Dataset Open Access

# Experimental data for "Spot-On: robust model-based analysis of single-particle tracking experiments"

Anders Sejr Hansen; Maxime Woringer; Jonathan B Grimm; Luke D Lavis; Robert Tjian; Xavier Darzacq

### JSON-LD (schema.org) Export

{
"description": "<p><strong>Overview of experimental spaSPT data</strong></p>\n\n<p>To comprehensively test Spot-On over many different conditions, we conducted 1064 spaSPT experiments. The raw data is freely available and the purpose of this ReadMe file is to describe the organization, acquisition parameters and format of the data. The data is for 4 different cell lines imaged over 15 different conditions yielding a total of 60 different conditions. The four cell lines were:</p>\n\n<ul>\n\t<li>\n\t<p>U2OS C32 Halo-CTCF</p>\n\t</li>\n\t<li>\n\t<p>U2OS H2B-Halo-SNAP</p>\n\t</li>\n\t<li>\n\t<p>U2OS Halo-3xNLS</p>\n\t</li>\n\t<li>\n\t<p>mESC (JM8.N4) C3 Halo-Sox2</p>\n\t</li>\n</ul>\n\n<p>The cell lines were constructed in different ways. U2OS C32 Halo-CTCF was made by homozygous endogenous N-terminal tagging of CTCF in human osteosarcoma U2OS cells using CRISPR/Cas9-mediated genome-editing as described (C32 refers to clone number 32)<sup>1</sup>. We note the CTCF is an essential gene and that N-terminal tagging did not appear to affect CTCF function or expression level according to a series of control experiments<sup>1</sup>. Moreover, C32 Halo-CTCF has been authenticated using Short Tandem Repeat (STR) profiling (performed by Dr. Alison N. Killilea at the UC Berkeley Cell Culture Facility) against the following loci: THO1, D5S818, D13S317, D7S820, D16S539, CSF1PO, AMEL, vWA and TPOX. The C32 Halo-CTCF cell line showed a 100% match with U2OS.</p>\n\n<p>U2OS H2B-Halo-SNAP was made through random integration of a H2B-HaloTag-SNAP-Tag transgene expressed using the EF1a promoter with an IRES-NeoR gene for drug selection. After transfection, cells were selected using G418 until a pure cell population was obtained. This cell line has also been described previously<sup>1</sup>. The wild-type U2OS cell line used to make this cell line was also authenticated using STR profiling against the same loci as C32 and also showed a 100% match with U2OS.</p>\n\n<p>U2OS Halo-3xNLS was made through random integration of a FLAG-Halo-3xNLS (3x SV40 NLS: PKKKRKV) transgene expressed using the EF1a promoter. NeoR for drug selection was separately expressed using an SV40 promoter. After transfection, cells were selected using G418 until a pure cell population was obtained. This cell line has also been described previously<sup>1</sup>. The wild-type U2OS cell line used to make this cell line was also authenticated using STR profiling against the same loci as C32 and also showed a 100% match with U2OS.</p>\n\n<p>mESC C3 Halo-Sox2 was made through homozygous N-terminal tagging of Sox2 in JM8.N4<sup>2</sup> mouse embryonic stem cells using CRISPR/Cas9-mediated genome editing as previously described (C3 refers to clone number 3)<sup>3</sup>. The functionality of the C3 Halo-Sox2 knock-in was validated through control experiments and pluripotency through teratoma assays as described previously<sup>3</sup>.</p>\n\n<p>Each file contains single-molecule trajectories from a single cell imaged over 30,000 frames. Localization and tracking was performed using a custom-written Matlab implementation of the MTT-algorithm<sup>4</sup> and the following settings: Localization error: 10<sup>-6.25</sup>; deflation loops: 0; Blinking (frames): 1; max competitors: 3; max <em>D</em> (\uf06dm<sup>2</sup>/s): 20.</p>\n\n<p>The same 15 conditions were used for each of the 4 cell lines.</p>\n\n<p><strong>ExpA PA-JF549</strong></p>\n\n<p>The purpose of this experiment was to test the effect of \u201cmotion-blurring\u201d on the Spot-On estimated <em>D</em><sub>FREE</sub> and <em>F</em><sub>BOUND</sub>. 