Survival of starving yeast is correlated with oxidative PNAS PLUS stress response and nonrespiratory mitochondrial function

Allegra A. Pettia,b, Christopher A. Crutchfielda,c, Joshua D. Rabinowitza,c, and David Botsteina,b,1

aLewis-Sigler Institute for Integrative Genomics and Departments of bMolecular Biology and cChemistry, Princeton University, Princeton, NJ 08544

Edited by Jasper Rine, University of California, Berkeley, CA, and approved June 8, 2011 (received for review January 31, 2011) Survival of yeast during starvation has been shown to depend on tions for other areas of biology, because connections among the the nature of the missing nutrient(s). In general, starvation for same processes that are influenced by nutrient starvation have “natural” nutrients such as sources of carbon, phosphate, nitro- been documented in cancer, aging, and the yeast metabolic cycle. gen, or sulfate results in low death rates, whereas starvation for As a first step toward understanding general determinants of amino acids or other metabolites in auxotrophic mutants results in starvation phenotype, we sought to identify transcriptional cor- rapid loss of viability. Here we characterized phenotype, ex- relates of “successful” or “survivable” starvation—that is, starva- pression, and metabolite abundance during starvation for methi- tion that leads to concerted cell cycle arrest, glucose conservation, onine. Some methionine auxotrophs (those with blocks in the and, most importantly, survival. To this end, we compared the biosynthetic pathway) respond to methionine starvation like yeast physiology and of S. cerevisiae in response to starving for natural nutrients such as phosphate or sulfate: they starvation for a variety of previously characterized nutrients, and undergo a uniform cell cycle arrest, conserve glucose, and survive. for one additional nutrient, methionine. We chose methionine In contrast, methionine auxotrophs with defects in the transcrip- because previous studies hint that it coordinates diverse cellular tion factors Met31p and Met32p respond poorly, like other auxo- functions, thereby acting as a regulatory hub. For example, me- trophs. We combined physiological and gene expression data from thionine starvation of a methionine auxotroph causes rapid and a variety of nutrient starvations (in both respiratory competent uniform G0/G1 cell cycle arrest (2), unlike the result obtained and incompetent cells) to show that successful starvation response with other auxotrophies (3). In addition, genome-wide analyses is correlated with expression of encoding oxidative stress of periodic gene expression during the cell cycle showed that response and nonrespiratory mitochondrial functions, but not res- methionine is the only amino acid whose biosynthetic genes ex- piration per se. hibit periodic expression (4). In the yeast metabolic cycle, the methionine-regulated transcription factors exhibit the most highly | longevity | Warburg effect periodic transcriptional activity, implying a connection between the methionine regulon and the respiro-fermentative balance (5– 7). This implied connection is strengthened by a study of glucose

nderstanding global coordination of subcellular processes SYSTEMS BIOLOGY Uduring adaptation to environmental change is a central chal- repletion in yeast, which shows that methionine biosynthetic lenge in systems biology. The ability of free-living organisms to genes are highly induced upon relief from glucose starvation adapt to changes in their nutritional environment is clearly one (8). The methionine-regulated transcription factors are also well of the driving forces of their evolution. In natural environments, known to regulate the response to various toxins, including heavy yeast are exposed to extreme variations in “natural nutrient” metals and oxidizing agents (9, 10). availability, particularly in their sources of carbon (and energy), We began our comparison of multiple nutrient starvations by phosphorus, sulfur, and nitrogen. Unlike wild type strains, characterizing physiology, gene expression, and metabolite abun- fi auxotrophic mutant yeast strains unable to make an essential dance during methionine starvation. We rst created a panel of metabolite (e.g., leucine or uracil) can also be starved for the isogenic methionine auxotrophs. Two of these deletion mutants met6Δ met13Δ missing metabolite, but adaptation to this kind of “nonnatural” ( and ) lack genes encoding steps in methionine “ ” starvation has not been subject to evolutionary selection. Star- biosynthesis, creating a metabolic defect. The others lack vation of Saccharomyces cerevisiae for a single, growth-limiting genes encoding one or more methionine transcription factors, “ ” nutrient offers the opportunity to study the coordination of nu- thereby creating regulatory defects that result in a methionine trient sensing, metabolism, growth, and cell division. Proper requirement. Phenotypic characterization of these strains con- fi coordination results in prolonged survival, concerted cell cycle rmed that methionine starvation is indeed different from the arrest, and glucose conservation during starvation, and depends previously studied auxotrophic starvations and results in a pheno- strongly on the specific nutrient being depleted. For instance, the type intermediate between that of the natural nutrient starvations survival of auxotrophic yeast starved for leucine, histidine, or and the other auxotrophic starvations. Methionine starvation of uracil is substantially impaired (exhibiting a roughly 10-fold difference in half-life) relative to the same strain starved for the “natural” nutrients sulfate or phosphate (1). Starvation for sul- Author contributions: A.A.P., J.D.R., and D.B. designed research; A.A.P. and C.A.C. per- fate or phosphate elicits rapid, nearly uniform G0/G1 cell cycle formed research; A.A.P. contributed new reagents/analytic tools; A.A.P. analyzed data; arrest and slows glucose consumption, whereas starvation for and A.A.P. and D.B. wrote the paper. leucine, histidine, or uracil results in incomplete cell cycle arrest The authors declare no conflict of interest. and markedly higher rates of glucose consumption. This article is a PNAS Direct Submission. We are interested in understanding what, if any, general Freely available online through the PNAS open access option. principles determine starvation phenotype. Early work on nu- Data deposition: The microarray expression data reported in this paper have been de- trient starvation posited the existence of a starvation “signal” posited at http://genomics-pubs.princeton.edu/StarvationSurvival/. that promotes concerted cell cycle arrest and survival in response 1To whom correspondence should be addressed. E-mail: [email protected]. to nutritional scarcity (2). However, fundamental questions See Author Summary on page 18217. about the identity and effects of the starvation signal have never This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. been addressed. The answers to these questions have implica- 1073/pnas.1101494108/-/DCSupplemental.

www.pnas.org/cgi/doi/10.1073/pnas.1101494108 PNAS | November 8, 2011 | vol. 108 | no. 45 | E1089–E1098 Downloaded by guest on October 1, 2021 met6Δ or met13Δ mutants, like sulfate or phosphate starvation of a wild-type strain, results in uniform G0/G1 arrest, substantially A increased survival relative to leucine or uracil starvation (assessed 100 in mutants with analogous metabolic defects), and in conservation of residual glucose. 10 By comparing mRNA levels during methionine starvation in met6Δ met13Δ and with the previously published results of similar 1 experiments during starvation for leucine, uracil, phosphate, and sulfate, we found a group of genes whose expression is strongly Percent Viability 0.1 correlated with successful response to starvation. These nuclearly encoded genes are enriched for assorted mitochondrial functions, 0.01 response to heat and oxidative stress, and regulation of the 0184 12 6 respiro-fermentative balance. We then narrowed down the role of these functions in survival: during starvation for various nutrients, Days we measured survival of ρ0 mutants and hydrogen peroxide- treated (ρ+) strains, which showed that oxidative phosphorylation B is not required for survival but that survival half-life is correlated 90 with ability to detoxify reactive oxygen species (ROS). This result is fortified by our observation that the short-lived regulatory methionine auxotroph, met31Δmet32Δ, differs from the long-lived 70 metabolic methionine auxotrophs primarily in its reduced ability to combat oxidative stress during methionine starvation. Our results speak against the intuitive and commonly held 50 view that oxidative metabolism is deleterious per se. Instead, the Percent Arrested data suggest that induction of the transcriptional programs as- sociated with, but not dependent on, respiration exerts a pro- 30 tective effect on the cell during nutritional shortages, possibly 5152535 because the many protective mechanisms against oxidative Hours damage and related stresses become increasingly engaged as the cell shifts from fermentative to oxidative metabolism. C 120 Results Starvation for Methionine Resembles Starvation for Natural Nutrients. 80 The response of S. cerevisiae to starvation for phosphate, sulfate, ammonium, leucine, and uracil has been previously described (1, 3, 11). To determine where methionine starvation lies on the spectrum of starvation phenotypes, we measured survival, glucose 40 consumption, and cell cycle arrest during methionine starvation of the metabolic methionine auxotrophs met6Δ and met13Δ.To

