Browsing by Author "Apiyo, Davina-Nelson"

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    The effect of environmental conditions on growth and phenotype switching in Mycobacterium smegmatis
    (Stellenbosch : Stellenbosch University, 2020-03) Apiyo, Davina-Nelson; Louw, Tobias M.; Mouton, J. M.; Sampson, S. L.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
    ENGLISH ABSTRACT: Mycobacterium tuberculosis can exist within a host in a seemingly dormant state, in which it can tolerate antibiotic challenge. This non-heritable survival mechanism is thought to be the cause of latent tuberculosis (TB) infection. The viable but non-replicating population exhibits a phenotype known as antibiotic tolerance, with these cells being referred to as ‘persisters’. The intracellular environment of alveolar macrophages (a key habitat of M. tuberculosis bacilli) is detrimental to the survival of the bacteria, constituting antimicrobial effectors such as hypoxia, nutrient deficiency, nitrosative stress and acidic stress. Persistence arises when the bacilli can tolerate these host defence mechanisms. This study sought to investigate replication dynamics and phenotype switching of bacteria, but under in vitro environmental stresses — nutrient deficiency and acidic stress. Mycobacterium smegmatis (a non-pathogenic, fast growing Mycobacterium species) was used as a model for M. tuberculosis. To determine the response of M. smegmatis to the various growth stresses, two methods were utilized: mathematical modelling (for parameter estimation and prediction of cellular growth) and fluorescence dilution (FD — for examination of the persister population, using a dual-fluorescence replication reporter system). Results from the experimental studies indicated that the fluorescence reporter was suitable for measuring bacterial replication dynamics for up to four generations, when compared to other conventional techniques such as optical density. Under acidic conditions (pH 4.6 media), the acute decline in bacterial growth, based on the calculated mean fluorescence intensity, was apparent. Under circumstances of nutrient deficiency, results from the reporter were inconclusive, since its minimum intensity had been reached before the cells in the culture could be influenced by the stresses (from t = 16 h). As for mathematical modelling, optimization of the relevant growth parameters was done through a weighted non-linear least squares approach. Quantitative comparison of the optimized model to the validation data — by calculating the normalized root mean squared error (NRMSE) — revealed a relatively good fit for the pH. For each of the five validation experiments (with varying environmental conditions), the NRMSE of the pH was 13.40%, 12.67%, 13.96%, 5.28% and 3.38%. Based on these results, we conclude that the developed mathematical model was able to predict bacterial growth under diverse conditions, and that the reporter could accurately measure mycobacterial replication. Nonetheless, model predictability (more so for the biomass and ammonia variables) could be improved, by adding biochemical elements that influence the uptake and utilization of the substrates. It would also be beneficial to apply the model to slow-growing mycobacteria, to gauge its suitability in predicting M. tuberculosis growth. Finally, FD results under nutrient-deficient conditions could be made more conclusive by withdrawing the inducer of the far-red fluorescent protein at a later timepoint during the experiment. This makes the comparison of replication dynamics to the normal case more perceptible.