Coupling Microdroplet-Based Sample Preparation, Multiplexed Isobaric Labeling, and Nanoflow Peptide Fractionation for Deep Proteome Profiling of the Tissue Microenvironment

Abstract

There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity in a cell-type-specific manner to better understand and predict the function of complex biological systems such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverage due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (microdroplet processing in one pot for trace samples), multiplexed isobaric labeling, and a nanoflow peptide fractionation approach. The integrated workflow allowed us to maximize proteome coverage of laser-isolated tissue samples containing nanogram levels of proteins. We demonstrated that the deep spatial proteomics platform can quantify more than 5000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 μm²) and differentiate unique protein abundance patterns in pancreas. Furthermore, the use of the microPOTS chip eliminated the requirement for advanced microfabrication capabilities and specialized nanoliter liquid handling equipment, making it more accessible to proteomic laboratories.

Figure 1

Schematic overview of the deep spatial proteomics analysis pipeline.

Figure 2

Evaluation of the deep spatial proteomics platform. (a) Median log10 intensities in the 11-plex set. (b) Fraction count in which a given peptide was detected. (c) Sampling depth (peptide count) for each fractionation. (d) Median CVs calculated across 5 replicates of each of the two pancreas functional units.

Figure 3

(a) PCA showing sample variation in 2D PC space for islet and acinar proteomic profiles. (b) Heat map depicts hierarchical clustering of top 50 differently expressed genes in 2 functional units of the pancreas. (c) Gene set enrichment analysis for 2339 genes differentially expressed in endocrine and exocrine pancreas.

Figure 4

Proteome imaging data obtained using our advanced microPOTS platform for deep spatial proteomics profiling. (a) Optical image of the 10 μm-thick PAS-stained pancreas section with the regions selected for LCM-proteome imaging. (b-f) Colored maps with scaled protein log2 abundance values (yellow–high and red–low), as examples of protein abundance changes across all 9 imaged pixels.