[{"publication_identifier":{"eissn":["1546-1696"],"issn":["1087-0156"]},"citation":{"ama":"Maddipatla SA, Sellam NE, Bojan MI, et al. Experiment-guided AlphaFold3 resolves measurement-consistent protein ensembles. <i>Nature Biotechnology</i>. 2026. doi:<a href=\"https://doi.org/10.1038/s41587-026-03166-5\">10.1038/s41587-026-03166-5</a>","chicago":"Maddipatla, Sai A, Nadav E Sellam, Meital I Bojan, Vova Masalitin, Sanketh Vedula, Paul Schanda, Ailie Marx, and Alex M. Bronstein. “Experiment-Guided AlphaFold3 Resolves Measurement-Consistent Protein Ensembles.” <i>Nature Biotechnology</i>. Springer Nature, 2026. <a href=\"https://doi.org/10.1038/s41587-026-03166-5\">https://doi.org/10.1038/s41587-026-03166-5</a>.","apa":"Maddipatla, S. A., Sellam, N. E., Bojan, M. I., Masalitin, V., Vedula, S., Schanda, P., … Bronstein, A. M. (2026). Experiment-guided AlphaFold3 resolves measurement-consistent protein ensembles. <i>Nature Biotechnology</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41587-026-03166-5\">https://doi.org/10.1038/s41587-026-03166-5</a>","ieee":"S. A. Maddipatla <i>et al.</i>, “Experiment-guided AlphaFold3 resolves measurement-consistent protein ensembles,” <i>Nature Biotechnology</i>. Springer Nature, 2026.","short":"S.A. Maddipatla, N.E. Sellam, M.I. Bojan, V. Masalitin, S. Vedula, P. Schanda, A. Marx, A.M. Bronstein, Nature Biotechnology (2026).","mla":"Maddipatla, Sai A., et al. “Experiment-Guided AlphaFold3 Resolves Measurement-Consistent Protein Ensembles.” <i>Nature Biotechnology</i>, Springer Nature, 2026, doi:<a href=\"https://doi.org/10.1038/s41587-026-03166-5\">10.1038/s41587-026-03166-5</a>.","ista":"Maddipatla SA, Sellam NE, Bojan MI, Masalitin V, Vedula S, Schanda P, Marx A, Bronstein AM. 2026. Experiment-guided AlphaFold3 resolves measurement-consistent protein ensembles. Nature Biotechnology."},"_id":"22268","date_updated":"2026-08-04T09:25:18Z","pmid":1,"year":"2026","license":"https://creativecommons.org/licenses/by/4.0/","title":"Experiment-guided AlphaFold3 resolves measurement-consistent protein ensembles","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","publisher":"Springer Nature","related_material":{"link":[{"description":"News on ISTA website","relation":"press_release","url":"https://ista.ac.at/en/news/toward-experiment-guided-alphafold/"}]},"tmp":{"short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"ddc":["570"],"type":"journal_article","date_created":"2026-07-12T22:02:19Z","publication":"Nature Biotechnology","publication_status":"epub_ahead","article_type":"original","abstract":[{"lang":"eng","text":"AlphaFold3 predicts highly accurate protein structures from sequence but tends to collapse to a single dominant conformation, even when the underlying structure is inherently heterogeneous. Moreover, its predictions are oblivious to experimental conditions that can alter local sequence conformation. In this work, we show that AlphaFold3 can be guided to match data obtained by nuclear magnetic resonance (NMR) spectroscopy, X-ray crystallography and cryogenic electron microscopy (cryo-EM) experiments and combinations thereof. Our approach can also incorporate data that explicitly report on dynamics, such as site-resolved order parameters. We demonstrate that this methodology generates compact structural ensembles whose ensemble-averaged observables agree with experiment, with fewer distance restraint violations than traditionally resolved NMR structures and with unmodeled alternate conformations uncovered in electron density. This methodology paves the way for experimentally aware predictive models that generate structural ensembles consistent with the measurements, potentially over multiple modalities, and that can be further refined toward thermodynamically grounded ensembles by incorporating energetics."