Total PBMC from whole blood obtained from 18 RV254 participants 48 weeks after ART initiation were processed for CITE-seq on the 10x Genomics platform as described previously (Shangguan et al., 2021 ). Briefly, cell counts and viability were assessed by both the Countess II FL (Thermo Fisher) and trypan blue staining. Donor cells were hashed with TotalSeq-C anti-human Hashtag antibodies (BioLegend) and stained with a cocktail comprised of 63 TotalSeq-C antibodies targeting surface-expressed proteins. Cells from batches consisting of 9 or 10 samples were loaded into each of four Chromium chip wells before loading into the Chromium instrument. Cell mRNA gene expression (GEX) and antibody-derived tag (ADT) libraries were subsequently generated using the Chromium Next GEM Single Cell 5’ Library and Gel Bead Kit v1.1 (10x Genomics) according to the manufacturer’s instructions. Pooled libraries were quantitated with the MiSeq Nano v2 reagent cartridge (Illumina) and sequenced on an Illumina NovaSeq 6000 using an S4 reagent cartridge (2×100 bp)(Illumina). A modified version of the scRNA-seq assay was performed in RV254 participants at the acute HIV time point (n = 6) without feature barcodes.
Totalseq c anti human hashtag antibodies
Manufactured by BioLegend
TotalSeq-C anti-human Hashtag antibodies are designed for use in single-cell sequencing experiments. They provide a unique molecular identifier (UMI) to track the origin of individual cells, enabling the analysis of gene expression at the single-cell level.
Automatically generated - may contain errors
Lab products found in correlation
Countess 2 fl, by Thermo Fisher Scientific (1 mentions)
Chromium next gem single cell 5 library and gel bead kit v1, by 10x Genomics (1 mentions)
Novaseq 6000, by Illumina (1 mentions)
Fc blocker, by BioLegend (1 mentions)
Anti cd27 pe, by BioLegend (1 mentions)
Anti cd3 bv421, by BioLegend (1 mentions)
Anti cd38 apc cy7, by BioLegend (1 mentions)
Alexa fluor 647, by Thermo Fisher Scientific (1 mentions)
Aria 2 cell sorter, by BD (1 mentions)
5 protocols using totalseq c anti human hashtag antibodies
1
CITE-seq Analysis of PBMC from RV254 Participants
2
Multimodal Profiling of Antigen-Specific CD8+ T Cells
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Cells were processed in 6 batches with each batch making a separate 10X Chromium reaction. In each batch, individual PBMC samples were uniquely labeled with a combination of DNA-barcoded hashing antibody (TotalSeq-C anti-human Hashtag antibodies 1–10, Biolegend) and a set of DNA-barcoded MHC-multimers. We attributed a cell to a certain hashtag if more than 50% of UMIs derived from hashing antibodies matched that hashtag. Cells specific to certain dextramers were called similarly: we required more than 30% of dextramer-derived UMIs to contain a dextramer-specific barcode, and if multiple dextramers passed this threshold the cell was considered specific to both. If the most abundant dextramer barcode per cell was ≤ 3 UMIs, we did not assign any epitope specificity to it. Cells were assigned to donors using a combination of hashing antibody and dextramer barcode. TCRα and TCRβ sequences were assembled from aggregated VDJ-enriched libraries using the CellRanger (v. 6.0.0) vdj pipeline. For each cell we assigned the TCRβ and TCRα chain with the largest UMI count. The R script performing feature barcode deconvolution, GEX and TCR join is available on Github (https://github.com/pogorely/COVID_vax_CD8 ) as well as the resulting Supplementary Table 4 .
3
Antigen-experienced B Cell Sorting
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Cryopreserved PBMCs were rapidly thawed in a 37°C water bath for 1 min and then washed with 10 mL cold PBS. After centrifugation, the supernatant was removed, and the PBMCs were resuspended in PBS supplemented with 2% FBS (Cytiva). PBMCs were incubated with Fc-blocker (BioLegend) followed by staining with an antibody cocktail containing anti CD19-AF488 (BioLegend), anti CD3-BV421 (BioLegend), anti CD27-PE (BioLegend), and anti CD38-APC.Cy7 (BioLegend) for 30 min together with fluorescence-labeled antigen probes. Additionally, four different Total-Seq C anti-human hashtag antibodies (BioLegend) were used to label the donor. After three washes, cells from different donors were combined in FACS buffer (2% FBS in PBS) and sorted using BD Aria II Cell Sorter, with the gating strategy described in Fig. S1B. Antigen-experienced B cells (CD19+CD27+) were sorted, and double negative controls were utilized to gate the toxin- and non-binding cells: unlabeled toxin and the non-conjugated anti-His APC (BioLegend) for DT and TT, or non-conjugated Alexa Fluor 647 (Invitrogen) for PT.
4
High-throughput COVID-19 vaccine-reactive CD8+ T cell analysis
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Cells were processed in 6 batches with each batch making a separate 10X Chromium reaction. In each batch, individual PBMC samples were uniquely labeled with a combination of DNA-barcoded hashing antibody (TotalSeq-C anti-human Hashtag antibodies 1–10, Biolegend) and a set of DNA-barcoded MHC-multimers. We attributed a cell to a certain hashtag if more than 50% of UMIs derived from hashing antibodies matched that hashtag. Cells specific to certain dextramers were called similarly: we required more than 30% of dextramer-derived UMIs to contain a dextramer-specific barcode, and if multiple dextramers passed this threshold the cell was considered specific to both. If the most abundant dextramer barcode per cell was ≤ 3 UMIs, we did not assign any epitope specificity to it. Cells were assigned to donors using a combination of hashing antibody and dextramer barcode. TCRα and TCRβ sequences were assembled from aggregated VDJ-enriched libraries using the CellRanger (v. 6.0.0) vdj pipeline. For each cell we assigned the TCRβ and TCRα chain with the largest UMI count. The R script performing feature barcode deconvolution, GEX and TCR join is available on Github (https://github.com/pogorely/COVID_vax_CD8 ) as well as the resulting Extended data Table 4 .
5
Multimodal Profiling of Antigen-Specific CD8+ T Cells
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