PhD Projects
Challenge 1: Enzyme catalysis at the polymer surface
Glycogen is a glucose-based polymer, comprising linear and branched components in a tree-like arrangement. Hence, an enzyme acting upon glycogen can cleave or rearrange the polymer backbone at multiple sites. The challenge will be to develop novel experimental and computational tools that can resolve spatiotemporal aspects of enzyme catalysis at the complex polymer surface and apply these to clinical samples and data to identify bottlenecks and therapeutic targets.
Kinetic analysis of enzymes of glycogen metabolism
Host organisation: University of Manchester, UK
The PhD student will implement methods to generate gold biosensor chip and nanoparticles for the presentation of glycogen mimetic surfaces. These novel glyconanomaterials will be used both for kinetic analysis of the enzyme modification of glycopolymers, using surface plasmon resonance, and for the assessment of the impact of enzyme action on glycogen structure, by transmission electron microscopy.
Structural analysis of glycogen from in vitro models and patients with Glycogen Storage Diseases
Host organisation: Iceni Diagnostics, Norwich UK
The PhD student will develop and implement analysis tools to assess the structural features of glycogens associated with glycogen storage disease from cell culture, organoids and patient samples. Using NMR, mass spectrometry and HPLC methods, the PhD student will determine polymer length, positions and number of branching points, and extent and position of phosphorylation.
Mathematical modelling of glycogen metabolism and glycogen-related disorders
Host organisation: Heinrich Heine Universität Düsseldorf, DE
The PhD student will develop a computational model to study overall dynamics of glycogen formation and analyse which parameters determine the structural properties of glycogen, such as branching pattern and size. The PhD student will reproduce metabolic disorders related to glycogen metabolism and develop intervention strategies how to counteract glycogen-related metabolic disorders by drug applications.
Challenge 2: Combinatorial explosion of molecular species
Classically, enzymes are thought to have a specific affinity for one well-defined substrate. In contrast, enzymes acting on larger molecules catalyse the conversion of a functional group in the substrate with a lesser specificity for the remaining part of the molecule. This promiscuity results in a combinatorial explosion of different molecular species, particularly in lipid metabolism. The challenge is to develop innovative analytical methods and genome-scale modelling approaches to analyse and interpret complex lipid profiles in a meaningful way, and apply these to clinical samples and data to identify novel causes of patient-to-patient variability.
Quantitative and miniaturised assays for structure-resolved lipidomics
Host organisation: Leiden University, NL
The PhD student will develop novel analytical methods for lipid profiling, and thereby will focus on detailed analysis of modified lipidsand to identify structural isomers.This will be achieved using hydrophilic interaction chromatography (HILIC) or normal phase liquid chromatography (NPLC)-based separation coupled to a reversed-phase liquid chromatography (RPLC)-mass spectrometry analysis. The methods developed will be miniaturised to allow the analysis of biomass-limited samples, such as patient-derived iPS hepatocytes or organ-on-a-chip samples.
Development of in vitro liver models for inborn errors in glycogen and fatty-acid metabolism
Host organisation: MIMETAS, Leiden NL
The PhD student will develop 3D liver-on-chip for Glycogen Storage Diseases type I (GSD I) and or fatty-acid oxidation deficient patients (CRISPR-Cas). Organ-on-chips are microfluidic devices for culturing living cells in continuously perfused, micrometer-sized chambers, such that they maintain tissue- and organ-level functions. Subsequently, the PhD student will develop proteomics and lipidomics protocols for these cultures in collaboration with expert partners.
Stoichiometric modularisation of combinatorial lipid metabolism
Host organisation: National University of Ireland, Galway IE
The PhD student will develop a novel approach to represent promiscuous enzymes (enzymes acting on lipid classes rather than on single lipid species) more efficiently in a genome-scale model (GEM). This innovation will be implemented in a comprehensive genome-scale model of human metabolism. The PhD student will map lipidomics data in the metabolic network analyse computationally different disease specific scenarios.
Challenge 3: Pathway dynamics
If enzymes catalyse multiple reactions, alternative substrates compete with each other for binding to the enzyme, thereby inhibiting each other’s conversion. This implies that only a fraction of the total enzyme capacity is used for a specific reaction. At the level of metabolic pathways and networks this causes feedback and feedforward inhibition and may lead to complex dynamics, which has hitherto hardly been explored. The challenge will be to develop novel experimental tools and computational models to analyse the impact of substrate competition on pathway dynamics, and apply these to patient samples and data to identify putative therapeutic targets
Instability of glucose production in fatty-acid oxidation defects
Host organisation: University Medical Centre Groningen, NL
The PhD student will formalise competing hypotheses for the origin of hypoglycaemia in mitochondrial fatty-acid oxidation (mFAO) defects by constructing a dynamic computational model based on detailed enzyme kinetics. Based on the model the PhD student will investigate mechanisms to rescue the disease phenotype. The model predictions will be experimentally tested in mFAO-deficient cell lines and patient-derived cell cultures.
Interplay between coenzyme and energy metabolism in fatty-acid oxidation defects
Host organisation: University of Bergen, NO
The PhD student will identify alterations of NAD and CoA coenzyme metabolism in mitochondrial fatty-acid oxidation (mFAO) deficient liver cells. Furthermore, the PhD student will modulate the availability of these coenzymes by pharmacological and genetic interventions and analyse the impact on energy metabolism, using metabolomics and 13C-fluxomics. The interventions will be done in cell cultures of mFAO-deficient hepatocytes or patient-derived fibroblasts.
