Identification of signal transduction pathways involved in the formation of platelet subpopulations upon activation

Platelets are formed elements of blood. Upon activation, they externalize phosphatidylserine, thus accelerating membrane‐dependent reactions of blood coagulation. Activated platelets form two subpopulations, only one of which expresses phosphatidylserine. This study aimed to identify signalling pathways responsible for this segregation. Gel‐filtered platelets, intact or loaded with calcium‐sensitive dyes, were activated and labelled with annexin V and antibodies, followed by flow cytometric analysis. Calcium Green and Fura Red dyes were compared, and only the latter was able to detect calcium level differences in the platelet subpopulations. Phosphatidylserine‐positive platelets produced by thrombin had stably high intracellular calcium level; addition of convulxin increased and stabilized calcium level in the phosphatidylserine‐negative subpopulation. PAR1 agonist SFLLRN also induced calcium rise and subpopulation formation, but the resulting platelets were not coated with alpha‐granule proteins. Adenylatecyclase activator forskolin inhibited phosphatidylserine‐positive platelets formation several‐fold, while its inhibitor SQ22536 had no effect. This suggests that adenylatecyclase inactivation is necessary, but not rate‐limiting, for subpopulation segregation. Inhibition of mitogen‐activated protein kinase kinase (U0126) and glycoprotein IIb‐IIIa (Monafram^®) was without effect, whereas inhibitors of phosphatidylinositol 3‐kinase (wortmannin) and Src tyrosine kinase (PP2) decreased the procoagulant subpopulation threefold. These data identify the principal signalling pathways controlling platelet heterogeneity.     

CD14−/CD34+ is the founding population of umbilical cord blood-derived endothelial progenitor cells and angiogenin1 is an important factor promoting the colony formation

The origin of endothelial progenitor cells (EPCs) in umbilical cord blood (UCB) is unknown. In this study, we explored the origin of UCB-derived EPCs by culturing CD14+ or CD14− subpopulation separately and co-culturing these two subpopulations either with or without transwells. We found no colony formation with CD14+ or CD14− subpopulation alone, but there were EPC colonies observed in direct co-cultures of both subpopulations. Transwell culture system was used to further study the effect of cytokines on EPC colony formation. We observed the presence of EPC colonies derived from CD14− subpopulation in the presence of CD14+ subpopulation in the upper compartment whereas there was no colony generated from CD14+ subpopulation with CD14− subpopulation in the upper compartment. Therefore, CD14− subpopulation is likely to be the origin of EPCs and EPC colony derivation requires cytokines released from CD14+ subpopulation. We further characterized the founding population of UCB-derived EPCs by separating CD14− subpopulation into CD14−/CD34+ and CD14−/CD34− subpopulations. There were colonies observed only in co-cultures of CD14+ with CD14−/CD34+ subpopulation but not with CD14−/CD34− subpopulation either with or without transwells. We screened 42 cytokines involving in angiogenesis using an ELISA array in the supernatant collected from CD14+ compared to CD14− subpopulations. We found consistently the presence of angiogenin1 in the supernatant of CD14+ subpopulation but not in that of CD14− subpopulation. The addition of angiogenin1 in culture of CD14− subpopulation yielded EPC colonies. We conclude that UCB-derived EPCs are confined to CD14−/CD34+ subpopulation and angiogenin1 released from CD14+ subpopulation may be an important factor promoting the EPC colony formation.     

Hepatitis B virus DNA is more powerful than HBeAg in predicting peripheral T-lymphocyte subpopulations in chronic HBV-infected individuals with normal liver function tests

AIM： To investigate the peripheral T-lymphocyte subpopulation profile, and its correlations with hepatitis B virus （HBV） replication level in chronic HBV-infected （CHI） individuals with normal liver function tests （LFTs）. METHODS： Frequencies of T-lymphocyte subpopulations in peripheral blood were measured by flow cytometry in 216 CHI individuals. HBV markers were detected with ELISA. Serum HBV DNA load was assessed with quantitative real-time PCR. Information of age at HBV infection, and maternal HBV infection status was collected. ANOVA linear trend test and linear regression were used in statistical analysis.
RESULTS： CHI individuals had significantly decreased relative frequencies of CD^3＋, CD^4＋ subpopulations and CD^4＋/CD^8＋ ratio, and increased CD^8＋ subset percentage compared with uninfected individuals （all P 〈 0.001）. There was a significant linear relationship between the load of HBV DNA and the parameters of T-lymphocyte subpopulations （ANOVA linear trend test P 〈 0.01）. The parameters were also significantly worse among individuals whose mothers were known to be HBV carriers, and those having gained infection before the age of 8 years. In multiple regressions, after adjustment for age at HBV infection and status of maternal HBV infection, log copies of HBV DNA maintained its highly significant predictive coefficient on T-lymphocyte subpopulations, whereas the effect of HBeAg was not significant.
CONCLUSION： HBV DNA correlates with modification in the relative T-lymphocyte subpopulation frequencies. High viral load is more powerful than HBeAg in predicting the impaired balance of T-cell subsets.     

