Quantification of Natural Growth of Two Strains of Mycobacterium Marinum for Translational Antituberculosis Drug Development

Rob C. Van Wijk, Astrid M. van der Sar, Elke H.J. Krekels, Theo Verboom, Herman P. Spaink, Ulrika S.H. Simonsson*, Piet H. van der Graaf

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The zebrafish infected with Mycobacterium marinum (M. marinum) is an attractive tuberculosis disease model, showing similar pathogenesis to Mycobacterium tuberculosis (M. tuberculosis) infections in humans. To translate pharmacological findings from this disease model to higher vertebrates, a quantitative understanding of the natural growth of M. marinum in comparison to the natural growth of M. tuberculosis is essential. Here, the natural growth of two strains of M. marinum, E11 and MUSA, is studied over an extended period using an established model-based approach, the multistate tuberculosis pharmacometric (MTP) model, for comparison to that of M. tuberculosis. Poikilotherm-derived strain E11 and human-derived strain MUSA were grown undisturbed up to 221 days and viability of cultures (colony forming unit (CFU)/mL) was determined by plating at different time points. Nonlinear mixed effects modeling using the MTP model quantified the bacterial growth, the transfer among fast, slow, and non-multiplying states, and the inoculi. Both strains showed initial logistic growth, reaching a maximum after 20–25 days for E11 and MUSA, respectively, followed by a decrease to a new plateau. Natural growth of both E11 and MUSA was best described with Gompertz growth functions. For E11, the inoculum was best described in the slow-multiplying state, for MUSA in the fast-multiplying state. Natural growth of E11 was most similar to that of M. tuberculosis, whereas MUSA showed more aggressive growth behavior. Characterization of natural growth of M. marinum and quantitative comparison with M. tuberculosis brings the zebrafish tuberculosis disease model closer to the quantitative translational pipeline of antituberculosis drug development.

Original languageEnglish
JournalClinical and Translational Science
DOIs
Publication statusAccepted/In press - 1 Jan 2020

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