Filled Internships

Already filled Internship positions.

 


TitleTypeSupervisor
Improving the efficiency of yeast by evolving them in millions of parallel pico-liter reactorsExperimental (Bachelor or Master) Position filled
Rinke van Tatenhove
r.j.van.tatenhove-pel@vu.nl
Many systems show a trade-off between speed and efficiency. Think for instance of a car: when you drive fast it is less fuel efficient than when you drive slower, which means that when you drive fast you can drive less kilometers per unit of fuel. For the growth of the yeast S. cerevisiae it is the same: when this yeast grows fast it is generally less efficient in converting glucose to biomass, which means that it can make less biomass from one unit of glucose. This inefficient but fast growth in yeast usually occurs when the glucose concentration is high, while S. cerevisiae grows slow and efficient when the glucose concentration is low.
We would like to study this trade-off between growth rate and efficiency by finding efficient mutant strains regardless of the glucose concentration. Can we select for a yeast strain with a high efficiency in the presence of high glucose concentrations?
Yeast cells normally grow in suspension, sharing their environment and the available substrate. However, an efficient mutant cannot be enriched in suspension, because such a mutant will grow slower than its fast growing neighbors. Efficient but slow mutants can therefore not be selected in a shared environment. To be able to select efficient cells we separate them from each other in medium droplets floating in oil. In such a water-in-oil emulsion we have millions of separated pico-liter compartments, in which each cell has its own substrate pool and its own extracellular space. All these individual compartments can be analyzed in seconds and mutants can be picked out with a flow cytometer, allowing for high-throughput mutant selection.
In this project you will develop a platform to select efficient yeast strains, using water-in-oil emulsions. You will design a medium which is suitable to perform these selections and you will apply this method to select efficient yeast cells at a high glucose concentration.
S. pombe as an alternative model for eukaryotic central metabolismExperimental (Master)
Position filled
Johan van Heerden
j.van.heerden@vu.nl
Background
The two distantly related yeast species, Saccharomyces cerevisiae and Schizosaccharomyces pombe, have been instrumental in our current understanding of the eukaryotic cell and its processes. Much of what we know about the cell cycle and its regulation was borne from pioneering studies with S. pombe, while S. cerevisiae has been a favourite workhorse in studies on eukaryotic metabolism (especially central carbon metabolism) and textbooks on this subject are therefore filled with insights derived from this organism.

While the cell-cycle field has embraced S. cerevisiae as a complementary eukaryotic model, researchers with a focus on metabolism have yet to harvest the potential insights to be gained from systematic (and comparative) studies of S. pombe metabolism. Today, the majority of research on S. pombe is still dedicated to unraveling cell cycle regulation and other cellular functions such as DNA repair, maintenance and aging, with very little fundamental research on the central metabolism of this yeast.

While there are many similarities between these two species, there are also several important differences including: cell morphology, the mode of cell division, the position of cell-size checkpoints during cell-cycle progression, the role of glucose sensors, the ability to respire ethanol, the presence of a glyoxylate cycle and differences in mitochondrial functions.

As many of the differences between these two species pertain to metabolic functions, a better understanding of the metabolic profile of S. pombe should serve to greatly expand our compendium of knowledge on eukaryotic metabolism, beyond that of S. cerevisiae and cancer cell lines.

The project
In this project you will lay down the foundation for metabolic studies that use S. pombe as an alternative to S. cerevisiae. You will perform both physiological and metabolic characterisations of S. pombe - in experimental settings that are typical for S. cerevisiae - in order to gain detailed descriptions of (1) growth kinetics, (2) cell size distributions and (3) profiles of intracellular pH and glycolytic intermediates, under different growth conditions. It is hoped that these results will serve to identify key differences, but also similarities, between these two species and that these insights will form a basis for future research.

Techniques
Batch and/or chemostat cultivations
Genetic transformations to express fluorescent reporter proteins
Enzymatic assays to determine intracellular metabolite concentrations
And, depending on the progress of the project, one or several of the following analytical techniques: HPLC, Coulter counter, Flow cytometry and Fluorescence spectroscopy, Fluorescent microscopy.

Duration of project: 5-9 months

Your CV: Ideally you will have an experimental background, with experience working in a microbiological setting.

Start date: February 2017 or later.
The regulation of glycolytic-to-gluconeogenic transitions in different yeast speciesTheoretical/Experimental (Master)
Position filled
Phillipp Schmidt
p.schmidt@vu.nl
&
Johan van Heerden
j.van.heerden@vu.nl
The preferred mode of metabolism for most yeast species is glycolysis. This metabolic pathway breaks down glucose or other sugars and produces pyruvate, which can further be utilized in fermentation or respiration in order to produce energy and precursors for biosynthesis. When encountering excess levels of glucose, the baker’s yeast Saccharomyces cerevisiae performs aerobic fermentation, which leads to the formation of ethanol. This is also called the Crabtree effect. Upon depletion of glucose it can utilize the previously produced ethanol as carbon source. This metabolic transition is called the diauxic shift. In order to grow on ethanol, the cells need to synthesize glucose and other metabolic intermediates. This achieved through the gluconeogenic pathway, which is a essentially glycolysis operating in the reverse direction. Due to the irreversibility of two glycolytic reactions, new enzymes need to be expressed for this pathway including FBPase (Fructose 1,6-bisphosphatase). The regulation of this enzyme is not completely understood, even though it has been intensely studied in S. cerevisiae. For example, an open question remains regarding the specific signals that lead to induction of this gluconeogenic enzyme - are low glucose levels sufficient to signal activation of gluconeogenic enzymes, or does extracellular ethanol play a role?

To find answers to these questions, other yeast species may provide clues. For example, Schizosaccharomyces pombe, like S. cerevisiae, exhibits the crabtree effect, but cannot consume the ethanol it produces via aerobic fermentation. Does ethanol still play a role in inducing gluconeogenesis? There are also crabtree negative yeasts, like Kluyveromyces lactis, that do not produce ethanol from glucose in the presence of oxygen. Clearly, in this case ethanol cannot play a role in signaling glycolytic-to-gluconeogenic transitions.

In this project, we want to compare the dynamic regulation of glycolytic-to-gluconeogenic transitions in these three different yeast species. We will use a technique called RNA FISH to count single mRNA molecules for PFK (Phosphofructokinase, a glycolytic gene) and FBPase (a gluconeogenic gene) in individual cells as they transition from excess to no glucose. By comparing differences in the induction of FBPase between these yeast species, the aim is to gain a better understanding of the roles that glucose and ethanol concentrations respectively play in inducing gluconeogenesis.

Duration of project: 5-9 months

Your CV: Ideally you will have a strong experimental background, and some basic programming skills (e.g. Python, R, Matlab).

