Literature Update: Synthetic biology applied to the engineering of tissue homeostasis

Fig1_System1_ODEanalysis_newIn synthetic biology, the challenges to engineering individual cells to do useful things are already significant given the monstrous complexity of even the simplest of cells. Now imagine trying to do enginering at the individual cell level, in order to modulate the bulk properties of a population of such cells working cooperatively as tissue in vivo. That is exactly the problem that a bioengineering research group at MIT set out to tackle, as described in their PLOS One paper that appeared this month.

The applications of this problem are clinically and economically significant – a fact amply illustrated by this team’s decision to focus upon the challenges around creating synthetic tissue for transplant into patients with diabetes. The central problem described in this paper, is the creation of engineered stem cells capable of maintaining a stable population of insulin-producing β-cells in a diabtetes patient. Tissue homestasis in this case, is defined by the authors as “the property of balancing growth, death, and differentiation of multiple cell-types within a multicellular community“.

The authors found that the design of such a system defies any simple, intuitive thinking, requiring a multifactorial approach that takes into acount a number of parameters governing the equilibrium between the population of self-renewing stem cells and the steady state population of adult, insulin-producing β-cells. Far from optimizing a system of synchromized, homogeneous cells, the best solutions proposed by the mathematical model were characterized by the optimization of the heterogeneity of the cell population against the required steady state behavior – a key component of this approach being a phenotypic sensitivity analysis to determine how the behaviors of the various synthetic functional module contribute to the performance of the system as a whole.

The full text of the paper is available online at the NCBI.

  © The Digital Biologist | All Rights Reserved