Acquisition of murine splenic myeloid cells for protein and gene expression profiling by advanced flow cytometry and CITE-seq.
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ABSTRACT:
SUBMITTER: Rodahl I
PROVIDER: S-EPMC8456112 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe rapid advancement of new genomic sequencing technology has enabled the development of multi-omic single-cell sequencing assays. These assays profile multiple modalities in the same cell and can often yield new insights not revealed with a single modality. For example, Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) simultaneously profiles the RNA transcriptome and the surface protein expression. The surface protein markers in CITE-Seq can be used to identify cell populations similar to the iterative filtration process in flow cytometry, also called "gating", and is an essential step for downstream analyses and data interpretation. While several packages allow users to interactively gate cells, they often do not process multi-omic sequencing datasets and may require writing redundant code to specify gate boundaries. To streamline the gating process, we developed CITEViz which allows users to interactively gate cells in Seurat-processed CITE-Seq data. CITEViz can also visualize basic quality control (QC) metrics allowing for a rapid and holistic evaluation of CITE-Seq data.ResultsWe applied CITEViz to a peripheral blood mononuclear cell CITE-Seq dataset and gated for several major blood cell populations (CD14 monocytes, CD4 T cells, CD8 T cells, NK cells, B cells, and platelets) using canonical surface protein markers. The visualization features of CITEViz were used to investigate cellular heterogeneity in CD14 and CD16-expressing monocytes and to detect differential numbers of detected antibodies per patient donor. These results highlight the utility of CITEViz to enable the robust classification of single cell populations.ConclusionsCITEViz is an R-Shiny app that standardizes the gating workflow in CITE-Seq data for efficient classification of cell populations. Its secondary function is to generate basic feature plots and QC figures specific to multi-omic data. The user interface and internal workflow of CITEViz uniquely work together to produce an organized workflow and sensible data structures for easy data retrieval. This package leverages the strengths of biologists and computational scientists to assess and analyze multi-omic single-cell datasets. In conclusion, CITEViz streamlines the flow cytometry gating workflow in CITE-Seq data to help facilitate novel hypothesis generation.
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Project description:Flow cytometry allows the visualization of physical, functional, and/or biological properties of cells including antigens, cytokines, size, and complexity. With increasingly large flow cytometry panels able to analyze up to 50 parameters, there is a need to standardize flow cytometry protocols to achieve high-quality data that can be input into analysis algorithms. Without this clean data, algorithms may incorrectly categorize the cell populations present in the samples. In this protocol, we outline a comprehensive methodology to prepare samples for polychromatic flow cytometry. The use of multiple washing steps and rigorous controls creates high-quality data with good separation between cell populations. Experimental data acquired using this protocol can be analyzed via computational algorithms that perform end-to-end analysis. © 2020 by John Wiley & Sons, Inc. Basic Protocol 1: Preparation of single-cell suspension for flow cytometry Support Protocol 1: Lung preparation Support Protocol 2: Counting cells on a flow cytometer Basic Protocol 2: Surface and intracellular flow cytometry staining Support Protocol 3: Single-color bead controls.
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Project description:Meiotic prophase I (MPI), is an initial stage of meiosis characterized by intricate homologous chromosome interactions, synapsis, and DNA recombination. These processes depend on the complex, but poorly understood early MPI events of homologous chromosome search, alignment, and pairing. Detailed molecular investigation of these early events requires isolation of individual MPI substages. Enrichment for Pachytene (P) and Diplotene (D) substages of late MPI was previously accomplished using flow cytometry. However, separation of early MPI spermatocytes, specifically, of Leptotene (L) and Zygotene (Z) substages, has been a challenge due to these cells' similar characteristics. In this report, we describe an optimized Hoechst-33342 (Hoechst)-based flow cytometry approach for isolating individual MPI populations from adult mouse testis. We get significant enrichment for individual L and Z spermatocytes, previously inseparable from each other, and optimize the isolation of other MPI substages. Our flow cytometry approach is a combination of three optimized strategies. The first is optimization of testis dissociation protocol that yields more consistent and reproducible testicular single cell suspension. The second involves optimization of flow cytometric gating protocol where a critical addition to the standard protocol for cell discrimination based on Hoechst fluorescence, involves a back-gating technique based on light scattering parameters. This step specifies selection of individual MPI substages. The third, is an addition of DNA content restriction to the gating protocol to minimize contamination from non-meiotic cells. Finally, we confirm significant enrichment of high-purity Preleptotene (PreL), L, Z, P, and D MPI spermatocytes using stage-specific marker distribution. The technique will facilitate understanding of the molecular events underlying MPI.
