Biomedical subjects

Boris I Shraiman

Publications and source records attributed to Boris I Shraiman.

9 recordsLinked to original sources

PubMed2006

On the role of glypicans in the process of morphogen gradient formation.

Glypicans are cell surface molecules that influence signaling and gradient formation of secreted morphogens and growth factors. Several distinct functions have been ascribed to glypicans including acting as co-receptors for signaling proteins. Recent data show that glypicans are also necessary for morphogen propagation in the tissue. In the present study, a model describing the interaction of a morphogen with glypicans is formulated, analyzed and compared with measurements of the effect of glypican Dally-like (Dlp) overexpression on Wingless (Wg) morphogen signaling in Drosophila melanogaster wing imaginal discs. The model explains the opposing effect that Dlp overexpression has on Wg signaling in the distal and proximal regions of the disc and makes a number of quantitative predictions for further experiments. In particular, our model suggests that Dlp acts by allowing Wg to diffuse on cell surface while protecting it from loss and degradation, and that Dlp rather than acting as Wg co-receptor competes with receptors for morphogen binding.

Animals↗

PubMed2005

Mechanical feedback as a possible regulator of tissue growth.

Regulation of cell growth and proliferation has a fundamental role in animal and plant development and in the progression of cancer. In the context of development, it is important to understand the mechanisms that coordinate growth and patterning of tissues. Imaginal discs, which are larval precursors of fly limbs and organs, have provided much of what we currently know about these processes. Here, we consider the mechanism that is responsible for the observed uniformity of growth in wing imaginal discs, which persists in the presence of gradients in growth inducing morphogens in spite of the stochastic nature of cell division. The phenomenon of "cell competition," which manifests in apoptosis of slower-growing cells in the vicinity of faster growing tissue, suggests that uniform growth is not a default state but a result of active regulation. How can a patch of tissue compare its growth rate with that of its surroundings? A possible way is furnished by mechanical interactions. To demonstrate this mechanism, we formulate a mathematical model of nonuniform growth in a layer of tissue and examine its mechanical implications. We show that a clone growing faster or slower than the surrounding tissue is subject to mechanical stress, and we propose that dependence of the rate of cell division on local stress could provide an "integral-feedback" mechanism stabilizing uniform growth. The proposed mechanism of growth control is not specific to imaginal disc growth and could be of general relevance. Several experimental tests of the proposed mechanism are suggested.

Animals↗

PubMed2005

G-protein-coupled enzyme cascades have intrinsic properties that improve signal localization and fidelity.

G-protein-coupled enzyme cascades are used by eukaryotic cells to detect external signals and transduce them into intracellular messages that contain biological information relevant to the cell's function. Since G-protein-coupled receptors that are designed to detect different kinds of external signals can generate the same kind of intracellular response, effective signaling requires that there are mechanisms to increase signal specificity and fidelity. Here we examine the kinetic equations for the initial three stages in a generic G-protein-coupled cascade and show that the physical properties of the transduction pathway result in two intrinsic features that benefit signaling. 1), The response to a single activated receptor is naturally confined to a localized spatial domain, which could improve signal specificity by reducing cross talk. 2), The peak of the response generated by such a signaling domain is limited. This saturation effect reduces trial-to-trial variability and increases signaling fidelity by limiting the response to receptors that remain active for longer than average. We suggest that this mechanism for reducing response fluctuations may be a contributing factor in making the single photon responses of vertebrate retinal rods so remarkably reproducible.

Animals↗

PubMed2004

Multistability in the lactose utilization network of Escherichia coli.

Multistability, the capacity to achieve multiple internal states in response to a single set of external inputs, is the defining characteristic of a switch. Biological switches are essential for the determination of cell fate in multicellular organisms, the regulation of cell-cycle oscillations during mitosis and the maintenance of epigenetic traits in microbes. The multistability of several natural and synthetic systems has been attributed to positive feedback loops in their regulatory networks. However, feedback alone does not guarantee multistability. The phase diagram of a multistable system, a concise description of internal states as key parameters are varied, reveals the conditions required to produce a functional switch. Here we present the phase diagram of the bistable lactose utilization network of Escherichia coli. We use this phase diagram, coupled with a mathematical model of the network, to quantitatively investigate processes such as sugar uptake and transcriptional regulation in vivo. We then show how the hysteretic response of the wild-type system can be converted to an ultrasensitive graded response. The phase diagram thus serves as a sensitive probe of molecular interactions and as a powerful tool for rational network design.

Biological Transport↗

PubMed2003

Metabolic switching in the sugar phosphotransferase system of Escherichia coli.

Bacteria grown in a mixture of multiple sugars will first metabolize a preferred sugar until it is nearly depleted, only then turning to other carbon sources in the medium. This sharp switching of metabolic preference is characteristic of systems that optimize fitness. Here we consider the mechanism by which switching can occur in the Escherichia coli phosphotransferase system (PTS), which regulates the uptake and metabolism of several sugars. Using a model combining the description of fast biochemical processes and slower genetic regulation, we derive metabolic phase diagrams for the uptake of two PTS sugars, indicating regions of distinct sugar preference as a function of external sugar concentrations. We then propose a classification of bacterial phenotypes based on the topology of the metabolic phase diagram, and enumerate the possible topologically distinct phenotypes that can be achieved through mutations of the PTS. This procedure reveals that there is only one nontrivial switching phenotype that is insensitive to large changes in biochemical parameters. This phenotype exhibits diauxic growth, a manifestation of the winner-take-all dynamics enforced by PTS architecture. Winner-take-all behavior is implemented by the induction of sugar-specific operons, combined with competition between sugars for limited phosphoryl flux. We propose that flux-limited competition could be a common mechanism for introducing repressive interactions in cellular networks, and we argue that switching behavior similar to that described here should occur generically in systems that implement such a mechanism.

Adaptation, Physiological↗

PubMed2003

A biophysical approach to transcription factor binding site discovery.

Identification of transcription factor binding sites within regulatory segments of genomic DNA is an important step toward understanding of the regulatory circuits that control expression of genes. Here, we describe a novel bioinformatics method that bases classification of potential binding sites explicitly on the estimate of sequence-specific binding energy of a given transcription factor. The method also estimates the chemical potential of the factor that defines the threshold of binding. In contrast with the widely used information-theoretic weight matrix method, the new approach correctly describes saturation in the transcription factor/DNA binding probability. This results in a significant improvement in the number of expected false positives, particularly in the ubiquitous case of low-specificity factors. In the strong binding limit, the algorithm is related to the "support vector machine" approach to pattern recognition. The new method is used to identify likely genomic binding sites for the E. coli transcription factors collected in the DPInteract database. In addition, for CRP (a global regulatory factor), the likely regulatory modality (i.e., repressor or activator) of predicted binding sites is determined.

Algorithms↗

PubMed2002

Olfactory search at high Reynolds number.

Locating the source of odor in a turbulent environment-a common behavior for living organisms-is nontrivial because of the random nature of mixing. Here we analyze the statistical physics aspects of the problem and propose an efficient strategy for olfactory search that can work in turbulent plumes. The algorithm combines the maximum likelihood inference of the source position with an active search. Our approach provides the theoretical basis for the design of olfactory robots and the quantitative tools for the analysis of the observed olfactory search behavior of living creatures (e.g., odor-modulated optomotor anemotaxis of moths).

Algorithms↗

PubMed2002

Assigning numbers to the arrows: parameterizing a gene regulation network by using accurate expression kinetics.

A basic challenge in systems biology is to understand the dynamical behavior of gene regulation networks. Current approaches aim at determining the network structure based on genomic-scale data. However, the network connectivity alone is not sufficient to define its dynamics; one needs to also specify the kinetic parameters for the regulation reactions. Here, we ask whether effective kinetic parameters can be assigned to a transcriptional network based on expression data. We present a combined experimental and theoretical approach based on accurate high temporal-resolution measurement of promoter activities from living cells by using green fluorescent protein (GFP) reporter plasmids. We present algorithms that use these data to assign effective kinetic parameters within a mathematical model of the network. To demonstrate this, we employ a well defined network, the SOS DNA repair system of Escherichia coli. We find a strikingly detailed temporal program of expression that correlates with the functional role of the SOS genes and is driven by a hierarchy of effective kinetic parameter strengths for the various promoters. The calculated parameters can be used to determine the kinetics of all SOS genes given the expression profile of just one representative, allowing a significant reduction in complexity. The concentration profile of the master SOS transcriptional repressor can be calculated, demonstrating that relative protein levels may be determined from purely transcriptional data. This finding opens the possibility of assigning kinetic parameters to transcriptional networks on a genomic scale.

Algorithms↗

PubMed2002

Specificity and robustness in transcription control networks.

Recognition by transcription factors of the regulatory DNA elements upstream of genes is the fundamental step in controlling gene expression. How does the necessity to provide stability with respect to mutation constrain the organization of transcription control networks? We examine the mutation load of a transcription factor interacting with a set of n regulatory response elements as a function of the factor/DNA binding specificity and conclude on theoretical grounds that the optimal specificity decreases with n. The predicted correlation between variability of binding sites (for a given transcription factor) and their number is supported by the genomic data for Escherichia coli. The analysis of E. coli genomic data was carried out using an algorithm suggested by the biophysical model of transcription factor/DNA binding. Complete results of the search for candidate transcription factor binding sites are available at http://www.physics.rockefeller.edu/~boris/public/search_ecoli.

Algorithms↗