Viscoelasticity as a biomarker for high-throughput flow cytometry
The mechanical properties of living cells are a label-free biophysical marker of cell viability and health; however, their use has been greatly limited by low measurement throughput. Although examining individual cells at high rates is now commonplace with fluorescence activated cell sorters, develo...
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| Published in: | Biophysical journal Vol. 105; no. 10; p. 2281 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
United States
19.11.2013
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| Subjects: | |
| ISSN: | 1542-0086, 1542-0086 |
| Online Access: | Get more information |
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| Summary: | The mechanical properties of living cells are a label-free biophysical marker of cell viability and health; however, their use has been greatly limited by low measurement throughput. Although examining individual cells at high rates is now commonplace with fluorescence activated cell sorters, development of comparable techniques that nondestructively probe cell mechanics remains challenging. A fundamental hurdle is the signal response time. Where light scattering and fluorescence signatures are virtually instantaneous, the cell stress relaxation, typically occurring on the order of seconds, limits the potential speed of elastic property measurement. To overcome this intrinsic barrier to rapid analysis, we show here that cell viscoelastic properties measured at frequencies far higher than those associated with cell relaxation can be used as a means of identifying significant differences in cell phenotype. In these studies, we explore changes in erythrocyte mechanical properties caused by infection with Plasmodium falciparum and find that the elastic response alone fails to detect malaria at high frequencies. At timescales associated with rapid assays, however, we observe that the inelastic response shows significant changes and can be used as a reliable indicator of infection, establishing the dynamic viscoelasticity as a basis for nondestructive mechanical analogs of current high-throughput cell classification methods. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1542-0086 1542-0086 |
| DOI: | 10.1016/j.bpj.2013.10.003 |