Publication: The resistome and genomic reconnaissance in the age of malaria elimination
Issued Date
2019-01-01
Resource Type
ISSN
17548411
17548403
17548403
Other identifier(s)
2-s2.0-85077209116
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
DMM Disease Models and Mechanisms. Vol.12, No.12 (2019)
Suggested Citation
Krittikorn Kümpornsin, Theerarat Kochakarn, Thanat Chookajorn The resistome and genomic reconnaissance in the age of malaria elimination. DMM Disease Models and Mechanisms. Vol.12, No.12 (2019). doi:10.1242/dmm.040717 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/50340
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
The resistome and genomic reconnaissance in the age of malaria elimination
Other Contributor(s)
Abstract
© 2019. Published by The Company of Biologists Ltd. Malaria is an infectious disease caused by parasitic protozoa in the Plasmodium genus. A complete understanding of the biology of these parasites is challenging in view of their need to switch between the vertebrate and insect hosts. The parasites are also capable of becoming highly motile and of remaining dormant for decades, depending on the stage of their life cycle. Malaria elimination efforts have been implemented in several endemic countries, but the parasites have proven to be resilient. One of the major obstacles for malaria elimination is the development of antimalarial drug resistance. Ineffective treatment regimens will fail to remove the circulating parasites and to prevent the local transmission of the disease. Genomic epidemiology of malaria parasites has become a powerful tool to track emerging drug-resistant parasite populations almost in real time. Population-scale genomic data are instrumental in tracking the hidden pockets of Plasmodium in nationwide elimination efforts. However, genomic surveillance data can be useful in determining the threat only when combined with a thorough understanding of the malarial resistome - the genetic repertoires responsible for causing and potentiating drug resistance evolution. Even though long-term selection has been a standard method for drug target identification in laboratories, its implementation in largescale exploration of the druggable space in Plasmodium falciparum, along with genome-editing technologies, have enabled mapping of the genetic repertoires that drive drug resistance. This Review presents examples of practical use and describes the latest technology to show the power of real-time genomic epidemiology in achieving malaria elimination.