SWIFT clustering analysis of intracellular cytokine staining flow cytometry data of the HVTN 105 vaccine trial reveals high frequencies of HIV-specific CD4+ T cell responses and associations with humoral responses.

Introduction: The HVTN 105 vaccine clinical trial tested four combinations of two immunogens - the DNA vaccine DNA-HIV-PT123, and the protein vaccine AIDSVAX B/E. All combinations induced substantial antibody and CD4+ T cell responses in many participants. We have now re-examined the intracellular cytokine staining flow cytometry data using the high-resolution SWIFT clustering algorithm, which is very effective for enumerating rare populations such as antigen-responsive T cells, and also determined correlations between the antibody and T cell responses. Methods: Flow cytometry samples across all the analysis batches were registered using the swiftReg registration tool, which reduces batch variation without compromising biological variation. Registered data were clustered using the SWIFT algorithm, and cluster template competition was used to identify clusters of antigen-responsive T cells and to separate these from constitutive cytokine producing cell clusters. Results: Registration strongly reduced batch variation among batches analyzed across several months. This in-depth clustering analysis identified a greater proportion of responders than the original analysis. A subset of antigen-responsive clusters producing IL-21 was identified. The cytokine patterns in each vaccine group were related to the type of vaccine - protein antigens tended to induce more cells producing IL-2 but not IFN-γ, whereas DNA vaccines tended to induce more IL-2+ IFN-γ+ CD4 T cells. Several significant correlations were identified between specific antibody responses and antigen-responsive T cell clusters. The best correlations were not necessarily observed with the strongest antibody or T cell responses. Conclusion: In the complex HVTN105 dataset, alternative analysis methods increased sensitivity of the detection of antigen-specific T cells; increased the number of identified vaccine responders; identified a small IL-21-producing T cell population; and demonstrated significant correlations between specific T cell populations and serum antibody responses. Multiple analysis strategies may be valuable for extracting the most information from large, complex studies.

Opportunities and challenges for T cell-based influenza vaccines.

Vaccination remains our main defence against influenza, which causes substantial annual mortality and poses a serious pandemic threat. Influenza virus evades immunity by rapidly changing its surface antigens but, even when the vaccine is well matched to the current circulating virus strains, influenza vaccines are not as effective as many other vaccines. Influenza vaccine development has traditionally focused on the induction of protective antibodies, but there is mounting evidence that T cell responses are also protective against influenza. Thus, future vaccines designed to promote both broad T cell effector functions and antibodies may provide enhanced protection. As we discuss, such vaccines present several challenges that require new strategic and economic considerations. Vaccine-induced T cells relevant to protection may reside in the lungs or lymphoid tissues, requiring more invasive assays to assess the immunogenicity of vaccine candidates. T cell functions may contain and resolve infection rather than completely prevent infection and early illness, requiring vaccine effectiveness to be assessed based on the prevention of severe disease and death rather than symptomatic infection. It can be complex and costly to measure T cell responses and infrequent clinical outcomes, and thus innovations in clinical trial design are needed for economic reasons. Nevertheless, the goal of more effective influenza vaccines justifies renewed and intensive efforts.

Rapid reduction in Staphylococcus aureus in atopic dermatitis subjects following dupilumab treatment.

BACKGROUND: Atopic dermatitis (AD) is an inflammatory disorder characterized by dominant type 2 inflammation leading to chronic pruritic skin lesions, allergic comorbidities, and Staphylococcus aureus skin colonization and infections. S aureus is thought to play a role in AD severity. OBJECTIVES: This study characterized the changes in the host-microbial interface in subjects with AD following type 2 blockade with dupilumab. METHODS: Participants (n = 71) with moderate-severe AD were enrolled in a randomized (dupilumab vs placebo; 2:1), double-blind study at Atopic Dermatitis Research Network centers. Bioassays were performed at multiple time points: S aureus and virulence factor quantification, 16s ribosomal RNA microbiome, serum biomarkers, skin transcriptomic analyses, and peripheral blood T-cell phenotyping. RESULTS: At baseline, 100% of participants were S aureus colonized on the skin surface. Dupilumab treatment resulted in significant reductions in S aureus after only 3 days (compared to placebo), which was 11 days before clinical improvement. Participants with the greatest S aureus reductions had the best clinical outcomes, and these reductions correlated with reductions in serum CCL17 and disease severity. Reductions (10-fold) in S aureus cytotoxins (day 7), perturbations in TH17-cell subsets (day 14), and increased expression of genes relevant for IL-17, neutrophil, and complement pathways (day 7) were also observed. CONCLUSIONS: Blockade of IL-4 and IL-13 signaling, very rapidly (day 3) reduces S aureus abundance in subjects with AD, and this reduction correlates with reductions in the type 2 biomarker, CCL17, and measures of AD severity (excluding itch). Immunoprofiling and/or transcriptomics suggest a role for TH17 cells, neutrophils, and complement activation as potential mechanisms to explain these findings.

