Abstract

Developing a common medication strategy for disease control and management could be greatly beneficial. Investigating the differences between diseased and healthy states using differentially expressed genes aids in understanding disease pathophysiology and enables the exploration of protein-drug interactions. This study aimed to find the most common genes in diarrhea-causing bacteria such as Salmonella enterica serovar Typhimurium, Campylobacter jejuni, Escherichia coli, Shigella dysenteriae (CESS) to find new drugs. Thus, differential gene expression datasets of CESS were screened through computational algorithms and programming. Subsequently, hub and common genes were prioritized from the analysis of extensive protein–protein interactions. Binding predictions were performed to identify the common potential therapeutic targets of CESS. We identified a total of 827 dysregulated genes that are highly linked to CESS. Notably, no common gene interaction was found among all CESS bacteria, but we identified 3 common genes in both Salmonella-Escherichia and Escherichia-Campylobacter infections. Later, out of 73 protein complexes, molecular simulations confirmed 5 therapeutic candidates from the CESS. We have developed a new pipeline for identifying therapeutic targets for a common medication strategy against CESS. However, further wet-lab validation is needed to confirm their effectiveness.

Details

Title
Pathogen-driven gene expression patterns lead to a novel approach to the identification of common therapeutic targets
Author
Hossain, Mohammad Uzzal 1 ; Ferdous, Nadim 2 ; Reza, Mahjerin Nasrin 2 ; Ahammad, Ishtiaque 3 ; Tiernan, Zachary 4 ; Wang, Yi 4 ; O’Hanlon, Fergus 5 ; Wu, Zijia 6 ; Sarker, Shishir 7 ; Mohiuddin, A. K. M. 2 ; Das, Keshob Chandra 8 ; Keya, Chaman Ara 9 ; Salimullah, Md. 10 

 University of Oxford, Department of Pharmacology, Medical Sciences Division, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948); National Institute of Biotechnology, Bioinformatics Division, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh (GRID:grid.4991.5) 
 Mawlana Bhashani Science and Technology University, Department of Biotechnology and Genetic Engineering, Santosh, Tangail, Bangladesh (GRID:grid.443019.b) (ISNI:0000 0004 0479 1356) 
 National Institute of Biotechnology, Bioinformatics Division, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh (GRID:grid.443019.b) 
 University of Oxford, Department of Pharmacology, Medical Sciences Division, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948) 
 University of Oxford, Mathematical Institute, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948) 
 University of Oxford, Department of Chemistry, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948) 
 Jagannath University, Department of Microbiology, Dhaka, Bangladesh (GRID:grid.443016.4) (ISNI:0000 0004 4684 0582) 
 National Institute of Biotechnology, Molecular Biotechnology Division, Ministry of Science and Technology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh (GRID:grid.443019.b) 
 North South University, Department of Biochemistry and Microbiology, Dhaka, Bangladesh (GRID:grid.443020.1) (ISNI:0000 0001 2295 3329) 
10  National Institute of Biotechnology, Molecular Biotechnology Division, Ministry of Science and Technology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh (GRID:grid.443020.1) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2747147284
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.