PROJECT CATALOG 2020 SciLifeLab Stockholm Summer Fellow program
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2020
PROJECT CATALOG
SciLifeLab Stockholm Summer Fellow program
1
1. Impact of hormone signalling in colorectal cancer - microbiome, RNA-Seq and database
analysis
PI: Cecilia Williams’ lab, Experimental Oncology
Supervisor: Linnea Pettersson, PhD student
We are looking for a student interested in bioinformatics work. We have a lot of large-
scale data that needs to be analyzed and the project can be formed according to the
student’s interest.
We are studying estrogen signaling in colorectal cancer. Estrogen hormones protect
against colorectal cancer (CRC) in women and a preventative role of estrogen receptor
beta (ERβ) on CRC has been supported using full knockout animals. However, it is
unclear how and through which cells or organ ERβ mediates this effect and if ERβ has
any impact in the male colon. To investigate the functional role of intestinal ERβ during
colitis-associated CRC we used intestine-specific ERβ knockout mice of both sexes
treated with azoxymethane and dextran sodium sulfate. Our results show that intestinal
ERβ is protective against tumor formation in both sexes by modulating the NFκB
signaling pathway. We have also performed whole genome sequencing (WGS) of the
microbiota composition to see how/if the microbiota can contribute to the CRC protective
effects of ERβ.
The project includes analyzing the WGS results to find differentially abundant microbial
species between wild type and intestine-specific ERβ knockout mice, and study if there
are any sex-differences. Some of the findings will also be confirmed using quantitative
PCR. A PhD student will supervise the work.
• Analyze WGS metagenomics data.
• qPCR confirmation of interesting findings.
We have found a protective role of intestinal estrogen receptor beta and there are sex-
differences in the risk of colorectal cancer. There is a need to investigate potential sex
differences in biomarker discovery, which may be one of many reasons why a lot of
biomarkers fail to reach the clinic. Sex-specific strategies for screening, prevention and
treatment should be considered in order to reduce the CRC mortality. We have RNA-
sequencing from matched normal and clinical colorectal cancer material from both sexes
that has been analyzed for differentially expressed genes to find diagnostic biomarkers.
We found sex-differences in the top biomarkers and would like to perform survival
analysis of TCGA data for the different sexes to find potential sex-specific prognostic
biomarkers. In addition, since we have paired normal and cancer samples it is ideal
material to study somatic mutations and see if there are any-sex differences. The project
work requires the student to work independently but will include discussions with the
supervisor in the form of a PhD student.
• Analyze TCGA for survival analysis.
• Analyze RNA-sequencing data for somatic mutations.2. Next generation multianalyte assays for liquid biopsy
SciLifeLab Stockholm Summer Fellow 2020
Project proposal for internship at the Plasma Profiling National Facility (PPNF)
Title:
Next Generation multianalytes assays for liquid biopsy
Supervisor: Claudia Fredolini, PhD, Head of Plasma Profiling National Facility (PPNF)
Project description:
PPNF mission is to support clinical and academic researchers carrying large biomarkers studies in
biological fluids using affinity proteomics technologies. The facility, has a strong focus on translational
research and precision medicine. We are equipped with cutting edge analytical instrumentation to
perform bead-based multiplex immunoassay and ultrasensitive single molecule quantification and we are
committed to a continuous technology development to offer new strategies to quantify clinical relevant
targets in biological fluids.
The concept of liquid biopsy in precision medicine, refers to different class of analytes detectable in
patient blood samples such as proteins, glycans, DNA and RNA. Currently, multiple technologies are
implemented to profile different targets, and a future need for multi-analyte assays has been envisioned
(Mattox et al, Science Translational Medicine 2019).
The student joining PPNF during the summer, will be part of our new initiative aiming to develop a next-
generation assay concept, where, we will explore potentials and challenges of multi-analytes detection.
She/he (i) will be involved in affinity reagents and targets selection; (ii) will experience crucial aspects in
the development of assays in bodyfluids such as dynamic range, cross-reactivity, and multiplex potential;
and (iii) will have the opportunity to get hands-on experience with the latest instrumentation in the
immunoassay field.
The student will be supervised directly by the Head of PPNF and in the lab by expert research engineers.