Evaluation of T cells in blood after a short gluten challenge for coeliac disease diagnosis

Background and aimTo diagnose coeliac disease (CD) in individuals on a gluten free diet (GFD), we aimed to assess the utility of detecting activated γδ and CD8 T cells expressing gut-homing receptors after a short gluten challenge.MethodsWe studied 15 CD patients and 35 non-CD controls, all exposed to three days of gluten when following a GFD. Peripheral blood was collected before and six days after starting gluten consumption, and the expression of CD103, β7 and CD38 in γδ and CD8 T cells was assessed by flow cytometry. Determination of IFN-γ and IP-10 was performed by means of ELISPOT and/or Luminex technology.ResultsWe observed both γδ and CD8 T cells coexpressing CD103, β7^hi and CD38 in every patient with CD on day six, but only in one control. The studied CD8 T subpopulation was easier to detect than the γδ subpopulation. Increased IFN-γ and IP-10 levels after challenge were observed in patients with CD, but not in controls.ConclusionA short three-day gluten challenge elicits the activation of CD103⁺ β7^hi CD8⁺ T cells in CD. These cells can be detected by flow cytometry in peripheral blood, opening new possibilities for CD diagnosis in individuals on a GFD.     

Cytogenetically aberrant cells in the stem cell compartment (CD34+lin-) in acute myeloid leukemia

Leukemia may be viewed as a clonal expansion of blast cells; however, the role of primitive cells and/or stem cells in disease etiology and progression is unclear. We investigated stem cell involvement in leukemia using fluorescence in situ hybridization (FISH), immunofluorescence labeling of hematopoietic subpopulations, and flow cytometric analysis/sorting to discriminate and quantify cytogenetically aberrant stem cells in 12 acute myeloid leukemia (AML) and three myelodysplastic (MDS) specimens. Flow cytometric analysis and sorting were used to discriminate and collect a primitive subpopulation enriched in stem cells expressing CD34+ and lacking CD33 and CD38 (CD34+lin-). A subpopulation containing progenitors and differentiating myeloid cells expressed CD34, CD33, and CD38 (CD34+lin+). Nine specimens contained less than 10% CD34+ cells and, thus, were considered to be CD34- leukemias. Mature lymphoid, myeloid, and erythroid subpopulations were sorted on the basis of antigen-linked immunofluorescence. Cytogenetically aberrant cells in sorted subpopulations were identified using FISH with enumerator probes selected on the basis of diagnosis karyotype. Cytogenetically aberrant CD34+lin- cells were present at frequencies between 9% and 99% in all specimens. CD34+lin- cytogenetically aberrant cells comprised between 0.05% and 11.9% of the marrow/blood specimens. Cytogenetically aberrant CD34+lin+ cells constituted 0.01% tp 56% of the marrow/blood population. These data demonstrate that aberrant cells are present in primitive CD34+ stem cell compartments, even in CD34- leukemias. Stem cell involvement was confirmed further by sorting lymphoid and erythroid subpopulations from eight specimens in which the predominant leukemic population lacked lymphoid/erythroid differentiation markers. In these specimens, as well as in multiple lineages, suggests involvement of a cell(s) with multilineage capabilities. The ability of aberrant CD34+lin- stem cells to contribute to clonal and compartment expansion within immunofluorescently defined subpopulations was evaluated to explore the functional phenotype of aberrant CD34+lin- cells. Analysis of compartment size and aberrant cell frequency suggests that frequency of cytogenetically aberrant stem cells is uncoupled from compartment size. These data suggest that cytogenetically aberrant cells in the primitive compartment show varying abilities to expand primitive compartments. Cytogenetically aberrant CD34+lin- cells precede the blast subpopulation in hierarchical maturation and may in some cases by considered preleukemic, requiring maturation or additional mutations before transformation (eg, compartmental expansion) occurs.     

Altered immunophenotypic features of peripheral blood platelets in myelodysplastic syndromes

Background

Multiparameter flow cytometric analysis of bone marrow and peripheral blood cells has proven to be of help in the diagnostic workup of myelodysplastic syndromes. However, the usefulness of flow cytometry for the detection of megakaryocytic and platelet dysplasia has not yet been investigated. The aim of this pilot study was to evaluate by flow cytometry the diagnostic and prognostic value of platelet dysplasia in myelodysplastic syndromes.

Design and Methods

We investigated the pattern of expression of distinct surface glycoproteins on peripheral blood platelets from a series of 44 myelodysplastic syndrome patients, 20 healthy subjects and 19 patients with platelet alterations associated to disease conditions other than myelodysplastic syndromes. Quantitative expression of CD31, CD34, CD36, CD41a, CD41b, CD42a, CD42b and CD61 glycoproteins together with the PAC-1, CD62-P, fibrinogen and CD63 platelet activation-associated markers and platelet light scatter properties were systematically evaluated.

