436 research outputs found

    Kinetic approaches to lactose operon induction and bimodality

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    The quasi-equilibrium approximation is acceptable when molecular interactions are fast enough compared to circuit dynamics, but is no longer allowed when cellular activities are governed by rare events. A typical example is the lactose operon (lac), one of the most famous paradigms of transcription regulation, for which several theories still coexist to describe its behaviors. The lac system is generally analyzed by using equilibrium constants, contradicting single-event hypotheses long suggested by Novick and Weiner (1957). Enzyme induction as an all-or-none phenomenon. Proc. Natl. Acad. Sci. USA 43, 553-566) and recently refined in the study of (Choi et al., 2008. A stochastic single-molecule event triggers phenotype switching of a bacterial cell. Science 322, 442-446). In the present report, a lac repressor (LacI)-mediated DNA immunoprecipitation experiment reveals that the natural LacI-lac DNA complex built in vivo is extremely tight and long-lived compared to the time scale of lac expression dynamics, which could functionally disconnect the abortive expression bursts and forbid using the standard modes of lac bistability. As alternatives, purely kinetic mechanisms are examined for their capacity to restrict induction through: (i) widely scattered derepression related to the arrival time variance of a predominantly backward asymmetric random walk and (ii) an induction threshold arising in a single window of derepression without recourse to nonlinear multimeric binding and Hill functions. Considering the complete disengagement of the lac repressor from the lac promoter as the probabilistic consequence of a transient stepwise mechanism, is sufficient to explain the sigmoidal lac responses as functions of time and of inducer concentration. This sigmoidal shape can be misleadingly interpreted as a phenomenon of equilibrium cooperativity classically used to explain bistability, but which has been reported to be weak in this system

    Genotype to phenotype mapping and the fitness landscape of the E. coli lac promoter

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    Genotype-to-phenotype maps and the related fitness landscapes that include epistatic interactions are difficult to measure because of their high dimensional structure. Here we construct such a map using the recently collected corpora of high-throughput sequence data from the 75 base pairs long mutagenized E. coli lac promoter region, where each sequence is associated with its phenotype, the induced transcriptional activity measured by a fluorescent reporter. We find that the additive (non-epistatic) contributions of individual mutations account for about two-thirds of the explainable phenotype variance, while pairwise epistasis explains about 7% of the variance for the full mutagenized sequence and about 15% for the subsequence associated with protein binding sites. Surprisingly, there is no evidence for third order epistatic contributions, and our inferred fitness landscape is essentially single peaked, with a small amount of antagonistic epistasis. There is a significant selective pressure on the wild type, which we deduce to be multi-objective optimal for gene expression in environments with different nutrient sources. We identify transcription factor (CRP) and RNA polymerase binding sites in the promotor region and their interactions without difficult optimization steps. In particular, we observe evidence for previously unexplored genetic regulatory mechanisms, possibly kinetic in nature. We conclude with a cautionary note that inferred properties of fitness landscapes may be severely influenced by biases in the sequence data

    Optimality principles in the regulation of metabolic networks.

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    One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular “task” of the network—its function—should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide

    Characterization of Motility and Surface Attachment in Thirteen Members of the Roseobacter Clade

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    The Roseobacter clade is an abundant and biogeochemically relevant group of marine bacteria. Physiological and ecological traits identified in specific representatives of the clade are often universally attributed to all Roseobacter group members, however, culture-dependent studies utilizing phylogenetically distinct members are rare. Other attributes often associated with this clade include motility, biofilm formation and surface attachment, chemotaxis and quorum sensing. This study compared a collection of 13 diverse Roseobacter strains both pheno- and genotypically on the basis of these traits. Motility was determined for seven previously uncharacterized strains, with five of the strains demonstrating motility. Microscopic analysis using both phase contrast and transmission electron microscopy supported this finding. A crystal violet assay was used to assess biofilm formation on plastic and glass surfaces with a range of surface properties and yielded a wide array of phenotypic responses. Taking into account the variety of surface types and media types tested approximately half (54%) of the strains showed pronounced biofilm formation and all motile strains were capable of forming biofilms. Degenerate primer sets were designed to probe strains for which no genome sequence is currently available for genes involved in flagellar synthesis and chemotaxis. Two strains that demonstrated no signs of motility in the laboratory were found to possess a necessary gene for flagellar formation and a flagellar-associated chemotaxis gene. Genome analysis including other sequenced Roseobacter strains revealed that flagellar, chemotaxis and quorum sensing operons are abundant in members of this lineage, with 89% possessing flagellar and chemotaxis operons and 78% possessing genes believed to be involved in quorum sensing. This study underscores the diversity of this clade and emphasizes the difficulty of assigning phenotypic capabilities to all lineage members

