Summary

Introduction: Saccharomyces cerevisiae is an excellent model organism for studies of transcriptional regu­lation of metabolic processes in other eukaryotic cells including human cells. Cellular acid­-base balance can be disturbed in pathologic situations such as renal acidosis or cancer. The extracellular pH of malignant solid tumors is acidic in the range of 6.5-6.9. EG07 and EG37 aci mutants of Saccharomyces cerevisiae excessively excrete carboxylic acids to glucose-containing media or distilled water. The excreted acids are Krebs and/or glyoxylate cycle intermediates. The genes restoring the wild-type phenotype have function that does not easily explain the Aci⁺ phenotype.
Material/Methods: In this study, using real-time PCR we measured relative mRNA expression, in the mutants compared to the wild-type strain, of selected genes associated with both carboxylic acid cycles and two cell transporters, Pma1 and Pdr12, of organic acids.
Results: Unexpectedly, we found that the relative expression of the selected Krebs cycle and glyoxylate cycle genes did not change significantly. However, the expression of the two transporter genes was strongly elevated in EG37 and moderately increased in EG07.
Conclusion: These results indicate that the induction of the two cell transporter genes plays an important role in acid excretion by the aci mutants.

Key words:Saccharomyces cerevisiae • aci mutants • Krebs and glyoxylate cycle • acid transporters

Abbreviations:

Aci⁺ – mutant phenotype excreting acids; aci – mutated gene; Cit1, Cit2 and Cit3 – citrate syntha­se isozymes; ICL1 – isocitrate lyase isozyme; MDH1, MDH2 and MDH3 – malate dehydrogenase isozymes; PDR12 – plasma membrane ABC transporter; PMA1 – plasma membrane H+-ATPase; R – relative expression ratio: mutant/wild type; WAR1 – transcription factor of PDR12.

Introduction

The yeast Saccharomyces cerevisiae is an excellent mo­del organism for studies of transcriptional regulation of metabolic processes, such as Krebs cycle, glyoxylate cycle or cellular transport of organic acids in eukaryotic cells [10,12,13,17,21]. For example, such model studies may be very helpful in finding molecular mechanisms that explain metabolic acidosis in renal cells [18] or how solid tumors generate acid and export it into the surrounding parenchyma [24]. The entire genome of S. cerevisiae was sequenced in 1996 [7]. However, despite a broad know­ledge of many metabolic reactions in this organism, the transcriptional regulation of the metabolic pathways, including the ones named above, is complex and rema­ins unclear [6]. Metabolic mutants like those defective in Krebs cycle genes [1,23] have been very useful in this kind of research. Gonchar et al. [8] using a mutagenic re­agent ethyl methanesulfonate (EMS) generated a group of S. cerevisiae aci mutants that on complete Kok me­dium [11] containing glucose excrete acids. The excreted acids were later identified as intermediates of the Krebs cycle or the glyoxylate cycle [2,16]. Quick release of acid was also observed when the mutants were suspended in water [16]. The aci mutants were found to be the result of single gene mutations and distributed among 16 com­plementation groups [9]. Transformation of the mutants with a genomic DNA library on the multicopy shuttle plasmid pFL44L [3] restored the wild-type AciŻ [2]. Also, in our preliminary studies (unpublished results) a sin­gle-copy plasmid containing the YLR376C gene had this ability. Overall, three genes, YJL185C, YLR376C and YJR129C, restoring the AciŻ phenotype were identified. YJL185C en­codes Pex3p interacting protein required for pexophagy (www.yeastgenome.org). YLR376C encodes a component of the Shu complex, which promotes error-free DNA re­pair (www.yeastgenome.org). YJR129C encodes a putati­ve adenosylmethionine-dependent methyltransferase (www.yeastgenome.org) [2]. However, the functions of these proteins do not easily explain the Aci+ phenotype. Presumably, the discovered genes play unknown regula­tory roles that indirectly influence the function of the Krebs and/or glyoxylate cycle. In such a case the exces­sive accumulation of the organic acids in the cytoplasm induces an acid stress response that leads to the removal of the acids from the cell. Another possibility is that the mutated genes regulate the expression or activity of an organic anion transporter such as Pdr12 cooperating with a proton pump such as Pma1 [21].

