scholarly journals Single-Cell Transcriptomics of a Human Kidney Allograft Biopsy Specimen Defines a Diverse Inflammatory Response

2018 ◽  
Vol 29 (8) ◽  
pp. 2069-2080 ◽  
Author(s):  
Haojia Wu ◽  
Andrew F. Malone ◽  
Erinn L. Donnelly ◽  
Yuhei Kirita ◽  
Kohei Uchimura ◽  
...  
Keyword(s):  
Endothelial Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Biopsy Specimen ◽  
Kidney Biopsy ◽  
Human Kidney ◽  
Cell Types ◽  
Biopsy Specimens ◽  
Single Cell Rna Sequencing ◽  
Transplant Biopsy

Background Single-cell genomics techniques are revolutionizing our ability to characterize complex tissues. By contrast, the techniques used to analyze renal biopsy specimens have changed little over several decades. We tested the hypothesis that single-cell RNA-sequencing can comprehensively describe cell types and states in a human kidney biopsy specimen.Methods We generated 8746 single-cell transcriptomes from a healthy adult kidney and a single kidney transplant biopsy core by single-cell RNA-sequencing. Unsupervised clustering analysis of the biopsy specimen was performed to identify 16 distinct cell types, including all of the major immune cell types and most native kidney cell types, in this biopsy specimen, for which the histologic read was mixed rejection.Results Monocytes formed two subclusters representing a nonclassical CD16+ group and a classic CD16− group expressing dendritic cell maturation markers. The presence of both monocyte cell subtypes was validated by staining of independent transplant biopsy specimens. Comparison of healthy kidney epithelial transcriptomes with biopsy specimen counterparts identified novel segment-specific proinflammatory responses in rejection. Endothelial cells formed three distinct subclusters: resting cells and two activated endothelial cell groups. One activated endothelial cell group expressed Fc receptor pathway activation and Ig internalization genes, consistent with the pathologic diagnosis of antibody-mediated rejection. We mapped previously defined genes that associate with rejection outcomes to single cell types and generated a searchable online gene expression database.Conclusions We present the first step toward incorporation of single-cell transcriptomics into kidney biopsy specimen interpretation, describe a heterogeneous immune response in mixed rejection, and provide a searchable resource for the scientific community.

scholarly journals Kidney pathological changes alter cell clustering features in single-cell RNA sequencing

2021 ◽  
Author(s):  
Lijun Ma ◽  
Mariana Murea ◽  
Young A Choi ◽  
Ashok K. Hemal ◽  
Alexei V. Mikhailov ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Expression Profiles ◽  
Kidney Tissue ◽  
Human Kidney ◽  
Cell Types ◽  
Specific Gene ◽  
Glomerular Injury ◽  
Cell Clustering ◽  
Single Cell Rna Sequencing

The kidney is composed of multiple cell types, each with specific physiological functions. Single-cell RNA sequencing (scRNA-Seq) is useful for classifying cell-specific gene expression profiles in kidney tissue. Because viable cells are critical in scRNA-Seq analyses, we report an optimized cell dissociation process and the necessity for histological screening of human kidney sections prior to performing scRNA-Seq. We show that glomerular injury can result in loss of select cell types during the cell clustering process. Subsequent fluorescence microscopy confirmed reductions in cell-specific markers among the injured cells seen on kidney sections and these changes need to be considered when interpreting results of scRNA-Seq.

scholarly journals Monocytes and Macrophages in Kidney Transplantation and Insights from Single Cell RNA-Seq Studies

Kidney360 ◽  
2021 ◽  
pp. 10.34067/KID.0003842021
Author(s):  
Andrew F Malone
Keyword(s):  
Kidney Transplantation ◽  
Single Cell ◽  
Rna Sequencing ◽  
Kidney Transplant ◽  
New Technologies ◽  
Immune Cell ◽  
Human Kidney ◽  
Cell Types ◽  
Single Cell Rna Sequencing ◽  
And Function

