Journal Article

Fragment-sequencing unveils local tissue microenvironments at single-cell resolution

Bach, Karsten, Moor, Andreas E., Acar, Ilhan E., Borrelli, Costanza, Ficht, Xenia, Handler, Kristina, Piscuoglio, Salvatore

2023

Overview

Cells collectively determine biological functions by communicating with each other—both through direct physical contact and secreted factors. Consequently, the local microenvironment of a cell influences its behavior, gene expression, and cellular crosstalk. Disruption of this microenvironment causes reciprocal changes in those features, which can lead to the development and progression of diseases. Hence, assessing the cellular transcriptome while simultaneously capturing the spatial relationships of cells within a tissue provides highly valuable insights into how cells communicate in health and disease. Yet, methods to probe the transcriptome often fail to preserve native spatial relationships, lack single-cell resolution, or are highly limited in throughput, i.e. lack the capacity to assess multiple environments simultaneously. Here, we introduce fragment-sequencing (fragment-seq), a method that enables the characterization of single-cell transcriptomes within multiple spatially distinct tissue microenvironments. We apply fragment-seq to a murine model of the metastatic liver to study liver zonation and the metastatic niche. This analysis reveals zonated genes and ligand-receptor interactions enriched in specific hepatic microenvironments. Finally, we apply fragment-seq to other tissues and species, demonstrating the adaptability of our method. Experimentally preserving tissue microenvironments remains challenging for single-cell sequencing methods. Here, the authors introduce fragment-sequencing, a method that can preserve three-dimensional microenvironments in single-cell RNA-seq, thus allowing the reconstruction of spatial tissue niches.

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 13 / 38/32 / 38/39 / 45 / 49/91 / 631/1647/2017 / 631/337/2019 / 631/67/2329 / 631/67/327 / 631/67/69 / 64/60 / Adaptability / Animal models / Animals / Communication / Gene expression / Gene Expression Profiling - methods / Humanities and Social Sciences / Liver / Liver - metabolism / Metastases / Metastasis / Mice / Microenvironments / multidisciplinary / Niches / Science / Science (multidisciplinary) / Sequence Analysis, RNA - methods / Single-Cell Analysis - methods / Tissues / Transcriptome - genetics / Transcriptomes / Zonation