Skip to main content
SpringerLink
Log in

Dynamic flux balance analysis for microbial conversion of glycerol into 1,3-propanediol by Klebsiella pneumoniae

  • Research Paper
  • Published:
Bioprocess and Biosystems Engineering Aims and scope Submit manuscript

Abstract

To investigate the relationship between the yield of 1,3-propanediol (1,3-PD) and the flux variation in metabolic pathways of Klebsiella pneumoniae, an optimized calculation method was constructed on basis of dynamic flux balance analysis by combining genome-scale flux balance analysis with a kinetic model of extracellular metabolites. Through optimizing calculations, a more completely expanded metabolic pathway was obtained, which includes the previously reported metabolic pathway and additional three pathways or site: a pentose phosphate pathway (PPP) elicited at the dihydroxyacetone (DHA) node to provide more reducing equivalents; a branch of synthetic amino acids at the 3-phosphoglycerate (3PG) node; and the α-ketoglutarate site in the tricarboxylic acid (TCA) cycle leading to anabolic pathways for glutamate and other amino acids. On this basis, the relationships between the dynamic flux distribution of the important nodes in the metabolic pathway and the yield of 1,3-propanediol were analyzed. First, dynamic flux change from DHA to the PPP is positively correlated with the yield. Second, variation in flux in the TCA cycle is also positively correlated with the yield of 1,3-propanediol. In addition, the influence of the feedback loop formed by the cofactor tetrahydrofolate on the flux change of TCA in the amino acid anabolic pathway was examined. These results are of important reference value and have guiding significance for the extension of the glycerol metabolism pathway in K. pneumoniae, the rational transformation of genetic engineering in bacteria, and the optimization of metabolic pathways for industrial production.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Abbreviations

1,3-PD:

1,3-Propanediol

10fThf:

10-Formyltetrahydrofolate

3HPA:

3-Hydroxypropanal

3PG:

3-Phosphoglycerate

3PHP:

3-Phosphohydroxypyruvate

Ac:

Acetic acid

AKG:

α-Ketoglutarate

Cit:

Citrate

DFBA:

Dynamic flux balance analysis

DHA:

Dihydroxyacetone

dha :

Dha regulon

DHAK:

Dihydroxyacetone phosphate kinase

DHAP:

Dihydroxyacetone phosphate

DHAPT:

Dihydroxyacetone phosphotransferase

DOA:

Dynamic optimization method

EtOH:

Ethanol

F6P:

6-Phosphofructose

FBA:

Flux balance analysis

Fum:

Fumarate

G3P:

3-Phosphoglyceraldehyde

GDH:

Glycerol dehydrogenase

GDHt:

Glycerol dehydratase

Glu:

Glutamate

Gly:

Glycine

Glyc:

Glycerol

LP:

Linear programming

Mal:

Malate

mlThf:

Methylenetetrahydrofolate

Oaa:

Oxaloacetate

ODE:

Ordinary differential equation

PDH:

Pyruvate dehydrogenase

PDOR:

1,3-Propanediol oxidoreductase

PEP:

Phosphoenolpyruvate

PFL:

Pyruvate formate lyase

PGCD:

Phosphoglycerate dehydrogenase

PGM:

Phosphoglycerate mutase

PPP:

Pentose phosphate pathway

PYR:

Pyruvate

QP:

Quadratic programming

Ser:

Serine

SOA:

Static optimization method

Succ:

Succinate

SuccCoA:

Succinyl-coA

TCA:

Tricarboxylic acid

Thf:

Tetrahydrofolate

References

  1. Gungormusler-Yilmaz M, Cicek N, Levin DB, Azbar N (2016) Cell immobilization for microbial production of 1,3-propanediol. Crit Rev Biotechnol 36:482–494

    CAS  PubMed  Google Scholar 

  2. Lee CS, Aroua MK, Daud WMAW, Cognet P, Pérès-Lucchese Y, Fabre PL, Reynes O, Latapie L (2015) A review: conversion of bioglycerol into 1,3-propanediol via biological and chemical method. Renew Sust Energ Rev 42:963–972

    Article  CAS  Google Scholar 

  3. Vivek N, Sindhu R, Madhavan A, Anju AJ, Castro E, Faraco V, Pandey A, Binod P (2017) Recent advances in the production of value added chemicals and lipids utilizing biodiesel industry generated crude glycerol as a substrate–metabolic aspects, challenges and possibilities: an overview. Bioresour Technol 239:507–517

