GUBS, a Behavior-based Language for Open System Dedicated to Synthetic Biology

In this article, we propose a domain specific language, GUBS (Genomic Unified Behavior Specification), dedicated to the behavioral specification of synthetic biological devices, viewed as discrete open dynamical systems. GUBS is a rule-based declarative language. By contrast to a closed system, a program is always a partial description of the behavior of the system. The semantics of the language accounts the existence of some hidden non-specified actions possibly altering the behavior of the programmed device. The compilation framework follows a scheme similar to automatic theorem proving, aiming at improving synthetic biological design safety.Comment: In Proceedings MeCBIC 2012, arXiv:1211.347

Conformational changes in a pore-forming region underlie voltage-dependent “loop gating” of an unapposed connexin hemichannel

The structure of the pore is critical to understanding the molecular mechanisms underlying selective permeation and voltage-dependent gating of channels formed by the connexin gene family. Here, we describe a portion of the pore structure of unapposed hemichannels formed by a Cx32 chimera, Cx32*Cx43E1, in which the first extracellular loop (E1) of Cx32 is replaced with the E1 of Cx43. Cysteine substitutions of two residues, V38 and G45, located in the vicinity of the border of the first transmembrane (TM) domain (TM1) and E1 are shown to react with the thiol modification reagent, MTSEA–biotin-X, when the channel resides in the open state. Cysteine substitutions of flanking residues A40 and A43 do not react with MTSEA–biotin-X when the channel resides in the open state, but they react with dibromobimane when the unapposed hemichannels are closed by the voltage-dependent “loop-gating” mechanism. Cysteine substitutions of residues V37 and A39 do not appear to be modified in either state. Furthermore, we demonstrate that A43C channels form a high affinity Cd2+ site that locks the channel in the loop-gated closed state. Biochemical assays demonstrate that A43C can also form disulfide bonds when oocytes are cultured under conditions that favor channel closure. A40C channels are also sensitive to micromolar Cd2+ concentrations when closed by loop gating, but with substantially lower affinity than A43C. We propose that the voltage-dependent loop-gating mechanism for Cx32*Cx43E1 unapposed hemichannels involves a conformational change in the TM1/E1 region that involves a rotation of TM1 and an inward tilt of either each of the six connexin subunits or TM1 domains

Modular Design of Artificial Tissue Homeostasis: Robust Control through Synthetic Cellular Heterogeneity

Synthetic biology efforts have largely focused on small engineered gene networks, yet understanding how to integrate multiple synthetic modules and interface them with endogenous pathways remains a challenge. Here we present the design, system integration, and analysis of several large scale synthetic gene circuits for artificial tissue homeostasis. Diabetes therapy represents a possible application for engineered homeostasis, where genetically programmed stem cells maintain a steady population of β-cells despite continuous turnover. We develop a new iterative process that incorporates modular design principles with hierarchical performance optimization targeted for environments with uncertainty and incomplete information. We employ theoretical analysis and computational simulations of multicellular reaction/diffusion models to design and understand system behavior, and find that certain features often associated with robustness (e.g., multicellular synchronization and noise attenuation) are actually detrimental for tissue homeostasis. We overcome these problems by engineering a new class of genetic modules for ‘synthetic cellular heterogeneity’ that function to generate beneficial population diversity. We design two such modules (an asynchronous genetic oscillator and a signaling throttle mechanism), demonstrate their capacity for enhancing robust control, and provide guidance for experimental implementation with various computational techniques. We found that designing modules for synthetic heterogeneity can be complex, and in general requires a framework for non-linear and multifactorial analysis. Consequently, we adapt a ‘phenotypic sensitivity analysis’ method to determine how functional module behaviors combine to achieve optimal system performance. We ultimately combine this analysis with Bayesian network inference to extract critical, causal relationships between a module's biochemical rate-constants, its high level functional behavior in isolation, and its impact on overall system performance once integrated.National Institutes of Health (U.S.) (NIH NIGMS grant R01GM086881)National Science Foundation (U.S.) (NSF Award #1001092)National Science Foundation (U.S.) (NSF Graduate Research Fellowship Program)Swiss National Science Foundation (SystemsX.ch grant