calibrate our measurements against those in the literature, we Percent Residual Glucose 0 also measured these parameters during starvation of a previously 20 40 60 80 leu2Δ studied leucine auxotroph, . We compared all measure- Hours ments with those made during phosphate starvation. To measure the starvation survival of met6Δ, met13Δ,andleu2Δ, Pho (met6 (panel A)) Met (met6 ) a single colony of each strain was grown in medium limited for Pho (FY4 (panel B)) Met (met13 ) a single nutrient, either phosphate or the required amino acid. Each Pho (met13 ) Met (met31Δmet32 ) strain was then diluted into medium lacking only that nutrient, and Pho (leu2 ) Leu (leu2 ) viability over time was measured (Materials and Methods). These Pho (met31Δmet32 ) Ura (ura3-52) methionine auxotrophs, when starved for methionine, survived longer than leucine or uracil auxotrophs starved for their respective Fig. 1. Physiological responses to nutrient starvation. (A) Survival over time requirements but not as long as the same strains starved for phos- during starvation for methionine (Met), phosphate (Pho), or Leucine (Leu) phate or sulfate (Fig. 1A and Table S1)(1).Fig.1A also contains using the indicated strains. Survival was measured as the ability to form met31Δmet32Δ a colony on rich medium plates. (B) Cell cycle arrest, as measured by per- data for the regulatory methionine auxotroph ,in centage of cells with no bud (assessed by light microscopy), during starvation which the methionine requirement is caused by the deletion of two for Met, Pho, Leu, or Uracil (Ura) using the indicated strains. Representa- genes, MET31 and MET32, which encode transcription factors; we tive time courses are shown, with more comprehensive data provided in address its properties below. We classified the starvations as long- Table S1.(C) Glucose consumption (measured as described in Materials and lived [phosphate, sulfate, and methionine (metabolic; met6Δ or Methods) after biomass (measured by optical density) has reached its pla- met13Δ)] or short-lived [(leucine, uracil, and methionine (regula- teau during starvation for Met or Leu. Error bars show SD of technical tory; met31Δmet32Δ)] according to the data in Fig. 1A. replicates. Survival during starvation correlates strongly with uniformity of cell cycle arrest in stationary phase cultures (1, 3, 11). We measured bud index for three cultures each of met6Δ and met13Δ nearly the same extent as phosphate starvation (P=0.07 by two- sided Student t test) but to a significantly greater extent than undergoing methionine starvation, and for one culture each of − strains undergoing leucine (leu2Δ), uracil (ura3-52), and phos- leucine and uracil starvation (P=9.9 × 10 5). This, as expected, phate starvation (FY4) (Fig. 1B and Table S1). Combining our recapitulates the cell cycle arrest during methionine starvation results with those in ref. 3, we found that methionine starvation is that was initially observed decades ago (2). an outlier with respect to the other studied auxotrophic starva- In previously studied starvations, survival time and arrest tions: methionine starvation induces cell cycle arrest in G0/G1 to phenotype correlated with the rate of glucose consumption after

E1090 | www.pnas.org/cgi/doi/10.1073/pnas.1101494108 Petti et al. Downloaded by guest on October 1, 2021 biomass accumulation stopped increasing (1, 12). We measured PNAS PLUS M M M LP SU the concentration of residual, extracellular glucose in batch cul- (6) (13) (TF) tures of met6Δ, met13Δ, leu2Δ, and the exceptional met31Δmet32Δ Cluster 31: Genes specifi- undergoing starvation for the required amino acid. Like proto- cally induced by methio- trophs starving for a natural nutrient, metabolic methionine aux- nine starvation otrophs starving for methionine stopped consuming glucose once Process: No GO enrich- biomass accumulation reached a plateau. In contrast, the leucine ment; MIPS enrichment for auxotroph continued consuming glucose, as reported previously DNA topology; stress (Fig. 1C) (1). response; aerobic respiration A diverse set of survival assays has been used to show that re- Component: Mitochodrial pression of glucose-activated signaling pathways, such as PKA inner membrane*, integral to fl and Tor, prolongs survival (1, 13, 14). To test the in uence of membrane*, respiratory glucose-activated signaling on survival during methionine star- chain* vation, we repeated the met6Δ and met13Δ survival measurements using a combination of glycerol and ethanol as the carbon source, which increased survival during methionine starvation almost twofold (Table S1).

