Internships
at the section Molecular Cell Physiology
We offer BSc and MSc internships in two
(overlapping) research areas at our section; systems biology and microbial
ecology. Internships are in principle also open for non-VU/foreign
students, click here for more information. Below you
will find a list of recent openings for student projects. If you find a particular
student project interesting, please contact the mentioned supervisor(s) to
obtain more details on the subject and its availability. For further
information, contact Dr. Wilfred Röling (wilfred.roling@falw.vu.nl, room
M220, +31 (0)20-5987192).
De sectie
Moleculaire celfysiologie doet onderzoek op het gebied van systeembiologie en microbiële
ecologie. Een lijst van studenten projecten (MSc, BSc) vind je hieronder. Als
je interesse hebt in een specifiek project kun je het best contact opnemen met
de betreffende begeleider, omdat beschikbaarheid en inhoud op korte termijn
kunnen veranderen. Voor VU BSc studenten hebben we een specifiek begeleidingssysteem opgezet.
Current
openings:
Microbial laboratory evolution of yeast under dynamic conditions (BSc, MSc)
It takes two to tango: (optimal) regulation between metabolic and
gene network (MSc)
Improving and
finalizing FiJo, a biologically inspired semi-automatic model construction tool
(BSc, MSc)
Measurement of cell division of Saccharomycs cerevisiae at the level of
single cells (MSc)
Simulations of signaling dynamics
of bacteria at the single-molecule level (MSc)
Milking
the yoghurt (MSc)
Microbiology and Society -The introduction of a probiotic yogurt in Uganda.
(MSc)
For students with interest in bioinformatics topics, please see for internship offers: http://wiki.cs.vu.nl/mp/index.php/Bioinformatics
Short descriptions of
internships
Microbial laboratory
evolution of yeast under dynamic conditions
Supervisor:
Jan Berkhout (Room N-229a, jan.berkhout@falw.vu.nl)
Project for MSc
student
Motivation
Evolution continuously moulds
biochemical networks towards optimality under various biological and
physicochemical constraints and selective pressures. Microbial fitness depends
to a large extent on adequate adaptation, involving altered gene expression
profiles and protein activities. In order to maintain a high fitness, cells
have to regulate themselves in such a way to keep some of their network
functions robust while delicately changing others. Laboratory evolution studies
provide fundamental biological insight through direct observation of the
evolution process and the corresponding fitness. I have performed such an evolutionary
experiment culturing yeast under three different experimental conditions: i) in
a glucose medium ii) in a medium containing galactose and iii) switching
everyday between glucose and galactose containing medium.
Your task
From the abovementioned evolutionary
experiment I have obtained strains which have been growing in the indicated
medium for about 600 generations (two months). This strain-collection will be
used to study:
·
The
physiological differences between the reference and evolved strains for the
three experimental conditions.
·
The
trade-off between response time and robustness. It might be expected that the
“switchers” are better anticipated for a changing environment as the two
strains which have been solely growing on glucose or galactose. Which molecular
mechanism is involved and is this anticipation at the expense of other
characteristics?
·
The
growth-rate yield trade-off (i.e. have faster growing cells a lower
yield?).
·
Measure
the enzyme capacities of the different strains and test whether these
differences (if any) correspond with in
silico predictions using a cost-benefit analysis.
·
Perform
competition experiments under different experimental conditions to test what
different cells have been optimized for (and how) during the evolution experiment.
·
Compare
the response time of gene expression for the three environmental conditions,
upon a changing environment by means of q-pcr.
Applicant should have a Bachelor degree or
equivalent.
It takes two to tango: (optimal) regulation between
metabolic and gene network
Supervisor: Jan Berkhout (Room
N-229a: jan.berkhout@falw.vu.nl)
Project for MSc student
Motivation
Microorganisms continuously face dynamics in their environment.
