There are no further conflicts of interest associated with this publication.įluorescence microscopy allows the tagging of particular macromolecules of interest and the subsequent study of their role in biological processes. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products to declare. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: NVIDIA corporation sponsored the GPU that was used in this project. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All the samples that were analysed in this paper is available from the following link: DOI: 10.6084/m9.figshare.6670742.įunding: NVIDIA corporation sponsored the GPU that was used in this project. Received: MaAccepted: JPublished: August 29, 2018Ĭopyright: © 2018 Theart et al. We conclude that, using 3D colocalization analysis, biologically relevant samples can be interrogated and assessed with greater precision, thereby better exploiting the potential of fluorescence-based image analysis in biomedical research.Ĭitation: Theart RP, Loos B, Powrie YSL, Niesler TR (2018) Improved region of interest selection and colocalization analysis in three-dimensional fluorescence microscopy samples using virtual reality. This behavior could not be reliably detected using a 2D based projection. Moreover, by carefully delimiting the 3D structures under analysis using the 3D VR system, we were able to reveal a time dependent loss in colocalization between the Tau and microtubule network as an early event in neuronal injury. We demonstrate that performing colocalization analysis in 3D enhances its sensitivity, leading to a greater number of statistically significant differences than could be established when using 2D methods. Using a neuronal injury model, we investigate the change in colocalization between Tau and acetylated α-tubulin at control conditions, after 6 hours and again after 24 hours. We calculate several key colocalization metrics using both 2D and 3D derived super-resolved structured illumination-based data sets. Using a virtual reality (VR) enabled system, we demonstrate that 3D visualization, sample interrogation and analysis can be achieved in a highly controlled and precise manner. Furthermore, 2D ROI selections cannot adequately select complex 3D structures which may inadvertently lead to either the exclusion of relevant or the inclusion of irrelevant data points, consequently affecting the accuracy of the colocalization analysis. However, these 2D projections exclude much of the available data. Although modern fluorescence microscopy produces detailed three-dimensional (3D) datasets, colocalization analysis and region of interest (ROI) selection is most commonly performed two-dimensionally (2D) using maximum intensity projections (MIP).
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