Edwin Pierre-Louis, Julia Kelley, Dhruviben Patel, Christina Carlson, Eldin Talundzic, David Jacobson, Joel Leonard Nicholas Barratt
{"title":"利用 Pfs47 和 Pfcpmp 基因序列对耐药性旅行相关恶性疟原虫进行地理分类(美国,2018-2021 年)。","authors":"Edwin Pierre-Louis, Julia Kelley, Dhruviben Patel, Christina Carlson, Eldin Talundzic, David Jacobson, Joel Leonard Nicholas Barratt","doi":"10.1128/aac.01203-24","DOIUrl":null,"url":null,"abstract":"<p><p>Travel-related malaria is regularly encountered in the United States, and the U.S. Centers for Disease Control and Prevention (CDC) characterizes <i>Plasmodium falciparum</i> drug-resistance genotypes routinely for travel-related cases. An important aspect of antimalarial drug resistance is understanding its geographic distribution. However, specimens submitted to CDC laboratories may have missing, incomplete, or inaccurate travel data. To complement genotyping for drug-resistance markers <i>Pfcrt</i>, <i>Pfmdr1</i>, <i>Pfk13</i>, <i>Pfdhps</i>, <i>Pfdhfr</i>, and <i>PfcytB</i> at CDC, amplicons of <i>Pfs47</i> and <i>Pfcpmp</i> are also sequenced as markers of geographic origin. Here, a bi-allele likelihood (BALK) classifier was trained using <i>Pfs47</i> and <i>Pfcpmp</i> sequences from published <i>P. falciparum</i> genomes of known geographic origin to classify clinical genotypes to a continent. Among <i>P. falciparum</i>-positive blood samples received at CDC for drug-resistance genotyping from 2018 to 2021 (<i>n</i> = 380), 240 included a travel history with the submission materials, though 6 were excluded due to low sequence quality. Classifications obtained for the remaining 234 were compared to their travel histories. Classification results were over 96% congruent with reported travel for clinical samples, and with collection sites for field isolates. Among travel-related samples, only two incongruent results occurred; a specimen submitted citing Costa Rican travel classified to Africa, and a specimen with travel referencing Sierra Leone classified to Asia. Subsequently, the classifier was applied to specimens with unreported travel histories (<i>n</i> = 140; 5 were excluded due to low sequence quality). For the remaining 135 samples, geographic classification data were paired with results generated using CDC's Malaria Resistance Surveillance (MaRS) protocol, which detects single-nucleotide polymorphisms in and generates haplotypes for <i>Pfcrt</i>, <i>Pfmdr1</i>, <i>Pfk13</i>, <i>Pfdhps</i>, <i>Pfdhfr</i>, and <i>PfcytB</i>. Given the importance of understanding the geographic distribution of antimalarial drug resistance, this work will complement domestic surveillance efforts by expanding knowledge on the geographic origin of drug-resistant <i>P. falciparum</i> entering the USA.</p>","PeriodicalId":8152,"journal":{"name":"Antimicrobial Agents and Chemotherapy","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Geo-classification of drug-resistant travel-associated <i>Plasmodium falciparum</i> using <i>Pfs47</i> and <i>Pfcpmp</i> gene sequences (USA, 2018-2021).\",\"authors\":\"Edwin Pierre-Louis, Julia Kelley, Dhruviben Patel, Christina Carlson, Eldin Talundzic, David Jacobson, Joel Leonard Nicholas Barratt\",\"doi\":\"10.1128/aac.01203-24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Travel-related malaria is regularly encountered in the United States, and the U.S. Centers for Disease Control and Prevention (CDC) characterizes <i>Plasmodium falciparum</i> drug-resistance genotypes routinely for travel-related cases. An important aspect of antimalarial drug resistance is understanding its geographic distribution. However, specimens submitted to CDC laboratories may have missing, incomplete, or inaccurate travel data. To complement genotyping for drug-resistance markers <i>Pfcrt</i>, <i>Pfmdr1</i>, <i>Pfk13</i>, <i>Pfdhps</i>, <i>Pfdhfr</i>, and <i>PfcytB</i> at CDC, amplicons of <i>Pfs47</i> and <i>Pfcpmp</i> are also sequenced as markers of geographic origin. Here, a bi-allele likelihood (BALK) classifier was trained using <i>Pfs47</i> and <i>Pfcpmp</i> sequences from published <i>P. falciparum</i> genomes of known geographic origin to classify clinical genotypes to a continent. Among <i>P. falciparum</i>-positive blood samples received at CDC for drug-resistance genotyping from 2018 to 2021 (<i>n</i> = 380), 240 included a