Automated quantification of quantum‐dot‐labelled epidermal growth factor receptor internalization via multiscale image segmentation
Summary The ability to monitor epidermal growth factor receptor (EGFr) internalization specifically, and cellular protein concentrations and activation states in general, has been recently improved by the use of appropriately functionalized quantum dots (QDs), as a result of the long‐lasting fluores...
Saved in:
Published in | Journal of microscopy (Oxford) Vol. 222; no. 1; pp. 22 - 27 |
---|---|
Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Oxford, UK
Blackwell Publishing Ltd
01.04.2006
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Summary
The ability to monitor epidermal growth factor receptor (EGFr) internalization specifically, and cellular protein concentrations and activation states in general, has been recently improved by the use of appropriately functionalized quantum dots (QDs), as a result of the long‐lasting fluorescence, brightness and multicolour of these nanoparticles. However, important quantitative information about locational proteomics is based on the analysis of the properties of many cells and cell cultures on a per‐cell basis, rather than tracking individual events within one cell. Moreover, relative positional information is often gained from traditional staining protocols of distinct cellular compartments that are prone to noise, fading and low contrast. We apply a novel multiscale image segmentation based on region growing to classify automatically objects in fixed cell preparations and to define regional zones in all cells prior to QD concentration measures. This allows rapid quantitative description of EGFr internalization as it changes with incubation time. The capabilities realizable by simultaneous application of confocal imaging and functionalized QDs in conjunction with advanced image analysis are a prerequisite for automated and multiplexed cytomics assays. |
---|---|
Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
ISSN: | 0022-2720 1365-2818 |
DOI: | 10.1111/j.1365-2818.2006.01564.x |