SwiftReg cluster registration automatically reduces flow cytometry data variability including batch effects.

Biological differences of interest in large, high-dimensional flow cytometry datasets are often obscured by undesired variations caused by differences in cytometers, reagents, or operators. Each variation type requires a different correction strategy, and their unknown contributions to overall variability hinder automated correction. We now describe swiftReg, an automated method that reduces undesired sources of variability between samples and particularly between batches. A high-resolution cluster map representing the multidimensional data is generated using the SWIFT algorithm, and shifts in cluster positions between samples are measured. Subpopulations are aligned between samples by displacing cell parameter values according to registration vectors derived from independent or locally-averaged cluster shifts. Batch variation is addressed by registering batch control or consensus samples, and applying the resulting shifts to individual samples. swiftReg selectively reduces batch variation, enhancing detection of biological differences. swiftReg outputs registered datasets as standard .FCS files to facilitate further analysis by other tools.

Women who received varicella vaccine versus natural infection have different long-term T cell immunity but similar antibody levels.

BACKGROUND: Varicella-zoster virus (VZV) infection during pregnancy is associated with serious fetal anomalies. The live-attenuated VZV vaccine was approved in 1995, so many vaccinated women are now of childbearing age. The question of long-term immunity to varicella is critical because breakthrough chickenpox can occur after vaccination. OBJECTIVE: To compare humoral and T cell immunity between women of childbearing age who were immunized by vaccination or chickenpox disease. STUDY DESIGN: Non-pregnant females between 18 and 36 years old with a history of VZV immunization (n = 20) or prior chickenpox disease (n = 20) were recruited. IgG antibody titers and T cell responses were measured by flow cytometry-based methods in serum and peripheral blood, respectively. RESULTS: There were no significant differences in median antibody titers between vaccinated and chickenpox groups (p = 0.34). The chickenpox group had significantly higher levels of VZV antigen-specific CD4 T cells (p = 0.004). CONCLUSION: Natural infection induced higher VZV-specific T cell immune responses than vaccination.

Automated Analysis of Flow Cytometry Data to Reduce Inter-Lab Variation in the Detection of Major Histocompatibility Complex Multimer-Binding T Cells.

Manual analysis of flow cytometry data and subjective gate-border decisions taken by individuals continue to be a source of variation in the assessment of antigen-specific T cells when comparing data across laboratories, and also over time in individual labs. Therefore, strategies to provide automated analysis of major histocompatibility complex (MHC) multimer-binding T cells represent an attractive solution to decrease subjectivity and technical variation. The challenge of using an automated analysis approach is that MHC multimer-binding T cell populations are often rare and therefore difficult to detect. We used a highly heterogeneous dataset from a recent MHC multimer proficiency panel to assess if MHC multimer-binding CD8+ T cells could be analyzed with computational solutions currently available, and if such analyses would reduce the technical variation across different laboratories. We used three different methods, FLOw Clustering without K (FLOCK), Scalable Weighted Iterative Flow-clustering Technique (SWIFT), and ReFlow to analyze flow cytometry data files from 28 laboratories. Each laboratory screened for antigen-responsive T cell populations with frequency ranging from 0.01 to 1.5% of lymphocytes within samples from two donors. Experience from this analysis shows that all three programs can be used for the identification of high to intermediate frequency of MHC multimer-binding T cell populations, with results very similar to that of manual gating. For the less frequent populations (<0.1% of live, single lymphocytes), SWIFT outperformed the other tools. As used in this study, none of the algorithms offered a completely automated pipeline for identification of MHC multimer populations, as varying degrees of human interventions were needed to complete the analysis. In this study, we demonstrate the feasibility of using automated analysis pipelines for assessing and identifying even rare populations of antigen-responsive T cells and discuss the main properties, differences, and advantages of the different methods tested.

