Deep phenotyping of T cell populations under long-term treatment of tacrolimus and rapamycin in patients receiving renal transplantations by mass cytometry

Tacrolimus (FK506) and rapamycin (RAPA) are widely used to maintain long-term immunosuppression after organ transplantation. However, the impact of accumulative drug administration on the recipients' immune systems remains unclear. We investigated the impact of 3-year FK506 or RAPA treatment after renal transplantation on the human immune systems. A discovery cohort of 30 patients was first recruited, and we discovered two distinctive T lineage suppressive regulatory patterns induced by chronic treatment of FK506 and RAPA. The increased percentage of senescent CD8+ CD57+ T lineages and less responsive T cell receptor (TCR) pathway in the FK506 group indicate better graft acceptance. Meanwhile, percentages of regulatory T cells (Tregs) and expression of CTLA-4 were both up to two-fold higher in the RAPA group, suggesting the inconsistent reactivation potential of the FK506 and RAPA groups when an anti-tumour or anti-infection immune response is concerned. Additionally, up-regulation of phosphorylated signaling proteins in T lineages after in vitro CD3/CD28 stimulation suggested more sensitive TCR-signaling pathways reserved in the RAPA group. An independent validation cohort of 100 renal transplantation patients was further investigated for the hypothesis that long-term RAPA administration mitigates the development of tumours and infections during long-term intake of immunosuppressants. Our results indicate that RAPA administration indeed results in less clinical oncogenesis and infection. The deep phenotyping of T-cell lineages, as educated by the long-term treatment of different immunosuppressants, provides new evidence for personalized precision medicine after renal transplantations.

Understanding the Activation of Platelets in Diabetes and Its Modulation by Allyl Methyl Sulfide, an Active Metabolite of Garlic

BACKGROUND

Diabetes mellitus (DM) is a chronic metabolic disorder associated with higher risk of having cardiovascular disease. Platelets play a promising role in the pathogenesis of cardiovascular complications in diabetes. Since last several decades, garlic and its bioactive components are extensively studied in diabetes and its complications. Our aim was to explore the antiplatelet property of allyl methyl sulfide (AMS) focusing on ameliorating platelet activation in diabetes.

METHOD

We used streptozotocin- (STZ-) induced diabetic rats as model for type 1 diabetes. We have evaluated the effect of allyl methyl sulfide on platelet activation by administrating AMS to diabetic rats for 10 weeks. Flow cytometry-based analysis was used to evaluate the platelet activation, platelet aggregation, platelet macrophage interaction, and endogenous ROS generation in the platelets obtained from control, diabetes, and AMS- and aspirin-treated diabetic rats.

RESULTS

AMS treatment for 10 weeks effectively reduced the blood glucose levels in diabetic rats. Three weeks of AMS (50 mg/kg/day) treatment did not reduce the activation of platelets but a significant (p < 0.05) decrease was observed after 10 weeks of treatment. Oral administration of AMS significantly (p < 0.05) reduced the baseline and also reduced ADP-induced aggregation of platelets after 3 and 10 weeks of treatment. Furthermore, 10 weeks of AMS treatment in diabetic rats attenuated the endogenous ROS content (p < 0.05) of platelets and platelet macrophage interactions. The inhibition of platelet activation in diabetic rats after AMS treatment was comparable with aspirin treatment (30 mg/kg/day).

CONCLUSION

We observed an inhibitory effect of allyl methyl sulfide on platelet aggregation, platelet activation, platelet macrophage interaction, and increased ROS levels in type 1 diabetes. Our data suggests that AMS can be useful to control cardiovascular complication in diabetes via inhibition of platelet activation.

Flow cytometry multiplexed method for the detection of neutralizing human antibodies to the native SARS-CoV-2 spike protein

A correct identification of seropositive individuals for the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is of paramount relevance to assess the degree of protection of a human population to present and future outbreaks of the COVID-19 pandemic. We describe here a sensitive and quantitative flow cytometry method using the cytometer-friendly non-adherent Jurkat T-cell line that stably expresses the full-length native spike "S" protein of SARS-CoV-2 and a truncated form of the human EGFR that serves a normalizing role. S protein and huEGFRt coding sequences are separated by a T2A self-cleaving sequence, allowing to accurately quantify the presence of anti-S immunoglobulins by calculating a score based on the ratio of fluorescence intensities obtained by double-staining with the test sera and anti-EGFR. The method allows to detect immune individuals regardless of the result of other serological tests or even repeated PCR monitoring. As examples of its use, we show that as much as 28% of the personnel working at the CBMSO in Madrid is already immune. Additionally, we show that anti-S antibodies with protective neutralizing activity are long-lasting and can be detected in sera 8 months after infection.

Nonspecific probe binding and automatic gating in flow cytometry and fluorescence activated cell sorting (FACS)

Flow cytometry is extensively used in cell biology to differentiate cells of interest (mutants) from control cells (wild-types). For mutant cells characterized by expression of a distinct membrane surface structure, fluorescent marker probes can be designed to bind specifically to these structures while the cells are in suspension, resulting in a sufficiently high fluorescence intensity measurement by the cytometer to identify a mutant cell. However, cell membranes may have relatively weak, nonspecific binding affinity to the probes, resulting in false positive results. Furthermore, the same effect would be present on mutant cells, allowing both specific and nonspecific binding to a single cell. We derive and analyze a kinetic model of fluorescent probe binding dynamics by tracking populations of mutant and wild-type cells with differing numbers of probes bound specifically and nonspecifically. By assuming the suspension is in chemical equilibrium prior to cytometry, we use a two-species Langmuir adsorption model to analyze the confounding effects of non-specific binding on the assay. Furthermore, we analytically derive an expectation maximization method to infer an appropriate estimate of the total number of mutant cells as an alternative to existing, heuristic methods. Lastly, using our model, we propose a new method to infer physical and experimental parameters from existing protocols. Our results provide improved ways to quantitatively analyze flow cytometry data.

diffcyt: Differential discovery in high-dimensional cytometry via high-resolution clustering

High-dimensional flow and mass cytometry allow cell types and states to be characterized in great detail by measuring expression levels of more than 40 targeted protein markers per cell at the single-cell level. However, data analysis can be difficult, due to the large size and dimensionality of datasets as well as limitations of existing computational methods. Here, we present diffcyt, a new computational framework for differential discovery analyses in high-dimensional cytometry data, based on a combination of high-resolution clustering and empirical Bayes moderated tests adapted from transcriptomics. Our approach provides improved statistical performance, including for rare cell populations, along with flexible experimental designs and fast runtimes in an open-source framework.