Start date: May 2017 or later.
Drug targeting in metabolism: from antiparasitic target to drug screening assaysExperimental (Master)
Position filled
Jurgen Haanstra
j.r.haanstra[at]vu.nl and Marijke Wagner
Trypanosoma brucei is the causative agent of deadly African Sleeping Sickness. In its lifestage inside the mammalian host this unicellular parasite relies almost exclusively on glycolysis to generate ATP. As 50% inhibition of glycolysis is sufficient to kill the parasite, glycolysis is a prominent target pathway for antiparasitic drugs. A network-based analysis has shown that the glucose transporter has the highest control over the glycolytic flux in T. brucei and is therefore a prominent drug target.
To get to a semi- to high throughput assay to test drugs against the T. brucei transporter we have complemented a yeast glucose-transporter null mutant with the trypanosome transporter. In this project you will design and test drug screening assays on live T. brucei and for the yeast complementation mutant.
If desired, this project can incorporate a modelling part as we have a kinetic model of T. brucei glycolysis (and yeast).
To what extent does Lactococcus lactis need to adapt its proteome upon environmental transition?Experimental (Master)
Position filled
Sieze Douwenga
s.douwenga@vu.nl
WUR supervisor: Berdien van Olst
Background
Microorganisms like bacteria optimize their growth by adapting to their environment. When the environment changes, they might need different proteins or metabolic states to continue growing. This can result in temporary growth arrest, a lag-phase. For example, a lag phase is observed when the bacterium Lactococcus lactis is transitioned from glucose to maltose. A potential determinant of the lag phase duration is the time required to synthesize the alternate proteins required for growing in the new environment.
We do not always observe a lag phase upon transition, as L. lactis may be a generalist in certain environments. Generalists can grow under multiple conditions; and must express extra proteins which are non-essential for the current environment. This burden likely results in a reduced growth rate. It is therefore likely that conditions exist in which L. lactis specializes -instead of generalizes- in order to increase the growth rate. However, when a specialist encounters a new environment, it must synthesize the newly required proteins to continue growing. The amount of new proteins required is likely to depend on the pathway similarities between the new and old environment. On the contrary, a generalist might already have (part of) these proteins and is able to grow directly (or has a shorter lag phase). The degree of adaptation necessary to continue growing in a new environment can be determined by analyzing the complete proteome of L. lactis under various growth conditions. Additionally, characterizing the RNA, product and substrate fluxes is required, as certain proteins may be present below the detection limit.

The project
You will design and run several controlled batch reactor experiments under various conditions. From these reactors you will sample and analyze the proteome, RNA, and product and substrate fluxes of L. lactis. The project is a collaboration between the Systems Bioinformatics group at Vrije Universiteit Amsterdam (VU) and the Laboratory of Biochemistry at Wageningen University (WUR). Therefore, you will have the help of two daily supervisors (one at each university) and work at both of these sites. At the VU, you will have the facilities for running reactor experiments and for determining the product and substrate fluxes. At the WUR, you will characterize the proteome and RNA profile of L. lactis. By the end of your project, you will have obtained new insights on the proteome differences in L.lactis between the tested conditions.

Requirements
• Background in molecular biology/biochemistry and previous experience in microbiological culturing
• Interest in proteins/proteomics is important
• 6-9 month availability
Variability of glycogen metabolic abilities amongst Lactobacillus crispatus vaginal isolates.Experimental (Bachelor or Master)Position filledRosanne Hertzberger (topic expertise) and Jurgen Haanstra (lab/daily support) - contact: rosanne dot hertzberger at gmail dot com
Note: This project will follow “Open Kitchen Science” principles, which means that we will aim to publish all outcomes, including methods, data, posters, positive and negative results, on a blog www.reblab.org and on various other open science platforms (Zenodo, FigShare etc). This does not preclude publishing at a later stage in most traditional academic literature, such as the ASM journals.

Background :
The bacterial communities colonizing the vagina of reproductive-age women have a remarkable low level of diversity. In most cohorts studied sofar, a majority of women harbor bacterial communities dominated by lactobacilli. The most frequently encountered species of lactobacilli are Lactobacillus crispatus and iners. These lactobacilli produce high levels of lactate (up to 100 mM) and acidify the vagina (pH<4). The absence of Lactobacillus species is frequently accompanied by an overgrowth of various gram-negative and –variable species, commonly referred to as Bacterial Vaginosis (BV). This common vaginal microbial state is often asymptomatic, but in some cases leads to abnormal odor and secretions and is generally associated with a higher risk of acquiring sexually transmitted infection and premature birth.

Little is known about the carbon sources that fuel colonization and acidification by vaginal lactobacilli. One of the possible vaginal carbohydrates available to microbes is glycogen, which is present in high levels in the epithelial layers of the uterus, exocervix and vagina of reproductive-age women. Previous experiments suggest that various BV-associated microbes (Gardnerella and Prevotella) as well as Lactobacillus iners and some Lactobacillus crispatus isolates can utilize glycogen as a carbon and energy source.

Recently we found remarkable variability in glycogen metabolism amongst a group of ~20 vaginal isolates of Lactobacillus crispatus. This ability to use external glycogen for growth and acidification was found to correspond to a type 1 pullulanase gene variant. The strains that are able to grow using glycogen as their sole carbon and energy source have an intact N-terminal signal peptide in their type 1 pullulanase gene.
We hypothesize that this signal peptide may be involved in allocating the enzyme to the outermost S-layer which is probably important to access and breakdown the large molecules of extracellular glycogen in smaller units that can be transported over the cell membrane. The subset of Lactobacillus crispatus strains that are unable to grow using glycogen as a carbon source have various mutations disrupting the signal peptide in this area of the type 1 pullulanase gene.

Lastly, expression of the activity was only detected during growth of L. crispatus on glycogen and not on glucose. This indicates either (1) carbon catabolite repression: repression of the expression of some or all genes involved in glycogen metabolism when extracellular glucose is detected or (2) induction of genes involved in glycogen metabolism in the presence of glycogen or one of the breakdown product or (3) regulation on enzymatic level (feed-back inhibition?).

Understanding these basic aspects of vaginal microbial metabolism may lead to developing better treatment for these very common vaginal symptoms, thereby increasing reproductive health.
Hypothesis: An intact S-layer signal peptide of the Lactobacillus crispatus type 1 pullulanase is essential for allocating the pullulanase that is responsible for catalysis of the first step of glycogen metabolism to the outermost membrane layer.

