Nitrogen regulation involved in the accumulation of urea in Saccharomyces cerevisiae

Authors

  • Xinrui Zhao,

    1. Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, People's Republic of China
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  • Huijun Zou,

    1. Zhejiang Guyuelongshan Shaoxing Wine Company, Shaoxing, Zhengjiang, People's Republic of China
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  • Jianwei Fu,

    1. Zhejiang Guyuelongshan Shaoxing Wine Company, Shaoxing, Zhengjiang, People's Republic of China
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  • Jian Chen,

    1. Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, People's Republic of China
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  • Jingwen Zhou,

    Corresponding author
    1. Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, People's Republic of China
    • Correspondence to: J. W. Zhou, School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, People's Republic of China. E-mail: zhoujw1982@jiangnan.edu.cn

      G. C. Du, School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, People's Republic of China.

      E-mail: gcdu@jiangnan.edu.cn

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  • Guocheng Du

    Corresponding author
    1. Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, People's Republic of China
    • Correspondence to: J. W. Zhou, School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, People's Republic of China. E-mail: zhoujw1982@jiangnan.edu.cn

      G. C. Du, School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, People's Republic of China.

      E-mail: gcdu@jiangnan.edu.cn

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Abstract

Rice wine is a popular traditional alcoholic drink with a long history in China. However, the presence of the potential carcinogen ethyl carbamate (EC) raises a series of food safety concerns. Although the metabolic pathway of urea (the major precusor of EC) has been characterized in Saccharomyces cerevisiae, the regulation of urea accumulation remains unclear, making the efficient elimination of urea difficult. To demonstrate the regulatory mechanisms governing urea accumulation, three key nitrogen sources that can inhibit urea utilization for a commercial S. cerevisiae strain were identified. In addition, regulators of nitrogen catabolite repression (NCR) and target of rapamycin (TOR) pathways were identified as being involved in urea accumulation by real-time quantitative PCR. Based on these results, preferred nitrogen sources were found to repress urea utilization by converting them to glutamine or glutamate. Moreover, the results indicated that the manner of urea metabolism regulation was different for two positive regulators involved in NCR; Gln3p can be retained in the cytoplasm by glutamine, while Gat1p can be retained by glutamine and glutamate. Furthermore, this was confirmed by fluorescence location detection. These new findings provide new targets for eliminating EC and other harmful nitrogen-containing compounds in fermented foods. Copyright © 2013 John Wiley & Sons, Ltd.

Introduction

Rice wine is one of the oldest drinks in the world. It has been consumed throughout 4000 years of history and is still one of the most popular alcoholic beverages in China (Shen et al., 2010; Shen et al., 2011). During the process of industrial fermentation, Saccharomyces cerevisiae plays a leading role in the formation of ethanol and the characteristic flavour compounds (Chen and Xu, 2010). However, detailed analysis found that there were a few potentially harmful by-products produced by S. cerevisiae (Fu et al., 2010; Lu et al., 2007). Among these hazardous compounds, ethyl carbamate (EC; also called urethane) is a potential genotoxic carcinogen that can be widely found in a variety of alcoholic beverages and fermented foods, such as rice wine, grape wine, sake (Japanese liquor) and soybean sauce (Weber and Sharypov, 2009). EC has been shown to induce dose-dependent increases in liver and lung tumourigenesis in mice (Hernandez and Forkert, 2007; Miller et al., 2003). There is evidence that EC can cause liver disease, especially hepatic angiosarcoma, in humans (Cadranel et al., 1993). Therefore, the International Agency for Research on Cancer (IARC) classified EC in group 2A, which is probably carcinogenic to humans (Lachenmeier, 2007).

In rice wine, the main precursors of EC were identified to be urea and ethanol (Fu et al., 2010). During fermentation, urea is a direct metabolite of arginine (Monteiro and Bisson, 1991). As urea is toxic to S. cerevisiae at high concentrations, the cells secrete urea into the rice wine, and then the urea reacts with ethanol to produce EC over time (Monteiro et al., 1989). Therefore, urea accumulation is the main reason for the production of EC. Reducing the accumulation of urea could decrease the final EC concentration (Andrich et al., 2009).

