MicroRNA predictors of longevity in Caenorhabditis elegans

Neither genetic nor environmental factors fully account for variability in individual longevity: genetically identical invertebrates in homogenous environments often experience no less variability in lifespan than outbred human populations. Such variability is often assumed to result from stochasticity in damage accumulation over time; however, the identification of early-life gene expression states that predict future longevity would suggest that lifespan is least in part epigenetically determined. Such "biomarkers of aging," genetic or otherwise, nevertheless remain rare. In this work, we sought early-life differences in organismal robustness in unperturbed individuals and examined the utility of microRNAs, known regulators of lifespan, development, and robustness, as aging biomarkers. We quantitatively examined Caenorhabditis elegans reared individually in a novel apparatus and observed throughout their lives. Early-to-mid-adulthood measures of homeostatic ability jointly predict 62% of longevity variability. Though correlated, markers of growth/muscle maintenance and of metabolic by-products ("age pigments") report independently on lifespan, suggesting that graceful aging is not a single process. We further identified three microRNAs in which early-adulthood expression patterns individually predict up to 47% of lifespan differences. Though expression of each increases throughout this time, mir-71 and mir-246 correlate with lifespan, while mir-239 anti-correlates. Two of these three microRNA "biomarkers of aging" act upstream in insulin/IGF-1-like signaling (IIS) and other known longevity pathways, thus we infer that these microRNAs not only report on but also likely determine longevity. Thus, fluctuations in early-life IIS, due to variation in these microRNAs and from other causes, may determine individual lifespan.     

The metabolome as a biomarker of aging in Drosophila melanogaster

Many biomarkers have been shown to be associated not only with chronological age but also with functional measures of biological age. In human populations, it is difficult to show whether variation in biological age is truly predictive of life expectancy, as such research would require longitudinal studies over many years, or even decades. We followed adult cohorts of 20 Drosophila Genetic Reference Panel (DGRP) strains chosen to represent the breadth of lifespan variation, obtain estimates of lifespan, baseline mortality, and rate of aging, and associate these parameters with age‐specific functional traits including fecundity and climbing activity and with age‐specific targeted metabolomic profiles. We show that activity levels and metabolome‐wide profiles are strongly associated with age, that numerous individual metabolites show a strong association with lifespan, and that the metabolome provides a biological clock that predicts not only sample age but also future mortality rates and lifespan. This study with 20 genotypes and 87 metabolites, while relatively small in scope, establishes strong proof of principle for the fly as a powerful experimental model to test hypotheses about biomarkers and aging and provides further evidence for the potential value of metabolomic profiles as biomarkers of aging.     

Acquired temperature-sensitive paralysis as a biomarker of declining neuronal function in aging Drosophila

General locomotor activity decreases with normal aging in animals and could be partially explained by decreases in neuronal function. Voltage-gated Na⁺ channels are essential in initiating and propagating rapid electrical impulses underlying normal locomotor activity and behavior in animals. Isolation of mutations conferring temperature-sensitive (ts) paralysis has been an extremely powerful paradigm for identifying genes involved in neuronal functions, such as membrane excitability and synaptic transmission. For instance, decreased expression of wild-type Na⁺ channels in flies harboring the no-action-potential ( nap ) mutant allele ( mle^napts ) confers rapid and reversible ts paralysis, because of failure of action potential propagation. Here, we report that aging wild-type Drosophila gradually develops an acquired susceptibility to ts paralysis that is indistinguishable from that seen in young ts paralytic mle^napts mutants. Moreover, we show that this general age-dependent susceptibility is also present in mle^napts flies, although the effects are shifted to lower temperature regimes. The mle^napts flies also exhibit decreased lifespan and increased frailty. Paralysis and decreased lifespan of mle^napts flies were partially rescued by increasing the dosage of para , the structural gene for the major action potential Na⁺ channel in central nervous system of Drosophila . Lastly, we show a dramatic scaling of ts paralysis susceptibility with chronological age in short-lived and long-lived mutant flies, further demonstrating that this age-dependent risk is independent of genetic background. Thus, decreased neural transmission, a hallmark of which is ts paralysis, is a biomarker of aging.     

