Personalized medicine entails a vision where biomedical data is used to generate both static individual risk profiles (through personalized genomes) and to track patients' health longitudinally using dynamic molecular and physiological data. Mass spectrometry (MS) plays a critical role in providing quantitative molecular profiles of patients over time, allowing early detection of disease and monitoring of interventions. While MS-based proteomics and metabolomics technologies capture crucial dynamic information on the molecular level, they currently lag behind sequencing-based technologies due to a lack of throughput, reproducibility and coverage.
Our lab works on developing high-throughput metabolomics and lipidomics methods using mass spectrometry to better understand complex biological samples. With robust instrumentation like the Bruker timsTOF Pro, our methods provide multidimensional data with mass-to-charge, retention time, fragmentation and ion mobility to facilitate the increased separation of analytes while improving our capabilities to identify them. Using our developed methods, we aim to explore various clinical landscapes (i.e., cancer, diabetes, etc.) to better understand the complexity of metabolites in the context of disease and personalized medicine.
In addition to experimental mass spectrometry, our lab has a strong focus on software and computational analysis of mass spectrometric data. The software developed in our lab is capable of analyzing millions of mass spectrometric scans, identify the measured analytes and extract accurate quantitative information from this data. We collaborate with researchers and doctors around the world using our tools and algorithms, helping them to interpret mass spectrometric data or develop new ways to answer long-standing biological questions.
We are using targeted and untargeted mass spectrometry to measure proteins and metabolites with unprecedented accuracy and throughput, allowing researchers to obtain a systems-level view of analytes in mammalian cells, tissues and blood. One promising area of research has been the development of DIA methods in mass spectrometry with we are investing for their potential to increase specificity and throughput by orders of magnitude. These methods allow us to extract biological information from complex mass spectrometric datasets and apply this information to answer questions in systems biology and personalized medicine. We are currently applying our work to study global changes in humans during the progressions of diseases as diverse as diabetes, neurological diseases, connective tissue disorders and other disorders.