کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5527243 1401573 2017 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Research articleHigh-content image informatics of the structural nuclear protein NuMA parses trajectories for stem/progenitor cell lineages and oncogenic transformation
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی تحقیقات سرطان
پیش نمایش صفحه اول مقاله
Research articleHigh-content image informatics of the structural nuclear protein NuMA parses trajectories for stem/progenitor cell lineages and oncogenic transformation
چکیده انگلیسی


- High-content analysis of nuclear shape and organization classify stem and progenitor cells poised for distinct lineages.
- Early oncogenic changes in mesenchymal stem cells (MSCs) are also detected with nuclear descriptors.
- A new class of cancer-mitigating biomaterials was identified based on image informatics.
- Textural metrics of the nuclear structural protein NuMA are sufficient to parse emergent cell phenotypes.

Stem and progenitor cells that exhibit significant regenerative potential and critical roles in cancer initiation and progression remain difficult to characterize. Cell fates are determined by reciprocal signaling between the cell microenvironment and the nucleus; hence parameters derived from nuclear remodeling are ideal candidates for stem/progenitor cell characterization. Here we applied high-content, single cell analysis of nuclear shape and organization to examine stem and progenitor cells destined to distinct differentiation endpoints, yet undistinguishable by conventional methods. Nuclear descriptors defined through image informatics classified mesenchymal stem cells poised to either adipogenic or osteogenic differentiation, and oligodendrocyte precursors isolated from different regions of the brain and destined to distinct astrocyte subtypes. Nuclear descriptors also revealed early changes in stem cells after chemical oncogenesis, allowing the identification of a class of cancer-mitigating biomaterials. To capture the metrology of nuclear changes, we developed a simple and quantitative “imaging-derived” parsing index, which reflects the dynamic evolution of the high-dimensional space of nuclear organizational features. A comparative analysis of parsing outcomes via either nuclear shape or textural metrics of the nuclear structural protein NuMA indicates the nuclear shape alone is a weak phenotypic predictor. In contrast, variations in the NuMA organization parsed emergent cell phenotypes and discerned emergent stages of stem cell transformation, supporting a prognosticating role for this protein in the outcomes of nuclear functions.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Experimental Cell Research - Volume 351, Issue 1, 1 February 2017, Pages 11-23
نویسندگان
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