Ahead of the curve: Next generation estimators of drug resistance in malaria infections

Nicole Mideo, David A. Kennedy, Jane M. Carlton, Jeffrey A. Bailey, Jonathan J. Juliano, Andrew F. Read

Research output: Contribution to journalReview article

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.

Original languageEnglish (US)
Pages (from-to)321-328
Number of pages8
JournalTrends in Parasitology
Volume29
Issue number7
DOIs
StatePublished - Jul 2013

Keywords

  • Artemisinin
  • Deep sequencing
  • Mixed infections
  • Parasite clearance curves
  • Plasmodium
  • Selection differential

ASJC Scopus subject areas

  • Parasitology
  • Infectious Diseases

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