AutoCLEM: an automated workflow for correlative live-cell fluorescence microscopy and cryo-electron tomography
Correlative light and electron microscopy (CLEM) combines the strengths of both light and electron imaging modalities and enables linking of biological spatiotemporal information from live-cell fuorescence light microscopy (fLM) to high-resolution cellular ultra-structures from cryo-electron microsc...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Springer Nature
2019
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| _version_ | 1826270161860034560 |
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| author | Fu, X Ning, J Zhong, Z Ambrose, Z Charles Watkins, S Zhang, P |
| author_facet | Fu, X Ning, J Zhong, Z Ambrose, Z Charles Watkins, S Zhang, P |
| author_sort | Fu, X |
| collection | OXFORD |
| description | Correlative light and electron microscopy (CLEM) combines the strengths of both light and electron imaging modalities and enables linking of biological spatiotemporal information from live-cell fuorescence light microscopy (fLM) to high-resolution cellular ultra-structures from cryo-electron microscopy and tomography (cryoEM/ET). This has been previously achieved by using fLM signals to localize the regions of interest under cryogenic conditions. The correlation process, however, is often tedious and time-consuming with low throughput and limited accuracy, because multiple correlation steps at diferent length scales are largely carried out manually. Here, we present an experimental workfow, AutoCLEM, which overcomes the existing limitations and improves the performance and throughput of CLEM methods, and associated software. The AutoCLEM system encompasses a highspeed confocal live-cell imaging module to acquire an automated fLM grid atlas that is linked to the cryoEM grid atlas, followed by cryofLM imaging after freezing. The fLM coordinates of the targeted areas are automatically converted to cryoEM/ET and refned using fuorescent fducial beads. This AutoCLEM workfow signifcantly accelerates the correlation efciency between live-cell fuorescence imaging and cryoEM/ET structural analysis, as demonstrated by visualizing human immunodefciency virus type 1 (HIV-1) interacting with host cells. |
| first_indexed | 2024-03-06T21:36:30Z |
| format | Journal article |
| id | oxford-uuid:46725d04-98cb-482f-b20f-0962dfd159fd |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T21:36:30Z |
| publishDate | 2019 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | oxford-uuid:46725d04-98cb-482f-b20f-0962dfd159fd2022-03-26T15:13:45ZAutoCLEM: an automated workflow for correlative live-cell fluorescence microscopy and cryo-electron tomographyJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:46725d04-98cb-482f-b20f-0962dfd159fdEnglishSymplectic Elements at OxfordSpringer Nature2019Fu, XNing, JZhong, ZAmbrose, ZCharles Watkins, SZhang, PCorrelative light and electron microscopy (CLEM) combines the strengths of both light and electron imaging modalities and enables linking of biological spatiotemporal information from live-cell fuorescence light microscopy (fLM) to high-resolution cellular ultra-structures from cryo-electron microscopy and tomography (cryoEM/ET). This has been previously achieved by using fLM signals to localize the regions of interest under cryogenic conditions. The correlation process, however, is often tedious and time-consuming with low throughput and limited accuracy, because multiple correlation steps at diferent length scales are largely carried out manually. Here, we present an experimental workfow, AutoCLEM, which overcomes the existing limitations and improves the performance and throughput of CLEM methods, and associated software. The AutoCLEM system encompasses a highspeed confocal live-cell imaging module to acquire an automated fLM grid atlas that is linked to the cryoEM grid atlas, followed by cryofLM imaging after freezing. The fLM coordinates of the targeted areas are automatically converted to cryoEM/ET and refned using fuorescent fducial beads. This AutoCLEM workfow signifcantly accelerates the correlation efciency between live-cell fuorescence imaging and cryoEM/ET structural analysis, as demonstrated by visualizing human immunodefciency virus type 1 (HIV-1) interacting with host cells. |
| spellingShingle | Fu, X Ning, J Zhong, Z Ambrose, Z Charles Watkins, S Zhang, P AutoCLEM: an automated workflow for correlative live-cell fluorescence microscopy and cryo-electron tomography |
| title | AutoCLEM: an automated workflow for correlative live-cell fluorescence microscopy and cryo-electron tomography |
| title_full | AutoCLEM: an automated workflow for correlative live-cell fluorescence microscopy and cryo-electron tomography |
| title_fullStr | AutoCLEM: an automated workflow for correlative live-cell fluorescence microscopy and cryo-electron tomography |
| title_full_unstemmed | AutoCLEM: an automated workflow for correlative live-cell fluorescence microscopy and cryo-electron tomography |
| title_short | AutoCLEM: an automated workflow for correlative live-cell fluorescence microscopy and cryo-electron tomography |
| title_sort | autoclem an automated workflow for correlative live cell fluorescence microscopy and cryo electron tomography |
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