Kathy Ragheb

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.

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.

Investigations of phagosomes, mitochondria, and acidic granules in human neutrophils using fluorescent probes

The oxidative burst is frequently evaluated by the conversion of dihydrorhodamine 123 (DHR) to rhodamine 123 (R123) and hydroethidium (HE) to ethidium with the use of flow cytometry (FCM). Added R123 accumulates in mitochondria, but during phagocytosis R123 originating from DHR has been observed in neutrophil granules. The present study was designed to identify the site of reactive oxygen species (ROS) formation and the intracellular traffic of R123 in neutrophils by using mitochondrial membrane potential probes and the lysosomotropic probe LysoTracker Red, which have not previously been applied to neutrophils. Quiescent and phagocytosing human peripheral blood neutrophils were incubated with DHR, HE, R123, MitoTracker Green (MTG), MitoTracker Red (CMX‐Ros), and LysoTracker Red alone and in all combinations of red and green probes, and studied by FCM and confocal laser scanning microscopy (CLSM). Phagosomes were filled with R123 originating from DHR. Phagocytosis also triggered the oxidative burst in oxidative response granules that differed from acidic granules. All the neutrophils stained with mitochondrial and lysosomotropic dyes. Added R123 and MTG selectively accumulated in mitochondria. Added R123, MTG, and DHR increased the fluorescence of CMX‐Ros and LysoTracker Red. This is the first FCM and CLSM demonstration of ROS formation in phagosomes. A distinct subpopulation of neutrophil granules, termed oxidative response granules, also was identified. Neutrophil mitochondrial membrane potential may be evaluated by incubating the cells with R123 and MTG, but results with CMX‐Ros should be interpreted with caution. HE and DHR seem to measure a common pathway in the oxidative burst. The simultaneous application of several probes for investigations of organelles carries the risk of probe interference. Cytometry Part B (Clin. Cytometry) 51B:21–29, 2003.

Hyperspectral cytometry at the single-cell level using a 32-channel photodetector

Despite recent progress in cell‐analysis technology, rapid classification of cells remains a very difficult task. Among the techniques available, flow cytometry (FCM) is considered especially powerful, because it is able to perform multiparametric analyses of single biological particles at a high flow rate–up to several thousand particles per second. Moreover, FCM is nondestructive, and flow cytometric analysis can be performed on live cells. The current limit for simultaneously detectable fluorescence signals in FCM is around 8–15 depending upon the instrument. Obtaining multiparametric measurements is a very complex task, and the necessity for fluorescence spectral overlap compensation creates a number of additional difficulties to solve. Further, to obtain well‐separated single spectral bands a very complex set of optical filters is required. This study describes the key components and principles involved in building a next‐generation flow cytometer based on a 32‐channel PMT array detector, a phase‐volume holographic grating, and a fast electronic board. The system is capable of full‐spectral data collection and spectral analysis at the single‐cell level. As demonstrated using fluorescent microspheres and lymphocytes labeled with a cocktail of antibodies (CD45/FITC, CD4/PE, CD8/ECD, and CD3/Cy5), the presented technology is able to simultaneously collect 32 narrow bands of fluorescence from single particles flowing across the laser beam in <5 μs. These 32 discrete values provide a proxy of the full fluorescence emission spectrum for each single particle (cell). Advanced statistical analysis has then been performed to separate the various clusters of lymphocytes. The average spectrum computed for each cluster has been used to characterize the corresponding combination of antibodies, and thus identify the various lymphocytes subsets. The powerful data‐collection capabilities of this flow cytometer open up significant opportunities for advanced analytical approaches, including spectral unmixing and unsupervised or supervised classification.

High speed classification of individual bacterial cells using a model-based light scatter system and multivariate statistics

We describe a model-based instrument design combined with a statistical classification approach for the development and realization of high speed cell classification systems based on light scatter. In our work, angular light scatter from cells of four bacterial species of interest, Bacillus subtilis, Escherichia coli, Listeria innocua, and Enterococcus faecalis, was modeled using the discrete dipole approximation. We then optimized a scattering detector array design subject to some hardware constraints, configured the instrument, and gathered experimental data from the relevant bacterial cells. Using these models and experiments, it is shown that optimization using a nominal bacteria model (i.e., using a representative size and refractive index) is insufficient for classification of most bacteria in realistic applications. Hence the computational predictions were constituted in the form of scattering-data-vector distributions that accounted for expected variability in the physical properties between individual bacteria within the four species. After the detectors were optimized using the numerical results, they were used to measure scatter from both the known control samples and unknown bacterial cells. A multivariate statistical method based on a support vector machine (SVM) was used to classify the bacteria species based on light scatter signatures. In our final instrument, we realized correct classification of B. subtilis in the presence of E. coli,L. innocua, and E. faecalis using SVM at 99.1%, 99.6%, and 98.5%, respectively, in the optimal detector array configuration. For comparison, the corresponding values for another set of angles were only 69.9%, 71.7%, and 70.2% using SVM, and more importantly, this improved performance is consistent with classification predictions.