Single-cell RNA sequencing (scRNA-seq) is a powerful technology that allows for the identification of minority cell types in complex tissues, such as immune cells in the kidney. Previously, gene expression from infrequent cell types was missed using bulk RNA-sequencing methods due to an averaging effect. Additionally, single-cell RNA sequencing facilitates assignment of cell origin in a sample, a shortcoming of previous bulk sequencing technologies. Thus, scRNA-seq is ideal to study the immune cell landscape and the alloimmune response in the human kidney transplant. However, there are few studies published to date. Macrophages are known to play an important role in health and disease in the kidney. Furthermore, it is known that macrophages play key roles in rejection of the kidney transplant. The definition, ontogeny, and function of these cells is complex and nomenclature has evolved as new technologies have become available. In this review, an overview of monocyte and macrophage nomenclature, ontogeny, and function with a specific focus on kidney transplantation is provided with novel scRNA-seq findings included. Single-cell RNA sequencing offers an unbiased transcriptional approach to defining macrophages and provides insights into macrophage ontogeny and function not possible with contemporary methods.

scholarly journals Single-cell data clustering based on sparse optimization and low-rank matrix factorization

2021 ◽  
Author(s):  
Yinlei Hu ◽  
Bin Li ◽  
Falai Chen ◽  
Kun Qu
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Matrix Factorization ◽  
Data Clustering ◽  
Cell Types ◽  
Low Rank ◽  
Sequencing Data ◽  
Rank Matrix ◽  
Single Cell Rna Sequencing ◽  
Low Rank Matrix

Abstract Unsupervised clustering is a fundamental step of single-cell RNA sequencing data analysis. This issue has inspired several clustering methods to classify cells in single-cell RNA sequencing data. However, accurate prediction of the cell clusters remains a substantial challenge. In this study, we propose a new algorithm for single-cell RNA sequencing data clustering based on Sparse Optimization and low-rank matrix factorization (scSO). We applied our scSO algorithm to analyze multiple benchmark datasets and showed that the cluster number predicted by scSO was close to the number of reference cell types and that most cells were correctly classified. Our scSO algorithm is available at https://github.com/QuKunLab/scSO. Overall, this study demonstrates a potent cell clustering approach that can help researchers distinguish cell types in single-cell RNA sequencing data.

scholarly journals Single cell sequencing reveals endothelial plasticity with transient mesenchymal activation after myocardial infarction

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lukas S. Tombor ◽  
David John ◽  
Simone F. Glaser ◽  
Guillermo Luxán ◽  
Elvira Forte ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Endothelial Cells ◽  
Endothelial Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Endothelial Cell Migration ◽  
Metabolic Adaptation ◽  
Endothelial Cell Proliferation ◽  
Mesenchymal Transition ◽  
Single Cell Rna Sequencing

AbstractEndothelial cells play a critical role in the adaptation of tissues to injury. Tissue ischemia induced by infarction leads to profound changes in endothelial cell functions and can induce transition to a mesenchymal state. Here we explore the kinetics and individual cellular responses of endothelial cells after myocardial infarction by using single cell RNA sequencing. This study demonstrates a time dependent switch in endothelial cell proliferation and inflammation associated with transient changes in metabolic gene signatures. Trajectory analysis reveals that the majority of endothelial cells 3 to 7 days after myocardial infarction acquire a transient state, characterized by mesenchymal gene expression, which returns to baseline 14 days after injury. Lineage tracing, using the Cdh5-CreERT2;mT/mG mice followed by single cell RNA sequencing, confirms the transient mesenchymal transition and reveals additional hypoxic and inflammatory signatures of endothelial cells during early and late states after injury. These data suggest that endothelial cells undergo a transient mes-enchymal activation concomitant with a metabolic adaptation within the first days after myocardial infarction but do not acquire a long-term mesenchymal fate. This mesenchymal activation may facilitate endothelial cell migration and clonal expansion to regenerate the vascular network.

scholarly journals Modeling cellular crosstalk and organotypic vasculature development with human iPSC-derived endothelial cells and cardiomyocytes

2020 ◽  
Author(s):  
Emmi Helle ◽  
Minna Ampuja ◽  
Alexandra Dainis ◽  
Laura Antola ◽  
Elina Temmes ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Shear Stress ◽  
Endothelial Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Tissue Growth ◽  
Cell Phenotype ◽  
Cell Populations ◽  
Pump System ◽  
Single Cell Rna Sequencing

