TRIC-B channels display labile gating: evidence from the TRIC-A knockout mouse model.

The online version of this article (doi:10.1007/s00424-013-1251-y) contains supplementary material, which is available to authorized usersPublished online: 7 March 2013. ©The Author(s) 2013. This article is published with open access at Springerlink.com via: doi:10.1007/s00424-013-1251-y)Available under Open AccessSarcoplasmic/endoplasmic reticulum (SR) and nuclear membranes contain two related cation channels named TRIC-A and TRIC-B. In many tissues, both subtypes are co-expressed, making it impossible to distinguish the distinct single-channel properties of each subtype. We therefore incorporated skeletal muscle SR vesicles derived from Tric-a-knockout mice into bilayers in order to characterise the biophysical properties of native TRIC-B without possible misclassification of the channels as TRIC-A, and without potential distortion of functional properties by detergent purification protocols. The native TRIC-B channels were ideally selective for cations. In symmetrical 210 mM K(+), the maximum (full) open channel level (199 pS) was equivalent to that observed when wild-type SR vesicles were incorporated into bilayers. Analysis of TRIC-B gating revealed complex and variable behaviour. Four main sub-conductance levels were observed at approximately 80 % (161 pS), 60 % (123 pS), 46 % (93 pS), and 30 % (60 pS) of the full open state. Seventy-five percent of the channels were voltage sensitive with Po being markedly reduced at negative holding potentials. The frequent, rapid transitions between TRIC-B sub-conductance states prevented development of reliable gating models using conventional single-channel analysis. Instead, we used mean-variance plots to highlight key features of TRIC-B gating in a more accurate and visually useful manner. Our study provides the first biophysical characterisation of native TRIC-B channels and indicates that this channel would be suited to provide counter current in response to Ca(2+) release from the SR. Further experiments are required to distinguish the distinct functional properties of TRIC-A and TRIC-B and understand their individual but complementary physiological roles.British Heart FoundationEngineering and Physical Sciences Research Council (EPSRC)Japan Society for the Promotion of Scienc

BSim: an agent-based tool for modeling bacterial populations in systems and synthetic biology.

Open Access ArticleLarge-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.Engineering and Physical Sciences Research Council (EPSRC)Biotechnology and Biological Sciences Research Council (BBSRC

An Orthogonal Multi-input Integration System to Control Gene Expression in <i>Escherichia coli</i>

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 <i>Escherichia coli</i>, a system that compares the concentration of two signal molecules, and tunes GFP expression proportionally to their relative abundance. The computation is performed <i>via</i> 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 <i>in silico</i> 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

Subconductance Gating and Voltage Sensitivity of Sarcoplasmic Reticulum K⁺ Channels:A Modeling Approach

Open Access articleSarcoplasmic 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.British Heart FoundationJapan Society for the Promotion of Science (Core to Core Program)Engineering and Physical Sciences Research Council (EPSRC

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

Voltage-Dependent Stochastic Gating Models of TRIC-B Channels

TRIC-A and TRIC-B are two, related, trimeric intracellular cation channels present in sarcoplasmic/endoplasmic reticulum (SR) and are thought to provide counter-current for SR Ca2+-release. TRIC-B knockout mice die immediately after birth demonstrating the importance of this isoform [Yazawa et al., 2007, Nature, 448, 78-82]. To study the distinct single-channel gating behaviour of TRIC-B, we incorporated skeletal muscle light SR from TRIC-A knockout mice into artificial membranes under voltage-clamp conditions in symmetrical 210 mM K-PIPES, pH 7.2. We developed Markov models of TRIC-B gating, with up to 4 distinct sub-conductance states (S1-S4), using both QuB [Qin F., 2004, Biophys J.,86(3), 1488-501] and our own software. Our models incorporate different connectivity schemes to account for the intrinsic variability in gating that was observed between different channels. Despite the variability, some obvious trends emerged. TRIC-B activity was higher at positive than at negative holding potentials. At positive potentials, the majority of channels exhibited long bursts of openings where predominant gating transitions were between the full open state and S1, the largest sub-conductance state. Some channels, however, gated preferentially in sub-states S3 and S4, only visiting the full open state briefly. At negative potentials, channel activity consisted primarily of brief transitions between sub-conductance states. Closed lifetime distributions at positive potentials comprised of fast components (τ ≈ 1 ms), corresponding to brief transitions from the full open state, as well as slower components corresponding to inter-burst intervals. At negative potentials, inter-burst intervals were orders of magnitude longer demonstrating that the frequency of channel opening is heavily dependent on voltage. It will be important to develop comprehensive models of TRIC-B channel gating in order to fully understand the role of this important ion-channel in intracellular Ca2+-release

In-Silico Analysis and Implementation of a Multicellular Feedback Control Strategy in a Synthetic Bacterial Consortium

Living organisms employ endogenous negative feedback loops to maintain homeostasis despite environmental fluctuations. A pressing open challenge in Synthetic Biology is to design and implement synthetic circuits to control host cells' behavior, in order to regulate and maintain desired conditions. To cope with the high degree of circuit complexity required to accomplish this task and the intrinsic modularity of classical control schemes, we suggest the implementation of synthetic endogenous feedback loops across more than one cell population. The distribution of the sensing, computation, and actuation functions required to achieve regulation across different cell populations within a consortium allows the genetic engineering in a particular cell to be reduced, increases the robustness, and makes it possible to reuse the synthesized modules for different control applications. Here, we analyze, in-silico, the design of a synthetic feedback controller implemented across two cell populations in a consortium. We study the effects of distributing the various functions required to build a control system across two populations, prove the robustness and modularity of the strategy described, and provide a computational proof-of-concept of its feasibility