Cellular susceptibility and oxidative stress response to menadione of logarithmic, quiescent, and nonquiescent Saccharomyces cerevisiae cell populations

The aim of the present study was to compare cellular susceptibility and oxidative stress response of S. cerevisiae logarithmic (log), quiescent (Q), and non-quiescent (NQ) cell populations to menadione – a well-known inducer of oxidative stress. Three main approaches were used: microbiological – cell survival, molecular – constant field gel electrophoresis for detection of DNA double-strand breaks (DSB), and biochemical – measurement of reactive oxygen species (ROS) levels, oxidized proteins, lipid peroxidation, glutathione, superoxide dismutase (SOD) and catalase on S. cerevisiae haploid strain BY4741. The doses causing 20% (LD20) and 50% (LD50) lethality were calculated. The effect of menadione as a well-known oxidative stress inducer is compared in the log, Q, and NQ cells. Survival data reveal that Q cells are the most susceptible to menadione with LD50 corresponding to 9 µM menadione. On the other hand, dose-dependent DSB induction is found only in Q cells confirming the results shown above. No effect on DSBs levels is observed in log and NQ cells. Further, the oxidative stress response of the cell populations is clarified. Results show significantly higher levels of SOD and ROS in Q cells than in log cells after the treatment with 100 µM menadione. On the other side, higher induction of oxidized proteins, malondialdehyde, and glutathione is observed after menadione treatment of log cells. Our study provides evidence that Saccharomyces cerevisiae quiescent cells are the most susceptible to the menadione action. It might be suggested that the DNA damaging and genotoxic action of menadione in Saccharomyces cerevisiae quiescent cells could be related to ROS production

Saccharomyces cerevisiae yeast cells as a test system for assessing Zeocin toxicity

Having unique genetic machinery and a high degree of conservation with higher eukaryotes, the yeast Saccharomyces cerevisiae is recognised as a smart experimental system for studying the modes of chemical toxicity. The present study was undertaken to elucidate the changes in the intracellular redox homeostasis and key macromolecule structure following exposure to Zeocin. Cell populations of logarithmic, quiescent (Q) and non-quiescent (NQ) cells of Saccharomyces cerevisiae BY4741 were used as a model to examine the cytotoxic effect of this radiomimetic. The levels of endogenous ROS, oxidized lipids, carbonylated proteins, and glutathione were analysed after treatment with Zeocin (IC50). An increase in ROS production and respectively increased oxidative stress was detected in all three types of cell populations, with the highest degree being observed in proliferating S. cerevisiae BY4741 cells. The stress response of both proliferating and stationary phase (Q and NQ) cells to Zeocin included an overexpression of glutathione. The quiescent cells also showed very low DNA susceptibility to high Zeocin concentration (100–300 µg/ml), presented as no induced double-strand breaks (DSBs) in the macromolecule. Based on our research it could be concluded that the cellular physiological state is a critical factor determining the resistance to environmental stress with Q cells being the most robust

Software compatibility analysis for quantitative measures of [18F]flutemetamol amyloid PET burden in mild cognitive impairment

Rationale: Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods. Methods: Composite SUVr using the pons as the reference region was generated from [18F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVrpons was applied. Quantitative results from MIM Software’s MIMneuro, Syntermed’s NeuroQ, Hermes Medical Solutions’ BRASS and GE Healthcare’s CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores. Results: Using an Aβ positivity threshold of ≥ 0.6 SUVrpons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss’) and individual software pairings (Cohen’s), were ≥ 0.9 signifying “almost perfect” inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957–0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r 2 = 0.98). Conclusion: Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [18F]flutemetamol amyloid PET with a ≥ 0.6 SUVrpons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages