Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Trajectories of cell-cycle progression from fixed cell populations.

ABSTRACT: An accurate dissection of sources of cell-to-cell variability is crucial for quantitative biology at the single-cell level but has been challenging for the cell cycle. We present Cycler, a robust method that constructs a continuous trajectory of cell-cycle progression from images of fixed cells. Cycler handles heterogeneous microenvironments and does not require perturbations or genetic markers, making it generally applicable to quantifying multiple sources of cell-to-cell variability in mammalian cells.

SUBMITTER: Gut G

PROVIDER: S-EPMC6004611 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Trajectories of cell-cycle progression from fixed cell populations.

Gut Gabriele G Tadmor Michelle D MD Pe'er Dana D Pelkmans Lucas L Liberali Prisca P

Nature methods 20150824 10

An accurate dissection of sources of cell-to-cell variability is crucial for quantitative biology at the single-cell level but has been challenging for the cell cycle. We present Cycler, a robust method that constructs a continuous trajectory of cell-cycle progression from images of fixed cells. Cycler handles heterogeneous microenvironments and does not require perturbations or genetic markers, making it generally applicable to quantifying multiple sources of cell-to-cell variability in mammali ...[more]

PMID: 26301842

Similar Datasets

TCM visualizes trajectories and cell populations from single cell data.

Project description:Profiling single cell gene expression data over specified time periods are increasingly applied to the study of complex developmental processes. Here, we describe a novel prototype-based dimension reduction method to visualize high throughput temporal expression data for single cell analyses. Our software preserves the global developmental trajectories over a specified time course, and it also identifies subpopulations of cells within each time point demonstrating superior visualization performance over six commonly used methods.

| S-EPMC6048168 | biostudies-literature

Dynamics extracted from fixed cells reveal feedback linking cell growth to cell cycle.

Project description:Biologists have long been concerned about what constrains variation in cell size, but progress in this field has been slow and stymied by experimental limitations. Here we describe a new method, ergodic rate analysis (ERA), that uses single-cell measurements of fixed steady-state populations to accurately infer the rates of molecular events, including rates of cell growth. ERA exploits the fact that the number of cells in a particular state is related to the average transit time through that state. With this method, it is possible to calculate full time trajectories of any feature that can be labelled in fixed cells, for example levels of phosphoproteins or total cellular mass. Using ERA we find evidence for a size-discriminatory process at the G1/S transition that acts to decrease cell-to-cell size variation.

| S-EPMC3730528 | biostudies-literature

A map of protein dynamics during cell-cycle progression and cell-cycle exit

Project description: Not available

| S-BSST21 | biostudies-other

A map of protein dynamics during cell-cycle progression and cell-cycle exit.

Project description:The cell-cycle field has identified the core regulators that drive the cell cycle, but we do not have a clear map of the dynamics of these regulators during cell-cycle progression versus cell-cycle exit. Here we use single-cell time-lapse microscopy of Cyclin-Dependent Kinase 2 (CDK2) activity followed by endpoint immunofluorescence and computational cell synchronization to determine the temporal dynamics of key cell-cycle proteins in asynchronously cycling human cells. We identify several unexpected patterns for core cell-cycle proteins in actively proliferating (CDK2-increasing) versus spontaneously quiescent (CDK2-low) cells, including Cyclin D1, the levels of which we find to be higher in spontaneously quiescent versus proliferating cells. We also identify proteins with concentrations that steadily increase or decrease the longer cells are in quiescence, suggesting the existence of a continuum of quiescence depths. Our single-cell measurements thus provide a rich resource for the field by characterizing protein dynamics during proliferation versus quiescence.

| S-EPMC5608403 | biostudies-literature

Cortical branched actin determines cell cycle progression.

Project description:The actin cytoskeleton generates and senses forces. Here we report that branched actin networks from the cell cortex depend on ARPC1B-containing Arp2/3 complexes and that they are specifically monitored by type I coronins to control cell cycle progression in mammary epithelial cells. Cortical ARPC1B-dependent branched actin networks are regulated by the RAC1/WAVE/ARPIN pathway and drive lamellipodial protrusions. Accordingly, we uncover that the duration of the G1 phase scales with migration persistence in single migrating cells. Moreover, cortical branched actin more generally determines S-phase entry by integrating soluble stimuli such as growth factors and mechanotransduction signals, ensuing from substratum rigidity or stretching of epithelial monolayers. Many tumour cells lose this dependence for cortical branched actin. But the RAC1-transformed tumour cells stop cycling upon Arp2/3 inhibition. Among all genes encoding Arp2/3 subunits, ARPC1B overexpression in tumours is associated with the poorest metastasis-free survival in breast cancer patients. Arp2/3 specificity may thus provide diagnostic and therapeutic opportunities in cancer.

| S-EPMC6796858 | biostudies-literature

Lactobacillus decelerates cervical epithelial cell cycle progression.

