Using genetic epidemiology to inform vaccination policy and reduce the global burden of meningitis

通过与非洲的医疗中心和研究机构合作，该项目将首先帮助组织和完成疫苗接种政策分子流行病学（MEVacP）和全球脑膜炎基因组实验室（GMBL）非洲细菌性脑膜炎基因组数据库。然后，它将分析这些数据，以提供非洲脑膜炎的流行病学地图，并确定新的和正在出现的细菌菌株。利用基因组分析，该项目将描绘出造成最大疾病负担的细菌的荚膜类型。准确的诊断测试对于临床医生正确诊断疾病、处方适当的抗生素和正确报告疾病以通知疫情暴发程序至关重要。GMBL数据库将包含患者人口统计数据、临床诊断测试结果、细菌分离物元数据和致病性脑膜炎细菌的全基因组序列。对基因组序列的询问将允许评估最常用的分子（例如基于pcr的）诊断测试的敏感性和特异性。如果目前的任何一种检测方法不理想，那么该项目将致力于设计新的分子诊断检测方法，以确定脑膜炎的病因。基因组文库可以通过识别特定细菌物种的特定基因来帮助这一过程。然后可以开发针对这些基因靶点的微生物测定方法，这将使非洲的临床医生和科学家能够更准确地诊断致病细菌，更快地识别疫情，并促使国家和国际公共卫生当局更快地作出反应。对临床样本中分离的细菌菌株进行基因组分析，并将其与用于治疗的药物知识和患者疾病的结果（死亡或存活）联系起来，将用于监测药物的疗效并分析抗生素耐药性的遗传基础。利用抗生素耐药基因的知识，该项目将致力于监测它们在基因组文库中的长期存在，从而跟踪它们的传播。经解释的基因组数据，以及样本采集的时间和地点，将使鉴定具有获得性抗生素耐药性的菌株成为可能。这些信息又可被当地卫生保健工作者用来选择适当的抗生素。此外，该分析可用于鉴定引起抗生素耐药性的基因的蛋白质产物，这可能有助于通过靶向药物开发设计新型抗生素。全基因组序列可用于预测某一菌株在其荚膜表面所显示的抗原。由于疫苗对这些胶囊表位产生免疫，基因组文库可用于估计非洲特定地区不同疫苗的潜在有效性。此外，引起脑膜炎的细菌可以有许多不同的荚膜类型，目前的疫苗只能保护少数子集。在这个项目中，基因组文库的分析将用于了解在非洲造成最大健康负担的细菌菌株中哪些荚膜最常见，这反过来将指导疫苗开发人员优先考虑哪些荚膜类型。最后，基因组文库将用于研究细菌种群如何对新疫苗的引入作出反应。这些信息可用于为疫苗接种实施战略提供信息，并为免疫规划提供建议。

By collaborating with medical centres and research institutions in Africa, this project will first help to organise and complete the Molecular Epidemiology for Vaccination Policy (MEVacP) and Global Meningitis Genome Laboratory (GMBL) databases of bacterial meningitis genomes in Africa. It will then analyse these data to provide an epidemiological map of meningitis in Africa, and identify new and emerging strains of bacteria. Using genomic analysis, the project will delineate the capsular types of the bacteria responsible for the greatest disease burden. Accurate diagnostic tests are crucial for clinicians to correctly diagnose disease, prescribe appropriate antibiotics, and correctly report disease to inform outbreak procedures. The GMBL database will contain patient demographic data, results of clinical diagnostic tests, bacterial isolate metadata and whole genome sequences of the causative meningitis bacteria. Interrogation of the genome sequences will allow for the most commonly used molecular (e.g. PCR-based) diagnostic tests to be assessed for sensitivity and specificity. If any of the current assays are suboptimal, then the project will aim to design new molecular diagnostic assays to identify the aetiological agents of meningitis. Genomic libraries can aid this process by allowing identification of genes that are specificfor a particular bacterial species. Microbiological assays for these gene targets can then be developed, which would allow African clinicians and scientists to diagnose the causative bacteria more accurately, identify outbreaks more quickly, and trigger faster responses from national and international public health authorities. Genomic analysis of the bacterial strains isolated in clinical samples, linked with knowledge of medication used for treatment and the outcome of the patient illness (death or survival) will be used to monitor the efficacy of drugs and analyse the genetic underpinning of antibiotic resistance. Using knowledge of antibiotic resistance genes, the project will aim to monitor their presence over time in the genomic libraries, thus tracking their transmission. The interpreted genomic data, mapped to the time and place of sample collection, will allow the identification of strains with acquired antibiotic resistance. This information can in turn be used by local healthcare workers to choose appropriate antibiotics. Further, this analysis can be used to identify the protein products of genes that cause antibioticresistance, which may aid the design of novel antibiotics via targeted drug development. Whole genome sequences can be used to predict the antigens a certain bacterial strain will display on its capsule surface. As vaccines immunise against these capsule epitopes, the genomic libraries can be used to estimate the potential effectiveness of different vaccines in specific regions of Africa. In addition, bacteria causing meningitis can have many different capsular types and current vaccines only protect against a minority subset. In this project, analysis of genomic libraries will beused to inform which capsules are most common among the bacterial strains causing the greatest health burdens in Africa, which will in turn guide prioritisation of which capsular types should be targeted by vaccine developers. Finally, genomic libraries will be used to investigate how bacterial populations respond to the introduction of a novel vaccine. This information can be used to inform vaccination implementation strategies and to advise immunisation programmes.