}],"day":"29","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1038/s41587-026-03166-5"}],"researchdata_availability":"yes","scopus_import":"1","language":[{"iso":"eng"}],"article_processing_charge":"Yes (via OA deal)","OA_place":"publisher","has_accepted_license":"1","doi":"10.1038/s41587-026-03166-5","das_tickbox":"1","month":"06","PlanS_conform":"1","supplementarymaterial":"yes","corr_author":"1","acknowledgement":"A. Marx acknowledges the financial support of the Helmsley Fellowships Program for Sustainability and Health. A.M.B. and P.S. are supported by the Institute of Science and Technology Austria Internal Project Call grant Generative Protein NMR. S.V. was supported in part by funding from the Eric and Wendy Schmidt Center at the Broad Institute of MIT and Harvard. Open access funding provided by Institute of Science and Technology (IST Austria).","author":[{"id":"e957f5e5-91c9-11f0-a95f-e090f66ecb4d","first_name":"Sai A","full_name":"Maddipatla, Sai A","last_name":"Maddipatla"},{"id":"ef280fe0-91c9-11f0-a95f-8dea3f5bc513","full_name":"Sellam, Nadav E","last_name":"Sellam","first_name":"Nadav E"},{"full_name":"Bojan, Meital I","last_name":"Bojan","first_name":"Meital I","id":"11d88cf5-91ca-11f0-a95f-edf9f08f47b7"},{"last_name":"Masalitin","full_name":"Masalitin, Vova","first_name":"Vova","id":"ff7958eb-91c9-11f0-a95f-f3bf65828cf6"},{"last_name":"Vedula","full_name":"Vedula, Sanketh","first_name":"Sanketh"},{"first_name":"Paul","full_name":"Schanda, Paul","last_name":"Schanda","orcid":"0000-0002-9350-7606","id":"7B541462-FAF6-11E9-A490-E8DFE5697425"},{"first_name":"Ailie","full_name":"Marx, Ailie","last_name":"Marx"},{"id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","last_name":"Bronstein","orcid":"0000-0001-9699-8730","first_name":"Alexander"}],"dataavailabilitystatement":"All structures and metrics reported in this paper are openly available on Harvard Dataverse - https://doi.org/10.7910/DVN/PLYUHN. All code is openly available on GitHub (https://github.com/sai-advaith/guided_alphafold); the version used for this paper (version 0.9.1) is permanently archived on Zenodo https://doi.org/10.5281/zenodo.17307005","oa":1,"OA_type":"hybrid","date_published":"2026-06-29T00:00:00Z","external_id":{"pmid":["42374114"]},"quality_controlled":"1","status":"public","department":[{"_id":"PaSc"},{"_id":"AlBr"},{"_id":"GradSch"}],"oa_version":"Published Version"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Springer Nature","ec_funded":1,"title":"Imaging brain tissue architecture across millimeter to nanometer scales","year":"2024","pmid":1,"date_updated":"2026-04-14T08:34:35Z","_id":"14257","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"Bio"},{"_id":"PreCl"},{"_id":"LifeSc"},{"_id":"M-Shop"},{"_id":"E-Lib"}],"citation":{"apa":"Michalska, J. M., Lyudchik, J., Velicky, P., Korinkova, H., Watson, J., Cenameri, A., … Danzl, J. G. (2024). Imaging brain tissue architecture across millimeter to nanometer scales. <i>Nature Biotechnology</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41587-023-01911-8\">https://doi.org/10.1038/s41587-023-01911-8</a>","chicago":"Michalska, Julia M, Julia Lyudchik, Philipp Velicky, Hana Korinkova, Jake Watson, Alban Cenameri, Christoph M Sommer, et al. “Imaging Brain Tissue Architecture across Millimeter to Nanometer Scales.” <i>Nature Biotechnology</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41587-023-01911-8\">https://doi.org/10.1038/s41587-023-01911-8</a>.","mla":"Michalska, Julia M., et al. “Imaging Brain Tissue Architecture across Millimeter to Nanometer Scales.” <i>Nature Biotechnology</i>, vol. 42, Springer Nature, 2024, pp. 1051–64, doi:<a href=\"https://doi.org/10.1038/s41587-023-01911-8\">10.1038/s41587-023-01911-8</a>.","ista":"Michalska JM, Lyudchik J, Velicky P, Korinkova H, Watson J, Cenameri A, Sommer CM, Amberg N, Venturino A, Roessler K, Czech T, Höftberger R, Siegert S, Novarino G, Jonas PM, Danzl JG. 2024. Imaging brain tissue architecture across millimeter to nanometer scales. Nature Biotechnology. 42, 1051–1064.","short":"J.M. Michalska, J. Lyudchik, P. Velicky, H. Korinkova, J. Watson, A. Cenameri, C.M. Sommer, N. Amberg, A. Venturino, K. Roessler, T. Czech, R. Höftberger, S. Siegert, G. Novarino, P.M. Jonas, J.G. Danzl, Nature Biotechnology 42 (2024) 1051–1064.","ieee":"J. M. Michalska <i>et al.</i>, “Imaging brain tissue architecture across millimeter to nanometer scales,” <i>Nature Biotechnology</i>, vol. 42. Springer Nature, pp. 1051–1064, 2024.","ama":"Michalska JM, Lyudchik J, Velicky P, et al. Imaging brain tissue architecture across millimeter to nanometer scales. <i>Nature Biotechnology</i>. 