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1,127 results for “cell cycle”
Figure S3. Cell cycle phase distribution in MRT68921-treated MEC-1 cells
<p>MEC-1 cells (3 ×10<sup>5</sup> cells/mL) were treated with the vehicle control (0.1% DMSO) or 1 µM MRT68921 for 24 h. Cell cycle analysis was performed using flow cytometry. Data are means ±SEM of ≥3 independent experiments.</p>
Removing the effects of cell cycle genes data
<p>This data is used for the Galaxy Training Network tutorial 'Removing the effects of cell cycle genes'. It includes lists of cell cycle genes in mice and a dataset that is also used in the GTN tutorial 'Filter, Plot and Explore Single-cell RNA-seq Data'.</p> <p>The original dataset can be found here: Bacon, Wendi Anne. (2022). AnnData object for case study tutorials [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.7053673">https://doi.org/10.5281/zenodo.7053673</a> The version uploaded here has been processed according to the 'Filter, Plot and Explore Single-cell RNA-seq Data' tutorial up to the point of scaling the data. The data was published in Bacon, W. A., R. S. Hamilton, Z. Yu, J. Kieckbusch, D. Hawkes <em>et al.</em>, 2018 Single-Cell Analysis Identifies Thymic Maturation Delay in Growth-Restricted Neonatal Mice. Frontiers in Immunology 9: <a href="https://doi.org/10.3389/fimmu.2018.02523">10.3389/fimmu.2018.02523</a></p> <p>The cell cycle gene lists were obtained from the Harvard Chan School: Bioinformatics Core tinyatlas (2017) cell_cycle/Mus_musculus via GitHub:<a href="https://github.com/hbc/tinyatlas/blob/master/cell_cycle/Mus_musculus.csv"> https://github.com/hbc/tinyatlas/blob/master/cell_cycle/Mus_musculus.csv</a> </p> <p> </p>
Cell cycle heterogeneity in pancreatic ductal adenocarcinoma
<p>Multiplexed, single-cell imaging data for PDAC cell lines.</p>
Study of an Early Change of a Chemotherapeutic Doublet Versus Four Cycles of Chemotherapy in Advanced Non Small Cell Lung Cancer
ClinicalTrials.gov study NCT00199758. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Intensified 1st Cycle Rituximab Plus 8th Cycles of R-CHOP Chemotherapy in Patients With Advanced or Bulky CD20+ Diffuse Large B-cell Lymphoma (DLBCL)
ClinicalTrials.gov study NCT01054781. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Trial of 1 Cycle of Adjuvant BEP Chemotherapy in High Risk, Stage 1 Non-seminomatous Germ Cell Testis Tumours
ClinicalTrials.gov study NCT01726374. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Human Heterologous Liver Cells for Infusion in Children With Urea Cycle Disorders
ClinicalTrials.gov study NCT01195753. IPD Sharing: Not stated. Countries: 2. Publications: 1.
Data from: The non-coding RNA CcnA modulates the master cell cycle regulators CtrA and GcrA in Caulobacter crescentus
Open the record for dataset details and reuse information.
High throughput measurement of single HeLa cell volume growth and cell cycle progression using FXm
Open the record for dataset details and reuse information.
Data from: Cell cycle-dependent differentiation dynamics balances growth and endocrine differentiation in the pancreas
Organogenesis relies on the spatiotemporal balancing of differentiation and proliferation driven by an expanding pool of progenitor cells. In the mouse pancreas, lineage tracing at the population level has shown that the expanding pancreas progenitors can initially give rise to all endocrine, ductal, and acinar cells but become bipotent by embryonic day 13.5, giving rise to endocrine cells and ductal cells. However, the dynamics of individual progenitors balancing self-renewal and lineage-specific differentiation has never been described. Using three-dimensional live imaging and in vivo clonal analysis, we reveal the contribution of individual cells to the global behaviour and demonstrate three modes of progenitor divisions: symmetric renewing, symmetric endocrinogenic, and asymmetric generating a progenitor and an endocrine progenitor. Quantitative analysis shows that the endocrine differentiation process is consistent with a simple model of cell cycle–dependent stochastic priming of progenitors to endocrine fate. The findings provide insights to define control parameters to optimize the generation of β-cells in vitro.
Data from: A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells
Technological advances have enabled the analysis of cellular protein and RNA levels with unprecedented depth and sensitivity, allowing for an unbiased re-evaluation of gene regulation during fundamental biological processes. Here, we have chronicled the dynamics of protein and mRNA expression levels across a minimally perturbed cell cycle in human myeloid leukemia cells using centrifugal elutriation combined with mass spectrometry-based proteomics and RNA-Seq, avoiding artificial synchronization procedures. We identify myeloid-specific gene expression and variations in protein abundance, isoform expression and phosphorylation at different cell cycle stages. We dissect the relationship between protein and mRNA levels for both bulk gene expression and for over ∼6000 genes individually across the cell cycle, revealing complex, gene-specific patterns. This data set, one of the deepest surveys to date of gene expression in human cells, is presented in an online, searchable database, the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd/).