Our ultimate goal is the identification of the mutated genes, and genetic cascades with corollary metabolic pathways triggered by the mutations. However, before the attainment of this goal we decided to broaden bio­chemical characterization of the aci mutants. In this study, using a real-time PCR technique, we compared mRNA expression of several important metabolic ge­nes in two selected aci mutants to that in the wild-type strain D273-10B/A1 of S. cerevisiae. The two selected aci mutants, EG07 and EG37, display the strongest aci cha­racter but differ in their growth ability on non-fermen­table carbon sources [16]. The chosen metabolic genes encode enzymes of the Krebs and glyoxylate cycles, ABC anion transporter Pdr12 [21], proton pump Pma1 [25], and the transcription factor War1 that induces Pdr12 activity [12].

Materials and methods

Yeast strains

Saccharomyces cerevisiae strains, wild type and mutants, used in this work are listed in Table 1.

Table 1. Saccharomyces cerevisiae strains

Growth conditions

The yeast cells were maintained on YPD (yeast extract 1%, bacto-peptone 1%, dextrose 2%) agar slopes at 4°C, and cultivated 24 hours at 28°C in liquid YPD medium with shaking.

PolyA+ mRNA isolation

Total RNA was extracted from yeast cells using a Total RNA kit (A&A Biotechnology, Gdansk, Poland) according to the manufacturer’s protocol. PolyA+ mRNA purification was performed using FastTrack^® MAG mRNA Isolation Kits (Invitrogen, Carlsbad, CA, USA). Reverse transcription was performed using SuperScriptTM III Platinum^® RT­-PCR System (Invitrogen) in a total volume of 20 µl, then obtained cDNA was used to analyze gene expression by real-time PCR.

Real-time PCR assay

The PCR primers (Table 2) were custom synthesized by the DNA Sequencing and Oligonucleotide Synthesis La­boratory at the Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland (www.oli­go.pl). The synthetic oligonucleotides were purified by HPLC. The gene specificity of the primers was checked by searching the Saccharomyces Genome Database at www. yeastgenome.org with the Wu-BLAST2 program available on the same Internet site.

Table 2. Real-time PCR primers

Real-time PCR was performed using an ABI Prism 7900HT Sequence Detection System (Applied Biosystems, Foster City, CA, USA) in the presence of SYBR Green. Individual real-time PCR reactions were carried out in a 96-well pla­te containing 10 µl of 2x SYBR Green Master Mix, 10 µl of 0.25 µM primers (Table 2) and 5 µl of cDNA template. All reactions were performed using SYBR Green Two-Step qPCR-PCR Kit with ROX (Invitrogen). We used the PDA1 gene as a primary endogenous control to standardize the amount of cDNA added to the reactions. The PCR reac­tions of target genes were run in triplicate or occasional­ly in duplicate. The duplicates were accepted only if the obtained Ct values were very similar (with a deviation less than 0.40 from the average, and only one duplicate had a Ct deviation of 0.72). The endogenous controls had 4 or 5 data points. The PCR amplification protocol was as follows: incubation of reaction mixture at 50°C for 2 mi­nutes, the initial denaturation step at 95°C for 2 minutes, then 40 cycles of heating and cooling at 95°C for 15 se­conds and 60°C for 1 minute, respectively. After the runs, melting curves were analyzed to check if dimer primers or unspecific products were formed.

The ΔDCt [15,28] and Pfaffl methods [20,28] were used to calculate relative amounts (R or LogR values) of mutan­t’s mRNA vs. wild strain’s mRNA normalized to the en­dogenous reference (PDA1). Here the ΔDCt values were calculated from: ΔDCt = ΔCtwild – ΔCtmutant, where ΔCt = Ctsample – CtPDA1. Both methods basically gave the same results except for ICL1, which displayed about 20% lower amplification efficiency than the other genes. To estimate experimental variability of the results, propaga­ted standard deviations (SD) were calculated for the ΔDCt values, then the range of the relative expression ratios (Rmin to Rmax) was calculated using the E-ΔDCt-SD and E-ΔDCt+SD formulas [29] adjusted for the amplification efficiency if needed [15,29]. The Ct, ΔCt and ΔDCt values were normalized for a constant efficiency (E) of 1.83 that was obtained for PDA1. The measured efficiencies were in the range of 1.82-1.94, except for the ICL1 efficiency of 1.65. In addition, the standard statistical t-test was used for comparison of the means of the mutant’s and wild strain’s ΔCt values.

