scholarly journals Quantitative assessment of cell fate decision between autophagy and apoptosis

2017 ◽  
Author(s):  
Bing Liu ◽  
Zoltán N. Oltvai ◽  
Hulya Bayir ◽  
Gary A. Silverman ◽  
Stephen C. Pak ◽  
...  
Keyword(s):  
Cell Fate ◽  
Cellular Damage ◽  
G Protein Signaling ◽  
Protein Signaling ◽  
Cell Fate Decision ◽  
Cell Fate Decisions ◽  
Dynamic Cell ◽  
Stress Signals ◽  
Fate Decision ◽  
Amp Activated Protein Kinase

AbstractAutophagy and apoptosis regulate cell survival and death, and are implicated in the pathogenesis of many diseases. The same type of stress signals can induce either process, but it is unclear how cells ‘assess’ cellular damage and make a ‘life’ or ‘death’ decision by activating autophagy or apoptosis. A computational model of coupled apoptosis and autophagy is built here to study the systems-level dynamics of the underlying signaling network. The model explains the differential dynamics of autophagy and apoptosis in response to various experimental stress signals. Autophagic response dominates at low-to-moderate stress; whereas the response shifts from autophagy (graded activation) to apoptosis (switch-like activation) with increasing intensity of stress. The model reveals that this dynamic cell fate decision is conferred by a core regulatory network involving cytoplasmic Ca2+ as a rheostat that fine-tunes autophagic and apoptotic responses. A G-protein signaling-mediated feedback loop maintains cytoplasmic Ca2+ level, which in turn governs autophagic response through an AMP-activated protein kinase (AMPK)-mediated feedforward loop. The model identified Ca2+/calmodulin-dependent kinase kinase β (CaMKKβ) as a determinant of the opposite roles of cytoplasmic Ca2+ in autophagy regulation. The results also demonstrated that the model could contribute to the development of pharmacological strategies modulate cell fate decisions.

scholarly journals Cell fate clusters in ICM organoids arise from cell fate heredity and division: a modelling approach

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tim Liebisch ◽  
Armin Drusko ◽  
Biena Mathew ◽  
Ernst H. K. Stelzer ◽  
Sabine C. Fischer ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Cell Division ◽  
Cell Fate ◽  
Inner Cell Mass ◽  
Cell Mass ◽  
Cell Lineage ◽  
Cell Fate Decision ◽  
Cell Fate Decisions ◽  
Chemical Signalling ◽  
Fate Decision

AbstractDuring the mammalian preimplantation phase, cells undergo two subsequent cell fate decisions. During the first decision, the trophectoderm and the inner cell mass are formed. Subsequently, the inner cell mass segregates into the epiblast and the primitive endoderm. Inner cell mass organoids represent an experimental model system, mimicking the second cell fate decision. It has been shown that cells of the same fate tend to cluster stronger than expected for random cell fate decisions. Three major processes are hypothesised to contribute to the cell fate arrangements: (1) chemical signalling; (2) cell sorting; and (3) cell proliferation. In order to quantify the influence of cell proliferation on the observed cell lineage type clustering, we developed an agent-based model accounting for mechanical cell–cell interaction, i.e. adhesion and repulsion, cell division, stochastic cell fate decision and cell fate heredity. The model supports the hypothesis that initial cell fate acquisition is a stochastically driven process, taking place in the early development of inner cell mass organoids. Further, we show that the observed neighbourhood structures can emerge solely due to cell fate heredity during cell division.

scholarly journals Variability in β-catenin pulse dynamics in a stochastic cell fate decision in C. elegans

2018 ◽  
Author(s):  
Jason R. Kroll ◽  
Jasonas Tsiaxiras ◽  
Jeroen S. van Zon
Keyword(s):  
Caenorhabditis Elegans ◽  
Cell Fate ◽  
Cell Fusion ◽  
Precursor Cell ◽  
Cell Fate Decision ◽  
Absolute Level ◽  
Cell Fate Decisions ◽  
Pulse Dynamics ◽  
Significant Variability ◽  
Fate Decision

