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March 28, 2017, VU University, O|2 building, room 01W08, Amsterdam, NL
The location of the meeting is in the O|2 building (map for finding locating it) in room 01W08 (first floor, you cannot miss it when you take the stairs). For more information about BioSB please visit their website. RobustYeast is an EraSysApp funded project.
PROGRAMME (ABSTRACTS ARE BELOW)
0900-0915 Coffee break
0915-1000 Bram Cerulus, Cellular memory in the lag phase under fluctuating carbon environments
1000-1045 Brett Olivier, Computational Systems Biology & Software
1045-1115 Coffee break
1115-1200 Bas Teusink, Understanding the regulation of glycolysis under dynamic conditions
1200-1245 Alexander Bockmayr, deFBA: A dynamic optimization framework for metabolic regulation
1245-1330 Lunch break
1330-1415 Pascale Daran-Lapujade, Pathway swapping: a new approach to simply and efficiently remodel essential native cellular functions
1415-1500 Alex Papagiannakis, Intrinsic, periodic and tunable metabolic dynamics: a scaffold for cellular coherence
1500-1515 Coffee Break
1515-1600 Bob Planque, qORAC: maintaining maximal metabolic rates using gene expression control
1600-1645 Aljosha Wahl, It takes 13C to see flux
1645-1730 Herwig Bachmann, The yield/rate trade-off and the selection of bacterial cells in water in oil emulsions
Title: deFBA: A dynamic optimization framework for metabolic regulation
Author list*: Bockmayr Alexander1; Lindhorst Henning2; Reimers Alexandra-M.1,3; Waldherr Steffen4.
1 Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 6, D-14195 Berlin, Germany.
2 Institute for Automation Engineering, Otto von Guericke University Magdeburg, Universitätsplatz 2, D-39106 Magdeburg, Germany.
3 International Max Planck Research School for Computational Biology and Scientific Computing, Max-Planck-Institut für molekulare Genetik, Ihnestraße 63-73, D-14195 Berlin, Germany.
4 Department of Chemical Engineering, KU Leuven, Celestijnenlaan 200F bus 2424, B-3001 Heverlee, Belgium.
* In alphabetical order
Email presenting author: Alexander.Bockmayr@fu-berlin.de
The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization techniques. However, metabolic adaptations driven by changes in gene expression cannot be analyzed by steady state models, as these models do not account for temporal changes in biomass composition.
In this talk, we present the dynamic optimization framework deFBA (dynamic enzyme-cost flux balance analysis) that integrates the metabolic network with the dynamics of biomass production and composition. An approximation by a timescale separation leads to a coupled model of quasi-steady state constraints on the metabolic reactions, and differential equations for the substrate concentrations and biomass composition. We propose a dynamic optimization approach to determine reaction fluxes for this model, explicitly taking into account enzyme production costs and enzymatic capacity. In contrast to the established dynamic flux balance analysis, our approach allows predicting dynamic changes in both the metabolic fluxes and the biomass composition during metabolic adaptations. Discretization of the optimization problem leads to a linear program that can be efficiently solved.
So far, deFBA has been successfully applied at genome scale to study the metabolite partitioning and glycogen dynamics under a diurnal cycle in a cyanobacterium. Furthermore, it is currently used in the Robustyeast project to study the optimal metabolic resource allocation of yeast cells in dynamically changing environments.
Title: Pathway swapping: a new approach to simply and efficiently remodel essential native cellular functions
Author list: Markus M.M. Bisschops, Francine Boonekamp, Jean-Marc Daran, Pascale Daran-Lapujade, Niels G.A. Kuijpers, Marijke A.H. Luttik, Jack T. Pronk, Daniel Solis-Escalante, Marcel van den Broek
Affiliations: Department of Biotechnology, Delft University of Technology, van der Maasweg 9, 2629 HZ, Delft, The Netherlands
Email presenting author: firstname.lastname@example.org
Abstract: Replacement of petrochemistry by bio-based processes requires microbes equipped with novel-to-nature capabilities. The efficiency of such engineered microbes strongly depends on their native metabolic networks which, forged by aeons of evolution, are complex and encoded by mosaic microbial genomes. The absence of a modular organization of genomes tremendously restricts genetic accessibility and presents a major hurdle for fundamental understanding and rational engineering of central metabolism. To eliminate this limitation, we propose and explore the concept of ‘pathway swapping’, using yeast glycolysis as the experimental model. Construction of a ‘single-locus glycolysis’ Saccharomyces cerevisiae platform enabled quick and easy replacement of this yeast’s entire complement of 26 glycolytic (iso-)enzymes by any alternative, functional glycolytic pathway configuration. The potential of this approach was demonstrated by the construction and characterization of S. cerevisiae strains whose growth depended on two non-native glycolytic pathways: a complete glycolysis from the related yeast S. kudriavzevii and a mosaic glycolysis consisting of yeast and human enzymes. This work demonstrates the feasibility and potential of modular, combinatorial approaches to engineering and analysis of core cellular processes.
