ABSTRACT
BACKGROUND: Recent advancements in omics measurement technologies have led to an ever-increasing amount of available experimental data that necessitate systems-oriented methodologies for efficient and systematic integration of data into consistent large-scale kinetic models. These models can help us to uncover new insights into cellular physiology and also to assist in the rational design of bioreactor or fermentation processes. Optimization and Risk Analysis of Complex Living Entities (ORACLE) framework for the construction of large-scale kinetic models can be used as guidance for formulating alternative metabolic engineering strategies. RESULTS: We used ORACLE in a metabolic engineering problem: improvement of the xylose uptake rate during mixed glucose-xylose consumption in a recombinant Saccharomyces cerevisiae strain. Using the data from bioreactor fermentations, we characterized network flux and concentration profiles representing possible physiological states of the analyzed strain. We then identified enzymes that could lead to improved flux through xylose transporters (XTR). For some of the identified enzymes, including hexokinase (HXK), we could not deduce if their control over XTR was positive or negative. We thus performed a follow-up experiment, and we found out that HXK2 deletion improves xylose uptake rate. The data from the performed experiments were then used to prune the kinetic models, and the predictions of the pruned population of kinetic models were in agreement with the experimental data collected on the HXK2-deficient S. cerevisiae strain. CONCLUSIONS: We present a design-build-test cycle composed of modeling efforts and experiments with a glucose-xylose co-utilizing recombinant S. cerevisiae and its HXK2-deficient mutant that allowed us to uncover interdependencies between upper glycolysis and xylose uptake pathway. Through this cycle, we also obtained kinetic models with improved prediction capabilities. The present study demonstrates the potential of integrated "modeling and experiments" systems biology approaches that can be applied for diverse applications ranging from biotechnology to drug discovery.
ABSTRACT
Xylose is present with glucose in lignocellulosic streams available for valorisation to biochemicals. Saccharomyces cerevisiae has excellent characteristics as a host for the bioconversion, except that it strongly prefers glucose to xylose, and the co-consumption remains a challenge. Further, since xylose is not a natural substrate of S. cerevisiae, the regulatory response it induces in an engineered strain cannot be expected to have evolved for its utilisation. Xylose-induced effects on metabolism and gene expression during anaerobic growth of an engineered strain of S. cerevisiae on medium containing both glucose and xylose medium were quantified. The gene expression of S. cerevisiae with an XR-XDH pathway for xylose utilisation was analysed throughout the cultivation: at early cultivation times when mainly glucose was metabolised, at times when xylose was co-consumed in the presence of low glucose concentrations, and when glucose had been depleted and only xylose was being consumed. Cultivations on glucose as a sole carbon source were used as a control. Genome-scale dynamic flux balance analysis models were simulated to analyse the metabolic dynamics of S. cerevisiae. The simulations quantitatively estimated xylose-dependent flux dynamics and challenged the utilisation of the metabolic network. A relative increase in xylose utilisation was predicted to induce the bi-directionality of glycolytic flux and a redox challenge even at low glucose concentrations. Remarkably, xylose was observed to specifically delay the glucose-dependent repression of particular genes in mixed glucose-xylose cultures compared to glucose cultures. The delay occurred at a cultivation time when the metabolic flux activities were similar in the both cultures.
