A High-Throughput Screen for Yeast Replicative Lifespan Identifies Lifespan-Extending Compounds

Astaxanthin and meclizine extend lifespan in UM-HET3 male mice; fisetin, SG1002 (hydrogen sulfide donor), dimethyl fumarate, mycophenolic acid, and 4-phenylbutyrate do not significantly affect lifespan in either sex at the doses and schedules used

In genetically heterogeneous (UM-HET3) mice produced by the CByB6F1 × C3D2F1 cross, the Nrf2 activator astaxanthin (Asta) extended the median male lifespan by 12% (p = 0.003, log-rank test), while meclizine (Mec), an mTORC1 inhibitor, extended the male lifespan by 8% (p = 0.03). Asta was fed at 1840 ± 520 (9) ppm and Mec at 544 ± 48 (9) ppm, stated as mean ± SE (n) of independent diet preparations. Both were started at 12 months of age. The 90th percentile lifespan for both treatments was extended in absolute value by 6% in males, but neither was significant by the Wang-Allison test. Five other new agents were also tested as follows: fisetin, SG1002 (hydrogen sulfide donor), dimethyl fumarate, mycophenolic acid, and 4-phenylbutyrate. None of these increased lifespan significantly at the dose and method of administration tested in either sex. Amounts of dimethyl fumarate in the diet averaged 35% of the target dose, which may explain the absence of lifespan effects. Body weight was not significantly affected in males by any of the test agents. Late life weights were lower in females fed Asta and Mec, but lifespan was not significantly affected in these females. The male-specific lifespan benefits from Asta and Mec may provide insights into sex-specific aspects of aging.

Single cell sorting of young yeast based on label-free fluorescence lifetime imaging microscopy

Saccharomyces cerevisiae is an attractive organism used in the fermentation industry and is an important model organism for virus research. The ability to sort yeast cells is important for diverse applications. Replicative aging of Saccharomyces Cerevisiae is accompanied by metabolic changes that are related to an essential coenzyme, reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H). Here, a single cell sorting method based on fluorescence lifetime imaging microscopy (FLIM) and laser-induced forward transfer (LIFT) was implemented for the first time. The aging level of yeast was determined based on the FLIM by NAD(P)H, which was a label-free and noninvasive method for studying individual cells. Then, young and active yeast cells were sorted by the LIFT system at the single cell level. During the entire experiment, a sterile and humid environment was maintained to ensure the activity of cells. The high viability of sorted cells was achieved by the LIFT combining with FLIM.

Single-Cell Time-Lapse Observation Reveals Cell Shrinkage upon Cell Death in Batch Culture of Saccharomyces cerevisiae

Saccharomyces cerevisiae is a model organism for aging and longevity studies. In a clonal population of S. cerevisiae, the timing of cell death in the stationary phase is not synchronized, indicating that heterogeneity exists in survival at a single-cell level. Heterogeneity also exists in the cell size, and its correlation with the death rate has been discussed in past studies. However, the direct cause of the heterogeneity in survival remains unknown. In this report, we revisited this question and asked whether the death rate has any correlation with cell size. Past studies did not exclude a possibility that cells change their size upon or after death. If such a change exists, the size dependence of cell death could be misinterpreted. Therefore, we analyzed the correlation between the death rate and cell size before death by time-lapse imaging. It turned out that the size dependence of the death rate varied from one strain to another, suggesting that general principles between cell size and death do not exist. Instead, cells shrink upon cell death, resulting in the accumulation of small dead cells. The degree of cell shrinkage was proportional to the cell size, and the ratio was constant in two strains, which is between 25 and 28%, suggesting the presence of general principles and mechanisms behind the shrinkage event upon cell death. Further investigation of the cause and mechanism of the shrinkage will help us to understand the process of cell death and the origin of the heterogeneity in survival.

The Potential of Calorie Restriction and Calorie Restriction Mimetics in Delaying Aging: Focus on Experimental Models

Aging is a biological process determined by multiple cellular mechanisms, such as genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication, that ultimately concur in the functional decline of the individual. The evidence that the old population is steadily increasing and will triplicate in the next 50 years, together with the fact the elderlies are more prone to develop pathologies such as cancer, diabetes, and degenerative disorders, stimulates an important effort in finding specific countermeasures. Calorie restriction (CR) has been demonstrated to modulate nutrient sensing mechanisms, inducing a better metabolic profile, enhanced stress resistance, reduced oxidative stress, and improved inflammatory response. Therefore, CR and CR-mimetics have been suggested as powerful means to slow aging and extend healthy life-span in experimental models and humans. Taking into consideration the difficulties and ethical issues in performing aging research and testing anti-aging interventions in humans, researchers initially need to work with experimental models. The present review reports the major experimental models utilized in the study of CR and CR-mimetics, highlighting their application in the laboratory routine, and their translation to human research.