5 different experimental conditions were considered. Full details are given in the Methods section. Briefly, cells were grown overnight on plasma-cleaned 25 mm circular coverslips either directly (U2OS) and MatriGel coated as described<sup>1</sup>. Cell were labeled with 5-50 nM PA-JF549<sup>5</sup> for around 15-30 min, washed twice and medium exchanged to phenol-red free medium. 30,000 frames were collected at a camera exposure time (Andor iXon Ultra 897; frame-transfer mode; vertical shift speed: 0.9 \u03bcs; -70\uf0b0C) of 9.5 ms which together with a ~447 \u03bcs camera integration time gave a frame rate of ~100 Hz. PA-JF549 dyes were photo-activated during the ~447 \u03bcs camera integration time using 405 nm pulses and the 405 nm pulse intensity optimized to achieve a mean density of \uf0a31 molecule per frame per nucleus. The JF549 dye was excited using a 561 nm laser and the total number of excitation photons kept constant but either delivered during a 1 ms pulse, a 2 ms pulse, a 4 ms pulse, a 7 ms pulse or with constant illumination.</p>\n\n<p>For each cell line and condition, 4 replicates were performed. We count a replicate as an independent experiment performed on a different day. For each replicate around 5 cells were imaged. Occasionally, fewer than 5 cells are available. To avoid tracking errors, we removed cells with too high a localization density from the analysis. All of this information is available in the file name. For example, \u201cU2OS_C32_Halo-CTCF_PA-JF549_1ms-561nm_100Hz_rep2_cell03\u201d refers to the third cell imaged in the second replicate of U2OS C32 Halo-CTCF using a 1 ms excitation pulse of 561 nm laser at a frame rate of 100 Hz. Similarly, \u201cU2OS_C32_Halo-CTCF_PA-JF549_cont-561nm_100Hz_rep4_cell01\u201d refers to the first cell imaged in the fourth replicate of U2OS C32 Halo-CTCF using constant 561 nm laser at a frame rate of 100 Hz.</p>\n\n<p>The five ExpA_PAJF549 conditions are separated by cell line such that each cell line is provided in a separate directory. E.g. the directory \u201cU2OS_H2B_ExpA_PAJF549\u201d contains all data for the U2OS H2B-Halo-SNAP cell line.</p>\n\n<p><strong>ExpA PA-JF646</strong></p>\n\n<p>This experiment was exactly identical to the \u201cExpA_PA-JF549\u201d experiment except cell were labeled with PA-JF646<sup>5</sup> and excited using a 633 nm laser. The file names and data organization was otherwise the same and the same five excitation conditions were considered.</p>\n\n<p><strong>ExpB PA-JF646</strong></p>\n\n<p>The purpose of this experiment was to test if the Spot-On estimated <em>D</em><sub>FREE</sub> and <em>F</em><sub>BOUND</sub> values would depend on the frame rate. In particular, all four proteins exhibit some levels of apparent anomalous diffusion, which could cause a dependence on the frame rate. Cells were labeled with PA-JF646 and grown and imaged as described above. Photo-activation took place during the ~447 \u03bcs camera integration time and JF646 dyes were excited using 1 ms stroboscopic 633 nm excitation pulses. To change the frame rate, the camera exposure time was set to 4.5 ms (~201 Hz), 5.5 ms (~167 Hz), 7 ms (~134 Hz), 13 ms (~74 Hz) and 19.5 ms (~50 Hz) when also counting the ~447 \u03bcs camera integration time. All of this information is available in the file name. For example, \u201cU2OS_Halo-3xNLS_PA-JF646_1ms-633nm_74Hz_rep2_cell04\u201d refers to the fourth cell imaged in the second replicate of U2OS Halo-3xNLS using a 1 ms excitation pulse of 633 nm laser at a frame rate of 74 Hz. Similarly, \u201cmESC_C3_Halo-Sox2_PA-JF646_1ms-633nm_201Hz_rep1_cell03\u201d refers to the third cell imaged in the first replicate of mESC Halo-Sox2 using a 1 ms excitation pulse of 633 nm laser at a frame rate of 201 Hz.