Experimental plan
Currently, the evidence supporting the hypothesis consists of a link between glycogen breakdown phenotype and type 1 pullulanase genotype in a set of ~20 Lactobacillus crispatus strains (genotype-fenotype). In this project we aim to gather further evidence for the hypothesis by:
-identification of the pullulanase with various substrates (glycogen, starch, amylose) and studying production of breakdown products (maltotriose, maltopentaose, maltose, glucose) using TLC. (The enzymatic activity has been detected sofar only with a basic starch-iodine assay.)
-studying cellular location of the activity by comparing supernatants and pellets before and after disruption of the cells.
-studying the regulation of expression: tracking enzymatic activity during growth experiments on glycogen and/or glucose in various concentrations and in growth experiments perturbed with glucose, glycogen or glycogen breakdown products.
-Several basic microbial skills will be developed: anaerobic culture, enzymatic assay, medium preparation, sterile working, optical density measurements, inoculation and plating.
Analyzing the interactions between yeast and bacteria.Experimental (Bachelor). Position filledRinke van Tatenhove
r.j.van.tatenhove-pel@vu.nl
rob.van.spanning@vu.nl
In most controlled microbiological experiments the behavior of one single organisms is studied. However, in nature micro-organisms are never alone, but they live together with many different species and they interact with each other. This project focusses on interactions between yeast and bacteria. We will use a synthetic consortium in which yeast and bacteria grow together and one organism grows on a metabolic product of the other. This interaction will eventually be used to select for increased metabolite yields.
In this project you will develop a medium to co-culture yeast and bacteria and you will analyze the interactions between these organisms using a flow cytometer. You will furthermore investigate how we can attach these cells to each other, to reduce the distance between them and make their interactions more efficient.
Biodegradation of novel pharmaceutical products. Experimental (Master)Baptiste Poursat
B.A.J.Poursat@uva.nl
Organic pollutants, such as pharmaceutical and industrial products, are frequently detected in the environment, especially in aquatic habitats and in wastewater treatment plant (WWTP) discharges. They are considered as “emerging contaminants” since most of them are not currently covered by existing water-quality regulations, and their effects on the environment are still poorly understood. Knowledge on environmental persistency is essential to make an efficient environmental risk assessment of new manufactured chemicals. Indeed, a key component of both hazard determination and environmental risk assessment is the accurate estimation of the degradation of a chemical in the environment. Ready biodegradation tests (RBT) from the OECD guideline are required by the European REACH regulation to evaluate the biodegradability of chemical substances produced by industry. However, RBT suffer from several drawbacks related to the heterogeneity of their inoculum, due to their different origin and history. Indeed, the source, concentration and pretreatment of the inoculum are one of the most important factors that influence the RBT results and the extent of biodegradation of chemicals in the environment. The aim of this master thesis project is to compare the biodegradation rates of several pharmaceutical and industrial products (using LC-MS/MS) by different inocula from municipal, hospital and industrial WWTPs. Microbial communities will be characterized by Illumina sequencing and metagenomic analyses. Laboratory work for this project will mostly be performed in the laboratory of the University of Amsterdam (Science Park). For more information, please contact Baptiste Poursat, Dr John Parsons (UvA-ESS) or Dr Rob Van Spanning (VU Amsterdam).
The role of metabolic interactions in antibiotic toleranceTheoretical (Master)Bas Teusink
b.teusink@vu.nl
Bacteria in polymicrobial infections interact with each other. These interactions can change the environment to such an extent that some bacteria can become more or less susceptible to antibiotics. Metabolic interactions likely underlie this antibiotic tolerance effect. By means of metabolic modeling you will investigate some of these potential antibiotic-tolerance interactions in polymicrobial infections.

This internship is a cooperation with Dr Marjon de Vos from Wageningen University

Bacteria in polymicrobial infections interact with each other. These interactions can change the environment to such an extent that some bacteria can become more or less susceptible to antibiotics. Metabolic interactions likely underlie this antibiotic tolerance effect. By means of metabolic modeling you will investigate some of these potential antibiotic-tolerance interactions in polymicrobial infections.

This internship is a cooperation with Dr Marjon de Vos from Wageningen University
Segmentation of microscopy images using deep learningTheoretical (Bachelor or Master)Philipp Savakis
p.e.savakis@vu.nl
Under dynamic conditions (changes in nutrient availability, ion concentrations, toxic compounds etc.), individual cells within a population show different responses. In order to quantify these responses, we aim to use a combination of microfluidics, phase contrast, and fluorescence microscopy. Images taken with the microscope need to be pre-processed for further analysis: the analysis algorithm needs to know in which part of the image the cells are located and what their shape is. So, in the first part of the data analysis, we need to solve a pixel-wise classification problem. The project focuses on implementing deep learning techniques (convolutional neural networks in caffe) to generate segmented images, which are then fed into a downstream processing pipeline. Proficiency in python and a general interest in deep learning techniques and pattern recognition are required, knowledge of Matlab/octave and caffe would be very helpful.
Segmentation of microscopy images using deep learningTheoretical (Bachelor or Master)Philipp Savakis
p.e.savakis@vu.nl
Under dynamic conditions (changes in nutrient availability, ion concentrations, toxic compounds etc.), individual cells within a population show different responses. In order to quantify these responses, we aim to use a combination of microfluidics, phase contrast, and fluorescence microscopy. Images taken with the microscope need to be pre-processed for further analysis: the analysis algorithm needs to know in which part of the image the cells are located and what their shape is. So, in the first part of the data analysis, we need to solve a pixel-wise classification problem. The project focuses on implementing deep learning techniques (convolutional neural networks in caffe) to generate segmented images, which are then fed into a downstream processing pipeline. Proficiency in python and a general interest in deep learning techniques and pattern recognition are required, knowledge of Matlab/octave and caffe would be very helpful.
Studying aggregation and localization of glycolytic enzymesExperimental (Master or Bachelor)Dennis Botman
d.botman@vu.nl
Glycolysis is a major metabolic pathway in yeast as it produces energy and building blocks. Localization and aggregation of glycolytic enzymes has drawn increasingly more attention as a novel way for cells to regulate glycolysis. We found that aggregation of glycolytic enzymes occurs under specific conditions. However, why these enzymes aggregate and if this aggregation occurs at specific cellular locations is still unknown. During the internship we will try to get more insights into these processes. We will use molecular cloning, fluorescence microscopy, plate reader experiments and enzymatic assays to study the localization/aggregation of glycolytic enzymes in yeast cells.
Characterizing fluorescent proteins in yeast cellsExperimental (Bachelor)Dennis Botman
d.botman@vu.nl
Nowadays, fluorescence microscopy is an essential tool to visualize protein amounts, protein localisation and interactions or to monitor time-bound events. Fluorescence microscopy can be performed in various species. However, the performance of FPs can differ per species. To use the correct FP for a specific experiment in a specific species, FPs should be characterised in a consistent manner in the specific species. Therefore, we want to characterize FPs in yeast cells. We will characterize the FPs on traits like brightness, photostability, maturation, pH sensitivity, monomeric properties, quantum yield and FRET efficiency. By this, we can provide a useful guide for choosing the right FP based on the wishes of the user and the FP properties.
Improving the efficiency of yeast by evolving them in millions of parallel pico-liter reactorsExperimental (Bachelor or Master) Position filled
Rinke van Tatenhove
r.j.van.tatenhove-pel@vu.nl
Many systems show a trade-off between speed and efficiency. Think for instance of a car: when you drive fast it is less fuel efficient than when you drive slower, which means that when you drive fast you can drive less kilometers per unit of fuel. For the growth of the yeast S. cerevisiae it is the same: when this yeast grows fast it is generally less efficient in converting glucose to biomass, which means that it can make less biomass from one unit of glucose. This inefficient but fast growth in yeast usually occurs when the glucose concentration is high, while S. cerevisiae grows slow and efficient when the glucose concentration is low.
We would like to study this trade-off between growth rate and efficiency by finding efficient mutant strains regardless of the glucose concentration. Can we select for a yeast strain with a high efficiency in the presence of high glucose concentrations?
Yeast cells normally grow in suspension, sharing their environment and the available substrate. However, an efficient mutant cannot be enriched in suspension, because such a mutant will grow slower than its fast growing neighbors. Efficient but slow mutants can therefore not be selected in a shared environment. To be able to select efficient cells we separate them from each other in medium droplets floating in oil. In such a water-in-oil emulsion we have millions of separated pico-liter compartments, in which each cell has its own substrate pool and its own extracellular space. All these individual compartments can be analyzed in seconds and mutants can be picked out with a flow cytometer, allowing for high-throughput mutant selection.
In this project you will develop a platform to select efficient yeast strains, using water-in-oil emulsions. You will design a medium which is suitable to perform these selections and you will apply this method to select efficient yeast cells at a high glucose concentration.
How I wish I could measure phosphate in single cellsExperimental (Bachelor)Laura Guilherme Luzia
l.r.guilhermeluzia@vu.nl
Description: Pi is an important molecule in metabolism, signal transduction, enzyme regulation and a structural component of nucleic acids and cell membranes. In order to better understand how yeast central metabolism adapt and evolve in response to environmental changes, we want to quantify Pi levels in single cells. To do that, we will explore a FRET (Fluorescence Resonance Energy Transfer) sensor to measure the intracellular concentration of Pi under different carbon sources conditions in time-scale. Here, we want to characterize this ratiometric Pi sensor using kinetics assays and fluorescence spectrometry/microscopy techniques. In the end, we should be able to monitor Pi fluctuations in Saccharomyces cerevisiae in a range of conditions and to understand how free energy flows inside cells and is affected by external changes.
Variability of glycogen metabolic abilities amongst Lactobacillus crispatus vaginal isolates.Experimental (Bachelor or Master)Rosanne Hertzberger (topic expertise) and Jurgen Haanstra (lab/daily support) - contact: rosanne dot hertzberger at gmail dot com
Note: This project will follow “Open Kitchen Science” principles, which means that we will aim to publish all outcomes, including methods, data, posters, positive and negative results, on a blog www.reblab.org and on various other open science platforms (Zenodo, FigShare etc). This does not preclude publishing at a later stage in most traditional academic literature, such as the ASM journals.

