Linking cellular proteostasis to yeast longevity

Replicative aging in yeast involves dynamic intron retention patterns associated with mRNA processing/export and protein ubiquitination

Saccharomyces cerevisiae (baker's yeast) has yielded relevant insights into some of the basic mechanisms of organismal aging. Among these are genomic instability, oxidative stress, caloric restriction and mitochondrial dysfunction. Several genes are known to have an impact on the aging process, with corresponding mutants exhibiting short- or long-lived phenotypes. Research dedicated to unraveling the underlying cellular mechanisms can support the identification of conserved mechanisms of aging in other species. One of the hitherto less studied fields in yeast aging is how the organism regulates its gene expression at the transcriptional level. To our knowledge, we present the first investigation into alternative splicing, particularly intron retention, during replicative aging of S. cerevisiae. This was achieved by utilizing the IRFinder algorithm on a previously published RNA-seq data set by Janssens et al. (2015). In the present work, 44 differentially retained introns in 43 genes were identified during replicative aging. We found that genes with altered intron retention do not display significant changes in overall transcript levels. It was possible to functionally assign distinct groups of these genes to the cellular processes of mRNA processing and export (e.g., YRA1) in early and middle-aged yeast, and protein ubiquitination (e.g., UBC5) in older cells. In summary, our work uncovers a previously unexplored layer of the transcriptional program of yeast aging and, more generally, expands the knowledge on the occurrence of alternative splicing in baker's yeast.

Targeted Deletion of Los1 Homologue Affects the Production of a Recombinant Model Protein in Pichia pastoris

Background:

The methylotrophic yeast Pichia pastoris is an appealing production host for a variety of recombinant proteins, including biologics. In this sense, various genetic- and non-genetic-based techniques have been implemented to improve the production efficiency of this expression platform. Los1 (loss of supression) encodes a non-essential nuclear tRNA exporter in Saccharomyces cerevisiae, which its deletion extends RLS. Herein, a los1-deficient strain of P. pastoris was generated and characterized.

Methods:

A gene disruption cassette was prepared and transformed into an anti-CD22-expressing strain of P. pastoris. A δ los1 mutant was isolated and confirmed. The drug sensitivity of the mutant was also assessed. The growth pattern and the level of anti-CD22 ScFv expression were compared between the parent and mutant strains.

Results:

The los1 homologue was found to be a non-essential gene in P. pastoris. Furthermore, the susceptibility of los1 deletion strain to protein synthesis inhibitors was altered. This strain showed an approximately 1.85-fold increase in the extracellular level of anti-CD22 scFv (p < 0.05). The maximum concentrations of total proteins secreted by δ los1 and parent strains were 125 mg/L and 68 mg/L, respectively.

Conclusion:

The presented data suggest that the targeted disruption of los1 homologue in P. pastoris can result in a higher expression level of our target protein. Findings of this study may improve the current strategies used in optimizing the productivity of recombinant P. pastoris strains.

Identifying longevity associated genes by integrating gene expression and curated annotations

Aging is a complex process with poorly understood genetic mechanisms. Recent studies have sought to classify genes as pro-longevity or anti-longevity using a variety of machine learning algorithms. However, it is not clear which types of features are best for optimizing classification performance and which algorithms are best suited to this task. Further, performance assessments based on held-out test data are lacking. We systematically compare five popular classification algorithms using gene ontology and gene expression datasets as features to predict the pro-longevity versus anti-longevity status of genes for two model organisms (C. elegans and S. cerevisiae) using the GenAge database as ground truth. We find that elastic net penalized logistic regression performs particularly well at this task. Using elastic net, we make novel predictions of pro- and anti-longevity genes that are not currently in the GenAge database.

Aging is a complex process with poorly understood genetic mechanisms. Recent studies have sought to classify genes as pro-longevity or anti-longevity using a variety of machine learning algorithms. However, it is not clear which types of features are best for optimizing classification performance and which algorithms are best suited to this task. Further, performance assessments based on held-out test data are lacking. We systematically compare five popular classification algorithms using gene ontology and gene expression datasets as features to predict the pro-longevity versus anti-longevity status of genes for two model organisms (nematode worms and yeast) using the GenAge database as ground truth. We find that elastic net penalized logistic regression performs particularly well at this task. Using elastic net, we make novel predictions of pro- and anti-longevity genes that are not currently in the GenAge database.

