Carboxyfluorescein diacetate succinimidyl ester and the virgin lymphocyte: a marriage made in heaven

Carboxyfluorescein diacetate succinimidyl ester (CFSE) labelling of na?ve lymphocyte populations provides unique insights into the immune response. The clonal nature of immune responses, necessitating clonal expansion to achieve a sufficiently large number of Ag-reactive effector cells, combined with the dependence of lymphocyte differentiation on cell division, underlie the usefulness of CFSE in understanding the factors that regulate responses both in vitro and in vivo. We have combined CFSE labelling with Ag receptor transgenic models, using seven channel flow cytometry to track the correlation between cell division and a number of other parameters, such as surface expression of activation markers, cytokine receptors and homing receptors, cytokine production, cytotoxic activity and indicators of apoptosis. Our data have allowed us to classify and understand immune responses in novel ways, suggesting many further avenues of enquiry and indicating previously unrecognized relationships between cell division and eventual cell fate.     

Divided we stand: tracking cell proliferation with carboxyfluorescein diacetate succinimidyl ester

Most techniques for assessing cell division can either detect limited numbers of cell divisions (bromodeoxyuridine incorporation) or only quantify overall proliferation (tritiated thymidine incorporation). In the majority of cases, viable cells of known division history cannot subsequently be obtained for functional studies. The cells of the immune system undergo marked proliferation and differentiation during the course of an immune response. The relative lack of an organized structure of the lymphohaemopoietic system, in contrast with other organ systems, makes lineage interrelationships difficult to study. Coupled with the remarkable degree of mobility engendered by recirculation, the differentiation occurring along with cell division in the immune system has not been readily accessible for investigation. The present article reviews the development of a cell division analysis procedure based on the quantitative serial halving of the membrane permeant, stably incorporating fluorescent dye carboxyfluorescein diacetate succinimidyl ester (CFSE or CFDA, SE). The technique can be used both in vitro and in vivo, allowing eight to 10 successive divisions to be resolved by flow cytometry. Furthermore, viable cells from defined generation numbers can be sorted by flow cytometry for functional analysis.     

Stochastic analogues of deterministic single-species population models

Although single-species deterministic difference equations have long been used in modeling the dynamics of animal populations, little attention has been paid to how stochasticity should be incorporated into these models. By deriving stochastic analogues to difference equations from first principles, we show that the form of these models depends on whether noise in the population process is demographic or environmental. When noise is demographic, we argue that variance around the expectation is proportional to the expectation. When noise is environmental the variance depends in a non-trivial way on how variation enters into model parameters, but we argue that if the environment affects the population multiplicatively then variance is proportional to the square of the expectation. We compare various stochastic analogues of the Ricker map model by fitting them, using maximum likelihood estimation, to data generated from an individual-based model and the weevil data of Utida. Our demographic models are significantly better than our environmental models at fitting noise generated by population processes where noise is mainly demographic. However, the traditionally chosen stochastic analogues to deterministic models--additive normally distributed noise and multiplicative lognormally distributed noise--generally fit all data sets well. Thus, the form of the variance does play a role in the fitting of models to ecological time series, but may not be important in practice as first supposed.     

Computation of steady-state probability distributions in stochastic models of cellular networks

Cellular processes are "noisy". In each cell, concentrations of molecules are subject to random fluctuations due to the small numbers of these molecules and to environmental perturbations. While noise varies with time, it is often measured at steady state, for example by flow cytometry. When interrogating aspects of a cellular network by such steady-state measurements of network components, a key need is to develop efficient methods to simulate and compute these distributions. We describe innovations in stochastic modeling coupled with approaches to this computational challenge: first, an approach to modeling intrinsic noise via solution of the chemical master equation, and second, a convolution technique to account for contributions of extrinsic noise. We show how these techniques can be combined in a streamlined procedure for evaluation of different sources of variability in a biochemical network. Evaluation and illustrations are given in analysis of two well-characterized synthetic gene circuits, as well as a signaling network underlying the mammalian cell cycle entry.     