Various methods for minimizing the concentration of EC have been tried. As urea is a precursor of EC, inhibition of the yeast CAR1 gene, which encodes arginase, was employed to lower the cytoplasmic urea concentration (Park et al., 2001). Using this approach, the Δcar1 strain can reduce EC formation by at least 60% compared to the wild-type strain (Schehl et al., 2007). However, this method wastes arginine in the medium and affects the taste of the product. The other solution is to constitutively express the DUR1,2 gene (encoding urea amidolyase, which can degrade urea into ammonia) or the DUR3 gene (encoding urea permease) in the yeast. By overexpressing these genes, urea-degrading strains produced 87% and 15% less EC than the original strain, respectively (Coulon et al., 2006). However, this method also may affect the wine's taste. Besides, the addition of acid urease can efficiently eliminate the urea in wine and repress EC formation indirectly (Andrich et al., 2009). Nevertheless, the utilization of urease is restricted because of its special requirement for nickel ions, which are harmful to humans (Miyagawa et al., 1999). Therefore, it is necessary to find a safe and effective method resulting in minimal changes in wine taste.

It is difficult to eliminate EC because of the lack of a comprehensive understanding of urea accumulation in S. cerevisiae. In fact, urea and most of the remaining nitrogen sources in fermented food can be degraded into non-harmful metabolites in S. cerevisiae under suitable conditions (Monteiro and Bisson, 1991). The key reason for urea accumulation is the inhibitory effect on urea utilization of nitrogen regulation (Magasanik and Kaiser, 2002). Therefore, a promising approach for minimizing urea accumulation is to control nitrogen regulation in S. cerevisiae. It is thought that the metabolism of nitrogen sources is generally regulated by the nitrogen catabolite repression (NCR) effect (Beltran et al., 2004), the TOR pathway (Cooper, 2002) and some unknown pathways. However, the relationships between urea accumulation and nitrogen regulation remain unclear.

Among the known nitrogen regulation pathways, NCR is the most important mechanism for preventing or reducing the unnecessary formation of enzymes and permeases for the utilization of non-preferred nitrogen sources (e.g. urea, proline or γ-amino butyrate, etc.) when a preferred nitrogen source (e.g. glutamine, asparagine or glutamate, etc.) is available (Deed et al., 2011). Therefore, NCR may be a main factor causing urea accumulation in cells. NCR is dependent on several transcription factors (Gln3p, Gat1p, Dal80p, Gzf3p, etc.) at the transcription level, on the regulation of gene expression at the post-transcriptional level by the processes of phosphorylation (Cooper, 2002) and on the regulation of degradation rate of enzymes or permeases at the post-translation level by ubiquitination (Soetens et al., 2001). Although much research has been performed on NCR, the regulatory mechanisms of the main transcription factors remain unclear. In addition, the TOR pathway also controls many gene expressions of nitrogen metabolism at the transcriptional level through phosphorylation in S. cerevisiae (Crespo and Hall, 2002). The TOR pathway has been widely investigated and is thought to play an important role in nitrogen metabolism (Duvel and Broach, 2003).

The focus of this study was to demonstrate the profile of nitrogen regulation involved in urea accumulation by examining the changes in gene expression related to urea metabolism. Based on the experimental results, the relationships between some nitrogen regulation pathways and urea accumulation were established. Information on the regulatory process provided important clues to eliminating EC production in rice wine or similar fermented foods.

Materials and methods

Yeast strain and growth conditions

S. cerevisiae diploid strain N85 used in this study was provided by the Guyuelongshan Shaoxing wine company. To obtain N85 haploids, diploid strain was precultured on a YPD plate (10 g/l yeast extract, 20 g/l peptone, 20 g/l glucose, 2% agar) at 30°C for 24 h. Then, yeast cells were transferred to a McClary plate (2.5 g/l yeast extract, 8.2 g/l natrium acetate, 1.8 g/l potassium chloride, 1 g/l glucose, 2% agar) and cultured at 30°C for 5–7 days. The cells were washed off from McClary plate using sterilized water and treated at 60°C for 10 min. The cell suspension was spread on a YPD plate and incubated at 30°C for 2–3 days. The N85 haploid colonies were confirmed by previously described methods (Katou et al., 2008). S. cerevisiae N85 Δura3 strains were obtained by transformation of a Δura3 fragment from S. cerevisiae CEN-PK2 amplified with the primer pairs: CGA GTG AAA CAC AGG AAG ACC AG/GCA TTT ACT TAT AAT ACA GTT TTG ATT TAT CTT CGT TTC CTG CAG GT; and ACC TGC AGG AAA CGA AGA TAA ATC AAA ACT GTA TTA TAA GTA AAT GC/CAA GGT CTG TTG AGT GCA AT. Uracil auxotroph transformants were screened on a 5-fluoroorotic acid medium (7 g/l yeast nitrogen base, 1 g/l 5-fluoroorotic acid, 50 mg/l uracil, 20 g/l glucose, 2% agar) (Boeke et al., 1987).

