Using immune cell repertoires to identify pathogen threats

使用免疫细胞库来识别病原体威胁

• 批准号: NE/X010295/1
• 负责人: Mark Viney
• 金额: $ 4.65万
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FX010295%2F1
• 关键词: Using; immune; cell; repertoires; identify

Wild animals live with a myriad of infections - viruses, bacteria, fungi, worms. The harm that these infections cause and the costly efforts animals make to resist these infections affects their ecology and the evolution. So, if we want to properly understand wild animals, we also need to know what infections they have and what immune responses they make against them.Animal infections also matter directly to humans because they can sometimes jump into humans and then transmit among people directly, so-called zoonoses. The recent COVID pandemic is the most recent example of a zoonosis, in this case with a virus coming from bats. Predicting future zoonoses is another reason why we need to know the infections of wild animals.But, it is really quite difficult to find out what infections wild animals actually have. While we've lots of specific tests for common infections of humans, livestock and pets these often don't work with wild animals. Our long term vision to solve this problem is to use wild animals' immune cells to find out what infections wild animals have. Here we would harness what immune systems have evolved to do so well: to look very carefully for pathogens everywhere inside an animal. Specifically, when an animal makes an immune response, its immune cells take small bits of the pathogen to then generate a very targeted response. There are different genetic types of immune cells, one for each different pathogen, so that individual animals have a very large collection of different immune cell types. By collecting these cells and sequencing the gene that makes them specific for a pathogen, there is the potential to identify the pathogen infecting the animals.In the work we are now proposing we want to take the first step on this path: to look at the diversity of immune cell specificity genes in a wild animal, specifically wild mice. We already know that wild mouse immune responses are quite different to those of lab mice, so we expect to see a new pattern of immune cell types in wild mice. We expect the wild animals to have a more diverse set of immune cells than lab mice, because wild mice are infected with more, diverse infections. We will also see to what extent different individual wild mice share immune cell types; such sharing would be evidence that different individuals have the same infection.The work we're proposing is "blue skies" - that is to have a first look at immune cell diversity in wild animals to see what we find. But, we are doing this with the longer term vison of using this method to study wild animal infections and immune responses, to better understand wild animal ecology, but to also use this to survey wild animals for infections and the next zoonosis that could lead to a global pandemic.

野生动物生活在病毒、细菌、真菌、蠕虫等无数传染病的环境中。这些感染所造成的伤害和动物为抵抗这些感染所付出的代价影响了它们的生态和进化。因此，如果我们想要正确地了解野生动物，我们还需要知道它们感染了什么，以及它们对它们产生了什么样的免疫反应。动物感染对人类也有直接的影响，因为它们有时会跳到人类身上，然后直接在人与人之间传播，即所谓的人畜共患病。最近的COVID大流行是人畜共患病的最新例子，在这种情况下，病毒来自蝙蝠。预测未来的人畜共患病是我们需要了解野生动物感染的另一个原因。但是，要找出野生动物实际上感染了什么真的很困难。虽然我们有很多针对人类、牲畜和宠物常见感染的特异性测试，但这些测试通常对野生动物不起作用。我们解决这个问题的长期愿景是利用野生动物的免疫细胞来找出野生动物的感染。在这里，我们将利用免疫系统已经进化得很好的东西：非常仔细地寻找动物体内各处的病原体。具体来说，当动物产生免疫反应时，它的免疫细胞会吸收少量的病原体，然后产生非常有针对性的反应。免疫细胞有不同的遗传类型，每种不同的病原体都有一种，所以个体动物有非常大的不同免疫细胞类型的集合。通过收集这些细胞并对使它们对病原体具有特异性的基因进行测序，有可能识别感染动物的病原体。在我们现在提出的工作中，我们希望在这条道路上迈出第一步：观察野生动物，特别是野生小鼠的免疫细胞特异性基因的多样性。我们已经知道野生小鼠的免疫反应与实验室小鼠的免疫反应完全不同，因此我们希望在野生小鼠中看到一种新的免疫细胞类型。我们预计野生动物比实验室小鼠具有更多样化的免疫细胞，因为野生小鼠感染了更多，更多样化的感染。我们还将看到不同的野生小鼠个体在多大程度上共享免疫细胞类型;这种共享将是不同个体具有相同感染的证据。我们提议的工作是“蓝天”--即首先看看野生动物的免疫细胞多样性，看看我们发现了什么。但是，我们这样做的长远目的是使用这种方法来研究野生动物的感染和免疫反应，更好地了解野生动物生态学，同时也用这种方法来调查野生动物的感染和下一个可能导致全球大流行的人畜共患病。

项目成果

The ecology of viruses in urban rodents with a focus on SARS-CoV-2.

• DOI: 10.1080/22221751.2023.2217940
• 发表时间: 2023-12
• 期刊: Emerging microbes & infections
• 影响因子: 13.2