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Fluorescence measurements for evaluating the application of multivariate analysis techniques to optically thick environments

Reichardt, Thomas A.; Schmitt, Randal L.; Sickafoose, Shane S.; Jones, Howland D.; Timlin, Jerilyn A.

Laser-induced fluorescence measurements of cuvette-contained laser dye mixtures are made for evaluation of multivariate analysis techniques to optically thick environments. Nine mixtures of Coumarin 500 and Rhodamine 610 are analyzed, as well as the pure dyes. For each sample, the cuvette is positioned on a two-axis translation stage to allow the interrogation at different spatial locations, allowing the examination of both primary (absorption of the laser light) and secondary (absorption of the fluorescence) inner filter effects. In addition to these expected inner filter effects, we find evidence that a portion of the absorbed fluorescence is re-emitted. A total of 688 spectra are acquired for the evaluation of multivariate analysis approaches to account for nonlinear effects.

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From benchtop to raceway : spectroscopic signatures of dynamic biological processes in algal communities

Timlin, Jerilyn A.; Garcia, Omar F.; Aragon, Michelle L.; Powell, Amy J.; Jones, Howland D.; Reichardt, Thomas A.; Ricken, James B.; Trahan, Christine A.; Ruffing, Anne R.; Collins, Aaron M.; Dwyer, Brian P.

The search is on for new renewable energy and algal-derived biofuel is a critical piece in the multi-faceted renewable energy puzzle. It has 30x more oil than any terrestrial oilseed crop, ideal composition for biodiesel, no competition with food crops, can be grown in waste water, and is cleaner than petroleum based fuels. This project discusses these three goals: (1) Conduct fundamental research into the effects that dynamic biotic and abiotic stressors have on algal growth and lipid production - Genomics/Transcriptomics, Bioanalytical spectroscopy/Chemical imaging; (2) Discover spectral signatures for algal health at the benchtop and greenhouse scale - Remote sensing, Bioanalytical spectroscopy; and (3) Develop computational model for algal growth and productivity at the raceway scale - Computational modeling.

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Optimizing algal cultivation & productivity : an innovative, multidiscipline, and multiscale approach

Timlin, Jerilyn A.; Jones, Howland D.; Ricken, James B.; Murton, Jaclyn K.; Dwyer, Brian P.; Ruffing, Anne R.; Powell, Amy J.; Reichardt, Thomas A.

Progress in algal biofuels has been limited by significant knowledge gaps in algal biology, particularly as they relate to scale-up. To address this we are investigating how culture composition dynamics (light as well as biotic and abiotic stressors) describe key biochemical indicators of algal health: growth rate, photosynthetic electron transport, and lipid production. Our approach combines traditional algal physiology with genomics, bioanalytical spectroscopy, chemical imaging, remote sensing, and computational modeling to provide an improved fundamental understanding of algal cell biology across multiple cultures scales. This work spans investigations from the single-cell level to ensemble measurements of algal cell cultures at the laboratory benchtop to large greenhouse scale (175 gal). We will discuss the advantages of this novel, multidisciplinary strategy and emphasize the importance of developing an integrated toolkit to provide sensitive, selective methods for detecting early fluctuations in algal health, productivity, and population diversity. Progress in several areas will be summarized including identification of spectroscopic signatures for algal culture composition, stress level, and lipid production enabled by non-invasive spectroscopic monitoring of the photosynthetic and photoprotective pigments at the single-cell and bulk-culture scales. Early experiments compare and contrast the well-studied green algae chlamydomonas with two potential production strains of microalgae, nannochloropsis and dunnaliella, under optimal and stressed conditions. This integrated approach has the potential for broad impact on algal biofuels and bioenergy and several of these opportunities will be discussed.

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Resolving dynamics of cell signaling via real-time imaging of the immunological synapse

Timlin, Jerilyn A.; Burns, A.R.; Aaron, Jesse S.; Carson, Bryan C.; Stevens, Mark J.

This highly interdisciplinary team has developed dual-color, total internal reflection microscopy (TIRF-M) methods that enable us to optically detect and track in real time protein migration and clustering at membrane interfaces. By coupling TIRF-M with advanced analysis techniques (image correlation spectroscopy, single particle tracking) we have captured subtle changes in membrane organization that characterize immune responses. We have used this approach to elucidate the initial stages of cell activation in the IgE signaling network of mast cells and the Toll-like receptor (TLR-4) response in macrophages stimulated by bacteria. To help interpret these measurements, we have undertaken a computational modeling effort to connect the protein motion and lipid interactions. This work provides a deeper understanding of the initial stages of cellular response to external agents, including dynamics of interaction of key components in the signaling network at the 'immunological synapse,' the contact region of the cell and its adversary.

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Accurate measurement of cellular autofluorescence is critical for imaging of host-pathogen interactions

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Timlin, Jerilyn A.; Noek, Rachel M.; Kaiser, Julia N.; Sinclair, Michael B.; Jones, Howland D.; Davis, Ryan W.; Lane, Todd L.

