Experimental evolution links post-transcriptional regulation to Leishmania fitness gain
Jazyk angličtina Země Spojené státy americké Médium electronic-ecollection
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
35294501
PubMed Central
PMC8959184
DOI
10.1371/journal.ppat.1010375
PII: PPATHOGENS-D-21-02620
Knihovny.cz E-zdroje
- MeSH
- Leishmania donovani * genetika MeSH
- leishmanióza viscerální * parazitologie MeSH
- lidé MeSH
- nestabilita genomu MeSH
- proteomika MeSH
- regulace genové exprese MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
The protozoan parasite Leishmania donovani causes fatal human visceral leishmaniasis in absence of treatment. Genome instability has been recognized as a driver in Leishmania fitness gain in response to environmental change or chemotherapy. How genome instability generates beneficial phenotypes despite potential deleterious gene dosage effects is unknown. Here we address this important open question applying experimental evolution and integrative systems approaches on parasites adapting to in vitro culture. Phenotypic analyses of parasites from early and late stages of culture adaptation revealed an important fitness tradeoff, with selection for accelerated growth in promastigote culture (fitness gain) impairing infectivity (fitness costs). Comparative genomics, transcriptomics and proteomics analyses revealed a complex regulatory network associated with parasite fitness gain, with genome instability causing highly reproducible, gene dosage-independent and -dependent changes. Reduction of flagellar transcripts and increase in coding and non-coding RNAs implicated in ribosomal biogenesis and protein translation were not correlated to dosage changes of the corresponding genes, revealing a gene dosage-independent, post-transcriptional mechanism of regulation. In contrast, abundance of gene products implicated in post-transcriptional regulation itself correlated to corresponding gene dosage changes. Thus, RNA abundance during parasite adaptation is controled by direct and indirect gene dosage changes. We correlated differential expression of small nucleolar RNAs (snoRNAs) with changes in rRNA modification, providing first evidence that Leishmania fitness gain in culture may be controlled by post-transcriptional and epitranscriptomic regulation. Our findings propose a novel model for Leishmania fitness gain in culture, where differential regulation of mRNA stability and the generation of modified ribosomes may potentially filter deleterious from beneficial gene dosage effects and provide proteomic robustness to genetically heterogenous, adapting parasite populations. This model challenges the current, genome-centric approach to Leishmania epidemiology and identifies the Leishmania transcriptome and non-coding small RNome as potential novel sources for the discovery of biomarkers that may be associated with parasite phenotypic adaptation in clinical settings.
Department of Parasitology Faculty of Science Charles University Prague Czech Republic
Institut Pasteur Biomics Paris France; Institut Pasteur UTechS MSBio Paris France
Université Paris Saclay CEA Centre National de Recherche en Génomique Humaine Evry France
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WHO. Leishmaniasis in high-burden countries: an epidemiological update based on data reported in 2014. 2016 Jun 3. Report No.: 0049–8114 (Print) 0049–8114 (Linking) Contract No.: 22. PubMed
Lindgren E, Andersson Y, Suk JE, Sudre B, Semenza JC. Public health. Monitoring EU emerging infectious disease risk due to climate change. Science. 2012;336(6080):418–9. doi: 10.1126/science.1215735 PubMed DOI
Koonin EV, Wolf YI. Evolution of microbes and viruses: a paradigm shift in evolutionary biology? Front Cell Infect Microbiol. 2012;2:119. doi: 10.3389/fcimb.2012.00119 PubMed DOI PMC
Michaeli S. Trans-splicing in trypanosomes: machinery and its impact on the parasite transcriptome. Future Microbiol. 2011;6(4):459–74. doi: 10.2217/fmb.11.20 PubMed DOI