2024;42:1051-1064. doi:<a href=\"https://doi.org/10.1038/s41587-023-01911-8\">10.1038/s41587-023-01911-8</a>"},"publication_identifier":{"issn":["1087-0156"],"eissn":["1546-1696"]},"abstract":[{"text":"Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease.","lang":"eng"}],"article_type":"original","publication_status":"published","publication":"Nature Biotechnology","volume":42,"date_created":"2023-09-03T22:01:15Z","type":"journal_article","ddc":["570"],"file":[{"file_id":"18784","checksum":"57d5fafb16f02dcb9f7dddb1bd7e2a71","file_name":"2024_NatureBiotech_Michalska.pdf","file_size":26065165,"success":1,"relation":"main_file","access_level":"open_access","content_type":"application/pdf","date_created":"2025-01-09T07:48:01Z","date_updated":"2025-01-09T07:48:01Z","creator":"dernst"}],"tmp":{"short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"related_material":{"record":[{"id":"18660","relation":"dissertation_contains","status":"deleted"},{"relation":"research_data","id":"13126","status":"public"},{"relation":"dissertation_contains","id":"18674","status":"public"}],"link":[{"relation":"software","url":"https://github.com/danzllab/CATS"}]},"file_date_updated":"2025-01-09T07:48:01Z","month":"07","doi":"10.1038/s41587-023-01911-8","has_accepted_license":"1","OA_place":"publisher","article_processing_charge":"Yes (in subscription journal)","language":[{"iso":"eng"}],"scopus_import":"1","day":"01","department":[{"_id":"SaSi"},{"_id":"GaNo"},{"_id":"PeJo"},{"_id":"JoDa"},{"_id":"Bio"},{"_id":"RySh"}],"oa_version":"Published Version","quality_controlled":"1","status":"public","external_id":{"isi":["001065254200001"],"pmid":["37653226"]},"project":[{"call_identifier":"FWF","name":"Optical control of synaptic function via adhesion molecules","_id":"265CB4D0-B435-11E9-9278-68D0E5697425","grant_number":"I03600"},{"_id":"2548AE96-B435-11E9-9278-68D0E5697425","name":"Molecular Drug Targets","call_identifier":"FWF","grant_number":"W1232"},{"_id":"25C5A090-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Synaptic communication in neuronal microcircuits","grant_number":"Z00312"},{"grant_number":"LS18-022","_id":"23889792-32DE-11EA-91FC-C7463DDC885E","name":"High content imaging to decode human immune cell interactions in health and allergic disease"},{"grant_number":"715508","_id":"25444568-B435-11E9-9278-68D0E5697425","name":"Probing the Reversibility of Autism Spectrum Disorders by Employing in vivo and in vitro Models","call_identifier":"H2020"},{"call_identifier":"H2020","name":"Biophysics and circuit function of a giant cortical glutamatergic synapse","_id":"25B7EB9E-B435-11E9-9278-68D0E5697425","grant_number":"692692"},{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program","call_identifier":"H2020"},{"grant_number":"101026635","_id":"fc2be41b-9c52-11eb-aca3-faa90aa144e9","name":"Synaptic computations of the hippocampal CA3 circuitry","call_identifier":"H2020"}],"date_published":"2024-07-01T00:00:00Z","oa":1,"OA_type":"hybrid","isi":1,"intvolume":"        42","author":[{"first_name":"Julia M","orcid":"0000-0003-3862-1235","full_name":"Michalska, Julia M","last_name":"Michalska","id":"443DB6DE-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Julia","last_name":"Lyudchik","full_name":"Lyudchik, Julia","id":"46E28B80-F248-11E8-B48F-1D18A9856A87"},{"id":"39BDC62C-F248-11E8-B48F-1D18A9856A87","first_name":"Philipp","last_name":"Velicky","full_name":"Velicky, Philipp","orcid":"0000-0002-2340-7431"},{"last_name":"Korinkova","full_name":"Korinkova, Hana","first_name":"Hana","id":"ee3cb6ca-ec98-11ea-ae11-ff703e2254ed"},{"last_name":"Watson","full_name":"Watson, Jake","orcid":"0000-0002-8698-3823","first_name":"Jake","id":"63836096-4690-11EA-BD4E-32803DDC885E"},{"first_name":"Alban","full_name":"Cenameri, Alban","last_name":"Cenameri","id":"9ac8f577-2357-11eb-997a-e566c5550886"},{"id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87","full_name":"Sommer, Christoph M","last_name":"Sommer","orcid":"0000-0003-1216-9105","first_name":"Christoph M"},{"id":"4CD6AAC6-F248-11E8-B48F-1D18A9856A87","last_name":"Amberg","full_name":"Amberg, Nicole","orcid":"0000-0002-3183-8207","first_name":"Nicole"},{"first_name":"Alessandro","orcid":"0000-0003-2356-9403","last_name":"Venturino","full_name":"Venturino, Alessandro","id":"41CB84B2-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Karl","full_name":"Roessler, Karl","last_name":"Roessler"},{"first_name":"Thomas","last_name":"Czech","full_name":"Czech, Thomas"},{"first_name":"Romana","full_name":"Höftberger, Romana","last_name":"Höftberger"},{"id":"36ACD32E-F248-11E8-B48F-1D18A9856A87","first_name":"Sandra","orcid":"0000-0001-8635-0877","last_name":"Siegert","full_name":"Siegert, Sandra"},{"id":"3E57A680-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-7673-7178","last_name":"Novarino","full_name":"Novarino, Gaia","first_name":"Gaia"},{"id":"353C1B58-F248-11E8-B48F-1D18A9856A87","last_name":"Jonas","full_name":"Jonas, Peter