Ries Lab

We are studying nanoscale multi-protein machineries in their functional cellular context, and elucidates their dynamic structural organisation using tailor-made superresolution microscopy technologies.

Research in the Ries Lab

Previous and current research

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.

Future projects and goals

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.

People

Ries Lab 2018

Group Members

Jonas Ries
Group Leader
Takahiro Deguchi
Takahiro Deguchi
PostDoc
Angelica Maria Estrada Pacheco
Angelica Maria Estrada Pacheco
Research Technician
Philipp Hoess
Philipp Hoess
PhD Student
Sheng Liu
Sheng Liu
PostDoc
Ulf Matti
Ulf Matti
Research Technician
Aline Tschanz
Aline Tschanz
PhD Student
Jervis Vermal Thevathasan
Jervis Vermal Thevathasan
PostDoc
Yu-Le Wu
Yu-Le Wu
PhD Student
Tomas Noordzij
Tomas Noordzij
Master Student

Associated PostDocs

Rafael Martins Galupa
Markus Mund

Open positions

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.

Alumni

NamePositionTopicPeriodCurrent affiliation
Lisa NechyporenkoInternAnalysis of kinetochore super-resolution data & exploring fluorescent proteins in yeast04.2020 - 08.2020University of Heidelberg
Vincent CasamayouInternVR visualization of super-resolution data03.2020 - 08.2020 
Lucas-Raphael MuellerMaster StudentHigh-density fitting by neural networks11.2018 - 08.2020DKFZ, Heidelberg
Joran DeschampsPhD Student & Scientific OfficerSALM, automation of SMLM, software development (EMU, FPGA, and device adapters for Micro-Manager),...10.2013 - 07.2020 
Leonard KrupnikMaster StudentSMLM of α-synuclein10.2019 - 05.2020 
Robin DiekmannPostDocRatiometric SMLM, Camera Calibration, slowSTORM, 4 Pi Microscopy01.2018 - 04.2020LaVision BioTec, Bielefeld
Andreas SchoenitInternThe NPC as imaging standard11.2019 - 03.2020 
Anindita DasguptaMaster StudentSupercritical Angle Localization Microscopy09.2018 - 11.2019Institute of Applied Optics and Biophysics, Jena
Maurice KahnwaldMaster StudentThe NPC as imaging standard08.2018 - 11.2019FMI, Basel
Yiming LiPostDoc4 Pi Microscopy & Experimental PSF Modeling01.2016 - 10.2019Southern University of Science and Technology, Shenzhen
Amir RahmaniInternOptimizing Dual-Color SMLM07.2019 - 09.2019 
Cheng-Yu HuangInternPSF Modeling06.2019 - 09.2019Cambridge University
Eric MaurerInternSuper-resolution microscopy using small tags06.2019 - 08.2019University of Heidelberg
Konstanty CieślińskiPhD Student & PostDocSuper-resolution imaging of the yeast kinetochore10.2013 - 12.2018DKFZ, Heidelberg
Alejandro ColcheroMaster StudentOptimizing Dual-Color SMLM04.2018 - 09.2018University of Madrid
Sudheer Kumar PenetiMaster StudentQuantifying labeling efficiency in SMLM03.2018 - 07.2018Newcastle University
Rayka KarimiIntern4 Pi software development04.2018 - 06.2018 
Julia BottaInternCounting by SMLM and Kinetochore02.2018 - 04.2018University of Heidelberg
Daniel HeidInternQuantifying labeling efficiency in SMLM01.2018 - 03.2018University of Heidelberg
Li-Ling YangPostDocInverted lattice light-sheet microscope06.2014 - 12.2017Charité Berlin
Markus MundPhD Student & PostDocEndocytosis09.2012 - 12.2017University of Geneva
Sarah HoernerMaster StudentCounting with SMLM06.2017 - 12.2017Heidelberg University
Daniel SchroederMaster StudentMicroscopy Development04.2017 - 10.2017FU Berlin
Elena BuglakovaInternModeling of 4Pi-PSF07.2017 - 09.2017 
Krishna KasubaInternProtein counting by SMLM10.2016 - 08.2017ETH Zürich
Johanna MehlInternSuperresolution imaging of endocytosis10.2016 - 04.2017ETH Zürich
Jooske MonsterInternSuperresolution imaging of endocytosis10.2016 - 12.2016Utrecht University
Joanna ZarebaInternFluorophores07.2016 - 10.2016Chicago University
Katharina LindnerInternKinetochore01.2016 - 05.2016Heidelberg University
Tooba QuidwaiInternSuperresolution imaging of platelets04.2014 - 08.2015Edinburgh
Jan van der BeekInternSuperresolution imaging of endocytosis12.2014 - 07.2015Utrecht University
Rohit PrakashInternSuperresolution imaging of endocytosis11.2013 - 03.2015Rochester University
Andreas RowaldInternMicroscopy development09.2014 - 02.2015Erlangen University
Nagaraja ChandramohanInternProgramming01.2014 - 12.2014HITS
Sven SpachmannBachelor studentCo-localization in superresolution05.2014 - 07.2014 
Sunil Kumar DoggaInternEndocytosis12.2013 - 02.2014 
Sanchari DattaInternEndocytosis06.2013 - 07.2013 
Meet Mukesh PaswanInternProgramming06.2013 - 07.2013 
Johannes BuesInternSuperresolution in yeast04.2013 - 05.2013 

