Publications

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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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Multivariate curve resolution (MCR) using constrained alternating least squares algorithms represents a powerful analysis capability for the quantitative analysis of hyperspectral image data. We will demonstrate the application of MCR using data from a new hyperspectral fluorescence imaging microarray scanner for monitoring gene expression in cells from thousands of genes on the array. The new scanner collects the entire fluorescence spectrum from each pixel of the scanned microarray. Application of MCR with nonnegativity and equality constraints reveals several sources of undesired fluorescence that emit in the same wavelength range as the reporter fluorophores. MCR analysis of the hyperspectral images confirms that one of the sources of fluorescence is due to contaminant fluorescence under the printed DNA spots that is spot localized. Thus, traditional background subtraction methods used with data collected from the current commercial microarray scanners will lead to errors in determining the relative expression of low-expressed genes. With the new scanner and MCR analysis, we generate relative concentration maps of the background, impurity, and fluorescent labels over the entire image. Since the concentration maps of the fluorescent labels are relatively unaffected by the presence of background and impurity emissions, the accuracy and useful dynamic range of the gene expression data are both greatly improved over those obtained by commercial microarray scanners.

We describe the design, construction, and operation of a hyperspectral microarray scanner for functional genomic research. The hyperspectral instrument operates with spatial resolutions ranging from 3 to 30 {micro}m and records the emission spectrum between 490 and 900 nm with a spectral resolution of 3 nm for each pixel of the microarray. This spectral information, when coupled with multivariate data analysis techniques, allows for identification and elimination of unwanted artifacts and greatly improves the accuracy of microarray experiments. Microarray results presented in this study clearly demonstrate the separation of fluorescent label emission from the spectrally overlapping emission due to the underlying glass substrate. We also demonstrate separation of the emission due to green fluorescent protein expressed by yeast cells from the spectrally overlapping autofluorescence of the yeast cells and the growth media.