Like nanoscopic machines, protein complexes and assemblies carry out a variety of essential cellular processes. Understanding their function and mechanics requires knowing their in situ structural organisation, which is barely accessible to classical structural biology techniques (EM, NMR, crystallography). Recently developed superresolution microscopy techniques however are ideal tools that allow us to study these assemblies in their natural cellular environment and to understand their modus operandi.
In our group, we push the limits of the technology by developing optical, biological and computational methods for superresolution microscopy:
We are developing novel techniques to achieve highest 3D resolution of single fluorophores using Supercritical Angle Localization Microscopy and correlative superresolution and electron microscopy, and are implementing quantitative superresolution imaging based on counting reference standards. Lattice-light sheet microscopy allows us to dynamically visualise structures in thick samples and organisms.
High-content superresolution microscopy and a computational analysis framework enables the acquisition of large datasets of structures with powerful statistics.
In the past, we introduced nanobodies as versatile superresolution labels and pioneered superresolution microscopy in yeast, where strain libraries with tags and mutations allow system-wide superresolution studies.
We then apply our newly developed technologies to exciting cell biological systems:
In one project, we study the complex and dynamic protein machinery that performs clathrin-mediated endocytosis in yeast. Using automated high-content superresolution imaging and quantitative data analysis, we determined how more than a dozen endocytic proteins are organised at the nanoscale. The architectural principles we discovered allowed us to understand how the endocytic machinery achieves remarkably high regularity and efficiency. Our vision is to reconstruct the time-resolved distributions of all endocytic proteins and integrate this data with mathematical modelling, to understand key aspects of the endocytic mechanism, including how the machinery assembles, how membrane curvature is induced and how vesicle scission is mediated.
In other projects, we are studying the structure of the kinetochore, we are investigating intracellular aggregation of Parkinsons’ α-synuclein and we aim at reconstructing the 3D organisation of DNA in a cell nucleus.
Our vision is to further extend superresolution microscopy as a tool for structural cell biology in situ. We aim to push its limits on all fronts to establish a technique which combines nanometre 3D resolution with maximum labelling efficiencies, absolute measurements of protein copy numbers, precise multi-colour measurements, high-throughput for large scale statistics and novel data analysis approaches, to address the vast array of exciting biological questions at the nanoscale, which are becoming accessible only now.
|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.
|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).
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 preprint 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.