{"lab": {"uuid": "e30d3cc6-74fc-4c59-92e0-656cfea3c9a8", "@type": ["Lab", "Item"], "title": "David Baddeley, YALE", "status": "current", "correspondence": [{"contact_email": "ZGF2aWQuYmFkZGVsZXlAeWFsZS5lZHU=", "@id": "/users/82332a78-7709-431b-b063-25ec65d82a90/", "display_title": "David Baddeley"}], "@id": "/labs/david-baddeley-lab/", "display_title": "David Baddeley, YALE", "pi": {"error": "no view permissions"}, "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin", "role.lab_submitter", "submits_for.e30d3cc6-74fc-4c59-92e0-656cfea3c9a8"]}}, "award": {"name": "1U01EB021232-01", "@type": ["Award", "Item"], "description": "IT: The complex of DNA, protein, and RNA known as chromatin is the substrate for essential cellular processes such as gene transcription, regulation, replication, and repair. Unravelling its structure and dynamics is therefore essential f we are to understand the mechanics of these processes and their effects in development and disease. Chromatin is, however, a difficult target to study: it is found in a crowded environment within the nucleus, is structurally organized on multiple length scales, is variable within and between nuclei, and is highly dynamic. Capturing this information requires instrumentation which can (i) measure on multiple length scales, from the whole cell down to tens of nm, (ii) follow chromatin dynamics in living cells, and (iii) acquire and quantify thousands of images in a manageable time frame to overcome the intrinsic variability and provide a statistical description of chromatin behavior. Such an instrument does not yet exist, with existing instrumentation being limited in resolution, dynamic speed, and throughput. We propose an innovative multi-disciplinary approach that combines developments in optics, data processing and modeling to realize an integrated system for automated high-throughput super- resolution imaging and dense single-molecule tracking in the cell nucleus. Our Specific Aims are: 1) Develop an automated multicolor 3D single-molecule switching (SMS) nanoscope for dynamic imaging and particle-tracking in the nucleus, 2) Develop data processing tools for high-throughput 3D- SMS nanoscopy of 100-1,000 cells/h, 3) Develop chromatin modeling tools that take advantage of the unprecedented level of detail and statistical depth of the 4D data provided by high-throughput particle- tracking and SMS nanoscopy, and 4) test the performance and refine our technical developments by applying them to a diverse set of representative and important questions in the field of chromatin architecture, including the mobility and dynamics of transcription factors and nucleosomes, and the processes of synaptonemal assembly and telomere recombination. The proposal represents a fundamental departure from the traditional view of the nanoscopy image generation procedure as a hands-on process heavily involving an expert user to an automated, high- throughput method with focus on quantification and efficiency. By making nanoscopy studies of tens of thousands of cells feasible, we anticipate that our instrument will enable, for the first time, the spatiotemporal dynamics of the nucleome to be quantitatively investigated down to the single nucleosome level.", "@id": "/awards/1U01EB021232-01/", "center_title": "IT - Bewersdorf", "status": "current", "project": "4DN", "uuid": "83702425-25f4-413b-9826-7257e2732506", "display_title": "AN INTEGRATED IMAGING SYSTEM FOR HIGH-THROUGHPUT NANOSCOPY OF THE 4D NUCLEOME", "pi": {"error": "no view permissions"}, "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, "badges": [{"badge": {"@id": "/badges/replicate-numbers/", "badge_classification": "Warning", "display_title": "Replicate Numbers", "@type": ["Badge", "Item"], "warning": "Replicate Numbers", "title": "Replicate Numbers", "uuid": "24a64a84-3c33-4d76-aaf2-e5ef45eff347", "status": "released", "badge_icon": "/static/img/badges/replicates-orange-circle.svg", "description": "Issues with replicate numbers", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, "messages": ["Replicate set contains only a single biological replicate"]}], "status": "released", "aliases": ["joerg-bewersdorf-lab:HTSMS-IMR90-LAD2lamin"], "accession": "4DNESVDDCXBV", "condition": "LAD/lamin in IMR90", "description": "Validation experiment of fast 3D, two-color single-molecule switching