Methionine Starvation Activates a Characteristic Gene Expression Program. We followed gene expression during methionine star- vation of the metabolic methionine auxotrophs met6Δ and met13Δ using a filter-based cell growth protocol that permits instantaneous removal of external methionine (Materials and Methods). This facilitates comparison of multiple strains because it allows the time courses to be aligned to the instant of methi- Cluster 12: Genes specifi- Cluster 25: Genes onine removal. As described in SI Materials and Methods, linear cally repressed by regulated by methionine regression was used to select genes exhibiting (i) a statistically methionine starvation and sulfur starvation significant dependence on time and (ii) at least a twofold change Process: Cell cycle; Process: Sulfur amino acid in one or both time courses. In this regression analysis, the nucleotide metabolism; cell biosynthesis; methionine P value of the F statistic for the regression model represents the fi aging; chromatid segrega- metabolism; serine family signi cance of the time dependence, and Q-VALUE software tion; nuclear division; DNA metabolism; aspartate (15) was used to identify P values corresponding to a false dis- replication; cell wall organiza- family metabolism; sulfate covery rate (FDR) of at most 0.01 (SI Materials and Methods). The resulting gene set shows that a wide variety of biological tion assimilation; response to processes are perturbed during methionine starvation. We fo- Component: Chromosomal drug; oxidation reduction; cused on identifying processes that are perturbed specifically part, mitotic cohesin siroheme metabolism; SYSTEMS BIOLOGY during methionine starvation and might therefore provide insight complex, intrinsic to plasma responses to metal ion and into the unique role of methionine in the cell cycle, the metabolic membrane hydrogen peroxide; cycle, and carbohydrate metabolism. To isolate such processes, phosphatidylcholine we compared our methionine starvation gene expression data biosynthesis with previously published gene expression data collected during Component: Sulfite phosphate, sulfate, leucine, and uracil starvations, the “Mega- -3 0 3 reductase complex ” Cluster in ref. 3. (NADPH) We processed, combined, and filtered these data sets as de- scribed in SI Materials and Methods. To control for potential Fig. 2. Expression profiles specific to methionine and sulfate starvation. differences between our instantaneous starvation protocol and K-means clusters characterized by gene expression specific to methionine the gradual starvation protocols used for leucine, phosphate, starvation (cluster 31 and cluster 12) or methionine and sulfate starvation sulfate, and uracil, we also collected expression data for met13Δ (cluster 25). Each heatmap shows microarray expression data for seven starvation time courses, separated by gray columns. The starvations are, according to the protocol used for these other nutrients. A Δ Δ comparison of met13Δ expression data using the two alternate from left to right, methionine using met6 [M(6)], methionine using met13 [M(13)], methionine using the Transcription factor mutant met31Δmet32Δ protocols showed essentially identical patterns of gene expression [M(T)], leucine using leu2Δ (L), phosphate using FY4 (P), sulfate using FY4 (S), (Fig. S1 and Dataset S1). To identify genes whose differential and uracil using ura3-52 (U). The grayscale triangles above each time course expression is specific to methionine starvation, we clustered the show how the time courses were grouped for analysis and interpretation. combined expression data set into 40 distinct clusters using Here, for example, methionine starvation in metabolic methionine auxo- k-means clustering (SI Materials and Methods, Fig. S2A,and trophs (black triangles) was compared with phosphate, sulfur, leucine, and Dataset S1). We then focused on gene clusters displaying expres- uracil starvation (gray triangles). met31Δmet32Δ expression data (white tri- sion profiles specific to methionine starvation or to both methio- angle) is displayed but was not used in the analysis. The functional enrich- ≤ nine and sulfate starvation. ment (FDR 0.1, or, where indicated with an asterisk, between 0.1 and 0.2) k of each gene set is summarized next to the corresponding heat map. The -means clustering yielded a cluster of genes (cluster 25) Detailed enrichment data are provided in Table S2. that are induced only in methionine or sulfate starvation (Fig. 2, Table S2,andDataset S1). As expected, a significant number of these genes function in sulfur metabolism and methionine bio- ” “ ” YAP1 GSH1 OPT1 synthesis, including the entire methionine biosynthetic pathway. response, and response to drug (e.g., , , , GRX8 MXR1 ZWF1 “ ” Remarkably, this cluster also contains a number of the NAD and , ,and )and phosphatidylcholine biosynthesis NADP-binding enzymes on which methionine biosynthesis in- (OPI3, CKI1, SER33). directly depends. Several other biological processes that depend The substantial overlap between the transcriptional responses to heavily on methionine abundance are also enriched here, including sulfate and methionine starvation suggests that methionine might the overlapping categories “oxidation reduction,”“oxidative stress serve as an “indicator metabolite” for sulfate starvation. Despite

Petti et al. PNAS | November 8, 2011 | vol. 108 | no. 45 | E1091 Downloaded by guest on October 1, 2021 this overlap, some genes are purely methionine starvation-specific. Of these, the repressed subset (cluster 12) is enriched for cell cycle regulation (e.g., TOR2, NDD1, PCL1, YOX1, RAD9, RAD53)and L-methionine related processes, such as chromatid segregation, DNA replication, A 4-methylthio-2-oxobutanoic acid S-adenosyl-L-methionine and nucleotide metabolism. It is also enriched for genes implicated homocysteine allantoate in response to aging (SCH9, HDA2, LAC1, SGS1,andACS2)and d-fructose 1,6-bisphosphate 5’-methylthioadenosine cell wall organization through the SHO1 osmosensing pathway. cystationine NADH 2-propylmalic acid Genes that are repressed in all starvations but methionine L-2-aminoadipic acid D-lactate (cluster 27) are enriched for assorted mitochondrial functions, kynurenic acid ascorbic acid including the folate cycle (GCV1, GCV2, GCV3) and 2-dehydro-D-gluconate D-gluconate (e.g., AIM10, MST1, MSK1, MSD1, QCR6, MRPS17, PPA2, L-methylhistidine myo-inositol MRPL22, ALG6). This reflects the fact that the methionine maleic acid citraconic acid methylmalonic acid biosynthetic pathway interacts directly with the folate pathway at o-acetylcarnitine 2-aminoisobutyric acid its penultimate step, in which the methylenetetrahydrofolate re- glycerophosphocholine dihydroxyacetone phosphate ductase encoded by MET13 catalyzes the reduction of 5,10- D-glyceraldehyde 3-phosphate D-ribose 5-phosphate methylenetetrahydrofolate to 5-methyltetrahydrofolate. cellobiose phosphatidylglycerophosphate fi pyruvate Only a few terms are signi cantly overrepresented among the nicotinate fi pyridoxine genes that are most strongly and speci cally induced during L-alanine L-threonine methionine depletion (cluster 31) [e.g., the Munich Information pantothenate sucrose Center for Sequences (MIPS) categories related to DNA indole-3-carboxylic acid D-glucono-1,5-lactone topology and aerobic respiration]. At a more lenient FDR, genes 6-phosphate p-aminobenzoate QCR2 QCR8 COX6 L-glutamine involved in ATP biosynthesis ( , , and ) and L-dihydroorotate IPT1 PBN1 adenosine metabolism of membrane phospholipids (e.g., , , UDP cytidine PSD1, TGL2, and TLG2) are overrepresented. cytosine n-acetylornithine L-proline L-alanine Transcriptional Regulation of Metabolic Pathways and Isozymes L-threonine cis-aconitate During Methionine Starvation. D-glucose 1-phosphate To understand metabolic changes L-histidinol D-fructose 6-phosphate during methionine starvation from a transcriptional perspective, L-malate NAD+ (1) we mapped the most differentially regulated enzyme-encoding ATP phenylpropiolic acid genes (≥32-fold change in met6Δ and/or met13Δ) onto the met- 3-hydroxy-3-methylglutarate (1) 3-hydroxy-3-methylglutarate (2) abolic network (Fig. S3). Notable are the high induction of an- control trehalose tioxidant biosynthetic genes (CTT1, GSH1, GTT1, GTT2,and cysteine GPX1 isocitrate ); differential regulation of most pentose phosphate NADP+ hexose pathway genes; induction of the NAD metabolic genes BNA3 sedoheptulose 7-phosphate glutathione (1) and PNC1; and repression of nucleotide biosynthesis and the control alpha-D-glucose 6-phosphate thiamine folate cycle. shikimate 3-phosphate glutathione (2) The set of differentially expressed genes contains several iso- NAD+ (2) 4-pyridoxic acid zyme pairs that are particularly informative because they exhibit inosine guanosine different specificities for anaerobic and aerobic conditions. In ADP phenylpyruvate every pair, the isozyme specific to respiration is induced, whereas L-ornithine adenine fi cf. GLK1 HXK1 AMP that speci c to fermentation is repressed ( and n-acetyl-glutamine HXK2 PDC5 PDC6 ALD4 ALD6 GDH1 GDH3 n6-acetyl-L-lysine vs. , vs. , vs. , vs. , glutamate L-glutamine GND1 vs. GND2, and TKL1 vs. TKL2). This suggests that me- L-pipecolate L-arginine thionine starvation may cause the cell to rely increasingly on L-asparagine L-leucine respiration for energy generation. udp-D-glucose L-phenylalanine L-histidine L-lysine O-acetylhomoserine Direct Assessment of Metabolism During Methionine Starvation. We udp-n-acetyl-D-glucosamine L-aspartate measured intracellular metabolites for one methionine auxo- serine UTP troph, met13Δ, during starvation (Materials and Methods). Nor- CTP GTP malization and processing of these data are described in SI ATP citrulline Materials and Methods. Hierarchical clustering was used to iden- trehalose 6-phosphate L-valine tify clusters of metabolites that exhibit coordinated changes in L-isoleucine tyrosine abundance (Fig. 3A and Dataset S1). As expected, the metabo- tryptophan n-acetylputrescine lites whose abundance decreases earliest and most dramatically citrate (1) (Fig. 3A, turquoise bar) are predominantly associated with me- citrate (2) -7 0 7 thionine biosynthesis or salvage (e.g., methionine, 4-methyl- 10 thio-2-oxobutanoic acid, S-adenosyl methionine, homocysteine, B ′ fl ’ 8 5 -methylthioadensoine, and cysteine), re ecting the cell sneed 6 to replenish methionine. However, the set of rapidly depleted 4 metabolites also includes fructose-1,6-bisphosphate and NADH, 2

