Combining computer analysis with microscopy

OLYMPUS DIGITAL CAMERA31 March 2016:

CNBP researchers have successfully combined computer analysis with microscopy, to extract highly detailed cellular information that will help distinguish between healthy and diseased cells, in areas as diverse as cancer, injury and inflammation.

The approach, reported in the journal ‘Scientific Reports’, has shown that subtle biochemical signatures of cells can be captured and then categorized, to an extent that has never been seen before.

Paper Title: Quantitative non-invasive cell characterisation and discrimination based on multispectral autofluorescence features.

Authors: Martin E. Gosnell, Ayad G. Anwer, Saabah B. Mahbub, Sandeep Menon Perinchery, David W. Inglis, Partho P. Adhikary, Jalal A. Jazayeri, Michael A. Cahill, Sonia Saad, Carol A. Pollock, Melanie L. Sutton-McDowall, Jeremy G. Thompson & Ewa M. Goldys.

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 autofluorescent metabolites, enzymes and cofactors in cells. However extracting high content information from autofluorescence imaging 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. Our optimal discrimination approach enables statistical hypothesis testing and intuitive visualisations where previously undetectable differences become clearly apparent. Label-free classifications are validated by the analysis of Classification Determinant (CD) antigen expression. The versatility of our method is 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.

The research paper is accessible online. A CNBP media release is also available.