mammalian-cell-division-3d-matrices-via-quantitative-confocal

Mammalian Cell Division in 3D Matrices via Quantitative Confocal Reflection Microscopy

The study of how mammalian cell division is regulated in a 3D environment remains largely unexplored despite its physiological relevance and therapeutic ...

Johns Hopkins University

How the division axis is determined in mammalian cells embedded in three-dimensional (3D) matrices remains elusive, despite that many types of cells divide in 3D environments. Cells on two-dimensional (2D) substrates typically round up completely to divide. Here, we show that in 3D collagen matrices, mammalian cells such as HT1080 human fibrosarcoma and MDA-MB-231 breast cancer cells exhibit division modes distinct from their Counterparts on 2D substrates, with a markedly higher fraction of cells remaining highly elongated through mitosis in 3D matrices. The long axis of elongated mitotic cells accurately predicts the division axis, independently of matrix density and cell-matrix interactions. This 3D-specific elongated division mode is determined by the local confinement produced by the matrix and the ability of cells to protrude and locally remodel the matrix via β1 integrin. Elongated division is readily recapitulated using collagen-coated microfabricated channels. Cells depleted of β1 integrin still divide in the elongated mode in microchannels, suggesting that 3D confinement is sufficient to induce the elongated cell-division phenotype.

Local 3D matrix confinement determines division axis through cell shape.

Image-based assays, such as alkaline phosphatase staining or immunocytochemistry for pluripotent markers, are common methods used in the stem cell field to assess pluripotency. Although an increased number of image-analysis approaches have been described, there is still a lack of software availability to automatically quantify pluripotency in large images after pluripotency staining. To address this need, we developed a robust and rapid image processing software, Pluri-IQ, which allows the automatic evaluation of pluripotency in large low-magnification images. Using mouse embryonic stem cells (mESC) as a model, we combined an automated segmentation algorithm with a supervised machine-learning platform to classify colonies as pluripotent, mixed, or differentiated. In addition, Pluri-IQ allows the automatic comparison between different culture conditions. This efficient user-friendly open-source software can be easily implemented in images derived from pluripotent cells or cells that express pluripotent markers (e.g., OCT4-GFP) and can be routinely used, decreasing image assessment bias.

Weitong Chen

Department of Chemical and Biomolecular Engineering

Johns Hopkins University

Mammalian Cell Division in 3D Matrices via Quantitative Confocal Reflection Microscopy

Weitong Chen

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Chemical and Biomolecular Engineering

Johns Hopkins University

Mammalian Cell Division in 3D Matrices via Quantitative Confocal Reflection Microscopy

Department of Chemical and Biomolecular Engineering