NADP-Glutamate Dehydrogenase Isoenzymes of Saccharomyces cerevisiae

DeLuna, Alexander; Avendaño, Amaranta; Riego, Lina; González, Alicia

doi:10.1074/jbc.m107986200

Cited by 140 publications

(85 citation statements)

References 47 publications

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“…The second node is directly perturbed, and it makes sense that this change results in a transcriptional response of enzymes around this node. It has indeed been shown that in a ⌬gdh1 mutant, the level of ␣-ketoglutarate is increased (19), which is consistent with a decreased expression of the genes KGD and LSC, both encoding enzymes downstream of ␣-ketoglutarate.…”

Section: Resultsmentioning

confidence: 62%

Uncovering transcriptional regulation of metabolism by using metabolic network topology

Patil

Nielsen

2005

Proc. Natl. Acad. Sci. U.S.A.

552

576

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Cellular response to genetic and environmental perturbations is often reflected and͞or mediated through changes in the metabolism, because the latter plays a key role in providing Gibbs free energy and precursors for biosynthesis. Such metabolic changes are often exerted through transcriptional changes induced by complex regulatory mechanisms coordinating the activity of different metabolic pathways. It is difficult to map such global transcriptional responses by using traditional methods, because many genes in the metabolic network have relatively small changes at their transcription level. We therefore developed an algorithm that is based on hypothesis-driven data analysis to uncover the transcriptional regulatory architecture of metabolic networks. By using information on the metabolic network topology from genome-scale metabolic reconstruction, we show that it is possible to reveal patterns in the metabolic network that follow a common transcriptional response. Thus, the algorithm enables identification of so-called reporter metabolites (metabolites around which the most significant transcriptional changes occur) and a set of connected genes with significant and coordinated response to genetic or environmental perturbations. We find that cells respond to perturbations by changing the expression pattern of several genes involved in the specific part(s) of the metabolism in which a perturbation is introduced. These changes then are propagated through the metabolic network because of the highly connected nature of metabolism.bioinformatics ͉ reporter metabolites ͉ metabolic subnetworks L inking the genome to its functioning metabolism is of substantial interest not only in studying human diseases (1) but also for identifying metabolic engineering targets in biotechnological applications (2, 3). Transcriptional analysis represents a high-throughput and genome-wide approach for linking the set of expressed genes to functional metabolism of the cell. Indeed, several studies using genome-wide gene-expression analysis have shown that transcriptional regulation plays an important role in regulating metabolism in response to perturbations (4-6). Although many statistical methods and clustering algorithms provide tools to analyze such transcriptomics data (7-9), these methods seldom provide insight into the regulatory architecture of the metabolic networks without intelligent analysis of the results (up͞down-regulation of genes of interest or correlation between genes of interest). This shortcoming is primarily due to the hypothesis that there may be all-to-all interactions among the genes being analyzed, resulting into many biologically nonsignificant results. One of the ways to address this problem is to integrate known biological interactions, e.g., protein-protein interactions, in the analysis of transcription data (10). Such an approach essentially reduces the degrees of freedom in data analysis by using knowledge of molecular interactions occurring in the cell. The organization and functioning of the cell can be ...

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Section: Resultsmentioning

confidence: 62%

Uncovering transcriptional regulation of metabolism by using metabolic network topology

Patil

Nielsen

2005

Proc. Natl. Acad. Sci. U.S.A.

552

576

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“…The glutamate/ glutamine pair has been reported to play a major role in the CNM, collecting NH 3 groups from the available nitrogen sources and then serving as amine donors for the transamination of ␣-keto acids (67,68). Interestingly, during 15 N-labeled arginine assimilation, isotopic enrichment occurred earlier in glutamate than in the other proteinogenic amino acids, supporting the key contribution of this compound as a mediator for nitrogen redistribution.…”

Section: Discussionmentioning

confidence: 76%

Management of Multiple Nitrogen Sources during Wine Fermentation by Saccharomyces cerevisiae

Crépin

Truong

Bloem

et al. 2017

Appl Environ Microbiol

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During fermentative growth in natural and industrial environments, Saccharomyces cerevisiae must redistribute the available nitrogen from multiple exogenous sources to amino acids in order to suitably fulfill anabolic requirements. To exhaustively explore the management of this complex resource, we developed an advanced strategy based on the reconciliation of data from a set of stable isotope tracer experiments with labeled nitrogen sources. Thus, quantifying the partitioning of the N compounds through the metabolism network during fermentation, we demonstrated that, contrary to the generally accepted view, only a limited fraction of most of the consumed amino acids is directly incorporated into proteins. Moreover, substantial catabolism of these molecules allows for efficient redistribution of nitrogen, supporting the operative de novo synthesis of proteinogenic amino acids. In contrast, catabolism of consumed amino acids plays a minor role in the formation of volatile compounds. Another important feature is that the ␣-keto acid precursors required for the de novo syntheses originate mainly from the catabolism of sugars, with a limited contribution from the anabolism of consumed amino acids. This work provides a comprehensive view of the intracellular fate of consumed nitrogen sources and the metabolic origin of proteinogenic amino acids, highlighting a strategy of distribution of metabolic fluxes implemented by yeast as a means of adapting to environments with changing and scarce nitrogen resources. IMPORTANCE A current challenge for the wine industry, in view of the extensive competition in the worldwide market, is to meet consumer expectations regarding the sensory profile of the product while ensuring an efficient fermentation process. Understanding the intracellular fate of the nitrogen sources available in grape juice is essential to the achievement of these objectives, since nitrogen utilization affects both the fermentative activity of yeasts and the formation of flavor compounds. However, little is known about how the metabolism operates when nitrogen is provided as a composite mixture, as in grape must. Here we quantitatively describe the distribution through the yeast metabolic network of the N moieties and C backbones of these nitrogen sources. Knowledge about the management of a complex resource, which is devoted to improvement of the use of the scarce N nutrient for growth, will be useful for better control of the fermentation process and the sensory quality of wines.KEYWORDS complex nitrogen resource, metabolic network, metabolism, nitrogen, quantitative analysis, regulation, yeasts T he management of nutrients provided by the external environment, mainly carbon and nitrogen, and their redistribution inside the cells for the formation of biosynthetic precursors through the metabolic network are essential for all living organisms. The topology of the metabolic network of the yeast Saccharomyces cerevisiae is one of