Synthetic minimal urea medium (MU medium; 1.6 g/l yeast nitrogen base with no ammonium sulphate or amino acids, 20 g/l glucose, 10 mm urea) was used as a control. Complex nitrogen medium (CN medium), which was used to select the preferred nitrogen sources, was made up as MU medium but with the addition of the 20 common amino acids (10 mm each) and ammonium sulphate (10 mm). For each of the sole nitrogen media (SN media) that were used to examine the inhibitory effects of different kinds of nitrogen sources on urea utilization, one of the nitrogen sources (10 mm) was added to the MU medium. SC minimal medium agar plates (0.17% w/v yeast nitrogen base without amino acids, 0.5% w/v ammonium sulphate, 2% w/v glucose, 1.6% w/v agar) was used to select the positive transformants of S. cerevisiae N85 haploid Δura3. All cultivations were carried out in shake flasks (150 rpm) at 30 °C and yeast growth was monitored by determining the optical density at 600 nm (OD600).

Urea, ammonium and amino acids assay

The urea, ammonium sulphate and amino acid standards were obtained from Sigma-Aldrich (St. Louis, MO, USA). All other chemicals and solvents were of analytical grade. Urea was determined after the addition of 4-dimethylaminobenzaldehyde by measuring the optical density at a wavelength of 420 nm (Knorst et al., 1997). Ammonium was determined based on the formation of indophenol blue (Kanda, 1995). Analyses of amino acids were performed using the Agilent HPLC system 1200 (Palo Alto, CA, USA) and a Zorbax Eclipse AAA (4.6 × 150 mm) column, according to a previously described method (Cigic et al., 2008). All experiments were performed in biological replicates with an independent measurement of each sample and mean values were used for further calculations.

RNA preparation and cDNA synthesis

The S. cerevisiae N85 cells were incubated in YPD medium at 30°C for 20 h with constant shaking at 200 rpm. Then, the strains were inoculated into sole nitrogen media supplemented with urea + glutamine, urea + glutamate and urea + arginine, respectively, and were incubated at 30°C for 10 h with continuous shaking at 200 rpm (before the preferred nitrogen sources were exhausted). Cells were harvested at 10 000 × g for 5 min, then washed twice with double-distilled water and immediately used for RNA preparation.

Total RNA was extracted using Trizol reagent (Invitrogen, Carlsbad, CA, USA), according to the manufacturer's instructions, including a DNase digestion step. The RNA was quantified and checked in a Nanodrop ND-2000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA) at 260 and 280 nm. Integrity of the isolated RNA was verified using an automated electrophoresis system (Bio-Rad, Hercules, CA, USA). cDNA was synthesized from 5 µg total RNA, using PrimeScript RT Reagent Kit Perfect Real Time (Takara, Dalian, China).

Real time quantitative PCR (qPCR)

qPCR was performed with the synthesized cDNA as template. All primer sequences are listed in Table 1. The efficiencies and specificities of the primers were tested by dilution experiments and melting curves, respectively. qPCR experiments were performed using SYBR Premix Ex Taq™ Kit (Takara, Dalian, China). The parameters for PCR were: pre-incubation at 95°C for 30 s; 40 cycles of amplification step 95°C for 5 s, 60°C for 20 s; and finally a cooling step at 50°C for 30 s. Reactions were conducted using a LightCycler 480 II Real-time PCR instrument (Roche Applied Science, Mannheim, Germany). All experiments were performed in biological replicates with an independent measurement of each sample and mean values were used for further calculations. The fold changes were determined by the 2ΔΔCt method normalized to the ACT1 gene (Boer et al., 2007).