Data from: Synthesis of gypsogenin derivatives with capabilities to arrest cell cycle and induce apoptosis in human cancer cells
Thirty-two gypsogenin derivatives were synthesized and screened for their cytotoxic activities. Their structures were established using IR, 1H NMR, 13C NMR, and LC-MS spectroscopic data. In MTT assays nearly all the compounds displayed good cytotoxicity in the low μM range for several human tumour cell lines (A549, LOVO, SKOV3 and HepG2). Low IC50 values were obtained especially for the carboxamides 7a–7j, for an oxime derivative 3 and a (2,4-dinitrophenyl)hydrazono derivative 4. In particular, the IC50 values of compounds 4 (IC50 = 2.97 ± 1.13 µΜ) and 7 g (IC50 = 3.59 ± 2.04 µΜ) against LOVO cells were found to be much lower than those of the other derivatives and parent compound. These compounds were submitted to an extensive biological testing and proved compounds 4 and 7 g to act mainly by an arrest of the tumour cells in the S phase of the cell cycle. In addition, compounds 4 and 7 g triggered the apoptotic pathway in cancer cells, showing high apoptosis ratios.
Data from: SiSTL1, encoding a large subunit of ribonucleotide reductase, is crucial for plant growth, chloroplast biogenesis, and cell cycle progression in Setaria italica
The activity of ribonucleotide reductase (RNR), which catalyzes the transformation of four ribonucleoside diphosphates (NDPs) to their corresponding deoxyribonucleoside diphosphates (dNDPs), is the main determiner of the cellular concentration of dNTP pools and should be tightly coordinated with DNA synthesis and cell-cycle progression. Either constitutively increased or decreased RNR activity are indeed likely to interfere with DNA replication and lead to arrested cell cycle progression; however, the mechanisms underlying these disruptive effects in higher plants remain to be uncovered. In this study, we identified a RNR large subunit mutant, sistl1, in Setaria italica (foxtail millet), that exhibited growth retardation as well as striped leaf phenotype, i.e., irregularly reduced leaf vein distances and decreased chloroplast biogenesis. We determined that a Gly737 to Glu substitution occurrring in the C-terminus of the SiSTL1 protein slightly affected its optimal function, leading in turn to the reduced expression of genes variously involved in the assembly and activation of the DNA pre-replicative complex, elongation of replication forks and S phase entry. Our study provides new insight into how SiSTL1 regulates plant growth, chloroplast biogenesis, and cell cycle progression in Poaceae crops.
Data from: Screening of cytotoxic or cytostatic flavonoids with quantitative FUCCI-based cell cycle assay
The Fluorescence-Ubiquitin Cell Cycle Indicator (FUCCI) system can be used not only to study gene expression at a specific cell cycle stage, but also to monitor cell cycle transitions in real time. In this study, we used a single clone of FUCCI-expressing HeLa cells (FUCCI-HeLa cells) and monitored the cell cycle in individual live cells over time by determining the ratios between red fluorescence (RF) of RFP-Cdt1 and green fluorescence (GF) of GFP-Geminin. Cytotoxic and cytostatic compounds, the latter of which induced G2 or mitotic arrest, were identified based on periodic cycling of the RF/GF and GF/RF ratios in FUCCI-HeLa cells treated with anticancer drugs. With this cell cycle monitoring system, ten flavonoids were screened. Of these, apigenin and luteolin, which have a flavone backbone, were cytotoxic, whereas kaempferol, which has a flavonol backbone, was cytostatic and induced G2 arrest. In summary, we developed a system to quantitatively monitor the cell cycle in real time. This system can be used to identify novel compounds that modulate the cell cycle and to investigate structure–activity relationships.
Data from: Effects of cell-cycle-dependent expression on random fluctuations in protein levels
Expression of many genes varies as a cell transitions through different cell-cycle stages. How coupling between stochastic expression and cell cycle impacts cell-to-cell variability (noise) in the level of protein is not well understood. We analyse a model where a stable protein is synthesized in random bursts, and the frequency with which bursts occur varies within the cell cycle. Formulae quantifying the extent of fluctuations in the protein copy number are derived and decomposed into components arising from the cell cycle and stochastic processes. The latter stochastic component represents contributions from bursty expression and errors incurred during partitioning of molecules between daughter cells. These formulae reveal an interesting trade-off: cell-cycle dependencies that amplify the noise contribution from bursty expression also attenuate the contribution from partitioning errors. We investigate the existence of optimum strategies for coupling expression to the cell cycle that minimize the stochastic component. Intriguingly, results show that a zero production rate throughout the cell cycle, with expression only occurring just before cell division, minimizes noise from bursty expression for a fixed mean protein level. By contrast, the optimal strategy in the case of partitioning errors is to make the protein just after cell division. We provide examples of regulatory proteins that are expressed only towards the end of the cell cycle, and argue that such strategies enhance robustness of cell-cycle decisions to the intrinsic stochasticity of gene expression.
