Time resolved, live cell transcriptomics to dissect cell fate in time and space – LiveSeq

Single Cell Omics has revolutionized biology by elucidating cell heterogeneity and identifying rare cell subpopulations. However, these technologies require cell lysis for analysis, precluding downstream phenotypic caracterization of that same cell. While pseudotime reconstructions from snapshot measurements attempt to overcome this limitation, this approach uses statistical assumptions that are not always verified in cells, like the independence of cell processes. As cells are highly dynamic, being able to study cell differentiation or reaction to stimuli over time and space is crucial for a better understanding of fundamental processes such as cell plasticity and response to infection.
Recently, the Swiss team of this project has pioneered Live-seq, a method to repeatedly extract picoliter volumes from the cytoplasm of cells while preserving viability and function, followed by molecular characterization of these extracts by RNA sequencing. Live-seq revealed in a proof-of-concept (PoC) that cell state and NFKB expression are phenotypic determinants of a macrophage’s response to LPS.
To expand the biological scope of Live-seq beyond PoC studies, at least two aspects must be improved: 1) RNA-seq sensitivity, which will be addressed by Partners 2 and 3 to enhance Live-seq’s overall efficacy; and 2) Imaging, which will be made more performant by leveraging Partner 1’s expertise in smart microscopy to establish automated image analysis workflows for tracking cells along multiple samplings and phenotypically characterizing them. These new features will enhance Live-seq’s ability to 1) investigate the molecular players underlying epithelial-mesenchymal transition (EMT), and 2) explore how infected host cells communicate with non-infected bystander cells during viral infection.
This project aims to unlock Live-seq’s full potential for spatio-temporal single-cell transcriptomics and thus to provide unprecedented insights into cell fate dynamics and cell-cell communication