Results

Endogenous reference genes

To normalize the mRNA levels in different samples of the yeast strains we chose PDA1 as a reference gene. PDA1 is recommended here rather than ACT1 because it has been shown that in the case of S. cerevisiae, mRNA of PDA1 is expressed at a constant level over a longer period than that of ACT1, whose expression substantially drops when cultures of S. cerevisiae reach the stationary phase [27]. Anyway, we included ACT1 because this reference gene is frequently reported in the literature. The expression level of ACT1 vs. PDA1 in our mutants was somewhat hi­gher than that in the wild strain, probably due to faster growth of the latter (data not shown).

Expression of selected structural genes associated with Krebs and glyoxylate cycles

Since the aci mutants excrete acids that are intermedia­tes of the Krebs and glyoxylate cycles [16] we first exa­mined several genes, CIT1, CIT2, CIT3, MDH1, MDH2, MDH3 and ICL, of enzymes involved in these two cycles. The Cit and Mdh isozymes are the first and last enzymes in the two cycles, respectively, and changes in their expression levels could result in accumulation of the acidic inter­mediates. These enzymes are often induced due to muta­tion of other related metabolic genes [4,14] or changes of cell environmental conditions [14,19]. Cit1, Cit3 and Mdh1 are the mitochondrial isozymes involved in the Krebs cycle. Cit2, Mdh2, and Icl1 are involved in the glyoxylate cycle, and Mdh3 is the peroxisomal isozyme. Somewhat surprisingly, the expression levels of these genes in the mutants, except for CIT3 in EG37 (3.7-fold increase), were not significantly different from those in the wild strain (Figures 1 and 2).

Figure 1. Relative expression of Krebs cycle genes; R, mRNA expression ratio relative to WT strain; WT, wild-type; EG07 and EG37, mutants; CIT1 and CIT3, genes coding citrate synthase isozymes 1 and 3; MDH1, gene coding malate dehydrogenase isozyme 1; Error bars represent propagated SD (see Materials and Methods); two asterisks denote t-test significance level at p<0.05 (see Materials and Methods).

Figure 2. Relative expression of glyoxylate cycle genes; CIT2, gene coding citrate synthase isozyme 2; MDH2 and MDH3, genes coding malate dehydrogenase isozymes 2 and 3; ICL1, gene coding isocitrate lyase isozyme 1; other symbols are the same as described in Fig. 1.

Expression of transporter genes, PDR12 and PMA1

PDR12 and PMA1 were included in the study because Piper et al. [21] reported that S. cerevisiae cultures incubated at pH 4.5 displayed 10-fold elevated PDR12 expression, when compared with pH 7.0 cultures. In the proposed mecha­nism of anion extrusion by the Pdr12 transporter, the ac­tivity of Pdr12 is postulated to be coupled to that of the Pma1 proton pump [21]. Since our mutants overproduce carboxylic acids, it was probable that the expression level of the two major acid transporters would increase relative to the wild strain. Indeed, this supposition has been con­firmed in our experiments. The relative expression values (R) were 2.4 and 24 (0.38 and 1.38 on log scale) for PDR12 in EG07 and EG37, respectively. The corresponding R va­lues for PMA1 were 7.5 and 53 (0.88 and 1.72 on log scale), respectively (Figure 3). We also measured the expression level of WAR1 (Figure 3) encoding a transcription factor that mediates PDR12 induction [12]. The expression levels of WAR1 in the mutants were not significantly different from those in the wild strain (R values were 0.46 and 1.1 for EG07 and EG37, respectively).

Figure 3. Relative expression of cell transporter genes PMA1, PDR12 and transcription factor gene WAR1; PMA1, gene coding Pma1 proton pump; PDR12, gene coding Pdr12 anion transporter; one and three asterisks denote t-test significance level at p<0.1 and p<0.01, respectively (see Materials and Methods); other symbols are the same as described in the previous figures.