travel history with the submission materials, though 6 were excluded due to low sequence quality. Classifications obtained for the remaining 234 were compared to their travel histories. Classification results were over 96% congruent with reported travel for clinical samples, and with collection sites for field isolates. Among travel-related samples, only two incongruent results occurred; a specimen submitted citing Costa Rican travel classified to Africa, and a specimen with travel referencing Sierra Leone classified to Asia. Subsequently, the classifier was applied to specimens with unreported travel histories (<i>n</i> = 140; 5 were excluded due to low sequence quality). For the remaining 135 samples, geographic classification data were paired with results generated using CDC's Malaria Resistance Surveillance (MaRS) protocol, which detects single-nucleotide polymorphisms in and generates haplotypes for <i>Pfcrt</i>, <i>Pfmdr1</i>, <i>Pfk13</i>, <i>Pfdhps</i>, <i>Pfdhfr</i>, and <i>PfcytB</i>. Given the importance of understanding the geographic distribution of antimalarial drug resistance, this work will complement domestic surveillance efforts by expanding knowledge on the geographic origin of drug-resistant <i>P. falciparum</i> entering the USA.</p>\",\"PeriodicalId\":8152,\"journal\":{\"name\":\"Antimicrobial Agents and Chemotherapy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2024-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Antimicrobial Agents and Chemotherapy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1128/aac.01203-24\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Antimicrobial Agents and Chemotherapy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1128/aac.01203-24","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
Geo-classification of drug-resistant travel-associated Plasmodium falciparum using Pfs47 and Pfcpmp gene sequences (USA, 2018-2021).
Travel-related malaria is regularly encountered in the United States, and the U.S. Centers for Disease Control and Prevention (CDC) characterizes Plasmodium falciparum drug-resistance genotypes routinely for travel-related cases. An important aspect of antimalarial drug resistance is understanding its geographic distribution. However, specimens submitted to CDC laboratories may have missing, incomplete, or inaccurate travel data. To complement genotyping for drug-resistance markers Pfcrt, Pfmdr1, Pfk13, Pfdhps, Pfdhfr, and PfcytB at CDC, amplicons of Pfs47 and Pfcpmp are also sequenced as markers of geographic origin. Here, a bi-allele likelihood (BALK) classifier was trained using Pfs47 and Pfcpmp sequences from published P. falciparum genomes of known geographic origin to classify clinical genotypes to a continent. Among P. falciparum-positive blood samples received at CDC for drug-resistance genotyping from 2018 to 2021 (n = 380), 240 included a travel history with the submission materials, though 6 were excluded due to low sequence quality. Classifications obtained for the remaining 234 were compared to their travel histories. Classification results were over 96% congruent with reported travel for clinical samples, and with collection sites for field isolates. Among travel-related samples, only two incongruent results occurred; a specimen submitted citing Costa Rican travel classified to Africa, and a specimen with travel referencing Sierra Leone classified to Asia. Subsequently, the classifier was applied to specimens with unreported travel histories (n = 140; 5 were excluded due to low sequence quality). For the remaining 135 samples, geographic classification data were paired with results generated using CDC's Malaria Resistance Surveillance (MaRS) protocol, which detects single-nucleotide polymorphisms in and generates haplotypes for Pfcrt, Pfmdr1, Pfk13, Pfdhps, Pfdhfr, and PfcytB. Given the importance of understanding the geographic distribution of antimalarial drug resistance, this work will complement domestic surveillance efforts by expanding knowledge on the geographic origin of drug-resistant P. falciparum entering the USA.
期刊介绍:
Antimicrobial Agents and Chemotherapy (AAC) features interdisciplinary studies that build our understanding of the underlying mechanisms and therapeutic applications of antimicrobial and antiparasitic agents and chemotherapy.