Characterisation of the secretion mechanisms of microbial cell factories using organelle proteomics strategies.

Lead Research Organisation: University of Cambridge
Department Name: Biochemistry


We propose to take a proteomics approach to the study of protein secretion and turnover in two yeasts: the microbial cell factory, Pichia pastoris, and the model eukaryote, Saccharomyces cerevisiae. We shall use a proteomics based approach to look, in both species, at the dynamics of transport of a heterologous protein from the site of its synthesis to the cell exterior. In both hosts we shall use recombinant human lysozyme (HuLy) as the test object. Previous work has demonstrated, using a series of lysozyme mutants, that the degree of unfolding of HuLY is a major factor in determining its secreted yield (1). Highly unfolded variants show poor secretion yield and trigger the unfolded protein response (UPR). We shall use a global proteomics approach to determine where in the secretion pathway from the ER to the cell exterior lysozyme and its variants accumulate. Highly unfolded proteins are known to induce both ER stress and the unfolded protein response (UPR). Our rationale for taking a global approach to dissect the secretion pathways of heterologous proteins in yeasts, is based on the need to determine not only the subcellular locations at which such proteins accumulate, but also their binding partners within each specific location. Standard methodologies to capture protein complexes using immunopreciptation of a bait do not yield information about compartmentalisation of intermediates and the dynamic nature of binding partners within compartments. We will thus make use of state-of-the-art technologies developed in the Lilley laboratory which allow accurate assignment of proteins to subcellular locations using distribution patterns of subcellular compartments on density gradients as determined by quantitation proteomics methods coupled with sophisticated statistical tools (2). In this project we will work with Jim Langridge who is Director of Proteomics at Waters to further develop this method employing up-to-date label-free proteomics methodologies to determine the distribution of thousands of proteins simultaneously. This label-free approach has been pioneered by Waters and has many advantages over the methods that the Lilley lab. has used to date, namely isobaric stable isotope in vitro labels. Recent work by the Lilley lab. has shown that these labels, such as iTRAQ, have significant problems regarding both their precision and accuracy (3). Robust label-free approaches have been shown not to suffer from the same shortcomings as the iTRAQ tags (4,5) and their use in determining the distribution patterns of organelle proteins within density gradients are more likely to lead to accurate measurement of such patterns and thus better resolution of the patterns associated with different sub cellular structures. Moreover, the label-free method to be employed, MSE, also estimates the absolute amount of proteins within different fractions, enabling measurement of stoichiometeries of proteins in complexes, as absolute distributions of protein species in terms of molecules of protein per compartment. Having further developed label free quantitative proteomics approaches to determine methods accurate subcellular locations of proteins and their binding partners, we will focus on examining the compartmentalisation of the recombinant protein. We will carry out global analysis of its association with other proteins including the unfolded-protein chaperone, Kar2p (a BiP ortholog) and the proteasome. We shall be particularly interested in the amyloidogenic version of HuLy (I156T) and will validate our results using this variant by expressing the Alzheimer's protein Abeta, both in its native form and as Abeta42 -GFP fusions. 1. Kumita, JR et al (2006) FEBS J273(4):711-20 2. Dunkley, T et al, (2006)Proc. Natl. Acad. Sci 103(17):6518-23 3. Karp, NA et al (2010) Mol. Cell Prot. in press 4. Silva, JC et al (2005), Anal Chem. 1;77(7):2187-200 5. Stapel, M et al (2010) Sci Signal.2;3(111)


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