Background :
The bacterial communities colonizing the vagina of reproductive-age women have a remarkable low level of diversity. In most cohorts studied sofar, a majority of women harbor bacterial communities dominated by lactobacilli. The most frequently encountered species of lactobacilli are Lactobacillus crispatus and iners. These lactobacilli produce high levels of lactate (up to 100 mM) and acidify the vagina (pH<4). The absence of Lactobacillus species is frequently accompanied by an overgrowth of various gram-negative and –variable species, commonly referred to as Bacterial Vaginosis (BV). This common vaginal microbial state is often asymptomatic, but in some cases leads to abnormal odor and secretions and is generally associated with a higher risk of acquiring sexually transmitted infection and premature birth.

Little is known about the carbon sources that fuel colonization and acidification by vaginal lactobacilli. One of the possible vaginal carbohydrates available to microbes is glycogen, which is present in high levels in the epithelial layers of the uterus, exocervix and vagina of reproductive-age women. Previous experiments suggest that various BV-associated microbes (Gardnerella and Prevotella) as well as Lactobacillus iners and some Lactobacillus crispatus isolates can utilize glycogen as a carbon and energy source.

Recently we found remarkable variability in glycogen metabolism amongst a group of ~20 vaginal isolates of Lactobacillus crispatus. This ability to use external glycogen for growth and acidification was found to correspond to a type 1 pullulanase gene variant. The strains that are able to grow using glycogen as their sole carbon and energy source have an intact N-terminal signal peptide in their type 1 pullulanase gene.
We hypothesize that this signal peptide may be involved in allocating the enzyme to the outermost S-layer which is probably important to access and breakdown the large molecules of extracellular glycogen in smaller units that can be transported over the cell membrane. The subset of Lactobacillus crispatus strains that are unable to grow using glycogen as a carbon source have various mutations disrupting the signal peptide in this area of the type 1 pullulanase gene.

Lastly, expression of the activity was only detected during growth of L. crispatus on glycogen and not on glucose. This indicates either (1) carbon catabolite repression: repression of the expression of some or all genes involved in glycogen metabolism when extracellular glucose is detected or (2) induction of genes involved in glycogen metabolism in the presence of glycogen or one of the breakdown product or (3) regulation on enzymatic level (feed-back inhibition?).

Understanding these basic aspects of vaginal microbial metabolism may lead to developing better treatment for these very common vaginal symptoms, thereby increasing reproductive health.
Hypothesis: An intact S-layer signal peptide of the Lactobacillus crispatus type 1 pullulanase is essential for allocating the pullulanase that is responsible for catalysis of the first step of glycogen metabolism to the outermost membrane layer.

Experimental plan
Currently, the evidence supporting the hypothesis consists of a link between glycogen breakdown phenotype and type 1 pullulanase genotype in a set of ~20 Lactobacillus crispatus strains (genotype-fenotype). In this project we aim to gather further evidence for the hypothesis by:
-identification of the pullulanase with various substrates (glycogen, starch, amylose) and studying production of breakdown products (maltotriose, maltopentaose, maltose, glucose) using TLC. (The enzymatic activity has been detected sofar only with a basic starch-iodine assay.)
-studying cellular location of the activity by comparing supernatants and pellets before and after disruption of the cells.
-studying the regulation of expression: tracking enzymatic activity during growth experiments on glycogen and/or glucose in various concentrations and in growth experiments perturbed with glucose, glycogen or glycogen breakdown products.
-Several basic microbial skills will be developed: anaerobic culture, enzymatic assay, medium preparation, sterile working, optical density measurements, inoculation and plating.
Biodegradation of novel pharmaceutical products.
Experimental (Master)Baptiste Poursat
B.A.J.Poursat@uva.nl
Organic pollutants, such as pharmaceutical and industrial products, are frequently detected in the environment, especially in aquatic habitats and in wastewater treatment plant (WWTP) discharges. They are considered as “emerging contaminants” since most of them are not currently covered by existing water-quality regulations, and their effects on the environment are still poorly understood. Knowledge on environmental persistency is essential to make an efficient environmental risk assessment of new manufactured chemicals. Indeed, a key component of both hazard determination and environmental risk assessment is the accurate estimation of the degradation of a chemical in the environment. Ready biodegradation tests (RBT) from the OECD guideline are required by the European REACH regulation to evaluate the biodegradability of chemical substances produced by industry. However, RBT suffer from several drawbacks related to the heterogeneity of their inoculum, due to their different origin and history. Indeed, the source, concentration and pretreatment of the inoculum are one of the most important factors that influence the RBT results and the extent of biodegradation of chemicals in the environment. The aim of this master thesis project is to compare the biodegradation rates of several pharmaceutical and industrial products (using LC-MS/MS) by different inocula from municipal, hospital and industrial WWTPs. Microbial communities will be characterized by Illumina sequencing and metagenomic analyses. Laboratory work for this project will mostly be performed in the laboratory of the University of Amsterdam (Science Park). For more information, please contact Baptiste Poursat, Dr John Parsons (UvA-ESS) or Dr Rob Van Spanning (VU Amsterdam).
S. pombe as an alternative model for eukaryotic central metabolismExperimental (Master)
Position filled
Johan van Heerden
j.van.heerden@vu.nl
Background
The two distantly related yeast species, Saccharomyces cerevisiae and Schizosaccharomyces pombe, have been instrumental in our current understanding of the eukaryotic cell and its processes. Much of what we know about the cell cycle and its regulation was borne from pioneering studies with S. pombe, while S. cerevisiae has been a favourite workhorse in studies on eukaryotic metabolism (especially central carbon metabolism) and textbooks on this subject are therefore filled with insights derived from this organism.

