Single virus detection by means of atomic force microscopy in combination with advanced image analysis

Abstract

In the present contribution virions of five different virus species, namely Varicella-zoster virus, Porcine teschovirus, Tobacco mosaic virus, Coliphage M13 and Enterobacteria phage PsP3, are investigated using atomic force microscopy (AFM). From the resulting height images quantitative features like maximal height, area and volume of the viruses could be extracted and compared to reference values. Subsequently, these features were accompanied by image moments, which quantify the morphology of the virions. Both types of features could be utilized for an automatic discrimination of the five virus species. The accuracy of this classification model was 96.8%. Thus, a virus detection on a single-particle level using AFM images is possible. Due to the application of advanced image analysis the morphology could be quantified and used for further analysis. Here, an automatic recognition by means of a classification model could be achieved in a reliable and objective manner.

Keywords: Atomic force microscopy; Image analysis; Statistical modeling; Virus detection.