Various external and internal factors damaging DNA constantly disrupt the stability of the genome. Cells use numerous dedicated DNA repair systems to detect damage and restore genomic integrity in a timely manner. Ribonucleotide reductase (RNR) is a key enzyme providing dNTPs for DNA repair. Molecular mechanisms of indirect regulation of yeast RNR activity are well understood, whereas little is known about its direct regulation. The study was aimed at elucidation of the proteasome-dependent mechanism of direct regulation of RNR subunits in Saccharomyces cerevisiae. Proteome analysis followed by Western blot, RT-PCR, and yeast plating analysis showed that upregulation of RNR by proteasome deregulation is associated with yeast hyper resistance to 4-nitroquinoline-1-oxide (4-NQO), a UV-mimetic DNA-damaging drug used in animal models to study oncogenesis. Inhibition of RNR or deletion of RNR regulatory proteins reverses the phenotype of yeast hyper resistance to 4-NQO. We have shown for the first time that the yeast Rnr1 subunit is a substrate of the proteasome, which suggests a common mechanism of RNR regulation in yeast and mammals.

Image analysis is widely applied in plant science for phenotyping and monitoring botanic and agricultural species. Although a lot of software is available, tools integrating image analysis and statistical assessment of seedling growth in large groups of plants are limited or absent, and do not cover the needs of the researchers. In this study, we developed Morley, a free, open-source graphical user interface written in Python. Morley automates the following workflow: (1) group-wise analysis of a few thousand seedlings from multiple images; (2) recognition of seeds, shoots and roots in seedling images; (3) calculation of shoot and root lengths and surface areas, (4) evaluation of statistically significant differences between plant groups, (5) calculation of germination rates, (6) visualization and interpretation. Morley is designed for laboratory studies of biotic effects on seedling growth, when molecular mechanisms underlying morphometric changes are analyzed. Performance was tested using cultivars of T. aestivum, P. sativum on seedlings of up to 1 week old. Accuracy of the measured morphometric parameters was comparable with the ones obtained using ImageJ and manual measurements. Dose-dependent laboratory tests for germination affected by new bioactive compounds and fertilizers, assuming extraction of seedlings from a substrate and/or dissection are among the suggested applications.

Image analysis is widely applied in plant science for phenotyping and monitoring botanic and agricultural species. Although a lot of software is available, tools integrating image analysis and statistical assessment of seedling growth in large groups of plants are limited or absent, and do not cover the needs of researchers. In this study, we developed Morley, a free, open-source graphical user interface written in Python. Morley automates the following workflow: (1) group-wise analysis of a few thousand seedlings from multiple images; (2) recognition of seeds, shoots, and roots in seedling images; (3) calculation of shoot and root lengths and surface area; (4) evaluation of statistically significant differences between plant groups; (5) calculation of germination rates; and (6) visualization and interpretation. Morley is designed for laboratory studies of biotic effects on seedling growth, when the molecular mechanisms underlying the morphometric changes are analyzed. The performance was tested using cultivars of Triticum aestivum and Pisum sativum on seedlings of up to 1 week old. The accuracy of the measured morphometric parameters was comparable with that obtained using ImageJ and manual measurements. Possible applications of Morley include dose-dependent laboratory tests for germination affected by new bioactive compounds and fertilizers.