Exhibitor Tutorial
Bogdan Budnik, PhD
The Weiss Institute at Harvard University
Alexander Schmidt
University of Basel, Basel-Stadt, Switzerland
René M. Overmeer, PhD
HUB Organoids, Utrecht, Netherlands
Lesley Schultz
Tecan
Michael Lewandowski1, Shad Morton1, Mariana Garcia-Corral1, Katharina Meyer1, Jenny M. Tam1,2, Rushdy Ahmad1, George M. Church1,2,3, David R. Walt1,2, 4, Bogdan Budnik1Drug discovery and development are being transformed by single-cell technologies such as single-cell RNA sequencing (scRNA-seq). We can improve our understanding of disease mechanisms by using cell subtyping to identify targets. Proteomics data at a single cell resolution are necessary due to the lack of correlation between RNA and protein abundances.In its early stages, single-cell proteomics (SCP) was used to study cancer cell monocultures and their response to drug treatments. For further analysis of proteome heterogeneity of very complex cell mixtures as brain organoids, we developed an automated workflow that can prepare single cells. We have demonstrated that different classes of drug treatments result in unique cell responses, and our findings indicate that single-cell proteomics provides important data that can be used to uncover novel biology processes that can lead to better treatments by revealing complex biological systems.Our technique was validated by treating human induced pluripotent stem cells (hiPSCs) derived from healthy and bipolar patients with three different drugs. Cells were grown both mono-cultured and co-cultured. Compared to bulk proteomics, single-cell proteomics revealed inherent heterogeneity in cell populations and differences in drug response. We observed subpopulations of cells with unique drug response profiles. Hence, SCP analysis is necessary to understand the effects of drugs under different disease states, and discoveries made from single-cell data can lead to effective treatments for this disease that are greatly needed.