Variable pathogenicity determines individual lifespan in Caenorhabditis elegans

A common property of aging in all animals is that chronologically and genetically identical individuals age at different rates. To unveil mechanisms that influence aging variability, we identified markers of remaining lifespan for Caenorhabditis elegans. In transgenic lines, we expressed fluorescent reporter constructs from promoters of C. elegans genes whose expression change with age. The expression levels of aging markers in individual worms from a young synchronous population correlated with their remaining lifespan. We identified eight aging markers, with the superoxide dismutase gene sod-3 expression being the best single predictor of remaining lifespan. Correlation with remaining lifespan became stronger if expression from two aging markers was monitored simultaneously, accounting for up to 49% of the variation in individual lifespan. Visualizing the physiological age of chronologically-identical individuals allowed us to show that a major source of lifespan variability is different pathogenicity from individual to individual and that the mechanism involves variable activation of the insulin-signaling pathway.     

Microarray analysis of gene expression with age in individual nematodes

We compare the aging of wild-type and long-lived C. elegans by gene expression profiling of individual nematodes. Using a custom cDNA array, we have characterized the gene expression of 4-5 individuals at 4 distinct ages throughout the adult lifespan of wild-type N2 nematodes, and at the same ages for individuals of the long-lived strain daf-2(e1370). Using statistical tools developed for microarray data analysis, we identify genes that differentiate aging N2 from aging daf-2, as well as classes of genes that change with age in a similar way in both genotypes. Our novel approach of studying individual nematodes provides practical advantages, since it obviates the use of mutants or drugs to block reproduction, as well as the use of stressful mass-culturing procedures, that have been required for previous microarray studies of C. elegans. In addition, this approach has the potential to uncover the molecular variability between individuals of a population, variation that is missed when studying pools of thousands of individuals.     

A Microarray-Based Genetic Screen for Yeast Chronological Aging Factors

Model organisms have played an important role in the elucidation of multiple genes and cellular processes that regulate aging. In this study we utilized the budding yeast, Saccharomyces cerevisiae, in a large-scale screen for genes that function in the regulation of chronological lifespan, which is defined by the number of days that non-dividing cells remain viable. A pooled collection of viable haploid gene deletion mutants, each tagged with unique identifying DNA “bar-code” sequences was chronologically aged in liquid culture. Viable mutants in the aging population were selected at several time points and then detected using a microarray DNA hybridization technique that quantifies abundance of the barcode tags. Multiple short- and long-lived mutants were identified using this approach. Among the confirmed short-lived mutants were those defective for autophagy, indicating a key requirement for the recycling of cellular organelles in longevity. Defects in autophagy also prevented lifespan extension induced by limitation of amino acids in the growth media. Among the confirmed long-lived mutants were those defective in the highly conserved de novo purine biosynthesis pathway (the ADE genes), which ultimately produces IMP and AMP. Blocking this pathway extended lifespan to the same degree as calorie (glucose) restriction. A recently discovered cell-extrinsic mechanism of chronological aging involving acetic acid secretion and toxicity was suppressed in a long-lived ade4Δ mutant and exacerbated by a short-lived atg16Δ autophagy mutant. The identification of multiple novel effectors of yeast chronological lifespan will greatly aid in the elucidation of mechanisms that cells and organisms utilize in slowing down the aging process.     

Identification of evolutionarily conserved genetic regulators of cellular aging

To identify new genetic regulators of cellular aging and senescence, we performed genome-wide comparative RNA profiling with selected human cellular model systems, reflecting replicative senescence, stress-induced premature senescence, and distinct other forms of cellular aging. Gene expression profiles were measured, analyzed, and entered into a newly generated database referred to as the GiSAO database. Bioinformatic analysis revealed a set of new candidate genes, conserved across the majority of the cellular aging models, which were so far not associated with cellular aging, and highlighted several new pathways that potentially play a role in cellular aging. Several candidate genes obtained through this analysis have been confirmed by functional experiments, thereby validating the experimental approach. The effect of genetic deletion on chronological lifespan in yeast was assessed for 93 genes where (i) functional homologues were found in the yeast genome and (ii) the deletion strain was viable. We identified several genes whose deletion led to significant changes of chronological lifespan in yeast, featuring both lifespan shortening and lifespan extension. In conclusion, an unbiased screen across species uncovered several so far unrecognized molecular pathways for cellular aging that are conserved in evolution.     

Mutations in the RAD27 and SGS1 genes differentially affect the chronological and replicative lifespan of yeast cells growing on glucose and glycerol

The Sgs1 protein from Saccharomyces cerevisiae is a member of the RecQ helicases. Defects in RecQ helicases result in premature aging phenotypes in both yeasts and humans, which appear to be promoted by replicative stress. Yeast rad27 mutants also suffer from premature aging. As the human Rad27p and Sgs1p homologs interact, a similar interaction between the yeast proteins could be important for promoting longevity in S. cerevisiae. We tested the contribution of a potential interaction between Rad27p and Sgs1p to longevity by analyzing lifespan and parameters associated with longevity in rad27 and sgs1 mutants. The carbon source supporting growth also modulated longevity as evaluated by replicative and chronological lifespan measurements. Growth on glycerol promoted chronological lifespan, while maximum replicative lifespan was obtained with glucose-supported growth. In comparison to the individual mutants, the sgs1 rad27 double mutant displayed a shortened replicative lifespan and was also more sensitive to DNA-damaging agents. In addition to promoting replicative lifespan, the activity of Rad27p was critical for achieving full chronological lifespan. The rad27 mutants exhibited increased oxidative stress levels along with an elevated spontaneous mutation rate. Removal of Sgs1p activity additionally increased the oxidative stress and spontaneous mutation rate in rad27 mutants without affecting the chronological lifespan.     

Explainable machine learning framework to predict personalized physiological aging

Attaining personalized healthy aging requires accurate monitoring of physiological changes and identifying subclinical markers that predict accelerated or delayed aging. Classic biostatistical methods most rely on supervised variables to estimate physiological aging and do not capture the full complexity of inter-parameter interactions. Machine learning (ML) is promising, but its black box nature eludes direct understanding, substantially limiting physician confidence and clinical usage. Using a broad population dataset from the National Health and Nutrition Examination Survey (NHANES) study including routine biological variables and after selection of XGBoost as the most appropriate algorithm, we created an innovative explainable ML framework to determine a Personalized physiological age (PPA). PPA predicted both chronic disease and mortality independently of chronological age. Twenty-six variables were sufficient to predict PPA. Using SHapley Additive exPlanations (SHAP), we implemented a precise quantitative associated metric for each variable explaining physiological (i.e., accelerated or delayed) deviations from age-specific normative data. Among the variables, glycated hemoglobin (HbA1c) displays a major relative weight in the estimation of PPA. Finally, clustering profiles of identical contextualized explanations reveal different aging trajectories opening opportunities to specific clinical follow-up. These data show that PPA is a robust, quantitative and explainable ML-based metric that monitors personalized health status. Our approach also provides a complete framework applicable to different datasets or variables, allowing precision physiological age estimation.     

pH neutralization protects against reduction in replicative lifespan following chronological aging in yeast

Chronological and replicative aging have been studied in yeast as alternative paradigms for post-mitotic and mitotic aging, respectively. It has been known for more than a decade that cells of the S288C background aged chronologically in rich medium have reduced replicative lifespan relative to chronologically young cells. Here we report replication of this observation in the diploid BY4743 strain background. We further show that the reduction in replicative lifespan from chronological aging is accelerated when cells are chronologically aged under standard conditions in synthetic complete medium rather than rich medium. The loss of replicative potential with chronological age is attenuated by buffering the pH of the chronological aging medium to 6.0, an intervention that we have previously shown can extend chronological lifespan. These data demonstrate that extracellular acidification of the culture medium can cause intracellular damage in the chronologically aging population that is asymmetrically segregated by the mother cell to limit subsequent replicative lifespan.     

pH neutralization protects against reduction in replicative lifespan following chronological aging in yeast

Chronological and replicative aging have been studied in yeast as alternative paradigms for post-mitotic and mitotic aging, respectively. It has been known for more than a decade that cells of the S288C background aged chronologically in rich medium have reduced replicative lifespan relative to chronologically young cells. Here we report replication of this observation in the diploid BY4743 strain background. We further show that the reduction in replicative lifespan from chronological aging is accelerated when cells are chronologically aged under standard conditions in synthetic complete medium rather than rich medium. The loss of replicative potential with chronological age is attenuated by buffering the pH of the chronological aging medium to 6.0, an intervention that we have previously shown can extend chronological lifespan. These data demonstrate that extracellular acidification of the culture medium can cause intracellular damage in the chronologically aging population that is asymmetrically segregated by the mother cell to limit subsequent replicative lifespan.     