Determination of essential phenotypic elements of clusters in high-dimensional entities-DEPECHE

Technological advances have facilitated an exponential increase in the amount of information that can be derived from single cells, necessitating new computational tools that can make such highly complex data interpretable. Here, we introduce DEPECHE, a rapid, parameter free, sparse k-means-based algorithm for clustering of multi- and megavariate single-cell data. In a number of computational benchmarks aimed at evaluating the capacity to form biologically relevant clusters, including flow/mass-cytometry and single cell RNA sequencing data sets with manually curated gold standard solutions, DEPECHE clusters as well or better than the currently available best performing clustering algorithms. However, the main advantage of DEPECHE, compared to the state-of-the-art, is its unique ability to enhance interpretability of the formed clusters, in that it only retains variables relevant for cluster separation, thereby facilitating computational efficient analyses as well as understanding of complex datasets. DEPECHE is implemented in the open source R package DepecheR currently available at github.com/Theorell/DepecheR.

DAFi: A directed recursive data filtering and clustering approach for improving and interpreting data clustering identification of cell populations from polychromatic flow cytometry data

Computational methods for identification of cell populations from polychromatic flow cytometry data are changing the paradigm of cytometry bioinformatics. Data clustering is the most common computational approach to unsupervised identification of cell populations from multidimensional cytometry data. However, interpretation of the identified data clusters is labor-intensive. Certain types of user-defined cell populations are also difficult to identify by fully automated data clustering analysis. Both are roadblocks before a cytometry lab can adopt the data clustering approach for cell population identification in routine use. We found that combining recursive data filtering and clustering with constraints converted from the user manual gating strategy can effectively address these two issues. We named this new approach DAFi: Directed Automated Filtering and Identification of cell populations. Design of DAFi preserves the data-driven characteristics of unsupervised clustering for identifying novel cell subsets, but also makes the results interpretable to experimental scientists through mapping and merging the multidimensional data clusters into the user-defined two-dimensional gating hierarchy. The recursive data filtering process in DAFi helped identify small data clusters which are otherwise difficult to resolve by a single run of the data clustering method due to the statistical interference of the irrelevant major clusters. Our experiment results showed that the proportions of the cell populations identified by DAFi, while being consistent with those by expert centralized manual gating, have smaller technical variances across samples than those from individual manual gating analysis and the nonrecursive data clustering analysis. Compared with manual gating segregation, DAFi-identified cell populations avoided the abrupt cut-offs on the boundaries. DAFi has been implemented to be used with multiple data clustering methods including K-means, FLOCK, FlowSOM, and the ClusterR package. For cell population identification, DAFi supports multiple options including clustering, bisecting, slope-based gating, and reversed filtering to meet various autogating needs from different scientific use cases. © 2018 International Society for Advancement of Cytometry.

QFMatch: multidimensional flow and mass cytometry samples alignment

Part of the flow/mass cytometry data analysis process is aligning (matching) cell subsets between relevant samples. Current methods address this cluster-matching problem in ways that are either computationally expensive, affected by the curse of dimensionality, or fail when population patterns significantly vary between samples. Here, we introduce a quadratic form (QF)-based cluster matching algorithm (QFMatch) that is computationally efficient and accommodates cases where population locations differ significantly (or even disappear or appear) from sample to sample. We demonstrate the effectiveness of QFMatch by evaluating sample datasets from immunology studies. The algorithm is based on a novel multivariate extension of the quadratic form distance for the comparison of flow cytometry data sets. We show that this QF distance has attractive computational and statistical properties that make it well suited for analysis tasks that involve the comparison of flow/mass cytometry samples.

Novel flowcytometry-based approach of malignant cell detection in body fluids using an automated hematology analyzer

Morphological microscopic examinations of nucleated cells in body fluid (BF) samples are performed to screen malignancy. However, the morphological differentiation is time-consuming and labor-intensive. This study aimed to develop a new flowcytometry-based gating analysis mode “XN-BF gating algorithm” to detect malignant cells using an automated hematology analyzer, Sysmex XN-1000. XN-BF mode was equipped with WDF white blood cell (WBC) differential channel. We added two algorithms to the WDF channel: Rule 1 detects larger and clumped cell signals compared to the leukocytes, targeting the clustered malignant cells; Rule 2 detects middle sized mononuclear cells containing less granules than neutrophils with similar fluorescence signal to monocytes, targeting hematological malignant cells and solid tumor cells. BF samples that meet, at least, one rule were detected as malignant. To evaluate this novel gating algorithm, 92 various BF samples were collected. Manual microscopic differentiation with the May-Grunwald Giemsa stain and WBC count with hemocytometer were also performed. The performance of these three methods were evaluated by comparing with the cytological diagnosis. The XN-BF gating algorithm achieved sensitivity of 63.0% and specificity of 87.8% with 68.0% for positive predictive value and 85.1% for negative predictive value in detecting malignant-cell positive samples. Manual microscopic WBC differentiation and WBC count demonstrated 70.4% and 66.7% of sensitivities, and 96.9% and 92.3% of specificities, respectively. The XN-BF gating algorithm can be a feasible tool in hematology laboratories for prompt screening of malignant cells in various BF samples.

High throughput automated analysis of big flow cytometry data

The rapid expansion of flow cytometry applications has outpaced the functionality of traditional manual analysis tools used to interpret flow cytometry data. Scientists are faced with the daunting prospect of manually identifying interesting cell populations in 50-dimensional datasets, equalling the complexity previously only reached in mass cytometry. Data can no longer be analyzed or interpreted fully by manual approaches. While automated gating has been the focus of intense efforts, there are many significant additional steps to the analytical pipeline (e.g., cleaning the raw files, event outlier detection, extracting immunophenotypes). We review the components of a customized automated analysis pipeline that can be generally applied to large scale flow cytometry data. We demonstrate these methodologies on data collected by the International Mouse Phenotyping Consortium (IMPC).

Scalable multi-sample single-cell data analysis by Partition-Assisted Clustering and Multiple Alignments of Networks

Mass cytometry (CyTOF) has greatly expanded the capability of cytometry. It is now easy to generate multiple CyTOF samples in a single study, with each sample containing single-cell measurement on 50 markers for more than hundreds of thousands of cells. Current methods do not adequately address the issues concerning combining multiple samples for subpopulation discovery, and these issues can be quickly and dramatically amplified with increasing number of samples. To overcome this limitation, we developed Partition-Assisted Clustering and Multiple Alignments of Networks (PAC-MAN) for the fast automatic identification of cell populations in CyTOF data closely matching that of expert manual-discovery, and for alignments between subpopulations across samples to define dataset-level cellular states. PAC-MAN is computationally efficient, allowing the management of very large CyTOF datasets, which are increasingly common in clinical studies and cancer studies that monitor various tissue samples for each subject.