Results

Overall, flow cytometry identified multiple immunophenotypic abnormalities on platelets of myelodysplastic syndrome patients, including altered light scatter characteristics, over-and under expression of specific platelet glycoproteins and asynchronous expression of CD34; decreased expression of CD36 (n=5), CD42a (n=1) and CD61 (n=2), together with reactivity for CD34 (n=1) were only observed among myelodysplastic syndrome cases, while other alterations were also found in other platelet disorders. Based on the overall platelet alterations detected for each patient, an immunophenotypic score was built which identified a subgroup of myelodysplastic syndrome patients with a high rate of moderate to severe alterations (score>1.5; n=16) who more frequently showed thrombocytopenia, megakaryocytic dysplasia and high-risk disease, together with a shorter overall survival.

Conclusions

Our results show the presence of altered phenotypes by flow cytometry on platelets from around half of the myelodysplastic syndrome patients studied. If confirmed in larger series of patients, these findings may help refine the diagnostic and prognostic assessment of this group of disorders.     

Cytotoxic Natural Killer Subpopulations as a Prognostic Factor of Malignant Pleural Effusion

Background

Malignant pleural effusion (MPE) is a sign of advanced disease of poor prognosis. As natural killer (NK) cells are involved in the first line of tumour defence, we aimed to validate a new diagnostic and prognostic indicator for MPE based on NK subpopulations of pleural fluid (PF) and peripheral blood (PB).

Methods

NK subpopulations were determined in PF and PB in 71 patients with malignant, paramalignant or benign pleural effusion. The receiver operating characteristic (ROC) curves, Kaplan–Meier, multivariable Cox model and decision trees created with the CHAID (Chi-square automatic interaction detector) methodology were employed.

Results

We demonstrated that the PF/PB ratios of the CD56 bright CD16− and CD56 dim CD16− NK subpopulations were higher (p = 0.013 and p = 0.003, respectively) in MPEs and paramalignant pleural effusions (PPEs) than in benign ones, with an AUC of 0.757 and 0.741, respectively. The PF/PB ratio of CD16+ NK and CD57+ NK obtained a higher hazard ratio (HR) in the crude Cox’s regression analysis. In the adjusted Cox’s regression analysis, the PF/PB ratio of CD16+ NK gave the highest HR (HR 6.1 [1.76–21.1]) (p = 0.004). In the decision tree created for the MPE prognosis, we observed that the main predictor variable among the studied clinical, radiological, and analytical variables was lung mass, and that 92.9% of the patients who survived had a PF/PB ratio of the CD56 dim CD16+ NK subpopulation ≤ 0.43.

Conclusions

Our data suggest that both the PF/PB ratios of cytotoxic subpopulations CD57+ NK and CD16+ NK are useful as a prognostic factor of MPE. Other subpopulations (CD56 bright CD16− and CD56 dim CD16− NK) could help to diagnose MPE.

     

Phenotypic quantitative features of patients with acute myeloid leukemia

The recent WHO classification for acute myeloid leukemias (AML) separates entities by recurrent cytogenetic abnormalities and immunophenotypic features presenting prognostic impact. We have examined the expression of several lineage and maturation linked antigens used in routine immunophenotyping of patients with de novo AML, using a 3-color two-step panel. Cases were diagnosed by peripheral blood counts, bone marrow cytology, cytochemistry, cytogenetics and immunophenotyping (CD2, CD3, CD7, CD19, CD13, CD33, myeloperoxydase -- MPO, CD14, CD15, HLA-DR, CD34, CD56 and CD45). Antigen expression was measured by mean fluorescence intensity (MFI) by flow cytometry (Paint-a-gate software). Thirty five patients were analyzed. Median age: 51 years (15-79). Predominant FAB types were M2 and M4. In 6 cases more than one phenotypically distinct blast subpopulation could be detected. Although our set was small, we tried to analyze the impact of MFI of the examined antigens on the overall survival of the patients. In Cox univariate analysis, age, peripheral leukocytes (WBC) at diagnosis, MFI of CD45, and MPO were significant for worse a survival. In the multivariate analysis only MFI of CD45 and WBC remained in the model (p=0.018 and p=0.014 respectively). After bootstrap resampling, MFI of CD45 entered the model in 69%, WBCin 60%, age in 42% and MFI of MPO in 35% of the sets. Analysis of antigen expression by MFI permitted to detect cases presenting phenotypically distinct blast subpopulations. This may represent a pitfall in studies of minimal residual disease by flow cytometry, as chemotherapy may select one of these subsets.     

