{"title":"DeepQR:用于光学基因表达分析的单分子 QR 码","authors":"Jonathan Jeffet, Barak Hadad, Sahar Froim, Kawsar Kaboub, Keren M. Rabinowitz, Jasline Deek, Sapir Margalit, Iris Dotan, Alon Bahabad, Yuval Ebenstein","doi":"10.1515/nanoph-2024-0236","DOIUrl":null,"url":null,"abstract":"Optical imaging and single-molecule imaging, in particular, utilize fluorescent tags in order to differentiate observed species by color. The degree of color multiplexing is dependent on the available spectral detection window and the ability to distinguish between fluorophores of different colors within this window. Consequently, most single-molecule imaging techniques rely on two to four colors for multiplexing. DeepQR combines compact spectral imaging with deep learning to enable 4 color acquisition with only 3 spectral detection windows. It allows rapid high-throughput acquisition and decoding of hundreds of unique single-molecule color combinations applied here to tag native RNA targets. We validate our method with clinical samples analyzed with the NanoString gene-expression inflammation panel side by side with the commercially available NanoString nCounter system. We demonstrate high concordance with “gold-standard” filter-based imaging and over a four-fold decrease in acquisition time by applying a single snapshot to record four-color barcodes. The new approach paves the path for extreme single-molecule multiplexing.","PeriodicalId":19027,"journal":{"name":"Nanophotonics","volume":"380 1","pages":""},"PeriodicalIF":6.5000,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DeepQR: single-molecule QR codes for optical gene-expression analysis\",\"authors\":\"Jonathan Jeffet, Barak Hadad, Sahar Froim, Kawsar Kaboub, Keren M. Rabinowitz, Jasline Deek, Sapir Margalit, Iris Dotan, Alon Bahabad, Yuval Ebenstein\",\"doi\":\"10.1515/nanoph-2024-0236\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optical imaging and single-molecule imaging, in particular, utilize fluorescent tags in order to differentiate observed species by color. The degree of color multiplexing is dependent on the available spectral detection window and the ability to distinguish between fluorophores of different colors within this window. Consequently, most single-molecule imaging techniques rely on two to four colors for multiplexing. DeepQR combines compact spectral imaging with deep learning to enable 4 color acquisition with only 3 spectral detection windows. It allows rapid high-throughput acquisition and decoding of hundreds of unique single-molecule color combinations applied here to tag native RNA targets. We validate our method with clinical samples analyzed with the NanoString gene-expression inflammation panel side by side with the commercially available NanoString nCounter system. We demonstrate high concordance with “gold-standard” filter-based imaging and over a four-fold decrease in acquisition time by applying a single snapshot to record four-color barcodes. The new approach paves the path for extreme single-molecule multiplexing.\",\"PeriodicalId\":19027,\"journal\":{\"name\":\"Nanophotonics\",\"volume\":\"380 1\",\"pages\":\"\"},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2024-07-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nanophotonics\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.1515/nanoph-2024-0236\",\"RegionNum\":2,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nanophotonics","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1515/nanoph-2024-0236","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
DeepQR: single-molecule QR codes for optical gene-expression analysis
Optical imaging and single-molecule imaging, in particular, utilize fluorescent tags in order to differentiate observed species by color. The degree of color multiplexing is dependent on the available spectral detection window and the ability to distinguish between fluorophores of different colors within this window. Consequently, most single-molecule imaging techniques rely on two to four colors for multiplexing. DeepQR combines compact spectral imaging with deep learning to enable 4 color acquisition with only 3 spectral detection windows. It allows rapid high-throughput acquisition and decoding of hundreds of unique single-molecule color combinations applied here to tag native RNA targets. We validate our method with clinical samples analyzed with the NanoString gene-expression inflammation panel side by side with the commercially available NanoString nCounter system. We demonstrate high concordance with “gold-standard” filter-based imaging and over a four-fold decrease in acquisition time by applying a single snapshot to record four-color barcodes. The new approach paves the path for extreme single-molecule multiplexing.
期刊介绍:
Nanophotonics, published in collaboration with Sciencewise, is a prestigious journal that showcases recent international research results, notable advancements in the field, and innovative applications. It is regarded as one of the leading publications in the realm of nanophotonics and encompasses a range of article types including research articles, selectively invited reviews, letters, and perspectives.
The journal specifically delves into the study of photon interaction with nano-structures, such as carbon nano-tubes, nano metal particles, nano crystals, semiconductor nano dots, photonic crystals, tissue, and DNA. It offers comprehensive coverage of the most up-to-date discoveries, making it an essential resource for physicists, engineers, and material scientists.