Abstract
Introduction
Human African trypanosomiasis, commonly known as sleeping sickness, is a vector-borne parasitic disease prevalent in sub-Saharan Africa and transmitted by the tsetse fly. Suramin, a medication with a long history of clinical use, has demonstrated varied modes of action against Trypanosoma brucei. This study employs a comprehensive workflow to investigate the metabolic effects of suramin on T. brucei, utilizing a multimodal metabolomics approach.
Objectives
The primary aim of this study is to comprehensively analyze the metabolic impact of suramin on T. brucei using a combined liquid chromatography-mass spectrometry (LC–MS) and nuclear magnetic resonance spectroscopy (NMR) approach. Statistical analyses, encompassing multivariate analysis and pathway enrichment analysis, are applied to elucidate significant variations and metabolic changes resulting from suramin treatment.
Methods
A detailed methodology involving the integration of high-resolution data from LC–MS and NMR techniques is presented. The study conducts a thorough analysis of metabolite profiles in both suramin-treated and control T. brucei brucei samples. Statistical techniques, including ANOVA-simultaneous component analysis (ASCA), principal component analysis (PCA), ANOVA 2 analysis, and bootstrap tests, are employed to discern the effects of suramin treatment on the metabolomics outcomes.
Results
Our investigation reveals substantial differences in metabolic profiles between the control and suramin-treated groups. ASCA and PCA analysis confirm distinct separation between these groups in both MS-negative and NMR analyses. Furthermore, ANOVA 2 analysis and bootstrap tests confirmed the significance of treatment, time, and interaction effects on the metabolomics outcomes. Functional analysis of the data from LC–MS highlighted the impact of treatment on amino-acid, and amino-sugar and nucleotide-sugar metabolism, while time effects were observed on carbon intermediary metabolism (notably glycolysis and di- and tricarboxylic acids of the succinate production pathway and tricarboxylic acid (TCA) cycle).
Conclusion
Through the integration of LC–MS and NMR techniques coupled with advanced statistical analyses, this study identifies distinctive metabolic signatures and pathways associated with suramin treatment in T. brucei. These findings contribute to a deeper understanding of the pharmacological impact of suramin and have the potential to inform the development of more efficacious therapeutic strategies against African trypanosomiasis.
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Notes
EC50 should be read as the half maximal effective concentration that describes the inhibitory effects on the growth of cultured cells, unlike the IC50 mentioned later that describes the half maximal inhibitory concentration to describe effects on (purified) proteins.(Borchardt, 2012; Kazakova & Masson, n.d.).
References
Adusumilli, R., & Mallick, P. (2017). Data conversion with ProteoWizard msConvert. Methods in Molecular Biology (Clifton, N.J.), 1550, 339–368. https://doi.org/10.1007/978-1-4939-6747-6_23
Alsford, S., Eckert, S., Baker, N., Glover, L., Sanchez-Flores, A., Leung, K. F., Turner, D. J., Field, M. C., Berriman, M., & Horn, D. (2012). High-throughput decoding of antitrypanosomal drug efficacy and resistance. Nature, 482(7384), 232–236. https://doi.org/10.1038/nature10771
Bakker, B. M., Michels, P. A. M., Opperdoes, F. R., & Westerhoff, H. V. (1999). What controls glycolysis in bloodstream form Trypanosoma brucei? Journal of Biological Chemistry, 274(21), 14551–14559. https://doi.org/10.1074/jbc.274.21.14551
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Borchardt, R. T. (2012). Mechanism of drug action: Basic concepts. In Retrometabolic drug design and targeting (8th ed., Vol. 74, pp. 9–38). Wiley.