reflecting the broader metabolic reconfiguration that occurs dur- Arbitrary Units 0 ing methionine starvation. Fructose-1,6-bisphosphate (F1,6BP) is 0 246 produced from fructose-6-phosphate (F6P) by phosphofructoki- Hours nase (PFK), the main regulator of glycolytic flux (16). Two Fig. 3. Metabolite abundance during methionine starvation of met13Δ.(A) observations suggest that PFK activity is reduced. First, F6P Metabolite abundance data in arbitrary units of fold-change relative to the abundance increases concomitantly with the decrease in F1,6BP, zero time point. Colored bars indicate the metabolites exhibiting the implying inhibition of PFK. Second, citrate, a major inhibitor of greatest changes in abundance (range is ±128-fold). (B) NAD:NADH ratio PFK, is the metabolite whose abundance increases most. The de- during the time course.

E1092 | www.pnas.org/cgi/doi/10.1073/pnas.1101494108 Petti et al. Downloaded by guest on October 1, 2021 crease in NADH abundance causes an increase in the NAD:NADH M M M PNAS PLUS ratio (Fig. 3B), which is also consistent with an increase in respi- (6)(13)(TF) ration. The NAD:NADH ratio is a potentially important clue to the mechanism by which methionine starvation prolongs survival. This Methionine biosynthesis; sulfur assimilation; DNA fl ratio is widely thought to re ect the overall cellular energy balance, repair; antioxidant biosynthesis and an increase in NAD:NADH due to falling NADH has been explicitly implicated in longevity extension by dietary restriction (17). Taken together, the metabolite measurements support the Iron homeostasis; folate cycle; purines inference made from gene expression patterns that methionine starvation tips the metabolic balance toward respiration. There are two broad classes of metabolites whose abundance changes in a consistent and correlated fashion: amino acid levels Fig. 4. MET31/MET32-dependent genes and oxidative stress response. increase throughout the time course, and the nucleotide tri- Genes whose expression depends most strongly on MET31 and MET32 as phosphates ATP, GTP, UTP, and CTP increase transiently. The determined by multiple regression (Materials and Methods). Functional en- increase in amino acid abundance may result from a combination richment is indicated as in Fig. 2 and further described in Table S3. of factors, including decreased amino acid consumption and degradation of and other . with iron homeostasis. The most striking examples are the purine SHM2 FCY2 ADE1 ADE2 ADE5,7 ADE13 Genes at the Intersection of Methionine Metabolism, Oxidative Stress biosynthetic genes , , , , , , and ADE17; the folate metabolic genes MTD1, GCV2,andGCV3; Response, and Mitochondrial Function Are Required for Maximal —FET3 FTR1 SIT1 TIS11— Survival Under Multiple Starvations. Methionine-specificgeneex- and several genes , , ,and that are induced pression depends largely on the activity of several transcription when mitochondrial iron-sulfur cluster biogenesis is disrupted (19). factors, Met4p, Met31p, Met32p, Met28p, and Cbf1p (18). We Gene Expression Patterns Correlated with Starvation Phenotype deleted these transcription factors individually and in pairwise fi combinations and found that the double mutant met31Δmet32Δ Across Multiple Nutrient Starvations. As a rst step toward identi- dies much faster than the met6Δ and met13Δ mutants during me- fying and characterizing the starvation signal proposed in previous A met4Δ work (2), we compared gene expression data for methionine, thionine starvation (Fig. 1 and Table S1). ( also dies much fi more quickly but was not further analyzed in this work.) The phosphate, sulfate, leucine, and uracil starvations to nd expres- portion of methionine-specific gene expression regulated by sion signatures that correlate with various starvation phenotypes. Met31p and Met32p is therefore required for survival during We analyzed the combined expression data for these nutrients methionine starvation. met31Δmet32Δ arrests in G0/G1 with with the hope of identifying groups of genes whose expression slightly lower efficiency than the other (metabolic) methionine patterns are correlated with survival, arrest, and glucose conser- fi fi auxotrophs (Fig. 1B), but it does conserve glucose (Fig. 1C). vation. To this end, we rst ltered out expression patterns that fi To test whether the MET31/MET32-dependent expression are common to all starvations and expression patterns speci cto i program is relevant to survival more generally, we measured the a single starvation. We then asked three related questions: ( ) “ ” survival of the met31Δmet32Δ double mutant during phosphate Which genes are expressed differently in the survivable (i.e., SYSTEMS BIOLOGY starvation, which differs more from methionine starvation than the glucose-conserving, cell cycle arresting, long-lived) starvations “ ” other starvations studied. Deleting MET31 and MET32 signifi- compared with the unsurvivable (i.e., glucose-wasting, shortest- cantly decreases survival during phosphate starvation (Fig. 1A, P= lived) starvations? (ii) Which genes are expressed differently in all − 1 × 10 4), but the decrease is significantly smaller than the decrease of the auxotrophs (including methionine) compared with the − observed under methionine starvation (P=3 × 10 7)(SI Materials longest-lived, natural nutrient starvations? (iii) Which expression and Methods). The Met31p/Met32p regulon is therefore required patterns best correlate with survival half-life? for full survival during methionine and phosphate starvation. To better understand how Met31p and Met32p contribute to Genes That Are Expressed Differently Between Survivable and survival, we measured gene expression during methionine star- Unsurvivable Starvations. To identify genes that are expressed vation of met31Δmet32Δ. These data were combined with that differently during the survivable starvations (methionine, phos- from met6Δ and met13Δ, and multiple regression was used to phate, sulfate) than during the unsurvivable starvations (leucine, identify genes whose expression is significantly different in uracil), we used two independent methods, multiple regression met31Δmet32Δ compared with met6Δ and met13Δ (SI Materials (Fig. 5A) and k-means clustering (SI Materials and Methods and and Methods). We then selected genes that rank higher than the Fig. S2B), which yielded similar results. Multiple regression was 95th or 90th percentile with respect to the F statistic P value (P ≤ used to extract a set of genes with a statistically significant de- − − 9.19 × 10 6 or 2.07 × 10 4; FDR ≤ 0.01), depend statistically pendence on the survivability of the starvation (SI Materials and significantly on time (FDR ≤ 0.01), and change twofold or more Methods). As before, we selected genes that rank higher than in at least one time course. The resulting genes are strongly the 95th or 90th percentile with respect to the F statistic P value −14 10−11 −14 −10 enriched for (i) -encoding genes and (ii) genes (P ≤ 1.6 × 10 or 9.03 × ;FDR≤ 5.7 × 10 or 1.6 × 10 ), that function at the intersection of methionine biosynthesis, depend statistically significantly on time (FDR ≤ 0.01), and regulation of cell division, and mitochondrial function, such as change twofold or more in at least one time course. Hierarchical purine biosynthesis, folate metabolism, serine and glycine me- clustering of these genes revealed two subclusters, one charac- tabolism, iron metabolism, inositol metabolism, and aspartate terized by stronger induction in the successful starvations, the metabolism (Table S3 and Dataset S1). other by stronger repression (Fig. 5A and Dataset S1). This gene set contains two particularly informative subsets (Fig. Overall, the functional enrichment of these clusters implies 4). The first, which depends on Met31p and Met32p for induction, that successful starvation is correlated with expression of genes is enriched for sulfur and methionine metabolism, oxidation- that support stress response and several functions executed reduction, siroheme biosynthesis, glutathione biosynthesis, and re- largely within the mitochondria, such as aerobic metabolism, sponse to oxidative stress (including key oxidative stress response oxidative stress response, and redox homeostasis (Fig. 5A and genes such as GSH1, ZWF1, GTO1, OPT1,andMXR1). The second Table S4). More specifically, genes expressed more highly in the subset, which is repressed by met31Δmet32Δ, is strongly enriched for successful starvations are enriched for heat stress, mitochondrial genes associated with purine, nucleotide, or glycine biosynthesis, or translation, and energy generation through respiration, including

