Live-seq enables temporal transcriptomic recording of single cells

Abstract

Single-cell transcriptomics (scRNA-seq) has greatly advanced our ability to characterize cellular heterogeneity1. However, scRNA-seq requires lysing cells, which impedes further molecular or functional analyses on the same cells. Here, we established Live-seq, a single-cell transcriptome profiling approach that preserves cell viability during RNA extraction using fluidic force microscopy2,3, thus allowing to couple a cell’s ground-state transcriptome to its downstream molecular or phenotypic behaviour. To benchmark Live-seq, we used cell growth, functional responses and whole-cell transcriptome read-outs to demonstrate that Live-seq can accurately stratify diverse cell types and states without inducing major cellular perturbations. As a proof of concept, we show that Live-seq can be used to directly map a cell’s trajectory by sequentially profiling the transcriptomes of individual macrophages before and after lipopolysaccharide (LPS) stimulation, and of adipose stromal cells pre- and post-differentiation. In addition, we demonstrate that Live-seq can function as a transcriptomic recorder by preregistering the transcriptomes of individual macrophages that were subsequently monitored by time-lapse imaging after LPS exposure. This enabled the unsupervised, genome-wide ranking of genes on the basis of their ability to affect macrophage LPS response heterogeneity, revealing basal Nfkbia expression level and cell cycle state as important phenotypic determinants, which we experimentally validated. Thus, Live-seq can address a broad range of biological questions by transforming scRNA-seq from an end-point to a temporal analysis approach.

Epigenetic Dynamics and Regulation of Plant Male Reproduction

“…In addition, further investigation is required to link genes associated with the epigenetic regulation of plant male reproduction with the epigenetic status of different cell types of the plant male organ. The single-cell technology [ 103 , 104 ] developed recently and CUT&Tag-based chromatin profiling technology [ 105 ] will provide additional and more precise transcriptional and epigenetic dynamic information at the single cell level, which will facilitate the disclosure of mysteries of the epigenetic regulation mechanisms in plant male reproduction.…”

Totem: a user-friendly tool for clustering-based inference of tree-shaped trajectories from single-cell data

“…In addition, unlike the updated Slingshot, Totem cannot currently handle disconnected trajectories. However, we do not consider this a major limitation because determining automatically which cell types belong to which disconnected sub-trajectories is not an easy task 10 . A safer approach is to analyse the disconnected parts as separate trajectories by segregating the cell types manually before trajectory inference.…”

Single-cell temporal transcriptomics from tiny cytoplasmic biopsies

“…The collaborative project between the groups of Vorholt (ETH) and Deplancke (EPFL), published in a recent issue of Nature ( Chen et al., 2022 ) has now solved the above problem in an elegant way. Instead of cell lysis, they employed fluidic force microscopy (FluidFM) to take tiny, picoliter scale single-cell biopsies directly from the cytoplasm of the investigated living cell.…”