Hyperlog-a flexible log-like transform for negative, zero, and positive valued data.

BACKGROUND: The remarkable success of cytometry over the past 30 years is largely due to its uncanny ability to display populations that vastly differ in numbers and fluorescence intensities on one scale. The log transform implemented in hardware as a log amplifier or in software normalizes signals or channels so that these populations appear as clearly discernible peaks. With the advent of multiple fluorescence cytometry, spectral crossover compensation of these signals has been necessary to properly interpret the data. Unfortunately, because compensation is a subtractive process, it can produce negative and zero valued data. The log transform is undefined for these values and, as a result, forces computer algorithms to truncate these values, creating a few problems for cytometrists. Data truncation biases displays making properly compensated data appear undercompensated; thus, enticing many operators to overcompensate their data. Also, events truncated into the first histogram channel are not normally visible with typical two-dimensional graphic displays, thus hiding a large number of events and obscuring the true proportionality of negative distributions. In addition, the log transform creates unequal binning that can dramatically distort negative population distributions. METHODS AND RESULTS: The HyperLog transform is a log-like transform that admits negative, zero, and positive values. The transform is a hybrid type of transform specifically designed for compensated data. One of its parameters allows it to smoothly transition from a logarithmic to linear type of transform that is ideal for compensated data. CONCLUSIONS: The HyperLog transform is easily implemented in computer systems and results in display systems that present compensated data in an unbiased manner.     

Determination of linear fluorescence intensities from flow cytometric data accumulated with logarithmic amplifiers

Logarithmic amplifiers are useful in accumulating flow cytometric data with a large dynamic range. However, quantitative comparison of fluorescence intensities for different samples or different subpopulations within a sample is simplified by the conversion of data from log space back to linear space. A method is described in which fluorescent polystyrene spheres of differing intensities are used to construct a calibration curve for the logarithmic intensity scale. This allows calculation of relative linear intensity for each channel of the logarithmically accumulated data and determination of linear fluorescence means and coefficients of variation for comparative purposes. Fluorescent spheres of appropriate intensity may also be used as internal standards to monitor instrument and/or stain stability for samples accumulated using logarithmic amplifiers.     

Optimizing transformations for automated,high throughput analysis of flow cytometry data

Background  

In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations.     

Conversion of linear histogram flow cytometry data to a logarithmic display

A routine is described that readily allows the rescaling of linear histographic data to a corresponding logarithmic histogram. This procedure significantly improves data display, particularly where a wide range in the measured parameter is encountered. The logarithmic scale displays peaks with band widths more proportional to their respective coefficients of variation than is the case in a linear display. Rescaling several linear histograms to a common logarithmic scale allows the combination of these linear data even though the linear ranges are different. This routine is presented as a program written in BASIC for execution on a microcomputer.     

Increased light scattering resolution facilitates multidimensional flow cytometric analysis

Multidimensional flow cytometry identifies cell populations as clusters in a space created by the analysis of multiple parameters simultaneously. Optimal use of this multidimensional space requires each of the individual parameters to provide additional information for cell population discrimination as well as maximum utilization of the dynamic range available for each parameter. In this study we improve the visualization of the information present in light scattering signals from leukocytes to facilitate multidimensional flow cytometric analysis. Optimization of cell preparation techniques are essential to obtain high resolution light scattering signals that give complete separation of the granulocytes, monocytes, and granular and nongranular lymphocytes. The angle at which the forward scattered light was collected was modified to enhance the separation between leukocyte populations. Although orthogonal light scattering signals separate granular and nongranular lymphocytes, the resolution and dynamic range could not be displayed using linear or logarithmic functions. By applying a polynomial function to the orthogonal light scattering signals, all leukocyte populations could be displayed while maintaining high resolution. The combination of high resolution light scattering with a nonlinear display resulted in an equally spaced distribution of the cell populations distinguished by correlating forward and orthogonal light scattering signals. Using this approach, peripheral blood neutrophils, eosinophils, basophils, monocytes, and granular and nongranular lymphocytes were shown to occupy distinct locations in the correlation of orthogonal and forward light scattering. Surprisingly, the basophilic granulocytes were located close to granular lymphocytes and monocytes rather than near neutrophils and eosinophils.     

