  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. Researchers in the field of synthetic biology -
the application of engineering principles to living systems - have, for
example, recently shown how useful decision-making circuits may be distributed
across a bacterial population. The ability of cells to interact through small
signalling molecules (a mechanism known as it 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. We present an agent-based model for conjugation dynamics, with
realistic handling of physical forces. Our framework combines the management of
intercellular interactions together with simulation of intracellular genetic
networks, to provide a general-purpose platform. We validate our simulations
against existing experimental data, and then demonstrate how the emergent
mixing patterns of multi-strain populations can affect conjugation dynamics.
Our model of conjugation, based on a probability distribution, may be easily
tuned to correspond to the behaviour of different cell types. Simulation code
and movies are available at http://code.google.com/p/discus/.
