Evaluation of cellular response to Clostridium difficile toxin-A: a network analysis
Gastroenterology and Hepatology from Bed to Bench,
Vol. 15 No. 4 (2022),
3 October 2022
https://doi.org/10.22037/ghfbb.v15i4.2634
Abstract
Aim: The current study aimed to determine crucial genes targeted by toxin-A through network analysis.
Background: Clostridium difficile (C difficile) produces toxin-A and toxin-B and is known as a risk factor for hospital infection, especially after broad spectrum antibiotic therapy. Bioinformatics findings have led to the introduction of a set of genes and biological terms that are targeted by toxin-B in colon epithelia.
Methods: The significant differentially expressed genes (DEGs) of human intestinal Caco-2 cells treated by toxin-A versus control were retrieved from gene expression omnibus (GEO). The queried DEGs were analyzed using by protein-protein interaction (PPI) network analysis through STRING database and Cytoscape software v.3.7.2.
Results: Among 157 significant DEGs, JUN, VEGFA, CDKN1A, ATF3, SNAI1, DUSP1, HSPB1, MCL1, KLF4, FOSL1, HSPA1A, and SQSTM1 were determined as hubs and JUN, DUSP1, DUSP5, EZR, MAP1LC3B, and SQSTM1 were highlighted as bottlenecks.
Conclusion: JUN, DUSP1, and SQSTM1 are possible drug targets to prevent and treat C difficile infection.
- Clostridium difficile; Infection; Drug target; Network analysis; Treatment
How to Cite
References
Kelly CP, LaMont JT. Clostridium difficile infection. Annu Rev Med 1998;49:375.
Voth DE, Ballard JD. Clostridium difficile toxins: mechanism of action and role in disease. Clin Microbiol Rev 2005;18:247-63.
Czepiel J, Dróżdż M, Pituch H, Kuijper EJ, Perucki W, Mielimonka A, et al. Clostridium difficile infection. Eur J Clin Microbiol Infect Dis 2019;38:1211-21.
Maaß S, Otto A, Albrecht D, Riedel K, Trautwein-Schult A, Becher D. Proteomic signatures of Clostridium difficile stressed with metronidazole, vancomycin, or fidaxomicin. Cells 2018;7:213.
Janezic S, Garneau JR, Monot M. Comparative genomics of Clostridium difficile. Adv Exp Med Biol 2018;1050:59-75.
Gao Y, Gao W, Cheng J, Ma L, Su J. Identification of the role of toxin B in the virulence of Clostridioides difficile based on integrated bioinformatics analyses. Int Microbiol 2020;23:575-87.
McHaney‐Lindstrom M, Hebert C, Miller H, Moffatt‐Bruce S, Root E. Network analysis of intra‐hospital transfers and hospital onset clostridium difficile infection. Health Info Libr J 2020;37:26-34.
Alhifany AA, Almutairi AR, Almangour TA, Shahbar AN, Abraham I, Alessa M, et al. Comparing the efficacy and safety of faecal microbiota transplantation with bezlotoxumab in reducing the risk of recurrent Clostridium difficile infections: a systematic review and Bayesian network meta-analysis of randomised controlled trials. BMJ Open 2019;9:031145.
Safari-Alighiarloo N, Taghizadeh M, Rezaei-Tavirani M, Goliaei B, Peyvandi AA. Protein-protein interaction networks (PPI) and complex diseases. Gastroenterol Hepatol Bed Bench 2014;7:17.
Rezaei-Tavirani M, Nejad MR, Arjmand B, Tavirani SR, Razzaghi M, Mansouri V. Fibrinogen dysregulation is a prominent process in fatal conditions of COVID-19 infection; a proteomic analysis. Arch Acad Emerg Med 2021;9.
Feng X, Wang Y, Xu L. Mechanism of the use of four chemotherapeutic drugs for intestinal metaplasia in the treatment of precancerous gastric cancer lesions based on network pharmacology and molecular docking technology. Gastroenterol Hepatol Res 2022;4:2.
Di Silvestre D, Vigani G, Mauri P, Hammadi S, Morandini P, Murgia I. Network topological analysis for the identification of novel hubs in plant nutrition. Front Plant Sci 2021;12:629013.
Kumar R, Haider S. Protein network analysis to prioritize key genes in amyotrophic lateral sclerosis. IBRO Neurosci Rep 2022;12:25-44.
Acharya D, Dutta TK. Elucidating the network features and evolutionary attributes of intra-and interspecific protein–protein interactions between human and pathogenic bacteria. Sci Rep 2021;11:1-11.
Haas Bueno R, Recamonde-Mendoza M. Meta-analysis of transcriptomic data reveals pathophysiological modules involved with atrial fibrillation. Mol Diagn Ther 2020;24:737-51.
Carillo S, Pariat M, Steff A-M, Roux P, Etienne-Julan M, Lorca T, et al. Differential sensitivity of FOS and JUN family members to calpains. Oncogene 1994;9:1679-89.
Lee JY, Park HR, Oh Y-K, Kim Y-J, Youn J, Han J-S, et al. Effects of transcription factor activator protein-1 on interleukin-8 expression and enteritis in response to Clostridium difficile toxin A. J Mol Med 2007;85:1393-404.
Li Y, Xu S, Xu Q, Chen Y. Clostridium difficile toxin B induces colonic inflammation through the TRIM46/DUSP1/MAPKs and NF-κB signalling pathway. Artif Cells, Nanomed Biotechnol 2020;48:452-62.
Hu J, Shan Y, Yang H. Clostridium difficile Toxin B: insights into its target genes. Open J Appl Sci 2022;12:368-86.
Chan H, Zhao S, Zhang L, Ho J, Leung CC, Wong WT, et al. Clostridium difficile toxin B induces autophagic cell death in colonocytes. J Cell Mol Med 2018;22:2469-77.
- Abstract Viewed: 120 times
- PDF Downloaded: 105 times