دورية أكاديمية
أعرض في EDS

Automated counting of Drosophila imaginal disc cell nuclei.

التفاصيل البيبلوغرافية
العنوان: Automated counting of Drosophila imaginal disc cell nuclei.
المؤلفون: Sanchez Bosch P; Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA., Axelrod JD; Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA.
المصدر: Biology open [Biol Open] 2024 Feb 15; Vol. 13 (2). Date of Electronic Publication: 2024 Feb 22.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Company of Biologists Ltd Country of Publication: England NLM ID: 101578018 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2046-6390 (Electronic) Linking ISSN: 20466390 NLM ISO Abbreviation: Biol Open Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Cambridge : Company of Biologists Ltd.
مواضيع طبية MeSH: Drosophila* , Imaginal Discs*, Animals ; Drosophila melanogaster ; Larva ; Cell Nucleus
مستخلص: Automated image quantification workflows have dramatically improved over the past decade, enriching image analysis and enhancing the ability to achieve statistical power. These analyses have proved especially useful for studies in organisms such as Drosophila melanogaster, where it is relatively simple to obtain high sample numbers for downstream analyses. However, the developing wing, an intensively utilized structure in developmental biology, has eluded efficient cell counting workflows due to its highly dense cellular population. Here, we present efficient automated cell counting workflows capable of quantifying cells in the developing wing. Our workflows can count the total number of cells or count cells in clones labeled with a fluorescent nuclear marker in imaginal discs. Moreover, by training a machine-learning algorithm we have developed a workflow capable of segmenting and counting twin-spot labeled nuclei, a challenging problem requiring distinguishing heterozygous and homozygous cells in a background of regionally varying intensity. Our workflows could potentially be applied to any tissue with high cellular density, as they are structure-agnostic, and only require a nuclear label to segment and count cells.
Competing Interests: Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(© 2024. Published by The Company of Biologists Ltd.)
التعليقات: Update of: bioRxiv. 2023 May 26;:. (PMID: 37292877)
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معلومات مُعتمدة: P40 OD018537 United States OD NIH HHS; R35 GM131914 United States GM NIGMS NIH HHS; P400PB_199258 Switzerland SNSF_ Swiss National Science Foundation; R35 GM131914 United States NH NIH HHS
فهرسة مساهمة: Keywords: Drosophila; Clonal analysis; Image quantification; Imaginal discs
تواريخ الأحداث: Date Created: 20240212 Date Completed: 20240223 Latest Revision: 20240302
رمز التحديث: 20240302
مُعرف محوري في PubMed: PMC10903266
DOI: 10.1242/bio.060254
PMID: 38345430
قاعدة البيانات: MEDLINE
الوصف
تدمد:2046-6390
DOI:10.1242/bio.060254