Clayton CE. Gene expression in Kinetoplastids. Curr Opin Microbiol. 2016;32:46–51. doi: 10.1016/j.mib.2016.04.018 PubMed DOI
Sterkers Y, Walton EL. The Leishmania chromosome lottery. Microbes Infect. 2014;16(1):2–5. doi: 10.1016/j.micinf.2013.11.008 PubMed DOI
Rogers MB, Hilley JD, Dickens NJ, Wilkes J, Bates PA, Depledge DP, et al.. Chromosome and gene copy number variation allow major structural change between species and strains of Leishmania. Genome Res. 2011;21(12):2129–42. doi: 10.1101/gr.122945.111 PubMed DOI PMC
Dumetz F, Imamura H, Sanders M, Seblova V, Myskova J, Pescher P, et al.. Modulation of Aneuploidy in Leishmania donovani during Adaptation to Different In Vitro and In Vivo Environments and Its Impact on Gene Expression. mBio. 2017;8(3). doi: 10.1128/mBio.00599-17 PubMed DOI PMC
Iantorno SA, Durrant C, Khan A, Sanders MJ, Beverley SM, Warren WC, et al.. Gene Expression in Leishmania Is Regulated Predominantly by Gene Dosage. mBio. 2017;8(5). doi: 10.1128/mBio.01393-17 PubMed DOI PMC
Prieto Barja P, Pescher P, Bussotti G, Dumetz F, Imamura H, Kedra D, et al.. Haplotype selection as an adaptive mechanism in the protozoan pathogen Leishmania donovani. Nat Ecol Evol. 2017;1(12):1961–9. doi: 10.1038/s41559-017-0361-x PubMed DOI
Brotherton M-C, Bourassa S, Leprohon P, Légaré D, Poirier GG, Droit A, et al.. Proteomic and Genomic Analyses of Antimony Resistant Leishmania infantum Mutant. PLOS ONE. 2013;8(11):e81899. doi: 10.1371/journal.pone.0081899 PubMed DOI PMC
Downing T, Imamura H, Decuypere S, Clark TG, Coombs GH, Cotton JA, et al.. Whole genome sequencing of multiple Leishmania donovani clinical isolates provides insights into population structure and mechanisms of drug resistance. Genome Res. 2011;21(12):2143–56. doi: 10.1101/gr.123430.111 PubMed DOI PMC
Laffitte MN, Leprohon P, Papadopoulou B, Ouellette M. Plasticity of the Leishmania genome leading to gene copy number variations and drug resistance. F1000Res. 2016;5:2350. doi: 10.12688/f1000research.9218.1 PubMed DOI PMC
Leprohon P, Legare D, Raymond F, Madore E, Hardiman G, Corbeil J, et al.. Gene expression modulation is associated with gene amplification, supernumerary chromosomes and chromosome loss in antimony-resistant Leishmania infantum. Nucleic Acids Res. 2009;37(5):1387–99. doi: 10.1093/nar/gkn1069 PubMed DOI PMC
Ubeda JM, Raymond F, Mukherjee A, Plourde M, Gingras H, Roy G, et al.. Genome-wide stochastic adaptive DNA amplification at direct and inverted DNA repeats in the parasite Leishmania. PLoS Biol. 2014;12(5):e1001868. doi: 10.1371/journal.pbio.1001868 PubMed DOI PMC
Zhang WW, Ramasamy G, McCall LI, Haydock A, Ranasinghe S, Abeygunasekara P, et al.. Genetic analysis of Leishmania donovani tropism using a naturally attenuated cutaneous strain. PLoS Pathog. 2014;10(7):e1004244. doi: 10.1371/journal.ppat.1004244 PubMed DOI PMC
Bussotti G, Piel L., Pescher P., Domagalska M., Rajan K. S., Doniger T., Hiregange D., Myler P. J., Unger R., Michaeli S., and Spath G. F. Genome instability drives epistatic adaptation in the human pathogen Leishmania. bioRxiv, PNAS accepted for publication. 2021. doi: 10.1073/pnas.2113744118 PubMed DOI PMC
Yona AH, Manor YS, Herbst RH, Romano GH, Mitchell A, Kupiec M, et al.. Chromosomal duplication is a transient evolutionary solution to stress. Proceedings of the National Academy of Sciences of the United States of America. 2012;109(51):21010–5. doi: 10.1073/pnas.1211150109 PubMed DOI PMC
Negrini S, Gorgoulis VG, Halazonetis TD. Genomic instability—an evolving hallmark of cancer. Nat Rev Mol Cell Biol. 2010;11(3):220–8. doi: 10.1038/nrm2858 PubMed DOI
Bussotti G, Gouzelou E, Cortes Boite M, Kherachi I, Harrat Z, Eddaikra N, et al.. Leishmania Genome Dynamics during Environmental Adaptation Reveal Strain-Specific Differences in Gene Copy Number Variation, Karyotype Instability, and Telomeric Amplification. mBio. 2018;9(6). PubMed PMC
