Skip to main content
SpringerLink
Log in

Microbe and Multienzyme Systems of High-solid and Multi-phase Bioreaction

  • Chapter
  • First Online:
High-solid and Multi-phase Bioprocess Engineering

Part of the book series: Green Chemistry and Sustainable Technology ((GCST))

  • 485 Accesses

Abstract

Biocatalysts (microbe and enzymes) are sensitive to environmental factors. In high-solid and multi-phase bioprocess system, high-solid loading leads to special colony structure and “microbial ecosystems”. It is necessary to screen microorganisms and enzymes which have high osmotic tolerance and substrate-capturing ability. In this chapter, based on feature of high-solid and multi-phase process, suitable screening principles and methods of microorganisms and enzymes are discussed. Clostridium acetobutylicum with high butanol productivity is taken as an example to carry out the engineering practice of rational selection of strains and construct the domestication microbial system and enzyme catalysis systems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Xue C, Zhao XQ, Liu CG et al (2013) Prospective and development of butanol as an advanced biofuel. Biotech Adv. 31(8):1575–1584

    Article  CAS  Google Scholar 

  2. Qureshi N, Blaschek H (2000) Butanol production using Clostridium beijerinckii BA101 hyper-butanol producing mutant strain and recovery by pervaporation. In: Twenty-first symposium on biotechnology for fuels and chemicals. Humana Press, Colorado, pp 225–235

    Chapter  Google Scholar 

  3. Jang YS, Malaviya A, Lee SY (2013) Acetone–butanol–ethanol production with high productivity using Clostridium acetobutylicum BKM19. Biotech Bioeng 110(6):1646–1653

    Article  CAS  Google Scholar 

  4. Bowring SN, Morris J (1985) Mutagenesis of Clostridium acetobutylicum. J Appl Microbiol 58(6):577–584

    CAS  Google Scholar 

  5. Borden JR, Papoutsakis ET (2007) Dynamics of genomic-library enrichment and identification of solvent tolerance genes for Clostridium acetobutylicum. Appl Environ Microb 73(9):3061–3068

    Article  CAS  Google Scholar 

  6. Glass JI, Alperovich N, Assad-Garcia N et al (2005) Estimation of the minimal Mycoplasma Gene set using global transposon mutagenesis and comparative genomics. In: Genomes to life contractor-grantee workshop III, February 6–9

    Google Scholar 

  7. Robey-Bond SM, Barrantes-Reynolds R, Bond JP et al (2008) Clostridium acetobutylicum 8-Oxoguanine DNA Glycosylase (Ogg) differs from Eukaryotic Oggs with respect to opposite base discrimination. Biochemistry-us 47(29):7626–7636

    Article  CAS  Google Scholar 

  8. Allcock ER, Reid SJ, Jones DT et al (1981) Autolytic activity and an autolysis-deficient mutant of Clostridium acetobutylicum. Appl Environ Microb 42(6):929–935

    CAS  Google Scholar 

  9. Dreyfus-Fourcade M, Sebald M, Zavadova M (1972) Restriction and modification of phage r by Clostridium perfringens NCTC 8798 and its mutants. Ann Inst Pasteur 122:1117–1127

    CAS  Google Scholar 

  10. Liu XB, Gu QY, Yu XB (2013) Repetitive domestication to enhance butanol tolerance and production in Clostridium acetobutylicum through artificial simulation of bio-evolution. Bioresource Technol 130:638–643

    Article  CAS  Google Scholar 

  11. Xue C, Zhao J, Lu C et al (2012) High-titer n-butanol production by clostridium acetobutylicum JB200 in fed-batch fermentation with intermittent gas stripping. Biotechnol Bioeng 109(11):2746–2756

    Article  CAS  PubMed  Google Scholar 

  12. Lau MW, Dale BE, Balan V (2008) Ethanolic fermentation of hydrolysates from ammonia fiber expansion (AFEX) treated corn stover and distillers grain without detoxification and external nutrient supplementation. Biotechnol Bioeng 99(3):529–539

