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A genome-scale metabolic model of the effect of dissolved oxygen on 1,3-propanediol fermentation by Klebsiella pneumoniae

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Abstract

Although 1,3-propanediol (1,3-PD) is usually considered an anaerobic fermentation product from glycerol by Klebsiella pneumoniae, microaerobic conditions proved to be more conducive to 1,3-PD production. In this study, a genome-scale metabolic model (GSMM) specific to K. pneumoniae KG2, a high 1.3-PD producer, was constructed. The iZY1242 model contains 2090 reactions, 1242 genes and 1433 metabolites. The model was not only able to accurately characterise cell growth, but also accurately simulate the fed-batch 1,3-PD fermentation process. Flux balance analyses by iZY1242 was performed to dissect the mechanism of stimulated 1,3-PD production under microaerobic conditions, and the maximum yield of 1,3-PD on glycerol was 0.83 mol/mol under optimal microaerobic conditions. Combined with experimental data, the iZY1242 model is a useful tool for establishing the best conditions for microaeration fermentation to produce 1,3-PD from glycerol in K. pneumoniae.

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Data availability

The data that supports the findings of this study are available in the supplementary material of this article.

References

  1. Jha V, Purohit H, Dafale NA (2021) Revealing the potential of Klebsiella pneumoniae PVN-1 for plant beneficial attributes by genome sequencing and analysis. 3 Biotech 11:473

    Article  PubMed  PubMed Central  Google Scholar 

  2. Martin RM, Bachman MA (2018) Colonization, infection, and the accessory genome of Klebsiella pneumoniae. Front Cell Infect Microbiol 8:4

    Article  PubMed  PubMed Central  Google Scholar 

  3. Kaur G, Srivastava AK, Chand S (2012) Advances in biotechnological production of 1,3-propanediol. Biochem Eng J 64:106–118

    Article  CAS  Google Scholar 

  4. Dobson R, Gray V, Rumbold K (2012) Microbial utilization of crude glycerol for the production of value-added products. J Ind Microbiol Biotechnol 39:217–226

    Article  CAS  PubMed  Google Scholar 

  5. Liu H, Xu Y, Zheng Z, Liu D (2010) 1,3-Propanediol and its copolymers: research, development and industrialization. Biotechnol J 5:1137–1148

    Article  CAS  PubMed  Google Scholar 

  6. Wang XL, Zhou JJ, Shen JT, Zheng YF, Sun YQ, Xiu ZL (2020) Sequential fed-batch fermentation of 1,3-propanediol from glycerol by Clostridium butyricum DL07. Appl Microbiol Biotechnol 104:9179–9191

    Article  CAS  PubMed  Google Scholar 

  7. Avci FG, Huccetogullari D, Azbar N (2014) The effects of cell recycling on the production of 1,3-propanediol by Klebsiella pneumoniae. Bioprocess Biosyst Eng 37:513–519

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

  9. Ju JH, Wang D, Heo SY, Kim MS, Seo JW, Kim YM, Kim DH, Kang SA, Kim CH, Oh BR (2020) Enhancement of 1,3-propanediol production from industrial by-product by Lactobacillus reuteri CH53. Microb Cell Fact 19:6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Jolly J, Hitzmann B, Ramalingam S, Ramachandran KB (2014) Biosynthesis of 1,3-propanediol from glycerol with Lactobacillus reuteri: effect of operating variables. J Biosci Bioeng 118:188–194

    Article  CAS  PubMed  Google Scholar 

  11. Jeng WY, Panjaitan NSD, Horng YT, Chung WT, Chien CC, Soo PC (2017) The negative effects of KPN00353 on glycerol kinase and microaerobic 1,3-propanediol production in Klebsiella pneumoniae. Front Microbiol 8:2441

    Article  PubMed  PubMed Central  Google Scholar 

  12. Zhu C, Fang B, Wang S (2016) Effects of culture conditions on the kinetic behavior of 1,3-propanediol fermentation by Clostridium butyricum with a kinetic model. Bioresour Technol 212:130–137

