Publications

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The biocompatibility and possible toxicological consequences of engineered nanomaterials, including quantum dots (QDs) due to their unique suitability for biomedical applications, remain intense areas of interest. We utilized advanced imaging approaches to characterize the interactions of CdSe QDs of various sizes and shapes with live immune cells. Particle diffusion and partitioning within the plasma membrane, cellular uptake kinetics, and sorting of particles into lysosomes were all independantly characterized. Using high-speed total internal reflectance fluorescence (TIRF) microscopy, we show that QDs with an average aspect ratio of 2.0 (i.e., rod-shaped) diffuse nearly an order of magnitude slower in the plasma membrane than more spherical particles with aspect ratios of 1.2 and 1.6, respectively. Moreover, more rod-shaped QDs were shown to be internalized into the cell 2-3 fold more slowly. Hyperspectral confocal fluorescence microscopy demonstrates that QDs tend to partition within the cell membrane into regions containing a single particle type. Furthermore, data examining QD sorting mechanisms indicate that endocytosis and lysosomal sorting increases with particle size. Together, these observations suggest that both size and aspect ratio of a nanoparticle are important characteristics that significantly impact interactions with the plasma membrane, uptake into the cell, and localization within intracellular vesicles. Thus, rather than simply characterizing nanoparticle uptake into cells, we show that utilization of advanced imaging approaches permits a more nuanced and complete examination of the multiple aspects of cell-nanoparticle interactions that can ultimately aid understanding possible mechanisms of toxicity, resulting in safer nanomaterial designs. Using hyperspectral confocal fluorescence (HCF) microscopy, it is shown that quantum dots of various sizes and shapes partition themselves into distinct regions within the cell membrane of RBL-2H3 rat mast cells. HCF microscopy allows for deconvolving the signal from multiple, overlapping fluorophores in the sample in order to reveal precise concentrations and distributions of nanoparticles in the cell. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Over the past decade optical approaches were introduced that effectively break the diffraction barrier. Of particular note were introductions of Stimulated Emission/Depletion (STED) microscopy, Photo-Activated Localization Microscopy (PALM), and the closely related Stochastic Optical Reconstruction Microscopy (STORM). STORM represents an attractive method for researchers, as it does not require highly specialized optical setups, can be implemented using commercially available dyes, and is more easily amenable to multicolor imaging. We implemented a simultaneous dual-color, direct-STORM imaging system through the use of an objective-based TIRF microscope and filter-based image splitter. This system allows for excitation and detection of two fluorophors simultaneously, via projection of each fluorophor's signal onto separate regions of a detector. We imaged the sub-resolution organization of the TLR4 receptor, a key mediator of innate immune response, after challenge with lipopolysaccharide (LPS), a bacteria-specific antigen. While distinct forms of LPS have evolved among various bacteria, only some LPS variations (such as that derived from E. coli) typically result in significant cellular immune response. Others (such as from the plague bacteria Y. pestis) do not, despite affinity to TLR4. We will show that challenge with LPS antigens produces a statistically significant increase in TLR4 receptor clusters on the cell membrane, presumably due to recruitment of receptors to lipid rafts. These changes, however, are only detectable below the diffraction limit and are not evident using conventional imaging methods. Furthermore, we will compare the spatiotemporal behavior of TLR4 receptors in response to different LPS chemotypes in order to elucidate possible routes by which pathogens such as Y. pestis are able to circumvent the innate immune system. Finally, we will exploit the dual-color STORM capabilities to simultaneously image LPS and TLR4 receptors in the cellular membrane at resolutions at or below 40nm.

A considerable amount research is being conducted on microalgae, since microalgae are becoming a promising source of renewable energy. Most of this research is centered on lipid production in microalgae because microalgae produce triacylglycerol which is ideal for biodiesel fuels. Although we are interested in research to increase lipid production in algae, we are also interested in research to sustain healthy algal cultures in large scale biomass production farms or facilities. The early detection of fluctuations in algal health, productivity, and invasive predators must be developed to ensure that algae are an efficient and cost-effective source of biofuel. Therefore we are developing technologies to monitor the health of algae using spectroscopic measurements in the field. To do this, we have proposed to spectroscopically monitor large algal cultivations using LIDAR (Light Detection And Ranging) remote sensing technology. Before we can deploy this type of technology, we must first characterize the spectral bio-signatures that are related to algal health. Recently, we have adapted our confocal hyperspectral imaging microscope at Sandia to have two-photon excitation capabilities using a chameleon tunable laser. We are using this microscope to understand the spectroscopic signatures necessary to characterize microalgae at the cellular level prior to using these signatures to classify the health of bulk samples, with the eventual goal of using of LIDAR to monitor large scale ponds and raceways. By imaging algal cultures using a tunable laser to excite at several different wavelengths we will be able to select the optimal excitation/emission wavelengths needed to characterize algal cultures. To analyze the hyperspectral images generated from this two-photon microscope, we are using Multivariate Curve Resolution (MCR) algorithms to extract the spectral signatures and their associated relative intensities from the data. For this presentation, I will show our two-photon hyperspectral imaging results on a variety of microalgae species and show how these results can be used to characterize algal ponds and raceways.

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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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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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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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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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