Biomechanics: A Frontier Microbial Biotechnology

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While cellular system mechanics is an emerging area in need of additional study. Preliminary research suggests that cells grow, respond to and provide mechanical stimuli. This discovery of the impact of mechanics on cellular function has led to a better understanding of human cellular physiology, including phagocytosis, the autoimmune system, and even cancer cell proliferation. Each of these systems relies on mechanical stimuli from contact with other cells or within the cell itself. The capabilities of computational modeling have increased exponentially in the past decade thanks to improved computational resources. The combination of molecular dynamics, quantum mechanics, and computational Nano mechanics has greatly increased researchers’ ability to analyze nanoscale systems in a way that uses less resources and time. Perhaps the most challenging aspect of modeling cellular function is the need to operate on multiple temporal and spatial scales [1]. Many of modeling schemes that account for multi-scale space are built on multi-scale homogenization theory. In addition to the aforementioned techniques, immersed molecular electrokinetic finite element uses multi-scale frameworks. Such abilities are able to accurately model RNA binding at a Nano level [2]. This combination is especially powerful as it draws on the expertise of material mechanics to solve problems of material properties within the cell and the cellular membrane. Extensions of this form of finite element analysis have included tight binding, to address crack propagation on a cellular level within bone and could address failure criteria in tissue [3,4]. Other cellular modeling examples include the study of red blood cell aggregation [4] as well as single and multi-phase tumors. Such complicated processes associated with tumor cells used thermodynamically consistent mixture models based on Cahn-Hilliard theory [5,6]. Advanced computational models can be developed by observing in vitro behaviors of cells. The beauty of using cell culture is that the researcher can control the environment, changing factors such as temperature, initial amount of cells, pH, growth medium, etc. These factors and behaviors can then be developed into a computational model such as the explanatory models described by Smallwood et al. [7]. Unfortunately many of these computational methods have not been fully applied to microbial behavior mechanisms, and validation of these models is often based upon the agent-based model of cellular interaction [7]; wherein each cell, or agent, is independently governed by a set of rules that account for each behavior in response to real situations [7].