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Weinreb, Caleb

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Weinreb

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Caleb

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Weinreb, Caleb
Author's Publications: search.filters.isAuthorOfPublication.c61938b6-e39e-4618-b788-8001a7410959

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    Fundamental limits on dynamic inference from single-cell snapshots
    (National Academy of Sciences, 2018) Weinreb, Caleb; Wolock, Samuel; Tusi, Betsabeh K.; Socolovsky, Merav; Klein, Allon
    Single-cell expression profiling reveals the molecular states of individual cells with unprecedented detail. Because these methods destroy cells in the process of analysis, they cannot measure how gene expression changes over time. However, 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.
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    Single-Cell Lineage Tracing Unveils a Role for TCF15 in Haematopoiesis
    (Springer Science and Business Media LLC, 2020-07-15) Rodriguez-Fraticelli, Alejo E.; Weinreb, Caleb; Wang, Shou-Wen; Migueles, Rosa P.; Jankovic, Maja; Usart, Marc; Klein, Allon; Lowell, Sally; Camargo, Fernando
    Bone marrow transplantation therapy relies on the life-long regenerative capacity of haematopoietic stem cells (HSCs). HSCs present a complex variety of regenerative behaviours at the clonal level, but the mechanisms underlying this diversity are still undetermined. Recent advances in single cell RNA sequencing (scRNAseq) have revealed transcriptional differences amongst HSCs, providing a possible explanation for their functional heterogeneity. However, the destructive nature of sequencing assays prevents simultaneous observation of stem cell state and function. To solve this challenge, we implemented expressible lentiviral barcoding, which enabled simultaneous analysis of lineages and transcriptomes from single adult HSCs and their clonal trajectories during long-term bone marrow reconstitution. Differential gene expression analysis between clones with distinct behaviour unveiled an intrinsic molecular signature that characterizes functional long-term repopulating HSCs. Probing this signature through in vivo CRISPR screening, we found the transcription factor Tcf15 to be required, and sufficient, to drive HSC quiescence and long-term self-renewal. In situ, Tcf15 expression labels the most primitive subset of true multipotent HSCs. In conclusion, our work elucidates clone-intrinsic molecular programs associated with functional stem cell heterogeneity, and identifies a mechanism for the maintenance of the self-renewing haematopoietic stem cell state.