Abstract

BackgroundRecent 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.ResultsWe 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.ConclusionsWe 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.

Highlights

  • 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 integra‐ tion of data into consistent large-scale kinetic models

  • In efforts to enable xylose utilization in S. cerevisiae, the wild-type strains have been modified in two ways: (1) by introducing heterologous XYL1 and XYL2 genes from Scheffersomyces stipitis [5] or XYL1 from Candida tenuis and XYL2 from Galactocandida mastotermitis [6, 7] that encode for xylose reductase (XR) and xylitol dehydrogenase (XDH), respectively, which enable the two-step transformation from xylose to xylulose; (2) by expressing a heterologous xylose isomerase (XI) from fungi such as Piromyces [8] and Orpinomyces [9], or from Clostridium phytofermentans [10] which converts xylose to xylulose in one step

  • The main goals of this study were to: (1) analyze the impact of the network enzymes on pentose sugar utilization in a genetically recombinant XR/XDH S. cerevisiae strain caused by network-wide couplings and limitations rather than by a substrate competition for hexose transporters; (2) identify the sources of interdependencies between upper glycolysis and xylose uptake rate; (3) engineer genetically a recombinant S. cerevisiae strain with improved xylose uptake capabilities based on hypotheses generated in (2); and (4) use the experimental data acquired on the engineered strain to further improve predictive capabilities of the kinetic models

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Summary

Introduction

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 integra‐ tion of data into consistent large-scale kinetic models. These models can help us to uncover new insights into cellular physiology and to assist in the rational design of bioreactor or fermentation processes. Comparison of the two engineered pathways in the same background strain revealed that strains with XR/XDH pathway show higher xylose uptake rates under anaerobic conditions and better aerobic growth [11]. It appears that strains with XI have higher ethanol yields due to better cofactor balancing as compared to XR/XDH strains

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