UPDATE ON THE 2021 Systems Biology lab INTERNSHIPS (Bachelor and Master) – November 15th 2020
To comply with the VU Corona regulations, the Systems Biology group established a maximum number of experimental internships students that can be safely hosted in the lab.
For the period from February 2021 to July 2021 all available positions are now filled. Thus, we cannot accept any more students.
Summer internship positions are still available.
Students can do various types of projects in our lab. We supervise bachelor and master internship projects but you can also find supervisors for your literature thesis. Practical internships can be in the wet lab (here termed experimental) , can be computational (here termed theoretical) or can consist of a combination of those two. All of them qualify as ‘research internships’ in virtually all of the study programs.
Below is a list of projects that we thought of. If you are interested in one, just contact the person that is associated to that project. But there are options beyond this list. Check the Team and the Projects pages and click on the different team members to see their lines of research. If you are interested in a specific topic that we work on, but do not see an internship within that project listed below, just contact the team member and check for the possibilities. This is especially relevant if you are looking for a literature thesis project – these are usually tailor-made based on your interests.
If you have general questions about internships in our department see the contact information at the end of the page
|Project title||Type of research||Supervisor(s)|
|Production of cultured red blood cells for transfusion purposes: analysis of metabolomics data to achieve high cell density erythroblast cultures||Theoretical (Master)||Jurgen Haanstra (in collaboration with Sanquin)|
|Transfusion of donor-derived red blood cells (RBC) to alleviate anemia is the most common form of cellular therapy. In addition, red blood cells hold great promise as delivery agents of e.g. specific drugs or enzymes. However, the availability of transfusion units depends on volunteers and carries a potential risk of alloimmunization and blood borne diseases. More than 30 bloodgroup systems encode >300 bloodgroup antigens and bloodgroup matching becomes increasingly challenging in a multiethnic society. Particularly the chronically transfused patients are at risk for alloimmunisation. In vitro cultured, customizable red blood cells (cRBC) would negate these concerns and introduce precision medicine both in transfusion medicine as well as in drug delivery applications. We aim to produce human cRBC at large-scale and cost effective, for which we need to optimize culture conditions and reduce cost-drivers.
Transfusion-ready erythrocytes can be cultured from hematopoietic progenitors but at market-incompatible high costs. A limitation in maximum cell density, 2 million cells/mL, has been observed in in vitro erythroblast expansion. Understanding the origin of this cell density limitation may provide strategies, both at media composition and feeding regime levels, to facilitate economically feasible upscaling.
Analysis of cell-conditioned media indicated that small molecules (<3kDa) are responsible for growth limitation. A metabolic by-product may be the culprit. Alternatively, or in addition, depletion of nutrients may also contribute to the growth stop. Therefore we aim to analyse the metabolic activity of erythroblasts with the aim to adapt the media such that cells can be cultured at much higher densities.
We have produced transcriptome and proteome data from which we can deduce the metabolic pathways that are active in our erythroblast cultures. We also determined metabolic profiles of erythroblasts seeded in defined medium, and the corresponding profiles of the medium, and sampled at timepoints 0, 12, 24 and 36 hours.
In this project you are going to use the genome-scale reconstruction of human metabolism. The transcriptome and proteome data will be used to restrict the enzymes in this model to what is actually expressed in erythroblasts. The measured metabolic profiles will be either used as input to understand internal flux distributions and elucidate potential unwanted byproducts - or to compare them to predictions of flux distributions that would give optimal growth. Furthermore, investigating theoretical flux profiles that would give high growth rates (i.e. biomass production) will reveal options to adjust the culture media.
We are looking for an enthusiastic Master student with a bioinformatics background and an interest in metabolic networks
This project will be conducted in close cooperation between Sanquin Research, dept Hematopoiesis, and the Amsterdam Institute of Molecular and Life Sciences (AIMMS), Systems Biology Lab.
|Integration of quantitative multi-omics data into genome-scale metabolic models||Theoretical (Master)||Pranas Grigaitis
Eunice van Pelt-KleinJan (email@example.com)
|Computational models of microbial metabolism are useful tools in biotechnology and medical sciences due to their ability to predict and analyze microbial cell behavior in silico. Stoichiometric modeling is an attractive technique to use knowledge-bases to aid analysis of microbial metabolism at genome-scale level. However, these models have limited predictive power in a number of situations due to the assumption of analyzing (1) optimally-functioning networks in (2) a steady state, fully driven by reaction stoichiometry. Recent approaches to improve the predictions of these models usually rely on the detailed descriptions of protein turnover costs (proteome-constrained, pc-Models), and would provide a platform to aid the model by using quantitative -omics data.
In this project, we want to develop a framework of straightforward and standardized integration of multiple types of -omics data, namely, transcriptomics, proteomics and fluxomics.
Planned activities (and methods)
- Automatizing the integration of RNA-seq and mass spectrometry-driven label-free quantitative proteomics experiments into pcModels of Saccharomyces cerevisiae, Lactococcus lactis and/or Schizosaccharomyces pombe (scripting: Python, bash)
- Simulation of cross-condition pcModels on both local machine and compute cluster (Lisa/SURFsara) and biological interpretation of the resulting simulation results (scripting: Python, bash; data analysis: Python, R)
Internships are in principle open for students from other universities in the Netherlands or outside the Netherlands. We welcome for example ERASMUS students. Please note a few things:
If you are a non-VU student and from abroad you should contact Dr. Rob van Spanning (firstname.lastname@example.org) if you want to do an internship in our group, and indicate your preferred project(s), starting date, length of internship, and how you will support yourself (costs for food, accommodation), as we are unable to support you financially.
VU students and other Dutch students can contact the putative internship supervisor directly.