    Article  CAS  PubMed  Google Scholar 

  13. Tian S, Zhu J, Yang X (2011) Evaluation of an adapted inhibitor-tolerant yeast strain for ethanol production from combined hydrolysate of softwood. Appl Energ 88(5):1792–1796

    Article  CAS  Google Scholar 

  14. Ding MZ, Zhou X, Yuan YJ (2010) Metabolome profiling reveals adaptive evolution of Saccharomyces cerevisiae during repeated vacuum fermentations. Metabolomics 6(1):42–55

    Article  CAS  Google Scholar 

  15. Wallace-Salinas V, Gorwa-Grauslund MF (2013) Adaptive evolution of an industrial strain of Saccharomyces cerevisiae for combined tolerance to inhibitors and temperature. Biotechnol Biofuels 6(1):151

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Fan C, Qi K, Xia XX et al (2013) Efficient ethanol production from corncob residues by repeated fermentation of an adapted yeast. Bioresource Technol 136:309–315

    Article  CAS  Google Scholar 

  17. Xia ML (2016) Digital image analysis for rapid detection and fermentation process intensification by periodic-peristole agitation. Graduate University of the Chinese Academy of Sciences (Institute of Process Engineering)

    Google Scholar 

  18. Jiang Y, Xu C, Dong F et al (2009) Disruption of the acetoacetate decarboxylase gene in solvent-producing Clostridium acetobutylicum increases the butanol ratio. Metab Eng 11(4–5):284–291

    Article  CAS  PubMed  Google Scholar 

  19. Harris LM, Desai RP, Welker NE et al (2000) Characterization of recombinant strains of the Clostridium acetobutylicum butyrate kinase inactivation mutant: need for new phenomenological models for solventogenesis and butanol inhibition? Biotechnol Bioeng 67(1):1–11

    Article  CAS  PubMed  Google Scholar 

  20. Jang YS, Lee J Y, Lee J et al (2012) Enhanced butanol production obtained by reinforcing the direct butanol-forming route in Clostridium acetobutylicum. MBio, 3(5):e00314–12

    Article  CAS  Google Scholar 

  21. Ou J, Ma C, Xu N et al (2015) High butanol production by regulating carbon, redox and energy in Clostridia. Front Chem Sci Eng 9(3):317–323

    Article  CAS  Google Scholar 

  22. Harris L, Blank L, Desai R et al (2001) Fermentation characterization and flux analysis of recombinant strains of Clostridium acetobutylicum with an inactivated solR gene. J Ind Microbio Biot 27(5):322–328

    Article  CAS  Google Scholar 

  23. Tummala SB, Welker NE, Papoutsakis ET (2003) Design of antisense RNA constructs for downregulation of the acetone formation pathway of Clostridium acetobutylicum. J Bacteriol 185(6):1923–1934

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Sillers R, Al-Hinai MA, Papoutsakis ET (2009) Aldehyde–alcohol dehydrogenase and/or thiolase overexpression coupled with CoA transferase downregulation lead to higher alcohol titers and selectivity in Clostridium acetobutylicum fermentations. Biotechnol Bioeng 102(1):38–49

    Article  CAS  PubMed  Google Scholar 

  25. Mahesh S, Jayas D, Paliwal J et al (2015) Comparison of partial least squares regression (PLSR) and principal components regression (PCR) methods for protein and hardness predictions using the near-infrared (NIR) hyperspectral images of bulk samples of Canadian wheat. Food Bioprocess Tech 8(1):31–40

    Article  CAS  Google Scholar 

  26. Elshikh M, Ahmed S, Funston S et al (2016) Resazurin-based 96-well plate microdilution method for the determination of minimum inhibitory concentration of biosurfactants. Biotechnol Lett 38(6):1015–1019

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Liu C-G, Xue C, Lin Y-H et al (2013) Redox potential control and applications in microaerobic and anaerobic fermentations. Biotechnol Adv 31(2):257–265

    Article  CAS  PubMed  Google Scholar 

  28. Huang H, Liu H, Gan Y-R (2010) Genetic modification of critical enzymes and involved genes in butanol biosynthesis from biomass. Biotechnol Adv 28(5):651–657

