Skip to main content
Applied Biological Chemistry
Download PDF
  • Article
  • Published:

Optimization for the enhanced production of avermectin B1b from Streptomyces avermitilis DSM 41445 using artificial neural network

Journal of the Korean Society for Applied Biological Chemistry volume 57, pages 677–683 (2014)Cite this article

Abstract

Avermectin is an environment friendly bio-insecticide. Optimization of the culture conditions for avermectin B1b production has not been carried out before using Artificial Neural Network (ANN) method. The present work is therefore conducted to optimize some important factors including yeast extract, MgSO4.7H2O, and temperature for the avermectin B1b production using ANN methodology from Streptomyces avermitilis DSM 41445. The optimum levels for the yeast extract, MgSO4.7H–O, and temperature were 16.0 (g/L), 5.0 (g/L) and 32°C respectively. Maximum effect was observed by yeast extract. Avermectin B1b yield was increased up to 150% after optimization. ANN was found to be a powerful technique for the optimization and prediction of avermectin B1b production from Streptomyces avermitilis DSM 41445.

References

  • Azaman S, Ramakrishnan N, Tan J, Rahim R, Abdullah M, and Ariff A. (2010) Optimization of an induction strategy for improving interferonalpha2b production in the periplasm of Escherichia coli using response surface methodology. Biotechnol Appl Biochem 56, 141–50.

    Article  CAS  Google Scholar 

  • Burg RW, Miller BM, Baker EE, Birnbaum J, Currie SA, Hartman R, Kong YL, Monaghan RL, Olson G, and Putter I. (1979) Avermectins, new family of potent anthelmintic agents: producing organism and fermentation. Antimicrob Agents Chemother 15, 361–7.

    Article  CAS  Google Scholar 

  • Cheema JJS, Sankpal NV, Tambe SS, and Kulkarni BD. (2002) Genetic programming assisted stochastic optimization strategies for optimization of glucose to gluconic acid fermentation. Biotechnol Prog 18, 1356–65.

    Article  CAS  Google Scholar 

  • Chen XC, Bai JX, Cao JM, Li ZJ, Xiong J, Zhang L, Hong Y, and Ying HJ. (2009) Medium optimization for the production of cyclic adenosine 3, 5- monophosphate by Microbacterium sp. no. 205 using response surface methodology. Bioresour Technol 100, 919–24.

    Article  CAS  Google Scholar 

  • Chen Z, Wen J, Song Y, Wen Y, and Li JL. (2007) Enhancement and selective production of avermectin B by recombinants of Streptomyces avermitilis via intraspecific protoplast fusion. Chinese Sci Bull 52, 616–22.

    Article  CAS  Google Scholar 

  • Curdova E, Jechova V, Zima J, and Vanek Z. (1989) The effect of inorganic phosphate on the production of avermectin in Streptomyces avermitilis. J Basic Microbiol 29, 341–6.

    Article  CAS  Google Scholar 

  • Dasari VRRK, Donthireddy SRR, Nikku MY, and Garapati HR. (2009) Optimization of medium constituents for cephalosporin C production using response surface methodology and artificial neural networks. J Biochem Technol 1, 69–74.

    CAS  Google Scholar 

  • Da-silva I, Martins M, Carvalho C, De-azevedo J, and Procopio REL. (2012) The effect of varying culture conditions on the production of antibiotics by Streptomyces spp. iIsolated from the amazonian soil. Ferment Technol 1(3).

    Google Scholar 

  • Dey G, Mitra A, Banerjee R, and Maiti B. (2001) Enhanced production of amylase by optimization of nutritional constituents using response surface methodology. Biochem Eng J 7, 227–31.

    Article  CAS  Google Scholar 

  • Dutta JR, Dutta PK, and Banerjee R. (2004) Optimization of culture parameters for extracellular protease production from a newly isolated Pseudomonas sp. using response surface and artificial neural network models. Proc Biochem 39, 2193–8.

    Article  CAS  Google Scholar 

  • Elibol M. (2004) Optimization of medium composition for actinorhodin production by Streptomyces coelicolor A3. (2) with response surface methodology. Proc Biochem 39, 1057–62.

    Article  CAS  Google Scholar 

  • Hill T and Lewicki P. (2006) Statistics: Methods and applications: A comprehensive reference for science, industry, and data mining: StatSoft, Inc., USA.

    Google Scholar 

  • Hong G, Mei L, Jintao L, Huanqin D, Xianlong Z, Xiangyang L, Ying Z, Wenquan Z, and Lixin Z. (2009) Medium optimization for the production of avermectin B1a by Streptomyces avermitilis 14-12A using response surface methodology. Bioresour Technol 100, 4012–6.

    Article  Google Scholar 

  • Hornik K, Stinchcombe M, and White H. (1989) Multilayer feedforward networks are universal approximators. Neu Net Arch 2, 359–66.

    Article  Google Scholar 

  • Ikeda H and Omura S. (1997) Avermectin biosynthesis. Chem Rev 97, 259–609.