M","orcid":"0000-0001-5001-4804","first_name":"Peter M"},{"last_name":"Danzl","full_name":"Danzl, Johann G","orcid":"0000-0001-8559-3973","first_name":"Johann G","id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87"}],"corr_author":"1","acknowledgement":"We thank J. Vorlaufer, N. Agudelo-Dueñas, W. Jahr and A. Wartak for microscope maintenance and troubleshooting; C. Kreuzinger, A. Freeman and I. Erber for technical assistance; and M. Tomschik for support with obtaining human samples. We gratefully acknowledge E. Miguel for setting up webKnossos and M. Šuplata for computational support and hardware control. We are grateful to R. Shigemoto and B. Bickel for generous support and M. Sixt and S. Boyd (Stanford University) for discussions and critical reading of the paper. PSD95-HaloTag mice were kindly provided by S. Grant (University of Edinburgh). We acknowledge expert support by Institute of Science and Technology Austria’s scientific computing, imaging and optics, preclinical and lab support facilities and by the Miba machine shop and library. We gratefully acknowledge funding by the following sources: Austrian Science Fund (FWF) grant I3600-B27 (J.G.D.); Austrian Science Fund (FWF) grant DK W1232 (J.G.D. and J.M.M.); Austrian Science Fund (FWF) grant Z 312-B27, Wittgenstein award (P.J.); Austrian Science Fund (FWF) projects I4685-B, I6565-B (SYNABS) and DOC 33-B27 (R.H.); Gesellschaft für Forschungsförderung NÖ (NFB) grant LSC18-022 (J.G.D.); European Union’s Horizon 2020 research and innovation programme, European Research Council (ERC) grant 715508 – REVERSEAUTISM (G.N.); European Union’s Horizon 2020 research and innovation programme, European Research Council (ERC) grant 692692 – GIANTSYN (P.J.); Marie Skłodowska-Curie Actions Fellowship GA no. 665385 under the EU Horizon 2020 program (J.M.M. and J.L.); and Marie Skłodowska-Curie Actions Individual Fellowship no. 101026635 under the EU Horizon 2020 program (J.F.W.).","page":"1051-1064"},{"abstract":[{"text":"Regulation of chromatin states involves the dynamic interplay between different histone modifications to control gene expression. Recent advances have enabled mapping of histone marks in single cells, but most methods are constrained to profile only one histone mark per cell. Here, we present an integrated experimental and computational framework, scChIX-seq (single-cell chromatin immunocleavage and unmixing sequencing), to map several histone marks in single cells. scChIX-seq multiplexes two histone marks together in single cells, then computationally deconvolves the signal using training data from respective histone mark profiles. This framework learns the cell-type-specific correlation structure between histone marks, and therefore does not require a priori assumptions of their genomic distributions. Using scChIX-seq, we demonstrate multimodal analysis of histone marks in single cells across a range of mark combinations. Modeling dynamics of in vitro macrophage differentiation enables integrated analysis of chromatin velocity. Overall, scChIX-seq unlocks systematic interrogation of the interplay between histone modifications in single cells.","lang":"eng"}],"publication_status":"published","article_type":"original","publication":"Nature Biotechnology","volume":41,"date_created":"2023-01-08T23:00:53Z","type":"journal_article","file":[{"creator":"dernst","date_updated":"2023-08-16T11:30:45Z","date_created":"2023-08-16T11:30:45Z","content_type":"application/pdf","access_level":"open_access","file_size":12040976,"success":1,"relation":"main_file","checksum":"668447a1c8d360b68f8aaf9e08ed644f","file_name":"2023_NatureBioTech_Yeung.pdf","file_id":"14066"}],"ddc":["570"],"tmp":{"short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"publisher":"Springer Nature","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"scChIX-seq infers dynamic relationships between histone modifications in single cells","year":"2023","date_updated":"2025-04-23T08:45:24Z","pmid":1,"_id":"12106","citation":{"ama":"Yeung J, Florescu M, Zeller P, De Barbanson BA, Wellenstein MD, Van Oudenaarden A. scChIX-seq infers dynamic relationships between histone modifications in single cells. <i>Nature Biotechnology</i>. 