Ries Lab

Max Perutz Labs, University of Vienna

Superresolution Microscopy for Structural Cell Biology

We develop superresolution microscopy technologies to visualize the structure and dynamics of molecular machines in cells on the nanoscale. We use these techniques to investigate the dynamic structural organization of the machinery that drives clathrin-mediated endocytosis.

Research in the Ries Lab

Previous and current research

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.

Here you can watch a presentation on the main research activities in the group (Jonas Ries, 13.4.2021 at the EMBL/Janelia Optical Interest group).

Future projects and goals

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.

People

Ries Lab 2023

Group Members in Vienna

Jonas Ries
Group Leader
Amr Abouelezz
Amr Abouelezz
Postdoc
Gabin Agbale
Gabin Agbale
Master student
Nestor Castillo
Nestor Castillo
Senior Scientist
Nikolay Sergeev
Michaela Janka
Master student
Phylicia Kidd
Phylicia Kidd
Visiting Scientist
Amr Abouelezz
Alejandro Linares
PhD student
 Zach Marin
Zach Marin
Postdoc
Maxime Mathieu
Maxime Mathieu
Postdoc
Amr Abouelezz
Francesco Reina
Technical Officer

Group Members in Heidelberg

Takahiro Deguchi
Takahiro Deguchi
PostDoc
Soheil Mojiri
Soheil Mojiri
PostDoc
Lucas-Raphael Mueller
Lucas-Raphael Mueller
PhD Student
Nikolay Sergeev
Lukas Scheiderer
Postdoc
Nikolay Sergeev
Nikolay Sergeev
PhD Student
Nikolay Sergeev
Valerie Segatz
Intern

Open positions

With our move to the Max Perutz Labs at the University of Vienna we have competitive positions for applicants with a background in physics, programming or biology on all levels. Please contact Jonas directly.

Have a look at our job advertisements at the Max Perutz Labs.

If you want to join as a PhD student, please note that admission is exclusively via the Vienna BioCenter PhD program.

Alumni

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 and Installation notes.
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

uiPSF

Universal inverse modeling of point spread functions for SMLM localization and microscope optimization. On our GitHub repository.

DECODE

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. Here you can find the journal article. Additionally, there is a recording of the tutorial given during the virtual conference "From Images to Knowledge with ImageJ & Friends" available on Youtube.

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.

LocMoFit

LocMoFit is a framework to fit SMLM data with geometric models. For details please consult the documentation, the corresponding bioRxiv preprint, and the example data.

globLoc

globLoc is a global fitting algorithm running on the GPU. You can find example data here and the corresponding publication contains further information.

Resources

EMBL SMLM

A step-by-step protocol for constructing our automated 3D and multi color SMLM microscopes on bioRxiv. blue-prints can be found on the corresponding Github page.

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.

MicroFPGA

MicroFPGA is an FPGA-based platform for the electronic control of microscopes. It aims at using affordable FPGA to generate or read signals from a variety of devices, including cameras, lasers, servomotors, filter-wheels, etc. It can be controlled via Micro-Manager, or its Java, Python and LabView communication libraries, and comes with optional complementary electronics. Published in HardwareX.

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 publication 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.

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)

Publication in Nature Communications
Example data and step-by-step guide for analysing dSALM data

ACCéNT

ACCéNT is a Micro-Manager and Fiji plugin to precisely calibrate the pixel-wise noise characteristics of sCMOS cameras from dark images alone. Example data can be found here, the source code is available on GitHub and this is the corresponding publication.

LocMoFit datasets

Here you can find the datasets used in the LocMoFit manuscript (Wu et al., Nature Methods 2023). These datasets contain the localization data (in both .csv and _sml.mat files) and LocMoFit analysis (only in the _sml.mat files) of the imaged structures of the nuclear pore complex, microtubules and the yeast endocytic sites.

Publications

2024

Universal inverse modelling of point spread functions for SMLM localization and microscope characterization
Liu S, Chen J, Hellgoth J, Mueller L-R, Ferdman B, Karras C, Xiao D, Lidke KA, Heintzmann R, Shechtman Y, Li Y, Ries J.
Nature Methods, doi: 10.1038/s41592-024-02282-x.
Free  PDF
Previosly onbioRxiv, doi: 10.1101/2023.10.31.564945
Decoding microscopy images by accurate measurement of point spread functions
Li Y, Ries J.
Nature Methods, doi: 10.1038/s41592-024-02283-w.
Build and operation of a custom 3D, multicolor, single-molecule localization microscope
Power RM, Tschanz A, Zimmermann T, Ries J.
Nature Protocols, doi: 10.1038/s41596-024-00989-x
Previosly onbioRxiv, doi: 10.1101/2023.10.23.563122
Skp1 proteins are structural components of the synaptonemal complex in C. elegans.
Blundon J, Cesar B, Bae JW, Čavka I, Haversat J, Ries J, Köhler S, Kim Y.
Science Advances, doi: 10.1126/sciadv.adl4876.
Previously on bioRxiv, doi: 10.1101/2023.05.13.540652.