Melo GD, Goyard S, Lecoeur H, Rouault E, Pescher P, Fiette L, et al.. New insights into experimental visceral leishmaniasis: Real-time in vivo imaging of Leishmania donovani virulence. PLoS Negl Trop Dis. 2017;11(9):e0005924. doi: 10.1371/journal.pntd.0005924 PubMed DOI PMC
Bakin A, Ofengand J. Mapping of the 13 pseudouridine residues in Saccharomyces cerevisiae small subunit ribosomal RNA to nucleotide resolution. Nucleic Acids Res. 1995;23(16):3290–4. doi: 10.1093/nar/23.16.3290 PubMed DOI PMC
Chikne V, Doniger T, Rajan KS, Bartok O, Eliaz D, Cohen-Chalamish S, et al.. A pseudouridylation switch in rRNA is implicated in ribosome function during the life cycle of Trypanosoma brucei. Sci Rep. 2016;6:25296. doi: 10.1038/srep25296 PubMed DOI PMC
Rajan KS, Doniger T, Cohen-Chalamish S, Chen D, Semo O, Aryal S, et al.. Pseudouridines on Trypanosoma brucei spliceosomal small nuclear RNAs and their implication for RNA and protein interactions. Nucleic Acids Res. 2019;47(14):7633–47. doi: 10.1093/nar/gkz477 PubMed DOI PMC
Liang XH, Xu YX, Michaeli S. The spliced leader-associated RNA is a trypanosome-specific sn(o) RNA that has the potential to guide pseudouridine formation on the SL RNA. RNA. 2002;8(2):237–46. doi: 10.1017/s1355838202018290 PubMed DOI PMC
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al.. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078–9. doi: 10.1093/bioinformatics/btp352 PubMed DOI PMC
DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, et al.. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet. 2011;43(5):491–8. doi: 10.1038/ng.806 PubMed DOI PMC
Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26(6):841–2. doi: 10.1093/bioinformatics/btq033 PubMed DOI PMC
Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30(7):923–30. doi: 10.1093/bioinformatics/btt656 PubMed DOI
Cokelaer T, Desvillecharbrol D, Legendre R, Cardon M. Sequana’: a Set of Snakemake NGS pipelines. Journal of Open Source Software. 2017;2(16):352.
Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. 2011. 2011;17(1):3.
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al.. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2012;29(1):15–21. doi: 10.1093/bioinformatics/bts635 PubMed DOI PMC
Team RC. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing; 2016.
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550. doi: 10.1186/s13059-014-0550-8 PubMed DOI PMC
Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B (Methodological). 1995;57(1):289–300.
Edgar R, Domrachev M, Lash AE. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002;30(1):207–10. doi: 10.1093/nar/30.1.207 PubMed DOI PMC
Cox J, Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol. 2008;26(12):1367–72. doi: 10.1038/nbt.1511 PubMed DOI
Cox J, Neuhauser N, Michalski A, Scheltema RA, Olsen JV, Mann M. Andromeda: a peptide search engine integrated into the MaxQuant environment. J Proteome Res. 2011;10(4):1794–805. doi: 10.1021/pr101065j PubMed DOI
Cox J, Hein MY, Luber CA, Paron I, Nagaraj N, Mann M. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol Cell Proteomics. 2014;13(9):2513–26. doi: 10.1074/mcp.M113.031591 PubMed DOI PMC
Perez-Riverol Y, Csordas A, Bai J, Bernal-Llinares M, Hewapathirana S, Kundu DJ, et al.. The PRIDE database and related tools and resources in 2019: improving support for quantification data. Nucleic Acids Res. 2019;47(D1):D442–D50. doi: 10.1093/nar/gky1106 PubMed DOI PMC
Wieczorek S, Combes F, Lazar C, Giai Gianetto Q, Gatto L, Dorffer A, et al.. DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics. Bioinformatics. 2017;33(1):135–6. doi: 10.1093/bioinformatics/btw580 PubMed DOI PMC
Smyth GK. limma: Linear Models for Microarray Data. In: Gentleman R, Carey VJ, Huber W, Irizarry RA, Dudoit S, editors. Bioinformatics and Computational Biology Solutions Using R and Bioconductor. New York, NY: Springer New York; 2005. p. 397–420.