2023;41:813–823. doi:<a href=\"https://doi.org/10.1038/s41587-022-01560-3\">10.1038/s41587-022-01560-3</a>","ieee":"J. Yeung, M. Florescu, P. Zeller, B. A. De Barbanson, M. D. Wellenstein, and A. Van Oudenaarden, “scChIX-seq infers dynamic relationships between histone modifications in single cells,” <i>Nature Biotechnology</i>, vol. 41. Springer Nature, pp. 813–823, 2023.","short":"J. Yeung, M. Florescu, P. Zeller, B.A. De Barbanson, M.D. Wellenstein, A. Van Oudenaarden, Nature Biotechnology 41 (2023) 813–823.","ista":"Yeung J, Florescu M, Zeller P, De Barbanson BA, Wellenstein MD, Van Oudenaarden A. 2023. scChIX-seq infers dynamic relationships between histone modifications in single cells. Nature Biotechnology. 41, 813–823.","mla":"Yeung, Jake, et al. “ScChIX-Seq Infers Dynamic Relationships between Histone Modifications in Single Cells.” <i>Nature Biotechnology</i>, vol. 41, Springer Nature, 2023, pp. 813–823, doi:<a href=\"https://doi.org/10.1038/s41587-022-01560-3\">10.1038/s41587-022-01560-3</a>.","chicago":"Yeung, Jake, Maria Florescu, Peter Zeller, Buys Anton De Barbanson, Max D. Wellenstein, and Alexander Van Oudenaarden. “ScChIX-Seq Infers Dynamic Relationships between Histone Modifications in Single Cells.” <i>Nature Biotechnology</i>. Springer Nature, 2023. <a href=\"https://doi.org/10.1038/s41587-022-01560-3\">https://doi.org/10.1038/s41587-022-01560-3</a>.","apa":"Yeung, J., Florescu, M., Zeller, P., De Barbanson, B. A., Wellenstein, M. D., &#38; Van Oudenaarden, A. (2023). scChIX-seq infers dynamic relationships between histone modifications in single cells. <i>Nature Biotechnology</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41587-022-01560-3\">https://doi.org/10.1038/s41587-022-01560-3</a>"},"publication_identifier":{"issn":["1087-0156"],"eissn":["1546-1696"]},"oa_version":"Published Version","department":[{"_id":"ScienComp"}],"status":"public","quality_controlled":"1","external_id":{"isi":["000909067600003"],"pmid":["36593403"]},"date_published":"2023-06-01T00:00:00Z","oa":1,"isi":1,"intvolume":"        41","author":[{"id":"123012b2-db30-11eb-b4d8-a35840c0551b","orcid":"0000-0003-1732-1559","last_name":"Yeung","full_name":"Yeung, Jake","first_name":"Jake"},{"first_name":"Maria","full_name":"Florescu, Maria","last_name":"Florescu"},{"first_name":"Peter","full_name":"Zeller, Peter","last_name":"Zeller"},{"full_name":"De Barbanson, Buys Anton","last_name":"De Barbanson","first_name":"Buys Anton"},{"first_name":"Max D.","full_name":"Wellenstein, Max D.","last_name":"Wellenstein"},{"full_name":"Van Oudenaarden, Alexander","last_name":"Van Oudenaarden","first_name":"Alexander"}],"acknowledgement":"We thank M. van Loenhout for experimental advice on purifying cell types from the bone marrow, R. van der Linden for expertise with FACS and M. Blotenburg for help with cell typing the mouse organogenesis dataset. We thank M. Saraswat and O. Stegle for discussions on multinomial distributions. This work was supported by a European Research Council Advanced grant (ERC-AdG 742225-IntScOmics); Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) TOP grant (NWO CW 714.016.001) and NWO grant (OCENW.GROOT.2019.017); the Swiss National Science Foundation Early Postdoc Mobility (P2ELP3-184488 to P.Z. and P2BSP3-174991 to J.Y.); Marie Sklodowska-Curie Actions Postdoc (798573 to P.Z.) and the Human Frontier for Science Program Long-Term Fellowships (LT000209-2018-L to P.Z. and LT000097-2019-L to J.Y.). This work is part of the Oncode Institute which is financed partly by the Dutch Cancer Society.","corr_author":"1","page":"813–823","file_date_updated":"2023-08-16T11:30:45Z","month":"06","doi":"10.1038/s41587-022-01560-3","has_accepted_license":"1","article_processing_charge":"No","language":[{"iso":"eng"}],"scopus_import":"1","day":"01"},{"citation":{"ama":"Mitiouchkina T, Mishin AS, Gonzalez Somermeyer L, et al. Plants with genetically encoded autoluminescence. <i>Nature Biotechnology</i>. 2020;38:944-946. doi:<a href=\"https://doi.org/10.1038/s41587-020-0500-9\">10.1038/s41587-020-0500-9</a>","mla":"Mitiouchkina, Tatiana, et al. “Plants with Genetically Encoded Autoluminescence.” <i>Nature Biotechnology</i>, vol. 38, Springer Nature, 2020, pp. 944–46, doi:<a href=\"https://doi.org/10.1038/s41587-020-0500-9\">10.1038/s41587-020-0500-9</a>.","ista":"Mitiouchkina T, Mishin AS, Gonzalez Somermeyer L, Markina NM, Chepurnyh TV, Guglya EB, Karataeva TA, Palkina KA, Shakhova ES, Fakhranurova LI, Chekova SV, Tsarkova AS, Golubev YV, Negrebetsky VV, Dolgushin SA, Shalaev PV, Shlykov D, Melnik OA, Shipunova VO, Deyev SM, Bubyrev AI, Pushin AS, Choob VV, Dolgov SV, Kondrashov F, Yampolsky IV, Sarkisyan KS. 2020. Plants with genetically encoded autoluminescence. Nature Biotechnology. 