Characterization of the impact of GMP/GDP synthesis inhibition on replicative lifespan extension in yeast

Low-Molecular Weight Compounds that Extend the Chronological Lifespan of Yeasts, Saccharomyces cerevisiae, and Schizosaccharomyces pombe

Yeast is an excellent model organism for research for regulating aging and lifespan, and the studies have made many contributions to date, including identifying various factors and signaling pathways related to aging and lifespan. More than 20 years have passed since molecular biological perspectives are adopted in this research field, and intracellular factors and signal pathways that control aging and lifespan have evolutionarily conserved from yeast to mammals. Furthermore, these findings have been applied to control the aging and lifespan of various model organisms by adjustment of the nutritional environment, genetic manipulation, and drug treatment using low-molecular weight compounds. Among these, drug treatment is easier than the other methods, and research into drugs that regulate aging and lifespan is consequently expected to become more active. Chronological lifespan, a definition of yeast lifespan, refers to the survival period of a cell population under nondividing conditions. Herein, low-molecular weight compounds are summarized that extend the chronological lifespan of Saccharomyces cerevisiae and Schizosaccharomyces pombe, along with their intracellular functions. The low-molecular weight compounds are also discussed that extend the lifespan of other model organisms. Compounds that have so far only been studied in yeast may soon extend lifespan in other organisms.

Integrated metabolomics and transcriptomics reveal glyphosate based-herbicide induced reproductive toxicity through disturbing energy and nucleotide metabolism in mice testes

Glyphosate is a widely used herbicide that has deleterious effects on animal reproduction. However, details regarding the systematic mechanisms of glyphosate-induced reproductive toxicity are limited. This study aimed to investigate the toxic effects of glyphosate-based herbicide (GBH) on reproduction in mice exposed to 0 (control group), 50 (low-dose group), 250 (middle-dose group), and 500 (high-dose group) mg/kg/day GBH for 30 days. Toxicological parameters, metabolomics, and transcriptomics were performed to reveal GBH-induced reproductive toxicity. Our findings demonstrated that GBH exposure damaged mitochondrial pyknosis and the nuclear membrane of spermatogonia. GBH triggered a significant increase in sperm malformations in the high-dose group. Omics data showed that GBH impaired the Krebs cycle and respiratory chain, blocked pyruvate metabolism and glycolysis/gluconeogenesis, and influenced the pentose phosphate pathway and nucleotide synthesis and metabolism. Overall, the multi-omics results revealed systematic and comprehensive evidence of the adverse effects of GBH exposure, providing new insights into the reproductive toxicity of organophosphorus pesticides.

A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels

Stochastic gene expression leads to inherent variability in expression outcomes even in isogenic single-celled organisms grown in the same environment. The Drop-Seq technology facilitates transcriptomic studies of individual mammalian cells, and it has had transformative effects on the characterization of cell identity and function based on single-cell transcript counts. However, application of this technology to organisms with different cell size and morphology characteristics has been challenging. Here we present yeastDrop-Seq, a yeast-optimized platform for quantifying the number of distinct mRNA molecules in a cell-specific manner in individual yeast cells. Using yeastDrop-Seq, we measured the transcriptomic impact of the lifespan-extending compound mycophenolic acid and its epistatic agent guanine. Each treatment condition had a distinct transcriptomic footprint on isogenic yeast cells as indicated by distinct clustering with clear separations among the different groups. The yeastDrop-Seq platform facilitates transcriptomic profiling of yeast cells for basic science and biotechnology applications.