Cellular autofluorescence, though ubiquitous when imaging cells and tissues, is often assumed to be small in comparison to the signal of interest. Uniform estimates of autofluorescence intensity obtained from separate control specimens are commonly employed to correct for autofluorescence. While these may be sufficient for high signal-to-background applications, improvements in detector and probe technologies and introduction of spectral imaging microscopes have increased the sensitivity of fluorescence imaging methods, exposing the possibility of effectively probing the low signal-to-background regime. With spectral imaging, reliable monitoring of signals near or even below the noise levels of the microscope is possible if autofluorescence and background signals can be accurately compensated for. We demonstrate the importance of accurate autofluorescence determination and utility of spectral imaging and multivariate analysis methods using a case study focusing on fluorescence confocal spectral imaging of host-pathogen interactions. In this application fluorescent proteins are produced when bacteria invade host cells. Unfortunately the analyte signal is spectrally overlapped and typically weaker than the cellular autofluorescence. In addition to discussing the advantages of spectral imaging for following pathogen invasion, we present the spectral properties of mouse macrophage autofluorescence. The imaging and analysis methods developed are widely applicable to cell and tissue imaging. © 2008 Copyright SPIE - The International Society for Optical Engineering.

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"Trojan Horse" strategy for deconstruction of biomass for biofuels production

Timlin, Jerilyn A.; Tran-Gyamfi, Mary B.; Sapra, Rajat S.; Sinclair, Michael B.; Simmons, Blake S.

Production of renewable biofuels to displace fossil fuels currently consumed in the transportation sector is a pressing multi-agency national priority. Currently, nearly all fuel ethanol is produced from corn-derived starch. Dedicated 'energy crops' and agricultural waste are preferred long-term solutions for renewable, cheap, and globally available biofuels as they avoid some of the market pressures and secondary greenhouse gas emission challenges currently facing corn ethanol. These sources of lignocellulosic biomass are converted to fermentable sugars using a variety of chemical and thermochemical pretreatments, which disrupt cellulose and lignin cross-links, allowing exogenously added recombinant microbial enzymes to more efficiently hydrolyze the cellulose for 'deconstruction' into glucose. This process is plagued with inefficiencies, primarily due to the recalcitrance of cellulosic biomass, mass transfer issues during deconstruction, and low activity of recombinant deconstruction enzymes. Costs are also high due to the requirement for enzymes and reagents, and energy-intensive and cumbersome pretreatment steps. One potential solution to these problems is found in synthetic biology; they propose to engineer plants that self-produce a suite of cellulase enzymes targeted to the apoplast for cleaving the linkages between lignin and cellulosic fibers; the genes encoding the degradation enzymes, also known as cellulases, are obtained from extremophilic organisms that grow at high temperatures (60-100 C) and acidic pH levels (<5). These enzymes will remain inactive during the life cycle of the plant but become active during hydrothermal pretreatment i.e., elevated temperatures. Deconstruction can be integrated into a one-step process, thereby increasing efficiency (cellulose-cellulase mass-transfer rates) and reducing costs. The proposed disruptive technologies address biomass deconstruction processes by developing transgenic plants encoding a suite of enzymes used in cellulosic deconstruction. The unique aspects of this technology are the rationally engineered, highly productive extremophilic enzymes, targeted to specific cellular locations (apoplast) and their dormancy during normal plant proliferation, which become Trojan horses during pretreatment conditions. They have been leveraging established Sandia's enzyme-engineering and imaging capabilities. Their technical approach not only targets the recalcitrance and mass-transfer problem during biomass degradation but also eliminates the costs associated with industrial-scale production of microbial enzymes added during processing.

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Advanced imaging of multiple mRNAs in brain tissue using a custom hyperspectral imager and multivariate curve resolution

Journal of Neuroscience Methods

Sutherland, Vicki L.; Timlin, Jerilyn A.; Nieman, Linda T.; Guzowski, John F.; Chawla, Monica K.; Worley, Paul F.; Roysam, Badri; McNaughton, Bruce L.; Sinclair, Michael B.; Barnes, Carol A.

Simultaneous imaging of multiple cellular components is of tremendous importance in the study of complex biological systems, but the inability to use probes with similar emission spectra and the time consuming nature of collecting images on a confocal microscope are prohibitive. Hyperspectral imaging technology, originally developed for remote sensing applications, has been adapted to measure multiple genes in complex biological tissues. A spectral imaging microscope was used to acquire overlapping fluorescence emissions from specific mRNAs in brain tissue by scanning the samples using a single fluorescence excitation wavelength. The underlying component spectra obtained from the samples are then separated into their respective spectral signatures using multivariate analyses, enabling the simultaneous quantitative measurement of multiple genes either at regional or cellular levels. © 2006 Elsevier B.V. All rights reserved.

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3D optical sectioning with a new hyperspectral confocal fluorescence imaging system

Haaland, David M.; Sinclair, Michael B.; Jones, Howland D.; Timlin, Jerilyn A.; Bachand, George B.; Sasaki, Darryl Y.; Davidson, George S.; Van Benthem, Mark V.

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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Hyperspectral imaging system for quantitative identification and discrimination of fluorescent labels in the presence of autofluorescence

2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings

Nieman, Linda T.; Sinclair, Michael B.; Timlin, Jerilyn A.; Jones, Howland D.; Haaland, David M.

Multivariate data analysis applied to hyperspectral images offers the unique opportunity to dramatically increase the amount of information gained from a single biological sample. Numerous fluorescent tags can be used to perform multiple studies in parallel from a single hyperspectral image scan. Highly spatially and spectrally overlapping fluorophores can be separated even amidst a large autofluorescence background with the use of multivariate curve resolution methods. The results of two biological samples with multiple fluorescent labels are shown and compared to a traditional filter-based multispectral system. These examples illustrate the combined power of the hyperspectral microscope hardware and the multivariate image analysis software for biomedical imaging. This technique has the potential to be applied to a broad array of biological applications where fluorescent tags are a central and ubiquitous tool, and to biomedical areas that focus on the discovery and identification of weak, broad spectrum native fluorescence. © 2006 IEEE.

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Results 226–250 of 263
Results 226–250 of 263