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.

Inactivating histone deacetylase HDA promotes longevity by mobilizing trehalose metabolism

Histone acetylations are important epigenetic markers for transcriptional activation in response to metabolic changes and various stresses. Using the high-throughput SEquencing-Based Yeast replicative Lifespan screen method and the yeast knockout collection, we demonstrate that the HDA complex, a class-II histone deacetylase (HDAC), regulates aging through its target of acetylated H3K18 at storage carbohydrate genes. We find that, in addition to longer lifespan, disruption of HDA results in resistance to DNA damage and osmotic stresses. We show that these effects are due to increased promoter H3K18 acetylation and transcriptional activation in the trehalose metabolic pathway in the absence of HDA. Furthermore, we determine that the longevity effect of HDA is independent of the Cyc8-Tup1 repressor complex known to interact with HDA and coordinate transcriptional repression. Silencing the HDA homologs in C. elegans and Drosophila increases their lifespan and delays aging-associated physical declines in adult flies. Hence, we demonstrate that this HDAC controls an evolutionarily conserved longevity pathway.

Anti-senescent drug screening by deep learning-based morphology senescence scoring

Advances in deep learning technology have enabled complex task solutions. The accuracy of image classification tasks has improved owing to the establishment of convolutional neural networks (CNN). Cellular senescence is a hallmark of ageing and is important for the pathogenesis of ageing-related diseases. Furthermore, it is a potential therapeutic target. Specific molecular markers are used to identify senescent cells. Moreover senescent cells show unique morphology, which can be identified. We develop a successful morphology-based CNN system to identify senescent cells and a quantitative scoring system to evaluate the state of endothelial cells by senescence probability output from pre-trained CNN optimised for the classification of cellular senescence, Deep Learning-Based Senescence Scoring System by Morphology (Deep-SeSMo). Deep-SeSMo correctly evaluates the effects of well-known anti-senescent reagents. We screen for drugs that control cellular senescence using a kinase inhibitor library by Deep-SeSMo-based drug screening and identify four anti-senescent drugs. RNA sequence analysis reveals that these compounds commonly suppress senescent phenotypes through inhibition of the inflammatory response pathway. Thus, morphology-based CNN system can be a powerful tool for anti-senescent drug screening.

Cellular senescence is a hallmark of ageing and is important for the pathogenesis of ageing-related diseases. Here, the authors develop a morphology-based deep learning system to identify senescent cells and a quantitative scoring system to evaluate the state of endothelial cells to evaluate the effects of anti-senescent reagents.

Replicative Aging in Pathogenic Fungi

Candida albicans, Candida auris, Candida glabrata, and Cryptococcus neoformans are pathogenic yeasts which can cause systemic infections in immune-compromised as well as immune-competent individuals. These yeasts undergo replicative aging analogous to a process first described in the nonpathogenic yeast Saccharomyces cerevisiae. The hallmark of replicative aging is the asymmetric cell division of mother yeast cells that leads to the production of a phenotypically distinct daughter cell. Several techniques to study aging that have been pioneered in S. cerevisiae have been adapted to study aging in other pathogenic yeasts. The studies indicate that aging is relevant for virulence in pathogenic fungi. As the mother yeast cell progressively ages, every ensuing asymmetric cell division leads to striking phenotypic changes, which results in increased antifungal and antiphagocytic resistance. This review summarizes the various techniques that are used to study replicative aging in pathogenic fungi along with their limitations. Additionally, the review summarizes some key phenotypic variations that have been identified and are associated with changes in virulence or resistance and thus promote persistence of older cells.

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.

Recent advances in high-throughput flow cytometry for drug discovery

INTRODUCTION

High-throughput flow cytometry (HTFC) has proven to be an important technology in drug discovery. The use of HTFC enables multi-parametric screening of suspension cells containing heterogenous cell populations and coated particles for screening proteins of interest. Novel targets, novel cell markers and compound clusters for drug development have been identified from HTFC screens.

