Like nanoscopic machines, protein assemblies carry out a multitude of cellular processes. Understanding their function and mechanics requires knowing their in situ structural organisation and dynamics, which are barely accessible to classical structural biology techniques (EM, NMR, crystallography). Superresolution microscopy, and specifically Single-Molecule Localization Microscopy (SMLM), is an ideal tool to study these assemblies in their natural cellular environment and to understand their modus operandi.
In our group, we push the limits of superresolution microscopy by developing optical, biological and computational methods:
To enable quantitative measurements, we developed novel reference samples , taking advantage of the well-defined symmetry and stoichiometry of the nuclear pore complex (NPC). These standards allow quantifying the resolution of microscopes, labeling efficiencies, and the precise copy numbers of proteins in complexes.
To achieve highest 3D resolution, we are developing new analysis tools and the new microscope technologies Supercritical Angle Localization Microscopy and 4Pi-SMLM.
High-throughput superresolution microscopy and a comprehensive analysis software enable the acquisition of large datasets and their interpretation with powerful statistics.
The main biological question that drives technology development in my group is clathrin-mediated endocytosis. We achieved a first breakthrough by applying our high-throughput superresolution microscopy to determine the nanoscale distribution of 23 endocytosis proteins in over 100’000 yeast endocytic structures. As the superresolution images contained timing markers, we could computationally reconstruct the dynamic molecular architecture of a forming endocytic vesicle from this massive data set. This allowed us to discover how actin generates and transfers the force to pull in a membrane vesicle.
Our research vision is to develop the microscopy technologies that will allow us to visualize the structure and the dynamics of molecular machines in living cells on the nanoscale. This will add key technology to enable the emerging field of in situ structural biology, and, maybe most importantly, make the dimension of time accessible to structural analysis. By visualizing the conformational and compositional changes macromolecular complexes undergo during their functional cycle, we will be able to see molecular machines in action and obtain unprecedented insights into the mechanisms of the core machinery of life.
To fulfill this vision, we will further develop our advanced microscopes for maximal 3D resolution and multi-color on native samples, and develop computational tools to reconstruct dynamic protein assemblies from thousands of snapshot images. We will establish the novel MINFLUX superresolution technology to directly image dynamic conformational changes of protein assemblies in living cells with nanometer spatial and millisecond temporal resolution. To highlight specific protein complexes in defined functional states inside electron densities we will build seamless workflows for correlative superresolution microscopy and electron tomography. We will drive the development of these technologies by investigating the dynamic structural organization of the endocytic machinery in yeast and mammals.
We will continue to make these technologies available to our biological collaborators and as open-source to the community to investigate structure – function relationships of other cellular machines.
|Since 2012||Group leader at the EMBL in Heidelberg|
|2009 - 2012||Postodoc at ETH Zürich with Vahid Sandoghdar and Helge Ewers: Novel labeling schemes for superresolution microscopy|
|2005 - 2008||PhD at TU Dresden with Petra Schwille: Advanced fluorescence correlation methods to study membrane dynamics|
Rafael Martins Galupa
We are always looking for motivated Master students and interns with a background in physics, programming or biology. Please contact Jonas directly.
If you want to join as a PhD student, please note that admission is exclusively via the EMBL PhD program.
|Tomas Noordzij||Intern||Endocytosis in Drosophila||01.2020 - 10.2020||University of Utrecht|
|Lisa Nechyporenko||Intern||Analysis of kinetochore super-resolution data & exploring fluorescent proteins in yeast||04.2020 - 08.2020||University of Heidelberg|
|Vincent Casamayou||Intern||VR visualization of super-resolution data||03.2020 - 08.2020|
|Lucas-Raphael Mueller||Master Student||High-density fitting by neural networks||11.2018 - 08.2020||DKFZ, Heidelberg|
|Joran Deschamps||PhD Student & Scientific Officer||SALM, automation of SMLM, software development (EMU, FPGA, and device adapters for Micro-Manager),...||10.2013 - 07.2020|
|Leonard Krupnik||Master Student||SMLM of α-synuclein||10.2019 - 05.2020|
|Robin Diekmann||PostDoc||Ratiometric SMLM, Camera Calibration, slowSTORM, 4 Pi Microscopy||01.2018 - 04.2020||LaVision BioTec, Bielefeld|
|Andreas Schoenit||Intern||The NPC as imaging standard||11.2019 - 03.2020|
|Anindita Dasgupta||Master Student||Supercritical Angle Localization Microscopy||09.2018 - 11.2019||Institute of Applied Optics and Biophysics, Jena|
|Maurice Kahnwald||Master Student||The NPC as imaging standard||08.2018 - 11.2019||FMI, Basel|
|Yiming Li||PostDoc||4 Pi Microscopy & Experimental PSF Modeling||01.2016 - 10.2019||Southern University of Science and Technology, Shenzhen|