Evaluating flow cytometer performance with weighted quadratic least squares analysis of LED and multi-level bead data

We developed a fully automated procedure for analyzing data from LED pulses and multilevel bead sets to evaluate backgrounds and photoelectron scales of cytometer fluorescence channels. The method improves on previous formulations by fitting a full quadratic model with appropriate weighting and by providing standard errors and peak residuals as well as the fitted parameters themselves. Here we describe the details of the methods and procedures involved and present a set of illustrations and test cases that demonstrate the consistency and reliability of the results. The automated analysis and fitting procedure is generally quite successful in providing good estimates of the Spe (statistical photoelectron) scales and backgrounds for all the fluorescence channels on instruments with good linearity. The precision of the results obtained from LED data is almost always better than that from multilevel bead data, but the bead procedure is easy to carry out and provides results good enough for most purposes. Including standard errors on the fitted parameters is important for understanding the uncertainty in the values of interest. The weighted residuals give information about how well the data fits the model, and particularly high residuals indicate bad data points. Known photoelectron scales and measurement channel backgrounds make it possible to estimate the precision of measurements at different signal levels and the effects of compensated spectral overlap on measurement quality. Combining this information with measurements of standard samples carrying dyes of biological interest, we can make accurate comparisons of dye sensitivity among different instruments. Our method is freely available through the R/Bioconductor package flowQB. © 2017 International Society for Advancement of Cytometry.

New tools in cytometry

Cytometry aims to analyze cells, of any type, using dedicated instruments. The quantitative aspect makes flow cytometry (FCM) a good complementary tool for morphology. Most of the identification tools are based on immunostaining of cell structure details and more and more tools are available in terms of specificities and labels. FCM is under exponential development thanks to technical, immunological and data analysis progresses. Actual generations are now routinely using 6 to 10 simultaneous immuno-labeling on 20 to 100,000 cells, at high speed and short sample preparation and can easily detect rare events at frequency below 10^-4 cells. Data interpretation is complex and requires expertise. Mathematical tools are available to support analysis and classification of cells based. Cells from tissues can also be analyzed by FCM after mechanical and or enzymatic separation, but in situ cells can also be analyzed with the help of cytometry. Very new instruments bring spectral analysis, image in flow and mass spectrometry. Medical applications are very broad, notably in hemopathies, immunology, solid tumors, but also microbiology, toxicology, drug discovery, food and environmental industry. But, the limit of FCM is its dependence on operator from sample preparation, instrument settings up to data analysis and a strong effort is now under progress for standardization and constitution of international data bank for references and education.

Novel statistical approach for evaluating flow cytometric in vitro micronucleus data

Statistical methods currently recommended for analysis of in vitro micronucleus data are based on small sample sizes. The tests are designed to evaluate linear trends and differences between treated and control samples. When using flow cytometric analysis, >5 times the number of cells are easily evaluated, and the variance estimates from these large samples are small. Application of these recommended tests to large samples resulted in statistically significant outcomes which were not considered to be biologically meaningful. Alternative statistical methods for testing trends and differences among treatments that were either widely used, or sample-size independent, were investigated. Using data from 95 experiments (from 2011-2013) where 19% of the experiments were considered positive, results for the various statistical methods were compared. When using either the recommended or alternate methods, 42-68% of the experiments resulted in statistically significant results (p < 0.05). A new concept was then tested using the same data sets: the "z' factor", designed to identify 'hits' during high throughput screening. Using this simple-to-compute statistic the number of significant calls was reduced to 27%. Then, when combined with a biological criterion based on historical vehicle control data, there was restoration of the original positive frequency (19%). Given the larger sample sizes evaluated using flow cytometry, we have demonstrated that traditional statistical tests may be overly sensitive to small changes in micronucleus induction, and that a simple-to-compute index of separation (z') may be a better tool for analysis, provided that the response is first determined to be biologically meaningful. Environ. Mol. Mutagen. 57:589-604, 2016. © 2016 Wiley Periodicals, Inc.

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.

The use of flow cytometry to assess a novel drug efficacy in multiple sclerosis

Applying different technologies to monitor disease activity and treatment efficacy are essential in a complex disease such as multiple sclerosis. Combining current assays with flow cytometry could create a powerful tool for such analyses. The cell surface expression level of CD74, the MHC class II invariant chain, is a potential disease biomarker that could be monitored by FACS analysis in order to assess disease progression and the clinical efficacy of partial MHC class II constructs in treating MS. These constructs, which can bind to and down-regulate CD74 cell-surface expression on monocytes and inhibit macrophage migration inhibitory factor (MIF) effects, can reverse clinical and histological signs of EAE. These properties of partial class II constructs are highly compatible with a flow cytometry approach for monitoring CD74 expression as a possible biomarker for disease activity/progression and as a treatment response marker.

Rmax: A systematic approach to evaluate instrument sort performance using center stream catch

Sorting performance can be evaluated with regard to Purity, Yield and/or Recovery of the sorted fraction. Purity is a check on the quality of the sample and the sort decisions made by the instrument. Recovery and Yield definitions vary with some authors regarding both as how efficient the instrument is at sorting the target particles from the original sample, others distinguishing Recovery from Yield, where the former is used to describe the accuracy of the instrument's sort count. Yield and Recovery are often neglected, mostly due to difficulties in their measurement. Purity of the sort product is often cited alone but is not sufficient to evaluate sorting performance. All of these three performance metrics require re-sampling of the sorted fraction. But, unlike Purity, calculating Yield and/or Recovery calls for the absolute counting of particles in the sorted fraction, which may not be feasible, particularly when dealing with rare populations and precious samples. In addition, the counting process itself involves large errors. Here we describe a new metric for evaluating instrument sort Recovery, defined as the number of particles sorted relative to the number of original particles to be sorted. This calculation requires only measuring the ratios of target and non-target populations in the original pre-sort sample and in the waste stream or center stream catch (CSC), avoiding re-sampling the sorted fraction and absolute counting. We called this new metric Rmax, since it corresponds to the maximum expected Recovery for a particular set of instrument parameters. Rmax is ideal to evaluate and troubleshoot the optimum drop-charge delay of the sorter, or any instrument related failures that will affect sort performance. It can be used as a daily quality control check but can be particularly useful to assess instrument performance before single-cell sorting experiments. Because we do not perturb the sort fraction we can calculate Rmax during the sort process, being especially valuable to check instrument performance during rare population sorts.

