Evolutionary analyses of the major variant surface antigen-encoding genes reveal population structure of Plasmodium falciparum within and between continents.
Evolutionary analyses of the major variant surface antigen-encoding genes reveal population structure of Plasmodium falciparum within and between continents.
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主要变异体表面抗原编码基因的进化分析揭示了大陆内和大陆间恶性疟原虫的种群结构。
DOI：
10.1371/journal.pgen.1009269
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发表时间：
2021-03
期刊：
影响因子：
4.5
通讯作者：
Day KP
中科院分区：
文献类型：
--
作者：
Tonkin-Hill G;Ruybal-Pesántez S;Tiedje KE;Rougeron V;Duffy MF;Zakeri S;Pumpaibool T;Harnyuttanakorn P;Branch OH;Ruiz-Mesía L;Rask TS;Prugnolle F;Papenfuss AT;Chan YB;Day KP
疟疾在许多国家仍然是一个主要的公共卫生问题。与流感和艾滋病毒不同，人们在地理上了解免疫优势表面抗原的多样性，以便为疾病监测提供信息，而对PfEMP1的全球种群结构知之甚少，PfEMP1是疟疾寄生虫恶性疟原虫的主要变异表面抗原。到目前为止，编码PfEMP1并通过重组而多样化的var多基因家族的复杂性阻碍了其在疟疾监测中的使用。最近的研究表明，对编码PfEMP1DBLα结构域的VAR基因区域进行成本效益高的深度测序，并随后对宿主内序列进行96%的同源性分类，以确定独特的DBLα类型，可以揭示国家内部的结构和菌株动态。然而，到目前为止，还没有对这些DBLα类型在国家之间进行全面的比较。通过利用生物信息学方法(跳跃隐马尔可夫模型)分析var基因内部的重组，并将其应用于来自10个国家的DBLα类型的数据集，我们能够在全球范围内描述DBLα类型的种群结构。该方法的敏感性允许将全球数据集与Laverania疟原虫物种的类人猿样本进行比较。我们的分析表明，从非洲出现的寄生虫种群的进化是当前DBLα类型多样性模式的基础。最重要的是，我们可以区分非洲内部的地理人口结构，西非的加蓬和加纳，东非的乌干达。我们的进化论发现在全球化的背景下具有翻译意义。首先，Dblα类型多样性可以为恶性疟原虫快速演变的传播动态的地理监测提供一个简单的诊断框架。它还可以为了解全球、区域和当地人口对主要表面抗原变体的免疫力的存在或不存在的努力提供信息。此外，我们确定了一些高度保守的DBLα类型，它们存在于全球，可能具有生物学意义，需要进一步鉴定。全球化通过增加人类活动导致病原体的传播。微生物学家通过对编码变异表面抗原(VSA)的基因的地理多样性进行分类，追踪这些病原体的流行情况。在这里，我们开发了一种计算方法来探索人类疟疾寄生虫恶性疟原虫主要VSA基因的特定DNA序列的进化。首先，我们通过比较恶性疟原虫和感染黑猩猩和大猩猩的疟原虫的DNA序列来测试这种方法。我们展示了它可以区分每个物种特有的DNA签名。接下来，我们询问我们的方法是否可以通过分析来自10个国家23个地点的恶性疟原虫分离株的全球集合，来检测这些基因的地理特征。我们工作的重要成果是能够识别特定于国家和大陆的地理特征，这些特征与恶性疟原虫“走出非洲”的起源一致。我们现在可以使用VSA基因的不同区域来识别来自非洲、南美洲和亚洲/大洋洲国家的疟疾寄生虫，而不必对整个寄生虫基因组进行测序和组装。这种方法在疟疾监测中有潜在的应用，可以追踪寄生虫在世界各地传播的情况。
Malaria remains a major public health problem in many countries. Unlike influenza and HIV, where diversity in immunodominant surface antigens is understood geographically to inform disease surveillance, relatively little is known about the global population structure of PfEMP1, the major variant surface antigen of the malaria parasite Plasmodium falciparum. The complexity of the var multigene family that encodes PfEMP1 and that diversifies by recombination, has so far precluded its use in malaria surveillance. Recent studies have demonstrated that cost-effective deep sequencing of the region of var genes encoding the PfEMP1 DBLα domain and subsequent classification of within host sequences at 96% identity to define unique DBLα types, can reveal structure and strain dynamics within countries. However, to date there has not been a comprehensive comparison of these DBLα types between countries. By leveraging a bioinformatic approach (jumping hidden Markov model) designed specifically for the analysis of recombination within var genes and applying it to a dataset of DBLα types from 10 countries, we are able to describe population structure of DBLα types at the global scale. The sensitivity of the approach allows for the comparison of the global dataset to ape samples of Plasmodium Laverania species. Our analyses show that the evolution of the parasite population emerging out of Africa underlies current patterns of DBLα type diversity. Most importantly, we can distinguish geographic population structure within Africa between Gabon and Ghana in West Africa and Uganda in East Africa. Our evolutionary findings have translational implications in the context of globalization. Firstly, DBLα type diversity can provide a simple diagnostic framework for geographic surveillance of the rapidly evolving transmission dynamics of P. falciparum. It can also inform efforts to understand the presence or absence of global, regional and local population immunity to major surface antigen variants. Additionally, we identify a number of highly conserved DBLα types that are present globally that may be of biological significance and warrant further characterization. Globalization has led to the spread of pathogens through increased human movement. Microbiologists track epidemics of these pathogens by cataloguing geographic diversity in the genes that encode for variant surface antigens (VSA). Here, we developed a computational approach to explore the evolution of specific DNA sequences of the major VSA gene of the human malaria parasite, Plasmodium falciparum. First, we tested the method by comparing DNA sequences of these genes from P. falciparum to those of Plasmodium species that infect chimpanzees and gorillas. We showed that it could distinguish DNA signatures specific to each species. Next, we asked whether our method could detect geographic signatures within these genes by analyzing a global collection of P. falciparum isolates from 23 locations in 10 countries. The important outcome of our work was the ability to identify geographic signatures specific to countries and continents that were consistent with the “out of Africa” origin of P. falciparum. We can now identify malaria parasites from countries within Africa, South America, and Asia/Oceania using a diverse region of VSA genes without having to sequence and assemble whole parasite genomes. This methodology has potential applications in malaria surveillance to track parasites as they move around the world.
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DOI：
10.1073/pnas.96.8.4563
发表时间：
1999-04-13
影响因子：
11.1
作者：
Hayward, RE;Tiwari, B;Day, KP
通讯作者：
Day, KP
影响因子：
64.8
作者：
Freitas-Junior, LH;Bottius, E;Scherf, A
通讯作者：
Scherf, A
影响因子：
4.4
作者：
Bengtsson, Anja;Joergensen, Louise;Jensen, Anja T. R.
通讯作者：
Jensen, Anja T. R.
影响因子：
6.4
作者：
Hopkins, Heidi;Bebell, Lisa;Dorsey, Grant
通讯作者：
Dorsey, Grant
影响因子：
6.7
作者：
Barry AE;Leliwa-Sytek A;Tavul L;Imrie H;Migot-Nabias F;Brown SM;McVean GA;Day KP
通讯作者：
Day KP