Cell size is a complex quantitative trait resulting from interactions between intricate genetic networks and environmental conditions. Here, taking advantage of previous studies that uncovered hundreds of genes affecting budding yeast cell size homeostasis, we performed a wide pharmaco‐epistasis analysis using drugs mimicking cell size mutations. Simple epistasis relationship emerging from this approach allowed us to characterize a new cell size homeostasis pathway comprising the sirtuin Sir2, downstream effectors including the large ribosomal subunit (60S) and the transcriptional regulators Swi4 and Swi6. We showed that this Sir2/60S signaling route acts independently of other previously described cell size controlling pathways and may integrate the metabolic status of the cell through NAD+ intracellular concentration. Finally, although Sir2 and the 60S subunits regulate both cell size and replicative aging, we found that there is no clear causal relationship between these two complex traits. This study sheds light on a pathway of >50 genes and illustrates how pharmaco‐epistasis applied to yeast offers a potent experimental framework to explore complex genotype/phenotype relationships.
Pharmaco‐epistasis analyses using drugs mimicking cell size mutations in yeast uncovered a novel pathway in cell size homeostasis regulation. This pathway involves the sirtuin Sir2, the large ribosomal subunit (60S) and the Swi4/Swi6 transcription factors.
Drug–gene epistatic interactions with nicotinamide and diazaborine were analyzed using 189 previously identified small and 155 large mutants, showing that cell size homeostasis is the result of signals emanating from several independent pathways.
Ribosome biogenesis affects cell size homeostasis in different ways.
Modulation of cell size by Sir2 correlates with NAD+ intracellular variation.
No simple causal relationship was found between cell size and replicative aging even though both Sir2 and the 60S ribosomal subunit are contributing to these two complex traits.
Cell size, similar to the majority of phenotypic characters, is the result of complex genetic interactions. Cell size can vary substantially across cell types and organisms. It is influenced by endogenous factors such as ploidy but also by environmental conditions. However, for a given cell type in a defined growth condition, cell volume distribution is constant, thus arguing for a homeostatic control of cell size (Jorgensen and Tyers, 2004). Preserving cell size homeostasis necessitates gauging cell size and coordinating growth (increase in volume) and proliferation (increase in cell number). In unicellular organisms such as bacteria or yeast, cell size drastically varies with the richness of the medium (Wright and Lockhart, 1965; Johnston et al, 1979), implying a supplementary level of cell size regulation herein referred to as ‘nutrient control’. In fact, cells grown in poor media are significantly smaller than those grown in rich media (Johnston et al, 1979). Two major non‐exclusive hypotheses have been proposed to account for nutrient control of cell size. First, decreasing cell size leads to an increase of the cell surface to volume ratio and could, therefore, be advantageous for the uptake of scarce nutrients (Hennaut et al, 1970; Adams and Hansche, 1974). Second, diminishing cell size minimizes the amount of biomass needed for each division round and, therefore, allows the increase of cell number before complete starvation (Jorgensen et al, 2004; Jorgensen and Tyers, 2004). In both scenarios, cell size regulation by nutrients would contribute to an increased fitness of the population under sub‐optimal conditions.
In microorganisms, nutrient control of cell size has been studied for decades. In Bacillus subtilis (Weart et al, 2007), it has been shown that nutrient control of cell size occurs through a mechanism involving a metabolic enzyme (the glucosyltransferase UgtP), which, together with its substrate (UDP‐glucose), inhibits cell division. This elegant work has provided the first mechanism connecting a specific metabolic activity to the control of cell size and proliferation. In budding yeast, the key notion of ‘critical size’ has emerged, defined as the minimal size required for entering a new cell division cycle (Hartwell et al, 1974; Johnston et al, 1977). Although the averaged ‘critical size’ is relatively constant in a defined culture condition, it varies with the nutrient content of the medium (Johnston et al, 1979). How yeast cells convert a ‘sufficient biomass signal’, which could reflect volume, mass and/or biosynthetic capacity, into a ‘division signal’ is not entirely understood. Genetic approaches have been widely used to identify the key factors in this process. The first characterized mutants with a reduced cell size (named whi) affected the cyclin Cln3p. Although alleles of CLN3 stabilizing the protein lead to cell size diminution (Carter and Sudbery, 1980; Sudbery et al, 1980; Nash et al, 1988), knockout of CLN3 leads to a cell size increase (Lew et al, 1992). Cln3p interacts with the cyclin‐dependent kinase Cdc28p and inhibits Whi5p, a Rb homolog that negatively regulates the MBF (Swi6/Mbp1) and SBF (Swi6/Swi4) transcription activators (Costanzo et al, 2004; de Bruin et al, 2004). Thereby, Cln3p/Cdc28p stimulates the transcriptional activation of >100 genes involved in the transition from G1 to S phase (Spellman et al, 1998). However, Cln3 is not essential for cell cycle progression, possibly because of a partial functional redundancy with Bck2 (Ferrezuelo et al, 2009). The precise function of Bck2 is unclear, but this protein contributes to the activation of many genes, including most of Cln3 targets (Ferrezuelo et al, 2009). Together, these results pointed to the G1/S transition machinery as a major factor in cell size regulation, yet other cell cycle regulators could also have a role in cell size homeostasis (Harvey and Kellogg, 2003). In a reciprocal way, cell size control contributes to G1 length variability (Goranov and Amon, 2010). Moreover, cell growth capacity varies with cell cycle position, this capacity being higher in G1 and anaphase than during other cell cycle stages (Goranov et al, 2009). Recently, Polymenis and coworkers (Hoose et al, 2012) further substantiated the complex relations between cell cycle progression and cell size control by reporting that many mutations disturbing cell cycle progression do not affect cell size. Therefore, our understanding on how the upstream ‘cell size signals’ are conveyed and integrated to the control of cell cycle progression remains to be clarified.
Systematic identification of yeast cell size mutants, using knockout collections, has revealed the complexity of cell size homeostasis pathways (Jorgensen et al, 2002; Zhang et al, 2002a). Indeed, these authors identified hundreds of mutants with a median cell volume diverging significantly from that of the isogenic wild type. These large‐scale approaches have revealed new master regulators (Sch9p and Sfp1p) and have pointed to a central role for ribosome biogenesis and general nutrient sensing pathways (Ras and Tor) in the regulation of cell size homeostasis (Jorgensen et al, 2004). However, although important regulators have been well characterized, the vast majority of the identified cell size mutants, either small (whi) or large (lge and uge), have not yet been positioned into defined signaling pathways. Cell size control is thus a very interesting situation, where multiple loci contributing to a complex quantitative trait have been identified, but their organization into a network and their individual and combined influence remain to be elucidated.
In this study, we used a large‐scale pharmaco‐epistasis approach, which allowed us to characterize a new pathway containing >50 genes and responding to a metabolic signal identified as NAD+ or a derivative. Effectors in the pathway include the sirtuin Sir2, the ribosome large subunit 60S and the transcription factors Swi4 and Swi6. Interaction with previously described master regulators, as well as intrinsic and extrinsic signals such as ploidy or medium richness, was evaluated in order to arrange this pathway within the known cell size controlling network.
Cell size homeostasis is modulated by Sir2
Searching for compounds that affect yeast median cell volume (hereafter referred to as ‘cell size’), we observed that nicotinamide (Nam) treatment of a wild‐type strain resulted in cell size increase (Figure 1A and B). Nam, the amide form of nicotinic acid (Na), inhibits the sirtuin Sir2 (Bitterman et al, 2002). Accordingly, we found that deleting SIR2 caused an ∼20% increase of the cell size, as previously reported in Yang et al (2011), just as did a Nam treatment on wild‐type cells (Figure 1A and B). Further, Nam had no effect on sir2Δ cell size (Figure 1A and B), thus demonstrating that Nam affects cell size through Sir2, most probably by inhibition of its enzymatic activity. As expected, the sir2Δ large phenotype was rescued by the SIR2 gene reintroduced on a centromeric plasmid (Supplementary Figure 1). Nam is one of the two byproducts of the deacetylation reaction catalyzed by Sir2, the other reaction product being O‐acetyl‐ADP‐ribose (Figure 1C). The ysa1 mutant, known to accumulate O‐acetyl‐ADP‐ribose (Lee et al, 2008), displayed a wild‐type cell volume (Figure 1D). Therefore, O‐acetyl‐ADP‐ribose does not seem to be involved in cell size homeostasis.
Sir2 is a histone deacetylase involved in chromatin silencing (Guarente, 1999) at specific loci together—or not—with Sir3 and Sir4. Yet, deletion of SIR3 or SIR4 did not affect cell size, and sir3 or sir4 cells were fully responsive to Nam (Figure 1B), thus showing that the effect of Sir2 on cell size is independent of Sir3 or Sir4. Importantly, unlike sir2Δ, other large mutants such as cln3Δ or bck2Δ were further enlarged in response to Nam (Figure 1B), thus indicating that a maximal cell size had not been reached. Accordingly, Amon and coworkers (Goranov et al, 2009) have shown that Saccharomyces cerevisiae cells can reach a cell volume as big as 800 fl. We conclude that Nam affects cell size by phenocopying the sir2 deletion.