Bringaud, F., Baltz, D., & Baltz, T. (1998). Functional and molecular characterization of a glycosomal PPi-dependent enzyme in trypanosomatids: Pyruvate, phosphate dikinase. Proceedings of the National Academy of Sciences of the United States of America, 95(14), 7963–7968. https://doi.org/10.1073/pnas.95.14.7963
Creek, D. J., Mazet, M., Achcar, F., Anderson, J., Kim, D.-H., Kamour, R., Morand, P., Millerioux, Y., Biran, M., Kerkhoven, E. J., Chokkathukalam, A., Weidt, S. K., Burgess, K. E. V., Breitling, R., Watson, D. G., Bringaud, F., & Barrett, M. P. (2015). Probing the metabolic network in bloodstream-form Trypanosoma brucei using untargeted metabolomics with stable isotope labelled glucose. PLoS Pathogens. https://doi.org/10.1371/journal.ppat.1004689
Fall, F., Mamede, L., Schioppa, L., Ledoux, A., De Tullio, P., Michels, P., Frédérich, M., & Quetin-Leclercq, J. (2022). Trypanosoma brucei: Metabolomics for analysis of cellular metabolism and drug discovery. Metabolomics, 18(4), 20. https://doi.org/10.1007/s11306-022-01880-0
Giacomoni, F., Le Corguillé, G., Monsoor, M., Landi, M., Pericard, P., Pétéra, M., Duperier, C., Tremblay-Franco, M., Martin, J.-F., Jacob, D., Goulitquer, S., Thévenot, E. A., & Caron, C. (2015). Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics, 31(9), 1493–1495. https://doi.org/10.1093/bioinformatics/btu813
Hannaert, V. (2011). Sleeping sickness pathogen (Trypanosoma brucei) and natural products: Therapeutic targets and screening systems. Planta Medica, 77(6), 586–597. https://doi.org/10.1055/s-0030-1250411
Hirumi, H., & Hirumi, K. (1994). Axenic culture of African trypanosome bloodstream forms. Parasitology Today, 10(2), 80–84. https://doi.org/10.1016/0169-4758(94)90402-2
Jansen, J. J., Hoefsloot, H. C. J., Van der Greef, J., Timmerman, M. E., & Smilde, A. K. (2005). ASCA: Analysis of multivariate data obtained from an experimental design. Journal of Chemometrics, 19(9), 469–481. https://doi.org/10.1002/cem.952
Kazakova, R. R., & Masson, P. (n.d.). Quantitative Measurements of Pharmacological and Toxicological Activity of Molecules. Chemestry, 4(4), 1466–1474. https://doi.org/10.3390/chemistry4040097
Kushwaha, V., & Capalash, N. (2022). Aminoacyl-tRNA synthetase (AARS) as an attractive drug target in neglected tropical trypanosomatid diseases-Leishmaniasis, Human African Trypanosomiasis and Chagas disease. Molecular and Biochemical Parasitology, 251, 111510. https://doi.org/10.1016/j.molbiopara.2022.111510
Li, S., Park, Y., Duraisingham, S., Strobel, F. H., Khan, N., Soltow, Q. A., Jones, D. P., & Pulendran, B. (2013). Predicting network activity from high throughput metabolomics. PLoS Computational Biology, 9(7), e1003123. https://doi.org/10.1371/journal.pcbi.1003123
Marchese, L., de Nascimento, J. F., Damasceno, F. S., Bringaud, F., Michels, P. A. M., & Silber, A. M. (2018). The Uptake and metabolism of amino acids, and their unique role in the biology of pathogenic trypanosomatids. Pathogens, 7(2), 36. https://doi.org/10.3390/pathogens7020036
Mazet, M., Morand, P., Biran, M., Bouyssou, G., Courtois, P., Daulouède, S., Millerioux, Y., Franconi, J.-M., Vincendeau, P., Moreau, P., & Bringaud, F. (2013). Revisiting the central metabolism of the bloodstream forms of Trypanosoma brucei: Production of acetate in the mitochondrion is essential for parasite viability. PLoS Neglected Tropical Diseases, 7(12), e2587. https://doi.org/10.1371/journal.pntd.0002587
Michels, P. A. M., & Gualdrón-López, M. (2022). Biogenesis and metabolic homeostasis of trypanosomatid glycosomes: New insights and new questions. The Journal of Eukaryotic Microbiology, 69(6), e12897. https://doi.org/10.1111/jeu.12897
Michels, P. A. M., Villafraz, O., Pineda, E., Alencar, M. B., Cáceres, A. J., Silber, A. M., & Bringaud, F. (2021). Carbohydrate metabolism in trypanosomatids: New insights revealing novel complexity, diversity and species-unique features. Experimental Parasitology, 224, 108102. https://doi.org/10.1016/j.exppara.2021.108102
