HTLV-1 Research Project

Computational Analysis of Human T-lymphotropic Virus Type 1 Genomics and Pathogenesis

HTLV-1 Research

Project Overview

This advanced bioinformatics research project investigates Human T-lymphotropic Virus Type 1 (HTLV-1), a retrovirus that infects approximately 5-10 million people worldwide and causes severe diseases including Adult T-cell Leukemia/Lymphoma (ATL) and HTLV-1 Associated Myelopathy/Tropical Spastic Paraparesis (HAM/TSP). Through computational genomics and systems biology approaches, we analyze viral genetic diversity, host-pathogen interactions, and molecular mechanisms of pathogenesis.

Our research combines genomic sequence analysis, transcriptomics, and network biology to understand how HTLV-1 establishes persistent infection and drives oncogenesis. By integrating multi-omics data and employing machine learning techniques, we aim to identify biomarkers for disease progression and potential therapeutic targets.

Project Details

  • Status: Ongoing
  • Duration: 2023-2024
  • Role: Computational Biologist
  • Field: Viral Genomics, Oncology
  • Institution: Research Collaboration

Research Focus Areas

Genomic Variability

Analyze genetic diversity, mutation patterns, and evolutionary dynamics of HTLV-1 strains across different geographic regions.

Host-Virus Interactions

Investigate molecular mechanisms of viral integration, gene expression regulation, and immune evasion strategies.

Disease Biomarkers

Identify genetic and transcriptomic signatures associated with disease progression and clinical outcomes.

Computational Methods

Genomic Analysis

  • Whole genome sequencing data analysis
  • Comparative genomics and phylogenetic reconstruction
  • Mutation landscape characterization
  • Integration site analysis and mapping
  • Structural variant detection

Systems Biology Approaches

  • RNA-seq differential expression analysis
  • Pathway enrichment and network analysis
  • Machine learning for biomarker discovery
  • Host-pathogen interaction modeling
  • Multi-omics data integration

Key Research Contributions

  • Characterized genomic diversity of HTLV-1 isolates from endemic regions with high-resolution variant calling
  • Identified novel mutations in Tax and HBZ viral oncogenes associated with increased transforming potential
  • Analyzed host transcriptome profiles in HTLV-1 infected cells revealing dysregulated immune pathways
  • Developed computational models predicting disease progression risk based on viral and host genetic factors
  • Discovered potential therapeutic targets through network analysis of virus-host protein interactions
  • Contributed to understanding of viral latency mechanisms and reactivation triggers

Technology Stack

Bioinformatics RNA-Seq Analysis Python R Machine Learning Phylogenetics Network Biology Statistical Analysis Data Visualization

Research Impact

500+

Samples Analyzed

15+

Countries Studied

Novel

Biomarkers

High

Clinical Impact

Clinical & Research Applications

🔬 Diagnostic Development

Biomarker discovery for early detection of ATL and HAM/TSP in asymptomatic carriers.

💊 Therapeutic Targets

Identification of viral and host proteins as potential targets for antiviral and anticancer therapies.

🧬 Precision Medicine

Personalized risk assessment and treatment strategies based on genomic profiles.

Interested in Viral Genomics Research?

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