Mutants impairing ribosome biogenesis are epistatic to sir2
We then wanted to determine the genetic network through which Sir2 acts on cell size control. In order to identify downstream genetic effectors, we performed a large‐scale epistasis analysis to identify small size (whi) mutants masking the effect of sir2 on cell size. As the sir2 mutants is mating deficient (Wang et al, 2008), the combination of sir2 with whi mutations could hardly be done by large‐scale mating and sporulation methods such as those developed for Synthetic Genetic Array (SGA) analysis (Tong et al, 2001). Instead, we took advantage of the fact that Nam affects cell size similarly to the sir2 knockout and that the effect of Nam is totally dependent on Sir2 (Figure 1A). As Nam phenocopied the lack of Sir2, we used this drug to perform a pharmaco‐epistasis analysis on 189 previously identified small size (whi) mutants (corresponding to the smallest mutants identified by Tyers and coworkers (Jorgensen et al, 2002)).
Among the 189 mutants, 22 mutants were clearly not affected by Nam (0.95<Nam treated/untreated ratio <1.05; Figure 2A red dots and Supplementary Table 1), indicating that these mutants act downstream of Sir2 in the pathway. Of note, we found that several mutants described as whi by Tyers and coworkers (Jorgensen et al, 2002) were larger than wild type. This most probably reflects the differences in growth conditions used between the two studies. The pharmaco‐epistasis relationship was confirmed by classical genetics. We combined sir2 deletion with 2 of the 22 mutants, rpl35b (Figure 2B) and rpa49 (Figure 2C), and found that both mutants were fully epistatic to sir2 and, hence, presumably act downstream of Sir2 in the pathway. Another set of 74 mutants responded to Nam similar to wild‐type cells (1.18<Nam treated/untreated ratio <1.28), indicating that the mutated gene and the Nam treatment probably act through independent means on cell size control. Interestingly, most of these mutants (42/74, P‐value=3.6 × 10−13) affected various components of mitochondria (Supplementary Table 2). In addition to these fully responsive and unresponsive mutants, the remaining 93 mutants behaved in an intermediary way (54/93; 1.05<Nam treated/untreated ratio <1.18) or appeared hyper‐responsive to Nam (39/93; Nam treated/untreated ratio >1.28; Supplementary Table 2). This reveals complex gene/gene relationships that cannot be easily arranged into a pathway but may, in the future, be informative to understand the whole network.
Strikingly, most of the Nam‐unresponsive mutants (18/22) corresponded to knockout of genes encoding proteins implicated in diverse ribosome biogenesis steps (Supplementary Table 1). This was confirmed by GO term analyses (Supplementary Table 2) revealing a very significant enrichment for components of the cytosolic ribosome (13/22; P‐value=2.2 × 10−14) and more specifically cytoplasmic large ribosomal subunit (10/22; P‐value=3.5 × 10−12). In addition to the intrinsic constituents of the ribosome, six other proteins affected in the NAM‐unresponsive mutants are involved in rRNA synthesis/maturation (Pih1, Uaf30 and Rpa49), or required for ribosome assembly (Yvh1, Zuo1 and Jjj1). Finally, we noticed that for two mutants, bud19 and ygr160w, the deletion of the coding region affected overlapping genes, namely RPL39 and NSR1, both required for ribosome synthesis. Hence, our pharmaco‐epistasis analysis revealed a very strong enrichment for cytosolic ribosome mutants, although, quite surprisingly, strains deleted for two major ribosome biogenesis regulators, namely sfp1 or sch9 (Jorgensen et al, 2002; Jorgensen et al, 2004), were fully responsive to Nam (Figure 2A, blue dots), indicating that Sfp1 and Sch9 affect cell size mostly independently of Sir2.
To get a more complete view of the role of the ribosome in cell size homeostasis, we measured the volume of every non‐essential ribosomal protein mutants. Most of the yeast genes encoding ribosomal proteins are duplicated and, therefore, knockout of one of the two gene copies is generally not lethal. This analysis revealed a strong bias among ribosomal protein mutants: knockout of most of the large ribosomal subunit (60S) genes resulted in a Whi phenotype, whereas small subunit (40S) mutant cells were generally larger than wild‐type cells (Figure 3A and Supplementary Table 3). It should be stressed that for each ribosomal protein, the respective contribution of the two copies can be different. Therefore, for most of the mutants, the absence of a major cell volume phenotype could just reflect a minor contribution of the mutated gene copy. In any case, the cell volume distribution between 40S and 60S mutants was significantly different (Figure 3B) as previously observed by Hoose et al (2012), although in their study the significance of the difference between the two subunits was lower.
