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Article

A Bioinformatics Approach to Identifying Potential Biomarkers for Cryptosporidium parvum: A Coccidian Parasite Associated with Fetal Diarrhea

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Norwich Medical School, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich NR4 7TJ, UK
2
Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
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Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, UK
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Centre of Excellence in Bionanoscience Research, King Abdulaziz University, Jeddah 21589, Saudi Arabia
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Department of Biological Sciences, King AbdulAziz University, Jeddah 21589, Saudi Arabia
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School of Computational and Integrative Science, Jawaharlal Nehru University, New Delhi 110067, India
*
Authors to whom correspondence should be addressed.
Academic Editors: David Arranz-Solís, Yanina Paola Hecker and Valentin Pérez
Vaccines 2021, 9(12), 1427; https://doi.org/10.3390/vaccines9121427
Received: 26 September 2021 / Revised: 25 November 2021 / Accepted: 27 November 2021 / Published: 2 December 2021
(This article belongs to the Special Issue Vaccines in Farm Animals)
Cryptosporidium parvum (C. parvum) is a protozoan parasite known for cryptosporidiosis in pre-weaned calves. Animals and patients with immunosuppression are at risk of developing the disease, which can cause potentially fatal diarrhoea. The present study aimed to construct a network biology framework based on the differentially expressed genes (DEGs) of C. parvum infected subjects. In this way, the gene expression profiling analysis of C. parvum infected individuals can give us a snapshot of actively expressed genes and transcripts under infection conditions. In the present study, we have analyzed microarray data sets and compared the gene expression profiles of the patients with the different data sets of the healthy control. Using a network medicine approach to identify the most influential genes in the gene interaction network, we uncovered essential genes and pathways related to C. parvum infection. We identified 164 differentially expressed genes (109 up- and 54 down-regulated DEGs) and allocated them to pathway and gene set enrichment analysis. The results underpin the identification of seven significant hub genes with high centrality values: ISG15, MX1, IFI44L, STAT1, IFIT1, OAS1, IFIT3, RSAD2, IFITM1, and IFI44. These genes are associated with diverse biological processes not limited to host interaction, type 1 interferon production, or response to IL-gamma. Furthermore, four genes (IFI44, IFIT3, IFITM1, and MX1) were also discovered to be involved in innate immunity, inflammation, apoptosis, phosphorylation, cell proliferation, and cell signaling. In conclusion, these results reinforce the development and implementation of tools based on gene profiles to identify and treat Cryptosporidium parvum-related diseases at an early stage. View Full-Text
Keywords: Cryptosporidium parvum infection; Differentially Expressed Genes (DEGs); key protein; miRNA; gene ontology Cryptosporidium parvum infection; Differentially Expressed Genes (DEGs); key protein; miRNA; gene ontology
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MDPI and ACS Style

Sabir, M.J.; Low, R.; Hall, N.; Kamli, M.R.; Malik, M.Z. A Bioinformatics Approach to Identifying Potential Biomarkers for Cryptosporidium parvum: A Coccidian Parasite Associated with Fetal Diarrhea. Vaccines 2021, 9, 1427. https://doi.org/10.3390/vaccines9121427

AMA Style

Sabir MJ, Low R, Hall N, Kamli MR, Malik MZ. A Bioinformatics Approach to Identifying Potential Biomarkers for Cryptosporidium parvum: A Coccidian Parasite Associated with Fetal Diarrhea. Vaccines. 2021; 9(12):1427. https://doi.org/10.3390/vaccines9121427

Chicago/Turabian Style

Sabir, Mumdooh J., Ross Low, Neil Hall, Majid R. Kamli, and Md. Z. Malik. 2021. "A Bioinformatics Approach to Identifying Potential Biomarkers for Cryptosporidium parvum: A Coccidian Parasite Associated with Fetal Diarrhea" Vaccines 9, no. 12: 1427. https://doi.org/10.3390/vaccines9121427

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