Sometimes simpler is better: VLog, a general but easy-to-implement log-like transform for cytometry.

The fundamental purpose of log and log-like transforms for cytometry is to make measured population variabilities as uniform as possible. The long-standing success of the log transform was its ability to stabilize linearly increasing gain-dependent uncertainties and the success of the log-like transforms is that they extend this notion to include zero and negative measurement values. This study derives and examines a transform called VLog that stabilizes the three general sources of variability: (1) gain-dependent variability, (2) photo-electron counting error, and (3) signal-independent sources of error. Somewhat surprisingly, this transform has a closed-form solution and therefore is relatively simple to implement. By including some quantitation elements in its formulation, the shape-dependent arguments, α and ß, usually do not require optimization for different datasets. The simplicity and generality of the transform may make it a useful tool for cytometry and possibly other technologies. © 2016 International Society for Advancement of Cytometry.

Impaired Subset Progression and Polyfunctionality of T Cells in Mice Exposed to Methamphetamine during Chronic LCMV Infection.

Methamphetamine (METH) is a widely used psychostimulant that severely impacts the host's innate and adaptive immune systems and has profound immunological implications. T cells play a critical role in orchestrating immune responses. We have shown recently how chronic exposure to METH affects T cell activation using a murine model of lymphocytic choriomeningitis virus (LCMV) infection. Using the TriCOM (trinary state combinations) feature of GemStone™ to study the polyfunctionality of T cells, we have analyzed how METH affected the cytokine production pattern over the course of chronic LCMV infection. Furthermore, we have studied in detail the effects of METH on splenic T cell functions, such as cytokine production and degranulation, and how they regulate each other. We used the Probability State Modeling (PSM) program to visualize the differentiation of effector/memory T cell subsets during LCMV infection and analyze the effects of METH on T cell subset progression. We recently demonstrated that METH increased PD-1 expression on T cells during viral infection. In this study, we further analyzed the impact of PD-1 expression on T cell functional markers as well as its expression in the effector/memory subsets. Overall, our study indicates that analyzing polyfunctionality of T cells can provide additional insight into T cell effector functions. Analysis of T cell heterogeneity is important to highlight changes in the evolution of memory/effector functions during chronic viral infections. Our study also highlights the impact of METH on PD-1 expression and its consequences on T cell responses.

Probability state modeling theory.

As the technology of cytometry matures, there is mounting pressure to address two major issues with data analyses. The first issue is to develop new analysis methods for high-dimensional data that can directly reveal and quantify important characteristics associated with complex cellular biology. The other issue is to replace subjective and inaccurate gating with automated methods that objectively define subpopulations and account for population overlap due to measurement uncertainty. Probability state modeling (PSM) is a technique that addresses both of these issues. The theory and important algorithms associated with PSM are presented along with simple examples and general strategies for autonomous analyses. PSM is leveraged to better understand B-cell ontogeny in bone marrow in a companion Cytometry Part B manuscript. Three short relevant videos are available in the online supporting information for both of these papers. PSM avoids the dimensionality barrier normally associated with high-dimensionality modeling by using broadened quantile functions instead of frequency functions to represent the modulation of cellular epitopes as cells differentiate. Since modeling programs ultimately minimize or maximize one or more objective functions, they are particularly amenable to automation and, therefore, represent a viable alternative to subjective and inaccurate gating approaches.

Human B-cell and progenitor stages as determined by probability state modeling of multidimensional cytometry data.

BACKGROUND: Human progenitor and B-cell development is a highly regulated process characterized by the ordered differential expression of numerous cell-surface and intracytoplasmic antigens. This study investigates the underlying coordination of these modulations by examining a series of normal bone marrow samples with the method of probability state modeling or PSM. RESULTS: The study is divided into two sections. The first section examines B-cell stages subsequent to CD19 up-regulation. The second section assesses an earlier differentiation stage before and including CD19 up-regulation. POST-CD19 ANTIGENIC UP-REGULATION: Statistical analyses of cytometry data derived from sixteen normal bone marrow specimens revealed that B cells have at least three distinct coordinated changes, forming four stages labeled as B1, B2, B3, and B4. At the end of B1; CD34 antigen expression down-regulates with TdT while CD45, CD81, and CD20 slightly up-regulate. At the end of B2, CD45 and CD20 up-regulate. At the end of B3 and beginning of B4; CD10, CD38, and CD81 down-regulate while CD22 and CD44 up-regulate. PRE-CD19 ANTIGENIC UP-REGULATION: Statistical analysis of ten normal bone marrows revealed that there are at least two measurable coordinated changes with progenitors, forming three stages labeled as P1, P2, and P3. At the end of P1, CD38 up-regulates. At the end of P2; CD19, CD10, CD81, CD22, and CD9 up-regulate while CD44 down-regulates slightly. CONCLUSIONS: These objective results yield a clearer immunophenotypic picture of the underlying cellular mechanisms that are operating in these important developmental processes. Also, unambiguously determined stages define what is meant by "normal" B-cell development and may serve as a preliminary step for the development of highly sensitive minimum residual disease detection systems. A companion article is simultaneously being published in Cytometry Part A that will explain in further detail the theory behind PSM. Three short relevant videos are available in the online supporting information for both of these papers.