    Article  CAS  Google Scholar 

  4. Celinska E (2010) Debottlenecking the 1,3-propanediol pathway by metabolic engineering. Biotechnol Adv 28:519–530

    Article  CAS  Google Scholar 

  5. Lee JH, Jung M-Y, Oh M-K (2018) High-yield production of 1,3-propanediol from glycerol by metabolically engineered Klebsiella pneumoniae. Biotechnol Biofuels 11:104

    Article  Google Scholar 

  6. Zeng AP, Ross A, Biebl H, Tag C, Günzel B, Deckwer WD (1994) Multiple product inhibition and growth modeling of clostridium butyricum and Klebsiella pneumoniae in glycerol fermentation. Biotechnol Bioeng 44:902–911

    Article  CAS  Google Scholar 

  7. Zeng AP (1995) A kinetic model for product formation of microbial and mammalian cells. Biotechnol Bioeng 46:314–324

    Article  CAS  Google Scholar 

  8. Zeng AP, Deckwer WD (1995) A kinetic model for substrate and energy consumption of microbial growth under substrate-sufficient conditions. Biotechnol Prog 11:71–79

    Article  CAS  Google Scholar 

  9. Xiu ZL, Zeng AP, An LJ (2000) Mathematical modeling of kinetics and research on multiplicity of glycerol bioconversion to 1,3-propanediol. J Dalian Univ Technol 40:428–433

    CAS  Google Scholar 

  10. Sun YQ, Qi WT, Teng H, Xiu ZL, Zeng AP (2008) Mathematical modeling of glycerol fermentation by Klebsiella pneumoniae: concerning enzyme-catalytic reductive pathway and transport of glycerol and 1,3-propanediol across cell membrane. Biochem Eng J 38:22–32

    Article  CAS  Google Scholar 

  11. Yuan JL, Zhu X, Zhang X, Yin HC, Feng EM, Xiu ZL (2014) Robust identification of enzymatic nonlinear dynamical systems for 1, 3-propanediol transport mechanisms in microbial batch culture. Appl Math Comput 232:150–163

    Google Scholar 

  12. Guo YJ, Feng EM, Wang L, Xiu ZL (2014) Complex metabolic network of 1,3-propanediol transport mechanisms and its system identification via biological robustness. Bioprocess Biosyst Eng 37:677–686

    Article  CAS  Google Scholar 

  13. Zhang QR, Teng H, Sun YQ, Xiu ZL (2007) Metabolic flux analysis of bioconversion of glycerol into 1,3-propanediol by Klebsiella pneumoniae. In: 2007 1st international conference on bioinformatics and biomedical engineering, July ICBBE 6, 2007 July 8, 2007, IEEE, Wuhan, pp 1269–1272

  14. Zhang QR, Teng H, Sun YQ, Xiu ZL, Zeng AP (2008) Metabolic flux and robustness analysis of glycerol metabolism in Klebsiella pneumoniae. Bioprocess Biosyst Eng 31:127–135

    Article  CAS  Google Scholar 

  15. Zhang QR, Xiu ZL (2009) Metabolic pathway analysis of glycerol metabolism in Klebsiella pneumoniae incorporating oxygen regulatory system. Biotechnol Prog 25:103–115

    Article  Google Scholar 

  16. Xu GX, Li CX (2017) Identifying the shared metabolic objectives of glycerol bioconversion in Klebsiella pneumoniae under different culture conditions. J Biotechnol 248:59–68

    Article  CAS  Google Scholar 

  17. Feist AM, Herrgard MJ, Thiele I, Reed JL, Palsson BO (2009) Reconstruction of biochemical networks in microorganisms. Nat Rev Microbiol 7:129–143

    Article  CAS  Google Scholar 

  18. Yilmaz LS, Walhout AJM (2017) Metabolic network modeling with model organisms. Curr Opin Chem Biol 36:32–39

    Article  CAS  Google Scholar 

  19. Dai Z, Locasale JW (2017) Understanding metabolism with flux analysis: From theory to application. Metab Eng 43:94–102

    Article  CAS  Google Scholar 

  20. Chen P-W, Theisen MK, Liao JC (2017) Metabolic systems modeling for cell factories improvement. Curr Opin Biotechnol 46:114–119

    Article  CAS  Google Scholar 

  21. Palsson B (2015) Systems biology: constraint-based reconstruction and analysis. Cambridge University Press, Cambridge

    Book  Google Scholar 

  22. Mahadevan R, Edwards JS, Doyle FJ (2002) Dynamic flux balance analysis of diauxic growth in Escherichia coli. Biophys J 83:1331–1340