Data analysis as a source of variability of the HLA-peptide multimer assay: from manual gating to automated recognition of cell clusters

Multiparameter flow cytometry is an indispensable method for assessing antigen-specific T cells in basic research and cancer immunotherapy. Proficiency panels have shown that cell sample processing, test protocols and data analysis may all contribute to the variability of the results obtained by laboratories performing ex vivo T cell immune monitoring. In particular, analysis currently relies on a manual, step-by-step strategy employing serial gating decisions based on visual inspection of one- or two-dimensional plots. It is therefore operator dependent and subjective. In the context of continuing efforts to support inter-laboratory T cell assay harmonization, the CIMT Immunoguiding Program organized its third proficiency panel dedicated to the detection of antigen-specific CD8(+) T cells by HLA-peptide multimer staining. We first assessed the contribution of manual data analysis to the variability of reported T cell frequencies within a group of laboratories staining and analyzing the same cell samples with their own reagents and protocols. The results show that data analysis is a source of variation in the multimer assay outcome. To evaluate whether an automated analysis approach can reduce variability of proficiency panel data, we used a hierarchical statistical mixture model to identify cell clusters. Challenges for automated analysis were the need to process non-standardized data sets from multiple centers, and the fact that the antigen-specific cell frequencies were very low in most samples. We show that this automated method can circumvent difficulties inherent to manual gating strategies and is broadly applicable for experiments performed with heterogeneous protocols and reagents.

Quantifying Distribution of Flow Cytometric TCR-Vβ Usage with Economic Statistics

Measuring changes of the T cell receptor (TCR) repertoire is important to many fields of medicine. Flow cytometry is a popular technique to study the TCR repertoire, as it quickly provides insight into the TCR-Vβ usage among well-defined populations of T cells. However, the interpretation of the flow cytometric data remains difficult, and subtle TCR repertoire changes may go undetected. Here, we introduce a novel means for analyzing the flow cytometric data on TCR-Vβ usage. By applying economic statistics, we calculated the Gini-TCR skewing index from the flow cytometric TCR-Vβ analysis. The Gini-TCR skewing index, which is a direct measure of TCR-Vβ distribution among T cells, allowed us to track subtle changes of the TCR repertoire among distinct populations of T cells. Application of the Gini-TCR skewing index to the flow cytometric TCR-Vβ analysis will greatly help to gain better understanding of the TCR repertoire in health and disease.

Increase in CD14+HLA-DR -/low myeloid-derived suppressor cells in hepatocellular carcinoma patients and its impact on prognosis

Myeloid-derived suppressor cells (MDSCs) are known as key immune regulators in various human malignancies, and it is reported that CD14(+)HLA-DR(-/low) MDSCs are increased in hepatocellular carcinoma (HCC) patients. However, the host factors that regulate the frequency and the effect on the prognosis of HCC patients are still unclear. We investigated these issues and clarified the relationships between a feature of MDSCs and host factors in HCC patients. We examined the frequency of MDSCs in 123 HCC patients, 30 chronic liver disease patients without HCC, and 13 healthy controls by flow cytometric analysis. The relationships between the clinical features and the frequency of MDSCs were analyzed. In 33 patients who received curative radiofrequency ablation (RFA) therapy, we examined the impact of MDSCs on HCC recurrence. The frequency of MDSCs in HCC patients was significantly increased. It was correlated with tumor progression, but not with the degree of liver fibrosis and inflammation. In terms of serum cytokines, the concentrations of IL-10, IL-13, and vascular endothelial growth factor were significantly correlated with the frequency of MDSCs. In HCC patients who received curative RFA therapy, the frequency of MDSCs after treatment showed various changes and was inversely correlated with recurrence-free survival time. The frequency of MDSCs is correlated with tumor progression, and this frequency after RFA is inversely correlated with the prognosis of HCC patients. Patients with a high frequency of MDSCs after RFA should be closely followed and the inhibition of MDSCs may improve the prognosis of patients.

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.

Rapid cell population identification in flow cytometry data

We have developed flowMeans, a time-efficient and accurate method for automated identification of cell populations in flow cytometry (FCM) data based on K-means clustering. Unlike traditional K-means, flowMeans can identify concave cell populations by modelling a single population with multiple clusters. flowMeans uses a change point detection algorithm to determine the number of sub-populations, enabling the method to be used in high throughput FCM data analysis pipelines. Our approach compares favorably to manual analysis by human experts and current state-of-the-art automated gating algorithms. flowMeans is freely available as an open source R package through Bioconductor.

Nine-color flow cytometry for accurate measurement of T cell subsets and cytokine responses. Part I: Panel design by an empiric approach

Polychromatic flow cytometry offers the unprecedented ability to investigate multiple antigens per cell. Unfortunately, unwanted spectral overlaps and compensation problems increase when more than four colors are used, but these problems can be minimized if staining combinations are chosen carefully. We used an empiric approach to design, test and identify six-color T cell immunophenotyping reagent panels that can be expanded to include three or more functional or other markers in the FITC, PE, and APC channels without significant spectral limitations. Thirty different six-color T cell surface antigen reagent panels were constructed to identify major T cell subsets and maturational subtypes as defined by CCR7 and CD45RA expression, while excluding monocytes, B and non-viable cells. Staining performance of each panel was compared on cryopreserved cells from a single healthy donor recorded on a multiparameter cell sorter. Ten of the thirty reagent panels offered reliable resolution of T cell major and maturational surface markers. Of these, two panels were selected that showed the least spectral overlap and resulting background increase in the FITC, PE, and APC channels. These channels were left unoccupied for inclusion of additional phenotypic or functional markers, such as cytokines. Careful reagent titration and testing of multiple candidate panels are necessary to ensure quality results in multiparametric measurements.