Petti et al. PNAS | November 8, 2011 | vol. 108 | no. 45 | E1093 Downloaded by guest on October 1, 2021 A the (GO) categories “oxidation reduction” and “generation of precursor metabolites and energy.” (In GO, the M M M L PSU M M M L PSU “ ” (6) (13) (T) (6) (13) (T) descendents of the oxidation reduction term are involved in mitochondrial respiration and its constituent functions, such as electron transport and ATP synthesis. “Generation of precursor metabolites and energy” contains TCA cycle components and enzymes that transfer electrons from metabolites to the electron transport chain.) Specifically, this gene set contains several indicators of aerobic metabolism (e.g., HXK1, ENO1, PGK1, and GPM1), which we also identified using k-means. With respect to Genes with positive Genes with negative oxidative stress response, it contains key regulators of oxidative dependence on successful dependence on success- stress, including the superoxide dismutase SOD1, the thioredoxin starvation ful starvation TRX3, and the glutathione synthetase GTT1, as well as TDH1, Response to heat; oxidation- Assorted amino acid BNA2, RCK2, PST2 (a Yap1p target), OYE3, and the pentose reduction; mitochondrial biosynthesis; nucleotide TAL1 GND2 translation; glycine & serine transport; nucleocytoplas- phosphate pathway components and . metabolism; TCA cycle; mic transport; response to This gene set is also enriched for the mitochondrial folate glycolysis; gluconeogenesis; glucose stimulus; vitamin cycle [including glycine and serine metabolism (e.g., SER33)] membrane fraction; assorted biosynthetic process (Table S4) and for several documented starvation-response mitochondrial; large genes (SVF1, SSA4, GIS1, SIP2, and PNC1) that were also ribosomal subunit; identified using k-means. Although not statistically enriched as -3 0 3 AMP-activated protein kinase a GO class, we also identified in this cluster a number of phos- pholipid biosynthetic genes, including OPI1 (a PKA-activated B transcriptional repressor of phospholipid biosynthetic genes), OPI3 CHO1 CHO2 GPI6 SER33. M M M L PSU M M M L PSU , , , , and This gene set is enriched (6) (13) (T) (6) (13) (T) for genes whose products are localized to the mitochondrion, , and cell membrane.

Genes That Are Expressed Differently During Starvation for Natural Nutrients vs. Starvation for Auxotrophic Requirements. Presumably, the auxotrophic starvations—including methionine—share some physiological features that limit survival relative to the natural nutrient starvations. We used multiple regression to identify genes with a statistically significant dependence on nutrient class Higher expression in Higher expression in “ ” auxotrophic starvations natural nutrient starva- (either auxotrophic or natural ), selecting genes that rank P ≤ × −13 Assorted amino acid metabo- tions higher than the 95th or 90th percentile as above ( 1.2 10 −9 −13 −9 lism; autophagy; triglyceride & Glycolysis; glutamate or 1.5 × 10 ; FDR ≤ 5.4 × 10 or 3.3 × 10 ). Hierarchical glycerol catabolism; cardiolipin biosynthesis; Red genes: clustering of the significant genes yielded two main subclusters, metabolism; phosphatidylglyc- oxidation-reduction; TCA one containing genes that are more highly induced during erol metabolism; sulfur cycle enzyme complex, phosphate or sulfate starvation than in methionine, leucine, or metabolism; vitamin biosyn- cytoplasm, assorted uracil starvation, and a second with the opposite expression thesis mitochondrion, etc. pattern (Fig. 5B, Table S5, and Dataset S1). [Results obtained using k-means clustering (Fig. S2C) are discussed in SI Results.] C M M L PSU The first cluster, containing genes that are more highly (6) (13) expressed in the natural nutrient starvations, is enriched for oxidative stress response (e.g., BNA2, GTO3, GRX2, TRX2, OYE3, and HYR1). Using FunSpec (20) to identify enrichment M M M L PSU M M M L PSU (6) (13) (T) (6) (13) (T) for MIPS functional categories (21), we found enrichment for genes involved in glutamate biosynthesis and genes involved in generating input to the citric acid cycle and thence to the elec- tron transport chain (e.g., IDH1, IDH2, ACO1,andMEU1). [This cluster is also enriched for genes annotated to the GO Positive correlation Negative correlation glucose metabolism category (YOR283W, PGK1, HXK2, TDH3, Response to heat; oxidation Assorted amino acid ENO2 TDH1 reduction; electron metabolism; tRNA , and ); because most of those genes function in both transport chain; TCA cycle; aminoacylation; pyrimidine glycolysis and gluconeogenesis, the meaning of this enrichment glucose catabolism; redox transport; folic acid is ambiguous.] homeostasis; response to biosynthesis; cytosolic oxidative stress; ; mitochondrion membrane; cytoplasm; assorted mitochondrial Functional enrichment is further described in Table S4.(B) Expression profiles dependent on nutrient class. Genes that are expressed differently in the Fig. 5. Genes that differ by starvation phenotype or nutrient class, as iden- natural nutrient starvations (Pho and Sul) than in the auxtrophic starvations tified using multiple regression. Each panel shows genes ranking above the (Met, Leu, and Ura). Genes with particularly strong induction in Pho and Sul 90th percentile with respect to statistical significance for the given compari- (red boxes) are strongly enriched for functions related to aerobic metabolism. son. Functional enrichment and color coding are as specified in Fig. 2. These Functional enrichment is further described in Table S5.(C) Expression profiles are independent analyses that address related questions (see text) and give correlated with survival time. The gene expression template used for the consistent results; thus, the resulting gene sets (and their functional enrich- Pavlidis template matching (SI Materials and Methods) is shown above genes ments) necessarily overlap. (A) Expression profiles shared by successful star- whose expression profiles match the template mean with a Pearson correla- vations. Genes that are expressed differently in the survivable starvations tion coefficient of at least 0.7 (“Positive correlation,” Left)or−0.7 (“Negative (Met, Pho, and Sul) than in the unsurvivable starvations (Leu and Ura). correlation,” Right). Functional enrichment is further described in Table S6.

