Project description:Single-cell methods offer a high-resolution approach for characterizing cell populations. Many studies rely on single-cell transcriptomics to draw conclusions regarding cell state and behavior, with the underlying assumption that transcriptomic readouts largely parallel their protein counterparts and subsequent activity. However, the relationship between transcriptomic and proteomic measurements is imprecise, and thus datasets that probe the extent of their concordance will be useful to refine such conclusions. Additionally, novel single-cell analysis tools often lack appropriate gold standard datasets for the purposes of assessment. Integrative (combining the two data modalities) and predictive (using one modality to improve results from the other) approaches in particular, would benefit from transcriptomic and proteomic data from the same sample of cells. For these reasons, we performed single-cell RNA sequencing, mass cytometry, and flow cytometry on a split-sample of human peripheral blood mononuclear cells. We directly compare the proportions of specific cell types resolved by each technique, and further describe the extent to which protein and mRNA measurements correlate within distinct cell types.
Project description:New techniques for single-cell analysis have led to insights into hematopoiesis and the immune system, but the ability of these techniques to cross-validate and reproducibly identify the biological variation in diverse human samples is currently unproven. We therefore performed a comprehensive assessment of human bone marrow cells using both single-cell RNA sequencing and multiparameter flow cytometry from twenty healthy adult human donors across a broad age range. These data characterize variation between healthy donors as well as age-associated changes in cell population frequencies. Direct comparison of techniques revealed discrepancy in the quantification of T lymphocyte and natural killer cell populations. Orthogonal validation of immunophenotyping using mass cytometry demonstrated good correlation with flow cytometry. Technical replicates using single-cell RNA sequencing matched robustly, while biological replicates showed variation. Given the increasing use of single-cell technologies in translational research, this resource serves as an important reference dataset and highlights opportunities for further refinement. [Funding source] Project Number: 1ZIAHL006163-05 Contact PI / Project Leader: HOURIGAN, CHRISTOPHER Title: DETECTION, PREVENTION AND TREATMENT OF ACUTE MYELOID LEUKEMIA (AML) RELAPSE. Awardee Organization: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE
Project description:To investigate a non-invasive strategy for immune monitoring the peripheral blood by flow cytometry, to address the critical need to itdentify predictive immunological biomarkers that correlate with treatment response Peripheral blood mononuclear cells (PBMCs) from 19 non–small-cell lung cancer (NSCLC) patients before and after ICI treatment and four healthy human donors were evaluated, utilizing spectral flow to monitor 24 immune cell markers simultaneously over the course of treatment. We performed immune cell profiling analysis using data obtained from RNA-seq of 19 different patients before and after immunotherapy, to validate the multi-color flow based immune profiling
Project description:Mass and fluorescence cytometry are quantitative single cell flow cytometry approaches that are powerful tools for characterizing diverse tissues and cellular systems. Here mass cytometry was directly compared with fluorescence cytometry by studying phenotypes of healthy human peripheral blood mononuclear cells (PBMC) in the context of superantigen stimulation. One mass cytometry panel and five fluorescence cytometry panels were used to measure 20 well-established lymphocyte markers of memory and activation. Comparable frequencies of both common and rare cell subpopulations were observed with fluorescence and mass cytometry using biaxial gating. The unsupervised high-dimensional analysis tool viSNE was then used to analyze data sets generated from both mass and fluorescence cytometry. viSNE analysis effectively characterized PBMC using eight features per cell and identified similar frequencies of activated CD4+ T cells with both technologies. These results suggest combinations of unsupervised analysis programs and extended multiparameter cytometry will be indispensable tools for detecting perturbations in protein expression in both health and disease.
Project description:Mass cytometry is developing as a means of multiparametric single-cell analysis. In this study, we present an approach to barcoding separate live human PBMC samples for combined preparation and acquisition on a cytometry by time of flight instrument. Using six different anti-CD45 Ab conjugates labeled with Pd104, Pd106, Pd108, Pd110, In113, and In115, respectively, we barcoded up to 20 samples with unique combinations of exactly three different CD45 Ab tags. Cell events carrying more than or less than three different tags were excluded from analyses during Boolean data deconvolution, allowing for precise sample assignment and the electronic removal of cell aggregates. Data from barcoded samples matched data from corresponding individually stained and acquired samples, at cell event recoveries similar to individual sample analyses. The approach greatly reduced technical noise and minimizes unwanted cell doublet events in mass cytometry data, and it reduces wet work and Ab consumption. It also eliminates sample-to-sample carryover and the requirement of instrument cleaning between samples, thereby effectively reducing overall instrument runtime. Hence, CD45 barcoding facilitates accuracy of mass cytometric immunophenotyping studies, thus supporting biomarker discovery efforts, and it should be applicable to fluorescence flow cytometry as well.