Modeling and Microbial Communities
We publish internships via the Biosb-interns mailing list server. If you subscribe to this mailing server you will obtain emails with internship projects in the fields of Bioinformatics and Systems Biology. You can also browse the archive of earlier mails.
You can also contact the team leader Douwe Molenaar directly with questions about opportunities for internships: d.molenaar@vu.nl
For additional internships, see the table below or contact Matti Gralka.
| Project title | Type of research | Supervisor(s) |
|---|---|---|
| Assessing (co-)evolution in a water kefir community using strain resolved metagenomics | Computational (Master) | Sabine Michielsen (s.michielsen[at]vu.nl) |
| Background: Outside of the laboratory, microbes often coexist with other (microbial) species, and occasionally form (stable) communities, such as the gut- and soil microbiome, or the communities used to ferment our food. These communities are not static and species will evolve depending on interactions with their neighboring species or changes in the environment. However, while we know a lot about microbial evolution on an individual level, several questions about evolutionary trajectories in communities remain. To gain insight into how communities evolve and adapt over time we need a stable community in which members are constantly in proximity to one another. In an ongoing project we use the water kefir (a fermented fizzy drink) community as a model system for community evolution. It consists of various species of lactic acid bacteria, acetic acid bacteria and yeasts contained in a self-produced granular structure. 1 Using this community, we aim to identify how the species interact and co-evolve when exposed to novel substrate, so that down the line, we may adapt the community to fermentation of plant based-substrates for the creation of plant-based dairy alternatives. To this end, we have obtained metagenomes of several water kefir communities adapted to growth on different media. Using these metagenomes we will follow community evolution through changes in relative species abundance and species evolution by tracking mutation events. As a first step, we need a method for calculating species abundances and a method with which to follow mutation events such as the development of Single Nucleotide Polymorphisms (SNPs). While we can easily use metagenomes to follow changes in the community on a species level using taxonomic profiling, following evolution of strains remains a challenge. Recently, different tools have been developed for the identification of SNPs from metagenome data and to follow SNP accumulation within species throughout samples taken at different timepoints. 2–4 Additionally, Meijer et al. have developed a method for resolving strains from metagenome assembled genomes (MAGs) using monomorphic SNP populations and for calculation of strain abundances and tracking SNP accumulation in the strains throughout different timepoints in bacteriophage communities.5 Project goal: The goal of this internship project is to use the recently developed approaches of the field to identify when novel SNPs develop in the different species in water kefir, and to follow SNP accumulation. For this project, we have a comprehensive short-read metagenomics dataset available. Currently, the dataset consists of 6 timeseries of water kefir, totaling 26 samples. The dataset will be further expanded, as sequencing of an additional 4 datasets comprising an additional 26 samples is underway. This internship project consists of three different phases, during which you will experience different stages of the research process. In the first phase of the internship you will get familiarized with standard metagenomics analysis. During the second phase, we will identify SNPs and trace if and when strains carrying SNPs become sufficiently abundant to fix (become a dominant strain) into the community. Lastly, after evaluation of the initial results, we will investigate the impact of functional alteration by a few promising SNPs on the strain phenotype. Using this approach we aim to identify which SNPs are likely to carry mutations that are beneficial to the species/community and gain more insight in the drivers of evolution within communities. Learning outcomes: During this project you will work with the following methods: - Metagenomics data preprocessing (QC, filtering, interpreting data to select correct thresholds) - Recovering and curating metagenome-assembled genomes - Single Nucleotide Variant calling - Strain resolved metagenomics - Gene annotation and functional analysis - Calculating strain abundance estimations - Estimating most probable evolutionary trajectories - Data visualization using R Additionally, you’ll deepen your understanding of microbial ecology and evolution theory, and gain in-depth knowledge of how to set up a workflow optimized for your specific use case. Your background: An enthusiastic Bioinformatics student with an interest in metagenomics and evolution. Strong coding skills are essential, and prior experience in microbiome research is highly desirable. Additionally, good writing skills are appreciated. |
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| Design of a simplified water kefir-based consortium in a chemically defined medium | Experimental (Master) | Sabine Michielsen (s.michielsen[at]vu.nl) |