Data from: Transcriptome and proteome dynamics of a light-dark synchronized bacterial cell cycle
BACKGROUND: Growth of the ocean's most abundant primary producer, the cyanobacterium Prochlorococcus, is tightly synchronized to the natural 24-hour light-dark cycle. We sought to quantify the relationship between transcriptome and proteome dynamics that underlie this obligate photoautotroph's highly choreographed response to the daily oscillation in energy supply. METHODOLOGY/PRINCIPAL FINDINGS: Using Illumina RNA-sequencing transcriptomics and mass spectrometry-based quantitative proteomics, we measured timecourses of paired mRNA-protein abundances for 312 genes every 2 hours over a light-dark cycle. These temporal expression patterns reveal strong oscillations in transcript abundance that are broadly damped at the protein level, with mRNA levels varying on average 2.3 times more than the corresponding protein. The single strongest observed protein-level oscillation is in a ribonucleotide reductase, which may reflect a defense strategy against phage infection. The peak in abundance of most proteins also lags that of their transcript by 2-8 hours, and the two are completely antiphase for some genes. While abundant antisense RNA was detected, it apparently does not account for the observed divergences between expression levels. The redirection of flux through central carbon metabolism from daytime carbon fixation to nighttime respiration is associated with quite small changes in relative enzyme abundances. CONCLUSIONS/SIGNIFICANCE: Our results indicate that expression responses to periodic stimuli that are common in natural ecosystems (such as the diel cycle) can diverge significantly between the mRNA and protein levels. Protein expression patterns that are distinct from those of cognate mRNA have implications for the interpretation of transcriptome and metatranscriptome data in terms of cellular metabolism and its biogeochemical impact.
Supplementary data for Life-cycle assessment shows that retrofitting coal-fired power plants with fuel cells will substantially reduce greenhouse gas emissions
<p>This dataset contains supplementary data for "Life-cycle assessment shows that retrofitting coal-fired power plants with fuel cells will substantially reduce greenhouse gas emissions" DOI: <strong>10.1016/j.oneear.2022.03.009</strong>.</p> <p>S1-S10 contains life-cycle inventories of solid oxide fuel cells, molten carbonate fuel cells, phosphoric acid fuel cells, and proton exchange membrane fuel cells with either natural gas or wind-electrolysis hydrogen as a feedstock.</p> <p>S11-S13 contains technological information of coal-fired power plants in China</p>
Cell cycle
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CALIPERS: Cell cycle-aware live imaging for phenotyping experiments and regeneration studies
<p><strong>Abstract:</strong></p> <p>We introduce CALIPERS, a Fluorescence Ubiquitin Cell Cycle Indicator enabling cell cycle-aware phenotyping based on multiplexed live-cell imaging. We validate CALIPERS in three- and four-color reporter lines (HaCaT) and human induced pluripotent stem cells (WTC-11), co-expressing genetically encoded structural and functional fluorescent sensors. To exemplify the broad applications of CALIPERS, we show cell cycle-aware phenotyping in live-cell imaging applications ranging from proliferation and migration to cardiac-specific maturation and drug testing.</p> <p>Code submission: <a href="https://github.com/alessandro-bertero/FUCCIplex">https://github.com/alessandro-bertero/FUCCIplex.git</a></p> <p><strong>Dataset description:</strong></p> <ol> <li>This dataset includes all data and the additional files to recreate the sc-RNAseq analysis in our manuscript. The Rmd files include the Seurat QC pipeline to preprocess the counts data from cellranger (<strong>QC_Seurat_gitgub_polished.RmD</strong>) and the monocle pipeline to re-create the clusters and pseudotime analysis (<strong>monocle_github_polished.Rmd</strong>).</li> <li><strong>Data obtained from Cellranger 7.2 pipeline</strong> are also available here including all the 3 files, usually placed in the path "outs/count/filtered_feature_bc_matrix" by cellrancer. This includes: <strong>barcodes.tsv.gz, features.tsv.gz and matrix.mtx.gz</strong> (alternatively the h5 file filtered_feature_bc_matrix.h5 can be loaded directly in Seurat v5).</li> <li>We also added few RData files to recreate our graphs and follow our pipeline smoothly. <strong>240111_seurat_before_clean.RData, 240111_seurat_clean.RData</strong> and <strong>240111_seurat_processed.RData</strong> are the files created by the codes in QC_Seurat_gitgub_polished.RmD pipeline. Then, <strong>240118_monocle_cds_clustered_proteincoding_PSEUDOTIME_clean_gene_info.RData</strong> is the file set created by the<strong> </strong>monocle_github_polished.Rmd pipeline.</li> </ol> <p>We also suggest to use this pipeline within a docker container by pulling our docker image with R studio:</p> <p><strong>docker pull hedgelab/rstudio-hedgelab:latest</strong></p>
Heat oscillations driven by the embryonic cell cycle reveal the energetic costs of signaling
<p>R scripts and calorimetry data used and generated in "Heat oscillations driven by the embryonic cell cycle reveal the energetic costs of signaling" by Rodenfels <em>et al. </em></p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.