Proteomics Goes Viral: Novel Resources for Identification and Quantification of Virus Proteins

病毒在自然界扮演着重要的角色，常常对人类人口产生深远的影响。然而，我们对病毒感染的分子机制的理解受到当前数据分析方法的限制。在这个项目中，我们将生产创新的新软件，为研究人员提供更准确的病毒感染细胞中发生的情况的图像。现代生物分析科学提供了许多工具，可以帮助建立对生物系统的理解。这些工具包括高分辨率成像、下一代测序、代谢组学和蛋白质组学。蛋白质组学是这项提议的重点，它旨在揭示给定样本中蛋白质的身份和数量。对病毒感染的研究提出了特别的挑战，因为病毒只在宿主体内发挥作用(例如人类的流感)，因此分析必须同时对宿主和病毒进行。(事实上，大多数研究兴趣在于宿主和病毒之间的相互作用。)病毒的研究更加复杂，因为病毒进化迅速，经常产生具有不同基因组的新菌株，以努力逃避宿主的免疫系统。这使得研究病毒蛋白质变得困难，因为我们不能像在高等生物体中那样依赖于给定的蛋白质由单一的共识序列代表。今天使用的蛋白质组学有两种主要类型：鸟枪式蛋白质组学和选择性反应监测(SRM)。这两种方法都遵循这样一个过程，即在被研究的样本中加入一种酶，将所有蛋白质分解成更容易管理的亚段(多肽)。然后，样品由一种名为液色谱串联质谱仪(LC-MS/MS)的仪器进行分析，该仪器提供了大量数据，可用于确定样品中存在哪些多肽，并通过推断哪些蛋白质存在。SRM是一种有针对性的技术，在这种技术中，LC-MS/MS被编程为寻找与感兴趣的蛋白质相对应的特定多肽，从而最大化灵敏度。猎枪蛋白质组学表面上是一种更开放的技术，因为它考虑了样本中可能存在的所有蛋白质，但这仍然需要事先编制所有这些蛋白质的有限序列列表。因此，对于宿主病毒研究，猎枪蛋白质组学和SRM都需要事先了解样本中可能存在的来自病毒和宿主的蛋白质序列。对于鸟枪式蛋白质组学，我们只需用可能存在于该宿主中的所有病毒株的蛋白质列表来扩充宿主蛋白质序列。然而，由于需要考虑这么多不同的菌株，搜索空间变得太大，错误阳性识别的概率变得不可接受。同样，在一次SRM实验中监测如此多的多肽也是不可能的。该项目将生产专门为支持宿主病毒蛋白质组学研究而设计的创新软件。该软件的一个部分将首次利用不同病毒株之间的关系知识，在处理来自鸟枪式蛋白质组学的数据时将搜索空间降至最小，从而实现更可靠、更灵敏的蛋白质识别。软件的另一部分将使用类似的方法来支持SRM实验的设计，以监测宿主内的病毒蛋白。这些进展将显著提高蛋白质组学在宿主病毒研究中的适用性，从而在该项目(我们将进行两个小实验，包括寻找以前未证实的基因产品)和之外的方面带来新的生物学见解。

Viruses play a significant role in the natural world, often with profound effects for the human population. However, our understanding of the molecular mechanisms of virus infection is being held back by limitations in current data analysis methods. In this project we will produce innovative new software that will provide researchers with a much more accurate picture of what is happening in virus infected cells.Modern bioanalytical science provides many tools that can be used to help build understanding of biological systems. These tools include high resolution imaging, next generation sequencing, metabolomics and proteomics. Proteomics, which aims to reveal the identity and quantity of proteins in a given sample, is the focus of this proposal. The study of viral infections poses particular challenges because viruses only function within a host organism (e.g. influenza in human) so analysis must be of both the host and virus together. (Indeed, it is the interaction between host and virus where most research interest lies.) Virus studies are further complicated because viruses evolve rapidly, frequently producing new strains with different genomes in an effort to evade the host's immune system. This makes it difficult to study virus proteins because we cannot rely on a given protein being represented by a single consensus sequence as it would be in a higher organism.There are two main types of proteomics in use today: shotgun proteomics and selected reaction monitoring (SRM). Both of these follow a process in which an enzyme is added to the sample under study to break all the proteins down into more manageable sub-sections (peptides). The sample is then analysed by an instrument called a liquid chromatograph tandem mass spectrometer (LC-MS/MS) which provides large amounts of data that can be used to determine which peptides, and by inference which proteins, were present in the sample. SRM is a targeted technique, where the LC-MS/MS is programmed to look for specific peptides corresponding to proteins of interest, thereby maximising sensitivity. Shotgun proteomics is ostensibly the more open technique in that it considers all proteins that may be present in the sample, but this still requires a finite list of the sequences of all those proteins to be compiled beforehand.So for a host-virus study, both shotgun proteomics and SRM require prior knowledge of the protein sequences that are likely to be in the sample, from both virus and host. For shotgun proteomics, we could just augment the list of host protein sequences with a list of proteins from all virus strains that might be present in that host. However, with so many different strains to consider, the search space becomes too large and the probability of false positive identifications becomes unacceptable. Similarly, it would be impossible to monitor so many peptides in a single SRM experiment.This project will produce innovative new software designed specifically to support host-virus proteomics studies. One part of the software will, for the first time, use knowledge of relationships between different virus strains to minimise the search space when processing data from shotgun proteomics, resulting in more reliable and more sensitive protein identification. The other part of the software will use a similar approach to support the design of SRM experiments for monitoring virus proteins within their hosts. These developments will significantly increase the applicability of proteomics to host-virus studies, leading to new biological insights both within this project (we will perform two small experiments, including looking for previously unconfirmed gene products) and beyond.