Fragmentation of macrophages during isolation confounds analysis of single cell preparations from mouse hematopoietic tissues

SummaryMouse hematopoietic tissues contain abundant and heterogeneous populations of tissue-resident macrophages attributed trophic functions in control of immunity, hematopoiesis and bone homeostasis. A systematic strategy to characterise macrophage subsets in mouse bone marrow (BM), spleen and lymph node, unexpectedly revealed macrophage surface marker staining typically emanated from membrane-bound subcellular remnants associated with unrelated cell types. Remnant-restricted macrophage-specific membrane markers, cytoplasmic fluorescent reporters and mRNA were all detected in non-macrophage cell populations including isolated stem and progenitor cells. The profile of macrophage remnant association reflects adhesive interactions between macrophages and other cell types in vivo. Applying this knowledge, reduced macrophage remnant attachment to BM granulocytes in Siglec1 deficient mice was associated with compromised emergency granulocytosis, revealing a function for Siglec1-dependent granulocyte-macrophage interactions. Analysis of published RNA-seq data for purified macrophage and non-macrophage populations indicates that macrophage fragmentation is a general phenomenon that confounds bulk and single cell analysis of disaggregated tissues.

Download Full-text

Assessing the Heterogeneity of Cardiac Non-myocytes and the Effect of Cell Culture with Integrative Single Cell Analysis

10.1101/2020.03.04.975177 ◽

2020 ◽

Author(s):

Brian S. Iskra ◽

Logan Davis ◽

Henry E. Miller ◽

Yu-Chiao Chiu ◽

Alexander R. Bishop ◽

...

Keyword(s):

Cell Culture ◽

Single Cell ◽

Single Cell Analysis ◽

Cell Types ◽

Cell Analysis ◽

Mass Cytometry ◽

Single Cell Rna Sequencing ◽

High Depth

AbstractCardiac non-myocytes comprise a diverse and crucial cell population in the heart that plays dynamic roles in cardiac wound healing and growth. Non-myocytes broadly fall into four cell types: endothelium, fibroblasts, leukocytes, and pericytes. Here we characterize the diversity of the non-myocytes in vivo and in vitro using mass cytometry. By leveraging single-cell RNA sequencing we inform the design of a mass cytometry panel. To aid in annotation of the mass cytometry datasets, we utilize data integration with a neural network. We introduce approximately 460,000∼ single cell proteomes of non-myocytes as well as 5,000∼ CD31 negative single cell transcriptomes. Using our data, as well as previously reported datasets, we characterize cardiac non-myocytes with high depth in six mice, characterizing novel surface markers (CD9, CD200, Notch3, and FolR2). Further, we find that extended cell culture promotes the proliferation of CD45+CD11b+FolR2+IAIE- myeloid cells in addition to fibroblasts.

Download Full-text

A Meta-Analytic Single-Cell Atlas of Mouse Bone Marrow Hematopoietic Development

10.1101/2021.08.12.456098 ◽

2021 ◽

Author(s):

Benjamin D Harris ◽

John Lee ◽

Jesse Gillis

Keyword(s):

Bone Marrow ◽

Single Cell ◽

Progenitor Cells ◽

Cell Types ◽

Marker Genes ◽

Mouse Bone Marrow ◽

Clear Understanding ◽

Hematopoietic Stem ◽

Hematopoietic Development ◽

Stem And Progenitor Cells

The clinical importance of the hematopoietic system makes it one of the most heavily studied lineages in all of biology. A clear understanding of the cell types and functional programs during hematopoietic development is central to research in aging, cancer, and infectious diseases. Known cell types are traditionally identified by the expression of proteins on the surface of the cells. Stem and progenitor cells defined based on these markers are assigned functions based on their lineage potential. The rapid growth of single cell RNA sequencing technologies (scRNAseq) provides a new modality for evaluating the cellular and functional landscape of hematopoietic stem and progenitor cells. The popularity of this technology among hematopoiesis researchers enables us to conduct a robust meta-analysis of mouse bone marrow scRNAseq data. Using over 300,000 cells across 12 datasets, we evaluate the classification and function of cell types based on discrete clustering, in silico FACS sorting, and a continuous trajectory. We identify replicable signatures that define cell types based on genes and known cellular functions. Additionally, we evaluate the conservation of signatures associated with erythroid and monocyte lineage development across species using co-expression networks. The co-expression networks predict the effectiveness of the signature at identifying erythroid and monocyte cells in zebrafish and human scRNAseq data. Together, this analysis provides a robust reference, particularly marker genes and functional annotations, for future experiments in hematopoietic development.

Download Full-text

Single-cell analysis of human retina identifies evolutionarily conserved and species-specific mechanisms controlling development

10.1101/779694 ◽

2019 ◽

Cited By ~ 1

Author(s):

Yufeng Lu ◽

Fion Shiau ◽

Wenyang Yi ◽

Suying Lu ◽

Qian Wu ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Cell Fate ◽

Single Cell Analysis ◽

Retinal Development ◽

Cell Types ◽

Retinal Cell ◽

Transcriptional Networks ◽

Species Specific

SummaryThe development of single-cell RNA-Sequencing (scRNA-Seq) has allowed high resolution analysis of cell type diversity and transcriptional networks controlling cell fate specification. To identify the transcriptional networks governing human retinal development, we performed scRNA-Seq over retinal organoid and in vivo retinal development, across 20 timepoints. Using both pseudotemporal and cross-species analyses, we examined the conservation of gene expression across retinal progenitor maturation and specification of all seven major retinal cell types. Furthermore, we examined gene expression differences between developing macula and periphery and between two distinct populations of horizontal cells. We also identify both shared and species-specific patterns of gene expression during human and mouse retinal development. Finally, we identify an unexpected role for ATOH7 expression in regulation of photoreceptor specification during late retinogenesis. These results provide a roadmap to future studies of human retinal development, and may help guide the design of cell-based therapies for treating retinal dystrophies.

