Dynamic mathematical model development and validation of in vitro Mycobacterium smegmatis growth under nutrient- and pH-stress.

Mycobacterium tuberculosis can exist within a host for lengthy periods, tolerating even antibiotic challenge. This non-heritable, antibiotic tolerant "persister" state, is thought to underlie latent Tuberculosis (TB) infection and a deeper understanding thereof could inform treatment strategies. In addition to experimental studies, mathematical and computational modelling approaches are widely employed to study persistence from both an in vivo and in vitro perspective. However, specialized models (partial differential equations, agent-based, multiscale, etc.) rely on several difficult to determine parameters. In this study, a dynamic mathematical model was developed to predict the response of Mycobacterium smegmatis (a model organism for M. tuberculosis) grown in batch culture and subjected to a range of in vitro environmental stresses. Lag phase dynamics, pH variations and internal nitrogen storage were mechanistically modelled. Experimental results were used to train model parameters using global optimization, with extensive subsequent model validation to ensure extensibility to more complex modelling frameworks. This included an identifiability analysis which indicated that seven of the thirteen model parameters were uniquely identifiable. Non-identifiable parameters were critically evaluated. Model predictions compared to validation data (based on experimental results not used during training) were accurate with less than 16% maximum absolute percentage error, indicating that the model is accurate even when extrapolating to new experimental conditions. The bulk growth model can be extended to spatially heterogeneous simulations such as an agent-based model to simulate in vitro granuloma models or, eventually, in vivo conditions, where distributed environmental conditions are difficult to measure.

MYBPH acts as modifier of cardiac hypertrophy in hypertrophic cardiomyopathy (HCM) patients.

Left ventricular hypertrophy is a risk factor for cardiovascular morbidity and mortality. Hypertrophic cardiomyopathy (HCM) is considered a model disease to study causal molecular factors underlying isolated cardiac hypertrophy. However, HCM manifests with various clinical symptoms, even in families bearing the same genetic defects, suggesting that additional factors contribute to hypertrophy. The gene encoding the cardiac myosin binding protein C (cMYBPC) is one of the most frequently implicated genes in HCM. Recently another myosin binding protein, myosin binding protein H (MYBPH) was shown to function in concert with cMYBPC in regulating cardiomyocyte contraction. Given the similarity in sequence, structure and the critical role MYBPH plays in sarcomere contraction, we proposed that MYBPH may be involved in HCM pathogenesis. Family-based genetic association analysis was employed to investigate the contribution of MYBPH in modifying hypertrophy. Seven single nucleotide polymorphisms and haplotypes in MYBPH were investigated for hypertrophy modifying effects in 388 individuals (27 families), in which three unique South African HCM-causing founder mutations (p.R403W and pA797T in ß-myosin heavy chain gene (MYH7) and p.R92W in the cardiac troponin T gene (TNNT2)) segregate. We observed a significant association between rs2250509 and hypertrophy traits in the p.A797T MYH7 mutation group. Additionally, haplotype GGTACTT significantly affected hypertrophy within the same mutation group. MYBPH was for the first time assessed as a candidate hypertrophy modifying gene. We identified a novel association between MYBPH and hypertrophy traits in HCM patients carrying the p.A797T MYH7 mutation, suggesting that variation in MYBPH can modulate the severity of hypertrophy in HCM.