Discussion

In our previous studies we isolated and biochemically cha­racterized 16 S. cerevisiae mutants that excessively excre­ted acidic intermediates of the Krebs and/or glyoxylate cycle. Genetic analysis indicated single mutation of dif­ferent genes [9,16]. Since the acid excretion occurs in the presence of glucose, one could assume that the glyoxylate cycle is turned off. However, this is not necessarily true for the mutants; therefore we decided to include this cycle in our studies. Our primary supposition was that the excre­tion of the organic acids was caused by a blockage of one of the cycles resulting in the accumulation of the acidic intermediates. However, there is no simple explanation for these findings because the genes restoring the wild­-type phenotype Aci^– do not encode the enzymes of the two cycles and have functions not directly related to the acid excretion (www.yeastgenome.org) [2].

In this work we decided to investigate the mRNA expression of selected genes associated with both cycles in two mu­tants displaying the strongest Aci+ phenotype. In addition, since the excretion of the acids involves membrane trans­porters, two of them, Pdr12 and Pma1, extensively described in the literature, were included in the present studies. The two chosen aci mutants, EG07 and EG37, belong to diffe­rent complementation groups [16] and therefore are assu­med to have different mutated genes. Aside from the strong Aci+ phenotype, EG07 and EG37 are also interesting because they require very different growth conditions. EG37 easi­ly utilizes non-fermentable substrates (except for ethanol) such as acetate but EG07 does not [16]. So, we expected to detect differences in regulation of both the cycles not only between each mutant and the wild strain but also betwe­en the mutants themselves (EG07 and EG37). The selected CIT1, CIT2, CIT3, MDH1, MDH2, MDH3 and ICL genes encode important Krebs and glyoxylate cycle enzymes whose level can be expected to influence the kinetics of the two cycles. Since malate together with other carboxylic acid interme­diates (citrate, succinate, and fumarate) accumulated to high concentrations in the medium [16] we first focused our at­tention on MDH and CIT. Mdh is the last enzyme in the two cycles and it catalyzes the energetically unfavorable reac­tion. The product oxalacetate has to be removed efficiently and therefore Mdh acts in a complex with Cit preventing excessive accumulation of oxalacetate [5,26]. Moreover, li­terature data show that the expression of the genes selec­ted here, including ICL1 associated with the glyoxylate cycle only, changes dramatically when glucose is replaced with non-fermentable substrates [19]. However, except for CIT3 in EG37, our real-time PCR experiments did not reveal any significant expression changes of these genes between the studied strains (Figures 1 and 2). Only the R value for CIT3 in EG37 was moderately elevated to 3.7 but we do not have a good explanation for this result. By contrast, we observed significant increases in the expression levels of the cell trans­porter genes PDR12 and PMA1 in the mutants relative to the wild strain (Figure 3). Especially large R values of 24 and 53, respectively, were obtained for EG37. EG07 displayed mode­rate R values of 2.4 and 7.5, respectively. The R value of 2.4 is low and its significance at p < 0.1 questionable, but PDR12 expression in EG07 might be higher at the protein level. It is probable that EG07 and EG37 have different mutations. This supposition is supported by the fact that these two mutants belong to different complementation groups [9] and behave differently with respect to acetate as a source of carbon. So far we have been mostly focusing our attention on genetic regulation of the Krebs and glyoxylate cycles and more stu­dies are needed in this area, but the present results point to a different and probably more promising avenue of research dealing more with the regulation of the transporters rather than the enzymes of both cycles. After obtaining the first results for PDR12 and PMA1 we added WAR1 to our studies. PMA1 expression is known to be regulated by transcription factors Rap1 and Gcr1 [22], but first we focused our attention on Pdr12, which transports organic anions. WAR1 is a gene encoding the transcription factor War1 of PDR12 [12]. We hoped that the expression of WAR1 at least in EG37 would be higher than that in the wild strain but only small diffe­rences were observed. The R value for EG07 was even below one (0.46) with the 90% confidence level (Figure 3). Intere­stingly, this result is consistent with the low expression of PDR12 in EG07 but further studies are necessary to exclude experimental coincidence. Anyway, such a result is not very surprising because literature data [12] suggest that War1 requires phosphorylation for its activation, yet the kinase responsible for the phosphorylation is not known. At this moment, an unresolved question is whether the induction of PDR12 and PMA1 is caused by the accumulation of the acids in the mutant cells or by the mutation(s) of regulatory gene(s) associated with the transporters. This issue will be addressed in subsequent studies. In addition, we can conclude that one of the previously considered possibilities, that a physical le­akage of the acids through the cell membrane is responsible for the Aci+ phenotype [16], should probably be excluded.

