ABSTRACT
During early embryogenesis, mechanical constraints and localized biochemical signals co-occur around anteroposterior axis determination and symmetry breaking. Their relative roles, however, are hard to tease apart in vivo Using brachyury (Bra), a primitive streak and mesendoderm marker in mouse embryoid bodies (EBs), we studied how contact, biochemical cues and neighboring cell cues affect the positioning of a primitive streak-like locus and thus determine the anteroposterior axis. We show that a Bra-competent layer must be formed in the EB before Bra expression initiates, and that Bra onset locus position is biased by contact points of the EB with its surrounding, probably through modulation of chemical cues rather than by mechanical signaling. We can push or pull Bra onset away from contact points by introducing a separate localized Wnt signal source, or maneuver Bra onset to a few loci or to an isotropic peripheral pattern. Furthermore, we show that Foxa2-positive cells are predictive of the future location of Bra onset, demonstrating an earlier symmetry-breaking event. Our analysis of factors affecting symmetry breaking and spatial fate choice during this developmental process could prove valuable for in vitro differentiation and organoid formation.
Subject(s)
Embryoid Bodies/cytology , Embryoid Bodies/metabolism , Animals , Cell Differentiation/genetics , Cell Differentiation/physiology , Cells, Cultured , Embryonic Stem Cells/cytology , Embryonic Stem Cells/metabolism , Fetal Proteins/genetics , Fetal Proteins/metabolism , Gene Expression Regulation, Developmental , Hepatocyte Nuclear Factor 3-beta/genetics , Hepatocyte Nuclear Factor 3-beta/metabolism , Mice , Primitive Streak/cytology , Primitive Streak/metabolism , T-Box Domain Proteins/genetics , T-Box Domain Proteins/metabolismABSTRACT
Human cellular reprogramming to induced pluripotency is still an inefficient process, which has hindered studying the role of critical intermediate stages. Here we take advantage of high efficiency reprogramming in microfluidics and temporal multi-omics to identify and resolve distinct sub-populations and their interactions. We perform secretome analysis and single-cell transcriptomics to show functional extrinsic pathways of protein communication between reprogramming sub-populations and the re-shaping of a permissive extracellular environment. We pinpoint the HGF/MET/STAT3 axis as a potent enhancer of reprogramming, which acts via HGF accumulation within the confined system of microfluidics, and in conventional dishes needs to be supplied exogenously to enhance efficiency. Our data suggest that human cellular reprogramming is a transcription factor-driven process that it is deeply dependent on extracellular context and cell population determinants.
Subject(s)
Induced Pluripotent Stem Cells , Humans , Induced Pluripotent Stem Cells/metabolism , Cellular Reprogramming , Gene Expression Regulation , Transcription Factors/genetics , Transcription Factors/metabolism , Cells, CulturedABSTRACT
Thanks to innovative sample-preparation and sequencing technologies, gene expression in individual cells can now be measured for thousands of cells in a single experiment. Since its introduction, single-cell RNA sequencing (scRNA-seq) approaches have revolutionized the genomics field as they created unprecedented opportunities for resolving cell heterogeneity by exploring gene expression profiles at a single-cell resolution. However, the rapidly evolving field of scRNA-seq invoked the emergence of various analytics approaches aimed to maximize the full potential of this novel strategy. Unlike population-based RNA sequencing approaches, scRNA seq necessitates comprehensive computational tools to address high data complexity and keep up with the emerging single-cell associated challenges. Despite the vast number of analytical methods, a universal standardization is lacking. While this reflects the fields' immaturity, it may also encumber a newcomer to blend in.In this review, we aim to bridge over the abovementioned hurdle and propose four ready-to-use pipelines for scRNA-seq analysis easily accessible by a newcomer, that could fit various biological data types. Here we provide an overview of the currently available single-cell technologies for cell isolation and library preparation and a step by step guide that covers the entire canonical analytic workflow to analyse scRNA-seq data including read mapping, quality controls, gene expression quantification, normalization, feature selection, dimensionality reduction, and cell clustering useful for trajectory inference and differential expression. Such workflow guidelines will escort novices as well as expert users in the analysis of complex scRNA-seq datasets, thus further expanding the research potential of single-cell approaches in basic science, and envisaging its future implementation as best practice in the field.