Publications

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The innate immune system represents our first line of defense against microbial pathogens, and in many cases is activated by recognition of pathogen cellular components (dsRNA, flagella, LPS, etc.) by cell surface membrane proteins known as toll-like receptors (TLRs). As the initial trigger for innate immune response activation, TLRs also represent a means by which we can effectively control or modulate inflammatory responses. This proposal focused on TLR4, which is the cell-surface receptor primarily responsible for initiating the innate immune response to lipopolysaccharide (LPS), a major component of the outer membrane envelope of gram-negative bacteria. The goal was to better understand TLR4 activation and associated membrane proximal events, in order to enhance the design of small molecule therapeutics to modulate immune activation. Our approach was to reconstitute the receptor in biomimetic systems in-vitro to allow study of the structure and dynamics with biophysical methods. Structural studies were initiated in the first year but were halted after the crystal structure of the dimerized receptor was published early in the second year of the program. Methods were developed to determine the association constant for oligomerization of the soluble receptor. LPS-induced oligomerization was observed to be a strong function of buffer conditions. In 20 mM Tris pH 8.0 with 200 mM NaCl, the onset of receptor oligomerization occurred at 0.2 uM TLR4/MD2 with E coli LPS Ra mutant in excess. However, in the presence of 0.5 uM CD14 and 0.5 uM LBP, the onset of receptor oligomerization was observed to be less than 10 nM TLR4/MD2. Several methods were pursued to study LPS-induced oligomerization of the membrane-bound receptor, including CryoEM, FRET, colocalization and codiffusion followed by TIRF, and fluorescence correlation spectroscopy. However, there approaches met with only limited success.

Cell membranes are dynamic substrates that achieve a diverse array of functions through multi-scale reconfigurations. We explore the morphological changes that occur upon protein interaction to model membrane systems that induce deformation of their planar structure to yield nanotube assemblies. In the two examples shown in this report we will describe the use of membrane adhesion and particle trajectory to form lipid nanotubes via mechanical stretching, and protein adsorption onto domains and the induction of membrane curvature through steric pressure. Through this work the relationship between membrane bending rigidity, protein affinity, and line tension of phase separated structures were examined and their relationship in biological membranes explored.

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A novel hyperspectral fluorescence microscope for high-resolution 3D optical sectioning of cells and other structures has been designed, constructed, and used to investigate a number of different problems. We have significantly extended new multivariate curve resolution (MCR) data analysis methods to deconvolve the hyperspectral image data and to rapidly extract quantitative 3D concentration distribution maps of all emitting species. The imaging system has many advantages over current confocal imaging systems including simultaneous monitoring of numerous highly overlapped fluorophores, immunity to autofluorescence or impurity fluorescence, enhanced sensitivity, and dramatically improved accuracy, reliability, and dynamic range. Efficient data compression in the spectral dimension has allowed personal computers to perform quantitative analysis of hyperspectral images of large size without loss of image quality. We have also developed and tested software to perform analysis of time resolved hyperspectral images using trilinear multivariate analysis methods. The new imaging system is an enabling technology for numerous applications including (1) 3D composition mapping analysis of multicomponent processes occurring during host-pathogen interactions, (2) monitoring microfluidic processes, (3) imaging of molecular motors and (4) understanding photosynthetic processes in wild type and mutant Synechocystis cyanobacteria.

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We have developed a new nanotagging technology for detecting and imaging the self-organization of proteins and other components of membranes at nanometer resolution for the purpose of investigating cell signaling and other membrane-mediated biological processes. We used protein-, lipid-, or drug-bound porphyrin photocatalysts to grow in-situ nanometer-sized metal particles, which reveal the location of the porphyrin-labeled molecules by electron microscopy. We initially used photocatalytic nanotagging to image assembled multi-component proteins and to monitor the distribution of lipids and porphyrin labels in liposomes. For example, by exchanging the heme molecules in hemoproteins with a photocatalytic tin porphyrin, a nanoparticle was grown at each heme site of the protein. The result obtained from electron microscopy for a tagged multi-subunit protein such as hemoglobin is a symmetric constellation of a specific number of nanoparticle tags, four in the case of the hemoglobin tetramer. Methods for covalently linking photocatalytic porphyrin labels to lipids and proteins were also developed to detect and image the self-organization of lipids, protein-protein supercomplexes, and membrane-protein complexes. Procedures for making photocatalytic porphyrin-drug, porphyrin-lipid, and porphyrin-protein hybrids for non-porphyrin-binding proteins and membrane components were pursued and the first porphyrin-labeled lipids was investigated in liposomal membrane models. Our photocatalytic nanotagging technique may ultimately allow membrane self-organization and cell signaling processes to be imaged in living cells. Fluorescence and plasmonic spectra of the tagged proteins might also provide additional information about protein association and membrane organization. In addition, a porphyrin-aspirin or other NSAID hybrid may be used to grow metal nanotags for the pharmacologically important COX enzymes in membranes so that the distribution of the protein can be imaged at the nanometer scale.