bioRxivImmunologyPreprint
Stimulation strategy matters: A B-cell focused single-cell transcriptomic study on in vitro stimulated immune cells
Tine D'hamersiD, Jana NeirinckiD, Malicorne BuysseiD, Ciel De VriendtiD, Tessa C. C. KerreiD, Filomeen HaerynckiD, Mattias HofmansiD, Carolien BonroyiD, Celine EveraertiD
Abstract
Distinct in vitro B-cell stimulation strategies, defined by stimulation condition and incubation duration, have been described in diverse studies. Often, these approaches are considered interchangeable due to comparable flow-cytometric outputs concerning fluorescence intensities and B-cell subset distributions. However, whether these phenotypic similarities also reflect comparable underlying transcriptional states have not been systematically evaluated yet. In this study, we provide an unbiased comparison of B-cell activation strategies on healthy individuals, resulting in a single-cell transcriptomic atlas (4 donors; ~2,029 cells per sample; 81,160 cells in total with 56.3% annotated as B cells). Two T-cell independent stimulators targeting toll-like receptors (ODN2006 and IFN-{gamma}/R-848), were assessed next to two T-cell dependent stimulators (anti-CD40 and anti-CD3/CD28 antibodies), all incubated for eight and 30 hours. Observed overlap for differential abundance, differential gene expression and cell-cell interactions could directly be linked to T-cell (in)dependent working mechanism. Strategy-specific results uncovered time-point specific transcriptional changes, revealed the largest set of differentially expressed genes for IFN-{gamma}/R-848 and ODN2006, and showed that IFN-{gamma}/R-848 and anti-CD3/CD28 induced the majority of the cell-cell interactions. Ultimately, our reference atlas emphasizes the importance and facilitates the rational selection of optimal B-cell stimulation strategies, particularly for studies aiming to interrogate B-cell dysregulation in immune-mediated diseases.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
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