An Automated and Fast Sample Preparation Workflow for Laser Microdissection Guided Ultrasensitive Proteomics.

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 3 h. 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 4000 µm2 to a depth of ∼2000 proteins and with high cell type specificity. We finally provide detailed equipment templates and experimental guidelines for broad accessibility.

An Automated Nanowell-Array Workflow for Quantitative Multiplexed Single-Cell Proteomics Sample Preparation at High Sensitivity.

Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation including multiplexed labeling up to 16-plex with high sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE, reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1500 protein groups per TMT10-plex with reduced or eliminated need for a carrier proteome. We evaluated the effect of wider precursor isolation windows at single-cell input levels and found that using 2 Da isolation windows increased overall sensitivity without significantly impacting interference. Using the dedicated mass spectrometry acquisition strategies detailed here, we identified on average close to 2000 proteins per TMT10-plex across 170 multiplexed single cells that readily distinguished human cell types. Overall, our workflow combines highly efficient sample preparation, chromatographic and ion mobility-based filtering, rapid wide-window data-dependent acquisition analysis, and intelligent data analysis for optimal multiplexed single-cell proteomics. This versatile and automated proteoCHIP-based sample preparation approach is sufficiently sensitive to drive biological applications of single-cell proteomics and can be readily adopted by proteomics laboratories.

Label-Free Sample Preparation for Single-Cell Proteomics.

In recent years, single-cell proteomics (SCP) has become a valuable addition to other single-cell omics technologies for studying cellular heterogeneity. The amount of protein in a single cell is very limited, and in contrast to sequencing techniques, there are currently no means for protein amplification. Therefore, most single-cell proteomics approaches aim to maximize sample preparation efficiency while minimizing peptide loss. By reducing processing volumes to sub-microliters and avoiding manual transfer steps that could lead to peptide loss, peptide recovery, and the robustness of SCP workflows have been significantly improved. In this chapter, we describe a protocol for label-free SCP sample preparation using the cellenONE® platform and the proteoCHIP LF 48 substrate prior to analysis with high-performance liquid chromatography-mass spectrometry.