nanoscopy on a volume the size of the nucleus. Test of imaging immunofluorescence and FISH probes simultaneously.", "date_created": "2019-08-05T15:32:54.281983+00:00", "sample_image": {"@type": ["Image", "Item"], "@id": "/images/b851bd9b-ce9c-465e-b1eb-6ceea0b2c170/", "caption": "Sample frame of rendered image - chr13 LAD (red) and Lamin A/C (green)", "display_title": "Thumbnail for 4DNFIQFW2AZO", "status": "released", "uuid": "b851bd9b-ce9c-465e-b1eb-6ceea0b2c170", "microscopy_file": {"display_title": "4DNFIQFW2AZO.ome.tiff", "accession": "4DNFIQFW2AZO", "uuid": "7508e5cb-c652-4388-ad74-b81768b801c8", "omerolink": "https://omero.hms.harvard.edu/pathviewer/vanilla-viewer/975140", "@id": "/files-microscopy/4DNFIQFW2AZO/", "status": "released", "@type": ["FileMicroscopy", "File", "Item"], "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, "attachment": {"type": "image/jpeg", "download": "4DNFIQFW2AZO.jpeg", "md5sum": "74990ea1d9e145051121639bf7302bdc", "href": "@@download/attachment/4DNFIQFW2AZO.jpeg", "width": 1301, "height": 1411}, "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, "submitted_by": {"error": "no view permissions"}, "dataset_label": "SMSN (Barentine et al 2019 bioRxiv)", "last_modified": {"modified_by": {"error": "no view permissions"}, "date_modified": "2019-11-15T18:24:02.507216+00:00"}, "public_release": "2019-11-15", "replicate_exps": [{"bio_rep_no": 1, "tec_rep_no": 1, "replicate_exp": {"display_title": "DNA FISH on IMR-90 (Tier 1) - 4DNEX2VUG2MU", "@type": ["ExperimentMic", "Experiment", "Item"], "accession": "4DNEX2VUG2MU", "uuid": "7e8dae2a-9de1-4419-86a7-4333cce1b1b1", "status": "released", "@id": "/experiments-mic/4DNEX2VUG2MU/", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}}], "schema_version": "2", "static_headers": [{"body": "**DNA FISH**\n\nDNA FISH is a method to detect the position of specific DNA regions in the cell through fluorescent labeling. It can be used to measure the 3D distances between multiple genomic loci. Additionally, it is often used to corroborate the findings of chromosome capture techniques (3C).\n\nThe protocol involves fixing and permeabilizing the cells. Then, the DNA is slightly denatured to allow the binding of fluorescently labeled probes to the region of interest (hybridization). After the hybridization is performed, unbound and partially unbound probes are removed. The target loci are then visualized using fluorescent microscopy. Analysis of the resulting images provides the physical localization of the target genomic regions in the cell.", "name": "item-page-headers.ExperimentType.fish", "award": {"display_title": "4D NUCLEOME NETWORK DATA COORDINATION AND INTEGRATION CENTER - PHASE I", "status": "current", "@id": "/awards/1U01CA200059-01/", "uuid": "b0b9c607-f8b4-4f02-93f4-9895b461334b", "@type": ["Award", "Item"], "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, "title": "Assay Description", "status": "released", "aliases": ["4dn-dcic-lab:experiment_infobox_fish"], "options": {"filetype": "md", "collapsible": false, "default_open": false, "convert_ext_links": true}, "date_created": "2018-09-07T18:16:30.519497+00:00", "section_type": "Item Page Header", "submitted_by": {"error": "no view permissions"}, "last_modified": {"modified_by": {"error": "no view permissions"}, "date_modified": "2023-09-26T12:26:08.887894+00:00"}, "schema_version": "2", "@id": "/static-sections/911424f9-21c7-49fc-b1df-865dd64ae91e/", "@type": ["StaticSection", "UserContent", "Item"], "uuid": "911424f9-21c7-49fc-b1df-865dd64ae91e", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin", "role.owner", "userid.56c9c683-bb11-471b-b590-c656f7dc03c1"]}, "display_title": "Assay Description", "external_references": [], "content": "**DNA FISH**\n\nDNA FISH is a method to detect the position of specific DNA regions in the cell through fluorescent labeling. It can be used to measure the 3D distances between multiple genomic loci. Additionally, it is often used to corroborate the findings of chromosome capture techniques (3C).