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Genetic dissection of drug resistance in trypanosomes

Published online by Cambridge University Press:  03 April 2013

SAM ALSFORD*
Affiliation:
London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
JOHN M. KELLY
Affiliation:
London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
NICOLA BAKER
Affiliation:
London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
DAVID HORN
Affiliation:
London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
*
*Corresponding author: London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK. Tel/Fax: +44 20 7927 2352. E-mail: sam.alsford@lshtm.ac.uk
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Summary

The trypanosomes cause two neglected tropical diseases, Chagas disease in the Americas and African trypanosomiasis in sub-Saharan Africa. Over recent years a raft of molecular tools have been developed enabling the genetic dissection of many aspects of trypanosome biology, including the mechanisms underlying resistance to some of the current clinical and veterinary drugs. This has led to the identification and characterization of key resistance determinants, including transporters for the anti-Trypanosoma brucei drugs, melarsoprol, pentamidine and eflornithine, and the activator of nifurtimox-benznidazole, the anti-Trypanosoma cruzi drugs. More recently, advances in sequencing technology, combined with the development of RNA interference libraries in the clinically relevant bloodstream form of T. brucei have led to an exponential increase in the number of proteins known to interact either directly or indirectly with the anti-trypanosomal drugs. In this review, we discuss these findings and the technological developments that are set to further revolutionise our understanding of drug-trypanosome interactions. The new knowledge gained should inform the development of novel interventions against the devastating diseases caused by these parasites.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
The online version of this article is published within an Open Access environment subject to the conditions of the Creative Commons Attribution-NonCommercial-ShareAlike licence . The written permission of Cambridge University Press must be obtained for commercial re-use.
Copyright
Copyright © Cambridge University Press 2013
Figure 0

Table 1. Current drugs – their application, and resistance mechanisms identified by low throughput analysis of laboratory-derived and clinical resistant isolates

Figure 1

Fig. 1. Structures of the nitroheterocyclic drugs used to treat T. cruzi infections and their toxic metabolites. The highlighted regions of nifurtimox and benznidazole correspond to the 5-nitrofuran and the 2-nitroimidazole groups, respectively. The structures of the toxic unsaturated open chain nitrile and glyoxal metabolites (Hall et al.2011; Hall and Wilkinson, 2012) are shown below the corresponding drugs.

Figure 2

Fig. 2. A comparison of low and high throughput approaches to understanding drug resistance in trypanosomes.

Figure 3

Fig. 3. Developments in T. brucei molecular genetics and advances in the understanding of drug resistance in trypanosomes since 1990. (A) The development of the bloodstream form T. brucei RNAi library and the RIT-seq methodology was dependent upon a number of earlier methodological advances. Although concurrent progress was made in dissecting drug resistance mechanisms in trypanosomes, the establishment of a high throughput approach rapidly led to a significant increase in our understanding of both potential resistance mechanisms and the networks of proteins that influence drug efficacy. See text for abbreviations and references. (B) Drug selection of the tetracycline induced RNAi library can rapidly generate a resistant population. The RNAi targets, whose expression confers drug resistance, are sequenced using RNAi plasmid-specific primers (grey bars) on a next generation sequencing platform, such as Illumina, and mapped to the reference genome to identify candidate drug efficacy determinants.