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Antibody conjugates applicable in both conventional flow and mass cytometry would offer interesting options for cross-platform comparison, as well as the enrichment of rare target cells by conventional flow cytometry (FC) sorting prior to deep phenotyping by mass cytometry (MC). Here, we introduce a simple method to generate dual fluorochrome/metal-labelled antibodies by consecutive orthogonal labelling. First, we compared different fluorochrome-conjugated antibodies specific for CD4, such as FITC, Vio667, VioGreen or VioBlue for their compatibility with the conventional secondary MAXPAR® labelling protocol. After labelling with 141 Pr, the fluorescence emission spectra of all fluorochromes investigated retained their characteristics, and CD4 dual conjugates (DCs) provided consistent results in immune phenotyping assays performed by FC and MC. The phenotypical composition of CD4+ T-cells was maintained after enrichment by FC sorting using different CD4 DCs. Finally, magnetic cell depletion was combined with FC sorting using CD19-VioBlue-142 Nd, CD20-VioGreen-147 Sm, CD27-Cy5-167 Er and CD38-Alexa488-143 Nd DC to enrich rare human plasmablasts to purities >80%, which allowed a subsequent deep phenotyping by MC. In conclusion, DCs have been successfully established for direct assay comparison between FC and MC, and help to minimise MC data acquisition time for deep phenotyping of rare cell subsets.

Keywords: mass cytometry; panel design; mass-response characteristic; human blood leukocytes; immune phenotyping; immune monitoring; autoimmunity; rheumatism; systemic lupus erythematosus (SLE); biomarker and clinical trial

Mass cytometry has pioneered >40-parameter single-cell analyses that allow for the characterization of complex cellular networks at unprecedented depth. Up to 135 parameters can be simultaneously detected, but limited availability of metal tags suitable for labeling of specific probes prevents optimal exploitation of the analytical capacity of mass cytometers. To this end, we here establish the application of elemental silver nanoparticles (AgNP) of different size for reporting cell surface antigens on human leukocytes in mass cytometry assays. The mass channels at 107 Da and 109 Da are uniquely occupied by silver isotopes and do not interfere with other mass cytometry reagents. Streptavidin-coated AgNP (SA-AgNP) facilitated distinct and specific detection of various antigens, such as CD8, CD244 and CD294 on peripheral blood leukocytes pre-incubated with respective biotinylated primary antibodies. Signal intensities elicited by 40 nm-sized AgNP allowed specific detection of the low abundance antigen CD25 on both, peripheral blood regulatory T cells and CD25lo CD127+ CD4+ T cells, enabling their distinct clustering in viSNE plots. SA-AgNP were of high elemental purity, showed minor background binding to cells in immunoassays, and were compatible with previously established staining protocols for PBMC and leukocytes, facilitating their use in complex mass cytometry panels. Considering the synthesis of AgNP from isotopically purified silver, the usage of AgNP extends the analytical capacity of mass cytometry panels by one, prospectively two, additional parameters, suitable for the detection of cellular targets of low abundance. © 2016 International Society for Advancement of Cytometry.

Multiparametric fluorescence and mass cytometry offers new perspectives to disclose and to monitor the high diversity of cell populations in the peripheral blood for biomarker research. While high-end cytometric devices are currently available to detect theoretically up to 120 individual parameters at the single cell level, software tools are needed to analyze these complex datasets automatically in acceptable time and without operator bias or knowledge. We developed an automated analysis pipeline, immunoClust, for uncompensated fluorescence and mass cytometry data, which consists of two parts. First, cell events of each sample are grouped into individual clusters. Subsequently, a classification algorithm assorts these cell event clusters into populations comparable between different samples. The clustering of cell events is designed for datasets with large event counts in high dimensions as a global unsupervised method, sensitive to identify rare cell types even when next to large populations. Both parts use model-based clustering with an iterative expectation maximization algorithm and the integrated classification likelihood to obtain the clusters. A detailed description of both algorithms is presented. Testing and validation was performed using 1) blood cell samples of defined composition that were depleted of particular cell subsets by magnetic cell sorting, 2) datasets of the FlowCAP III challenges to identify populations of rare cell types and 3) high-dimensional fluorescence and mass-cytometry datasets for comparison with conventional manual gating procedures. In conclusion, the immunoClust-algorithm is a promising tool to standardize and automate the analysis of high-dimensional cytometric datasets. As a prerequisite for interpretation of such data, it will support our efforts in developing immunological biomarkers for chronic inflammatory disorders and therapy recommendations in personalized medicine. immunoClust is implemented as an R-package and is provided as source code from www.bioconductor.org.

From city to megacity: Dhaka in Bangladesh is an example of how people living in peripheral settlements strive to secure their survival. But this “informal urbanisation” presents urban planners with enormous challenges.

Vom System Stadt zum System Megacity: Das Beispiel Dhakas in Bangladesch zeigt, wie Menschen mit Siedlungen an der Stadtperipherie ihr Uberleben sichern wollen. Doch die „informelle Urbanisierung” stellt Stadt- und Raumplaner vor gewaltige Herausforderungen.