Software

SMAP

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

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.

Excitation Intensities

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).

Direct Supercritical Angle Localization microscopy (dSALM)

Preprint on bioRxiv
Example data and step-by-step guide for analysing dSALM data

Tools

RiesPieces

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.

LaserEngine

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.

Easier Micro-manager User interface (EMU)

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.

Nup96 cell lines

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.

Publications

2020

How good are my data? Reference standards in superresolution microscopy
Mund M, Ries J.
Molecular Biology of the Cell doi: 10.1091/mbc.E19-04-0189
Quantitative Data Analysis in Single-Molecule Localization Microscopy
Wu Y, Tschanz A, Krupnik L, Ries J.
Trends in Cell Biology doi: 10.1016/j.tcb.2020.07.005
SMAP - A Modular Superresolution Microscopy Analysis Platform for SMLM Data
Ries J.
Nature Methods doi: 10.1038/s41592-020-0938-1
Previously onbioRxiv doi: 10.1101/2020.07.24.219188
More information and links to the software can be found above
Teaching deep neural networks to localize single molecules for super-resolution microscopy
Speiser A, Müller LR, Matti U, Obara CJ, Legant WR, Ries J, Macke JH, Turaga SC.
arXiv: 1907.00770
Optimizing imaging speed and excitation intensity for single-molecule localization microscopy
Diekmann R, Kahnwald M, Schoenit A, Deschamps J, Matti U, Ries J.
Nature Methods doi: 10.1038/s41592-020-0918-5
A link to the data can be found above
Direct Supercritical Angle Localization Microscopy for Nanometer 3D Superresolution
Dasgupta A, Deschamps J, Matti U, Hübner U, Becker J, Strauss S, Jungman R, Heintzmann R, Ries J.
Accurate 4Pi single-molecule localization using an experimental PSF model
Li Y, Buglakova E, Zhang Y, Thevathasan JV, Bewersdorf J, Ries J.
Optics Letters doi: 10.1364/OL.397754
Previously onbioRxiv doi: 10.1101/2020.03.18.997163
Identification of novel synaptonemal complex components inC. elegans
Hurlock ME, Čavka I, Kursel LE, Haversat J, Wooten M, Nizami Z, Turniansky R, Hoess P, Ries J, Gall JG, Rog O, Köhler S, Kim Y.
Journal of Cell Biology doi: 10.1083/jcb.201910043
EMU: reconfigurable graphical user interfaces for Micro-Manager
Deschamps J, Ries J.
Corresponding GitHub repository
Nanoscale pattern extraction from relative positions of sparse 3D localisations
Curd A, Leng J, Hughes R, Cleasby A, Rogers B, Trinh C, Baird M, Takagi Y, Tiede C, Sieben C, Manley S, Schlichthaerle T, Jungmann R, Ries J, Shroff H, Peckham M.
MINFLUX nanoscopy delivers 3D multicolor nanometer resolution in cells
Gwosch K, Pape JK, Balzarotti F, Hoess P, Ellenberg J, Ries J, Hell SW.
Nature Methods doi: 10.1038/s41592-019-0688-0
Previously onbioRxiv doi: 10.1101/734251
Nanoscale subcellular architecture revealed by multicolor three-dimensional salvaged fluorescence imaging
Zhang Y, Schroeder LK, Lessard MD, Kidd P, Chung J, Song Y, Benedetti L, Li Y, Ries J, Grimm JB, Lavis LD, De Camilli P, Rothman JE, Baddeley D & Bewersdorf J.
Nature Methods doi: 10.1038/s41592-019-0676-4
Previously onbioRxiv doi: 10.1101/613174
A cost-efficient open source laser engine for microscopy
Schroeder D, Deschamps J, Dasgupta A, Matti U, Ries J.
Biomedical Optics Express doi: 10.1364/BOE.380815
Previously onbioRxiv doi: 10.1101/796482
Corresponding GitHub repository