While the cell-cycle field has embraced S. cerevisiae as a complementary eukaryotic model, researchers with a focus on metabolism have yet to harvest the potential insights to be gained from systematic (and comparative) studies of S. pombe metabolism. Today, the majority of research on S. pombe is still dedicated to unraveling cell cycle regulation and other cellular functions such as DNA repair, maintenance and aging, with very little fundamental research on the central metabolism of this yeast.

While there are many similarities between these two species, there are also several important differences including: cell morphology, the mode of cell division, the position of cell-size checkpoints during cell-cycle progression, the role of glucose sensors, the ability to respire ethanol, the presence of a glyoxylate cycle and differences in mitochondrial functions.

As many of the differences between these two species pertain to metabolic functions, a better understanding of the metabolic profile of S. pombe should serve to greatly expand our compendium of knowledge on eukaryotic metabolism, beyond that of S. cerevisiae and cancer cell lines.

The project
In this project you will lay down the foundation for metabolic studies that use S. pombe as an alternative to S. cerevisiae. You will perform both physiological and metabolic characterisations of S. pombe - in experimental settings that are typical for S. cerevisiae - in order to gain detailed descriptions of (1) growth kinetics, (2) cell size distributions and (3) profiles of intracellular pH and glycolytic intermediates, under different growth conditions. It is hoped that these results will serve to identify key differences, but also similarities, between these two species and that these insights will form a basis for future research.

Techniques
Batch and/or chemostat cultivations
Genetic transformations to express fluorescent reporter proteins
Enzymatic assays to determine intracellular metabolite concentrations
And, depending on the progress of the project, one or several of the following analytical techniques: HPLC, Coulter counter, Flow cytometry and Fluorescence spectroscopy, Fluorescent microscopy.

Duration of project: 5-9 months

Your CV: Ideally you will have an experimental background, with experience working in a microbiological setting.

Start date: February 2017 or later.
The role of metabolic interactions in antibiotic toleranceTheoretical (Master)Bas Teusink
b.teusink@vu.nl
Bacteria in polymicrobial infections interact with each other. These interactions can change the environment to such an extent that some bacteria can become more or less susceptible to antibiotics. Metabolic interactions likely underlie this antibiotic tolerance effect. By means of metabolic modeling you will investigate some of these potential antibiotic-tolerance interactions in polymicrobial infections.

This internship is a cooperation with Dr Marjon de Vos from Wageningen University
The regulation of glycolytic-to-gluconeogenic transitions in different yeast speciesTheoretical/Experimental (Master)
Position filled
Phillipp Schmidt
p.schmidt@vu.nl
&
Johan van Heerden
j.van.heerden@vu.nl
The preferred mode of metabolism for most yeast species is glycolysis. This metabolic pathway breaks down glucose or other sugars and produces pyruvate, which can further be utilized in fermentation or respiration in order to produce energy and precursors for biosynthesis. When encountering excess levels of glucose, the baker’s yeast Saccharomyces cerevisiae performs aerobic fermentation, which leads to the formation of ethanol. This is also called the Crabtree effect. Upon depletion of glucose it can utilize the previously produced ethanol as carbon source. This metabolic transition is called the diauxic shift. In order to grow on ethanol, the cells need to synthesize glucose and other metabolic intermediates. This achieved through the gluconeogenic pathway, which is a essentially glycolysis operating in the reverse direction. Due to the irreversibility of two glycolytic reactions, new enzymes need to be expressed for this pathway including FBPase (Fructose 1,6-bisphosphatase). The regulation of this enzyme is not completely understood, even though it has been intensely studied in S. cerevisiae. For example, an open question remains regarding the specific signals that lead to induction of this gluconeogenic enzyme - are low glucose levels sufficient to signal activation of gluconeogenic enzymes, or does extracellular ethanol play a role?

To find answers to these questions, other yeast species may provide clues. For example, Schizosaccharomyces pombe, like S. cerevisiae, exhibits the crabtree effect, but cannot consume the ethanol it produces via aerobic fermentation. Does ethanol still play a role in inducing gluconeogenesis? There are also crabtree negative yeasts, like Kluyveromyces lactis, that do not produce ethanol from glucose in the presence of oxygen. Clearly, in this case ethanol cannot play a role in signaling glycolytic-to-gluconeogenic transitions.

In this project, we want to compare the dynamic regulation of glycolytic-to-gluconeogenic transitions in these three different yeast species. We will use a technique called RNA FISH to count single mRNA molecules for PFK (Phosphofructokinase, a glycolytic gene) and FBPase (a gluconeogenic gene) in individual cells as they transition from excess to no glucose. By comparing differences in the induction of FBPase between these yeast species, the aim is to gain a better understanding of the roles that glucose and ethanol concentrations respectively play in inducing gluconeogenesis.

Duration of project: 5-9 months

Your CV: Ideally you will have a strong experimental background, and some basic programming skills (e.g. Python, R, Matlab).

Start date: May 2017 or later.
Identification of grape skin compound inhibition in wine making
Experimental (Master)Chrats Melkonian
c.melkonian@vu.nl
&
Douwe Molenaar
d.molenaar@vu.nl
In wine making malolactic fermentation is a key process normally taking place after alcoholic fermentation. Lactic acid bacteria and specifically Onococcus oeni is a prominent contender for the role. In the search for alternative bacteria to fulfil that role, Lactobacillus plantarum is promising. However, computational analysis revealed that L. plantarum is probably inhibited by a phenolic compound released from grape skins during wine fermentation. This experimental project aims to identify the mechanism of this inhibition in the lab. Which phenolic compounds are more toxic? Where in metabolism does the inhibition take place? And is there a way to overcome it? These are few question you will try to answer. Furthermore, evolutionary adaptation of strains toward highly resistant strains could be explored.

For more information contact Chrats Melkonian(c.melkonian@vu.nl)

This internship is a cooperation with Ingrid Collombel from CBQF, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Porto - Portugal
Drug targeting in metabolism: from antiparasitic target to drug screening assaysExperimental (Master)
Position filled
Jurgen Haanstra
j.r.haanstra[at]vu.nl and Marijke Wagner
Trypanosoma brucei is the causative agent of deadly African Sleeping Sickness. In its lifestage inside the mammalian host this unicellular parasite relies almost exclusively on glycolysis to generate ATP. As 50% inhibition of glycolysis is sufficient to kill the parasite, glycolysis is a prominent target pathway for antiparasitic drugs. A network-based analysis has shown that the glucose transporter has the highest control over the glycolytic flux in T. brucei and is therefore a prominent drug target.
To get to a semi- to high throughput assay to test drugs against the T. brucei transporter we have complemented a yeast glucose-transporter null mutant with the trypanosome transporter. In this project you will design and test drug screening assays on live T. brucei and for the yeast complementation mutant.
If desired, this project can incorporate a modelling part as we have a kinetic model of T. brucei glycolysis (and yeast).
What are the costs of protein turnover?Theoretical (Master)Eunice van Pelt-Kleinjan
e.van.pelt-kleinjan[at]vu.nl
Douwe Molenaar
d.molenaar[at]vu.nl
External supervisor Berdien van Olst
Background
A cell needs proteins to catalyze reactions. These proteins do not have an indefinite lifetime and are degraded over time. In steady state conditions, the protein level should be constant, so the cell needs to synthesize new proteins to replace the degraded ones. This constant protein production, degradation and renewal is called protein turnover. In addition, the proteins are diluted upon growth, so in steady state, the cell also needs to produce protein during growth. There are many different factors involved in protein production, like transcription and translation. Therefore, turnover rate is expected to be protein specific. We want to find out whether there is a relation between turnover rate and these different factors. Ultimately, we want to know how the costs of protein turnover determine optimal metabolic and growth strategies of bacteria.

