The role of RIFINs and their interaction with blood type in vulnerability to severe malaria in Malian children

项目摘要/摘要 恶性疟原虫每年在全球造成近43.5万人死亡。严重疟疾的受害者是 主要是撒哈拉以南地区的儿童，他们可能出现严重贫血或无法唤醒的昏迷症状。 重症疟疾的发病机制尚不清楚，但由黏附变异体的表达介导 受感染红细胞表面抗原(VSA)。这些VSA参与了隔离和玫瑰花环的形成， 独特的毒力因子，使寄生虫能够逃避宿主免疫反应，并阻止清除 脾。特别是，ABO血型对玫瑰花环至关重要，玫瑰花环是感染病毒的自发结合 和未感染的红细胞结合在一起。A型血型的人特别容易感染严重的疟疾， 与O型血的人不同，O型血的人似乎对严重疾病相对安全。一个相对未被研究过的 VSA家族，即重复的散布家族(RIFIN)蛋白，最近被发现在 玫瑰花环。RIFIN优先与A型血型抗原结合，形成比血型更大、更紧密的花环 O.RIFINs可能在ABO血型和严重疟疾易感性之间起中介作用；这些 蛋白质似乎也是保护性免疫的目标。针对RIFIN的体液免疫反应 与无症状感染有关。因此，我们假设RIFIN的子集在 严重疟疾发病机制以及对这一亚群缺乏免疫力的人最容易感染 患上严重的疟疾。在2014年开始于马里的一项病例对照研究中，我们小组收集了血液和血清 来自严重疟疾病例的样本和与不复杂疟疾相匹配的对照组。在此，我们建议 使用下一代RNA测序技术识别和测序在严重疟疾中表达的RIFIN。 使用定制的蛋白质芯片，我们将确定是否缺乏对这些RIFIN蛋白质的抗体 与发展成严重疾病有关。在目标1中，我们将确定RIFIN转录子的亚组 在患有严重疟疾的受试者和患有简单疟疾的配对对照组中通过 RNA-Seq.我们假设RIFIN-AS的一个子集将主要在严重疟疾病例中表达 与A型血型相比，RIFIN的异质性组表达--就像在其他感染中一样。在目标2中， 我们将使用在AIM 1中确定的主要RIFIN转录本和其他寄生虫抗原来填充海关 蛋白质微阵列，以确定与重症易感性增加相关的RIFIN蛋白质子集 疟疾。我们假设，患有严重疟疾的急性患者的血清将识别较少的RIFIN蛋白 在蛋白质芯片上，与它们的恢复期血清和配对的血清相比，反应不那么强烈 控制不复杂的疟疾，特别是A型血的严重疟疾病例。 在生物信息学分析方面获得宝贵的专业知识，特别是从微阵列和转录数据中获得 高通量测序平台；使用流行病学技术进行翻译感染 疾病研究；并应用这些技能来支持有效的公共卫生干预措施，如疫苗。

PROJECT SUMMARY/ABSTRACT Plasmodium falciparum causes nearly 435,000 deaths annually worldwide. Victims of severe malaria are predominantly sub-Saharan children, who may present with symptoms of severe anemia or unarousable coma. The pathogenesis of severe malaria is poorly understood but mediated by the expression of adhesive variant surface antigens (VSAs) on infected red blood cells. These VSAs are involved in sequestration and rosetting, unique virulence factors that allow the parasite to evade host immune responses and prevent clearance in the spleen. In particular, ABO blood groups are critical for rosetting, which is the spontaneous binding of infected and uninfected erythrocytes together. Individuals with blood type A are particularly vulnerable to severe malaria, unlike those with blood type O who appear relatively protected against severe disease. A relatively unstudied family of VSAs, the repetitive interspersed family (RIFIN) proteins, have been recently found to be important in rosetting. RIFINs preferentially bind blood type A antigens, forming larger and tighter rosettes than in blood type O. RIFINs may mediate the association between ABO blood type and severe malaria susceptibility; these proteins also appear to be targets for protective immunity. Humoral immune responses against RIFINs have been correlated with asymptomatic infections. As such, we posit that a subset of RIFINs play a critical role in severe malaria pathogenesis and that individuals who lack immunity to this subset are the most susceptible to develop severe malaria. In a case-control study that began in Mali in 2014, our group collected blood and serum samples from severe malaria cases and matched controls with uncomplicated malaria. Here, we propose to identify and sequence RIFINs expressed in severe malaria using next-generation RNA-sequencing technologies. Using a custom protein microarray, we will then determine whether a lack of antibodies to these RIFIN proteins is associated with developing severe disease. In Aim 1, we will identify subgroups of RIFIN transcripts that are differentially expressed in subjects with severe malaria versus matched controls with uncomplicated malaria via RNA-Seq. We hypothesize that a subset of RIFIN-As will be predominantly expressed in severe malaria cases with blood type A, in contrast to expression of a heterogeneous group of RIFIN-As in other infections. In Aim 2, we will use the predominant RIFIN transcripts identified in Aim 1 and other parasite antigens to populate a custom protein microarray in order to define a subset of RIFIN proteins associated with increased vulnerability to severe malaria. We hypothesize that sera from children acutely ill with severe malaria will recognize fewer RIFIN proteins on a protein microarray and react to them less intensely than their convalescent sera and sera from matched controls with uncomplicated malaria, particularly for severe malaria cases with blood type A. The candidate will gain valuable expertise in bioinformatics analysis, particularly from microarrays and transcriptomic data from high-throughput sequencing platforms; use epidemiological techniques to conduct translational infectious disease research; and apply these skills to support effective public health interventions such as a vaccine.