Sofia Hu
Resident in Cardiothoracic Surgery - Thoracic Surgery
Affiliate, Department Funds
All Publications
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Transcription factor antagonism regulates heterogeneity in embryonic stem cell states
MOLECULAR CELL
2022; 82 (23): 4410-+
Abstract
Gene expression heterogeneity underlies cell states and contributes to developmental robustness. While heterogeneity can arise from stochastic transcriptional processes, the extent to which it is regulated is unclear. Here, we characterize the regulatory program underlying heterogeneity in murine embryonic stem cell (mESC) states. We identify differentially active and transcribed enhancers (DATEs) across states. DATEs regulate differentially expressed genes and are distinguished by co-binding of transcription factors Klf4 and Zfp281. In contrast to other factors that interact in a positive feedback network stabilizing mESC cell-type identity, Klf4 and Zfp281 drive opposing transcriptional and chromatin programs. Abrogation of factor binding to DATEs dampens variation in gene expression, and factor loss alters kinetics of switching between states. These results show antagonism between factors at enhancers results in gene expression heterogeneity and formation of cell states, with implications for the generation of diverse cell types during development.
View details for DOI 10.1016/j.molcel.2022.10.022
View details for Web of Science ID 000922730600005
View details for PubMedID 36356583
View details for PubMedCentralID PMC9722640
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Lineages of embryonic stem cells show non-Markovian state transitions
ISCIENCE
2021; 24 (8): 102879
Abstract
Pluripotent embryonic stem cells (ESCs) constitute the cell types of the adult vertebrate through a series of developmental state transitions. These states can be defined by expression levels of marker genes, such as Nanog and Sox2. In culture, ESCs reversibly transition between states. However, whether ESCs retain memory of their previous states or transition in a memoryless (Markovian) process remains relatively unknown. Here, we show some highly dynamic lineages of ESCs do not exhibit the Markovian property: their previous states and kin relations influence future choices. Unexpectedly, the distribution of lineages across their composition between states is constant over time, contrasting with the predictions of a Markov model. Additionally, highly dynamic ESC lineages show skewed cell fate distributions after retinoic acid differentiation. Together, these data suggest ESC lineage is an important variable governing future cell states, with implications for stem cell function and development.
View details for DOI 10.1016/j.isci.2021.102879
View details for Web of Science ID 000686897200066
View details for PubMedID 34401663
View details for PubMedCentralID PMC8353490
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MicroRNAs organize intrinsic variation into stem cell states
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2020; 117 (12): 6942-6950
Abstract
Pluripotent embryonic stem cells (ESCs) contain the potential to form a diverse array of cells with distinct gene expression states, namely the cells of the adult vertebrate. Classically, diversity has been attributed to cells sensing their position with respect to external morphogen gradients. However, an alternative is that diversity arises in part from cooption of fluctuations in the gene regulatory network. Here we find ESCs exhibit intrinsic heterogeneity in the absence of external gradients by forming interconverting cell states. States vary in developmental gene expression programs and display distinct activity of microRNAs (miRNAs). Notably, miRNAs act on neighborhoods of pluripotency genes to increase variation of target genes and cell states. Loss of miRNAs that vary across states reduces target variation and delays state transitions, suggesting variable miRNAs organize and propagate variation to promote state transitions. Together these findings provide insight into how a gene regulatory network can coopt variation intrinsic to cell systems to form robust gene expression states. Interactions between intrinsic heterogeneity and environmental signals may help achieve developmental outcomes.
View details for DOI 10.1073/pnas.1920695117
View details for Web of Science ID 000521821800084
View details for PubMedID 32139605
View details for PubMedCentralID PMC7104302