REFERENCES

[1] Boniewska-Bernacka E., Lachowicz T., Kotylak Z.: Genetical and biochemical characterization of cycle Krebs mutants in yeast. Acta Microbiol. Pol., 1998; 47: 131-140
[PubMed]  

[2] Boniewska-Bernacka E., Wysocki R., Grochowalska R., Machnicka B., Ułaszewski S., Lachowicz T.: The YJL185C, YLR376C and YJR129C genes of Saccharomyces cerevisiae are probably involved in regulation of the glyoxylate cycle. Acta Biochim. Pol., 2006; 53: 739-745
[PubMed]  [Full Text PDF]  

[3] Bonneaud N., Ozier-Kalogeropoulos O., Li G., Labouesse M., Minvielle-Sebastia L., Lacroute F.: A family of low and hight copy replicative, integrative and single-stranded S. cerevisiae/E. coli shutte vectors. Yeast, 1991; 7: 609-615
[PubMed]  

[4] Epstein C.B., Waddle J., Hale W., Dave V., Thornton J., Macatee T., Garner H., Butow R.: Genome-wide responses to mitochondrial dysfunction. Mol. Biol. Cell, 2001; 12: 297-308
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[5] Gibson N., McAllister-Henn L.: Physical and genetic interaction of cytosolic malate dehydrogenase with other gluconeogenic enzymes. J. Biol. Chem., 2003; 278: 25628-25636
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[6] Goffeau A.: Four years of post-genomic life 6000 yeast genes. FEBS Lett., 2000; 480: 37-41
[PubMed]  

[7] Goffeau A., Barrel B., Bussey H., Davis R., Dujon B., Feldmann H., Galibert F., Hoheisel D.J., Jacq C., Johnston M., Louis E.J., Mewes H.W., Murokami Y., Philippsen P., Tettelin H., Oliver S.G.: Life with 6000 genes. Science, 1996; 274: 546, 563-567
[PubMed]  

[8] Gonchar M., Lachowicz T.M., Sybirny A., Witkowska R., Zakowska Z.: Genetics, physiology and biochemistry of some Saccharomyces cerevisiae mutants excreting acidic products. Genetics of respiratory enzymes in yeast. Wroclaw University Press, 1990; 53-64

[9] Grochowalska R., Machnicka B., Wysocki R., Lachowicz T.M.: The genetic characteristics Saccharomyces cerevisiae aci(+) mutants. Cell. Mol. Biol. Lett., 2003; 8: 261-268
[PubMed]  

[10] Ihmels J., Levy R., Barkai N.: Principles of transcriptional control in the metabolic network of Saccharomyces cerevisiae. Nat. Biotechnol., 2004; 22: 86-92
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[11] Kok J., Muller J.L., Slater E.C.: EPR studies on the respiratory chain of wild type Saccharomyces cerevisiae and mutants with deficiency in succinate dehydrogenase. Biochem. Biophys. Acta, 1975; 387: 441-450
[PubMed]  