Computational analysis of CFSE proliferation assay

CFSE based tracking of the lymphocyte proliferation using flow cytometry is a powerful experimental technique in immunology allowing for the tracing of labelled cell populations over time in terms of the number of divisions cells undergone. Interpretation and understanding of such population data can be greatly improved through the use of mathematical modelling. We apply a heterogenous linear compartmental model, described by a system of ordinary differential equations similar to those proposed by Kendall. This model allows division number-dependent rates of cell proliferation and death and describes the rate of changes in the numbers of cells having undergone j divisions. The experimental data set that we specifically analyze specifies the following characteristics of the kinetics of PHA-induced human T lymphocyte proliferation assay in vitroL (1) the total number of live cells, (2) the total number of dead but not disintegrated cells and (3) the number of cells divided j times. Following the maximum likelihood approach for data fitting, we estimate the model parameters which, in particular, present the CTL birth- and death rate “functions”. It is the first study of CFSE labelling data which convincingly shows that the lymphocyte proliferation and death both in vitro and in vivo are division number dependent. For the first time, the confidence in the estimated parameter values is analyzed by comparing three major methods: the technique based on the variance–covariance matrix, the profile-likelihood-based approach and the bootstrap technique. We compare results and performance of these methods with respect to their robustness and computational cost. We show that for evaluating mathematical models of differing complexity the information-theoretic approach, based upon indicators measuring the information loss for a particular model (Kullback–Leibler information), provides a consistent basis. We specifically discuss methodological and computational difficulties in parameter identification with CFSE data, e.g. the loss of confidence in the parameter estimates starting around the sixth division. Overall, our study suggests that the heterogeneity inherent in cell kinetics should be explicitly incorporated into the structure of mathematical models.      

Immune monitoring in xenotransplantation: the multiparameter flow cytometric mixed lymphocyte culture assay

Xenotransplantation requires monitoring of complex cellular interactions in vitro. A tool to monitor cell proliferation in detail would be instrumental in understanding these cellular interactions in heterogeneous xenogeneic lymphocyte cultures and in patients after xenotransplantation. To accomplish this, we used a fluorescent cell proliferation marker, 5,6-carboxyfluorescein diacetate succinimidyl ester (CFSE), in combination with flow cytometry. CFSE, a green fluorescent molecule, binds covalently to intracellular macromolecules. Each cell division reduces the fluorescent intensity per cell by half and shows a characteristic multipeak pattern in flow cytometric analysis. For this study, human lymphocytes were labeled with CFSE and cultured in the presence of irradiated porcine lymphocytes. Cell proliferation was detected in CFSE-labeled lymphocytes in both a single and a multiparameter flow cytometry setting. Concurrently, tritiated ((3)H) thymidine incorporation, a common method to measure gross cell proliferation, was assessed. The kinetics of CFSE-labeled cell proliferation correlated with (3)H-thymidine incorporation in that both methods showed a lag phase for days 1-3 and a log phase for days 4-7. Multiparameter flow cytometric monitoring of mixed lymphocyte cultures allowed phenotyping and assessment of viability of proliferating populations in heterogeneous xenogeneic stimulated human lymphocyte cultures and complemented the classical (3)H-thymidine incorporation assay. The use of this technique will allow a wide array of immunologic parameters to be measured in a heterogeneous xenogeneic mixed lymphocyte culture. The information gained from these assays is essential to understanding the biological significance of xenogeneic cellular interaction and for monitoring the immune status of the xenotransplanted patient.     

Stochastic Models of Lymphocyte Proliferation and Death

Quantitative understanding of the kinetics of lymphocyte proliferation and death upon activation with an antigen is crucial for elucidating factors determining the magnitude, duration and efficiency of the immune response. Recent advances in quantitative experimental techniques, in particular intracellular labeling and multi-channel flow cytometry, allow one to measure the population structure of proliferating and dying lymphocytes for several generations with high precision. These new experimental techniques require novel quantitative methods of analysis. We review several recent mathematical approaches used to describe and analyze cell proliferation data. Using a rigorous mathematical framework, we show that two commonly used models that are based on the theories of age-structured cell populations and of branching processes, are mathematically identical. We provide several simple analytical solutions for a model in which the distribution of inter-division times follows a gamma distribution and show that this model can fit both simulated and experimental data. We also show that the estimates of some critical kinetic parameters, such as the average inter-division time, obtained by fitting models to data may depend on the assumed distribution of inter-division times, highlighting the challenges in quantitative understanding of cell kinetics.     

