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Below, you can find the updated list of Bachelor and Master internships available at the moment.
Jurgen Haanstra – j.r.haanstra[at]vu[dot]nl
(All positions starting FEB 2023 for ‘Metabolism in Health and Disease’ are filled)
Herwig Bachmann – firstname.lastname@example.org
Remco Kort – email@example.com
|Project title||Type of research||Supervisor(s)|
|Literature survey on how distinct dietary fibres can affect microbiome composition||Literature thesis (Bachelor or Master)||Prof, Remco Kort (firstname.lastname@example.org)|
|KeepFoodSimple ( https://keepfoodsimple.nl) is looking for a student Food Science or related fields of study who is interested in an internship studying the relation between type or chemical structure of food fibre and its effect on the composition of the microbioom. A further questions is: what is the effect of combinations of different types of fibre on the composition of the microbioom. Fibre in this context is defined as non-digestible oligo- and poly saccharides. This study will also include an evaluation of the various methods to establish microbioom composition. If possible this study will be linked to ongoing experiments on the relation between fibre type and microbioom composition.
This internship will be guided by prof. dr. Remco Kort, Microbiology, Free University Amsterdam and Fons Voragen Em. prof. of Food Chemistry, Wageningen University & Research. Start coming months.
KFS will pay a compensation of 250€ per month.
Literature survey on how distinct dietary fibres can affect microbiome composition
It is well known that dietary fibers have a positive effect on gut and metabolic health. They slow down gastric emptying and reduce sugar response after eating.
They thicken the contents of the intestinal tract, causing a better stool consistency which help removing potentially toxic metabolites from the colon.
The fibers are also important substrates for a wide range of gut bacteria. These bacteria produce various short chain fatty acids that strengthen the gut membrane, stimulate immune response and affect lipid, glucose and cholesterol metabolism in various tissues. Regular high consumption of dietary fibers result in a very diverse microbiome and it suppresses pathogenic bacteria that excrete carcinogenic metabolites.
These insights have led to a general recommendation to consume at least 30 to 40 grams of dietary fibers per day. However, food scientist and dieticians have not yet specified what particular type of fibre and what mix has the most beneficial health effect.
Various studies have shown that different types of fibers stimulate different groups of bacteria, leading to different metabolic effects. Arabinoxylans, for instance, stimulate growth of the bacterial genera Bifidobacterium and Akkermansia. This is much less so with inulin. Different types of pectins have different physiological effects. Rhamnogalacturonan 1 is well noted for its immune stimulating effects.
The objective of this study is to make a comprehensive survey on how all the major dietary fibers present in grains, beets & carrots, fruits, nuts, beans and vegetables affect microbiome composition and the resulting physiological and metabolic effects.
Please contact Remco Kort in case of any interest
|Understanding optimal resource allocation strategies in yeasts||Computational|
Bachelor (with strong interest in computational methods)/Master
|Optimal allocation of limited resources, such as nutrients, energy, or physical volume of the cell enables to sustain cell maintenance and growth of cells, and is critical for unicellular microorganisms to strive. Moreover, the optimal allocation pattern can be context-specific, heavily depending on the environment the microorganisms live in. Therefore, computational techniques are of great help in order to capture and analyse resource allocation strategies/patterns, preferably at genome-scale. Thus in this topic, we blend existing knowledge of biochemistry and microbial physiology together with different types of computational modelling to advance the understanding of the organization of metabolism of two major eukaryal model organisms: budding yeast Saccharomyces cerevisiae and fission yeast Schizosaccharomyces pombe.
Techniques: genome-scale metabolic modelling (both conventional and proteome-constrained) (PySCes CBMpy, COBRA etc.), kinetic modelling (COPASI), programming with Python and/or R for data analysis and visualization
|Metabolism in health and disease||Experimental or computational (combinations are possible)|
|The work in this topic aims to understanding control and regulation of metabolism to reveal selective drug targets in pathogens and other disease-causing cells. In addition, we also want to understand these aspects for healthy cells to make sure that interventions against the disease will not harm them. We work with the parasite Trypanosoma brucei and with liver cancer cells in the wetlab, but also do research on the parasite Schistosoma mansoni, on head- and neck cancer and blood cell precursors in the dry-lab (always in collaboration with experimental labs
Techniques: Wetlab: cell culture, metabolite measurements, enzyme assays. Dry lab: kinetic modelling (COPASI, PySCes (python-based), genome-scale modelling
|Using CRISPR/CAS to create mutant yeast strains||Experimental (Bachelor or Master)||Dennis Botman
|In the lab, mutants strains of micro organisms are used routinely to explore and elucidate cellular physiology. This also holds for yeast, where mutants are often created by using so-called auxotrophic markers. These markers are metabolic genes that are deleted and can be restored again by replacing the studied gene of interest for the auxotrophic marker. Auxotrophic markers themselves can already affect cellular physiology, thereby making this technique debatable. In order to make clean mutant strains, we want to set up and use CRISPR/CAS to make gene knockouts without using any markers (scarless). In this internship, you will use CRISPR/CAS to knock out specific genes important in our research in a fully WT strain without any auxotrophic markers (scarless). You will also perform whole genome sequencing and characterization of the mutant strains.|