scholarly journals Autoregulation of pre-mRNA processing for buffering noisy gene expression

2019 ◽  
Author(s):  
Madeline Smith ◽  
Khem Raj Ghusinga ◽  
Abhyudai Singh
Keyword(s):  
Gene Expression ◽  
Cell Fate ◽  
Mrna Decay ◽  
Noise Suppression ◽  
Cell Types ◽  
Stochastic Variation ◽  
Protein Levels ◽  
Analytic Expressions ◽  
Fate Decision ◽  
Decision Circuit

AbstractStochastic variation in the level of a protein among cells of the same population is ubiquitous across cell types and organisms. These random variations are a consequence of low-copy numbers, amplified by the characteristically probabilistic nature of biochemical reactions associated with gene-expression. We systematically compare and contrast negative feedback architectures in their ability to regulate random fluctuations in protein levels. Our stochastic model consists of gene synthesizing pre-mRNAs in transcriptional bursts. Each pre-mRNA transcript is exported to the cytoplasm and is subsequently translated into protein molecules. In this setup, three feedbacks architectures are implemented: protein inhibiting transcription of its own gene (I), protein enhancing the nuclear pre-mRNA decay rate (II), and protein inhibiting the export of pre-mRNAs (III). Explicit analytic expressions are developed to quantify the protein noise levels for each feedback strategy. Mathematically controlled comparisons provide insights into the noise-suppression properties of these feedbacks. For example, when the protein half-life is long, or the pre-mRNA decay is fast, then feedback architecture I provides the best noise attenuation. In contrast, when the timescales of export, mRNA, and protein turnover are similar, then III is superior to both II and I. We finally discuss biological relevance of these findings in context of noise suppression in an HIV cell-fate decision circuit.

scholarly journals Decision tree models and cell fate choice

2020 ◽  
Author(s):  
Ivan Croydon Veleslavov ◽  
Michael P.H. Stumpf
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Fate ◽  
Cell Types ◽  
Lineage Tree ◽  
Tree Models ◽  
Fate Decision ◽  
Average Gene ◽  
Lineage Trees ◽  
Cell Data

AbstractSingle cell transcriptomics has laid bare the heterogeneity of apparently identical cells at the level of gene expression. For many cell-types we now know that there is variability in the abundance of many transcripts, and that average transcript abun-dance or average gene expression can be a unhelpful concept. A range of clustering and other classification methods have been proposed which use the signal in single cell data to classify, that is assign cell types, to cells based on their transcriptomic states. In many cases, however, we would like to have not just a classifier, but also a set of interpretable rules by which this classification occurs. Here we develop and demonstrate the interpretive power of one such approach, which sets out to establish a biologically interpretable classification scheme. In particular we are interested in capturing the chain of regulatory events that drive cell-fate decision making across a lineage tree or lineage sequence. We find that suitably defined decision trees can help to resolve gene regulatory programs involved in shaping lineage trees. Our approach combines predictive power with interpretabilty and can extract logical rules from single cell data.

Serrate and Notch specify cell fates in the heart field by suppressing cardiomyogenesis

Development ◽  
2000 ◽  
Vol 127 (17) ◽  
pp. 3865-3876
Author(s):  
M.S. Rones ◽  
K.A. McLaughlin ◽  
M. Raffin ◽  
M. Mercola
Keyword(s):  
Gene Expression ◽  
Notch Signaling ◽  
Cell Fate ◽  
Notch Pathway ◽  
Cell Types ◽  
Myocardial Cell ◽  
Dominant Negative ◽  
Cell Fates ◽  
Cell Fate Decisions ◽  
Heart Field

