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.
| Original language | English |
|---|---|
| Article number | 166 |
| Journal | Biotechnology for Biofuels |
| Volume | 10 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2017 |
| MoE publication type | A1 Journal article-refereed |
Funding
The research leading to these results has received funding from the European Community\u2019s Seventh Framework Programme for research and technological development (FP7) under the project NEMO for bioethanol (Grant Agreement No. 222699).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- bioethanol
- hexokinase
- HXK2 deletion
- large-scale kinetic models
- metabolic control analysis
- S. cerevisiae
- xylose utilization
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