J. Paul Robinson

Current Protocols in Cytometry

Current Protocols in Cytometry (CPC), published in affiliation with the International Society for Analytical Cytology, features carefully edited flow and image cytometry methods provided by leading laboratories from around the world. All methods included in the one-volume looseleaf manual are rigorously tested and proven before being selected for CPC. Carefully edited, step-by-step protocols replete with material lists, expert commentaries, and safety and troubleshooting tips ensure that you can duplicate the experimental results in your own laboratory. This publication also includes extensive coverage of cytometry instrumentation, safety and quality control, and data processing and analysis. Quarterly updates, which are filed into the looseleaf, keep the set current with the latest developments in cytometry methods. The initial purchase includes one year of updates and then subscribers may renew their annual subscriptions. Current Protocols publishes a family of laboratory manuals for bioscientists, including Molecular Biology, Immunology, Human Genetics, Protein Science, Cell Biology, Neuroscience, Pharmacology, and Toxicology.

Label-free detection of multiple bacterial pathogens using light-scattering sensor

Technologies for rapid detection and classification of bacterial pathogens are crucial for securing the food supply. This report describes a light-scattering sensor capable of real-time detection and identification of colonies of multiple pathogens without the need for a labeling reagent or biochemical processing. Bacterial colonies consisting of the progeny of a single parent cell scatter light at 635 nm to produce unique forward-scatter signatures. Zernike moment invariants and Haralick descriptors aid in feature extraction and construction of the scatter-signature image library. The method is able to distinguish bacterial cultures at the genus and species level for Listeria, Staphylococcus, Salmonella, Vibrio, and Escherichia with an accuracy of 90-99% for samples derived from food or experimentally infected animal. Varied amounts of exopolysaccharide produced by the bacteria causes changes in phase modulation distributions, resulting in strikingly different scatter signatures. With the aid of a robust database the method can potentially detect and identify any bacteria colony essentially instantaneously. Unlike other methods, it does not destroy the sample, but leaves it intact for other confirmatory testing, if needed, for forensic or outbreak investigations.

DPI induces mitochondrial superoxide-mediated apoptosis

The iodonium compounds diphenyleneiodonium (DPI) and diphenyliodonium (IDP) are well-known phagocyte NAD(P)H oxidase inhibitors. However, it has been shown that at high concentrations they can inhibit the mitochondrial respiratory chain as well. Since inhibition of the mitochondrial respiratory chain has been shown to induce superoxide production and apoptosis, we investigated the effect of iodonium compounds on mitochondria-derived superoxide and apoptosis. Mitochondrial superoxide production was measured on both cultured cells and isolated rat-heart submitochondrial particles. Mitochondria function was examined by monitoring mitochondrial membrane potential. Apoptotic pathways were studied by measuring cytochrome c release and caspase 3 activation. Apoptosis was characterized by detecting DNA fragmentation on agarose gel and measuring propidium iodide- (PI-) stained subdiploid cells using flow cytometry. Our results showed that DPI could induce mitochondrial superoxide production. The same concentration of DPI induced apoptosis by decreasing mitochondrial membrane potential and releasing cytochrome c. Addition of antioxidants or overexpression of MnSOD significantly reduced DPI-induced mitochondrial damage, cytochrome c release, caspase activation, and apoptosis. These observations suggest that DPI can induce apoptosis via induction of mitochondrial superoxide. DPI-induced mitochondrial superoxide production may prove to be a useful model to study the signaling pathways of mitochondrial superoxide.

Acrolein-induced cell death in PC12 cells: role of mitochondria-mediated oxidative stress.

Oxidative stress has been implicated in acrolein cytotoxicity in various cell types, including mammalian spinal cord tissue. In this study we report that acrolein also decreases PC12 cell viability in a reactive oxygen species (ROS)-dependent manner. Specifically, acrolein-induced cell death, mainly necrosis, is accompanied by the accumulation of cellular ROS. Elevating ROS scavengers can alleviate acrolein-induced cell death. Furthermore, we show that exposure to acrolein leads to mitochondrial dysfunction, denoted by the loss of mitochondrial transmembrane potential, reduction of cellular oxygen consumption, and decrease of ATP level. This raises the possibility that the cellular accumulation of ROS could result from the increased production of ROS in the mitochondria of PC12 cells as a result of exposure to acrolein. The acrolein-induced significant decrease of ATP production in mitochondria may also explain why necrosis, not apoptosis, is the dominant type of cell death. In conclusion, our data suggest that one possible mechanism of acrolein-induced cell death could be through mitochondria as its initial target. The subsequent increase of ROS then inflicts cell death and further worsens mitochondria function. Such mechanism may play an important role in CNS trauma and neurodegenerative diseases.

Intracellularly grown gold nanoparticles as potential surface-enhanced Raman scattering probes

Gold nanoparticles grown within the intracellular confines of living cells are introduced as potential surface-enhanced Raman scattering (SERS) substrates for confocal Raman spectrometry. Electron microscopy and a silver-enhanced reflectance laser scanning confocal microscopic approach were used to visualize the size, shape, and distribution of intracellularly grown gold nanoparticles (IGAuN) as small as 1 nm. Passive uptake as the conventional approach for delivering nanoparticles inside cells faces the insurmountable challenge of escaping the endosomal/lysosomal pathway. In contrast, IGAuN provides an unprecedented advantage of providing access to cytoplasm and nucleus.