AbstractDuring development, cell fate decisions are often highly stochastic, but with the frequency of the different possible fates tightly controlled. To understand how signaling networks control the cell fate frequency of such random decisions, we studied the stochastic decision of the Caenorhabditis elegans P3.p cell to either fuse to the hypodermis or assume vulva precursor cell fate. Using time-lapse microscopy to measure the single-cell dynamics of two key inhibitors of cell fusion, the Hox gene LIN-39 and Wnt signaling through the β-catenin BAR-1, we uncovered significant variability in the dynamics of LIN-39 and BAR-1 levels. Most strikingly, we observed that BAR-1 accumulated in a single, 1-4 hour pulse at the time of the P3.p cell fate decision, with strong variability both in pulse slope and time of pulse onset. We found that the time of BAR-1 pulse onset was delayed relative to the time of cell fusion in mutants with low cell fusion frequency, linking BAR-1 pulse timing to cell fate outcome. Overall, a model emerged where animal-to-animal variability in LIN-39 levels and BAR-1 pulse dynamics biases cell fate by modulating their absolute level at the time cell fusion is induced. Our results highlight that timing of cell signaling dynamics, rather than its average level or amplitude, could play an instructive role in determining cell fate.Article summaryWe studied the stochastic decision of the Caenorhabditis elegans P3.p cell to either fuse to the hypodermis or assume vulva precursor cell fate. We uncovered significant variability in the dynamics of LIN-39/Hox and BAR-1/β-catenin levels, two key inhibitors of cell fusion. Surprisingly, we observed that BAR-1 accumulated in a 1-4 hour pulse at the time of the P3.p cell fate decision, with variable pulse slope and time of pulse onset. Our work suggests a model where animal-to-animal variability in LIN-39 levels and BAR-1 pulse dynamics biases cell fate by modulating their absolute level at the time cell fusion is induced.

scholarly journals G protein signaling governing cell fate decisions involves opposing Gα subunits inCryptococcus neoformans

2007 ◽  
Vol 18 (9) ◽  
pp. 3237-3249 ◽  
Author(s):  
Yen-Ping Hsueh ◽  
Chaoyang Xue ◽  
Joseph Heitman
Keyword(s):  
G Protein ◽  
Cell Fate ◽  
G Protein Coupled Receptors ◽  
G Protein Signaling ◽  
Protein Signaling ◽  
Pheromone Receptor ◽  
Cell Fate Decisions ◽  
Regulatory Circuit ◽  
Receptor Recognition ◽  
G Protein Coupled

Communication between cells and their environments is often mediated by G protein-coupled receptors and cognate G proteins. In fungi, one such signaling cascade is the mating pathway triggered by pheromone/pheromone receptor recognition. Unlike Saccharomyces cerevisiae, which expresses two Gα subunits, most filamentous ascomycetes and basidiomycetes have three Gα subunits. Previous studies have defined the Gα subunit acting upstream of the cAMP-protein kinase A pathway, but it has been unclear which Gα subunit is coupled to the pheromone receptor and response pathway. Here we report that in the pathogenic basidiomycetous yeast Cryptococcus neoformans, two Gα subunits (Gpa2, Gpa3) sense pheromone and govern mating. gpa2 gpa3 double mutants, but neither gpa2 nor gpa3 single mutants, are sterile in bilateral crosses. By contrast, deletion of GPA3 (but not GPA2) constitutively activates pheromone response and filamentation. Expression of GPA2 and GPA3 is differentially regulated: GPA3 expression is induced by nutrient-limitation, whereas GPA2 is induced during mating. Based on the phenotype of dominant active alleles, Gpa2 and Gpa3 signal in opposition: Gpa2 promotes mating, whereas Gpa3 inhibits. The incorporation of an additional Gα into the regulatory circuit enabled increased signaling complexity and facilitated cell fate decisions involving choice between yeast growth and filamentous asexual/sexual development.

scholarly journals A single-cell resolved cell-cell communication model explains lineage commitment in hematopoiesis

Development ◽  
2021 ◽  
Vol 148 (24) ◽  
Author(s):  
Megan K. Rommelfanger ◽  
Adam L. MacLean
Keyword(s):  
Cell Fate ◽  
Cell Communication ◽  
Communication Model ◽  
Cell Fate Decision ◽  
Cell Coupling ◽  
Environmental Signals ◽  
Cell Fate Decisions ◽  
Wide Range ◽  
Fate Decision ◽  
Cell Cell

ABSTRACT Cells do not make fate decisions independently. Arguably, every cell-fate decision occurs in response to environmental signals. In many cases, cell-cell communication alters the dynamics of the internal gene regulatory network of a cell to initiate cell-fate transitions, yet models rarely take this into account. Here, we have developed a multiscale perspective to study the granulocyte-monocyte versus megakaryocyte-erythrocyte fate decisions. This transition is dictated by the GATA1-PU.1 network: a classical example of a bistable cell-fate system. We show that, for a wide range of cell communication topologies, even subtle changes in signaling can have pronounced effects on cell-fate decisions. We go on to show how cell-cell coupling through signaling can spontaneously break the symmetry of a homogenous cell population. Noise, both intrinsic and extrinsic, shapes the decision landscape profoundly, and affects the transcriptional dynamics underlying this important hematopoietic cell-fate decision-making system. This article has an associated ‘The people behind the papers’ interview.