2019

Organotypic slice culture model demonstrates inter-neuronal spreading of alpha-synuclein aggregates
Elfarrash S, Møller Jensen N, Ferreira N, Betzer C, Thevathasan JV, Diekmann R, Adel M, Mansour Omar N, Boraie MZ, Gad S, Ries J, Kirik D, Nabavi S, Jensen H.
Acta Neuropathologica Communications doi: 10.1186/s40478-019-0865-5
Previously onbioRxiv doi: 10.1101/681064
Three dimensional particle averaging for structural imaging of macromolecular complexes by localization microscopy
Rieger B, Stallinga S, Heydarian H, Schueder F, Jungmann R, Ries J, Przybylski A, Bates M, Keller-Findeisen J, van Werkhoven B.
bioRxiv doi: 10.1101/837575
Topological data analysis quantifies biological nano-structure from single molecule localization microscopy
Pike JA, Khan AO, Pallini C, Thomas SG, Mund M, Ries J, Poulter NS, Styles IB.
Bioinformatics doi: 10.1093/bioinformatics/btz788
Previously onbioRxiv doi: 10.1101/400275
Photoactivation of silicon rhodamines via a light-induced protonation
Frei MS, Hoess P, Lampe M, Nijmeijer B, Kueblbeck M, Ellenberg J, Wadepohl H, Ries J, Pitsch S, Reymond L, Johnsson K.
Nature Communications doi: 10.1038/s41467-019-12480-3
Previously onbioRxiv doi: 10.1101/626853
Nuclear pores as versatile reference standards for quantitative superresolution microscopy
Thevathasan JV, Kahnwald M, Cieśliński K, Hoess P, Peneti SK, Reitberger M, Heid D, Kasuba KC, Hoerner SJ, Li Y, Wu Y, Mund M, Matti U, Pereira PM, Henriques R, Nijmeijer B, Kueblbeck M, Sabinina VJ, Ellenberg J, Ries J.
Nature Methods doi: 10.1038/s41592-019-0574-9
Previously onbioRxiv doi: 10.1101/582668
Type-I myosins promote actin polymerization to drive membrane bending in endocytosis
Manenschijn HE, Picco A, Mund M, Rivier-Cordey AS, Ries J, Kaksonen M.
eLife doi: eLife.44215
Previously onbioRxiv doi: 10.1101/490011
Direct Visualization of Single Nuclear Pore Complex Proteins Using Genetically‐Encoded Probes for DNA‐PAINT
Schlichthaerle T, Strauss MT, Schueder F, Auer A, Nijmeijer B, Kueblbeck M, Sabinina VJ, Thevathasan JV, Ries J, Ellenberg J, Jungmann R.
Angewandte Chemie International Edition doi: 10.1002/anie.201905685
Previously onbioRxiv doi: 10.1101/579961
A tessellation-based colocalization analysis approach for single-molecule localization microscopy
Levet F, Julien G, Galland R, Butler C, Beghin A, Chazeau A, Hoess P, Ries J, Giannone G, Sibarita JB.
Nature Communications doi: 10.1038/s41467-019-10007-4
Depth-dependent PSF calibration and aberration correction for 3D single-molecule localization
Li Y, Wu Y, Hoess P, Mund M, Ries J.
Biomedical Optics Express doi: 10.1364/BOE.10.002708
Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software
Sage D, Pham T, Babcock H, Lukes T, Pengo T, Chao J, Velmurugan R, Herbert A, Agrawal A, Colabrese S, Wheeler A, Archetti A, Rieger B, Ober R, Hagen GM, Sibarita J, Ries J, Henriques R, Unser M, Holden S.
Nature Methods doi: 10.1038/s41592-019-0364-4
Previously onbioRxiv doi: 10.1101/362517

