Dataset Information

Development of a sensitive, scalable method for spatial, cell-type-resolved proteomics of the human brain

ABSTRACT: While nearly comprehensive proteome coverage can be achieved from bulk tissue or cultured cells, the data usually lacks spatial resolution. As a result, tissue based proteomics averages protein abundance across multiple cell types and/or localisations. With proteomics platforms lacking sensitivity and throughput to undertake deep single-cell proteome studies to resolve spatial or cell type dependent protein expression gradients within tissue, proteome analysis has been combined with sorting techniques to enrich for certain cell populations. However, the tissue context and spatial resolution is lost in the sorting process. Here, we report an optimised method for the proteomic analysis of neurons isolated from post-mortem human brain by Laser Capture Microdissection (LCM). We tested combinations of sample collection methods, lysis buffers and digestion methods to maximize the number of identifications and quantitative performance, identifying up to 1500 proteins from 60,000 µm2 of cerebellar molecular layer with excellent reproducibility. In order to demonstrate the ability of our workflow to resolve for the first time cell type specific proteomes within a tissue, we isolated sets of individual Betz and Purkinje cells. Both neuronal cell types are involved in motor coordination and were found to express highly specific proteomes to a depth of 2800 to 3600 proteins.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Brain

SUBMITTER: Simon Davis

LAB HEAD: Roman Fischer

PROVIDER: PXD012101 | Pride | 2019-03-04

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	FL0473_MSQ1043_20170512_ConnorScott_Ex12_Cells100.raw	Raw
	FL0473_MSQ1043_20170512_ConnorScott_Ex12_Cells200.raw	Raw
	FL0473_MSQ1043_20170512_ConnorScott_Ex12_Cells400.raw	Raw
	FL0473_MSQ1043_20170512_ConnorScott_Ex12_Cells800.raw	Raw
	FL0476_MSQ1031_20170429_cells10.raw	Raw

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Publications

Development of a Sensitive, Scalable Method for Spatial, Cell-Type-Resolved Proteomics of the Human Brain.

Davis Simon S Scott Connor C Ansorge Olaf O Fischer Roman R

Journal of proteome research 20190225 4

While nearly comprehensive proteome coverage can be achieved from bulk tissue or cultured cells, the data usually lacks spatial resolution. As a result, tissue based proteomics averages protein abundance across multiple cell types and/or localizations. With proteomics platforms lacking sensitivity and throughput to undertake deep single-cell proteome studies in order to resolve spatial or cell type dependent protein expression gradients within tissue, proteome analysis has been combined with sor ...[more]

PMID: 30768908

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