Using whole genome sequence data to develop molecular barcodes to profile Plasmodium malaria parasites

使用全基因组序列数据开发分子条形码来分析疟原虫疟原虫

• 批准号: 1923171
• 金额: --
• 依托单位: London School of Hygiene & Tropical Medicine
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1923171
• 关键词: Using; whole; genome; sequence; data

Malaria is an important disease caused by parasites of the Plasmodium genus. Whilst theincidence of malaria has decreased in recent years, the burden still remains significant,with approximately 212 million new cases of malaria in 2015. Imported malaria canjeopardise disease control and elimination, and its prevalence is likely to increase due togreater travel. When assessing whether a country has successfully eliminated malaria,there is a need to distinguish imported cases from the cases transmitted locally. Amolecular barcode has been developed for P. falciparum parasites to predict thegeographical region of parasite origin, to high (>90%) accuracy. The barcode wasdeveloped by investigating the genetic variation within two parasite organelles, themitochondrion and the apicoplast. These organelles are present within all Plasmodiumparasite species, and both contain specific sequences of DNA. There is regional geneticdiversity within these genomes, and this diversity can be used within the barcode topredict the origin of the parasite.The barcode developed could prove to be an important tool for malaria control, but thereare limitations, which if overcome would improve its performance. P. falciparum parasitesare the main cause of malaria-related deaths worldwide, however there are many otherhuman-infective Plasmodium species, including P. vivax, P. malariae, P. knowlesi, P.ovale wallikeri and P. ovale curtisi. I propose to broaden the scope of the barcode byincluding additional genetic markers to profile multiple Plasmodium species. In addition,the previous barcode was developed using parasite samples from West Africa, EastAfrica, Southeast Asia and a limited set of countries in South America and Oceania.Therefore, I will aim to broaden the geographical scope of the barcode by inputting datafrom currently underrepresented regions. The barcode was also less efficient at predictingsamples from East Africa which were occasionally mistaken for parasites from WestAfrica, this is thought to be due to the high levels of genetic diversity within East AfricanPlasmodium parasites. I will address this issue by using more samples from East Africa toappreciate the high levels of genetic diversity within this region.2A further complication in disease control is the emergence of drug resistance toArtemisinin Combination Therapy (ACT), which is the current first line of treatment foruncomplicated P. falciparum malaria. Specific genetic regions known to be associated withACT resistance may be incorporated into the barcode to allow for the detection of drugresistant parasites. Combined with the geographical information within the barcode, thisallows for tracking the spread of drug resistant parasites, which may aid as a revolutionarytool for malaria control in the near future.During the process of this project, strong bioinformatics skills will be gained to analyselarge sets of genetic sequence data, this will develop my quantitative skills, fitting in withthe 'Quantitative Skills for Large Data Sets' MRC research theme. Many Plasmodiumsamples will be investigated for genetic diversity using whole genome sequencing; this willtrain me within the field of genomics, enhancing my skills on whole organism physiology.Finally, the aim of the project is to develop a platform known as a molecular barcode,which can track the movement and spread of Plasmodium parasites globally. I will aim toincorporate the barcode into a diagnostic tool that can be used in the evaluation ofcomplex malaria interventions and control programmes.

疟疾是由疟原虫属的寄生虫引起的重要疾病。虽然近年来疟疾发病率有所下降，但负担仍然很重，2015年约有2.12亿例新发疟疾病例。输入性疟疾会危及疾病控制和消灭，而且由于旅行的增加，其流行率可能会增加。在评估一个国家是否已成功消除疟疾时，需要区分输入病例和本地传播病例。恶性疟原虫的分子条形码已被开发出来，用于预测疟原虫的地理来源，准确率高达90%以上。条形码是通过研究寄生虫线粒体和顶质体两种细胞器内的遗传变异而开发的。这些细胞器存在于所有的疟原虫物种中，并且都含有特定的DNA序列。这些基因组中存在区域性遗传多样性，而这种多样性可以用在条形码中来预测寄生虫的起源。开发的条形码可能被证明是控制疟疾的重要工具，但也存在局限性，如果克服这些局限性，将提高其性能。恶性疟原虫是世界范围内疟疾相关死亡的主要原因，然而还有许多其他人感染的疟原虫物种，包括间日疟原虫、三日疟原虫、诺氏疟原虫、卵形疟原虫和卵形疟原虫。我建议通过加入额外的遗传标记来扩大条形码的范围，以分析多种疟原虫。此外，以前的条形码是使用西非，东非，东南亚以及南美洲和大洋洲的一组有限国家的寄生虫样本开发的。因此，我将通过输入目前代表性不足的地区的数据来扩大条形码的地理范围。条形码在预测来自东非的样本时也不太有效，这些样本偶尔会被误认为是来自西非的寄生虫，这被认为是由于东非疟原虫寄生虫的遗传多样性水平较高。我将通过使用更多来自东非的样本来了解该地区的高水平遗传多样性来解决这个问题。2疾病控制的另一个复杂因素是对青蒿素联合疗法（ACT）耐药性的出现，青蒿素联合疗法是目前治疗无并发症的恶性疟原虫疟疾的一线疗法。已知与ACT耐药相关的特定遗传区域可以被整合到条形码中，以允许检测耐药寄生虫。结合条形码中的地理信息，这允许跟踪抗药性寄生虫的传播，这可能有助于在不久的将来成为疟疾控制的革命性工具。在这个项目的过程中，将获得强大的生物信息学技能来分析大数据集的基因序列数据，这将培养我的定量技能，符合“大数据集的定量技能”MRC研究主题。许多疟原虫样本将通过全基因组测序进行遗传多样性研究;这将在基因组学领域训练我，提高我在整个生物体生理学方面的技能。最后，该项目的目的是开发一个被称为分子条形码的平台，它可以跟踪疟原虫寄生虫在全球的移动和传播。我的目标是将条形码纳入诊断工具，用于评估复杂的疟疾干预和控制方案。