Publications

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The purpose of this LDRD was to generate data that could be used to populate and thereby reduce the uncertainty in global carbon cycle models. These efforts were focused on developing a system for determining the dissolution rate of biogenic calcite under oceanic pressure and temperature conditions and on carrying out a digital transcriptomic analysis of gene expression in response to changes in pCO2, and the consequent acidification of the growth medium.

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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.

We present a rapid method for the identification of viruses using microfluidic chip gel electrophoresis (CGE) of high-copy number proteins to generate unique protein profiles. Viral proteins are solubilized by heating at 95°C in borate buffer containing detergent (5 min), then labeled with fluorescamine dye (10 s), and analyzed using the μChemLab CGE system (5 min). Analyses of closely related T2 and T4 bacteriophage demonstrate sufficient assay sensitivity and peak resolution to distinguish the two phage. CGE analyses of four additional viruses - MS2 bacteriophage, Epstein - Barr, respiratory syncytial, and vaccinia viruses - demonstrate reproducible and visually distinct protein profiles. To evaluate the suitability of the method for unique identification of viruses, we employed a Bayesian classification approach. Using a subset of 126 replicate electropherograms of the six viruses and phage for training purposes, successful classification with non-training data was 66/69 or 95% with no false positives. The classification method is based on a single attribute (elution time), although other attributes such as peak width, peak amplitude, or peak shape could be incorporated and may improve performance further. The encouraging results suggest a rapid and simple way to identify viruses without requiring specialty reagents such as PCR probes and antibodies. © 2008 American Chemical Society.

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This short-term, late-start LDRD examined the effects of nutritional deprivation on the energy harvesting complex in microalgae. While the original experimental plan involved a much more detailed study of temperature and nutrition on the antenna system of a variety of TAG producing algae and their concomitant effects on oil production, time and fiscal constraints limited the scope of the study. This work was a joint effort between research teams at Sandia National Laboratories, New Mexico and California. Preliminary results indicate there is a photosystem response to silica starvation in diatoms that could impact the mechanisms for lipid accumulation.