{"publisher":"Springer Nature","scopus_import":"1","oa":1,"oa_version":"Published Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2023-07-23T22:01:13Z","quality_controlled":"1","title":"Dense 4D nanoscale reconstruction of living brain tissue","related_material":{"link":[{"url":"https://github.com/danzllab/LIONESS","relation":"software"}],"record":[{"relation":"research_data","id":"12817","status":"public"},{"id":"14770","relation":"shorter_version","status":"public"}]},"status":"public","article_processing_charge":"Yes","month":"08","pmid":1,"date_updated":"2024-01-10T08:37:48Z","type":"journal_article","day":"01","department":[{"_id":"PeJo"},{"_id":"GaNo"},{"_id":"BeBi"},{"_id":"JoDa"},{"_id":"Bio"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1038/s41592-023-01936-6"}],"abstract":[{"text":"Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure–function relationships of the brain’s complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue.","lang":"eng"}],"date_published":"2023-08-01T00:00:00Z","publication_status":"published","year":"2023","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"Bio"},{"_id":"PreCl"},{"_id":"E-Lib"},{"_id":"LifeSc"},{"_id":"M-Shop"}],"intvolume":" 20","volume":20,"project":[{"grant_number":"I03600","name":"Optical control of synaptic function via adhesion molecules","_id":"265CB4D0-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"},{"grant_number":"W1232-B24","name":"Molecular Drug Targets","_id":"2548AE96-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"},{"call_identifier":"FWF","grant_number":"Z00312","name":"The Wittgenstein Prize","_id":"25C5A090-B435-11E9-9278-68D0E5697425"},{"name":"High content imaging to decode human immune cell interactions in health and allergic disease","_id":"23889792-32DE-11EA-91FC-C7463DDC885E"},{"call_identifier":"H2020","name":"International IST Doctoral Program","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385"},{"grant_number":"715767","_id":"24F9549A-B435-11E9-9278-68D0E5697425","name":"MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and Modeling","call_identifier":"H2020"},{"_id":"25444568-B435-11E9-9278-68D0E5697425","name":"Probing the Reversibility of Autism Spectrum Disorders by Employing in vivo and in vitro Models","grant_number":"715508","call_identifier":"H2020"},{"call_identifier":"H2020","name":"Biophysics and circuit function of a giant cortical glumatergic synapse","_id":"25B7EB9E-B435-11E9-9278-68D0E5697425","grant_number":"692692"},{"name":"Synaptic computations of the hippocampal CA3 circuitry","_id":"fc2be41b-9c52-11eb-aca3-faa90aa144e9","grant_number":"101026635","call_identifier":"H2020"},{"name":"High-speed 3D-nanoscopy to study the role of adhesion during 3D cell migration","_id":"2668BFA0-B435-11E9-9278-68D0E5697425","grant_number":"LT00057"}],"isi":1,"acknowledgement":"We thank J. Vorlaufer, N. Agudelo and A. Wartak for microscope maintenance and troubleshooting, C. Kreuzinger and A. Freeman for technical assistance, M. Šuplata for hardware control support and M. Cunha dos Santos for initial exploration of software. We\r\nthank P. Henderson for advice on deep-learning training and M. Sixt, S. Boyd and T. Weiss for discussions and critical reading of the manuscript. L. Lavis (Janelia Research Campus) generously provided the JF585-HaloTag ligand. We acknowledge expert support by IST\r\nAustria’s scientific computing, imaging and optics, preclinical, library and laboratory support facilities and by the Miba machine shop. We gratefully acknowledge funding by the following sources: Austrian Science Fund (F.W.F.) grant no. I3600-B27 (J.G.D.), grant no. DK W1232\r\n(J.G.D. and J.M.M.) and grant no. Z 312-B27, Wittgenstein award (P.J.); the Gesellschaft für Forschungsförderung NÖ grant no. LSC18-022 (J.G.D.); an ISTA Interdisciplinary project grant (J.G.D. and B.B.); the European Union’s Horizon 2020 research and innovation programme,\r\nMarie-Skłodowska Curie grant 665385 (J.M.M. and J.L.); the European Union’s Horizon 2020 research and innovation programme, European Research Council grant no. 715767, MATERIALIZABLE (B.B.); grant no. 715508, REVERSEAUTISM (G.N.); grant no. 695568, SYNNOVATE (S.G.N.G.); and grant no. 692692, GIANTSYN (P.J.); the Simons\r\nFoundation Autism Research Initiative grant no. 529085 (S.G.N.G.); the Wellcome Trust Technology Development grant no. 202932 (S.G.N.G.); the Marie Skłodowska-Curie Actions Individual Fellowship no. 101026635 under the EU Horizon 2020 program (J.F.W.);\r\nthe Human Frontier Science