Reduced T-Helper 17 Responses to Streptococcus pneumoniae in Infection-Prone Children Can Be Rescued by Addition of Innate Cytokines.

Background: T-helper (Th) 17 cells are important in the control of Streptococcus pneumoniae. We sought to understand the mechanism of failure of Th17 immunity resulting in S. pneumoniae infections in children <2 years old. Methods: Peripheral blood mononuclear cells (PBMCs) from infection-prone (IP) and non-IP (NIP) children 9-18 months old were examined for their responses to heat-killed S. Pneumoniae, using flow cytometry, reverse-transcription polymerase chain reaction, and enzyme-linked immunoassay. We measured cytokine production, proliferation, and differentiation of Th17 cells and the expression of transcription factors in response to S. pneumoniae. Results: PBMCs of IP children stimulated with heat-killed S. pneumoniae had significantly reduced percentages of CD4+ Th1 (interleukin2, tumor necrosis factor α) and Th17 (interleukin 17A) cells compared with NIP children. Addition of exogenous Th17-promoting cytokines (interleukin 6, 1ß, and 23 and transforming growth factor ß) restored CD4+ Th17 cell function in cells from IP children to levels measured in NIP children. Conclusions: Reduced Th17 responses to S. pneumoniae in PBMCs of IP children can be rescued by addition of Th17-promoting cytokines.

Functional Immune Cell Differences Associated With Low Vaccine Responses in Infants.

BACKGROUND: We sought to understand why some children respond poorly to vaccinations in the first year of life. METHODS: A total of 499 children (6-36 months old) provided serum and peripheral blood mononuclear cell samples after their primary and booster vaccination. Vaccine antigen-specific antibody levels were analyzed with enzyme-linked immunosorbent assay, and frequency of memory B cells, functional T-cell responses, and antigen-presenting cell responses were assessed in peripheral blood mononuclear cell samples with flow cytometric analysis. RESULTS: Eleven percent of children were low vaccine responders, defined a priori as those with subprotective immunoglobulin G antibody levels to ≥66% of vaccines tested. Low vaccine responders generated fewer memory B cells, had reduced activation by CD4(+) and CD8(+) T cells on polyclonal stimulation, and displayed lower major histocompatibility complex II expression by antigen-presenting cells. CONCLUSIONS: We conclude that subprotective vaccine responses in infants are associated with a distinct immunologic profile.

Standardizing Flow Cytometry Immunophenotyping Analysis from the Human ImmunoPhenotyping Consortium.

Standardization of immunophenotyping requires careful attention to reagents, sample handling, instrument setup, and data analysis, and is essential for successful cross-study and cross-center comparison of data. Experts developed five standardized, eight-color panels for identification of major immune cell subsets in peripheral blood. These were produced as pre-configured, lyophilized, reagents in 96-well plates. We present the results of a coordinated analysis of samples across nine laboratories using these panels with standardized operating procedures (SOPs). Manual gating was performed by each site and by a central site. Automated gating algorithms were developed and tested by the FlowCAP consortium. Centralized manual gating can reduce cross-center variability, and we sought to determine whether automated methods could streamline and standardize the analysis. Within-site variability was low in all experiments, but cross-site variability was lower when central analysis was performed in comparison with site-specific analysis. It was also lower for clearly defined cell subsets than those based on dim markers and for rare populations. Automated gating was able to match the performance of central manual analysis for all tested panels, exhibiting little to no bias and comparable variability. Standardized staining, data collection, and automated gating can increase power, reduce variability, and streamline analysis for immunophenotyping.

Competitive SWIFT cluster templates enhance detection of aging changes.