    Article  CAS  PubMed  Google Scholar 

  13. 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 

  14. Celinska E, Drozdzynska A, Jankowska M, Bialas W, Czaczyk K, Grajek W (2015) Genetic engineering to improve 1,3-propanediol production in an isolated Citrobacter freundii strain. Process Biochem 50:48–60

    Article  CAS  Google Scholar 

  15. Chen X, Xiu Z, Wang J, Zhang D, Xu P (2003) Stoichiometric analysis and experimental investigation of glycerol bioconversion to 1,3-propanediol by Klebsiella pneumoniae under microaerobic conditions. Enzyme Microb Technol 33:386–394

    Article  CAS  Google Scholar 

  16. Cheng KK, Liu HJ, Liu DH (2005) Multiple growth inhibition of Klebsiella pneumoniae in 1,3-propanediol fermentation. Biotechnol Lett 27:19–22

    Article  CAS  PubMed  Google Scholar 

  17. Huang H, Gong CS, Tsao GT (2002) Production of 1,3-propanediol by Klebsiella pneumoniae. Appl Biochem Biotechnol 98–100:687–698

    Article  PubMed  Google Scholar 

  18. Sarathy C, Breuer M, Kutmon M, Adriaens ME, Evelo CT, Arts ICW (2021) Comparison of metabolic states using genome-scale metabolic models. PLoS Comput Biol 17:e1009522

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Huang M, Zhao Y, Li R, Huang W, Chen X (2020) Improvement of l-arginine production by in silico genome-scale metabolic network model guided genetic engineering. 3 Biotech 10:126

    Article  PubMed  PubMed Central  Google Scholar 

  20. He M, Wen J, Yin Y, Wang P (2021) Metabolic engineering of Bacillus subtilis based on genome-scale metabolic model to promote fengycin production. 3 Biotech 11:448

    Article  PubMed  PubMed Central  Google Scholar 

  21. O’Brien EJ, Lerman JA, Chang RL, Hyduke DR, Palsson BO (2013) Genome-scale models of metabolism and gene expression extend and refine growth phenotype prediction. Mol Syst Biol 9:693

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Fouladiha H, Marashi SA, Torkashvand F, Mahboudi F, Lewis NE, Vaziri B (2020) A metabolic network-based approach for developing feeding strategies for CHO cells to increase monoclonal antibody production. Bioprocess Biosyst Eng 43:1381–1389

    Article  CAS  PubMed  Google Scholar 

  24. Bideaux C, Montheard J, Cameleyre X, Molina-Jouve C, Alfenore S (2016) Metabolic flux analysis model for optimizing xylose conversion into ethanol by the natural C5-fermenting yeast Candida shehatae. Appl Microbiol Biotechnol 100:1489–1499

    Article  CAS  PubMed  Google Scholar 

  25. Agren R, Otero JM, Nielsen J (2013) Genome-scale modeling enables metabolic engineering of Saccharomyces cerevisiae for succinic acid production. J Ind Microbiol Biotechnol 40:735–747

    Article  CAS  PubMed  Google Scholar 

  26. Mesquita TJB, Sargo CR, Fuzer JRN, Paredes SAH, Giordano RC, Horta ACL, Zangirolami TC (2019) Metabolic fluxes-oriented control of bioreactors: a novel approach to tune micro-aeration and substrate feeding in fermentations. Microb Cell Fact 18:150

    Article  PubMed  PubMed Central  Google Scholar 

  27. Garcia-Albornoz MA, Nielsen J (2013) Application of genome-scale metabolic models in metabolic engineering. Ind Biotechnol 9:203–214

    Article  CAS  Google Scholar 

  28. Nanda P, Patra P, Das M, Ghosh A (2020) Reconstruction and analysis of genome-scale metabolic model of weak Crabtree positive yeast Lachancea kluyveri. Sci Rep 10:16314

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Zhu C, Jiang X, Zhang Y, Lin J, Fu S, Gong H (2015) Improvement of 1,3-propanediol production in Klebsiella pneumoniae by moderate expression of puuC (encoding an aldehyde dehydrogenase). Biotechnol Lett 37:1783–1790

