Abstract

A continuous flow of cells replenishes blood throughout life to maintain hematopoietic homeostasis. This flow originates from hematopoietic stem cells (HSCs) and progresses through a complex hierarchy of progenitors, collectively called hematopoietic stem and progenitor cells (HSPCs). The ever-increasing throughput of modern single cell ‘omics methods means that datasets encapsulating the cellular complexity of entire organ systems can now be generated. However, ‘omics protocols deliver snapshot measurements, because cells need to be destroyed to characterize their molecular states. As a result, it’s impossible to determine from those measurements how long it takes for a given cell to complete a differentiation process, nor at which precise stages cell numbers expand or contract. New research from Göttgens group provides a strategy to create predictive dynamic models of a regenerative organ in vivo, at single cell resolution and over extended timeframes. The Göttgens team went on to use novel time-series datasets for blood development to generate new computational models capturing the tissue dynamics of mouse bone marrow haematopoiesis. This allowed the coupling of cascading single-cell expression patterns with dynamic changes in differentiation and growth speeds. Changes in tissue dynamics underlie many major diseases, such as ageing associated defects in tissue maintenance and regeneration as well as clonal stem cell competition during early premalignant growth. To quantify such defects, researchers must first define tissue dynamics in the unperturbed healthy state. This new work provides such critical information for the blood system.