Issue 7, 2015

Colocalization of fluorescence and Raman microscopic images for the identification of subcellular compartments: a validation study

Abstract

A major promise of Raman microscopy is the label-free detailed recognition of cellular and subcellular structures. To this end, identifying colocalization patterns between Raman spectral images and fluorescence microscopic images is a key step to annotate subcellular components in Raman spectroscopic images. While existing approaches to resolve subcellular structures are based on fluorescence labeling, we propose a combination of a colocalization scheme with subsequent training of a supervised classifier that allows label-free resolution of cellular compartments. Our colocalization scheme unveils statistically significant overlapping regions by identifying correlation between the fluorescence color channels and clusters from unsupervised machine learning methods like hierarchical cluster analysis. The colocalization scheme is used as a pre-selection to gather appropriate spectra as training data. These spectra are used in the second part as training data to establish a supervised random forest classifier to automatically identify lipid droplets and nucleus. We validate our approach by examining Raman spectral images overlaid with fluorescence labelings of different cellular compartments, indicating that specific components may indeed be identified label-free in the spectral image. A Matlab implementation of our colocalization software is available at http://www.mathworks.de/matlabcentral/fileexchange/46608-frcoloc.

Graphical abstract: Colocalization of fluorescence and Raman microscopic images for the identification of subcellular compartments: a validation study

Supplementary files

Article information

Article type
Paper
Submitted
22 Nov. 2014
Accepted
09 Febr. 2015
First published
09 Febr. 2015

Analyst, 2015,140, 2360-2368

Author version available

Colocalization of fluorescence and Raman microscopic images for the identification of subcellular compartments: a validation study

S. D. Krauß, D. Petersen, D. Niedieker, I. Fricke, E. Freier, S. F. El-Mashtoly, K. Gerwert and A. Mosig, Analyst, 2015, 140, 2360 DOI: 10.1039/C4AN02153C

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements