Detection of Infiltrating Fibroblasts by Single-Cell Transcriptomics in Human Kidney Allografts

Abstract We tested the hypothesis that single-cell RNA-sequencing (scRNA-seq) analysis of human kidney allograft biopsies will reveal distinct cell types and states and yield insights to decipher the complex heterogeneity of alloimmune rejection. We selected 3 kidney biopsies from 3 individuals for scRNA-seq and processed them fresh using an identical protocol on the 10x Chromium platform; (i) HK: native kidney biopsy from a living donor, (ii) AK1: allograft kidney with transplant glomerulopathy and tubulointerstitial fibrosis, and worsening graft function, and (iii) AK2: allograft kidney after successful treatment of active antibody-mediated rejection. We generated 7217 high-quality single cell transcriptomes. Taking advantage of the recipient-donor sex mismatches, we determined that in AK1 with fibrosis, more than half of the kidney allograft fibroblasts were—unexpectedly—recipient-derived and therefore likely migratory and graft infiltrative, whereas in the AK2 without fibrosis, all the fibroblasts were donor-derived. Furthermore, AK1 was enriched by tubular cells that overexpressed profibrotic extracellular matrix genes. AK2, eight months after successful treatment of rejection, contained endothelial cells that expressed T-cell chemoattractant cytokines. In addition to these key findings, our analysis revealed unique cell types and cell states. Altogether, single cell transcriptomics yielded novel mechanistic insights for individualizing the care of transplant recipients.

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Single Cell Transcriptomics of Human Native Kidney and Kidney Allografts and New Insights into the Mechanism of Fibrosis

10.1101/2020.09.03.281733 ◽

2020 ◽

Author(s):

Hemant Suryawanshi ◽

Hua Yang ◽

Michelle Lubetzky ◽

Pavel Morozov ◽

Mila Lagman ◽

...

Keyword(s):

Single Cell ◽

Successful Treatment ◽

Kidney Biopsy ◽

Cell Types ◽

Transplant Recipients ◽

Hla Antibodies ◽

Kidney Allograft ◽

Antibody Mediated Rejection ◽

Native Kidney ◽

Allograft Kidney

AbstractBackgroundSingle-cell RNA-sequencing (scRNA-seq) provides unique opportunity to study cell types and cell states at a hitherto unavailable level of precision. We tested the hypothesis that scRNA-seq and computational analysis of human kidney allograft biopsies will reveal new cell types and cell states and yield insights to personalize the care of transplant recipients.MethodsWe selected 3 kidney biopsies from 3 individuals for scRNA-seq using the 10x Chromium Single Cell platform; (i) HK: native kidney biopsy from a living kidney, (ii) AK1: allograft kidney biopsy with transplant glomerulopathy, fibrosis, and worsening kidney function but with undetectable circulating anti-HLA antibodies, and (iii) AK2: allograft kidney biopsy after successful treatment of active antibody-mediated rejection but with persistent circulating donor-specific anti-HLA antibodies.ResultsWe generated 7,217 high-quality single cell transcriptomes. Taking advantage of the recipient-donor sex mismatches, we determined that in the AK1 biopsy with fibrosis, more than half of the kidney allograft fibroblasts were—unexpectedly—recipient-derived and therefore likely migratory and graft infiltrative, whereas in the AK2 biopsy without fibrosis, all the fibroblasts were donor-derived. Furthermore, tubular progenitor cells that overexpress profibrotic extracellular matrix genes potentially contributing to fibrosis, were enriched in AK1 biopsy. Eight months after successful treatment of antibody-mediated rejection, AK2 biopsy contained endothelial cells that expressed mRNA for T-cell chemoattractant cytokines. In addition to these key findings, our analysis revealed unique cell types and cell states in the kidney.ConclusionsAltogether, single cell transcriptomics complemented histopathology and yielded novel mechanistic insights for individualizing the care of transplant recipients.