Notch signaling mediates numerous developmental cell fate decisions in organisms ranging from flies to humans, resulting in the generation of multiple cell types from equipotential precursors. In this paper, we present evidence that activation of Notch by its ligand Serrate apportions myogenic and non-myogenic cell fates within the early Xenopus heart field. The crescent-shaped field of heart mesoderm is specified initially as cardiomyogenic. While the ventral region of the field forms the myocardial tube, the dorsolateral portions lose myogenic potency and form the dorsal mesocardium and pericardial roof (Raffin, M., Leong, L. M., Rones, M. S., Sparrow, D., Mohun, T. and Mercola, M. (2000) Dev. Biol., 218, 326–340). The local interactions that establish or maintain the distinct myocardial and non-myocardial domains have never been described. Here we show that Xenopus Notch1 (Xotch) and Serrate1 are expressed in overlapping patterns in the early heart field. Conditional activation or inhibition of the Notch pathway with inducible dominant negative or active forms of the RBP-J/Suppressor of Hairless [Su(H)] transcription factor indicated that activation of Notch feeds back on Serrate1 gene expression to localize transcripts more dorsolaterally than those of Notch1, with overlap in the region of the developing mesocardium. Moreover, Notch pathway activation decreased myocardial gene expression and increased expression of a marker of the mesocardium and pericardial roof, whereas inhibition of Notch signaling had the opposite effect. Activation or inhibition of Notch also regulated contribution of individual cells to the myocardium. Importantly, expression of Nkx2. 5 and Gata4 remained largely unaffected, indicating that Notch signaling functions downstream of heart field specification. We conclude that Notch signaling through Su(H) suppresses cardiomyogenesis and that this activity is essential for the correct specification of myocardial and non-myocardial cell fates.

scholarly journals Stochastic antagonism between two proteins governs a bacterial cell fate switch

Science ◽  
2019 ◽  
Vol 366 (6461) ◽  
pp. 116-120 ◽  
Author(s):  
Nathan D. Lord ◽  
Thomas M. Norman ◽  
Ruoshi Yuan ◽  
Somenath Bakshi ◽  
Richard Losick ◽  
...  
Keyword(s):  
Cell Fate ◽  
Regulatory Networks ◽  
Cell Types ◽  
Feedback Loops ◽  
Cell Fate Determination ◽  
Cell Fate Decision ◽  
A Cell ◽  
Fate Decision ◽  
Antagonistic Interactions

Cell fate decision circuits must be variable enough for genetically identical cells to adopt a multitude of fates, yet ensure that these states are distinct, stably maintained, and coordinated with neighboring cells. A long-standing view is that this is achieved by regulatory networks involving self-stabilizing feedback loops that convert small differences into long-lived cell types. We combined regulatory mutants and in vivo reconstitution with theory for stochastic processes to show that the marquee features of a cell fate switch in Bacillus subtilis—discrete states, multigenerational inheritance, and timing of commitments—can instead be explained by simple stochastic competition between two constitutively produced proteins that form an inactive complex. Such antagonistic interactions are commonplace in cells and could provide powerful mechanisms for cell fate determination more broadly.

scholarly journals A single cell brain atlas in human Alzheimer’s disease

2019 ◽  
Author(s):  
Alexandra Grubman ◽  
Gabriel Chew ◽  
John F. Ouyang ◽  
Guizhi Sun ◽  
Xin Yi Choo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Single Cell ◽  
Cell Fate ◽  
Expression Patterns ◽  
Cell Types ◽  
Gene Expression Patterns ◽  
Cell Type ◽  
Web Resource ◽  
Cell Type Specific

