Metabolic flux analysis for metabolome data validation of naturally xylose-fermenting yeasts

Abstract

Background: Efficient xylose fermentation still demands knowledge regarding xylose catabolism. In this study, metabolic flux analysis (MFA) and metabolomics were used to improve our understanding of xylose metabolism. Thus, a stoichiometric model was constructed to simulate the intracellular carbon flux and used to validate the metabolome data collected within xylose catabolic pathways of non-Saccharomyces xylose utilizing yeasts.

Results: A metabolic flux model was constructed using xylose fermentation data from yeasts Scheffersomyces stipitis, Spathaspora arborariae, and Spathaspora passalidarum. In total, 39 intracellular metabolic reactions rates were utilized validating the measurements of 11 intracellular metabolites, acquired by mass spectrometry. Among them, 80% of total metabolites were confirmed with a correlation above 90% when compared to the stoichiometric model. Among the intracellular metabolites, fructose-6-phosphate, glucose-6-phosphate, ribulose-5-phosphate, and malate are validated in the three studied yeasts. However, the metabolites phosphoenolpyruvate and pyruvate could not be confirmed in any yeast. Finally, the three yeasts had the metabolic fluxes from xylose to ethanol compared. Xylose catabolism occurs at twice-higher flux rates in S. stipitis than S. passalidarum and S. arborariae. Besides, S. passalidarum present 1.5 times high flux rate in the xylose reductase reaction NADH-dependent than other two yeasts.

Conclusions: This study demonstrated a novel strategy for metabolome data validation and brought insights about naturally xylose-fermenting yeasts. S. stipitis and S. passalidarum showed respectively three and twice higher flux rates of XR with NADH cofactor, reducing the xylitol production when compared to S. arborariae. Besides then, the higher flux rates directed to pentose phosphate pathway (PPP) and glycolysis pathways resulted in better ethanol production in S. stipitis and S. passalidarum when compared to S. arborariae.

Keywords: Cofactor balance; Ethanol; MFA; Metabolome; Metabolomics; Xylose metabolism.

Fig. 1

Intracellular carbon fluxes distributions during xylose catabolism to ethanol production. S. stipitis (green), S. arborariae (red), and S. passalidarum (blue). Xylose consumption rates are represented by a negative signal. The first intracellular reaction (xylose to xylitol) shows two arrows; left represents reaction using NADPH, right represents reaction using NADH cofactor. The extracellular metabolites highlighted in black boxes had its flux rates used as constraints to the MFA-calculated

Fig. 2

Correlation between measured and calculated fluxes for ethanol production. S. stipitis (green cycle), S. arborariae (red square) and S. passalidarum (blue triangle)

Fig. 3

Intracellular metabolites concentrations (mM). Yeast S. stipitis (green column), S. arborariae (red column), and S. passalidarum (blue column). All experiments performed in biological triplicates. [c] represent the cytosol metabolites. The presented values are the average of ANOVA analysis for three biological replicates and nine technical replicates

Fig. 4

Metabolic reaction rates using NAD(P) H / NAD(P)⁺ cofactors. S. stipitis (green), S. arborariae (red), and S. passalidarum (blue). R01 – XYL to XOL; R02 - XYL to XOL; R03 – XOL to XYLU; R10 – G6P to RU5P; R15 – DHAP to GOL; R16 – GAP to PEP; R19 – ACCOA to ETOH; R20 – ACDH to ACE; R25 – ISO to AKG; R26 – AKG to SUC; and R29 – MAL to OXA

Fig. 5

Intracellular carbon flux distribution using measured data. S. stipitis (green), S. arborariae (red), and S. passalidarum (blue). Xylose consumption rates are represented by a negative signal. The first reaction (xylose to xylitol) shows two arrows; left represents reaction using NADPH, right represents reaction using NADH cofactor. Extracellular metabolites highlighted in black boxes had the flux rates used as constraints. Intracellular metabolites highlighted in white boxes limited the reaction rates with its concentration in MFA-measured

Fig. 6

Correlation test (R²) between calculated and measured flux rates (mM/gCDW.h^− 1). The relationship assessed with all metabolites measured that present a correlation higher than 0.90 for S. stipitis (a), S. arborariae (b), and S. passalidarum. (c)

Fig. 7

Percentage of errors between calculated and measured flux rates. Columns are showing that the errors are less than 10% for most of the metabolic reaction rates from xylose to ethanol: S. stipitis (green), S. arborariae (red), and S. passalidarum (blue)