1. Home
  2. People Index
  3. Bas Teusink

Bas Teusink

About Bas Teusink:

Since August 2008 I am professor in Systems Biology at the VU University Amsterdam. My Systems Bioinformatics group focusses on systems biology with a special focus on integrative bioinformatics. It aims at forming bridges between the classical bottom-up approaches in systems biology and the more data-driven approaches in classical bioinformatics. We combine experimental, modeling and theoretical approaches to study cellular physiology, with an emphasis on metabolic networks.

SEEK ID: https://fairdomhub.org/people/45

Location:  Netherlands

Expertise: Metabolic Pathway Analysis and Engineering Microbial Physiology Modeling of Biological Networks Industrial Systems Biotechnology White Biotech..., genome-scale modeling, enzyme kinetics, Dynamics and Control of Biological Networks

Tools: Metabolomics, enzymatic analyses, Chemostat culture, Kinetic Modeling

ORCID: https://orcid.org/0000-0003-3929-0423

project_administratorasset_housekeeper
help Their tags

This person has not yet tagged anything.

Related items

IMOMESIC

IMOMESIC - Integrating Modelling of Metabolism and Signalling towards an Application in Liver Cancer

One of the most challenging questions in cancer research is currently the interconnection of metabolism and signalling. An understanding of mechanisms that facilitate the physiological shift towards a proliferative metabolism in cancer cells is considered a major upcoming topic in oncology and is a key activity for future drug development. Due to the complexity of interrelations, a systems biology
...

Programme: ERASysAPP

Public web page: Not specified

SysMilk

Designer microbial communities for fermented milk products: A Systems Biology Approach

Programme: ERASysAPP

Public web page: Not specified

SysMO-LAB

Comparative Systems Biology: Lactic Acid Bacteria

Programme: SysMO

Public web page: http://www.sysmo.net/index.php?index=57

presentation in Oxford 2011
SysMO-LAB

overview of sysmo-LAB2

Creator: Bas Teusink

Submitter: Bas Teusink

Download
Genome-scale metabolic model of Enterococcus faecalis V583
SysMO-LAB

A reconstruction of the cellular metabolism of the opportunistic human pathogen Enterococcus faecalis V583 represented as stoichiometric model and analysed using constraint-based modelling approaches

Creators: Nadine Veith, Margrete Solheim, Koen van Grinsven, Jennifer Levering, Jeroen Hugenholtz, Helge Holo, Ingolf Nes, Bas Teusink, Ursula Kummer, Brett G Olivier, Ruth Grosseholz

Submitter: Nadine Veith

Download
1 hidden item
Quantitative analysis of amino acid metabolism in liver cancer links glutamate excretion to nucleotide synthesis
IMOMESIC

Abstract (Expand)

Many cancer cells consume glutamine at high rates; counterintuitively, they simultaneously excrete glutamate, the first intermediate in glutamine metabolism. Glutamine consumption has been linked to … replenishment of tricarboxylic acid cycle (TCA) intermediates and synthesis of adenosine triphosphate (ATP), but the reason for glutamate excretion is unclear. Here, we dynamically profile the uptake and excretion fluxes of a liver cancer cell line (HepG2) and use genome-scale metabolic modeling for in-depth analysis. We find that up to 30% of the glutamine is metabolized in the cytosol, primarily for nucleotide synthesis, producing cytosolic glutamate. We hypothesize that excreting glutamate helps the cell to increase the nucleotide synthesis rate to sustain growth. Indeed, we show experimentally that partial inhibition of glutamate excretion reduces cell growth. Our integrative approach thus links glutamine addiction to glutamate excretion in cancer and points toward potential drug targets.

Authors: Avlant Nilsson, Jurgen R. Haanstra, Martin Engqvist, Albert Gerding, Barbara M. Bakker, Ursula Klingmüller, Bas Teusink, Jens Nielsen

Date Published: 27th Apr 2020

Publication Type: Journal

Using a Genome-Scale Metabolic Model of Enterococcus faecalis V583 To Assess Amino Acid Uptake and Its Impact on Central Metabolism
SysMO-LAB

Abstract (Expand)

Increasing antibiotic resistance in pathogenic bacteria necessitates the development of new medication strategies. Interfering with the metabolic network of the pathogen can provide novel drug targets … but simultaneously requires a deeper and more detailed organism-specific understanding of the metabolism, which is often surprisingly sparse. In light of this, we reconstructed a genome-scale metabolic model of the pathogen Enterococcus faecalis V583. The manually curated metabolic network comprises 642 metabolites and 706 reactions. We experimentally determined metabolic profiles of E. faecalis grown in chemically defined medium in an anaerobic chemostat setup at different dilution rates and calculated the net uptake and product fluxes to constrain the model. We computed growth-associated energy and maintenance parameters and studied flux distributions through the metabolic network. Amino acid auxotrophies were identified experimentally for model validation and revealed seven essential amino acids. In addition, the important metabolic hub of glutamine/glutamate was altered by constructing a glutamine synthetase knockout mutant. The metabolic profile showed a slight shift in the fermentation pattern toward ethanol production and increased uptake rates of multiple amino acids, especially l-glutamine and l-glutamate. The model was used to understand the altered flux distributions in the mutant and provided an explanation for the experimentally observed redirection of the metabolic flux. We further highlighted the importance of gene-regulatory effects on the redirection of the metabolic fluxes upon perturbation. The genome-scale metabolic model presented here includes gene-protein-reaction associations, allowing a further use for biotechnological applications, for studying essential genes, proteins, or reactions, and the search for novel drug targets.

Authors: N. Veith, M. Solheim, K. W. van Grinsven, B. G. Olivier, J. Levering, R. Grosseholz, J. Hugenholtz, H. Holo, I. Nes, B. Teusink, U. Kummer

Date Published: 19th Dec 2014

Publication Type: Not specified

Role of phosphate in the central metabolism of two lactic acid bacteria - a comparative systems biology approach
SysMO-LAB

Abstract (Expand)

Lactic acid-producing bacteria survive in distinct environments, but show common metabolic characteristics. Here we studied the dynamic interactions of the central metabolism in Lactococcus lactis, … extensively used as starter in dairy industry, and Streptococcus pyogenes, a human pathogen. Glucose-pulse experiments and enzymatic measurements were performed to parameterize kinetic models of glycolysis. Significant improvements were made to existing kinetic models for L. lactis, which subsequently accelerated the development of the first kinetic model of S. pyogenes glycolysis. The models revealed an important role for extracellular phosphate in regulation of central metabolism and the efficient use of glucose. Thus, phosphate which is rarely taken into account as an independent species in models of central metabolism has to be considered more thoroughly in the analysis of metabolic systems in the future. Insufficient phosphate supply can lead to a strong inhibition of glycolysis at high glucose concentration in both species, but more severely in S. pyogenes. S. pyogenes is more efficient in converting glucose to ATP, showing a higher tendency towards heterofermentative energy metabolism than L. lactis. Our comparative systems biology approach revealed that the glycolysis of L. lactis and S. pyogenes have similar characteristics, but are adapted to their individual natural habitats with respect to phosphate regulation. The mathematical models described here have been submitted to the Online Cellular Systems Modelling Database and can be accessed at http://jjj.biochem.sun.ac.za/database/levering/index.html free of charge.

Editor:

Date Published: 14th Feb 2012

Publication Type: Not specified

1 hidden item
Powered by
 (v.1.10.3)
FAIRDOMHub | Funding and Programmes | Credits | Terms & Conditions | Imprint
Copyright © 2008 - 2020 The University of Manchester and HITS gGmbH