Dynamic computational modelling of lipid synthesis and storage in the human liver
Host organisation: Heinrich Heine Universität Düsseldorf, DE
The PhD student will focus on construction and validation of a dynamic computational model of lipid synthesis based on ordinary differential equations and detailed kinetic data. Patients with defects in the mitochondrial fatty-acid oxidation (mFAO) accumulate acyl-CoA esters which are substrates for chain elongation into longer lipids. The PhD student will connect the lipid synthesis model to an existing and experimentally validated mFAO model and explore pathway stability and lipid profiles in various mFAO disorders and at different diets.
Dietary interventions and compensatory substrate switch in fatty-acid oxidation defects
Host organisation: Universitätsklinikum Freiburg, DE
The PhD will test the protective effects of dietary and exercise interventions on a severe mitochondrial fatty acid oxidation (mFAO) disorder in a mouse model of this disease. Substrate switching between fatty acids and carbohydrates may compensate a clinical phenotype. Enzyme activity measurements, characterization of the metabolome and proteome will be performed in order to identify tissue adaptation. In addition, the PhD will collect existing clinical and biochemical knowledge to allow realistic simulation of disease mutations and dietary, medical and environmental interventions.
Challenge 4: Spatial and hierarchical regulation
Metabolic fluxes and metabolite homeostasis are regulated extensively through gene expression and signalling. Unlike metabolism of small molecules, which diffuse readily through the cell, biopolymer metabolism also depends on spatial regulation. Recently, the physiological importance of autophagy-like pathways for glycogen and lipid metabolism has become apparent. The challenge is to develop novel experimental and computational methodologies to follow polymers in the cell and to integrate this spatial regulation with classical levels of regulation, potentially identifying novel mechanisms for patient-to-patient variability
Multi-level regulation of metabolism in fatty-acid oxidation defects
Host organisation: University Medical Centre Groningen, NL
The PhD student will measure 13C fluxomics, quantitative targeted proteomics, metabolomics, and autophagic flux in cell cultures of patient-derived fibroblasts or lymphoblasts available from the different clinical partners in the project. Interesting cases will be selected for RNASeq and development of organ-on-chip liver cultures. The results will be incorporated in the dynamic model of mitochondrial fatty-acid oxidation and a genome-scale model of human metabolism.
Directing signal transduction pathways to establish novel therapies for glycogen storage disease type I
Host organisation: University Medical Centre Groningen, NL
The PhD student will study the interplay between glucose-sensitive signal transduction, hepatic glycogen and lipid metabolism, autophagy, and transcription in Glycogen Storage Disease type I mouse models. The PhD student will measure lipid and carbohydrate fluxes by stable-isotope labelling in mice and link this to regulation at the transcriptome and proteome level. The effect of mTOR signalling and autophagy of glycogen (glycophagy) on hepatic glucose production and lipid accumulation will be assessed using a liver-specific mTOR knockout mouse and established interventions to activate glycophagy. To assess patient-to-patient variation, the PhD student will analyse key metabolic readouts in patient-iPS-derived hepatocytes.
The role of autophagy and mTOR signalling in inborn errors of glycogen metabolism in hepatocytes
Host organisation: Carl von Ossietzky Universität Oldenburg (DE) and University of Innsbruck (AT)
The PhD student will study altered signalling in Glycogen Storage Disease type I in mechanistic detail. In particular, the candidate will dissect mechanisms via which disease-specific accumulation of metabolites affects autophagy downstream of the metabolic master regulators mTOR (mammalian target of rapamycin) and its antagonist AMPK (AMP-dependent kinase) in hepatocytes. The PhD student will rely on an extensive set of experimental tools for imaging and protein/ metabolite biochemistry. Published computational dynamic models of the AMPK-mTOR-autophagy network will be expanded with targeted and shotgun quantitative proteomic data, to unravel the dynamic fine tuning and discover new key regulators of autophagy in Glycogen Storage Disease type I.
Integrations of genome-scale models with signalling networks
Host organisation: KTH Royal Institute of Technology, Stockholm SE
The PhD student will develop new methods to connect computational models of the signalling networks to genome-scale models and exploit methods developed previously by the host organisation to incorporate information on transcriptome, proteome and protein-protein interaction networks. Based on specific data for Glycogen Storage Disease (GSD) and mitochondrial fatty-acid oxidation (mFAO) defects the PhD student will predict which hitherto unknown signalling pathways or transcription factors may be implicated in GSDs and mFAO defects.
Challenge 5: Data and model management
A key challenge in Systems Medicine research is making the extremely diverse data FAIR. FAIR means Findability, Accessibility, Interoperability and Reusability of data. Within this project we base ourselves on the FAIRDOM Hub, a platform for FAIR data, and explore improving the Findability of data using information retrieval methods. How can we enable users to store their results in a way that the results are most easily found, even if the query is imprecise?
Data and model management and information retrieval
Host organisation: HITS gGmbH, Heidelberg DE
The PhD student will provide FAIR data management services to the PoLiMeR consortium based on the FAIRDOM Hub (the data sharing site hosted at HITS) and on GitLab. The PhD student will use the database generated in the PoLiMeR project together with pre-existing and public data to determine how changes in data collection, metadata quality and data feature extraction affect the information that can be found. The PhD student will seek to improve existing tools for data collection as well as querying at critical points.