</p>\n\n<p><strong>Data format</strong></p>\n\n<p>All data is available in two different formats: CSV-files and Matlab MAT-files. Both file formats are readable by the web-version of Spot-On. The Matlab version of Spot-On is only able to read the MAT-files. The CSV format consists of comma-separated values and contains headers. If opened with Microsoft Excel, it should appear as shown:</p>\n\n<p>Here the \u201cframe\u201d column contains the frame number in which the molecule was detected. The \u201ct\u201d column contains the timestamp. The \u201ctrajectory\u201d column contains the trajectory number. For example, trajectory number 1 was only detected in frame 13 after which it disappeared. In contrast, trajectory number 4 was detected in frames 20, 21 22, 23 and 24. Finally, the \u201cx\u201d and \u201cy\u201d columns contain the x,y coordinates of the localization in units of micrometers (\u03bcm).</p>\n\n<p>The MAT-files contain a structure array named \u201ctrackedPar\u201d. trackedPar contains three variables:</p>\n\n<ul>\n\t<li>\n\t<p>trackedPar.xy: \u201cxy\u201d is a matrix with 2 columns and a number of rows corresponding to the number of localizations in that trajectory. The first column is the x-coordinate and the second column is the y-coordinate. The units are micrometers (\u03bcm).</p>\n\t</li>\n\t<li>\n\t<p>trackedPar.Frame: \u201cFrame\u201d is a column vector where each element is the frame where the particle was localized.</p>\n\t</li>\n\t<li>\n\t<p>trackedPar.TimeStamp: \u201cTimeStamp\u201d is a column vector where each element is the timepoint where the particle was localized.</p>\n\t</li>\n</ul>\n\n<p>Each element in the structure array \u201ctrackedPar\u201d correspond to a different trajectory.</p>",
"creator": [
{
"affiliation": "Howard Hughes Medical Institute, Berkeley, CA 94720, USA  and Department of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, CIRM Center of Excellence, University of California, Berkeley, CA 94720, USA.",
"@type": "Person",
"name": "Anders Sejr Hansen"
},
{
"affiliation": "Department of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, CIRM Center of Excellence, University of California, Berkeley, CA 94720, USA and Unit\u00e9 Imagerie et Mod\u00e9lisation, Institut Pasteur, 25 rue du Docteur Roux, 75015 Paris, France and Sorbonne Universit\u00e9s, UPMC Univ Paris 06, IFD, 4 Place Jussieu, 75252 Paris cedex 05, France and Centre National de la Recherche Scientifique (CNRS), UMR 3691, Paris, France and Centre de Bioinformatique, Biostatistique et Biologie Int\u00e9grative (C3BI), USR 3756, Institut Pasteur et CNRS, Paris, France",
"@type": "Person",
"name": "Maxime Woringer"
},
{
"affiliation": "Janelia Research Campus, Howard Hughes Medical Institute",
"@type": "Person",
"name": "Jonathan B Grimm"
},
{
"affiliation": "Janelia Research Campus, Howard Hughes Medical Institute",
"@type": "Person",
"name": "Luke D Lavis"
},
{
"affiliation": "Howard Hughes Medical Institute, Berkeley, CA 94720, USA  and Department of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, CIRM Center of Excellence, University of California, Berkeley, CA 94720, USA.",
"@type": "Person",
"name": "Robert Tjian"
},
{
"affiliation": "Department of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, CIRM Center of Excellence, University of California, Berkeley, CA 94720, USA",
"@type": "Person",
"name": "Xavier Darzacq"
}
],
"url": "https://zenodo.org/record/834781",
"datePublished": "2017-07-25",
"keywords": [
"superresolution microscopy",
"SPT",
"single particle tracking"
],
"@context": "https://schema.org/",
"distribution": [
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
},
{
"encodingFormat": "zip",
}
],
"identifier": "https://doi.org/10.5281/zenodo.834781",
"@id": "https://doi.org/10.5281/zenodo.834781",
"@type": "Dataset",
"name": "Experimental data for \"Spot-On: robust model-based analysis of single-particle tracking experiments\""
}
493
388
views