2021/09/21 Grant Jensen

Jensen, Grant

Grant Jensen

Dean, College of Physical and Mathematical Sciences, Brigham Young University

Professor of Biology and Biophysics
California Institute of Technology

Date and time: September 29th, 2021
Wednesday, at 8am PT / 11am ET / 4pm BST / 5pm CEST / 11pm China

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Montage tomography of cryo-preserved specimens

Ariana Peck, Stephen D. Carter, Huanghao Mai, Songye Chen, Alister Burt, and Grant J. Jensen

Cryo-electron tomography reveals detailed views of macromolecules in situ, but the fields of view can be quite limited. Decades ago, montage tomography methods were developed to large areas of plastic sections, which are less radiation-sensitive than samples in vitreous ice. The dose sensitivity of vitreous samples has been considered prohibitive to montaging approaches, since portions of the sample must be exposed multiple times to allow image stitching. Taking advantage of several technical advances, we have now developed a montage data collection scheme that distributes the extra dose evenly throughout the specimen. We applied this method to image the thin edge of frozen-hydrated HeLa cells, and show that macromolecular details can be resolved across montage tomograms several microns across. Montage cryo-ET could be especially useful for imaging lamellae.

2021/06/16 Amit Singer

Amit Singer

Amit Singer

Professor of Mathematics at Princeton University

Wilson Statistics: Derivation, Generalization, and Applications to Cryo-EM

Date and time: June 16, 2021

Wednesday, at 8am PT / 11am ET / 3pm GMT / 5pm CET / 11pm China

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Note that we no longer use the zoom registration system, so old zoom links may not work. The new links will be sent via the mailing list.

The power spectrum of proteins at high frequencies is remarkably well described by the flat Wilson statistics. Wilson statistics therefore plays a significant role in X-ray crystallography and more recently in cryo-EM. Specifically, modern computational methods for three-dimensional map sharpening and atomic modelling of macromolecules by single particle cryo-EM are based on Wilson statistics. In this talk we provide the first rigorous mathematical derivation of Wilson statistics. The derivation pinpoints the regime of validity of Wilson statistics in terms of the size of the macromolecule. Moreover, the analysis naturally leads to generalizations of the statistics to covariance and higher order spectra. These in turn provide theoretical foundation for assumptions underlying the widespread Bayesian inference framework for three-dimensional refinement and for explaining the limitations of autocorrelation based methods in cryo-EM.

2021/05/19 Lauren Ann Metskas

Lauren Ann Metskas

Lauren Ann Metskas

Postdoctoral Fellow at California Institute of Technology
Incoming Assistant Professor at Purdue University

Illuminating the Map: Current Practices, Challenges, and Future Applications of Cryo-CLEM

Date and time: May 19, 2021

Wednesday, at 8am PT / 11am ET / 3pm GMT / 5pm CET / 11pm China

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Note that we no longer use the zoom registration system, so old zoom links may not work. The new links will be sent via the mailing list.

Correlated cryo-light and cryo-electron microscopy (cryo-CLEM) has become an increasingly popular method for combining the resolving power of cryo-EM with the specificity of fluorescence. Although cryo-fluorescence microscopy suffers from optical limitations, it is a powerful way to target the resolving power of cryo-EM toward proteins of interest in heterogeneous cellular environments. Two large areas of methods developments are ongoing in both hardware and software: improving the correlation precision and accuracy to facilitate single-protein targeting, and expanding the cryo-fluorescence toolkit to include room-temperature approaches capable of targeting functions or specific protein conformations. This webinar will begin with a theoretical overview of current obstacles and considerations for software developers seeking to improve correlation precision and accuracy, and conclude with our recent efforts to improve cryo-fluorescence data quality, including characterizing the effect of cryo temperatures on fluorophores and establishing function-based localization in cryo-CLEM.

2021/05/05 Dong Si

Dong Si

Dong Si

Assistant Professor at University of Washington Bothell

Artificial Intelligence Advances for De Novo Molecular Structure Modeling in Cryo-EM

Date and time: May 5, 2021

Wednesday, at 8am PT / 11am ET / 3pm GMT / 5pm CET / 11pm China

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Note that we no longer use the zoom registration system, so old zoom links may not work. The new links will be sent via the mailing list.

Although cryo-EM has been drastically improved to generate high-resolution three-dimensional (3D) maps that contain detailed structural information about macromolecules, the computational methods for using the data to automatically build structure models are lagging far behind. The traditional cryo-EM model building approach is template-based homology modeling. Manual de novo modeling is very time-consuming when no template model is found in the database. In recent years, de novo cryo-EM modeling using machine learning (ML) and deep learning (DL) has ranked among the top-performing methods in macromolecular structure modeling. Deep-learning-based de novo cryo-EM modeling is an important application of artificial intelligence, with impressive results and great potential for the next generation of molecular biomedicine. Accordingly, I will talk about the representative ML/DL-based de novo cryo-EM modeling methods that we developed.

