RESUMO
The spatial distribution of lymphocyte clones within tissues is critical to their development, selection, and expansion. We have developed spatial transcriptomics of variable, diversity, and joining (VDJ) sequences (Spatial VDJ), a method that maps B cell and T cell receptor sequences in human tissue sections. Spatial VDJ captures lymphocyte clones that match canonical B and T cell distributions and amplifies clonal sequences confirmed by orthogonal methods. We found spatial congruency between paired receptor chains, developed a computational framework to predict receptor pairs, and linked the expansion of distinct B cell clones to different tumor-associated gene expression programs. Spatial VDJ delineates B cell clonal diversity and lineage trajectories within their anatomical niche. Thus, Spatial VDJ captures lymphocyte spatial clonal architecture across tissues, providing a platform to harness clonal sequences for therapy.
Assuntos
Linfócitos B , Receptores de Células Precursoras de Linfócitos B , Receptores de Antígenos de Linfócitos T , Linfócitos T , Humanos , Linfócitos B/metabolismo , Células Clonais/metabolismo , Perfilação da Expressão Gênica/métodos , Receptores de Células Precursoras de Linfócitos B/genética , Receptores de Antígenos de Linfócitos T/genética , Linfócitos T/metabolismoRESUMO
Reconstruction of heterogeneity through single cell transcriptional profiling has greatly advanced our understanding of the spatial liver transcriptome in recent years. However, global transcriptional differences across lobular units remain elusive in physical space. Here, we apply Spatial Transcriptomics to perform transcriptomic analysis across sectioned liver tissue. We confirm that the heterogeneity in this complex tissue is predominantly determined by lobular zonation. By introducing novel computational approaches, we enable transcriptional gradient measurements between tissue structures, including several lobules in a variety of orientations. Further, our data suggests the presence of previously transcriptionally uncharacterized structures within liver tissue, contributing to the overall spatial heterogeneity of the organ. This study demonstrates how comprehensive spatial transcriptomic technologies can be used to delineate extensive spatial gene expression patterns in the liver, indicating its future impact for studies of liver function, development and regeneration as well as its potential in pre-clinical and clinical pathology.