DiSCUS: A Simulation Platform for Conjugation Computing

In bacterial populations, cells are able to cooperate in order to yield complex collective functionalities. Interest in population-level cellular behaviour is increasing, due to both our expanding knowledge of the underlying biological principles, and the growing range of possible applications for engineered microbial consortia. The ability of cells to interact through small signalling molecules (a mechanism known as quorum sensing) is the basis for the majority of existing engineered systems. However, horizontal gene transfer (or conjugation) offers the possibility of cells exchanging messages (using DNA) that are much more information-rich. The potential of engineering this conjugation mechanism to suit specific goals will guide future developments in this area. Motivated by a lack of computational models for examining the specific dynamics of conjugation, we present a simulation framework for its further study.

[1]  Mat E. Barnet,et al.  A synthetic Escherichia coli predator–prey ecosystem , 2008, Molecular systems biology.

[2]  Chris Hanson,et al.  Amorphous computing , 2000, Commun. ACM.

[3]  Javier Macía,et al.  Distributed computation: the new wave of synthetic biology devices. , 2012, Trends in biotechnology.

[4]  E. Andrianantoandro,et al.  Synthetic biology: new engineering rules for an emerging discipline , 2006, Molecular systems biology.

[5]  Fernando de la Cruz,et al.  Determination of conjugation rates on solid surfaces. , 2012, Plasmid.

[6]  Fernando de la Cruz,et al.  Conjugative DNA metabolism in Gram-negative bacteria. , 2010, FEMS microbiology reviews.

[7]  Drew Endy,et al.  Engineered cell-cell communication via DNA messaging , 2012, Journal of biological engineering.

[8]  S. Atkinson,et al.  Quorum sensing and social networking in the microbial world , 2009, Journal of The Royal Society Interface.

[9]  Martyn Amos,et al.  Population-based microbial computing: a third wave of synthetic biology? , 2014, Int. J. Gen. Syst..

[10]  Juan F. Poyatos,et al.  Dynamical Principles of Two-Component Genetic Oscillators , 2006, PLoS Comput. Biol..

[11]  Martyn Amos,et al.  A reconfigurable NAND/NOR genetic logic gate , 2012, BMC Systems Biology.

[12]  Thomas E. Gorochowski,et al.  BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology , 2012, PloS one.

[13]  Jacob Beal,et al.  Cells Are Plausible Targets for High-Level Spatial Languages , 2008, 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops.

[14]  Jacob Beal Bridging Biology and Engineering Together with Spatial Computing , 2011, Int. Conf. on Membrane Computing.

[15]  Javier Macía,et al.  Distributed biological computation with multicellular engineered networks , 2011, Nature.

[16]  Andrew Phillips,et al.  Computational modeling of synthetic microbial biofilms. , 2012, ACS synthetic biology.

[17]  Michael J. North,et al.  AgentCell: a digital single-cell assay for bacterial chemotaxis , 2005, Bioinform..

[18]  T. Lu,et al.  Synthetic biology: an emerging engineering discipline. , 2012, Annual review of biomedical engineering.

[19]  Markus Wieland,et al.  Programmable single-cell mammalian biocomputers , 2012, Nature.

[20]  Stephen M. Krone,et al.  Modelling the spatial dynamics of plasmid transfer and persistence. , 2007, Microbiology.

[21]  D. Volfson,et al.  Biomechanical ordering of dense cell populations , 2008, Proceedings of the National Academy of Sciences.

[22]  J. Collins,et al.  Construction of a genetic toggle switch in Escherichia coli , 2000, Nature.

[23]  Martyn Amos,et al.  Multicellular Computing Using Conjugation for Wiring , 2013, PloS one.

[24]  Andre Levchenko,et al.  A Cell-Based Model for Quorum Sensing in Heterogeneous Bacterial Colonies , 2010, PLoS Comput. Biol..

[25]  G. Booth,et al.  BacSim, a simulator for individual-based modelling of bacterial colony growth. , 1998, Microbiology.

[26]  Arnaud Dechesne,et al.  An individual-based approach to explain plasmid invasion in bacterial populations. , 2011, FEMS microbiology ecology.

[27]  Fernando de la Cruz,et al.  Why is entry exclusion an essential feature of conjugative plasmids? , 2008, Plasmid.

[28]  Sara Kalvala,et al.  Spatial Simulations of Myxobacterial Development , 2010, PLoS Comput. Biol..

[29]  Christopher A. Voigt,et al.  Robust multicellular computing using genetically encoded NOR gates and chemical ‘wires’ , 2011, Nature.

[30]  Matthias Heinemann,et al.  Synthetic biology - putting engineering into biology , 2006, Bioinform..

[31]  Staffan Schedin,et al.  Physical properties of Escherichia coli P pili measured by optical tweezers. , 2004, Biophysical journal.

[32]  William I. Bacchus,et al.  Engineering of synthetic intercellular communication systems. , 2013, Metabolic engineering.

[33]  Christopher A. Voigt,et al.  A Synthetic Genetic Edge Detection Program , 2009, Cell.

[34]  Jesús A. Izaguirre,et al.  COMPUCELL, a multi-model framework for simulation of morphogenesis , 2004, Bioinform..

[35]  Cristian Picioreanu,et al.  iDynoMiCS: next-generation individual-based modelling of biofilms. , 2011, Environmental microbiology.

[36]  F. Arnold,et al.  Engineering microbial consortia: a new frontier in synthetic biology. , 2008, Trends in biotechnology.

[37]  S. Basu,et al.  A synthetic multicellular system for programmed pattern formation , 2005, Nature.