Multi-user system for analysis of data from flow cytometry.

A new program is described for the analysis of DNA histograms from flow cytometry. The fundamental model representing the cell population is similar to one described previously. It assumes the population is grouped into compartments, each consisting of cells having approximately the same DNA content. After staining the cells with an appropriate fluorochrome, the fluorescence distribution of cells within each compartment is assumed to be Gaussian. In the present algorithm, the parameters of the model can either be computed directly by the program from the data, or can be specified as input by the user. When synchronous cell populations lacking distinct G1 and G2/M phases are analyzed, the parameter values must first be obtained using an appropriate control. Percentages of cells in the various compartments are computed using a gradient search method described by Bevington.     

Optimization of flow-cytometric discrimination between reticulocytes and erythrocytes

An automatized technique to count reticulocytes by means of flow cytometry is described. Blood samples were stained by the fluorescent dye acridine orange without the use of fixative. Scatter and red fluorescence of the blood cells were measured in a flow cytometer. A discrimination between reticulocytes and erythrocytes was only achieved by using logarithmic amplification. The discrimination was better in peak mode than in area mode. The optimum dye concentration was 0.5 mg/liter acridine orange. At lower dye concentrations, not all reticulocytes were measured, whereas at higher dye concentrations the degree of discrimination between reticulocytes and erythrocytes decreased. There was a suitable discrimination between reticulocytes and erythrocytes. The reticulocyte numbers were scored by flow cytometry as well as by microscope for blood samples with 0.1-14% reticulocytes. The correlation between both methods was close.     

Fluorescence as an alternative to light-scatter gating strategies to identify frozen–thawed cells with flow cytometry

Flow cytometry is a key instrument in biological studies, used to identify and analyze cells in suspension. The identification of cells from debris is commonly based on light scatter properties as it has been shown that there is a relationship between forward scattered light and cell volume and this has become common practice in flow cytometry. Cryobiological conditions induce changes in cells that alter their light scatter properties. Cells with membrane damage from freeze–thaw stress produce lower forward scatter signals and may fall below standard forward scatter thresholds. In contrast to light scatter properties that cannot identify damaged cells from debris, fluorescent dyes used in membrane integrity and mitochondrial polarization assays are capable of labeling and discriminating all cells in suspension. Under cryobiological conditions, isolating cell populations is more effectively accomplished by gating on fluorescence rather than light scatter properties. This study shows the limitations of using forward scatter thresholds in flow cytometry to identify and gate cells after exposure to a freeze–thaw protocol and demonstrates the use of fluorescence as an alternative means of identifying and analyzing cells.     

Combination of quantification and observation methods for study of "Side Population" cells in their "in vitro" microenvironment.

BACKGROUND: Qualitative and quantitative analyses of the rare phenotypic variants in in vitro culture systems is necessary for the understanding of cell differentiation in cell culture of primary cells or cell lines. Slide-based cytometry combines image acquisition and data treatment, and associates the power of flow cytometry (FCM) and the resolution of the microscopic studies making it suitable for the analysis of cells with rare phenotype. In this paper we develop a method that applies these principles to a particularly hot problem in cell biology, the study of stem cell like cells in cultures of primary cells, cancer cells, and various cell lines. METHODS: The adherent cells were labeled by the fluorescent dye Hoechst 33342. The images of cell populations were collected by a two-photon microscope and processed by a software developed by us. The software allows the automated segmentation of the nuclei in a very dense cell environment, the measurement of the fluorescence intensity of each nucleus and the recording of their position in the plate. The cells with a given fluorescence intensity can then be located easily on the recorded image of the culture plate for further analysis. RESULTS: The potential of our method is illustrated by the identification and localization of SP cells in the cultures of the C2C12 cell line. Although these cells represent only about 1% of the total population as calculated by flow cytometry, they can be identified in the culture plate with high precision by microscopy. CONCLUSION: Cells with the rare stem-cell like phenotype can be efficiently identified in the undisturbed cultures. Since the fluorescence intensity of rare events and the position of thousands of surrounding cells are recorded at the same time, the method associates the advantage of the FCM analysis and the microscopic observation.     