Program postdoctoral fellowship LT000557/2018 (W.J.); and the National Science Foundation grant no. IIS-1835231 (H.P.) and NCS-FO-2124179 (H.P.).","external_id":{"pmid":["37429995"],"isi":["001025621500001"]},"publication_identifier":{"issn":["1548-7091"],"eissn":["1548-7105"]},"doi":"10.1038/s41592-023-01936-6","page":"1256-1265","author":[{"first_name":"Philipp","last_name":"Velicky","full_name":"Velicky, Philipp","id":"39BDC62C-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2340-7431"},{"id":"3FB91342-F248-11E8-B48F-1D18A9856A87","full_name":"Miguel Villalba, Eder","last_name":"Miguel Villalba","first_name":"Eder","orcid":"0000-0001-5665-0430"},{"orcid":"0000-0003-3862-1235","id":"443DB6DE-F248-11E8-B48F-1D18A9856A87","full_name":"Michalska, Julia M","first_name":"Julia M","last_name":"Michalska"},{"full_name":"Lyudchik, Julia","id":"46E28B80-F248-11E8-B48F-1D18A9856A87","last_name":"Lyudchik","first_name":"Julia"},{"full_name":"Wei, Donglai","last_name":"Wei","first_name":"Donglai"},{"full_name":"Lin, Zudi","last_name":"Lin","first_name":"Zudi"},{"orcid":"0000-0002-8698-3823","first_name":"Jake","last_name":"Watson","id":"63836096-4690-11EA-BD4E-32803DDC885E","full_name":"Watson, Jake"},{"full_name":"Troidl, Jakob","first_name":"Jakob","last_name":"Troidl"},{"full_name":"Beyer, Johanna","last_name":"Beyer","first_name":"Johanna"},{"full_name":"Ben Simon, Yoav","id":"43DF3136-F248-11E8-B48F-1D18A9856A87","first_name":"Yoav","last_name":"Ben Simon"},{"first_name":"Christoph M","last_name":"Sommer","id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87","full_name":"Sommer, Christoph M","orcid":"0000-0003-1216-9105"},{"full_name":"Jahr, Wiebke","id":"425C1CE8-F248-11E8-B48F-1D18A9856A87","first_name":"Wiebke","last_name":"Jahr"},{"id":"9ac8f577-2357-11eb-997a-e566c5550886","full_name":"Cenameri, Alban","last_name":"Cenameri","first_name":"Alban"},{"full_name":"Broichhagen, Johannes","last_name":"Broichhagen","first_name":"Johannes"},{"last_name":"Grant","first_name":"Seth G.N.","full_name":"Grant, Seth G.N."},{"id":"353C1B58-F248-11E8-B48F-1D18A9856A87","full_name":"Jonas, Peter M","first_name":"Peter M","last_name":"Jonas","orcid":"0000-0001-5001-4804"},{"orcid":"0000-0002-7673-7178","full_name":"Novarino, Gaia","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","last_name":"Novarino","first_name":"Gaia"},{"full_name":"Pfister, Hanspeter","first_name":"Hanspeter","last_name":"Pfister"},{"last_name":"Bickel","first_name":"Bernd","id":"49876194-F248-11E8-B48F-1D18A9856A87","full_name":"Bickel, Bernd","orcid":"0000-0001-6511-9385"},{"orcid":"0000-0001-8559-3973","last_name":"Danzl","first_name":"Johann G","id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87","full_name":"Danzl, Johann G"}],"publication":"Nature Methods","language":[{"iso":"eng"}],"_id":"13267","ec_funded":1,"article_type":"original","citation":{"chicago":"Velicky, Philipp, Eder Miguel Villalba, Julia M Michalska, Julia Lyudchik, Donglai Wei, Zudi Lin, Jake Watson, et al. “Dense 4D Nanoscale Reconstruction of Living Brain Tissue.” Nature Methods. Springer Nature, 2023. https://doi.org/10.1038/s41592-023-01936-6.","ista":"Velicky P, Miguel Villalba E, Michalska JM, Lyudchik J, Wei D, Lin Z, Watson J, Troidl J, Beyer J, Ben Simon Y, Sommer CM, Jahr W, Cenameri A, Broichhagen J, Grant SGN, Jonas PM, Novarino G, Pfister H, Bickel B, Danzl JG. 2023. Dense 4D nanoscale reconstruction of living brain tissue. Nature Methods. 20, 1256–1265.","apa":"Velicky, P., Miguel Villalba, E., Michalska, J. M., Lyudchik, J., Wei, D., Lin, Z., … Danzl, J. G. (2023). Dense 4D nanoscale reconstruction of living brain tissue. Nature Methods. Springer Nature. https://doi.org/10.1038/s41592-023-01936-6","ama":"Velicky P, Miguel Villalba E, Michalska JM, et al. Dense 4D nanoscale reconstruction of living brain tissue. Nature Methods. 2023;20:1256-1265. doi:10.1038/s41592-023-01936-6","short":"P. Velicky, E. Miguel Villalba, J.M. Michalska, J. Lyudchik, D. Wei, Z. Lin, J. Watson, J. Troidl, J. Beyer, Y. Ben Simon, C.M. Sommer, W. Jahr, A. Cenameri, J. Broichhagen, S.G.N. Grant, P.M. Jonas, G. Novarino, H. Pfister, B. Bickel, J.G. Danzl, Nature Methods 20 (2023) 1256–1265.","mla":"Velicky, Philipp, et al. “Dense 4D Nanoscale Reconstruction of Living Brain Tissue.” Nature Methods, vol. 20, Springer Nature, 2023, pp. 1256–65, doi:10.1038/s41592-023-01936-6.","ieee":"P. Velicky et al., “Dense 4D nanoscale reconstruction of living brain tissue,” Nature Methods, vol. 20. Springer Nature, pp. 1256–1265, 2023."}}