Literature DB >> 33596821

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

Momoko Imakubo1,2,3, Jun Takayama3, Hatsumi Okada2,3, Shuichi Onami4,5,6.   

Abstract

BACKGROUND: Oocyte 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.
RESULTS: We 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 nematode Caenorhabditis 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 feature Correlation (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.
CONCLUSIONS: The Max-min value and COR objectively quantify age-related changes in C. elegans oocyte in Nomarski DIC microscopy images. Our methods provide new opportunities for understanding the mechanism underlying oocyte aging.

Entities:  

Keywords:  Caenorhabditis elegans; Gray level co-occurrence matrix; Image texture analysis; Nomarski DIC microscopy; Oocyte aging; Statistical image processing

Year:  2021        PMID: 33596821     DOI: 10.1186/s12859-021-03990-3

Source DB:  PubMed          Journal:  BMC Bioinformatics        ISSN: 1471-2105            Impact factor:   3.169


  2 in total

1.  Genetic analysis of tissue aging in Caenorhabditis elegans: a role for heat-shock factor and bacterial proliferation.

Authors:  Delia Garigan; Ao-Lin Hsu; Andrew G Fraser; Ravi S Kamath; Julie Ahringer; Cynthia Kenyon
Journal:  Genetics       Date:  2002-07       Impact factor: 4.562

2.  SSBD: a database of quantitative data of spatiotemporal dynamics of biological phenomena.

Authors:  Yukako Tohsato; Kenneth H L Ho; Koji Kyoda; Shuichi Onami
Journal:  Bioinformatics       Date:  2016-07-13       Impact factor: 6.937

  2 in total
  1 in total

Review 1.  Germline Stem and Progenitor Cell Aging in C. elegans.

Authors:  Theadora Tolkin; E Jane Albert Hubbard
Journal:  Front Cell Dev Biol       Date:  2021-07-08
  1 in total

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