    Article  CAS  PubMed  Google Scholar 

  30. Cui YL, Zhou JJ, Gao LR, Zhu CQ, Jiang X, Fu SL, Gong H (2014) Utilization of excess NADH in 2,3-butanediol-deficient Klebsiella pneumoniae for 1,3-propanediol production. J Appl Microbiol 117:690–698

    Article  CAS  PubMed  Google Scholar 

  31. Liao YC, Huang TW, Chen FC, Charusanti P, Hong JS, 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  PubMed  PubMed Central  Google Scholar 

  32. Reed JL, Vo TD, Schilling CH, Palsson BO (2003) An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biol 4:R54

    Article  PubMed  PubMed Central  Google Scholar 

  33. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL (2009) BLAST+: architecture and applications. BMC Bioinform 10:421

    Article  Google Scholar 

  34. Wang H, Marcisauskas S, Sanchez BJ, Domenzain I, Hermansson D, Agren R, Nielsen J, Kerkhoven EJ (2018) RAVEN 2.0: a versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor. PLoS Comput Biol 14:1006541

    Article  Google Scholar 

  35. Henry CS, DeJongh M, Best AA, Frybarger PM, Linsay B, Stevens RL (2010) High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol 28:977–982

    Article  CAS  PubMed  Google Scholar 

  36. King ZA, Lu J, Drager A, Miller P, Federowicz S, Lerman JA, Ebrahim A, Palsson BO, Lewis NE (2016) BiGG models: a platform for integrating, standardizing and sharing genome-scale models. Nucl Acids Res 44:D515-522

    Article  CAS  PubMed  Google Scholar 

  37. Norsigian CJ, Attia H, Szubin R, Yassin AS, Palsson BO, Aziz RK, Monk JM (2019) Comparative genome-scale metabolic modeling of metallo-beta-lactamase-producing multidrug-resistant Klebsiella pneumoniae clinical isolates. Front Cell Infect Microbiol 9:161

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Henry CS, Rotman E, Lathem WW, Tyo KE, Hauser AR, Mandel MJ (2017) Generation and validation of the iKp1289 metabolic model for Klebsiella pneumoniae KPPR1. J Infect Dis 215:S37–S43

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Heirendt L, Arreckx S, Pfau T, Mendoza SN, Richelle A, Heinken A, Haraldsdottir HS, Wachowiak J, Keating SM, Vlasov V, Magnusdottir S, Ng CY, Preciat G, Zagare A, Chan SHJ, Aurich MK, Clancy CM, Modamio J, Sauls JT, Noronha A, Bordbar A, Cousins B, El Assal DC, Valcarcel LV, Apaolaza I, Ghaderi S, Ahookhosh M, Ben Guebila M, Kostromins A, Sompairac N, Le HM, Ma D, Sun YK, Wang L, Yurkovich JT, Oliveira MAP, Vuong PT, El Assal LP, Kuperstein I, Zinovyev A, Hinton HS, Bryant WA, Artacho FJA, Planes FJ, Stalidzans E, Maass A, Vempala S, Hucka M, Saunders MA, Maranas CD, Lewis NE, Sauter T, Palsson BO, Thiele I, Fleming RMT (2019) Creation and analysis of biochemical constraint-based models using the COBRA Toolbox vol 3.0. Nat Protoc 14:639–702

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. O’Brien EJ, Monk JM, Palsson BO (2015) Using genome-scale models to predict biological capabilities. Cell 161:971–987

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Shakeri-Garakani A, Brinkkotter A, Schmid K, Turgut S, Lengeler JW (2004) The genes and enzymes for the catabolism of galactitol, d-tagatose, and related carbohydrates in Klebsiella oxytoca M5a1 and other enteric bacteria display convergent evolution. Mol Genet Genomics 271:717–728

    Article  CAS  PubMed  Google Scholar 

  42. Shu HY, Fung CP, Liu YM, Wu KM, Chen YT, Li LH, Liu TT, Kirby R, Tsai SF (2009) Genetic diversity of capsular polysaccharide biosynthesis in Klebsiella pneumoniae clinical isolates. Microbiology (Reading) 155:4170–4183

