scRNA-seq of lymph node stromal cells from naïve mice and heart allograft transplanted mice with/without anti-CD40L

Lymph node stromal cells (LNSCs) are the master regulator of the LN microenvironment. Single-cell genomics has revealed a multitude of LNSCs subsets, each playing unique and critical roles in immune responses and tissue homeostasis. However, the role of specific LNSC subsets controlling tolerance within draining LNs (DLNs) in heart allograft transplanted recipients remains to be explored. In order to assess the phenotype of LNSCs and effect of LNSCs on transplant tolerance or allograft rejection after heart transplantation, we performed single cell RNA sequencing (scRNA-seq) of LNSCs from naive mice and heart allograft transplanted mice with/without anti-CD40L (day8 after heart transplantation, anti-CD40L (250 μg, day 0)). In order to investigate the effect of heart transplantation (HTx) on LNSC phenotypes, three groups were prepared (naïve C57BL/6 mice, C57BL/6 mice after HTx, and anti-CD40L-treated C57BL/6 mice after HTx). C57BL/6 mice were transplanted with heart allograft from BALB/c mice. Recipients of CD40L-treated group were treated with anti-CD40L (250 μg, day 0). On day8, drainage LNs were hervested and enzymatically digested. CD45- cells were purified with the CD45 negative selection beads and were stained with anti-mouse CD45 before sorting for viable CD45- cells. For scRNA-seq, about 1.0 x 104 CD45- LNSCs were run on the 10X Chromium Controller (10X Genomics) to partition single cells into nanoliter-scale droplets containing uniquely barcoded beads and processed for sequencing library preparation using the Chromium Single Cell 3’ Reagent Kit (v3 chemistry) (10x Genomics, Pleasanton, CA). Generated cDNA libraries were sequenced on a NovaSeq 6000 sequencing system. Reads were demultiplexed, aligned to the GRCm38 mm10 assembly reference genome, and filtered; and cell barcodes and UMIs were quantified using the Cell Ranger 6.1 with default parameters (https://support.10xgenomics.com/single-cell-gene-expression/software/overview/welcome).