Title: Intrinsic, periodic and tunable metabolic dynamics: a scaffold for cellular coherence
Author list: Alexandros Papagiannakis1; Bastian Niebel1; Ernst Wit2; Matthias Heinemann1
1 Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 4, 9747 AG Groningen, The Netherlands;
2 Probability and Statistics, Johann Bernoulli Institute of Mathematics and Computer Science, University of Groningen, Nijenborgh 9, 9747 AG Groningen, The Netherlands.
Email presenting author: email@example.com
The eukaryotic cell division is thought to be orchestrated by successive, strictly ordered waves of cyclins, and the periodic activity of the cyclin dependent kinase (CDK). However, the late advent of CDKs in the evolution of eukaryotes (1), together with the fact that cell cycle initiation occurs even in the absence of all early cyclins (2), as well as the previously reported oscillations in global transcription even during cell cycle arrest (3), suggest the existence of cell cycle regulators external to the cyclin/CDK machinery. A metabolic oscillator could operate as a global cell cycle regulator.
Using microfluidics in combination with single cell metabolite and cell cycle reporters, we found that yeast metabolism is an autonomous oscillator, which orbits across nutrients and different metabolic modes (e.g. respiration or fermentation), in synchrony with the cell cycle, but also in non-dividing cells. Using environmental perturbations and conditional depletion of cell cycle proteins, we found that the metabolic oscillator and the cyclin/CDK machinery form a system of coupled oscillators. In this system, the metabolic oscillator robustly gates the phase of the early and the late cell cycle, setting the duration of cell division in a nutrient dependent manner. A minimal metabolic frequency threshold must be reached for the cell cycle to START, separating dividing from non-dividing yeast cells when nutrients are poor, reminiscent to “the Warburg effect” and the altered metabolic phenotype of proliferating versus normal differentiated cells.
Cell cycle control is a higher order function emerging from the collective synchrony of coupled and mutually entrained oscillators, including the cyclin/CDK machinery and the autonomous metabolic oscillator. Because metabolic pathways are conserved across life kingdoms, the metabolic oscillator may constitute an ancestral regulator of cell division, and a potential therapeutic target against proliferative disorders.
Title: It takes 13C to see flux
Author list: Camilo Suarez-Mendez1; Robin Schumacher1; Aljoscha Wahl1
1 Delft University of Technology, van der Maasweg 9, 2629HZ Delft
Email presenting author: firstname.lastname@example.org
Abstract: Microbial growth and product formation are driven metabolism, the intracellular network of biochemical reactions and transport processes. While the stoichiometry is well characterized and can be measured in vitro, the metabolic flux can only be measured in living cells. To identify flux and obtain insights into metabolic regulation and single enzyme kinetics experimental and modeling approaches are needed that work in living systems. Combining dynamic experimental setups and current approaches in metabolomics and 13C tracing, cellular metabolism can be observed under different conditions. Of special interest are conditions that mimic relevant environments in the lab. We compared microbial metabolism ‘trained’ under dynamic conditions to single disturbances. The response of the yeast S. cerevisiae to a single shift from low to high substrate conditions is characterized by a significant drop in adenosine nucleotides and onset of ethanol production. A cell experiencing continuous perturbation reacts surprisingly different – there is no change in AxP’s and no ethanol production but rather an increase in energy charge with substrate addition while the single pulse lead to a significant drop. Carbon storage metabolism alone is not sufficient to buffer, it rather seems a combination of various pools in the network, including amino acids.
Title: Understanding the regulation of glycolysis under dynamic conditions
Author list: Rick Nijhout, Daan de Groot, Dennis Botman, Phillipp Schmidt, Philipp Savakis, Angelica Rodriguez Prado, Johan van Heerden, Frank Bruggeman and Bas Teusink1
1 Systems Bioinformatics, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, The Netherlands
Email presenting author: email@example.com
Microorganisms, including Baker’s yeast, have to cope with dynamic environments, either predictable ones caused by the organism’s own metabolism such as diauxie, or sudden transitions in nutrient availability or stress. Glycolysis, as a central pathway from which many routes branch out towards biosynthesis and production of stress protectants, thus needs to be able to accommodate dynamic demands of its products. We study the regulation of the glycolytic pathway from such a dynamic perspective; we hypothesize (and demonstrated before) that many regulatory mechanisms have developed to cope specifically to navigate between transitions.
Because transitions can result in subpopulations – due to bistability in glycolysis, energetic constraints or heterogeneity in response times- we are developing tools to study glycolysis not only at the population level, but also at the single cell level. This includes microfluidic devices, flow cytometry, FRET-based metabolite sensors and RNA-FISH techniques. We furthermore develop theory and modeling to understand the functional and evolutionary implications of regulatory strategies.
One of the focus areas is on the role of fructose 2,6-bisphosphate in nutrient transitions. Mutants in F26bP metabolism do not show an appreciable phenotype at steady state, but the mutations do impact on the dynamics during transitions. For example, like with trehalose metabolism mutants, we see an impact on subpopulation structure upon addition of glucose. The aim is to define the function of this system, for which a number of hypotheses are currently described1.