A cluster pattern algorithm for the analysis of multiparametric cell assays

The issue of multiparametric analysis of complex single cell assays of both static and flow cytometry (SC and FC, respectively) has become common in recent years. In such assays, the analysis of changes, applying common statistical parameters and tests, often fails to detect significant differences between the investigated samples. The cluster pattern similarity (CPS) measure between two sets of gated clusters is based on computing the difference between their density distribution functions' set points. The CPS was applied for the discrimination between two observations in a four-dimensional parameter space. The similarity coefficient (r) ranges between 0 (perfect similarity) to 1 (dissimilar). Three CPS validation tests were carried out: on the same stock samples of fluorescent beads, yielding very low r's (0, 0.066); and on two cell models: mitogenic stimulation of peripheral blood mononuclear cells (PBMC), and apoptosis induction in Jurkat T cell line by H2O2. In both latter cases, r indicated similarity (r < 0.23) within the same group, and dissimilarity (r > 0.48) otherwise. This classification and algorithm approach offers a measure of similarity between samples. It relies on the multidimensional pattern of the sample parameters. The algorithm compensates for environmental drifts in this apparatus and assay; it also may be applied to more than four dimensions.

[Main milestones of development and application of ductal cytometry at the Russian Federal Research Center for Radiology and Surgical Technology, St. Petersburg]

Ductal cytometry provides data on cellular DNA and RNA levels and overall profile of specific proteins identifiable by monoclonal antibodies. Results of its long-term use in clinical and oncological research are presented. Application of dosage ranging 0.28-1.1 mGy/sec was followed by stable 1.8-2-fold increase in the myelokariocyte profile cbering DNA synthesis. Bone marrow proliferation did not increase until relatively low dosage was used. A study of combined effects of prolonged gamma irradiation and lead and cadmium ions on rat's hemopoiesis pointed to radiation as the sole causative factor when cadmium chloride was used. Hemopoietic characteristics came back to normal when a combination of lead acetate and ionizing radiation was used, as a result of the oppositely directed action of the two factors. Standard monoclonal antibodies should not be employed for evaluating immunological vigor of patients with malignant gliomas due to the presence of a specific pathological link in their immune system.

Flow cytometric lymphocyte subset enumeration: 10 years of external quality assessment in the Benelux countries

A biannual external quality assessment (EQA) scheme for flow cytometric lymphocyte immunophenotyping is operational in the Benelux countries since 1996. We studied the effects of the methods used on assay outcome, and whether or not this EQA exercise was effective in reducing between-laboratory variation. Eighty test samples were distributed in 20 biannual send-outs. Per send-out, 50-71 participants were requested to enumerate CD3+, CD4+, and CD8+ T cells, B cells, and NK cells, and to provide methodological details. Participants received written debriefings with personalized recommendations after each send-out. For this report, data were analyzed using robust multivariate regression. Five variables were associated with significant positive or negative bias of absolute lymphocyte subset counts: (i) platform methodology (i.e., single-platform assays yielded lower CD4+ and CD8+ T-cell counts than did dual-platform assays); (ii) sample preparation technique (i.e., assays based on mononuclear cells isolation yielded lower T-cell counts than those based on red cell lysis); (iii) gating strategies based on CD45 and sideward scatter gating of lymphocytes yielded higher CD4+ T-cell counts than those based on "backgating" of lymphocytes guided by CD45 and CD14); (iv) stabilized samples were generally associated with higher lymphocyte subset counts than nonstabilized samples; and (v) laboratory. Platform methodology, sample stabilization, and laboratory also affected assay variability. With time, assay variability tended to decline; this trend was significant for B-cell counts only. In addition, significant bias and variability of results, independent of the variables tested for in this analysis, were also associated with individual laboratories. In spite of our recommendations, participants tended to standardize their techniques mainly with respect to sample preparation and gating strategies, but less with absolute counting techniques. Failure to fully standardize protocols may have led to only modest reductions in variability of results between laboratories.

Noninvasive time-dependent cytometry monitoring by digital holography

Using a digital holographic microscope setup, it is possible to measure dynamic volume changes in living cells. The cells were investigated time-dependently in transmission mode for different kinds of stimuli affecting their morphology. The measured phase shift was correlated to the cellular optical thickness, and then of the cell volume as well as the refractive index were calculated and interpreted. For the characterization of the digital holographic microscope setup, we have developed a transparent three-dimensional (3-D) reference chart that can be used as a lateral resolution chart and step-height resolution chart included in one substrate. For the monitoring of living cells, a biocompatible and autoclavable flow chamber was designed, which allows us to add, exchange, or dilute the fluid within the flow chamber. An integrated changeable coverslip enables inverse microscopic applications. Trypsinization, cell swelling and shrinking induced by osmolarity changes, and apoptosis served as model processes to elucidate the potential of the digital holographic microscopy (DHM).

Pharmacodynamic monitoring of the immunosuppressive therapy in patients after heart transplantation: Whole blood flow cytometric analysis of lymphocyte function

Despite therapeutic monitoring and daily measurements of blood concentrations (pharmacokinetics) of immunosuppressive medications, immunosuppressive therapy remains still a challenge after heart transplantation (HTx) due to drug interactions, toxicities and individual responses to drug effects. We established whole blood flow cytometric assays of lymphocyte function to assess the pharmacodynamics of immunosuppressive therapy and investigated both pharmacokinetic and pharmacodynamic approaches after HTx. Our results showed that pharmacodynamic measurements provide a more direct assessment of the functional activity of immunosuppressants on immune cells compared to drug level monitoring alone. The information from both pharmacokinetic and pharmacodynamic monitoring has the potential to increase the efficacy and safety of individual immunosuppressive therapy after HTx.

An internal positive control for the enumeration of CD45(+) and CD34(+) cells by flow cytometry allows monitoring of reagent and operator performance

BACKGROUND

Three-color flow cytometry assays are used to determine CD34(+) cell doses prior to stem cell transplantation. These assays require high-quality reagents that are dispensed accurately to ensure reproducible results. We have developed a flow cytometry assay for CD34(+) cells with an integral positive control (KG1a cells) for monitoring reagent and operator performance.

METHODS

The method was validated using samples from 127 allogeneic donations (42 BM, 85 PBSC) from healthy donors and 195 autologous donations (46 BM, 149 PBSC) from patients in remission from hematologic malignancies. The mean, SD and range of CD45(+) and CD34(+)cell counts were determined for each donation type. An internal control was used to assess performance of reagents and operators by comparison with a predetermined target value and an experienced operator.

RESULTS

Replicate studies showed the method to be accurate and precise, with KG1a cells at 97.7+/-3.9% of the target value and a CV of 4.0%. In routine use over 322 samples, the accuracy was 91.7+/-17.7% of the target value, with a CV of 19.3%. Investigations into the cause of the reduced precision showed that reagents performed consistently well but operator performance was variable, with two of six operators significantly under-dispensing KG1a cells.

DISCUSSION

This study validates our three-color flow cytometry assay and demonstrates that KG1a cells may be used to monitor test performance in the routine working environment. In addition to monitoring performance within a single laboratory, its wider use in multicenter studies may be helpful regarding standardization of methods.