Measuring lymphocyte proliferation, survival and differentiation using CFSE time-series data

Cellular proliferation is an essential feature of the adaptive immune response. The introduction of the division tracking dye carboxyfluorescein diacetate succinimidyl ester (CFSE) has made it possible to monitor the number of cell divisions during proliferation and to examine the relationship between proliferation and differentiation. Although qualitative examination of CFSE data may be useful, substantially more information about division and death rates can be extracted from quantitative CFSE time-series experiments. Quantitative methods can reveal in detail how lymphocyte proliferation and survival are regulated and altered by signals such as those received from co-stimulatory molecules, drugs and genetic polymorphisms. In this protocol, we present a detailed method for examining time-series data using graphical and computer-based procedures available to all experimenters.     

The Use of Carboxyfluorescein Diacetate Succinimidyl Ester (CFSE) to Monitor Lymphocyte Proliferation

Carboxyfluorescein succinimidyl ester (CFSE) is an effective and popular means to monitor lymphocyte division^1-3. CFSE covalently labels long-lived intracellular molecules with the fluorescent dye, carboxyfluorescein. Thus, when a CFSE-labeled cell divides, its progeny are endowed with half the number of carboxyfluorescein-tagged molecules and thus each cell division can be assessed by measuring the corresponding decrease in cell fluorescence via Flow cytometry. The capacity of CFSE to label lymphocyte populations with a high fluorescent intensity of exceptionally low variance, coupled with its low cell toxicity, make it an ideal dye to measure cell division. Since it is a fluorescein-based dye it is also compatible with a broad range of other fluorochromes making it applicable to multi-color flow cytometry. This article describes the procedures typically used for labeling mouse lymphocytes for the purpose of monitoring up to 8 cell divisions. These labeled cells can be used both for in vitro and in vivo studies.     

Cytokine flow cytometry: multiparametric approach to immune function analysis

More precise quantitation of cellular immune responses has become possible with the advent of single-cell assays of immune function, such as cytokine flow cytometry, enzyme-linked immunospot (ELISPOT), and MHC-peptide multimers. Cytokine flow cytometry is an attractive technique because it allows the detection of responses to whole antigens without regard to MHC restriction, while also collecting additional information on responding cells via multiparameter flow cytometry. In this review, we compare cytokine flow cytometry with other assays of immune function, summarize some of that data that have been collected in various disease states using cytokine flow cytometry, and describe some methodological improvements designed to increase the robustness, throughput, and information content of this technique. We hypothesize that a new generation of automated cytokine flow cytometry assays will allow elucidation of the correlates of protection for diseases involving cellular immunity, through application of these assays in more and large clinical trials.     

Neural organization and responses to complex stimuli in the dorsal cochlear nucleus.

The dorsal division of the cochlear nucleus (DCN) is the most complex of its subdivisions in terms of both anatomical organization and physiological response types. Hypotheses about the functional role of the DCN in hearing are as yet primitive, in part because the organizational complexity of the DCN has made development of a comprehensive and predictive model of its input-output processing difficult. The responses of DCN cells to complex stimuli, especially filtered noise, are interesting because they demonstrate properties that cannot be predicted, without further assumptions, from responses to narrow band stimuli, such as tones. In this paper, we discuss the functional organization of the DCN, i.e. the morphological organization of synaptic connections within the nucleus and the nature of synaptic interactions between its cells. We then discuss the responses of DCN principal cells to filtered noise stimuli that model the spectral sound localization cues produced by the pinna. These data imply that the DCN plays a role in interpreting sound localization cues; supporting evidence for such a role is discussed.     

On the impact of correlation between collaterally consanguineous cells on lymphocyte population dynamics

