Lymphocyte subset analysis by Boolean algebra: a phenotypic approach using a cocktail of 5 antibodies and 3 color immunofluorescence

From Discrete to Continuous Modeling of Lymphocyte Development and Plasticity in Chronic Diseases

The molecular events leading to differentiation, development, and plasticity of lymphoid cells have been subject of intense research due to their key roles in multiple pathologies, such as lymphoproliferative disorders, tumor growth maintenance and chronic diseases. The emergent roles of lymphoid cells and the use of high-throughput technologies have led to an extensive accumulation of experimental data allowing the reconstruction of gene regulatory networks (GRN) by integrating biochemical signals provided by the microenvironment with transcriptional modules of lineage-specific genes. Computational modeling of GRN has been useful for the identification of molecular switches involved in lymphoid specification, prediction of microenvironment-dependent cell plasticity, and analyses of signaling events occurring downstream the activation of antigen recognition receptors. Among most common modeling strategies to analyze the dynamical behavior of GRN, discrete dynamic models are widely used for their capacity to capture molecular interactions when a limited knowledge of kinetic parameters is present. However, they are less powerful when modeling complex systems sensitive to biochemical gradients. To compensate it, discrete models may be transformed into regulatory networks that includes state variables and parameters varying within a continuous range. This approach is based on a system of differential equations dynamics with regulatory interactions described by fuzzy logic propositions. Here, we discuss the applicability of this method on modeling of development and plasticity processes of adaptive lymphocytes, and its potential implications in the study of pathological landscapes associated to chronic diseases.

From big flow cytometry datasets to smart diagnostic strategies: The EuroFlow approach

The rise in the analytical speed of mutiparameter flow cytometers made possible by the introduction of digital instruments, has brought up the possibility to manage progressively higher number of parameters simultaneously on significantly greater numbers of individual cells. This has led to an exponential increase in the complexity and volume of flow cytometry data generated about cells present in individual samples evaluated in a single measurement. This increase demands for new developments in flow cytometry data analysis, graphical representation, and visualization and interpretation tools to address the new big data challenges, i.e. processing data files of ≥10-25 parameters per cell in samples with >5-10 million cells (= up to 250 million data points per cell sample) obtained in a few minutes. Here, we present a comprehensive review of some of the tools developed by the EuroFlow consortium for processing flow cytometric big data files in diagnostic laboratories, particularly focused on automated EuroFlow approaches for: i) identification of all cell populations coexisting in a sample (automated gating); ii) smart classification of aberrant cell populations in routine diagnostics; iii) automated reporting; together with iv) new tools developed to visualize n-dimensional data in 2-dimensional plots to support expert-guided automated data analysis. The concept of using reference data bases implemented into software programs, in combination with multivariate statistical analysis pioneered by EuroFlow, provides an innovative, highly efficient and fast approach for diagnostic screening, classification and monitoring of patients with distinct hematological and immune disorders, as well as other diseases.

Orthotopic Implantation and Peripheral Immune Cell Monitoring in the II-45 Syngeneic Rat Mesothelioma Model

The enormous upsurge of interest in immune-based treatments for cancer such as vaccines and immune checkpoint inhibitors, and increased understanding of the role of the tumor microenvironment in treatment response, collectively point to the need for immune-competent orthotopic models for pre-clinical testing of these new therapies. This paper demonstrates how to establish an orthotopic immune-competent rat model of pleural malignant mesothelioma. Monitoring disease progression in orthotopic models is confounded by the internal location of the tumors. To longitudinally monitor disease progression and its effect on circulating immune cells in this and other rat models of cancer, a single tube flow cytometry assay requiring only 25 µl whole blood is described. This provides accurate quantification of seven immune parameters: total lymphocytes, monocytes and neutrophils, as well as the T-cell subsets CD4 and CD8, B-cells and Natural Killer cells. Different subsets of these parameters are useful in different circumstances and models, with the neutrophil to lymphocyte ratio having the greatest utility for monitoring disease progression in the mesothelioma model. Analyzing circulating immune cell levels using this single tube method may also assist in monitoring the response to immune-based treatments and understanding the underlying mechanisms leading to success or failure of treatment.

