Information capacity of genetic regulatory elements

Changes in a cell's external or internal conditions are usually reflected in the concentrations of the relevant transcription factors. These proteins in turn modulate the expression levels of the genes under their control and sometimes need to perform non-trivial computations that integrate several inputs and affect multiple genes. At the same time, the activities of the regulated genes would fluctuate even if the inputs were held fixed, as a consequence of the intrinsic noise in the system, and such noise must fundamentally limit the reliability of any genetic computation. Here we use information theory to formalize the notion of information transmission in simple genetic regulatory elements in the presence of physically realistic noise sources. The dependence of this "channel capacity" on noise parameters, cooperativity and cost of making signaling molecules is explored systematically. We find that, at least in principle, capacities higher than one bit should be achievable and that consequently genetic regulation is not limited the use of binary, or "on-off", components.Comment: 17 pages, 9 figure

Optimizing information flow in small genetic networks. I

In order to survive, reproduce and (in multicellular organisms) differentiate, cells must control the concentrations of the myriad different proteins that are encoded in the genome. The precision of this control is limited by the inevitable randomness of individual molecular events. Here we explore how cells can maximize their control power in the presence of these physical limits; formally, we solve the theoretical problem of maximizing the information transferred from inputs to outputs when the number of available molecules is held fixed. We start with the simplest version of the problem, in which a single transcription factor protein controls the readout of one or more genes by binding to DNA. We further simplify by assuming that this regulatory network operates in steady state, that the noise is small relative to the available dynamic range, and that the target genes do not interact. Even in this simple limit, we find a surprisingly rich set of optimal solutions. Importantly, for each locally optimal regulatory network, all parameters are determined once the physical constraints on the number of available molecules are specified. Although we are solving an over--simplified version of the problem facing real cells, we see parallels between the structure of these optimal solutions and the behavior of actual genetic regulatory networks. Subsequent papers will discuss more complete versions of the problem

Entropy and information in neural spike trains: Progress on the sampling problem

The major problem in information theoretic analysis of neural responses and other biological data is the reliable estimation of entropy--like quantities from small samples. We apply a recently introduced Bayesian entropy estimator to synthetic data inspired by experiments, and to real experimental spike trains. The estimator performs admirably even very deep in the undersampled regime, where other techniques fail. This opens new possibilities for the information theoretic analysis of experiments, and may be of general interest as an example of learning from limited data.Comment: 7 pages, 4 figures; referee suggested changes, accepted versio

Planet Occurrence within 0.25 AU of Solar-type Stars from Kepler

We report the distribution of planets as a function of planet radius (R_p), orbital period (P), and stellar effective temperature (Teff) for P < 50 day orbits around GK stars. These results are based on the 1,235 planets (formally "planet candidates") from the Kepler mission that include a nearly complete set of detected planets as small as 2 Earth radii (Re). For each of the 156,000 target stars we assess the detectability of planets as a function of R_p and P. We also correct for the geometric probability of transit, R*/a. We consider first stars within the "solar subset" having Teff = 4100-6100 K, logg = 4.0-4.9, and Kepler magnitude Kp < 15 mag. We include only those stars having noise low enough to permit detection of planets down to 2 Re. We count planets in small domains of R_p and P and divide by the included target stars to calculate planet occurrence in each domain. Occurrence of planets varies by more than three orders of magnitude and increases substantially down to the smallest radius (2 Re) and out to the longest orbital period (50 days, ~0.25 AU) in our study. For P < 50 days, the radius distribution is given by a power law, df/dlogR= k R^\alpha. This rapid increase in planet occurrence with decreasing planet size agrees with core-accretion, but disagrees with population synthesis models. We fit occurrence as a function of P to a power law model with an exponential cutoff below a critical period P_0. For smaller planets, P_0 has larger values, suggesting that the "parking distance" for migrating planets moves outward with decreasing planet size. We also measured planet occurrence over Teff = 3600-7100 K, spanning M0 to F2 dwarfs. The occurrence of 2-4 Re planets in the Kepler field increases with decreasing Teff, making these small planets seven times more abundant around cool stars than the hottest stars in our sample. [abridged]Comment: Submitted to ApJ, 22 pages, 10 figure

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio

Agonist-induced membrane nanodomain clustering drives GLP-1 receptor responses in pancreatic beta cells

The glucagon-like peptide-1 receptor (GLP-1R), a key pharmacological target in type 2 diabetes (T2D) and obesity, undergoes rapid endocytosis after stimulation by endogenous and therapeutic agonists. We have previously highlighted the relevance of this process in fine-tuning GLP-1R responses in pancreatic beta cells to control insulin secretion. In the present study, we demonstrate an important role for the translocation of active GLP-1Rs into liquid-ordered plasma membrane nanodomains, which act as hotspots for optimal coordination of intracellular signaling and clathrin-mediated endocytosis. This process is dynamically regulated by agonist binding through palmitoylation of the GLP-1R at its carboxyl-terminal tail. Biased GLP-1R agonists and small molecule allosteric modulation both influence GLP-1R palmitoylation, clustering, nanodomain signaling, and internalization. Downstream effects on insulin secretion from pancreatic beta cells indicate that these processes are relevant to GLP-1R physiological actions and might be therapeutically targetable