    Article  CAS  PubMed  Google Scholar 

  29. Grimmler C, Janssen H, Krausse D et al (2011) Genome-Wide Gene Expression Analysis of the Switch between Acidogenesis and Solventogenesis in Continuous Cultures of Clostridium acetobutylicum. J Mol Microb Biotech 20(1):1–15

    Article  CAS  Google Scholar 

  30. Grupe H, Gottschalk G (1992) Physiological events in Clostridium acetobutylicum during the shift from acidogenesis to solventogenesis in continuous culture and presentation of a model for shift induction. Appl Environ Microb 58(12):3896–3902

    CAS  Google Scholar 

  31. Lee J, Yun H, Feist AM et al (2008) Genome-scale reconstruction and in silico analysis of the Clostridium acetobutylicum ATCC 824 metabolic network. Appl Microbiol Biot 80(5):849–862

    Article  CAS  Google Scholar 

  32. Alsaker KV, Paredes C, Papoutsakis ET (2010) Metabolite stress and tolerance in the production of biofuels and chemicals: gene-expression-based systems analysis of butanol, butyrate, and acetate stresses in the anaerobe Clostridium acetobutylicum. Biotechnol Bioeng 105(6):1131–1147

    PubMed  CAS  Google Scholar 

  33. Lütke-Eversloh T, Bahl H (2011) Metabolic engineering of Clostridium acetobutylicum: recent advances to improve butanol production. Curr Opin Biotech 22(5):634–647

    Article  CAS  PubMed  Google Scholar 

  34. MlL Xia, Wang L, Yang ZX et al (2015) Periodic-peristole agitation for process enhancement of butanol fermentation. Biotechnol Biofuels 8(1):1

    Article  CAS  Google Scholar 

  35. Maddox IS, Steiner E, Hirsch S et al (2000) The cause of “acid crash” and “acidogenic fermentations” duping the batch acetone-butanol-ethanol (ABE) fermentation process. J Mol Microb Biotech 2(1):95–100

    CAS  Google Scholar 

  36. Liu H, Huang D, Wen J (2016) Integrated intracellular metabolic profiling and pathway analysis approaches reveal complex metabolic regulation by Clostridium acetobutylicum. Microb Cell Fact 15(1):1

    Article  CAS  Google Scholar 

  37. Ozyurek D, Kalyon A, Yildirim M et al (2014) Experimental investigation and prediction of wear properties of Al/SiC metal matrix composites produced by thixomoulding method using Artificial Neural Networks. Mater Design 63:270–277

    Article  CAS  Google Scholar 

  38. Mikulandric R, Loncar D, Boehning D et al (2014) Artificial neural network modelling approach for a biomass gasification process in fixed bed gasifiers. Energ Convers Manage 87:1210–1223

    Article  CAS  Google Scholar 

  39. Hore S, Bhattacharya T, Dey Net al (2016) A real time dactylology based feature extractrion for selective image encryption and artificial neural network. In: Image feature detectors and descriptors. Springer International Publishing, pp 203–226

    Chapter  Google Scholar 

  40. Wang SC (2003) Artificial neural network. In: Interdisciplinary Computing in Java Programming. Springer, US, pp 81–100

    Chapter  Google Scholar 

  41. Thompson KV, Chmielewski J, Gaines MS et al (2013) Competency-based reforms of the undergraduate biology curriculum: integrating the physical and biological sciences. Cbe-Life Sci Edu 12(2):162–169

    Article  Google Scholar 

  42. Vale RD, DeRisi J, Phillips R et al (2012) Interdisciplinary Graduate Training in Teaching labs. Science 338(6114):1542–1543

    Article  PubMed  Google Scholar 

  43. Bialek W, Botstein D (2004) Introductory science and mathematics education for 21st-century biologists. Science 303(5659):788–790

    Article  CAS  PubMed  Google Scholar 

  44. Jin XQ, Zhou H, Wu XM et al (2008) A rapid screening method of producing strain in acetone-butanol fermentation. Chin J Process Eng 6:1185–1189

