Quantification of Confocal Images Using LabVIEW for Tissue Engineering Applications

使用 LabVIEW 对组织工程应用中的共聚焦图像进行量化

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作者:Lauren Sfakis, Tim Kamaldinov, Melinda Larsen, James Castracane, Alexander Khmaladze

Abstract

Quantifying confocal images to enable location of specific proteins of interest in three-dimensional (3D) is important for many tissue engineering (TE) applications. Quantification of protein localization is essential for evaluation of specific scaffold constructs for cell growth and differentiation for application in TE and tissue regeneration strategies. Although obtaining information regarding protein expression levels is important, the location of proteins within cells grown on scaffolds is often the key to evaluating scaffold efficacy. Functional epithelial cell monolayers must be organized with apicobasal polarity with proteins specifically localized to the apical or basolateral regions of cells in many organs. In this work, a customized program was developed using the LabVIEW platform to quantify protein positions in Z-stacks of confocal images of epithelial cell monolayers. The program's functionality is demonstrated through salivary gland TE, since functional salivary epithelial cells must correctly orient many proteins on the apical and basolateral membranes. Bio-LabVIEW Image Matrix Evaluation (Bio-LIME) takes 3D information collected from confocal Z-stack images and processes the fluorescence at each pixel to determine cell heights, nuclei heights, nuclei widths, protein localization, and cell count. As a demonstration of its utility, Bio-LIME was used to quantify the 3D location of the Zonula occludens-1 protein contained within tight junctions and its change in 3D position in response to chemical modification of the scaffold with laminin. Additionally, Bio-LIME was used to demonstrate that there is no advantage of sub-100 nm poly lactic-co-glycolic acid nanofibers over 250 nm fibers for epithelial apicobasal polarization. Bio-LIME will be broadly applicable for quantification of proteins in 3D that are grown in many different contexts.

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