Stochastic Measurement Models for Quantifying Lymphocyte Responses Using Flow Cytometry

Adaptive immune responses are complex dynamic processes whereby B and T cells undergo division and differentiation triggered by pathogenic stimuli. Deregulation of the response can lead to severe consequences for the host organism ranging from immune deficiencies to autoimmunity. Tracking cell division and differentiation by flow cytometry using fluorescent probes is a major method for measuring progression of lymphocyte responses, both in vitro and in vivo. In turn, mathematical modeling of cell numbers derived from such measurements has led to significant biological discoveries, and plays an increasingly important role in lymphocyte research. Fitting an appropriate parameterized model to such data is the goal of these studies but significant challenges are presented by the variability in measurements. This variation results from the sum of experimental noise and intrinsic probabilistic differences in cells and is difficult to characterize analytically. Current model fitting methods adopt different simplifying assumptions to describe the distribution of such measurements and these assumptions have not been tested directly. To help inform the choice and application of appropriate methods of model fitting to such data we studied the errors associated with flow cytometry measurements from a wide variety of experiments. We found that the mean and variance of the noise were related by a power law with an exponent between 1.3 and 1.8 for different datasets. This violated the assumptions inherent to commonly used least squares, linear variance scaling and log-transformation based methods. As a result of these findings we propose a new measurement model that we justify both theoretically, from the maximum entropy standpoint, and empirically using collected data. Our evaluation suggests that the new model can be reliably used for model fitting across a variety of conditions. Our work provides a foundation for modeling measurements in flow cytometry experiments thus facilitating progress in quantitative studies of lymphocyte responses.     

Comparative Study of Microsporidian Spores by Flow Cytometric Analysis

ABSTRACT. Spore suspensions of microsporidian parasites of fish (Microsporidium ovoideum, Glugea stephani, Glugea atherinae and Spraguea lophii ) have been analyzed by flow cytometry. Spore nuclei were dyed either by propidium iodide or bis-benzimide (Hoechst 33342). By observation of forward light scatter and fluorescence the four species could be distinguished and the mono- and diplokaryotic populations of S. lophii identified. Staining of DNA by bis-benzimide was better and easier than propidium iodide. Forward light scatter and fluorescence values were characteristic of each species and remained unchanged throughout the year, so flow cytometry can be used for distinction of spores of some microsporidian parasites once their flow cytometric parameters are known. However, special care has to be taken in tool calibration and material preparation for analysis because of the high precision of the technique.     

Data quality assessment of ungated flow cytometry data in high throughput experiments.

BACKGROUND: The recent development of semiautomated techniques for staining and analyzing flow cytometry samples has presented new challenges. Quality control and quality assessment are critical when developing new high throughput technologies and their associated information services. Our experience suggests that significant bottlenecks remain in the development of high throughput flow cytometry methods for data analysis and display. Especially, data quality control and quality assessment are crucial steps in processing and analyzing high throughput flow cytometry data. METHODS: We propose a variety of graphical exploratory data analytic tools for exploring ungated flow cytometry data. We have implemented a number of specialized functions and methods in the Bioconductor package rflowcyt. We demonstrate the use of these approaches by investigating two independent sets of high throughput flow cytometry data. RESULTS: We found that graphical representations can reveal substantial nonbiological differences in samples. Empirical Cumulative Distribution Function and summary scatterplots were especially useful in the rapid identification of problems not identified by manual review. CONCLUSIONS: Graphical exploratory data analytic tools are quick and useful means of assessing data quality. We propose that the described visualizations should be used as quality assessment tools and where possible, be used for quality control.     