Multiple platelet defects identified by flow cytometry at diagnosis in acute myeloid leukaemia

Summary Previous findings of megakaryocytic hypogranulation and dysmegakaryocytopoietic features in acute myeloid leukaemia (AML) strongly indicate defects in platelet production. The bleeding tendency of these patients may result from dysregulated platelet production, resulting in thrombocytopenia as well as qualitative platelet defects. The present study examined platelet function at diagnosis in 50 AML patients by whole blood flow cytometry. Following in vitro platelet agonist stimulation, platelet activation markers were analysed and compared with 20 healthy individuals. To detect recent in vivo platelet activation, plasma soluble P-selectin (sP-selectin) was measured. Flow cytometric analysis of platelet activation markers demonstrated reduced CD62P [35.6 vs. 118.5 x 10(3) molecules of equivalent soluble fluorochrome (MESF); P < 0.0001], CD63 (11.3 vs. 50.7 x 10(3) MESF; P < 0.0001), and PAC-1 (41.5 vs. 90.5%; P = 0.0001) while reductions in CD42b were abnormal (45.6 vs. 70%; P < 0.0001). sP-selectin levels were similar in patients and healthy controls (0.04 vs. 0.27 fg/platelet; P = 0.84). The presented data indicate that AML pathogenesis may result in multiple platelet defects, involving adhesion, aggregation, and secretion and demonstrate that flow cytometry is a feasible method for platelet function analysis in patients with thrombocytopenia.     

Differential Expression of Platelet Activation Markers CD62P and CD63 Following Stimulation with PAF,Arachidonic Acid and Collagen

The effects of varying concentrations of platelet-activating factor (PAF), arachidonic acid (AA) and collagen on the expression of the platelet activation markers CD63 and CD62P were assessed in 10 normal subjects using flow cytometry. CD63 expression was significantly greater than CD62P expression, with PAF (80 nM) inducing mean maximum CD63 expression of 32.9 ± 6.4% and mean maximum CD62P expression of 5.5 ± 1.8%. AA (1 mM) induced maximum CD63 expression of 37.7 ± 7% and maximum CD62P expression of 9.3 ± 1%. Collagen (2-80 pg/ml) induced minimal expression but 800 pg/ml induced mean CD63 expression of 33.1 ± 4.1% and mean CD62P expression of 6.1 ± 0.8%. Greater CD63 and CD62P expression were induced by phorbol myristate acetate (1.6 pM, 70.9 ± 11% and 69.4 ± 9.9%, respectively) and thrombin (0.1 U/ml, 70.7 ± 9.3% and 73.5 ± 5.4%, respectively). With PAF and collagen only one platelet population was detected whereas with 1 mM AA two populations were observed. These results indicate that expression of platelet adhesion receptors depends on the nature and concentration of agonist and that subpopulations of platelets may exist. Importantly, PAF concentrations inducing moderate CD63 and CD62P expression did not induce platelet aggregation, suggesting that platelets can be activated independently of aggregation.     

Flow cytometric analysis of platelet activation and fibrinogen binding

Human blood platelets can be activated by a variety of physiological activators such as adenosine diphosphate (ADP), thrombin or collagen, leading to activation of GPIIb-IIIa into a high-affinity receptor for Fg (FgR), binding of fibrinogen (Fg), and subsequent platelet aggregation required for normal hemostasis. Although enormous progress has been made in the biochemistry of platelet activation, of the platelet membrane GPIIb-IIIa, and of solution Fg, much less is known of the dynamics of expression of FgR, of its occupancy by Fg, and of their relation to the dynamics of platelet aggregation. Since platelet activation and aggregation occur within ～1 s of stirring with activators such as ADP, a methodology was required for determining the rapid dynamics of expression of FgR and binding of Fg, and their correlation with platelet aggregation kinetics. We therefore developed the theoretical and experimental base for determining these dynamic changes under non-equilibrium conditions, using fluorescently-labelled probes and flow cytometry. This approach has yielded a novel general technique for assessing the rapid dynamics of any cell surface molecule, as well as unexpected new insights into the kinetic expression and nature of FgR formed on platelet surfaces activated with ADP and PMA. The same approach has been extended to an analysis of the size-dependent (subpopulation) behaviour of platelets in expressing FgR, obtainable by analytically selecting platelets of different size from forward scatter profiles obtained in studies of the whole population. Parallel measurements of kinetics of platelet recruitment into microaggregates and expression and Fg occupancy of FgR as a function of ADP concentration, led to an unexpected new model for platelet activation and recruitment based once again on the selective recruitment of platelet subpopulation and an 'all or none, quantal' response of any single platelet in expressing all of its FgR and becoming recruitable for aggregation, but at a critical ADP concentration dependent on its own subpopulation characteristics. This approach has also led to novel insights into problems associated with platelet 'activation' arising with different isolation procedures. Dynamic binding studies of Fg to FgR on activated platelets has become possible using appropriately FITC-labelled Fg and flow cytometry. This has also led to studies of the relation between shear-dependent capture efficiency of platelets into doublet formation and the fraction of Fg-occupied receptors. In addition, we have successfully used FITC-labelled human and bovine Fg to demonstrate a delayed expression of FgR and Fg binding to ADP-activated platelets from bleeding Simmental cattle, although the final expression of numbers and accessibility of FgR, measured at equilibrium, were normal. Some future directions for dynamic flow cytometric studies of platelet activation and function are discussed.     