    A practical guide to mechanistic systems modeling in biology using a logic-based approach

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    Mechanistic computational models enable the study of regulatory mechanisms implicated in various biological processes. These models provide a means to analyze the dynamics of the systems they describe, and to study and interrogate their properties, and provide insights about the emerging behavior of the system in the presence of single or combined perturbations. Aimed at those who are new to computational modeling, we present here a practical hands-on protocol breaking down the process of mechanistic modeling of biological systems in a succession of precise steps. The protocol provides a framework that includes defining the model scope, choosing validation criteria, selecting the appropriate modeling approach, constructing a model and simulating the model. To ensure broad accessibility of the protocol, we use a logical modeling framework, which presents a lower mathematical barrier of entry, and two easy-to-use and popular modeling software tools: Cell Collective and GINsim. The complete modeling workflow is applied to a well-studied and familiar biological process—the lac operon regulatory system. The protocol can be completed by users with little to no prior computational modeling experience approximately within 3 h

    Decomposition of the lactose operon

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    Mutual Regulation of CRP and N(epsilon)-Lysine Acetylation in Escherichia Coli

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    Post-translational modifications, such as N(epsilon)-lysine acetylation, are known to alter the behavior of transcriptional regulators in eukaryotes, but very little is known about the consequences of acetylation on transcriptional regulation in bacteria. Here, I provide evidence that a global transcriptional regulator of carbon metabolism, cAMP Receptor Protein (CRP), promotes both enzymatic and non-enzymatic lysine acetylation in E. coli. Non-enzymatic lysine acetylation occurs when cells ferment acetate, such as during growth on high concentrations of glucose. Intriguingly, CRP can be non-enzymatically acetylated on several lysines, including lysine 100 (K100). I provide evidence that neutralization of the K100 positive charge, as would occur upon K100 acetylation, has a dual effect on CRP activity. First, K100 neutralization decreases CRP activity at some Class II promoters. This decreased activity likely results from disruption of the interaction between Activating Region 2 (AR2) of CRP and the RNA polymerase alpha subunit N-terminal domain. Second, K100 neutralization increases the CRP half-life, leading to increased CRP steady state levels. Due to increased steady state levels, CRP activity is increased at some Class I promoters, in which CRP does not require AR2. Taken together, I propose that CRP promotes global acetylation, including CRP K100 acetylation, when cells are grown on glucose by positively regulating non-enzymatic acetylation. A consequence of K100 acetylation may be inverse regulation of Class II and Class I promoters under these conditions. This mechanism may help regulate carbon flux though central metabolism

    Development of a stochastic simulator for biological systems based on Calculus of Looping Sequences.

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    Molecular Biology produces a huge amount of data concerning the behavior of the single constituents of living organisms. Nevertheless, this reductionism view is not sucient to gain a deep comprehension of how such components interact together at the system level, generating the set of complex behavior we observe in nature. This is the main motivation of the rising of one of the most interesting and recent applications of computer science: Computational Systems Biology, a new science integrating experimental activity and mathematical modeling in order to study the organization principles and the dynamic behavior of biological systems. Among the formalisms that either have been applied to or have been inspired by biological systems there are automata based models, rewrite systems, and process calculi. Here we consider a formalism based on term rewriting called Calculus of Looping Sequences (CLS) aimed to model chemical and biological systems. In order to quantitatively simulate biological systems a stochastic extension of CLS has been developed; it allows to express rule schemata with the simplicity of notation of term rewriting and has some semantic means which are common in process calculi. In this thesis we carry out the study of the implementation of a stochastic simulator for the CLS formalism. We propose an extension of Gillespie's stochastic simulation algorithm that handles rule schemata with rate functions, and we present an efficient bottom-up, pre-processing based, CLS pattern matching algorithm. A simulator implementing the ideas introduced in this thesis, has been developed in F#, a multi-paradigm programming language for .NET framework modeled on OCaml. Although F# is a research project, still under continuous development, it has a product quality performance. It merges seamlessly the object oriented, the functional and the imperative programming paradigms, allowing to exploit the performance, the portability and the tools of .NET framework
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