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）被认为是螺旋体细菌引起的称为Treponema，是一种全球，严重的传染病，影响了多种宿主物种，包括牛，绵羊和山羊。在全球范围内，牛最常见于脚后跟灯泡之间发炎的病变，导致严重的la行。这种疾病具有重要意义，因为它极为痛苦，导致动物福利不良。虽然局部抗生素治疗可以进行一些愈合，但病变经常出现，并且没有单一的有效治疗方法。此外，由于牛奶产量的降低和生殖能力降低而导致严重的经济损失，而全球健康的抗生素使用和化学脚注会影响拥有。英国的经济成本为每年7400万英镑，全世界数以千万计的动物被感染，每年至少耗资10亿美元。为牲畜的重要内在疾病产生负担得起的疫苗，它可以使全球吸收，提高动物健康，福利和生产力，同时降低抗生素使用和抗菌素的耐药性。这对于牛DD尤其重要，该牛在全球范围内越来越多，并继续在新宿主物种中出现。细菌表面蛋白被认为是重要的候选疫苗，可提供一系列致病性螺旋菌细菌的保护性免疫。螺旋体的免疫进化被认为涉及这些细菌涂有宿主分子。虽然DD treponemes有分歧，但它们必须在相同的机械上共享该免疫调节的机械，必须存在于细菌表面上以允许宿主结合并因此代表理想的疫苗靶标。因此，细菌表面蛋白的表征，尤其是参与免疫抗性的蛋白，应促进新型疫苗或治疗的发展。最近的研究，突变细菌表面蛋白以防止宿主分子的结合以及增强蛋白质稳定性，在用作疫苗时提高了这些细菌成分的保护能力。这种新型蛋白质工程的应用已用于开发疫苗的重要人类病原体，该病原体现在已获得许可，现在可以应用于兽医病原体。此外，人工智能（AI）在结构预测方面的尖端进步非常准确，现在可以用来指导这种工程。在这里，我们结合了AI，合成生物学和在硅酸方法中，以指导关键细胞表面蛋白的识别和工程，使用尖端的疫苗疫苗管道来开发具有广泛treponome特异性的新型有效疫苗，这将增强反向疫苗管道。1）使用AI产生的结构模型，是否具有量化的量化，是否识别出量的量化，是否识别出AI生成的量化，是否具有量化的量化，是否具有量化的量化，是否具有量化的量化，是否具有量化的量化，是否具有量化的量化，是否具有量化的量化，是否具有量化的量化，是否具有量化的量化，是否具有量子的功能，是否具有量化的功能，或者是否具有量化的功能，或者是否具有量化的功能，是否具有量化的功能性，或2）使用序列多样性/保护和粘合能力的差异以及AI生成的结构模型以及在硅氧上使用限制性宿主附着的合成表面蛋白质，3）使用序列多样性，使用AI生成的结构蛋白质，并在硅质上识别硅质，并在硅质上使用硅质，从而在粘合蛋白上使用硅质，从而在硅质上使用硅质，从而在硅质上使用硅质，从而使合成的表面蛋白质以及在硅质上识别硅质，从而在粘合蛋白中使用AI INSTINE，从而在粘合蛋白中使用AI INSTICE，从而在粘合蛋白中使用AI INSTICE，从而在硅质上使用硅质，从而使硅质多样性与硅质相关，从而使合成的表面蛋白质以及在硅质上识别合成的，细菌表面蛋白受到最保护，并且可以使用上述协同方法识别和工程DD疫苗的候选糖类的DD TREPONOME表面糖的免疫调节能力，应更好地表征毒细菌，改善疾病的理解并产生保护性疫苗。这样的研究迫切需要预防这种严重的全球疾病。此外，这种新颖的，增强的管道应通过使用计算机方法减少研究候选数量来减少未来的疫苗研究中的动物使用。