Real time optimization of electron-based fragmentation for middle and top-down proteomics in mass spectrometry

质谱中中自上而下蛋白质组学基于电子的碎片实时优化

• 批准号: 10081127
• 负责人: Valery G. Voinov
• 金额: $ 21.28万
• 依托单位: E-MSION, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10081127
• 关键词: Acceleration; Affect; Arthritis; Artificial Intelligence; Automobile Driving; Basic Science; Big Data; Biological; Biological Products; Biological Response Modifier Therapy; Businesses; Cells; Collection; Communities; Complex; Computer software; Computers; Continuous Infusion; DNA Sequence; Data; Data Analyses; Data Collection; Diabetes Mellitus; Diagnosis; Digital Signal Processing; Disease; Dissociation; Electronics; Electrons; Engineering; Face; Family; Feasibility Studies; Generations; Goals; Grant; Health; Heart Diseases; Individual; Industrialization; Industry; Ions; Isoleucine; Laboratories; Leucine; Macromolecular Complexes; Malignant Neoplasms; Maps; Mass Spectrum Analysis; Methodology; Methods; Modernization; Multiprotein Complexes; Nerve Degeneration; Noise; Optics; Peptides; Periodicity; Phase; Polysaccharides; Post-Translational Protein Processing; Price; Process; Protein Analysis; Protein Fragment; Proteins; Proteomics; Reading; Research Personnel; Resolution; Signal Transduction; Small Business Innovation Research Grant; Speed; Structure; Techniques; Technology; Time; Tissues; Transistors; Trypsin; United States National Institutes of Health; Vendor; Water; Work; base; blind; computational platform; computerized data processing; cost effective; data acquisition; diagnostic biomarker; disulfide bond; electron energy; encryption; experience; fragment X; improved; instrument; instrumentation; interest; macromolecule; mass spectrometer; meetings; operation; preservation; programs; protein complex; signal processing; success; therapeutic biomarker

The identification and quantification of biological macromolecules remains challenging despite major advances in the speed, resolution and mass accuracy of modern mass spectrometers. A key weakness with current instrumentation lies in the methods used to induce fragmentation. The reliance in particular on collision-induced dissociation (CID) has limited such analyses to bottom-up workflows of trypsin-digested peptides of 10-30 residues. At e-MSion, we have developed an efficient electron-fragmentation technology called ExD for large proteins and are now co-marketed our ExD Option with Agilent, and soon will be with Thermo and Waters instruments. What has really captured the interest of the biopharma and top-down communities in the past year is the exceptional sequence coverage of native proteins we obtain with the same ExD cell. The resulting spectra are less congested than those obtained with currently available ETD/UVPD/CID fragmentation methodologies. We have shown that our technology works faster and gives cleaner spectra with more complete dissociation with larger macromolecular protein complexes than has ever been possible before, while still preserving labile post translational modifications. In addition, fragmentation with higher energy electrons can be used to provide complementary data to improve protein and glycan identification. The challenge now has become how to optimally collect and process these data to maximize the utility of ExD fragmentation. Last summer, Xilinx released its Versal Adaptive Compute Acceleration Platform (ACAP), a massively parallel processor with 50 billion transistors targeted to transform digital signal processing, handling of big data and artificial intelligence. This ACAP technology has already accelerated Illumina DNA sequence assembly by 90-fold. Our feasibility question asks how to effectively harness this new highly parallelized technology to preprocess complex top-down mass spectra on- the-fly. This will allow us to actively optimize data acquisition by enabling adaptive operation of the ExD cell and mass spectrometer. The objective is to maximize both fragmentation and dissociation of native proteins, enabling faster and comprehensive characterization of challenging proteoforms important to the biopharmaceutical industry and biomedical researchers. Success will offer an extremely fast, cost-effective solution to characterize complexes of macromolecules under native conditions with increased accuracy, speed, and fewer misidentifications. Our ExD technology with the Versal ACAP can be both retrofitted into existing mass spectrometers as well as being available in new generations of mass spectrometers at a price below other less-effective alternative fragmentation technologies like ETD and UVPD. Thus, it will provide new abilities for many NIH investigators to advance basic research, probe disease mechanisms and permit more sophisticated searches for both diagnostic and therapeutic biomarkers.

生物大分子的鉴定和定量仍然具有挑战性，尽管 现代质谱仪在速度、分辨率和质量精度方面的进展。的一个主要弱点 目前的手段在于用于诱导碎片化的方法。尤其是对 碰撞诱导解离(CID)将这种分析限制在胰酶消化的自下而上的工作流程中 10-30个残基的多肽。在e-MSion，我们开发了一种高效的电子碎裂技术 被称为EXD的大型蛋白质，现在与安捷伦共同营销我们的EXD选项，不久将与 Thermo and Waters仪器。什么真正吸引了生物制药和自上而下的兴趣 在过去的一年中，我们获得的天然蛋白质的特殊序列覆盖率与 EXD单元格。由此得到的光谱比目前可用的得到的光谱不那么拥挤 ETD/UVPD/CID碎片方法。我们已经证明，我们的技术工作得更快，并提供 更干净的光谱，与更大的大分子蛋白质复合体更完全解离 以前从未实现过的，同时仍然保留了不稳定的翻译后修改。此外, 高能电子的碎裂可以用来提供补充数据来改善蛋白质 和葡聚糖鉴定。现在的挑战是如何以最佳方式收集和处理这些数据 最大限度地发挥EXD碎片的效用。去年夏天，Xilinx发布了Versal自适应计算 加速平台(ACAP)，一个拥有500亿个晶体管的大规模并行处理器，旨在 转变数字信号处理、大数据处理和人工智能。这项ACAP技术具有 已经将Illumina DNA序列组装加速了90倍。我们的可行性问题是问如何 有效地利用这种高度并行化的新技术来对复杂的自上而下的质谱图进行前处理- 苍蝇。这将允许我们通过启用EXD单元的自适应操作来主动优化数据采集 和质谱仪。其目标是最大化天然蛋白质的碎裂和解离， 使具有挑战性的蛋白质形式能够更快、更全面地表征 生物制药行业和生物医学研究人员。 Success将提供一个极快、经济高效的解决方案来表征复杂的 在自然条件下的大分子，具有更高的准确性、速度和更少的误识别。我们的 带有Versal ACAP的EXD技术既可以改装到现有的质谱仪上，也可以改装成 在新一代质谱仪中以低于其他效率较低的替代产品的价格提供 ETD和UVPD等碎片化技术。因此，它将为许多NIH提供新的能力 调查人员将推进基础研究，探索疾病机制，并允许进行更复杂的搜索 用于诊断和治疗生物标记物。