An LBS-<i>κ</i> version of the chemotactic switch ring.

<p>An LBS-<i>κ</i> version of the chemotactic switch ring.</p

The abstract syntax for Kappa rules.

<p>The abstract syntax for Kappa rules.</p

A screenshot of the web application for LBS-<i>κ</i>.

<p>The left hand side provides a syntax-highlighting editor, and the right hand side shows time course simulation plots.</p

Some of the symbols used in LBS-<i>κ</i> syntax and semantics.

<p>Some of the symbols used in LBS-<i>κ</i> syntax and semantics.</p

The MAPK cascade.

<p>An illustration of the MAPK cascade, amplifying a signal through three layers of protein modification. The lines with circular heads indicate catalysis, and the Ps indicate phosphorylation.</p

An LBS-<i>κ</i> version of the MAPK cascade from [21].

<p>An LBS-<i>κ</i> version of the MAPK cascade from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114296#pone.0114296.ref021" target="_blank">21</a>].</p

The abstract syntax for definitions.

<p>The abstract syntax for definitions.</p

The chemotactic switch ring.

<p>An illustration of the chemotactic switch ring (a) and the activation reactions taking place within the ring (b). The black dots indicate the active state, and the black lines indicate the bound state. The reaction rate depends on both the active state and the binding state of the neighbouring protomers.</p

The abstract syntax for LBS-<i>κ</i> site types and expressions.

<p>The abstract syntax for LBS-<i>κ</i> site types and expressions.</p

Computational Modeling of Synthetic Microbial Biofilms

Microbial biofilms are complex, self-organized communities of bacteria, which employ physiological cooperation and spatial organization to increase both their metabolic efficiency and their resistance to changes in their local environment. These properties make biofilms an attractive target for engineering, particularly for the production of chemicals such as pharmaceutical ingredients or biofuels, with the potential to significantly improve yields and lower maintenance costs. Biofilms are also a major cause of persistent infection, and a better understanding of their organization could lead to new strategies for their disruption. Despite this potential, the design of synthetic biofilms remains a major challenge, due to the complex interplay between transcriptional regulation, intercellular signaling, and cell biophysics. Computational modeling could help to address this challenge by predicting the behavior of synthetic biofilms prior to their construction; however, multiscale modeling has so far not been achieved for realistic cell numbers. This paper presents a computational method for modeling synthetic microbial biofilms, which combines three-dimensional biophysical models of individual cells with models of genetic regulation and intercellular signaling. The method is implemented as a software tool (<i>CellModeller</i>), which uses parallel Graphics Processing Unit architectures to scale to more than 30,000 cells, typical of a 100 μm diameter colony, in 30 min of computation time