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DoubletDecon: Cell-State Aware Removal of Single-Cell RNA-Seq Doublets

10.1101/364810 ◽

2018 ◽

Cited By ~ 15

Author(s):

Erica A.K. DePasquale ◽

Daniel J. Schnell ◽

Íñigo Valiente-Alandí ◽

Burns C. Blaxall ◽

H. Leighton Grimes ◽

...

Keyword(s):

Single Cell ◽

Individual Cell ◽

Cell Types ◽

Rna Seq ◽

Cell State ◽

Detection Algorithms ◽

Distinct Cell ◽

Standard Quality ◽

Control Step ◽

Unique Cell

SUMMARYMethods for single-cell RNA sequencing (scRNA-Seq) have greatly advanced in recent years. While droplet- and well-based methods have increased the capture frequency of cells for scRNA-Seq, these technologies readily produce technical artifacts, such as doublet-cell and multiplet-cell captures. Doublets occurring between distinct cell-types can appear as hybrid scRNA-Seq profiles, but do not have distinct transcriptomes from individual cell states. We introduce DoubletDecon, an approach that detects doublets with a combination of deconvolution analyses and the identification of unique cell-state gene expression. We demonstrate the ability of DoubletDecon to identify synthetic and cell-hashing cell singlets and doublets from scRNA-Seq datasets of varying cellular complexity. DoubletDecon is able to account for cell-cycle effects and is compatible with diverse species and unsupervised population detection algorithms (e.g., ICGS, Seurat). We believe this approach has the potential to become a standard quality control step for the accurate delineation of cell states.

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Single-cell profiling of healthy human kidney reveals features of sex-based transcriptional programs and tissue-specific immunity

10.1101/2021.12.09.471943 ◽

2021 ◽

Author(s):

Caitriona M McEvoy ◽

Julia M Murphy ◽

Lin Zhang ◽

Sergi Clotet-Freixas ◽

Jessica A Mathews ◽

...

Keyword(s):

Single Cell ◽

Human Kidney ◽

Cell Types ◽

Significant Heterogeneity ◽

Proximal Tubular Cells ◽

Healthy Human ◽

Fresh Tissue ◽

Tubular Cells ◽

Distinct Cell ◽

Proximal Tubular

Maintaining organ homeostasis requires complex functional synergy between distinct cell types, a snapshot of which is glimpsed through the simultaneously broad and granular analysis provided by single-cell atlases. Knowledge of the transcriptional programs underpinning the complex and specialized functions of human kidney cell populations at homeostasis is limited by difficulty accessing healthy, fresh tissue. Here, we present a single-cell perspective of healthy human kidney from 19 living donors, with equal contribution from males and females, profiling the transcriptome of 27677 high-quality cells to map healthy kidney at high resolution. Our sex-balanced dataset revealed sex-based differences in gene expression within proximal tubular cells, specifically, increased anti-oxidant metallothionein genes in females and the predominance of aerobic metabolism-related genes in males. Functional differences in metabolism were confirmed between male and female proximal tubular cells, with male cells exhibiting higher oxidative phosphorylation and higher levels of energy precursor metabolites. Within the immune niche, we identified kidney-specific lymphocyte populations with unique transcriptional profiles indicative of kidney-adapted functions and validated findings by flow cytometry. We observed significant heterogeneity in resident myeloid populations and identified an MRC1+ LYVE1+ FOLR2+ C1QC+ population as the predominant myeloid population in healthy kidney. This study provides a detailed cellular map of healthy human kidney, revealing novel insights into the complexity of renal parenchymal cells and kidney-resident immune populations.

