100 research outputs found
Efficient Reduction of Kappa Models by Static Inspection of the Rule-Set
No full textWhen designing genetic circuits, the typical primitives used in major existing modelling formalisms are gene interaction graphs, where edges between genes denote either an activation or inhibition relation. However, when designing experiments, it is important to be precise about the low-level mechanistic details as to how each such relation is implemented. The rule-based modelling language Kappa allows to unambiguously specify mechanistic details such as DNA binding sites, dimerisation of transcription factors, or co-operative interactions. Such a detailed description comes with complexity and computationally costly executions. We propose a general method for automatically transforming a rule-based program, by eliminating intermediate species and adjusting the rate constants accordingly. To the best of our knowledge, we show the first automated reduction of rule-based models based on equilibrium approximations. Our algorithm is an adaptation of an existing algorithm, which was designed for reducing reaction-based programs; our version of the algorithm scans the rule-based Kappa model in search for those interaction patterns known to be amenable to equilibrium approximations (e.g. Michaelis-Menten scheme). Additional checks are then performed in order to verify if the reduction is meaningful in the context of the full model. The reduced model is efficiently obtained by static inspection over the rule-set. The tool is tested on a detailed rule-based model of a λ- phage switch, which lists 92 rules and 13 agents. The reduced model has 11 rules and 5 agents, and provides a dramatic reduction in simulation time of several orders of magnitude
Model Checking Gene Regulatory Networks
No full textThe behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace this approach by a formal verification-like method that gives higher assurance and scalability. We focus on Wagner’s weighted GRN model with varying weights, which is used in evolutionary biology. In the model, weight parameters represent the gene interaction strength that may change due to genetic mutations. For a property of interest, we synthesise the constraints over the parameter space that represent the set of GRNs satisfying the property. We experimentally show that our parameter synthesis procedure computes the mutational robustness of GRNs –an important problem of interest in evolutionary biology– more efficiently than the classical simulation method. We specify the property in linear temporal logics. We employ symbolic bounded model checking and SMT solving to compute the space of GRNs that satisfy the property, which amounts to synthesizing a set of linear constraints on the weights
A bacterial toxin-antitoxin system as a native defence element against RNA phages
Full text linkBacteria have evolved a wide range of defence strategies to protect themselves against bacterial viruses (phages). Most known bacterial antiphage defence systems target phages with DNA genomes, which raises the question of how bacteria defend against phages with RNA genomes. Bacterial toxin–antitoxin systems that cleave intracellular RNA could potentially protect bacteria against RNA phages, but this has not been explored experimentally. In this study, we investigated the role of a model toxin–antitoxin system, MazEF, in protecting Escherichia coli against two RNA phage species. When challenged with these phages, the native presence of mazEF moderately reduced population susceptibility and increased the survival of individual E. coli cells. Genomic analysis further revealed an underrepresentation of the MazF cleavage site in genomes of RNA phages infecting E. coli, indicating selection against cleavage. These results show that, in addition to other physiological roles, RNA-degrading toxin–antitoxin systems may also help defend against RNA phages
Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose
No full textCopy-number and point mutations form the basis for most evolutionary novelty through the process of gene duplication and divergence. While a plethora of genomic sequence data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic system that allows us to distinguish copy-number and point mutations, we study their early and transient adaptive dynamics in real-time in Escherichia coli. We find two qualitatively different routes of adaptation depending on the level of functional improvement selected for: In conditions of high gene expression demand, the two types of mutations occur as a combination. Under low gene expression demand, negative epistasis between the two types of mutations renders them mutually exclusive. Thus, owing to their higher frequency, adaptation is dominated by copy-number mutations. Ultimately, due to high rates of reversal and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation but also constrain sequence divergence over evolutionary time scales.R script that accesses data and plots all of it; Figure plots are indicated in the script.1. Flow cytometry data of E.coli populations evolved in galactose for 12 days.
Data: EE24.4/8/12 (evolution experiment 24, day 4/8/12) plates 1-3 (delta IS1C - medium C,B,A) + plates 7-10 (IT030 - medium C, B, A; controll plate medium E)
Evolution in galactose (A-1%, B-0.1%, C-0.01%, E - 0%) + 0.1% CASAMINOACIDS.
FlowJo used to export data as scale values into new folder with naming scheme: "ScaleVal_EE24_12C30" (evolution experiment 24_day12 populations_0.01%galactose_strain IT030)
Autogating was used in flow jo to gate the a single concise population of cells (by eye, same within plate, and similar (~60%) for all different plates).
