A single-cell transcriptional roadmap of the mouse and human lymph node lymphatic vasculature

Abstract

<jats:p>Single-cell transcriptomics promises to revolutionize our understanding of the vasculature. Emerging computational methods applied to high dimensional single cell data allow integration of results between samples and species, and illuminate the diversity and underlying developmental and architectural organization of cell populations. Here, we illustrate these methods in analysis of mouse lymph node (LN) lymphatic endothelial cells (LEC) at single cell resolution. Clustering identifies five well-delineated subsets, including two medullary sinus subsets not recognized previously as distinct. Nearest neighbor alignments in trajectory space position the major subsets in a sequence that recapitulates known and suggests novel features of LN lymphatic organization, providing a transcriptional map of the lymphatic endothelial niches and of the transitions between them. Differences in gene expression reveal specialized programs for (1) subcapsular ceiling endothelial interactions with the capsule connective tissue and cells, (2) subcapsular floor regulation of lymph borne cell entry into the LN parenchyma and antigen presentation, and (3) medullary subset specialization for pathogen interactions and LN remodeling. LEC of the subcapsular sinus floor and medulla, which represent major sites of cell entry and exit from the LN parenchyma respectively, respond robustly to oxazolone inflammation challenge with enriched signaling pathways that converge on both innate and adaptive immune responses. Integration of mouse and human single-cell profiles reveals a conserved cross-species pattern of lymphatic vascular niches and gene expression, as well as specialized human subsets and genes unique to each species. The examples provided demonstrate the power of single-cell analysis in elucidating endothelial cell heterogeneity, vascular organization and endothelial cell responses. We discuss the findings from the perspective of LEC functions in relation to niche formations in the unique stromal and highly immunological environment of the LN.</jats:p>

Lymph Node Stromal Cells: Mapmakers of T Cell Immunity

“…Similar to FRCs, LECs release CCL21 to promote lymphocyte homing into LNs. Moreover, single-cell mRNA sequencing of LN cells identified four LN LEC subsets in mouse samples, while up to six subsets were defined in human LNs [ 20 , 21 , 22 ]. LN LEC subsets are so far less characterized compared to FRC subsets.…”

Molecular tracking devices quantify antigen distribution and archiving in the lymph node

“…We classified cell types using an automated approach 48 , comparing measured mRNA expression patterns to reference data sets for DCs 49,50 , FRCs 51 , and LECs 52,53,54 (Supplementary Table 2). As expected, the CD45+ fraction contained DCs, monocytes, T cells, and B cells (Fig.…”

“…We used an automated approach 48 that uses correlation between reference and measured gene expression profiles to assign unknown cell types to subtypes defined by previous studies. While strong correlation reflects a good match between reference and query profiles, high correlation between multiple reference LEC subtypes 52,53,54 , and changes in expression induced by antigen acquisition made definitive cell type assignments challenging ( Supplementary Fig. 7b-d).…”

“…7b-d). Notwithstanding these issues, we classified LEC subsets based on the highest correlation values to reference cell types ( Supplementary Fig 7d,e) 54 and identified three LEC subtypes 52,53,54 including Ptx3 LECs, ceiling LECs, and Marco LECs with high levels of antigen at the early time point ( Supplementary Fig. 7a).…”

“…The samples were then divided into separate objects for DCs, LECs, and FRCs. Cell subsets were then annotated using clustifyr with reference bulk RNA-seq data for DCs 49,50 , FRCs 51 , and LECs 52,53,54 .…”