Publications

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Algal biofuels are a renewable energy source with the potential to replace conventional petroleum-based fuels, while simultaneously reducing greenhouse gas emissions. The economic feasibility of commercial algal fuel production, however, is limited by low productivity of the natural algal strains. The project described in this SAND report addresses this low algal productivity by genetically engineering cyanobacteria (i.e. blue-green algae) to produce free fatty acids as fuel precursors. The engineered strains were characterized using Sandias unique imaging capabilities along with cutting-edge RNA-seq technology. These tools are applied to identify additional genetic targets for improving fuel production in cyanobacteria. This proof-of-concept study demonstrates successful fuel production from engineered cyanobacteria, identifies potential limitations, and investigates several strategies to overcome these limitations. This project was funded from FY10-FY13 through the President Harry S. Truman Fellowship in National Security Science and Engineering, a program sponsored by the LDRD office at Sandia National Laboratories.

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Magnetic resonance spectroscopy has been used in a high-risk, high-payoff search for neuronal current (NC) signals in the free induction decay (FID) data from the visual cortex of human subjects during visual stimulation. If successful, this approach could make possible the detection of neuronal currents in the brain at high spatial and temporal resolution. Our initial experiments indicated the presence of a statistically significant change in the FID containing the NC relative to FIDs with the NC absent, and this signal was consistent with the presence of NC. Unfortunately, two follow-on experiments were not able to confirm or replicate the positive findings of the first experiment. However, even if the result from the first experiment were evidence of NC in the FID, it is clear that its effect is so small, that a true NC imaging experiment would not be possible with the current instrumentation and experimental protocol used here.

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Cyanobacteria are oxygenic photosynthetic prokaryotes that are the progenitors of the chloroplasts of algae and plants. These organisms harvest light using large membrane-extrinsic phycobilisome antenna in addition to membrane-bound chlorophyllcontaining proteins. Similar to eukaryotic photosynthetic organisms, cyanobacteria possess thylakoid membranes that house photosystem (PS) I and PSII, which drive the oxidation of water and the reduction of NADP+, respectively. While thylakoid morphology has been studied in some strains of cyanobacteria, the global distribution of PSI and PSII within the thylakoid membrane and the corresponding location of the light-harvesting phycobilisomes are not known in detail, and such information is required to understand the functioning of cyanobacterial photosynthesis on a larger scale. Here, we have addressed this question using a combination of electron microscopy and hyperspectral confocal fluorescence microscopy in wild-type Synechocystis species PCC 6803 and a series of mutants in which phycobilisomes are progressively truncated. We show that as the phycobilisome antenna is diminished, large-scale changes in thylakoid morphology are observed, accompanied by increased physical segregation of the two photosystems. Finally, we quantified the emission intensities originating from the two photosystems in vivo on a per cell basis to show that the PSI:PSII ratio is progressively decreased in the mutants. This results from both an increase in the amount of photosystem II and a decrease in the photosystem I concentration. We propose that these changes are an adaptive strategy that allows cells to balance the light absorption capabilities of photosystems I and II under light-limiting conditions. © 2012 American Society of Plant Biologists. All Rights Reserved.

Ceragenins were used to create biofouling resistant water-treatment membranes. Ceragenins are synthetically produced antimicrobial peptide mimics that display broad-spectrum bactericidal activity. While ceragenins have been used on bio-medical devices, use of ceragenins on water-treatment membranes is novel. Biofouling impacts membrane separation processes for many industrial applications such as desalination, waste-water treatment, oil and gas extraction, and power generation. Biofouling results in a loss of permeate flux and increase in energy use. Creation of biofouling resistant membranes will assist in creation of clean water with lower energy usage and energy with lower water usage. Five methods of attaching three different ceragenin molecules were conducted and tested. Biofouling reduction was observed in the majority of the tests, indicating the ceragenins are a viable solution to biofouling on water treatment membranes. Silane direct attachment appears to be the most promising attachment method if a high concentration of CSA-121a is used. Additional refinement of the attachment methods are needed in order to achieve our goal of several log-reduction in biofilm cell density without impacting the membrane flux. Concurrently, biofilm forming bacteria were isolated from source waters relevant for water treatment: wastewater, agricultural drainage, river water, seawater, and brackish groundwater. These isolates can be used for future testing of methods to control biofouling. Once isolated, the ability of the isolates to grow biofilms was tested with high-throughput multiwell methods. Based on these tests, the following species were selected for further testing in tube reactors and CDC reactors: Pseudomonas ssp. (wastewater, agricultural drainage, and Colorado River water), Nocardia coeliaca or Rhodococcus spp. (wastewater), Pseudomonas fluorescens and Hydrogenophaga palleronii (agricultural drainage), Sulfitobacter donghicola, Rhodococcus fascians, Rhodobacter katedanii, and Paracoccus marcusii (seawater), and Sphingopyxis spp. (groundwater). The testing demonstrated the ability of these isolates to be used for biofouling control testing under laboratory conditions. Biofilm forming bacteria were obtained from all the source water samples.