Reproductive Potential of Yeast Cells Depends on Overall Action of Interconnected Changes in Central Carbon Metabolism, Cellular Biosynthetic Capacity, and Proteostasis

Carbon metabolism is a crucial aspect of cell life. Glucose, as the primary source of energy and carbon skeleton, determines the type of cell metabolism and biosynthetic capabilities, which, through the regulation of cell size, may affect the reproductive capacity of the yeast cell. Calorie restriction is considered as the most effective way to improve cellular physiological capacity, and its molecular mechanisms are complex and include several nutrient signaling pathways. It is widely assumed that the metabolic shift from fermentation to respiration is treated as a substantial driving force for the mechanism of calorie restriction and its influence on reproductive capabilities of cells. In this paper, we propose another approach to this issue based on analysis the connection between energy-producing and biomass formation pathways which are closed in the metabolic triangle, i.e., the respiration-glycolysis-pentose phosphate pathway. The analyses were based on the use of cells lacking hexokinase 2 (∆hxk2) and conditions of different glucose concentration corresponding to the calorie restriction and the calorie excess. Hexokinase 2 is the key enzyme involved in central carbon metabolism and is also treated as a calorie restriction mimetic. The experimental model used allows us to explain both the role of increased respiration as an effect of calorie restriction but also other aspects of carbon metabolism and the related metabolic flux in regulation of reproductive potential of the cells. The obtained results reveal that increased respiration is not a prerequisite for reproductive potential extension but rather an accompanying effect of the positive role of calorie restriction. More important seems to be the changes connected with fluxes in central carbon metabolic pathways resulting in low biosynthetic capabilities and improved proteostasis.

Probing Pedomorphy and Prolonged Lifespan in Naked Mole-Rats and Dwarf Mice

Pedomorphy, maintenance of juvenile traits throughout life, is most pronounced in extraordinarily long-lived naked mole-rats. Many of these traits (e.g., slow growth rates, low hormone levels, and delayed sexual maturity) are shared with spontaneously mutated, long-lived dwarf mice. Although some youthful traits likely evolved as adaptations to subterranean habitats (e.g., thermolability), the nature of these intrinsic pedomorphic features may also contribute to their prolonged youthfulness, longevity, and healthspan.

Proteomics of Long-Lived Mammals

Mammalian species differ up to 100-fold in their aging rates and maximum lifespans. Long-lived mammals appear to possess traits that extend lifespan and healthspan. Genomic analyses have not revealed a single pro-longevity function that would account for all longevity effects. In contrast, it appears that pro-longevity mechanisms may be complex traits afforded by connections between metabolism and protein functions that are impossible to predict by genomic approaches alone. Thus, metabolomics and proteomics studies will be required to understand the mechanisms of longevity. Several examples are reviewed that demonstrate the naked mole rat (NMR) shows unique proteomic signatures that contribute to longevity by overcoming several hallmarks of aging. SIRT6 is also discussed as an example of a protein that evolves enhanced enzymatic function in long-lived species. Finally, it is shown that several longevity-related proteins such as Cip1/p21, FOXO3, TOP2A, AKT1, RICTOR, INSR, and SIRT6 harbor posttranslational modification (PTM) sites that preferentially appear in either short- or long-lived species and provide examples of crosstalk between PTM sites. Prospects of enhancing lifespan and healthspan of humans by altering metabolism and proteoforms with drugs that mimic changes observed in long-lived species are discussed.

Cellular Aging Characteristics and Their Association with Age-Related Disorders

Different molecular signaling pathways, biological processes, and intercellular communication mechanisms control longevity and are affected during cellular senescence. Recent data have suggested that organelle communication, as well as genomic and metabolic dysfunctions, contribute to this phenomenon. Oxidative stress plays a critical role by inducing structural modifications to biological molecules while affecting their function and catabolism and eventually contributing to the onset of age-related dysfunctions. In this scenario, proteins are not adequately degraded and accumulate in the cell cytoplasm as toxic aggregates, increasing cell senescence progression. In particular, carbonylation, defined as a chemical reaction that covalently and irreversibly modifies proteins with carbonyl groups, is considered to be a significant indicator of protein oxidative stress and aging. Here, we emphasize the role and dysregulation of the molecular pathways controlling cell metabolism and proteostasis, the complexity of the mechanisms that occur during aging, and their association with various age-related disorders. The last segment of the review details current knowledge on protein carbonylation as a biomarker of cellular senescence in the development of diagnostics and therapeutics for age-related dysfunctions.

Yeast at the Forefront of Research on Ageing and Age-Related Diseases

Ageing is a complex and multifactorial process driven by genetic, environmental and stochastic factors that lead to the progressive decline of biological systems. Mechanisms of ageing have been extensively investigated in various model organisms and systems generating fundamental advances. Notably, studies on yeast ageing models have made numerous and relevant contributions to the progress in the field. Different longevity factors and pathways identified in yeast have then been shown to regulate molecular ageing in invertebrate and mammalian models. Currently the best candidates for anti-ageing drugs such as spermidine and resveratrol or anti-ageing interventions such as caloric restriction were first identified and explored in yeast. Yeasts have also been instrumental as models to study the cellular and molecular effects of proteins associated with age-related diseases such as Parkinson's, Huntington's or Alzheimer's diseases. In this chapter, a review of the advances on ageing and age-related diseases research in yeast models will be made. Particular focus will be placed on key longevity factors, ageing hallmarks and interventions that slow ageing, both yeast-specific and those that seem to be conserved in multicellular organisms. Their impact on the pathogenesis of age-related diseases will be also discussed.