E1094 | www.pnas.org/cgi/doi/10.1073/pnas.1101494108 Petti et al. Downloaded by guest on October 1, 2021 PNAS PLUS The second cluster, characterized by greater induction during A Pho (FY4) Leu (leu2 ) the auxotrophic starvations, is strongly enriched for amino acid biosynthesis (as expected), autophagy, metabolism of glycer- 100 olipids, cardiolipin, phosphatidylglycerol, and related compounds. This cluster is also enriched for the MIPS categories related to morphogenesis and cell wall integrity (e.g., MKK2, SLT2, RLM1, 1 SOG2,andSOG2) and contains PPM1, whose deletion dramati-

cally increases the survival during leucine starvation (1, 22, 23). % viability ρ0 strains Gene Expression Program Correlated with Survival Time over All ρ+ strains Types of Starvations. The preceding analyses began with classi- 0.001 fications based on either (i) the observation that met6Δ and 0 7140 714 met13Δ auxotrophs survive longer during starvation than leu2Δ or days days ura3Δ auxotrophs, or (ii) the fact that methionine-requiring mutants are auxotrophs. To avoid potential bias introduced by Met (met6 ) Met (met31 met32 ) fi prior classi cation, we used Pavlidis template matching (24) to 100 identify genes that are highly correlated with survival time per se (91 genes with correlation at least ±0.7; Fig. 5C, Table S6,and Dataset S1). These genes are significantly enriched for the same heat and oxidative stress, redox, citric acid cycle, and respiration- 1 related processes previously identified, with many genes having

annotations in several of these categories. % viability

Overlap Between Met31p/Met32p-Dependent Gene Expression and 0.001 Survival-Correlated Gene Expression. Deletion of MET31 and 0 7140 714 MET32 significantly decreases survival during methionine days days and phosphate starvation. To determine whether Met31p and Met32p promote survival by the same means as the survival- 45 correlated gene expression signature discussed above, we ex- B amined the intersection between Met31p/Met32p-dependent 40 replicate 1 genes and survival-correlated genes. Nine genes are shared be- 35 replicate 2 tween these gene sets. They are involved in methylmethionine import and metabolism (MMP1 and MHT1), methionine im- 30 port (MUP1), glutathione transport (OPT1), purine bio- 25 synthesis (SHM2 and ADE5,7), the folate cycle (MTD1 and 20 GCV2), and glycine/serine metabolism (SER33). From this we SYSTEMS BIOLOGY

conclude that, through Met31p and Met32p, these methionine- % viability 15 regulated processes must be properly regulated during starva- 10 tion for a variety of nutrients, not just methionine. 5 Cells Undergoing Survivable Starvations Consume More Oxygen, but 0 Met an Intact Electron Chain Is Not Required for Survival. The analysis of Pho Met Leu (met31 gene expression patterns directly correlated with survival impli- (FY4) (met6 ) (leu2 ) cates processes associated with mitochondria and processes met32 ) associated with oxidative stress response. We carried out two Fig. 6. (A) Survival of ρ0 derivatives during starvation for phosphate, me- experiments to better characterize the involvement of these thionine, and leucine. Survival of ρ0 derivatives of FY4, met6Δ, leu2Δ,and processes. In one, we studied oxygen consumption during star- met31Δmet32Δ (black lines) was measured as the ability to form colonies on vation, and in the other, we studied survival in strains lacking rich medium plates (Materials and Methods). Survival of the ρ+ parent strains mitochondrial DNA (and therefore lacking an electron transport is shown for comparison (gray lines). (B) Viability after hydrogen peroxide chain). Fig. S4 shows that there are indeed differences in oxygen treatment. For duplicate cultures limited for phosphate (FY4), methionine consumption for different starvation regimes and that the cul- (met6Δ or met31Δmet32Δ), or leucine (leu2Δ), colony-forming units on rich tures with poorer survival consume less oxygen. By the second medium plates after treatment with 20 mM hydrogen peroxide, a source of day of starvation, methionine-starved (met6Δ) cells consume oxidative stress, is reported as a percentage of colony-forming units after slightly more oxygen than leucine-starved or methionine- treatment with water. Black and gray bars indicate biological replicates. starved (met31Δmet32Δ) cells, but the difference is not statis- fi tically signi cant. Strikingly, cells starved for phosphate (FY4 drial DNA) results in only marginal impairment of survival of the met6Δ P= × −7 or ) consume by far the most oxygen ( 4.3 10 ), methionine regulatory mutant and the leucine mutant. Because paralleling their extraordinarily prolonged survival. the presence of an electron transport chain had no consistent These results led us to test whether respiration is required for starvation survival. We used ethidium bromide to create effect on survival, we conclude that survival does not depend on ρ0 (cytoplasmic petite) derivatives of the strains tested above respiration per se (although respiration may contribute to sur- (Materials and Methods) and measured starvation survival as de- vival in certain cases). Of course, this experiment does not rule scribed above (Fig. 6A). The ρ0 derivatives survive nearly per- out the possibility that the efficiency of respiration in yeast with fectly in phosphate starvation, almost as well in methionine an intact electron transport chain also influences survival. starvation of the metabolic methionine auxotroph, and very poorly in leucine starvation and methionine starvation of the Survival Is Correlated with Ability to Detoxify ROS. If survival is not regulatory methionine auxotroph. Loss of the electron transport affected by the respiration genes we identified in the expression chain (and all of the other functions encoded in the mitochon- analysis, it may be affected by the other respiration-associated

