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Article: Multimodal FACED imaging for large-scale single-cell morphological profiling

TitleMultimodal FACED imaging for large-scale single-cell morphological profiling
Authors
Issue Date2021
PublisherAIP Publishing: Open Access Journals. The Journal's web site is located at http://scitation.aip.org/content/aip/journal/app
Citation
APL Photonics, 2021, v. 6 n. 7, p. article no. 070801 How to Cite?
AbstractFree-space angular-chirp-enhanced delay (FACED) is an ultrafast laser-scanning technique that allows for high imaging speed at the scale orders of magnitude greater than the current technologies. However, this speed advantage has only been restricted to bright-field and fluorescence imaging—limiting the variety of image contents and hindering its applicability in image-based bioassay, which increasingly demands rich phenotypic readout at a large scale. Here, we present a new high-speed quantitative phase imaging (QPI) based on time-interleaved phase-gradient FACED image detection. We further integrate this system with a microfluidic flow cytometer platform that enables synchronized and co-registered single-cell QPI and fluorescence imaging at an imaging throughput of 77 000 cells/s with sub-cellular resolution. Combined with deep learning, this platform empowers comprehensive image-based profiling of single-cell biophysical phenotypes that can offer not only sufficient label-free power for cell-type classification but also cell-cycle phase tracking with high accuracy comparable to the gold-standard fluorescence method. This platform further enables correlative, compartment-specific single-cell analysis of the spatially resolved biophysical profiles at the throughput inaccessible with existing QPI methods. The high imaging throughput and content given by this multimodal FACED imaging system could open new opportunities in image-based single-cell analysis, especially systematic analysis that correlates the biophysical and biochemical information of cells, and provide new mechanistic insights into biophysical heterogeneities in many biological processes.
Persistent Identifierhttp://hdl.handle.net/10722/303947
ISSN
2023 Impact Factor: 5.4
2023 SCImago Journal Rankings: 1.880
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYIP, GGK-
dc.contributor.authorLO, MCK-
dc.contributor.authorYan, W-
dc.contributor.authorLEE, KCM-
dc.contributor.authorLAI, QTK-
dc.contributor.authorWong, KKY-
dc.contributor.authorTsia, KK-
dc.date.accessioned2021-09-23T08:53:02Z-
dc.date.available2021-09-23T08:53:02Z-
dc.date.issued2021-
dc.identifier.citationAPL Photonics, 2021, v. 6 n. 7, p. article no. 070801-
dc.identifier.issn2378-0967-
dc.identifier.urihttp://hdl.handle.net/10722/303947-
dc.description.abstractFree-space angular-chirp-enhanced delay (FACED) is an ultrafast laser-scanning technique that allows for high imaging speed at the scale orders of magnitude greater than the current technologies. However, this speed advantage has only been restricted to bright-field and fluorescence imaging—limiting the variety of image contents and hindering its applicability in image-based bioassay, which increasingly demands rich phenotypic readout at a large scale. Here, we present a new high-speed quantitative phase imaging (QPI) based on time-interleaved phase-gradient FACED image detection. We further integrate this system with a microfluidic flow cytometer platform that enables synchronized and co-registered single-cell QPI and fluorescence imaging at an imaging throughput of 77 000 cells/s with sub-cellular resolution. Combined with deep learning, this platform empowers comprehensive image-based profiling of single-cell biophysical phenotypes that can offer not only sufficient label-free power for cell-type classification but also cell-cycle phase tracking with high accuracy comparable to the gold-standard fluorescence method. This platform further enables correlative, compartment-specific single-cell analysis of the spatially resolved biophysical profiles at the throughput inaccessible with existing QPI methods. The high imaging throughput and content given by this multimodal FACED imaging system could open new opportunities in image-based single-cell analysis, especially systematic analysis that correlates the biophysical and biochemical information of cells, and provide new mechanistic insights into biophysical heterogeneities in many biological processes.-
dc.languageeng-
dc.publisherAIP Publishing: Open Access Journals. The Journal's web site is located at http://scitation.aip.org/content/aip/journal/app-
dc.relation.ispartofAPL Photonics-
dc.rightsAuthor names, Journal Title, Vol. 6, Article ID 070801, (2021); licensed under a Creative Commons Attribution (CC BY) license.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleMultimodal FACED imaging for large-scale single-cell morphological profiling-
dc.typeArticle-
dc.identifier.emailWong, KKY: kywong@eee.hku.hk-
dc.identifier.emailTsia, KK: tsia@hku.hk-
dc.identifier.authorityWong, KKY=rp00189-
dc.identifier.authorityTsia, KK=rp01389-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1063/5.0054714-
dc.identifier.scopuseid_2-s2.0-85109184618-
dc.identifier.hkuros325281-
dc.identifier.volume6-
dc.identifier.issue7-
dc.identifier.spagearticle no. 070801-
dc.identifier.epagearticle no. 070801-
dc.identifier.isiWOS:000668677500002-
dc.publisher.placeUnited States-

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