High-Throughput Secondary Screening at the Single-Cell Level

We have developed an automated system for drug screening using a single-cell–multiple functional response technology. The approach uses a semiautomated preparatory system, high-speed sample collection, and a unique analytical tool that provides instantaneous results for compound dilutions using 384-well plates. The combination of automation and rapid robotic sampling increases quality control and robustness. High-speed flow cytometry is used to collect single-cell results together with a newly defined analytical tool for extraction of IC50 curves for multiple assays per cell. The principal advantage is the extreme speed of sample collection, with results from a 384-well plate being completed for both collection and data processing in less than 10 min. Using this approach, it is possible to extract detailed drug response information in a highly controlled fashion. The data are based on single-cell results, not populations. With simultaneous assays for different functions, it is possible to gain a more detailed understanding of each drug/compound interaction. Combined with integrated advanced data processing directly from raw data files, the process from sampling to analytical results is highly intuitive. Direct PubMed links allow review of drug structure and comparisons with similar compounds.

Measurement and analysis of angle-resolved scatter from small particles in a cylindrical microchannel

Scatter of a two-dimensional Gaussian beam of a rectangular cross section by individual particles suspended in a fluid in a cylindrical channel is modeled by using a full-wave approach. First, the internal and scattered fields associated with the cylindrical channel and the two-dimensional Gaussian beam are computed. The spatial variations of the computed electromagnetic field inside the channel indicate that particles and cells of sizes relevant to flow cytometry are subjected to essentially plane-wave illumination, and hence Lorenz-Mie theory is applicable for spherical particles. Further, it is assumed that the perturbation of the electromagnetic field in the channel that is due to the presence of a particle is negligible, allowing us to ignore the interactive scatter of the particle and the channel (they are electromagnetically uncoupled). This approximation is valid when the particle intercepts a small fraction of the total energy inside the channel and when the particle or cell has a low relative refractive index. Measurements of scatter from the channel agree with the analytical model and are used to determine the location of detectors to measure scatter from particles in the channel. Experimental results of accumulated scatter from single latex spheres flowing in the channel show good agreement with computed results, thereby validating the internal field and uncoupled scatter models.

Alternatives to current flow cytometry data analysis for clinical and research studies

Flow cytometry has well-established methods for data analysis based on traditional data collection techniques. These techniques typically involved manual insertion of tube samples into an instrument that, historically, could only measure 1-3 colors. The field has since evolved to incorporate new technologies for faster and highly automated sample preparation and data collection. For example, the use of microwell plates on benchtop instruments is now a standard on virtually every new instrument, and so users can easily accumulate multiple data sets quickly. Further, because the user must carefully define the layout of the plate, this information is already defined when considering the analytical process, expanding the opportunities for automated analysis. Advances in multi-parametric data collection, as demonstrated by the development of hyperspectral flow-cytometry, 20-40 color polychromatic flow cytometry, and mass cytometry (CyTOF), are game-changing. As data and assay complexity increase, so too does the complexity of data analysis. Complex data analysis is already a challenge to traditional flow cytometry software. New methods for reviewing large and complex data sets can provide rapid insight into processes difficult to define without more advanced analytical tools. In settings such as clinical labs where rapid and accurate data analysis is a priority, rapid, efficient and intuitive software is needed. This paper outlines opportunities for analysis of complex data sets using examples of multiplexed bead-based assays, drug screens and cell cycle analysis - any of which could become integrated into the clinical environment.

Automated classification and recognition of bacterial particles in flow by multi-angle scatter measurement and a support-vector machine classifier

Biological microparticles 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 at two nominal angles (2°⩽θ1⩽20° and 70°⩽θ2⩽110°) of scattered light intensity from individual microparticles with a speed varying from 10 to 10000 particles per second. The choice of angle is dictated by the fact that scattered light in the small-angle region is primarily influenced by cell size and refractive index, whereas side scatter intensity is related to the granularity of cellular structures. These rudimentary measurements cannot be used to separate populations of cells of similar shape, size, or structure. Hence, there have been several attempts in cytometry to measure the entire scatter patterns. However, the published concepts required use of unique custom-built cytometers and could not be applied to existing instruments. 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. Our approach can be used with existing instruments and requires only the addition of a custom-built scatter-detector. Our analytical model of scatter of laser beams by individual bacterial cells suspended in a fluid was used to determine the location for scatter sensors. Experimental results were used to train the pattern recognition system. It has been shown that information provided just by six scatter-related parameters was sufficient to recognize various bacteria with 90-99% success rate.