Assistant Professor
Research
Research in the Pergande Lab aims to uncover the molecular mechanisms driving neurodegenerative diseases, with a particular focus on the contribution of glial cells to disease onset and progression. We employ high-resolution mass spectrometry-based multiomic approaches, including proteomics, lipidomics, and metabolomics, to define cell-type-specific dysfunction and identify novel therapeutic targets.
To model disease-relevant mutations in a human context, we utilize induced pluripotent stem cell (hiPSC)-derived neurons and glia. These scalable in vitro systems enable systems-level profiling of pathogenic mechanisms in a cell-type-resolved manner. By integrating multiomic datasets, we map how disease-associated perturbations alter cellular pathways and network interactions. Our long-term goal is to establish a systems-level understanding of glial biology that can guide the development of targeted treatments for neurodegenerative diseases.
Publications
Techniques & Resources
The Pergande Lab leverages advanced instrumentation and cellular models to drive discovery:
- Mass Spectrometry Platforms: Bruker timsTOF Pro2, Thermo Orbitrap Eclipse Tribrid, and Agilent 6495D triple quadrupole for discovery-based and targeted analyses
- Chromatography Systems: Agilent 1290 Bioinert UHPLC, Dionex Ultimate 3000 HPLC, Evosep One and Thermo Easy-nLC 1200.
- Cellular Models: hiPSC-derived neurons, astrocytes and microglia; CRISPR-edited mammalian cell lines to model disease-relevant mutations
- Bioinformatics Infrastructure: Two dedicated high-performance computing systems for multiomic integration (proteomics, lipidomics, metabolomics) and pathway/network analysis
Together, these tools enable systems-level, quantitative mapping of molecular dysfunction in glial cells.
What’s Next for Graduates of the Pergande Group?
Pergande lab members will obtain a broad range of skills spanning analytical chemistry, biochemistry and neurobiology. Primarily, they will gain substantial experience in the use of high-resolution mass spectrometry data collection and analysis, multiomic data integration, and the design and implementation of hiPSC-based disease models. Group members will also have opportunities to learn and implement proteomic, lipidomic, and metabolomic workflows and computational analysis of large-scale datasets. In addition, trainees will develop expertise in translational neurobiology, collaborative research, and scientific communication, preparing them for careers across both academia and industry.