Abstract
Purpose :
Fusarium keratitis (FK) is considered to be one of the leading causes of ocular morbidity particularly in developing countries including India. Several host factors, Fusarium virulence, and anti-fungal mechanisms have been implicated in the pathogenesis of the disease. However, the mechanisms of pathogenesis are elusive in poor-outcome patients due to impaired inflammation and wound healing. Here, we aim to profile the dysregulated miRNAs and to understand their role in Fusarium keratitis.
Methods :
Corneal tissues were collected post-TPK surgery. Human donor corneas served as control. Total RNA was isolated from corneal tissues and was sequenced for both small RNAseq and mRNAseq in different sets of samples. The differential expression (DE) analysis was performed to identify the dysregulated miRNAs and mRNAs. miRNAs were filtered based on log fold change > ± 2; -Log10P-value >2 and Log CPM>4 and mRNAs were filtered based on log fold change > ± 2 with P-Value <0.05. Targets were predicted for the filtered miRNAs and matched with DE mRNAs. In silico functional analysis was performed for these matched Targets
Results :
We identified 46 upregulated and 42 downregulated miRNAs in Fusarium keratitis corneas compared to the control. Pathway enrichment showed pathways like phagosome, cytokine- cytokine receptor interaction, IL-17 signaling pathway, and GO analysis showed wound healing, inflammatory, and immune response as of our interest. Based on network analysis, we selected 17 potential miRNAs for qPCR validation. We identified 9 significantly dysregulated miRNAs, which showed potential role in cytokine - cytokine receptor interaction, IL-17 signaling pathways, and GO terms like wound healing and inflammatory response. We further showed dysregulated genes involved in these pathways
Conclusions :
This study has profiled human corneal miRNAs in Fusarium keratitis and has shown dysregulated miRNAs. Further functional analysis reveals their role in Fusarium keratitis pathogenesis, which warrants further studies.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.