19 research outputs found

    A Complete Pathway Model for Lipid A Biosynthesis in Escherichia coli.

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    Lipid A is a highly conserved component of lipopolysaccharide (LPS), itself a major component of the outer membrane of Gram-negative bacteria. Lipid A is essential to cells and elicits a strong immune response from humans and other animals. We developed a quantitative model of the nine enzyme-catalyzed steps of Escherichia coli lipid A biosynthesis, drawing parameters from the experimental literature. This model accounts for biosynthesis regulation, which occurs through regulated degradation of the LpxC and WaaA (also called KdtA) enzymes. The LpxC degradation signal appears to arise from the lipid A disaccharide concentration, which we deduced from prior results, model results, and new LpxK overexpression results. The model agrees reasonably well with many experimental findings, including the lipid A production rate, the behaviors of mutants with defective LpxA enzymes, correlations between LpxC half-lives and cell generation times, and the effects of LpxK overexpression on LpxC concentrations. Its predictions also differ from some experimental results, which suggest modifications to the current understanding of the lipid A pathway, such as the possibility that LpxD can replace LpxA and that there may be metabolic channeling between LpxH and LpxB. The model shows that WaaA regulation may serve to regulate the lipid A production rate when the 3-deoxy-D-manno-oct-2-ulosonic acid (KDO) concentration is low and/or to control the number of KDO residues that get attached to lipid A. Computation of flux control coefficients showed that LpxC is the rate-limiting enzyme if pathway regulation is ignored, but that LpxK is the rate-limiting enzyme if pathway regulation is present, as it is in real cells. Control also shifts to other enzymes if the pathway substrate concentrations are not in excess. Based on these results, we suggest that LpxK may be a much better drug target than LpxC, which has been pursued most often

    The Knockout of Secretin in Cerebellar Purkinje Cells Impairs Mouse Motor Coordination and Motor Learning

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    Secretin (SCT) was first considered to be a gut hormone regulating gastrointestinal functions when discovered. Recently, however, central actions of SCT have drawn intense research interest and are supported by the broad distribution of SCT in specific neuronal populations and by in vivo physiological studies regarding its role in water homeostasis and food intake. The direct action of SCT on a central neuron was first discovered in cerebellar Purkinje cells in which SCT from cerebellar Purkinje cells was found to potentiate GABAergic inhibitory transmission from presynaptic basket cells. Because Purkinje neurons have a major role in motor coordination and learning functions, we hypothesize a behavioral modulatory function for SCT. In this study, we successfully generated a mouse model in which the SCT gene was deleted specifically in Purkinje cells. This mouse line was tested together with SCT knockout and SCT receptor knockout mice in a full battery of behavioral tasks. We found that the knockout of SCT in Purkinje neurons did not affect general motor ability or the anxiety level in open field tests. However, knockout mice did exhibit impairments in neuromuscular strength, motor coordination, and motor learning abilities, as shown by wire hanging, vertical climbing, and rotarod tests. In addition, SCT knockout in Purkinje cells possibly led to the delayed development of motor neurons, as supported by the later occurrence of key neural reflexes. In summary, our data suggest a role in motor coordination and motor learning for SCT expressed in cerebellar Purkinje cells

    On the design of random metasurface based devices

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    Metasurfaces are generally designed by placing scatterers in periodic or pseudo-periodic grids. We propose and discuss design rules for functional metasurfaces with randomly placed anisotropic elements that randomly sample a well-defined phase function. By analyzing the focusing performance of random metasurface lenses as a function of their density and the density of the phase-maps used to design them, we find that the performance of 1D metasurfaces is mostly governed by their density while 2D metasurfaces strongly depend on both the density and the near-field coupling configuration of the surface. The proposed approach is used to design all-polarization random metalenses at near infrared frequencies. Challenges, as well as opportunities of random metasurfaces compared to periodic ones are discussed. Our results pave the way to new approaches in the design of nanophotonic structures and devices from lenses to solar energy concentrators
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