Assessment of GFP Expression and Viability Using the Tali Image-Based Cytometer

Single-cell and population information are commonly obtained either by flow cytometry or fluorescence microscopy. However, these two methods provide different information. Flow cytometry gives quantitative multi-parametric information about physical characteristics and staining or expression, but doesn''t allow for visualization. Stand-alone fluorescence microscopy provides visual data, but doesn''t allow for straightforward quantitative measurements¹.Image-based cytometry bridges the gap between these two methods, enabling the quick visualization and simultaneous quantitative analysis of thousands of cells in heterogeneous populations². Here, we present a method for performing cell viability and green fluorescent protein (GFP) expression assays using the Tali Image-Based Cytometer³. The Tali instrument is a 3-channel (bright field, green fluorescence, red fluorescence) benchtop assay platform that offers several advantages over flow cytometry and fluorescence microscopy. The Tali cytometer is less expensive, takes up less bench space, requires less maintenance, and the work flow has been simplified so that the operation and analysis is much simpler and quicker. The Tali cytometer is capable of performing a range of suspension cell-based assays, including GFP and red fluorescent protein (RFP) expression, apoptosis^4-6 and cell viability analysis with propidium iodide (PI)^7-11.Here, we demonstrate the use of the Tali instrument in performing a cell viability assay in cells expressing GFP. GFP-transduced cells are stained using the Tali Viability Kit - Dead Cell Red. The cells are then pipetted into a Tali Cellular Analysis Slide and loaded into the cytometer. Bright field, red fluorescence and green fluorescence images are captured and analyzed using assay specific algorithms. Histograms are then generated to display cell size, PI fluorescence intensity, and GFP fluorescence intensity. These parameters can then be thresholded to home in on a specific cell population.A side-by side comparison of the Tali Image-Based Cytometer and traditional flow cytometry demonstrates that the two methods provide comparable data regarding cell viability and protein expression. However, the Tali instrument provides additional visual information about the cell population that cannot be obtained using a flow cytometer.Download video file.^{(64M, mov)}     

Cytological response of hemocytes in the European flat oyster, Ostrea edulis, experimentally exposed to mercury

Molluscs bivalves have been widely used as bioindicators to monitor contamination levels in coastal waters. In addition, many studies have attempted to analyze bivalve organs, considered pollutant-targets, to understand the bio-accumulation process and to characterize the effects of pollutants on the organisms. Here we analyzed the effects of mercury exposure on flat oyster hemocytes. Optical and electronic microscope procedures were used to characterize hemocyte morphology. In addition, cell solutions treated with acridine orange were analyzed by flow cytometry and laser scanning cytometry in order to evaluate the variations of cytoplasmic granules (red fluorescence, ARF) and cell size (green fluorescence, AGF) of hemocyte populations over time. Light and electron microscopical studies enabled us to differentiate four hemocyte subpopulations, agranulocytes (Types I and II) and granulocytes (Types I and II). Slight morphological differences were observed between control and Hg-exposed cells only in granulocytes exposed to Hg for 30 days, where condensed chromatin and partially lysed cytoplasmic regions were detected. Flow and laser scanning cytometry studies allowed us to differentiate three hemocyte populations, agranulocytes (R1) and granulocytes (R2 and R3). The exposure time to Hg increased the average red fluorescence (ARF) of agranulocytes and small granulocytes, while there was no change in large granulocytes, which showed a loss of membrane integrity. In control oysters, the three hemocyte populations showed an increase of ARF after 19 days of exposure although initial values were restored after 30 days. The average green fluorescence (AGF) was more stable than the ARF throughout the experiment. In Hg-exposed oysters, the values of AGF of agranulocytes showed an increase at half Hg-exposure period while the AGF values of large granulocytes decreased throughout the experiment, confirming the instability of these types of cells. The relative percentage of small granulocytes and granulocytes showed time variations in both control and exposed oysters. However, the values of small granulocytes remained constant during the whole experiment. The fact that there were only changes in agranulocytes and large granulocytes suggested a possible relationship between these two types of cells. In a quantitative study, we found a significant linear relationship between the agranulocytes and large granulocytes.     