Petti et al. PNAS | November 8, 2011 | vol. 108 | no. 45 | E1095 Downloaded by guest on October 1, 2021 genes we identified. In our data, oxidative stress response is one enriched for localization in the mitochondrion than any other of the most prominent respiration-associated functions. More- cellular component. over, the data in Fig. 4 suggest that impairing the oxidative stress Determining more precisely whether, how, and why mitochon- response, such as by deleting MET31 and MET32, impairs sur- dria influence starvation survival is a complex task. The various vival in multiple nutrient starvations. To test the idea that star- processes that occur in the mitochondrion might influence star- vation survival correlates more generally with the ability to vation survival in different, even opposing, ways. For instance, survive oxidative stress, we measured the survival of hydrogen electron transport generates ROS that might shorten survival, but peroxide-treated cultures limited for methionine (met6Δ and compensatory stress response mechanisms might ultimately met31Δmet32Δ), leucine (leu2Δ), or phosphate (FY4)(Materials lengthen survival. Indeed, the literature is rife with conflicting and Methods). Fig. 6B shows that starvation survival is indeed reports on the role of mitochondrial function in chronological highly correlated (Pearson correlation, 0.997) with the robust- aging (e.g., refs. 14 and 27). Our results concerning survival of ness of the oxidative stress response. mutants lacking mitochondrial DNA show that respiration per se is not the major determinant of survival. Discussion If survival does not depend on respiration, then it may depend Previous work suggested the existence of a starvation signal-and- on the stress response pathways that seem to be coupled to re- response network that is differently activated in different nutri- spiratory growth. This dependency is supported by our results tional environments, thereby leading to different phenotypes (2). with the short-lived met31Δmet32Δ mutant, which cannot mount Under this interpretation, the signal-and-response network is a response to oxidative stress, and our results showing that ability triggered during starvation for naturally required nutrients (e.g., to detoxify hydrogen peroxide is correlated with starvation sur- sulfate, phosphate, nitrogen, and carbon), resulting in cell cycle vival across a variety of starvations. Previous work suggested that arrest, glucose conservation, and survival, but is not triggered glucose signaling during leucine and uracil starvation activates during starvation for auxotrophic requirements. We sought to the Tor pathway, leading to an inappropriate progrowth signal better characterize the function of this signal by studying starva- that results in cell death (1). Our data suggest that the survival- tion for diverse nutrients. We have shown that cells undergoing correlated stress response pathways are the same ones that are survivable starvations (i.e., those in which cells survive for many repressed by the Tor pathway [many of which are regulated by days or weeks) induce expression of genes involved in mitochon- MSN2/MSN4 (23)]. Thus, survivable starvation conditions may drial function and/or stress response. They also survive externally repress the Tor pathway, thereby derepressing the Tor-regulated applied oxidative stress far better than those undergoing unsur- stress response pathways. vivable starvations. In addition, we have shown that cells un- Other recent systems-level gene expression analyses have also dergoing survivable starvations consume more oxygen than cells found connections between mitochondrial functions and stress undergoing unsurvivable starvations, but that respiration per se is response pathways. It may be that over evolutionary time, induc- not required for prolonged starvation survival. We conclude that tion of oxidative metabolism became associated with induction the differences between the survivable and unsurvivable starva- of protective mechanisms (e.g., thioredoxins, glutathione, super- tions represent differential activation of the signal-and-response oxide dismutases, etc.) that provide recourse against respiration- network, and that this network controls functions that support generated ROS. Consequently, inducing oxidative metabolism stress response and nonrespiratory mitochondrial functions. may increase the abundance of antioxidants, whose protective fi Role of Mitochondrial Function and Stress Response in Starvation effects may bene t the entire cell. This interpretation suggests that Survival. According to our gene expression analyses, “successful” oxidative metabolism indirectly exerts a protective effect on the response to starvation is associated with induction of genes that cell, in direct contrast with the standard view that increased oxi- can be broadly characterized as supporting stress response and/or dative metabolism is necessarily associated with increased abun- mitochondrial function. When we identified genes whose ex- dance of damaging ROS. pression is correlated with survival time during starvation, we found that many of them are involved in three basic cellular Methionine Regulates Cellular Redox Homeostasis and Oxidative functions: (i) electron transport, aerobic respiration, and general Stress Response, Which Contributes to Longevity During Methionine mitochondrial activity (such as mitochondrial translation), (ii) Starvation. Our results beg the question of why starvation for met6Δ met13Δ acetyl-CoA and storage carbohydrate metabolism, and (iii) re- methionine (in or mutants) is more like starvation sponse to heat and oxidative stress. Some of the genes involved in for a natural nutrient. Our interpretation, based on the similarity the latter are mitochondrial and help maintain mitochondrial of gene expression during methionine starvation and sulfur “ ” integrity and respiratory efficiency—for example, through syn- starvation, is that methionine is the indicator metabolite for thesis of antioxidants such as superoxide dismutase, thioredoxin, sulfate availability. Our data show that regulation of methionine peroxiredoxin, glutaredoxin, and glutathione, which neutralize metabolism, iron and sulfur metabolism, oxidative metabolism, ROS generated by electron transport (25). Additionally, aerobic- antioxidant biosynthesis, and one-carbon metabolism is highly specific isozymes are preferentially induced relative to their interdependent. Thus, methionine auxotrophs ultimately up- fermentation-specific counterparts, particularly in methionine regulate some or all of the protective functions normally asso- starvation. The fact that many genes typically associated with the ciated with increased oxidative metabolism. It is therefore not canonical MSN2/MSN4-mediated stress response cocluster with surprising that deleting MET31 and MET32, which curtails sur- genes involved in aerobic metabolism suggests that stress re- vival during methionine starvation, phosphate starvation, and sponse and aerobic metabolism are transcriptionally coordinated. hydrogen peroxide exposure, severely affects the expression of Physiological measurements suggest that the relationship be- oxidative stress response genes. tween survival and mitochondrial function may well be causative We conclude that proper regulation of these interdependent rather than merely correlative: we and others have shown that processes, particularly induction of the oxidative stress response forcing the cell to respire during starvation (for example, by genes, contributes to longevity in multiple starvations. This sup- providing only a nonfermentable carbon source), increases sur- ports previous evidence for the role of oxidative stress in aging (28– vival time. The case for causality is supported by a recent study 32) and contributes to a growing body of evidence suggesting that that measured survival of the prototrophic yeast deletion collec- methionine abundance regulates the pathways that protect the cell tion during phosphate and leucine starvation (26): genes whose from the ravages of oxidative metabolism. In higher organisms, deletion decreased survival in both starvations were more highly methionine restriction has been found to increase longevity and

E1096 | www.pnas.org/cgi/doi/10.1073/pnas.1101494108 Petti et al. Downloaded by guest on October 1, 2021 reduce oxidative damage to proteins and mitochondrial DNA and methionine or 240 mg/L leucine. ρ0 mutants were generated using ethidium PNAS PLUS to decrease ROS generated in the mitochondria (32). bromide as described in ref. 41.

