Cross Institutional Bioimaging PhD Course
Fall semester 2020
Level: PhD course
Time: September 7th to November 23rd, 2020
Locations: Copenhagen, Odense, Århus, Kng. Lyngby
Number of contact hours: 80
Capacity limits: 20
The Cross Institutional Bioimaging Ph.D. course is interdisciplinary and cross-institutional and will be given by a series of lecturers who are experts within each their field of bioimaging. The course will take place at different institutions in order to expose the students to different research groups, their researchers and experimental research facilities. The course will thus give the student a unique opportunity of orienting him or herself within an active and diverse field of interdisciplinary science within bioimaging.
The course is relevant for PhD students within medicine, physics, chemistry, biochemistry, molecular biology, nano-bioscience, pharmaceutical sciences, agricultural science or biology. The emphasis of the course is a tour of all bioimaging techniques available in Denmark and will cover subjects like live cell imaging, spinning disk microscopy, electron microscopy, photoactivated localization microscopy, single particle techniques, structured illumination, stimulated emission depletion microscopy, imaging of neurons and cell migration.
Time schedule for the course
The course starts September 7th 2020, and runs consecutive Mondays for 10 weeks at 4 different universities and by different lecturers. Each module of the course covers around 8 hours, from 09:30-17:30. In general, the morning session will consist of a set of lectures and the afternoon session will predominantly involve either the student's active participation in experiments, specific numerical exercises, or inspection of the local experimental facilities.
Course credit and evaluation
The workload of the course corresponds to 10 ECTS points, the total workload includes reading material for each module and the preparation of the final talk (presentation). Credit for the course requires the student's presence at minimum 8 of 10 modules. For any missed modules, students will have to write a 3-page report on the topic of the missed module.
The student’s presence on the entire exam day is mandatory but the venue, KU or SDU, can be chosen by the student according to what is most convenient. The examination consists of 20 minutes of presentation and 15 minutes of questions from the examiners and student opponents. Each student must act as an opponent for the presentation of one other student. In the presentation each student will describe an experiment using one of the applications described in the course including an image analysis strategy. The task for the presentation will be given in advance (on the last module day the 9th of November).
Registration can be requested by email to email@example.com with information about your institution, department, supervisor(s) and your research topic.
Students must hold a master’s degree in physics, engineering, life science, biology or medicine and accepted in a PhD program.
Eva Arnspang Christensen and Jonathan Brewer (SDU)
(AU) Lene Niemann Nejsum, Morten Nielsen, Victoria Birkedal, Thomas Boesen
(DTU) Rasmus Reinhold Paulsen, Anders Bjorholm Dahl
(KU) Clara Prats, Ivana Novak, Michael Lisby, Alexander Schulz, Jon Sporring
(SDU) Eva Arnspang Christensen, Martin Hedegaard, Jonathan Brewer, Daniel Wüstner, Helge Thisgaard
Will be announced every week during the course or be found on the course page on the BlackBoard platform.
Short description of course modules
Fluorescence and Two Photon Microscopy and Image Analysis
Jonathan Brewer & Eva Arnspang Christensen
This day will cover the basics of fluorescence and epifluorescence widefield microscopy which form the bases for understanding many of the more advanced techniques introduced later in the course. This will be followed by an introduction to multiphoton excitation microscopy with applications and a short introduction to image analysis using ImageJ.
Students will be introduced to the Principles and Essentials of Single Point Scanning Microscopy. Lectures and hands-on practical exercises will be combined to teach the students the critical components of a Confocal Microscope and, how to properly construct imaging light paths and settings to avoid artifacts and collect proper bioimaging data
Live Imaging in Yeast, Plants and Mammalian Cells
Ivana Novak, Michael Lisby, Alexander Schultz
Joint morning lectures for all students will be followed by three separate demonstrations/hands-on of various techniques in live cell imaging in yeast, plants and mammalian cells. Students should choose one demonstration to follow.
Alexander Schulz, Frederiksberg Campus
Live cell imaging of plants is able to uncover development-related physiological changes and responses due to abiotic and biotic stress. We will present examples including cell signalling, the cell-to-cell and long-distance transport of photoassimilates, and the defence of plants against pathogens. Show-cases at the point and spinning confocal microscopes will present the opportunities and limitations of advanced microscopy approaches in this research field.
