The fluxes through glycolytic enzymes in Saccharomyces cerevisiae are predominantly regulated at posttranscriptional levels

Abstract

Metabolic fluxes may be regulated ''hierarchically,'' e.g., by changes of gene expression that adjust enzyme capacities (Vmax) and/or ''metabolically'' by interactions of enzymes with substrates, products, or allosteric effectors. In the present study, a method is developed to dissect the hierarchical regulation into contributions by transcription, translation, protein degradation, and posttranslational modification. The method was applied to the regulation of fluxes through individual glycolytic enzymes when the yeast Saccharomyces cerevisiae was confronted with the absence of oxygen and the presence of benzoic acid depleting its ATP. Metabolic regulation largely contributed to the Ϸ10-fold change in flux through the glycolytic enzymes. This contribution varied from 50 to 80%, depending on the glycolytic step and the cultivation condition tested. Within the 50 -20% hierarchical regulation of fluxes, transcription played a minor role, whereas regulation of protein synthesis or degradation was the most important. These also contributed to 75-100% of the regulation of protein levels.gene-expression cascade ͉ glycolysis ͉ posttranscriptional regulation ͉ regulation analysis ͉ systems biology T he 1990s have witnessed a revolution in molecular cell biology. Nucleotide sequences of complete genomes were elucidated, and new techniques enabled genome-wide analysis of mRNA and protein concentrations and accurate estimates of metabolic flux distributions (1). The central dogma of molecular biology is that DNA encodes mRNA and mRNA encodes proteins, which in turn fulfill the many functions in the cell. Therefore, a strong correlation was anticipated among mRNA concentrations, protein concentrations, and metabolic fluxes. However, subsequent gene-expression studies led to the paradoxical conclusion that correlations between mRNA levels and protein levels (2, 3), between mRNA and in vivo fluxes (4, 5), and between enzyme activities and fluxes (6, 7) were far from perfect.There are several explanations for the lack of correlation between the different levels of gene expression. Clearly defined and strictly controlled cultivation methods are required to obtain highquality datasets (8, 9). Furthermore, there should be a time delay between changes at the mRNA level and the corresponding changes of protein concentrations and enzyme activities. However, even in steady-state chemostat cultures, in which the cells grow in a constant environment for prolonged periods of time, mRNA levels, protein concentrations/activities, and fluxes correlated poorly (4, 6, 10). A remaining explanation might be that much of the regulation of gene expression is posttranscriptional. Indeed, regulatory mechanisms that affect translation, protein degradation, posttranslational modification of proteins, and enzymes directly have been documented extensively. High-throughput measurements of translation rates and protein turnover in Saccharomyces cerevisiae showed that these varied significantly between proteins and conditions (11-13). Posttranslational mo...

Running‐wheel activity delays mitochondrial respiratory flux decline in aging mouse muscle via a post‐transcriptional mechanism

“…Subsequently, we used Regulation Analysis (Kuile & Westerhoff, 2001; Daran‐Lapujade et al., 2007; cf. Introduction) to elucidate how the age‐related decline in oxygen consumption rate in isolated muscle mitochondria was regulated in the different groups.…”

“…included proteins across all functional groups and only 13 of 55 were metabolic enzymes. In this respect, our results correspond to a targeted study in yeast in which energy metabolism was regulated at the level of proteome and metabolome, and less so at the level of the transcriptome (Daran‐Lapujade et al., 2007). One might wonder if our focus on mitochondrial proteins affected the results, as mitochondria have their own DNA and may behave somewhat independently from the rest of the cell.…”

“…Regulation Analysis (Daran‐Lapujade et al., 2007; Kuile & Westerhoff, 2001) is a quantitative methodology that integrates different levels of regulation and dissects how much each factor contributes to a change in metabolic flux. In this framework, the flux regulation upon a transition from one condition to another, for example from young to old, is first dissected into two main contributions: hierarchical and metabolic regulation (Figure 1a).…”

“…Metabolic regulation integrates all metabolic effects, including the concentrations of substrates, products and allosteric effectors, as well as the affinity of the enzymes towards these metabolites, for example due to post‐translational modifications. Subsequently, hierarchical regulation can be dissected further into contributions of the involved processes (Daran‐Lapujade et al., 2007; Haanstra et al., 2008), such as translation efficiency.…”

Regulatory crosstalk of the metabolic network

“…For example, following leucine deprivation, its concentration and turnover must be monitored and the synthesis pathway activated. This is achieved by post-translational stimulation of enzymatic activity (common in central metabolism [20]), by transcriptional regulation, or by stabilisation of mRNA or protein levels. Notably, the supply of network-interconnecting metabolites [e.g., ATP or NAD(H)] must be rapidly adjusted, as alterations in their concentration would disturb the entire network.…”