An assay for the identification of Plasmodium simium infection for diagnosis of zoonotic malaria in the Brazilian Atlantic Forest View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Denise Anete Madureira de Alvarenga, Richard Culleton, Anielle de Pina-Costa, Danielle Fonseca Rodrigues, Cesare Bianco, Sidnei Silva, Ana Júlia Dutra Nunes, Julio César de Souza, Zelinda Maria Braga Hirano, Sílvia Bahadian Moreira, Alcides Pissinatti, Filipe Vieira Santos de Abreu, André Luiz Lisboa Areas, Ricardo Lourenço-de-Oliveira, Mariano Gustavo Zalis, Maria de Fátima Ferreira-da-Cruz, Patricia Brasil, Cláudio Tadeu Daniel-Ribeiro, Cristiana Ferreira Alves de Brito

ABSTRACT

Zoonotic malaria poses a unique problem for malaria control. Autochthonous cases of human malaria in the Atlantic Forest have recently been attributed to Plasmodium simium, a parasite that commonly infects non-human primates in this Brazilian biome. However, due to its close similarity at both the morphological and molecular level to Plasmodium vivax, the diagnosis of P. simium in this region remains problematic. Therefore, a diagnostic assay able to accurately identify P. simium is important for malaria surveillance. Based on mitochondrial genome sequences, primers were designed to amplify a region containing a SNP specific to P. simium. This region can then be digested with the restriction enzyme HpyCH4III, which results in digestion of P. simium sequences, but not of any other malaria parasite. Fifty-two human and monkey blood samples from different regions and infected with different Plasmodium species were used to validate this protocol. This easy and inexpensive tool can be used for the diagnosis of P. simium in non-human primates and human infections from the Atlantic Forest region to monitor zoonotic malaria transmission in Brazil. More... »

PAGES

86

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-017-18216-x

DOI

http://dx.doi.org/10.1038/s41598-017-18216-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100172305

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29311638


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