From October to December, our master students participate in a series of introductory methods courses in small groups. In these courses you learn fundamental techniques applied in current research and meet members of the participating research groups.
Three different course types differ in length and concept: The 4-day courses with proteins and nucleic acids introduce you to integrate various and basic and advanced techniques in the style of short projects. Several 2-day courses provide you with hands-on experience with a variety of different methods as indicated below. In addition, you are offered a choice of two (out of four) 5-day special courses (week 8-9) with an integrated concept of lectures and hands-on experiments in the fields of intergrated structural biology, electron microscopy (including 3-D cryo EM), NMR spectroscopy, mass spectrometry, proteomics and metabolomics.
Two addition course weeks focus on the introduction to bioinformatics including topics such as next generation sequencing, protein bioinformatics, comparative sequence analysis, gene ontologies and biological networks. These courses are preceded by an introduction to R in five course modules starting already during the orientation weeks in September.
Please click on the different modules and respective course topics in order to see more details.
The MSc class will be divided into four course groups and each group will take one of the listed DNA and one of the listed Protein courses, respectively.
Outline: In this course, you will learn how DNA of your gene of interest can be amplified, inserted into a vector (a carrier DNA) and transferred into a new host (bacteria); the process known as molecular cloning. The aim is to cover all the basic steps of cloning up the point of a functional vector ready for protein expression. Techniques included: Plasmid isolation from E. coli, PCR amplification of DNA, agarose gel electrophoresis, spectroscopic determination of nucleic acid concentrations, Gibson assembly, transformation of E. coli, cloning of multi-protein complexes.
Outline: Cloning procedure. PCR amplification of DNA. Principles of primer design. Agarose gel electrophoresis. Spectroscopic determination of nucleic acid concentrations. Gibson assembly. Restriction enzyme cloning strategy. Transformation of E. coli by heat shock. Plasmid isolation from E. coli via alkaline lysis.
Outline: Principles of plasmid construction, PCR and primer design. Restriction enzyme and Gibson assembly cloning. Site-directed mutagenesis strategy. Electroporation of E. coli. Identification of positive clones. Plasmid amplification and purification.
Outline: NCloning procedure, primer design, PCR amplification of DNA, agarose gel electrophoresis, restriction enzyme digestion, in-fusion cloning, transformation of E. coli, miniprep
Outline: Purification of a recombinant His-tagged protein by affinity, ion-exchange and size exclusion chromatography. Protein concentration measurement by spectroscopic and calorimetric methods. SDS PAGE. In vitro ubiquitination reaction reaction with the purified protein. Isothermal titration calorimetry (ITC).
Outline: Purification of elongation factor G (EF-G) via affinity chromatography and protein concentration determination; EF-G binding to ribosomes assay by ultra-centrifugation, fast kinetics of nucleotide binding to EF-G (stopped flow).
Outline: Purification of IgG from hybridoma cell supernatants. We will use patch affinity exchange chromatography. Eluated IgG will be further purified by gel filtration. Determination of the concentration of purified IgG by Bradford protein assay. Analysis of purified IgG by reducing SDS-PAGE following Coomassie staining.
Outline: Analysis of the structural dynamics of the RNA helicase Prp43 by single molecule FRET using TIRF microscopy; single molecule fluorescence detection; FRET distribution analysis; kinetic analysis by Hidden-Markov Model; interpretation of single molecule fluorescence data.
Outline: RNA extraction, in vitro transcription, separation of RNAs by gel electrophoresis, Northern blotting, RNA-protein interactions, fluorescence anisotropy, RNA structure analysis, methods for RNA quantification
Outline: Purification of human RNA by acidic phenol-chloroform extraction; RNA analysis using Agilent 2200 TapeStation and agarose gel electrophoresis; In vitro transcription and self-cleavage of ribozymes; Analysis of protein-RNA interaction by fluorescent anisotropy
Outline: During this course we will give an overview over light microscopy techniques and perform live imaging as well as fixation and immunostaining of cells. We will also discuss principles of image analysis.
Outline: Methodology: 3D time-lapse imaging of live cells by confocal microscopy; Biology: Live imaging of cytoskeletal dynamics in meiotic divisions of oocytes.
Outline: Day 1: Fractionation of bacterial cells; purification of an autofluorescent signal-bearing model protein from E. coli; chemical labelling of an NPC-ligand with fluorescent dyes. Day 2: Preparation of permeabilized mammalian cells (fractionation into soluble contents and membrane-enclosed compartments); in vitro targeting of fluorescent signal-bearing proteins to selected compartments (nuclei, mitochondria, possibly peroxisomes); analysis by fluorescence microscopy.
Outline: Day 1: Introduction to cell fractionation, isolation of synaptic vesicles from mouse brain: homogenization, differential centrifugation, density gradient centrifugation, size exclusion chromatography. Day 2: Analysis of the column fractions: dot blot, acidification assay of synaptic vesicles by a dual-wavelength spectrophotometer.
