Advanced digital image analysis method dedicated to the characterization of the morphology of filamentous fungus

• Published in: Journal of microscopy (Oxford) 2017-05, Vol.266 (2), p.126-140
• Main Authors: HARDY, N., MOREAUD, M., GUILLAUME, D., AUGIER, F., NIENOW, A., BÉAL, C., BEN CHAABANE, F.
• Format: Article
• Language: English
• Subjects: Automated image analysis; Biotechnology; Chemical and Process Engineering; Engineering Sciences; fermentation; filamentous fungus; Fungi; Life Sciences; Morphology; Shear stress; Trichoderma reesei
• ISSN: 0022-2720; 1365-2818
• DOI: 10.1111/jmi.12523

Summary Filamentous fungi have a complex morphology that induces fermentation process development issues, as a consequence of viscosity increase and diffusion limitations. In order to better understand the relationship between viscosity changes and fungus morphology during fermentations of Trichoderma reesei, an accurate image analysis method has been developed to provide quantitative and representative data for morphological analysis. This method consisted of a new algorithm called FACE that allowed sharp images to be created at all positions, segmentation of fungus, and morphological analysis using skeleton and topological approaches. It was applied and validated by characterizing samples of an industrial strain of Trichoderma reesei that had or had not been exposed to an extreme shear stress. This method allowed many morphological characteristics to be identified, among which nine relevant criteria were extracted, regarding the impact of shear stress on the fungus and on the viscosity of the fermentation medium. Lay description Humans use moulds or filamentous fungi in a lot of industrial applications, mainly to produce drugs (antibiotics) and enzymes that are used to make biofuels or “stone washed” jeans. Moulds are microscopic organisms that are too small to be seen by the naked eye, thus requiring a microscope (for example http://zeiss-campus.magnet.fsu.edu). However, as they form tri‐dimensional structures, classical microscopes are not suitable, because they cannot focus the fungus as a whole. To overcome this challenge, this work developed innovative tools based on focus stacking that permit the taking of sharp pictures of moulds. These tools were coupled to dedicated image analysis software, in order to extract relevant information about moulds from those pictures and to identify morphological criteria allowing differentiation of various morphologies of moulds.