Search

Background: The Human Cell Differentiation Molecules (HCDM) organizes Human Leukocyte Differentiation Antigen (HLDA) workshops to test and name clusters of antibodies that react with a specific antigen. These cluster of differentiation (CD) markers have provided the scientific community with validated antibody clones, consistent naming of targets and reproducible identification of leukocyte subsets. Still, quantitative CD marker expression profiles and benchmarking of reagents at the single-cell level are currently lacking., Objective: To develop a flow cytometric procedure for quantitative expression profiling of surface antigens on blood leukocyte subsets that is standardized across multiple research laboratories., Methods: A high content framework to evaluate the titration and reactivity of Phycoerythrin (PE)-conjugated monoclonal antibodies (mAbs) was created. Two flow cytometry panels were designed: an innate cell tube for granulocytes, dendritic cells, monocytes, NK cells and innate lymphoid cells (12-color) and an adaptive lymphocyte tube for naive and memory B and T cells, including TCRγδ + , regulatory-T and follicular helper T cells (11-color). The potential of these 2 panels was demonstrated via expression profiling of selected CD markers detected by PE-conjugated antibodies and evaluated using 561 nm excitation., Results: Using automated data annotation and dried backbone reagents, we reached a robust workflow amenable to processing hundreds of measurements in each experiment in a 96-well plate format. The immunophenotyping panels enabled discrimination of 27 leukocyte subsets and quantitative detection of the expression of PE-conjugated CD markers of interest that could quantify protein expression above 400 units of antibody binding capacity. Expression profiling of 4 selected CD markers (CD11b, CD31, CD38, CD40) showed high reproducibility across centers, as well as the capacity to benchmark unique clones directed toward the same CD3 antigen., Conclusion: We optimized a procedure for quantitative expression profiling of surface antigens on blood leukocyte subsets. The workflow, bioinformatics pipeline and optimized flow panels enable the following: 1) mapping the expression patterns of HLDA-approved mAb clones to CD markers; 2) benchmarking new antibody clones to established CD markers; 3) defining new clusters of differentiation in future HLDA workshops., Competing Interests: BioLegend and Exbio kindly donated reagents used in this study. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.​​​​​​​​​​​​​​​​​​​​, (Copyright © 2022 Kužílková, Puñet-Ortiz, Aui, Fernández, Fišer, Engel, van Zelm and Kalina.)

We collected a multi-centric retrospective dataset of patients (N = 213) who were admitted to ten hospitals in Czech Republic and tested positive for SARS-CoV-2 during the early phases of the pandemic in March-October 2020. The dataset contains baseline patient characteristics, breathing support required, pharmacological treatment received and multiple markers on daily resolution. Patients in the dataset were treated with hydroxychloroquine (N = 108), azithromycin (N = 72), favipiravir (N = 9), convalescent plasma (N = 7), dexamethasone (N = 4) and remdesivir (N = 3), often in combination. To explore association between treatments and patient outcomes we performed multiverse analysis, observing how the conclusions change between defensible choices of statistical model, predictors included in the model and other analytical degrees of freedom. Weak evidence to constrain the potential efficacy of azithromycin and favipiravir can be extracted from the data. Additionally, we performed external validation of several proposed prognostic models for Covid-19 severity showing that they mostly perform unsatisfactorily on our dataset., Competing Interests: The authors have declared that no competing interests exist.

The nuclear pore complex (NPC) has emerged as a hub for the transcriptional regulation of a subset of genes, and this type of regulation plays an important role during differentiation. Nucleoporin TPR forms the nuclear basket of the NPC and is crucial for the enrichment of open chromatin around NPCs. TPR has been implicated in the regulation of transcription; however, the role of TPR in gene expression and cell differentiation has not been described. Here we show that depletion of TPR results in an aberrant morphology of murine proliferating C2C12 myoblasts (MBs) and differentiated C2C12 myotubes (MTs). The ChIP-Seq data revealed that TPR binds to genes linked to muscle formation and function, such as myosin heavy chain ( Myh4 ), myocyte enhancer factor 2C ( Mef2C ) and a majority of olfactory receptor ( Olfr ) genes. We further show that TPR, possibly via lysine-specific demethylase 1 (LSD1), promotes the expression of Myh4 and Olfr376 , but not Mef2C . This provides a novel insight into the mechanism of myogenesis; however, more evidence is needed to fully elucidate the mechanism by which TPR affects specific myogenic genes.

Summary: ShinySOM offers a user-friendly interface for reproducible, high-throughput analysis of high-dimensional flow and mass cytometry data guided by self-organizing maps. The software implements a FlowSOM-style workflow, with improvements in performance, visualizations and data dissection possibilities. The outputs of the analysis include precise statistical information about the dissected samples, and R-compatible metadata useful for the batch processing of large sample volumes., Availability and Implementation: ShinySOM is free and open-source, available online at gitlab.com/exaexa/ShinySOM., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2020. Published by Oxford University Press.)

Objective:  Blood monocyte subsets are emerging as biomarkers of cardiovascular inflammation. However, our understanding of human monocyte heterogeneity and their immunophenotypic features under healthy and inflammatory conditions is still evolving., Rationale:  In this study, we sought to investigate the immunophenome of circulating human monocyte subsets., Methods:  Multiplexed, high-throughput flow cytometry screening arrays and computational data analysis were used to analyze the expression and hierarchical relationships of 242 specific surface markers on circulating classical (CD14 ++ CD16 - ), intermediate (CD14 ++ CD16 + ), and nonclassical (CD14 + CD16 ++ ) monocytes in healthy adults., Results:  Using generalized linear models and hierarchical cluster analysis, we selected and clustered epitopes that most reliably differentiate between monocyte subsets. We validated existing transcriptional profiling data and revealed potential new surface markers that uniquely define the classical (e.g., BLTR1, CD35, CD38, CD49e, CD89, CD96), intermediate (e.g., CD39, CD275, CD305, CDw328), and nonclassical (e.g., CD29, CD132) subsets. In addition, our analysis revealed phenotypic cell clusters, identified by dendritic markers CMRF-44 and CMRF-56, independent of the traditional monocyte classification., Conclusion:  These results reveal an advancement of the clinically applicable multiplexed screening arrays that may facilitate monocyte subset characterization and cytometry-based biomarker selection in various inflammatory disorders., Competing Interests: None declared., (Georg Thieme Verlag KG Stuttgart · New York.)

Hematopoiesis in mammalian embryos proceeds through three successive waves of hematopoietic progenitors. Since their emergence spatially and temporally overlap and phenotypic markers are often shared, the specifics regarding their origin, development, lineage restriction and mutual relationships have not been fully determined. The identification of wave-specific markers would aid to resolve these uncertainties. Here, we show that toll-like receptors (TLRs) are expressed during early mouse embryogenesis. We provide phenotypic and functional evidence that the expression of TLR2 on E7.5 c-kit + cells marks the emergence of precursors of erythro-myeloid progenitors (EMPs) and provides resolution for separate tracking of EMPs from primitive progenitors. Using in vivo fate mapping, we show that at E8.5 the Tlr2 locus is already active in emerging EMPs and in progenitors of adult hematopoietic stem cells (HSC). Together, this data demonstrates that the activation of the Tlr2 locus tracks the earliest events in the process of EMP and HSC specification.

CD molecules are surface molecules expressed on cells of the immune system that play key roles in immune cell-cell communication and sensing the microenvironment. These molecules are essential markers for the identification and isolation of leukocytes and lymphocyte subsets. Here, we present the results of the first phase of the CD Maps study, mapping the expression of CD1-CD100 ( n = 110) on 47 immune cell subsets from blood, thymus, and tonsil using an eight-color standardized EuroFlow approach and quantification of expression. The resulting dataset included median antibody binding capacities (ABCs) and percentage of positivity for all markers on all subsets and was developed into an interactive CD Maps web resource. Using the resource, we examined differentially expressed proteins between granulocyte, monocyte, and dendritic cell subsets, and profiled dynamic expression of markers during thymocyte differentiation, T-cell maturation, and between functionally distinct B-cell subset clusters. The CD Maps resource will serve as a benchmark of antibody reactivities ensuring improved reproducibility of flow cytometry-based research. Moreover, it will provide a full picture of the surfaceome of human immune cells and serves as a useful platform to increase our understanding of leukocyte biology, as well as to facilitate the identification of new biomarkers and therapeutic targets of immunological and hematological diseases., (Copyright © 2019 Kalina, Fišer, Pérez-Andrés, Kužílková, Cuenca, Bartol, Blanco, Engel and van Zelm.)

