Internships
We are always looking for talented bachelor and master students who are interested in origins of life, synthetic cells, coacervates, physical biology, big data and machine learning or multi-omics analysis methods, who like to work in an interdisciplinary cutting-edge environment. If you are interested in joining, please contact us here, or approach one of the members of the group directly.
Development of high- throughput platforms for cancer diagnosis
The goal of this project is to develop a high-throughput fluidic platform for single-cell detection of cells contributing to the metastatic process. You will work on a platform that will provide a breakthrough technology for future downstream single-cell multi-omics analysis and for monitoring of treatment efficacy in cancer patients.
Keywords: Microfluidics, Cell culture, Flow cytometry, Sequencing, -omics, Patients’ material
Supervisors: Kinga Matuła, Francesca Rivello
Construction of a noise-cancelling enzymatic reaction network
The goal of this project is to realize the construction of a noise-cancelling enzymatic reaction network under out-of-equilibrium conditions. Throughout the project, you will work at the interface of organic synthesis, flow-chemistry, enzymology and photocatalysis.
Keywords: Microfluidics, synthesis (SPPS, Schlenk techniques), Flow chemistry, Kinetics
Supervisors: Michael Teders
Studying dynamics of cell response using single-cell omic tools
The aim of this project is to further our understanding of how biochemical information flows through cells upon external, dynamic stimulation (e.g. drugs) and during disease progression. You will work on the development and application of a platform for single-cell (phospho)proteome and transcriptome analysis to study cell response.
Keywords Microfluidics, Cell culture, data analysis, -omics, Biochemistry, Molecular biology, Flow cytometry, Immunoassays, Sequencing, Patients’ material
Supervisor Kinga Matuła, Jessie van Buggenum, Francesca Rivello, Erik van Buijtenen, Melde Witmond
Building a synthetic cell: reconstituting E. coli’s proteome in a cell-free system
To build a synthetic cell it is important to know if cell-free protein expression can be performed on a genome wide scale. Therefore, the aim of the project is to visualize and compare, using non-natural amino acid incorporation and 2D gel electrophoresis, the proteome expressed from E. coli genomes both in cells (in vivo) as well as cell-free (in vitro).
Keywords Cell-free expression, 2D gel Electrophoresis, Click chemistry, Bacterial cell culture, Lysate Fabrication, Genome isolation
Supervisor Andrei Sakai, Roel Maas
Analysis of single-cell sequencing results and implementation of new tools
The aim of this project is to develop, combine and use state-of-the art bioinformatics tools for single-cell multi-omics analysis. In particular, we are interested in understanding how biochemical information flows through cells upon external stimulation (e.g. drugs) and during disease progression. To study cell response, sequencing results will be generated using a platform for single-cell (phospho)proteome and transcriptome analysis.
Keywords Bioinformatics, Single-cell omics
Supervisor Francesca Rivello, Jessie van Buggenum, Melde Witmond
Constructing a glucose dependent neuron
In this project you will be working on building an artificial neuron, the smallest unit of a neural network, making use of enzymes and photoprotected glucose. It will be your job to synthesize a photoprotected glucose, to measure the rate constants and to make a model of the neuron itself.
Keywords Molecular computing, Carbohydrate synthesis, Enzymes, Neuron
Supervisor Jeroen van de Wiel
Studying bacterial protein coacervation in vitro, in droplets, and in liposomes
In this project, we aim to explore several (confirmed) candidate proteins involved in bacterial liquid-liquid phase separation (LLPS) in an in vitro setting. Proteins will be purified, and their phase behaviour will be investigated in vitro, in droplets, and in liposomes. This project is part of a larger collaborative effort to investigate bacterial LLPS.
Keywords Biochemistry, Enzyme purification, NusA, DPS, FtsZ, Microfluidics, IVTT
Supervisor Ludo Schoenmakers
Synthetic cell construction in Giant Unilamellar Vesicles (GUVs)
In this project, we aim at constructing synthetic cell-like structures in Giant Unilamellar Vesicles (GUVs) using a number of different approaches. The key aim is to realize robust communication between the inside and outside environment of synthetic cells by way of the membrane protein inserting membrane protein: the Sec translocon.
Keywords Synthetic biology, GUV formation, Microfluidics, Membrane protein insertion, IVTT
Supervisor Ludo Schoenmakers
Exploring chemotypic diversity in prebiotic reaction networks.
The self-organisation of reaction pathways from abiotic precursors was a vital component in the transition from inanimate to animate matter. In this project, we wish to understand the principles for how abiotic environments shaped the development of modern biochemical pathways. You will explore the incorporation of redox reactions and alpha-ketoacids into the formose reaction.
Keywords Prebiotic chemistry, Reaction networks, Kinetics, Data analysis, Air sensitive handling, HPLC, GC-MS, Machine learning methods
Supervisor Will Robinson, Peer van Duppen, Elena Daines
Uniting Metabolism and Information Replication at the Origins of Life
In the biochemistry of extant Life there is an intimate link between metabolism and information replication+transfer found in ribonucleotides and their reactions. In this project we aim to trace this link all the way back to the origins of Life by constructing oligonucleotide-based chemical reaction networks that can demonstrate both metabolic and information replication functions.
Keywords Prebiotic Chemistry, (Oligo)Ribonucleotides, Chemical Reaction Networks, PAGE gels, Mass Spectrometry
Supervisor Oliver Maguire
Environmental dynamics as a driving force for the organization of chemical reaction networks
The network of metabolic reactions in Life is postulated to find its origin in prebiotic waters, in the absence of sophisticated enzymes or genetic inheritance. We hypothesize environmental dynamics were a fundamental driving force for the organization of chemical reaction networks. In this project, you will simulate a changing environment by imposing temporal patterns on the network via modulation of the inflow profile of catalyst or feedstock molecules.
Keywords Origin of life, Chemical reaction networks, Flow chemistry, Python modelling, HPLC, GC-MS, Python, Machine learning
Supervisor Peer van Duppen