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Project description:Measurable residual disease (MRD) assessment provides a potent indicator of the efficacy of anti-leukemic therapy. It is unknown, however, whether integrating MRD with molecular profiling better identifies patients at risk of relapse. To investigate the clinical relevance of MRD in relation to a molecular-based prognostic schema, we measured MRD by flow cytometry in 189 AML patients enrolled in ECOG-ACRIN E1900 trial (NCT00049517) in morphologic complete remission (CR) (28.8 % of the original cohort) representing 44.4 % of CR patients. MRD positivity was defined as ≥ 0.1 % of leukemic bone marrow cells. Risk classification was based on standard cytogenetics, fluorescence-in-situ-hybridization, somatic gene analysis, and sparse whole genome sequencing for copy number ascertainment. At 84.6 months median follow-up of patients still alive at the time of analysis (range 47.0-120 months), multivariate analysis demonstrated that MRD status at CR (p = 0.001) and integrated molecular risk (p = 0.0004) independently predicted overall survival (OS). Among risk classes, MRD status significantly affected OS only in the favorable risk group (p = 0.002). Expression of CD25 (α-chain of the interleukin-2 receptor) by leukemic myeloblasts at diagnosis negatively affected OS independent of post-treatment MRD levels. These data suggest that integrating MRD with genetic profiling and pre-treatment CD25 expression may improve prognostication in AML.
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Project description:MotivationDeep profiling the phenotypic landscape of tissues using high-throughput flow cytometry (FCM) can provide important new insights into the interplay of cells in both healthy and diseased tissue. But often, especially in clinical settings, the cytometer cannot measure all the desired markers in a single aliquot. In these cases, tissue is separated into independently analysed samples, leaving a need to electronically recombine these to increase dimensionality. Nearest-neighbour (NN) based imputation fulfils this need but can produce artificial subpopulations. Clustering-based NNs can reduce these, but requires prior domain knowledge to be able to parameterize the clustering, so is unsuited to discovery settings.ResultsWe present flowBin, a parameterization-free method for combining multitube FCM data into a higher-dimensional form suitable for deep profiling and discovery. FlowBin allocates cells to bins defined by the common markers across tubes in a multitube experiment, then computes aggregate expression for each bin within each tube, to create a matrix of expression of all markers assayed in each tube. We show, using simulated multitube data, that flowType analysis of flowBin output reproduces the results of that same analysis on the original data for cell types of >10% abundance. We used flowBin in conjunction with classifiers to distinguish normal from cancerous cells. We used flowBin together with flowType and RchyOptimyx to profile the immunophenotypic landscape of NPM1-mutated acute myeloid leukemia, and present a series of novel cell types associated with that mutation.
