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High-throughput decoding of antitrypanosomal drug efficacy and resistance

Nature volume 482, pages 232–236 (2012)Cite this article

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Abstract

The concept of disease-specific chemotherapy was developed a century ago. Dyes and arsenical compounds that displayed selectivity against trypanosomes were central to this work1,2, and the drugs that emerged remain in use for treating human African trypanosomiasis (HAT)3. The importance of understanding the mechanisms underlying selective drug action and resistance for the development of improved HAT therapies has been recognized, but these mechanisms have remained largely unknown. Here we use all five current HAT drugs for genome-scale RNA interference target sequencing (RIT-seq) screens in Trypanosoma brucei, revealing the transporters, organelles, enzymes and metabolic pathways that function to facilitate antitrypanosomal drug action. RIT-seq profiling identifies both known drug importers4,5 and the only known pro-drug activator6, and links more than fifty additional genes to drug action. A bloodstream stage-specific invariant surface glycoprotein (ISG75) family mediates suramin uptake, and the AP1 adaptin complex, lysosomal proteases and major lysosomal transmembrane protein, as well as spermidine and N-acetylglucosamine biosynthesis, all contribute to suramin action. Further screens link ubiquinone availability to nitro-drug action, plasma membrane P-type H+-ATPases to pentamidine action, and trypanothione and several putative kinases to melarsoprol action. We also demonstrate a major role for aquaglyceroporins in pentamidine and melarsoprol cross-resistance. These advances in our understanding of mechanisms of antitrypanosomal drug efficacy and resistance will aid the rational design of new therapies and help to combat drug resistance, and provide unprecedented molecular insight into the mode of action of antitrypanosomal drugs.

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Figure 1: Identification of drug efficacy determinants in T. brucei.
Figure 2: A network of proteins link ISG75, endocytosis and lysosomal functions to suramin action.
Figure 3: aqp2/aqp3 -null cells are melarsoprol, pentamidine cross-resistant.
Figure 4: Determinants of drug efficacy in African trypanosomes.

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Data deposits

Sequence data from this study have been submitted to the European Nucleotide Archive at http://www.ebi.ac.uk/ena under accession number ERA071064.

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Acknowledgements

We thank J. Morris, Z. Wang, M. Drew and P. Englund for the RNAi plasmid library, V. Yardley for antitrypanosomal drugs, J. Bangs for anti-p67 and CatL sera, D. Russell for anti-GLP1 sera, A. Varghese for assistance with preliminary Sanger sequencing and J. Kelly, M. Taylor and B. Wren for comments on the draft manuscript. The work was funded by grants from The Wellcome Trust (093010/Z/10/Z at the London School of Hygiene & Tropical Medicine, 085775/Z/08/Z at The Wellcome Trust Sanger Institute and 090007/Z/09/Z at The University of Cambridge). N.B. was supported by a Bloomsbury colleges PhD studentship.

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  1. Sabine Eckert & Daniel J. Turner

    Present address: Present address: Oxford Nanopore Technologies, 4 Robert Robinson Avenue, Oxford, OX4 4GA, UK.,

Authors and Affiliations

  1. London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK,

    Sam Alsford, Nicola Baker, Lucy Glover & David Horn

  2. The Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK,

    Sabine Eckert, Alejandro Sanchez-Flores, Daniel J. Turner & Matthew Berriman

  3. Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge, CB2 1QP, UK,

    Ka Fai Leung & Mark C. Field

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Contributions

S.A., N.B., L.G. and K.F.L. carried out the T. brucei manipulation and analyses, S.E., A.S.-F. and D.J.T. carried out the Illumina sequencing and mapping, D.H. coordinated the study and S.A., M.C.F., M.B. and D.H. wrote the paper.

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Correspondence to David Horn.

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Supplementary information

Supplementary Information

This file contains Supplementary Figures 1-6 with legends, Supplementary Table 1 and additional references. Growth curves, sequence read-density signatures, EC50 data and comparative genomic information and HAT drug information are included. (PDF 497 kb)

Supplementary Data 1

This file shows two spreadsheets. The first (a) shows all 'primary' and 'secondary' hits from the HAT drug resistance screens with comments and links to databases. The second (b) shows all genes associated with >9 sequence reads in the HAT drug resistance screens. (XLS 362 kb)

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Alsford, S., Eckert, S., Baker, N. et al. High-throughput decoding of antitrypanosomal drug efficacy and resistance. Nature 482, 232–236 (2012). https://doi.org/10.1038/nature10771

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