Antoni Matyjaszkiewicz

BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology

Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI) recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher.

Subconductance gating and voltage sensitivity of sarcoplasmic reticulum K(+) channels: a modeling approach.

Sarcoplasmic reticulum (SR) K+ channels are voltage-regulated channels that are thought to be actively gating when the membrane potential across the SR is close to zero as is expected physiologically. A characteristic of SR K+ channels is that they gate to subconductance open states but the relevance of the subconductance events and their contribution to the overall current flowing through the channels at physiological membrane potentials is not known. We have investigated the relationship between subconductance and full conductance openings and developed kinetic models to describe the voltage sensitivity of channel gating. Because there may be two subtypes of SR K+ channels (TRIC-A and TRIC-B) present in most tissues, to conduct our study on a homogeneous population of SR K+ channels, we incorporated SR vesicles derived from Tric-a knockout mice into artificial membranes to examine the remaining SR K+ channel (TRIC-B) function. The channels displayed very low open probability (Po) at negative potentials (≤0 mV) and opened predominantly to subconductance open states. Positive holding potentials primarily increased the frequency of subconductance state openings and thereby increased the number of subsequent transitions into the full open state, although a slowing of transitions back to the sublevels was also important. We investigated whether the subconductance gating could arise as an artifact of incomplete resolution of rapid transitions between full open and closed states; however, we were not able to produce a model that could fit the data as well as one that included multiple distinct current amplitudes. Our results suggest that the apparent subconductance openings will provide most of the K+ flux when the SR membrane potential is close to zero. The relative contribution played by openings to the full open state would increase if negative charge developed within the SR thus increasing the capacity of the channel to compensate for ionic imbalances.

An Orthogonal Multi-input Integration System to Control Gene Expression in Escherichia coli

In many biotechnological applications, it is useful for gene expression to be regulated by multiple signals, as this allows the programming of complex behavior. Here we implement, in Escherichia coli, a system that compares the concentration of two signal molecules, and tunes GFP expression proportionally to their relative abundance. The computation is performed via molecular titration between an orthogonal σ factor and its cognate anti-σ factor. We use mathematical modeling and experiments to show that the computation system is predictable and able to adapt GFP expression dynamically to a wide range of combinations of the two signals, and our model qualitatively captures most of these behaviors. We also demonstrate in silico the practical applicability of the system as a reference-comparator, which compares an intrinsic signal (reflecting the state of the system) with an extrinsic signal (reflecting the desired reference state) in a multicellular feedback control strategy.

BSim 2.0: An Advanced Agent-Based Cell Simulator

Agent-based models (ABMs) provide a number of advantages relative to traditional continuum modeling approaches, permitting incorporation of great detail and realism into simulations, allowing in silico tracking of single-cell behaviors and correlation of these with emergent effects at the macroscopic level. In this study we present BSim 2.0, a radically new version of BSim, a computational ABM framework for modeling dynamics of bacteria in typical experimental environments including microfluidic chemostats. This is facilitated through the implementation of new methods including cells with capsular geometry that are able to physically and chemically interact with one another, a realistic model of cellular growth, a delay differential equation solver, and realistic environmental geometries.

Tangible Networks: A toolkit for exploring network science

We present Tangible Networks (TN), a novel electronic toolkit for communicating and explaining concepts and models in complexity sciences to a variety of audiences. TN is an interactive hands-on platform for visualising the real-time behaviour of mathematical and computational models on complex networks. Compared to models running on a computer, the physical interface encourages playful exploration. We discuss the design of the toolkit, the implementation of different mathematical models and how TN has been received to date.