Project description:This dataset was generated using adult (11 weeks) wild-type mice as a part of multiorgan profiling project. The samples were analyzed using the Chromium Single-cell 3'RNA-sequencing system.
Project description:Immune responses against tumor cells depend on T lymphocyte attraction and activity within the tumor microenvironment. Specialized immune-interacting fibroblasts, commonly referred to as fibroblastic reticular cells (FRC), form specialized niches in secondary lymphoid organs, originate from embryonic progenitors and foster T cell activation. FRCs have also been detected in tertiary lymphoid structures (TLS) in tumors, differentiating from cancer associated fibroblasts. However, the identity and differentiation of niche-forming cells that foster intra-tumoral T cell activity have remained elusive. Here, we employed single cell RNA-sequencing of EYFP+ fibroblasts and GP33/34-Tetramer+CD8+ T cells from experimental murine lung cancer and cell fate-mapping analysis, which revealed the ability of FRC subsets in lung tumors to differentiate from progenitors situated in mural and adventitial sites. Ablation of FRC progenitors in Tumor T cell environments (TTEs) of murine lungs led to reduced anti-tumor T cell activity and loss of tumor control during experimental coronavirus vector-based immunotherapy. Collectively, our study defines lung cancer-associated FRC niches and key processes involved in stromal-T cell interaction that could pave the way for improved cancer immunotherapy.
Project description:We describe Smart-seq-total, a method capable of assaying a broad spectrum of coding and non-coding RNA from a single cell. Built upon the template-switch mechanism, Smart-seq-total bears the key feature of its predecessor, Smart-seq2, namely, the ability to capture full-length transcripts with high yield and quality. It outperforms current poly(A)–independent total RNA-seq protocols by capturing transcripts of a broad size range, thus, allowing us to simultaneously analyze protein-coding, long non-coding, microRNA and other non-coding RNA from single cells. We used Smart-seq-total to analyze the total RNAome of human primary fibroblasts, HEK293T and MCF7 cells as well as that of induced murine embryonic stem cells differentiated into embryoid bodies. We show that simultaneous measurement of non-coding RNA and mRNA from the same cell enables elucidation of new roles of non-coding RNA throughout essential processes such as cell cycle or lineage commitment. Moreover, we show that cell types can be distinguished based on the abundance of non-coding transcripts only.