Mammalian adipogenesis regulator (Areg) cells use retinoic acid signalling to be non- and anti-adipogenic in age-dependent manner

Adipose stem and precursor cells (ASPCs) give rise to adipocytes and determine the composition and plasticity of adipose tissue. Recently, several studies have demonstrated that ASPCs partition into at least three distinct cell subpopulations, including the enigmatic CD142+ cells. An outstanding challenge is to functionally characterise this population, as discrepant properties, from adipogenic to non- and anti-adipogenic, have been reported for these cells. To resolve these phenotypic ambiguities, we characterised mammalian subcutaneous CD142+ ASPCs across various experimental conditions, demonstrating that CD142+ ASPCs exhibit high molecular and phenotypic robustness. Specifically, we find these cells to be firmly non- and anti-adipogenic both in vitro and in vivo, with their inhibitory signals also impacting adipogenic human cells. However, these CD142+ ASPC-specific properties exhibit surprising temporal phenotypic alterations, and emerge only in an age-dependent manner. Finally, using multi-omic and functional assays, we show that the inhibitory nature of these adipogenesis-regulatory CD142+ ASPCs (Aregs) is driven by specifically expressed secretory factors that cooperate with the retinoic acid signalling pathway to transform the adipogenic state of CD142- ASPCs into a non-adipogenic, Areg-like state

A single-cell-based identification and characterisation of Aregs, an inhibitory subpopulation of adipose stem and precursor cells

Adipose tissue is an essential element in energy conservation mechanisms. Its unique plasticity is driven by the ability of adipocytes to accumulate and liberate lipids as a function of the energetic status of the organism. Given the recent rise in the global incidence of obesity, there is great interest in understanding the mechanisms behind disturbed energy balance. However, the heterogeneity of adipose tissue and of the somatic stem cells giving rise to mature adipocytes, makes it extremely challenging to characterise the cellular and molecular identity of fat depots. Single-cell RNA sequencing has recently enabled ground-breaking insights into the composition of complex cell populations. Our single cell-based dissection of adipogenic precursors revealed the existence of distinct cell sub-populations within the murine subcutaneous fat depot. We demonstrated that one of these populations, characterised by a high expression of F3 gene (encoding CD142), showed a completely non-adipogenic phenotype. Moreover, it revealed to be regulatory towards other adipose stem and precursor cells by supressing their ability to form adipocytes in a paracrine manner. These adipogenic regulatory cells, which we termed Aregs, proved to maintain their inhibitory properties in vivo and were shown phenotypically conserved in humans. We next established the robustness of Aregs as a novel cell sub-type in the context of various isolation strategies, the strength of the adipogenic cue and sex-based differences. Interestingly, we observed that Aregs isolated from the bourgeoning subcutaneous depots of new-born mice had high adipogenic propensity, suggesting that the appearance of classical phenotypical and functional properties of Aregs is development-dependent. In the light of the considerable implications of Aregs in adipose tissue composition and plasticity and, subsequently metabolic health, it is critical to understand the mechanism of their inhibitory nature. Integration of transcriptomic and proteomic datasets allowed us to identify a comprehensive set of highly specific candidates, which we validated in the context of Aregsâ identity and function. Our findings revealed a few potentially involved molecular actors. These include secreted factors CD142, GDF10 and MGP, which proved to be directly capable of inhibiting adipogenesis of Areg-depleted adipose stem and precursor cells, and transcription factors PKNOX2 and MEOX2, whose inactivation in Aregs compromised their ability to inhibit adipogenesis of co-cultured differentiating pre-adipocytes. Collectively, these molecules point out to a potential functional relationship of Aregs with vasculature as well as evoke a plausible association of Aregsâ phenotype to visceral-like non-adipogenic properties. We are now integrating these findings and completing them by investigating the transcriptional regulation and signalling pathways underlying the elusive mechanism of Aregsâ activity

Live-seq enables temporal transcriptomic recording of single cells

Single-cell transcriptomics (scRNA-seq) has greatly advanced our ability to characterize cellular heterogeneity. 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 microscopy, 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.ISSN:0028-0836ISSN:1476-468