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Development of novel mass spectrometry approaches that enable phosphoproteomic analysis in tandem with cellular localisation

开发新型质谱方法，使磷酸蛋白质组分析与细胞定位同时进行

基本信息

批准号：
1944418
负责人：
金额：
--
依托单位：
University of Cambridge
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1944418
关键词：
Development novel mass spectrometry approaches

项目摘要

As a key mediator of cellular signalling, phosphorylation remains a principal target for biological question. Identifying and quantifying the phosphorylation state of proteins involved in cell progression, metabolism, growth and disease is critical for the elucidation of cellular function. The initial aim of the project with be to extend recent developments that have demonstrated that the combination of phospho-peptides enrichment using titanium matrices and isobaric chemical labelling (TMT) allows the identification of 10,000 to 15,000 phosphopeptides from total cell lysate (1, 2). This coupled with the hyperLOPIT methodology (Localisation of Organelle proteins by isotope tagging, (3-5), which combines a biochemical organelle fractionation with a quantitative mass spectrometry analysis, will enable proteomic analysis at the organelle level. Whilst scientifically and experimentally challenging it is realistic to envisage the combination of these methods to deliver a novel approach which will add cellular resolution to phosphoproteomic analysis.The second goal of the research will be the application of these methods to probe disease relevant cell types and response to compound treatment. This will leverage AstraZeneca's disease expertise and wealth of annotated probe compounds. Hypotheses generated from these analyses with be further tested by, targeted proteomic strategies (Selected Reaction Monitoring) and antibody methods to directly characterise the phosphorylation state of the protein candidates and their localisation within the cell using fluorescence microscopy. Finally, exploiting AstraZeneca's access to disease relevant tissues, the expression of targeted protein candidates can be validated on mouse/human samples.(1) Evaluating multiplexed quantitative phosphopeptide analysis on a hybrid quadrupole mass filter/linear ion trap/orbitrap mass spectrometer. Erickson BK, Jedrychowski MP, McAlister GC, Everley RA, Kunz R, Gygi SP. Anal Chem. (2015).(2) Comprehensive quantitative comparison of the membrane proteome, phosphoproteome, and sialiome of human embryonic and neural stem cells. Melo-Braga MN, Schulz M, Liu Q, Swistowski A, Palmisano G, Engholm-Keller K, Jakobsen L, Zeng X, Larsen MR. Mol Cell Proteomics. (2014).(3) A draft map of the mouse pluripotent stem cell spatial proteome. Christoforou A, Mulvey CM, Breckels LM, Geladaki A, Hurrell T, Hayward PC, Naake T, Gatto L, Viner R, Martinez Arias A, Lilley KS. Nat Commun. 2016.(4) Using hyperLOPIT to perform high-resolution mapping of the spatial proteome. Mulvey CM and et al Nature Protocols 12(6):1110-1135. doi: 10.1038/nprot.2017.026 (2017).(5) A subcellular map of the human proteome. Thul, PJ et al, Science 356(6340). pii: eaal3321. doi: 10.1126/science.aal3321 (2017).

作为细胞信号传导的关键介质，磷酸化仍然是生物学问题的主要目标。鉴定和量化参与细胞进展、代谢、生长和疾病的蛋白质的磷酸化状态对于阐明细胞功能至关重要。该项目的最初目标是扩展最近的发展，这些发展表明，使用钛基质和等压化学标记（TMT）的磷酸肽富集组合可以从总细胞裂解物中鉴定10,000至15,000个磷酸肽（1,2）。这与hyperLOPIT方法（通过同位素标记定位细胞器蛋白质）相结合，将生化细胞器分离与定量质谱分析相结合，将使细胞器水平的蛋白质组学分析成为可能。虽然在科学和实验上具有挑战性，但设想将这些方法结合起来提供一种新的方法是现实的，这种方法将增加磷酸化蛋白质组学分析的细胞分辨率。研究的第二个目标将是应用这些方法来探测疾病相关的细胞类型和对复合治疗的反应。这将利用阿斯利康的疾病专业知识和丰富的带注释探针化合物。从这些分析中产生的假设将通过靶向蛋白质组学策略（选择反应监测）和抗体方法进一步测试，以直接表征候选蛋白质的磷酸化状态及其在细胞内的定位，使用荧光显微镜。最后，利用阿斯利康获得疾病相关组织的途径，靶向候选蛋白的表达可以在小鼠/人类样本上进行验证。(1)评价混合四极质过滤器/线性离子阱/轨道阱质谱仪的多路定量磷酸肽分析。Erickson BK, Jedrychowski MP, McAlister GC, Everley RA, Kunz R, Gygi SP.肛门化学。(2015)。(2)人胚胎干细胞和神经干细胞膜蛋白质组、磷蛋白质组、唾液组的综合定量比较。Melo-Braga MN, Schulz M, Liu Q, Swistowski A, Palmisano G, Engholm-Keller K, Jakobsen L, Zeng X， Larsen先生。(2014)。(3)小鼠多能干细胞空间蛋白质组图谱初稿。Christoforou A, Mulvey CM, brekels LM, Geladaki A, Hurrell T, Hayward PC, Naake T, Gatto L, Viner R, Martinez Arias A, Lilley KS。Nat common . 2016。(4)利用hyperLOPIT进行空间蛋白质组的高分辨率制图。Mulvey CM和et al . Nature, 12(6):1110-1135。Doi: 10.1038/nprot.2017.026（2017）。(5)人类蛋白质组亚细胞图谱。Thul， PJ等人，Science 356（6340）。pii: eaal3321。doi: 10.1126 /科学。aal3321(2017)。