On-the-fly decoding luminescence lifetimes in the microsecond region for lanthanide-encoded suspension arrays

Significant multiplexing capacity of optical time-domain coding has been recently demonstrated by tuning luminescence lifetimes of the upconversion nanoparticles called ‘τ-Dots’. It provides a large dynamic range of lifetimes from microseconds to milliseconds, which allows creating large libraries of nanotags/microcarriers. However, a robust approach is required to rapidly and accurately measure the luminescence lifetimes from the relatively slow-decaying signals. Here we show a fast algorithm suitable for the microsecond region with precision closely approaching the theoretical limit and compatible with the rapid scanning cytometry technique. We exploit this approach to further extend optical time-domain multiplexing to the downconversion luminescence, using luminescence microspheres wherein lifetimes are tuned through luminescence resonance energy transfer. We demonstrate real-time discrimination of these microspheres in the rapid scanning cytometry, and apply them to the multiplexed probing of pathogen DNA strands. Our results indicate that tunable luminescence lifetimes have considerable potential in high-throughput analytical sciences.

Feature extraction from light-scatter patterns of Listeria colonies for identification and classification

Bacterial contamination by Listeria monocytogenes not only puts the public at risk, but also is costly for the food-processing industry. Traditional biochemical methods for pathogen identification require complicated sample preparation for reliable results. Optical scattering technology has been used for identification of bacterial cells in suspension, but with only limited success. Therefore, to improve the efficacy of the identification process using our novel imaging approach, we analyze bacterial colonies grown on solid surfaces. The work presented here demonstrates an application of computer-vision and pattern-recognition techniques to classify scatter patterns formed by Listeria colonies. Bacterial colonies are analyzed with a laser scatterometer. Features of circular scatter patterns formed by bacterial colonies illuminated by laser light are characterized using Zernike moment invariants. Principal component analysis and hierarchical clustering are performed on the results of feature extraction. Classification using linear discriminant analysis, partial least squares, and neural networks is capable of separating different strains of Listeria with a low error rate. The demonstrated system is also able to determine automatically the pathogenicity of bacteria on the basis of colony scatter patterns. We conclude that the obtained results are encouraging, and strongly suggest the feasibility of image-based biodetection systems.

Biophysical modeling of forward scattering from bacterial colonies using scalar diffraction theory

A model for forward scattering from bacterial colonies is presented. The colonies of interest consist of approximately 10(12) - 10(13) individual bacteria densely packed in a configuration several millimeters in diameter and approximately 0.1-0.2 mm in thickness. The model is based on scalar diffraction theory and accounts for amplitude and phase modulation created by three macroscopic properties of the colonies: phase modulation due to the surface topography, phase modulation due to the radial structure observed from some strains and species, and diffraction from the outline of the colony. Phase contrast and confocal microscopy were performed to provide quantitative information on the shape and internal structure of the colonies. The computed results showed excellent agreement with the experimental scattering data for three different Listeria species: Listeria innocua, Listeria ivanovii, and Listeria monocytogenes. The results provide a physical explanation for the unique and distinctive scattering signatures produced by colonies of closely related Listeria species and support the efficacy of forward scattering for rapid detection and classification of pathogens without tagging.

Automated classification of bacterial particles in flow by multiangle scatter measurement and support vector machine classifier

Biological microparticles, including bacteria, scatter light in all directions when illuminated. The complex scatter pattern is dependent on particle size, shape, refraction index, density, and morphology. Commercial flow cytometers allow measurement of scattered light intensity at forward and perpendicular (side) angles (2° ≤ θ1 ≤ 20° and 70° ≤ θ2 ≤ 110°, respectively) with a speed varying from 10 to 10,000 particles per second. The choice of angle is dictated by the fact that scattered light in the forward region is primarily dependent on cell size and refractive index, whereas side‐scatter intensity is dependent on the granularity of cellular structures. However, these two‐parameter measurements cannot be used to separate populations of cells of similar shape, size, or structure. Hence, there have been several attempts in flow cytometry to measure the entire scatter patterns. The published concepts require the use of unique custom‐built flow cytometers and cannot be applied to existing instruments. It was also not clear how much information about patterns is really necessary to separate various populations of cells present in a given sample. The presented work demonstrates application of pattern‐recognition techniques to classify particles on the basis of their discrete scatter patterns collected at just five different angles, and accompanied by the measurement of axial light loss. The proposed approach can be potentially used with existing instruments because it requires only the addition of a compact enhanced scatter detector. An analytical model of scatter of laser beams by individual bacterial cells suspended in a fluid was used to determine the location of scatter sensors. Experimental results were used to train the support vector machine‐based pattern recognition system. It has been shown that information provided just by five angles of scatter and axial light loss can be sufficient to recognize various bacteria with 68–99% success rate.

Isolation of two populations of myoblasts from porcine skeletal muscle

Studies on the effects of time and passage on porcine primary muscle cell cultures and methods to purify myoblasts were conducted using flow cytometry and fluorescence‐activated cell sorting (FACS). Primary muscle cells cultured on single plates revealed a small cell (<10 mm diameter) population consisting of 90% desmin‐positive myoblasts and a large cell (≥10 mm diameter) population containing desmin‐positive myoblasts and nonmyoblasts. The small myoblasts were detectable up to 28 days but after cell sorting and passage, they became indistinguishable from the large myoblast population. This indicates that pig muscle contains small self‐renewing myoblasts similar to humans, that become larger when induced to proliferate. A human myoblast‐specific monoclonal antibody allows FACS of both large and small myoblasts from primary cells within 2 days of culture and independent of passage. These characteristics of porcine myoblasts indicate that the pig may be a suitable large animal model for myoblast‐mediated gene transfer.