The fidelity of dynamic signaling by noisy biomolecular networks

This is the final version of the article. Available from Public Library of Science via the DOI in this record.Cells live in changing, dynamic environments. To understand cellular decision-making, we must therefore understand how fluctuating inputs are processed by noisy biomolecular networks. Here we present a general methodology for analyzing the fidelity with which different statistics of a fluctuating input are represented, or encoded, in the output of a signaling system over time. We identify two orthogonal sources of error that corrupt perfect representation of the signal: dynamical error, which occurs when the network responds on average to other features of the input trajectory as well as to the signal of interest, and mechanistic error, which occurs because biochemical reactions comprising the signaling mechanism are stochastic. Trade-offs between these two errors can determine the system's fidelity. By developing mathematical approaches to derive dynamics conditional on input trajectories we can show, for example, that increased biochemical noise (mechanistic error) can improve fidelity and that both negative and positive feedback degrade fidelity, for standard models of genetic autoregulation. For a group of cells, the fidelity of the collective output exceeds that of an individual cell and negative feedback then typically becomes beneficial. We can also predict the dynamic signal for which a given system has highest fidelity and, conversely, how to modify the network design to maximize fidelity for a given dynamic signal. Our approach is general, has applications to both systems and synthetic biology, and will help underpin studies of cellular behavior in natural, dynamic environments.We acknowledge support from a Medical Research Council and Engineering and Physical Sciences Council funded Fellowship in Biomedical Informatics (CGB) and a Scottish Universities Life Sciences Alliance chair in Systems Biology (PSS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

A synthetic circuit for selectively arresting daughter cells to create aging populations

The ability to engineer genetic programs governing cell fate will permit new safeguards for engineered organisms and will further the biological understanding of differentiation and aging. Here, we have designed, built and implemented a genetic device in the budding yeast Saccharomyces cerevisiae that controls cell-cycle progression selectively in daughter cells. The synthetic device was built in a modular fashion by combining timing elements that are coupled to the cell cycle, i.e. cell-cycle specific promoters and protein degradation domains, and an enzymatic domain which conditionally confers cell arrest. Thus, in the presence of a drug, the device is designed to arrest growth of only newly-divided daughter cells in the population. Indeed, while the engineered cells grow normally in the absence of drug, with the drug the engineered cells display reduced, linear growth on the population level. Fluorescence microscopy of single cells shows that the device induces cell arrest exclusively in daughter cells and radically shifts the age distribution of the resulting population towards older cells. This device, termed the ‘daughter arrester’, provides a blueprint for more advanced devices that mimic developmental processes by having control over cell growth and death

Processing DNA molecules as text

Polymerase Chain Reaction (PCR) is the DNA-equivalent of Gutenberg’s movable type printing, both allowing large-scale replication of a piece of text. De novo DNA synthesis is the DNA-equivalent of mechanical typesetting, both ease the setting of text for replication. What is the DNA-equivalent of the word processor? Biology labs engage daily in DNA processing—the creation of variations and combinations of existing DNA—using a plethora of manual labor-intensive methods such as site-directed mutagenesis, error-prone PCR, assembly PCR, overlap extension PCR, cleavage and ligation, homologous recombination, and others. So far no universal method for DNA processing has been proposed and, consequently, no engineering discipline that could eliminate this manual labor has emerged. Here we present a novel operation on DNA molecules, called Y, which joins two DNA fragments into one, and show that it provides a foundation for DNA processing as it can implement all basic text processing operations on DNA molecules including insert, delete, replace, cut and paste and copy and paste. In addition, complicated DNA processing tasks such as the creation of libraries of DNA variants, chimeras and extensions can be accomplished with DNA processing plans consisting of multiple Y operations, which can be executed automatically under computer control. The resulting DNA processing system, which incorporates our earlier work on recursive DNA composition and error correction, is the first demonstration of a unified approach to DNA synthesis, editing, and library construction