Realtime acquisition, storage, and display of correlated three-parameter flow cytometric data

A microprocessor-based system which performs realtime correlated acquisition, storage and display of multiparameter (3-parameter) data from a flow cytometer (FACS-III) is presented. List-mode techniques are not employed. The 3-parameter data is collected and correlated, then displayed along with cell-frequency as a realtime 3-parameter colour scattergram, while the experiment is in progress; in addition, correlated and uncorrelated higher-resolution projections of the 3-parameter data are collected and stored. The data projections may also be displayed: as 1-parameter histograms, or as 2-parameter colour or grey-scale scattergrams. Examples of 2- and 3-parameter colour scattergrams are presented. The speed and some characteristics of the realtime acquisition and display software are examined; methods to increase the realtime speed are discussed.     

Web servlet-assisted, dial-in flow cytometry data analysis

BACKGROUND: The obvious benefits of centralized data storage notwithstanding, the size of modern flow cytometry data files discourages their transmission over commonly used telephone modem connections. The proposed solution is to install at the central location a web servlet that can extract compact data arrays, of a form dependent on the requested display type, from the stored files and transmit them to a remote client computer program for display. METHODS: A client program and a web servlet, both written in the Java programming language, were designed to communicate over standard network connections. The client program creates familiar numerical and graphical display types and allows the creation of gates from combinations of user-defined regions. Data compression techniques further reduce transmission times for data arrays that are already much smaller than the data file itself. RESULTS: For typical data files, network transmission times were reduced more than 700-fold for extraction of one-dimensional (1-D) histograms, between 18 and 120-fold for 2-D histograms, and 6-fold for color-coded dot plots. Numerous display formats are possible without further access to the data file. CONCLUSIONS: This scheme enables telephone modem access to centrally stored data without restricting flexibility of display format or preventing comparisons with locally stored files.     

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.     

On multiparameter data analysis in flow cytometry

Increasing numbers of parameters that are accessible to simultaneous measurement in flow cytometric instruments, combined with the extremely large sample sizes common in flow cytometry, make it necessary to examine methods of multivariate statistics for their applicability to problems of visualization and quantitative analysis of flow cytometric data. This article describes some approaches to dimensionality reduction that appear well suited for data sets obtained by flow cytometry.     

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.     

Small-volume rapid-mix device for subsecond kinetic analysis in flow cytometry.

BACKGROUND: Rapid-mix flow cytometry has emerged as a powerful tool for mechanistic analysis of ligand binding, cell response, and molecular assembly. Although progress has come from improving sample delivery capabilities, little attention has been paid to the volumetric requirements associated with precious biological reagents. METHODS: By using programmable syringes, valves, and other fluidic components, we created a modular, precisely regulated rapid-mix device for the delivery of small-volume samples to the flow cytometer. The device was tested using a bead-based assay in which the binding kinetics between native biotin and fluorescein biotin-bearing beads were characterized. RESULTS: Bead suspensions and reagents paired in 35- to 45-microl aliquots were efficiently mixed by the device and delivered to the flow cytometer. Kinetic data associated with the fluorescein biotin beads were analyzed and used to calibrate the performance characteristics of the device in terms of sample delivery and mixing efficiency. CONCLUSION: The rapid-mix device is capable of detecting subsecond kinetics of biological reactions using microliter volume of samples. Dimensions of the device have been minimized, and the quantitative aspects of sample delivery and analysis have been optimized. Further, the modular design has been optimized for adaptation to a variety of experimental protocols.     

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.     

Modified histogram subtraction technique for analysis of flow cytometry data

Analysis of flow cytometry histogram data by the subjective selection of an integration window can be a tedious and time-consuming task and is often inaccurate. A new method for automated calculation of the percent positive from immunofluorescence histograms is presented. This new method is a modification of the currently used method of channel-by-channel histogram subtraction. Its accuracy is compared to that of the channel-by-channel histogram subtraction method and to another currently used automated method, which selects an integration window by finding the channels that contain the most fluorescent 2% of a control histogram. The new histogram subtraction method is objective, easy to use, and is more accurate than other currently used automated analysis methods. PASCAL source code is given for each method of analysis.     

A novel statistical analysis and interpretation of flow cytometry data

A recently developed class of models incorporating the cyton model of population generation structure into a conservation-based model of intracellular label dynamics is reviewed. Statistical aspects of the data collection process are quantified and incorporated into a parameter estimation scheme. This scheme is then applied to experimental data for PHA-stimulated CD4+T and CD8+T cells collected from two healthy donors. This novel mathematical and statistical framework is shown to form the basis for accurate, meaningful analysis of cellular behaviour for a population of cells labelled with the dye carboxyfluorescein succinimidyl ester and stimulated to divide.     