The scientific environment will include also a bio-informatician, a Post-Doc and a PhD student associated
to the facility (members of the Schwenk Lab team).
Techniques student will get familiar with:
Chemical coupling of affinity reagents to beads
Bead-based immunoassays (Luminex Technology)
Digital read-out immunoassays (Quanterix SRX Simoa Technology)
Use of automated systems for processing magnetic beads and precision liquid transfer.
Software for immunoassay data analysisResearch project for a SciLifeLab Stockholm summer student
3 “Deciphering mechanistic roles of regulatory RNAs
using cutting-edge experimental and computational tools”
A. Responsible PI and supervisor
Claudia Kutter (group leader), Ionut Atanasoai (PhD student) and Jonas Sondergaard (Senior
research specialized) at KI-MTC, SciLifeLab Stockholm fellow
B. Description of scientific project
Over 200 specialized cells with diverse morphologies and functions exist in the human
body, yet virtually every cell in the body contains the same genetic information. That means
that high fidelity mechanisms evolved to restrict the synthesis and processing of specialized
regulatory RNAs in order to exert cell-specific functions. By using state-of-the-art deep
sequencing technology and comparative genomics, our group investigates the genetic and
transcriptional control of gene expression in mammalian cells. We have identified that
transcription of coding and noncoding RNAs is entwined to ensure proper cellular function.
This process is dynamic and tightly controlled when a cell is undergoing normal differentiation
during development but gets unhinged when cell transforms into a malignant state.
The research project of the summer student is embedded in the ongoing research activities
of the group. It is designed to study the processes that regulate gene expression and processing
of RNA molecules by combining computational and experimental techniques. In particular, the
student will (i) perform transcriptomic analysis in cancer cells to identify cancer-driving
abnormalities, (ii) study RNA signatures that are altered in cancer cells compared to healthy
cells to discover molecular differences and (iii) perform functional cell-based assays to
understand the impact of these molecular differences in normal cell development.
C. List of techniques the student will use
The student will use techniques established in the group. Experimentally, the student will learn
tissue culturing (hepatocytes and liver cancer cell lines), cell-based assays (cell viability, cell
cycle arrest and kinase activity), basic molecular techniques (RNA isolation and common
cloning techniques), loss- and gain-of-function experiments (siRNA, CRISPRi and CRISPRa),
recently developed advanced techniques for next generation sequencing (RNA enrichment,
library preparation and NextSeq 500 sequencing [our group shares the sequencing machine
allowing fast sequencing turnover]). Computationally, the student will evoke command lines to
assess sequencing quality (FastQC), align sequencing reads to the reference genome (Tophat2),
count transcripts (HTSeq) and perform differential gene expression analysis (DESeq2). The
techniques can be adjusted according to the student’s prior experience.
D. Short plan for supervision of intern
The research plan is based on experimental and computational research expertise in my
laboratory and aligns well with the educational background of a master student. It involves
understanding and gaining knowledge in the described research area, advancing of technical
abilities and critical assessment of the research results in the scientific context. The project is
designed to achieve completion within eight weeks.
E. Intern supervision
I will be the main supervisor and have regular update meetings with all my group members.