Clustering-based algorithms for automated analysis of flow cytometry datasets have achieved more efficient and objective analysis than manual processing. Clustering organizes flow cytometry data into subpopulations with substantially homogenous characteristics but does not directly address the important problem of identifying the salient differences in subpopulations between subjects and groups. Here, we address this problem by augmenting SWIFT--a mixture model based clustering algorithm reported previously. First, we show that SWIFT clustering using a "template" mixture model, in which all subpopulations are represented, identifies small differences in cell numbers per subpopulation between samples. Second, we demonstrate that resolution of inter-sample differences is increased by "competition" wherein a joint model is formed by combining the mixture model templates obtained from different groups. In the joint model, clusters from individual groups compete for the assignment of cells, sharpening differences between samples, particularly differences representing subpopulation shifts that are masked under clustering with a single template model. The benefit of competition was demonstrated first with a semisynthetic dataset obtained by deliberately shifting a known subpopulation within an actual flow cytometry sample. Single templates correctly identified changes in the number of cells in the subpopulation, but only the competition method detected small changes in median fluorescence. In further validation studies, competition identified a larger number of significantly altered subpopulations between young and elderly subjects. This enrichment was specific, because competition between templates from consensus male and female samples did not improve the detection of age-related differences. Several changes between the young and elderly identified by SWIFT template competition were consistent with known alterations in the elderly, and additional altered subpopulations were also identified. Alternative algorithms detected far fewer significantly altered clusters. Thus SWIFT template competition is a powerful approach to sharpen comparisons between selected groups in flow cytometry datasets.

A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes.

The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of computational methods for identifying cell populations in multidimensional flow cytometry data. Here we report the results of FlowCAP-IV where algorithms from seven different research groups predicted the time to progression to AIDS among a cohort of 384 HIV+ subjects, using antigen-stimulated peripheral blood mononuclear cell (PBMC) samples analyzed with a 14-color staining panel. Two approaches (FlowReMi.1 and flowDensity-flowType-RchyOptimyx) provided statistically significant predictive value in the blinded test set. Manual validation of submitted results indicated that unbiased analysis of single cell phenotypes could reveal unexpected cell types that correlated with outcomes of interest in high dimensional flow cytometry datasets.

Optimization of the cytokine secretion assay for human IL-2 in single and combination assays.

The cytokine secretion assay identifies live cytokine-secreting cells by capturing the secreted cytokine on a surface-bound capture antibody in dilute suspension culture, followed by detection with a fluorescent anti-cytokine antibody. However, examining the kinetics of cytokine detection revealed that IL-2 staining reached a maximum at early times and then declined, whereas staining for other cytokines including interferon (IFNγ) increased for up to 90 min. The decline in IL-2 staining could have been due to rapid cessation of cytokine synthesis, coupled with internalization of cytokine/antibody complexes from the cell surface. Consistent with this model, addition of the anti-IL-2 detection antibody during the cytokine secretion step resulted in higher and more sustained staining. This modified method enhanced staining of IL-2 and IL-4, but not IFNγ, tumor necrosis factor alpha (TNFα), or IL-5. However, the longer secretion times possible in the modified assay also improved detection of other cytokines in multi-cytokine combinations.

Microbubble array diffusion assay for the detection of cell secreted factors.

The therapeutic potential of monoclonal antibodies (mAbs) makes them an ideal tool in both clinical and research applications due to their ability to recognize and bind specific epitopes with high affinity and selectivity. While mAbs offer significant therapeutic potential, their utility is overshadowed by the cost associated with their production, which often relies on the ability to identify minor antigen-specific cells out of a heterogeneous population. To address concerns with suboptimal methods for screening cells, we have developed a cell-sorting array composed of nanoliter spherical cell culture compartments termed microbubble (MB) wells. We demonstrate a proof-of-concept system for the detection of cell secreted factors from both immortalized cell lines and primary B cell samples. Exploiting the unique ability of the MB well architecture to accumulate cell secreted factors as well as affinity capture coatings, we demonstrate on-chip detection and recovery of antibody-secreting cells for sequencing of immunoglobin genes. Furthermore, rapid image capture and analysis capabilities were developed for the processing of large MB arrays, thus facilitating the ability to conduct high-throughput screening of heterogeneous cell samples faster and more efficiently than ever before. The proof-of-concept assays presented herein lay the groundwork for the progression of MB well arrays as an advanced on-chip cell sorting technology.

Modeling the dynamics and migratory pathways of virus-specific antibody-secreting cell populations in primary influenza infection.