Suppressors of a lin-12 hypomorph define genes that interact with both lin-12 and glp-1 in Caenorhabditis elegans.

Genetics ◽  
1993 ◽  
Vol 135 (3) ◽  
pp. 765-783 ◽  
Author(s):  
M Sundaram ◽  
I Greenwald
Keyword(s):  
Caenorhabditis Elegans ◽  
Cell Fate ◽  
Gene Dosage ◽  
Egg Laying ◽  
Loss Of Function ◽  
Cell Fate Decision ◽  
Cell Fates ◽  
Cell Fate Decisions ◽  
Suppressor Mutations ◽  
Fate Decision

Abstract The lin-12 gene of Caenorhabditis elegans is thought to encode a receptor which mediates cell-cell interactions required to specify certain cell fates. Reversion of the egg-laying defective phenotype caused by a hypomorphic lin-12 allele identified rare extragenic suppressor mutations in five genes, sel-1, sel-9, sel-10, sel-11 and sel(ar40) (sel = suppressor and/or enhancer of lin-12). Mutations in each of these sel genes suppress defects associated with reduced lin-12 activity, and enhance at least one defect associated with elevated lin-12 activity. None of the sel mutations cause any obvious phenotype in a wild-type background. Gene dosage experiments suggest that sel-1 and sel(ar40) mutations are reduction-of-function mutations, while sel-9 and sel-11 mutations are gain-of-function mutations. sel-1, sel-9, sel-11 and sel(ar40) mutations do not suppress amorphic lin-12 alleles, while sel-10 mutations are able to bypass partially the requirement for lin-12 activity in at least one cell fate decision. sel-1, sel-9, sel-10, sel-11 and sel(ar40) mutations are also able to suppress the maternal-effect lethality caused by a partial loss-of-function allele of glp-1, a gene that is both structurally and functionally related to lin-12. These sel genes may therefore function in both lin-12 and glp-1 mediated cell fate decisions.

scholarly journals Accessible chromatin reveals regulatory mechanisms underlying cell fate decisions during early embryogenesis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tongqiang Fan ◽  
Youjun Huang
Keyword(s):  
Cell Fate ◽  
Chromatin Accessibility ◽  
Early Embryogenesis ◽  
Regulatory Sequences ◽  
Cell Fate Decision ◽  
Joint Research ◽  
Cell Fate Decisions ◽  
Fate Decision ◽  
Multiple Species ◽  
Accessible Chromatin

AbstractThis study was conducted to investigate epigenetic landscape across multiple species and identify transcription factors (TFs) and their roles in controlling cell fate decision events during early embryogenesis. We made a comprehensively joint-research of chromatin accessibility of five species during embryogenesis by integration of ATAC-seq and RNA-seq datasets. Regulatory roles of candidate early embryonic TFs were investigated. Widespread accessible chromatin in early embryos overlapped with putative cis-regulatory sequences. Sets of cell-fate-determining TFs were identified. YOX1, a key cell cycle regulator, were found to homologous to clusters of TFs that are involved in neuron and epidermal cell-fate determination. Our research provides an intriguing insight into evolution of cell-fate decision during early embryogenesis among organisms.

scholarly journals Quantifying Waddington landscapes and paths of non-adiabatic cell fate decisions for differentiation, reprogramming and transdifferentiation

2013 ◽  
Vol 10 (89) ◽  
pp. 20130787 ◽  
Author(s):  
Chunhe Li ◽  
Jin Wang
Keyword(s):  
Decision Making ◽  
Stem Cell ◽  
Cell Fate ◽  
Intermediate State ◽  
Regulatory Networks ◽  
Experimental Studies ◽  
Cell Fate Decision ◽  
Cell Fate Decisions ◽  
Decision Making Processes ◽  
Fate Decision

Cellular differentiation, reprogramming and transdifferentiation are determined by underlying gene regulatory networks. Non-adiabatic regulation via slow binding/unbinding to the gene can be important in these cell fate decision-making processes. Based on a stem cell core gene network, we uncovered the stem cell developmental landscape. As the binding/unbinding speed decreases, the landscape topography changes from bistable attractors of stem and differentiated states to more attractors of stem and other different cell states as well as substates. Non-adiabaticity leads to more differentiated cell types and provides a natural explanation for the heterogeneity observed in the experiments. We quantified Waddington landscapes with two possible cell fate decision mechanisms by changing the regulation strength or regulation timescale (non-adiabaticity). Transition rates correlate with landscape topography through barrier heights between different states and quantitatively determine global stability. We found the optimal speeds of these cell fate decision-making processes. We quantified biological paths and predict that differentiation and reprogramming go through an intermediate state (IM1), whereas transdifferentiation goes through another intermediate state (IM2). Some predictions are confirmed by recent experimental studies.

