Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Single-cell RNAseq of phenotypically defined human B cell subsets

ABSTRACT: Separation of B cells has been historically important in discovering their functional relevance, particularly in relation to infection, immune disorders and vaccination. Traditional use of phenotypic markers often poses problems in distinguishing heterogeneous populations such as the Double Negative (DN, CD19+CD27-IgD-) cells. B cells represent a small subset of PBMCs; this represents challenges to use bottom-up approaches such as single-cell transcriptomics in defining B cell subpopulations. In this study we therefore used the 10X single-cell RNAseq platform on B cell populations already defined by FACS sorting (Transitional, CD19+CD27-IgD+CD10+; Naïve, CD19+CD27-IgD+CD10-; Classical Memory, CD19+CD27+IgD-; IgM Memory, CD19+CD27+IgD+; and DN). These data match known phenotypes to transcriptionally defined B cell subpopulations, and provide a reference atlas for researchers interested in better defining B cell subsets in their data.

INSTRUMENT(S): Illumina HiSeq 2500

ORGANISM(S): Homo sapiens

SUBMITTER: Joseph Ng

PROVIDER: E-MTAB-9544 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Single-Cell Transcriptomic Analyses Define Distinct Peripheral B Cell Subsets and Discrete Development Pathways.

Stewart Alexander A Ng Joseph Chi-Fung JC Wallis Gillian G Tsioligka Vasiliki V Fraternali Franca F Dunn-Walters Deborah K DK

Frontiers in immunology 20210318

Separation of B cells into different subsets has been useful to understand their different functions in various immune scenarios. In some instances, the subsets defined by phenotypic FACS separation are relatively homogeneous and so establishing the functions associated with them is straightforward. Other subsets, such as the "Double negative" (DN, CD19+CD27-IgD-) population, are more complex with reports of differing functionality which could indicate a heterogeneous population. Recent advances ...[more]

PMID: 33815362

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Project description:Protein tyrosine phosphatase nonreceptor type 22 (PTPN22) gene segregates with most autoimmune diseases; its risk allele encodes overactive PTPN22 phosphatases that alter B cell receptor (BCR) signaling potentially involved in the regulation of central B cell tolerance. To assess whether PTPN22 risk allele affects the removal of developing autoreactive B cells, we tested by ELISA the reactivity of recombinant antibodies isolated from single B cells from asymptomatic healthy individuals carrying one or two PTPN22 risk allele(s). We found that new emigrant/transitional and mature naive B cells from PTPN22 risk allele carriers contained high frequencies of autoreactive clones compared to non-carrier control donors. Hence, a single PTPN22 risk allele has a dominant effect on altering autoreactive B cell counterselection, suggesting that early B cell tolerance checkpoint defects precede the onset of autoimmunity. In addition, gene array experiments comparing mature naÃ¯ve B cells from healthy individuals carrying or not PTPN22 risk allele(s) revealed that the strength of association of PTPN22 for autoimmunity, second in importance only to the MHC, may not only be due to BCR signaling alteration but also to the regulation of other genes, which themselves have also been identified as involved in the development of autoimmune diseases. The PTPN22 risk allele is a single nucleotide change (cytidine to thymidine) at residue 1858, which results in a single amino acid substitution from arginine to tryptophan at position 620 of the PTPN22/Lyp protein. Data from mature naÃ¯ve B cell populations from patients carrying 1 or 2 PTPN22 T alleles and non-carrier patients were compared in order to characterize the impact of PTPN22 polymorphism on B cell physiology. RNA was extracted from batch-sorted CD19+CD10-CD21+CD27- conventional mature naive B cells using the Absolutely RNA microprep kit (Stratagene). 100-200 ng of RNA was obtained per sample, and the quality of the purified RNA was assessed by the Bioanalyzer from Agilent. Using the Ovation biotin system kit from Nugen, 30-50ng of RNA was amplified and labeled to produce cDNA. Labeled cDNA was hybridized on chips containing the whole human genome (Human Genome U133 Plus 2.0 from Affymetrix).

Project description:Memory B cells play a fundamental role in host defenses against viruses. This dataset aimed at understanding the recruitment and remodeling of the memory B cell repertoire in the context of BA.1-breakthrough infection in BNT162b2 mRNA vaccinated individuals. All four donors enrolled in the study had received a booster (3rd dose) of BNT162b2 mRNA vaccine and had no history of prior SARS-CoV-2 infection. All four experienced a documented breakthrough infection between 12/24/2021 and 01/30/2022 when BA.1 was responsible for > 85% of SARS-CoV-2 infections in France. All donors were sampled at Henri Mondor University Hospital (AP-HP, Paris France), and samples used for scRNA-seq were collected shortly after breakthrough infection (PO_M0 samples; between day 7 and day 18) and 5 to 6 months after infection (PO_M6 samples; between day 152 and day 173). Clinical and biological characteristics of these patients are summarized in the Patient_information.csv file. For each sample, an initial pool of 50.000 total peripheral CD3-CD14-CD56- CD19+ IgD- cells was always sorted and afterward, to enrich for cells of interest, only CD19+CD38low antibody secreting cells (ASCs), CD19hi IgD+ cells and SARS-CoV-2 Spike/RBD PE/tetramer positive B cells were sorted, leading to approximately 55000-60000 total sorted cells per sample. Sorted cells were then counted and up to 20 000 cells were loaded in the 10x Chromium Controller to generate single-cell gel-beads in emulsion. The scRNA-seq libraries for gene expression (mRNA), ADT and VDJ BCR libraries were generated using Chromium Next GEM Single Cell V(D)J Reagent Kit v.1.1 with Feature Barcoding (10x Genomics) according to the manufacturer’s protocol. PBMCs were initially isolated from venous blood samples via standard density gradient centrifugation and used after cryopreservation at -150°C. PBMCs were thawed using RPMI-1640 (Gibco) 10% FBS, washed twice and approximately 15x106 cells were then resuspended in 100µL PBS 2%FBS and incubated for 40 minutes at 4°C with a decoy tetramer (biotinylated Bovine Serum albumin coupled with BV785 streptavidin) and Hu-1 Spike, BA.1 Spike, Hu-1 RBD and BA.1 RBD tetramers (constructed using PE-labelled TotalSeqC® streptavidin with different barcodes for each individual antigens (see feature_reference.csv.gz files).). Cells were washed, resuspended in 100µL PBS 2%FBS and stained with a cocktail of fluorochrome conjugated (CD3, CD14 both APC-H7 at 1:100 each; CD15 and CD56 BV785 at 1:100 each, CD19 PECF594 at 1:100, IgD FITC at 1:100, CD38 PercP-Cy5.5 at 1:100) and TotalSeqC® (CD38, CD27, CD71, CD21, CD11c, CD39, FCRL5, CD95 all at 1:40 (all obtained from BioLegend)) antibodies for 40 minutes on ice. Viable cells were identified using a LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (Thermo Fisher Scientific, 1:200) incubated with conjugated antibodies. Two distinct sorts were performed for each donor: one at the early time-point (PO_M0) and one at the 6 months’ time-point (PO_M6).

Dataset Information

Single-cell RNAseq of phenotypically defined human B cell subsets

Publications

Single-Cell Transcriptomic Analyses Define Distinct Peripheral B Cell Subsets and Discrete Development Pathways.

Similar Datasets

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