Table 1. Oligonucleotides for RT–PCR
GeneForward/reverseSequence (5′–3′)Product size (bp)Mean PCR efficiency
ACT1FTTATTGATAACGGTTCTGGTATG1001.907
RCCTTGGTGTCTTGGTCTAC
DUR1,2FGGTGTCCCTATTGCTGTTAAG1861.943
RCCGTGTGCCGACTAATCC
DUR3FACTGCCTGTGGGTGTTGTTG2001.932
RCGTCTACTGGATGCCTCTTGG
GLN3FCGAAGTAATGAAGAGCCGAGAC1131.917
RAATGTGCCGCCGTTTAATCC  
GAT1FTTCTAACTCTATTATGGACTTCTC1841.901
RGTCATCATCATCGTCATCG
DAL80FGGTGCTTAGTGATTCGTTG1381.968
RTGTTCATCTCTTCTCCATAGG
GZF3FCGCAGATTCTCCTCAATTACCTC1541.940
RAGTCGTCCGTGAAGAAGTGG
TOR1FCTTCACGACTGGCTGGTTAC1001.927
RCCTGGAACGGCTAACTTGC
TOR2FGCTCATCCGCAGGCATTAG1501.941
 RCAATTCGTGGCTGACAAGTTC  
MKS1FCCATCCAACAATGAGCGGTTATCG1931.923
 RGCGTATTACTACCAGTGGCAATCG
DAL81FAATGAATGCTTCTCCCTTGACCTC1161.909
RGTTCCGTTGATGATTCCTCGTTGG
DAL82FACCAGAACATCCAAGACCAAGAAC1701.939
RGCGGTTGTGAGCCTGAATGC
NPR1FACCGAGAACTTCTGCTGATACG1101.918
RTGCTGCTATTACTCACGCTACC
NPR2FTCCACAACAACACCCTCCAC1191.920
RCTGTATCTGCTGCTTCTCATATCC

Construction of yeast expression vectors for fluorescence location detection of Gln3p and Gat1p

Plasmid pQE60–EGFP (Qiagen, Valencia, CA, USA) was used as a template for PCR amplification of the EGFP gene without the stop codon (EGFP forward primer, 5′-CAT GCC ATG GGT AAG GGA GAA GAA C-3′ incorporating a NcoI site; and EGFP reverse primer, 5′-ACG CGT CGA CTT TGT ATA GTT CAT CCA TGC-3′ incorporating a SalI site). The genomic DNA of S. cerevisiae N85 was extracted using a Genomic Extraction Kit (Qiagen) and used as the DNA template for amplifying the GLN3 or GAT1 genes. Primers were designed from the published GLN3 or GAT1 gene (GenBank Accession Nos NC_001137.3 and NC_001138). Then 5× (Gly + Ala) linker was fused to the ATG codon of the GLN3 or GAT1 gene (GLN3 forward primer, 5′-ACG CGT CGA CGG TGC TGG TGC TGG TGC TGG TGC TGG TGC TAT GCA AGA CGA CCC CGA A-3′ incorporating a SalI site; and GLN3 reverse primer, 5′-CGA GCT CTC ATA TAC CAA ATT TTA ACC AAT CC-3′ incorporating a SacI site; GAT1 forward primer, 5′-ACG CGT CGA CGG TGC TGG TGC TGG TGC TGG TGC TGG TGC TAT GCA CGT TTT CTT TCC T-3′ incorporating a SalI site; and GAT1 reverse primer, 5′-CGA GCT CCT ATA AAT TCA GAT TCA ACC AAT-3′ incorporating a SacI site).

The PCR-amplified EGFP fragment was inserted into the NcoI and SalI sites of the expression vector pYX212 (Ingenius, Madison, WI, USA) to construct pYX212–EGFP. Then the PCR-amplified GLN3 and GAT1 fragments were inserted into the SalI and SacI sites to construct pYX212–EGFP–GLN3 and pYX212–EGFP–GAT1, respectively. Correct insertions of the target genes were confirmed by DNA sequencing. The verified plasmids were transformed into a S. cerevisiae N85 haploid Δura3 strain using the lithium acetate method (Gietz and Woods, 2002), with selection on SC minimal medium agar plates.