Microbial fitness depends to a large extent on adequate adaptation, involving
altered gene expression profiles and protein activities. In order to maintain a
high fitness, cells have to regulate themselves in such a way to keep some of
their network functions robust while delicately changing others. If a metabolic network operates at an
optimal state, say maximal flux, then it should be regulated upon an
environmental change in such a way that it attains again an optimal state. This
typically requires a (signalling and) gene network that senses changes from the
optimal state and brings about a compensatory change in expression levels of
metabolic enzymes. We have found that the coarse-grained structure of such an optimal-regulation gene network
can be predicted from a kinetic model of the metabolic network alone. This
approach is referred to as an optimal input-output relationship.
Your task
In this project you will explore the properties of
such an input-output relationship with a systems biology approach. A good
candidate system to study this is the galactose metabolic network in S. cerevisiae. Your task will be to
develop and improve existing metabolic and genetic networks of this system.
With those models we can apply an input-output approach and generate testable
hypothesis, which can be tested by performing experiments on the galactose
system.
By doing so, different questions can be explored:
i)
Can
the regulatory gene network as described in literature generate (some of) the
optimal enzyme expressions levels of the metabolic network?
ii) If question one can be verified, does the
gene network in that case still has some residual degrees of freedom in its
parameters? Where can they be used for?
iii) Why has evolution selected for certain
signallers instead of others, i.e. what makes some metabolites better
signallers than others?
Improving and finalizing
FiJo, a biologically inspired semi-automatic model construction tool
Supervisor: Joost Boele
(room M262, joost.boele@falw.vu.nl)
Project for BSc or MSc student
The
genome era has brought major changes to the way systems biology research is
performed. Where the biochemistry of individual reactions used to be the
modeler’s starting point, today, massive whole-genome reconstructions are a
laborious but potentially rewarding avenue of investigation. Genome-scale
metabolic models (GSMMs, see e.g. [1]) are all the rage, but creating a good
one has turned out to be quite challenging. The step from genome sequence to
proteins to reactions is not a trivial one, as bioinformaticians will
appreciate. Thus, so far, genomic reconstruction efforts have mainly centered
around shaking a tree and seeing what falls down: gene or protein sequences are
BLASTed and results are manually inspected; if acceptable, the associated
reaction is looked up and included in the model.
To provide a sensible alternative
to this process, we have been developing FiJo, a software tool that eliminates
much of the human involvement in this task by BLASTing against (protein)
sequences that are associated with curated chemical equations from existing
models. The bare bones of this tool are now in place. We aim to implement
biologically inspired functionality to make FiJo’s predictions more accurate,
and biologically acceptable shortcuts to make FiJo’s predictions the fastest
ones to acquire. In designing the algorithms to accomplish those things,
insight in both the computational and biological perspective is required;
subsequently quantifying the effects of these algorithms will most likely be
more of a computational challenge.
If you are interested in helping
develop and benchmark a novel approach to whole-genome reconstruction, and
perhaps doing a reconstruction of your own as you go along, then this may well
be the project for you. FiJo is currently a well-documented cocktail of PHP/JavaScript
(the front-end), Python (the back-end), Perl (for inParanoid [2]) and C (for
BLAST), so any programming experience you bring to the table will increase the
probability of successfully completing this project (code need only be produced
in Python and the web languages, though).
[1] Terzer M et al.: Genome-scale
metabolic networks. Wiley Interdiscip Rev Syst Biol Med 1(3): 285-97.
[2] Ostlund G et al.: InParanoid 7: new algorithms and tools for eukaryotic
orthology analysis. Nucleic Acids Res. 38(Database issue):D196-203.
Measurement of cell division of Saccharomycs cerevisiae at the level of single cells
Supervisor:
Frank Bruggeman (room F-240; f.j.bruggeman@vu.nl) and Yves Bollen
For: Master student biology or biophysics
Saccharomyces cerevisiae, aka
Baker’s yeast, is used in the food industry for bread and beer production. It
is an organism with a flexible metabolism that supports growth under a variety
of carbon sources. To better understand how yeast adapts to varying conditions,
the student will study the growth rate dynamics of single
yeast cells when it is confronted with a shift in glucose to ethanol
conditions. This phenomenon is well documented for population of yeast cells
but not at the single cell level. In this project, the master student uses
time-lapsed microscopy to make movies of dividing yeast cells and will use
image analysis software to determine the growth rate of cells at the single
cell level to assess cell-to-cell variability.