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Resolving Transcriptional States and Predicting Lineages in the Annelid Capitella teleta Using Single-Cell RNAseq

Frontiers in Ecology and Evolution ◽

10.3389/fevo.2020.618007 ◽

2021 ◽

Vol 8 ◽

Author(s):

Abhinav Sur ◽

Néva P. Meyer

Keyword(s):

Single Cell ◽

Cell Fate ◽

Cell Types ◽

Neurosecretory Cells ◽

Animal Evolution ◽

Distinct Cell ◽

Capitella Teleta ◽

Unique Cell ◽

Changes Over Time ◽

Larval Cell

Evolution and diversification of cell types has contributed to animal evolution. However, gene regulatory mechanisms underlying cell fate acquisition during development remains largely uncharacterized in spiralians. Here we use a whole-organism, single-cell transcriptomic approach to map larval cell types in the annelid Capitella teleta at 24- and 48-h post gastrulation (stages 4 and 5). We identified eight unique cell clusters (undifferentiated precursors, ectoderm, muscle, ciliary-band, gut, neurons, neurosecretory cells, and protonephridia), thus helping to identify uncharacterized molecular signatures such as previously unknown neurosecretory cell markers in C. teleta. Analysis of coregulatory programs in individual clusters revealed gene interactions that can be used for comparisons of cell types across taxa. We examined the neural and neurosecretory clusters more deeply and characterized a differentiation trajectory starting from dividing precursors to neurons using Monocle3 and velocyto. Pseudotime analysis along this trajectory identified temporally-distinct cell states undergoing progressive gene expression changes over time. Our data revealed two potentially distinct neural differentiation trajectories including an early trajectory for brain neurosecretory cells. This work provides a valuable resource for future functional investigations to better understanding neurogenesis and the transitions from neural precursors to neurons in an annelid.

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Resolving transcriptional states and predicting lineages in the annelid Capitella teleta using single-cell RNAseq

10.1101/2020.10.16.342709 ◽

2020 ◽

Author(s):

Abhinav Sur ◽

Néva P. Meyer

Keyword(s):

Single Cell ◽

Cell Fate ◽

Cell Types ◽

Neurosecretory Cells ◽

Animal Evolution ◽

Distinct Cell ◽

Capitella Teleta ◽

Unique Cell ◽

Changes Over Time ◽

Larval Cell

AbstractEvolution and diversification of cell types has contributed to animal evolution. However, gene regulatory mechanisms underlying cell fate acquisition during development remains largely uncharacterized in spiralians. Here we use a whole-organism, single-cell transcriptomic approach to map larval cell types in the annelid Capitella teleta at 24- and 48-hours post gastrulation (stages 4 and 5). We identified eight unique cell clusters (undifferentiated precursors, ectoderm, muscle, ciliary-band, gut, neurons, neurosecretory cells and protonephridia), thus helping to identify previously uncharacterized molecular signatures such as novel neurosecretory cell markers. Analysis of coregulatory programs in individual clusters revealed gene interactions that can be used for comparisons of cell types across taxa. We examined the neural and neurosecretory clusters more deeply and characterized a differentiation trajectory starting from dividing precursors to neurons using Monocle3 and velocyto. Pseudotime analysis along this trajectory identified temporally-distinct cell states undergoing progressive gene expression changes over time. Our data revealed two potentially distinct neural differentiation trajectories including an early trajectory for brain neurosecretory cells. This work provides a valuable resource for future functional investigations to better understanding neurogenesis and the transitions from neural precursors to neurons in an annelid.

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Integrated profiling of single cell epigenomic and transcriptomic landscape of Parkinson’s disease mouse brain

10.1101/2020.02.04.933259 ◽

2020 ◽

Author(s):