Independent and Additive Effects of Glutamic Acid and Methionine on Yeast Longevity

It is established that glucose restriction extends yeast chronological and replicative lifespan, but little is known about the influence of amino acids on yeast lifespan, although some amino acids were reported to delay aging in rodents. Here we show that amino acid composition greatly alters yeast chronological lifespan. We found that non-essential amino acids (to yeast) methionine and glutamic acid had the most significant impact on yeast chronological lifespan extension, restriction of methionine and/or increase of glutamic acid led to longevity that was not the result of low acetic acid production and acidification in aging media. Remarkably, low methionine, high glutamic acid and glucose restriction additively and independently extended yeast lifespan, which could not be further extended by buffering the medium (pH 6.0). Our preliminary findings using yeasts with gene deletion demonstrate that glutamic acid addition, methionine and glucose restriction prompt yeast longevity through distinct mechanisms. This study may help to fill a gap in yeast model for the fast developing view that nutrient balance is a critical factor to extend lifespan.     

Biomarkers of aging in Drosophila

Low environmental temperature and dietary restriction (DR) extend lifespan in diverse organisms. In the fruit fly Drosophila, switching flies between temperatures alters the rate at which mortality subsequently increases with age but does not reverse mortality rate. In contrast, DR acts acutely to lower mortality risk; flies switched between control feeding and DR show a rapid reversal of mortality rate. Dietary restriction thus does not slow accumulation of aging‐related damage. Molecular species that track the effects of temperatures on mortality but are unaltered with switches in diet are therefore potential biomarkers of aging‐related damage. However, molecular species that switch upon instigation or withdrawal of DR are thus potential biomarkers of mechanisms underlying risk of mortality, but not of aging‐related damage. Using this approach, we assessed several commonly used biomarkers of aging‐related damage. Accumulation of fluorescent advanced glycation end products (AGEs) correlated strongly with mortality rate of flies at different temperatures but was independent of diet. Hence, fluorescent AGEs are biomarkers of aging‐related damage in flies. In contrast, five oxidized and glycated protein adducts accumulated with age, but were reversible with both temperature and diet, and are therefore not markers either of acute risk of dying or of aging‐related damage. Our approach provides a powerful method for identification of biomarkers of aging.     

Using measures of single‐cell physiology and physiological state to understand organismic aging

Genetically identical organisms in homogeneous environments have different lifespans and healthspans. These differences are often attributed to stochastic events, such as mutations and ‘epimutations’, changes in DNA methylation and chromatin that change gene function and expression. But work in the last 10 years has revealed differences in lifespan‐ and health‐related phenotypes that are not caused by lasting changes in DNA or identified by modifications to DNA or chromatin. This work has demonstrated persistent differences in single‐cell and whole‐organism physiological states operationally defined by values of reporter gene signals in living cells. While some single‐cell states, for example, responses to oxygen deprivation, were defined previously, others, such as a generally heightened ability to make proteins, were, revealed by direct experiment only recently, and are not well understood. Here, we review technical progress that promises to greatly increase the number of these measurable single‐cell physiological variables and measureable states. We discuss concepts that facilitate use of single‐cell measurements to provide insight into physiological states and state transitions. We assert that researchers will use this information to relate cell level physiological readouts to whole‐organism outcomes, to stratify aging populations into groups based on different physiologies, to define biomarkers predictive of outcomes, and to shed light on the molecular processes that bring about different individual physiologies. For these reasons, quantitative study of single‐cell physiological variables and state transitions should provide a valuable complement to genetic and molecular explanations of how organisms age.     

