摘要：The nanoscale molecular assembly of mammalian viruses during their infectious life cycle remains poorly understood. Their small dimensions, generally bellow the 300nm diffraction limit of light microscopes, has limited most imaging studies to electron microscopy. The recent development of super-resolution (SR) light microscopy now allows the visualisation of viral structures at resolutions of tens of nanometers. In addition, these techniques provide the added benefit of molecular specific labelling and the capacity to investigate viral structural dynamics using live-cell microscopy. However, there is a lack of robust analytical tools that allow for precise mapping of viral structure within the setting of infection. Here we present an open-source analytical framework that combines super-resolution imaging and naïve single-particle analysis to generate unbiased molecular models. This tool, VirusMapper, is a high-throughput, user-friendly, ImageJ-based software package allowing for automatic statistical mapping of conserved multi-molecular structures, such as viral substructures or intact viruses. We demonstrate the usability of VirusMapper by applying it to SIM and STED images of vaccinia virus in isolation and when engaged with host cells. VirusMapper allows for the generation of accurate, high-content, molecular specific virion models and detection of nanoscale changes in viral architecture.