Jixing Zhong ◽

Gen Tang ◽

Jiacheng Zhu ◽

Xin Qiu ◽

Weiying Wu ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Single Cell ◽

Early Stage ◽

Cell Types ◽

Cellular Heterogeneity ◽

Rna Seq ◽

Cell Level ◽

Distinct Cell ◽

Single Nucleus

AbstractParkinson’s disease (PD) is a neurodegenerative disease leading to the impairment of execution of movement. PD pathogenesis has been largely investigated, but either restricted in bulk level or at certain cell types, which failed to capture cellular heterogeneity and intrinsic interplays among distinct cell types. To overcome this, we applied single-nucleus RNA-seq and single cell ATAC-seq on cerebellum, midbrain and striatum of PD mouse and matched control. With 74,493 cells in total, we comprehensively depicted the dysfunctions under PD pathology covering proteostasis, neuroinflammation, calcium homeostasis and extracellular neurotransmitter homeostasis. Besides, by multi-omics approach, we identified putative biomarkers for early stage of PD, based on the relationships between transcriptomic and epigenetic profiles. We located certain cell types that primarily contribute to PD early pathology, narrowing the gap between genotypes and phenotypes. Taken together, our study provides a valuable resource to dissect the molecular mechanism of PD pathogenesis at single cell level, which could facilitate the development of novel methods regarding diagnosis, monitoring and practical therapies against PD at early stage.

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Kidney organoid reproducibility across multiple human iPSC lines and diminished off target cells after transplantation revealed by single cell transcriptomics

10.1101/516807 ◽

2019 ◽

Cited By ~ 4

Author(s):

Ayshwarya Subramanian ◽

Eriene-Heidi Sidhom ◽

Maheswarareddy Emani ◽

Nareh Sahakian ◽

Katherine Vernon ◽

...

Keyword(s):

Single Cell ◽

Human Kidney ◽

Cell Types ◽

Mouse Kidney ◽

Target Cells ◽

Rna Seq ◽

Kidney Capsule ◽

Human Ipsc ◽

Kidney Organoids

AbstractHuman iPSC-derived kidney organoids have the potential to revolutionize discovery, but assessing their consistency and reproducibility across iPSC lines, and reducing the generation of off-target cells remain an open challenge. Here, we used single cell RNA-Seq (scRNA-Seq) to profile 415,775 cells to show that organoid composition and development are comparable to human fetal and adult kidneys. Although cell classes were largely reproducible across iPSC lines, time points, protocols, and replicates, cell proportions were variable between different iPSC lines. Off-target cell proportions were the most variable. Prolonged in vitro culture did not alter cell types, but organoid transplantation under the mouse kidney capsule diminished off-target cells. Our work shows how scRNA-seq can help score organoids for reproducibility, faithfulness and quality, that kidney organoids derived from different iPSC lines are comparable surrogates for human kidney, and that transplantation enhances their formation by diminishing off-target cells.

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Single cell derived mRNA signals across human kidney tumors

10.1101/2020.03.19.998815 ◽

2020 ◽

Cited By ~ 1

Author(s):

Matthew D Young ◽

Thomas J Mitchell ◽

Lars Custers ◽

Thanasis Margaritis ◽

Francisco Morales ◽

...

Keyword(s):

Single Cell ◽

Human Cancer ◽

Human Kidney ◽

Cell Types ◽

Renal Tumors ◽

Tumor Type ◽

Kidney Tumors ◽

Cell Renal Cell Carcinoma ◽

Cellular Origin ◽

Normal Tissues

AbstractThe cellular transcriptome may provide clues into the differentiation state and origin of human cancer, as tumor cells may retain patterns of gene expression similar to the cell they derive from. Here, we studied the differentiation state and cellular origin of human kidney tumors, by assessing mRNA signals in 1,300 childhood and adult renal tumors, spanning seven different tumor types. Using single cell mRNA reference maps of normal tissues generated by the Human Cell Atlas project, we measured the abundance of reference “cellular signals” in each tumor. Quantifying global differentiation states, we found that, irrespective of tumor type, childhood tumors exhibited fetal cellular signals, thus replacing the long-held presumption of “fetalness” with a precise, quantitative readout of immaturity. By contrast, in adult cancers our assessment refuted the suggestion of dedifferentiation towards a fetal state in the overwhelming majority of cases, with the exception of lethal variants of clear cell renal cell carcinoma. Examining the specific cellular phenotype of each tumor type revealed an intimate connection between the different mesenchymal populations of the developing kidney and childhood renal tumors, whereas adult tumors mostly represented specific mature tubular cell types. RNA signals of each tumor type were remarkably uniform and specific, indicating a possible therapeutic and diagnostic utility. We demonstrated this utility with a case study of a cryptic renal tumor. Whilst not classifiable by clinical pathological work-up, mRNA signals revealed the diagnosis. Our findings provide a cellular definition of human renal tumors through an approach that is broadly applicable to human cancer.

