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      High-throughput decoding of anti-trypanosomal drug efficacy and resistance

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          Summary

          The concept of specific chemotherapy was developed a century ago by Paul Ehrlich and others. Dyes and arsenical compounds that displayed selectivity against trypanosomes were central to this work 1, 2 , and the drugs that emerged remain in use for treating Human African Trypanosomiasis (HAT) 3 . Ehrlich recognised the importance of understanding the mechanisms underlying selective drug action and resistance for the development of improved HAT therapies, but these mechanisms have remained largely mysterious. Here, we use all five current HAT drugs for genome-scale RNA interference (RNAi) target sequencing (RIT-seq) screens in Trypanosoma brucei, revealing the transporters, organelles, enzymes and metabolic pathways that function to facilitate anti-trypanosomal drug action. RIT-seq profiling identifies both known drug importers 4, 5 and the only known pro-drug activator 6 , and links more than fifty additional genes to drug action. A specific bloodstream stage invariant surface glycoprotein (ISG75) family mediates suramin uptake while the AP-1 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 multiple 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 anti-trypanosomal drug efficacy and resistance will aid the rational design of new therapies and help to combat drug resistance, and provide unprecedented levels of molecular insight into the mode of action of anti-trypanosomal drugs.

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          Most cited references42

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          The genome of the African trypanosome Trypanosoma brucei.

          African trypanosomes cause human sleeping sickness and livestock trypanosomiasis in sub-Saharan Africa. We present the sequence and analysis of the 11 megabase-sized chromosomes of Trypanosoma brucei. The 26-megabase genome contains 9068 predicted genes, including approximately 900 pseudogenes and approximately 1700 T. brucei-specific genes. Large subtelomeric arrays contain an archive of 806 variant surface glycoprotein (VSG) genes used by the parasite to evade the mammalian immune system. Most VSG genes are pseudogenes, which may be used to generate expressed mosaic genes by ectopic recombination. Comparisons of the cytoskeleton and endocytic trafficking systems with those of humans and other eukaryotic organisms reveal major differences. A comparison of metabolic pathways encoded by the genomes of T. brucei, T. cruzi, and Leishmania major reveals the least overall metabolic capability in T. brucei and the greatest in L. major. Horizontal transfer of genes of bacterial origin has contributed to some of the metabolic differences in these parasites, and a number of novel potential drug targets have been identified.
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            SSAHA: a fast search method for large DNA databases.

            We describe an algorithm, SSAHA (Sequence Search and Alignment by Hashing Algorithm), for performing fast searches on databases containing multiple gigabases of DNA. Sequences in the database are preprocessed by breaking them into consecutive k-tuples of k contiguous bases and then using a hash table to store the position of each occurrence of each k-tuple. Searching for a query sequence in the database is done by obtaining from the hash table the "hits" for each k-tuple in the query sequence and then performing a sort on the results. We discuss the effect of the tuple length k on the search speed, memory usage, and sensitivity of the algorithm and present the results of computational experiments which show that SSAHA can be three to four orders of magnitude faster than BLAST or FASTA, while requiring less memory than suffix tree methods. The SSAHA algorithm is used for high-throughput single nucleotide polymorphism (SNP) detection and very large scale sequence assembly. Also, it provides Web-based sequence search facilities for Ensembl projects.
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              Is Open Access

              Artemis and ACT: viewing, annotating and comparing sequences stored in a relational database

              Motivation: Artemis and Artemis Comparison Tool (ACT) have become mainstream tools for viewing and annotating sequence data, particularly for microbial genomes. Since its first release, Artemis has been continuously developed and supported with additional functionality for editing and analysing sequences based on feedback from an active user community of laboratory biologists and professional annotators. Nevertheless, its utility has been somewhat restricted by its limitation to reading and writing from flat files. Therefore, a new version of Artemis has been developed, which reads from and writes to a relational database schema, and allows users to annotate more complex, often large and fragmented, genome sequences. Results: Artemis and ACT have now been extended to read and write directly to the Generic Model Organism Database (GMOD, http://www.gmod.org) Chado relational database schema. In addition, a Gene Builder tool has been developed to provide structured forms and tables to edit coordinates of gene models and edit functional annotation, based on standard ontologies, controlled vocabularies and free text. Availability: Artemis and ACT are freely available (under a GPL licence) for download (for MacOSX, UNIX and Windows) at the Wellcome Trust Sanger Institute web sites: http://www.sanger.ac.uk/Software/Artemis/ http://www.sanger.ac.uk/Software/ACT/ Contact: artemis@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                16 December 2011
                25 January 2012
                09 August 2012
                : 482
                : 7384
                : 232-236
                Affiliations
                [1 ]London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
                [2 ]The Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK.
                [3 ]Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge, CB2 1QP, UK
                Author notes
                [4]

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

                [§ ]To whom correspondence should be addressed. david.horn@ 123456lshtm.ac.uk

                Author Contributions S.A., N.B., L.G. and K.F.L. carried out the T. brucei manipulation and analyses; S.E., A.S. 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.

                Article
                UKMS40204
                10.1038/nature10771
                3303116
                22278056
                8d253562-aa91-4e53-98fa-2aa47fa4324e

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                History
                Funding
                Funded by: Wellcome Trust :
                Award ID: 093010 || WT
                Funded by: Wellcome Trust :
                Award ID: 090007 || WT
                Funded by: Wellcome Trust :
                Award ID: 085775 || WT
                Categories
                Article

                Uncategorized
                isg75,eflornithine,nifurtimox,rnai,dfmo
                Uncategorized
                isg75, eflornithine, nifurtimox, rnai, dfmo

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