Plug flow cytometry: An automated coupling device for rapid sequential flow cytometric sample analysis.

BACKGROUND: The tools for high throughput flow cytometry have been limited in part because of the requirement that the samples must flow under pressure. We describe a simple system for sampling repetitively from an open vessel. METHODS: Under computer control, the sample is loaded into a sample loop in a reciprocating eight-way valve by the action of a syringe. When the valve position is switched, the plug of sample in the sample loop is transported to the flow cytometer by a pressure-driven fluid line. By coupling the plug-forming capability to a second multi-port valve, samples can be delivered sequentially from separate vessels. RESULTS: The valve is able to deliver samples at rates ranging up to about 9 samples per minute. Each plug of sample has uniform delivery characteristics with a reproducible coefficient of variation (CV). Even at the highest sampling rate, carryover between samples is limited. CONCLUSIONS: Plug-flow flow cytometry has the potential to automate the delivery of small samples from unpressurized sources at rates compatible with many screening and assay applications.     

A device for sample pretreatment during flow cytometry]

A device for the preliminary treatment of samples immediately prior to flow cytofluorimetric analysis is described. The device is intended for several procedures: (a) mixing of batched sample volumes with the reagent and efficient stirring of the mixture; (b) disintegration of cell aggregates; and (c) disruption of cell membranes to release the cell contents (chromosomes, micronuclei, nuclei etc.). The pretreatment is useful for studying the kinetic parameters of fast cellular processes in the flow, a more correct analysis of the cell cycle and the study of karyotypes of single mitotic cells. The device was called a magnetic microstirrer.     

Fine affinity discrimination by yeast surface display and flow cytometry

Yeast surface display is a eucaryotic system for the directed evolution of protein binding and stability. For antibody affinity maturation, achievable single-pass enrichment factors are a critical variable. Both reliable recovery of rare clones (yield) and effective differentiation between clones of only slightly improved affinity (purity) are paramount. To validate yeast display's purification potential, trial sorting experiments were performed. The D1.3 (anti-hen egg lysozyme) single chain variable fragment antibody and a 2-fold higher affinity mutant (M3) were each displayed on the surface of Saccharomyces cerevisiae. M3-displaying cells were mixed into the D1.3-displaying cells at a ratio of 1:1000. Cells were fluorescently labeled according to antigen equilibrium binding and then sorted using a flow cytometer. Single-pass enrichment of M3-displaying cells was 125-fold (+/- 65-fold). This level of performance is achievable because of the precision and reproducibility of optimal labeling conditions. This work further demonstrates the capability of yeast display for very fine discrimination between mutant clones of similar affinity. Because large improvements in affinity typically result from combinations of small changes, this capability to identify subtle improvements is essential for rapid affinity maturation.     

Interactive display and analysis of data from bivariate flow cytometers.

An interactive computer program, SWELL, displayss and analyzes bivariate distributions generated by flow cytometers. SWELL is modular with options available via a menu, is written in Fortran, and utilizes a video color display system. Data are accumulated as a bivariate distribution that is transferred to the computer as a 64 x 64 matrix. For ease of visualization, matrices are displayed in pseudocolor. The distribution values are broken into eight ranges and each range is represented by a color. Each element of the matrix is then displayed in its assigned color. To allow pooling and comparison, distributions are aligned, edited, and standardized. Unknown samples are pooled or analyzed singly and compared to the normal pool by subtraction. Differences are displayed as pseudocolor matrices of sign, magnitude, or statistical magnitude in units of standard deviation. This latter display, scaled to tolerance limits, readily reveals regions of significant difference between normal and abnormal samples. Counts within such regions can be compared to diagnose samples automatically.     

Evaluation of staphylococcal cell surface display and flow cytometry for postselectional characterization of affinity proteins in combinatorial protein engineering applications

For efficient generation of high-affinity protein-based binding molecules, fast and reliable downstream characterization platforms are needed. In this work, we have explored the use of staphylococcal cell surface display together with flow cytometry for affinity characterization of candidate affibody molecules directly on the cell surface. A model system comprising three closely related affibody molecules with different affinities for immunoglobulin G and an albumin binding domain with affinity for human serum albumin was used to investigate advantages and differences compared to biosensor technology in a side-by-side manner. Equilibrium dissociation constant (K(D)) determinations as well as dissociation rate analysis were performed using both methods, and the results show that the on-cell determinations give both K(D) and dissociation rate values in a very fast and reproducible manner and that the relative affinities are very similar to the biosensor results. Interestingly, the results also show that there are differences between the absolute affinities determined with the two different technologies, and possible explanations for this are discussed. This work demonstrates the advantages of cell surface display for directed evolution of affinity proteins in terms of fast postselectional, on-cell characterization of candidate clones without the need for subcloning and subsequent protein expression and purification but also demonstrates that it is important to be aware that absolute affinities determined using different methods often vary substantially and that such comparisons therefore could be difficult.     