\n\nThe protocol involves fixing and permeabilizing the cells. Then, the DNA is slightly denatured to allow the binding of fluorescently labeled probes to the region of interest (hybridization). After the hybridization is performed, unbound and partially unbound probes are removed. The target loci are then visualized using fluorescent microscopy. Analysis of the resulting images provides the physical localization of the target genomic regions in the cell.", "filetype": "md", "content_as_html": "<p><strong>DNA FISH</strong></p>\n<p>DNA FISH is a method to detect the position of specific DNA regions in the cell through fluorescent labeling. It can be used to measure the 3D distances between multiple genomic loci. Additionally, it is often used to corroborate the findings of chromosome capture techniques (3C).</p>\n<p>The protocol involves fixing and permeabilizing the cells. Then, the DNA is slightly denatured to allow the binding of fluorescently labeled probes to the region of interest (hybridization). After the hybridization is performed, unbound and partially unbound probes are removed. The target loci are then visualized using fluorescent microscopy. Analysis of the resulting images provides the physical localization of the target genomic regions in the cell.</p>"}, {"lab": {"display_title": "4DN DCIC, HMS", "status": "current", "@id": "/labs/4dn-dcic-lab/", "@type": ["Lab", "Item"], "uuid": "828cd4fe-ebb0-4b36-a94a-d2e3a36cc989", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin", "role.lab_submitter", "submits_for.828cd4fe-ebb0-4b36-a94a-d2e3a36cc989"]}}, "body": "Localization files for the HT-SMSN dataset are in an hdf5 \nformat, generated by PYME (Python Microscopy Environment). \nEven without PYME or other specialized software packages, \nthese can be opened in python using the h5py library. \n\nDescription of file format and included data can be found [here](\n/documents/933f2977-05f4-43c7-9eeb-7994290ff56a/@@download/attachment/ht-smsn-h5.pdf).\n\nSome sample commands for looking at h5 file contents can be \nfound [here](/publications/7d9fad19-54c4-419e-8d99-8157f5c1904b/#processed_data).", "name": "ht-smsn.h5-header", "award": {"display_title": "4D NUCLEOME NETWORK DATA COORDINATION AND INTEGRATION CENTER - PHASE I", "status": "current", "@id": "/awards/1U01CA200059-01/", "uuid": "b0b9c607-f8b4-4f02-93f4-9895b461334b", "@type": ["Award", "Item"], "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin"]}}, "title": "Note on Localization h5 Processed Files", "status": "released", "aliases": ["4dn-dcic-lab:h5-note"], "options": {"filetype": "md", "collapsible": true, "default_open": false, "convert_ext_links": true}, "date_created": "2019-11-14T21:00:30.923825+00:00", "section_type": "Item Page Header", "submitted_by": {"error": "no view permissions"}, "last_modified": {"modified_by": {"error": "no view permissions"}, "date_modified": "2023-09-26T12:26:04.745079+00:00"}, "schema_version": "2", "@id": "/static-sections/037ffbe7-bc11-47aa-99eb-b9759ced1fa3/", "@type": ["StaticSection", "UserContent", "Item"], "uuid": "037ffbe7-bc11-47aa-99eb-b9759ced1fa3", "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin", "role.owner", "userid.e2324f87-0625-4bbc-803b-d47677aebe08"]}, "display_title": "Note on Localization h5 Processed Files", "external_references": [], "content": "Localization files for the HT-SMSN dataset are in an hdf5 \nformat, generated by PYME (Python Microscopy Environment). \nEven without PYME or other specialized software packages, \nthese can be opened in python using the h5py library. \n\nDescription of file format and included data can be found [here](\n/documents/933f2977-05f4-43c7-9eeb-7994290ff56a/@@download/attachment/ht-smsn-h5.pdf).\n\nSome sample commands for looking at h5 file contents can be \nfound [here](/publications/7d9fad19-54c4-419e-8d99-8157f5c1904b/#processed_data).", "filetype": "md", "content_as_html": "<p>Localization files for the HT-SMSN dataset are in an hdf5 \nformat, generated by PYME (Python Microscopy Environment). \nEven without PYME or other specialized software packages, \nthese can be opened in python using the h5py library. </p>\n<p>Description of file format and included data can be found <a href=\"/documents/933f2977-05f4-43c7-9eeb-7994290ff56a/@@download/attachment/ht-smsn-h5.pdf\">here</a>.</p>\n<p>Some sample commands for looking at h5 file contents can be \nfound <a href=\"/publications/7d9fad19-54c4-419e-8d99-8157f5c1904b/#processed_data\">here</a>.