The organization of the nuclear periphery is crucial for many nuclear functions. Nuclear lamins form dense network at the nuclear periphery and play a substantial role in chromatin organization, transcription regulation and in organization of nuclear pore complexes (NPCs). Here, we show that TPR, the protein located preferentially within the nuclear baskets of NPCs, associates with lamin B1. The depletion of TPR affects the organization of lamin B1 but not lamin A/C within the nuclear lamina as shown by stimulated emission depletion microscopy. Finally, reduction of TPR affects the distribution of NPCs within the nuclear envelope and the effect can be reversed by simultaneous knock-down of lamin A/C or the overexpression of lamin B1. Our work suggests a novel role for the TPR at the nuclear periphery: the TPR contributes to the organization of the nuclear lamina and in cooperation with lamins guards the interphase assembly of nuclear pore complexes.

The Flow Cytometry Standard (FCS) format is a widely accepted norm for storing Flow Cytometry (FCM) data. Its goal as a standard is to allow FCM data sharing and re-analysis. Over more than three decades of its existence FCS has evolved into a well-defined, flexible file format reflecting technical changes in the FCM field. Its flexibility as well as rising numbers of instrument vendors leads to suboptimal implementations of FCS in some cases. Such situations compromise the primary goal of the standard and hinder the ability to reproduce FCM analyses. It is further underlined by rapid rise of advanced FCM analyses, often carried out outside traditional software tools and heavily relying on standard data storage and presentation. We have developed flowIO, an R package which tests FCS file conformance with the standard as defined by International Society for Advancement of Cytometry (ISAC) normative. Along with the package we provide a web based application (also at http://bioinformin.cesnet.cz/flowIO/) allowing user friendly access to the conformance testing as well as FCS file editing and export for further analysis., (© 2018 International Society for Advancement of Cytometry.)

The combination of color-coded microspheres as carriers and flow cytometry as a detection platform provides new opportunities for multiplexed measurement of biomolecules. Here, we developed a software tool capable of automated gating of color-coded microspheres, automatic extraction of statistics from all subsets and validation, normalization, and cross-sample analysis. The approach presented in this article enabled us to harness the power of high-content cellular proteomics. In size exclusion chromatography-resolved microsphere-based affinity proteomics (Size-MAP), antibody-coupled microspheres are used to measure biotinylated proteins that have been separated by size exclusion chromatography. The captured proteins are labeled with streptavidin phycoerythrin and detected by multicolor flow cytometry. When the results from multiple size exclusion chromatography fractions are combined, binding is detected as discrete reactivity peaks (entities). The information obtained might be approximated to a multiplexed western blot. We used a microsphere set with >1,000 subsets, presenting an approach to extract biologically relevant information. The R-project environment was used to sequentially recognize subsets in two-dimensional space and gate them. The aim was to extract the median streptavidin phycoerythrin fluorescence intensity for all 1,000+ microsphere subsets from a series of 96 measured samples. The resulting text files were subjected to algorithms that identified entities across the 24 fractions. Thus, the original 24 data points for each antibody were compressed to 1-4 integrated values representing the areas of individual antibody reactivity peaks. Finally, we provide experimental data on cellular protein changes induced by treatment of leukemia cells with imatinib mesylate. The approach presented here exemplifies how large-scale flow cytometry data analysis can be efficiently processed to employ flow cytometry as a high-content proteomics method., (Copyright © 2011 International Society for Advancement of Cytometry.)

Flow cytometry is a valuable tool in research and diagnostics including minimal residual disease (MRD) monitoring of hematologic malignancies. However, its gradual advancement toward increasing numbers of fluorescent parameters leads to information rich datasets, which are challenging to analyze by standard gating and do not reflect the multidimensionality of the data. We have developed a novel method to analyze complex flow cytometry data, based on hierarchical clustering analysis (HCA) but with a new underlying algorithm, using Mahalanobis distance measure. HCA is scalable to analyze complex multiparameter datasets (here demonstrated on up to 12 color flow cytometry and on a 20-parameter synthetic dataset). We have validated this method by comparison with standard gating approaches when performed independently by expert cytometrists. Acute lymphoblastic leukemia blast populations were analyzed in diagnostic and follow-up datasets (n = 123) from three centers. HCA results correlated very well (Passing-Bablok correlation coefficient = 0.992, slope = 1, intercept = -0.01) with standard gating data obtained by the I-BFM FLOW-MRD study group. To further improve the performance in follow-up samples with low MRD levels and to automate MRD detection, we combined HCA with support vector machine (SVM) learning. HCA in combination with SVM provides a novel diagnostic tool that not only allows analysis of increasingly complex flow cytometry data but also is less observer-dependent compared with classical gating and has potential for automation., (Copyright © 2011 International Society for Advancement of Cytometry.)