Understanding reproductive allometry in turtles: A slippery “slope”

Measures of reproductive output in turtles are generally positively correlated with female body size. However, a full understanding of reproductive allometry in turtles requires logarithmic transformation of reproductive and body size variables prior to regression analyses. This allows for slope comparisons with expected linear or cubic relationships for linear to linear and linear to volumetric variables, respectively. We compiled scaling data using this approach from published and unpublished turtle studies (46 populations of 25 species from eight families) to quantify patterns among taxa. Our results suggest that for log–log comparisons of clutch size, egg width, egg mass, clutch mass, and pelvic aperture width to shell length, all scale hypoallometrically despite theoretical predictions of isometry. Clutch size generally scaled at ~1.7 to 2.0 (compared to an isometric expectation of 3.0), egg width at ~0.5 (compared to an expectation of 1.0), egg mass at ~1.1 to 1.3 (3.0), clutch mass at ~2.5 to 2.8 (3.0), and pelvic aperture width at 0.8–0.9 (1.0). We also found preliminary evidence that scaling may differ across years and clutches even in the same population, as well as across populations of the same species. Future investigators should aspire to collect data on all these reproductive parameters and to report log–log allometric analyses to test our preliminary conclusions regarding reproductive allometry in turtles.     

Differential fluorochromasia of human lymphocytes as measured by flow cytometry.

Peripheral human lymphocytes reacted with fluorescein diacetate and analyzed by flow cytometry produced a bimodal fluorescence distribution that was shown to be attributable to the differential staining of T and B lymphocytes. Lymphocytes were fractionated into rosetting (T cell) and nonrosetting (B cell) populations. Both subfractions were reacted with fluorescein diacetate and analyzed by flow cytometry. The rosetting fraction was more fluorescent than the nonrosetting fraction, and the analysis of an appropriate mixture of the subfractionated populations produced a fluorescence distribution very similar to that obtained with unfractionated lymphocytes.     

Can Power-Law Scaling and Neuronal Avalanches Arise from Stochastic Dynamics?

The presence of self-organized criticality in biology is often evidenced by a power-law scaling of event size distributions, which can be measured by linear regression on logarithmic axes. We show here that such a procedure does not necessarily mean that the system exhibits self-organized criticality. We first provide an analysis of multisite local field potential (LFP) recordings of brain activity and show that event size distributions defined as negative LFP peaks can be close to power-law distributions. However, this result is not robust to change in detection threshold, or when tested using more rigorous statistical analyses such as the Kolmogorov–Smirnov test. Similar power-law scaling is observed for surrogate signals, suggesting that power-law scaling may be a generic property of thresholded stochastic processes. We next investigate this problem analytically, and show that, indeed, stochastic processes can produce spurious power-law scaling without the presence of underlying self-organized criticality. However, this power-law is only apparent in logarithmic representations, and does not survive more rigorous analysis such as the Kolmogorov–Smirnov test. The same analysis was also performed on an artificial network known to display self-organized criticality. In this case, both the graphical representations and the rigorous statistical analysis reveal with no ambiguity that the avalanche size is distributed as a power-law. We conclude that logarithmic representations can lead to spurious power-law scaling induced by the stochastic nature of the phenomenon. This apparent power-law scaling does not constitute a proof of self-organized criticality, which should be demonstrated by more stringent statistical tests.     