[12] Kren A., Mammun Y.M., Bauer B.E., Schuller C., Wolfger H., Hatzixanthis K., Mollapour M., Gregori C., Piper P., Kuchler K.: War1p, a novel transcription factor controlling weak acid stress response in yeast. Moll. Cell. Biol., 2003; 23: 1775-1785
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[13] Lin A.P., Anderson S.L., Minard K.I., McAlister-Henn L.: Effects of excess succinate and retrograde control of metabolite accumulation in yeast TCA cycle mutants. J. Biol. Chem., 2011; 286: 33737-33746
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[14] Liu Z., Butow R.A.: A transcriptional switch in the expression of yeast tricarboxylic acid cycle genes in response to a reduction or loss of respiratory function. Moll. Cell. Biol., 1999; 19: 6720-6728
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[15] Livak K.J., Schmittgen T.D.: Analysis of relative gene expression data using real-time quantitative PCR and the 2^-ΔΔCt method. Methods, 2001; 25: 402-408
[PubMed]  

[16] Machnicka B., Grochowalska R., Boniewska-Bernacka E., Słominska L., Lachowicz T.: Acid excreting mutants of yeast Saccharomyces cerevisiae. Biochem. Biophys. Res. Comm., 2004; 325: 1030-1036
[PubMed]  

[17] McCammon M.T., Epstein C.B., Przybyla-Zawislak B., McAlister-Henn L., Butow R.A.: Global transcription analysis of Krebs tricarboxylic acid cycle mutants reveals an alternating pattern of gene expression and effects on hypoxic and oxidative genes. Mol. Biol. Cell, 2003; 14: 958-972
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[18] Nowik M., Lecca M.R., Velic A., Rehrauer H., Brandli A.W., Wagner C.A.: Genome-wide gene expression profiling reveals renal genes regulated during metabolic acidosis. Physiol. Genomics, 2008; 32: 322-334
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[19] Paiva S., Devaux F., Barbosa S., Jacq C., Casal M.: Ady2p is essential for the acetate permease activity in the yeast Saccharomyces cerevisiae. Yeast, 2004. 21: 201-210
[PubMed]  

[20] Pfaffl M.W.: A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res., 2001; 29: e45
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[21] Piper P., Mahe Y., Thompson S., Pandjaitan R., Holyoak C., Egner R., Muhlbauer M., Coote P., Kuchler K.: The Pdr12 ABC transporter is required for the development of weak organic acid resistance in yeast. EMBO J., 1998; 7: 4257-4265
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[22] Portillo F.: Regulation of plasma membrane H⁺-ATPase in fungi and plants. Biochim. Biophys. Acta, 2000; 1469: 31-42
[PubMed]  

[23] Przybyla-Zawislak B., Gadde D.M., Ducharme K., McCommon M.T.: Genetic and biochemical interactions involving tricarboxylic acid cycle (TCA) function using a collection of mutants defective in all TCA cycle genes. Genetics, 1999; 152: 153-166
[PubMed]  [Full Text PDF]  

[24] Robey I.F., Baggett B.K., Kirkpatrick N.D., Roe D.J., Dosescu J., Sloane B.F., Hashim A.I., Morse D.L., Raghunand N., Gatenby R.A., Gillies R.J.: Bicarbonate increases tumor pH and inhibits spontaneous metastases. Cancer Res., 2009; 69: 2260-2268
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[25] Serrano R.: Structure, function and regulation of plasma membrane H+-ATPase. FEBS Lett., 1993; 325: 108-111
[PubMed]  

[26] Velot C., Srere P.: Reversible transdominant inhibition of a metabolic pathway. In vivo evidence of interaction between two sequential tricarboxylic acid cycle enzymes in yeast. J. Biol. Chem., 2000; 275: 12926-12933
[PubMed]  [Full Text HTML]  [Full Text PDF]  

[27] Wenzel T.J., Teunissen A.W., de Steensma H.Y.: PDA1 mRNA: a standard for quantitation of mRNA in Saccharomyces cerevisiae superior to ACT1 mRNA. Nucleic Acids Res., 1995; 23: 883-884
[PubMed]  [Full Text PDF]  

[28] Wong W.L., Medrano J.: Real-time PCR for mRNA quantitation. BioTechniques, 2005; 39: 75-85

[29] Yuan J.S., Reed A., Chen F., Stewart C.N. Jr.: Statistical analysis of real-time PCR data. BMC Bioinformatics, 2006; 7: 85
[PubMed]  [Full Text HTML]  [Full Text PDF]  

The authors have no potential conflicts of interest to declare.

Pełna treść artykułu