2023

Direct observation of motor protein stepping in living cells using MINFLUX
Deguchi T, Iwanski MK, Schentarra E-M, Heidebrecht C, Schmidt L, Heck J, Weihs T, Schnorrenberg S, Hoess P, Liu S, Chevyreva V, Noh K-M, Kapitein LC, Ries J.
Science, doi: 10.1126/science.ade2676
Free  PDF
Previously on bioRxiv, doi: 10.1101/2022.07.25.500391
Fast and robust 3D MINFLUX excitation with a variable phase plate
Deguchi T, Ries J.
Maximum-likelihood model fitting for quantitative analysis of SMLM data
Wu Y, Hoess P, Tschanz A, Matti U, Mund M, Ries J.
Nature Methods, doi: 10.1038/s41592-022-01676-z
Previously on bioRxiv, doi: 10.1101/2021.08.30.456756
LocMoFit quantifies cellular structures in super-resolution data
Wu Y, Strack R, Ries J.
Nature Methods, doi: 10.1038/s41592-022-01696-9
Clathrin coats partially preassemble and subsequently bend during endocytosis
Mund* M, Tschanz* A, Wu Y, Frey F, Mehl JL, Kaksonen M, Avinoam O, Schwarz US, Ries J.
Journal of Cell Biology, doi: 10.1083/jcb.202206038
Previously on bioRxiv, doi: 10.1101/2021.10.12.463947
Nanoscale structural organization and stoichiometry of the budding yeast kinetochore
Cieśliński* K, Wu* Y, Nechyporenko L, Hörner SJ, Conti D, Skruzny M, Ries J.
Journal of Cell Biology, doi: 10.1083/jcb.202209094
Previously on bioRxiv, doi: 10.1101/2021.12.01.469648
MicroFPGA: an affordable FPGA platform for microscope control
Deschamps J, Kieser C, Hoess P, Deguchi T, Ries J.
Previously on bioRxiv, doi: 10.1101/2022.06.07.495178
Reply to: Assessment of 3D MINFLUX data for quantitative structural biology in cells
Gwosch KC, Balzarotti F, Pape JK, Hoess P, Ellenberg J, Ries J, Matti U, Schmidt R, Sahl SJ, Hell SW.
Nature Methods, doi: 10.1038/s41592-022-01695-w
Previously on bioRxiv, doi: 10.1101/2022.05.13.491065
Field dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging
Fu S, Shi W, Luo T, He Y, Zhou L, Yang J, Yang Z, Liu J, Liu X, Guo Z, Yang C, Liu C, Huang Z, Ries J, Zhang M, Xi P, Jin D, Li Y
Nature Methods, doi: 10.1038/s41592-023-01775-5
Previously on bioRxiv, doi: 10.1101/2022.10.14.512179
Better than a lens? Increasing the signal-to-noise ratio through pupil splitting
Becker J, Deguchi T, Jügler A, Förster R, Hübner U, Ries J, Heintzmann R
Simulating structurally variable nuclear pore complexes for microscopy.
Theiss M, Hériché JK, Russell C, Helekal D, Soppitt A, Ries J, Ellenberg J, Brazma A, Uhlmann V.
Bioinformatics, doi: 10.1093/bioinformatics/btad587.
Particle fusion of super-resolution data reveals the unit structure of Nup96 in Nuclear Pore Complex
Wang W, Jakobi A, Wu YL, Ries J, Stallinga S, Rieger B
Scientific Reports, doi: doi:10.1038/s41598-023-39829-5
Previously on
bioRxiv, doi: 10.1101/2022.10.04.510818

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Contact

Ries Lab

Department of Structural and Computational Biology
Max Perutz Labs at the Vienna BioCenter, University of Vienna

Campus Vienna Biocenter 5
1030 Wien

Room 1.606
Phone number: +43 1 4277 74380
E-Mail: jonas.ries(at)univie.ac.at

Ries Lab website at EMBL Heidelberg
Ries Lab website at Max Perutz Labs, University of Vienna