Ionut Atanasoai and Jonas Sondergaard (two highly experienced researchers in the Kutter lab)
will support the supervision. This project is part of our research efforts in the lab and the
successful contribution of the student will be acknowledged in the planned research
publication. There is the opportunity to extend and continue the project in form of a master
project.4. Structure-function studies of drug binding to ligand-gated ion channels PI: Erik Lindahl, erik.lindahl@scilifelab.se Supervisor: Rebecca J (Reba) Howard, rebecca.howard@scilifelab.se Title: Structure-function studies of drug binding to ligand-gated ion channels Description: Drugs such as alcohol, anesthetics, and insecticides have important effects on the human nervous system, mediated at least in part by allosteric modulation of ligand- gated ion channels. However, due to a lack of high-resolution structural data, the mechanistic basis for these effects remain poorly understood. In this project, you will characterize drug modulation in a ligand-gated ion channel using laboratory and/or computational methods. Areas of focus may include electrophysiological studies of receptor function, preparation and analysis of data from cryo-electron microscopy, and/or computational modeling of ion channel structure and dynamics. Whatever your focus, all team members will be engaged in regular interdisciplinary interaction with specialists in other areas. Techniques may include: Molecular biology, oocyte electrophysiology, pharmacological data analysis, structure visualization, homology modeling, molecular dynamics simulations, protein purification, cryo-electron microscopy sample preparation and data analysis Short plan for supervision: Professor Lindahl will supervise project direction, periodic status reports, large-scale goals and assessments. Senior Researcher Howard manages the ion channels team, including currently active PhD and Master’s students, and will supervise daily training, data collection and analysis, weekly group meetings/journal clubs with other team members, and project reports as needed. Person responsible for salary payment: Ann Nielsen, Department of Biochemistry & Biophysics, Stockholm University, ann_n@dbb.su.se
5. Mass Spectrometry-based Protein Quantification Using Novel Enzymes
RESPONSIBLE PI AND SUPERVISOR
Fredrik Edfors, fredrik.edfors@scilifelab.se (PI); David Kotol, david.kotol@scilifelab.se (Supervisor)
DESCRIPTION OF SCIENTIFIC PROJECT
Proteomics, the large-scale analysis of proteins by mass spectrometry is a technology driven field that has
developed into an indispensable tool for biomedical research in recent years. Understanding and generating
high-quality proteomics data is a multifaceted task that requires many decisions to be made upfront to get
the most comprehensive information from an experiment. Bottom-up proteomics is the most commonly
used method today used to identify and quantify proteins. This is done by first digesting the proteins into
peptides, which is almost exclusively performed by trypsin as the proteolytic reagent (1). This enzyme
cleaves protein sequences after R or K but not if followed by P. This generates a peptide repertoire with
high specificity but is also limiting the analysis to proteins based on their sequences. The proteomics
community has begun to explore alternative proteases to complement trypsin and to overcome the problem
and increase the coverage of proteins (2).
The introduction of Stable Isotope Standard (SIS) peptide or protein fragment standards into proteomics
experiments has been a successful approach to improve the quantitative accuracy and precision.
SIS proteins display identical physiochemical properties and chemical reactivity as their non-labeled
counterparts and proteins are usually labeled at the arginine (R) or lysine (K) residue. The Human Protein
Atlas (HPA) project has generated a resource of isotope labeled reagents (3) aimed towards proteins present
in our blood. These standards show great quantitative precision (4) and all tryptic peptides originating from
this resource contain heavy stable isotopes following trypsin digestion. A compliment to trypsin would be
to use LysargiNase (5) that cleaves protein and peptide substrates N-terminal of lysines and arginines with
even higher specificity than trypsin. This would generate a novel and previously unexplored set of peptides
suitable for quantitative proteomics. This project aims at exploring the benefits of using LysargiNase for
blood plasma proteomics, quantifying clinically interesting proteins and potentially FDA approved protein
targets previously unreachable if using trypsin alone. The project is closely related to ongoing research but
not overlapping with any current efforts. The student will be able to plan labwork independently but will
be co-supervised by FE and DK.
THE STUDENT WILL
1. Learn the basics of mass spectrometry-based proteomics.
2. Operate orbitrap and triple quadrupole instruments (under supervision).
3. Learn state-of-the-art targeted proteomics software (i.e. Skyline, Panorama).
4. Perform digestion of blood plasma proteins using a novel enzyme and evaluate the results
independently.
5. After the summer be able to plan, design and perform targeted proteomics experiments.
REFERENCES
1. Tsiatsiani L, Heck AJR. Proteomics beyond trypsin. FEBS J. 2015 Jul;282(14):2612–26.
2. Giansanti P, Tsiatsiani L, Low TY, Heck AJR. Six alternative proteases for mass spectrometry-based proteomics beyond trypsin. Nat Protoc. 2016
May;11(5):993–1006.
3. Edfors F, Forsström B, Vunk H, Kotol D, Fredolini C, Maddalo G, et al. Screening a Resource of Recombinant Protein Fragments for Targeted
Proteomics. J Proteome Res. American Chemical Society; 2019 May 28;18(7):2706–18.
4. Hober A, Edfors F, Ryaboshapkina M, Malmqvist J, Rosengren L, Percy AJ, et al. Absolute Quantification of Apolipoproteins Following Treatment
with Omega-3 Carboxylic Acids and Fenofibrate Using a High Precision Stable Isotope-labeled Recombinant Protein Fragments Based SRM Assay.
MCP. American Society for Biochemistry and Molecular Biology; 2019 Dec 1;18(12):2433–46.
5. Huesgen PF, Lange PF, Rogers LD, Solis N, Eckhard U, Kleifeld O, et al. LysargiNase mirrors trypsin for protein C-terminal and methylation-site
identification. Nature Methods. Nature Research; 2014 Nov 24;12(1):55–8.6. New modes of optical bio-imaging using reversible switchable fluorescent proteins
PI: SciLife fellow, Associate Professor Ilara Testa, PhD.
Supervisor: Dirk Ollech, PhD.
Motivation/Project description:
New modes of optical bio-imaging using reversible switchable fluorescent proteins
One focus of the Advanced Optical Bio-Imaging Lab is to employ reversible switchable fluorescent proteins
(rsFPs) for Reversible Saturable Optical Fluorescence Transitions (RESOLFT) super resolution microscopy.
RESOLFT super resolution microscopy, also referred to as nanoscopy, allows us to lower the spatial
resolution by switching the fluorophores of rsFPs between molecular ON and OFF states, which inhibit or
permit their ability to fluorescence if exposed to visible light. Recently, we developed rsFPs with modified
photo-physical properties, that enable new modes of multicolor nanoscopy in living mammalian cells.
Furthermore, we set out to exploit the “long-lived” (µs-ms) molecular states to measure molecular
dynamics that are not accessible with present optical techniques.
The summer fellow will be involved in an ongoing project to develop new modes of RESOLFT imaging.
He/she will create fusion constructs of rsFPs with different target proteins or functional peptides via
molecular cloning. The fusion constructs will be purified from bacterial cultures for biophysical
characterizations and measurements of molecular dynamics in vitro. These will involve e.g. protein
immobilization on specifically modified surfaces for calibration measurements. Afterwards, the imaging
modes that have been tested positive in vitro will be applied for measuring the dynamics of biomolecules
inside living cells.
Techniques to use/learn:
- Molecular cloning
- Expression, purification and characterization of recombinant proteins from bacterial cultures
- Surface functionalization for protein immobilization
- Gene transfer and expression of recombinant proteins in mammalian cells
- Live cell super resolution imaging with custom made, state of the art RESOLFT microscopes
- Testing new modes for RESOLFT imaging7. Interpreting the diversity of cancer cells in tumors using machine learning
algorithms inspired by evolution
PI and supervisor
Jean Hausser jean.hausser@scilifelab.se
Project description
Tumors are made of millions of cancer cells. These cells express different gene expression programs.
These differences make it difficult to choose a therapy: there is always a chance that some cancer cells
in the tumor express a gene expression program that protects them against therapy. For this reason, it is
important to understand the gene program differences between cancer cells within a tumor.
The recent years have seen a lot of progress in describing these differences, for example by using single
cell genomics to explore the diversity of cancer cells. But we still don’t know how these differences
can be explained. For example, are cancer cells different because of random differences in gene
expression? Or are there rules that explain why cancer cells express different gene programs? If there
are such rules, what are these rules? And how can we use them to design better therapies?
These are questions that we are currently investigating in the lab. To explain the diversity of cancer
cells in tumors, we analyze single cancer cell gene expression data using machine learning algorithms
that we designed. The design of these machine learning algorithms is inspired by the theory of
evolution because cancer is thought to be a case of evolution inside the body.
The aim of this project will be to learn and apply these machine learning algorithms to recent single
cancer cell gene expression datasets in order to explain the diversity of gene programs expressed by
cancer cells in terms of evolutionary theory.
Techniques that you will learn
• Analyzing large gene expression data matrices
• Machine-learning techniques: archetype analysis, principle components analysis, non-linear
embeddings
• Software: R, the Seurat package for single-cell genomics, Linux
• Statistical tests: t test, Mann-Whitney, Anova, Fisher test, …
• If time allows: combining different datasets (mutations, pathways, spatial gene expression)
through bioinformatics to interpret diversity of gene programs among cancer cells
This project fits in the main research direction of the lab – read more at http://www.hausserlab.org.
The tasks build up on previous work by lab members and may be integrated with those of a postdoc
with computational background, pending an ongoing recruitment process.
Economics and administrive contact
Head of HR at KI/CMB Margaret.Ulander@ki.se
Head of Finance at KI/CMB Eva.Hoglund@ki.seTitle:
8. Elucidating genomic architecture and interactions in 3D using fluorescence in-situ
hybridization
Description:
In eukaryotic cells, the cell nucleus is highly spatially organized, perturbations of the nuclear
structure and of the three-dimensional (3D) architecture of the genome inside the nucleus
have been associated with deregulation of gene expression and diseases. Herein, we will
apply our expertise in fluorescence in-situ hybridization (FISH) to illuminate the 3D genomic
architecture and interactions in nucleus. Our major goal is to draw the fractal shapes of
various chromosomes, so as to gain a deeper insight into the chromosomal territories and
intermingling.
The flow of this project is simple and straight forward. Specific probes targeting the regions
of interest will be produced, which will be used to hybridize onto the targets subsequently.
Fluorescent microscope will be employed to detect the probes. Finally, data analysis will
illustrate the fractal shapes and territories of labelled chromosomes. To expand further,
various cell lines will be subjected to the test, with the purpose to examine any potential cell
line specific patterns.
Major techniques involved:
• PCR
• FISH
• Wide field fluorescent microscopy
• Cell culture
Supervision plan:
The master student will be supervised by Su Wang (a postdoc in our group, su.wang@ki.se)
throughout the intern.
Administrative contact: Emma Inns (emma.inns@ki.se)9. Viral DNA packaging with internal-coordinate modeling and CryoEM: software developer DNA is packaged in many icosohedral viruses in an approximate spherical helix pattern. Thus it is very useful to have a fast way to generate DNA whose axis follows a spherical helix, as a starting point for fine grained fitting. An early algorithm for this has enjoyed initial success in a collaborating experimental Cryo Electron Microscopy lab, though computer time is an issue. The Fellow will examine the current code and make limited changes which will greatly reduce computer time. The changes will replace current dynamics-based methods with explicit translation-rotation operations. The Fellow will learn: 1. A limited amount of C++, as required to make modifications to a restricted region of existing code 2. Translation-rotation matrix algebra, for the purpose of placing nucleic acids in the correct position and orientation to follow both local DNA helix geometry and the large-scale helical spiral. 3. Practical aspects of working with nuclear coordinate and density data The fellow will be supervised by the PI most of the summer. Arrangements for when the PI is away on travel have been / will be discussed with interested students. Economy will be handled by Ann Nielsen
10. Viral DNA packaging with internal-coordinate modeling and CryoEM: molecular modeling DNA is packaged in many icosohedral viruses in an approximate spherical helix pattern. To fit DNA into low-resolution density maps of viruses, we first generate an idealized DNA geometry which follows a spherical spiral. Then we use the Phenix density map fitting software to adjust fine details of the DNA geometry to better explain the experimental density. However Phenix is developed more for proteins than nucleic acids, and the result has been unsatisfactory in terms of quality and labor requirement. We have our own multiscale modeling package, MMB, which performs many tasks including fitting, which is suitable for very large complexes and in particular nucleic acids. The Fellow will use MMB to refine the DNA conformation, much as Phenix would except that (1) chemistry and double-helical parameters would be respected throughout, (2) only a limited window of DNA would be fitted at one time, with the endpoints constrained to the remaining helical-spiral DNA, and (3) the process would be automated, with a simple script moving the flexibility window. The method has been tested in an ongoing collaboration with an experimental CryoEM lab, but needs further development. The Fellow will learn: 1. Multiscale molecular modeling with MMB, including its simple scripting language 2. Practical aspects of working with nuclear coordinate and density data 3. Structural biology of DNA packaging in viruses The fellow will be supervised by the PI most of the summer. Arrangements for when the PI is away on travel have been / will be discussed with interested students. Economy will be handled by Ann Nielsen
11. Finding the mystery vitamin B12 producer
• Name of PI: Sarahi Garcia
• Short description of project
Finding the mystery vitamin B12 producer
Aquatic ecosystems tremendously influence our quality of life. Microorganisms inhabiting
such ecosystems are responsible for the adequate cycling of elements, including carbon.
Nearly half of all photosynthesis happens in the aquatic systems, in communities of
microscopic microbial plankton. Vitamins are important factors that control microbial
communities. The most abundant microbial components of aquatic systems depend on
vitamin B12, however they do not produce it. Part of the proposed project is to mine data to
find the producers of vitamin B12. In the project, we will combine existing and currently
collected data on chemical characteristics and microbial processes in 40 water bodies from
Europe and North America, cultivated model communities and single cell isolation
approaches. The project aims at characterizing the microorganisms responsible for vitamin
B12 production in aquatic ecosystem
• Bullet-point list of techniques student will use/learn
o Quantitative skills and experience in the computational analysis of genomic
and biological data
o Programming and R
o Analyse and interpretation of data from large scale sequencing projects
o Data mining and integration, including the visualization and interpretation of
complex data sets
• Explicitly state what type of supervision intern will have during the 8 weeks. For example,
are the tasks intertwined with work of a Ph.D. student or postdoc, or is the project a “stand
alone” ?
o The project is intertwined with a postdoc project12. Investigation of host immune pathways during Zika virus infection and treatment with a novel
antiviral compound
Scilifelab Summer project proposal
PI: Prof. Thomas Helleday
Direct supervisor: Aleksandra Pettke, MD, PhD Student
Place: Helleday Laboratory, SciLifeLab Stockholm, OnkPath, KI
Timing: summer 2020
Contact: aleksandra.pettke@scilifelab.se
Economy Handling: Teresa Sandvall: teresa.sandvall@scilifelab.se
Investigation of host immune pathways during Zika virus
infection and treatment with a novel antiviral compound
The re-emergence of Zika virus in the Americas in 2015 caused a major public health crisis
all over the world. Although infection by Zika virus usually causes only mild and short
disease with symptoms like cutaneous rush and fever, it has also been linked to serious
neurological disorders such as severe microcephaly in fetuses, if women are infected during
pregnancy.
Latest research has shown activation of inflammatory host pathways through infection by
Zika virus in neuronal cells. These pathways can lead to either an uninflammatory cell death
through apoptosis, or to an inherently inflammatory process called pyroptosis. However, it
is still poorly understood, how the different forms of cell death are triggered, and the
determinants of one or the other pathway are unclear.
At Helleday laboratory, we have developed and characterized a small molecular inhibitor
with antiviral properties against Zika virus infected cells. Now we aim to investigate the
host reaction caused by Zika virus infection and determine how it is modulated by the
newly identified antiviral compound. To answer this question, we will study gene
expression levels of key immune genes and cell death pathways after infection with Zika
virus and treatment with our inhibitors.
The overall aim of this project is to investigate in detail how our compounds influence host
pathways which are altered by Zika virus infection.
Specific objectives:
✔ Objective 1: Gene expression analysis of regulatory and downstream genes in
key immune pathways upon Zika virus infection and treatment with
compounds from our library.
Our lab’s existing data from RNA arrays in Zika virus infected and treated U87 cells will
be evaluated. Expression of a few key immune genes upon infection with Zika
virus and treatment with our compounds will be validated in U87 glioblastoma
cells by qPCR.✔ Objective 2: Investigation of cell death after Zika virus infection and upon
treatment with our compounds in U87 glioblastoma cells
Various subsets of caspases indicative of apoptotic or pyroptotic cell death will be
analysed together with several Zika virus proteins and in cell lysates from
infected and treated U87 cells.
