Biology subjects

Socolovsky, M.

Publications and source records attributed to Socolovsky, M..

6 recordsLinked to original sources

bioRxiv2025

Epo and hypoxia accelerate a pattern of gradual cell cycle shortening in BFU-e and CFU-e erythroid progenitors in vivo

Regulation of the earliest erythroid progenitors is not well understood, yet it is relevant to some types of anemia that are refractory to treatment with Erythropoietin (Epo). Recent work shows that early erythroid BFU-e and CFU-e progenitors form a developmental continuum characterized by gradual increase in the proportion of cells in S phase of the cycle. Here we proposed two distinct hypotheses to explain this finding, either the presence of quiescent progenitors or the gradual shortening of G1 and the cycle with differentiation. Using a mouse expressing a timer -protein transgene that reports cell cycle duration, we determined that, in vivo, early erythroid progenitors undergo orderly gradual shortening of the cycle as they mature and approach terminal differentiation. There was no evidence of quiescent BFU-e or CFU-e progenitors in tissue. We found that BFU-e and CFU-e progenitors are highly responsive to hypoxic stress and to its Epo and glucocorticoid mediators. Epo and hypoxia accelerated the pattern of gradual cell cycle shortening throughout early erythropoiesis, while conversely, dexamethasone prolonged the cycle specifically in proerythroblasts. Further, Epo and hypoxia generated rapid increase in early progenitor cell size and dynamic changes in cell surface marker expression. Our data suggest that high Epo or hypoxic stress promote rapid increase in the rate of growth in biomass across the entire erythroid trajectory including in the earliest BFU-e progenitors, and indicates that stress progenitors are of the same type and lineage as those sustaining basal erythropoiesis. Key PointsO_LIA maturational process of gradual cell cycle shortening and increasing cell size in BFU-e and CFU-e is accelerated by Epo and hypoxia C_LIO_LIThere are no quiescent BFU-e and CFU-e in tissue. Stress CFU-e arise from the same cell type and lineage as CFU-e in the basal state. C_LI

cell biology↗

bioRxiv2024

IL-17A primes an early progenitor compartment to tune the erythropoietic feedback circuit

Feedback control of erythropoiesis exemplifies conflicting goals in tissue homeostasis: maintaining fast reactivity to stress while minimizing proliferative burden on progenitors in the steady state. Here we show that these conflicting goals are tuned through the combinatorial action of cytokines. We find that IL-17A, a pro-inflammatory cytokine, mediates striking synergism with the negative feedback signal erythropoietin (Epo) in vivo, accelerating the erythropoietic response to hypoxia. A model of erythropoietic control shows increased reactivity may occur through two cell circuit designs, with one having far lower constitutive progenitor burden in normoxia. IL-17A acts through this optimal design by sensitizing progenitors to Epo, a model supported by multiple experimental observations. We suggest that IL-17A signals impending hypoxia during infections, tuning erythropoiesis in favor of a faster stress response. Our study highlights IL-17A as a potential erythropoietic therapeutic agent and serves as a model of homeostatic tuning in stem and progenitor cell circuits.

systems biology↗

bioRxiv2020

The Erythropoietin Receptor Stimulates Rapid Cycling and Formation of Larger Red Cells During Mouse and Human Erythropoiesis

Erythroid terminal differentiation entails cell divisions that are coupled to progressive decreases in cell size. EpoR signaling is essential for the survival of erythroid precursors, but it is unclear whether it has other functions in these cells. Here we endowed mouse precursors that lack the EpoR with survival signaling, finding that this was sufficient to support their differentiation into enucleated red cells, but that the process was abnormal. Precursors underwent fewer and slower cell cycles and yet differentiated into smaller red cells. Surprisingly, EpoR further accelerated cycling of early erythroblasts, the fastest cycling cells in the bone marrow, while simultaneously increasing their cell size. EpoR-mediated formation of larger red cells was independent of the established pathway regulating red cell size by iron through Heme-regulated eIF2 kinase (HRI). We confirmed the effect of Epo on red cell size in human volunteers, whose mean corpuscular volume (MCV) increased following Epo administration. This increase persisted after Epo declined and was not the result of increased reticulocytes. Our work reveals a unique effect of EpoR signaling on the interaction between the cell cycle and cell growth. Further, it suggests new diagnostic interpretations for increased red cell volume, as reflecting high Epo and erythropoietic stress.

developmental biology↗

bioRxiv2019

Dissection of the 4D chromatin structure of the α-globin locus through in vivo erythroid differentiation with extreme spatial and temporal resolution