Fluorescence microscopy analysis

Yeast strains expressing pYX212–EGFP–GLN3 or pYX212–EGFP–GAT1 were grown in SC minimal medium until OD600 = 1.0 was reached, and then collected by centrifugation and resuspended in a 10-fold greater volume of buffered SC minimal medium. Live cells were observed by fluorescence microscopy with a Nikon DXM1200C camera (Nikon, Tokyo, Japan) and digital images by Nikon ACT-1C acquisition software (Nikon, Tokyo, Japan) (Zhou et al., 2009). Unaltered file images were used for scoring intracellular distributions of GATA regulators, as previously described (Georis et al., 2011).

Results

Screening of the preferred nitrogen sources in S. cerevisiae N85

The medium with the 20 common amino acids and ammonium sulphate was used to examine the consumptions of each nitrogen source during the 48 h of fermentation. The consumptions of the 20 amino acids and ammonium were remarkably different (Figure 1). There were seven nitrogen sources with higher consumption, including asparagine, glutamine, serine, glutamate, ammonium, aspartate and arginine. The results meant that these nitrogen sources were preferable for use in S. cerevisiae N85 compared to the others. Therefore, these seven nitrogen sources were considered as the preferred nitrogen sources in the following study.

Figure 1.

The consumptions of different nitrogen sources. The strains were cultured in the complex nitrogen medium (CN medium) during fermentation for 48 h. The utilization efficiencies were computed as the ratio of the consumption for each amino acid at 48 h divided by the total amount of each amino acid added to the CN medium. The amino acids were split into three groups: high utilization efficiency (> 50%), moderate utilization efficiency (40–50%) and low utilization efficiency (< 40%). Analysis of variance (ANOVA) was used to measure the relative significance of different utilization efficiencies by calculation of their mean differences. Significant differences among means were determined by Duncan's multiple range test, at *p ≤ 0.05 and **p ≤ 0.01. Data were analysed using SPSS 18.0. The dark grey columns represent nitrogen sources with high and moderate consumptions that were considered preferred nitrogen sources; the light grey columns represent nitrogen sources with lower consumptions. Each value represents the mean of three independent measurements, and the deviation from the mean is < 5%

Repression of urea utilization by the preferred nitrogen sources in S. cerevisiae N85

The media with the preferred nitrogen sources were employed to examine the inhibitory effects of each preferred nitrogen source individually, and the MU medium was selected as control. The value of OD600, concentration of urea and the preferred nitrogen sources during the 48 h of fermentation are shown in Figure 2. The consumptions of urea were calculated at 10 h (Figure 3), except the medium added with arginine, because the urea had accumulated. According to the consumptions of urea, some nitrogen sources, including asparagine, glutamine and ammonium, could strongly repress urea utilization; the others, including serine, glutamate and aspartate, could only slightly repress urea utilization.

Figure 2.

The concentrations of urea and the nitrogen sources in each sole nitrogen medium (SN medium) and control. Each SN medium contained urea and one preferred nitrogen source (10 mm). The control contained urea only. The cells were harvested and the concentrations of urea and the nitrogen source were examined every 4 h during the 48 h of fermentation. (A–G) Concentrations of urea (▼), concentrations of other nitrogen sources (ammonium ■; arginine ●; asparagine ♦; aspartate □; glutamine ◊; glutamate ○; serine ∆) and the value of OD600 (▷) in each SN medium. (H) Concentration of urea and the value of OD600 in the control. Each value represents the mean of three independent measurements, and the deviation from the mean is < 5%

Figure 3.