Simulations
of signaling dynamics of bacteria at the single-molecule level
Supervisor:
Frank Bruggeman (room F-240; f.j.bruggeman@vu.nl)
Mathematical modeling project for a master student
(background: systems biology, bioinformatics, engineering, (bio-)physics,
mathematics)
 |
Escherichia coli, and most other bacteria, use two-component signaling systems to sense changes in their environment and regulate gene expression to initiate an adaptive response. In this project, we will develop a mathematical model of two-component signal transduction to study its spatial and stochastic dynamics. We model the fates of individual molecules in the membrane as well as the cytoplasm to simulate induction of two-component signaling and gene expression regulation. We will use the software package MesoRD (http://mesord.sourceforge.net). An example of the outcome of such a simulation is shown below.
If you are interested in this topic and enjoy a
little bit of programming and testing software, then please send an email to f.j.bruggeman@vu.nl.
Supervisors: Ruchir Khandelwal/Wilfred Röling/Frank
Bruggeman: room M214: ruchir.khandelwal@falw.vu.nl
Project for MSc student
Aim
To evolve the “interactions”
between bacteria in yoghurt consortium
Description
When lactose in
milk is fermented to mainly lactic acid and exo-polysaccharides by the
interactions between two lactic-acid-bacteria, Lactobacillius bulgaricus and Streptococcus
thermophilus, yoghurt is made. L. bulgaricus has an exoprotease enzyme
that breaks down milk-casein into smaller peptides outside the cell; it takes
up these peptides, further breaks them down to amino acids, consumes these
amino acids for its growth and spills the extra amino acids out of the cell.
And, S. thermophilus cannot break
down milk casein, so it takes up these extra amino acids and in return provides
mainly formate and folate to L.
bulgaricus.
As there is some
amount of free amino acids, formate and folate in typical milk, there is no
need for these microbes to interact at the beginning of their mixed culture
growth. But, when one of these cross-feeding metabolites runs out, these
microbes have to depend on the other one, and that’s when they form a stable consortium.
To further
understand this stable consortium situation, we are going to evolve these
microbes together in a cultured milk (devoid of cross-feeding metabolites like
free amino acids, formate and folate), where the interactions would be
established from the beginning of their mixed culture growth. Once an evolved
consortia is achieved, after some large number of generations, we will do some
growth experiments to measure their mixed-culture growth (using qPCR),
metabolite consumption and production rates (using HPLC) and other parameters.
This data will
then be used as input for the steady state, stoichiometric model of the
consortia, made using genome-scale metabolic network models of both the
organisms.
So, you see, we
will be asking so many questions, and changing so many parameters from yoghurt
while learning new and new things about the interactions that is required for
the yoghurt; we will essentially be “milking” the yoghurt.
Supervisor: Remco Kort: room F240: remco.kort@tno.nl
Background
Wiki: Listeria
monocytogenes
is one of the most virulent foodborne pathogens, with 20 to 30 percent of
clinical infections resulting in death. Responsible for approximately 2,500
illnesses and 500 deaths in the United States (U.S.) annually, listeriosis is
the leading cause of death among foodborne bacterial pathogens.
Approach
Cultures of the foodborne pathogen Listeria monocytoneges were exposed to 5
widely applied disinfectants in a range of inhibitory and sub-inhibitory concentrations.
The genome-wide transcriptional response was monitored after RNA isolation,
labelling and hybridizations with oligonucleotide-based microarrays.
Aim
The
aim of this study is to evaluate the gene expression data, check for the
induction of virulence genes as a result of sub-lethal exposures to
disinfectants, and analyze the underlying transcriptional programs
Tasks - no experimental work involved
1.
Literature research
2.
Microarray data (gene expression) analysis (TIGR MeV package)
3.
Comparative analysis of novel and reported gene expression data
4.
Writing of a scientific report / publication
Reference
Toledo-Arana
et al (2009) The Listeria transcriptional landscape from saprophytism to
virulence. Nature 459:950-6.
How to apply
Send a motivation letter (1 A4) to remco.kort@tno.nl
Supervision
by Remco Kort on Mondays, VU University, room F240.
