Immune, endothelial and neuronal network map in human lymph node and spleen

Abstract

As secondary lymphoid organs, the spleen and lymph node represent important hubs for both innate and adaptive immunity. Neuroanatomical and tracing data, largely derived from rodents, suggest that lymph nodes contain sensory and sympathetic innervation, whereas the spleen contains postganglionic sympathetic innervation, with conflicting views regarding the existence of cholinergic or vagal innervation. Herein, we map the neuronal, vascular, and sinus cell networks from human spleen and lymph node using highly multiplexed CODEX (CO-Detection by indEXing) and 3D light sheet microscopy of cleared tissues. These data demonstrate striking delineation of two distinct layers within the lymph node subcapsular sinus-the ceiling defined by Podoplanin expression and floor by LYVE1, which overlays the lymph node follicles. Within the lymph node interior, we observed a mesh-like vessel network innervated with GAP43 and beta3-tubulin. Dense perivascular innervation occurred in both tissues, including a subset of axonal processes expressing choline acetyl transferase (ChAT). Four neuronal markers (ChAT, PGP9.5, tyrosine hydroxylase, and beta3-tubulin) localized to the arterial tunica externa suggest expression in the nervi vasorum while GAP43 was expressed within the internal elastic membrane of arteries. These data represent highly novel 3D visualization of perivascular and periductal autonomic innervation within these two key human organs.

Characterizing cell-type spatial relationships across length scales in spatially resolved omics data

“…Delineating the spatial organization of cell types in the spleen can provide insights into how these different cellular populations may achieve such diverse immunologic functions. Therefore, we focused on six single-cell resolution spatial proteomics datasets of the human spleen from three individuals assayed by CODEX as part of The Human BioMolecular Atlas Program (HuBMAP) 9,11 . We first performed graph-based clustering for one representative 9400µm by 9100µm section of a human spleen with 154,446 cells to identify 12 cell types based on 28 protein markers (Figure 3a-c, Online Methods).…”

Unsupervised discovery of tissue architecture in multiplexed imaging

“…Likewise, systematic application of UTAG in image data from various organs will undoubtedly accelerate projects such as spatial cell atlases 38–40 , by providing microanatomical context to the cells, and enabling ground-up discovery of tissue architecture beyond cell type composition of tissues. Another exciting future application is the discovery of microanatomy in volumetric images of tissue 13,41–43 , since there is no conceptual limitation to use UTAG in 3 dimensions. This would enable robust morphometry of tissue structures since a current challenge in two-dimensional analysis of tissue is the detection of structure independent of the cutting angle.…”

“…Another exciting future application is the discovery of microanatomy in volumetric images of tissue 13,[41][42][43] , since there is no conceptual limitation to use UTAG in 3 dimensions. This would enable robust morphometry of tissue structures since a current challenge in two-dimensional analysis of tissue is the detection of structure independent of the cutting angle.…”

Mapping the lymphatic system across body scales and expertise domains: A report from the 2021 National Heart, Lung, and Blood Institute workshop at the Boston Lymphatic Symposium

“…In addition, the transcriptome may not always reflect protein expression, thus validation of marker gene expression in the tissue is critical for establishing the identified gene expression profiles. A detailed visualization of the three-dimensional blood and lymphatic vasculature within human tissues, including skin and LNs, remains challenging ( Currlin et al, 2022 ). Construction of a human body biomolecular atlas across the body scales requires extensive knowledge of its cellular composition and tissue architecture ( Regev et al, 2017 ; Snyder et al, 2019 ).…”