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Statistical analysis of 3D localisation microscopy images for quantification of membrane protein distributions in a platelet clot model

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  • Sandra Mayr
  • Fabian Hauser
  • Sujitha Puthukodan
  • Markus Axmann
  • Janett Göhring
  • Jaroslaw Jacak

Abstract

We present the software platform 2CALM that allows for a comparative analysis of 3D localisation microscopy data representing protein distributions in two biological samples. The in-depth statistical analysis reveals differences between samples at the nanoscopic level using parameters such as cluster-density and -curvature. An automatic classification system combines multiplex and multi-level statistical approaches into one comprehensive parameter for similarity testing of the compared samples. We demonstrated the biological importance of 2CALM, comparing the protein distributions of CD41 and CD62p on activated platelets in a 3D artificial clot. Additionally, using 2CALM, we quantified the impact of the inflammatory cytokine interleukin-1β on platelet activation in clots. The platform is applicable to any other cell type and biological system and can provide new insights into biological and medical applications.Author summary: Single-molecule localisation microscopy (LM) became more accessible over the past years. Companies and research facilities developed instruments for 3D/2D LM, but there is a lack of comparison methods for LM-images. Our tool offers a new comparative analysis of LM data. Our system is capable of showing the difference on the level of single molecule clusters and provides information on differences between images on various scales. We determine if clusters formed of molecule localisations are comparable. We display the difference on density or the shape of these formed clusters for a certain dimension. Since the comparison is performed for all dimensions, the differences between cluster properties are observed very precisely. Thereby, we learn if clusters of molecules are formed and how they differ in both samples. For a fast/concluding comparison, we have added tools which derive a percentage of equality of both images based on all comparison results. The tool is useful for comparison of images of molecules in cells, which are expected to differ from each other (exemplified with platelets). The differences might be caused by drug treatment, different disease progress or other environmental/genetical issues. The analysis is performed at a single cell level as well as cell cluster level.

Suggested Citation

  • Sandra Mayr & Fabian Hauser & Sujitha Puthukodan & Markus Axmann & Janett Göhring & Jaroslaw Jacak, 2020. "Statistical analysis of 3D localisation microscopy images for quantification of membrane protein distributions in a platelet clot model," PLOS Computational Biology, Public Library of Science, vol. 16(6), pages 1-34, June.
    • Handle: RePEc:plo:pcbi00:1007902
    DOI: 10.1371/journal.pcbi.1007902
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    1. Thibault Lagache & Alexandre Grassart & Stéphane Dallongeville & Orestis Faklaris & Nathalie Sauvonnet & Alexandre Dufour & Lydia Danglot & Jean-Christophe Olivo-Marin, 2018. "Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics," Nature Communications, Nature, vol. 9(1), pages 1-15, December.
    2. Jasmine Burguet & Philippe Andrey, 2014. "Statistical Comparison of Spatial Point Patterns in Biological Imaging," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-12, February.
    3. William Day & Herbert Edelsbrunner, 1984. "Efficient algorithms for agglomerative hierarchical clustering methods," Journal of Classification, Springer;The Classification Society, vol. 1(1), pages 7-24, December.
    4. Oleg V. Kim & Rustem I. Litvinov & Mark S. Alber & John W. Weisel, 2017. "Quantitative structural mechanobiology of platelet-driven blood clot contraction," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
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