Skip to main content

Advertisement

Log in

Studies on process optimization methods for rapamycin production using Streptomyces hygroscopicus ATCC 29253

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

Abstract

Rapamycin is a high-value product finding immense use as a drug, in organ transplantation, and as a potential immunosuppressant. Optimization of fermentation parameters of rapamycin production by Streptomyces hygroscopicus NRRL 5491 has been carried out. The low titer value of rapamycin in the original producer strain limits its applicability at industrial level. This study aims at improving the production of rapamycin by optimizing the nutrient requirements. Addition of l-lysine increased the production of rapamycin up to a significant level which supports the fact that it acts as precursor for rapamycin production, as found in previous studies. Effect of optimized medium on the Streptomyces growth rate as well as rapamycin production has been studied. The optimization study incorporates one at a time parameter optimization studies followed by tool-based hybrid methodology. This methodology includes the Plackett–Burman design (PBD) method, artificial neural networks (ANN), and genetic algorithms (GA). PBD screened mannose, soyabean meal, and l-lysine concentrations as significant factors for rapamycin production. ANN was used to construct rapamycin production model. This strategy has led to a significant increase of rapamycin production up to 320.89 mg/L at GA optimized concentrations of 25.47, 15.39, and 17.48 g/L for mannose, soyabean meal, and l-lysine, respectively. The present study must find its application in scale-up study for industrial level production of rapamycin.

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

Access this article

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

Similar content being viewed by others

References

  1. Vezina C, Kudelski A, Sehgal SN (1975) Rapamycin (AY-22,989), a new antifungal antibiotic. J Antibiot 28:721–726

    Article  CAS  Google Scholar 

  2. Martel RR, Klicius J, Galet S (1977) Inhibition of the immune response by rapamycin, a new antifungal antibiotic. Can J Physiol Pharmacol 55:48–51

    Article  CAS  Google Scholar 

  3. Durous J, Suffness M (1981) Cancer Treat Rev 8:63–69

    Article  Google Scholar 

  4. Kojima I, Cheng YR, Mohan V, Demain AL (1995) Carbon source nutrition of rapamycin biosynthesis by Streptomyces hygroscopicus. J Ind Microbiol 14:436–439

    Article  CAS  Google Scholar 

  5. Gallo R, Padurean A, Jayaraman T, Marx S, Roque M, Adelman S, Chesebro J, Fallon J, Fuster V, Marks A, Badimon JJ (1999) Inhibition of intimal thickening after balloon angioplasty in porcine coronary arteries by targeting regulators of the cell cycle. Circulation 27:2164–2170

    Article  Google Scholar 

  6. Wyzgal J, Paczek L, Senatorski G, Zygier J, Rowinski W, Szmidt J, Perkowska A (2002) Sirolimus rescue treatment in calcineurin-inhibitor nephrotoxicity after kidney transplantation. Transplant Proc 34:3185–3187

    Article  CAS  Google Scholar 

  7. Hetzel R, Klein B, Brause M, Westhoff A, Willers R, Sandmann W, Grabensee B (2002) Risk factors for delayed graft function after renal transplantation and their significance for long-term clinical outcome. Transpl Int 15:10–16

    Article  Google Scholar 

  8. Cheng YR, Fang A, Demain AL (1995) Effect of amino acids on rapamycin biosynthesis by Streptomyces hygroscopicus. Appl Microbiol Biotechnol 43:1096–1098

    Article  CAS  Google Scholar 

  9. Sehgal SN (1993) Immunosuppressive profile of rapamycin. Ann NY Acad Sci 696:1–8

    Article  CAS  Google Scholar 

  10. Gonzalez R, Lakhdar B, Redon P, Potaux L, Cambar J, Aparicio M (1990) Demonstration of direct vasoconstrictive effect of cyclosporin on glomeruli isolated from human kidney. C R Acad Sci III 311:109–114

    CAS  Google Scholar 

  11. Cortes J, Haydock SF, Roberts GA, Bevitt DJ, Leadlay PF (1990) An unusually large multifunctional polypeptide in the erythromycin producing polyketide synthase of Saccharopolyspora erythraea. Nature 348:176–178