Genetic alteration of normal aging processes is responsible for extended longevity in Drosophila

The first step in a genetic analysis of aging is to identify and characterize the genetic mutants and their controls that will be used. Such mutants or strains are initially identified by their effect on the life span. Yet many genetic interventions are known to have some effect on the life span without necessarily affecting the aging process. It is therefore necessary to prove that one is actually dealing with an aging mutant before one draws strong inferences from the data. Casarett's rules provide an operational test for doing so, relying as they do on the comparison of aging bio-markers in the experimental and reference strains. We show that our previously described genetically based long-lived NDC-L strain and its normal-lived NDC-R control strain differ only in the chronological age of expression of two behavioral and three physiological functional age biomarkers. They do not differ in the sequence or the physiological age of expression of these biomarkers. These two strains comply with the Casarett rules and thereby comprise a valid tool with which to conduct a comparative genetic analysis of aging. The implications of the available data are discussed, including the possibility that aging in these strains of Drosophila melanogaster may be the result of a multiphasic developmental process.     

酵母Sirtuins在细胞寿命中的作用

酿酒酵母(以下简略为酵母)作为寿命分析模型广泛应用于寿命研究领域。酵母寿命分析方法有两种,分别是复制型酵母寿命分析法和时序型酵母寿命分析法。目前,通过酵母寿命分析模型已识别出包括SIR2在内的多个寿命调节基因。SIR2是目前较好的被确立起来的寿命调节基因,具有NAD依赖型脱乙酰化酶的活性,从原核生物到真核生物都有良好的保守性。Sirtuins (Sir2蛋白家族的总称)在细胞内具有功能上的多样性,其中包括对于压力耐受的调节、基因转录的调节、代谢通路的调节以及寿命调节作用等。Sir2是Sirtuins家族最早发现的成员,其功能是参与异染色质结构域转录的沉默调节,同时还参与复制型酵母寿命的调节。已证明,SIR2的缺失会缩短酵母的寿命,基因表达的增高会延长寿命。Sir2的高等真核生物的同源蛋白也被证实参与衰老相关疾病的调节。本文中,我们将阐述Sir2以及Sir2的酵母同源蛋白Hst1-Hst4的功能,以及由它们调节的酵母寿命。     

Cancer Subtype Discovery and Biomarker Identification via a New Robust Network Clustering Algorithm

In cancer biology, it is very important to understand the phenotypic changes of the patients and discover new cancer subtypes. Recently, microarray-based technologies have shed light on this problem based on gene expression profiles which may contain outliers due to either chemical or electrical reasons. These undiscovered subtypes may be heterogeneous with respect to underlying networks or pathways, and are related with only a few of interdependent biomarkers. This motivates a need for the robust gene expression-based methods capable of discovering such subtypes, elucidating the corresponding network structures and identifying cancer related biomarkers. This study proposes a penalized model-based Student’s t clustering with unconstrained covariance (PMT-UC) to discover cancer subtypes with cluster-specific networks, taking gene dependencies into account and having robustness against outliers. Meanwhile, biomarker identification and network reconstruction are achieved by imposing an adaptive penalty on the means and the inverse scale matrices. The model is fitted via the expectation maximization algorithm utilizing the graphical lasso. Here, a network-based gene selection criterion that identifies biomarkers not as individual genes but as subnetworks is applied. This allows us to implicate low discriminative biomarkers which play a central role in the subnetwork by interconnecting many differentially expressed genes, or have cluster-specific underlying network structures. Experiment results on simulated datasets and one available cancer dataset attest to the effectiveness, robustness of PMT-UC in cancer subtype discovering. Moveover, PMT-UC has the ability to select cancer related biomarkers which have been verified in biochemical or biomedical research and learn the biological significant correlation among genes.     

Cell divisions and mammalian aging: integrative biology insights from genes that regulate longevity

Despite recent progress in the identification of genes that regulate longevity, aging remains a mysterious process. One influential hypothesis is the idea that the potential for cell division and replacement are important factors in aging. In this work, we review and discuss this perspective in the context of interventions in mammals that appear to accelerate or retard aging. Rather than focus on molecular mechanisms, we interpret results from an integrative biology perspective of how gene products affect cellular functions, which in turn impact on tissues and organisms. We review evidence suggesting that mutations that give rise to features resembling premature aging tend to be associated with cellular phenotypes such as increased apoptosis or premature replicative senescence. In contrast, many interventions in mice that extend lifespan and might delay aging, including caloric restriction, tend to either hinder apoptosis or result in smaller animals and thus may be the product of fewer cell divisions. Therefore, it appears plausible that changes in the number of times that cells, and particularly stem cells, divide during an organism's lifespan influence longevity and aging. We discuss possible mechanisms related to this hypothesis and propose experimental paradigms.