Title: qORAC: maintaining maximal metabolic rates using gene expression control
Author list: Bob Planqué1; Joost Hulshof1; Johan Hendriks; Bas Teusink2; Frank J. Bruggeman2
1 Department of Mathematics, Vrije Universiteit Amsterdam, De Boelelaan 1081, 1081 HV Amsterdam, The Netherlands.
2 Systems Bioinformatics, Vrije Universiteit Amsterdam, location code O2:2E51, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands.
Email presenting author: firstname.lastname@example.org
Many evolutionarily successful bacteria attain high growth rates in different growth-permissive conditions. They express metabolic networks that synthesise all cellular components at a high rate. Metabolic reaction rates are bounded by the concentration of the catalysing enzymes and cells have finite resources available for enzyme synthesis. Therefore, bacteria that grow fast should express needed metabolic enzymes at precisely tuned concentrations. To maintain fast growth in a dynamic environment, cells should adjust gene expression of metabolic enzymes.
The activity of many of the associated transcription factors is regulated by their binding to intracellular metabolites. We study optimal metabolite-mediated regulation of metabolic-gene expression that preserves maximisation of metabolic fluxes across varying conditions. We logically derive the underlying control logic of this type of optimal regulation, which we term `Specific Flux (q) Optimization by Robust Adaptive Control’ (qORAC), and illustrate it with several examples. We show that optimal metabolic flux can be maintained in the face of K changing parameters only if the number of transcription-factor-binding metabolites is at least equal to K. qORAC-regulation of metabolism can generally be achieved with basic biochemical interactions, indicating that metabolism can operate close to optimality.
If time permits, I will also present some new work on a new version of qORAC, in which the growth rate itself is dynamically optimised, rather than the specific flux. This does not use EFMs as the building blocks of metabolism, but so-called EGMs (Elementary Growth Modes).
Title: The yield/rate trade-off and the selection of bacterial cells in water in oil emulsions
Author list: Herwig Bachmann1,2, Iraes Rabbers1, Bas Teusink1, Frank Brugeman1
1VU University, Amsterdam, The Netherlands; 2 NIZO B.V., Ede, The Netherlands
Email presenting author: email@example.com
Abstract: Tradeoffs are described to be of importance for the phenotypic properties of an organism. A well-described example in microbiology is a negative correlation between growth rate and biomass yield. During laboratory evolution experiments, which are often carried out in spatially unstructured suspension cultures, this trade-off is typically observed by the selection of mutant cells with increased growth rates but lower biomass yields.
We were able to show that the introduction of spatial structure, through repetitive culturing of individual cells in the droplets of a water-in-oil emulsion, allowed for the selection of mutants with lower growth rates and a higher biomass yield. This is possible because substrate competition between cells is eliminated, which permits also slow growing variants to reach the maximum carrying capacity in each droplet. While experimental evolution in emulsion lead to the isolation of strains with increased biomass yield, it is important to realize that the selection pressure in this culturing system is on the number of viable offspring. For instance a decrease in cell size can lead to a higher number of offspring without a change in the biomass yield. Examples of evolved L. lactis and E. coli strains will be discussed with a focus on the role of cell size and its implications on cellular fitness in different environments.
Title: Cellular memory in the lag phase under fluctuating carbon environments
Author list: Cerulus Bram1,2; Perez-Samper Gemma1,2; Jariani Abbas1,2; Verstrepen Kevin1,2
1 VIB Center for Microbiology, Lab of Systems Biology, Gaston Geenslaan 1, B-3001 Leuven, Belgium.
2 CMPG Laboratory of Genetics and Genomics, Department M2S, KU Leuven, Gaston Geenslaan 1, B-3001 Leuven, Belgium.
Email presenting author: firstname.lastname@example.org
Many organisms, including the baker’s yeast S. cerevisiae, extract energy and building blocks from sugars or other carbon sources. While yeast is able to grow on a wide range of carbon sources, it shows a strong preference for glucose. As a result, however, shifts to alternative carbon sources often involve a period of delayed growth, called the lag phase.
We and others have shown that the lag phase length is dependent on the growth conditions before the transfer to the alternative sugar. Specifically, the longer cells are grown on glucose, the longer the lag phase becomes. Here, we investigate the molecular mechanisms that might explain this type of cellular memory.
It has previously been argued that the catabolic proteins required for growth on the alternative sugar can persist in the cytoplasm, allowing rapid re-induction of these genes and initiation of growth. However, we show that cellular memory occurs to the same extent when these genes were not expressed prior to glucose growth. Moreover, we find that many proteins involved in other functions (such as respiration) are induced early on during the lag phase, long before the induction of the alternative sugar’s catabolic genes. Interestingly, the timing and magnitude of induction of the former group of genes is predictive of the lag time of single cells. Finally, we have performed a genome-wide screen for gene-deletion mutants which have altered lag times. We find that the set of deletion mutants with increased lag times compared to the wild-type is highly enriched for mitochondrial genes and genes involved in respiration. Together, these results indicate that remodeling of general energy metabolism during glucose growth contributes to cellular memory in the lag phase during shifts between carbon sources.