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Project description:Hematopoietic stem cells (HSCs) remain the most well-characterized adult stem cell population both in terms of markers for purification and assays to assess functional potential. However, despite over 40 years of research, working with HSCs in the mouse remains challenging because of the relative abundance (or lack thereof) of these cells in the bone marrow. The frequency of HSCs in murine bone marrow is about 0.01% of total nucleated cells and ?5,000 can be isolated from an individual mouse depending on the age, sex, and strain of mice as well as purification scheme utilized. Adding to the challenge is the continual reporting of new markers for HSC purification, which makes it difficult for the uninitiated in the field to know which purification strategies yield the highest proportion of long-term, multilineage HSCs. In this updated version of our review from 2009, we review different strategies for hematopoietic stem and progenitor cell identification and purification. We will also discuss methods for rapid flow cytometric analysis of peripheral blood cell types, and novel strategies for working with rare cell populations such as HSCs in the analysis of cell cycle status by BrdU, Ki-67, and Pyronin Y staining. The purpose of updating this review is to provide insight into some of the recent experimental and technical advances in mouse hematopoietic stem cell biology.
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Project description:Tissue-resident macrophages in the spleen, including red pulp and white pulp macrophages, marginal zone macrophages (MZMs) and marginal zone metallophilic macrophages (MMMs), are highly heterogeneous as a consequence of adaptation to tissue-specific environments. Each macrophage sub-population in the spleen is usually identified based on the localization, morphology and membrane antigen expression by immunohistochemistry. However, their phenotypical and functional characteristics remain incompletely understood due to the difficulty of identification and isolation by flow cytometry. We used a cocktail of three enzymes (Collagenase D, Dispase I and DNase I), rather than traditional mechanical grinding, for isolation of each sub-population, which resulted in significant improvement of isolation of these macrophage sub-populations, particularly MZMs and MMMs, as determined by CD11bhiF4/80medTim4hi and CD11bhiF4/80medTim4med, respectively. This method should be helpful for molecular and functional characterization of each splenic resident macrophage sub-population.
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Project description:Acute myeloid leukemias (AMLs) are a group of hematologic malignancies that are heterogeneous in their molecular and immunophenotypic profiles. Identification of the immunophenotypic differences between AML blasts and normal myeloid hematopoietic precursors (myHPCs) is a prerequisite to achieving better performance in AML measurable residual disease follow-ups. In the present study, we applied high-dimensional analysis algorithms provided by the Infinicyt 2.0 and Cytobank software to evaluate the efficacy of antibody combinations of the EuroFlow AML/myelodysplastic syndrome panel to distinguish AML blasts with recurrent genetic abnormalities (n = 39 AML samples) from normal CD45low CD117+ myHPCs (n = 23 normal bone marrow samples). Two types of scores were established to evaluate the abilities of the various methods to identify the most useful parameters/markers for distinguishing between AML blasts and normal myHPCs, as well as to distinguish between different AML groups. The Infinicyt Compass database-guided analysis was found to be a more user-friendly tool than other analysis methods implemented in the Cytobank software. According to the developed scoring systems, the principal component analysis based algorithms resulted in better discrimination between AML blasts and myHPCs, as well as between blasts from different AML groups. The most informative markers for the discrimination between myHPCs and AML blasts were CD34, CD36, human leukocyte antigen-DR (HLA-DR), CD13, CD105, CD71, and SSC, which were highly rated by all evaluated analysis algorithms. The HLA-DR, CD34, CD13, CD64, CD33, CD117, CD71, CD36, CD11b, SSC, and FSC were found to be useful for the distinction between blasts from different AML groups associated with recurrent genetic abnormalities. This study identified both benefits and the drawbacks of integrating multiple high-dimensional algorithms to gain complementary insights into the flow-cytometry data.
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Project description:The recently developed method TEA-seq and similar DOGMA-seq single cell trimodal omics assays provide unprecedented opportunities for understanding cell biology, but independent evaluation is lacking. We explore the utility of DOGMA-seq compared to the bimodal CITE-seq assay in activated and stimulated human peripheral blood T cells. We find that single cell trimodal omics measurements after digitonin (DIG) permeabilization were generally better than after an alternative "low-loss lysis" (LLL) permeabilization condition. Next, we find that DOGMA-seq with optimized DIG permeabilization and its ATAC library provides more information, although its mRNA and cell surface protein libraries have slightly inferior quality, compared to CITE-seq.
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