Both CD4+ and CD8+ Tregs play a critical role in the control of immune responses and immune tolerance; however, our understanding of CD8+ Tregs is limited while they are particularly promising for therapeutic application. We report here existence of highly suppressive human CD8+CD45RClow/− Tregs expressing Foxp3 and producing IFNγ, IL-10, IL-34, and TGFβ to mediate their suppressive activity. We demonstrate that total CD8+CD45RClow/− Tregs can be efficiently expanded in the presence of anti-CD3/28 mAbs, high-dose IL-2 and IL-15 and that such expanded Tregs efficiently delay GVHD and human skin transplantation rejection in immune humanized mice. Robustly expanded CD8+ Tregs displayed a specific gene signature, upregulated cytokines and expansion in the presence of rapamycin greatly improved proliferation and suppression. We show that CD8+CD45RClow/− Tregs are equivalent to canonical CD4+CD25highCD127low/− Tregs for suppression of allogeneic immune responses in vitro. Altogether, our results open new perspectives to tolerogenic strategies in human solid organ transplantation and GVHD.

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Background Multi-omics experimental approaches are becoming common practice in biological and medical sciences underlining the need to design new integrative techniques and applications to enable the multi-scale characterization of biological systems. The integrative analysis of heterogeneous datasets generally allows to acquire additional insights and generate novel hypotheses about a given biological system. However, it can become challenging given the often-large size of omics datasets and the diversity of existing techniques. Moreover, visualization tools for interpretation are usually non-accessible to biologists without programming skills. Results Here, we present MiBiOmics, a web-based and standalone application that facilitates multi-omics data visualization, exploration, integration, and analysis by providing easy access to dedicated and interactive protocols. It implements classical ordination techniques and the inference of omics-based (multilayer) networks to mine complex biological systems, and identify robust biomarkers linked to specific contextual parameters or biological states. Conclusions MiBiOmics provides easy-access to exploratory ordination techniques and to a network-based approach for integrative multi-omics analyses through an intuitive and interactive interface. MiBiOmics is currently available as a Shiny app at https://shiny-bird.univ-nantes.fr/app/Mibiomics and as a standalone application at https://gitlab.univ-nantes.fr/combi-ls2n/mibiomics.