scholarly journals Investigating higher order interactions in single cell data with scHOT

2019 ◽  
Author(s):  
Shila Ghazanfar ◽  
Yingxin Lin ◽  
Xianbin Su ◽  
David M. Lin ◽  
Ellis Patrick ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Expression Profiles ◽  
Order Effect ◽  
Higher Order ◽  
Cell Fate Decision ◽  
Cell Fate Decisions ◽  
Novel Approach ◽  
Fate Decision ◽  
Cell Data

ABSTRACTSingle-cell RNA-sequencing has transformed our ability to examine cell fate choice. For example, in the context of development and differentiation, computational ordering of cells along ‘pseudotime’ enables the expression profiles of individual genes, including key transcription factors, to be examined at fine scale temporal resolution. However, while cell fate decisions are typically marked by profound changes in expression, many such changes are observed in genes downstream of the initial cell fate decision. By contrast, the genes directly involved in the cell fate decision process are likely to interact in subtle ways, potentially resulting in observed changes in patterns of correlation and variation rather than mean expression prior to cell fate commitment. Herein, we describe a novel approach, scHOT – single cell Higher Order Testing - which provides a flexible and statistically robust framework for identifying changes in higher order interactions among genes. scHOT is general and modular in nature, can be run in multiple data contexts such as along a continuous trajectory, between discrete groups, and over spatial orientations; as well as accommodate any higher order measurement such as variability or correlation. We demonstrate the utility of scHOT by studying embryonic development of the liver, where we find coordinated changes in higher order interactions of programs related to differentiation and liver function. We also demonstrate its ability to find subtle changes in gene-gene correlation patterns across space using spatially-resolved expression data from the mouse olfactory bulb. scHOT meaningfully adds to first order effect testing, such as differential expression, and provides a framework for interrogating higher order interactions from single cell data.

scholarly journals Cell Fate Clusters in ICM Organoids Arise from Cell Fate Heredity & Division – a Modelling Approach

2019 ◽  
Author(s):  
Tim Liebisch ◽  
Armin Drusko ◽  
Biena Mathew ◽  
Ernst H. K. Stelzer ◽  
Sabine C. Fischer ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Cell Division ◽  
Cell Fate ◽  
Inner Cell Mass ◽  
Cell Mass ◽  
Cell Lineage ◽  
Cell Fate Decision ◽  
Agent Based ◽  
Cell Fate Decisions ◽  
Fate Decision

ABSTRACTDuring the mammalian preimplantation phase, cells undergo two subsequent cell fate decisions. During the first cell fate decision, cells become either part of an outer trophectoderm or part of the inner cell mass. Subsequently, the inner cell mass (ICM) segregates into an embryonic and an extraembryonic lineage, giving rise to the epiblast and the primitive endoderm, respectively. Inner cell mass organoids represent an experimental model system for preimplantation development, mimicking the second cell fate decision taking place in in vivo mouse embryos. In a previous study, the spatial pattern of the different cell lineage types was investigated. The study revealed that cells of the same fate tend to cluster stronger than expected for purely random cell fate decisions. Three major processes are hypothesised to contribute to the final cell fate arrangements at the mid and late blastocysts or 24 h old and 48 h old ICM organoids, respectively: 1) intra- and intercellular chemical signalling; 2) a cell sorting process; 3) cell proliferation. In order to quantify the influence of cell proliferation on the emergence of the observed cell lineage type clustering behaviour, we developed an agent-based model. Hereby, cells are mechanically interacting with direct neighbours, and exert adhesion and repulsion forces. The model was applied to compare several current assumptions of how inner cell mass neighbourhood structures are generated. We tested how different assumptions regarding cell fate switches affect the observed neighbourhood relationships. The model supports the hypothesis that initial cell fate acquisition is a stochastically driven process, taking place in the early development of inner cell mass organoids. The model further shows that the observed neighbourhood structures can emerge due to cell fate heredity during cell division and allows the inference of a time point for the cell fate decision.STATEMENT OF SIGNIFICANCECell fate decisions in early embryogenesis have been considered random events, causing a random cell fate distribution. Using an agent-based mathematical model, fitted to ICM organoid data, we show that the assumed random distribution of cell fates occurs only for a short time interval, as cell fate heredity and cell division quickly lead to spatial cell fate clustering. Our results show that neighbourhood clustering can emerge without specific neighbourhood interactions affecting the cell fate decision. The approach indicates four consecutive phases of early development: 1) co-expression of cell fate markers, 2) cell fate decision, 3) division and local cell fate clustering, and 4) phase separation, whereby only the phases 1-3 occur in ICM organoids during the first 24h of growth.

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