    Google Scholar 

  • Lazim H, Mankai H, Slama N, Barkallah I, and Limam F. (2009) Production and optimization of thermophilic alkaline protease in solid-state fermentation by Streptomyces sp. CN902. J Ind Microbiol Biotechnol 36, 531–7.

    Article  CAS  Google Scholar 

  • Liao Y, Wei ZH, Bai L, Deng Z, and Zhong JJ. (2009) Effect of fermentation temperature on validamycin A production by Streptomyces hygroscopicus 5008. J Biotechnol 142, 271–4.

    Article  CAS  Google Scholar 

  • Lou W and Nakai S. (2001) Application of artificial neural networks for predicting the thermal inactivation of bacteria: a combined effect of temperature, pH and water activity. Food Res Int 34, 573–9.

    Article  Google Scholar 

  • Nelofer R, Ramanan R, Rahman R, Basri M, and Ariff A (2011) Sequential optimization of production of a thermostable and organic solvent tolerant lipase by recombinant Escherichia coli. Ann of Microbiol 61, 535–44.

    Article  CAS  Google Scholar 

  • Nelofer R, Ramanan RN, Rahman RNZRA, Basri M, and Ariff AB. (2012) Comparison of the estimation capabilities of response surface methodology and artificial neural network for the optimization of recombinant lipase production by E. coli BL21. J Indust Microbio Biotech 39, 243–54.

    Article  CAS  Google Scholar 

  • Noorossana R, Davanloo TS, and Saghaei A. (2009) An artificial neural network approach to multiple-response optimization. Inter J Adva Manufac Tech 40, 1227–38.

    Article  Google Scholar 

  • Ortiz F, Simpson JR, Pignatiello JJ, and Heredia-langner A. (2004) A genetic algorithm approach to multiple-response optimization. J Quality Technol 36, 432–50.

    Google Scholar 

  • Oskay M. (2011) Effects of some environmental conditions on biomass and antimicrobial metabolite production by Streptomyces sp., KGG32. Int J Agric Biol 13, 317–24.

    CAS  Google Scholar 

  • Rao KJ, Kim CH, and Rhee SK. (2000) Statistical optimization of medium for the production of recombinant hirudin from Saccharomyces cerevisiae using response surface methodology. Process Biochemistry 35, 639–47.

    Article  CAS  Google Scholar 

  • Stanbury PF. (2000) In Principles of Fermentation Technology. (2nd ed). Oxford; Melbourn: Butterworth-Heinemann, UK.

    Google Scholar 

  • Suutari M, Lignell U, Hyvarinen A, Nevalainen A. (2002) Media for cultivation of indoor streptomycetes. J Microbiol Methods 51, 411–6.

    Article  CAS  Google Scholar 

  • Tuncer M, Kuru A, Isikli M, Sahin N, and Celenk F. (2004) Optimization of extracellular endoxylanase, endoglucanase and peroxidase production by Streptomyces sp. F2621 isolated in Turkey. J Appl Microbiol 97, 783–91.

    Article  CAS  Google Scholar 

  • Viana D, Carneiro-Cunha M, Araujo J, Barros-Neto B, Lima-Filho J, Converti A, Pessoa-Jãnior A, and Porto ALF. (2010) Screening of variables influencing the clavulanic acid production by Streptomyces DAUFPE 3060 strain. Appl Biochem Biotechnol 160, 1797–807.

    Article  CAS  Google Scholar 

  • Xiong ZQ, Tu XR, and Tu GQ. (2008) Optimization of medium composition for actinomycin X2 production by Streptomyces spp JAU4234 using response surface methodology. J Indus Micro Biotech 35, 729–34.

    Article  CAS  Google Scholar 

  • Zhinan X and Peilin C. (1999) Enhanced production of avermectin B1a by medium optimization and glucose feeding with Streptomyces avermilitis. Bioproc Biosystems Eng 20, 67–71.

    CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Chemistry, Government College University, Lahore, Pakistan

    Samia Siddique & Ahmad Adnan

  2. Laboratories Complex, Food and Biotechnology Research Centre, PCSIR, 54600, Lahore, Pakistan

    Rubina Nelofer & Quratulain Syed

  3. Office of Research, Innovation and Commercialization, Comsats Institute of Information and Technology, ChakShahzad, Park Road, Islamabad, Pakistan

    Fahim Ashraf Qureshi

Authors
  1. Samia Siddique
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rubina Nelofer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Quratulain Syed
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ahmad Adnan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Fahim Ashraf Qureshi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Samia Siddique.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Siddique, S., Nelofer, R., Syed, Q. et al. Optimization for the enhanced production of avermectin B1b from Streptomyces avermitilis DSM 41445 using artificial neural network. J Korean Soc Appl Biol Chem 57, 677–683 (2014). https://doi.org/10.1007/s13765-014-4194-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13765-014-4194-x

Keywords