Integrative proteomics and bioinformatic prediction enable a high-confidence apicoplast proteome in malaria parasites.
Integrative proteomics and bioinformatic prediction enable a high-confidence apicoplast proteome in malaria parasites.
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DOI：
10.1371/journal.pbio.2005895
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发表时间：
2018-09
期刊：
影响因子：
9.8
通讯作者：
Yeh E
中科院分区：
文献类型：
--
作者：
Boucher MJ;Ghosh S;Zhang L;Lal A;Jang SW;Ju A;Zhang S;Wang X;Ralph SA;Zou J;Elias JE;Yeh E
疟疾寄生虫（疟原虫）和相关的顶复合体病原体含有一种称为顶质体的非光合质体。顶质体起源于一种不寻常的次生真核-真核生物内共生，是一种迷人的细胞器，其功能和生物发生依赖于细菌和藻类途径的复杂融合。由于这些途径不同于人类宿主，顶质体是新的抗疟疾靶点的极好来源。尽管顶质体蛋白质组具有重要的生物医学意义和进化意义，但由于缺乏可靠的顶质体蛋白质组，大多数研究仅限于通过与细菌或原生叶绿体同源性鉴定的少数途径，从而阻碍了我们研究最新颖的顶质体途径的能力。在这里，我们将基于邻近生物素的蛋白质组学（BioID）和一种新的机器学习算法结合起来，生成了由346个蛋白质组成的高置信度的顶质体蛋白质组。至关重要的是，该蛋白质组的高准确性显著优于先前基于预测的方法，并且超出了其他独特寄生虫区室的BioID研究。鉴定出的蛋白质中有一半功能未知，预计77%对正常的血期生长很重要。我们验证了一组新蛋白的顶质体定位，并表明atp结合盒蛋白ABCF1对血期生存至关重要，并在顶质体生物发生中起着以前未知的作用。这些发现表明新发现的顶质体蛋白具有重要的细胞器功能。顶质体蛋白质组将是阐明次生内共生的独特途径和优选抗疟药物靶点的重要资源。引起疟疾的疟原虫和属于顶复合体门的相关病原体含有一种被称为顶质体的废弃叶绿体。在进化过程中，顶质体失去了光合作用功能，但保留了感染宿主细胞所需的关键代谢途径。由于顶质体对寄生虫生存的重要性及其不寻常的进化起源，其独特的生物学特性及其产生新的抗疟药物靶点的潜力引起了人们的极大兴趣。然而，缺乏定位于顶质体的蛋白质的准确清单，阻碍了我们研究顶质体生物学中最新颖和最有趣的生物学方面的能力。为了解决这一限制，我们结合了基于接近生物素的蛋白质组学和一种新的机器学习算法，以准确和公正的方式识别顶质体蛋白质。我们确定了346个候选顶质体蛋白，并发现其中许多蛋白是新的，预计对寄生虫的生存很重要。因此，这种蛋白质组学资源将成为阐明顶质体独特的细胞生物学和确定新的抗疟疾药物靶点的有价值的工具。
Malaria parasites (Plasmodium spp.) and related apicomplexan pathogens contain a nonphotosynthetic plastid called the apicoplast. Derived from an unusual secondary eukaryote–eukaryote endosymbiosis, the apicoplast is a fascinating organelle whose function and biogenesis rely on a complex amalgamation of bacterial and algal pathways. Because these pathways are distinct from the human host, the apicoplast is an excellent source of novel antimalarial targets. Despite its biomedical importance and evolutionary significance, the absence of a reliable apicoplast proteome has limited most studies to the handful of pathways identified by homology to bacteria or primary chloroplasts, precluding our ability to study the most novel apicoplast pathways. Here, we combine proximity biotinylation-based proteomics (BioID) and a new machine learning algorithm to generate a high-confidence apicoplast proteome consisting of 346 proteins. Critically, the high accuracy of this proteome significantly outperforms previous prediction-based methods and extends beyond other BioID studies of unique parasite compartments. Half of identified proteins have unknown function, and 77% are predicted to be important for normal blood-stage growth. We validate the apicoplast localization of a subset of novel proteins and show that an ATP-binding cassette protein ABCF1 is essential for blood-stage survival and plays a previously unknown role in apicoplast biogenesis. These findings indicate critical organellar functions for newly discovered apicoplast proteins. The apicoplast proteome will be an important resource for elucidating unique pathways derived from secondary endosymbiosis and prioritizing antimalarial drug targets. Plasmodium parasites, which cause malaria, and related pathogens belonging to the phylum Apicomplexa contain a relict chloroplast called the apicoplast. During evolution, the apicoplast lost photosynthetic functions but retained critical metabolic pathways that are required for host cell infection. Because of its importance for parasite survival and its unusual evolutionary origin, the apicoplast is of major interest for its unique biology and its potential to yield new antimalarial drug targets. However, an accurate inventory of proteins that localize to the apicoplast is lacking, hindering our ability to study the most novel and biologically interesting aspects of apicoplast biology. To address this limitation, we combine proximity biotinylation-based proteomics and a new machine learning algorithm to identify apicoplast proteins in an accurate and unbiased manner. We identify 346 candidate apicoplast proteins with high confidence and find that many of these proteins are new and expected to be important for parasite survival. This proteomic resource will therefore be a valuable tool for elucidating the unique cell biology of the apicoplast and for identifying new antimalarial drug targets.
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影响因子：
6.4
作者：
Chen AL;Kim EW;Toh JY;Vashisht AA;Rashoff AQ;Van C;Huang AS;Moon AS;Bell HN;Bentolila LA;Wohlschlegel JA;Bradley PJ
通讯作者：
Bradley PJ
影响因子：
9.8
作者：
Bozdech, Zbynek;Llinas, Manuel;Pulliam, Brian Lee;Wong, Edith D;Zhu, Jingchun;DeRisi, Joseph L
通讯作者：
DeRisi, Joseph L
影响因子：
14.9
作者：
Deitsch, KW;Driskill, CL;Wellems, TE
通讯作者：
Wellems, TE
影响因子：
9.6
作者：
Dowse, TJ;Soldati, D
通讯作者：
Soldati, D
影响因子：
4.9
作者：
Dahl, Erica L.;Shock, Jennifer L.;Rosenthal, Philip J.
通讯作者：
Rosenthal, Philip J.