</p>"}], "project_release": "2019-11-15", "contributing_labs": [{"@id": "/labs/joerg-bewersdorf-lab/", "display_title": "Joerg Bewersdorf, YALE", "status": "current", "correspondence": [{"contact_email": "am9lcmcuYmV3ZXJzZG9yZkB5YWxlLmVkdQ==", "@id": "/users/9e620077-dc63-46bd-9dce-44bd016df029/", "display_title": "Joerg Bewersdorf"}], "@type": ["Lab", "Item"], "uuid": "37c44536-e572-49ab-85bb-d8a86875e0b7", "pi": {"error": "no view permissions"}, "principals_allowed": {"view": ["system.Everyone"], "edit": ["group.admin", "role.lab_submitter", "submits_for.37c44536-e572-49ab-85bb-d8a86875e0b7"]}}], 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The file and the information about its provenance, i.e. which files were used as input to generate this output was provided by or done in collaboration with the lab that did the experiments to generate the raw data. 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The multitude of camera frames required to reconstruct a super-resolved image limits the typical throughput of these techniques to tens of cells per day, rendering these methods incompatible with large-scale cell biological or clinical application. STORM acquisition rates can be increased by over an order of magnitude, however the data volumes of about 40 TB a day and concomitant analysis burdens exceed the capacity of existing workflows. Here we present an integrated platform which transforms SMLM from a trick-pony technique into a work horse for cell biology. We leverage our developments in microscopy-specific data compression, distributed storage, and distributed analysis to automatically perform real-time localization analysis, which enable SMLM at throughputs of 10,000 cells a day. We implemented these advances in a fully-integrated environment that supports a highly-flexible architecture for distributed analysis, enabling quickly- and graphically-reconfigurable analyses to be automatically initiated from the microscope during acquisition, remotely executed, and even feedback and queue new acquisition tasks on the microscope. We demonstrate the utility of this framework by imaging hundreds of cells per well in multi-well sample formats. Our platform, the PYthon-Microscopy Environment (PYME), is easily configurable for hardware control on custom microscopes, and includes a plugin framework so users can readily extend all components of their imaging, visualization, and analysis pipeline. 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The multitude of camera frames required to reconstruct a super-resolved image limits the typical throughput of these techniques to tens of cells per day, rendering these methods incompatible with large-scale cell biological or clinical application. STORM acquisition rates can be increased by over an order of magnitude, however the data volumes of about 40 TB a day and concomitant analysis burdens exceed the capacity of existing workflows. Here we present an integrated platform which transforms SMLM from a trick-pony technique into a work horse for cell biology. We leverage our developments in microscopy-specific data compression, distributed storage, and distributed analysis to automatically perform real-time localization analysis, which enable SMLM at throughputs of 10,000 cells a day. We implemented these advances in a fully-integrated environment that supports a highly-flexible architecture for distributed analysis, enabling quickly- and graphically-reconfigurable analyses to be automatically initiated from the microscope during acquisition, remotely executed, and even feedback and queue new acquisition tasks on the microscope. We demonstrate the utility of this framework by imaging hundreds of cells per well in multi-well sample formats. Our platform, the PYthon-Microscopy Environment (PYME), is easily configurable for hardware control on custom microscopes, and includes a plugin framework so users can readily extend all components of their imaging, visualization, and analysis pipeline. PYME is cross-platform, open source, and efficiently puts high-caliber visualization and analysis tools into the hands of both microscope developers and users.", "date_published": "2022-04-20", "ID": "doi:10.1101/606954", "authors": ["Barentine AES", "Lin Y", "Courvan EM", "Kidd P", "Liu M", "Balduf L", "Phan T", "Rivera-Molina F", "Grace MR", "Marin Z", "Lessard M", "Rios-Chen J", "Wang S", "Neugebauer KM", "Bewersdorf J", "Baddeley D"], "status": "current", "display_title": "Barentine AES et al. 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