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Haematococcus pluvialis is a freshwater unicellular green microalga belonging to the class Chlorophyceae and is of commercial interest for its ability to accumulate massive amounts of the red ketocarotenoid astaxanthin (3,3′-dihydroxy-β,β-carotene-4,4′-dione). Using confocal Raman microscopy and multivariate analysis, we demonstrate the ability to spectrally resolve resonance-enhanced Raman signatures associated with astaxanthin and β-carotene along with chlorophyll fluorescence. By mathematically isolating these spectral signatures, in turn, it is possible to locate these species independent of each other in living cells of H. pluvialis in various stages of the life cycle. Chlorophyll emission was found only in the chloroplast whereas astaxanthin was identified within globular and punctate regions of the cytoplasmic space. Moreover, we found evidence for β-carotene to be co-located with both the chloroplast and astaxanthin in the cytosol. These observations imply that β-carotene is a precursor for astaxanthin and the synthesis of astaxanthin occurs outside the chloroplast. Our work demonstrates the broad utility of confocal Raman microscopy to resolve spectral signatures of highly similar chromophores in living cells. © 2011 Collins et al.

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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.

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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Scoping studies have demonstrated that ceragenins, when linked to water-treatment membranes have the potential to create biofouling resistant water-treatment membranes. Ceragenins are synthetically produced molecules that mimic antimicrobial peptides. Evidence includes measurements of CSA-13 prohibiting the growth of and killing planktonic Pseudomonas fluorescens. In addition, imaging of biofilms that were in contact of a ceragenin showed more dead cells relative to live cells than in a biofilm that had not been treated with a ceragenin. This work has demonstrated that ceragenins can be attached to polyamide reverse osmosis (RO) membranes, though work needs to improve the uniformity of the attachment. Finally, methods have been developed to use hyperspectral imaging with multivariate curve resolution to view ceragenins attached to the RO membrane. Future work will be conducted to better attach the ceragenin to the RO membranes and more completely test the biocidal effectiveness of the ceragenins on the membranes.

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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.

Biofouling, the unwanted growth of biofilms on a surface, of water-treatment membranes negatively impacts in desalination and water treatment. With biofouling there is a decrease in permeate production, degradation of permeate water quality, and an increase in energy expenditure due to increased cross-flow pressure needed. To date, a universal successful and cost-effect method for controlling biofouling has not been implemented. The overall goal of the work described in this report was to use high-performance computing to direct polymer, material, and biological research to create the next generation of water-treatment membranes. Both physical (micromixers - UV-curable epoxy traces printed on the surface of a water-treatment membrane that promote chaotic mixing) and chemical (quaternary ammonium groups) modifications of the membranes for the purpose of increasing resistance to biofouling were evaluated. Creation of low-cost, efficient water-treatment membranes helps assure the availability of fresh water for human use, a growing need in both the U. S. and the world.

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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.

Scoping studies have demonstrated that ceragenins, when linked to water-treatment membranes have the potential to create biofouling resistant water-treatment membranes. Ceragenins are synthetically produced molecules that mimic antimicrobial peptides. Evidence includes measurements of CSA-13 prohibiting the growth of and killing planktonic Pseudomonas fluorescens. In addition, imaging of biofilms that were in contact of a ceragenin showed more dead cells relative to live cells than in a biofilm that had not been treated with a ceragenin. This work has demonstrated that ceragenins can be attached to polyamide reverse osmosis (RO) membranes, though work needs to improve the uniformity of the attachment. Finally, methods have been developed to use hyperspectral imaging with multivariate curve resolution to view ceragenins attached to the RO membrane. Future work will be conducted to better attach the ceragenin to the RO membranes and more completely test the biocidal effectiveness of the ceragenins on the membranes.

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The combination of hyperspectral confocal fluorescence microscopy and multivariate curve resolution (MCR) provides an ideal system for improved quantitative imaging when multiple fluorophores are present. However, the presence of multiple noise sources limits the ability of MCR to accurately extract pure-component spectra when there is high spectral and/or spatial overlap between multiple fluorophores. Previously, MCR results were improved by weighting the spectral images for Poisson-distributed noise, but additional noise sources are often present. We have identified and quantified all the major noise sources in hyperspectral fluorescence images. Two primary noise sources were found: Poisson-distributed noise and detector-read noise. We present methods to quantify detector-read noise variance and to empirically determine the electron multiplying CCD (EMCCD) gain factor required to compute the Poisson noise variance. We have found that properly weighting spectral image data to account for both noise sources improved MCR accuracy. In this paper, we demonstrate three weighting schemes applied to a real hyperspectral corn leaf image and to simulated data based upon this same image. MCR applied to both real and simulated hyperspectral images weighted to compensate for the two major noise sources greatly improved the extracted pure emission spectra and their concentrations relative to MCR with either unweighted or Poisson-only weighted data. Thus, properly identifying and accounting for the major noise sources in hyperspectral images can serve to improve the MCR results. These methods are very general and can be applied to the multivariate analysis of spectral images whenever CCD or EMCCD detectors are used. Copyright © 2008 John Wiley & Sons, Ltd.

