Abstract
Leishmania is still a major cause of mortality and morbidity worldwide. Few efficient drugs are available, and resistance threatens actual treatments. In order to improve knowledge about the mode of action of current drugs and those in development, as well as to understand the mechanisms pertaining to their resistance, we recently described a sensitive and high-throughput method termed Cos-Seq. Here we provide a detailed protocol for every step of the procedure, from library construction to drug selection, cosmid extraction, and next-generation sequencing of extracted cosmids. A section on the bioinformatics of Cos-Seq is also included. Cos-Seq facilitates the identification of gain-of-function resistance mechanisms and drug targets and is a useful tool in resistance and drug development studies.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ryan KA, Garraway LA, Descoteaux A et al (1993) Isolation of virulence genes directing surface glycosyl-phosphatidylinositol synthesis by functional complementation of Leishmania. Proc Natl Acad Sci U S A 90(18):8609–8613
Kundig C, Haimeur A, Legare D et al (1999) Increased transport of pteridines compensates for mutations in the high affinity folate transporter and contributes to methotrexate resistance in the protozoan parasite Leishmania tarentolae. EMBO J 18(9):2342–2351. https://doi.org/10.1093/emboj/18.9.2342
Coelho AC, Beverley SM, Cotrim PC (2003) Functional genetic identification of PRP1, an ABC transporter superfamily member conferring pentamidine resistance in Leishmania major. Mol Biochem Parasitol 130(2):83–90
Cotrim PC, Garrity LK, Beverley SM (1999) Isolation of genes mediating resistance to inhibitors of nucleoside and ergosterol metabolism in Leishmania by overexpression/selection. J Biol Chem 274(53):37723–37730
Kotze AC, Hunt PW, Skuce P et al (2014) Recent advances in candidate-gene and whole-genome approaches to the discovery of anthelmintic resistance markers and the description of drug/receptor interactions. Int J Parasitol Drugs Drug Resist 4(3):164–184. https://doi.org/10.1016/j.ijpddr.2014.07.007
Horn D, Duraisingh MT (2014) Antiparasitic chemotherapy: from genomes to mechanisms. Annu Rev Pharmacol Toxicol 54:71–94. https://doi.org/10.1146/annurev-pharmtox-011613-135915
Downing T, Imamura H, Decuypere S et al (2011) Whole genome sequencing of multiple Leishmania donovani clinical isolates provides insights into population structure and mechanisms of drug resistance. Genome Res 21(12):2143–2156. https://doi.org/10.1101/gr.123430.111
Coelho AC, Boisvert S, Mukherjee A et al (2012) Multiple mutations in heterogeneous miltefosine-resistant Leishmania major population as determined by whole genome sequencing. PLoS Negl Trop Dis 6(2):e1512. https://doi.org/10.1371/journal.pntd.0001512
Leprohon P, Fernandez-Prada C, Gazanion E et al (2015) Drug resistance analysis by next generation sequencing in Leishmania. Int J Parasitol Drugs Drug Resist 5(1):26–35. https://doi.org/10.1016/j.ijpddr.2014.09.005
Gazanion E, Fernandez-Prada C, Papadopoulou B et al (2016) Cos-Seq for high-throughput identification of drug target and resistance mechanisms in the protozoan parasite Leishmania. Proc Natl Acad Sci U S A 113(21):E3012–E3021. https://doi.org/10.1073/pnas.1520693113
Albert Descoteaux LAG, Ryan KA, Garrity LK, Tuco SJ, Beverly SM (1994) Identification of Genes by Functional Complementation in Protozoan Parasite Leihsmania. Methods Mol Biol 3:23
Fernandez-Prada C, Sharma M, Plourde M et al (2018) High-throughput Cos-Seq screen with intracellular Leishmania infantum for the discovery of novel drug-resistance mechanisms. Int J Parasitol Drugs Drug Resist 8(2):165–173. https://doi.org/10.1016/j.ijpddr.2018.03.004
Haas BJ, Papanicolaou A, Yassour M et al (2013) De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc 8(8):1494–1512. https://doi.org/10.1038/nprot.2013.084
Li B, Dewey CN (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323. https://doi.org/10.1186/1471-2105-12-323
Zhang C, Zhang B, Lin LL et al (2017) Evaluation and comparison of computational tools for RNA-seq isoform quantification. BMC Genomics 18(1):583. https://doi.org/10.1186/s12864-017-4002-1
Zakeri M, Srivastava A, Almodaresi F et al (2017) Improved data-driven likelihood factorizations for transcript abundance estimation. Bioinformatics 33(14):i142–i151. https://doi.org/10.1093/bioinformatics/btx262
Patro R, Duggal G, Love MI et al (2017) Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods 14(4):417–419. https://doi.org/10.1038/nmeth.4197
Bray NL, Pimentel H, Melsted P et al (2016) Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol 34(5):525–527. https://doi.org/10.1038/nbt.3519
Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26(1):139–140. https://doi.org/10.1093/bioinformatics/btp616
Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15(12):550. https://doi.org/10.1186/s13059-014-0550-8
Law CW, Chen Y, Shi W et al (2014) voom: Precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 15(2):R29. https://doi.org/10.1186/gb-2014-15-2-r29
White TC, Fase-Fowler F, van Luenen H et al (1988) The H circles of Leishmania tarentolae are a unique amplifiable system of oligomeric DNAs associated with drug resistance. J Biol Chem 263(32):16977–16983
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Potvin, JE., Leprohon, P., Gazanion, E., Sharma, M., Fernandez-Prada, C., Ouellette, M. (2019). Cos-Seq: A High-Throughput Gain-of-Function Screen for Drug Resistance Studies in Leishmania. In: Clos, J. (eds) Leishmania. Methods in Molecular Biology, vol 1971. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9210-2_7
Download citation
DOI: https://doi.org/10.1007/978-1-4939-9210-2_7
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-9209-6
Online ISBN: 978-1-4939-9210-2
eBook Packages: Springer Protocols