AREAS COVERED

In this article, the authors focus on reviewing the recent HTFC applications reported during the last 5-6 years, including drug discovery screens and studies for immune, immune-oncology, infectious and inflammatory diseases. The main HTFC approaches, development of HTFC systems, and automated sample preparation systems for HTFC are also discussed.

EXPERT OPINION

The advance of HTFC technology coupled with automated sample acquisition and sample preparation has demonstrated its utility in screening large numbers of compounds using suspension cells, facilitated screening of disease-relevant human primary cells, and enabled deep understanding of mechanism of action by analyzing multiple parameters. The authors see HTFC as a very valuable tool in immune, immune-oncology, infectious and inflammatory diseases where immune cells play essential roles.

Age-dependent decline in stress response capacity revealed by proteins dynamics analysis

The aging process is regarded as the progressive loss of physiological integrity, leading to impaired biological functions and the increased vulnerability to death. Among various biological functions, stress response capacity enables cells to alter gene expression patterns and survive when facing internal and external stresses. Here, we explored changes in stress response capacity during the replicative aging of Saccharomyces cerevisiae. To this end, we used a high-throughput microfluidic device to deliver intermittent pulses of osmotic stress and tracked the dynamic changes in the production of downstream stress-responsive proteins, in a large number of individual aging cells. Cells showed a gradual decline in stress response capacity of these osmotic-related downstream proteins during the aging process after the first 5 generations. Among the downstream stress-responsive genes and unrelated genes tested, the residual level of response capacity of Trehalose-6-Phosphate Synthase (TPS2) showed the best correlation with the cell remaining lifespan. By monitor dynamics of the upstream transcription factors and mRNA of Tps2, it was suggested that the decline in downstream stress response capacity was caused by the decline of translational rate of these proteins during aging.

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

Slowing down aging-associated accumulation of molecular damage or its prevention represents a promising therapeutic paradigm to combat aging-related disease and death. While several chemical compounds extend lifespan in model organisms, their mechanism of action is often unknown, reducing their therapeutic potential. Using a systematic approach, here we characterize the impact of the GMP pathway on yeast lifespan and elucidate GMP synthesis inhibition as a lifespan extension mechanism. We further discover that proteasome activation extends lifespan in part through the GMP pathway. GMP synthesis inhibition exerts its lifespan extension effect independently of the canonical nutrient-sensing pathway regulating lifespan. Exposing longitudinally aging yeast cells to GMP pathway inhibition in an age-dependent manner, we demonstrate that the lifespan extension is facilitated by slowing, rather than reversing, the aging process in cells. Using a GUK1 mutant with lower GMP-to-GDP conversion activity, we observe lifespan extension, suggesting that reduced GDP level by itself can also extend yeast lifespan. These findings elucidate the involvement of nucleotide metabolism in the aging process. The existence of clinically-approved GMP pathway inhibitors elicits the potential of a new class of therapeutics for aging-related disorders.

Roles of Telomere Biology in Cell Senescence, Replicative and Chronological Ageing

Telomeres with G-rich repetitive DNA and particular proteins as special heterochromatin structures at the termini of eukaryotic chromosomes are tightly maintained to safeguard genetic integrity and functionality. Telomerase as a specialized reverse transcriptase uses its intrinsic RNA template to lengthen telomeric G-rich strand in yeast and human cells. Cells sense telomere length shortening and respond with cell cycle arrest at a certain size of telomeres referring to the "Hayflick limit." In addition to regulating the cell replicative senescence, telomere biology plays a fundamental role in regulating the chronological post-mitotic cell ageing. In this review, we summarize the current understandings of telomere regulation of cell replicative and chronological ageing in the pioneer model system Saccharomyces cerevisiae and provide an overview on telomere regulation of animal lifespans. We focus on the mechanisms of survivals by telomere elongation, DNA damage response and environmental factors in the absence of telomerase maintenance of telomeres in the yeast and mammals.

The Systems Biology of Single-Cell Aging

Aging is a leading cause of human morbidity and mortality, but efforts to slow or reverse its effects are hampered by an incomplete understanding of its multi-faceted origins. Systems biology, the use of quantitative and computational methods to understand complex biological systems, offers a toolkit well suited to elucidating the root cause of aging. We describe the known components of the aging network and outline innovative techniques that open new avenues of investigation to the aging research community. We propose integration of the systems biology and aging fields, identifying areas of complementarity based on existing and impending technological capabilities.