The consumptions of urea in each sole nitrogen medium (SN medium) and control. Each SN medium contained urea and one preferred nitrogen source (10 mm). The control contained urea only. The 100% consumption of urea was defined that the 10 mm urea was completely used up by the yeast in the medium. The amino acids were split into three groups: low consumptions of urea (< 20%), moderate utilization efficiency (20–30%), high utilization efficiency (> 30%). The analysis of relative significance is similar to the description in Figure 1. The dark grey columns represent media with high consumptions of urea; the black columns represent media with moderate and low consumptions of urea; and the light grey column represents the control. Each value represents the mean of three independent measurements, and the deviation from the mean is < 5%

Transcriptional analysis of key genes involved in the repression of urea utilization by glutamine, glutamate and arginine in S. cerevisiae N85

To investigate the inhibitory effects of glutamine, glutamate and arginine, changes in gene expression related to urea metabolism were analysed at the transcriptional level by qPCR. There were four types of genes examined in this study: (a) genes encoding urea metabolic enzyme and transporter, including DUR1,2 and DUR3; (b) genes encoding regulators of NCR, including GLN3, GAT1, GZF3, DAL80 and URE2; (c) genes encoding regulators of the TOR pathway, including TOR1 and TOR2; (d) genes encoding regulators of urea metabolism reported in previous studies, including MKS1, DAL81, DAL82, NPR1 and NPR2.

When the media were supplemented with glutamine, glutamate and arginine, the following genes were remarkably downregulated: DUR1,2, DUR 3, NCR regulator genes (except GLN3) and NPR1; whereas the TOR1 gene was remarkably upregulated (Figure 4). Moreover, it was surprising that DAL82 were upregulated when arginine was added to the medium.

Figure 4.

Fold changes (log2) in gene regulation, measured by qPCR. The cells were cultured in SN medium supplemented with urea and glutamine, urea and glutamate, or urea and arginine. The SN medium with urea as sole nitrogen source was used as control. RNAs were purified from the samples collected and used in qPCR analyses. Data are presented as log2 ratios and are normalized to the ACT1 gene. If the log2 ratio = 0, the expression level of this gene was not changed. (A–C) Gene changes under the additions of glutamine and glutamate + arginine, respectively. Genes A–N represent DUR1,2, DUR3, GLN3, GAT1, GZF3, DAL80, URE2, TOR1, TOR2, MKS1, DAL81, DAL82, NPR1 and NPR2, respectively. Each value represents the mean of three independent measurements

Fluorescence location detection of Gln3p and Gat1p in S. cerevisiae

To investigate the inhibitory mechanisms of glutamine and glutamate, yeast strains with pYX212–EGFP–GLN3 or pYX212–EGFP–GAT1 were used to examine the fluorescence location of Gln3p and Gat1p in the cells; the results are shown in Figure 5. When the medium was supplemented with glutamine or glutamine + urea, both Gln3p and Gat1p were retained in the cytoplasm; whereas in media with added glutamate or glutamate + urea, Gln3p could enter the nucleus but Gat1p was retained in the cytoplasm.

Figure 5.

Fluorescence location detection of Gln3p and Gat1p in S. cerevisiae. The pYX212–EGFP–GLN3 and pYX212–EGFP–GAT1 plasmids were transformed into S. cerevisiae N85 Δura3. (A) The fluorescence locations of Gln3p and Gat1p were examined on medium containing glutamine and glutamate. (B) The fluorescence locations of Gln3p and Gat1p were examined on medium containing glutamine + urea and glutamate + urea

Discussion

Although yeast is able to use many nitrogen sources for growth, the utilization rates of these components are different (Godard et al., 2007). In this study, it was found that there were mainly two kinds of inhibitory effects on urea metabolism by preferred nitrogen sources. Asparagine, glutamine and ammonium can strongly repress urea utilization, while aspartate, glutamate and serine can just slightly repress urea utilization. The reason for the differences can be explained by analysing the nitrogen metabolic pathways (Figure 6). Aspartate and serine can be converted into glutamate (Gombert et al., 2001; Verleur et al., 1997), while asparagine can also be degraded into glutamate and ammonium by asparaginase (Sinclair et al., 1994). As for ammonium, it had to be converted into glutamine to exhibit repression of gene expression (Magasanik, 1992).

Figure 6.

The inhibitory mechanisms of different nitrogen sources in S. cerevisiae. Three key nitrogen sources (glutamine, glutamate and arginine) are considered to be key factors in the repression of urea utilization, and other nitrogen sources repressed urea utilization after they were converted into these key sources. Furthermore, glutamine repressed urea utilization by retaining Gln3p and Gat1p in the cytoplasm; while glutamate repressed urea utilization by retaining Gat1p in the cytoplasm

Therefore, it seems that the stronger inhibitory effects were induced by nitrogen sources that can be converted into glutamine, whereas the weaker inhibitory effects were induced by nitrogen sources that can be converted into glutamate (Stanbrough et al., 1995). The qPCR results supported this hypothesis and indicated that the stronger repression of urea metabolism was mainly induced by those nitrogen sources that can downregulate DUR1,2 and DUR3 significantly (Figure 4).

