Mapping intact protein isoforms in discovery mode using top-down proteomics

作者:Tran John C; Zamdborg Leonid; Ahlf Dorothy R; Lee Ji Eun; Catherman Adam D; Durbin Kenneth R; Tipton Jeremiah D; Vellaichamy Adaikkalam; Kellie John F; Li Mingxi; Wu Cong; Sweet Steve M M; Early Bryan P; Siuti Nertila; LeDuc Richard D; Compton Philip D; Thomas Paul M; Kelleher Neil L*
来源:Nature, 2011, 480(7376): 254-U141.
DOI:10.1038/nature10575

摘要

A full description of the human proteome relies on the challenging task of detecting mature and changing forms of protein molecules in the body. Large-scale proteome analysis(1) has routinely involved digesting intact proteins followed by inferred protein identification using mass spectrometry(2). This 'bottom-up' process affords a high number of identifications (not always unique to a single gene). However, complications arise from incomplete or ambiguous(2) characterization of alternative splice forms, diverse modifications (for example, acetylation and methylation) and endogenous protein cleavages, especially when combinations of these create complex patterns of intact protein isoforms and species(3). 'Top-down' interrogation of whole proteins can overcome these problems for individual proteins(4,5), but has not been achieved on a proteome scale owing to the lack of intact protein fractionation methods that are well integrated with tandem mass spectrometry. Here we show, using a new four-dimensional separation system, identification of 1,043 gene products from human cells that are dispersed into more than 3,000 protein species created by post-translational modification (PTM), RNA splicing and proteolysis. The overall system produced greater than 20-fold increases in both separation power and proteome coverage, enabling the identification of proteins up to 105 kDa and those with up to 11 transmembrane helices. Many previously undetected isoforms of endogenous human proteins were mapped, including changes in multiply modified species in response to accelerated cellular ageing (senescence) induced by DNA damage. Integrated with the latest version of the Swiss-Prot database(6), the data provide precise correlations to individual genes and proof-of-concept for large-scale interrogation of whole protein molecules. The technology promises to improve the link between proteomics data and complex phenotypes in basic biology and disease research(7).