The human immunodeficiency virus epidemic: a race against time for millions and the role of flow cytometry. A Caribbean and resource-constrained country perspective

There is a race against time for millions in the world today. Both the technology and the manpower are currently available to deliver the services that are required to meet the needs of the 40 million people currently living with HIV/AIDS, but at what price? The reality is therefore that we are a long shot away from this realization. What are the facts and why have we not achieved even the simplest deadlines set by the World Health Organization (WHO)? Are these objectives realistic? What role does hard science have to play in the search for cost-effective solutions and futuristic effective options? To stem this unrelenting epidemic and convert the natural history of the disorder in those already living with the virus into one of chronicity, rather than one characterized by a dehumanizing and stigmatized death, requires a global commitment at all levels. This discussion examines the reality and offers a snapshot of capacity and experiences in the developing world. Crucially, it looks at the immediate and long term role of flow cytometry in the expanded care and treatment programs for developing nations.

Establishment of a flow cytometric assay for determination of human platelet glycoprotein VI based on a mouse polyclonal antibody

Glycoprotein VI (GPVI) is the major signaling receptor for collagen on platelets. Recent studies suggest that the surface density of GPVI is related to the activation of platelets by collagen. To measure the level of GPVI on platelets, a mouse polyclonal antibody BJ010 was prepared using an amplified fragment of extracellular domain in GPVI. The specific reactivity of BJ010 was identified by anti-GPVI specific monoclonal antibody 11a12 using immunoprecipitation, sandwich enzyme-linked immunosorbent assay (ELISA) and flow cytometry. The antibody BJ010 recognized both native and denatured human GPVI so that it was used to set up a flow cytometric assay to detect the level of GPVI in normal subjects. The relative level of GPVI on platelets was detected in 101 healthydonors. The median geometric mean fluorescence intensity (GMFI) of platelet GPVI level was 57.7. The variation between minimum and maximum values of platelet GPVI and integrin alpha2beta1 were found to be 3.5- and 4.1-fold, respectively, in the normal subjects. There was a week correlation between the amount of GPVI and integrin alpha2beta1 on platelet surfaces. For the method, the intraassay and interassay coefficient of variation was 6.3% and 8.8%, respectively. The flow cytometric assay described here provides a simple, reliable, reproducible, and readily available means of quantitation of collagen receptor GPVI density on the platelet surface in a larger number of blood samples.

Validation of Primary CD4 Gating as an Affordable Strategy for Absolute CD4 Counting in Cambodia

OBJECTIVE

To validate primary CD4 gating in lysed whole blood for absolute CD4 counts in fresh and aged blood using an affordable compact volumetric commercial flow cytometer.

DESIGN

Comparison of CD4 counts between the FACSCount and the 2-parameter CyFlow SL Green.

METHODS

One hundred twenty fresh blood samples from patients likely to be infected with HIV were simultaneously run on a FACSCount at the Pasteur Institute of Cambodia and on a CyFlow SL Green at the Sihanouk Hospital Center of Hope (SHCH), Phnom Penh, Cambodia. Intra- and interrun precision was assessed using 2 blood samples. Stability of CD4 counting in blood stored up to 96 hours at room temperature was assessed using 27 blood samples.

RESULTS

CD4 counts on the CyFlow SL Green and on the FACSCount correlated well apart from a relative bias (R = 0.993, bias of -9.5%, 95% confidence interval [CI]: -11.8% to -7.1%, limits of agreement: -32.5% to 13.6%). Intra- and interrun variability ranged from 3% to 5% and from 5% to 6%, respectively. CD4 counts on aged blood using the CyFlow SL Green showed an interassay variability of <10%.

CONCLUSIONS

Primary CD4 gating in lysed whole blood using the CyFlow SL Green is an affordable and precise method for CD4 counting. Because the fluorescence (FL) and light scatter signals have to be analyzed manually, however, intensive training of the technician and/or operator is imperative.

Patterns of immune response to a vaccine or virus as measured by intracellular cytokine staining in flow cytometry: hypothesis generation and comparison of groups

Candidate HIV vaccines must show an immune response in order to be considered for further testing and development. What constitutes a "response," however, is still not clear. While the hunt for a protective vaccine continues, hypotheses are being formed by studying the immune responses across cohorts of people with differing responses to the infection, as well as the immune responses formed by healthy people to other viruses, ones that are generally common and well controlled. Here we examine the functional profile of the immune responses of a group of HIV+ long-term non-progressors as measured by intracellular cytokine staining using polychromatic flow cytometry, and compare these responses to those of a larger group of other HIV+ people. We describe some of the types of patterns in immune response that are of interest to vaccine researchers, and compare several statistical tests appropriate for this type of data.

A new automated flow cytometry data analysis approach for the diagnostic screening of neoplastic B-cell disorders in peripheral blood samples with absolute lymphocytosis

Currently, multiparameter flow cytometry immunophenotyping is the selected method for the differential diagnostic screening between reactive lymphocytosis and neoplastic B-cell chronic lymphoproliferative disorders (B-CLPD). Despite this, current multiparameter flow cytometry data analysis approaches still remain subjective due to the need of experienced personnel for both data analysis and interpretation of the results. In this study, we describe and validate a new automated method based on vector quantization algorithms to analyze multiparameter flow cytometry immunophenotyping data in a series of 307 peripheral blood (PB) samples. Our results show that the automated method of analysis proposed compares well with currently used manual approach and significantly improves semiautomated approaches and, that by using it, a highly efficient discrimination with 100% specificity and 100% sensitivity can be made between normal/reactive PB samples and cases with B-CLPD based on the total B-cell number and/or the sIgkappa+/sIglambda+ B-cell ratio. In addition, the method proved to be able to detect the presence of pathologic neoplastic B-cells even when these are present at low frequencies (<5% of all lymphocytes in the sample) and in poor-quality samples enriched in 'noise' events.

The repercussions of implementing flow cytometry as a single HLA antibody screening technique in prospective renal transplant recipients

In an effort to replace the complement-dependent cytotoxicity test (CDC) with a more sensitive single technique we looked at flow cytometry as a possible replacement. The Flow PRA Bead technique (One Lambda) performed well in our laboratory. Although as expected this technique was more sensitive and specific than CDC, there remained 11 samples from eight patients which were flow negative, CDC positive. The results of various antibody identification tests on these samples prompted us to alter the positive selection criteria which we had been using on our routine screening with the Flow PRA Beads and persuaded us that the initial CDC result was correctly positive in nine of the 11 samples.

