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1,036 results for “Cell mechanics”
Decoding NY-ESO-1 TCR T Cells: Transcriptomic Insights Reveal Dual Mechanisms of Tumor Targeting in a Melanoma Murine Xenograft Model
<p><span>Single-cell RNA-seq data of NY-ESO-1-specific TCR T-cells generated with the BD Rhapsody™ system.</span></p> <p><span>Biogroup information: Control (<em>n</em><span> </span>= 4), PB (murine peripheral blood, <em>n</em><span> </span>= 4).</span></p> <p><span>Cell preparation: NY-ESO-1-specific TCR T-cells were obtained via a retroviral transduction of an anti-NY-ESO-1-TCR construct, murine peripheral blood T-cells were enriched using anti-CD3 magnetic separation via MojoSortTM Human CD3 Selection Kit.</span></p> <p><span>Single-cell analysis system: BD Rhapsody™</span></p> <p><span>Library strategy: 3' mRNA sequencing</span></p> <p><span>Library preparation protocol: BD Rhapsody™ Targeted mRNA and Sample Tag Library Preparation</span></p> <p><span>mRNA panel: BD Rhapsody™ Immune Response Panel HS</span></p> <p><span>BD Pipeline version: 1.11L</span></p>
Single-cell profiling reveals immune-based mechanisms underlying tumor radiosensitization by a novel Mn porphyrin clinical candidate, MnTnBuOE-2-PyP5+ (BMX-001)
Open the record for dataset details and reuse information.
Population-based computational simulations elucidate mechanisms of focal arrhythmia following stem cell injection
Open the record for dataset details and reuse information.
Gigantic animal cells suggest organellar scaling mechanisms across a 50-fold range in cell volume
<p>Across the tree of life, cell size varies by orders of magnitude, and organelles scale to maintain cell function. Depending on their shape, organelles can scale by increasing volume, length, or number. Scaling may also reflect demands placed on organelles by increased cell size. The 8,653 species of amphibians exhibit diverse cell sizes, providing a powerful system to investigate organellar scaling. Using transmission electron microscopy and stereology, we analyzed three frog and salamander species whose enterocyte cell volumes range from 228 to 10,593 μm3. We show that the nucleus increases in radius while the mitochondria increase in total network length; the endoplasmic reticulum and Golgi apparatus, with their complex shapes, are intermediate. Notably, all four organelles increase in volume proportionate to cell volume. This pattern suggests that protein concentrations are the same across amphibian species that differ 50-fold in cell size, and that organellar building blocks are incorporated into more or larger organelles following the same "rules" across cell sizes, despite variation in metabolic and transport demands. This conclusion contradicts results from experimental cell size increases, which produce severe proteome dilution. We hypothesize that salamanders have evolved the biosynthetic capacity to maintain a functional proteome despite a huge cell volume. </p>
Dataset for the publication titlted "A computational mechanics model for producing molecular assembly using molecularly woven pantographs" in the journal Cell Reports Physical Science, authored by Byeonghwa Goh and Joonmyung Choi.
<p>Dataset for the publication titlted "A computational mechanics model for producing molecular assembly using molecularly woven pantographs" in the journal Cell Reports Physical Science, authored by Byeonghwa Goh and Joonmyung Choi.</p>
Data from: ESCRT-III-dependent adhesive and mechanical changes are triggered by a mechanism detecting alteration of Septate Junction integrity in Drosophila epithelial cells
<p><span>Barrier functions of proliferative epithelia are constantly challenged by mechanical and chemical constraints. How epithelia respond to and cope with disturbances of barrier functions to allow tissue integrity maintenance is poorly characterized. Cellular junctions play an important role in this process and intracellular traffic contribute to their homeostasis. Here, we reveal that, in <em>Drosophila</em> pupal <em>notum</em>, alteration of the bi- or tricellular septate junctions (SJs) triggers a mechanism with two prominent outcomes. On one hand, there is an increase in the levels of E-cadherin, F-Actin and non-muscle Myosin II in the plane of adherens junctions. On </span><span>the other hand, β-integrin/Vinculin-positive cell contacts are reinforced along the lateral and basal membranes. We found that the weakening of SJ integrity, caused by the depletion of bi- or tricellular SJ components, alters ESCRT-III/Vps32/Shrub distribution, reduces degradation, and instead favours recycling of SJ components, an effect that extends to other recycled transmembrane protein cargoes including Crumbs, its effector β-Heavy Spectrin</span><span> Karst, and </span><span>β-integrin</span><span>. We propose a mechanism by which epithelial cells, upon sensing alterations of the septate junction</span><span>,</span><span> reroute the function of Shrub to adjust the balance of degradation/recycling of junctional cargoes and thereby compensate for barrier junction defects to maintain epithelial integrity.</span></p>
Results of the mechanical characterization by tensile tests and the in vitro cell-biomaterial interaction analyses by WST-1 and Live/Dead of 3D-printed scaffolds generated by PLA, PCL, FF, FD and GelMA