    Article  CAS  Google Scholar 

  23. Feng X, Xu Y, Chen Y, Tang YJ (2012) Integrating flux balance analysis into kinetic models to decipher the dynamic metabolism of Shewanella oneidensis MR-1. PLoS Comp Biol. https://doi.org/10.1371/journal.pcbi.1002376

    Article  Google Scholar 

  24. Sánchez BJ, Pérez-Correa JR, Agosin E (2014) Construction of robust dynamic genome-scale metabolic model structures of Saccharomyces cerevisiae through iterative re-parameterization. Metab Eng 25:159–173

    Article  Google Scholar 

  25. Nikdel A, Braatz RD, Budman HM (2018) A systematic approach for finding the objective function and active constraints for dynamic flux balance analysis. Bioprocess Biosyst Eng 41:641–655

    Article  CAS  Google Scholar 

  26. Orth JD, Thiele I, Palsson BO (2010) What is flux balance analysis? Nat Biotechnol 28:245–248

    Article  CAS  Google Scholar 

  27. Feist AM, Palsson BO (2010) The biomass objective function. Curr Opin Microbiol 13:344–349

    Article  CAS  Google Scholar 

  28. Liao YC, Huang TW, Chen FC, Charusanti P, Hong JSJ, Chang HY, Tsai SF, Palsson BO, Hsiung CA (2011) An experimentally validated genome-scale metabolic reconstruction of Klebsiella pneumoniae MGH 78578, iYL1228. J Bacteriol 193:1710–1717

    Article  CAS  Google Scholar 

  29. Saitua F, Torres P, Pérez-Correa JR, Agosin E (2017) Dynamic genome-scale metabolic modeling of the yeast Pichia pastoris. BMC Syst Biol 11:27

    Article  Google Scholar 

  30. Sun J, van den Heuvel J, Soucaille P, Qu Y, Zeng AP (2003) Comparative genomic analysis of dha regulon and related genes for anaerobic glycerol metabolism in bacteria. Biotechnol Prog 19:263–272

    Article  CAS  Google Scholar 

  31. Schirch V, Szebenyi DM (2005) Serine hydroxymethyltransferase revisited. Curr Opin Chem Biol 9:482–487

    Article  CAS  Google Scholar 

  32. Lu XY, Ren SL, Lu JZ, Zong H, Song J, Zhuge B (2018) Enhanced 1,3-propanediol production in Klebsiella pneumoniae by a combined strategy of strengthening the TCA cycle and weakening the glucose effect. J Appl Microbiol 124:682–690

    Article  CAS  Google Scholar 

  33. Amador-Noguez D, Feng X-J, Fan J, Roquet N, Rabitz H, Rabinowitz JD (2010) Systems-level metabolic flux profiling elucidates a complete, bifurcated tricarboxylic acid cycle in Clostridium acetobutylicum. J Bacteriol 192:4452–4461

    Article  CAS  Google Scholar 

  34. Zhou Y, Pijuan M, Zeng RJ, Yuan Z (2009) Involvement of the tca cycle in the anaerobic metabolism of polyphosphate accumulating organisms (PAOs). Water Res 43:1330–1340

    Article  CAS  Google Scholar 

  35. Kajiura H, Mori K, Tobimatsu T, Toraya T (2001) Characterization and mechanism of action of a reactivating factor for adenosylcobalamin-dependent glycerol dehydratase. J Biol Chem 276:36514–36519

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant no. 21476042).

Author information

Authors and Affiliations

  1. School of Life Science and Biotechnology, Dalian University of Technology, 2 Linggong Road, Dalian, 116024, People’s Republic of China

    Duo-Tao Pan, Xu-Dong Wang & Zhi-Long Xiu

  2. Chemical Control Technology Key Laboratory of Liaoning Province, Shenyang University of Chemical Technology, Shenyang, 110142, People’s Republic of China

    Duo-Tao Pan, Hong-Yan Shi & De-Cheng Yuan

  3. Institute of Information and Engineering, Shenyang University of Chemical and Technology, Shenyang, 110142, People’s Republic of China

    Duo-Tao Pan, Hong-Yan Shi & De-Cheng Yuan

Authors
  1. Duo-Tao Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xu-Dong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hong-Yan Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. De-Cheng Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhi-Long Xiu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhi-Long Xiu.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal rights statement

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

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (XLS 813 KB)

Supplementary material 2 (DOC 285 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pan, DT., Wang, XD., Shi, HY. et al. Dynamic flux balance analysis for microbial conversion of glycerol into 1,3-propanediol by Klebsiella pneumoniae. Bioprocess Biosyst Eng 41, 1793–1805 (2018). https://doi.org/10.1007/s00449-018-2002-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00449-018-2002-4

Keywords

Search

Navigation