AbstractAlzheimer’s disease (AD) is a heterogeneous disease that is largely dependent on the complex cellular microenvironment in the brain. This complexity impedes our understanding of how individual cell types contribute to disease progression and outcome. To characterize the molecular and functional cell diversity in the human AD brain we utilized single nuclei RNA- seq in AD and control patient brains in order to map the landscape of cellular heterogeneity in AD. We detail gene expression changes at the level of cells and cell subclusters, highlighting specific cellular contributions to global gene expression patterns between control and Alzheimer’s patient brains. We observed distinct cellular regulation of APOE which was repressed in oligodendrocyte progenitor cells (OPCs) and astrocyte AD subclusters, and highly enriched in a microglial AD subcluster. In addition, oligodendrocyte and microglia AD subclusters show discordant expression of APOE. Integration of transcription factor regulatory modules with downstream GWAS gene targets revealed subcluster-specific control of AD cell fate transitions. For example, this analysis uncovered that astrocyte diversity in AD was under the control of transcription factor EB (TFEB), a master regulator of lysosomal function and which initiated a regulatory cascade containing multiple AD GWAS genes. These results establish functional links between specific cellular sub-populations in AD, and provide new insights into the coordinated control of AD GWAS genes and their cell-type specific contribution to disease susceptibility. Finally, we created an interactive reference web resource which will facilitate brain and AD researchers to explore the molecular architecture of subtype and AD-specific cell identity, molecular and functional diversity at the single cell level.HighlightsWe generated the first human single cell transcriptome in AD patient brainsOur study unveiled 9 clusters of cell-type specific and common gene expression patterns between control and AD brains, including clusters of genes that present properties of different cell types (i.e. astrocytes and oligodendrocytes)Our analyses also uncovered functionally specialized sub-cellular clusters: 5 microglial clusters, 8 astrocyte clusters, 6 neuronal clusters, 6 oligodendrocyte clusters, 4 OPC and 2 endothelial clusters, each enriched for specific ontological gene categoriesOur analyses found manifold AD GWAS genes specifically associated with one cell-type, and sets of AD GWAS genes co-ordinately and differentially regulated between different brain cell-types in AD sub-cellular clustersWe mapped the regulatory landscape driving transcriptional changes in AD brain, and identified transcription factor networks which we predict to control cell fate transitions between control and AD sub-cellular clustersFinally, we provide an interactive web-resource that allows the user to further visualise and interrogate our dataset.Data resource web interface:http://adsn.ddnetbio.com

scholarly journals Integrated time-lapse and single-cell transcription studies highlight the variable and dynamic nature of human hematopoietic cell fate commitment

2017 ◽  
Author(s):  
Alice Moussy ◽  
Jérémie Cosette ◽  
Romuald Parmentier ◽  
Cindy da Silva ◽  
Guillaume Corre ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Single Cell ◽  
Cell Fate ◽  
Morphological Changes ◽  
Gene Expression Pattern ◽  
Time Lapse ◽  
Dynamic Nature ◽  
Transcriptional Changes ◽  
Fate Decision

AbstractIndividual cells take lineage commitment decisions in a way that is not necessarily uniform. We address this issue by characterizing transcriptional changes in cord blood derived CD34+ cells at the single-cell level and integrating data with cell division history and morphological changes determined by time-lapse microscopy. We show, that major transcriptional changes leading to a multilineage-primed gene expression state occur very rapidly during the first cell cycle. One of the two stable lineage-primed patterns emerges gradually in each cell with variable timing. Some cells reach a stable morphology and molecular phenotype by the end of the first cell cycle and transmit it clonally. Others fluctuate between the two phenotypes over several cell cycles. Our analysis highlights the dynamic nature and variable timing of cell fate commitment in hematopoietic cells, links the gene expression pattern to cell morphology and identifies a new category of cells with fluctuating phenotypic characteristics, demonstrating the complexity of the fate decision process, away from a simple binary switch between two options as it is usually envisioned.

scholarly journals Defining cell identity beyond the premise of differential gene expression

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Hani Jieun Kim ◽  
Patrick P. L. Tam ◽  
Pengyi Yang
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Cell Fate ◽  
Differential Gene Expression ◽  
Cell Types ◽  
Cell Identity ◽  
Gene Transcripts ◽  
Differential Gene ◽  
Biological Attributes

AbstractIdentifying genes that define cell identity is a requisite step for characterising cell types and cell states and predicting cell fate choices. By far, the most widely used approach for this task is based on differential expression (DE) of genes, whereby the shift of mean expression are used as the primary statistics for identifying gene transcripts that are specific to cell types and states. While DE-based methods are useful for pinpointing genes that discriminate cell types, their reliance on measuring difference in mean expression may not reflect the biological attributes of cell identity genes. Here, we highlight the quest for non-DE methods and provide an overview of these methods and their applications to identify genes that define cell identity and functionality.

scholarly journals The single-cell epigenetic regulatory landscape in mammalian perinatal testis development

2021 ◽  
Author(s):  
Jinyue Liao ◽  
Hoi Ching Suen ◽  
Shitao Rao ◽  
Alfred Chun Shui Luk ◽  
Ruoyu Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Fate ◽  
Germ Cells ◽  
Somatic Cells ◽  
Cell Types ◽  
Regulatory Elements ◽  
Cellular Heterogeneity ◽  
Cell Populations ◽  
Cell Type

