Differential genes expression analysis of invasive aspergillosis: a bioinformatics study based on mRNA/microRNA

Maryam Hosseinipour1, Shirin Shahbazi2, Shahla Roudbar-Mohammadi1

  • 1Department of Medical Mycology, Faculty of Medical Science, Tarbiat Modares University, Tehran Iran.

Insights

Invasive aspergillosis (IA) is a severe fungal infection. This study identified 33 microRNAs regulating key genes, suggesting their potential as diagnostic biomarkers for IA.

Area of Science:

  • Medical Mycology
  • Molecular Biology
  • Bioinformatics

Background:

  • Invasive aspergillosis (IA) is a life-threatening opportunistic infection in immunocompromised individuals.
  • MicroRNAs play crucial roles in immune and inflammatory responses, making them relevant to IA pathogenesis.
  • Understanding molecular pathways is vital for developing diagnostic and therapeutic strategies for IA.

Purpose of the Study:

  • To identify microRNAs associated with invasive aspergillosis pathogenesis using bioinformatics.
  • To explore the molecular pathways regulated by these microRNAs.
  • To evaluate the diagnostic potential of identified microRNAs and gene combinations.

Main Methods:

  • Utilized bioinformatics approaches and extracted data from the Gene Expression Omnibus (GEO) database.
  • Identified differentially expressed genes (S100B, TDRD9, TMTC1) and predicted targeting microRNAs using miRWalk 2.0.
  • Performed microRNA target prediction, molecular pathway analysis, and Receiver Operating Characteristic (ROC) curve analysis.

Main Results:

  • Identified 33 common microRNAs regulating S100B, TDRD9, and TMTC1.
  • Found predicted microRNAs involved in innate immunity, toll-like receptor signaling, and platelet activation.
  • The S100B/TMTC1 combination showed 95.65% sensitivity and 69.23% specificity in ROC analysis.

Conclusions:

  • The identified microRNAs, particularly those involved in immune pathways, are potential diagnostic biomarkers for invasive aspergillosis.
  • Further research into microRNA expression and related pathways could lead to effective IA detection biomarkers.
  • The study highlights the role of microRNAs in IA pathogenesis and their diagnostic utility.