About Our Research
Project A1: PEP-TORCH Pipeline for Mycobacterial Identification
We developed the PEP-TORCH pipeline, an automated, algorithm-based method for identifying mycobacteria species from clinical specimens. This method improves peptide identification rates by 30% compared to other sensitive methods and has demonstrated 100% accuracy in identifying common clinical mycobacteria and subspecies, including those with distinct macrolide resistance phenotypes.
Project A2: Machine Learning Model for Targeted MS Data Analysis
Our lab has created a machine learning-based pipeline to enhance the analysis of targeted MS data. By using engineered features and a nested active learning algorithm, the model improves sensitivity, specificity, and accuracy, making it more applicable for clinical use.
Project B2: Adipose Tissue-Derived Extracellular Vesicles as Early Biomarkers of Type 2 Diabetes
Our research focuses on identifying extracellular vesicles (EVs) from adipose tissue as early biomarkers for type 2 diabetes (T2D). Collaborating with LOPA and Tulane Hospital, we have begun collecting fresh adipose tissue samples and have identified proteins enriched in EVs that may predict high-risk individuals for T2D development.
Platform B: Deep Bottom-Up Proteomics in Disease Biomarker Discovery
Project B1: Spatial and CSF Proteomics for Neurodegenerative Disease
Our lab uses advanced spatial proteomics and cerebrospinal fluid (CSF) analysis to discover biomarkers for neurodegenerative diseases. By studying proteomic changes in non-human primates infected with SARS-CoV-2 and in mice after traumatic brain injury (TBI), we've identified key proteins and pathways linked to neuroinflammation and neurodegeneration.
Our research revealed region-specific protein changes in the hippocampus and significant CSF protein alterations, providing insights into the molecular mechanisms underlying neurodegeneration. These findings contribute to the identification of biomarkers and therapeutic targets for neurological disorders.
Platform A: Algorithm-Based Proteomics in Pathogen Diagnosis