Dissecting treponemal immune-modulation to enable disease control.

剖析密螺旋体免疫调节以实现疾病控制。

• 批准号: BB/X016226/1
• 负责人: Nicholas Evans
• 金额: $ 100.48万
• 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: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FX016226%2F1
• 关键词: Dissecting; treponemal; immune; modulation; enable

Digital dermatitis (DD), considered caused by spirochete bacteria called Treponema, is a worldwide, severe infectious disease affecting multiple host species including cattle, sheep and goats. Globally, cattle are most frequently afflicted with inflamed lesions between the heel bulbs of feet causing severe lameness. The disease is of significance as it is extremely painful resulting in poor animal welfare. Whilst topical antibiotic treatment allows some healing, lesions frequently reappear and there is no single effective treatment. Moreover, severe economic losses result from reduced milk yield and reproductive ability whilst global health impacts ensue from increased antibiotic use and chemical footbathing. The UK economic cost is £74 million/year and worldwide tens of millions of animals are infected, annually costing at least a billion dollars. Generating affordable vaccines for important endemic diseases of livestock enables global uptake, increasing animal health, welfare and productivity whilst decreasing antibiotic use and antimicrobial resistance. This is especially important for bovine DD which is increasing in prevalence globally and continuing to emerge in new host species. Bacterial surface proteins are considered important vaccine candidates to provide protective immunity from a range of pathogenic spirochete bacteria. Immune evasion by spirochetes, is considered to involve these bacteria coating themselves with host molecules. Whilst DD treponemes are diverse, they must share near identical machinery for this immune-modulation, which must be present on the bacterial surface to allow host binding and thus represent ideal vaccine targets. Characterisation of bacterial surface proteins, especially those involved in immune evasion should therefore enable development of novel vaccines or therapeutics. Recent research, mutating bacterial surface proteins to prevent binding of host molecules, as well as enhancing protein stability, has increased the protective ability of these bacterial components when used as vaccines. The application of such novel protein engineering has been used in the development of a vaccine for an important human pathogen that is now licensed and can now be applied to veterinary pathogens. Moreover, cutting-edge advances in structure prediction by artificial intelligence (AI) are highly accurate and can now be used to guide such engineering. Here, we combine AI, synthetic biology and in silico approaches to guide identification and engineering of key cell surface proteins to develop a novel efficacious vaccine with broad treponeme specificity using a cutting edge enhanced reverse vaccinology pipeline.This study will 1) identify vaccine candidates using AI generated structural models and investigate functional diversity including quantifying whether orthologs from different species exhibit different adhesion abilities and whether orthologs from commensals lack ability to attach to key host molecules, 2) use sequence diversity/conservation and differences in adhesion ability together with AI generated structural models and in silico approaches to synthesise mutated surface proteins with restricted host attachment, 3) use sequence diversity together with AI generated structural models and in silico approaches to synthesise surface proteins with enhanced stability, 4) use a disease model to identify which engineered bacterial surface proteins are most protective and to decipher immunomodulatory ability of a DD treponeme surface associated sugar.Identifying and engineering DD vaccine candidates using the above synergistic methods, should better characterise causal bacteria, improve disease understanding, and generate a protective vaccine. Such studies are much needed to enable prevention of this severe, important global disease. Moreover, this novel, enhanced pipeline should enable reduced animal use in future vaccinology studies by reducing study candidate numbers using in silico methods.

数字皮肤炎（DD）被称为treponema引起的细菌，是一种全球物种，包括牛，绵羊和山羊，牛大部分都遭受了舒适性的舒适性病变。脚步数以千计的动物被感染，每年至少花费十亿美元的牲畜，可以增加动物健康，福利和生产力，从而降低抗生素的使用和抗菌耐药性。出现在新宿主物种中。 e涉及免疫逃避，使新的疫苗或EINS可以防止宿主分子的结合，并增强稳定性，在使用ASED ASED ASED疫苗时，可以增加对这些细菌的保护。在为兽医的兽医病原体（AI）预测的兽医病原体中，可以将疫苗用于人类病原体的重要人物病原体结合AI，合成生物学和用于指导关键细胞表面蛋白的识别和工程的计算机方法，以使用切割增强的反向串联管道来开发具有广泛treponeme特异性的AVEL有效疫苗。这将研究1）使用AI生成的结构模型和AI生成的结构模型和候选疫苗，调查功能，包括量化来自不同物种的直系同源物是否表现出不同的能力，以及来自共生的直系同源物是否缺乏与AI产生的结构模型以及在硅酸盐的方法中，以及在硅酸盐的方法中，粘附能力的差异以及粘附能力的差异以及静音方法的方法多样性以及AI生成的结构模型以及在硅化方法中综合表面伴随性的方法，4）使用疾病模型确定哪种发动机细菌表面蛋白最能使DD在Eme表面相关的糖中DD的免疫原子。协同方法应更好地表征贬值，并在这里产生这种研究，并通过减少研究研究候选数量，在未来的疫苗研究中减少动物的使用。