Furthermore, it was found that the gene expressions of NCR regulators and TOR1 were significantly changed. This finding suggested that NCR and TOR pathways might be involved in the repression of urea metabolism. This was not surprising, because some previous researches have shown that NCR and TOR pathways take part in the regulation of nitrogen metabolism in yeast. It has been proved that when preferred nitrogen sources, such as ammonium and asparagine, were presented in the media, the gene expressions of GAT1, DAL80 and GZF3 were downregulated (Mendes-Ferreira et al., 2007). As for TOR pathway, previous evidence has linked TOR signalling to the NCR pathway (Bertram et al., 2000). The gene expressions of NCR regulators also respond to the Tor1p activity and the interaction with TOR kinase is essential for the phosphorylation of NCR regulators (Cooper, 2002). Moreover, some genes involved in the metabolism of non-preferred nitrogen sources (DAL5) could be repressed by the TOR pathway (Georis et al., 2008).

Arginine is a special kind of nitrogen source that can be metabolized into urea directly. In this study, it was surprising that the consumption of arginine was high because the utilization of arginine can be repressed by NCR (Hofman-Bang, 1999). Furthermore, the stronger inhibitory effect of arginine was confirmed by the qPCR result of gene expressions of DUR1,2 and DUR3 (Figure 4). There have been few reports about the inhibitory effect of arginine on urea utilization. Although the inhibitory effect of arginine is strong, it can only be converted into glutamate in the cells (Jauniaux et al., 1978). Therefore, it is assumed that metabolites of arginine degradation (urea or ornithine) play important roles in the inhibitory process.

Based on the above results, it can be concluded that glutamine, glutamate and arginine were three key factors in the inhibitory effect. Nitrogen sources were converted into glutamate and glutamine through different metabolic pathways in the cells at first. Then glutamine could retain both Gln3p and Gat1p in the cytoplasm, while glutamate could retain only Gat1p in the cytoplasm. Once Gln3p and Gat1p were retained in the cytoplasm, they could not bind to the promoters of genes involved in the metabolism of non-preferred nitrogen sources (Beck and Hall, 1999; Georis et al., 2008, 2009; Kulkarni et al., 2001). Therefore, glutamine had a stronger inhibitory effect on urea metabolism than glutamate.

Two different evidences could support this hypothesis. First, Gln3p and Gat1p were highly sensitive to the intracellular concentrations of glutamine and glutamate (Kulkarni et al., 2006). Second, when an inhibitor of glutamine synthase, methionine sulphoximine, was added, cytoplasmic Gln3p transited into the nucleus, while nuclear Gat1p transited into the cytoplasm (Kulkarni et al., 2006). The hypothesis was further confirmed by the fluorescence location detection of Gln3p and Gat1p (Figure 5).

In summary, the inhibitory mechanisms of normal nitrogen sources in S. cerevisiae N85 can be profiled as in Figure 6. The current study lays a foundation for further research on the control of urea accumulation to eliminate EC production in rice wine and other similar fermented foods through metabolic engineering. Nevertheless, global and in-depth investigations of the mechanism of nitrogen regulation that is involved in urea accumulation are essential to reveal the regulatory mechanisms controlling urea accumulation in S. cerevisiae. It is believed that the urea accumulation can be minimized by rational regulation of these negative or active regulators.

Acknowledgements

This work was supported by the Major State Basic Research Development Programme of China (973 Programme, Grant No. 2012CB720802), the National Natural Science Foundation of China (Grant Nos 31130043, 31000807 and 21276109), the Natural Science Foundation of Jiangsu Province (Grant Nos BK2010150 and BK2011004), the Author of National Excellent Doctoral Dissertation of PR China (Grant No. FANEDD 2011046), the Program for New Century Excellent Talents in University (Grant No. NCET-12-0876) and the 111 Project (Grant No. 111-2-06).

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