| dc.contributor.author | Vickovic, S | |
| dc.contributor.author | Lötstedt, B | |
| dc.contributor.author | Klughammer, J | |
| dc.contributor.author | Mages, S | |
| dc.contributor.author | Segerstolpe, Å | |
| dc.contributor.author | Rozenblatt-Rosen, O | |
| dc.contributor.author | Regev, A | |
| dc.date.accessioned | 2023-01-13T15:33:02Z | |
| dc.date.available | 2023-01-13T15:33:02Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/147099 | |
| dc.description.abstract | <jats:title>Abstract</jats:title><jats:p>The spatial organization of cells and molecules plays a key role in tissue function in homeostasis and disease. Spatial transcriptomics has recently emerged as a key technique to capture and positionally barcode RNAs directly in tissues. Here, we advance the application of spatial transcriptomics at scale, by presenting Spatial Multi-Omics (SM-Omics) as a fully automated, high-throughput all-sequencing based platform for combined and spatially resolved transcriptomics and antibody-based protein measurements. SM-Omics uses DNA-barcoded antibodies, immunofluorescence or a combination thereof, to scale and combine spatial transcriptomics and spatial antibody-based multiplex protein detection. SM-Omics allows processing of up to 64 in situ spatial reactions or up to 96 sequencing-ready libraries, of high complexity, in a ~2 days process. We demonstrate SM-Omics in the mouse brain, spleen and colorectal cancer model, showing its broad utility as a high-throughput platform for spatial multi-omics.</jats:p> | en_US |
| dc.language.iso | en | |
| dc.publisher | Springer Science and Business Media LLC | en_US |
| dc.relation.isversionof | 10.1038/S41467-022-28445-Y | en_US |
| dc.rights | Creative Commons Attribution 4.0 International license | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.source | Nature | en_US |
| dc.title | SM-Omics is an automated platform for high-throughput spatial multi-omics | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Vickovic, S, Lötstedt, B, Klughammer, J, Mages, S, Segerstolpe, Å et al. 2022. "SM-Omics is an automated platform for high-throughput spatial multi-omics." Nature Communications, 13 (1). | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Biology | en_US |
| dc.relation.journal | Nature Communications | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2023-01-13T15:22:28Z | |
| dspace.orderedauthors | Vickovic, S; Lötstedt, B; Klughammer, J; Mages, S; Segerstolpe, Å; Rozenblatt-Rosen, O; Regev, A | en_US |
| dspace.date.submission | 2023-01-13T15:22:31Z | |
| mit.journal.volume | 13 | en_US |
| mit.journal.issue | 1 | en_US |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |