Malaria Branch, Division of Parasitic Diseases and Malaria, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States America.
Association of Public Health Laboratories, Silver Spring, Maryland, United States America.
PLoS One. 2019 Apr 30;14(4):e0215754. doi: 10.1371/journal.pone.0215754. eCollection 2019.
The ability to identify mixed-species infections and track the origin of Plasmodium parasites can further enhance the development of treatment and prevention recommendations as well as outbreak investigations. Here, we explore the utility of using the full Plasmodium mitochondrial genome to classify Plasmodium species, detect mixed infections, and infer the geographical origin of imported P. falciparum parasites to the United States (U.S.). Using the recently developed standardized, high-throughput Malaria Resistance Surveillance (MaRS) protocol, the full Plasmodium mitochondrial genomes of 265 malaria cases imported to the U.S. from 2014-2017 were sequenced and analyzed. P. falciparum infections were found in 94.7% (251/265) of samples. Five percent (14/265) of samples were identified as mixed- Plasmodium species or non-P. falciparum, including P. vivax, P. malariae, P. ovale curtisi, and P. ovale wallikeri. P. falciparum mitochondrial haplotypes analysis revealed greater than eighteen percent of samples to have at least two P. falciparum mitochondrial genome haplotypes, indicating either heteroplasmy or multi-clonal infections. Maximum-likelihood phylogenies of 912 P. falciparum mitochondrial genomes with known country origin were used to infer the geographical origin of thirteen samples from persons with unknown travel histories as: Africa (country unspecified) (n = 10), Ghana (n = 1), Southeast Asia (n = 1), and the Philippines (n = 1). We demonstrate the utility and current limitations of using the Plasmodium mitochondrial genome to classify samples with mixed-infections and infer the geographical origin of imported P. falciparum malaria cases to the U.S. with unknown travel history.
鉴定混合感染并追踪疟原虫寄生虫的起源可以进一步增强治疗和预防建议以及暴发调查的制定。在这里，我们探讨了使用完整的疟原虫线粒体基因组对疟原虫物种进行分类、检测混合感染以及推断输入性恶性疟原虫寄生虫到美国（U.S.）的地理起源的效用。使用最近开发的标准化高通量疟疾耐药监测（MaRS）方案，对 2014-2017 年从美国输入的 265 例疟疾病例的完整疟原虫线粒体基因组进行了测序和分析。94.7%（251/265）的样本中发现了恶性疟原虫感染。5%（14/265）的样本被鉴定为混合疟原虫物种或非恶性疟原虫，包括间日疟原虫、卵形疟原虫、卵形疟原虫 curtisi 和卵形疟原虫 wallikeri。恶性疟原虫线粒体单倍型分析显示，超过 18%的样本至少有两种恶性疟原虫线粒体基因组单倍型，表明存在异质性或多克隆感染。使用具有已知起源国家的 912 个恶性疟原虫线粒体基因组的最大似然系统发育树来推断 13 个未知旅行史患者样本的地理起源为：非洲（未指定国家）（n = 10）、加纳（n = 1）、东南亚（n = 1）和菲律宾（n = 1）。我们证明了使用疟原虫线粒体基因组对混合感染样本进行分类以及推断输入性恶性疟原虫疟疾病例到美国（U.S.）的地理起源的效用和当前局限性，这些病例的旅行史未知。