2. amplicon deep sequencing data of E. coli populations evolving in galactose.
Contains random P0 sequences of all evolving pooled populations and R script to generate the plots shown in the figures (Readme
Uncovering cis Regulatory Codes Using Synthetic Promoter Shuffling
No full textRevealing the spectrum of combinatorial regulation of transcription at individual promoters is essential for understanding the complex structure of biological networks. However, the computations represented by the integration of various molecular signals at complex promoters are difficult to decipher in the absence of simple cis regulatory codes. Here we synthetically shuffle the regulatory architecture--operator sequences binding activators and repressors--of a canonical bacterial promoter. The resulting library of complex promoters allows for rapid exploration of promoter encoded logic regulation. Among all possible logic functions, NOR and ANDN promoter encoded logics predominate. A simple transcriptional cis regulatory code determines both logics, establishing a straightforward map between promoter structure and logic phenotype. The regulatory code is determined solely by the type of transcriptional regulation combinations: two repressors generate a NOR: NOT (a OR b) whereas a repressor and an activator generate an ANDN: a AND NOT b. Three-input versions of both logics, having an additional repressor as an input, are also present in the library. The resulting complex promoters cover a wide dynamic range of transcriptional strengths. Synthetic promoter shuffling represents a fast and efficient method for exploring the spectrum of complex regulatory functions that can be encoded by complex promoters. From an engineering point of view, synthetic promoter shuffling enables the experimental testing of the functional properties of complex promoters that cannot necessarily be inferred ab initio from the known properties of the individual genetic components. Synthetic promoter shuffling may provide a useful experimental tool for studying naturally occurring promoter shuffling
Noise Underlies Switching Behavior of the Bacterial Flagellum
No full textAbstractWe report the switching behavior of the full bacterial flagellum system that includes the filament and the motor in wild-type Escherichia coli cells. In sorting the motor behavior by the clockwise bias, we find that the distributions of the clockwise (CW) and counterclockwise (CCW) intervals are either exponential or nonexponential with long tails. At low bias, CW intervals are exponentially distributed and CCW intervals exhibit long tails. At intermediate CW bias (0.5) both CW and CCW intervals are mainly exponentially distributed. A simple model suggests that these two distinct switching behaviors are governed by the presence of signaling noise within the chemotaxis network. Low noise yields exponentially distributed intervals, whereas large noise yields nonexponential behavior with long tails. These drastically different motor statistics may play a role in optimizing bacterial behavior for a wide range of environmental conditions
Electrochemical transport in CuCl/HCl(aq) electrolyzer cells and stack of the Cu–Cl cycle
No full textThis paper develops a comprehensive predictive model for the CuCl/HCl(aq) electrolyzer stack in the electrochemical unit of the Cu–Cl cycle of hydrogen production. A strong aqueous anolyte is fed into the stack and forms complex speciation. The unit single cell is modeled to predict the decomposition voltage by applying the Gibbs energy minimization method (GEM). The kinetic correlations are incorporated to take into account the overpotential losses during the hydrogen generation process under a non-equilibrium condition with the stack under potential. To evaluate the single-cell contribution to the average performance of stack, a hydrodynamic analysis reveals the anolyte and catholyte flow distribution using a finite element method for solutions of the equation of mass and momentum conservation equations of the flow field. Using the simulated stack, the voltage spread across the individual cells in the stack, cell and stack voltage efficiency, and the sensitivity of stack performance under the operating conditions, are investigated. It is shown that the speciation model has good agreement with data in past literature. With an increase in the stack operating temperature from 25 °C to 65 °C, the average stack efficiency improves from 68% to 72%. Cells close to the anolyte or catholyte input ports possess a higher voltage efficiency than other cells. This is mainly due to less electrolyte received by the cells placed in the middle of the stack for the X-shape bipolar modules, resulting in less decomposition potential
Adaptation dynamics between copy-number and point mutations
Full text linkTogether, copy-number and point mutations form the basis for most evolutionary novelty, through the process of gene duplication and divergence. While a plethora of genomic data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic reporter system that can distinguish between copy-number and point mutations, we study their early and transient adaptive dynamics in real time in Escherichia coli. We find two qualitatively different routes of adaptation, depending on the level of functional improvement needed. In conditions of high gene expression demand, the two mutation types occur as a combination. However, under low gene expression demand, copy-number and point mutations are mutually exclusive; here, owing to their higher frequency, adaptation is dominated by copy-number mutations, in a process we term amplification hindrance. Ultimately, due to high reversal rates and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation, but also constrain sequence divergence over evolutionary time scales
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