Flow cytometric analysis of platelet activation and fibrinogen binding

Human blood platelets can be activated by a variety of physiological activators such as adenosine diphosphate (ADP), thrombin or collagen, leading to activation of GPIIb-IIIa into a high-affinity receptor for Fg (FgR), binding of fibrinogen (Fg), and subsequent platelet aggregation required for normal hemostasis. Although enormous progress has been made in the biochemistry of platelet activation, of the platelet membrane GPIIb-IIIa, and of solution Fg, much less is known of the dynamics of expression of FgR, of its occupancy by Fg, and of their relation to the dynamics of platelet aggregation. Since platelet activation and aggregation occur within ～1 s of stirring with activators such as ADP, a methodology was required for determining the rapid dynamics of expression of FgR and binding of Fg, and their correlation with platelet aggregation kinetics. We therefore developed the theoretical and experimental base for determining these dynamic changes under non-equilibrium conditions, using fluorescently-labelled probes and flow cytometry. This approach has yielded a novel general technique for assessing the rapid dynamics of any cell surface molecule, as well as unexpected new insights into the kinetic expression and nature of FgR formed on platelet surfaces activated with ADP and PMA. The same approach has been extended to an analysis of the size-dependent (subpopulation) behaviour of platelets in expressing FgR, obtainable by analytically selecting platelets of different size from forward scatter profiles obtained in studies of the whole population. Parallel measurements of kinetics of platelet recruitment into microaggregates and expression and Fg occupancy of FgR as a function of ADP concentration, led to an unexpected new model for platelet activation and recruitment based once again on the selective recruitment of platelet subpopulation and an ‘all or none, quantal’ response of any single platelet in expressing all of its FgR and becoming recruitable for aggregation, but at a critical ADP concentration dependent on its own subpopulation characteristics. This approach has also led to novel insights into problems associated with platelet ‘activation’ arising with different isolation procedures. Dynamic binding studies of Fg to FgR on activated platelets has become possible using appropriately FITC-labelled Fg and flow cytometry. This has also led to studies of the relation between shear-dependent capture efficiency of platelets into doublet formation and the fraction of Fg-occupied receptors. In addition, we have successfully used FITC-labelled human and bovine Fg to demonstrate a delayed expression of FgR and Fg binding to ADP-activated platelets from bleeding Simmental cattle, although the final expression of numbers and accessibility of FgR, measured at equilibrium, were normal. Some future directions for dynamic flow cytometric studies of platelet activation and function are discussed.     

T cells in sputum of asthmatic patients are activated independently of disease severity or control

BackgroundT cells play an important role in bronchial asthma. Although airway CD4+ T cells have been extensively studied previously, there are hardly any studies relating CD8+ T cell activation and disease symptoms.ObjectivesThe aim of this study was to analyse the association between T cell activation in induced sputum T cells and asthma severity and control; and to evaluate T cell subpopulations in the same subgroups.MethodsFifty allergic asthmatic patients were recruited and lung function testing was performed. Airway cells were obtained by sputum induction via inhalation of hypertonic saline solution. CD3, CD4, CD8, CD28, CD25 and CD69 were studied by flow cytometry in whole induced sputum and peripheral blood cells.ResultsTotal induced sputum T cells and CD8+ T cells had a higher relative percentage of the activation markers CD25 and CD69 in comparison with peripheral blood. In sputum, the relative percentage of CD25 was higher in CD4+ T cells when compared to CD8+ T cells and the reverse was true regarding CD69. However, neither disease severity nor control were associated with the relative percentage of CD25 or CD69 expression on T cells in sputum.ConclusionsBoth CD4+ and CD8+ T cells are activated in the lungs and peripheral blood of asthmatic patients. However, with the possible exception of CD69+ CD8+ T lymphocytes in the sputum, there is no association between T cell activation phenotype in the target organ and disease severity or control.     

Flow-cytometric analysis of platelet activation during rotablation

Acute occlusion and subacute restenosis of the coronary artery are still the limiting factors of the otherwise successful interventional cardiology. Platelets and especially activated platelet populations play a key role concerning these typical and sometimes fatal complications. In this study we used flow-cytometry to determine the influence of the modern interventional technique of rotablation on platelet antigens and their possible alteration. A PTCA control group was included. We analyzed the fluorescence expression of structural antigens CD41a (GPII-IIIa) and CD42b (GPIb-V-IX), and of the activation-dependent antigens CD62p (P-selectin, PADGEM, GMP-140) and CD63 (GP53). Furthermore we analyzed the binding of fibrinogen to the platelet flow-cytometrically. CD41a and CD42b did not show significant alternations in fluorescence before, directly after and thirty minutes after finishing PTCA and rotablation (PTCA: CD41a p=0.8 and 0.9; CD42b p=0.5 and 0.2; rotablation: CD41a p=0.2 and 0.2; CD42b p=0.4 and 0.1). But platelet activation could be detected directly after PTCA and rotablation measuring the mean channel fluorescence intensity (MCFI) of CD62p, CD63 and fibrinogen binding (all p<0.05). Thirty minutes after finishing the procedures there were again significant changes in MCFI in PTCA (CD62p, CD63, fibrinogen binding; all p<0.05), but not in rotablation (CD62p p=0.1; CD63 p=0. 9; fibrinogen binding p=0.5). But MCFI for CD62p and fibrinogen binding in rotablation was higher than in PTCA. The results of our study show that rotablation also induces significant platelet activation that is higher than in PTCA alone. Flow cytometry is a sensitive and specific, multiparametric tool in establishing platelet activation. The individual platelet activation process is part of a complex cascade of events happening in the rotablated coronary segment leading to a vascular-molecular inflammatory process and consecutive clinical problems in some patients.     

Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE)

Mass cytometry enables an unprecedented number of parameters to be measured in individual cells at a high throughput, but the large dimensionality of the resulting data severely limits approaches relying on manual “gating.” Clustering cells based on phenotypic similarity comes at a loss of single-cell resolution and often the number of subpopulations is unknown a priori. Here we describe ACCENSE, a tool that combines nonlinear dimensionality reduction with density-based partitioning, and displays multivariate cellular phenotypes on a 2D plot. We apply ACCENSE to 35-parameter mass cytometry data from CD8⁺ T cells derived from specific pathogen-free and germ-free mice, and stratify cells into phenotypic subpopulations. Our results show significant heterogeneity within the known CD8⁺ T-cell subpopulations, and of particular note is that we find a large novel subpopulation in both specific pathogen-free and germ-free mice that has not been described previously. This subpopulation possesses a phenotypic signature that is distinct from conventional naive and memory subpopulations when analyzed by ACCENSE, but is not distinguishable on a biaxial plot of standard markers. We are able to automatically identify cellular subpopulations based on all proteins analyzed, thus aiding the full utilization of powerful new single-cell technologies such as mass cytometry.The immune system comprises many cell types that perform highly diverse functions and interact in complex ways during an immune response. The functional capabilities of individual cells are inextricably linked with their phenotypes, as defined by the expression levels of different proteins. These phenotypes are dynamic and alterations often occur, for example during the differentiation of lymphocytes from naive to memory cells upon encountering their specific antigens (1). Understanding which immune cell phenotypes exist is thus important for understanding the functional properties of the immune system as a whole. Flow cytometry, where cells are stained with fluorescently labeled antibodies and their protein targets quantified by light emission signals at single-cell resolution, has been the gold-standard technology for many years (2). Using this technique, hundreds of different immune cell populations have been defined based on differential protein expression. For example, T lymphocytes have been subdivided into helper T cells and killer T cells based on the expression of the coreceptors CD4 and CD8, respectively. In mice, these T-cell populations have also been further subdivided into antigen-naive cells (CD44⁻CD62L⁺) and multiple subpopulations of antigen-exposed cells [e.g., central memory (T_CM, CD44⁺CD62L⁺), effector memory (T_EM, CD44⁺CD62L⁻), and short-lived effector cells (T_SLEC, CD44⁺KLRG1⁺CD122⁺)]. Corresponding populations also exist in humans, although the defining markers differ. In both species, these T-cell subpopulations also exhibit functional differences in their proliferative potential, killing capacity, and cytokine production (3).Flow cytometry is currently constrained to 12–16 parameters per cell due to the limited light spectra and overlapping emission signals. In contrast, mass cytometry allows up to 42 parameters to be quantified on individual cells using metal-chelated probes without any significant signal overlap, thus resolving cellular phenotypes at an unprecedented level of detail (4). Using this technology, Newell et al. recently showed a continuous distribution of human CD8⁺ T-cell phenotypes and a previously unexpected level of functional diversity among these cells (5).The high-dimensional data (Fig. 1A) generated by mass cytometry are challenging to interpret in biologically meaningful ways. Conventional flow cytometry analysis involves manual analysis through a laborious and highly subjective process known as “gating” (Fig. 1B) (6). As the number of biaxial plots to analyze increases combinatorially with the number of markers analyzed, this process becomes intractable beyond 10–12 parameters. Important advances have been made toward developing better analytic tools for multivariate cytometry data (7). Many of these tools cluster cells with similar protein expression, like the recently developed spanning-tree progression analysis of density normalized events (SPADE) algorithm, which has been applied to mass cytometry data (8, 9). SPADE uses multivariate information to define cellular clusters and displays the underlying phenotypic hierarchy in a tree-like structure. The main drawbacks of clustering approaches are the loss of single-cell resolution and the requirement for prespecification of the number of target clusters desired, introducing bias regarding a quantity that is rarely known.Open in a separate windowFig. 1.ACCENSE applied to high-dimensional, high-throughput mass cytometry data. (A) Illustration of a sample mass cytometry dataset. Rows correspond to different cells whereas columns correspond to the different markers (cell-surface antigens and intracellular proteins) whose expressions are measured using metal-chelated antibodies. Entries correspond to transformed values (arcsinh) of mass–charge ratios that indicate expression levels of each marker. (B) Biaxial plots showing the expression of CD8α (y axis) against the expression of CD44 (Left), Ly6C (Middle), and CD8β (Right), respectively, and an illustration of the manual gating approach to identify cells expressing Ly6C (Middle). This group of cells is conventionally described as Ly6C⁺, whereas the remaining cells are tagged as Ly6C⁻. A similar approach is applied to classify cells based on other markers of interest. (C) The 2D t-SNE map of CD8⁺ T cells derived from SPF B6 mice. Each point represents a cell from the training set (M = 18,304) derived by down-sampling the original dataset. (D) A composite map depicting the local probability density of cells as embedded in panel C, computed using a kernel-based transform (Eq. 2 with γ = 7). Local maxima in this 2D density map represent centers of phenotypic subpopulations and were identified using a standard peak-detection algorithm (14).As an alternative, dimensionality reduction approaches aim at finding low-dimensional representations of high-dimensional data to allow easier visualization and interpretation, while retaining single-cell resolution. The spatial organization of datapoints in the low-dimensional space can be used to group cells into subpopulations with similar protein expression. Newell et al. applied principal component analysis (PCA) to 25-parameter mass cytometry data of human CD8⁺ T cells, and used the top three principal components (3D-PCA) to separate subpopulations (5). 3D-PCA represents the data in terms of three summary variables, each a linear combination of the original dimensions, defined so as to maximally capture the underlying variance in the data. That PCA finds the most optimal representation within the set of possible linear projections of the data is, however, also an important limitation––a linear projection may be too restrictive to yield accurate representations (10). To address this limitation, Amir et al. recently applied a nonlinear dimensionality reduction approach to visualize mass cytometry data (11). By using t-distributed stochastic neighbor embedding (or t-SNE) (12), multivariate cellular data could be represented on a 2D plot, similar to conventional biaxial flow plots. However, in contrast with these plots, wherein distance between cells reflects expression differences between only the two markers, distances on the t-SNE plot account for differences across all of the markers. Amir et al. demonstrated that t-SNE could effectively capture phenotypic relationships between cells, such as normal and leukemic bone marrow cells (11).Here we combine t-SNE with density-based partitioning into a single tool, ACCENSE (Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding), and use it to identify murine CD8⁺ T-cell subpopulations (SI Appendix, Tables S1 and S2) from high-dimensional mass cytometry data (SI Appendix 1) without having to predefine the number of expected populations. The work of Newell et al. (5) pertaining to human CD8⁺ T cells inspired us to ask to what extent a similar scenario was applicable in laboratory mice, which have been extensively used to advance our understanding of basic immunology over the years. Our analysis not only recovers well-known naive and memory CD8⁺ T-cell populations, but also identifies phenotypically distinct subpopulations within and outside of these. We believe that ACCENSE will be important for exploratory analysis by automatically extracting and quantifying cell populations, based not on only a few, but on the combined expression of the many different proteins measured by mass cytometry.     