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al.. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47. doi: 10.1093/nar/gkv007 PubMed DOI PMC
Giai Gianetto Q, Combes F, Ramus C, Bruley C, Coute Y, Burger T. Calibration plot for proteomics: A graphical tool to visually check the assumptions underlying FDR control in quantitative experiments. Proteomics. 2016;16(1):29–32. doi: 10.1002/pmic.201500189 PubMed DOI
Pounds S, Cheng C. Robust estimation of the false discovery rate. Bioinformatics. 2006;22(16):1979–87. doi: 10.1093/bioinformatics/btl328 PubMed DOI
Aulner N, Danckaert A, Rouault-Hardoin E, Desrivot J, Helynck O, Commere PH, et al.. High content analysis of primary macrophages hosting proliferating Leishmania amastigotes: application to anti-leishmanial drug discovery. PLoS Negl Trop Dis. 2013;7(4):e2154. doi: 10.1371/journal.pntd.0002154 PubMed DOI PMC
Volf P, Volfova V. Establishment and maintenance of sand fly colonies. J Vector Ecol. 2011;36 Suppl 1:S1–9. doi: 10.1111/j.1948-7134.2011.00106.x PubMed DOI
Seblova V, Volfova V, Dvorak V, Pruzinova K, Votypka J, Kassahun A, et al.. Phlebotomus orientalis sand flies from two geographically distant Ethiopian localities: biology, genetic analyses and susceptibility to Leishmania donovani. PLoS Negl Trop Dis. 2013;7(4):e2187. doi: 10.1371/journal.pntd.0002187 PubMed DOI PMC
Sadlova J, Price HP, Smith BA, Votypka J, Volf P, Smith DF. The stage-regulated HASPB and SHERP proteins are essential for differentiation of the protozoan parasite Leishmania major in its sand fly vector, Phlebotomus papatasi. Cell Microbiol. 2010;12(12):1765–79. doi: 10.1111/j.1462-5822.2010.01507.x PubMed DOI PMC
Pescher P, Blisnick T, Bastin P, Spath GF. Quantitative proteome profiling informs on phenotypic traits that adapt Leishmania donovani for axenic and intracellular proliferation. Cell Microbiol. 2011;13(7):978–91. doi: 10.1111/j.1462-5822.2011.01593.x PubMed DOI
Spath GF, Beverley SM. A lipophosphoglycan-independent method for isolation of infective Leishmania metacyclic promastigotes by density gradient centrifugation. Exp Parasitol. 2001;99(2):97–103. doi: 10.1006/expr.2001.4656 PubMed DOI
Rogers ME, Chance ML, Bates PA. The role of promastigote secretory gel in the origin and transmission of the infective stage of Leishmania mexicana by the sandfly Lutzomyia longipalpis. Parasitology. 2002;124(Pt 5):495–507. doi: 10.1017/s0031182002001439 PubMed DOI
Lei SM, Romine NM, Beetham JK. Population changes in Leishmania chagasi promastigote developmental stages due to serial passage. J Parasitol. 2010;96(6):1134–8. doi: 10.1645/GE-2566.1 PubMed DOI PMC
McGwire B, Chang KP. Genetic rescue of surface metalloproteinase (gp63)-deficiency in Leishmania amazonensis variants increases their infection of macrophages at the early phase. Mol Biochem Parasitol. 1994;66(2):345–7. doi: 10.1016/0166-6851(94)90160-0 PubMed DOI
