Advancing Multiplexed Isobaric Tag-based Strategies for Proteome Profiling

摘要 样品多路复用已经成为最近许多大规模蛋白质组学研究的催化剂。的出现 同量异位素标记，如iTRAQ（用于相对和绝对定量的同量异位素标记）和TMT所推广的 （串联质量标签）试剂，已成为典型的方法，多路蛋白表达 侧写存在两种主要的数据采集方法，每种方法都有自己的优点和缺点。一是 仅MS 2方法（本文中的“MS 2-IDQ”）可以在单个谱中鉴定（ID）和定量（Q）肽。 第二，同步前兆选择（SPS）-MS 3方法在MS 2阶段识别前兆，但 然后从MS 2级选择一系列碎片离子，这些碎片离子被进一步碎片化并作为MS 3读出 用于定量测量的光谱。MS 2-IDQ遭受MS 2-IDQ的共分离和共片段化。 前体离子（“干扰”），虽然SPS-MS 3有助于减轻干扰，但其代价是 速度，这是采集长MS 3扫描的直接结果。在这里，我们的目标是开发，评估和应用一个 新的数据采集平台，融合了当前方法的优点，并阐明了它们的主要警告。 赛默飞世尔科技公司的轨道阱聚变和Lumos仪器的最新发展是， 仪器应用程序编程接口（iAPI）的实现，该接口允许对 仪器超出了制造商的内置功能。使用这个界面，Gygi实验室和 其他人已经开始创建定制的即时实时搜索（RTS）算法。RTS使MS 2 频谱进行实时搜索，并作出关于MS 3扫描是否可能导致 显著的肽定量测量。通过省略MS 3扫描，可以收集更多的MS 2光谱 并且可以鉴定新的肽。使用iAPI，可以添加功能，包括目标列表和限制 设置每个蛋白质定量的肽的数量（在非常丰富和/或大的蛋白质的情况下）， 在转化研究中是有用的，例如血浆样本和其他体液的询问。 我们的具体目标是进一步发展成功应用RTS的方法， MS3。在具体目标1中，我们将使用TKO和 基于TMT的蛋白质组分析的HYPER（人酵母肽资源）标准。在具体目标2中， 将在几种样品类型（细菌培养物、小鼠组织、血液， 脑脊髓液、人细胞系和酵母培养物）与传统的MS 2-IDQ和SPS-MS 3方法进行比较 （具体目标2）。最后，在具体目标3中，我们将应用RTS-MS 3平台来分析整个酵母 缺失菌株收集在两种生长条件下，这将产生最大的酵母蛋白表达 分析数据集。实现这三个具体目标将建立RTS-MS 3平台， 颠覆性的技术，以目前的同量异位素标签为基础的多路复用方法，并将标志着一个范式转变， 基于同量异位素标签的定量蛋白质组学。

ABSTRACT Sample multiplexing has been the catalyst for many recent large-scale proteomics initiatives. The advent of isobaric tagging, as popularized by iTRAQ (isobaric tags for relative and absolute quantitation) and TMT (tandem mass tag) reagents, has become the quintessential methodology for multiplexed protein expression profiling. Two major data acquisition methods exist each with its own advantages and disadvantages. First, the MS2-only method (“MS2-IDQ” herein) can identify (ID) and quantify (Q) a peptide in a single spectrum. Second, the synchronous precursor selection (SPS)-MS3 method identifies the precursor in the MS2 stage, but then selects a series of fragment ions from the MS2 stage that are fragmented further and read out as an MS3 spectrum for quantification measurements. MS2-IDQ suffers from the co-isolation and co-fragmentation of precursor ions (“interference”), and although SPS-MS3 helps to alleviate interference, it is at the expense of speed, a direct result from the acquisition of long MS3 scans. Here we aim to develop, evaluate, and apply a novel data acquisition platform that merges the benefits of current methods and alleviates their major caveats. A recent development on ThermoFisher Scientific's Orbitrap Fusion and Lumos instruments has been the implementation of an instrument application programming interface (iAPI) that allows for expanded control of the instrumentation beyond the manufacturer's built-in functionality. Using this interface, the Gygi Lab and others have begun to create custom on-the-fly real-time search (RTS) algorithms. RTS enables an MS2 spectrum to be searched in real-time and decisions to be made as to whether an MS3 scan is likely to result in a significant peptide quantification measurement. By omitting MS3 scans, more MS2 spectra can be collected and new peptides may be identified. Using the iAPI, functions can be added including targeted lists and limits set for the number of peptides quantified per protein (in the case of very abundant and/or large proteins), which is useful in translational research, such as the interrogation of plasma samples and other body fluids. Our Specific Aims are geared toward developing further the methodology for successful application of RTS- MS3. In Specific Aim 1, we will benchmark emerging algorithms for RTS-MS3 using both the TKO and HYPER (human-yeast peptide resource) standards for TMT-based proteome profiling. In Specific Aim 2, we will evaluate the RTS-MS3 platform across several sample types (bacterial cultures, mouse tissues, blood, cerebral spinal fluid, human cell lines, and yeast cultures) against traditional MS2-IDQ and SPS-MS3 methods (Specific Aim 2). Finally, in Specific Aim 3 we will apply the RTS-MS3 platform to analyze an entire Yeast Deletion Strain Collection under two growth conditions, which will produce the largest yeast protein expression profiling data set to date. Accomplishing these three Specific Aims will establish the RTS-MS3 platform as a disruptive technology to current isobaric tag-based multiplexing methodology and will mark a paradigm shift in isobaric tag-based quantitative proteomics.