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Dr Fidele Tugizimana

Lecturer and Deputy Head of Department (Research)
Name: Fidele Tugizimana
Location: C2 Lab 3rd Floor Auckland Park Kingsway Campus
Biochemistry, Biochemistry Staff  Staff Members

Contact Details:
Tel: +27 (0)11 559 7784

Email: ftugizimana@uj.ac.za

About Dr Fidele Tugizimana

Fidele Tugizimana is among the leaders in the field of metabolomics nationally and internationally, contributing to the advancement and applications of metabolomics. He combines a multidisciplinary approach at the interface of mass spectrometry-based (computational) metabolomics, natural product research, plant biostimulants, big data analytics, artificial intelligence, and biochemistry. The three main research pillars are (i) biostimulant-plant interactions for an innovative formulation and application programs of biostimulant products, for sustainable and productive farming practices; (ii) natural product research for drug discovery, with a focus on medicinal plants in Africa; and (iii)methodology and workflows in metabolomics, addressing various bottlenecks in metabolomics workflows through community-driven efforts, innovatively designing strategies to maximize biological insights from metabolomics studies. His work aligns with the UNSDGs, the Africa Agenda 2063, and South Africa’s National Development Plan, addressing critical global, regional, and local challenges.

  • Director: the UJ Research Centre for Plant Metabolomics
  • Visiting Professor: University of Messina, Italy

LINKS:

Research articles

  1. Myoli, A., Choene, M., Kappo, A.P., Madala, N.E., van der Hooft, J.J.J., Tugizimana, F. (2024). Charting the Cannabis plant chemical space with computational metabolomics. Metabolomics 20, 62. https://doi.org/10.1007/s11306-024-02125-y
  2. Mutabdžija, L., Myoli, A., de Jonge, N.F., Damiani, T., Schmid, R., van der Hooft, J.J.J., Tugizimana, F., Pluskal, T. (2024). Studying Plant Specialized Metabolites Using Computational Metabolomics Strategies. In: Maghuly, F. (eds) Plant Functional Genomics. Methods in Molecular Biology, vol 2788. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3782-1_7
  3. Zuffa, S., Schmid, R., … Tugizimana, F., Dorrestein, P. C. (2024). microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data. Nature Microbiology (IF = 30.96), 9, 336-345.https://doi.org/10.1038/s41564-023-01575-9
  4. Lephatsi, M.M.; Choene, M.S.; Kappo, A.P.; Madala, N.E.; Tugizimana, F. (2023). An Integrated Molecular Networking and Docking Approach to Characterize the Metabolome of Helichrysum splendidum and Its Pharmaceutical Potentials. Metabolites, 13, 1104. https://doi.org/10.3390/metabo13101104
  5. Othibeng, K., Nephali, L., Tugizimana F. (2023). Computational metabolomics to elucidate molecular signalling and regulatory mechanisms associated with biostimulant-mediated growth promotion and abiotic stress tolerance in plant crops. In: Couée I (ed) Plant Abiotic Stress Signaling. Methods in Molecular Biology, vol 2642. Humana New York, NY, USA (Book Chapter). https://doi.org/10.1007/978-1-0716-3044-0_9
  6. Ramabulana, AT., Petras, D., Madala, N.E., Tugizimana, F. (2023). Mass spectrometry DDA parameters and global coverage of the metabolome: Spectral molecular networks of Momordica cardiospermoides Metabolomics 19, 18. https://doi.org/10.1007/s11306-023-01981-4
  7. Nephali L, Steenkamp P, Burgess K, Huyser J, Brand M, van der Hooft JJJ and Tugizimana F (2022) Mass Spectral Molecular Networking to Profile the Metabolome of Biostimulant Bacillus Strains. Plant Sci. 13:920963. https://doi.org/10.3389/fpls.2022.920963
  8. Winder, C.L., Witting, M., Tugizimana, F. et al. (2022). Providing metabolomics education and training: pedagogy and considerations. Metabolomics 18, 106. https://doi.org/10.1007/s11306-022-01957-w
  9. Tinte, M.M.; Chele, K.H.; van der Hooft, J.J.J.; Tugizimana, F. (2021). Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview. Metabolites, 11, 445. https://doi.org/10.3390/metabo11070445

   10. Aron, A.T., Gentry, E., (…), Tugizimana, F., et al. (2020). Reproducible Molecular Networking of Untargeted Mass Spectrometry Data Using GNPS. Nature        Protocols, 15 1954-1991 https://doi.org/10.1038/s41596-020-0317-5