An integrated approach to tackling drug resistance in livestock trypanosomes.

耐药性是全球许多疾病日益严重的问题。锥虫是采采蝇传播的单细胞生物体，主要在撒哈拉以南非洲引起牛-非洲动物锥虫病(AAT)的严重疾病，那里每年约有6000万头牛处于危险之中，AAT导致300万人死亡。农民对抗AAT的主要措施是药物治疗，但我们只有两种主要药物，这两种药物都已有50年的历史，并被广泛使用。对这些药物的抗药性报告越来越多，正在开发的药物很少，这意味着目前的控制方法具有非常令人怀疑的可持续性。尽管这是一个如此重要的问题，但我们对锥虫如何抵抗药物的影响，以及AAT耐药性如何出现和传播知之甚少。因此，我们部署知情战略以缓解这一问题的能力有限。该项目旨在产生数据和资源，以弥合这些知识差距。这些申请者自2011年以来一直在坦桑尼亚北部的一个地区工作。最近，农民报告药物治疗失败，需要更频繁地使用预防性药物异美他定(ISM)，这表明出现了耐药性。我们已经从2011年至2017年期间抽样的该地区农场队列中获得了5,000头牛和10,000只采采蝇的样本，以及农民药物使用的信息。此外，我们还开发了在实验室研究相关锥虫物种的资源和能力(大多数信息来自人类感染的布氏锥虫，但越来越明显的是，这些是非常不同的生物)。这个初步数据和资源平台将被用来回答我们的核心假设，即坦桑尼亚动物锥虫病的管理受到ISM新出现的未能提供足够预防措施的威胁。为了验证这一假设，我们将解决四个主要的研究问题：(I)ISM耐药发生的可能机制是什么，我们能否确定一个标记？(Ii)ISM失败的程度和原因是什么？(Iii)ISM失败的流行病学后果是什么？(Iv)如何防止对包括新药在内的色胺类药物的耐药性？为了实现这一目标，我们将：(1)通过在实验室产生耐药寄生虫，并使用生化、分子和基因组分析比较耐药寄生虫和敏感寄生虫来识别ISM抗性机制；(2)收集同一地区的现场数据，以便评估药物使用和药物质量，分离耐药寄生虫，并评估现场药物使用和耐药性的流行病学；(3)使用实验室和现场数据相结合的数据，生成一个数学模型，其参数由实验室和现场数据提供信息，使我们能够准确地评估抗药性是如何在田间AAT中产生和传播的；以及(4)应用模型和预测情景，该情景将告知我们的工业合作伙伴GALVmed对正在开发的一种新的杀胰酶化合物的抗药性的选择和传播。该项目的成果将为AAT耐药性的流行病学提供前所未有的详细见解，揭示与疾病相关的锥虫物种(包括潜在标记物)的耐药性机制，并将开发数学模型的首次应用，重要的是使用准确的参数，以深入了解AAT耐药性的出现和传播的动态。除了提供新的见解外，这些成果还有可能通过确定最有可能减轻耐药性的策略，为药物开发和药物使用提供信息，从而使现有药物和新药的寿命最大化。

Drug resistance is an increasing problem for many diseases worldwide. Trypanosomes are tsetse-fly transmitted single-celled organisms that cause serious disease in cattle - African Animal Trypanosomiasis (AAT), mainly in sub-Saharan Africa, where approximately 60 million cattle are at risk and AAT kills 3 million each year. The main measure farmers have to combat AAT is drug treatment, but we only have two main drugs, both of which are >50 years old and widely used. Resistance to these drugs is increasingly reported, and there are very few drugs in the development pipeline, meaning the current control methods have very doubtful sustainability. Despite being such a significant issue, we know very little about how trypanosomes resist the effect of the drug, and how AAT drug resistance emerges and spreads. Therefore we are limited in our ability to deploy informed strategies to mitigate the problem. This project aims to generate data and resources to bridge these knowledge gaps. The applicants have been working in an area in Northern Tanzania since 2011. Recently farmers have been reporting drug treatment failure and the need to use increasing amounts of the prophylactic drug Isometamidium chloride (ISM) more frequently, suggesting emerging resistance.We already have samples from 5,000 cattle and 10,000 tsetse flies, as well as information on farmer drug use, from a cohort of farms in the area sampled between 2011 and 2017. Additionally, we have developed resources and capabilities for working on the relevant trypanosome species, Trypanosoma congolense, in the laboratory (most information derives from the human-infective Trypanosoma brucei, but it is increasingly apparent that these are very distinct organisms). This platform of preliminary data and resources will be used to answer our central hypothesis, that the management of animal trypanosomiasis in Tanzania is threatened by an emerging failure of ISM to provide adequate prophylaxis. To test this hypothesis, we will address four main research questions: (i) what are the likely mechanisms by which resistance to ISM occurs and can we identify a marker?; (ii) what are the extent and cause of ISM failure?; (iii) what are the epidemiological consequences of ISM failure?; and (iv) how might resistance to trypanocides, including new drugs, be prevented? To achieve this we will: (1) identify ISM resistance mechanisms by generating resistant parasites in the laboratory and comparing resistant and susceptible parasites using biochemical, molecular and genomic analysis; (2) collect field data in the same area in order to assess drug use and drug quality, isolate drug resistant parasites, and assess the epidemiology of drug use and drug resistance in the field; (3) using data combined from the laboratory and the field, generate a mathematical model whose parameters are informed by both the laboratory and field data, allowing us to accurately assess how resistance emerges and spreads in AAT in the field; and (4) apply the model and predict scenarios that will inform on the selection and spread of resistance for a new trypanocidal compound in development by our industrial partners, GALVmed. The outputs of this project would provide unprecedented and detailed insight into the epidemiology of AAT drug resistance, uncover mechanisms of drug resistance in the disease-relevant trypanosome species (including potential markers), and will develop the first application of mathematical modelling, importantly using accurate parameters, to provide insights into the dynamics of AAT drug resistance emergence and spread. As well as providing novel insights, the outputs have the potential to inform drug development and drug usage, by identifying strategies that will have the best chances of mitigating resistance, and therefore maximising the lifetime of both existing and novel drugs.