Engineered genetic information processing circuits
ABSTRACT Cells implement functions through the computation of biological information that is often mediated by genetic regulatory networks. To reprogram cells with novel capabilities, a vast set of synthetic gene circuits has recently been created. These include simple modules, such as feedback circuits, feed-forward loops, ultrasensitive networks, band-pass filters, logic gate operators and others, with each carrying a specific information processing functionality. More advanced cellular computation can also be achieved by assembling multiple simple processing modules into integrated computational cores. Further, when coupled with other modules such as sensors and actuators, integrated processing circuits enable sophisticated biological functionalities at both intra- and intercellular levels. Engineered genetic information processing circuits are transforming our ability to program cells, offering us extraordinary opportunities to explore biological mechanisms and to address real-world challenges. WIREs Syst Biol Med 2013. doi: 10.1002/wsbm.1216 For further resources related to this article, please visit the WIREs website. Conflict of interest: The authors declare no conflict of interest. These authors contributed equally to the work.
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ABSTRACT: Cell cycles, essential for biological function, have been investigated extensively. However, enabling a global understanding and defining a physical quantification of the stability and function of the cell cycle remains challenging. Based upon a mammalian cell cycle gene network, we uncovered the underlying Mexican hat landscape of the cell cycle. We found the emergence of three local basins of attraction and two major potential barriers along the cell cycle trajectory. The three local basins of attraction characterize the G1, S/G2, and M phases. The barriers characterize the G1 and S/G2 checkpoints, respectively, of the cell cycle, thus providing an explanation of the checkpoint mechanism for the cell cycle from the physical perspective. We found that the progression of a cell cycle is determined by two driving forces: curl flux for acceleration and potential barriers for deceleration along the cycle path. Therefore, the cell cycle can be promoted (suppressed), either by enhancing (suppressing) the flux (representing the energy input) or by lowering (increasing) the barrier along the cell cycle path. We found that both the entropy production rate and energy per cell cycle increase as the growth factor increases. This reflects that cell growth and division are driven by energy or nutrition supply. More energy input increases flux and decreases barrier along the cell cycle path, leading to faster oscillations. We also identified certain key genes and regulations for stability and progression of the cell cycle. Some of these findings were evidenced from experiments whereas others lead to predictions and potential anticancer strategies.Proceedings of the National Academy of Sciences 09/2014; 111(39). DOI:10.1073/pnas.1408628111 · 9.81 Impact Factor
12/2014; 1(1):1-11. DOI:10.1186/s40643-014-0024-6
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ABSTRACT: Cancer is a disease regulated by the underlying gene networks. The emergence of normal and cancer states as well as the transformation between them can be thought of as a result of the gene network interactions and associated changes. We developed a global potential landscape and path framework to quantify cancer and associated processes. We constructed a cancer gene regulatory net-work based on the experimental evidences and uncovered the underlying landscape. The resulting tristable landscape characterizes important biological states: normal, cancer and apoptosis. The landscape topography in terms of barrier heights between stable state attractors quantifies the global stability of the cancer network system. We propose two mechanisms of cancerization: one is by the changes of landscape topography through the changes in regulation strengths of the gene networks. The other is by the fluctuations that help the system to go over the critical barrier at fixed landscape topography. The kinetic paths from least action principle quantify the transition processes among normal state, cancer state and apoptosis state. The kinetic rates provide the quantification of transition speeds among normal, cancer and apoptosis attractors. By the global sensitivity analysis of the gene network parameters on the landscape topography, we uncovered some key gene regulations deter-mining the transitions between cancer and normal states. This can be used to guide the design of new anti-cancer tactics, through cocktail strategy of targeting multiple key regulation links simultaneously, for preventing cancer occurrence or transforming the early cancer state back to normal state.Journal of The Royal Society Interface 09/2014; 11(100):20140774.. DOI:10.1098/rsif.2014.0774 · 3.86 Impact Factor