38, 944–946.","ieee":"T. Mitiouchkina <i>et al.</i>, “Plants with genetically encoded autoluminescence,” <i>Nature Biotechnology</i>, vol. 38. Springer Nature, pp. 944–946, 2020.","short":"T. Mitiouchkina, A.S. Mishin, L. Gonzalez Somermeyer, N.M. Markina, T.V. Chepurnyh, E.B. Guglya, T.A. Karataeva, K.A. Palkina, E.S. Shakhova, L.I. Fakhranurova, S.V. Chekova, A.S. Tsarkova, Y.V. Golubev, V.V. Negrebetsky, S.A. Dolgushin, P.V. Shalaev, D. Shlykov, O.A. Melnik, V.O. Shipunova, S.M. Deyev, A.I. Bubyrev, A.S. Pushin, V.V. Choob, S.V. Dolgov, F. Kondrashov, I.V. Yampolsky, K.S. Sarkisyan, Nature Biotechnology 38 (2020) 944–946.","apa":"Mitiouchkina, T., Mishin, A. S., Gonzalez Somermeyer, L., Markina, N. M., Chepurnyh, T. V., Guglya, E. B., … Sarkisyan, K. S. (2020). Plants with genetically encoded autoluminescence. <i>Nature Biotechnology</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41587-020-0500-9\">https://doi.org/10.1038/s41587-020-0500-9</a>","chicago":"Mitiouchkina, Tatiana, Alexander S. Mishin, Louisa Gonzalez Somermeyer, Nadezhda M. Markina, Tatiana V. Chepurnyh, Elena B. Guglya, Tatiana A. Karataeva, et al. “Plants with Genetically Encoded Autoluminescence.” <i>Nature Biotechnology</i>. Springer Nature, 2020. <a href=\"https://doi.org/10.1038/s41587-020-0500-9\">https://doi.org/10.1038/s41587-020-0500-9</a>."},"publication_identifier":{"eissn":["1546-1696"],"issn":["1087-0156"]},"date_updated":"2025-04-14T07:49:47Z","pmid":1,"_id":"7889","year":"2020","title":"Plants with genetically encoded autoluminescence","ec_funded":1,"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publisher":"Springer Nature","related_material":{"link":[{"relation":"erratum","url":"https://doi.org/10.1038/s41587-020-0578-0"}]},"file":[{"creator":"dernst","embargo":"2021-03-01","content_type":"application/pdf","date_updated":"2021-03-02T23:30:03Z","date_created":"2020-08-28T08:57:07Z","file_size":1180086,"relation":"main_file","access_level":"open_access","file_id":"8316","checksum":"1b30467500ec6277229a875b06e196d0","file_name":"2020_NatureBiotech_Mitiouchkina.pdf"}],"ddc":["570"],"date_created":"2020-05-25T15:02:00Z","type":"journal_article","publication":"Nature Biotechnology","volume":38,"abstract":[{"lang":"eng","text":"Autoluminescent plants engineered to express a bacterial bioluminescence gene cluster in plastids have not been widely adopted because of low light output. We engineered tobacco plants with a fungal bioluminescence system that converts caffeic acid (present in all plants) into luciferin and report self-sustained luminescence that is visible to the naked eye. Our findings could underpin development of a suite of imaging tools for plants."}],"article_type":"original","publication_status":"published","scopus_import":"1","article_processing_charge":"No","language":[{"iso":"eng"}],"day":"27","has_accepted_license":"1","doi":"10.1038/s41587-020-0500-9","file_date_updated":"2021-03-02T23:30:03Z","month":"04","acknowledgement":"This study was designed, performed and funded by Planta LLC. We thank K. Wood for assisting in manuscript development. Planta acknowledges support from the Skolkovo Innovation Centre. We thank D. Bolotin and the Milaboratory (milaboratory.com) for access to computing and storage infrastructure. We thank S. Shakhov for providing\r\nphotography equipment. The Synthetic Biology Group is funded by the MRC London Institute of Medical Sciences (UKRI MC-A658-5QEA0, K.S.S.). K.S.S. is supported by an Imperial College Research Fellowship. Experiments were partially carried out using equipment provided by the Institute of Bioorganic Chemistry of the Russian Academy\r\nof Sciences Сore Facility (CKP IBCH; supported by the Russian Ministry of Education and Science Grant RFMEFI62117X0018). The F.A.K. lab is supported by ERC grant agreement 771209—CharFL. This project received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie\r\nGrant Agreement 665385. K.S.S. acknowledges support by President’s Grant 075-15-2019-411. Design