CD4 and CD8 subpopulation changes during high dose intravenous immunoglobulin treatment

High doses of immunoglobulin, when given intravenously (IVIgG), influence lymphocyte subset numbers and function. T-lymphocytes may be subdivided into two functionally different groups, helper/inducer (CD4+) and suppressor/cytotoxic (CD8+). Considerable functional as well as phenotypic heterogeneity exists within the two major subsets. CD4+ cells have been further subdivided into helper/inducer and suppressor/inducer sets by the differential binding of two monoclonal antibodies 4B4 (CDw29) and 2H4 (CD45R). Similarly, the CD8+ subset may be subdivided into suppressor and cytotoxic populations by the differential binding of monoclonal antibodies which identify the C3bi receptor (CD11). During IVIgG treatment of patients with autoimmune thrombocytopenic purpura (ATP) the change in CD4/CD8, due to an absolute increase in CD8+ cells, has been shown to correlate with the response to treatment as determined by platelet increase. However, the total CD4+ and CD8- numbers may not reflect changes in their constituent subpopulations. To examine this possibility the CD4 and CD8 subpopulations were analysed in 15 ATP patients, during IVIgG treatment, using a double fluorescence technique. In 10 of these patients the in vitro response to pokeweed mitogen (PWM) and Staphylococcus aureus Cowan I (STA Cowan I) was determined. There was no correlation between the change in CD8+ subpopulations and response to treatment but there was a correlation between the CD4+ change and platelet increment. In addition there was a correlation between the 4B4/2H4 change and the in vitro response to PWM but no correlation with the response to STA Cowan I. These findings suggest that during IVIgG treatment the CD4+ 4B4+ helper/inducer population is influenced resulting in reduced T-dependent B-cell activation.     

