Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Lineage tracking reveals origins and relative affinities of antibodies produced by two subsets of memory B cells

ABSTRACT: Memory B cells comprise a heterogenous group of cells that differ in origin, and phenotype. During the early phases of the immune response, activated B cells can differentiate into IgM expressing memory cells, short-lived plasma cells or seed germinal centers (GCs). The memory compartment is subsequently enriched by B cells that have been through several rounds of division and selection in the GC. Here we report on the use of an unbiased lineage tracking approach to explore the origins and properties of memory B cell subsets in mice with an intact immune system. We find that activated B cells continue to differentiate into memory B cells throughout the immune response. When defined on the basis of their origins, the memory B cells originating from activated B cells or GCs differ in isotype and overall gene expression, somatic hypermutation, and in their affinity for antigen.

ORGANISM(S): Mus musculus

PROVIDER: GSE174394 | GEO | 2021/05/14

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Lineage tracking reveals origins and relative affinities of antibodies produced by two subsets of memory B cells

Project description:Lineage tracking reveals origins and relative affinities of antibodies produced by two subsets of memory B cells

| PRJNA729737 | ENA

Follicular dendritic cells restrict IL4 availability in germinal centers and foster memory B cell generation

Project description:Germinal centers (GCs) are sites of antibody affinity maturation and memory B cell generation. Follicular dendritic cells (FDCs) form a dense stromal network within GCs, but the full extent of their supportive activity is not understood. Here we showed that FDCs expressed IL4Ra and they reduced IL4 availability in GCs. We used scRNA-seq to examine IL4 actions within the GC and identified a subset of light zone cells marked by high IL4Ra and CD23 and lack of a Myc gene-expression signature. Trajectory inference analysis suggested this population could differentiate into pre-memory and pre-plasma cells. Genetic experiments showed that IL4Ra and STAT6 acted intrinsically to restrain pre-memory B cell generation. By reducing IL4 availability, FDCs enhanced GC B cell selection and fostered memory cell generation. This work suggests that GC FDCs provide a niche that limits bystander IL4 activity, focusing IL4 action on B cells undergoing selection and enhancing memory cell differentiation

2021-09-15 | GSE180920 | GEO

Synthetic circuits for tracking human cell fate

Project description:Cells respond heterogeneously to DNA damage. We engineered genetic circuits to detect differential responses in a population that persist for many days post-stimulus. We used microarrays to compare memory and non-memory subpopulations 3 days after DNA damage or doxycycline exposure. MD12/p53R2-RE and MD10/TetOx2 cells were either exposed to UV (10uJ/m^2) or doxycycline (1 ug/mL, 24 hours) and allowed to recover 3 days before sortng of memory and non-memory cells and RNA extraction. Two replicates were submitted for each condition (UV memory, UV non-memory, dox memory, dox non-memory)

2012-05-23 | E-GEOD-38189 | biostudies-arrayexpress

Tracking B Cell Responses to the SARS-CoV-2 mRNA-1273 Vaccine

Project description:The COVID-19 pandemic left an unprecedented social and economic impact on the world. This rapidly evolving global instigated a worldwide effort to develop an effective vaccine. Despite the generation of a protective antibody response in most individuals after two doses of an anti-spike mRNA vaccine, some studies have shown that a poorer response is elicited in some individuals, particularly those that are immunocompromised or elderly. To gain further insight into the cellular mechanisms driving B cell evolution in response to vaccination against SARS-CoV-2, we performed longitudinal single-cell transcriptomic, epitope sequencing (CITE-seq), and repertoire profiling of three COVID-19 vaccinees. Spike-specific (S-2P+) B cells showed early immune activation at v1D14 (14 days after vaccine dose 1) and accumulation of somatic hyper mutation (SHM) up to v2M6 (months 6). At v2D6, the S-2P+ cells expanded into memory B cell (MBC) cluster 5 with a dynamic kinetics over time. At v2M6, majority of S-2P+ cells were into resting memory (RM) subset within cluster 5. Analysis of B cell receptor (BCR) repertoire showed selection of genes commonly detected in neutralizing monoclonal antibodies from COVID-19 patients. Tracking of S-2P+ B cell response showed clonal association between earlier activated CD38+ memory, as well as tissue-like memory, with RM B cells at v2M6. These clones showed evolving signal with progressive accumulation of SHM over time. The presence of early plasmablast (PB) within these clones corroborates our previous report that associates PB response with sustained immunity. This integrated analysis allowed us to characterize the transcriptional activity underpinning the development of B cells involved in inducing an immune response to the COVID-19 vaccine.