Comparison of bone marrow and peripheral blood ZAP-70 status examined by flow cytometric immunophenotyping in patients with chronic lymphocytic leukemia

BACKGROUND

: The mutational status of the immunoglobulin heavy chain variable gene in patients with chronic lymphocytic leukemia correlates with prognosis. Patients with mutated IgVH genes fare better than those with unmutated genes. Gene expression profiling studies identified the tyrosine kinase ZAP-70 to be expressed in unmutated CLL samples. Flow cytometric examination of ZAP-70 expression in tumor cells has been proposed to be a convenient surrogate marker for IgVH mutational status. However, a few studies have shown a small number of discordant results between ZAP-70 positivity, IgVH mutational status, and clinical outcome. There have been no reported studies comparing bone marrow samples with peripheral blood for ZAP-70 expression in CLL patients.

METHODS

: We searched our flow cytometry files from October 2004 through April 2006 and identified CLL in 311 bone marrow and peripheral blood specimens from 256 patients. We defined ZAP-70 positivity as greater than 30% of the CD19(+) B-cells above the isotype control value that coexpress ZAP-70. Statistical analyses were performed using the Fisher exact test and student t-test.

RESULTS

: A significantly greater number of bone marrow specimens were positive for ZAP-70 when compared with the number of peripheral blood specimens. Of all the ZAP-70 negative specimens, CLL cells from bone marrow had a greater mean percentage of ZAP-70 positive cells when compared with the CLL cells from peripheral blood. Finally, six patients were identified who were ZAP-70 positive in the bone marrow but ZAP-70 negative in the peripheral blood.

CONCLUSIONS

: These results may be due to either an increase in the false positive rate in bone marrow specimens or to an intrinsic feature of CLL cells in the compartment that is biologically distinct from peripheral tumor cells. As prognosis and treatment decisions may be based on ZAP-70 results from either specimen type, it is prudent to further examine this observation. (c) 2006 International Society for Analytical Cytology.

Kolmogorov–Smirnov statistical test for analysis of ZAP-70 expression in B-CLL, compared with quantitative PCR and IgVH mutation status

BACKGROUND

ZAP-70 has been proposed as a surrogate marker for immunoglobulin heavy-chain variable region (IgV(H)) mutation status, which is known as a prognostic marker in B-cell chronic lymphocytic leukemia (CLL). The flow cytometric analysis of ZAP-70 suffers from difficulties in standardization and interpretation. We applied the Kolmogorov-Smirnov (KS) statistical test to make analysis more straightforward.

METHODS

We examined ZAP-70 expression by flow cytometry in 53 patients with CLL. Analysis was performed as initially described by Crespo et al. (New England J Med 2003; 348:1764-1775) and alternatively by application of the KS statistical test comparing T cells with B cells. Receiver-operating-characteristics (ROC)-curve analyses were performed to determine the optimal cut-off values for ZAP-70 measured by the two approaches. ZAP-70 protein expression was compared with ZAP-70 mRNA expression measured by a quantitative PCR (qPCR) and with the IgV(H) mutation status.

RESULTS

Both flow cytometric analyses correlated well with the molecular technique and proved to be of equal value in predicting the IgV(H) mutation status. Applying the KS test is reproducible, simple, straightforward, and overcomes a number of difficulties encountered in the Crespo-method.

CONCLUSIONS

The KS statistical test is an essential part of the software delivered with modern routine analytical flow cytometers and is well suited for analysis of ZAP-70 expression in CLL.

A simple correction for cell autofluorescence for multiparameter cell-based analysis of human solid tumors

BACKGROUND

Corrections that have been proposed to minimize the unwanted contribution of cell autofluorescence to the total fluorescence signal often require either specialized instrumentation or the sacrifice of a data channel so as to perform a measurement that can be used to correct for autofluorescence in individual cells. Here we propose a simple cell by cell correction for autofluorescence that is suitable for multiparameter laser scanning cytometry (LSC) studies in human solid tumors that relies on the ratio of mean autofluorescence to mean total cell fluorescence (mean Flauto/mean Fltotal). This approach assumes a correlation between the autofluorescence component and the total signal in individual cells. This correction does not require specialized instrumentation, and does not sacrifice a data channel in multiparameter studies. A potential disadvantage is that errors may be introduced by the assumption of a correlation between the two components of the total fluorescence signal in individual cells in samples in which no such correlation exists.

METHODS

Distributions of cell autofluorescence and total Her-2/neu cell fluorescence were obtained separately by LSC in three human breast cancer cell lines and in three samples of primary human lung cancer. In the breast cancer cell lines, autofluorescence measurements and Her-2/neu measurements were also obtained on the same cells.

RESULTS

We show that there is a partial correlation between autofluorescence and total Her-2/neu/FITC fluorescence in individual cells in the three breast cancer cell lines. We also show that the results of a ratio-based autofluorescence correction agree with those based on a true cell by cell correction. Computer simulation studies suggest that in samples with no correlation between the autofluorescence component and the true probe/dye fluorescence component, the ratio correction produces robust estimates of the mean true fluorescence signal, with relatively small but systematic underestimates of the coefficient of variation of such measurements under conditions commonly encountered in the measurement of human solid tumors.

CONCLUSIONS

A simple cell by cell correction for autofluorescence based on the ratio of mean Flauto to mean Fltotal can be applied in cell samples in which there is a correlation between cell autofluorescence and true probe/dye fluorescence in individual cells. In cell samples that lack this correlation, or in which it is not known whether such a correlation exists, this correction can be used with the reservation that there is a systematic but relatively small underestimation of the degree of variability of the measurements.

Classifying Antibodies Using Flow Cytometry Data: Class Prediction and Class Discovery

Classifying monoclonal antibodies, based on the similarity of their binding to the proteins (antigens) on the surface of blood cells, is essential for progress in immunology, hematology and clinical medicine. The collaborative efforts of researchers from many countries have led to the classification of thousands of antibodies into 247 clusters of differentiation (CD). Classification is based on flow cytometry and biochemical data. In preliminary classifications of antibodies based on flow cytometry data, the object requiring classification (an antibody) is described by a set of random samples from unknown densities of fluorescence intensity. An individual sample is collected in the experiment, where a population of cells of a certain type is stained by the identical fluorescently marked replicates of the antibody of interest. Samples are collected for multiple cell types. The classification problems of interest include identifying new CDs (class discovery or unsupervised learning) and assigning new antibodies to the known CD clusters (class prediction or supervised learning). These problems have attracted limited attention from statisticians. We recommend a novel approach to the classification process in which a computer algorithm suggests to the analyst the subset of the "most appropriate" classifications of an antibody in class prediction problems or the "most similar" pairs/ groups of antibodies in class discovery problems. The suggested algorithm speeds up the analysis of a flow cytometry data by a factor 10-20. This allows the analyst to focus on the interpretation of the automatically suggested preliminary classification solutions and on planning the subsequent biochemical experiments.

