Understanding the underlying mechanisms of pattern formation: biological tissue development to biofilm generation

Mukhopadhyay, Debangana (2022) Understanding the underlying mechanisms of pattern formation: biological tissue development to biofilm generation. PhD thesis, Indian Institute of Science Education and Research Kolkata.

Text (PhD thesis of Debangana Mukhopadhyay (15RS013)) 15RS013.pdf - Submitted Version Restricted to Repository staff only Download (32MB)

Abstract

Formation and development of tissues through self-assembly and organization of living cells are intriguing and complex phenomena. It is still not well understood how ordered tissue structures spontaneously develop from adaptive response of interacting multicellular components. Understanding the process of tissue organization, thus, would immensely benefit diverse areas of developmental biology, wound healing, cancer therapy, tissue engineering, and even organ printing to name a few. Several studies have been carried out to unravel the self-assembly and organization process in both living as well as non-living systems, such as flocking of birds, patterns of bacterial colony, aggregation of proteins, assembly of active filaments, growth of intricate snowflakes among many others. In such collective systems, the interactions among the constituent entities have been found to play a crucial role in determining the emergence of self-organized patterns. Thus, multiple pathways can promote the aggregation process; however, the difficulty lies in distinguishing the underlying mechanisms of cell-cell interactions that govern the cellular organization and lead to specialized tissue formation. Despite a multitude of attempts, our understanding is far from complete, and it remains a long-standing question in developmental biology. In this thesis, based on suitably constructed theoretical models, we probe how different pathways of cell-cell interactions affect the dynamics of aggregation from a seemingly random single cell population on a substrate. Here, we present our work on the cellular aggregation and reorganization process as cell-cell and cell-extracellular matrix interactions are systematically varied within the theoretical framework. Cellular aggregation grows gathering dispersed cells depending on both transport and attachment. We have studied different cluster interaction mechanisms and their influence on several properties of aggregates and emerging morphological structures and tissue patterns. Understanding the physical principles of biological self-assembly is crucial for developing various structural tissue patterns. In this thesis, first we have addressed the emergence of ordered tissue patterns from a randomly migrating single cell population without any external influence, within the framework of a cellular automata model. This model is based on the active motility of cells via diffusion on non-adhesive substrate and their ability to reorganize their structure due to cell-cell cohesivity. We have shown the temporal evolution of aggregates that leads to the compact tissue structures and characterized the time evolution of the surface area of clusters by the existence two distinct time scales. Besides, we studied the ruggedness of the growing aggregate structures and evaluated the fractal dimension to get insights into the complexity of tumorous tissue growth which were hitherto unexplored. Moreover, we have investigated the complex cellular aggregation process orchestrated by different pathways of cellular interactions. To distinguish the underlying mechanisms of cellular aggregation, we investigate the following three leading pathways of cell-cell interactions, namely, direct cell adhesion contacts, matrix mediated mechanical interaction, and chemical signaling. We simulate the aggregation dynamics using the Metropolis Monte Carlo (MMC) and Kinetic Monte Carlo method (KMC), taking into account the different cell-cell interaction mechanisms. Distinct signature of the specific cell-cell interactions to identify each pathway can be observed in our studies. Interestingly, we find that the average domain size and the mass of the clusters exhibit a power law growth in time under certain interaction mechanism which is intrinsic to the specific pathway. Further, as observed in experiments, the cluster size distribution can be characterized by stretched exponential functions demonstrating distinct cellular organization processes. KMC simulates the system in real time compared to MMC simulation steps. Generally, KMC time depends linearly on the number of MMC steps signifying that the growth kinetics characterization remains the same with both MMC and KMC methods, and they only differ by time scale. Further, as diffusion is a main means of cellular transport, we also study the cellular aggregation process incorporating diffusion along with the cellular interaction pathways. However, the growth kinetics also exhibit power law behaviour incorporating diffusion but the growth rate becomes faster with higher power law exponent values. The power law exponents depend upon the system, interaction mechanisms, transport trails, and the type of patterns. We have also shown that in the pure diffusion driven cluster aggregation process, fractal dimensional characterizes the aggregated structures. Apart from the cellular aggregation, we have presented mathematical model based on reactiondiffusion equations to describe the spatio-temporal dynamics of bacterial colony populations. Growing colonies form different patterns as a response to diverse environmental conditions, nutrients, and the presence of same or different species colonies. We examine the colony growth and the emerging patterns in the presence of sibling bacterial colonies. Our study shows the formation to demarcation zone and merging of two colonies, depending on the nutrient concentration and without the presence of any chemical inhibitors. The appearance of demarcation zone between two colonies is direct consequence of the depleting nutrient in the region. In our study, two distinct types of behaviour, i.e., merging and the demarcation between the two colony growth, depends strongly on initial nutrient concentration, initial separation between two colonies and the diffusion of the bacterial species. Interestingly, our study indicates that nutrient deficiency between the two colonies is sufficient for the demarcation formation without the need of any inhibitory agents. A phase diagram clearly showing merging and demarcation regimes, i.e., the separation distance between two colonies as a function of nutrient concentration and initial placing distance of two colonies, explains the emergence of these distinct phenomena. As tissue development is a complex process, our study based on a simple, generic model of active cellular aggregation is envisaged to pave the way for further extended studies to understand the governing pathways of cellular organizations.

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