FuGEFlow: data model and markup language for flow cytometry

Background  

Flow cytometry technology is widely used in both health care and research. The rapid expansion of flow cytometry applications has outpaced the development of data storage and analysis tools. Collaborative efforts being taken to eliminate this gap include building common vocabularies and ontologies, designing generic data models, and defining data exchange formats. The Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) standard was recently adopted by the International Society for Advancement of Cytometry. This standard guides researchers on the information that should be included in peer reviewed publications, but it is insufficient for data exchange and integration between computational systems. The Functional Genomics Experiment (FuGE) formalizes common aspects of comprehensive and high throughput experiments across different biological technologies. We have extended FuGE object model to accommodate flow cytometry data and metadata.     

Modeling flow cytometry data for cancer vaccine immune monitoring

Flow cytometry (FCM) is widely used in cancer research for diagnosis, detection of minimal residual disease, as well as immune monitoring and profiling following immunotherapy. In all these applications, the challenge is to detect extremely rare cell subsets while avoiding spurious positive events. To achieve this objective, it helps to be able to analyze FCM data using multiple markers simultaneously, since the additional information provided often helps to minimize the number of false positive and false negative events, hence increasing both sensitivity and specificity. However, with manual gating, at most two markers can be examined in a single dot plot, and a sequential strategy is often used. As the sequential strategy discards events that fall outside preceding gates at each stage, the effectiveness of the strategy is difficult to evaluate without laborious and painstaking back-gating. Model-based analysis is a promising computational technique that works using information from all marker dimensions simultaneously, and offers an alternative approach to flow analysis that can usefully complement manual gating in the design of optimal gating strategies. Results from model-based analysis will be illustrated with examples from FCM assays commonly used in cancer immunotherapy laboratories.     

Nonparametric discriminant analysis of phytoplankton species using data from analytical flow cytometry

BACKGROUND: Analytical flow cytometry (AFC) provides rapid and accurate measurement of particles from heterogeneous populations. AFC has been used to classify and identify phytoplankton species, but most methods of discriminant analysis of resulting data have depended on normality assumptions and outcomes have been disappointing. METHODS AND RESULTS: In this study, we consider nonparametric methods based on density estimation. In addition to the familiar kernel method, methods based on wavelets are also implemented. Full five-dimensional wavelet estimation proves to be computationally prohibitive with current workstation power, so we employ projection pursuit for reduction of dimensionality. AFC typically produces very large samples, so we also investigate data simplification through binning. Further modifications to the discrimination strategy are suggested by specific features of phytoplankton data, namely, a hierarchical group structure, the possible presence of many groups, and the likelihood of encountering an aberrant group in a test sample. CONCLUSIONS: We apply all the resultant procedures to appropriate subsets of a very large data set, demonstrate their efficacy, and compare their error rates with those of more conventional methods. We further show that incorporation of the specific features of phytoplankton data into the analysis leads to improved results and provides a general framework for analysis of such data.     

Microbead display by in vitro compartmentalisation: selection for binding using flow cytometry

In vitro compartmentalisation in an emulsion was used to physically link proteins to the DNA that encodes them via microbeads. These microbeads can be selected for catalysis, or, as demonstrated here, for binding. Genes encoding a peptide containing an epitope (haemagglutinin) were enriched to near purity from a 10(6)-fold excess of genes encoding a different peptide by two rounds of selection using flow cytometry, indicating approximately 1000-fold enrichment per round. Single beads can be isolated using flow sorting and the single gene on the bead amplified by polymerase chain reaction. Hence, the entire process can be performed completely in vitro.     

The relevance of flow cytometry for biochemical analysis

Flow cytometry (FCM) allows the simultaneous measurement of multiple fluorescences and light scatter induced by illumination of single cells or microscopic particles in suspension, as they flow rapidly through a sensing area. In some systems, individual cells or particles may be sorted according to the properties exhibited. By using appropriate fluorescent markers, FCM is unique in that multiple structural and functional parameters can be quantified simultaneously on a single-particle basis, whereas up to thousands of biological particles per second may be examined. FCM is increasingly used for basic, clinical, biotechnological, and environmental studies of biochemical relevance. In this critical review, we summarize the main advantages and limitations of FCM for biochemical studies and discuss briefly the most relevant parameters and analytical strategies. Graphical examples of the biological information provided by multiparametric FCM are presented. Also, this review contains specific sections on flow cytoenzymology, FCM analysis of isolated subcellular organelles, and cell-free FCM.