2021/04/07 David DeRosier

David DeRosier

David DeRosier

Professor Emeritus of Biology at Brandeis University

Where in the cell is my protein: revisited.

Date and time: April 7, 2021

Wednesday, at 8am PT / 11am ET / 3pm GMT / 5pm CET / 11pm China

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Note that we no longer use the zoom registration system, so old zoom links may not work. The new links will be sent via the mailing list.

Cryo electron tomograms (cryo-ET) are nothing short of amazing. There is so much to see, but wouldn’t it be nice if we could identify all those structural features in terms of their molecular identity? The combination of cryo-single molecule localization microscopy (cryo-SMLM) and cryo-ET should provide a pathway to making such identification. What are the challenges to realizing the combination’s full potential? Why the fish tank?

2021/03/24 Slavica Jonic

Slavica Jonic

Slavica Jonic

CNRS Research Director

Combining normal mode analysis, image analysis, and deep learning for in vitro and in situ studies of continuous conformational variability of macromolecular complexes

Date and time: March 24th, 2021
Wednesday, at 8am PT / 11am ET / 3pm GMT / 4pm CET / 11pm China

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Note that we no longer use the zoom registration system, so old zoom links may not work. The new links will be sent via the mailing list.

HEMNMA is a method to analyze continuous conformational variability of purified macromolecular complexes (in vitro), introduced in 2014 (Jin et al., Structure 22:496-506, 2014). Its software with user friendly graphical interface is part of the open-source ContinuousFlex plugin of Scipion 2 and Scipion 3 (Harastani et al., Protein Science 29:223–236, 2020). HEMNMA combines single particle image analysis, normal mode analysis, and dimension reduction techniques to visualize the full distribution of states (conformational landscape) in a low-dimensional space (usually 2D or 3D space), from which one can obtain 3D reconstructions and movies of molecular motions along desired directions. After a brief reminder on HEMNMA, I will present current developments, including combining HEMNMA with deep learning to accelerate the conformational landscape determination and an extension of HEMNMA to analyze continuous conformational variability of macromolecular complexes in cells from in situ cryo electron tomography data.     

2021/03/10-11: Pilot Poster Session

One World Cryo-EM Pilot Poster Session

Time and date: 3/10/2021
Live sessions:
March 10 11am-1pm EST,
March 10 8-10pm EST,
March 11 8am-10am EST
Location: gather.town (link available through our mailing list)

Information: https://cryoem.world/talks/2021-03-10-poster-session/

We are delighted to announce that we will be hosting a pilot virtual One World Cryo-EM Poster Session on March 10-11, 2021. This poster session, held on gather.town, will be a chance to discuss research with colleagues, share your own work, and socialize with others in the community.

A list of posters, presenters, and their availability can be found below or at the following link.

We have 3 live poster sessions on: March 10 11am-1pm EST, March 10 8-10pm EST, March 11 8am-10am EST. 

If you are interested in presenting, please submit your poster on this application form. With your poster, you may optionally submit a 3-5 minute video to be displayed alongside your poster for visitors outside of live poster sessions. More information and details are provided in the form.

Please make sure that you are on our mailing list. This is the only place where the links to the gather.town poster session will be posted. As always, you can find more information at https://cryoem.world

We are excited to host this poster session, and hope that you will join us.

Important Rules and Policies

As a participant, you agree that any information presented in the One World Cryo-EM poster session, whether in a poster, talk, video, or discussion, is private communication and that the information is not for public use.

You agree not to record the information by any means and not to quote or publish it without the written permission of the presenter. This includes posting information on social media, in publications, and on blogs. 

You understand that the posters are not peer-reviewed and not archivable.

You understand that it is up to each participant to follow these restrictions. The organizers are not responsible for enforcing these restrictions. 

Note that the list of poster titles and authors will be available on the OWCryo-EM website. Therefore, you may tweet a recommendation to visit poster #123 titled x by y (#OWCryoEMPosters) without referencing the content.

As a presenter, you may post your own poster on Twitter and invite people to retweet it and meet you at your poster #OWCryoEMPosters.

FAQ

Q: What is gather.town? What do posters there look like?
A: This is what a poster looks like on gather.town: https://gather.town/app/5Qb5FSmPM0wtDvpd/sample_poster (the actual session is expected to have a slightly larger number of posters).

Q: How do I view the gather.town session?
A: Please make sure that you are on our mailing list. This is the only place where the links to the gather.town poster session will be posted.

Q: What is the poster selection process?
A: In this pilot poster session, we expect to accept all novel work that satisfies the topic, quality, and form requirements.

Q: How do I submit a poster?
A: Please submit your completed poster on this application form. You are not required to submit a title and abstract before submitting the full poster.