Panleucogating as an accurate and affordable flow cytometric protocol to analyse lymphocyte subsets among HIV-positive patients on HAART treatment in Mozambique

In Africa tens of millions of people are HIV+. Prevention alone is not effective, and needs to be coupled with anti-retroviral treatment (HAART). Laboratory tests as CD4+ T cell count are fundamental tools in HIV disease monitoring, but they require costly equipment, reagents and specialised manpower. The goal of this study was to minimise and optimise the reagents needed for a reliable routine CD4+ cell count in a resource-poor setting (Mozambique). Panleucogating protocol (PLG), requires two antibodies only, CD45 and CD4, or three if CD8 is requested for special clinical reasons. PLG was compared with the current protocol used in two Mozambique hospitals, based on FSC/SSC gating and CD3/CD4/CD8 staining. 189 samples from HIV+ patients, included in the Community of Sant'Egidio's DREAM program and on HAART were processed with both protocols. The overall correlation of the lymphocyte subsets measurements was satisfactory, with r2 always >0.96. The Bland-Altman analysis of CD4+ cell count showed a negative bias when CD4+ cells were <15%, due to the imprecise FSC/SSC gating used previously. When CD4+ cells were >15% the negative bias tended to zero, further confirming the better quality of the PLG gating strategy. Two- or three color PLG protocol, in double platform, currently seems the most accurate and affordable method to monitor CD4+ lymphocytes and CD4/CD8 ratio by flow cytometry in resource-poor medical settings.

Multiplexed AtheNA multi-lyte immunoassay for ANA screening in autoimmune diseases

BACKGROUND

Multiplexed assays using fluorescence microspheres is an exciting technology with multiple applications including the detection of antinuclear autoantibodies (ANA) and autoantibody profiles. It is a rapid, sensitive and automatic method for simultaneous quantitative detection of several autoantibodies. The aim of our study was to determinate ANA and other autoantibodies to the nine extractable nuclear antigens by the AtheNA Multi-Lyte ANA system and compare the results achieved by this method to the routinely used enzyme immunoassay.

METHODS

Four hundred eighteen serum samples were tested utililizing the multiplexed method: 96 healthy donors, 86 requested ANA specimens obtained from routine lab, and 236 samples from patients with known autoimmune diseases (43-scleroderma, 113-systemic lupus erythematosus, 38-Sjogren's syndrome, and 42 rheumatoid arthritis). The ANA and antibodies to nine different analytes (SS/A, SS/B, Sm, RNP, Jo-1, Scl-70, dsDNA, Centromere B and Histone) were tested.

RESULTS

ANA screening by AtheNA system revealed high concordance of 99 and 97.7% with the enzyme immunoassay test in samples obtained from healthy donors and ANA requested samples, respectively. Evaluation of autoimmune disease-related samples for ANA by AtheNA technology also confirmed a high rate of concordance of 92-97.7% and correlated with the enzyme immunoassay. Positive discrepant results were found for Scl-70 specificity in 12.7% of SLE specimens by AtheNA technology, while all tested sera were negative for this antibody by enzyme immunoassay. Negative discrepant results were observed by the AtheNA system for anti-dsDNA. The sera (15 randomly obtained samples from SLE patients) were positive for anti-dsDNA in 50% of samples in Farr assay and 55% in enzyme immunoassay, respectively.

CONCLUSION

We suggest that the AtheNA technology may be a useful diagnostic tool for ANA screening. Additional investigations are required to compare an analytic performance between AtheNA and routine methods in determination of the individual autoantibody profile.

Effects of magnetic-activated cell sorting on sperm motility and cryosurvival rates

OBJECTIVE

To evaluate the effect of magnetic-activated cell sorting in cryopreservation-thawing protocols on sperm motility and cryosurvival rate.

DESIGN

Prospective-controlled study.

SETTING

Andrology department at a university-based medical institution.

PATIENT(S)

Ten healthy volunteer sperm donors.

INTERVENTION(S)

Sperm populations were separated using annexin-V magnetic-activated cell sorting before and after the cryopreservation-thawing process.

MAIN OUTCOME MEASURE(S)

Sperm motility and cryosurvival rate.

RESULT(S)

Annexin-negative sperm separated by magnetic-activated cell sorting had statistically significantly higher motility following cryopreservation-thawing than sperm that were not separated. Similarly, annexin-negative spermatozoa also had higher cryosurvival rate than sperm cryopreserved without magnetic-activated cell sorting and sperm that were annexin-positive.

CONCLUSION(S)

Superparamagnetic annexin V-conjugated microbeads can separate spermatozoa with externalized phosphatidylserine, which is considered one of the early features of late apoptosis. The separation of a distinctive population of nonapoptotic spermatozoa with intact membranes may optimize the cryopreservation-thawing outcome. Magnetic-activated cell sorting using annexin-V microbeads enhances sperm motility and cryosurvival rates following cryopreservation.

Concept for the Traceability of Fluorescence (Beads) in Flow Cytometry: Exploiting Saturation and Microscopic Single Molecule Bleaching

We have determined the fluorescence yield of stained micro beads, used for calibration purposes in flow cytometry, as function of the irradiance of the exciting laser beam. A rate equation model has been applied to derive the number of fluorescence molecules carried by each micro bead. To derive in situ photo-physical properties of the specific dye, required for the rate equation model, we discuss an approach based on flow cytometric sorting of micro beads, which have passed two laser beams with properly chosen different irradiances, and subsequent observation of single molecule bleaching employing high sensitivity microscopy. The feasibility of our approach is demonstrated presenting first results concerning saturation of fluorescence of beads in flow and single molecule bleaching by high sensitivity microscopy.

Skew-Laplace distribution in Gram-negative bacterial axenic cultures: new insights into intrinsic cellular heterogeneity

The application of flow cytometry and skew-Laplace statistical analysis to assess cellular heterogeneity in Gram-negative axenic cultures is reported. In particular, fit to the log-skew-Laplace distribution for cellular side scatter or ‘granulosity’ is reported, and a number of theoretical and applied issues are considered in relation to the biological significance of this fit.