Outline: Introduction into cell culture, harvesting of cells, cell lysis, immunoprecipitation of complexes, transfection of cells with plasmids coding for GFP- or RFP-tagged proteins, analysis of cells by fluorescence microscopy, analysis of cells by flow cytometry, preparation of primary cardiomyocytes.
Outline: General introduction into cell culture; monitoring of intracellular Ca2+ flux by flow cytometry; transfection of plamisds by electroporation; imaging flow cytometry.
Outline: Introduction to the Trim-Away technique; antibody preparation for Trim-Away, standard cell culture techniques (harvesting and plating of cells), electroporation of antibodies into mammalian cells, analysis of electroporation efficiency by fluorescent confocal microscopy, preparation of cell lysates, Western Blot, introduction to image analysis by IMARIS, analysis of spindle volume in mouse oocytes.
Outline: Fluorescent in situ hybridization to visualize RNA expression, quantifying mRNA expression using quantitative PCR, cryosections followed by immunofluorescence as well as Western blots to study protein expression in embryonic stem cells, high resolution melting curve analysis to detect CRISPR/Cas9-mediated mutations
Outline: Three-dimensional structure defines biological function. This holds true not only at the macroscopic scale, but also at the cellular and molecular level. Elucidating the atomic structure of biomolecules and their complex interactions is therefore crucial for understanding molecular biology. To date, a variety of experimental methods have been established to derive structural information from macromolecular complexes and cellular structures. While cryo-EM and X-ray crystallography are being used to directly image proteins and protein complexes, methods like crosslinking-mass spectrometry can provide essential information on the architecture of these. Beyond that, cryo-electron tomography allows investigating macromolecular complexes in their cellular environment. More recently, the collection of structural biology methods has been expanded by powerful prediction algorithms like alpha-Fold or RoseTTAFold. Although each of the methods is able to provide insights into protein function on their own, it is often the combination of these techniques that enables us to understand the underlying biology.
This course is intended to serve as an introduction to integrated modelling of proteins and macromolecular complexes. The lectures will cover the theoretical basis of the most frequently used structural biology techniques and how structural data is derived using these methods. The practical sessions will provide hands-on experience on how structural data can be interpreted (model building) and results from several methods can be combined across scales.
Lecture topics: Monday: General lecture on Electron Microscopy Tuesday: Electron Optics Wednesday: Image processing I (Tomography) Thursday: Image processing II (Single particle EM) Friday: Image processing III (Validation & Visualization)
Practical parts: Monday:Group 1: Techniques of molecular electron microscopy: negative stain preparation, cryo preparation, imaging.; Group 2: Techniques of cellular electron microscopy: Embedding of specimen, acquisition of tomograms Tuesday:Group 2: Techniques of molecular electron microscopy: negative stain preparation, cryo preparation, imaging.; Group 1: Techniques of cellular electron microscopy: Embedding of specimen, acquisition of tomograms Wednesday: Image processing I (Analysis of tomographic data) Thursday: Image processing II (Single particle analysis); Particle selection, basic image processing, alignment, multivariate statistics Friday: Image processing III (Validation and visualization of macromolecular complexes); Fourier Shell Correlation, introduction into UCSF chimera
Additional information regarding the course program: Dietmar Riedel (Electron Microscopy Group): Introduction to electron microscopy: staining procedures, fixation procedures, principles of different room temperature, low temperature and cryo embedding methods (all applied to cells, membranes and organelles). Ultrathin sectioning of embedded PC12 cells and acquisition of angular series in a transmission electron microscope. Processing of the serial sections for tomographic reconstruction and 3D modelling. Holger Stark, Niels Fischer (3D Cryo Electron Microscopy Group): Preparation of an electron microscopically grid by negative stain. Sample: 70 S ribosome. Image acquisition using different electron microscopes for negative stain and cryo samples. Extraction of individual molecular images. Multivariate statistical analysis, classification and averaging. Determination of projection angles. Calculation of the 3D structure of the complex by backprojection algorithms. Visualization and interpretation of the 3D structure (movies and animations).
Outline: This course will cover the following techniques: SDS-PAGE; in-gel digestion of proteins; peptide-mass-fingerprint analysis by MALDI-TOF-MS; database search using peptide masslists, electrospray ionization (ESI) MSMS.
Modules:
Spectrometer I and II (Introduction to hardware, measure principle, sample preparation etc.)
Measurement at the spectrometer (titration data points)
Outline: The course will provide the theoretical and practical basis of identification and quantification of peptides with ESI MS.
Proteins from a complex lysate (mitochondria from yeast, grown under two different conditions) will be digested in-solution. Changes in the proteome as response to different growth conditions will be analysed by label-free and isobaric label-based quantification.
