2019, Volume 12, Issue 2, pp 184 – 191

Bioinformatics analysis of various signal peptides for periplasmic expression of parathyroid hormone in E.coli

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Authors and Affiliations

Corresponding Author: Mohammad Hosein Rezadoust, Ph.D in nanobiotechnology, Faculty of Agriculture, University of Guilan, Rasht, Iran, E-mail: Rezadoost2012@gmail.com

Abstract

Hypoparathyroidism is a rare endocrine disease which is characterized by the deficiency of serum calcium levels. RhPTH is prescribed as a therapy for the management of refractory hypoparathyroidism. The aim of this study is to investigate 32 signal peptides of gram-negative bacterial origin and evaluate their potential for efficient secretion of recombinant human PTH (1–84)In E.coli to obtain higher expression of recombinant PTH in bacterial systems by using this fusion partner. SignalP and ProtParam servers were employed to predict the presence and location of signal peptide cleavage sites in protein sequence and computation of various physical and chemical parameters of protein respectively. Also, SOLpro server was applied for prediction of the protein solubility. Then ProtComp and SecretomeP online servers were employed to determine protein location. The evaluations showed that theoretically two signal peptides Lipopolysaccharide export system protein LptA (lptA) and Periplasmic pH-dependent serine endoprotease DegQ (degQ) are the most appropriate signal peptides examined. Due to the lack of post-translational modification in PTH, its periplasmic expression has preferences. Based on the results of this study, using bioinformatics and reliable servers signal peptides with appropriate secretory potential can be obtained which lead to the highest expression level.

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About this article

PMC ID: 6685308
PubMed ID: 31406522
DOI: 10.25122/jml-2018-0049

Article Publishing Date (print): Apr-Jun 2019
Available Online: 

Journal information

ISSN Printing: 1844-122X
ISSN Online: 1844-3117
Journal Title: Journal of Medicine and Life

Copyright License: Open Access

This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited.


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