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Resolving single-cell heterogeneity from hundreds of thousands of cells through sequential hybrid clustering and NMF

10.1101/608869 ◽

2019 ◽

Cited By ~ 5

Author(s):

Meenakshi Venkatasubramanian ◽

Kashish Chetal ◽

Gowtham Atluri ◽

Nathan Salomonis

Keyword(s):

Single Cell ◽

Gene Selection ◽

Cell Types ◽

Large Datasets ◽

Detection Methods ◽

Cell Populations ◽

List Type ◽

Hybrid Clustering ◽

Benchmark Datasets ◽

Unique Cell

ABSTRACTThe rapid proliferation of single-cell RNA-Sequencing (scRNA-Seq) technologies has spurred the development of diverse computational approaches to detect transcriptionally coherent populations. While the complexity of the algorithms for detecting heterogeneity have increased, most existing algorithms require significant user-tuning, are heavily reliant on dimensionality reduction techniques and are not scalable to ultra-large datasets. We previously described a multi-step algorithm, Iterative Clustering and Guide-gene selection (ICGS), which applies intra-gene correlation and hybrid clustering to uniquely resolve novel transcriptionally coherent cell populations from an intuitive graphical user interface. Here, we describe a new iteration of ICGS that outperforms state-of-the-art scRNA-Seq detection workflows when applied to well-established benchmarks. This approach combines multiple complementary subtype detection methods (HOPACH, sparse-NMF, cluster “fitness”, SVM) to resolve rare and common cell-states, while minimizing differences due to donor or batch effects. Using data from the Human Cell Atlas, we show that the PageRank algorithm effectively down samples ultra-large scRNA-Seq datasets, without losing extremely rare or transcriptionally similar distinct cell-types and while recovering novel transcriptionally unique cell populations. We believe this new approach holds tremendous promise in reproducibly resolving hidden cell populations in complex datasets.HighlightsICGS2 outperforms alternative approaches in small and ultra-large benchmark datasetsIntegrates multiple solutions for cell-type detection with supervised refinementScales effectively to resolve rare cell-states from ultra-large datasets using PageRank sampling with a low memory footprintIntegrated into AltAnalyze to enable sophisticated and automated downstream analysis

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High Resolution Single Cell Maps Reveals Distinct Cell Organization and Function Across Different Regions of the Human Intestine

10.1101/2021.11.25.469203 ◽

2021 ◽

Author(s):

John W Hickey ◽

Winston R Becker ◽

Stephanie A Nevins ◽

Aaron M Horning ◽

Almudena Espin Perez ◽

...

Keyword(s):

Single Cell ◽

Immune Surveillance ◽

Cell Types ◽

Open Chromatin ◽

Specific Cell ◽

Symbiotic Relationships ◽

Distinct Cell ◽

Cell Organization ◽

Reference Map ◽

And Function

The colon is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota, and affects overall health. To better understand its organization, functions, and its regulation at a single cell level, we performed CODEX multiplexed imaging, as well as single nuclear RNA and open chromatin assays across eight different intestinal sites of four donors. Through systematic analyses we find cell compositions differ dramatically across regions of the intestine, demonstrate the complexity of epithelial subtypes, and find that the same cell types are organized into distinct neighborhoods and communities highlighting distinct immunological niches present in the intestine. We also map gene regulatory differences in these cells suggestive of a regulatory differentiation cascade, and associate intestinal disease heritability with specific cell types. These results describe the complexity of the cell composition, regulation, and organization for this organ, and serve as an important reference map for understanding human biology and disease.

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