Skills and competences to be acquired (learning outcomes):
1. Extensive cell culture knowledge
2. RNA extraction and quality control
3. qPCR and gene expression analysis
4. Western Blot analysis of host and virus proteins
5. High-throughput imaging techniques and analysis
6. Theoretical knowledge about innate antiviral immune mechanisms
7. Experiment planning, big data analysis and data interpretation
Supervision:
- This project covers a small aspect of Aleksandra’s PhD project
- Aleksandra will be working all summer to ensure close supervision during the
period the student will join the lab
- Supervision is envisioned the following way: Upon starting the internship, the
student will be introduced to lab routines, safety rules and risk assessments. Especially
during the first week, the student will follow Aleksandra closely in the lab and all
techniques will be explained in detail while Aleksandra will be performing them. After
this introductory phase, the roles will be reversed and the supervisor will watch closely
how a technique is performed by the student to provide relevant feedback. When the
student feels confident to start working independently, he/she will get more responsibility
in planning, performing and analysing experiments while receiving feedback whenever
needed. All results will be discussed and put into relevant scientific context.
Requirements:
- Bachelor degree in biomedicine, biology, biochemistry or similar subjects
- Experience in basic molecular and cellular techniques (cell culture, working with
RNA, qPCR)
- The candidate should be highly motivated and pro-active, have good communication
skills and ability to interact effectively and work productively in a team.
- Fluency in English.
The selected student will be a part of the Helleday laboratory that takes a multidisciplinary
approach involving close collaboration between biochemists, medicinal chemists, molecular
biologists, virologists and pharmacologists. The high diversity of methods and competences
is a unique chance to acquire a very broad skillset depending on motivation of the
candidate.
The research group focuses on understanding basic cellular processes and developing novel
drugs for treating a variety of diseases related to these cellular pathways.Associate Professor Simon Elsässer, Ph.D.
Division of Genome Biology, Department of Medical Biochemistry and Biophysics,
Science for Life Laboratory, simon.elsasser@scilifelab.se, Tel. +46 85241227
13. In silico functional annotation of short open reading frame peptides
A. Responsible PI: Simon Elsässer Supervisor: Carmen Navarro (postdoc)
B. Description of project
Proteins are the molecular machines of life, performing a myriad of functions inside every cell of our
human body. Proteins are assembled from small building blocks, the amino acids, by large protein
factories called ribosomes. Biomedical research on proteins has historically been focused on those
that can be easily detected, isolated and characterized. Much less attention has been paid to shorter
amino acid chains referred to as 'polypeptides' of fifty or less amino acids. These peptides are
encoded by so-called short open reading frames (sORFs) and are also synthesized by the ribosome.
Intriguingly, new research suggests that our human genome has the potential to encode thousands of
such short polypeptides (sPEPs), and it appears that many could have very specific functions in the
human organism. Being small and more versatile in their biochemical and biophysical properties than
larger proteins, polypeptides may modulate many processes that happen in cells, or mediate
communication between cells or organs. Short polypeptides have less structural constraints and are
faster evolvable for new functions than larger proteins. Thus, they may play an important role in
human evolution, adaption and disease mechanisms. This project will use computational methods to
search through thousand possible sORFs that could give rise to novel sPEPs. We will adapt
strategies that have been successfully used to infer function and structure of proteins to predict the
function of putative sPEPs and to curate thousands of candidates to be tested in the wet lab. Notably,
due to the large number of potential sORFs, a robust computational pipeline is essential here to
narrow down the experimental search to a subset of likely functional sPEP candidates.
C. List of techniques the student will use
● optimize an existing pipeline to reproducibly process a list of sPEP sequences through a
number of existing prediction algorithms (Secondary structure content, JPred, TMPred).
Ideally this should be done through integration of the source code so that it can run locally,
but in some cases this may involve calling web services and parsing in the result.
● integrate CRISPR phenotypic screening results
● integrate published datasets/databases for mRNA expression in different tissues, cancers etc.
● annotate peptides with cancer mutation data
● Explore and visualize summary statistics - how does the avarage sORF peptide look like?
Can one cluster them in different groups by their properties? Machine Learning?
D. Short plan for supervision of intern
The project is closely related to ongoing research but not overlapping with current efforts. The project
will be co-supervised by SE and CN, as well as by experimentalists that work on sPEPs.
E. Name and contact information of the person who is responsible for the economy handling
of the salary payment.
Linnea Holm | Human Resources
Department of Medical Biochemistry and Biophysics (MBB)| Karolinska Institutet
SE-171 77 Stockholm | Scheeles väg 2
+46 (0)8-524 872 64 | linnea.holm@ki.se | ki.se/mbbYou can also read