    Article  CAS  Google Scholar 

  12. Donadio S, Staver MJ, McAlpine JB, Swanson SJ, Katz L (1991) Modular organization of genes required for complex polyketide biosynthesis. Science 252:675–679

    Article  CAS  Google Scholar 

  13. Paiva NL, Demain AL, Roberts MF (1993) The immediate precursor of the nitrogen-containing ring of rapamycin is free pipecolic acid. Enzym Microb Technol 15:581–585

    Article  CAS  Google Scholar 

  14. Sehgal SN, Baker H, Vezina C (1975) Rapamycin (AY-22,989), a new antifungal antibiotic II. Fermentation, isolation and characterization. J Antibiot 28:727–732

    Article  CAS  Google Scholar 

  15. Sallam LAR, El-Refai AF, Osman ME, Hamdy AA, Ahmed EM, Mohamed MA (2010) Some Physiological factors affecting rapamycin production by Streptomyces hygroscopicus ATCC 29253. J. Am Sci 6:188–194

    Google Scholar 

  16. Lee MS, Kojima I, Demain AL (1997) Effect of nitrogen source on biosynthesis of rapamycin by Streptomyces hygroscopicus. J Ind Microbiol Biotechnol 19:83–86

    Article  CAS  Google Scholar 

  17. Chen Y, Krol J, Sterkin V, Fan W, Yan X, Huang W, Cino J, Julien C (1999) New process control strategy used in a rapamycin fermentation. Process Biochem 34:383–389

    Article  CAS  Google Scholar 

  18. Xu ZN, Shen WH, Chen XY, Lin JP, Cen PL (2005) A high-throughput method for screening of rapamycin-producing strains of Streptomyces hygroscopicus by cultivation in 96-well microtiter plates. Biotechnol Lett 27(15):1135–1140

    Article  CAS  Google Scholar 

  19. Chen X, Wei P, Fan L, Yang D, Zhu X, Shen W, Xu Z, Cen P (2009) Generation of high-yield rapamycin-producing strains through protoplasts-related techniques. Appl Microbiol Biotechnol 83:507–512

    Article  CAS  Google Scholar 

  20. Chen Y, Krol J, Huang W, Cino J, Vyas R, Mirro R, Vaillancourt B (2008) DCO2 on-line measurement used in rapamycin fed-batch fermentation process. Process Biochem 43:351–355

    Article  CAS  Google Scholar 

  21. Zhu X, Zhang W, Chen X, Wu H, Duan Y, Xu Z (2010) Generation of high rapamycin producing strain via rational metabolic pathway-based mutagenesis and further titer improvement with fed-batch bioprocess optimization. Biotechnol Bioeng 107:506–515

    Article  CAS  Google Scholar 

  22. Fisher S, Sonnenshein A (1991) Control of carbon and nitrogen metabolism in Bacillus subtilis. Annu Rev Microbiol 45:107–135

    Article  CAS  Google Scholar 

  23. Vilches C, Mendez C, Hardisson C, Salas JA (1990) Biosynthesis of oleandomycin by Streptomyces antibioticus: influence of nutritional conditions and development of resistance. J Gen Microbiol 136:1447–1454

    Article  CAS  Google Scholar 

  24. Plackett RL, Burman JP (1946) The design of optimum multifactorial experiments. Biometrika 33:305–325

    Article  Google Scholar 

  25. Haaland PD (1989) Experimental design in biotechnology. Marcel Dekker, NY

    Google Scholar 

  26. Nandi S, Ghosh S, Tambe SS, Kulkarni BD (2001) Artificial neural-network-assisted stochastic process optimization strategies. AIChE J 47:126–141

    Article  CAS  Google Scholar 

  27. Michalewicz Z (1994) Genetic algorithms + data structures = evolution programs, 2nd edn. Springer, New York

    Google Scholar 

  28. Desai KM, Akolkar SK, Badhe YP, Tambe SS, Lele SS (2006) Optimization of fermentation media for exopolysaccharide production from Lactobacillus plantarum using artificial intelligence-based techniques. Process Biochem 41:1842–1848