Download Full-text

Single cell transcriptomic analysis of murine lung development on hyperoxia-induced damage

Nature Communications ◽

10.1038/s41467-021-21865-2 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Maria Hurskainen ◽

Ivana Mižíková ◽

David P. Cook ◽

Noora Andersson ◽

Chanèle Cyr-Depauw ◽

...

Keyword(s):

Single Cell ◽

Lung Development ◽

Alveolar Epithelium ◽

Cell Types ◽

Capillary Endothelium ◽

Stromal Fibroblasts ◽

Main Driver ◽

Macrophage Populations ◽

Induced Changes ◽

Cellular Compartments

AbstractDuring late lung development, alveolar and microvascular development is finalized to enable sufficient gas exchange. Impaired late lung development manifests as bronchopulmonary dysplasia (BPD) in preterm infants. Single-cell RNA sequencing (scRNA-seq) allows for assessment of complex cellular dynamics during biological processes, such as development. Here, we use MULTI-seq to generate scRNA-seq profiles of over 66,000 cells from 36 mice during normal or impaired lung development secondary to hyperoxia with validation of some of the findings in lungs from BPD patients. We observe dynamic populations of cells, including several rare cell types and putative progenitors. Hyperoxia exposure, which mimics the BPD phenotype, alters the composition of all cellular compartments, particularly alveolar epithelium, stromal fibroblasts, capillary endothelium and macrophage populations. Pathway analysis and predicted dynamic cellular crosstalk suggest inflammatory signaling as the main driver of hyperoxia-induced changes. Our data provides a single-cell view of cellular changes associated with late lung development in health and disease.

Download Full-text

Single-cell mapping of focused ultrasound-transfected brain

Gene Therapy ◽

10.1038/s41434-021-00226-0 ◽

2021 ◽

Author(s):

A. S. Mathew ◽

C. M. Gorick ◽

R. J. Price

Keyword(s):

Single Cell ◽

Focused Ultrasound ◽

Cell Types ◽

Brain Cell ◽

Therapeutic Modality ◽

Full Potential ◽

Stress Genes ◽

Multiple Cell ◽

Differential Gene

AbstractGene delivery via focused ultrasound (FUS) mediated blood-brain barrier (BBB) opening is a disruptive therapeutic modality. Unlocking its full potential will require an understanding of how FUS parameters (e.g., peak-negative pressure (PNP)) affect transfected cell populations. Following plasmid (mRuby) delivery across the BBB with 1 MHz FUS, we used single-cell RNA-sequencing to ascertain that distributions of transfected cell types were highly dependent on PNP. Cells of the BBB (i.e., endothelial cells, pericytes, and astrocytes) were enriched at 0.2 MPa PNP, while transfection of cells distal to the BBB (i.e., neurons, oligodendrocytes, and microglia) was augmented at 0.4 MPa PNP. PNP-dependent differential gene expression was observed for multiple cell types. Cell stress genes were upregulated proportional to PNP, independent of cell type. Our results underscore how FUS may be tuned to bias transfection toward specific brain cell types in vivo and predict how those cells will respond to transfection.

Download Full-text

Single-cell analysis of human adipose tissue identifies depot- and disease-specific cell types

Nature Metabolism ◽

10.1038/s42255-019-0152-6 ◽

2019 ◽

Vol 2 (1) ◽

pp. 97-109 ◽

Cited By ~ 17

Author(s):

Jinchu Vijay ◽

Marie-Frédérique Gauthier ◽

Rebecca L. Biswell ◽

Daniel A. Louiselle ◽

Jeffrey J. Johnston ◽

...

Keyword(s):

Adipose Tissue ◽

Single Cell ◽

Single Cell Analysis ◽

Human Adipose Tissue ◽

Cell Types ◽

Specific Cell ◽

Cell Analysis ◽

Disease Specific

Download Full-text

Single Cell Analysis Reveals That IL-4 Receptor/Stat6 Signaling Is Not Required for the In Vivo or In Vitro Development of CD4+Lymphocytes with a Th2 Cytokine Profile

The Journal of Immunology ◽

10.4049/jimmunol.164.6.3047 ◽

2000 ◽

Vol 164 (6) ◽

pp. 3047-3055 ◽

Cited By ~ 193

Author(s):

Dragana Jankovic ◽

Marika C. Kullberg ◽

Nancy Noben-Trauth ◽

Patricia Caspar ◽

William E. Paul ◽

...

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Cytokine Profile ◽

Cell Analysis ◽

In Vitro Development ◽

Th2 Cytokine ◽

Vitro Development ◽

Cd4 Lymphocytes

Download Full-text

Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BMC Genomics ◽

10.1186/s12864-020-07358-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Tracy M. Yamawaki ◽

Daniel R. Lu ◽

Daniel C. Ellwanger ◽

Dev Bhatt ◽

Paolo Manzanillo ◽

...

Keyword(s):

Single Cell ◽

High Throughput ◽

Immune Cell ◽

Cell Types ◽

Data Interpretation ◽

Detection Sensitivity ◽

Rna Seq ◽

Cell Recovery

Abstract Background Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

Download Full-text