Phosphopeptides from yeast mitochondria will be enriched by affinity columns and sequenced using ESI-MS/MS. The exact phosphorylation site and ideally an abundance change in response to the applied condition will be determined.
Students will learn to identify proteins and post-translational modifications from protein bands from Coomassie stained SDS-PAGE by in-gel digestion.
Outline: Metabolite fingerprinting is a comprehensive and comparative non-targeted metabolomics approach. It aims to describe biological processes on the metabolite level and to identify metabolites or even pathways as biomarker of environmental, developmental or genetic perturbation. This course will give a theoretical introduction into the strategy of metabolite marker identification and the principles of liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS).
Hands-on work will be done on the following steps of the non-targeted metabolomics approach:
Extraction of the metabolites from biological samples
Data acquisition by LC-HRMS
Generation of comprehensive metabolome data matrixes
Data processing and identification of metabolite markers (supported by the software MarVis)
Verification of the structure of metabolite markers by LC-HRMS/MS analysis
Outline:
- statistical thinking
- qualitative vs quantitative analysis
- statistical vocabulary: e.g. random variable, sample, population, probability, independence etc,
- distributions: what types of distributions are relevant in Biology; characteristics of distributions; revisit mean, median, standard deviation etc,
- hypothesis testing (frequentist): which tests are available/applicable (1-2 for discrete, 1-2 for continuous); null hypothesis and alternative hypothesis; p-value; significance; interpretation of test results; statistical vs practical significance; concept of multiple testing
- correlation, causation and confounders: correlation vs causation, non-parametric correlation (generally beyond Pearson)
- linear regression; confidence; goodness of fit; interpretation
- data visualization and presentation: need for data cleaning -> human factors (units, dates, inconsistent annotation of data); different types of plots; how to display distributions; box plots vs. full distribution; pros and cons for different visualization approaches (how to miss effects, how to create wrong effects, when not to use bar plots)
- statistics vs. intuition
- reproducibility of statistical analysis: code reviews – good practice in writing analysis code
Meta-gene analysis 16 / Libraries, Load *.bam les via a function from the Rsamtools package / Provide gene annotation / Set colors for dierent RNA types / How to generate genome browser plots / Select all transcripts of type "ORF-T" from gene.anno / How to generate metagene plots (non-scaled and aligned, aggregated and scaled) / Gather coverage profiles -2500:2500 bp around the transcript start site for both conditions (NoRapa and Rapa) on the antisense strand / Plot the gathered profiles / Gather coverage profiles -2000:6000 bp around the transcript 'start' site for both conditions ('NoRapa' and 'Rapa') on the antisense strand / Plot the gathered profiles / Ordinary dierential gene expression analysis with DEseq / Libraries / How to provide and handle count data / Basic quality control (visualization with LSD heatscatter) / significance testing (differential expression) / GO enrichment analysis
Outline: Meta-gene analysis 16 / Libraries, Load *.bam les via a function from the Rsamtools package / Provide gene annotation / Set colors for dierent RNA types / How to generate genome browser plots / Select all transcripts of type "ORF-T" from gene.anno / How to generate metagene plots (non-scaled and aligned, aggregated and scaled) / Gather coverage profiles -2500:2500 bp around the transcript start site for both conditions (NoRapa and Rapa) on the antisense strand / Plot the gathered profiles / Gather coverage profiles -2000:6000 bp around the transcript 'start' site for both conditions ('NoRapa' and 'Rapa') on the antisense strand / Plot the gathered profiles / Ordinary dierential gene expression analysis with DEseq / Libraries / How to provide and handle count data / Basic quality control (visualization with LSD heatscatter) / significance testing (differential expression) / GO enrichment analysis
Outline: Short intro to molecular evolution in proteins / Protein structure requires strong conservation of patterns of amino acid physic-chemical properties / Sequence searching, homology-based inference, BLAST, Uniprot / Secondary structure prediction, prediction of membrane helices etc. / Multiple sequence alignments / Sequence profiles, PSI-BLAST, HMMER/PFAM / Protein domains, SCOP, Pfam / HHpred, HHblits / Practical guide to structure and function prediction with HHpred / Homology modelling using MODELLER.
Outline: The students will acquire an understanding of the usage and usefulness of comparative approaches in analyzing large-scale biological data (foremost sequencing data). This will entail a hands-on experience with carrying out comparative analyses on genomic data, especially computing and interpreting phylogenetic trees.
Outline:
- Day 1: Intro to Python with exercises: Installing Python, elementary syntax (indentation, ranges, dictionaries), if-then-else, for loops, objects and classes, function calls;
- Day 2: Pytorch: matrices and tensors, k-means clustering; logistic regression; random forests; training and test sets, data leakage; ROC analysis, precision/recall, FDR
- Day 3: Intro to neural networks as universal function approximators; gradient descent in high dimensions, local optima, stochastic gradient descent; autodiff
- Day 4: Deep learning: image classification on MNIST and ImageNet10 using Pytorch