The opposite effects of small‐ and large‐subunit mutants on cell size may either reflect antagonistic impacts on the same pathway or separate effects on different pathways. To address this question, we constructed double mutants combining rpl and rps mutations. These double mutants showed an intermediary phenotype, suggesting that the large and small subunits could, at least in part, act independently on cell size homeostasis (Supplementary Figure 2). Together, our results establish that the 40S and 60S ribosomal subunits do not contribute similarly to cell size homeostasis. Consistent with the genetic data, we found that diazaborine (DAB), a drug that specifically impairs 60S assembly (Pertschy et al, 2004), caused a decrease of wild‐type cell size (Figure 3C). By contrast, the translation inhibitor cycloheximide (CHX) had no major effect (Figure 3C). Of note, in this experiment DAB and CHX were used at a low concentration, affecting only slightly and similarly the generation time (Figure 3C).
Together, these data point to an important role for the large ribosomal subunit in cell size homeostasis, most probably downstream of Sir2. It should be noted that those cell size mutants affect various steps of 60S synthesis and/or assembly, which take place in specific cellular compartments, suggesting that it is the assembled 60S particle rather than an intermediary assembled step that is important for cell size regulation.
Swi4 and Swi6 act in the downstream part of the Sir2–60S pathway
To further progress in our understanding of the genetic network involved in the Sir2/60S cell size control pathway, we again used a pharmaco‐epistasis approach. A set of 155 large mutants (corresponding to the largest mutants without major growth defect among those identified by Tyers and coworkers (Jorgensen et al, 2002)) were treated with DAB, which impairs 60S assembly and decreased cell size (Figure 3C). This allowed us to identify DAB‐unresponsive mutants, potentially acting downstream of the Sir2/60S part of the pathway (Figure 4A). As the wild‐type cell median volume ratio was 0.83±0.02, we considered as unresponsive the 40 mutants showing a ratio treated/untreated >0.95 (red dots in Figure 4A and Supplementary Table 4). To validate the pharmaco‐epistasis approach, we used classical genetics to combine each of the 40 unresponsive mutants with the rpa49 deletion, resulting in a robust Whi phenotype insensitive to Nam (Figure 2A) and epistatic to sir2 (Figure 2C). Among them, 33 were clearly epistatic to rpa49 (Figure 4B, red dots and Supplementary Table 5) fully validating the pharmaco‐epistasis results, 2 were hypostatic and were considered as false positive (i.e., not confirmed by classical genetics; orange dots in Figure 4B and Supplementary Table 5) and 5 double mutants could not be obtained (Supplementary Table 4). GO term analysis on the 33 confirmed mutants did not reveal any strong enrichment for a given cell component or function (Supplementary Table 6) that would give a clue on how the Sir2/60S pathway impinge on cell size. However, our attention was particularly drawn on swi4 and swi6, the subunits of the SBF complex (see Introduction section). We first verified that swi4 and swi6 mutants were fully epistatic to rpa49, rpl35b or rpl37a knockout (Figure 4C and D and Supplementary Figure 3A and B). As SBF (Swi4–Swi6) and MBF (Swi6–Mbp1) are known to act downstream of Cln3 and Whi5 in cell size control, we wished to examine how DAB affected cell size of these mutants. By contrast to swi4 and swi6, the mbp1 mutant showed a wild‐type cell size and was highly responsive to DAB (Figure 4A, blue dot). This result indicates that the SBF complex, but not the MBF complex, is required downstream of the Sir2–60S pathway. Unlike swi4 and swi6, the cln3 or bck2 mutants deleted for the upstream effectors were responsive to DAB (Figure 4A, blue dot). Together, these pharmaco‐epistasis analyses strongly suggest that Swi4 and Swi6 are positioned in the downstream portion of the Sir2/60S pathway, independently to their known upstream effectors (Cln3, Bck2 and Whi5).
NAD+ as a physiological signal modulating cell size through the Sir2/60s pathway
Our results establish that Sir2 and the 60S subunit define a new pathway that contributes to cell size homeostasis. We subsequently questioned the nature of the physiological signals that would modify Sir2 activity and thereby regulate cell size homeostasis. Sir2 activity is known to be modulated by NAD+ (Imai et al, 2000; Landry et al, 2000), which can be either synthesized de novo from tryptophan or recycled from Na (Figure 5A; Kucharczyk et al, 1998; Bieganowski and Brenner, 2004). Feeding wild‐type cells with increasing concentrations of Na resulted in a progressive cell size decrease (Figure 5B, yellow dots). As expected, Na addition also caused a drastic increase in cellular NAD+ in both wild‐type and sir2Δ cells (Figure 5C). However, although Na treatment affected wild‐type cell size, this was not the case for the sir2Δ mutant (Figure 5B, blue dots). Importantly, a npt1 mutant that is impaired for synthesis of NAD+ from Na was large and did not respond to extracellular Na (Figure 5D, black bars). In this mutant, intracellular Na concentration was high and NAD+ concentration was low compared with wild type (Figure 5D), as expected if the recycling of Na to NAD+ is impaired. Together, these results point to NAD+, or a derivative, as a physiological signal that regulates the Sir2/60S pathway. As NAD+ is thought to be the natural activator of Sir2 (Imai et al, 2000) and as sir2Δ cells are unresponsive to Na and NAD+ variations (Figure 5C), we conclude that NAD+ is a very strong candidate as a metabolic regulator of cell size in yeast. We thus propose that Sir2 contributes to the control of cell size homeostasis in yeast in response to variations of the NAD+ intracellular pool.
Positioning of the Sir2/60S pathway in the cell size control network
To get a more global view on how the Sir2/60S pathway impinges on cell size control in yeast, we examined the connections between known yeast cell size regulations and the Sir2/60S pathway. Cell size, similar to most complex traits, is not only affected by multiple genes but also by the environment and particularly by the richness of the growth medium. As an example, wild‐type yeast cells grown in the presence of raffinose, a carbon source less efficiently metabolized than glucose, have a 35%±4 reduced cell volume (Figure 6A). Importantly, carbon source control of cell size was still active in the Sir2/60S pathway mutants (Figure 6A). Yet, the most downstream mutants, swi4 and swi6, which are not specific to the Sir2/60s pathway, are less, although still significantly, affected by nutrients than wild‐type cells (Figure 6A). We conclude that the Sir2/60S pathway acts on cell size homeostasis independently of the raffinose/glucose nutritional control.
In our attempt to place the Sir2/60S pathway in a more global network resulting in cell size homeostasis, we also evaluated the relationships between the Sir2/60S pathway and ploidy. As previously shown (Galitski et al, 1999), we found that cell size increased with ploidy (Figure 6B). Yet, whatever the ploidy, a Nam treatment resulted in a 27±3% increase of cell size, whereas DAB led to a 19±4% decrease (Figure 6B). From these results, we conclude that the Sir2/60S pathway and the ploidy control of cell size are not linked.
Finally, we confirmed by classical genetics (Figure 6C) the pharmaco‐epistasis relationships found for whi5 (i.e., responsive to Nam; Figure 2A, blue dot) and cln3 (i.e., responsive to DAB; Figure 4A, blue dot). These results imply that the Sir2/60S pathway modulates cell size independently of the Cln3/Whi5 pathway, although both pathways have Swi4 and Swi6 in common (Figure 6D).
Mutations in SIR2 and 60S genes affect both cell size and replicative life span but the two phenomena are not strictly interdependent
It is noteworthy that Sir2 is a major factor of the yeast replicative aging, a process defined as the number of successive daughters produced by a cell before becoming senescent (Kaeberlein et al, 1999). In addition, a specific behavior for 60S ribosomal subunit mutants was previously reported in yeast for other phenotypes, including replicative aging (Steffen et al, 2008). The fact that SIR2, 60S mutants, medium richness and cell ploidy all affect both replicative aging and cell size homeostasis provocatively suggests that the two phenomena may be linked as previously proposed by others (Yang et al, 2011). To directly address this longstanding issue, we used combinations of mutations known to differently affect replicative life span. As reported previously, we found a clear increase in the generation number for the whi mutant rpl31a (Figure 7A; Steffen et al, 2008). However, the gcn4 deletion, suppressing the rpl31a replicative life span increase (Figure 7A; Steffen et al, 2008), had no effect on the rpl31a Whi phenotype (Figure 7B). Similarly, the fob1 mutation, which suppresses the sir2 replicative life span defect (Figure 7C; Kaeberlein et al, 1999), did not suppress the large phenotype of sir2 (Figure 7D). Finally, as previously observed, Nam decreased replicative life span (Bitterman et al, 2002) and this effect was found independent of the cell ploidy, as expected if it mimics a Sir2 defect (Figure 7E and F). However, replicative life span of untreated diploid and triploid cells was longer than that of haploid cells, despite the fact that increased ploidy resulted in an increased cell size (Figures 6C, and 7E and F, 7). Consequently, higher ploidy and Nam treatment of a wild‐type strain both increased cell size but had opposite effects on replicative life span. We thus conclude that cell size and replicative life span, although affected by a common set of mutants, can be disconnected.
Cell size, a highly complex trait regulated by hundreds of genes, offers a challenging framework to explore how complex genetic information is integrated in a phenotypic outcome. The understanding of such a complex network requires the identification of all the participating genes and the precise measurement of their individual and concerted contribution to the phenotype. These complex interactions between genes are referred to as epistasis, in the widest sense of the term. In yeast, epistasis is classically monitored after combining the mutations to be studied by mating and sporulation. This can be done on a large scale using approaches developed for SGAs (Tong et al, 2001). However, it still requires mating and sporulation, which take time, and may be difficult in some specific cases such as for sir2 mutants, which are mating deficient. Here we used a pharmaco‐epistasis approach based on the use of inhibitors to mimic specific mutations and thereby perform large‐scale epistasis analyses. To restrict possible off‐target effects, this approach needs the use of as low as possible concentrations of inhibitors, and when possible it should be validated by classical genetics. A major advantage of pharmaco‐epistasis is that as no meiosis is required, the phenotype comparison is done on strictly identical individuals in terms of genotype. Simple epistasis relationships are observed when one mutation (or drug mimicking the mutation) masks the effects of another mutation. We first concentrated on these situations, because they are relatively easy to interpret and allow positioning genes into linear regulatory pathways.
In the case of cell size control, we benefit from the large set of data provided by Tyers and coworkers (Jorgensen et al, 2002). We started from a set of knockout mutants showing the most extreme Whi (189 mutants) or Lge (155 mutants) phenotypes. It should be stressed that there is no theoretical reason to choose the most affected mutants, but this choice relies mainly on practical reasons. Indeed, measuring precisely cell size on multiple different yeast strains is a technically challenging issue (Turner et al, 2012). Accordingly, in the course of this work, we observed that cell size is exquisitely sensitive to growth conditions. Even though we paid a particular attention to this point, the experimental error is routinely ±5%. Consequently, it is much easier and it raises much stronger conclusions, in terms of statistical significance, to study combinations of mutants with extreme phenotypes.
We identified a subset of >50 genes belonging to a new cell size homeostasis pathway (Figure 6D). Remarkably, this pathway includes numerous mutants affecting ribosome biogenesis and more specifically the large ribosomal subunit. Of note, it would not be surprising that sir2 affects cell size homeostasis through its effect on silencing of rDNA (Smith and Boeke, 1997). Previous work from Tyers and coworkers (Jorgensen et al, 2004) had established a strong connection between ribosome biogenesis and cell size homeostasis. Here we observed that small ribosomal subunit mutants tend to be larger than the wild‐type control cells, whereas large ribosomal subunit mutants are often Whi. In addition, combination of 40S and 60S mutants resulted in an intermediary phenotype, strongly suggesting that these mutants affect cell size homeostasis by different mechanisms. It thus appears that there is not just one connection between ribosome biogenesis and cell size homeostasis but several layers of control. The first layer involves the Sfp1 and Sch9 effectors on the Ribi and RP regulons that connect nutrient control to critical size via the rate of ribosome production (Jorgensen et al, 2004). Our data establish that the Sir2/60S pathway is clearly distinct from the Sfp1/Sch9 network. First, as both sfp1 and sch9 mutants are fully responsive to Nam, and second, as Sir2/60S mutants are responsive to nutrients, whereas sfp1 or sch9 mutants are not (Jorgensen et al, 2004). However, the swi4 and swi6 mutants, the most downstream components of the pathway, although less responsive to the carbon source than wild‐type, are not fully insensitive (Figure 6A). This suggests that these components integrate regulatory signals from separate pathways (Figure 6D). A second layer of ribosomal effect on cell size involves the translational control of Cln3 (Polymenis and Schmidt, 1997). Yet, it is striking that Cln3 is neither required for ploidy control (Andalis et al, 2004) nor for nutrient control (Jorgensen et al, 2004) or the Sir2/60S pathway (this work). Further studies will be required to position Cln3 in the cell size homeostasis control network. The third layer, revealed by our pharmaco‐epistasis study, specifically involves the 60S ribosomal subunit. Intriguingly, a specific behavior of 60S mutants was previously reported in yeast for other phenotypes such as ER stress response (Miyoshi et al, 2002; Zhao et al, 2003) or replicative aging (Steffen et al, 2008). However, in both cases the underlying molecular mechanisms remain largely unknown.
