BACK TO CONTENTS   |    PDF   |   


Title

Analysis of glycoside hydrolases from oat (Avena sativa) seedling extract

Authors

Nihed Ben Halima*

 

Affiliation

Faculty of Medicine of Sfax, University of Sfax, Sfax-Tunisia

 

Email

Dr. Nihed Ben Halima - Phone: 00216 26 06 19 87; E-mails: nihedbenhalima@gmail.com; nihed.benhalima@medecinesfax.org;*Corresponding author

 

Article Type

Research Article

 

Date

Received April 12, 2019; Revised October 7, 2019; Accepted October 12, 2019; Published October 15, 2019

 

Abstract

The abundance and the diversity of oligo- and polysaccharides provide a wide range of biological roles attributed either to these carbohydrates or to their relevant enzymes, i.e., the glycoside hydrolases (GHs). The biocatalysis by these families of enzymes is highly attractive for the generation of products used in potential applications, e.g., pharmaceuticals and food industries. It is thus very important to extract and characterize such enzymes, particularly from plant tissues. In this study, we characterized novel sequences of class I chitinases from seedlings extract of the common oat (Avena sativa L.) using proteomics and sequence-structure-function analysis. These
enzymes, which belong to the GH19 family of protein, were extracted from oat and identified using SDS-PAGE, trypsin digestion, LC-MSMS, and sequence-structure-function analysis. The amino acid sequences of the oat tryptic peptides were used to identify cDNAs from the Avena sativa databases of the expressed sequence tags (ESTs) and transcriptome shotgun assembly (TSA). Based upon the Avena sativa sequences of ESTs and TSA, at least 4 predicted genes that encoded oat class I chitinases were identified and reported. The structural characterization of the oat sequences of chitinases provided valuable insights to the context.

 

Keywords

Avena sativa; Glycoside hydrolases; GH19; Functional proteomics; Mass spectrometry; Bioinformatics analysis.

 

Citation

Ben Halima, Bioinformation 15(9): 678-688 (2019)

 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.