The B cell response to influenza infection of the respiratory tract contributes to viral clearance and establishes profound resistance to reinfection by related viruses. Numerous studies have measured virus-specific antibody-secreting cell (ASC) frequencies in different anatomical compartments after influenza infection and provided a general picture of the kinetics of ASC formation and dispersion. However, the dynamics of ASC populations are difficult to determine experimentally and have received little attention. Here, we applied mathematical modeling to investigate the dynamics of ASC growth, death, and migration over the 2-week period following primary influenza infection in mice. Experimental data for model fitting came from high frequency measurements of virus-specific IgM, IgG, and IgA ASCs in the mediastinal lymph node (MLN), spleen, and lung. Model construction was based on a set of assumptions about ASC gain and loss from the sampled sites, and also on the directionality of ASC trafficking pathways. Most notably, modeling results suggest that differences in ASC fate and trafficking patterns reflect the site of formation and the expressed antibody class. Essentially all early IgA ASCs in the MLN migrated to spleen or lung, whereas cell death was likely the major reason for IgM and IgG ASC loss from the MLN. In contrast, the spleen contributed most of the IgM and IgG ASCs that migrated to the lung, but essentially none of the IgA ASCs. This finding points to a critical role for regional lymph nodes such as the MLN in the rapid generation of IgA ASCs that seed the lung. Results for the MLN also suggest that ASC death is a significant early feature of the B cell response. Overall, our analysis is consistent with accepted concepts in many regards, but it also indicates novel features of the B cell response to influenza that warrant further investigation.

An animated landscape representation of CD4+ T-cell differentiation, variability, and plasticity: insights into the behavior of populations versus cells.

Recent advances in understanding CD4(+) T-cell differentiation suggest that previous models of a few distinct, stable effector phenotypes were too simplistic. Although several well-characterized phenotypes are still recognized, some states display plasticity, and intermediate phenotypes exist. As a framework for reexamining these concepts, we use Waddington's landscape paradigm, augmented with explicit consideration of stochastic variations. Our animation program "LAVA" visualizes T-cell differentiation as cells moving across a landscape of hills and valleys, leading to attractor basins representing stable or semistable differentiation states. The model illustrates several principles, including: (i) cell populations may behave more predictably than individual cells; (ii) analogous to reticulate evolution, differentiation may proceed through a network of interconnected states, rather than a single well-defined pathway; (iii) relatively minor changes in the barriers between attractor basins can change the stability or plasticity of a population; (iv) intrapopulation variability of gene expression may be an important regulator of differentiation, rather than inconsequential noise; (v) the behavior of some populations may be defined mainly by the behavior of outlier cells. While not a quantitative representation of actual differentiation, our model is intended to provoke discussion of T-cell differentiation pathways, particularly highlighting a probabilistic view of transitions between states.

Cytokine diversity in the Th1-dominated human anti-influenza response caused by variable cytokine expression by Th1 cells, and a minor population of uncommitted IL-2+IFNγ- Thpp cells.

Within overall Th1-like human memory T cell responses, individual T cells may express only some of the characteristic Th1 cytokines when reactivated. In the Th1-oriented memory response to influenza, we have tested the contributions of two potential mechanisms for this diversity: variable expression of cytokines by a uniform population during activation, or different stable subsets that consistently expressed subsets of the Th1 cytokine pattern. To test for short-term variability, in vitro-stimulated influenza-specific human memory CD4+ T cells were sorted according to IL-2 and IFNγ expression, cultured briefly in vitro, and cytokine patterns measured after restimulation. Cells that were initially IFNγ+ and either IL-2+ or IL-2- converged rapidly, containing similar proportions of IL-2-IFNγ+ and IL-2+IFNγ+ cells after culture and restimulation. Both phenotypes expressed Tbet, and similar patterns of mRNA. Thus variability of IL-2 expression in IFNγ+ cells appeared to be regulated more by short-term variability than by stable differentiated subsets. In contrast, heterogeneous expression of IFNγ in IL-2+ influenza-specific T cells appeared to be due partly to stable T cell subsets. After sorting, culture and restimulation, influenza-specific IL-2+IFNγ- and IL-2+IFNγ+ cells maintained significantly biased ratios of IFNγ+ and IFNγ- cells. IL-2+IFNγ- cells included both Tbetlo and Tbethi cells, and showed more mRNA expression differences with either of the IFNγ+ populations. To test whether IL-2+IFNγ-Tbetlo cells were Thpp cells (primed but uncommitted memory cells, predominant in responses to protein vaccines), influenza-specific IL-2+IFNγ- and IL-2+IFNγ+ T cells were sorted and cultured in Th1- or Th2-generating conditions. Both cell types yielded IFNγ-secreting cells in Th1 conditions, but only IL-2+IFNγ- cells were able to differentiate into IL-4-producing cells. Thus expression of IL-2 in the anti-influenza response may be regulated mainly by short term variability, whereas different T cell subsets, Th1 and Thpp, may contribute to variability in IFNγ expression.