Nutrient Starvation in Yeast as a Model for the Warburg Effect in Hydrogen Peroxide Survival Assays. A single colony was inoculated into Cancer Cells. A major metabolic hallmark of cancer is rapid glu- nutrient-limited medium and grown for 24 h with shaking at 30 °C. The cose consumption even in the presence of oxygen, known as the culture was diluted into fresh nutrient-limited medium and grown with shaking at 30 °C until midexponential phase (the length of time required is Warburg effect. Although the uncontrolled glucose consumption strain-specific). An aliquot containing 1 × 108 cells was resuspended in 10 mL fi of yeast starving for leucine or uracil is super cially analogous, of fresh nutrient-limited medium, treated with 0 mM or 20 mM hydrogen there was no previous evidence that the two phenomena have peroxide for 20 min, washed twice with water, and plated for viable cells. a common cause. The Warburg effect was long thought ancillary Viability in 20 mM hydrogen peroxide is reported as a percentage of the to more fundamental molecular changes in cancer, but recent viable cells counted after treatment in 0 mM hydrogen peroxide. work suggests that it results directly from oncogene activation. Mounting evidence suggests that oncogene activation may cause Residual Glucose Measurements. A single colony was inoculated into nutrient- mitochondrial dysfunction, which increases the cell’s dependence limited medium (7.5 mg/L methionine or 40 mg/L leucine) and grown for 24 h with shaking at 30 °C. Each culture was diluted into fresh nutrient-limited on glycolysis (33) and the abundance of ROS (25, 34). medium to a density between 1 × 105 and 4 × 105 cells/mL and grown with Our gene expression data suggest that glucose wasting in yeast shaking at 30 °C. Starting 12–15 h after dilution, turbidity was measured, may also be caused by failure to induce a variety of mitochon- and 1-mL samples were frozen periodically over the course of 3 d. The drial functions. In our data, a major difference between glucose- glucose concentration in each thawed sample was measured in triplicate conserving and glucose-wasting starvations is greater induction using the Boehringer-Mannheim D-glucose UV test. of the mitochondrial genes in the glucose-conserving starvations. This suggests that glucose wasting during certain yeast starva- Methionine-Starvation Filter-Switching Time Courses for met6Δ, met13Δ, tions may be a useful model for the Warburg effect. and met31Δmet32Δ. A single colony of each strain was inoculated into methionine-limited minimal medium and grown with shaking at 30 °C. After × 5 × 6 Nutrient Starvation in Yeast as a Model for Aging. A variety of 24 h, each culture was diluted to low density (1 10 to 1 10 cells/mL) in 250–300 mL of fresh methionine-limited minimal medium and grown with studies on chronological and replicative aging show that a met- 6 shaking for 12–15 h to a density of 20–25 Klett units (approximately 5 × 10 abolic regime favoring respiration instead of glycolysis increases cells/mL). As described in ref. 42, the culture was then filtered in 5-mL ali- yeast lifespan (1, 14, 35–38), but there is conflicting evidence for quots onto 0.45-μm, 82-mm-diameter Nylon filters. Each filter was placed on the role of respiration itself (27, 39, 40). Our results suggest that a Petri dish containing YNB5 (minimal medium made with agarose) and the situation is more nuanced: survival during starvation, often 7.5 mg/L methionine. The plates were incubated at 30 °C for 4 h, until the called “longevity,” is correlated with the induction of a non- culture reached a density of 80–90 Klett units (approximately 2 × 107 cells/ respiratory subset of mitochondrial functions, particularly the mL). At this time, each filter was transferred to a fresh plate containing fi pathways that alleviate heat and oxidative stress. Protective YNB5 but no methionine. At speci ed time points thereafter (0 min, 10 min, 30 min, 1 h, 1.5 h, 2 h, 2.5 h, 3 h, 3.5 h, 4 h, and 6 h), filters from two plates mechanisms may be coinduced with oxidative metabolism, such were placed in 50-mL screw-capped tubes and immediately immersed in that metabolic perturbations that favor respiration over fer- liquid nitrogen. A third filter was washed and used for Klett readings, mentation may indeed increase longevity. We believe that the Coulter counts, and bud index measurements. essential connections between longevity, metabolism, and stress SYSTEMS BIOLOGY response may well be conserved in whole or in part between Metabolite Measurements in met13Δ. During the filter-switching time course yeast and higher organisms, and that data from yeast may well for met13Δ described above, samples were simultaneously collected for me- lead to a better understanding of the interplay between metab- tabolite extraction. Metabolites were extracted using methanol quenching, olism, stress response, cell growth control, and longevity. and their abundance was measured using LC-MS/MS as described in ref. 43. Materials and Methods Oxygen Consumption Measurements. A single colony was inoculated into 5 mL of nutrient-limited medium (7.5 mg/L methionine, 40 mg/L leucine, or 13.3 Media compositions are listed in Table S7. Strain descriptions are listed in mg/L postassium phosphate) and grown overnight with shaking at 30 °C. The Table S8. culture was diluted to a density between 1 × 105 and 4 × 105 cells/mL in 300 mL of fresh nutrient-limited medium and grown overnight with shaking at Establishing the Range of Linear Dependence on Methionine Concentration. 30 °C. At Klett 20 (≈5 × 106 cells/mL), 250 mL of the culture was transferred The range of linear dependence was determined as in ref. 3, using 0, 5, 10, 20, to a chemostat vessel equipped with two dissolved-oxygen probes and μ μ 40 or 200 mg/L [i.e., 0, 33.5, 67, 134, 268.1, or 1340.4 M(moles/L)] me- grown to stationary phase in batch mode (400 rpm, 30 °C) with an airflow μ thionine. A methionine concentration of 7.5 mg/L (i.e., 50.3 M) lies in the rate of 40. The oxygen probes were calibrated in water at 25 °C, so that full center of the linear range. probe saturation corresponded to a known dissolved oxygen concentration

(0.27 mMol O2/L). Three days after inoculation of the chemostat vessel, Methionine Dependence and Growth on Different Carbon Sources. A single cellular oxygen consumption was measured by periodically turning off the colony of each strain was grown to steady state in rich medium and spotted in chemostat air supply for 20 min and recording the change in dissolved ox- threefold serial dilutions on YNB agar plates containing 20 g/L glucose or ygen per unit time during the first 10 min. 12.6 g/L glycerol and 8.1 g/L ethanol as the carbon source, with or without 20 mg/L methionine. Methionine-Depletion Batch-Growth Time Course for met13Δ. A single colony was inoculated into 100 mL methionine-limited minimal medium and grown Cell Cycle Arrest. A single colony of each strain was grown for 24 h in 5–7mL with shaking at 30 °C for 32 h. The culture was then diluted to 5 × 105 cells/ of methionine-limited (7.5 mg/L) minimal medium, then diluted to a density mL in 500 mL of fresh methionine-limited minimal medium and grown in 5 5 around 1 × 10 to 5 × 10 cells/mL in fresh methionine-limited medium. batch with shaking. Beginning 5 h after dilution and every hour thereafter Beginning at the end of lag phase (12–15 h after dilution), turbidity (Klett until the culture reached steady state with respect to density and bud index, units), cell density (Coulter Count), and bud index were measured periodi- samples were removed for bud index, culture density, and cell count cally. Bud index, the fraction of unbudded cells in a stationary phase culture measurements, and cell samples for RNA extraction were obtained by fil- (Table S1 lists strain-specific stationary phase Klett values), was measured by tering and freezing in liquid nitrogen. manual scoring of a sonicated culture under a microscope. Preparation of Cells for Microarray Reference Samples. In a chemostat, FY4 Starvation Survival Assays. Survival assays on various carbon sources were was grown to steady state in chemostat medium containing limiting phos- − performed as described in ref. 1. Here, nutrient-limited medium contained phate (10 mg/L) at a dilution rate of 0.17 h 1. Cells were harvested by filtering 7.5 mg/L methionine, 40 mg/L leucine, or 13.3 mg/L phosphate plus 200 mg/L onto a nitrocellulose filter and frozen in liquid nitrogen.

Petti et al. PNAS | November 8, 2011 | vol. 108 | no. 45 | E1097 Downloaded by guest on October 1, 2021 RNA Isolation, Labeling, and Hybridization. RNA was collected from the Expression and Metabolite Data Analysis. Expression and metabolite data frozen filters using phenol-chloroform extraction, purified using an the analysis are described in SI Materials and Methods. Qiagen RNeasy kit, labeled with Cy5 CTP (samples) or Cy3 CTP (phosphate- limited chemostat reference) using the Agilent Low-input Linear Ampli- ACKNOWLEDGMENTS. We thank Sanford Silverman and Viktor Boer for ficationkit,andhybridizedto2× 105k, 4 × 44k, or 8 × 15k Agilent Yeast helpful discussions of this work and Olivia Ho-Shing for technical assistance with oxygen consumption measurements. A.A.P. was supported by Ruth Oligo V2 microarrays. Arrays were washed and scanned using extended Kirschstein Cancer Training Grant T32 CA-009528. Research was supported dynamic range according to Agilent protocols. Agilent Feature Extraction by National Institute of General Medical Sciences Center for Quantitative Software was used with default settings and linear and lowess dye Biology Grant P50 GM-071508 and National Institutes of Health Grant GM- bias correction. 046406 (to D.B.).

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