Cell Biology: Research & TherapyISSN: 2324-9293

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Editorial, Cell Biol Res Ther Vol: 2 Issue: 1

A Modular Network Regulates Longevity of Chronologically Aging Yeast

Adam Beach, Michelle T. Burstein, Vincent R. Richard, Alejandra Gomez-Perez, Anna Leonov, Tatiana Iouk and Vladimir I. Titorenko*
Department of Biology, Concordia University, Montreal, Quebec H4B 1R6, Canada
Corresponding author : Vladimir I. Titorenko
Department of Biology, Concordia University, 7141 Sherbrooke Street, West, SP Building, Room 501-13, Montreal, Quebec H4B 1R6, Canada
Tel: 514-848-2424
E-mail: [email protected]
Received: December 04, 2012 Accepted: December 05, 2012 Published: December 10, 2012
Citation: Beach A, Burstein MT, Richard VR, Gomez-Perez A, Leonov A, et al. (2013) A Modular Network Regulates Longevity of Chronologically Aging Yeast. Cell Biol: Res Ther 2:1. doi:10.4172/2324-9293.1000e110

Abstract

A Modular Network Regulates Longevity of Chronologically Aging Yeast

The fundamental mechanisms of aging are conserved across phyla. Aging of multicellular eukaryotic organisms affects numerous processes within cells. A challenge is to understand how cells integrate and control these processes. The yeast Saccharomyces cerevisiae, a genetically and biochemically manipulable unicellular eukaryote with annotated genome, is a valuable model for unveiling mechanisms of cellular aging in multicellular eukaryotes.

Keywords:

The fundamental mechanisms of aging are conserved across phyla [1-4]. Aging of multicellular eukaryotic organisms affects numerous processes within cells [5-15]. A challenge is to understand how cells integrate and control these processes. The yeast Saccharomyces cerevisiae, a genetically and biochemically manipulable unicellular eukaryote with annotated genome, is a valuable model for unveiling mechanisms of cellular aging in multicellular eukaryotes [16,17]. Yeast aging can be measured in two different ways. Replicative aging is defined by the maximum number of daughter cells that a mother cell can produce before senescence and models aging of mitotically active mammalian cells [16-18]. In contrast, chronological aging is measured by the length of time a yeast cell remains viable in a non dividing state and models aging of post mitotic mammalian cells [10,17,19].
Both the replicative and chronological aging of yeast can be decelerated by caloric restriction (CR), a low-calorie dietary regimen that extends lifespan in a wide spectrum of organisms and delays the onset of age-related diseases in rodent models [3,8,9,11,20-24]. Our recent study revealed that the levels of ATP and their age-dependent dynamics were very similar for CR and non-CR yeast [8]. We therefore concluded that CR yeast is not starving. Based on this conclusion, we hypothesized that: (i) CR yeast remodel their metabolism in order to match the level of ATP produced in non-CR yeast; and (ii) such specific remodeling of metabolism in CR yeast prolongs lifespan.
We sought to define a specific pattern of metabolism that is responsible for the anti-aging effect of CR and to establish the mechanisms underlying such effect. Recently, we monitored the agedependent dynamics of proteomes and metabolomes in wild-type and numerous long and short-lived mutant strains of yeast [7-10,13-15]. We also assessed the effect of a CR diet and various single-genedeletion mutations on the age-related alterations in carbohydrate and lipid metabolism, concentration of reactive oxygen species (ROS), essential processes in mitochondria, mitochondrial proteome, lipids of the mitochondrial membrane, frequency of mitochondrial DNA (mtDNA) mutations, composition of mitochondrial nucleoid, and mitochondrial shape [7-10,13-15]. Our strategy for elucidating the mechanisms of longevity in chronologically aging yeast is outlined in figure 1. We provided evidence that, before yeast enters the non-proliferative stationary phase; they establish a diet and genotypespecific pattern of metabolism and organelle dynamics during preceding diauxic and post-diauxic phases [7-10,13-15]. Our findings imply that, by designing such specific pattern prior to entry into nonproliferative state, yeast define their long-term viability. We therefore have come to the conclusion that the longevity of yeast is programmed by the level of metabolic capacity and organelle organization they reached prior to reproductive maturation. We found that yeast reach such level by establishing a diet- and genotype-specific configuration of what we call “a modular longevity network” (Figure 2). Based on our analysis of the spatiotemporal dynamics of the network, we proposed that it integrates modules operating in (i) trehalose and glycogen metabolism; (ii) glycolysis, glucose fermentation to ethanol, and gluconeogenesis; (iii) lipid metabolism in the endoplasmic reticulum, lipid bodies and peroxisomes; (iv) various routes of interorganellar metabolic flow; (v) maintenance of ROS homeostasis; (vi) essential oxidation-reduction reactions in mitochondria; (vii) protection of mtDNA from oxidative damage; and (viii) maintenance of the mitochondrial network (Figure 2) [2,3,5,9-11,18]. By evaluating how various genetic, dietary and pharmacological interventions alter the functional state of the network’s modules and affect chronological lifespan, we inferred the logistics of integrating individual modules into the network. Our findings suggest a model for the spatiotemporal dynamics of the longevity network operating in chronologically aging yeast (Figure 3). This model envisions that (i) yeast establish a diet-and genotype-specific configuration of the network by setting up the rates of the processes taking place within each of its modules; (ii) the establishment of a network’s configuration occurs before yeast enter a non-proliferative state; and (iii) different network’s configurations established prior to entry into a non-proliferative state define different rates of survival following such entry. Thus, by designing a specific configuration of the modular longevity network prior to reproductive maturation, yeast defines their chronological lifespan.
Figure 1: Our strategy for elucidating the mechanisms of longevity in chronologically aging yeast.
Figure 2: A modular network regulates longevity of chronologically aging yeast. The network integrates a number of cellular processes, which we call modules (see the text for detailed description of individual modules). CR and non-CR yeast establish different configurations of the longevity network by altering the dynamics of individual modules that comprise the network. During diauxic (D) and post-diauxic (PD) phases, yeast establishes a particular configuration of their longevity network by setting up the rates of the processes that take place within each of the network’s modules. Different configurations of the network designed during D and PD phases define different rates of survival during the non-proliferative stationary (ST) phase. The different network’s configurations established by CR and non-CR yeast entering ST phase are shown. The thickness of arrows correlates with the rates of the processes taking place within each of the network’s modules. The metabolites accumulated in bulk quantities and the processes accelerated to the highest extent are shown in bold.
Figure 3: A model for the spatiotemporal dynamics of the longevity network operating in chronologically aging yeast. The specific configurations of the longevity network that have been differently designed by CR and non-CR yeast during diauxic (D) phase and that have differently evolved in these yeast during the subsequent post-diauxic (PD) phase, result in establishing different rates of survival during the non-proliferative stationary (ST) phase. Thus, by designing a specific configuration of the modular longevity network prior to reproductive maturation, yeast defines their chronological lifespan. The thickness of arrows correlates with the rates of the processes taking place within each of the network’s modules. The metabolites accumulated in bulk quantities and the processes accelerated to the highest extent are shown in bold. The metabolites produced and the processes occurred during the step of the aging process preceding the step that is displayed is shown in gray colour.

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