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| Status |
Public on May 19, 2023 |
| Title |
PBMC_3_HC |
| Sample type |
SRA |
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| Source name |
PBMC
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| Organism |
Homo sapiens |
| Characteristics |
tissue: PBMC
cell type: PBMC
treatment: No enrichment
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| Extracted molecule |
total RNA |
| Extraction protocol |
Whole human blood was obtained from Research Blood Components, LLC (Watertown, MA), and PBMC were isolated by means of density gradient centrifugation and cryopreserved. Upon use, PBMC were thawed into Aim-V medium (ThermoFisher). B cells were isolated using an EasySep Human Pan-B Cell Enrichment kit (Stemcell Technologies, Vancouver, Canada).
Biotinylated pneumococcal serotype 3 polysaccharide with a 5% biotin load (ST3, from Pfizer EPBD) was coupled with high concentration streptavidin-phycoerythrin (SA-PE) and streptavidin-allophycocyanin (SA-APC, both from BioLegend) in separate reactions. Biotinylated ST3 and the fluorophore-conjugated streptavidin reagents were prepared with PBS at 4X working solutions of 20 µg/mL and 200 µg/mL, respectively. Equal volumes of ST3 and SA-PE; and, separately, equal volumes of ST3 and SA-APC working solutions were combined, thoroughly mixed and incubated at 4 ºC protected from light for a minimum incubation period of 60 minutes with thorough mixing at 30 minutes and directly prior to use. Coupled ST3-PE and ST3-APC solutions were maintained at 4 ºC, protected from light until use.
Seq-Well
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic single cell |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
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| Data processing |
Cell hashing data was aligned to HTO barcodes using CITE-seq-Count v1.4.2.
Raw read processing of scRNA-seq reads was performed as previously described35. Briefly, reads were aligned to the hg38 reference genome or Mmul_10 reference genome and collapsed by cell barcode and unique molecular identifier (UMI). Whole transcriptome data was further analyzed in Seurat66. First, cells with less than 300 unique genes detected and genes detected in fewer than 5 cells were filtered out. Variable features were then determined using the FindVariableFeatures function, and the ScaleData function was then used to regress out the number of RNA features in each cell. The number of principal components used for visualization was determined by examination of the elbow plot, and two-dimensional embeddings were generated using uniform manifold approximation and projection (UMAP). Clusters were determined using Louvain clustering, as implemented in the FindClusters function in Seurat. For analysis of ST3-reactive B cell data, clusters of cells that exhibited high expression of mitochondrial genes or markers associated with other cell phenotypes (i.e. monocytes) were moved and the data was reprocessed. Differential gene expression analysis was performed for each cluster and between indicated cell populations using the FindMarkers function.
Processing of BCR sequence data was performed with pRESTO and Change-O from the Immcantation software suite69,70. First, potential errors in cell barcode and UMI sequence were corrected for errors up to one nucleotide mismatch with a directional UMI collapse, as implemented in UMI-Tools71. Data was filtered by Q-score using the FilterSeq.py function to remove any sequences with an average Q score below 25. Then, the MaskPrimers.py function was used to annotate sequences with the correct isotype (R1 index) and V-region (R2) primer, as well as to mask the corresponding primer regions. The PairSeq.py function was used to retain only read pairs that passed both the FilterSeq.py and MaskPrimers.py processing steps. The data was then segregated by cell barcode and UMI, and the BuildConsensus.py function was used to call consensus sequences for read 1 index and read 2 of each barcode and UMI separately. The AssemblePairs.py function was used to assemble these consensus sequences into a single overlapping sequence. The resulting sequences were then analyzed with IgBlast72 using reference sequences provided by IMGT.
Assembly: hg38
Assembly: mmul_10
Supplementary files format and content: tab separated values files and comma separated files
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| Submission date |
May 19, 2023 |
| Last update date |
May 19, 2023 |
| Contact name |
Duncan Matthew Morgan |
| E-mail(s) |
dmmorgan@mit.edu
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| Organization name |
MIT
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| Department |
Koch Institute
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| Lab |
Love lab
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| Street address |
500 Main St
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| City |
CAMBRIDGE |
| State/province |
MA |
| ZIP/Postal code |
02139 |
| Country |
USA |
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| Platform ID |
GPL24676 |
| Series (1) |
| GSE232873 |
Full-length single-cell BCR sequencing paired with RNA sequencing reveals convergent responses to vaccination |
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| Relations |
| BioSample |
SAMN35178084 |
| SRA |
SRX20437254 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM7385309_PBMC_3_HC_processed.csv.gz |
14.1 Mb |
(ftp)(http) |
CSV |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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