In addition to the simple epistasis relationships, more complex gene/gene interactions were found, which cannot be simply interpreted. For instance, many mutants showed an intermediary response to Nam, indicating that they are not fully responsive to Nam but are neither totally irresponsive. Interestingly, among the 54 mutants behaving this way, more than half affected cytosolic ribosome. How should we interpret these partial effects? First, despite the fact that the mutants used in this study are knockout, some effects could be partial due to gene redundancy; this is clearly the case for ribosomal protein genes that are generally duplicated. Second, some gene interactions can be more complicated than just phenotypic masking. In particular, it is likely that many of the studied mutants have pleiotropic effects that could simultaneously affect more than one pathway. In this type of analyses, one should keep in mind the multiple levels of complexity due to allelic diversity and specificity. In this perspective, yeast offers a simplified model due to the possible use of knockout mutations and to the fact that the genetic network is analyzed in haploid cells.
Another major level of complexity is interaction between genetic factors and the environment. Once again, yeast, as it is a unicellular organism, provides a simpler experimental frame. Strikingly, we found that the abundance of the coenzyme NAD+ appears as a major regulator of cell size homeostasis. Abundance of free NAD+ results from de novo synthesis and recycling from precursors such as Na, but also from its equilibrium with the reduced NADH form. It has been shown that in living cells, free NAD+ is several orders of magnitude more abundant than free NADH (Williamson et al, 1967; Zhang et al, 2002b). NAD+ concentration in yeast has been estimated to be in the millimolar range (Belenky et al, 2007; this work). This concentration is by far higher than the Km of Sir2 for NAD+, which is about 30 μM (Bedalov et al, 2003; Borra et al, 2004). Consequently, it seems likely that activation of Sir2 by NAD+ does not simply reflect substrate availability but more probably relies on a more complex regulatory mechanism involving allosteric effects. Accordingly, our results show that moderate variations of NAD+ concentration may impinge on cell size. Through its role in regulating Sir2 activity, we propose that NAD+ acts as a ‘metabolic cell sizer,’ providing a simple and efficient mechanism to adapt cell size to metabolic status.
Finally, the discovery of the Sir2/60S pathway as a major factor in cell size homeostasis echoed its effect on replicative aging (Steffen et al, 2008), raising the hypothesis of a causal connection between cell size and aging. In addition, as noticed by Schneider and coworkers (Yang et al, 2011), many cell size mutants are also affected for replicative life span. Accordingly, growth under conditions where carbon is limiting results in a decreased cell size and an increased replicative life span. However, we showed here that Fob1 and Gcn4, which are clearly involved in the replicative aging process, do not affect cell size, thus disconnecting the two phenomena. Moreover, both the treatment of cells with Nam and an increased ploidy resulted in a larger median cell volume, while having opposite effects on replicative life span. Hence, it seems that no simple connection between the two phenomena can yet be drawn. A similar conclusion was reached by Guarente and coworkers (Kennedy et al, 1994) on yeast cells artificially enlarged by α‐factor arrest, although opposite results have also been reported (Zadrag et al, 2005). At this point, it is not possible to draw a definitive conclusion on this complex relationship between cell size and aging. Indeed, although many signaling pathways are shared by cell size and longevity, suggesting important common mechanisms, conspicuous counter examples such as those reported in this work rather argue for a disconnection of the two phenomena. The fascinating question of relationships between size and life span of living organisms rose by Aristotle in his essay ‘On Longevity and Shortness of Life’ 23 centuries ago, remains open.
Materials and methods
Media, strains and plasmids
SDcasaU is a synthetic minimal medium containing 5% ammonium sulfate, 0.67% yeast nitrogen base (Difco) and 2% glucose, supplemented with 0.2% casamino acids (Difco) and uracil (0.3 mM). SRafcasaU is a similar medium containing 2% raffinose instead of glucose. In specific experiments requiring modulation of Na concentrations, SDcasaU was made with Na‐free yeast nitrogen base (Formedium) and was supplemented with indicated concentrations of Na (Sigma‐Aldrich). The YPD medium used for replicative life span experiments contained 1% yeast extract, 2% peptone, 2% glucose. NAM (Sigma‐Aldrich) and DAB (kind gift from Dr H Bergler) were used at indicated concentrations. All yeast strains were derived from the parent strains BY4741 and BY4742 of the haploid yeast ORF deletion collections (Winzeler et al, 1999). Polyploid strains isogenic to BY4741 and BY4742 strains were obtained from David Pellman (Storchova et al, 2006). The rpa49:17444292:HIS3 mutants were obtained by transformation of wild‐type or single mutant strains with a PCR fragment obtained on genomic DNA from the SL107‐3B strain (Beckouet et al, 2008; generous gift from Michel Werner) with oligonucleotides RPA49up (5′‐CGACGCCAATTAGCAATACTG‐3′) and RPA49Rv (5′‐CTATTTGTACATATGTATCTTCTCAG‐3′). Histidine‐prototrophic transformants were selected and insertion of the rpa49:17444292:HIS3 cassette at RPA49 locus was verified by PCR with oligonucleotides RPA49prom (5′‐TTCTTTAGCTTGTGGCGTTGG‐3′) and RPA49Rv. All other multiple mutant strains used in this study were obtained by mating, sporulation and tetrad dissection. Double mutants were identified by PCR using the KanB oligonucleotide (internal to KanMX4; 5′‐CTGCAGCGAGGAGCCGTAAT‐3′) and an oligonucleotide complementary to the promoter of the disrupted gene. The sir2 mutation leading to a decreased mating efficiency (Shore et al, 1984), construction of double mutants was also done by crossing, but with a sir2 mutant strain covered by a SIR2 centromeric plasmid (p4099; URA3; lab collection). Meiotic sir2 segregants, having lost the plasmid, were then identified as uracil auxotroph. Doubling time of the most used strains in this study are as follows: wild‐type strain (105 min), rpl31a (120 min), rpl35b (130 min), rpa49 (135 min), sir2 (105 min), swi4 (165 min) and swi6 (165 min).
