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Prediction of Potential Drug Targets for Cutaneous Leishmaniasis By Leishmania major and Leishmania tropica: A Quantitative Proteomics and Bioinformatics Approach


Affiliations
1 Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran, Islamic Republic of
2 Diagnostic Laboratory Sciences and Technology Research Center,Shiraz University of Medical Sciences, Shiraz, Iran, Islamic Republic of
3 Department of Clinical Biochemistry, Zanjan University of Medical Sciences, Zanjan, Iran, Islamic Republic of
 

Leishmania spp. cause life-threatening infectious dis-eases which affect universal health. Novel treatments for leishmaniasis are crucially needed since those available are limited by emerging drug-resistant spe-cies, low efficacy and side effects. In this study, we have employed a quantitative shotgun proteomics and bioinformatics method to identify differentially ex-pressed proteins (DEPs) between Leishmania major and Leishmania tropica and to detect novel potential drug targets for cutaneous leishmaniasis, which may aid in the future drug discovery process. A total of 57 proteins were differentially expressed between the studied species. Based on KEGG pathway analysis, the more upregulated proteins in L. major are clearly re-lated to proteasome and metabolic pathways. In L. tropica, most of the upregulated proteins are related to the metabolic pathway and carbon metabolism. According to gene ontology analysis based on biologi-cal process, the upregulated proteins mainly partici-pated in translation and carbohydrate metabolism in L. tropica and L. major respectively. We have con-structed a protein–protein interaction network that is common for the two species. We detected the top 10 potential targets for drug design by topology analysis of the protein network. Additional in vivo studies are needed to confirm these targets. We have identified several new DEPs between the species which would help in the understanding of pathogenesis mecha-nisms, and offer potential drug targets and vaccine candidates. Analysis of the predicted protein network provides a catalogue of key proteins, which can be considered in future studies to be validated as drug-gable targets against cutaneous leishmaniasis.