Approach
We have turnover data of hundreds of proteins of a bacterial strain grown in a chemostat. The data consists of time-series of concentrations of heavy lysine wash-out and light lysine incorporation in proteins. Based on this data we want to calculate the turnover rate of each protein. For this we need to develop a statistical modeling approach. When we have the turnover rates we will analyze them (e.g. are there certain groups of proteins that cluster together because of a similar turnover rate, what does this mean in relation to e.g. their function?). This will improve our understanding of the protein economy in the cell.
Defining macrophage immunometabolism through omics data analysis
Background
Theoretical (Master)Jan vd Bossche,
Douwe Molenaar d.molenaar[at]vu.nl
Macrophages are innate immune cells that phagocytose and kill microbes. Although these are key features,
Macrophages are innate immune cell that are functionally very multifaceted and are involved in almost all aspects of life; from immunity and host defense, to homeostasis, tissue repair and development. To fulfil these distinct actions, macrophages adopt a plethora of polarization states. Understanding their regulation and phenotypic heterogeneity is crucial because macrophages are critical in many diseases and have emerged as attractive targets for therapy of cancer, atherosclerosis, asthma and many more “Western” killers.
We recently demonstrated the crucial role of metabolic reprogramming in distinct macrophage activation cues. LPS+IFNg-induced pro-inflammatory “M1” macrophages undergo metabolic rewiring, illustrated by heightened glycolysis. In contrast, IL-4-induced anti-inflammatory “M2” macrophages show and require high mitochondrial oxidative phosphorylation (OXPHOS). Thus, the way a macrophage digests its nutrients not only provides energy, but directly dictates its function.
To advance our findings to future therapeutic applications, our current knowledge now needs to be translated to the complex in vivo environment, where macrophages are exposed to a complex mixture of stimuli and don’t classify as M1 or M2. In other words, the metabolic roadmaps of non-M1/M2 macrophage subsets need to be defined in health and disease in both humans and animal models.

Method
In this project you will define the metabolic characteristics of different macrophage subsets using transcriptomics, proteomics and metabolomics data that are available online and with unique data that we generate(d) ourselves.


Outcome
Revealing the metabolic characteristics and needs of macrophages will reveal new (metabolic) targets to manipulate macrophage function and to improve disease outcome.
Single cell gene expression study of gluconeogenic genes during the diauxic shiftExperimental (Master)Phillipp Schmidt
p.schmidt@vu.nl
Philipp Savakis
p.e.savakis@vu.nl
During batch growth, Saccharomyces cerevisiae initially converts glucose into ethanol (glycolysis and fermentation). After glucose has been depleted, ethanol is taken up again and used as carbon source (gluconeogenesis and respiration). This behaviour is termed diauxic growth.
The transition from glycolysis to gluconeogenesis takes place via different levels of regulation. Transcriptional regulation is characterized by the expression of specific metabolic enzymes. The role of ethanol concentration and glucose/ethanol ratio on regulation is not well understood.
For instance, when ethanol has been produced, but glucose has not yet run out, the cells can co-utilize molecules: glucose is used as a starting point for biosynthetic building blocks, while ethanol is oxidised via the TCA cycle to yield NADH, which in turn is used for ATP generation. The enzyme indicative of this state is ADH2.
In this project, we are interested in labelling a number of different metabolic enzymes with a set of fluorescent proteins. This will allow us to observe the timing of the synthesis of these proteins as well as their interplay during diauxic shifts in individual cells. With the use of fluorescent microsocopy and flowcytometry we will be able to quantify expression levels at single cell level.
Analyzing the interactions between yeast and bacteria.Experimental (Bachelor)Rinke van Tatenhove
r.j.van.tatenhove-pel@vu.nl
rob.van.spanning@vu.nl
In most controlled microbiological experiments the behavior of one single organisms is studied. However, in nature micro-organisms are never alone, but they live together with many different species and they interact with each other. This project focusses on interactions between yeast and bacteria. We will use a synthetic consortium in which yeast and bacteria grow together and one organism grows on a metabolic product of the other. This interaction will eventually be used to select for increased metabolite yields.
In this project you will develop a medium to co-culture yeast and bacteria and you will analyze the interactions between these organisms using a flow cytometer. You will furthermore investigate how we can attach these cells to each other, to reduce the distance between them and make their interactions more efficient.

Multi-omics to unravel interactions in a benzene-degrading microbial consortiumTheoretical/Computational (Master)Chrats Melkonian
c.melkonian@vu.nl
Douwe Molenaar
& Rob van Spanning
Background
Benzene is a poisonous compound often found in soils contaminated by fuel hydrocarbons. Because oxygen seemed to be important in benzene degradation, researchers tried to understand the aerobic degradation of this organic compound for over a century. Later, anaerobic benzene degradation by microbial communities was observed. A lot is still to be discovered about the microbial physiology, biochemical pathways and metabolic intermediates involved in anaerobic benzene degradation.
To understand microbial anaerobic benzene degradation we used a microbial community that was fed with benzene and nitrate during 15 years. We initially thought that this community would consist of a few highly specialized species. However, the results showed a diverse community with more than 100 very diverse species.

Goal of the project
To find out how the species divide the labour in this benzene-degrading microbial consortium, and to identify dependencies between the members of the community and different type of microbial interaction.
You will work on a model system that allows you to take one step further and try to address more fundamental questions of microbiology, such as, how is fitness affected by the presence of many species in a microbial community?

i) You will have to use exploratory analysis, statistical modelling and cutting edge data science techniques, as well as tools builded in house for functional analysis of microbial communities on metagenomics and metatranscriptomics.
ii) You will apply the previous tools/techniques in a metagenomics/transcriptomics dataset obtained from the 15 years old chemostat.

Duration
From 4 to 6 months
Your CV
Ideally, you have a data science/bioinformatics background with programming experience (preferably R, Python). Experience in ecology and microbial community research is recommended.
Start Date
Right away
Bioremediation of oil contaminated mangrove forestsExperimental (Master)"Paul Iturbe Espinoza
p.iturbeespinoza@vu.nl"
"Shell uses land farming to clean up sites impacted by oil spills. Land farming reduces the concentration of petroleum constituents present in soils through processes associated with bioremediation. In sensitive ecosystems, such as mangroves, traditional remediation methodologies such as land farming can be particularly difficult due the soft ground conditions and sensitive nature of vegetation. In those types of environments, removal of surficial oil and gentle flushing of sediments to remove free oil can be effective in reducing oil concentrations. Any residual oil is further reduced by biodegradation to a level where mangrove vegetation can recover. The rate at which the biodegradation occurs is an important factor in the restoration of the mangrove ecosystem but relatively few data are available on this. Also, while it is widely acknowledged that microorganisms play an important role in the breakdown, linking rates to microbial community composition and other abiotic factors is very hard.