Isolation of Adipose Tissue Immune Cells

The discovery of increased macrophage infiltration in the adipose tissue (AT) of obese rodents and humans has led to an intensification of interest in immune cell contribution to local and systemic insulin resistance. Isolation and quantification of different immune cell populations in lean and obese AT is now a commonly utilized technique in immunometabolism laboratories; yet extreme care must be taken both in stromal vascular cell isolation and in the flow cytometry analysis so that the data obtained is reliable and interpretable. In this video we demonstrate how to mince, digest, and isolate the immune cell-enriched stromal vascular fraction. Subsequently, we show how to antibody label macrophages and T lymphocytes and how to properly gate on them in flow cytometry experiments. Representative flow cytometry plots from low fat-fed lean and high fat-fed obese mice are provided. A critical element of this analysis is the use of antibodies that do not fluoresce in channels where AT macrophages are naturally autofluorescent, as well as the use of proper compensation controls.     

Biotinylation and characterization of Cryptococcus neoformans cell surface proteins

AIMS: To develop a novel procedure for isolating and characterizing cryptococcal cell-surface proteins using biotinylation, fluorescein isothiocyanate (FITC)-streptavidin, flow cytometry and associated ligand-receptor analysis, confocal microscopy and electrophoretic separation. METHODS AND RESULTS: Cell proteins of both acapsulate and encapsulated Cryptococcus neoformans cells were labelled using sulfo-NHS-biotin which, in turn, was complexed with FITC-streptavidin. Resulting cell population fluorescence supported visualization of cell-surface protein distribution by confocal microscopy, as well as evaluation of protein exposure by flow cytometry and the calculation of the ligand-binding determinants EC(50), F(max) and H(n). Biotinylation of cell-surface proteins also supported their isolation by affinity chromatography and characterization by SDS/PAGE. Ligand-binding determinants, such as EC(50) values, indicated that acapsulate and stationary phase cells have greatest affinity for biotin. F(max) values demonstrated greatest protein exposure among stationary phase cells; in turn, encapsulated cells expose more protein than acapsulate counterparts. H(n) values of below unity potentially confirm the complex multi-receptor nature of biotin binding to cryptococcal cell surfaces under investigation. Fluorescence visualization showed marked but localized fluorescence indicative of protein exposure around sites of cell division. In turn, biotinylation of cell-surface proteins and their release under reducing conditions demonstrated at least two noncovalently linked proteinaceous entities, of 43 and 57 kDa, exposed on acapsulate cryptococcal cell walls. CONCLUSIONS: A novel method for identifying, in situ, cell-surface proteins exposed by C. neoformans was established. This novel technique was successfully implemented using both acapsulate and encapsulated C. neoformans cells, both were found to have dynamic and markedly localized protein distribution around sites of cell division and associated cell wall trauma. SIGNIFICANCE AND IMPACT OF THE STUDY: A novel procedure, employing a versatile combination of flow cytometry, ligand-receptor analysis, confocal microscopy and biotinylation, supported the characterization and isolation of cryptococcal cell-surface proteins.     

Cellometer image cytometry as a complementary tool to flow cytometry for verifying gated cell populations

Traditionally, many cell-based assays that analyze cell populations and functionalities have been performed using flow cytometry. However, flow cytometers remain relatively expensive and require highly trained operators for routine maintenance and data analysis. Recently, an image cytometry system has been developed by Nexcelom Bioscience (Lawrence, MA, USA) for automated cell concentration and viability measurement using bright-field and fluorescent imaging methods. Image cytometry is analogous to flow cytometry in that gating operations can be performed on the cell population based on size and fluorescent intensity. In addition, the image cytometer is capable of capturing bright-field and fluorescent images, allowing for the measurement of cellular size and fluorescence intensity data. In this study, we labeled a population of cells with an enzymatic vitality stain (calcein-AM) and a cell viability dye (propidium iodide) and compared the data generated by flow and image cytometry. We report that measuring vitality and viability using the image cytometer is as effective as flow cytometric assays and allows for visual confirmation of the sample to exclude cellular debris. Image cytometry offers a direct method for performing fluorescent cell-based assays but also may be used as a complementary tool to flow cytometers for aiding the analysis of more complex samples.