Keywords

Cutaneous Leishmaniasis, Leishmania tropica, Leishmania major, Protein Interaction Network, Quantitative Proteomics.
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  • Hepburn, N., Cutaneous leishmaniasis. Clin. Exp. Dermatol., 2000, 25, 363–370.
  • Amiri-Dashatan, N., Koushki, M., Rezaei Tavirani, M. and Ah-madi, N., Proteomic-based studies on Leishmania. J. Mazandaran Univ. Med. Sci., 2018, 28, 173–190.
  • Ahmadi, N., Modiri, M. and Mamdohi, S., First survey of cutane-ous leishmaniasis in Borujerd County, Western Islamic Republic of Iran. East. Mediterr. Health J., 2013, 19, 847–853.
  • Ashrafmansouri, M., Sarkari, B., Hatam, G., Habibi, P. and Kha-bisi, S. A., Utility of Western blot analysis for the diagnosis of cutaneous leishmaniasis. Iran. J. Parasitol., 2015, 10, 599.
  • Lawn, S. D., Armstrong, M., Chilton, D. and Whitty, C. J., Elec-trocardiographic and biochemical adverse effects of sodium stibogluconate during treatment of cutaneous and mucosal leish-maniasis among returned travellers. Trans. R. Soc. Trop. Med. Hyg., 2006, 100, 264–269.
  • Grogl, M., Thomason, T. N. and Franke, E. D., Drug resistance in leishmaniasis: its implication in systemic chemotherapy of cuta-neous and mucocutaneous disease. Am. J. Trop. Med. Hyg., 1992, 47, 117–126.
  • Singh, B. and Sundar, S., Leishmaniasis: vaccine candidates and perspectives. Vaccine, 2012, 30, 3834–3842.
  • Atan, N. A. D., Koushki, M., Ahmadi, N. A. and Rezaei-Tavirani, M., Metabolomics-based studies in the field of Leishmania/ leishmaniasis. Alexandria J. Med., 2018, 54, 383–390.
  • Dashatan, N. A., Tavirani, M. R., Zali, H., Koushki, M. and Ah-madi, N., Prediction of Leishmania major key proteins via topo-logical analysis of protein–protein interaction network. Galen Med. J., 2018, 7, e1129.
  • Amiri-Dashatan, N., Rezaei-Tavirani, M. and Ahmadi, N., A quantitative proteomic and bioinformatics analysis of proteins in metacyclogenesis of Leishmania tropica. Acta Trop., 2020, 202, 105227.
  • Ashrafmansouri, M., Amiri‐Dashatan, N., Ahmadi, N., Re-zaei‐Tavirani, M., Seyyed Tabaei, S. and Haghighi, A., Quantita-tive proteomic analysis to determine differentially expressed proteins in axenic amastigotes of Leishmania tropica and Leish-mania major. IUBMB Life, 2020, 72, 1715–1724.
  • Paape, D., Barrios-Llerena, M. E., Le Bihan, T., Mackay, L. and Aebischer, T., Gel free analysis of the proteome of intracellular Leishmania mexicana. Mol. Biochem. Parasitol., 2010, 169, 108–114.
  • Zhu, W., Smith, J. W. and Huang, C.-M., Mass spectrometry-based label-free quantitative proteomics. BioMed. Res. Int., 2009, 2010, 840518-6.
  • Singh, S. and Dubey, V. K., Quantitative proteome analysis of Leishmania donovani under spermidine starvation. PLoS ONE, 2016, 11, e0154262.
  • Gorgoni, B. and Gray, N. K., The roles of cytoplasmic poly(a)-binding proteins in regulating gene expression: a developmental perspective. Brief. Funct. Genom., 2004, 3, 125–141.
  • Takashima, E. et al., Characterization of the dihydroorotate dehy-drogenase as a soluble fumarate reductase in Trypanosoma cruzi. Mol. Biochem. Parasitol., 2002, 122, 189–200.
  • Feliciano, P. R., Cordeiro, A. T., Costa-Filho, A. J. and Nonato, M. C., Cloning, expression, purification, and characterization of Leishmania major dihydroorotate dehydrogenase. Protein Expr. Purif., 2006, 48, 98–103.
  • Coustou, V., Biran, M., Besteiro, S., Rivière, L., Baltz, T., Fran-coni, J.-M. and Bringaud, F., Fumarate is an essential intermediary metabolite produced by the procyclic Trypanosoma brucei. J. Biol. Chem., 2006, 281, 26832–26846.
  • Feliciano, P. R., Gupta, S., Dyszy, F., Dias-Baruffi, M., Costa-Filho, A. J., Michels, P. A. and Nonato, M. C., Fumarate hydratase isoforms of Leishmania major: subcellular localization, structural and kinetic properties. Int. J. Biol. Macromol., 2012, 51, 25–31.
  • Miura, A., Kameya, M., Arai, H., Ishii, M. and Igarashi, Y., A soluble NADH-dependent fumarate reductase in the reductive tri-carboxylic acid cycle of Hydrogenobacter thermophilus TK-6. J. Bacteriol., 2008, 190, 7170–7177.
  • Coustou, V. et al., A mitochondrial NADH-dependent fumarate reductase involved in the production of succinate excreted by pro-cyclic Trypanosoma brucei. J. Biol. Chem., 2005, 280, 16559–16570.
  • Leroux, A., Fleming-Canepa, X., Aranda, A., Maugeri, D., Cazzulo, J. J., Sánchez, M. A. and Nowicki, C., Functional charac-terization and subcellular localization of the three malate dehy-drogenase isozymes in Leishmania spp. Mol. Biochem. Parasitol., 2006, 149, 74–85.
  • Westrop, G. D., Williams, R. A., Wang, L., Zhang, T., Watson, D. G., Silva, A. M. and Coombs, G. H., Metabolomic analyses of Leishmania reveal multiple species differences and large differences in amino acid metabolism. PLoS ONE, 2015, 10, e0136891.
  • Parsons, M., Worthey, E. A., Ward, P. N. and Mottram, J. C., Comparative analysis of the kinomes of three pathogenic trypano-somatids: Leishmania major, Trypanosoma brucei and Trypano-soma cruzi. BMC Genom., 2005, 6, 127.
  • Merritt, C., Silva, L. E., Tanner, A. L., Stuart, K. and Pollastri, M. P., Kinases as druggable targets in trypanosomatid protozoan para-sites. Chem. Rev., 2014, 114, 11280–11304.
  • Cordeiro, A. T., Hardré, R., Michels, P. A., Salmon, L., Delboni, L. F. and Thiemann, O. H., Leishmania mexicana mexicana glucose-6-phosphate isomerase: crystallization, molecular-replace-ment solution and inhibition. Acta Crystallogr. Sect. D, 2004, 60, 915–919.
  • da Silva, M. F. L. and Floeter-Winter, L. M., Arginase in leishma-nia. In Proteins and Proteomics of Leishmania and Trypanosoma (eds Santos, A. et al.), Springer, 2014, pp. 103–117.
  • Wanasen, N. and Soong, L., L-arginine metabolism and its impact on host immunity against Leishmania infection. Immunol. Res., 2008, 41, 15–25.
  • Boitz, J. M. et al., Arginase is essential for survival of Leishmania donovani promastigotes but not intracellular amastigotes. Infect. Immunity, 2017, 85, e00554-00516.
  • Muleme, H. M. et al., Infection with arginase-deficient Leishma-nia major reveals a parasite number-dependent and cytokine-independent regulation of host cellular arginase activity and disease pathogenesis. J. Immunol., 2009, 183, 8068–8076.
  • Williams, R. A., Westrop, G. D. and Coombs, G. H., Two path-ways for cysteine biosynthesis in Leishmania major. Biochem. J., 2009, 420, 451–462.
  • Mojtahedi, Z., Clos, J. and Kamali-Sarvestani, E., Leishmania major: identification of developmentally regulated proteins in pro-cyclic and metacyclic promastigotes. Exp. Parasitol., 2008, 119, 422–429.
  • Jeong, H., Mason, S. P., Barabási, A.-L. and Oltvai, Z. N., Lethality and centrality in protein networks. Nature, 2001, 411, 41.
  • Fothergill-Gilmore, L., Rigden, D., Michels, P. and Phillips, S., Leishmania pyruvate kinase: the crystal structure reveals the struc-tural basis of its unique regulatory properties. Biochem. Soc. Trans., 2000, 28, 186–190.
  • Flórez, A. F., Park, D., Bhak, J., Kim, B.-C., Kuchinsky, A., Mor-ris, J. H., Espinosa, J. and Muskus, C., Protein network prediction and topological analysis in Leishmania major as a tool for drug target selection. BMC Bioinformat., 2010, 11, 1–9.

