High-throughput Differential Expression Proteomics

In 2001, a major milestone was reached with the publication of the draft sequence of the human genome. It has now become apparent that there are far fewer protein-coding genes in the human genome than proteins in the human proteome. Whilst the genome is relatively stable, each tissue exhibits radically different protein expression that also changes dynamically over its life cycle and with environmental stimulus. Proteomics is therefore playing a major role in elucidating the functional role of many novel genes and their products, as well as in understanding their involvement in biologically relevant phenotypes both in normal cellular processes and disease. Differential proteomics has become a vital tool in the development of earlier and more accurate screening and diagnostic tests for the detection and treatment of disease. Protein biomarkers are discovered through determination of protein expression that changes uniquely through early progression of a disease state. These biomarkers can then be targeted in the development of non-invasive diagnosis, or used as indicators of the efficacy of new medications in drug discovery. The high-throughput discovery of protein biomarkers and the screening of all human proteins to ascertain their functions and interactions are the two major biology driven challenges in proteomics today.These large-scale challenges are too great for the resources of a single laboratory, so open international collaborations are essential and are being championed by the Human Proteome Organisation (HUPO - http://www.hupo.org/). HUPO is an international consortium that promotes the development and awareness of proteomics research and facilitates scientific collaborations between HUPO members and its initiatives. One such initiative is the Brain Proteome Project (BPP / http://www.hbpp.org/). The aims of the BPP are:- To analyse the brain proteome of human and mouse models in healthy, neurodiseased and aged states with emphasis on Alzheimer's and Parkinson's diseases.- To advance knowledge of neurodiseases and aging for developing new diagnostic approaches and medications.- To make neuroproteomic research and its results available in the scientific community and society.The brain is the most complex tissue of higher organisms, and therefore elucidating the protein complement of the brain is the upper limit of a significant challenge to today's current technologies in proteome analysis. The UK is playing a major role in HUPO, significantly through the HUPO Proteomic Standards Initiative (PSI - http://psidev.sourceforge.net/) hosted by the European Bioinformatics Institute, Hixton, Cambridge. However, the UK is under-represented in the BPP and notably in proteome informatics research as a whole. The two greatest technical barriers to large-scale proteomic analyses are:- The need for considerable expert manual interaction in differential expression proteomics. With conventional techniques errors propagate down the pipeline and so considerable expert manual validation is also required, which adds significant subjectivity.- Marked protocol variation in proteomic workflows between laboratories, leading to heterogeneity of results and therefore challenging results integration and cross-validation issues. To lift these barriers, the proposed fellowship aims to underpin proteomics research with an automated proteome informatics pipeline that:- Integrates the statistical power of multiple replicated experiments in order to elucidate all information, so that the accuracy of differential analysis and expression quantification increases to a level where full automation is possible and subjectively is removed.- Build up a statistical formation model of differential expression proteomics from a history of proteomics experiments, to compare and contrast the sensitivity of subtly different proteomic sample preparation, separation and identification protocols for use in subsequent experiment design.