<p>Dataset containing the quantitative results of the mechanical characterization, and the in vitro cell-biomaterial interaction analyses with neural cells after 72 hours and 7 days of cell culture of the following 3D printed scaffolds:</p> <ul> <li>Polylactic acid (PLA)</li> <li>Polycaprolactone (PCL)</li> <li>Conductive Filaflex (FF)</li> <li>Flexdym (FD)</li> <li>GelMA (G)</li> </ul> <p>The Live/Dead results were quantified using ImageJ software to determine area fractions corresponding to live (green) and dead (red) cells.</p>
Supplementary Data for "Epigenetic mechanisms controlling human leukemia stem cells and therapy resistance"
<p><strong>We performed functional genomic profiling of diverse leukemias using label tracing techniques. We identified AML stem cell quiescence is defined by distinct promoter-centered chromatin and gene expression dynamics, and controlled by a novel transcription factor network, which is associated with disease persistence and chemotherapy resistance in multiple patients. </strong></p>
Data for: Molecular mechanisms behind safranal's toxicity to liver cancer cells from dual omics
<p>The spice saffron (<em>Crocus sativus</em>) has anticancer activity in several human tissues, but the molecular mechanisms underlying potential therapeutic effects are poorly understood. We investigated the impact of safranal, a small molecule secondary metabolite from saffron, on the HCC cell line HEP-G2 using untargeted metabolomics (HPLC-MS) and transcriptomics (RNAseq). Increases in glutathione disulfide and other biomarkers for oxidative damage contrasted with lower levels of the antioxidants biliverdin IX (139-fold decrease, p=5.3E-5), the ubiquinol precursor 3-4-dihydroxy-5-all-trans-decaprenylbenzoate (3-fold decrease, p=1.9E-5), and resolvin E1 (-3,282-fold decrease, p=4E-5), which indicates sensitization to reactive oxygen species. We observed a significant increase in intracellular hypoxanthine (538-fold increase, p=7.7E-6) that may be primarily responsible for oxidative damage in HCC after safranal treatment. The accumulation of free fatty acids and other biomarkers, such as S-methyl-5'-thioadenosine, are consistent with safranal-induced mitochondrial de-uncoupling and explain the sharp increase in hypoxanthine we observed. Overall, the dual omics datasets describe routes to widespread protein destabilization and DNA damage from safranal-induced oxidative stress in HCC cells.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (8/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (14/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (7/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (9/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (12/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (11/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (13/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (16/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
A B cell actomyosin arc network couples integrin co-stimulation to mechanical force-dependent immune synapse formation
<p>B-cell activation and immune synapse (IS) formation with membrane-bound antigens are actin-dependent processes that scale positively with the strength of antigen-induced signals. Importantly, ligating the B-cell integrin, LFA-1, with ICAM-1 promotes IS formation when antigen is limiting. Whether the actin cytoskeleton plays a specific role in integrin-dependent IS formation is unknown. Here we show using super-resolution imaging of mouse primary B cells that LFA-1: ICAM-1 interactions promote the formation of an actomyosin network that dominates the B-cell IS. This network is created by the formin mDia1, organized into concentric, contractile arcs by myosin 2A, and flows inward at the same rate as B-cell receptor (BCR): antigen clusters. Consistently, individual BCR microclusters are swept inward by individual actomyosin arcs. Under conditions where integrin is required for synapse formation, inhibiting myosin impairs synapse formation, as evidenced by reduced antigen centralization, diminished BCR signaling, and defective signaling protein distribution at the synapse. Together, these results argue that a contractile actomyosin arc network plays a key role in the mechanism by which LFA-1 co-stimulation promotes B-cell activation and IS formation.</p>
Additional movies for a manuscript titled 'Leaf epidermal cells respond to application and removal of mechanical force by distinct cytosolic calcium waves'
<p>This repository provides 21 additional videos that highlight the spectrum of mechanically stimulated calcium responses observed in the leaf epidermis of <em>Arabidopsis t</em>. expressing the genetically encoded calcium indicator R-GECO1. These movies correspond to figures in a manuscript entitled 'Leaf epidermal cells respond to application and removal of mechanical force by distinct cytosolic calcium waves'. In each movie, a cantilever exerts approximately 5 mN force to the epidermis (where the cantilever looks like a shadow in the movies). Each movie contains a scale bar and the relative time (hr:min:sec). Placement of the cantilever generally occurs after approximately 1 minute.</p>
Unveiling the Mechanisms of Solid-State Dewetting in Solid Oxide Cells with Novel 2D Electrodes
<p>Supporting videos as a part of the Supplementary Material of the paper published by the Journal of Power Sources, Volume 420, 30 April 2019, Pages 124-133 doi: 10.1016/j.jpowsour.2019.02.068</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.