AbstractSpermatogenesis depends on an orchestrated series of developing events in germ cells and full maturation of the somatic microenvironment. To date, the majority of efforts to study cellular heterogeneity in testis has been focused on single-cell gene expression rather than the chromatin landscape shaping gene expression. To advance our understanding of the regulatory programs underlying testicular cell types, we analyzed single-cell chromatin accessibility profiles in more than 25,000 cells from mouse developing testis. We showed that scATAC-Seq allowed us to deconvolve distinct cell populations and identify cis-regulatory elements (CREs) underlying cell type specification. We identified sets of transcription factors associated with cell type-specific accessibility, revealing novel regulators of cell fate specification and maintenance. Pseudotime reconstruction revealed detailed regulatory dynamics coordinating the sequential developmental progressions of germ cells and somatic cells. This high-resolution data also revealed putative stem cells within the Sertoli and Leydig cell populations. Further, we defined candidate target cell types and genes of several GWAS signals, including those associated with testosterone levels and coronary artery disease. Collectively, our data provide a blueprint of the ‘regulon’ of the mouse male germline and supporting somatic cells.

scholarly journals Foxi1 inactivation rescues loss of principal cell fate selection in Hes1-deficient kidneys but does not ensure maintenance of principal cell gene expression

2019 ◽  
Author(s):  
Malini Mukherjee ◽  
Jennifer DeRiso ◽  
Madhusudhana Janga ◽  
Eric Fogarty ◽  
Kameswaran Surendran
Keyword(s):  
Gene Expression ◽  
Notch Signaling ◽  
Cell Fate ◽  
Collecting Duct ◽  
Cell Types ◽  
Principal Cell ◽  
Intercalated Cell ◽  
Collecting Ducts ◽  
Cell Gene Expression ◽  
Cell Gene

AbstractThe distal nephron and collecting duct segments of the mammalian kidney consist of intercalated cell types intermingled among principal cell types. Notch signaling ensures that a sufficient number of cells select a principal instead of an intercalated cell fate. However, the precise mechanisms by which Notch signaling patterns the distal nephron and collecting duct cell fates is unknown. Here we observed that Hes1, a direct target of Notch signaling pathway, is required within the mouse developing collecting ducts for repression of Foxi1 expression, an essential intercalated cell specific transcription factor. Interestingly, inactivation of Foxi1 in Hes1-deficient collecting ducts rescues the deficiency in principal cell fate selection, overall urine concentrating deficiency, and reduces the occurrence of hydronephrosis. However, Foxi1 inactivation does not rescue the reduction in expression of all principal cell genes in the Hes1-deficient kidney collecting duct cells that select the principal cell fate. Additionally, suppression of Notch/Hes1 signaling in mature principal cells reduces principal cell gene expression without activating Foxi1. We conclude that Hes1 is a Notch signaling target that is essential for normal patterning of the collecting ducts with intermingled cell types by repressing Foxi1, and for maintenance of principal cell gene expression independent of repressing Foxi1.

scholarly journals Epigenetic Control of Mesenchymal Stromal Cell Fate Decision

2021 ◽  
Author(s):  
Haoli Ying ◽  
Ruolang Pan ◽  
Ye Chen
Keyword(s):  
Cell Fate ◽  
Molecular Mechanisms ◽  
Epigenetic Modification ◽  
Cell Types ◽  
Connective Tissues ◽  
Differentiation Potential ◽  
Cell Fate Decisions ◽  
Fate Decision ◽  
Msc Differentiation

Mesenchymal stem cells (MSCs) are progenitors of connective tissues, which have emerged as important tools for tissue engineering owing to their differentiation potential in various cell types. The therapeutic utility of MSCs hinges upon our understanding of the molecular mechanisms involved in cellular fate decisions. Thus, the elucidation of the regulation of MSC differentiation has attracted increasing attention in recent years. A variety of external cues contribute to the process of MSC differentiation, including chemical, physical, and biological factors. Among the multiple factors that are known to affect cell fate decisions, the epigenetic regulation of MSC differentiation has become a research hotspot. In this chapter, we summarize recent progress in the determination of the effects of epigenetic modification on the multilineage differentiation of MSCs.

Sign in / Sign up

Export Citation Format

Share Document