    Article  CAS  Google Scholar 

  29. Martin JF, Demain AL (1980) Control of antibiotic biosynthesis. Microbiol Rev 44:230–251

    CAS  Google Scholar 

  30. Kalil SJ, Maugeri F, Rodrigues MI (2000) Response surface analysis and simulation as a tool for bioprocess design and optimization. Process Biochem 35:539–550

    Article  CAS  Google Scholar 

  31. Analytical Methods Committee, AMCTB No 55 (2013) Experimental design and optimisation (4): Plackett–Burman designs. Anal Methods 5:1901–1903

    Article  CAS  Google Scholar 

  32. Soliman NA, Mahmoud MB, Fattah A (2005) Polyglutamic acid production by Bacillus sp. SAB-26: application of Plackett–Burman experimental design to evaluate culture requirements. Appl Microbiol Biotechnol 69:259–267

    Article  CAS  Google Scholar 

  33. Boonkerda S, Detaeverniera MR, Heydenb YV, Vindevogela J, Michottea Y (1996) Determination of the enantiomeric purity of dexfenfluramine by capillary electrophoresis: use of a Plackett–Burman design for the optimization of the separation. J Chromatogr A 736:281–289

    Article  Google Scholar 

  34. Pardeep Kumar, Satyanarayana T (2007) Optimization of culture variables for improving glucoamylase production by alginate-entrapped Thermomucorindicae-seudaticae using statistical methods. Bioresour Technol 98:1252–1259

    Article  CAS  Google Scholar 

  35. Smith KA, Gupta J (2002) Neural networks in business: techniques and applications. Idea Group, London

    Google Scholar 

  36. Xu M, Zeng G, Xu X, Huang G, Jiang R, Sun W (2006) Application of Bayesian regularized BP neural network model for trend analysis, acidity and chemical composition of precipitation in North Carolina. Water Air Soil Pollut 172:167–184

    Article  CAS  Google Scholar 

  37. Freyer S, Weuster-Botz D, Wandery C (1992) Medium optimisation using genetic algorithms. J Bioeng 8:16–25

    CAS  Google Scholar 

  38. Cromwell GL (1999) Soybean meal—the “gold standard” The farmer’s pride. KPPA News 1:20

    Google Scholar 

  39. Kuscer E, Coates N, Challis I, Gregory M, Wilkinson B, Sheridan R, Petkovic H (2007) Roles of rapH and rapG in positive regulation of rapamycin biosynthesis in Streptomyces hygroscopicus. J Bacteriol 189:4756–4763

    Article  CAS  Google Scholar 

  40. Yen HW, Hsiao PH, Chen LJ (2013) The enhancement of rapamycin production using Streptomyces hygroscopicus through a simple pH-shifted control. J Taiwan Inst Chem Eng 44:743–747

    Article  CAS  Google Scholar 

  41. Khuri AI, Cornell JA (1987) Response surfaces: design and analysis. Marcel Decker, New York

    Google Scholar 

  42. Miller GL (1959) Use of Dinitrosalicylic acid reagent for determination of reducing sugar. Anal Chem 31:426–428

    Article  CAS  Google Scholar 

  43. Gesheva V, Ivanova V, Gesheva R (2005) Effects of nutrients on the production of AK-111-81 macrolide antibiotic by Streptomyces hygroscopicus. Microbiol Res 160:243–248

    Article  CAS  Google Scholar 

  44. Sujatha P, Bapi Raju KVVSN, Ramana T (2005) Studies on a new marine Streptomycete BT-408 producing polyketide antibiotic SBR-22 effective against methicillin resistant. Staphylococcus aureus 160:119–126

    CAS  Google Scholar 

Download references

Acknowledgments

The authors would like to acknowledge National Centre for Agricultural Utilization Research (NRRL), USA, for providing lyophilized culture of S. hygroscopicus ATCC 29253.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pradeep Srivastava.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sinha, R., Singh, S. & Srivastava, P. Studies on process optimization methods for rapamycin production using Streptomyces hygroscopicus ATCC 29253. Bioprocess Biosyst Eng 37, 829–840 (2014). https://doi.org/10.1007/s00449-013-1051-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00449-013-1051-y

Keywords

Navigation