Publication: Nanocarrier imaging at single-cell resolution across entire mouse bodies with deep learning
| dc.contributor.coauthor | Luo, Jie | |
| dc.contributor.coauthor | Molbay, Muge | |
| dc.contributor.coauthor | Chen, Ying | |
| dc.contributor.coauthor | Horvath, Izabela | |
| dc.contributor.coauthor | Kadletz, Karoline | |
| dc.contributor.coauthor | Kick, Benjamin | |
| dc.contributor.coauthor | Zhao, Shan | |
| dc.contributor.coauthor | Al-Maskari, Rami | |
| dc.contributor.coauthor | Singh, Inderjeet | |
| dc.contributor.coauthor | Ali, Mayar | |
| dc.contributor.coauthor | Bhatia, Harsharan Singh | |
| dc.contributor.coauthor | Minde, David-Paul | |
| dc.contributor.coauthor | Negwer, Moritz | |
| dc.contributor.coauthor | Hoeher, Luciano | |
| dc.contributor.coauthor | Calandra, Gian Marco | |
| dc.contributor.coauthor | Groschup, Bernhard | |
| dc.contributor.coauthor | Su, Jinpeng | |
| dc.contributor.coauthor | Kimna, Ceren | |
| dc.contributor.coauthor | Rong, Zhouyi | |
| dc.contributor.coauthor | Galensowske, Nikolas | |
| dc.contributor.coauthor | Todorov, Mihail Ivilinov | |
| dc.contributor.coauthor | Jeridi, Denise | |
| dc.contributor.coauthor | Ohn, Tzu-Lun | |
| dc.contributor.coauthor | Roth, Stefan | |
| dc.contributor.coauthor | Simats, Alba | |
| dc.contributor.coauthor | Singh, Vikramjeet | |
| dc.contributor.coauthor | Khalin, Igor | |
| dc.contributor.coauthor | Pan, Chenchen | |
| dc.contributor.coauthor | Arús, Bernardo A. | |
| dc.contributor.coauthor | Bruns, Oliver T. | |
| dc.contributor.coauthor | Zeidler, Reinhard | |
| dc.contributor.coauthor | Liesz, Arthur | |
| dc.contributor.coauthor | Protzer, Ulrike | |
| dc.contributor.coauthor | Plesnila, Nikolaus | |
| dc.contributor.coauthor | Ussar, Siegfried | |
| dc.contributor.coauthor | Hellal, Farida | |
| dc.contributor.coauthor | Paetzold, Johannes | |
| dc.contributor.coauthor | Elsner, Markus | |
| dc.contributor.coauthor | Dietz, Hendrik | |
| dc.contributor.department | School of Medicine | |
| dc.contributor.kuauthor | Ertürk, Ali Maximilian | |
| dc.contributor.schoolcollegeinstitute | SCHOOL OF MEDICINE | |
| dc.date.accessioned | 2025-05-22T10:36:00Z | |
| dc.date.available | 2025-05-22 | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Efficient and accurate nanocarrier development for targeted drug delivery is hindered by a lack of methods to analyze its cell-level biodistribution across whole organisms. Here we present Single Cell Precision Nanocarrier Identification (SCP-Nano), an integrated experimental and deep learning pipeline to comprehensively quantify the targeting of nanocarriers throughout the whole mouse body at single-cell resolution. SCP-Nano reveals the tissue distribution patterns of lipid nanoparticles (LNPs) after different injection routes at doses as low as 0.0005 mg kg-1-far below the detection limits of conventional whole body imaging techniques. We demonstrate that intramuscularly injected LNPs carrying SARS-CoV-2 spike mRNA reach heart tissue, leading to proteome changes, suggesting immune activation and blood vessel damage. SCP-Nano generalizes to various types of nanocarriers, including liposomes, polyplexes, DNA origami and adeno-associated viruses (AAVs), revealing that an AAV2 variant transduces adipocytes throughout the body. SCP-Nano enables comprehensive three-dimensional mapping of nanocarrier distribution throughout mouse bodies with high sensitivity and should accelerate the development of precise and safe nanocarrier-based therapeutics. | |
| dc.description.fulltext | Yes | |
| dc.description.harvestedfrom | Manual | |
| dc.description.indexedby | WOS | |
| dc.description.indexedby | Scopus | |
| dc.description.openaccess | Gold OA | |
| dc.description.publisherscope | International | |
| dc.description.readpublish | N/A | |
| dc.description.sponsoredbyTubitakEu | TÜBİTAK | |
| dc.description.sponsorship | Vascular Dementia Research Foundation; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology [390857198]; DFG [390857198, EXC 2145, TR 296, 457586042, FOR 2879 (LI-2534/5-1)]; German Federal Ministry of Education and Research (Bundesministerium fur Bildung und Forschung (BMBF)) within the NATON collaboration [01KX2121]; European Research Council Consolidator grant [GA 865323]; Nomis Heart Atlas project grant (Nomis Foundation); BMBF (HIVacToGC); Helmholtz AI [ZT-I-PF-5-094]; Turkish Ministry of Education; European Research Council [ERC-StGs 802305]; China Scholarship Council; [SFB 1052] | |
| dc.description.version | Published Version | |
| dc.identifier.doi | 10.1038/s41587-024-02528-1 | |
| dc.identifier.eissn | 1546-1696 | |
| dc.identifier.embargo | No | |
| dc.identifier.filenameinventoryno | IR06242 | |
| dc.identifier.issn | 1087-0156 | |
| dc.identifier.quartile | Q1 | |
| dc.identifier.scopus | 2-s2.0-85217244775 | |
| dc.identifier.uri | https://doi.org/10.1038/s41587-024-02528-1 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14288/29519 | |
| dc.identifier.wos | 001395739100001 | |
| dc.keywords | Controlled drug delivery | |
| dc.keywords | Nanorods | |
| dc.keywords | Targeted drug delivery | |
| dc.language.iso | eng | |
| dc.publisher | Nature Research | |
| dc.relation.affiliation | Koç University | |
| dc.relation.collection | Koç University Institutional Repository | |
| dc.relation.ispartof | Nature Biotechnology | |
| dc.relation.openaccess | Yes | |
| dc.rights | CC BY (Attribution) | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Biotechnology and applied microbiology | |
| dc.title | Nanocarrier imaging at single-cell resolution across entire mouse bodies with deep learning | |
| dc.type | Journal Article | |
| dspace.entity.type | Publication | |
| person.familyName | Ertürk | |
| person.givenName | Ali Maximilian | |
| relation.isOrgUnitOfPublication | d02929e1-2a70-44f0-ae17-7819f587bedd | |
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