bioRxivImmunologyPreprint
Postnatal lymph node expansion of stromal progenitors towards reticular and CD34+ stromal cell subsets is determined by distinct transcriptional programs
J. Pezoldt, C. Wiechers, M. Litovchenko, M. Biocanin, M. Zou, K. Sitnik, M. Beckstette, W. Chen, V. Gardeux, S. Floess, M. Ebel, J. Russeil, P. Arampatzi, E. Vafardanejad, A.-E. Saliba, B. Deplancke, J. Huehn
Abstract
Gut-draining mesenteric lymph nodes (mLN) provide the framework and microenvironment to shape intestinal adaptive immune responses. We previously delineated transcriptional signatures in LN stromal cells (SC), pointing to tissue-specific variability in composition and immuno-modulatory function of SCs. Here, we dissect the tissue-specific epigenomic DNA accessibility and CpG methylation landscape of LN non-endothelial SCs and identify a microbiota-independent core epigenomic signature of LN SCs. By combined analysis of transcription factor (TF) binding sites together with the gene expression profiles of non-endothelial SCs, we delineated TFs poising skin-draining peripheral LN (pLN) SCs for pro-inflammatory responses. Furthermore, using scRNA-seq, we dissected the developmental trajectory of mLN SCs derived from postnatal to aged mice, identifying two distinct putative progenitors, namely CD34+ SC and fibroblastic reticular stromal cell (FRC) progenitors, which both feed the rapid postnatal LN expansion. Finally, we identified Irf3 as a key differentiation TF inferred from the epigenomic signature of mLN SCs that is dynamically expressed along the differentiation trajectories of FRCs, and validated Irf3 as a regulator of Cxcl9+ FRC differentiation. Together, our data constitute a comprehensive transcriptional and epigenomic map of mLN development and dissect location-specific, microbiota-independent properties of mLN non-endothelial SCs. As such, our findings represent a valuable resource to identify core transcriptional regulators that impinge on the developing mLN early in life, thereby shaping long-lasting intestinal adaptive immune responses.
- organism: mouse
- assay: scRNA-seq
- assay: DNA methylation
- research focus: cell type annotation
- research focus: trajectory inference
- research focus: gene regulatory network inference
- approach: statistical model
- approach: deep learning
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