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Understanding how microbial metabolism operates is a key issue for the design of efficient strategies to improve fermentation processes and modulate the production of fermentative compounds. Advances in genomics and functional genomics in these last two decades largely contributed to extending knowledge of the topology of metabolic networks in many microorganisms. Access to this information led to the development of approaches that aim for a comprehensive overview of cellular function1. These methodologies often rely on a model-based interpretation of measurable parameters. These experimental data include, on one hand, metabolite uptake and production rates and, on the other hand, quantitative intracellular information that is obtained from isotope tracer experiments. These data provide essential information for the deduction of the in vivo activity of different pathways in a defined metabolic network2,3,4. Currently, the available analytical techniques only enable the accurate detection of labeling patterns of molecules when using a single-element isotope and possibly when co-labeling with two isotopic elements. Moreover, under most growth conditions, the carbon source only consists of one or two-compounds. Consequently, approaches based on 13C-isotopic tracers from carbon substrates were widely and successfully applied to develop a complete understanding of carbon metabolic network operations5,6,7,8.
In contrast, in many natural and industrial environments, the available nitrogen resource that supports microbial growth is often composed of a wide range of molecules. For example, during wine or beer fermentation, nitrogen is provided as a mixture of 18 amino acids and ammonium at variable concentrations9. This array of N compounds that are accessible for anabolism makes these complex media conditions greatly different from those commonly used for physiological studies, as the latter are achieved using a unique source of nitrogen, typically ammonium.
Overall, internalized nitrogen compounds may be directly incorporated into proteins or catabolized. The network structure of nitrogen metabolism in many microorganisms, including the yeast Saccharomyces cerevisiae, is very complex in accordance with the diversity of substrates. Schematically, this system is based on the combination of the central core of nitrogen metabolism which catalyzes the interconversion of glutamine, glutamate, and α-ketoglutarate10,11, with transaminases and deaminases. Through this network, amine groups from ammonium or other amino acids are gathered and α-keto acids released. These intermediates are also synthetized through central carbon metabolism (CCM)12,13. This large number of branched reactions and intermediates, involved in both the catabolism of exogenous nitrogen sources and the anabolism of proteinogenic amino acids, fulfills the anabolic requirements of the cells. The activity through these different interconnected routes also results in the excretion of metabolites. In particular, α-keto acids may be redirected through the Ehrlich pathway to produce higher alcohols and their acetate ester derivatives14, which are essential contributors to the sensory profiles of products. Subsequently, how nitrogen metabolism operates plays a key role in biomass production and the formation of volatile molecules (aroma).
The reactions, enzymes, and genes involved in nitrogen metabolism are extensively described in the literature. However, the issue of the distribution of multiple nitrogen sources throughout a metabolic network has not yet been addressed. There are two main reasons that explain this lack of information. First, in view of the important complexity of the nitrogen metabolism network, a large amount of quantitative data is required for a complete understanding of its operation that was unavailable until now. Second, many experimental constraints and limitations of analytical methods prevented the implementation of approaches that were previously used for the elucidation of CCM function.
To overcome these problems, we chose to develop a system-level approach that is based on the reconciliation of data from a series of isotopic tracer experiments. The workflow includes:
- A set of fermentations carried out under the same environmental conditions, while a different selected nutrient source (substrate) is labeled each time.
- A combination of analytical procedures (HPLC, GC-MS) for an accurate determination, at different stages of the fermentation, of the residual concentration of labeled substrate and the concentration and the isotopic enrichment of compounds that are derived from the catabolism of the labeled molecule, including derived biomass.
- A calculation of the mass and isotopic balance for each consumed labeled molecule and a further integrated analysis of the dataset to obtain a global overview of the management of multiple nutrient sources by microorganisms through the determination of flux ratios.
To apply this methodology, attention must be paid to the reproducible behavior of the strain/microorganism between cultures. Furthermore, samples from different cultures must be taken during the same well-defined fermentation progress. In the experimental work reported in this manuscript, a robot-assisted system is used for online monitoring of fermentations to account for these constraints.
Furthermore, it is essential to choose a set of labeled substrates (compound, nature, and position of the labeling) that is appropriate to address the scientific problem of the study. Here, 15N-labeled ammonium, glutamine, and arginine were selected as the three major nitrogen sources found in grape juice. This allowed assessing the pattern of nitrogen redistribution from consumed compounds to the proteinogenic amino acids. We also aimed to investigate the fate of the carbon backbone of the consumed amino acids and their contribution to the production of volatile molecules. To meet this objective, uniformly 13C-labeled leucine, isoleucine, threonine, and valine were included in the study as amino acids that are derived from major intermediates of the Ehrlich pathway.
Overall, we quantitatively explored how yeast manages a complex nitrogen resource by redistributing exogenous nitrogen sources to fulfill its anabolic requirements throughout fermentation while additionally removing the excess of carbon precursors as volatile molecules. The experimental procedure reported in this paper can be applied to investigate other multiple nutrient sources used by any other microorganism. It appears to be an appropriate approach for the analysis of the impact of genetic background or environmental conditions on the metabolic behavior of microorganisms.