Project description:We investigated cell cycle progression in epithelial cervical ME-180 cells during colonization of three different Lactobacillus species utilizing live cell microscopy, bromodeoxyuridine incorporation assays, and flow cytometry. The colonization of these ME-180 cells by L. rhamnosus and L. reuteri, originating from human gastric epithelia and saliva, respectively, was shown to reduce cell cycle progression and to cause host cells to accumulate in the G1 phase of the cell cycle. The G1 phase accumulation in L. rhamnosus-colonized cells was accompanied by the up-regulation and nuclear accumulation of p21. By contrast, the vaginal isolate L. crispatus did not affect cell cycle progression. Furthermore, both the supernatants from the lactic acid-producing L. rhamnosus colonies and lactic acid added to cell culture media were able to reduce the proliferation of ME-180 cells. In this study, we reveal the diversity of the Lactobacillus species to affect host cell cycle progression and demonstrate that L. rhamnosus and L. reuteri exert anti-proliferative effects on human cervical carcinoma cells.

| S-EPMC3651132 | biostudies-literature

Mapping metabolic oscillations during cell cycle progression.

Project description:Proliferating cells must synthesize a wide variety of macromolecules while progressing through the cell cycle, but the coordination between cell cycle progression and cellular metabolism is still poorly understood. To identify metabolic processes that oscillate over the cell cycle, we performed comprehensive, non-targeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) based metabolomics of HeLa cells isolated in the G1 and SG2M cell cycle phases, capturing thousands of diverse metabolite ions. When accounting for increased total metabolite abundance due to cell growth throughout the cell cycle, 18% of the observed LC-HRMS peaks were at least twofold different between the stages, consistent with broad metabolic remodeling throughout the cell cycle. While most amino acids, phospholipids, and total ribonucleotides were constant across cell cycle phases, consistent with the view that total macromolecule synthesis does not vary across the cell cycle, certain metabolites were oscillating. For example, ribonucleotides were highly phosphorylated in SG2M, indicating an increase in energy charge, and several phosphatidylinositols were more abundant in G1, possibly indicating altered membrane lipid signaling. Within carbohydrate metabolism, pentose phosphates and methylglyoxal metabolites were associated with the cycle. Interestingly, hundreds of yet uncharacterized metabolites similarly oscillated between cell cycle phases, suggesting previously unknown metabolic activities that may be synchronized with cell cycle progression, providing an important resource for future studies.

| S-EPMC7644150 | biostudies-literature

mRNA-binding proteins and cell cycle progression.

Project description:Proteins that bind to each mRNA may affect the latter's abundance and location in the cell and how well ribosomes will translate that mRNA into a protein. Hence, mRNA-binding proteins (mRBPs) represent obvious control points in gene expression. Surprisingly, little is known about mRBPs and cell-cycle progression.

| S-EPMC9933138 | biostudies-literature

System-level feedbacks control cell cycle progression.

Project description:Repetitive cell cycles, which are essential to the perpetuation of life, are orchestrated by an underlying biochemical reaction network centered around cyclin-dependent protein kinases (Cdks) and their regulatory subunits (cyclins). Oscillations of Cdk1/CycB activity between low and high levels during the cycle trigger DNA replication and mitosis in the correct order. Based on computational modeling, we proposed that the low and the high kinase activity states are alternative stable steady states of a bistable Cdk-control system. Bistability is a consequence of system-level feedback (positive and double-negative feedback signals) in the underlying control system. We have also argued that bistability underlies irreversible transitions between low and high Cdk activity states and thereby ensures directionality of cell cycle progression.

| S-EPMC3811919 | biostudies-literature

Mir-33 regulates cell proliferation and cell cycle progression.

Project description:Cholesterol metabolism is tightly regulated at the cellular level and is essential for cellular growth. microRNAs (miRNAs), a class of noncoding RNAs, have emerged as critical regulators of gene expression, acting predominantly at posttranscriptional level. Recent work from our group and others has shown that hsa-miR-33a and hsa-miR-33b, miRNAs located within intronic sequences of the Srebp genes, regulate cholesterol and fatty acid metabolism in concert with their host genes. Here, we show that hsa-miR-33 family members modulate the expression of genes involved in cell cycle regulation and cell proliferation. MiR-33 inhibits the expression of the cyclin-dependent kinase 6 (CDK6) and cyclin D1 (CCND1), thereby reducing cell proliferation and cell cycle progression. Overexpression of miR-33 induces a significant G 1 cell cycle arrest in Huh7 and A549 cell lines. Most importantly, inhibition of miR-33 expression using 2'fluoro/methoxyethyl-modified (2'F/MOE-modified) phosphorothioate backbone antisense oligonucleotides improves liver regeneration after partial hepatectomy (PH) in mice, suggesting an important role for miR-33 in regulating hepatocyte proliferation during liver regeneration. Altogether, these results suggest that Srebp/miR-33 locus may cooperate to regulate cell proliferation, cell cycle progression and may also be relevant to human liver regeneration.

| S-EPMC3323796 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data