Elving Lecture with Lingjun Li

Title: Advancing Biomedical Research via Innovation in Mass Spectrometry (MS)-based Approaches
Abstract: Comprehensive characterization of all signaling molecules in a biological system with chemical, spatial and temporal information is often critical to deciphering their functional roles, yet it poses a daunting challenge. In this presentation, I will present our recent progress on the development of a multi-faceted mass spectrometry (MS)-based analytical platform to probe neuronal signaling with enhanced sensitivity and selectivity. By combining chemical labeling, micro-scale separation, and tandem MS sequencing techniques, we discovered more than 300 novel neuropeptides in several model organisms. Moreover, both mass spectrometric imaging (MSI) technology and in vivo microdialysis sampling tools have been developed and implemented to follow neuropeptide distribution and secretion with unprecedented details. Additionally, several in situ chemical derivatization strategies have been developed to enable spatial mapping of various biomolecules including lipids and glycans in complex biological samples, such as human cell lines and cancer tissue samples. Recent progress towards single-cell lipidomics enabled by dual-polarity ionization and ion mobility MS imaging will be highlighted as well.
Furthermore, we are developing multiplexed isobaric and isotopic tagging strategies to discover, identify and evaluate candidate biomarkers of Alzheimer’s disease (AD) in cerebrospinal fluids (CSFs) obtained from asymptomatic cognitively-healthy middle-aged adults, older cognitively-normal adults, and patients with mild cognitive impairment (MCI) and AD. A large-scale comparative glycoproteomic analysis via the 12-plex DiLeu (N,N-dimethyl leucine) tagging strategy revealed distinct glycosylation patterns and dynamic changes of certain glycoforms in CSF samples collected from the control, MCI, and AD patients. Additionally, we report on a multiplexed quantitation method for simultaneous proteomics and amine metabolomics analyses via nanoflow reversed phase LC-MS/MS, exploiting mass defect-based DiLeu (mdDiLeu) labeling. Several on-going efforts and future perspectives provided by these enabling technologies will be highlighted and discussed.