Mammalian gene expression patterns are controlled by regulatory elements, which interact within Topologically Associating Domains (TADs). The relationship between activation of regulatory elements, formation of structural chromatin interactions and gene expression during development is unclear. We developed Tiled-C, a low-input Chromosome Conformation Capture (3C) approach, to study chromatin architecture at high spatial and temporal resolution through in vivo mouse erythroid differentiation. Integrated analysis of matched chromatin accessibility and single-cell expression data shows that regulatory elements gradually become accessible within pre-existing TADs during early differentiation. This is followed by structural re-organization within the TAD and formation of specific contacts between enhancers and promoters. In contrast to previous reports, our high-resolution data show that these enhancer-promoter interactions are not established prior to gene expression, but formed gradually during differentiation, concomitant with progressive upregulation of gene activity. Together, these results provide new insight into the close, interdependent relationship between chromatin architecture and gene regulation during development.

genomics↗

bioRxiv2018

Emergence of the erythroid lineage from multipotent hematopoiesis

Red cell formation begins with the hematopoietic stem cell, but the manner by which it gives rise to erythroid progenitors, and their subsequent developmental path, remain unclear. Here we combined single-cell transcriptomics of murine hematopoietic tissues with fate potential assays to infer a continuous yet hierarchical structure for the hematopoietic network. We define the erythroid differentiation trajectory as it emerges from multipotency and diverges from 6 other blood lineages. With the aid of a new flow-cytometric sorting strategy, we validated predicted cell fate potentials at the single cell level, revealing a coupling between erythroid and basophil/mast cell fates. We uncovered novel growth factor receptor regulators of the erythroid trajectory, including the proinflammatory IL-17RA, found to be a strong erythroid stimulator; and identified a global hematopoietic response to stress erythropoiesis. We further identified transcriptional and high-purity FACS gates for the complete isolation of all classically-defined erythroid burst-forming (BFU-e) and colony-forming progenitors (CFU-e), finding that they express a dedicated transcriptional program, distinct from that of terminally-differentiating erythroblasts. Intriguingly, profound remodeling of the cell cycle is intimately entwined with CFU-e developmental progression and with a sharp transcriptional switch that extinguishes the CFU-e stage and activates terminal differentiation. Underlying these results, our work showcases the utility of theoretic approaches linking transcriptomic data to predictive fate models, providing key insights into lineage development in vivo.

systems biology↗

bioRxiv2017

Fundamental limits on dynamic inference from single cell snapshots

Single cell expression profiling reveals the molecular states of individual cells with unprecedented detail. However, because these methods destroy cells in the process of analysis, they cannot measure how gene expression changes over time. But some information on dynamics is present in the data: the continuum of molecular states in the population can reflect the trajectory of a typical cell. Many methods for extracting single cell dynamics from population data have been proposed. However, all such attempts face a common limitation: for any measured distribution of cell states, there are multiple dynamics that could give rise to it, and by extension, multiple possibilities for underlying mechanisms of gene regulation. Here, we describe the aspects of gene expression dynamics that cannot be inferred from a static snapshot alone and identify assumptions necessary to constrain a unique solution for cell dynamics from static snapshots. We translate these constraints into a practical algorithmic approach, Population Balance Analysis (PBA), which makes use of a method from spectral graph theory to solve a class of high dimensional differential equations. We use simulations to show the strengths and limitations of PBA, and then apply it to single-cell profiles of hematopoietic progenitor cells (HPCs). Cell state predictions from this analysis agree with HPC fate assays reported in several papers over the past two decades. By highlighting the fundamental limits on dynamic inference faced by any method, our framework provides a rigorous basis for dynamic interpretation of a gene expression continuum and clarifies best experimental designs for trajectory reconstruction from static snapshot measurements.\n\nSignificanceSeeing a snapshot of individuals at different stages of a process can reveal what the process would look like for a single individual over time. Biologists apply this principle to infer temporal sequences of gene expression states in cells from measurements made at a single moment in time. However, these inferences are fundamentally under-determined. Using a conservation law, we enumerate reasons that there is no unique dynamics associated with a single snapshot, limiting our ability to infer gene regulatory mechanisms. We then propose a method for dynamic inference that provides a unique dynamic solution under defined approximations and apply it to data from bone marrow stem cells. Overall, this study introduces formal biophysical approaches to single cell bioinformatics.\n\nClassificationBIOLOGICAL SCIENCES / Systems Biology

systems biology↗