Novel approach in soil zymography to assess enzyme activity in the rhizosphere

Soil zymography is increasingly used to study soil-plant root interactions and microbial hotspots in the rhizosphere. Over the past decade, several approaches have been proposed to quantitatively estimate enzymatic activity in rhizosphere hotspots using root masks based on normal light (NL) root photos. However, these approaches are often time-consuming and typically applied to small regions of zymograms. Therefore, obtaining automated, but precise root masks for crops with various root systems is necessary to improve and standardize soil zymography techniques in rhizosphere studies. Here we introduced a newly developed approach that involves photographing roots under ultraviolet (UV) light after applying zymography to create a root mask for six crops: maize, wheat, barley, rye, lupine, and faba bean grown on Loamy Luvisol. Our study revealed significant improvement in the quality of root masks thresholded from UV light root photos compared to NL photos. The β-glucosidase activity measured within the root mask thresholded from UV root photos enabled accurate estimation of the root-associated enzyme activity for all six crops. This offers substantial advantages over measuring enzyme activity across the entire zymogram, that often leads to imprecise interpretations of zymography results in the rhizosphere studies. Moreover, UV root photos after zymography application allow to detect metabolically active and growing roots. Additionally, high contrast of UV root photos and clear delineation of roots on the soil surface for all studied crops enables using these photos for precise alignment of soil images of different origin in co-localization analysis. • Distinguishing root from non-root-associated hotspots on zymograms is challenging • The UV root photo-based root mask highlights rhizosphere hotspots on zymograms • Post-zymography UV root photos reveal areas of active growth and metabolic activity • β-glucosidase activity within root mask accurately reflects root-derived hotspots