ABSTRACT: In contrast to batch cultivation, chemostat cultivation allows the identification of carbon source responses without interference by carbon-catabolite repression, accumulation of toxic products, and differences in specific growth rate. This study focuses on the yeast Saccharomyces cerevisiae, grown in aerobic, carbon-limited chemostat cultures. Genome-wide transcript levels and in vivo fluxes were compared for growth on two sugars, glucose and maltose, and for two C2-compounds, ethanol and acetate. In contrast to previous reports on batch cultures, few genes (180 genes) responded to changes of the carbon source by a changed transcript level. Very few transcript levels were changed when glucose as the growth-limiting nutrient was compared with maltose (33 transcripts), or when acetate was compared with ethanol (16 transcripts). Although metabolic flux analysis using a stoichiometric model revealed major changes in the central carbon metabolism, only 117 genes exhibited a significantly different transcript level when sugars and C2-compounds were provided as the growthlimiting nutrient. Despite the extensive knowledge on carbon source regulation in yeast, many of the carbon source-responsive genes encoded proteins with unknown or incompletely characterized biological functions. In silico promoter analysis of carbon source-responsive genes confirmed the involvement of several known transcriptional regulators and suggested the involvement of additional regulators. Transcripts involved in the glyoxylate cycle and gluconeogenesis showed a good correlation with in vivo fluxes. This correlation was, however, not observed for other important pathways, including the pentose-phosphate pathway, tricarboxylic acid cycle, and, in particular, glycolysis. These results indicate that in vivo fluxes in the central carbon metabolism of S. cerevisiae grown in steadystate, carbon-limited chemostat cultures are controlled to a large extent via post-transcriptional mechanisms. Experiment Overall Design: Cultivation of microorganisms in chemostats offers numerous advantages for studying the structure and regulation of metabolic networks (11). In chemostat cultures, individual culture parameters can be changed, while keeping other relevant physical and chemical culture parameters (composition of synthetic medium, pH, temperature, aeration, etc.) constant. An especially important parameter in this respect is the specific growth rate, which, in a chemostat, is equal to the dilution rate, which can be accurately controlled. This allows the experimenter to investigate the effects of environmental changes or genetic interventions at a fixed specific growth rate, even if these changes result in different specific growth rates in batch cultures. In a chemostat, growth can be limited by a single, selected nutrient. The very low residual concentrations of this growth-limiting nutrient in chemostat cultures alleviate effects of catabolite repression and inactivation. Furthermore, these low residual substrate concentrations prevent substrate toxicity, which, for example, occurs when S. cerevisiae is grown on ethanol or acetate as the carbon source in batch cultures . Experiment Overall Design: The central goal of the present study is to assess to what extent carbon source-dependent regulation of fluxes through central carbon metabolism in S. cerevisiae is regulated at the level of transcription. To this end, we compare the transcriptome of carbon-limited, aerobic chemostat cultures grown on four different carbon sources: glucose, maltose, ethanol, and acetate. Data from the transcriptome analysis are compared with flux distribution profiles calculated with a stoichiometric metabolic network model. Questions that will be addressed are as follows: (i) does glucose-limited aerobic cultivation lead to a complete alleviation of glucose-catabolite repression; (ii) how (in)complete is our understanding of the genes involved in the transcriptional response of S. cerevisiae to four of the most common carbon sources for this yeast; and (iii) to what extent do transcriptome analyses with microarrays provide a reliable indication of flux distribution in metabolic networks?