Automated analysis of flow cytometric data for measuring neutrophil CD64 expression using a multi-instrument compatible probability state model.

BACKGROUND: Leuko64™ (Trillium Diagnostics) is a flow cytometric assay that measures neutrophil CD64 expression and serves as an in vitro indicator of infection/sepsis or the presence of a systemic acute inflammatory response. Leuko64 assay currently utilizes QuantiCALC, a semiautomated software that employs cluster algorithms to define cell populations. The software reduces subjective gating decisions, resulting in interanalyst variability of <5%. We evaluated a completely automated approach to measuring neutrophil CD64 expression using GemStone™ (Verity Software House) and probability state modeling (PSM). METHODS: Four hundred and fifty-seven human blood samples were processed using the Leuko64 assay. Samples were analyzed on four different flow cytometer models: BD FACSCanto II, BD FACScan, BC Gallios/Navios, and BC FC500. A probability state model was designed to identify calibration beads and three leukocyte subpopulations based on differences in intensity levels of several parameters. PSM automatically calculates CD64 index values for each cell population using equations programmed into the model. GemStone software uses PSM that requires no operator intervention, thus totally automating data analysis and internal quality control flagging. Expert analysis with the predicate method (QuantiCALC) was performed. Interanalyst precision was evaluated for both methods of data analysis. RESULTS: PSM with GemStone correlates well with the expert manual analysis, r(2) = 0.99675 for the neutrophil CD64 index values with no intermethod bias detected. The average interanalyst imprecision for the QuantiCALC method was 1.06% (range 0.00-7.94%), which was reduced to 0.00% with the GemStone PSM. The operator-to-operator agreement in GemStone was a perfect correlation, r(2) = 1.000. CONCLUSION: Automated quantification of CD64 index values produced results that strongly correlate with expert analysis using a standard gate-based data analysis method. PSM successfully evaluated flow cytometric data generated by multiple instruments across multiple lots of the Leuko64 kit in all 457 cases. The probability-based method provides greater objectivity, higher data analysis speed, and allows for greater precision for in vitro diagnostic flow cytometric assays.

Isolation and culture of cells from the nephrogenic zone of the embryonic mouse kidney.

Embryonic development of the kidney has been extensively studied both as a model for epithelial-mesenchymal interaction in organogenesis and to gain understanding of the origins of congenital kidney disease. More recently, the possibility of steering naïve embryonic stem cells toward nephrogenic fates has been explored in the emerging field of regenerative medicine. Genetic studies in the mouse have identified several pathways required for kidney development, and a global catalog of gene transcription in the organ has recently been generated http://www.gudmap.org/, providing numerous candidate regulators of essential developmental functions. Organogenesis of the rodent kidney can be studied in organ culture, and many reports have used this approach to analyze outcomes of either applying candidate proteins or knocking down the expression of candidate genes using siRNA or morpholinos. However, the applicability of organ culture to the study of signaling that regulates stem/progenitor cell differentiation versus renewal in the developing kidney is limited as cultured organs contain a compact extracellular matrix limiting diffusion of macromolecules and virus particles. To study the cell signaling events that influence the stem/progenitor cell niche in the kidney we have developed a primary cell system that establishes the nephrogenic zone or progenitor cell niche of the developing kidney ex vivo in isolation from the epithelial inducer of differentiation. Using limited enzymatic digestion, nephrogenic zone cells can be selectively liberated from developing kidneys at E17.5. Following filtration, these cells can be cultured as an irregular monolayer using optimized conditions. Marker gene analysis demonstrates that these cultures contain a distribution of cell types characteristic of the nephrogenic zone in vivo, and that they maintain appropriate marker gene expression during the culture period. These cells are highly accessible to small molecule and recombinant protein treatment, and importantly also to viral transduction, which greatly facilitates the study of candidate stem/progenitor cell regulator effects. Basic cell biological parameters such as proliferation and cell death as well as changes in expression of molecular markers characteristic of nephron stem/progenitor cells in vivo can be successfully used as experimental outcomes. Ongoing work in our laboratory using this novel primary cell technique aims to uncover basic mechanisms governing the regulation of self-renewal versus differentiation in nephron stem/progenitor cells.

Hyperactivation and proliferation of lymphocytes from the spleens of flaky skin (fsn) mutant mice.

Mice homozygous for the flaky skin (fsn) single gene mutation have a severe hyperproliferative disease resulting in a complex phenotype, which includes widespread inflammation and autoimmunity. This study sought to characterize lymphocyte function of flaky skin mutant mice. Flaky skin lymphocytes show enhanced proliferation with in vitro mitogen stimulated spleen cells, as well as enriched splenic B- and T-cells. The production of IL-4 by fsn/fsn T-lymphocytes is increased dramatically compared with normal controls. Flaky skin lymphocytes exhibited increased responsiveness to IL-2, IL-4 and IL-7 in the absence of pre-activation, enhanced IgE production in response to ovalbumin immunization, and constitutive STAT6 activation. These data indicate that the cytokines IL-2, IL-4 and IL-7 likely contribute to the lymphocyte activation in fsn/fsn mutant mice. This lymphocyte hyperactivation may result in the development of systemic autoimmunity in fsn/fsn mutant mice.