A design-build-test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic models

Ljubisa Miskovic, Susanne Alff-Tuomala, Keng Cher Soh, Dorothee Barth, Laura Salusjärvi, Juha-Pekka Pitkänen, Laura Ruohonen, Merja Penttilä, Vassily Hatzimanikatis

Research output: Contribution to journalArticleScientificpeer-review

12 Citations (Scopus)

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 languageEnglish
Article number166
JournalBiotechnology for Biofuels
Volume10
Issue number1
DOIs
Publication statusPublished - 2017
MoE publication typeA1 Journal article-refereed

Fingerprint

Xylose
Glycolysis
Saccharomyces cerevisiae
kinetics
Kinetics
Metabolic Engineering
modeling
Bioreactors
Yeast
Metabolic engineering
experiment
Experiments
Fermentation
bioreactor
Risk analysis
fermentation
glucose
Glucose
Hexokinase
Systems Biology

Keywords

  • bioethanol
  • hexokinase
  • HXK2 deletion
  • large-scale kinetic models
  • metabolic control analysis
  • S. cerevisiae
  • xylose utilization

Cite this

@article{faeee3fde45e4fa380ba4d3f9c11db88,
title = "A design-build-test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic models",
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.",
keywords = "bioethanol, hexokinase, HXK2 deletion, large-scale kinetic models, metabolic control analysis, S. cerevisiae, xylose utilization",
author = "Ljubisa Miskovic and Susanne Alff-Tuomala and Soh, {Keng Cher} and Dorothee Barth and Laura Salusj{\"a}rvi and Juha-Pekka Pitk{\"a}nen and Laura Ruohonen and Merja Penttil{\"a} and Vassily Hatzimanikatis",
year = "2017",
doi = "10.1186/s13068-017-0838-5",
language = "English",
volume = "10",
journal = "Biotechnology for Biofuels",
issn = "1754-6834",
number = "1",

}

A design-build-test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic models. / Miskovic, Ljubisa; Alff-Tuomala, Susanne; Soh, Keng Cher; Barth, Dorothee; Salusjärvi, Laura; Pitkänen, Juha-Pekka; Ruohonen, Laura; Penttilä, Merja; Hatzimanikatis, Vassily.

In: Biotechnology for Biofuels, Vol. 10, No. 1, 166, 2017.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - A design-build-test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic models

AU - Miskovic, Ljubisa

AU - Alff-Tuomala, Susanne

AU - Soh, Keng Cher

AU - Barth, Dorothee

AU - Salusjärvi, Laura

AU - Pitkänen, Juha-Pekka

AU - Ruohonen, Laura

AU - Penttilä, Merja

AU - Hatzimanikatis, Vassily

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - bioethanol

KW - hexokinase

KW - HXK2 deletion

KW - large-scale kinetic models

KW - metabolic control analysis

KW - S. cerevisiae

KW - xylose utilization

UR - http://www.scopus.com/inward/record.url?scp=85021642215&partnerID=8YFLogxK

U2 - 10.1186/s13068-017-0838-5

DO - 10.1186/s13068-017-0838-5

M3 - Article

VL - 10

JO - Biotechnology for Biofuels

JF - Biotechnology for Biofuels

SN - 1754-6834

IS - 1

M1 - 166

ER -