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“…Normal ploidy was recovered through the massive loss of 90% of the duplicated genes and the selective retention and further diversification of 8% of the retained paralogous copies (17). Diversification of paralogous genes whose products are involved in amino acid metabolism has led to the separation and specialization of the ancestral function of the two duplicated genes, the retention of both copies fulfilling the function carried out by the original and unique ancestral gene (10,(18)(19)(20). Subfunctionalization of paralogous pairs can be achieved through various nonexclusive molecular mechanisms, i.e., (i) modifications of the coding sequence leading to paralogous proteins with particular kinetic properties (18), (ii) modifications of the regulatory region determining the differential expression of each copy (20), or (iii) different subcellular localization (21).…”

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confidence: 99%

“…Subfunctionalization of paralogous pairs can be achieved through various nonexclusive molecular mechanisms, i.e., (i) modifications of the coding sequence leading to paralogous proteins with particular kinetic properties (18), (ii) modifications of the regulatory region determining the differential expression of each copy (20), or (iii) different subcellular localization (21). Previous work by our laboratory had suggested that an additional mechanism that could lead to functional diversification of paralogous proteins could be determined by the selective organization of homo-or hetero-oligomeric isozymes with peculiar biochemical properties (18).…”

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confidence: 99%

Diversification of Paralogous α-Isopropylmalate Synthases by Modulation of Feedback Control and Hetero-Oligomerization in Saccharomyces cerevisiae

et al. 2015

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Production of ␣-isopropylmalate (␣-IPM) is critical for leucine biosynthesis and for the global control of metabolism. The budding yeast Saccharomyces cerevisiae has two paralogous genes, LEU4 and LEU9, that encode ␣-IPM synthase (␣-IPMS) isozymes.Little is known about the biochemical differences between these two ␣-IPMS isoenzymes. Here, we show that the Leu4 homodimer is a leucine-sensitive isoform, while the Leu9 homodimer is resistant to such feedback inhibition. The leu4⌬ mutant, which expresses only the feedback-resistant Leu9 homodimer, grows slowly with either glucose or ethanol and accumulates elevated pools of leucine; this phenotype is alleviated by the addition of leucine. Transformation of the leu4⌬ mutant with a centromeric plasmid carrying LEU4 restored the wild-type phenotype. Bimolecular fluorescent complementation analysis showed that Leu4-Leu9 heterodimeric isozymes are formed in vivo. Purification and kinetic analysis showed that the hetero-oligomeric isozyme has a distinct leucine sensitivity behavior. Determination of ␣-IPMS activity in ethanol-grown cultures showed that ␣-IPM biosynthesis and growth under these respiratory conditions depend on the feedback-sensitive Leu4 homodimer. We conclude that retention and further diversification of two yeast ␣-IPMSs have resulted in a specific regulatory system that controls the leucine-␣-IPM biosynthetic pathway by selective feedback sensitivity of homomeric and heterodimeric isoforms. The Leu4 and Leu9 ␣-isopropylmalate synthases (␣-IPMSs), paralogous isozymes from Saccharomyces cerevisiae, catalyze the first committed step of leucine biosynthesis: the synthesis of ␣-isopropylmalate (␣-IPM) from acetyl coenzyme A (acetylCoA) and ␣-ketoisovalerate (␣-KIV). This reaction is carried out in the mitochondria (1-8), and ␣-IPM is then transported from the mitochondria to the cytosol by the yeast oxaloacetate/sulfate carrier Oac1 (9). The concerted action of Leu1 and Leu2 converts ␣-IPM to ␣-ketoisocaproate, the immediate precursor of leucine; these reactions are performed in the cytoplasm (8). The last step in leucine biosynthesis is carried out on both the mitochondria and the cytoplasm through the action of the differentially localized Bat1 or Bat2 aminotransferase (10) (Fig. 1). Most of the ␣-IPMS activity in wild-type S. cerevisiae cells is provided by the mitochondrially localized LEU4-encoded isozyme and not by the Leu4 (Leu4 s) isoform, which naturally lacks the mitochondrial import sequence and is thus localized in the cytosol (1, 2).Leu4 enzymatic activity is inhibited by leucine and CoA, and the amino acid residues responsible for this property have been identified (7). Although no detailed biochemical characterization of the LEU9-encoded isozyme has been performed, it has been shown that it is less sensitive to leucine inhibition than Leu4 is (3).It is noteworthy that the leucine biosynthesis intermediate ␣-IPM plays a dual cellular role. On the one hand, it acts as an intermediate in leucine biosynthesis (5, 6), and on the other, it acts as t...

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NADP-Glutamate Dehydrogenase Isoenzymes of Saccharomyces cerevisiae

Cited by 140 publications

References 47 publications

Uncovering transcriptional regulation of metabolism by using metabolic network topology

Uncovering transcriptional regulation of metabolism by using metabolic network topology

Management of Multiple Nitrogen Sources during Wine Fermentation by Saccharomyces cerevisiae

Diversification of Paralogous α-Isopropylmalate Synthases by Modulation of Feedback Control and Hetero-Oligomerization in Saccharomyces cerevisiae

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