title: Ahead of the curve: next generation estimators of drug resistance in malaria infections.
abstract: Drug resistance is a major obstacle to controlling infectious diseases. A key challenge is detecting the early signs of drug resistance when little is known about its genetic basis. Focusing on malaria parasites, we propose a way to do this. Newly developing or low level resistance at low frequency in patients can be detected through a phenotypic signature: individual parasite variants clearing more slowly following drug treatment. Harnessing the abundance and resolution of deep sequencing data, our 'selection differential' approach addresses some limitations of extant methods of resistance detection, should allow for the earliest detection of resistance in malaria or other multi-clone infections, and has the power to uncover the true scale of the drug resistance problem.
authors.affiliation: Center for Infectious Disease Dynamics, Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA. nlm12@psu.edu
authors.forename: Nicole
authors.initials: N
authors.lastname: Mideo
authors.forename: David A
authors.initials: DA
authors.lastname: Kennedy
authors.forename: Jane M
authors.initials: JM
authors.lastname: Carlton
authors.forename: Jeffrey A
authors.initials: JA
authors.lastname: Bailey
authors.forename: Jonathan J
authors.initials: JJ
authors.lastname: Juliano
authors.forename: Andrew F
authors.initials: AF
authors.lastname: Read
mesh_terms: D000818:Animals; D000962:Antimalarials / Q000494:pharmacology* / Q000627:therapeutic use; D016903:Drug Monitoring / Q000379:methods*; D004351:Drug Resistance; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008288:Malaria / Q000188:drug therapy* / Q000469:parasitology; D010641:Phenotype; D010963:Plasmodium falciparum / Q000187:drug effects* / Q000235:genetics; D017422:Sequence Analysis, DNA
chemical_list: D000962:Antimalarials