The Cambridge Centre for Proteomics (CCP) is comprised of two sections, a research group that specialises in quantitative and spatial proteomics, and a core facility that provides facilities for the School of the Biological Sciences and for wider collaborators in Cambridge and the UK. CCP offers a fee for service proteomics resource and is part of PrimeXS, a pan-European FP7 funded proteomics consortium involved in platform development and transnational access.
We are interested in the development of technologies which enable measurement of the dynamics of the proteome in a high throughput manner in space and time during cellular processes such as signalling and differentiation.
1. Localisation of Organelle Proteins using Isotope Tagging (LOPIT) (1), which allows the assignment of proteins and protein complexes to sub-cellular locations, has been applied successfully to several biological systems (2,3). The ability to assign individual proteins accurately to specific sub-cellular structures and monitor their movement within cells is of paramount importance to our understanding of cellular mechanisms.
2. Interactomes using Parallel Affinity Capture (iPAC) is a method developed in collaboration with the St Johnston (Gurdon Institute) and Russell (Genetics Dept.) groups to determine genuine residents of multi protein complexes (4).
Robust statistical and computational data analysis is of vital importance to the above techniques, and to proteomics in general, to ensure that data sets are efficiently mined and do not contain unacceptable levels of false discovery. We now have a dedicated team of informaticians who work in collaboration with Matthew Trotter of the Anne McLaren Laboratory of Regenerative Medicine to develop bioinformatics and statistical tools, that utilize pattern recognition and machine learning methods to enable robust analysis of organelle proteomics and multi-protein complex data (5). The output of this research is manifested in the creation of open-source software solutions for quantitative data analysis that are applicable to the majority of quantitative proteomics applications.
Lab members: Irina Armean, Nick Bond, Phil Charles, Andy Christoforou, Michael Deery, Renata Feret, Laurent Gatto, Arnoud Groen, Adam Guterres, Julie Howard, Kathryn Lilley, Claire Mulvey, Isabelle Nett, Daniel Nightingale, Nino Nikolovski, Lisa Simpson, Pavel Shliaha
1. Dunkley TPJ, et al (2006) Mapping the Arabidopsis organelle proteome. Proc. Natl Acad. Sci. 103 (17): 6518-6523
2. Hall SL, et al (2009) The organelle proteome of the DT40 Lymphocyte cell line. Mol Cell Proteomics. 8(6):1295-305
3. Tan D, et al. (2009) Mapping organelle proteins and protein complexes in Drosophila melanogaster. J Proteome Res 8(6):2667-78
4. Rees JS, et al (2011) In vivo analysis of proteomes and interactomes using parallel affinity capture (iPAC) coupled to mass spectrometry. Mol Cell Proteomics. 10 (6) M110--002386
5. Trotter MW, et al (2010) Improved sub-cellular resolution via simultaneous analysis of organelle proteomics data across varied experimental conditions. Proteomics. 10(23):4213-9.