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

使用细胞器蛋白质组学策略表征微生物细胞工厂的分泌机制。

• 批准号: BB/I016147/1
• 金额: $ 11.71万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Training Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FI016147%2F1
• 关键词: Characterisation; secretion; mechanisms; microbial; cell

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)

我们建议采取蛋白质组学的方法来研究蛋白质的分泌和营业额在两个酵母：微生物细胞工厂，巴斯德毕赤酵母，和模式真核生物，酿酒酵母。我们将使用蛋白质组学为基础的方法来看，在这两个物种中，在运输的异源蛋白质从其合成的网站到细胞外部的动力学。在两种宿主中，我们将使用重组人溶菌酶（HuLy）作为试验对象。先前的工作已经证明，使用一系列溶菌酶突变体，HuLY的解折叠程度是决定其分泌产量的主要因素（1）。高度未折叠的变体显示出差的分泌产率并触发未折叠蛋白质反应（UPR）。我们将使用一个全球蛋白质组学的方法，以确定在哪里从ER到细胞外的分泌途径溶菌酶及其变体积累。已知高度未折叠的蛋白质诱导ER应激和未折叠蛋白质反应（UPR）。我们的理由采取一个全球性的方法来解剖酵母中异源蛋白的分泌途径，是基于需要确定不仅在这些蛋白质积累的亚细胞位置，而且在每个特定的位置内的结合伙伴。使用诱饵的免疫沉淀来捕获蛋白质复合物的标准方法不产生关于中间体的区室化和区室内结合伴侣的动态性质的信息。因此，我们将利用Lilley实验室开发的最先进的技术，利用定量蛋白质组学方法结合复杂的统计工具确定的密度梯度上亚细胞区室的分布模式，将蛋白质准确分配到亚细胞位置（2）。在本项目中，我们将与沃茨蛋白质组学总监Jim Langridge合作，采用最新的无标记蛋白质组学方法进一步开发该方法，以同时确定数千种蛋白质的分布。这种无标记的方法是由沃茨开创的，与Lilley实验室的方法相比具有许多优点。迄今为止，已使用，即同量异位素稳定同位素体外标记。Lilley实验室最近的工作。已经表明，这些标签，如iTRAQ，在其精度和准确性方面都存在严重问题（3）。已经证明，稳健的无标记方法不会遭受与iTRAQ标签相同的缺点（4，5），并且它们在确定密度梯度内细胞器蛋白质的分布模式中的使用更可能导致对此类模式的准确测量，从而更好地解析与不同亚细胞结构相关的模式。此外，所采用的无标记方法，MSE，还估计了不同组分内蛋白质的绝对量，使得能够测量复合物中蛋白质的化学计量，作为蛋白质种类在每个隔室的蛋白质分子方面的绝对分布。在进一步开发了无标记定量蛋白质组学方法以确定蛋白质及其结合伴侣的准确亚细胞位置的方法后，我们将专注于研究重组蛋白的区室化。我们将对它与其他蛋白质的关联进行全球分析，包括未折叠蛋白伴侣，Kar 2 p（BiP直系同源物）和蛋白酶体。我们将对HuLy（I156 T）的淀粉样变形式特别感兴趣，并将通过表达阿尔茨海默氏病蛋白Abeta（以其天然形式和Abeta 42-GFP融合物）来验证我们使用该变体的结果。1. Kumita，JR等人（2006）FEBS J273 ⑷：711-20 Dunkley，T等人，（2006）Proc.Natl. Acad. Sci 103（17）：6518-23 3. Karp，NA等人（2010）Mol.细胞保护按4。Silva，JC等人（2005），Anal Chem.1;77（7）：2187-200 Stapel，M等人（2010）Sci Signal.2;3（111）