Protocol for generating high-fidelity proteomic profiles using DROPPS

Matthew Waas; Meinusha Govindarajan; Amanda Khoo; Charlotte Zuo; Aastha Aastha; Jilin He; Michael Woolman; Annie Ha; Brian Lin; Thomas Kislinger

doi:10.1016/j.xpro.2024.103397

Protocol for generating high-fidelity proteomic profiles using DROPPS

STAR Protoc. 2024 Oct 17;5(4):103397. doi: 10.1016/j.xpro.2024.103397. Online ahead of print.

Authors

Affiliations

¹ Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada. Electronic address: waasmatthew@gmail.com.
² Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada.
³ Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada.
⁴ Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada. Electronic address: thomas.kislinger@utoronto.ca.

Abstract

Deep mass spectrometry-based proteomic profiling of rare cell populations has been constrained by sample input requirements. Here, we present a protocol for droplet-based one-pot preparation for proteomic samples (DROPPS), an accessible low-input platform that generates high-fidelity proteomic profiles of 100-2,500 cells. We describe steps for depositing cellular material, cell lysis, and digesting proteins in the same microliter-droplet well. We anticipate DROPPS will accelerate biology-driven proteomic research for a multitude of rare cell populations. For complete details on the use and execution of this protocol, please refer to Waas et al.¹.

Keywords: cell biology; flow cytometry; proteomics.