for Streptomyces avermitilis using an atmospheric pressure glow discharge plasma. J Appl Microbiol 108(3):851–858. PubMedCrossRefGoogle Scholar
  104. Wang YZ, Manow R, Finan C, Wang JH, Garza E, Zhou SD (2011) Adaptive evolution of nontransgenic Escherichia coli KC01 for improved ethanol tolerance and homoethanol fermentation from xylose. J Ind Microbiol Biotechnol 38(9):1371–1377. PubMedCrossRefGoogle Scholar
  105. Wang ZK, Gao CJ, Wang Q, Liang QF, Qi QS (2012) Production of pyruvate in Saccharomyces cerevisiae through adaptive evolution and rational cofactor metabolic engineering. Biochem Eng J 67:126–131. CrossRefGoogle Scholar
  106. Weikert C, Sauer U, Bailey JE (1997) Use of a glycerol-limited, long-term chemostat for isolation of Escherichia coli mutants with improved physiological properties. Microbiol-Uk 143:1567–1574. CrossRefGoogle Scholar
  107. Williams TC, Pretorius IS, Paulsen IT (2016) Synthetic evolution of mtabolic productivity using biosensors. Trends Biotechnol 34(5):371–381. PubMedCrossRefGoogle Scholar
  108. Winkler JD, Kao KC (2014) Recent advances in the evolutionary engineering of industrial biocatalysts. Genomics 104(6):406–411. PubMedCrossRefGoogle Scholar
  109. Wright J, Bellissimi E, de Hulster E, Wagner A, Pronk JT, van Maris AJA (2011) Batch and continuous culture-based selection strategies for acetic acid tolerance in xylose-fermenting Saccharomyces cerevisiae. FEMS Yeast Res 11(3):299–306. PubMedCrossRefGoogle Scholar
  110. Wu C, Zhang J, Chen W, Wang M, Du G, Chen J (2012) A combined physiological and proteomic approach to reveal lactic-acid-induced alterations in Lactobacillus casei Zhang and its mutant with enhanced lactic acid tolerance. Appl Microbiol Biotechnol 93(2):707–722. PubMedCrossRefGoogle Scholar
  111. Wu C, Zhang J, Du G, Chen J (2013) Heterologous expression of Lactobacillus casei RecO improved the multiple-stress tolerance and lactic acid production in Lactococcus lactis NZ9000 during salt stress. Bioresour Technol 143:238–241. PubMedCrossRefGoogle Scholar
  112. Wu CD, He GQ, Zhang J (2014) Physiological and proteomic analysis of Lactobacillus casei in response to acid adaptation. J Ind Microbiol Biotechnol 41(10):1533–1540. PubMedCrossRefGoogle Scholar
  113. Wu MK, Guan Z, Wang YJ, Ma JF, Wu H, Jiang M (2016) Efficient succinic acid production by engineered Escherichia coli using ammonia as neutralizer. J Chem Technol Biotechnol 91(9):2412–2418. CrossRefGoogle Scholar
  114. Xu F, Jin H, Li H, Tao L, Wang J, Lv J, Chen S (2012) Genome shuffling of Trichoderma viride for enhanced cellulase production. Ann Microbiol 62(2):509–515. CrossRefGoogle Scholar
  115. Xue Y-P, Yang Y-K, Lv S-Z, Liu Z-Q, Zheng Y-G (2016) High-throughput screening methods for nitrilases. Appl Microbiol Biotechnol 100(8):3421–3432. PubMedCrossRefGoogle Scholar
  116. Yu H, Tyo K, Alper H, Klein-Marcuschamer D, Stephanopoulos G (2008) A high-throughput screen for hyaluronic acid accumulation in recombinant Escherichia coli transformed by libraries of engineered sigma factors. Biotechnol Bioeng 101(4):788–796. PubMedCrossRefGoogle Scholar
  117. Yu S, Zhao Q, Miao X, Shi J (2013) Enhancement of lipid production in low-starch mutants Chlamydomonas reinhardtii by adaptive laboratory evolution. Bioresour Technol 147:499–507. PubMedCrossRefGoogle Scholar
  118. Zhang YX, Perry K, Vinci VA, Powell K, Stemmer WPC, del Cardayre SB (2002) Genome shuffling leads to rapid phenotypic improvement in bacteria. Nature 415(6872):644–646. PubMedCrossRefGoogle Scholar
  119. Zhang HF, Chong HQ, Ching CB, Jiang RR (2012a) Random mutagenesis of global transcription factor cAMP receptor protein for improved osmotolerance. Biotechnol Bioeng 109(5):1165–1172. PubMedCrossRefGoogle Scholar
  120. Zhang J, Wu CD, Du GC, Chen J (2012b) Enhanced acid tolerance in Lactobacillus casei by adaptive evolution and compared stress response during acid stress. Biotechnol Bioprocess Eng 17(2):283–289. CrossRefGoogle Scholar
  121. Zhang M, Chen J, Zhang J, Du G (2014a) The effects of RecO deficiency in Lactococcus lactis NZ9000 on resistance to multiple environmental stresses. J Sci Food Agric 94(15):3125–3133. PubMedCrossRefGoogle Scholar
  122. Zhang X, Zhang XF, Li HP, Wang LY, Zhang C, Xing XH, Bao CY (2014b) Atmospheric and room temperature plasma (ARTP) as a new powerful mutagenesis tool. Appl Microbiol Biotechnol 98(12):5387–5396. PubMedCrossRefGoogle Scholar
  123. Zhang F, Qian X, Si H, Xu G, Han R, Ni Y (2015a) Significantly improved solvent tolerance of Escherichia coli by global transcription machinery engineering. Microb Cell Factories 14(1):175. CrossRefGoogle Scholar
  124. Zhang X, Zhang C, Zhou QQ, Zhang XF, Wang LY, Chang HB, Li HP, Oda Y, Xing XH (2015b) Quantitative evaluation of DNA damage and mutation rate by atmospheric and room-temperature plasma (ARTP) and conventional mutagenesis. Appl Microbiol Biotechnol 99(13):5639–5646. PubMedCrossRefGoogle Scholar
  125. Zheng P, Zhang KK, Yan Q, Xu Y, Sun ZH (2013) Enhanced succinic acid production by Actinobacillus succinogenes after genome shuffling. J Ind Microbiol Biotechnol 40(8):831–840. PubMedCrossRefGoogle Scholar
  126. Zhou H, Cheng JS, Wang BL, Fink GR, Stephanopoulos G (2012) Xylose isomerase overexpression along with engineering of the pentose phosphate pathway and evolutionary engineering enable rapid xylose utilization and ethanol production by Saccharomyces cerevisiae. Metab Eng 14(6):611–622. PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Key Laboratory of Industrial Biotechnology, Ministry of Education, School of BiotechnologyJiangnan UniversityWuxiChina
  2. 2.School of BiotechnologyJiangnan UniversityWuxiChina
  3. 3.School of the EnvironmentJiangsu UniversityZhenjiangChina
  4. 4.The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of EducationJiangnan UniversityWuxiChina
  5. 5.National Engineering Laboratory for Cereal Fermentation TechnologyJiangnan UniversityWuxiChina

Personalised recommendations