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

The Acute Environment, Rather than T Cell Subset Pre-Commitment, Regulates Expression of the Human T Cell Cytokine Amphiregulin

Cytokine expression patterns of T cells can be regulated by pre-commitment to stable effector phenotypes, further modification of moderately stable phenotypes, and quantitative changes in cytokine production in response to acute signals. We showed previously that the epidermal growth factor family member Amphiregulin is expressed by T cell receptor-activated mouse CD4 T cells, particularly Th2 cells, and helps eliminate helminth infection. Here we report a detailed analysis of the regulation of Amphiregulin expression by human T cell subsets. Signaling through the T cell receptor induced Amphiregulin expression by most or all T cell subsets in human peripheral blood, including naive and memory CD4 and CD8 T cells, Th1 and Th2 in vitro T cell lines, and subsets of memory CD4 T cells expressing several different chemokine receptors and cytokines. In these different T cell types, Amphiregulin synthesis was inhibited by an antagonist of protein kinase A, a downstream component of the cAMP signaling pathway, and enhanced by ligands that increased cAMP or directly activated protein kinase A. Prostaglandin E2 and adenosine, natural ligands that stimulate adenylyl cyclase activity, also enhanced Amphiregulin synthesis while reducing synthesis of most other cytokines. Thus, in contrast to mouse T cells, Amphiregulin synthesis by human T cells is regulated more by acute signals than pre-commitment of T cells to a particular cytokine pattern. This may be appropriate for a cytokine more involved in repair than attack functions during most inflammatory responses

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

IntroductionThe 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.MethodsFlow 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.ResultsRegistration 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.ConclusionIn 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

Serum after Autologous Transplantation Stimulates Proliferation and Expansion of Human Hematopoietic Progenitor Cells

Regeneration after hematopoietic stem cell transplantation (HSCT) depends on enormous activation of the stem cell pool. So far, it is hardly understood how these cells are recruited into proliferation and self-renewal. In this study, we have addressed the question if systemically released factors are involved in activation of hematopoietic stem and progenitor cells (HPC) after autologous HSCT. Serum was taken from patients before chemotherapy, during neutropenia and after hematopoietic recovery. Subsequently, it was used as supplement for in vitro culture of CD34+ cord blood HPC. Serum taken under hematopoietic stress (4 to 11 days after HSCT) significantly enhanced proliferation, maintained primitive immunophenotype (CD34+, CD133+, CD45−) for more cell divisions and increased colony forming units (CFU) as well as the number of cobblestone area-forming cells (CAFC). The stimulatory effect decays to normal levels after hematopoietic recovery (more than 2 weeks after HSCT). Chemokine profiling revealed a decline of several growth-factors during neutropenia, including platelet-derived growth factors PDGF-AA, PDGF-AB and PDGF-BB, whereas expression of monocyte chemotactic protein-1 (MCP-1) increased. These results demonstrate that systemically released factors play an important role for stimulation of hematopoietic regeneration after autologous HSCT. This feedback mechanism opens new perspectives for in vivo stimulation of the stem cell pool

The EYA Tyrosine Phosphatase Activity Is Pro-Angiogenic and Is Inhibited by Benzbromarone

Eyes Absents (EYA) are multifunctional proteins best known for their role in organogenesis. There is accumulating evidence that overexpression of EYAs in breast and ovarian cancers, and in malignant peripheral nerve sheath tumors, correlates with tumor growth and increased metastasis. The EYA protein is both a transcriptional activator and a tyrosine phosphatase, and the tyrosine phosphatase activity promotes single cell motility of mammary epithelial cells. Since EYAs are expressed in vascular endothelial cells and cell motility is a critical feature of angiogenesis we investigated the role of EYAs in this process. Using RNA interference techniques we show that EYA3 depletion in human umbilical vein endothelial cells inhibits transwell migration as well as Matrigel-induced tube formation. To specifically query the role of the EYA tyrosine phosphatase activity we employed a chemical biology approach. Through an experimental screen the uricosuric agents Benzbromarone and Benzarone were found to be potent EYA inhibitors, and Benzarone in particular exhibited selectivity towards EYA versus a representative classical protein tyrosine phosphatase, PTP1B. These compounds inhibit the motility of mammary epithelial cells over-expressing EYA2 as well as the motility of endothelial cells. Furthermore, they attenuate tubulogenesis in matrigel and sprouting angiogenesis in the ex vivo aortic ring assay in a dose-dependent fashion. The anti-angiogenic effect of the inhibitors was also demonstrated in vivo, as treatment of zebrafish embryos led to significant and dose-dependent defects in the developing vasculature. Taken together our results demonstrate that the EYA tyrosine phosphatase activity is pro-angiogenic and that Benzbromarone and Benzarone are attractive candidates for repurposing as drugs for the treatment of cancer metastasis, tumor angiogenesis, and vasculopathies

Regulation of Immune Responses by T Cells with Different Cytokine Secretion Phenotypes: Role of a New Cytokine, Cytokine Synthesis Inhibitory Factor (IL10)

Subsets of T cells, defined by the patterns of cytokines that they secrete, show important functional differences, and appear to be at least partly responsible for the different immune responses induced by various pathogens. Two very distinct subsets, TH1 and TH2, are mutually inhibitory, and a newly discovered cytokine, ILI0, is one of the mediators of this cross-regulation. IL10 inhibits the synthesis of cytokines by TH1 cells but not TH2 cells. Since TH2 cells produce IL4 and IL5, which lead to some of the major manifestations of allergy, it is likely that IL10 production biases an immune response towards allergy.</jats:p