The objective of this MSc research project is to increase the understanding biodegradation processes in mangroves, both in terms of kinetics, involved micro-organisms and contributing abiotic factors. Shell can provide soil samples which will span a range of severity and type of oil contamination (fresh versus weathered) which can be used in experiments. It is envisaged that the student will develop a work plan based on a comprehensive literature study on this topic. Laboratory experiments can be used to establish laboratory estimates of the rate of biodegradation which can be combined with microbial community profiling as determined by Illumina amplicon sequencing.

The project is in collaboration with the Shell Technology Centre Amsterdam."
Fundamental insight in oil-degrading microbial communities using NGSExperimental (Master)"Paul Iturbe Espinoza
p.iturbeespinoza@vu.nl"
"The IUCN-Niger Delta Panel (IUCN-NDP) was established at the request of Shell Petroleum Development Company of Nigeria Limited (SPDC), to provide science-based recommendations for the remediation and rehabilitation of biodiversity and habitats of oil spill sites in the Niger Delta. Land farming is widely used by SPDC to clear residual oil from spillages to soil in the Niger Delta. This approach reduces the concentration of petroleum constituents present in soils through processes associated with bioremediation. It is proposed by the IUCN that the use of bio surfactants, enzymes and sorbents can improve the effectiveness of this treatment. SPDC is planning to perform comparative pilot scale testing in Nigeria to determine the relative efficacy of the IUCN-NDP recommended remediation agents. It is anticipated that the tests will be performed in fully contained bio cells. The success of soil remediation by land farming is generally dependent on availability of nutrients and oxygen within the system plus the ability to overcome some of the mass transfer issues associated with hydrocarbon biodegradation. Consequently, the effects of oxygen, nutrients mass transfer will also be incorporated into the test plan in order to gain a better understanding of what influences efficient biodegradation in Nigeria soils. The experiment will test the effectiveness of the following factors on remediation success:

Nutrients (Agricultural Fertilizer), (Bio)surfactants, Enzyme products, Natural Sorbents, Tilling (oxygen and mass transfer)

The IUCN have commented that the success of remediation maybe dependent on the composition of the indigenous microbial community within the soil as determined by Illumina amplicon sequencing. Therefore, we would like to understand if and how microbial communities differ during treatment with various forms of remediation agent. The size and scope and specific objectives of the study can be discussed in more detail if you are interested developing a project. The project is in collaboration with the Shell Technology Centre Amsterdam."
Microbial degradation of 2,4-dichlorophenoxyacetic acid and 2,4,5-trichlorophenoxyacetic acid (2,4,5-T)Experimental (Master)"Lan Anh Nguyen l.a.nguyenthi@vu.nl
Rob van Spanning rob.van.spanning@vu.nl"
"In the Vietnam War, Agent Orange was extensively used as a defoliant between 1962 and 1971. This herbicide comprises an equal mixture of 2,4-D and 2,4,5-T and also contains traces of 2,3,7,8-TCDD (2,3,7,8-tetrachlorodibenzo-p-dioxin). An estimated more than 45 million kg of 2,4-D (2,4-dichlorophenoxyacetic acid) and 2,4,5-T (2,4,5-trichlorophenoxyacetic acid) was sprayed over South Vietnam. Containers with the herbicides were supplied to and stored in Bien Hoa, a former military airbase in southern Dong Nai province. Until today, Bien Hoa is a site with some of the highest levels of herbicides and dioxins in Vietnam. Since these compounds are hazardous to biological life, they need to be removed from the environment.
The objective of this MSc research project is to increase our understanding of natural biodegradation processes involved in 2,4-D and 2,4,5-T degradation. Laboratory experiments will be used to determine 2,4-D- and 2,4,5-T-degrading ability by bacterial communities in time. LC/ MS/ MS (liquid chromatography followed by mass spectrometric analyses) will be used to determine concentrations of the herbicides and microbial community profiling will be determined by Illumina amplicon sequencing. In addition, key genes (tfdA and catA) involved in herbicide degradation will be quantified in these succession experiments by qPCR. Results may be of importance in understanding and improvement of bioremediation processes.
Practical
- Duration approximately 6 months, starting from September 2018
- MSc Student from Biology, Biological Sciences, Environmental sciences, Molecular Ecology, preferably with some laboratory experience
- Location: Molecular Cell Biology VU Amsterdam and VAST Institute Hanoi, Vietnam
- For more information, contact Lan Anh Nguyen (l.a.nguyenthi@vu.nl) or Rob van Spanning; (rob.van.spanning@vu.nl)"
Building a genome scale metabolic model for the fission yeast S. pombe Theoretical (Master)Johan van Heerden
j.van.heerden@vu.nl
&
Eunice van Pelt-Kleinjan
e.van.pelt-kleinjan@vu.nl
Background
The two distantly related yeast species, Saccharomyces cerevisiae and Schizosaccharomyces pombe, have been instrumental in our current understanding of the eukaryotic cell and its processes. Much of what we know about the cell cycle and its regulation was borne from pioneering studies with S. pombe, while S. cerevisiae has been a favourite workhorse in studies on eukaryotic metabolism (especially central carbon metabolism) and textbooks on this subject are therefore filled with insights derived from this organism.

While the cell-cycle field has embraced S. cerevisiae as a complementary eukaryotic model, researchers with a focus on metabolism have yet to harvest the potential insights to be gained from systematic (and comparative) studies of S. pombe metabolism. Today, the majority of research on S. pombe is still dedicated to unraveling cell cycle regulation and other cellular functions such as DNA repair, maintenance and aging, with very little fundamental research on the central metabolism of this yeast.

While there are many similarities between these two species, there are also several important differences including: cell morphology, the mode of cell division, the position of cell-size checkpoints during cell-cycle progression, the role of glucose sensors, the ability to respire ethanol, the presence of a glyoxylate cycle and differences in mitochondrial functions.

As many of the differences between these two species pertain to metabolic functions, a better understanding of the metabolic profile of S. pombe should serve to greatly expand our compendium of knowledge on eukaryotic metabolism, beyond that of S. cerevisiae and cancer cell lines.

Method
In this project you will build a new genome-scale metabolic model (GSMM) using software developed in our group, MetaDraft. This will enable the construction of a draft genome-scale model based only on a sequenced genome and a curated database of template models.

Outcome
You will use this GSMM model to predict the ability of S. pombe to produce biomass (i.e. to grow) on various carbon substrates. These predicitons can then be compared to existing and new experimental data, to improve and validate the model.

It is expected that this work will lead to a functional GSMM that will provide a valuable asset to the burgeoning field of S. pombe metabolic studies.

Duration of project: 5 months

Your CV: Ideally you will have a theoretical background and programming experience (preferably Python or Matlab).