| Microbes occupy most natural niches. They are typically in close proximity to one another and often form interactions ranging from antagonistic to commensal and even mutualistic. As evolution often works on the level of individual benefit, the onset of antagonistic reactions is relatively easy to explain. Microbes may, for example, scavenge nutrients from the exometabolome of nearby species. While mutualistic interactions often increase growth of both interaction partners through division of labour and specialisation, the downside is that the interaction partners become dependent on one another for nutrient production. For this to happen organisms need to have access to each other for an extended period. Due to this, mutualistic interactions may form more readily in a spatially structured environment. An example of a microbial community grown in a spatially structured environment is the water kefir community. A community typically used to ferment a mixture of tap water and table sugar supplemented with a piece of fruit into water kefir. In its original state, the water kefir community contains approximately 30 species, which makes it difficult to uncover underlying interactions. One way to study interactions in water kefir is by simplifying the community and establish which community members are essential. The aim of this project is to design a simplified spatially-structured water kefir consortium, which will be used to study interactions between consortium members. During this project you will: - Characterize potentially interesting strains (based on genome and metagenome data) isolated from the water kefir community. - Look for interactions and exopolysaccharide production in co-cultures - Design a simplified water kefir consortium and follow stability and aggregation over time using flowcytometry and microscopy |
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| Marine Bacteria Co-Culture Plate Validation | Experimental (Master) | Matti Gralka (m.gralka[at]vu.nl), Sarah Flickinger (s.f.flickinger[at]vu.nl) |
| Motivation: Studying microbial interactions is key to understanding ecological dynamics, especially regarding nutrient cycling and community stability. Co-culturing two bacterial strains is a basic way to explore these interactions, as it can reveal a range of outcomes such as competition, cooperation, or inhibition that reflect underlying ecological relationships. These outcomes provide valuable insights into how microbial communities function, adapt, and influence broader ecosystem processes. Aim of Project: In this project, you will test and validate a new co-culture plate setup consisting of 30 pairs of microwells connected by a 0.2 µm filter. The plate enables high-throughput co-culture experiments and allows for straightforward measurements of bacterial strain abundances. As this setup has not yet been used in our lab, you will establish and optimize a novel experimental tool. Initial goals include confirming that the filter prevents cross-contamination by bacteria while allowing diffusion of smaller molecules. You will test the permeability of the filter to various agents (e.g., nutrients, bacteriophages), followed by experiments to evaluate co-culture outcomes using strains from a marine bacterial library. Methods and techniques: Quantitative microbial physiology (growth rates, yield), high throughput culturing of bacteria, statistical analysis of biological data sets, experimental design |
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| Marine Bacteriophage Inactivation and Characterization | Experimental (Master) | Matti Gralka (m.gralka[at]vu.nl), Sarah Flickinger (s.f.flickinger[at]vu.nl) |
| Motivation: Bacteriophages are the most abundant biological entities in the ocean and may lyse up to 20% of marine bacteria daily, suggesting a major influence on bacterial abundance, diversity, and function. However, studies attempting to quantify phage impact have shown inconsistent results. This may be due to phages having narrow host ranges, with infectivity varying up to 10⁶-fold between potential hosts. Additionally, phages can be inactivated by environmental factors such as temperature, UV radiation, pH, or adsorption to particles. Understanding the extent of phage inactivation and their infectivity is essential to accurately assess their ecological role and potential to drive bacterial mortality in marine environments. Aim of Project: In this project, you will quantify the efficiency of plating (EOP) for multiple marine bacteriophages across a set of marine Vibrio bacteria. This will help determine infection efficiency across diverse phages and hosts. In addition, you will test potential phage inactivation mechanisms by exposing phages to marine polysaccharides and measuring reductions in phage titer. Other environmental inactivation factors such as UV exposure, pH, or enzymatic degradation may also be explored, depending on project progress. Methods and techniques: Aseptic technique, bacterial culturing, bacteriophage physiology (plaque assays, efficiency of plating), exposure experiments with marine polymers or environmental factors, viral titer quantification Impact: During this project, you will become proficient in standard microbiological methods used in academic, industrial, and clinical settings. You will also gain experience in experimental design, quantitative virology, and microbial ecology. |
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