An integrated bioinformatic analysis of microarray datasets to identify biomarkers and miRNA-based regulatory networks in leishmaniasis

Abstract

Micro RNAs (miRNAs, miRs) and relevant networks might exert crucial functions during differential host cell infection by the different Leishmania species. Thus, a bioinformatic analysis of microarray datasets was developed to identify pivotal shared biomarkers and miRNA-based regulatory networks for Leishmaniasis. A transcriptomic analysis by employing a comprehensive set of gene expression profiling microarrays was conducted to identify the key genes and miRNAs relevant for Leishmania spp. infections. Accordingly, the gene expression profiles of healthy human controls were compared with those of individuals infected with Leishmania mexicana, L. major, L. donovani, and L. braziliensis. The enrichment analysis for datasets was conducted by utilizing EnrichR database, and Protein-Protein Interaction (PPI) network to identify the hub genes. The prognostic value of hub genes was assessed by using receiver operating characteristic (ROC) curves. Finally, the miRNAs that interact with the hub genes were identified using miRTarBase, miRWalk, TargetScan, and miRNet. Differentially expressed genes were identified between the groups compared in this study. These genes were significantly enriched in inflammatory responses, cytokine-mediated signaling pathways and granulocyte and neutrophil chemotaxis responses. The identification of hub genes of recruited datasets suggested that TNF, SOCS3, JUN, TNFAIP3, and CXCL9 may serve as potential infection biomarkers and could deserve value as prognostic biomarkers for leishmaniasis. Additionally, inferred data from miRWalk revealed a significant degree of interaction of a number of miRNAs (hsa-miR-8085, hsa-miR-4673, hsa-miR-4743-3p, hsa-miR-892c-3p, hsa-miR-4644, hsa-miR-671-5p, hsa-miR-7106-5p, hsa-miR-4267, hsa-miR-5196-5p, and hsa-miR-4252) with the majority of the hub genes, suggesting such miRNAs play a crucial role afterwards parasite infection. The hub genes and hub miRNAs identified in this study could be potentially suggested as therapeutic targets or biomarkers for the management of leishmaniasis.

Keywords: Biomarkers; Gene expression profiling; Leishmaniasis; Microarray; Regulatory network; miRNA.

Figure 1

The flowchart of microarray analysis approach towards biomarker discovery in Leishmania infections. Six gene expression datasets were downloaded from GEO, and the differentially expressed genes (DEGs) in leishmaniasis patients and healthy controls with an adjusted P value < 0.05 and a |log fold change (FC)|> 1.5 were first identified by GEO2R or R language version 4.2.2. Next, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) analysis (www.kegg.jp/kegg/kegg1.html) were performed for enrichment analysis of these DEGs. Then, the hub genes were identified by the cytoHubba plugin and the other bioinformatics approaches including protein–protein interaction (PPI) network analysis, and miRNA-hub gene network construction was also performed. This approach promotes a comprehensive understanding of parasite infection and for biomarker discovery useful for early diagnosis.

Figure 2

Details of the recruited datasets related to each species of Leishmania along with the sort of the studied cells. Datasets belong to different cells of the different species of Leishmania.

Figure 3

Enrichment analysis associated with DEGs obtained from the Enricher database. Green nodes represent the genes while pink nodes display gene ontology terms, purple nodes show pathways and mammalian phenotype data displayed by orange node.

Figure 4

The overlap of hub genes between all analyzed datasets is shown by Venn diagram. Accordingly, there are no common genes between all of these datasets.

Figure 5

This figure showed the evaluation of sensitivity and specificity of hub genes in the diagnostic of the infection.

Figure 6

The interaction network between miRNAs and hub genes in miRWalk. Blue nodes represent miRNAs, while orang node displays hub genes.