Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom.
Max Planck Institute for Infection Biologygrid.418159.0, Berlin, Germany.
mBio. 2022 Oct 26;13(5):e0093722. doi: 10.1128/mbio.00937-22. Epub 2022 Aug 16.
The repeated emergence of antimalarial drug resistance in Plasmodium falciparum, including to the current frontline antimalarial artemisinin, is a perennial problem for malaria control. Next-generation sequencing has greatly accelerated the identification of polymorphisms in resistance-associated genes but has also highlighted the need for more sensitive and accurate laboratory tools to profile current and future antimalarials and to quantify the impact of drug resistance acquisition on parasite fitness. The interplay of fitness and drug response is of fundamental importance in understanding why particular genetic backgrounds are better at driving the evolution of drug resistance in natural populations, but the impact of parasite fitness landscapes on the epidemiology of drug resistance has typically been laborious to accurately quantify in the lab, with assays being limited in accuracy and throughput. Here we present a scalable method to profile fitness and drug response of genetically distinct P. falciparum strains with well-described sensitivities to several antimalarials. We leverage CRISPR/Cas9 genome-editing and barcode sequencing to track unique barcodes integrated into a nonessential gene (). We validate this approach in multiplex competitive growth assays of three strains with distinct geographical origins. Furthermore, we demonstrate that this method can be a powerful approach for tracking artemisinin response as it can identify an artemisinin resistant strain within a mix of multiple parasite lines, suggesting an approach for scaling the laborious ring-stage survival assay across libraries of barcoded parasite lines. Overall, we present a novel high-throughput method for multiplexed competitive growth assays to evaluate parasite fitness and drug response. The complex interplay between antimalarial resistance and parasite fitness has important implications for understanding the development and spread of drug resistance alleles and the impact of genetic background on transmission. One limitation with current methodologies to measure parasite fitness is the ability to scale this beyond simple head-to-head competition experiments between a wildtype control line and test line, with a need for a scalable approach that allows tracking of parasite growth in complex mixtures. In our study, we have used CRISPR editing to insert unique DNA barcodes into a safe-harbor genomic locus to tag multiple parasite strains and use next-generation sequencing to read out strain dynamics. We observe inherent fitness differences between the strains, as well as sensitive modulation of responses to challenge with clinically relevant antimalarials, including artemisinin.
疟原虫对青蒿素类抗疟药物的耐药性反复出现，这是疟疾控制的一个长期问题。新一代测序极大地加速了耐药相关基因中多态性的鉴定，但也凸显了需要更敏感和准确的实验室工具来分析当前和未来的抗疟药物，并量化耐药性获得对寄生虫适应性的影响。适应性和药物反应的相互作用对于理解为什么特定的遗传背景更有利于在自然种群中推动药物耐药性的进化至关重要，但寄生虫适应性景观对耐药性流行病学的影响在实验室中通常难以准确量化，因为测定方法在准确性和通量方面都受到限制。在这里，我们提出了一种可扩展的方法来分析具有不同遗传背景且对几种抗疟药物具有不同敏感性的疟原虫菌株的适应性和药物反应。我们利用 CRISPR/Cas9 基因组编辑和条形码测序来跟踪整合到非必需基因 () 中的独特条形码。我们在具有不同地理起源的三个菌株的多重竞争生长测定中验证了这种方法。此外，我们证明这种方法可以作为跟踪青蒿素反应的有力方法，因为它可以在多种寄生虫系的混合物中识别出青蒿素耐药株，这表明可以在包含条形码寄生虫系文库的范围内扩展繁琐的环体存活测定。总体而言，我们提出了一种用于多重竞争生长测定的新型高通量方法，以评估寄生虫适应性和药物反应。抗疟药物耐药性与寄生虫适应性之间的复杂相互作用对于理解耐药等位基因的发展和传播以及遗传背景对传播的影响具有重要意义。目前测量寄生虫适应性的方法存在一个局限性，即无法超越野生型对照系和测试系之间的简单头对头竞争实验进行扩展，需要一种可扩展的方法来跟踪复杂混合物中寄生虫的生长。在我们的研究中，我们使用 CRISPR 编辑将独特的 DNA 条形码插入安全港基因组座，以标记多个寄生虫系，并使用下一代测序读取系动态。我们观察到菌株之间存在固有适应性差异，以及对包括青蒿素在内的临床相关抗疟药物的反应敏感调节。