Ivana Novak, North Campus
Live cell imaging of mammalian cancer cells or endocrine cells will be demonstrating fast responses at the plasma cell membranes, cellular signalling and signalling between cells. Show-cases of CLSM, FRET, video rate imaging and long-term imaging will be presented.
Michael Lisby, North Campus
Budding yeast Saccharomyces cerevisiae is a widely used eukaryotic model for evolutionarily conserved processes. We will show-case an example of how specific protein-protein interactions can be monitored during the DNA damage response using Bimolecular Fluorescence Complementation (BiFC) on a high-resolution fluorescence wide-field microscope.
In this part of the course, you will get a quick introduction to image processing using Python. Using your own computer, you will learn how to do write short programs that perform simple noise reduction, segmentation, and object analysis on 2 dimensional images. We will work with example images, and you are welcome to bring your own as further work cases. Before class, you are expected to have installed Anaconda and have basic familiarity with the Jupyter notebook. If you have no programming experience in python, then it is strongly recommend that you work through the Introduction to Python Programming material to be distributed prior to class.
Single particle & Fluorescent Proteins
Morten S. Nielsen, Victoria Birkedal, Lene N. Nejsum
This module will consist of three parts. The first part will describe the theory and selected applications of total internal reflectance (TIRF) microscopy with high signal-to-noise ratio and spatial resolution in single molecule fluorescence and FRET studies.
The next part will focus on how to study receptor trafficking using imaging technologies. We will go through methods to follow endocytic receptors from the surface and through the endo-lysosomal system and demonstrate how we analyse if receptors are transcytosed in polarised endothelial and epithelial cells.
The last part will focus on how we use fluorescent proteins and bioimaging methods to study the effects of aquaporin water channels on cell migration and cell-cell adhesion.
Besides lectures, the module will include an ImageJ exercise in tracking of live, migrating cells as well as a facility tour.
Super-resolution, STED, ICS and Raman
Eva Arnspang Christensen, Daniel Wüstner, Jonathan Brewer & Martin Hedegaard
This day will cover a wide range of advanced imaging techniques. Specifically, the super resolution techniques including stimulated emission depletion microscopy (STED), structured illumination microscopy (SIM) and localization-based microscopies such as photoactivatable localization microscopy (PALM) will be introduced.
Coherent anti-Stokes Raman scattering (CARS) and confocal Raman imaging will be presented. They are label-free imaging technique based entirely on molecular vibrations. This course will include an introduction to basic working principles and choice of instrumentation including lasers, microscopes and spectrometers. In addition, there will be an introduction to pre-processing and analysis of Raman imaging data.
Furthermore, methods for dynamic measurements in samples such as fluorescence correlation spectroscopy (FCS) and k-space image correlation spectroscopy (kICS) will be shown. These techniques facilitate measurements of bulk diffusion coefficient from conventional confocal, epi fluorescence or TIRF imaging.
Rasmus Reinhold Paulsen, Anders Bjorholm Dahl
The image analysis course at DTU Compute is focused on two topics that are relevant for biomedical image analysis. The first topic is pixel classification, where the goal is to assign a relevant label to a given pixel. Labels are normally predefined like for example background, nuclei, and membrane. The classification is based on a using a training set of images to create a statistical assumption on the distribution of pixel values within the classes.
The second topic is BLOB analysis, where the goal is to classify objects in an image based on their shape. Typical examples are nuclei detection in cell images or organ identification in medical scans.
Non-invasive imaging modalities (PET-SPECT-CT-R)
The course will cover the basics concepts of preclinical nuclear medicine techniques using PET/SPECT/CT imaging modalities. The theory behind the techniques will be presented followed by hands-on experience in the laboratory
The course provides an introduction to the essential grounding in the basic principles of electron microscopy, covering topics such as electron optics, electromagnetic lenses, principles of transmission and scanning electron microscopy, electron sources, vacuum systems, specimen-electron interactions and diffraction. The state-of-the-art facilities available at EMBION allow for a strong practical element of demonstrations of both cryo- and room temperature electron microscopy. The course will be run by experienced microscopists in a relaxed atmosphere with the aim of promoting discussion and exchange of ideas between students and tutors.