ABI Innovation: ProteoCarta: a community-scale resource for multi-species proteomics big data

蛋白质组学的研究重点是蛋白质的高通量分析，其最终目标是了解它们在简单和复杂生物体的分子生物学中的作用。随着质谱（MS）技术的成功发展，已经能够鉴定和定量数百种物种中的数千种蛋白质，高通量串联质谱方法已成为绝大多数大规模蛋白质组学研究的首选方法。数据采集正在以越来越快的速度进行，并且，结合大规模存储库（例如，PRIDE， MassIVE等）的可靠性以及期刊出版质量和注释指南，结果是公众可以获得数百tb的记录良好的蛋白质组学MS数据。蛋白质组学数据的总量目前大约每1.5年翻一番。在这9000多个公共数据集中有巨大的潜力有待开发。不幸的是，共享原始数据的动力并没有伴随着提供蛋白质鉴定和丰度数据的相应努力，这些数据是由质谱专家进行初步验证和随后由非质谱专家重新使用所必需的。目前，在所有公开的非人类蛋白质组学质谱数据中，只有不到0.1%的数据报告了显示可接受的统计控制的最低标准的鉴定；基本上没有数据集报告定量结果。通过该奖项创建的ProteoCarta平台将通过以下方式解决这一问题：i)使用先进的计算质谱工作流程系统地重新分析公共数据集；ii)将结果组织在结构化数据库中，以便通过直观的查询界面访问结果。该方案建立在计算质谱平台的基础上，该平台已经处理了来自122个国家的数千名用户的70万个工作中超过100亿个光谱，旨在通过一个新的ProteoCarta资源来解决这一社区规模的挑战，该资源可以系统地重新处理来自数百个物种的蛋白质组学质谱大数据，并旨在将所有结果整合到一个开放的知识库中，索引储存库规模的全球蛋白质组学数据。ProteoCarta将显著扩展最先进的算法，使其能够分析数百tb的数据，并将扩展和集成新的光谱网络算法，用于大规模发现样品和物种内部和跨物种的蛋白质变异，包括序列变异的MS检测以及发现意想不到的或新颖的翻译后修饰。除了以标准的开放格式发布所有数据和分析结果外，ProteoCarta的结果将直接附加到重新分析的公共数据集中，并存储在MassIVE中，因此数百名科学家将自动收到更新通知，并直接鼓励他们在自己的数据上积极探索新的结果。资源链接将通过https://cseweb.ucsd.edu/~nbandeir/software.html和https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp提供。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Proteomics research focuses on high throughput analysis of proteins, with the ultimate goal of understanding their role in the molecular biology of both simple and complex organisms. Following the successful development of mass spectrometry (MS) technologies, that have enabled the identification and quantification of many thousands of proteins in hundreds of species, the high throughput tandem mass spectrometry approach has become the method of choice for the overwhelming majority of large scale proteomics studies. Data acquisition has proceeding at faster and faster rates, and, combined with the reliability of large scale repositories (e.g., PRIDE, MassIVE, etc) and with journal publication guidelines for quality and annotation, the result has been public availability of hundreds of terabytes of well documented proteomics MS data. The total volume of proteomics data is currently doubling about every 1.5 years. There is tremendous potential for untapped discoveries lying in these 9000+ public datasets. Unfortunately the drive for sharing of raw data has not been accompanied by corresponding efforts to provide protein identification and abundance data, that are required for initial verification by MS experts and subsequent re-use by scientists who are not MS experts. As it stands today, less than 0.1% of all public non-human proteomics MS data only report identifications at the most minimal standards that show acceptable statistical controls; essentially no datasets report quantitative results. The ProteoCarta platform created through this award will address this problem by i) systematically reanalyzing public datasets using advanced computational mass spectrometry workflows and ii) organizing the results in a structured database so that results will be accessible through intuitive query interfaces.Building on computational MS platforms that have already processed over 10 billion spectra in 700,000 jobs from thousands of users in 122 countries, this proposal aims to address this community-scale challenge with a new ProteoCarta resource equipped to systematically reprocess proteomics MS big data from hundreds of species and designed to integrate all results into an open knowledge base that indexes repository-scale global proteomics data. ProteoCarta will significantly scale state of the art algorithms to enable analysis of hundreds of terabytes of data and will extend and integrate new spectral network algorithms for large scale discovery of protein variations within and across samples and species, including MS detection of sequence variants as well as discovery of unexpected or novel post-translational modifications. In addition to releasing all data and analysis results in standard open formats, ProteoCarta results will be directly attached to reanalyzed public datasets, to be stored at MassIVE, whereby hundreds of scientists will be automatically notified of the updates and directly encouraged to actively explore the new results on their own data. Links to resources will be provided through https://cseweb.ucsd.edu/~nbandeir/software.html and https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp .This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.