Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy

Naomi McReynolds; Fiona G. M. Cooke; Mingzhou Chen; Simon J. Powis; Kishan Dholakia

doi:10.1038/srep43631

Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy

Naomi McReynolds, Fiona G. M. Cooke, Mingzhou Chen, Simon J. Powis, Kishan Dholakia

Research output: Contribution to journal › Article › peer-review

Abstract

The ability to identify and characterise individual cells of the immune system under label-free conditions would be a significant advantage in biomedical and clinical studies where untouched and unmodified cells are required. We present a multi-modal system capable of simultaneously acquiring both single point Raman spectra and digital holographic images of single cells. We use this combined approach to identify and discriminate between immune cell populations CD4+ T cells, B cells and monocytes. We investigate several approaches to interpret the phase images including signal intensity histograms and texture analysis. Both modalities are independently able to discriminate between cell subsets and dual-modality may therefore be used a means
for validation. We demonstrate here sensitivities achieved in the range of 86.8% to 100%, and specificities in the range of 85.4% to 100%. Additionally each modality provides information not available from the other providing both a molecular and a morphological signature of each cell.

Original language	English
Article number	43631
Number of pages	11
Journal	Scientific Reports
Volume	7
DOIs	https://doi.org/10.1038/srep43631
Publication status	Published - 3 Mar 2017

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McReynolds-2017-Multimodal-SREP-43631
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Final published version, 1.21 MBLicence: CC BY

Leverhulme Trust Snr Research Fellowship: Accelerating progress for light sheet microscopy
Dholakia, K. (PI)
The Royal Society
1/09/15 → 31/08/16
Project: Fellowship
EU FP7 FAMOS: Functional Anatomical Molecular Optical Screening
Dholakia, K. (PI)
European Commission
1/10/12 → 31/03/17
Project: Standard
Challening the Limits of Photonics: stru: Challenging the Limits of Photonics: Structured Light
Dholakia, K. (PI), Krauss, T. F. (CoI) & Samuel, I. D. W. (CoI)
EPSRC
1/06/12 → 31/05/17
Project: Standard

Data underpinning- Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy
McReynolds, N. (Creator), Cooke, F. G. M. (Creator), Chen, M. (Creator), Powis, S. J. (Creator) & Dholakia, K. (Supervisor), University of St Andrews, 15 Dec 2017
DOI: 10.17630/432f1c03-2e78-4bb3-8396-236a1dca0b50
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Cite this

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title = "Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy",

abstract = "The ability to identify and characterise individual cells of the immune system under label-free conditions would be a significant advantage in biomedical and clinical studies where untouched and unmodified cells are required. We present a multi-modal system capable of simultaneously acquiring both single point Raman spectra and digital holographic images of single cells. We use this combined approach to identify and discriminate between immune cell populations CD4+ T cells, B cells and monocytes. We investigate several approaches to interpret the phase images including signal intensity histograms and texture analysis. Both modalities are independently able to discriminate between cell subsets and dual-modality may therefore be used a meansfor validation. We demonstrate here sensitivities achieved in the range of 86.8% to 100%, and specificities in the range of 85.4% to 100%. Additionally each modality provides information not available from the other providing both a molecular and a morphological signature of each cell.",

author = "Naomi McReynolds and Cooke, {Fiona G. M.} and Mingzhou Chen and Powis, {Simon J.} and Kishan Dholakia",

note = "This work was supported by the UK Engineering and Physical Sciences Research Council under grant EP/J01771X/1, A European Union FAMOS project (FP7 ICT, 317744), and the {\textquoteright}BRAINS{\textquoteright} 600th anniversary appeal, and Dr. E. Killick. We would also like to thank The RS Macdonald Charitable Trust for funding support. KD acknowledges support of a Royal Society Leverhulme Trust Senior Fellowship. This work was also supported by the PreDiCT-TB consortium [IMI Joint undertaking grant agreement number 115337, resources of which are composed of financial contribution from the European Union{\textquoteright}s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies{\textquoteright} in kind contribution (www.imi.europa.eu)]",

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AU - McReynolds, Naomi

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AU - Chen, Mingzhou

AU - Powis, Simon J.

AU - Dholakia, Kishan

N1 - This work was supported by the UK Engineering and Physical Sciences Research Council under grant EP/J01771X/1, A European Union FAMOS project (FP7 ICT, 317744), and the ’BRAINS’ 600th anniversary appeal, and Dr. E. Killick. We would also like to thank The RS Macdonald Charitable Trust for funding support. KD acknowledges support of a Royal Society Leverhulme Trust Senior Fellowship. This work was also supported by the PreDiCT-TB consortium [IMI Joint undertaking grant agreement number 115337, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution (www.imi.europa.eu)]

PY - 2017/3/3

Y1 - 2017/3/3

N2 - The ability to identify and characterise individual cells of the immune system under label-free conditions would be a significant advantage in biomedical and clinical studies where untouched and unmodified cells are required. We present a multi-modal system capable of simultaneously acquiring both single point Raman spectra and digital holographic images of single cells. We use this combined approach to identify and discriminate between immune cell populations CD4+ T cells, B cells and monocytes. We investigate several approaches to interpret the phase images including signal intensity histograms and texture analysis. Both modalities are independently able to discriminate between cell subsets and dual-modality may therefore be used a meansfor validation. We demonstrate here sensitivities achieved in the range of 86.8% to 100%, and specificities in the range of 85.4% to 100%. Additionally each modality provides information not available from the other providing both a molecular and a morphological signature of each cell.

AB - The ability to identify and characterise individual cells of the immune system under label-free conditions would be a significant advantage in biomedical and clinical studies where untouched and unmodified cells are required. We present a multi-modal system capable of simultaneously acquiring both single point Raman spectra and digital holographic images of single cells. We use this combined approach to identify and discriminate between immune cell populations CD4+ T cells, B cells and monocytes. We investigate several approaches to interpret the phase images including signal intensity histograms and texture analysis. Both modalities are independently able to discriminate between cell subsets and dual-modality may therefore be used a meansfor validation. We demonstrate here sensitivities achieved in the range of 86.8% to 100%, and specificities in the range of 85.4% to 100%. Additionally each modality provides information not available from the other providing both a molecular and a morphological signature of each cell.

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Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy

Abstract

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Projects

Leverhulme Trust Snr Research Fellowship: Accelerating progress for light sheet microscopy

EU FP7 FAMOS: Functional Anatomical Molecular Optical Screening

Challening the Limits of Photonics: stru: Challenging the Limits of Photonics: Structured Light

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Data underpinning- Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy

Cite this