and assembly of some of the plasmids was supported by Russian Science Foundation grant 19-74-10102. Imaging experiments were partially supported by Russian Science Foundation grant 17-14-01169p. LC-MS/MS analyses of extracts were\r\nsupported by Russian Science Foundation grant 16-14-00052p. Design and assembly of plasmids was partially supported by grant 075-15-2019-1789 from the Ministry of Science and Higher Education of the Russian Federation allocated to the Center for Precision Genome Editing and Genetic Technologies for Biomedicine. The authors\r\nwould like to acknowledge the work of Genomics Core Facility of the Skolkovo Institute of Science and Technology, which performed the sequencing and bioinformatic analysis.","author":[{"full_name":"Mitiouchkina, Tatiana","last_name":"Mitiouchkina","first_name":"Tatiana"},{"first_name":"Alexander S.","full_name":"Mishin, Alexander S.","last_name":"Mishin"},{"id":"4720D23C-F248-11E8-B48F-1D18A9856A87","first_name":"Louisa","last_name":"Gonzalez Somermeyer","full_name":"Gonzalez Somermeyer, Louisa","orcid":"0000-0001-9139-5383"},{"first_name":"Nadezhda M.","full_name":"Markina, Nadezhda M.","last_name":"Markina"},{"first_name":"Tatiana V.","last_name":"Chepurnyh","full_name":"Chepurnyh, Tatiana V."},{"first_name":"Elena B.","last_name":"Guglya","full_name":"Guglya, Elena B."},{"first_name":"Tatiana A.","last_name":"Karataeva","full_name":"Karataeva, Tatiana A."},{"first_name":"Kseniia A.","last_name":"Palkina","full_name":"Palkina, Kseniia A."},{"first_name":"Ekaterina S.","full_name":"Shakhova, Ekaterina S.","last_name":"Shakhova"},{"first_name":"Liliia I.","last_name":"Fakhranurova","full_name":"Fakhranurova, Liliia I."},{"first_name":"Sofia V.","full_name":"Chekova, Sofia V.","last_name":"Chekova"},{"first_name":"Aleksandra S.","last_name":"Tsarkova","full_name":"Tsarkova, Aleksandra S."},{"first_name":"Yaroslav V.","last_name":"Golubev","full_name":"Golubev, Yaroslav V."},{"first_name":"Vadim V.","last_name":"Negrebetsky","full_name":"Negrebetsky, Vadim V."},{"last_name":"Dolgushin","full_name":"Dolgushin, Sergey A.","first_name":"Sergey A."},{"last_name":"Shalaev","full_name":"Shalaev, Pavel V.","first_name":"Pavel V."},{"first_name":"Dmitry","full_name":"Shlykov, Dmitry","last_name":"Shlykov"},{"last_name":"Melnik","full_name":"Melnik, Olesya A.","first_name":"Olesya A."},{"first_name":"Victoria O.","last_name":"Shipunova","full_name":"Shipunova, Victoria O."},{"first_name":"Sergey M.","full_name":"Deyev, Sergey M.","last_name":"Deyev"},{"full_name":"Bubyrev, Andrey I.","last_name":"Bubyrev","first_name":"Andrey I."},{"first_name":"Alexander S.","last_name":"Pushin","full_name":"Pushin, Alexander S."},{"full_name":"Choob, Vladimir V.","last_name":"Choob","first_name":"Vladimir V."},{"last_name":"Dolgov","full_name":"Dolgov, Sergey V.","first_name":"Sergey V."},{"orcid":"0000-0001-8243-4694","full_name":"Kondrashov, Fyodor","last_name":"Kondrashov","first_name":"Fyodor","id":"44FDEF62-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Yampolsky, Ilia V.","last_name":"Yampolsky","first_name":"Ilia V."},{"first_name":"Karen S.","full_name":"Sarkisyan, Karen S.","last_name":"Sarkisyan"}],"page":"944-946","intvolume":"        38","isi":1,"date_published":"2020-04-27T00:00:00Z","project":[{"name":"Characterizing the fitness landscape on population and global scales","call_identifier":"H2020","_id":"26580278-B435-11E9-9278-68D0E5697425","grant_number":"771209"}],"external_id":{"pmid":["32341562"],"isi":["000529298800003"]},"oa":1,"quality_controlled":"1","status":"public","oa_version":"Submitted Version","department":[{"_id":"FyKo"}]},{"volume":37,"publication":"Nature Biotechnology","article_type":"original","publication_status":"published","abstract":[{"text":"Multiple sequence alignments (MSAs) are used for structural1,2 and evolutionary predictions1,2, but the complexity of aligning large datasets requires the use of approximate solutions3, including the progressive algorithm4. Progressive MSA methods start by aligning the most similar sequences and subsequently incorporate the remaining sequences, from leaf-to-root, based on a guide-tree. Their accuracy declines substantially as the number of sequences is scaled up5. We introduce a regressive algorithm that enables MSA of up to 1.4 million sequences on a standard workstation and substantially improves accuracy on datasets larger