Supervisor: Remco Kort: room F240: remco.kort@tno.nl
Background
Wiki: Clostridium botulinum is a Gram-positive, rod-shaped bacterium that
produces several toxins. The best known are its neurotoxins, subdivided in
types A-G, that cause the flaccid muscular paralysis seen in botulism. It is
also the main paralytic agent in botox. C.
botulinum is an anaerobic spore-former, which produces oval, subterminal
endospores and is commonly found in soil.
Approach
A
gene bank was constructed of a number of C. bot strains and other clostridia.
Mixed species microarrays were constructed and DNA from a large number of C bot
and other clostridia was hybridized, showing genome-wide gene profiles.
Aim
The
aim of this study is to identify and analyze the function of specific genes,
which allow distinction of C. botulinum
from the closely related C. sporogenes.
Tasks - no experimental work involved
1.
Literature research
2.
Analysis of genome-genome hybridization data (TIGR MeV package)
3.
Phylogenetic tree construction and comparative genomics analysis of novel and
reported data
4.
Writing of a scientific report / publication
Reference
Peck, M. W. "Biology and genomic analysis of Clostridium botulinum."
Adv.Microb.Physiol 55 (2009): 183-265, 320.
How to apply
Send a motivation letter (1 A4) to remco.kort@tno.nl
Supervision
by Remco Kort on Mondays, VU University, room F240.
Microbiology and Society -The introduction of a probiotic yogurt in Uganda
(MSc).
Fermentation, Formulation, Comparative Genomics,
Marketing, Sustainable Business
Supervisor: Remco Kort: room F240: remco.kort@tno.nl
Introduction:
To date most probiotics
(bacteria which confer a health benefit to the host) are produced and added to
food products without being actively involved in the food fermentation process.
This procedure is associated with relatively high production costs, and
excludes the production of bioactives in the final food product. In this
project we aim to develop a fermentation protocol for an affordable probiotic
yogurt fermented by the probiotic strain of Lactobacillus rhamnosus and regular yoghurt strains. The product is
planned to be produced and distributed in developing countries. This
project is tightly linked to the activities of two interns that currently
formulate and develop probiotic yoghurt under challenging conditions in Uganda
(see www.yoba4life.com).
Tasks:
Compare the genomes of L. rhamnosus (an intestinal isolate) prior to and after milk
fermentation and check for adaptations.
Develop a protocol for a probiotic yoghurt by
setting up a combined milk fermentation by L. bulgaricus, S.
thermophilus and L. rhamnosus
Assess the viable count for each of these bacteria
and assess the individual growth pattern of the three strains during fermentation
Carry out a sensory
evaluation for the fermented milk products
Procedure:
Candidate(s)
will be selected on the basis of a motivation letter (1 A4) for this
intern.
A
related internship under challenging conditions can be performed in Uganda (see
www.yoba4life.com)
Supervisor: Remco Kort: room F240: remco.kort@tno.nl
Background:
Seventy percent of the global HIV infections or AIDS cases are in Africa,
and here the situation is complicated by the fact that many of the infected
patients cannot afford current conventional treatments and often do not even
have access to basic healthcare. There is a consequent increase in the use of
traditional medicine, often with reports of improvement in the well-being of
infected patients taking these treatments. These unconventional treatments,
often made up of highly complex plant based mixtures, cannot be ignored or
dismissed by scientists around the world who are looking for new treatments for
this disease and its secondary infections.
Aim and methods:
As the herbal preparations have been
reported to relieve symptoms of AIDS (diarrhoea), this project aims at evidence
for antimicrobial effects of herbal fractions and evaluate effects on the composition of the
intestinal microbiota by the use of an in
vitro intestinal model system. A representative intestinal microbiota has
been exposed to plant extracts from Tanzania for 24 hours. Subsequently, shifts
in the microbiota composition have been determined by the use of an intestinal
microarray chip (I-chip), developed at TNO Microbial Genomics (Zeist). Briefly,
16S rRNA genes of the intestinal model population have been amplified, labeled
and hybridized with pre-selected genes of ~ 400 intestinal species on the
I-chip. Accordingly, shifts in the microbial population can be monitored as a
result of ingredient addition.
