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- Publisher Website: 10.1002/cyto.a.23765
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- PMID: 31012276
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Article: Quantitative phase imaging flow cytometry for ultra-large-scale single-cell biophysical phenotyping
Title | Quantitative phase imaging flow cytometry for ultra-large-scale single-cell biophysical phenotyping |
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Authors | |
Keywords | imaging flow cytometry label-free biophysical phenotyping quantitative phase imaging ultrafast single cell imaging |
Issue Date | 2019 |
Publisher | John Wiley & Sons, Inc. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0196-4763/ |
Citation | Cytometry Part A, 2019, v. 95 n. 5, p. 510-520 How to Cite? |
Abstract | Cellular biophysical properties are the effective label-free phenotypes indicative of differences in cell types, states, and functions. However, current biophysical phenotyping methods largely lack the throughput and specificity required in the majority of cell-based assays that involve large-scale single-cell characterization for inquiring the inherently complex heterogeneity in many biological systems. Further confounded by the lack of reported robust reproducibility and quality control, widespread adoption of single-cell biophysical phenotyping in mainstream cytometry remains elusive. To address this challenge, here we present a label-free imaging flow cytometer built upon a recently developed ultrafast quantitative phase imaging (QPI) technique, coined multi-ATOM, that enables label-free single-cell QPI, from which a multitude of subcellularly resolvable biophysical phenotypes can be parametrized, at an experimentally recorded throughput of >10,000 cells/s—a capability that is otherwise inaccessible in current QPI. With the aim to translate multi-ATOM into mainstream cytometry, we report robust system calibration and validation (from image acquisition to phenotyping reproducibility) and thus demonstrate its ability to establish high-dimensional single-cell biophysical phenotypic profiles at ultra-large-scale (>1,000,000 cells). Such a combination of throughput and content offers sufficiently high label-free statistical power to classify multiple human leukemic cell types at high accuracy (~92–97%). This system could substantiate the significance of high-throughput QPI flow cytometry in enabling next frontier in large-scale image-derived single-cell analysis applied in biological discovery and cost-effective clinical diagnostics. © 2019 International Society for Advancement of Cytometry. © 2019 International Society for Advancement of Cytometry |
Persistent Identifier | http://hdl.handle.net/10722/276219 |
ISSN | 2023 Impact Factor: 2.5 2023 SCImago Journal Rankings: 1.331 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Lee, CM | - |
dc.contributor.author | Wang, M | - |
dc.contributor.author | Cheah, KSE | - |
dc.contributor.author | Chan, GCF | - |
dc.contributor.author | So, HKH | - |
dc.contributor.author | Wong, KKY | - |
dc.contributor.author | Tsia, KKM | - |
dc.date.accessioned | 2019-09-10T02:58:24Z | - |
dc.date.available | 2019-09-10T02:58:24Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Cytometry Part A, 2019, v. 95 n. 5, p. 510-520 | - |
dc.identifier.issn | 1552-4922 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276219 | - |
dc.description.abstract | Cellular biophysical properties are the effective label-free phenotypes indicative of differences in cell types, states, and functions. However, current biophysical phenotyping methods largely lack the throughput and specificity required in the majority of cell-based assays that involve large-scale single-cell characterization for inquiring the inherently complex heterogeneity in many biological systems. Further confounded by the lack of reported robust reproducibility and quality control, widespread adoption of single-cell biophysical phenotyping in mainstream cytometry remains elusive. To address this challenge, here we present a label-free imaging flow cytometer built upon a recently developed ultrafast quantitative phase imaging (QPI) technique, coined multi-ATOM, that enables label-free single-cell QPI, from which a multitude of subcellularly resolvable biophysical phenotypes can be parametrized, at an experimentally recorded throughput of >10,000 cells/s—a capability that is otherwise inaccessible in current QPI. With the aim to translate multi-ATOM into mainstream cytometry, we report robust system calibration and validation (from image acquisition to phenotyping reproducibility) and thus demonstrate its ability to establish high-dimensional single-cell biophysical phenotypic profiles at ultra-large-scale (>1,000,000 cells). Such a combination of throughput and content offers sufficiently high label-free statistical power to classify multiple human leukemic cell types at high accuracy (~92–97%). This system could substantiate the significance of high-throughput QPI flow cytometry in enabling next frontier in large-scale image-derived single-cell analysis applied in biological discovery and cost-effective clinical diagnostics. © 2019 International Society for Advancement of Cytometry. © 2019 International Society for Advancement of Cytometry | - |
dc.language | eng | - |
dc.publisher | John Wiley & Sons, Inc. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0196-4763/ | - |
dc.relation.ispartof | Cytometry Part A | - |
dc.rights | Preprint This is the pre-peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Postprint This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. | - |
dc.subject | imaging flow cytometry | - |
dc.subject | label-free biophysical phenotyping | - |
dc.subject | quantitative phase imaging | - |
dc.subject | ultrafast single cell imaging | - |
dc.title | Quantitative phase imaging flow cytometry for ultra-large-scale single-cell biophysical phenotyping | - |
dc.type | Article | - |
dc.identifier.email | Cheah, KSE: hrmbdkc@hku.hk | - |
dc.identifier.email | Chan, GCF: gcfchan@hku.hk | - |
dc.identifier.email | So, HKH: hso@eee.hku.hk | - |
dc.identifier.email | Wong, KKY: kywong@eee.hku.hk | - |
dc.identifier.email | Tsia, KKM: tsia@hku.hk | - |
dc.identifier.authority | Cheah, KSE=rp00342 | - |
dc.identifier.authority | Chan, GCF=rp00431 | - |
dc.identifier.authority | So, HKH=rp00169 | - |
dc.identifier.authority | Wong, KKY=rp00189 | - |
dc.identifier.authority | Tsia, KKM=rp01389 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1002/cyto.a.23765 | - |
dc.identifier.pmid | 31012276 | - |
dc.identifier.scopus | eid_2-s2.0-85064716554 | - |
dc.identifier.hkuros | 303379 | - |
dc.identifier.hkuros | 319006 | - |
dc.identifier.volume | 95 | - |
dc.identifier.issue | 5 | - |
dc.identifier.spage | 510 | - |
dc.identifier.epage | 520 | - |
dc.identifier.isi | WOS:000489698300006 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1552-4922 | - |