Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

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 sorting techniques to enrich for certain cell populations. However, the spatial resolution and context is lost after cell sorting. Here, we report an optimized 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 1500 proteins from 60 000 μm2 of 10 μm thick cerebellar molecular layer with excellent reproducibility. To demonstrate the ability of our workflow to resolve cell type specific proteomes within human brain 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.

Original publication

DOI

10.1021/acs.jproteome.8b00981

Type

Journal article

Journal

Journal of proteome research

Publication Date

25/02/2019

Addresses

Target Discovery Institute, Nuffield Department of Medicine , University of Oxford , Roosevelt Drive , Oxford , OX3 7FZ , U.K.