During an adaptive immune response, lymphocytes proliferate for five to twenty-five cell divisions, then stop and die over a period of weeks. Based on extensive flow cytometry data, Hawkins et al. (Proc Natl Acad Sci USA 104:5032–5037, 2007) introduced a cell-level stochastic model of lymphocyte population dynamics, called the Cyton Model, that accurately captures mean lymphocyte population size as a function of time. In Subramanian et al. (J Math Biol 56(6):861–892, 2008), we performed a branching process analysis of the Cyton Model and deduced from parameterizations for in vitro and in vivo data that the immune response is predictable despite each cell’s fate being highly variable. One drawback of flow cytometry data is that individual cells cannot be tracked, so that it is not possible to investigate dependencies in the fate of cells within family trees. In the absence of this information, while the Cyton Model abandons one of the usual assumptions of branching processes (the independence of lifetime and progeny number), it adopts another of the standard branching processes hypotheses: that the fates of progeny are stochastically independent. However, new experimental observations of lymphocytes show that the fates of cells in the same family tree are not stochastically independent. Hawkins et al. (2008, submitted) report on ciné lapse photography experiments where every founding cell’s family tree is recorded for a system of proliferating lymphocytes responding to a mitogenic stimulus. Data from these experiments demonstrate that the death-or-division fates of collaterally consanguineous cells (those in the same generation within a founding cell’s family tree) are strongly correlated, while there is little correlation between cells of distinct generations and between cells in distinct family trees. As this finding contrasts with one of the assumptions of the Cyton Model, in this paper we introduce three variants of the Cyton Model with increasing levels of collaterally consanguineous correlation structure to incorporate these new found dependencies. We investigate their impact on the predicted expected variability of cell population size. Mathematically we conclude that while the introduction of correlation structure leaves the mean population size unchanged from the Cyton Model, the variance of the population size distribution is typically larger. Biologically, through comparison of model predictions for Cyton Model parameterizations determined by in vitro and in vivo experiments, we deduce that if collaterally consanguineous correlation extends beyond cousins, then the immune response is less predictable than would be concluded from the original Cyton Model. That is, some of the variability seen in data that we previously attributed to experimental error could be due to intrinsic variability in the cell population size dynamics.      

携带HBV包膜大蛋白DNA疫苗的减毒沙门菌在小鼠诱导免疫应答

探索一种简便、有效的乙型肝炎病毒DNA疫苗免疫方法。将编码绿色荧光蛋白的真核表达质粒pEGFPN1转化到减毒鼠伤寒沙门菌SL7207,灌胃饲服BALB/c小鼠,流式细胞术检测出小鼠脾细胞内表达的绿色荧光蛋白;构建编码HBV包膜大蛋白的DNA疫苗pCIS1S2S,分别以SL7207为载体的口服途径或直接肌肉注射途径免疫BALB/c小鼠,检测小鼠的血清抗体、T细胞增殖和细胞毒性T淋巴细胞反应,结果表明两种免疫途径均能在小鼠体内诱生细胞和体液免疫应答,但口服途径诱导免疫应答的强度明显强于肌肉注射途径。口服携带HBV DNA疫苗的减毒伤寒沙门菌可能代表一种简便、有效的治疗乙型肝炎的新方法。      

FlowMax: A Computational Tool for Maximum Likelihood Deconvolution of CFSE Time Courses

The immune response is a concerted dynamic multi-cellular process. Upon infection, the dynamics of lymphocyte populations are an aggregate of molecular processes that determine the activation, division, and longevity of individual cells. The timing of these single-cell processes is remarkably widely distributed with some cells undergoing their third division while others undergo their first. High cell-to-cell variability and technical noise pose challenges for interpreting popular dye-dilution experiments objectively. It remains an unresolved challenge to avoid under- or over-interpretation of such data when phenotyping gene-targeted mouse models or patient samples. Here we develop and characterize a computational methodology to parameterize a cell population model in the context of noisy dye-dilution data. To enable objective interpretation of model fits, our method estimates fit sensitivity and redundancy by stochastically sampling the solution landscape, calculating parameter sensitivities, and clustering to determine the maximum-likelihood solution ranges. Our methodology accounts for both technical and biological variability by using a cell fluorescence model as an adaptor during population model fitting, resulting in improved fit accuracy without the need for ad hoc objective functions. We have incorporated our methodology into an integrated phenotyping tool, FlowMax, and used it to analyze B cells from two NFκB knockout mice with distinct phenotypes; we not only confirm previously published findings at a fraction of the expended effort and cost, but reveal a novel phenotype of nfkb1/p105/50 in limiting the proliferative capacity of B cells following B-cell receptor stimulation. In addition to complementing experimental work, FlowMax is suitable for high throughput analysis of dye dilution studies within clinical and pharmacological screens with objective and quantitative conclusions.     

