Rapid profiling of <i>Plasmodium</i> parasites from genome sequences to assist malaria control

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Citações na Scopus
1
Tipo de produção
article
Data de publicação
2023
DOI
Scopus
Web of Science
PubMed
Título da Revista
ISSN da Revista
Título do Volume
Editora
BMC
Autores
PHELAN, Jody E.
TURKIEWICZ, Anna
MANKO, Emilia
THORPE, Joseph
VANHEER, Leen N.
VEGTE-BOLMER, Marga van de
NGOC, Nguyen Thi Hong
BINH, Nguyen Thi Huong
THIEU, Nguyen Quang
GITAKA, Jesse
Citação
GENOME MEDICINE, v.15, n.1, article ID 96, 11p, 2023
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Background Malaria continues to be a major threat to global public health. Whole genome sequencing (WGS) of the underlying Plasmodium parasites has provided insights into the genomic epidemiology of malaria. Genome sequencing is rapidly gaining traction as a diagnostic and surveillance tool for clinical settings, where the profiling of co-infections, identification of imported malaria parasites, and detection of drug resistance are crucial for infection control and disease elimination. To support this informatically, we have developed the Malaria-Profiler tool, which rapidly (within minutes) predicts Plasmodium species, geographical source, and resistance to antimalarial drugs directly from WGS data. Results The online and command line versions of Malaria-Profiler detect similar to 250 markers from genome sequences covering Plasmodium speciation, likely geographical source, and resistance to chloroquine, sulfadoxine-pyrimethamine (SP), and other anti-malarial drugs for P. falciparum, but also providing mutations for orthologous resistance genes in other species. The predictive performance of the mutation library was assessed using 9321 clinical isolates with WGS and geographical data, with most being single-species infections (P. falciparum 7152/7462, P. vivax 1502/1661, P. knowlesi 143/151, P. malariae 18/18, P. ovale ssp. 5/5), but co-infections were identified (456/9321; 4.8%). The accuracy of the predicted geographical profiles was high to both continental (96.1%) and regional levels (94.6%). For P. falciparum, markers were identified for resistance to chloroquine (49.2%; regional range: 24.5% to 100%), sulfadoxine (83.3%; 35.4- 90.5%), pyrimethamine (85.4%; 80.0-100%) and combined SP (77.4%). Markers associated with the partial resistance of artemisinin were found in WGS from isolates sourced from Southeast Asia (30.6%). Conclusions Malaria-Profiler is a user-friendly tool that can rapidly and accurately predict the geographical regional source and anti-malarial drug resistance profiles across large numbers of samples with WGS data. The software is flexible with modifiable bioinformatic pipelines. For example, it is possible to select the sequencing platform, display specific variants, and customise the format of outputs. With the increasing application of next-generation sequencing platforms on Plasmodium DNA, Malaria-Profiler has the potential to be integrated into point-of-care and surveillance settings, thereby assisting malaria control. Malaria-Profiler is available online (bioinformatics.lshtm.ac.uk/malaria-profiler) and as standalone software (https://github.com/jodyphelan/malaria-profiler).
Palavras-chave
Drug resistance, Malaria, Plasmodium parasites, Genomics, Diagnostics, Whole genome sequencing
URI
https://observatorio.fm.usp.br/handle/OPI/58165
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Coleções
Artigos e Materiais de Revistas Científicas - HC/ICHC
Artigos e Materiais de Revistas Científicas - LIM/49
Artigos e Materiais de Revistas Científicas - ODS/03