Response surface methodology-artificial neural network based optimization and strain improvement of cellulase production by Streptomyces sp.

  • Ega Soujanya Lakshmi KL University
  • Manda Rama Narasinga Rao KL University
  • Muddada Sudhamani KL University
Keywords: Streptomyces durhamensis, Mutagenesis, Response surface methodology, Artificial neural network, Carboxy methyl Cellulose

Abstract

ABSTRACT

Thirty seven different colonies were isolated from decomposing logs of textile industries. From among these, a thermotolerant, grampositive, filamentous soil bacteria Streptomyces durhamensis vs15 was selected and screened for cellulase production. The strain showed clear zone formation on CMC agar plate after Gram’s iodine staining.  Streptomyces durhamensis vs15 was further confirmed for cellulase production by estimating the reducing sugars through dinitrosalicylic acid (DNS) method. The activity was enhanced by sequential mutagenesis using three mutagens of ultraviolet irradiation (UV), N methyl-N’-nitro-N-nitrosoguanidine (NTG) and Ethyl methane sulphonate (EMS). After mutagenesis, the cellulase activity of GC23 (mutant) was improved to 1.86 fold compared to the wild strain (vs15). Optimal conditions for the production of cellulase by the GC 23 strain were evaluated using Response Surface Methodology (RSM) and Artificial Neural Network (ANN). Effect of pH, temperature, duration of incubation, , and substrate concentration on cellulase production were evaluated. Optimal conditions for the production of cellulase enzyme using Carboxy Methyl Cellulase as a substrate are 55 oC of temperature, pH of 5.0 and incubation for 40 h. The cellulase activity of the mutant Streptomyces durhamensis GC23 was further optimised to 2 fold of the activity of the wild type by RSM and ANN.

 

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Author Biographies

Ega Soujanya Lakshmi, KL University

Research scholar,

Department of biotechnology,

KL University,

Vaddeswaram
Guntur
pincode-522502

Manda Rama Narasinga Rao, KL University

Dr. M.Rarasinga Rao M.Tech; Ph.D

Professor

Departamento de C.S.E

KLUniversity

Vaddeswaram

Guntur pincode-522502

Muddada Sudhamani, KL University
Dr.Sudhamani,
Assistant Professor,
Dept of Biotechnology,
KL university,
Greenfields, Vijaywada-522502       Attachments area      
Published
2020-03-24
How to Cite
Ega Soujanya Lakshmi, Rao, M. R. N., & Sudhamani, M. (2020). Response surface methodology-artificial neural network based optimization and strain improvement of cellulase production by Streptomyces sp. Bioscience Journal, 36(4). https://doi.org/10.14393/BJ-v36n4a2020-48006
Section
Biological Sciences