Blood platelet activation evaluated by flow cytometry: optimised methods for clinical studies

A variety of flow cytometry techniques are in use to evaluate in vivo blood platelet activation. We have in this study further developed and optimised these methods to be suitable for use in clinical studies. By preloading the Monovette® EDTA vacuum blood sampling tubes with 1/8 vol 4% (w/v) paraformaldehyde (PFA), we were able to assess platelet CD62P (P-selectin) expression in whole blood with less than 0.2% activated platelets. No washing or neutralising steps were required to remove excess fixative. Both basal and agonist-stimulated CD62P expression were stable for at least 48 h after sampling. The standard curve was linear from 1.9 (basal) to 8.1·10 3 (TRAP-stimulated) molecules of equivalent soluble fluorochrome units (MESF) in phycoerythrein-conjugated anti-CD62P labelled whole blood samples. These assay conditions were also well suited for assessment of platelet expression of CD41, CD42a, CD61 and CD63. The preanalytic storage period was extended from 10 min to at least 2 h for platelet PAC–1 and fibrinogen binding analysis by preloading Monovette® citrate tubes with 8/10 vol buffer. With PFA preloading, blood sampled into citrated tubes could be analysed for fractions of microparticles and platelet–platelet aggregates as well as for aggregate size.     

Differential maturation of megakaryocyte progenitor cells from cord blood and mobilized peripheral blood

OBJECTIVE: In comparison with stem cell transplantation using bone marrow or cytokine-mobilized peripheral blood, cord blood transplantation is characterized by delayed engraftment, in particular platelet recovery. The differences in the kinetics of engraftment may be related to quantitative differences in the numbers of stem cells and megakaryocyte progenitor cells and/or to qualitative differences between megakaryocyte progenitor cells in these grafts. We compared the hematopoietic composition of these grafts and determined the distribution of mature and immature megakaryocyte progenitor cells in cord blood and mobilized peripheral blood and their in vitro kinetic behavior. METHODS: Megakaryocyte progenitor cell subpopulations from cord blood (CB) and mobilized peripheral blood (PBSC) were expanded in vitro in the presence of mpl-ligand. The developmental differences during expansion of megakaryocyte progenitors were analyzed by flow cytometry and progenitor assays. RESULTS: We found that the immature (CD34(+)/CD41(-)) subpopulation from CB contains more than 98% of all megakaryocyte progenitor cells, responsible for 99% of all megakaryocytic cells cultured during 2 weeks. The CB CD34(+)/CD41(+) subpopulation shows no contribution to megakaryocytic cell formation. In contrast, in PBSC the mature (CD34(+)/CD41(+)) subpopulation contains 7% of all megakaryocyte progenitor cells. Moreover, CD34(+) cells from CB and PBSC also showed distinct phenotypic differences during maturation in vitro. PBSC megakaryocyte progenitor cells transiently express both CD34 and CD41 during maturation in vitro, whereas CB progenitor cells transiently lack expression of both markers before differention into (CD34(-)/CD41(+)) megakaryocytic cells. CONCLUSION: The in vitro data indicate the presence of different developmental stages of megakaryocyte progenitor cells in CB as compared to PBSC. These differences in composition and maturation between CB and PBSC may be related to the different kinetics of engraftment following transplantation of these stem cell sources.     

Antitumor response of CD14+/CD16+ monocyte subpopulation

OBJECTIVE: Two main subpopulations of human blood monocytes are distinguished on the basis of CD14 and CD16 expression: the major population with enhanced expression of CD14 (CD14++ monocytes) and the minor one with a weak expression of CD14 coexpressing CD16 (CD14+/CD16+ monocytes). As monocytes and macrophages are involved in antitumor response of the host, we assessed the ability of CD14+/CD16+ monocytes to produce cytokines (intracellular expression, release) and reactive oxygen and nitrogen (ROI, RNI) intermediates following stimulation in vitro with tumor cells. MATERIALS AND METHODS: Monocytes were isolated by elutriation and their subpopulations by FACS sorting. Monocytes and their subpopulations were cocultured with tumor cells. Cytokine (TNF-alpha, IL-12, and IL-10) production was assessed by determination of intracellular protein expression by flow cytometry, and release by ELISA. ROI induction was detected by chemiluminescence and O2- production by flow cytometry, whereas RNI by intracellular expression of inducible NO synthase (iNOS) and nitric oxide (NO) release assessed colorimetrically. RESULTS: CD14+/CD16+ monocytes stimulated with tumor cells showed significantly enhanced production of TNF-alpha, IL-12p40, IL-12p70 (intracellular expression, release), whereas little IL-10 release was observed. CD14+/CD16+ subpopulation did not produce ROI, but showed an increased iNOS expression and NO release. CD14+/CD16+ monocytes also exhibited enhanced cytotoxic and cytostatic activities against tumor cells. CONCLUSIONS: CD14+/CD16+ cells constitute the main subpopulation of blood monocytes involved in antitumor response as judged by enhanced production of proinflammatory cytokines, RNI, and increased cytotoxic/cytostatic activity.