Segregation of bacteria based on their metabolic activities in biofilms plays an important role in the development of antibiotic resistance. Mushroom-shaped biofilm structures, which are reported for many bacteria, exhibit topographically varying levels of multiple drug resistance from the cap of the mushroom to its stalk. Understanding the dynamics behind the formation of such structures can aid in design of drug delivery systems, antibiotics, or physical systems for removal of biofilms. We explored the development of metabolically heterogeneous Pseudomonas aeruginosa biofilms using numerical models and laboratory knockout experiments on wild-type and chemotaxis-deficient mutants. We show that chemotactic processes dominate the transformation of slender and hemispherical structures into mushroom structures with a signature cap. Cellular Potts model simulation and experimental data provide evidence that accelerated movement of bacteria along the periphery of the biofilm, due to nutrient cues, results in the formation of mushroom structures and bacterial segregation. Multidrug resistance of bacteria is one of the most threatening dangers to public health. Understanding the mechanisms of the development of mushroom-shaped biofilms helps to identify the multidrug-resistant regions. We decoded the dynamics of the structural evolution of bacterial biofilms and the physics behind the formation of biofilm structures as well as the biological triggers that produce them. Combining in vitro gene knockout experiments with in silico models showed that chemotactic motility is one of the main driving forces for the formation of stalks and caps. Our results provide physicists and biologists with a new perspective on biofilm removal and eradication strategies.
Background
The mechanisms of action and efficacy of cisplatin and paclitaxel at cell population level are well studied and documented, however the localized spatio-temporal effects of the drugs are less well understood. We explore the emergence of spatially preferential drug efficacy resulting from variations in mechanisms of cell-drug interactions.
Methods
3D spheroids of HeLa-C3 cells were treated with drugs, cisplatin and paclitaxel. This was followed by sectioning and staining of the spheroids to track the spatio-temporal apoptotic effects of the drugs. A mechanistic drug-cell interaction model was developed and simulated to analyse the localized efficacy of these drugs.
Results
The outcomes of drug actions on a local cell population was dependant on the interactions between cell repair probability, intracellular drug concentration and cell’s mitosis phase. In spheroids treated with cisplatin, drug induced apoptosis is found to be scattered throughout the volume of the spheroids. In contrast, effect of paclitaxel is found to be preferentially localized along the periphery of the spheroids. Combinatorial treatments of cisplatin and paclitaxel result in varying levels of cell apoptosis based on the scheduling strategy.
Conclusions
The preferential action of paclitaxel can be attributed to the cell characteristics of the peripheral population. The model simulations and experimental data show that treatments initiated with paclitaxel are more efficacious due to the cascading of spatial effects of the drugs.
Modelling and simulation of bacterial biofilms is a computationally expensive process necessitating use of parallel computing. Fluid dynamics and advection-consumption models can be decoupled and solved to handle the fluidsolute-bacterial interactions. Data exchange between the two processes add up to the communication overheads. The heterogenous distribution of bacteria within the simulation domain further leads to non-uniform load distribution in the parallel system. We study the effect of load imbalance and communication overheads on the overall performance of simulation at different stages of biofilm growth. We develop a model to optimize the parallelization procedure for computing the growth dynamics of bacterial biofilms.
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