Computational and experimental analysis reveals a requirement for eosinophil-derived IL-13 for the development of allergic airway responses in C57BL/6 mice

Eosinophils are found in the lungs of humans with allergic asthma, as well as in the lungs of animals in models of this disease. Increasing evidence suggests that these cells are integral to the development of allergic asthma in C57BL/6 mice. However, the specific function of eosinophils that is required for this event is not known. In this study, we experimentally validate a dynamic computational model and perform follow-up experimental observations to determine the mechanism of eosinophil modulation of T cell recruitment to the lung during development of allergic asthma. We find that eosinophils deficient in IL-13 were unable to rescue airway hyperresponsiveness, T cell recruitment to the lungs, and Th2 cytokine/chemokine production in ΔdblGATA eosinophil-deficient mice, even if Th2 cells were present. However, eosinophil-derived IL-13 alone was unable to rescue allergic asthma responses in the absence of competence of other IL-13-producing cells. We further computationally investigate the role of other cell types in the production of IL-13, which led to the various predictions including early and late pulses of IL-13 during airway hyperresponsiveness. These experiments suggest that eosinophils and T cells have an interdependent relationship, centered on IL-13, which regulates T cell recruitment to the lung and development of allergic asthma.

Modeling systems-level regulation of host immune responses

Many pathogens are able to manipulate the signaling pathways responsible for the generation of host immune responses. Here we examine and model a respiratory infection system in which disruption of host immune functions or of bacterial factors changes the dynamics of the infection. We synthesize the network of interactions between host immune components and two closely related bacteria in the genus Bordetellae. We incorporate existing experimental information on the timing of immune regulatory events into a discrete dynamic model, and verify the model by comparing the effects of simulated disruptions to the experimental outcome of knockout mutations. Our model indicates that the infection time course of both Bordetellae can be separated into three distinct phases based on the most active immune processes. We compare and discuss the effect of the species-specific virulence factors on disrupting the immune response during their infection of naive, antibody-treated, diseased, or convalescent hosts. Our model offers predictions regarding cytokine regulation, key immune components, and clearance of secondary infections; we experimentally validate two of these predictions. This type of modeling provides new insights into the virulence, pathogenesis, and host adaptation of disease-causing microorganisms and allows systems-level analysis that is not always possible using traditional methods.

The immune response is a complex network of processes activated in a host upon infection. Pathogens seek to disrupt or evade these processes to ensure their own survival and proliferation. This article provides a systems-level analysis of the immune response against two related bacterial species in the Bordetella genus, B. bronchiseptica and B. pertussis. B. pertussis, the causative agent of whooping cough, has lost many of the virulence factors of its B. bronchiseptica–like progenitor, and is using different strategies for the modulation of the immune system. We have synthesized two separate network models for the interaction of these pathogens with their hosts. Each network is then translated into a predictive dynamic model and is validated by comparison with available experimental data. The model offers predictions regarding cytokine regulation and the effects of perturbations of the immune system, as well as the time course of infections in hosts that had previously encountered the pathogens. We experimentally validate the prediction that convalescent hosts can rapidly clear both pathogens, while antibody transfer cannot substantially reduce the duration of a B. pertussis infection. This type of modeling provides new insights into the virulence, pathogenesis, and host adaptation of disease-causing microorganisms and can be readily extended to other pathogens.

Fluorescence-intensity multiplexing: Simultaneous seven-marker, two-color immunophenotyping using flow cytometry

BACKGROUND

Conventional immuno-based multiparameter flow cytometric analysis has been limited by the requirement of a dedicated detection channel for each antibody-fluorophore set. To address the need to resolve multiple biological targets simultaneously, flow cytometers with as many as 10-15 detection channels have been developed. In this study, a new Zenon immunolabeling technology is developed that allows for multiple antigen detection per detection channel using a single fluorophore, through a unique method of fluorescence-intensity multiplexing. By varying the Zenon labeling reagent-to-antibody molar ratio, the fluorescence intensity of the antibody-labeled cellular targets can be used as a unique identifier. Although demonstrated in the present study with lymphocyte immunophenotyping, this approach is broadly applicable for any immuno-based multiplexed flow cytomety assay.

METHODS

Lymphocyte immunophenotyping of 38 clinical blood specimens using CD3, CD4, CD8, CD16, CD56, CD19, and CD20 antibodies was performed using conventional flow cytometric analysis and fluorescence-intensity multiplexing analysis. Conventional analysis measures a single antibody-fluorophore per photomultiplier tube (PMT). Fluorescence-intensity multiplex analysis simultaneously measures seven markers with two PMTs, using Zenon labeling reagent-antibody complexes in a single tube: CD19, CD4, CD8, and CD16 antibodies labeled with Zenon Alexa Fluor 488 Mouse IgG(1) labeling reagent and CD56, CD3, and CD20 antibodies labeled with Zenon R-Phycoerythrin (R-PE) Mouse IgG(1) or IgG(2b) labeling reagents.