Spath GF, Epstein L, Leader B, Singer SM, Avila HA, Turco SJ, et al.. Lipophosphoglycan is a virulence factor distinct from related glycoconjugates in the protozoan parasite Leishmania major. Proceedings of the National Academy of Sciences of the United States of America. 2000;97(16):9258–63. doi: 10.1073/pnas.160257897 PubMed DOI PMC
Erben ED, Fadda A, Lueong S, Hoheisel JD, Clayton C. A genome-wide tethering screen reveals novel potential post-transcriptional regulators in Trypanosoma brucei. PLoS Pathog. 2014;10(6):e1004178. doi: 10.1371/journal.ppat.1004178 PubMed DOI PMC
Lueong S, Merce C, Fischer B, Hoheisel JD, Erben ED. Gene expression regulatory networks in Trypanosoma brucei: insights into the role of the mRNA-binding proteome. Mol Microbiol. 2016;100(3):457–71. doi: 10.1111/mmi.13328 PubMed DOI
de Pablos LM, Ferreira TR, Dowle AA, Forrester S, Parry E, Newling K, et al.. The mRNA-bound Proteome of Leishmania mexicana: Novel Genetic Insight into an Ancient Parasite. Mol Cell Proteomics. 2019;18(7):1271–84. doi: 10.1074/mcp.RA118.001307 PubMed DOI PMC
Rajan KS, Chikne V, Decker K, Waldman Ben-Asher H, Michaeli S. Unique Aspects of rRNA Biogenesis in Trypanosomatids. Trends Parasitol. 2019;35(10):778–94. doi: 10.1016/j.pt.2019.07.012 PubMed DOI
Kamina AD, Williams N. Ribosome Assembly in Trypanosomatids: A Novel Therapeutic Target. Trends Parasitol. 2017;33(4):256–7. doi: 10.1016/j.pt.2016.12.003 PubMed DOI PMC
Watkins NJ, Bohnsack MT. The box C/D and H/ACA snoRNPs: key players in the modification, processing and the dynamic folding of ribosomal RNA. Wiley Interdiscip Rev RNA. 2012;3(3):397–414. doi: 10.1002/wrna.117 PubMed DOI
Eliaz D, Doniger T, Tkacz ID, Biswas VK, Gupta SK, Kolev NG, et al.. Genome-wide analysis of small nucleolar RNAs of Leishmania major reveals a rich repertoire of RNAs involved in modification and processing of rRNA. RNA Biol. 2015;12(11):1222–55. doi: 10.1080/15476286.2015.1038019 PubMed DOI PMC
Lenski RE. What is adaptation by natural selection? Perspectives of an experimental microbiologist. PLoS Genet. 2017;13(4):e1006668. doi: 10.1371/journal.pgen.1006668 PubMed DOI PMC
Clayton C, Shapira M. Post-transcriptional regulation of gene expression in trypanosomes and leishmanias. Mol Biochem Parasitol. 2007;156(2):93–101. doi: 10.1016/j.molbiopara.2007.07.007 PubMed DOI
Tsai HJ, Nelliat A. A Double-Edged Sword: Aneuploidy is a Prevalent Strategy in Fungal Adaptation. Genes (Basel). 2019;10(10). doi: 10.3390/genes10100787 PubMed DOI PMC
Haile S, Papadopoulou B. Developmental regulation of gene expression in trypanosomatid parasitic protozoa. Curr Opin Microbiol. 2007;10(6):569–77. doi: 10.1016/j.mib.2007.10.001 PubMed DOI
Goldstrohm AC, Hall TMT, McKenney KM. Post-transcriptional Regulatory Functions of Mammalian Pumilio Proteins. Trends Genet. 2018;34(12):972–90. doi: 10.1016/j.tig.2018.09.006 PubMed DOI PMC
Thomas G. An encore for ribosome biogenesis in the control of cell proliferation. Nat Cell Biol. 2000;2(5):E71–2. doi: 10.1038/35010581 PubMed DOI