Misset, O., Bos, O. J., & Opperdoes, F. R. (1986). Glycolytic enzymes of Trypanosoma brucei. Simultaneous purification, intraglycosomal concentrations and physical properties. European Journal of Biochemistry, 157(2), 441–453. https://doi.org/10.1111/j.1432-1033.1986.tb09687.x
Morgan, H. P., Zhong, W., McNae, I. W., Michels, P. A. M., Fothergill-Gilmore, L. A., & Walkinshaw, M. D. (2014). Structures of pyruvate kinases display evolutionarily divergent allosteric strategies. Royal Society Open Science, 1(1), 140120. https://doi.org/10.1098/rsos.140120
Nare, Z., Moses, T., Burgess, K., Schnaufer, A., Walkinshaw, M. D., & Michels, P. A. M. (2023). Metabolic insights into phosphofructokinase inhibition in bloodstream-form trypanosomes. Frontiers in Cellular and Infection Microbiology, 13, 1129791. https://doi.org/10.3389/fcimb.2023.1129791
Nascimento, J. F., Souza, R. O. O., Alencar, M. B., Marsiccobetre, S., Murillo, A. M., Damasceno, F. S., Girard, R. B. M. M., Marchese, L., Luévano-Martinez, L. A., Achjian, R. W., Haanstra, J. R., Michels, P. A. M., & Silber, A. M. (2023). How much (ATP) does it cost to build a trypanosome? A theoretical study on the quantity of ATP needed to maintain and duplicate a bloodstream-form Trypanosoma brucei cell. PLoS Pathogens, 19(7), e1011522. https://doi.org/10.1371/journal.ppat.1011522
Nasim, F., & Qureshi, I. A. (2023). Aminoacyl tRNA synthetases: Implications of structural biology in drug development against trypanosomatid parasites. ACS Omega, 8(17), 14884–14899. https://doi.org/10.1021/acsomega.3c00826
NMR-based Metabolomics. (2018). The Royal Society of Chemistry. https://doi.org/10.1039/9781782627937
Opperdoes, F. R., & Borst, P. (1977). Localization of nine glycolytic enzymes in a microbody-like organelle in Trypanosoma brucei: The glycosome. FEBS Letters, 80(2), 360–364. https://doi.org/10.1016/0014-5793(77)80476-6
Pang, Z., Chong, J., Li, S., & Xia, J. (2020). MetaboAnalystR 3.0: Toward an optimized workflow for global metabolomics. Metabolites, 10(5), 186. https://doi.org/10.3390/metabo10050186
Pang, Z., Chong, J., Zhou, G., de Lima Morais, D. A., Chang, L., Barrette, M., Gauthier, C., Jacques, P. -É., Li, S., & Xia, J. (2021). MetaboAnalyst 5.0: Narrowing the gap between raw spectra and functional insights. Nucleic Acids Research, 49(1), W388–W396. https://doi.org/10.1093/nar/gkab382
Steverding, D., & Troeberg, L. (2023). 100 years since the publication of the suramin formula. Parasitology Research, 123(1), 11. https://doi.org/10.1007/s00436-023-08027-7
Thiel, M., Benaiche, N., Martin, M., Franceschini, S., Van Oirbeek, R., & Govaerts, B. (2023). limpca: An R package for the linear modeling of high-dimensional designed data based on ASCA/APCA family of methods. Journal of Chemometrics, 37(7), e3482. https://doi.org/10.1002/cem.3482
Thiel, M., Féraud, B., & Govaerts, B. (2017). ASCA+ and APCA+: Extensions of ASCA and APCA in the analysis of unbalanced multifactorial designs: Analyzing unbalanced multifactorial designs with ASCA+ and APCA+. Journal of Chemometrics, 31(6), e2895. https://doi.org/10.1002/cem.2895
Vincent, I. M., & Barrett, M. P. (2015). Metabolomic-based strategies for anti-parasite drug discovery. Journal of Biomolecular Screening, 20(1), 44–55. https://doi.org/10.1177/1087057114551519
Wiedemar, N., Hauser, D. A., & Mäser, P. (2020). 100 Years of Suramin. Antimicrobial Agents and Chemotherapy. https://doi.org/10.1128/AAC.01168-19
Wiemer, E. A., Michels, P. A., & Opperdoes, F. R. (1995). The inhibition of pyruvate transport across the plasma membrane of the bloodstream form of Trypanosoma brucei and its metabolic implications. The Biochemical Journal, 312(Pt 2), 479–484. https://doi.org/10.1042/bj3120479
