Big Data
Dengue virus infection triggers complex interactions between the virus and host cells, leading to diverse pathological outcomes. Understanding the pathobiology of dengue infection and its severity requires an integrative approach that combines molecular, cellular, and spatial analyses.
COMBAT integrates advanced multi-omics technologies to dissect the molecular and cellular mechanisms underlying dengue infection. By combining transcriptomics, proteomics, and metabolomics with spatial omics, we aim to generate a comprehensive systems-level understanding of dengue pathogenesis. We will use immune cells from patients, infected tissues from the mice experiments, and organoids to generate high-quality big data. By generating and analyzing high-quality big data from diverse biological sources, COMBAT aims to identify the mechanism, novel therapeutic targets, and advance strategies to combat dengue severity.
Below is an overview of the big-data technologies utilized in COMBAT:
Bulk and single-cell transcriptomics: We utilize high-resolution transcriptomics to analyze gene expression patterns and identify transcriptional changes associated with dengue infection and severity by both the bulk and single-cells from patients and infected cells and organoids. This approach provides insights into the regulatory networks and pathways activated during disease progression.
Proteomics: Proteomics allows us to study the protein landscape of dengue infection, identifying key proteins and post-translational modifications involved in the host-pathogen interaction. This enables a deeper understanding of the functional proteome and its role in disease mechanisms. We will use LC-MS/MS-based technologies and Olink’s Proximity Extension Assay (PEA) technology to map the protein landscape.
Metabolomics: Metabolomics focuses on profiling the metabolic changes induced by dengue infection. By analyzing metabolites and their pathways, we gain a comprehensive view of the biochemical alterations and their impact on cellular and systemic physiology.
Deep Immune Profiling with High-Dimensional Flow Cytometry and Spatial Omics: We will use high-dimensional flow cytometry to characterize immune cell populations (panel of T-, B-, NK- and myeloid cells), capturing the complexity of immune responses with unprecedented resolution. This approach provides critical insights into immune dynamics during dengue infection. We will also use PhenoCycler®-Fusion 2.0 system (Akoya Biosciences) for spatial mapping and microenvironment characterization. Spatial metabolomics will be performed in timsTOF fleX MALDI-2 system (Bruker). These techniques provide a multi-dimensional view of molecular interactions and cellular heterogeneity, essential for understanding the localized effects of dengue infection at the tissue and cellular levels.