McCutchan TF, de la Cruz VF, Good MF, Wellems TE. Antigenic diversity in Plasmodium falciparum. Prog Allergy. 1988;41:173–92. doi: 10.1159/000415223 PubMed DOI
Li J, Gutell RR, Damberger SH, Wirtz RA, Kissinger JC, Rogers MJ, et al.. Regulation and trafficking of three distinct 18 S ribosomal RNAs during development of the malaria parasite. J Mol Biol. 1997;269(2):203–13. doi: 10.1006/jmbi.1997.1038 PubMed DOI
Guo H. Specialized ribosomes and the control of translation. Biochem Soc Trans. 2018;46(4):855–69. doi: 10.1042/BST20160426 PubMed DOI
Ramagopal S, Ennis HL. Regulation of synthesis of cell-specific ribosomal proteins during differentiation of Dictyostelium discoideum. Proceedings of the National Academy of Sciences of the United States of America. 1981;78(5):3083–7. doi: 10.1073/pnas.78.5.3083 PubMed DOI PMC
Ramagopal S. Induction of cell-specific ribosomal proteins in aggregation-competent nonmorphogenetic Dictyostelium discoideum. Biochem Cell Biol. 1990;68(11):1281–7. doi: 10.1139/o90-190 PubMed DOI
Locati MD, Pagano JFB, Girard G, Ensink WA, van Olst M, van Leeuwen S, et al.. Expression of distinct maternal and somatic 5.8S, 18S, and 28S rRNA types during zebrafish development. RNA. 2017;23(8):1188–99. doi: 10.1261/rna.061515.117 PubMed DOI PMC
Belin S, Beghin A, Solano-Gonzalez E, Bezin L, Brunet-Manquat S, Textoris J, et al.. Dysregulation of ribosome biogenesis and translational capacity is associated with tumor progression of human breast cancer cells. PLoS One. 2009;4(9):e7147. doi: 10.1371/journal.pone.0007147 PubMed DOI PMC
Polacek N, Mankin AS. The ribosomal peptidyl transferase center: structure, function, evolution, inhibition. Crit Rev Biochem Mol Biol. 2005;40(5):285–311. doi: 10.1080/10409230500326334 PubMed DOI
Jack K, Bellodi C, Landry DM, Niederer RO, Meskauskas A, Musalgaonkar S, et al.. rRNA pseudouridylation defects affect ribosomal ligand binding and translational fidelity from yeast to human cells. Mol Cell. 2011;44(4):660–6. doi: 10.1016/j.molcel.2011.09.017 PubMed DOI PMC
King TH, Liu B, McCully RR, Fournier MJ. Ribosome structure and activity are altered in cells lacking snoRNPs that form pseudouridines in the peptidyl transferase center. Mol Cell. 2003;11(2):425–35. doi: 10.1016/s1097-2765(03)00040-6 PubMed DOI
Meleppattu S, Kamus-Elimeleh D, Zinoviev A, Cohen-Mor S, Orr I, Shapira M. The eIF3 complex of Leishmania-subunit composition and mode of recruitment to different cap-binding complexes. Nucleic Acids Res. 2015;43(13):6222–35. doi: 10.1093/nar/gkv564 PubMed DOI PMC
Yoffe Y, Leger M, Zinoviev A, Zuberek J, Darzynkiewicz E, Wagner G, et al.. Evolutionary changes in the Leishmania eIF4F complex involve variations in the eIF4E-eIF4G interactions. Nucleic Acids Res. 2009;37(10):3243–53. doi: 10.1093/nar/gkp190 PubMed DOI PMC
Yoffe Y, Zuberek J, Lerer A, Lewdorowicz M, Stepinski J, Altmann M, et al.. Binding specificities and potential roles of isoforms of eukaryotic initiation factor 4E in Leishmania. Eukaryot Cell. 2006;5(12):1969–79. doi: 10.1128/EC.00230-06 PubMed DOI PMC