Novel computational method development for shotgun proteomics

基于质谱学(MS)的蛋白质组学是鉴定蛋白质以了解生物功能和过程、阐明信号网络、发现人类疾病生物标志物和识别植物重要性状的关键基因的首选方法。蛋白质组学的计算方法在解释MS数据和产生生物学见解方面起着至关重要的作用，但它们的潜力仍有待充分开发。特别是在植物蛋白质组学实验中，只有不到20%的高质量MS/MS图谱可以被有意义地解释。这在很大程度上反映了目前计算方法的有限敏感性，以及缺乏完整、准确和简洁的蛋白质异构体序列信息。在这个项目中，我们的目标是通过开发一种新的基于概率的肽谱匹配计算方法来解决蛋白质组学中的这些关键问题，该方法将大量信息转换为序列信息，并通过提高准确性、灵敏度和解决质量转移事件和评估错误发现的能力来改进肽识别。博士生将深入了解基于质谱学的蛋白质组学技术，并对蛋白质组学数据处理的计算方法进行文献综述，包括峰检测、肽谱匹配、寻找翻译后修饰和假阳性控制的统计方法。博士生还将学习使用各种工具进行生物信息学分析。学生将学会对大规模蛋白质组学数据进行前处理，执行适当的质量控制，理解并掌握峰检测、肽/蛋白质/PTM鉴定的各种工具。学习使用R/python语言进行定制分析，并在Unix下使用外壳脚本。博士生将利用亨斯利实验室和沃实验室提供的大量拟南芥和大麦的鸟枪式蛋白质组学数据，以及邓迪大学的合作者提供的用于磷酸化、S酰化和泛素化的PTM蛋白质组学数据集。博士生将开发一种新的方法，将大量信息转化为序列信息，改进多肽鉴定，并验证和评估所开发的植物蛋白质组学数据集的方法。这个项目为学生提供了一个很好的机会，学习跨越多学科研究的各种学科的各种技能，包括生物信息学、植物生物学和现代生物技术。生物信息学：学生将学习对大规模蛋白质组学数据进行前处理，进行适当的质量控制，理解并掌握各种峰值检测、肽/蛋白质/PTM鉴定工具。植物生物学：学习翻译后修饰，特别是S-酰化，及其在不同条件下的调节机制。生物技术：学生将学习基于质谱学的蛋白质组学技术，为蛋白质组学实验准备样本的方法，并利用室内植物抗体资源进行验证，以提取具有新肽或PSM的蛋白质。这个项目将为学生提供一个在数据分析和湿法实验室实验方面成为专家的绝佳机会。这项前沿研究还将使学生在四年的学习中接触到新方法和新技术。此外，这两个项目都为学生提供了多种机会，以海报和口头形式展示他们的作品。因此，学生将进入一个激动人心的智力和支持的环境。

Mass spectrometry (MS) based proteomics is the method of choice for characterizing proteins to understand biological functions and processes, elucidate signalling networks, discover disease biomarkers for human and identify key genes underlying important traits in plants. Computational methods for proteomics play an essential role in interpreting MS data and generating biological insights, but their potentials remains to be fully exploited. Particularly in a plant proteomics experiments, fewer than 20% of the high-quality MS/MS spectra acquired can be meaningfully interpreted. This largely reflects the limited sensitivity of current computational methods and the lack of complete, accurate and concise protein isoform sequence information. In this project, we aim to address these critical issues in proteomics by developing a novel probability based computational approach for Peptide Spectrum Match (PSM), which transforms the mass information to sequence information and improves peptide identification by increasing accuracy, sensitivity, and capability for resolving mass shifting events and assessing false discoveries. The PhD candidate will develop in-depth knowledge about the technology of mass spectrometry-based proteomics and carry out literature reviews on the computational methods for proteomics data processing, including peak detection, peptide spectrum match, searching for post translational modifications and statistical methods on false positive control. The PhD candidate will also learn to use a variety of tools for bio-informatic analysis. The student will learn to pre-process large scale proteomics data, perform proper quality controls, understand and master various tools on peak detection, peptide/protein/PTM identifications. Learn to carry out customized analysis in R/python language and use shell script under Unix. The PhD candidate make use of the extensive shotgun proteomics data of Arabidopsis and barley available in Hemsley lab and Waugh lab and PTM proteomics data sets for phosphorylation, S-acylation and ubiquitination from University of Dundee collaborators.The PhD candidate will develop a novel method that transforms the mass information to sequence information and improves peptide identification and validate and evaluate the developed methodology on proteomics datasets in plants. This project provides a great opportunity for the student to learn a diverse set of skills spanning a variety of subjects for multi-disciplinary research, including bioinformatics, plant biology and modern bio-technology. Bioinformatics: The student will learn to pre-process large scale proteomics data, perform proper quality controls, understand and master various tools on peak detection, peptide/protein/PTM identifications. Learn to carry out customized analysis in R/python language and use shell script under Unix.Plant biology: the student will learn about post-translational modification, particularly S-acylation, and its regulatory mechanism under different conditions. Bio-technology: The student will learn mass spectrometry-based proteomics technology, methods to prepare samples for proteomics experiments, and carry out validations using plant antibody resources in house to pull down proteins with novel peptides or PSMs. This project will provide an exceptional opportunity for a student to become expert in both data analysis and wet lab experiments. This cutting-edge research will also expose the student to new methods and new technologies through the four years of study. In addition, both programs offer multiple opportunities for students to present their work in poster and oral formats. The student will therefore enter a stimulating intellectual and supportive environment.