Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Multi-modal single cell analysis reveals gut microbiota reshapes brain immune landscape in aged mouse model.

ABSTRACT: Multi-modal single cell analysis reveals gut microbiota reshapes brain immune landscape in aged mouse model.

PROVIDER: PRJNA673815 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR12964586_1.fastq.gz	Fastqsanger.gz
	SRR12964586_2.fastq.gz	Fastqsanger.gz
	SRR12964587_1.fastq.gz	Fastqsanger.gz
	SRR12964587_2.fastq.gz	Fastqsanger.gz
	SRR12964588_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 26

Similar Datasets

Multi-modal single cell analysis reveals gut microbiota reshapes brain immune landscape in aged mouse model

Project description:Multi-modal single cell analysis reveals gut microbiota reshapes brain immune landscape in aged mouse model

| PRJNA623317 | ENA

Multi-modal single cell analysis reveals gut microbiota reshapes brain immune landscape in aged mouse model

Project description:We used CITE-seq (10x Gemoics-based) to profile and compare the transcriptomes and cell surface expression of a set of immune markers of naïve brain myeloid cells from young-adult (12 weeks old) wild type C57Bl/6 mice, aged (72 weeks old) wild type C57Bl/6 mice and young-adult and aged C57Bl/6 mice with antibiotics induced gut microbiota depletion. In one sequencing round, we sequenced a total of 12 different mouse brains (3 young control, 3 aged control, 3 young depleted gut microbiota (ABX) and 3 aged depleted gut microbiota (ABX)). We created an antibody pool consisting of 31 different antibodies (CCR2/CD192, C117/c-kit, CD11b, CD11c, CD172a/SIRPα, CD25, CD3, CD38, CD4, CD44, CD45, CD45R/B220, CD86, CD8a, CD90.1, Cx3cr1, F4/80, I-A/I-E, Ly6C, Ly6G, NK1.1, PD-1, PD-L1, CD169/Siglec-1, Siglec-H, TMEM119, XCR1, CD24, CD103, CD64, CD83) and stained each brain individually with this antibody pool. Then, we stained each brain with it's own unique hashing antibody so that we could subsequently pool the samples for loading onto the 10x Chromium. Young Control and Young ABX brains were tagged with HTOs 1-6 (HTO 1-3 for young control and HTO 4-6 for young ABX). Aged control and Aged ABX brains were tagged with HTOs 1-6 (HTO 1-3 for aged control and HTO 4-6 for aged ABX). Young and aged were loaded in separate wells on the 10X Chromium. The samples were tagged with unique nextera index primers to allow for preparation of one sequencing library consisting of all 12 samples and were separated in silico by it's unique hashing antibody and nextera index barcode combinations.

2020-11-05 | GSE148127 | GEO

Multi-modal single cell analysis reveals gut microbiota reshapes brain immune landscape in aged mouse model.

Project description:We used 16S V3/V4 region amplification to evaluate the composition of bacteria species in mouse fecal pellets. Fecel pellets were collected from young-adult (12 weeks old) wild type C57Bl/6 mice and aged (72 weeks old) wild type C57Bl/6 mice after 21 days of vehicle or antibiotics treatment (to induce gut microbiota depletion). In one sequencing round, we sequenced a total of 12 different fecal samples (3 young control, 3 aged control, 3 young depleted gut microbiota (ABX) and 3 aged depleted gut microbiota (ABX)). Amplicons were indexed using the Nextera XT Index Kit and pooled into a library for Illumina sequencing.

2020-11-03 | GSE160628 | GEO

Multi-modal analysis of human Plasma-cells

Project description:Multi-modal analysis of human Plasma-cells

| PRJNA785264 | ENA

Multi-modal analysis of human Plasma-cells

Project description:Plasma cells are key components of humoral immunity by secreting antibodies and providing protection against pathogens. These cells can be of IgM, IgA, or IgG subclass and migrate to class-specific niches. Localization and rareness of plasma cells make it challenge to define subclass-specific molecular hallmarks. Here, we describe how in-vitro differentiation of peripheral B-cells results in antibody-secreting plasma cells. Using a single-cell multi-modal sequencing approach (RAID) we find subclass-specific hallmark transcriptional profiles, surface protein expression and signaling pathway activation.

2023-01-02 | GSE189953 | GEO

A single-cell multi-modal ATAC + gene expression sequencing in tendinopathy

Project description:As people become more motivated to exercise regularly and stay healthy, tendinopathy is a common problem in both active athletes and inactive individuals, which imposes a considerable social and economic burden. Here we provide a single-cell multi-modal ATAC + gene expression sequencing in tendinopathy. We have identified pathways and genes regulated in tendinopathy samples that will help contribute to further investigation into the development and molecular hallmarks of tendinopathy.

2023-05-31 | GSE213803 | GEO

Multi-modal single-cell sequencing of differentiating mESCs using Smart-seq3 and scATAC-seq

Project description:We report dynamics of X-chromosome upregulation (XCU) along X-chromosome inactivation (XCI) in mESCs as they differentiate into EpiSCs. F1 hybrid C57BL6/J × CAST/EiJ male and female mESCs were grown in serum/LIF conditions were differentiated using Fgf2 and Activin A for 1, 2, 4 and 7 days to induce random XCI in female cells. Multi-modal single-cell sequencing was performed using scATAC on nuclei and Smart-seq3 to assay chromatin accessibility and poly-A+ RNA expression, respectively. Allelic resolution is achieved using strain-specific SNPs in the data. We reveal dynamic balancing of X alleles as cells undergo XCI to compensate dosage imbalances between sexes as well as between X and autosomes. Furthermore, we reveal that female naïve mESCs with two active X chromosomes lack XCU on both alleles which has major implications for reprogramming studies. Finally, we estimate allelic transcriptional burst kinetics from the data and find that progressively increased burst frequencies underlies the XCU process.

2022-02-14 | E-MTAB-10714 | biostudies-arrayexpress

Multi-modal characterization and simulation of human epileptic circuitry

Project description:Multi-modal characterization and simulation of human epileptic circuitry

| PRJNA895917 | ENA

Multi-modal control of dendritic cell functions by nociceptors

Project description:Multi-modal control of dendritic cell functions by nociceptors

| PRJNA899112 | ENA

Characterizing the molecular regulation of inhibitory immune checkpoints with multi-modal single-cell screens.

Project description:The expression of inhibitory immune checkpoint molecules such as PD-L1 is frequently observed in human cancers and can lead to the suppression of T-cell mediated immune responses. Here we apply ECCITE-seq, a technology which combines pooled CRISPR screens with single-cell mRNA and surface protein measurements, to explore the molecular networks that regulate PD-L1 expression. We also develop a computational framework, mixscape, that substantially improves the signal-to-noise ratio in single-cell perturbation screens by identifying and removing confounding sources of variation. Applying these tools, we identify and validate regulators of PD-L1, and leverage our multi-modal data to identify both transcriptional and post-transcriptional modes of regulation. In particular, we discover that the kelch-like protein KEAP1 and the transcriptional activator NRF2, mediate levels of PD-L1 upregulation after IFNγ stimulation. Our results identify a novel mechanism for the regulation of immune checkpoints and present a powerful analytical framework for the analysis of multi-modal single-cell perturbation screens.

2020-06-29 | GSE153056 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data