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Multimodal single cell sequencing of human diabetic kidney disease implicates chromatin accessibility and genetic background in disease progression [cut-and-run and bulk ATAC-seq to support single cell data]

ABSTRACT: Multimodal single cell sequencing of human diabetic kidney disease implicates chromatin accessibility and genetic background in disease progression [cut-and-run and bulk ATAC-seq to support single cell data]

PROVIDER: PRJNA800684 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR17761973_1.fastq.gz	Fastqsanger.gz
	SRR17761973_2.fastq.gz	Fastqsanger.gz
	SRR17761974_1.fastq.gz	Fastqsanger.gz
	SRR17761974_2.fastq.gz	Fastqsanger.gz
	SRR17761975_1.fastq.gz	Fastqsanger.gz

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Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression

Project description:Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression

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Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression

Project description:Purpose: Single cell sequencing has advanced our understanding of kidney biology. The goals of this study are to compare single nucleus RNA (snRNA-seq) and single nucleus assay for transposase accessible chromatin sequencing (snATAC-seq) from healthy control donors and donors with type 2 diabetic kidney disease to identify altered signaling pathways and chromatin accessibility patterns observed in diabetic kidney disease. Methods: Nuclear dissociation of human kidney cortex samples was performed on samples obtained from patients undergoing tumor nephrectromy or deceased organ donors. snRNA-seq and snATAC-seq libraries were prepared using 10X Genomics kits according to manufacturers instructions. For this study, two healthy control libraries from one donor were prepared with the following chemistries (1 - single cell 3-prime v3, 1 - single cell ATAC v1) and nine DKD libraries from seven donors were prepared with the following chemistries (2 - single cell 5-prime v2 paired-end, 7 - single cell ATAC v1). Raw data for three healthy control and three DKD snRNA-seq libraries sequenced with single nucleus 5-prime R2 only can be found in GSE13188213. Raw data for two healthy control snRNA-seq sequenced with single nucleus 5-prime paired-end and five snATAC-seq single nucleus ATAC v1 libraries can be found in GSE151302. snRNA-seq and snATAC-seq libraries from these earlier studies were recounted with cellranger (v4.0) or cellranger-atac (v2.0) to provide consistency across processed data files.

2022-07-28 | GSE195460 | GEO

Monocyte Single-Cell Multimodal Profiling in Cardiovascular Disease Risk States

Project description:Monocyte Single-Cell Multimodal Profiling in Cardiovascular Disease Risk States

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Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression.

Project description:The proximal tubule is a key regulator of kidney function and glucose metabolism. Diabetic kidney disease leads to proximal tubule injury and changes in chromatin accessibility that modify the activity of transcription factors involved in glucose metabolism and inflammation. Here we use single nucleus RNA and ATAC sequencing to show that diabetic kidney disease leads to reduced accessibility of glucocorticoid receptor binding sites and an injury-associated expression signature in the proximal tubule. We hypothesize that chromatin accessibility is regulated by genetic background and closely-intertwined with metabolic memory, which pre-programs the proximal tubule to respond differently to external stimuli. Glucocorticoid excess has long been known to increase risk for type 2 diabetes, which raises the possibility that glucocorticoid receptor inhibition may mitigate the adverse metabolic effects of diabetic kidney disease.

| S-EPMC9448792 | biostudies-literature

Integrated analysis of multimodal single-cell data

Project description:The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce ‘weighted-nearest neighbor’ analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity.

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Multimodal single cell sequencing of human diabetic kidney disease implicates chromatin accessibility and genetic background in disease progression [cut-and-run and bulk ATAC-seq to support single cell data]

Project description:Purpose: Identification of glucocorticoid recepor binding sites on human kidney proximal tubular cells to better understand epigenetic alterations in diabetic kidney diseases Methods: CUT&RUN assay libraries for cultured cells or human kidneys were generated with the CUTANA kit (EpiCypher, 14-1048). 500,000 cells were mixed and incubated with Concanavalin A (ConA) conjugated paramagnetic beads. Antibodies to the glucocorticoid receptor were added to target samples and IgG was added to negative controls. The remaining steps were performed according to manufacturer’s instructions. Library preparation was performed using the NEBNext Ultra II DNA Library Prep Kit for Illumina (New England BioLabs, E7645S) with manufacturer’s instructions, including minor modifications indicated by CUTANA described above. CUT&RUN libraries were sequenced on a NovaSeq instrument (Illumina, 150 bp paired-end reads). For bulk ATAC-seq, 50,000 nuclei were transposed in 25 μL of ATAC-seq transposition mix [12.5 μL 2× Illumina Tagment DNA (TD) buffer; 10.5 μL nuclease-free water; 2.0 μL Tn5 transposase (Illumina/Nextera, FC-121-1030)] and incubated at 37°C for 1 h on a thermomixer. The transposed DNA was purified with QIAGEN MinElute kit (28004) and amplified with dual indexes.

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Integrated analysis of multimodal single-cell data

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Multimodal single cell analyses reveal mechanisms of perianal fistula in diverse Crohn’s disease [Multiome]

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Monocyte Single-Cell Multimodal Profiling in Cardiovascular Disease Risk States

Project description:Monocytes are a critical innate immune system cell type that serves homeostatic and immunoregulatory functions. They have been identified historically by the cell surface expression of CD14 and CD16. However, recent single-cell studies have revealed that they are much more heterogeneous than previously realized. We utilized cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-cell RNA sequencing (scRNA-seq) to describe the comprehensive transcriptional and phenotypic landscape of 437,126 monocytes. This high-dimensional multimodal approach identified vast phenotypic diversity and functionally distinct subsets, including IFN-responsive, MHCIIhi, monocyte-platelet aggregates, as well as non-classical, sand several subpopulations of classical monocytes. Using flow cytometry, we validated the existence of MHCII+CD275+ MHCIIhi, CD42b+ monocyte-platelet aggregates, CD16+CD99- non-classical monocytes, and CD99+ classical monocytes. Each subpopulation exhibited unique characteristics, developmental trajectories, transcriptional regulation, and tissue distribution. In addition, alterations associated with cardiovascular disease (CVD) risk factors, including race, smoking, and hyperlipidemia were identified. Moreover, the effect of hyperlipidemia was recapitulated in mouse models of elevated cholesterol. This integrative and cross-species comparative analysis provides a new perspective on comparison of alterations in monocytes in pathological conditions and offers insights into monocyte-driven mechanisms in CVD and the potential for monocyte subpopulation targeted therapies.

2025-05-08 | GSE296624 | GEO

Multimodal single cell analyses reveal mechanisms of perianal fistula in diverse Crohn’s disease [scRNA-seq]

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