Matthew L. Clarke

Low-cost, high-throughput, automated counting of bacterial colonies.

Research involving bacterial pathogens often requires enumeration of bacteria colonies. Here, we present a low‐cost, high‐throughput colony counting system consisting of colony counting software and a consumer‐grade digital camera or document scanner. We demonstrate that this software, called “NICE” (NISTs Integrated Colony Enumerator), can count bacterial colonies as part of a high‐throughput multiplexed opsonophagocytic killing assay used to characterize pneumococcal vaccine efficacy. The results obtained with NICE correlate well with the results obtained from manual counting, with a mean difference of less than 3%. NICE is also rapid; it can count colonies from multiple reaction wells within minutes and export the results to a spreadsheet for data processing. As this program is freely available from NIST, NICE should be helpful in bacteria colony enumeration required in many microbiological studies, and in standardizing colony counting methods. Published 2010 Wiley‐Liss, Inc.

Quantitative Characterization of Quantum Dot-Labeled Lambda Phage for Escherichia coli Detection

We characterize CdSe/ZnS quantum dot (QD) binding to genetically modified bacteriophage as a model for bacterial detection. Interactions among QDs, lambda (λ) phage, and Escherichia coli are examined by several cross‐validated methods. Flow and image‐based cytometry clarify fluorescent labeling of bacteria, with image‐based cytometry additionally reporting the number of decorated phage bound to cells. Transmission electron microscopy, image‐based cytometry, and electrospray differential mobility analysis allow quantization of QDs attached to each phage (4–17 QDs) and show that λ phage used in this study exhibits enhanced QD binding to the capsid by nearly a factor of four compared to bacteriophage T7. Additionally, the characterization methodology presented can be applied to the quantitative characterization of other fluorescent nanocrystal‐biological conjugates. Biotechnol. Bioeng. 2009;104: 1059–1067. Published 2009 Wiley Periodicals, Inc.

Absorption-Based Hyperspectral Imaging and Analysis of Single Erythrocytes

We report an absorption-based hyperspectral imaging and analysis technique to resolve unique physicochemical characteristics of subcellular substances in single erythrocytes. We constructed a microscope system installed with a spectral light engine capable of controlling the spectral shape of the illumination light by a digital micromirror device. The hyperspectral imaging system and the sequential maximum angle convex cone algorithm allow us to extract unique spectral signatures (i.e., endmembers) for different types of hemoglobin, such as oxyhemoglobin, methemoglobin, and hemozoin, and scatter from cell membrane in single erythrocytes. Further statistical endmember analysis, conducted on the hyperspectral image data, provides the abundances of specific endmembers, which can be used to build intracellular maps of the distribution of substances of interest. In addition, we perform modeling based on Mie theory to explain the scattering signatures as a function of scattering angle. The developed imaging and analysis technique enables label-free molecular imaging of endogenous biomarkers in single erythrocytes in order to build oxymetric standards on a cellular level and ultimately for in vivo as well.

Water-soluble DNA-wrapped single-walled carbon-nanotube/quantum-dot complexes.

In recent years, carbon nanotubes (CNTs), especially singlewalled carbon nanotubes (SWCNTs), have attracted much attention due to their unique properties and potential towards broad real-world applications. The integration of SWCNTs with other unique nanoscale luminescent materials, such as quantum dots (QDs), has enabled the manufacture of many novel nanocomposite materials with enhanced structural, mechanical, optical, and chemical properties. The performance of these composite materials strongly depends upon the properties of the individual components and additives as well as the conjugation chemistry required to assemble them into composite hybrids. Therefore, a variety of new techniques have been developed to modify the optical, mechanical, chemical, and electrical properties of SWCNTs to control the properties of the final composite materials. Among the additives to SWCNT-based composites, novel nanoparticles (NPs) have been increasingly employed. Functionalized NPs can be designed to covalently bind to the functional groups expressed on the sidewalls or ends of

Structural analysis of soft multicomponent nanoparticle clusters

Quantitative techniques are essential to analyze the structure of soft multicomponent nanobioclusters. Here, we combine electrospray differential mobility analysis (ES-DMA), which rapidly measures the size of the entire cluster, with transmission electron microscopy (TEM), which detects the hard components, to determine the presence and composition of the softer components. Coupling analysis of TEM and ES-DMA derived data requires the creation and use of analytical models to determine the size and number of constituents in nanoparticle complexes from the difference between the two measurements. Previous ES-DMA analyses have been limited to clusters of identical spherical particles. Here, we dramatically extend the ES-DMA analysis framework to accommodate more challenging geometries, including protein corona-coated nanorods, clusters composed of heterogeneously sized nanospheres, and nanobioclusters composed of both nanospheres and nanorods. The latter is critical to determining the number of quantum dots attached to lambda (λ) phage, a key element of a rapid method to detect bacterial pathogens in environmental and clinical samples.