Willson, M., Callens, M., Kuntz, D. A., Perié, J., & Opperdoes, F. R. (1993). Synthesis and activity of inhibitors highly specific for the glycolytic enzymes from Trypanosoma brucei. Molecular and Biochemical Parasitology, 59(2), 201–210. https://doi.org/10.1016/0166-6851(93)90218-m
Wishart, D. S., Tzur, D., Knox, C., Eisner, R., Guo, A. C., Young, N., Cheng, D., Jewell, K., Arndt, D., Sawhney, S., Fung, C., Nikolai, L., Lewis, M., Coutouly, M.-A., Forsythe, I., Tang, P., Shrivastava, S., Jeroncic, K., Stothard, P., … Querengesser, L. (2007). HMDB: The Human Metabolome Database. Nucleic Acids Research, 35(Database issue), D521–526. https://doi.org/10.1093/nar/gkl923
Wishart, D. S. (2010). Computational approaches to metabolomics. Methods in Molecular Biology (Clifton, N.J.), 593, 283–313. https://doi.org/10.1007/978-1-60327-194-3_14
Zíková, A., Verner, Z., Nenarokova, A., Michels, P. A. M., & Lukeš, J. (2017). A paradigm shift: The mitoproteomes of procyclic and bloodstream Trypanosoma brucei are comparably complex. PLoS Pathogens, 13(12), e1006679. https://doi.org/10.1371/journal.ppat.1006679
Zoltner, M., Campagnaro, G. D., Taleva, G., Burrell, A., Cerone, M., Leung, K.-F., Achcar, F., Horn, D., Vaughan, S., Gadelha, C., Zíková, A., Barrett, M. P., de Koning, H. P., & Field, M. C. (2020). Suramin exposure alters cellular metabolism and mitochondrial energy production in African trypanosomes. Journal of Biological Chemistry. https://doi.org/10.1074/jbc.RA120.012355
Zoltner, M., Leung, K. F., Alsford, S., Horn, D., & Field, M. C. (2015). Modulation of the surface proteome through multiple ubiquitylation pathways in African trypanosomes. PLoS Pathogens, 11(10), e1005236. https://doi.org/10.1371/journal.ppat.1005236
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This work was funded by Fonds De La Recherche Scientifique - FNRS (grant no. T.0092.20).
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Conceptualization: Fanta Fall, Joëlle Quetin-Leclercq, Bernadette Govaerts Literature search : Fanta Fall, Madeline Vast, Paul Michels Writing - original draft preparation: Fanta Fall, Paul Michels, Madeline Vast, Lucia Mamede Writing - review and editing: Fanta Fall, Paul Michels, Joëlle Quetin-Leclercq, Lucia Mamede, Bernadette Govaerts, Pascal De Tullio, Michel Frédérich, Marie-Pierre Hayette Supervision: Joëlle Quetin-Leclercq, Bernadette Govaerts
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Supplementary Fig. 1
Time-dependent decrease of viability of in vitro cultured T. brucei in the presence of 17.2 nM suramin compared to trypanosomes grown in the absence of the drug. Viable trypanosomes, as judged by their motility, were counted using a Bürker hemacytometer chamber and inverted optical microscope. Supplementary Fig. 2 APCA score plots resulting of the PCA on the augmented effect matrices (interaction and residuals) for the three analytical methods. A : MS-negative ionization, B : MS-positive ionization and C : NMR analysis. Supplementary Fig. 3 Example of plot for important feature visualization issued from ASCA and ANOVA 2 results. Supplementary Fig. 4 Total number of features (blue) at the start and number of significant features (red) issued from ANOVA separated by model effect. The number of features with potential matches (identification) and those with potential matches in significant pathways (pathway enrichment) were determined. A: MS data in negative mode, and B: MS data in positive mode. (DOCX 159 kb)
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Fall, F., Mamede, L., Vast, M. et al. First comprehensive untargeted metabolomics study of suramin-treated Trypanosoma brucei: an integrated data analysis workflow from multifactor data modelling to functional analysis. Metabolomics 20, 25 (2024). https://doi.org/10.1007/s11306-024-02094-2
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DOI: https://doi.org/10.1007/s11306-024-02094-2