than 10,000 sequences. Our regressive algorithm works the other way around to the progressive algorithm and begins by aligning the most dissimilar sequences. It uses an efficient divide-and-conquer strategy to run third-party alignment methods in linear time, regardless of their original complexity. Our approach will enable analyses of extremely large genomic datasets such as the recently announced Earth BioGenome Project, which comprises 1.5 million eukaryotic genomes6.","lang":"eng"}],"related_material":{"record":[{"status":"public","id":"13059","relation":"research_data"}]},"type":"journal_article","date_created":"2019-12-15T23:00:43Z","year":"2019","publisher":"Springer Nature","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","ec_funded":1,"title":"Large multiple sequence alignments with a root-to-leaf regressive method","publication_identifier":{"eissn":["1546-1696"],"issn":["1087-0156"]},"citation":{"ama":"Garriga E, Di Tommaso P, Magis C, et al. Large multiple sequence alignments with a root-to-leaf regressive method. <i>Nature Biotechnology</i>. 2019;37(12):1466-1470. doi:<a href=\"https://doi.org/10.1038/s41587-019-0333-6\">10.1038/s41587-019-0333-6</a>","short":"E. Garriga, P. Di Tommaso, C. Magis, I. Erb, L. Mansouri, A. Baltzis, H. Laayouni, F. Kondrashov, E. Floden, C. Notredame, Nature Biotechnology 37 (2019) 1466–1470.","ieee":"E. Garriga <i>et al.</i>, “Large multiple sequence alignments with a root-to-leaf regressive method,” <i>Nature Biotechnology</i>, vol. 37, no. 12. Springer Nature, pp. 1466–1470, 2019.","mla":"Garriga, Edgar, et al. “Large Multiple Sequence Alignments with a Root-to-Leaf Regressive Method.” <i>Nature Biotechnology</i>, vol. 37, no. 12, Springer Nature, 2019, pp. 1466–70, doi:<a href=\"https://doi.org/10.1038/s41587-019-0333-6\">10.1038/s41587-019-0333-6</a>.","ista":"Garriga E, Di Tommaso P, Magis C, Erb I, Mansouri L, Baltzis A, Laayouni H, Kondrashov F, Floden E, Notredame C. 2019. Large multiple sequence alignments with a root-to-leaf regressive method. Nature Biotechnology. 37(12), 1466–1470.","chicago":"Garriga, Edgar, Paolo Di Tommaso, Cedrik Magis, Ionas Erb, Leila Mansouri, Athanasios Baltzis, Hafid Laayouni, Fyodor Kondrashov, Evan Floden, and Cedric Notredame. “Large Multiple Sequence Alignments with a Root-to-Leaf Regressive Method.” <i>Nature Biotechnology</i>. Springer Nature, 2019. <a href=\"https://doi.org/10.1038/s41587-019-0333-6\">https://doi.org/10.1038/s41587-019-0333-6</a>.","apa":"Garriga, E., Di Tommaso, P., Magis, C., Erb, I., Mansouri, L., Baltzis, A., … Notredame, C. (2019). Large multiple sequence alignments with a root-to-leaf regressive method. <i>Nature Biotechnology</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41587-019-0333-6\">https://doi.org/10.1038/s41587-019-0333-6</a>"},"_id":"7181","date_updated":"2025-07-10T11:54:19Z","pmid":1,"oa":1,"external_id":{"pmid":["31792410"],"isi":["000500748900021"]},"project":[{"_id":"26580278-B435-11E9-9278-68D0E5697425","name":"Characterizing the fitness landscape on population and global scales","call_identifier":"H2020","grant_number":"771209"}],"date_published":"2019-12-01T00:00:00Z","oa_version":"Submitted Version","department":[{"_id":"FyKo"}],"quality_controlled":"1","status":"public","page":"1466-1470","author":[{"first_name":"Edgar","full_name":"Garriga, Edgar","last_name":"Garriga"},{"first_name":"Paolo","last_name":"Di Tommaso","full_name":"Di Tommaso, Paolo"},{"first_name":"Cedrik","last_name":"Magis","full_name":"Magis, Cedrik"},{"last_name":"Erb","full_name":"Erb, Ionas","first_name":"Ionas"},{"last_name":"Mansouri","full_name":"Mansouri, Leila","first_name":"Leila"},{"last_name":"Baltzis","full_name":"Baltzis, Athanasios","first_name":"Athanasios"},{"last_name":"Laayouni","full_name":"Laayouni, Hafid","first_name":"Hafid"},{"last_name":"Kondrashov","full_name":"Kondrashov, Fyodor","orcid":"0000-0001-8243-4694","first_name":"Fyodor","id":"44FDEF62-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Floden","full_name":"Floden, Evan","first_name":"Evan"},{"first_name":"Cedric","last_name":"Notredame","full_name":"Notredame, Cedric"}],"isi":1,"intvolume":"        37","doi":"10.1038/s41587-019-0333-6","month":"12","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6894943/","open_access":"1"}],"day":"01","article_processing_charge":"No","language":[{"iso":"eng"}],"scopus_import":"1","issue":"12"}]