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Hyperspectral imaging confocal microscopy (HSI-CM) is a powerful tool for the analysis of cellular processes such as the immune response. HSI-CM is a data rich technique that routinely generates two-way data having a spectral domain and an image or concentration domain. Using a variety of modifications to the instrument or experimental protocols, one can readily produce three-way data with HSI-CM. These data are often amenable to trilinear analysis. For example we have used a time series of 18 images acquired during photobleaching of the fluorophores in an effort to identify fluorescence resonance energy transfer (FRET). The resulting images represent intensity as a function of concentration, wavelength and photodegradation in time, to which we apply our techniques of trilinear decomposition. We have successfully employed trilinear decomposition of photobleaching spectral image data from fixed A549 cells transfected with yellow and green fluorescent proteins (YFP and GFP) as molecular probes of cellular proteins involved in the cellular immune response. While useful in the interpretation biological processes, the size of the data generated with the HSI-CM can be difficult to manage computationally. The 208 x 204 x 512 x 18 elements in the image data require careful processing and efficient analysis algorithms. Accordingly, we have implemented fast algorithms that can quickly perform the trilinear decomposition. In this paper we describe how three-way data are produced and the methods we have used to process them. Specifically, we show that co-adding spectra in a spatial neighborhood is a highly effective method for improving the performance of these algorithms without sacrificing resolution. Copyright © 2008 John Wiley & Sons, Ltd.

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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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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.

We have developed a new, high performance, hyperspectral microscope for biological and other applications. For each voxel within a three-dimensional specimen, the microscope simultaneously records the emission spectrum from 500 nm to 800 nm, with better than 3 nm spectral resolution. The microscope features a fully confocal design to ensure high spatial resolution and high quality optical sectioning. Optical throughput and detection efficiency are maximized through the use of a custom prism spectrometer and a backside thinned electron multiplying charge coupled device (EMCCD) array. A custom readout mode and synchronization scheme enable 512-point spectra to be recorded at a rate of 8300 spectra per second. In addition, the EMCCD readout mode eliminates curvature and keystone artifacts that often plague spectral imaging systems. The architecture of the new microscope is described in detail, and hyperspectral images from several specimens are presented.

Hyperspectral imaging provides complex image data with spectral information from many fluorescent species contained within the sample such as the fluorescent labels and cellular or pigment autofluorescence. To maximize the utility of this spectral imaging technique it is necessary to couple hyperspectral imaging with sophisticated multivariate analysis methods to extract meaningful relationships from the overlapped spectra. Many commonly employed multivariate analysis techniques require the identity of the emission spectra of each component to be known or pure component pixels within the image, a condition rarely met in biological samples. Multivariate curve resolution (MCR) has proven extremely useful for analyzing hyperspectral and multispectral images of biological specimens because it can operate with little or no a priori information about the emitting species, making it appropriate for interrogating samples containing autofluorescence and unanticipated contaminating fluorescence. To demonstrate the unique ability of our hyperspectral imaging system coupled with MCR analysis techniques we will analyze hyperspectral images of four-color in-situ hybridized rat brain tissue containing 455 spectral pixels from 550 - 850 nm. Even though there were only four colors imparted onto the tissue in this case, analysis revealed seven fluorescent species, including contributions from cellular autofluorescence and the tissue mounting media. Spectral image analysis will be presented along with a detailed discussion of the origin of the fluorescence and specific illustrations of the adverse effects of ignoring these additional fluorescent species in a traditional microscopy experiment and a hyperspectral imaging system.

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Basic research is needed to better understand the potential risk of dangerous biological agents that are unintentionally or intentionally introduced into a water distribution system. We report on our capabilities to conduct such studies and our preliminary investigations. In 2004, the Biofilms Laboratory was initiated for the purpose of conducting applied research related to biofilms with a focus on application, application testing and system-scale research. Capabilities within the laboratory are the ability to grow biofilms formed from known bacteria or biofilms from drinking water. Biofilms can be grown quickly in drip-flow reactors or under conditions more analogous to drinking-water distribution systems in annular reactors. Biofilms can be assessed through standard microbiological techniques (i .e, aerobic plate counts) or with various visualization techniques including epifluorescent and confocal laser scanning microscopy and confocal fluorescence hyperspectral imaging with multivariate analysis. We have demonstrated the ability to grow reproducible Pseudomonas fluorescens biofilms in the annular reactor with plate counts on the order of 10{sup 5} and 10{sup 6} CFU/cm{sup 2}. Stationary phase growth is typically reached 5 to 10 days after inoculation. We have also conducted a series of pathogen-introduction experiments, where we have observed that both polystyrene microspheres and Bacillus cereus (as a surrogate for B. anthracis) stay incorporated in the biofilms for the duration of our experiments, which lasted as long as 36 days. These results indicated that biofilms may act as a safe harbor for bio-pathogens in drinking water systems, making it difficult to decontaminate the systems.

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