2023-07-07 | GSE219098 | GEO

CD4+ cell transcriptional profiling by RNA sequencing

Project description:<p>We use next generation sequencing to investigate the different transcriptomes of closely related CD4+ T-cells from healthy human donors to elucidate the genetic programs that underlie their specialized immune functions. Six cell types were included: Regulatory T-cells (CD25hiCD127low/neg with >95% FOXP3+ purity), regulatory T-cells activated using PMA/ionomycin, CD25-CD45RA+ ('naive' helper T-cells), CD25-CD45RO+ ('memory' helper T-cells), activated Th17 cells (>98% IL17A+ purity) and activated IL17-CD4+ T-cells (called 'ThPI'). Poly-T capture beads were used to isolate mRNA from total RNA, and fragment sizes of ~200 were sequenced from both ends on Illumina's genome analyzer. We confirm many of the canonical signature genes of T-cell populations, but also discover new genes whose expression is limited to specific CD4 T-cell lineages, including long non-coding RNAs. Additionally, we find that genes encoded at loci linked to multiple human autoimmune diseases are enriched for preferential expression upon T-cell activation, suggesting that an aberrant response to T-cell activation is fundamental to pathogenesis.</p>

| phs000626 | dbGaP

Transcriptome analysis of TIML- and CIML-NK cells

Project description:NK cells may acquire under certain conditions features of adaptive immune cells. As the functional role of memory NK cells in cancer has so far remained elusive, we reasoned whether tumor-priming itself might promote memory NK cell generation. We provide substantial evidence that independent from pro-inflammatory stimulation, tumor-induced memory-like (TIML) NK cells exhibit a heightened, tumor-restricted cytotoxicity which is dependent on a higher/faster perforin but not IFN-Î³ release. Comparative transcriptome analysis reveals that gene expression patterns differ between TIML- and Cytokine-induced memory-like (CIML)-NK cells.

2016-04-15 | E-MTAB-4606 | biostudies-arrayexpress

Yakimchuk2019 - Mathematical modeling of immune modulation by glucocorticoids

Project description:Mathematical modeling of immune modulation by glucocorticoids Konstantin Yakimchuk https://doi.org/10.1016/j.biosystems.2019.104066 Abstract The cellular and molecular mechanisms of immunomodulatory actions of glucocorticoids (GC) remain to be identified. Using our experimental findings, a mathematical model based on a system of ordinary differential equations for characterization of the regulation of anti-tumor immune activity by the both direct and indirect GC effects was generated to study the effects of GC treatment on effector CD8+ T cells, GC-generated tolerogenic dendritic cells (DC), regulatory T cells and the growth of lymphoma cells. In addition, we compared the data from in vivo and in silico experiments. The mathematical simulations indicated that treatment with GCs may suppress anti-tumor immune response in a dose-dependent manner. The model simulations were in line with earlier experimental observations of inhibitory effects of GCs on T and NK cells and DCs. The results of this study might be useful for predicting clinical outcomes in patients receiving GC therapy.

2020-01-06 | MODEL1912170005 | BioModels

Expression data from murine follicular dendritic cells

Project description:Germinal centers (GCs) are clusters of activated B cells built on stromal cells known as follicular dendritic cells (FDCs). In the Peyer’s patches (PPs), GCs are chronically induced by bacteria and are the major sites for generation of gut IgA immune responses. Whether FDCs directly contribute to the IgA production in PP GCs is unknown. To investigate the role FDCs in gut immune system, we examined comprehensive gene profiles of FDCs purified from PPs or perypheral lymph nodes (pLNs) with or without immunization. We also tried to reconstitute the PP FDC signature in vitro by pulsed or continuous stimulation of pLN FDCs through TLRs, RARs or simultaneously through TLRs and RARs.

2010-07-05 | GSE19401 | GEO

Single-cell transcriptomics identifies an effectorness gradient shaping the response of CD4+ T cells to cytokines

Project description:Naïve CD4+ T cells coordinate the immune response by acquiring an effector phenotype in response to cytokines. However, the cytokine responses in memory T cells remain largely understudied. We used quantitative proteomics, bulk RNA-seq and single-cell RNA-seq of over 40,000 human naïve and memory CD4+ T cells to generate a detailed map of cytokine-regulated gene expression programs. We demonstrated that cytokine response differs substantially between naïve and memory T cells and showed that memory cells are unable to differentiate into the Th2 phenotype. Moreover, memory T cells acquire a Th17-like phenotype in response to iTreg polarization. At the single-cell level, we demonstrated that T cells form a continuum which progresses from naïve to effector memory T cells. This continuum is accompanied by a gradual increase in the expression levels of chemokines and cytokines and thus represents an effectorness gradient. Finally, we found that T cell cytokine responses are determined by where the cells lie in the effectorness gradient and identified genes whose expression is controlled by cytokines in an effectorness-dependent manner. Our results shed light on the heterogeneity of T cells and their responses to cytokines, provide insight into immune disease inflammation and could inform drug development.

2020-03-04 | PXD015315 | Pride

Dependence on Bcl6 and Blimp1 identifies distinct mechanisms driving memory and follicular helper CD4+ T cell differentiation [scRNA-Seq]

Project description:During the immune response, CD4+ T cells differentiate into distinct effector subtypes, including follicular helper T (Tfh) cells that help B cells, and into memory cells. Tfh and memory cells are required for long-term immunity; both depend on the transcription factor Bcl6, raising the question of whether they differentiate through similar mechanisms. Here, using notably single-cell RNA and ATAC sequencing, we show that virus-responding CD4+ T cells lacking both Bcl6 and Blimp1 can differentiate into cells with transcriptomic, chromatin accessibility and function attributes of memory cells, but not of Tfh cells. Thus, Bcl6 promotes memory cell differentiation primarily through its repression of Blimp1. These findings demonstrate that distinct mechanisms underpin the differentiation of memory and Tfh CD4+ cell and define the Bcl6-Blimp1 axis as a potential target for promoting long-term memory T cell differentiation.

2021-11-14 | GSE184847 | 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