Professor Angus Lamond FRS FRSE FMedSci is Professor of Biochemistry in the School of Life Sciences, Centre for Gene Regulation and Expression at the University of Dundee. Before moving to Dundee in 1995 Angus was a group leader at the European Molecular Biology Laboratory in Heidelberg, where he started using mass spectrometry based proteomics techniques. Angus’ group study gene expression in disease mechanisms and the functional organization of mammalian cell nuclei, using a strategy that combines quantitative mass spectrometry (MS) based proteomics and live cell fluorescence imaging (www.LamondLab.com). The Lamond group have developed new proteomic methods and pioneered multi-dimensional proteomics strategies together with innovative big data analytics solutions. They have created a software project – Peptracker – for the efficient analysis, integration and convenient sharing of multiple large proteomics datasets. This has led to a new spin out venture – Platinum Informatics (www.pt-informatics.com) to commercialise the powerful new tools they have created for laboratory data management and analysis. Angus Lamond is also working to establish a new biotechnology company that will commercialise state of the art multi-dimensional and high resolution proteomics for application in drug discovery programmes. This benefits from the unique expertise in the Lamond group.
Cell regulation and disease mechanisms can now be studied in unprecedented detail, combining high throughput ‘omics’ techniques, including mass spectrometry (MS) based proteomics and RNA seq with image-based phenotypic assays using microscopy. If properly designed, these methods provide the opportunity for making unbiased, system-wide, quantitative measurements of gene expression and phenotypes that underpin mechanisms causing disease. The opportunity here is clear: modern quantitative proteomics in particular can reveal detailed insights into proteome dynamics, providing a flexible suite of quantitative assays that we can use to characterize, system-wide, a multi-dimensional array of ‘Protein Properties’. Thus, time-dependent measurements, with isoform resolution, of protein abundance, subcellular protein localization, turnover rates, post-translational modifications, cell cycle variation and specific protein complexes and protein-protein interactions etc. allow a detailed characterization of cell phenotypes in both healthy and diseased cells. One of the major challenges in using proteomics and other ‘omics’ methods to study molecular mechanisms affecting biological regulation is how to manage, analyse and integrate the huge volumes of complex, quantitative data that are generated. I will describe some of the current projects in which we are doing quantitative proteomics to study gene expression mechanisms relevant to cancer, immune cells and nutritional responses in humans and in model organisms. I will also review our progress in building user-friendly, computational tools for the effective management and sharing of large, multidimensional data sets with the life sciences and biomedical research community.