|Amir Rahmani||Intern||Optimizing Dual-Color SMLM||07.2019 - 09.2019|
|Cheng-Yu Huang||Intern||PSF Modeling||06.2019 - 09.2019||Cambridge University|
|Eric Maurer||Intern||Super-resolution microscopy using small tags||06.2019 - 08.2019||University of Heidelberg|
|Konstanty Cieśliński||PhD Student & PostDoc||Super-resolution imaging of the yeast kinetochore||10.2013 - 12.2018||DKFZ, Heidelberg|
|Alejandro Colchero||Master Student||Optimizing Dual-Color SMLM||04.2018 - 09.2018||University of Madrid|
|Sudheer Kumar Peneti||Master Student||Quantifying labeling efficiency in SMLM||03.2018 - 07.2018||Newcastle University|
|Rayka Karimi||Intern||4 Pi software development||04.2018 - 06.2018|
|Julia Botta||Intern||Counting by SMLM and Kinetochore||02.2018 - 04.2018||University of Heidelberg|
|Daniel Heid||Intern||Quantifying labeling efficiency in SMLM||01.2018 - 03.2018||University of Heidelberg|
|Li-Ling Yang||PostDoc||Inverted lattice light-sheet microscope||06.2014 - 12.2017||Charité Berlin|
|Markus Mund||PhD Student & PostDoc||Endocytosis||09.2012 - 12.2017||University of Geneva|
|Sarah Hoerner||Master Student||Counting with SMLM||06.2017 - 12.2017||Heidelberg University|
|Daniel Schroeder||Master Student||Microscopy Development||04.2017 - 10.2017||FU Berlin|
|Elena Buglakova||Intern||Modeling of 4Pi-PSF||07.2017 - 09.2017|
|Krishna Kasuba||Intern||Protein counting by SMLM||10.2016 - 08.2017||ETH Zürich|
|Johanna Mehl||Intern||Superresolution imaging of endocytosis||10.2016 - 04.2017||ETH Zürich|
|Jooske Monster||Intern||Superresolution imaging of endocytosis||10.2016 - 12.2016||Utrecht University|
|Joanna Zareba||Intern||Fluorophores||07.2016 - 10.2016||Chicago University|
|Katharina Lindner||Intern||Kinetochore||01.2016 - 05.2016||Heidelberg University|
|Tooba Quidwai||Intern||Superresolution imaging of platelets||04.2014 - 08.2015||Edinburgh|
|Jan van der Beek||Intern||Superresolution imaging of endocytosis||12.2014 - 07.2015||Utrecht University|
|Rohit Prakash||Intern||Superresolution imaging of endocytosis||11.2013 - 03.2015||Rochester University|
|Andreas Rowald||Intern||Microscopy development||09.2014 - 02.2015||Erlangen University|
|Nagaraja Chandramohan||Intern||Programming||01.2014 - 12.2014||HITS|
|Sven Spachmann||Bachelor student||Co-localization in superresolution||05.2014 - 07.2014|
|Sunil Kumar Dogga||Intern||Endocytosis||12.2013 - 02.2014|
|Sanchari Datta||Intern||Endocytosis||06.2013 - 07.2013|
|Meet Mukesh Paswan||Intern||Programming||06.2013 - 07.2013|
|Johannes Bues||Intern||Superresolution in yeast||04.2013 - 05.2013|
SMAP (Superresolution Microscopy Analysis Platform) is a comprehensive software framework for single-molecule localization microscopy that can be used for fitting of raw data and subsequent analysis.
It is published in Nature Methods.
The most up-to-date source code can be obtained from GitHub.
You can download a compiled version for Windows and Mac, an example dataset and check the documentation.
The additional external software necessary to run SMAP can be downloaded from the respective websites: Bioformats MATLAB Toolbox (bfmatlab.zip) and Micro-Manager 1.4.22
fit3Dcspline is a GPU based 3D single molecule fitter for arbitrary, experimental point spread functions (PSF).
It was published in Nature Methods and is part of SMAP (see above).
Data obtained from the standalone version can be visualized using Felix Woitzel's Pointcloud-Loader.
dSTORM example data sets (Diekmann et al., 2020, Nature Methods).
SMLM (dSTORM) example data showing the effect of different excitation intensities (unprocessed TIF-stacks and SMAP-fitted localizations files).
Our deep-learning based fitter that can accurately localize fluorophores in 3D at high density is hosted on the GitHub repository of our collaborator Srini Turaga. You can find the preprint on bioRxiv.
The GitHub repository RiesPieces contains small and large internal projects from the lab that we hope can benefit other research groups. More specifically, you can find 3D designs for microscope parts, our recipe for focus stabilization, electronics pieces and many more.
In the GitHub repository LaserEngine you can find the design (machined parts and the optical path) of a custom laser box that is operated with cheap laser diodes. Furthermore, it contains the description of the necessary electronics and how to build the agitation module to scramble the modes of the multimode illumination. You can find more information in the corresponding paper.
EMU is a Micro-manager plugin that controls the device properties of the microscope via an accessible GUI. It is distributed with Micro-Manager 2.0-gamma (nightly build) or can be installed from its source on GitHub. There and in the publication you can find more information on its functionalities and how to adapt it to your microscope setup.
In these cell lines, the nuclear pore component Nup96 is homozygously labeled with mEGFP, SNAP-tag, HaloTag, or the photoconvertible fluorescent protein mMaple. They can be used as 3D resolution standards for calibration and quality control, to quantify absolute labeling efficiencies and as precise reference standards for molecular counting. You can find more information in the respective paper. The cell lines are available from the cell line repository CLS.