2018

Scanning Fluorescence Correlation Spectroscopy for Quantification of the Dynamics and Interactions in Tube Organelles of Living Cell
Unsay JD, Murad F, Hermann E, Ries J, García-Sáez AJ.
ChemPhysChem doi: 10.1002/cphc.201800705
Systematic Nanoscale Analysis of Endocytosis Links Efficient Vesicle Formation to Patterned Actin Nucleation
Mund M, van der Beek JA, Deschamps J, Dmitrieff S, Hoess P, Monster JL, Picco A, Nédélec F, Kaksonen M, Ries J.
Previously onbioRxiv doi: 10.1101/217836
Dual-Color and 3D Super-Resolution Microscopy of Multi-protein Assemblies
Hoess P, Mund M, Reitberger M, Ries J.
Methods in Molecular Biology doi: 10.1007/978-1-4939-7759-8_14
Site-specific labeling of Affimers for DNA-PAINT microscopy
Schlichthaerle T, Eklund A, Schueder F, Strauss M, Tiede C, Curd A, Ries J, Peckham M, Tomlinson D, Jungmann R.
Angewandte Chemie International Edition doi: 10.1002/anie.201804020
Real-time 3D single-molecule localization using experimental point spread functions
Li Y, Mund M, Hoess P, Deschamps J, Matti U, Nijmeijer B, Sabinina VJ, Ellenberg J, Schoen I, Ries J.
Nature Methods doi: 10.1038/nmeth.4661
ChromoTrace: Computational reconstruction of 3D chromosome configurations for super-resolution microscopy
Barton C, Morganella S, Ødegård-Fougner Ø, Alexander S, Ries J, Fitzgerald T, Ellenberg J, Birney E.
PLoS Computational Biology doi: 10.1371/journal.pcbi.1006002

2017

Nanoscale invaginations of the nuclear envelope: Shedding new light on wormholes with elusive function
Schoen I, Aires L, Ries J, Vogel V.
Aurora-B kinase pathway controls the lateral to end-on conversion of kinetochore-microtubule attachments in human cells
Shrestha RL, Conti D, Tamura N, Braun D, Ramalingam RA, Cieśliński K, Ries J, Draviam VM.
Nature Communications doi: 10.1038/s41467-017-00209-z
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Contact

Ries Lab

EMBL Heidelberg
Meyerhofstr. 1
69117 Heidelberg

Room 402
Phone number: +49 6221 3878199
E-Mail: ries(at)embl.de

Ries Lab website at www.embl.de
European Molecular Biology Laboratory