    Google Scholar 

  45. Strategy AE (1998) Design by directed evolution. Acc Chem Res 31(3):125–131

    Article  Google Scholar 

  46. Fu AY, Chou HP, Spence C et al (2002) An integrated microfabricated cell sorter. Anal Chem 74(11):2451–2457

    Article  CAS  PubMed  Google Scholar 

  47. Arnold FH, Moore JC (1997) Optimizing industrial enzymes by directed evolution. In: New enzymes for organic synthesis. Springer, Berlin, pp 1–14

    Google Scholar 

  48. Arnold F (1998) In IBC directed enzyme evolution. San Diego CA

    Google Scholar 

  49. Zhang JH, Dawes G, Stemmer WP (1997) Directed evolution of a fucosidase from a galactosidase by DNA shuffling and screening. Proc Natl Acad Sci 94(9):4504–4509

    Article  CAS  PubMed  Google Scholar 

  50. Chen K, Arnold FH (1993) Tuning the activity of an enzyme for unusual environments: sequential random mutagenesis of subtilisin E for catalysis in dimethylformamide. Proc Natl Acad Sci 90(12):5618–5622

    Article  CAS  PubMed  Google Scholar 

  51. Zhao H, Arnold FH (1997) Combinatorial protein design: strategies for screening protein libraries. Curr Opin Struc Biol 7(4):480–485

    Article  CAS  Google Scholar 

  52. Chen K, Arnold FH (1991) Enzyme engineering for nonaqueous solvents: random mutagenesis to enhance activity of subtilisin E in polar organic media. Nat Biotechnol 9(11):1073–1077

    Article  CAS  Google Scholar 

  53. Cadwell RC, Joyce GF (1992) Randomization of genes by PCR mutagenesis. Genome Res 2(1):28–33

    Article  CAS  Google Scholar 

  54. Wu WT (2004) Protein engineering technology and design of novel biocatalysts. Pharm Biotechno 11(1):1–6

    CAS  Google Scholar 

  55. Kikuchi M, Ohnishi K, Harayama S (2000) An effective family shuffling method using single-stranded DNA. Gene 243(1):133–137

    Article  CAS  PubMed  Google Scholar 

  56. Crameri A, Raillard SA, Bermudez E (1998) DNA shuffling of a family of genes from diverse species accelerates directed evolution. Nature 391(6664):288–291

    Article  CAS  PubMed  Google Scholar 

  57. Kikuchi M, Ohnishi K, Harayama S (1999) Novel family shuffling methods for the in vitro evolution of enzymes. Gene 236(1):159–167

    Article  CAS  PubMed  Google Scholar 

  58. You C, Chen H, Myung S et al (2013) Enzymatic transformation of nonfood biomass to starch. P Natl Acad Sci USA 110(18):7182–7187

    Article  Google Scholar 

  59. Wang J, Chen X, Zhu H et al (2003) Relationship between aging and renal high-affinity sodium-dependent dicarboxylate cotransporter-3 expression characterized with antifusion protein antibody. J Gerontol A-Biol 58(10):B879–B888

    Article  Google Scholar 

  60. Dueber JE, Wu GC, Malmirchegini GR et al (2009) Synthetic protein scaffolds provide modular control over metabolic flux. Nat Biotechnol 27(8):753–759

    Article  CAS  Google Scholar 

  61. Jandt U, You C, Zhang YP et al (2013) Compartmentalization and metabolic channeling for multienzymatic biosynthesis: practical strategies and modeling approaches. In: Fundamentals and application of new bioproduction systems. Springer, Berlin, pp 41–65

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Process Engineering, Chinese Academy of Sciences, Beijing, China

    Hongzhang Chen

Authors
  1. Hongzhang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hongzhang Chen .

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Chen, H. (2018). Microbe and Multienzyme Systems of High-solid and Multi-phase Bioreaction. In: High-solid and Multi-phase Bioprocess Engineering. Green Chemistry and Sustainable Technology. Springer, Singapore. https://doi.org/10.1007/978-981-10-6352-7_4

Download citation

Publish with us

Policies and ethics

Search

Navigation