    Article  CAS  PubMed  Google Scholar 

  43. Pan YJ, Lin TL, Chen CT, Chen YY, Hsieh PF, Hsu CR, Wu MC, Wang JT (2015) Genetic analysis of capsular polysaccharide synthesis gene clusters in 79 capsular types of Klebsiella spp. Sci Rep 5:15573

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Zhou X, Chu Q, Li S, Yang M, Bao Y, Zhang Y, Fu S, Gong H (2022) A new and effective genes-based method for phylogenetic analysis of Klebsiella pneumoniae. Infect Genet Evol 100:105275

    Article  CAS  PubMed  Google Scholar 

  45. Pan DT, Wang XD, Shi HY, Yuan DC, Xiu ZL (2018) Dynamic flux balance analysis for microbial conversion of glycerol into 1,3-propanediol by Klebsiella pneumoniae. Bioprocess Biosyst Eng 41:1793–1805

    Article  CAS  PubMed  Google Scholar 

  46. Sarma S, Anand A, Dubey VK, Moholkar VS (2017) Metabolic flux network analysis of hydrogen production from crude glycerol by Clostridium pasteurianum. Bioresour Technol 242:169–177

    Article  CAS  PubMed  Google Scholar 

  47. Chen X, Zhang DJ, Qi WT, Gao SJ, Xiu ZL, Xu P (2003) Microbial fed-batch production of 1,3-propanediol by Klebsiella pneumoniae under micro-aerobic conditions. Appl Microbiol Biotechnol 63:143–146

    Article  CAS  PubMed  Google Scholar 

  48. Supaporn P, Yeom SH (2018) Statistical optimization of 1,3-propanediol (1,3-PD) production from crude glycerol by considering four objectives: 1,3-PD concentration, yield, selectivity, and productivity. Appl Biochem Biotechnol 186:644–661

    Article  CAS  PubMed  Google Scholar 

  49. Cheng KK, Liu DH, Sun Y, Liu WB (2004) 1,3-Propanediol production by Klebsiella pneumoniae under different aeration strategies. Biotechnol Lett 26:911–915

    Article  CAS  PubMed  Google Scholar 

  50. Zeng AP, Biebl H, Schlieker H, Deckwer WD (1993) Pathway analysis of glycerol fermentation by Klebsiella pneumoniae: regulation of reducing equivalent balance and product formation. Enzyme Microb Technol 15:770–779

    Article  CAS  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant No. 31271862.

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Authors and Affiliations

  1. State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, People’s Republic of China

    Yang Zhang, Menglei Yang, Yangyang Bao, Weihua Tao, Jinyou Tuo, Boya Liu, Luxi Gan, Shuilin Fu & Heng Gong

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  1. Yang Zhang
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  2. Menglei Yang
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Contributions

YZ and HG conceived and designed the study. YZ constructed the model. YZ, WT and JT implemented the experiment. YZ, BL and LG collected the background information. YZ, MY, YB and SF checked the data of this study. YZ and HG drafted and edited the manuscript. All authors reviewed and approved the final manuscript.

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Correspondence to Heng Gong.

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Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file 1. Table S1

: M9 minimal medium composition in silico. (XLSX 11 KB)

Supplementary file 2. Table S2

: Shake flask culture medium composition in silico. (XLSX 11 KB)

Supplementary file 3. Table S3

: The results of Biolog Phenotypic Microarray assay. (XLSX 19 KB)

Supplementary file 4. Table S4

: Reactions and metabolites added to iZY1242 model that not present in BIGG database before. (XLSX 10 KB)

Supplementary file 5. Table S5

: The flowchart for the construction of iZY1242 model. (XLSX 15 KB)

Supplementary file 6. Data Sheet 1

: (ZIP 964KB)

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Zhang, Y., Yang, M., Bao, Y. et al. A genome-scale metabolic model of the effect of dissolved oxygen on 1,3-propanediol fermentation by Klebsiella pneumoniae. Bioprocess Biosyst Eng 46, 1319–1330 (2023). https://doi.org/10.1007/s00449-023-02899-w

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