Cell size distribution measurements
All cell size measurements were performed by determining the median cell volume of asynchronous yeast cell cultures using a Coulter‐counter apparatus (Beckman‐Coulter). Compared with other methods used for yeast cell volume measurement, this method is fast and accurate, and allows to process multiple samples (Turner et al, 2012). Cells were grown overnight in SDcasaU or SRaffcasaU media, and then diluted several times in order to maintain exponential growth (cell number is always kept under 2 × 107 cells/ml) for 24–48 h before cell size measurement. It should be stressed that we noticed a significant effect of culture conditions on wild‐type cell volume (Supplementary Figure 4). Consequently, volume comparisons require to be done on cells grown in the exact same conditions. To obtain each cell size distribution, 100 μl of culture were then diluted into 10 ml of IsotonII (Beckman‐Coulter) and size distribution of the population was analyzed with a multisizer4 (Beckman‐Coulter) by counting between 10 000 and 20 000 cells for each measurement. Results are given as the percentage of cells counted in each of the 400‐size classes. Median volume was obtained from the geometric cell volume distribution by using the Multi4 software (4.02 version; Beckman‐Coulter) with a smoothing of 7 as previously done in yeast (Jorgensen et al, 2002). Statistical significance of differences between two conditions has been determined through the use of an unpaired Student's t‐test (Graphpad Prism Software). For size determination in presence of Nam (100 μM), DAB (0.5 mg/l) and CHX (0.01 mg/l), cells were incubated in the presence of the indicated drugs for 8 h (Nam) or 16 h (DAB and CHX) before measurements. For epistasis studies, median cell volumes were determined on the four spores of at least four tetratypes.
Replicative life span analysis
All replicative life span experiments were carried out (at least twice) as described (Kaeberlein et al, 2005) on 50–100 daughters of daughter cells grown on standard YPD plates containing or not Nam (500 μM, a dose resulting in a 20% median volume increase on plates). Statistical significance of replicative life span changes between strains was determined using a Wilcoxon rank‐sum test (GraphPad Prism Software) using a cutoff value of P=0.05.
Intracellular metabolites determination
Wild‐type and mutant strains were kept in exponential phase for 48 h in SDcasaU Na‐free medium supplemented or not with extracellular Na (3 μM, corresponding to the concentration found in Na‐containing SD medium). Metabolites extraction by rapid filtration and ethanol boiling method, and metabolite separation by liquid chromatography were performed as described previously (Hurlimann et al, 2011; Laporte et al, 2011).
We thank Dr H Bergler for the kind gift of DAB, Drs D Pellman and M Werner for sharing biological materials; Drs PA Defossez and M Fromont‐Racine for helpful discussion; Drs JE Gomes and M Moenner for comments on the manuscript; J Ceschin, C Saint‐Marc and J Tissot‐Dupont for technical assistance. This work was supported by Conseil Régional d'Aquitaine, Université Bordeaux Segalen, CNRS PEPS program and Agence Nationale de la Recherche grant numbers ANR‐12‐BSV6‐0001‐02 and ANR‐12‐BSV6‐0001‐01.
Author contributions: BP and BD‐F conceived the study; FM, BP and IS designed and performed experiments; BP and BD‐F provided a supervisory role. All authors wrote and edited the manuscript.
Conflict of Interest
The authors declare that they have no conflict of interest.
Supplementary Figures 1–4 and Supplementary Tables 1–6 [msb201360-sup-0001.pdf]
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