Abstract
Single-cell technologies are currently widely applied to obtain a deeper understanding of the phenotype of single-cells in heterogenous mixtures. However, integrated multilayer approaches including simultaneous detection of mRNA, protein expression, and intracellular phospho-proteins are still challenging. Here, we combined an adapted method to in vitro-differentiate peripheral B-cells into antibody-secreting cells (ASCs) (i.e., plasmablasts and plasma cells) with integrated multi-omic single-cell sequencing technologies to detect and quantify immunoglobulin subclass-specific surface markers, transcriptional profiles, and signaling transduction pathway components. Using a common set of surface proteins, we integrated two multimodal datasets to combine mRNA, protein expression, and phospho-protein detection in one integrated dataset. Next, we tested whether ASCs that only seem to differ in its ability to secrete different IgM, IgA, or IgG antibodies exhibit other differences that characterize these different ASCs. Our approach detected differential expression of plasmablast and plasma cell markers, homing receptors, and TNF receptors. In addition, differential sensitivity was observed for the different cytokine stimulations that were applied during in vitro differentiation. For example, IgM ASCs were more sensitive to IL-15, while IgG ASC responded more to IL-6 and IFN addition. Furthermore, tonic BCR activity was detected in IgA and IgM ASCs, while IgG ASC exhibited active BCR-independent SYK activity and NF-κB and mTOR signaling. We confirmed these findings using flow cytometry and small molecules inhibitors, demonstrating the importance of SYK, NF-κB, and mTOR activity for plasmablast/plasma cell differentiation/survival and/or IgG secretion. Taken together, our integrated multi-omics approach allowed high-resolution phenotypic characterization of single cells in a heterogenous sample of in vitro-differentiated human ASCs. Our strategy is expected to further our understanding of human ASCs in healthy and diseased samples and provide a valuable tool to identify novel biomarkers and potential drug targets.