RESULTS

The lymphocyte immunophenotyping results from fluorescence-intensity multiplexing using Zenon labeling reagents in a single tube were comparable to results from conventional flow cytometric analysis.

CONCLUSIONS

Simultaneous evaluation of multiple antigens using a single fluorophore can be performed using antibodies labeled with varying ratios of a Zenon labeling reagent. Labeling two sets of antibodies with different Zenon labeling reagents can generate characteristic and distinguishable multivariate patterns. Combining multiple antibodies and fluorescent labels with fluorescence intensity multiplexing enables the resolution of more cellular targets than detection-channels, allowing sophisticated multiparameter flow cytometric studies to be performed on less complex 2- or 3-detection-channel flow cytometers. For typical biological samples, approximately 2-4 cellular targets per detection channel can be resolved using this technique.

Cytokine profiles of BAL T cells and T-cell clones obtained from human asthmatic airways after local allergen challenge

BACKGROUND

This study assessed the heterogeneity of cytokine expression in asthma before and after local allergen challenge.

METHODS

BAL T cells were obtained 10 min or 24 h after local endobronchial allergen challenge in atopic asthmatic subjects. T cells were cloned by direct limiting dilution. mRNA expression was assessed by RT-PCR, and cytokine protein production by ELISA.

RESULTS

Unstimulated baseline BAL T cells expressed mRNA for IFN-gamma, IL-13, and TNF-alpha. A minority of samples expressed IL-4 and IL-5, but no IL-3 mRNA was detected. PHA stimulation increased expression of IL-3, IL-4, and IL-5 mRNA in 4/6 samples. IL-13 and GM-CSF mRNA were found in BAL cells after allergen challenge, but expression of IFN-gamma was reduced. Both IL-4 and IL-3 were strongly upregulated after PHA stimulation, while the expression of TNF-alpha and IFN-gamma was reduced, compared to equivalent baseline samples. Seventeen panels of BAL T-cell clones were derived (average cloning efficiency 1/40 T cells). Seven panels survived to 8 weeks for analysis. Clones derived 4 h after saline challenge showed strong mRNA signals for IL-13, IL-4, and IFN-gamma, whereas clones derived 24 h after allergen challenge expressed IL-13, GM-CSF, IL-3, IL-4, and often IL-5 (i.e., closer to the Th2 profile). There was considerable heterogeneity in the patterns of cytokine mRNA and protein production by different clones.

CONCLUSIONS

T cells from asthmatic airways produce IL-13, IFN-gamma, and TNF-alpha, but after allergen challenge, type 2 cytokines are upregulated. mRNA and protein analysis provide complementary information on airways T-cell cytokine profiles.

A simple method for the propagation of cervical lymphocytes

Local immune function is most likely a key influence in the establishment of human papillomavirus infections and its subsequent disease. Unfortunately, little information is known about local cervical immunity, and even less is known about human papillomavirus immunoreactivity. In addition, studies of local immunoreactivity have been hampered by the technical difficulty in obtaining cervical lymphocytes. The objective of the present study was to develop a simple method for the propagation of cervical lymphocytes from biopsy-size specimens. Cervical tissue was obtained from women undergoing a hysterectomy. Cervical samples measuring approximately 3 by 5 by 2 mm were minced and divided into two portions. One portion was digested by standard digestion methods and density gradient lymphocyte separation. The sample was then immunocharacterized for CD4 and CD8 cells by flow cytometry. The other portion was minced into 1-mm3 sections, and each section was placed into a separate well with tissue culture medium and interleukin-2. Lymphocyte counts and immunophenotypic analysis were performed after 18 to 20 days in culture. After 18 to 20 days in culture, the analysis demonstrated that this method of direct lymphocyte culture from a biopsy specimen yielded approximately 1 x 10(6) to 5 x 10(6) lymphocytes. Immunophenotypic studies of the digested sample at day 0 revealed CD4-to-CD8 ratios of between 0.7:1 and 3.5:1, and at days 18 to 20 they revealed ratios of between 2.3:1 and 98:1. In summary, we developed a simple technique for propagating cervical lymphocytes from small tissue samples for the study of the local immune response. Studies are under way to optimize lymphocyte growth and to preserve CD8 populations.