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Statistical image processing quantifies the changes in cytoplasmic texture associated with aging in Caenorhabditis elegans oocytes

Authors :
Momoko Imakubo
Shuichi Onami
Jun Takayama
Hatsumi Okada
Source :
BMC Bioinformatics, BMC Bioinformatics, Vol 22, Iss 1, Pp 1-21 (2021)
Publication Year :
2021
Publisher :
Springer Science and Business Media LLC, 2021.

Abstract

BackgroundOocyte quality decreases with aging, thereby increasing errors in fertilization, chromosome segregation, and embryonic cleavage. Oocyte appearance also changes with aging, suggesting a functional relationship between oocyte quality and appearance. However, no methods are available to objectively quantify age-associated changes in oocyte appearance.ResultsWe show that statistical image processing of Nomarski differential interference contrast microscopy images can be used to quantify age-associated changes in oocyte appearance in the nematodeCaenorhabditis elegans. Max–min value (mean difference between the maximum and minimum intensities within each moving window) quantitatively characterized the difference in oocyte cytoplasmic texture between 1- and 3-day-old adults (Day 1 and Day 3 oocytes, respectively). With an appropriate parameter set, the gray level co-occurrence matrix (GLCM)-based texture featureCorrelation(COR) more sensitively characterized this difference than the Max–min Value. Manipulating the smoothness of and/or adding irregular structures to the cytoplasmic texture of Day 1 oocyte images reproduced the difference in Max–min Value but not in COR between Day 1 and Day 3 oocytes. Increasing the size of granules in synthetic images recapitulated the age-associated changes in COR. Manual measurements validated that the cytoplasmic granules in oocytes become larger with aging.ConclusionsThe Max–min value and COR objectively quantify age-related changes inC. elegansoocyte in Nomarski DIC microscopy images. Our methods provide new opportunities for understanding the mechanism underlying oocyte aging.

Details

ISSN :
14712105
Volume :
22
Database :
OpenAIRE
Journal :
BMC Bioinformatics
Accession number :
edsair.doi.dedup.....37019a4c993c42cf30d2daca8c482f4d