Agonist-induced membrane nanodomain clustering drives GLP-1 receptor responses in pancreatic beta cells

The glucagon-like peptide-1 receptor (GLP-1R), a key pharmacological target in type 2 diabetes (T2D) and obesity, undergoes rapid endocytosis after stimulation by endogenous and therapeutic agonists. We have previously highlighted the relevance of this process in fine-tuning GLP-1R responses in pancreatic beta cells to control insulin secretion. In the present study, we demonstrate an important role for the translocation of active GLP-1Rs into liquid-ordered plasma membrane nanodomains, which act as hotspots for optimal coordination of intracellular signaling and clathrin-mediated endocytosis. This process is dynamically regulated by agonist binding through palmitoylation of the GLP-1R at its carboxyl-terminal tail. Biased GLP-1R agonists and small molecule allosteric modulation both influence GLP-1R palmitoylation, clustering, nanodomain signaling, and internalization. Downstream effects on insulin secretion from pancreatic beta cells indicate that these processes are relevant to GLP-1R physiological actions and might be therapeutically targetable

Development and Characterization of Synthetic Glucopyranosyl Lipid Adjuvant System as a Vaccine Adjuvant

Innate immune responses to vaccine adjuvants based on lipopolysaccharide (LPS), a component of Gram-negative bacterial cell walls, are driven by Toll-like receptor (TLR) 4 and adaptor proteins including MyD88 and TRIF, leading to the production of inflammatory cytokines, type I interferons, and chemokines. We report here on the characterization of a synthetic hexaacylated lipid A derivative, denoted as glucopyranosyl lipid adjuvant (GLA). We assessed the effects of GLA on murine and human dendritic cells (DC) by combining microarray, mRNA and protein multiplex assays and flow cytometry analyses. We demonstrate that GLA has multifunctional immunomodulatory activity similar to naturally-derived monophosphory lipid A (MPL) on murine DC, including the production of inflammatory cytokines, chemokines, DC maturation and antigen-presenting functions. In contrast, hexaacylated GLA was overall more potent on a molar basis than heterogeneous MPL when tested on human DC and peripheral blood mononuclear cells (PBMC). When administered in vivo, GLA enhanced the immunogenicity of co-administered recombinant antigens, producing strong cell-mediated immunity and a qualitative TH1 response. We conclude that the GLA adjuvant stimulates and directs innate and adaptive immune responses by inducing DC maturation and the concomitant release of pro-inflammatory cytokines and chemokines associated with immune cell trafficking, activities which have important implications for the development of future vaccine adjuvants

Chemotactic and Inflammatory Responses in the Liver and Brain Are Associated with Pathogenesis of Rift Valley Fever Virus Infection in the Mouse

Rift Valley fever virus (RVFV) is a major human and animal pathogen associated with severe disease including hemorrhagic fever or encephalitis. RVFV is endemic to parts of Africa and the Arabian Peninsula, but there is significant concern regarding its introduction into non-endemic regions and the potentially devastating effect to livestock populations with concurrent infections of humans. To date, there is little detailed data directly comparing the host response to infection with wild-type or vaccine strains of RVFV and correlation with viral pathogenesis. Here we characterized clinical and systemic immune responses to infection with wild-type strain ZH501 or IND vaccine strain MP-12 in the C57BL/6 mouse. Animals infected with live-attenuated MP-12 survived productive viral infection with little evidence of clinical disease and minimal cytokine response in evaluated tissues. In contrast, ZH501 infection was lethal, caused depletion of lymphocytes and platelets and elicited a strong, systemic cytokine response which correlated with high virus titers and significant tissue pathology. Lymphopenia and platelet depletion were indicators of disease onset with indications of lymphocyte recovery correlating with increases in G-CSF production. RVFV is hepatotropic and in these studies significant clinical and histological data supported these findings; however, significant evidence of a pro-inflammatory response in the liver was not apparent. Rather, viral infection resulted in a chemokine response indicating infiltration of immunoreactive cells, such as neutrophils, which was supported by histological data. In brains of ZH501 infected mice, a significant chemokine and pro-inflammatory cytokine response was evident, but with little pathology indicating meningoencephalitis. These data suggest that RVFV pathogenesis in mice is associated with a loss of liver function due to liver necrosis and hepatitis yet the long-term course of disease for those that might survive the initial hepatitis is neurologic in nature which is supported by observations of human disease and the BALB/c mouse model