AbstractRationaleCell-cell interactions are crucial for the development and function of the organs. Endothelial cells act as essential regulators of tissue growth and regeneration. In the heart, endothelial cells engage in delicate bidirectional communication with cardiomyocytes. The mechanisms and mediators of this crosstalk are still poorly known. Furthermore, endothelial cells in vivo are exposed to blood flow and their phenotype is greatly affected by shear stress.ObjectiveWe aimed to elucidate how cardiomyocytes regulate the development of organotypic phenotype in endothelial cells. In addition, the effects of flow-induced shear stress on endothelial cell phenotype were studied.Methods and resultsHuman induced pluripotent stem cell (hiPSC) -derived cardiomyocytes and endothelial cells were grown either as a monoculture or as a coculture. hiPS-endothelial cells were exposed to flow using the Ibidi-pump system. Single-cell RNA sequencing was performed to define cell populations and to uncover the effects on their transcriptomic phenotypes. The hiPS-cardiomyocyte differentiation resulted in two distinct populations; atrial and ventricular. Coculture had a more pronounced effect on hiPS-endothelial cells compared to hiPS-cardiomyocytes. Coculture increased hiPS-endothelial cell expression of transcripts related to vascular development and maturation, cardiac development, and the expression of cardiac endothelial cell -specific genes. Exposure to flow significantly reprogrammed the hiPS-endothelial cell transcriptome, and surprisingly, promoted the appearance of both venous and arterial clusters.ConclusionsSingle-cell RNA sequencing revealed distinct atrial and ventricular cell populations in hiPS-cardiomyocytes, and arterial and venous-like cell populations in flow exposed hiPS-endothelial cells. hiPS-endothelial cells acquired cardiac endothelial cell identity in coculture. Our study demonstrated that hiPS-cardiomoycytes and hiPS-endothelial cells readily adapt to coculture and flow in a consistent and relevant manner, indicating that the methods used represent improved physiological cell culturing conditions that potentially are more relevant in disease modelling. In addition, novel cardiomyocyte-endothelial cell crosstalk mediators were revealed.

scholarly journals Single cell RNA sequencing of the Strongylocentrotus purpuratus larva reveals the blueprint of major cell types and nervous system of a non-chordate deuterostome

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Periklis Paganos ◽  
Danila Voronov ◽  
Jacob M Musser ◽  
Detlev Arendt ◽  
Maria Ina Arnone
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Sea Urchin ◽  
Regulatory Networks ◽  
Sea Urchins ◽  
Neuronal Cell ◽  
Cell Types ◽  
Molecular Fingerprint ◽  
Larval Body ◽  
Single Cell Rna Sequencing

Identifying the molecular fingerprint of organismal cell types is key for understanding their function and evolution. Here, we use single cell RNA sequencing (scRNA-seq) to survey the cell types of the sea urchin early pluteus larva, representing an important developmental transition from non-feeding to feeding larva. We identify 21 distinct cell clusters, representing cells of the digestive, skeletal, immune, and nervous systems. Further subclustering of these reveal a highly detailed portrait of cell diversity across the larva, including the identification of neuronal cell types. We then validate important gene regulatory networks driving sea urchin development and reveal new domains of activity within the larval body. Focusing on neurons that co-express Pdx-1 and Brn1/2/4, we identify an unprecedented number of genes shared by this population of neurons in sea urchin and vertebrate endocrine pancreatic cells. Using differential expression results from Pdx-1 knockdown experiments, we show that Pdx1 is necessary for the acquisition of the neuronal identity of these cells. We hypothesize that a network similar to the one orchestrated by Pdx1 in the sea urchin neurons was active in an ancestral cell type and then inherited by neuronal and pancreatic developmental lineages in sea urchins and vertebrates.

Localization of migraine susceptibility genes in human brain by single-cell RNA sequencing

Cephalalgia ◽  
2018 ◽  
Vol 38 (13) ◽  
pp. 1976-1983 ◽  
Author(s):  
William Renthal
Keyword(s):  
Human Brain ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Profiles ◽  
Cell Types ◽  
Susceptibility Genes ◽  
Brain Cell ◽  
Cell Type ◽  
Single Cell Rna Sequencing ◽  
Brain Cell Types

Background Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. Methods The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Results Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. Conclusions This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.

Sign in / Sign up

Export Citation Format

Share Document