Tasks:
- Short literature search and report on experience and evidence-based
health systems
- Microarray data analysis for determination of effects of herbs on the
human intestinal microbiota in a model system
- Comparative analysis with effects of other herbs on the intestinal
microbiota
- Conclusions
Procedure:
Candidate(s)
will be selected on the basis of a motivation letter (1 A4) for this
intern.
A
related internship under challenging conditions can be performed in Tanzania or
Uganda.
Begeleiding van bachelorstages bij de sectie Moleculaire
Celfysiologie
Elk jaar wordt een aantal onderwerpen aangeboden op
een tweetal (overlappende) deelgebieden: systeembiologie en microbiële
ecologie. Systeembiologie is de
werking van biologische systemen leren begrijpen op basis van detailkennis van
de processen in het systeem en de opbouw (structuur, organisatie) van dat
systeem. Dat betekent dat vragen (en antwoorden) vaak kwantitatief zijn, dat
experiment en model nauw verbonden zijn en dat men op zoek is naar nieuwe
algemene principes op dit gebied. Onderwerpen in deze sfeer komen in de sectie
vaak voort uit medische vraagstellingen (diabetes, kanker, parasitaire
infecties), maar ook biotechnologische en ecologische problemen worden op deze
manier onderzocht.
Microbiële ecologie richt zich op de rol van microben in ecologische systemen,
in relatie tot de chemische en biologische omgevings processen en factoren
zoals predatie. De onderzochte ecosystemen variëren van verontreinigde bodems
tot de condities voor leven op de planeet Mars. Bij dit onderzoek worden
systeembiologische methoden toegepast, en worden moleculaire technieken en het
geadvanceerd kweken van microorganismen gebruikt om kwantitatief inzicht te
krijgen in het functioneren van microbiële ecosystemen.
Begeleiding Elk student heeft zijn eigen begeleider, maar als back-up
organiseren we "studentenbesprekingen" (afhankelijk van het aantal
studenten binnen de afdeling) om het verloop van de stages te optimaliseren.
Deze besprekingen (die elke twee tot drie weken plaatsvinden) worden bijgewoond
door alle stagiaires van de afdeling en hun begeleiders. Op deze bijeenkomsten
bespreekt een klein aantal studenten de voortgang (resultaten, problemen) van
hun onderzoek, in eerste instantie met de collega-studenten, en in tweede
instantie met de begeleiders. De bijeenkomsten hebben als doel training van
presentatie en discussie vaardigheden in een minder intimiderende omgeving, en
het opvangen van incidentele afwezigheid van begeleiders. Er wordt naar
gestreefd dat elke student tijdens de stage periode ca. drie keer aan de beurt
komt. Na afloop van de stage is er uiteraard ook de gebruikelijke
eindpresentatie tijdens afdelingswerkbespreking.
Internships are in principle open for students from
other universities in the Netherlands or outside the Netherlands. For instance,
we welcome ERASMUS students. Please note a few things:
-
We ask
for a minimum stay of 4 months (3 months research, one month report writing)
with a starting date outside the holiday season (July, August).
-
You have
to be able to support your daily expenses (e.g. food, accommodation) and
travelling to/from the Netherlands. Often, the international office at your own
university can assist you in obtaining grants (e.g. ERASMUS grants). You may
also check http://www.nuffic.nl/international-students/scholarships/grantfinder.
Research costs will be covered by the internship project. We can help you with
providing letters etc. for applications.
-
Finding
accommodation in Amsterdam often takes 3 to 6 months. We can help you via our
international office with arranging accommodation in the VU hospitium in Amsterdam,
but please contact us at least three months before your preferred starting date
(and earlier if you want to start in September, October or November).
-
Students
from outside the EU should take into account that they may require a visa for
the Netherlands, and that arranging this may also take a few months. Please
check with the Dutch embassy in your country.
Please contact Wilfred Röling (wilfred.roling@falw.vu.nl) if you
want to do an internship in our group, and indicate your preferred project(s),
starting date, length of internship, how you will support yourself (costs for
food, accommodation) and whether you need help with finding accommodation