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Application of Gray Level co-Occurrence Matrix Algorithm for Detection of Discrete Structural Changes in Cell Nuclei After Exposure to Iron Oxide Nanoparticles and 6-Hydroxydopamine

Published online by Cambridge University Press:  18 June 2019

Dubravka Nikolovski ,
Jelena Cumic  and
Igor Pantic
Dubravka Nikolovski
Affiliation:
Institute of Public Health Pancevo, Pasterova 2, Pancevo, Serbia
Jelena Cumic
Affiliation:
Clinical Center of Serbia, School of Medicine, University in Belgrade, Dr.KosteTodorovića 8, RS-11129, Belgrade, Serbia
Igor Pantic*
Affiliation:
University of Belgrade, Faculty of Medicine, Institute of Medical Physiology, Laboratory for cellular physiology, Visegradska 26/II, RS-11129, Belgrade, Serbia University of Haifa, 199 Abba Hushi Blvd., Mount Carmel, Haifa, IL-3498838, Israel
*
*Author for correspondence: Igor Pantic, E-mail: [email protected]
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Abstract

The gray level co-occurrence matrix (GLCM) algorithm is a contemporary computational biology method which, today, is frequently used to detect small changes in texture that are not visible using conventional techniques. We demonstrate that the toxic compound 6-hydroxydopamine (6-OHDA) and iron oxide nanoparticles (IONPS) have opposite effects on GLCM features of cell nuclei. Saccharomyces cerevisiae yeast cells were treated with 6-OHDA and IONPs, and imaging with GLCM analysis was performed at three different time points: 30 min, 60 min, and 120 min after the treatment. A total of 200 cell nuclei were analyzed, and for each nucleus, 5 GLCM parameters were calculated: Angular second moment (ASM), Inverse difference moment (IDM), Contrast (CON), Correlation (COR) and Sum Variance (SVAR). Exposure to IONPs was associated with the increase of ASM and IDM while the values of SVAR and COR were reduced. Treatment with 6-OHDA was associated with the increase of SVAR and CON, while the values of nuclear ASM and IDM were reduced. This is the first study to indicate that IONPs and 6-OHDA have opposite effects on nuclear texture. Also, to the best of our knowledge, this is the first study to apply the GLCM algorithm in Saccharomyces cerevisiae yeast cells in this experimental setting.

Keywords

cellnanomaterialnucleusoxidopaminestructuretexture
Type
Biological Applications
Information
Microscopy and Microanalysis , Volume 25 , Issue 4 , August 2019 , pp. 982 - 988
Copyright
Copyright © Microscopy Society of America 2019 

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