Start date: May 2017 or later.
An optogenetic strategy to control glycolytic enzyme activityExperimental (Master)Johan van Heerden
j.van.heerden@vu.nl
Background
To make the appropriate adaptive decisions or to maintain homeostasis, cells monitor not only extracellular conditions, but also their internal metabolic state. Historically, changes in cellular physiology was considered to occur mainly in response to altered environmental conditions, but recent studies indicate that changes in metabolic fluxes can also trigger adaptations even when environmental conditions are stable. By monitoring changes in the concentrations of so called flux-sensing metabolites, cells can get information about their metabolic state, irrespective of the environmental state.

In microbes such as E. coli and S. cerevisiae, steady-state correlations between growth rate, mode of metabolism (respirations or fermentation) and certain key metabolic intermediates, have been interpreted as evidence for the existence of flux-sensing mechanisms. Particularly interesting is the possible role played by Fructose-1,6-bisphosphate (FBP).

FBP concentration correlates strongly with glycolytic flux, and several regulatory targets (allosteric and gene expression) have been described. FBP has therefore been suggested as part of the regulatory repertoire that modulates the physiological state of cells. In addition to FBP, Phosphoenolpyruvate (PEP) may be another flux-signalling metabolite. PEP mirrors the behaviour of FBP and could therefore serve to reinforce sensing of the central metabolic state.

The regulatory role played by flux-sensing metabolites have been inferred mainly from steady-state correlations, and many questions remain about the role these metabolites play in actually driving the adaptations associated with a specific physiological state and to what extent this is truly independent from the environment.

In this project we will attempt to gain further insight into the causative link between sensing of internal metabolic states and subsequent physiological adaptations to perturbations of the internal state, under constant environmental conditions. We will use an optogenetic strategy to design light-controllable variants of Phosphofructokinase (PFK) and Pyruvate kinase (PYK), which will allow for the dynamic in vivo manipulation of enzyme activities by illumination. Both these enzymes catalyse irreversible steps in glycolysis and changes in their relative activity is expected to impact the concentrations of FBP and PEP, respectively.

Using this novel strategy, we will explore the physiological adaptive responses of (single) cells to changes in their internal metabolic state, even though extracellular conditions remain unchanged.


Aims of the project
This project will have two major aims:
1) To develop light-controllable variants of Phosphofructokinase (PFK) and Pyruvate kinase (PYK), both glycolytic enzymes, using the latest optogenetic technologies
2) To assess the metabolic-adaptive responses of (single) yeast cells to PFK and PYK enzyme activity-levels modulated in real time via optogenetics

Duration
6-9 months (preferably 9 months, but the exact duration can be discussed).

Where
This project is a collaboration between the Teusink/Bruggeman group, at the Vrije Universiteit Amsterdam, and the Niopek group, at the University of Heidelberg.
The internship, therefore, offers the successful candidate the unique opportunity to spend time in both Amsterdam (The Netherlands) and Heidelberg (Germany). The first part of the project, the design and construction of light-controllable glycolytic enzymes, will be performed in Heidelberg. It is anticipated that this will take approximately 3-5 months. The second part, characterization and (single) cell experiments, will be completed in Amsterdam, and will take the remaining time 3-4 months.
Please note: The candidate will have to organize accommodation for themselves.

What we are looking for in a candidate
The ideal candidate should be motivated and up for of a challenge. Proven experience with molecular cloning techniques (PCR, digestion, ligation, transformation etc) is required and preferably some experience working with Saccharomyces cerevisiae. Experience with single cell measurement techniques, such as microscopy and flow cytometry, is a bonus, but not essential.
To memorize or to self-organize?Experimental (Bachelor)Age Tjalma (a.j.tjalma[at]vu.nl)
and Daan de Groot (d.h.de.groot[at]vu.nl)
Background

E. coli is known to exhibit diauxie: when multiple carbons sources are available it only consumes the carbon source on which it has the highest growth rate (often glucose). Only when the preferred carbon source runs out, the cells start eating the carbon source on which it has a lower growth rate (the most popular example being lactose).

It is unclear how E. coli decides which carbon source to consume first. The knowledge that consuming glucose leads to a high growth rate could be hardcoded in its genome. Alternatively, E. coli could have a regulatory mechanism that automatically selects the carbon source that leads to the highest growth rate. The main question is thus: *does E. coli memorize or adapt*?

To distinguish between these two options we want to make glucose the worst carbon source instead of the best. If E.coli memorizes, it will still prefer glucose. If it adapts, it will now prefer the alternative carbon source. This last observation would show that E. coli is much more versatile than previously thought, and would point towards 'self-organisation' within the metabolic regulation of E. coli.

In a paper by Bren et al., it is shown that the order of the maximum growth rates on different carbon sources is reversed when E. coli is grown with a single amino acid as its nitrogen source. They subsequently do a diauxie experiment, growing E. coli on a medium containing both glucose and maltotriose. It seems that E. coli then still prefers glucose, while consuming maltotriose would have led to a higher growth rate. However, this experiment might be somewhat flawed and it is therefore unclear whether the results are valid.


Methods

We firstly want to reproduce the experiment of Bren et al., where they show the reversal of the maximum growth rate order. For this we will grow the same strains in a plate reader, using glucose, lactose and maltotriose as carbon sources, and ammonia, proline and arginine as nitrogen sources.

When we have reproduced the reversal of the maximum growth rate order we will grow the cells on a mixture of carbon sources, with a sole amino acid as nitrogen source. We now want to define which carbon source each single cell is consuming, using fluorescence based Flow Cytometry and possibly microscopy.



What we expect

This is a quantitative experimental project which could lead to publishable results. We are therefore looking for a very precise student who is highly motivated to use single cell technologies to produce high-quality results. The project is challenging, but also a high reward if completed succesfully, the student should therefore be persevering and optimistic.
Determining the adaptability of Lactococcus lactis NCDO712 when grown on a poor nitrogen sourceExperimental (Bachelor)Sieze Douwenga
(s.douwenga@vu.nl)
Background
When a new environment occurs for an organism like Lactococcus lactis, different proteins, or metabolic states may be required to continue growth. L. lactis may prepare for new environments by expressing proteins that are currently not required. This often comes at a growth rate cost however. When growing quickly on the catabolite glucose, L. lactis NCDO712 is known to repress the catabolic genes required for the consumption of other sugars. When it is growing slowly on maltose, L. lactis is known to express redundant genes (not required for maltose growth). For example, L. lactis also expresses the catabolic genes required for growth on lactose and glucose, when only maltose is present.

Goal of the project
We hypothesize that the growth rate of L. lactis does not influence which catabolic genes it represses. Instead, it is likely only the presence of an excess amount high quality sugar, like glucose, that governs this behaviour. We would like to test this by growing L. lactis on glucose in medium with a poor nitrogen source –resulting in a low growth rate with a high quality sugar. Additionally, we would like to know whether glycolytic flux might be more predictive of which catabolic genes are repressed.

What you will be doing
You will run minimally two batch reactor experiments. From each reactor you will determine the product and substrate fluxes of L. lactis, through the use of HPLC and optical density measurements. Furthermore, you will determine the active catabolic pathways of L. lactis through the use of biolog plates in a platereader. Analysing the data will be fastest if you have experience with R, python or another programming language, although it could also be done in excel.

Requirements
• Background in biotechnology/biochemistry and previous experience in microbiological culturing
• Some experience with data analysis in R, python or another programming language will be useful