Abstract
Super-resolution microscopy coupled with multiplexing techniques can resolve specific spatial arrangements of different components within molecular complexes. However, reliable quantification and analysis of such specific organization is extremely problematic because it is frequently obstructed by random co-localization incidents between crowded molecular species and the intrinsic heterogeneity of molecular complexes. To address this, we present a Triple-Pair-Correlation (TPC) analysis approach for unbiased interpretation of the spatial organization of molecular assemblies in crowded three-color super-resolution (SR) images. We validate this approach using simulated data, as well as SR images of DNA replication foci in human cells. This demonstrates the applicability of TPC in deciphering the specific spatial organization of molecular complexes hidden in dense multi-color super-resolution images.
Highlights
Optical super-resolution (SR) imaging techniques greatly surpass diffraction-limited microscopy, enabling the visualization of subcellular architectures with an accuracy of tens of nanometers[1,2,3,4]
The TPC approach generates a correlation profile derived from three independent geometric features, providing accurate quantification of the spatial arrangements of three different species labeled with different colors within a specific molecular assembly
For each molecule located at vector coordinates R in channel 1 (CH1), the average probability of finding a molecule located at R + r1 in channel 2 (CH2), and another molecule located at R + r2 in channel 3 (CH3) is given by the TPC function (equation (1) and Fig. 1a(iii)): Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, 550 1st Avenue, New York, NY 10016, USA
Summary
Optical super-resolution (SR) imaging techniques greatly surpass diffraction-limited microscopy, enabling the visualization of subcellular architectures with an accuracy of tens of nanometers[1,2,3,4]. We report a Triple-Pair-Correlation (TPC) approach[14] for unbiased analysis of the organization of molecular complexes in three-color SR images.
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