Flow Cytometry Pulse Width Data Enables Rapid and Sensitive Estimation of Biomass Dry Weight in the Microalgae Chlamydomonas reinhardtii and Chlorella vulgaris

Dry weight biomass is an important parameter in algaculture. Direct measurement requires weighing milligram quantities of dried biomass, which is problematic for small volume systems containing few cells, such as laboratory studies and high throughput assays in microwell plates. In these cases indirect methods must be used, inducing measurement artefacts which vary in severity with the cell type and conditions employed. Here, we utilise flow cytometry pulse width data for the estimation of cell density and biomass, using Chlorella vulgaris and Chlamydomonas reinhardtii as model algae and compare it to optical density methods. Measurement of cell concentration by flow cytometry was shown to be more sensitive than optical density at 750 nm (OD₇₅₀) for monitoring culture growth. However, neither cell concentration nor optical density correlates well to biomass when growth conditions vary. Compared to the growth of C. vulgaris in TAP (tris-acetate-phosphate) medium, cells grown in TAP + glucose displayed a slowed cell division rate and a 2-fold increased dry biomass accumulation compared to growth without glucose. This was accompanied by increased cellular volume. Laser scattering characteristics during flow cytometry were used to estimate cell diameters and it was shown that an empirical but nonlinear relationship could be shown between flow cytometric pulse width and dry weight biomass per cell. This relationship could be linearised by the use of hypertonic conditions (1 M NaCl) to dehydrate the cells, as shown by density gradient centrifugation. Flow cytometry for biomass estimation is easy to perform, sensitive and offers more comprehensive information than optical density measurements. In addition, periodic flow cytometry measurements can be used to calibrate OD₇₅₀ measurements for both convenience and accuracy. This approach is particularly useful for small samples and where cellular characteristics, especially cell size, are expected to vary during growth.     

Quantitative analysis of lymphocyte differentiation and proliferation in vitro using carboxyfluorescein diacetate succinimidyl ester

Mature T and B lymphocytes respond to receptor-delivered signals received during and following activation. These signals regulate the rates of cell death, growth, differentiation and migration that ultimately establish the behaviour patterns collectively referred to as immune regulation. We have been pursuing the philosophy that in vitro systems of lymphocyte stimulation, when analysed quantitatively, help reveal the logical attributes of lymphocyte behaviour. The development of carboxyfluorescein diacetate succinimidyl ester (CFSE) to track division has enabled the variable of division number to be incorporated into these quantitative analyses. Our studies with CFSE have established a fundamental link between differentiation and division number. Isotype switching, expression of T cell cytokines, surface receptor alterations and changes to intracellular signalling components all display independent patterns of change with division number. The stochastic aspects of these changes and the ability of external signals to independently regulate them argue for a probabilistic modelling framework for describing and understanding immune regulation.     

Modeling Multivalent Ligand-Receptor Interactions with Steric Constraints on Configurations of Cell-Surface Receptor Aggregates

We use flow cytometry to characterize equilibrium binding of a fluorophore-labeled trivalent model antigen to bivalent IgE-FcεRI complexes on RBL cells. We find that flow cytometric measurements are consistent with an equilibrium model for ligand-receptor binding in which binding sites are assumed to be equivalent and ligand-induced receptor aggregates are assumed to be acyclic. However, this model predicts extensive receptor aggregation at antigen concentrations that yield strong cellular secretory responses, which is inconsistent with the expectation that large receptor aggregates should inhibit such responses. To investigate possible explanations for this discrepancy, we evaluate four rule-based models for interaction of a trivalent ligand with a bivalent cell-surface receptor that relax simplifying assumptions of the equilibrium model. These models are simulated using a rule-based kinetic Monte Carlo approach to investigate the kinetics of ligand-induced receptor aggregation and to study how the kinetics and equilibria of ligand-receptor interaction are affected by steric constraints on receptor aggregate configurations and by the formation of cyclic receptor aggregates. The results suggest that formation of linear chains of cyclic receptor dimers may be important for generating secretory signals. Steric effects that limit receptor aggregation and transient formation of small receptor aggregates may also be important.     

Misty Mountain clustering: application to fast unsupervised flow cytometry gating

Background  

There are many important clustering questions in computational biology for which no satisfactory method exists. Automated clustering algorithms, when applied to large, multidimensional datasets, such as flow cytometry data, prove unsatisfactory in terms of speed, problems with local minima or cluster shape bias. Model-based approaches are restricted by the assumptions of the fitting functions. Furthermore, model based clustering requires serial clustering for all cluster numbers within a user defined interval. The final cluster number is then selected by various criteria. These supervised serial clustering methods are time consuming and frequently different criteria result in different optimal cluster numbers. Various unsupervised heuristic approaches that have been developed such as affinity propagation are too expensive to be applied to datasets on the order of 10⁶ points that are often generated by high throughput experiments.