An automated and fast sample preparation workflow for laser microdissection guided ultrasensitive proteomics

Abstract

Spatial tissue proteomics integrating whole-slide imaging, laser microdissection and ultrasensitive mass spectrometry is a powerful approach to link cellular phenotypes to functional proteome states in (patho)physiology. To be applicable to large patient cohorts and low sample input amounts, including single-cell applications, loss-minimized and streamlined end-to-end workflows are key. We here introduce an automated sample preparation protocol for laser microdissected samples utilizing the cellenONE® robotic system, which has the capacity to process 192 samples in three hours. Following laser microdissection collection directly into the proteoCHIP LF 48 or EVO 96 chip, our optimized protocol facilitates lysis, formalin de-crosslinking and tryptic digest of low-input archival tissue samples. The seamless integration with the Evosep ONE LC system by centrifugation allows ‘on-the-fly’ sample clean-up, particularly pertinent for laser microdissection workflows. We validate our method in human tonsil archival tissue, where we profile proteomes of spatially-defined B-cell, T-cell and epithelial microregions of 4,000 µm2to a depth of ∼2,000 proteins and with high cell type specificity. We finally provide detailed equipment templates and experimental guidelines for broad accessibility.

Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications

“…In contrast to most standard HPLC systems, the Evosep One implements disposable trap columns for in-line sample cleanup prior to LC-MS/MS analysis. This has been demonstrated to greatly increase chromatographic throughput, reproducibility, and sensitivity in conjunction with rapid MS acquisition 10,43,45,46 .…”

Refining Spatial Proteomics by Mass Spectrometry: An Efficient Workflow Tailored for Archival Tissue

“…The accelerated developments within the field of Liquid Chromatography-Mass Spectrometry (LC-MS) have recently enabled a level of sensitivity capable of analyzing ultra-low sample input (8,9), which consequently sparked a rapid emergence of methods transitioning from bulk or high-load input to low-load and near single-cell analysis (10)(11)(12)(13)(14)(15). However, proteome coverage and ease of implementation on largescale cohorts is still limited by sample preparation, which is especially true for FFPE tissue.…”