Probing dynamic fluorescence properties of single and clustered quantum dots toward quantitative biomedical imaging of cells.

We present results on the dynamic fluorescence properties of bioconjugated nanocrystals or quantum dots (QDs) in different chemical and physical environments. A variety of QD samples was prepared and compared: isolated individual QDs, QD aggregates, and QDs conjugated to other nanoscale materials, such as single-wall carbon nanotubes (SWCNTs) and human erythrocyte plasma membrane proteins. We discuss plausible scenarios to explain the results obtained for the fluorescence characteristics of QDs in these samples, especially for the excitation time-dependent fluorescence emission from clustered QDs. We also qualitatively demonstrate enhanced fluorescence emission signals from clustered QDs and deduce that the band 3 membrane proteins in erythrocytes are clustered. This approach is promising for the development of QD-based quantitative molecular imaging techniques for biomedical studies involving biomolecule clustering.

Multimodal, nanoscale, hyperspectral imaging demonstrated on heterostructures of quantum dots and DNA-wrapped single-wall carbon nanotubes.

A multimodality imaging technique integrating atomic force, polarized Raman, and fluorescence lifetime microscopies, together with 2D autocorrelation image analysis is applied to the study of a mesoscopic heterostructure of nanoscale materials. This approach enables simultaneous measurement of fluorescence emission and Raman shifts from a quantum dot (QD)-single-wall carbon nanotube (SWCNT) complex. Nanoscale physical and optoelectronic characteristics are observed including local QD concentrations, orientation-dependent polarization anisotropy of the SWCNT Raman intensities, and charge transfer from photoexcited QDs to covalently conjugated SWCNTs. Our measurement approach bridges the properties observed in bulk and single nanotube studies. This methodology provides fundamental understanding of the charge and energy transfer between nanoscale materials in an assembly.

Algorithm validation using multicolor phantoms.

We present a framework for hyperspectral image (HSI) analysis validation, specifically abundance fraction estimation based on HSI measurements of water soluble dye mixtures printed on microarray chips. In our work we focus on the performance of two algorithms, the Least Absolute Shrinkage and Selection Operator (LASSO) and the Spatial LASSO (SPLASSO). The LASSO is a well known statistical method for simultaneously performing model estimation and variable selection. In the context of estimating abundance fractions in a HSI scene, the “sparse” representations provided by the LASSO are appropriate as not every pixel will be expected to contain every endmember. The SPLASSO is a novel approach we introduce here for HSI analysis which takes the framework of the LASSO algorithm a step further and incorporates the rich spatial information which is available in HSI to further improve the estimates of abundance. In our work here we introduce the dye mixture platform as a new benchmark data set for hyperspectral biomedical image processing and show our algorithm’s improvement over the standard LASSO.

Characterization of hyperspectral imaging and analysis via microarray printing of dyes

The application of hyperspectral imaging requires rigorous characterization of the spatial and spectral imaging domains of the system. We present a microarray printing methodology for the testing of absorption or reflectance microscopy measurements. This controlled system can serve as a platform for inter-system calibration and provides a common framework for the development of post-processing algorithms. Calibration of the illumination at the objective plane using a transfer standard spectroradiometer allows comparison of light levels regardless of the illumination used, different apertures, and different microscopes. The method uses standard commercial optomechanical components. Printed dyes enable multiplexed testing of the spectral capability of a hyperspectral instrument. The spectral signatures of individual or blended dyes can be analyzed and applied to the testing of spectral image processing tools. Customized programming of the microarrayer allows for arbitrary patterning of dye samples onto the substrate, allowing for the testing of image processing algorithms involving the spatial distribution of spectral features.

Designing microarray phantoms for hyperspectral imaging validation

The design and fabrication of custom-tailored microarrays for use as phantoms in the characterization of hyperspectral imaging systems is described. Corresponding analysis methods for biologically relevant samples are also discussed. An image-based phantom design was used to program a microarrayer robot to print prescribed mixtures of dyes onto microscope slides. The resulting arrays were imaged by a hyperspectral imaging microscope. The shape of the spots results in significant scattering signals, which can be used to test image analysis algorithms. Separation of the scattering signals allowed elucidation of individual dye spectra. In addition, spectral fitting of the absorbance spectra of complex dye mixtures was performed in order to determine local dye concentrations. Such microarray phantoms provide a robust testing platform for comparisons of hyperspectral imaging acquisition and analysis methods.