Informatics tools for exploiting ion mobility mass spectral data in proteomics

该应用程序旨在演示如何使用新兴技术离子迁移质谱（IMMS）来研究蛋白质。我们还将开发用于解释数据的相关软件包，使IMMS可以用作大规模实验（蛋白质组学）的分析工具。蛋白质组学已经成为一种非常宝贵的方法，通过检测和定量样品中存在的蛋白质来了解生物系统，例如，用于比较患病样品中存在的蛋白质与正常样品中存在的蛋白质，以深入了解疾病的分子机制。蛋白质组学中最重要的实验技术是质谱法，它通过分析蛋白质的短片段（称为肽）来鉴定蛋白质。每一次这样的分析都会产生一个由碎裂过程产生的不同质量（及其强度）的光谱。许多软件工具可用于解释这种质谱，并且这些软件工具使用统计技术来确定是否已经从谱上的复杂质量模式正确地鉴定了肽。这种统计分析是必要的，因为质谱的解释是非常具有挑战性的：每个光谱包含裂解产物的混合物加上相当大的背景噪音。在我们将采用的条件下，肽产生两种主要类型的裂解产物，称为B离子和y离子，它们一起可以提供关于被分析的肽序列的信息。然而，为了使这成为可能，我们需要知道哪些是B离子，哪些是y离子。区分光谱中的这两种类型的离子目前是困难的，并且经常导致对许多光谱的不正确或不完整的解释。最近在质谱仪的设计方面取得了技术上的进步。这种被称为离子迁移质谱（IMMS）的发展有可能简化光谱的解释。IMMS可用于检查肽片段的其他特性，基于它们通过充气室的速度。有证据表明，相同质量的B和y离子在这种腔室中具有不同的迁移率，理论上可以用于在分析之前区分离子类型。如果每种离子的类型都能自动识别，那么我们通过质谱分析蛋白质的能力就会有很大的提高。到目前为止，IMMS在蛋白质组学中的应用并不多，这是由于新仪器已经克服了某些技术限制，而且重要的是，因为没有软件工具能够使用这些数据来改进肽鉴定。在这个应用中，我们正在寻求开发IMMS，使其成为一种常规技术，提供改进的蛋白质组分析。首先，我们的目标是研究几个已知的标准蛋白质，以记录和了解由其肽片段化产生的离子的流动性。然后，我们将开发计算工具，可以使用这些信息来改善光谱的解释，允许肽被识别和表征，这将是非常具有挑战性的，如果不是不可能的，使用当前的技术。通过这种方式，我们打算证明IMMS技术的好处，以解决目前阻碍蛋白质组研究的几个关键挑战。

The application aims to demonstrate how an emerging technology, ion mobility mass spectrometry (IMMS), can be used to study proteins. We will also develop associated software packages for interpreting the data, allowing IMMS to be used as an analytical tool in large scale experiments (proteomics). Proteomics has become an invaluable methodology for understanding biological systems by the detection and quantification of the proteins present in a sample, used for example, to compare the proteins present in a diseased sample with those in a normal sample to gain insight to the molecular mechanisms of disease. The most important experimental technique in proteomics is mass spectrometry, which is used to identify proteins by analysis of the fragmentation of short pieces of proteins, called peptides. Each such analysis generates a spectrum of the different masses (and their intensities) that result from the fragmentation process. A number of software tools are available for interpreting such mass spectra and these use statistical techniques to determine if a peptide has been correctly identified from the complex pattern of masses on a spectrum. This statistical analysis is necessary because interpretation of mass spectra is highly challenging: each spectrum contains a mixture of fragmentation products plus considerable background noise. Under the conditions we will employ, peptides yield two main types of fragmentation products, called b ions and y ions, which, together, can give information about the peptide sequence being analysed. However, for this to be possible, we need to know which are the b ions and which the y ions. Differentiating these two types of ions within a spectrum is currently difficult and often leads to the incorrect or incomplete interpretation of many spectra. A recent technical advance has been made in the design of mass spectrometers. This development, called ion mobility mass spectrometry (IMMS), has the potential to simplify the interpretation of spectra. IMMS can be used to examine an additional property of peptide fragments, based on the speed at which they travel through a gas-filled chamber. There is evidence that b and y ions of the same mass have different mobilities in such a chamber, which in theory could be used to differentiate ion types prior to their analysis. If the type of each ion present could be identified automatically, there would be significant gains in our ability to characterise proteins by mass spectrometry. To date, IMMS has not been much used in proteomics due to certain technical limitations that newer instruments have overcome, and importantly, because there are no software tools capable of using these data to improve peptide identifications. In this application, we are seeking to develop IMMS such that it can become a routine technique offering improved proteome analysis. First we aim to study several known standard proteins to record and understand the mobility of ions produced by fragmentation of their peptides. We will then develop computational tools which can use this information to improve the interpretation of spectra, allowing peptides to be identified and characterised which would be highly challenging, if not impossible, using current technology. In this way, we intend to demonstrate the benefits of IMMS technology to solve several key challenges currently hindering proteome research.