Adult stem cells (ASCs) show remarkable self-renewing, proliferative and multi-lineage differentiation capacities. As such, they are essential for tissue homeostasis and hold great promise for regenerative medicine. However, as ASCs constitute small heterogeneous populations in tissues of complex composition, their identification and characterization remains highly challenging. A good example of such unresolved cell heterogeneity as well as lineage relationships is the adipose system, given the limited, and often conflicting knowledge about the molecular identity of white, brown and brite (brown-in-white) fat progenitors. Yet, understanding how fat cells arise, are maintained, and function in vivo is of great value for tackling global health burdens such as obesity and the metabolic syndrome.
In my talk, I will discuss how we exploited the power of single-cell RNA-sequencing (scRNA-seq) to molecularly dissect the adipose stem cell-enriched stromal vascular fraction. Specifically, I will describe a detailed characterization of precursors resident in mouse subcutaneous fat, arguing for the existence of several cell subpopulations with specific transcriptomic signatures and remarkably distinct differentiation potential. In addition, I will present a machine-learning based approach leveraging on publicly available data, which accurately identifies stem-like cells de novo across various scRNA-seq dissected somatic tissues. The presented findings provide a better understanding of both stem cell and adipose tissue biology and introduce novel approaches for the unbiased identification of ASCs.