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Proceedings Paper

Deconstructing autofluorescence: non-invasive detection and monitoring of biochemistry in cells and tissues (Conference Presentation)
Author(s): Ewa M. Goldys; Martin E. Gosnell; Ayad G. Anwer; Juan C. Cassano; Carolyn M. Sue; Saabah B. Mahbub; Sandeep M. Pernichery; David W. Inglis; Partho P. Adhikary; Jalal A. Jazayeri; Michael A. Cahill; Sonia Saad; Carol Pollock; Melanie L. Sutton-Mcdowall; Jeremy G. Thompson

Paper Abstract

Automated and unbiased methods of non-invasive cell monitoring able to deal with complex biological heterogeneity are fundamentally important for biology and medicine. Label-free cell imaging provides information about endogenous fluorescent metabolites, enzymes and cofactors in cells. However extracting high content information from imaging of native fluorescence has been hitherto impossible. Here, we quantitatively characterise cell populations in different tissue types, live or fixed, by using novel image processing and a simple multispectral upgrade of a wide-field fluorescence microscope. Multispectral intrinsic fluorescence imaging was applied to patient olfactory neurosphere-derived cells, cell model of a human metabolic disease MELAS (mitochondrial myopathy, encephalomyopathy, lactic acidosis, stroke-like syndrome). By using an endogenous source of contrast, subtle metabolic variations have been detected between living cells in their full morphological context which made it possible to distinguish healthy from diseased cells before and after therapy. Cellular maps of native fluorophores, flavins, bound and free NADH and retinoids unveiled subtle metabolic signatures and helped uncover significant cell subpopulations, in particular a subpopulation with compromised mitochondrial function. The versatility of our method is further illustrated by detecting genetic mutations in cancer, non-invasive monitoring of CD90 expression, label-free tracking of stem cell differentiation, identifying stem cell subpopulations with varying functional characteristics, tissue diagnostics in diabetes, and assessing the condition of preimplantation embryos. Our optimal discrimination approach enables statistical hypothesis testing and intuitive visualisations where previously undetectable differences become clearly apparent.

Paper Details

Date Published: 17 May 2016
PDF: 1 pages
Proc. SPIE 9703, Optical Biopsy XIV: Toward Real-Time Spectroscopic Imaging and Diagnosis, 97030R (17 May 2016); doi: 10.1117/12.2212443
Show Author Affiliations
Ewa M. Goldys, Macquarie Univ. (Australia)
Martin E. Gosnell, Macquarie Univ. (Australia)
Ayad G. Anwer, Macquarie Univ. (Australia)
Juan C. Cassano, The Univ. of Sydney (Australia)
Carolyn M. Sue, The Univ. of Sydney (Australia)
Saabah B. Mahbub, Macquarie Univ. (Australia)
Sandeep M. Pernichery, Macquarie Univ. (Australia)
David W. Inglis, Macquarie Univ. (Australia)
Partho P. Adhikary, Charles Sturt Univ. (Australia)
Jalal A. Jazayeri, Charles Sturt Univ. (Australia)
Michael A. Cahill, Charles Sturt Univ. (Australia)
Sonia Saad, The Univ. of Sydney (Australia)
Carol Pollock, The Univ. of Sydney (Australia)
Melanie L. Sutton-Mcdowall, The Univ. of Adelaide (Australia)
Jeremy G. Thompson, The Univ. of Adelaide (Australia)


Published in SPIE Proceedings Vol. 9703:
Optical Biopsy XIV: Toward Real-Time Spectroscopic Imaging and Diagnosis
Robert R. Alfano; Stavros G. Demos, Editor(s)

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