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  • Prediction of Potential Drug Targets for Cutaneous Leishmaniasis By Leishmania major and Leishmania tropica: A Quantitative Proteomics and Bioinformatics Approach

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Authors

Nasrin Amiri-Dashatan
Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran, Islamic Republic of
Marzieh Ashrafmansouri
Diagnostic Laboratory Sciences and Technology Research Center,Shiraz University of Medical Sciences, Shiraz, Iran, Islamic Republic of
Mostafa Rezaei-Tavirani
Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran, Islamic Republic of
Mehdi Koushki
Department of Clinical Biochemistry, Zanjan University of Medical Sciences, Zanjan, Iran, Islamic Republic of
Nayebali Ahmadi
Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran, Islamic Republic of

Abstract


Leishmania spp. cause life-threatening infectious dis-eases which affect universal health. Novel treatments for leishmaniasis are crucially needed since those available are limited by emerging drug-resistant spe-cies, low efficacy and side effects. In this study, we have employed a quantitative shotgun proteomics and bioinformatics method to identify differentially ex-pressed proteins (DEPs) between Leishmania major and Leishmania tropica and to detect novel potential drug targets for cutaneous leishmaniasis, which may aid in the future drug discovery process. A total of 57 proteins were differentially expressed between the studied species. Based on KEGG pathway analysis, the more upregulated proteins in L. major are clearly re-lated to proteasome and metabolic pathways. In L. tropica, most of the upregulated proteins are related to the metabolic pathway and carbon metabolism. According to gene ontology analysis based on biologi-cal process, the upregulated proteins mainly partici-pated in translation and carbohydrate metabolism in L. tropica and L. major respectively. We have con-structed a protein–protein interaction network that is common for the two species. We detected the top 10 potential targets for drug design by topology analysis of the protein network. Additional in vivo studies are needed to confirm these targets. We have identified several new DEPs between the species which would help in the understanding of pathogenesis mecha-nisms, and offer potential drug targets and vaccine candidates. Analysis of the predicted protein network provides a catalogue of key proteins, which can be considered in future studies to be validated as drug-gable targets against cutaneous leishmaniasis.

Keywords


Cutaneous Leishmaniasis, Leishmania tropica, Leishmania major, Protein Interaction Network, Quantitative Proteomics.

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DOI: https://doi.org/10.18520/cs%2Fv120%2Fi6%2F1040-1049