Waves, ChIPs, GEMMs, gears, markers and maps:Computational systems biology from cell cycle oscillations to metabolic fluxes

This thesis discusses six scientific works within the fields of systems biology and bioinformatics. These works are unified in their conception of the cell as a system of integrated fluxes of mass and information, in the application of computational approaches to answer the questions at hand and in their aim for computation to drive new biological discoveries. The overarching theme is that by bringing computational methodologies in contact with quantitative experimental data, new principles can be proposed and/or tested that would not otherwise have been discovered. The first three chapters of this thesis focus on (the cell cycle of) budding yeast. Specifically, Ch. 2 deals with kinetic models for waves-of-cyclins. Ch. 3 concerns analysis of ChIP-exo experiments to retrieve the specific binding sites at gene promoters where Forkhead transcription factors Fkh1 and Fkh2 bind. Ch. 4 presents a web-based database and visualization tool which integrates a variety of sources of information concerning all protein-coding genes and allows users to craft specific and visualizations of the topology of interaction networks. The last three chapters of this thesis focus on that other process by which life produces more of itself: metabolism. Specifically, our focus is on thermodynamics and metabolic networks in acetogenic bacteria (Ch. 5) and human liver (Ch. 6-7). Ch. 5 is concerned with the concept of gear-shifting: an organism's hypothetical ability to express metabolic enzymes that result in different stoichiometric yields in order to navigate a trade-off between rate and yield. In Ch. 6 and 7 we discuss two approaches to deal partially with concentrations in flux balance analysis, i.e. in terms of serum concentrations of biomarkers (Ch. 6) and in terms of uptake fluxes and concentrations of medium metabolites and metabolic enzymes (Ch. 7). The six chapters present new datasets, provide novel tools, develop new models, propose novel (extensions of) computational methodologies and rationalize and assess existing methodologies. As such, this thesis provides a glance into the cutting-edge of biomedical research in this data-driven, computation-assisted age

Waves, ChIPs, GEMMs, gears, markers and maps: Computational systems biology from cell cycle oscillations to metabolic fluxes

This thesis discusses six scientific works within the fields of systems biology and bioinformatics. These works are unified in their conception of the cell as a system of integrated fluxes of mass and information, in the application of computational approaches to answer the questions at hand and in their aim for computation to drive new biological discoveries. The overarching theme is that by bringing computational methodologies in contact with quantitative experimental data, new principles can be proposed and/or tested that would not otherwise have been discovered. The first three chapters of this thesis focus on (the cell cycle of) budding yeast. Specifically, Ch. 2 deals with kinetic models for waves-of-cyclins. Ch. 3 concerns analysis of ChIP-exo experiments to retrieve the specific binding sites at gene promoters where Forkhead transcription factors Fkh1 and Fkh2 bind. Ch. 4 presents a web-based database and visualization tool which integrates a variety of sources of information concerning all protein-coding genes and allows users to craft specific and visualizations of the topology of interaction networks. The last three chapters of this thesis focus on that other process by which life produces more of itself: metabolism. Specifically, our focus is on thermodynamics and metabolic networks in acetogenic bacteria (Ch. 5) and human liver (Ch. 6-7). Ch. 5 is concerned with the concept of gear-shifting: an organism's hypothetical ability to express metabolic enzymes that result in different stoichiometric yields in order to navigate a trade-off between rate and yield. In Ch. 6 and 7 we discuss two approaches to deal partially with concentrations in flux balance analysis, i.e. in terms of serum concentrations of biomarkers (Ch. 6) and in terms of uptake fluxes and concentrations of medium metabolites and metabolic enzymes (Ch. 7). The six chapters present new datasets, provide novel tools, develop new models, propose novel (extensions of) computational methodologies and rationalize and assess existing methodologies. As such, this thesis provides a glance into the cutting-edge of biomedical research in this data-driven, computation-assisted age

Systems Pharmacology: An opinion on how to turn the impossible into grand challenges

A pharmacology that hits single disease-causing molecules with a single drug passively distributing to the target tissue, was almost ready. Such a pharmacology is not (going to be) effective however: a great many diseases are systems biology diseases; complex networks of some hundred thousand types of molecule, determine the functions that constitute human health, through nonlinear interactions. Malfunctions are caused by a variety of molecular failures at the same time; rarely the same variety in different individuals; in complex constellations of OR and AND logics. Few molecules cause disease single-handedly and few drugs will cure the disease all by themselves when dosed for a limited amount of time. We here discuss the implications that this discovery of the network nature of disease should have for pharmacology. We suggest ways in which pharmacokinetics, pharmacodynamics, but also systems biology and genomics may have to change so as better to deal with systems-biology diseases

Learning to read and write in evolution: From static pseudoenzymes and pseudosignalers to dynamic gear shifters

We present a systems biology view on pseudoenzymes that acknowledges that genes are not selfish: the genome is. With network function as the selectable unit, there has been an evolutionary bonus for recombination of functions of and within proteins. Many proteins house a functionality by which they 'read' the cell's state, and one by which they 'write' and thereby change that state. Should the writer domain lose its cognate function, a 'pseudoenzyme' or 'pseudosignaler' arises. GlnK involved in Escherichia coli ammonia assimilation may well be a pseudosignaler, associating 'reading' the nitrogen state of the cell to 'writing' the ammonium uptake activity. We identify functional pseudosignalers in the cyclin-dependent kinase complexes regulating cell-cycle progression. For the mitogen-activated protein kinase pathway, we illustrate how a 'dead' pseudosignaler could produce potentially selectable functionalities. Four billion years ago, bioenergetics may have shuffled 'electron-writers', producing various networks that all served the same function of anaerobic ATP synthesis and carbon assimilation from hydrogen and carbon dioxide, but at different ATP/acetate ratios. This would have enabled organisms to deal with variable challenges of energy need and substrate supply. The same principle might enable 'gear-shifting' in real time, by dynamically generating different pseudo-redox enzymes, reshuffling their coenzymes, and rerouting network fluxes. Non-stationary pH gradients in thermal vents together with similar such shuffling mechanisms may have produced a first selectable proton-motivated pyrophosphate synthase and subsequent ATP synthase. A combination of functionalities into enzymes, signalers, and the pseudoversions thereof may offer fitness in terms of plasticity, both in real time and in evolution

Maps for when the living gets tough: Maneuvering through a hostile energy landscape

With genome sequencing of thousands of organisms, a scaffold has become available for data integration: molecular information can now be organized by attaching it to the genes and their gene-expression products. It is however, the genome that is selfish not the gene, making it necessary to organize the information into maps that enable functional interpretation of the fitness of the genome. Using flux balance analysis one can calculate the theoretical capabilities of the living organism. Here we examine whether according to this genome organized information, organisms such as the ones present when life on Earth began, are able to assimilate the Gibbs energy and carbon that life needs for its reproduction and maintenance, from a relatively poor Gibbs-energy environment. We shall address how Clostridium ljungdahlii may use at least two special features and one special pathway to this end: gear-shifting, electron bifurcation and the Wood-Ljungdahl pathway. Additionally, we examined whether the C. ljungdahlii map can also help solve the problem of waste management. We find that there is a definite effect of the choices of redox equivalents in the Wood-Ljungdahl pathway and the hydrogenase on the yield of interesting products like hydroxybutyrate. We provide a drawing of a subset of the metabolic network that may be utilized to project flux distributions onto by the community in future works. Furthermore, we make all the code leading to the results discussed here publicly available for the benefit of future work