Lysyl-tRNA synthetase (LysRS) was found to produce diadenosine tetraphosphate (Ap(4)A) in vitro more than two decades ago. Here, we used LysRS silencing in mast cells in combination with transfected normal and mutated LysRS to demonstrate in vivo the critical role played by LysRS in the production of Ap(4)A in response to immunological challenge. Upon such challenge, LysRS was phosphorylated on serine 207 in a MAPK-dependent manner, released from the multisynthetase complex, and translocated into the nucleus. We previously demonstrated that LysRS forms a complex with MITF and its repressor Hint-1, which is released from the complex by its binding to Ap(4)A, enabling MITF to transcribe its target genes. Here, silencing LysRS led to reduced Ap(4)A production in immunologically activated cells, which resulted in a lower level of MITF inducible genes. Our data demonstrate that specific LysRS serine 207 phosphorylation regulates Ap(4)A production in immunologically stimulated mast cells, thus implying that LysRS is a key mediator in gene regulation.

Cell-to-cell communication can be inferred from ligand–receptor expression in cell transcriptomic datasets. However, important challenges remain: global integration of cell-to-cell communication; biological interpretation; and application to individual cell population transcriptomic profiles. We develop ICELLNET, a transcriptomic-based framework integrating: 1) an original expert-curated database of ligand–receptor interactions accounting for multiple subunits expression; 2) quantification of communication scores; 3) the possibility to connect a cell population of interest with 31 reference human cell types; and 4) three visualization modes to facilitate biological interpretation. We apply ICELLNET to three datasets generated through RNA-seq, single-cell RNA-seq, and microarray. ICELLNET reveals autocrine IL-10 control of human dendritic cell communication with up to 12 cell types. Four of them (T cells, keratinocytes, neutrophils, pDC) are further tested and experimentally validated. In summary, ICELLNET is a global, versatile, biologically validated, and easy-to-use framework to dissect cell communication from individual or multiple cell-based transcriptomic profiles.