Q: What are the requirements for the poster?
A: Posters should be in an image format (eg .png, .jpg, but not .pdf), and should be at least 4000×6000 pixels. You may resubmit posters up to 10 times until February 22nd. These will be collectively posted in gather.town, and we will let you know your poster ID number. Here is a poster size example.

Q: What are the requirements for the video?
A: Videos are optional, and should be between 3-5 minutes long and provide viewers a brief description of your poster. These will be posted next to your poster for visitors that cannot make the live session, or to provide visitors context about your poster.

2021/03/03 Pilar Cossio

Pilar Cossio

Pilar Cossio

Max Planck Tandem Group Leader associated with the University of Antioquia (Colombia) and the Max Planck Institute of Biophysics (Germany)

Cryo-BIFE: Cryo-EM Bayesian Inference of Free Energy profiles

Date and time: March 3rd, 2021
Wednesday, at 8am PT / 11am ET / 4pm GMT / 5pm CET / Feb 18th midnight China

For the zoom and gather.town links, please join the One World Cryo-EM mailing list.
Note that we no longer use the zoom registration system, so old zoom links may not work. The new links will be sent via the mailing list.

Cryo-electron microscopy (cryo-EM) extracts single-particle density projections of individual biolmolecules. Although cryo-EM is widely used for 3D reconstruction, due to its single-particle nature, it has the potential to provide information about a biomolecule’s conformational variability and underlying free energy landscape. However, treating cryo-EM as a single molecule technique is challenging because of the low signal-to-noise ratio in the individual particles. In this work, we developed the cryo-BIFE method, a Bayesian framework that uses a path collective variable to extract free energy profiles and their uncertainties from cryo-EM images. We tested the framework over several systems, finding that for realistic cryo-EM environments, and relevant biomolecular systems, it is possible to recover the underlying free energy.

2021/02/17 Dari Kimanius, Gustav Zickert

Dari Kimanius
Gustav Zickert

Dari Kimanius & Gustav Zickert

Dari Kimanius – Postdoc at MRC Laboratory of Molecular Biology
Gustav Zickert – Guest researcher at KTH Royal Institute of Technology

Cryo-EM structure determination with data-driven priors

Date and time: Feb 17th, 2021
Wednesday, at 8am PT / 11am ET / 4pm GMT / 5pm CET / Feb 18th midnight China

For the zoom and gather.town links, please join the One World Cryo-EM mailing list.
Note that we no longer use the zoom registration system, so old zoom links may not work. The new links will be sent via the mailing list.

Three-dimensional reconstruction of the electron-scattering potential of biological macromolecules from electron cryo-microscopy (cryo-EM) projection images is an ill-posed problem. The most popular cryo-EM software solutions to date rely on a regularization approach that is based on the prior assumption that the scattering potential varies smoothly over three-dimensional space. Although this approach has been hugely successful in recent years, the amount of prior knowledge that it exploits compares unfavorably with the knowledge about biological structures that has been accumulated over decades of research in structural biology. Here, a regularization framework for cryo-EM structure determination is presented that exploits prior knowledge about biological structures through a convolutional neural network that is trained on known macromolecular structures. This neural network is inserted into the iterative cryo-EM structure-determination process through an approach that is inspired by regularization by denoising. It is shown that the new regularization approach yields better reconstructions than the current state of the art for simulated data, and options to extend this work for application to experimental cryo-EM data are discussed.

2020/12/02: Alberto Bartesaghi: CryoET – high-speed or high-resolution? BISECT tackles both

Alberto Bartesaghi

Alberto Bartesaghi

Associate Professor of Computer Science, Biochemistry and Electrical and Computer Engineering, Duke University

CryoET – high-speed or high-resolution? BISECT tackles both

Date and time: Dec 2nd, 2020 Wednesday, at 8am PT / 11am ET / 4pm GMT / 5pm CET / Dec 3rd midnight China

For the zoom and gather.town links, please join the One World Cryo-EM mailing list.
Note that we no longer use the zoom registration system, so old zoom links may not work. The new links will be sent via the mailing list.

Tomographic reconstruction of cryo-preserved specimens followed by extraction and averaging of sub-volumes has been successfully used to determine the structure of macromolecules in their native environment.
Eliminating biochemical isolation steps required by other techniques, this method opens up the cell to in-situ structural studies. Delays introduced during mechanical navigation of the specimen and stage tilting, however, significantly slow down data collection thus limiting its practical value. Here, I present BISECT (beam image-shift electron cryo-tomography), a new protocol to accelerate tilt-series acquisition without sacrificing resolution. I also describe improvements to our constrained single particle tomography (CSPT) framework, leading to higher resolution reconstructions determined by sub-volume averaging.
For validation, we collected tilt-series from a low molecular weight target (~300kDa) using BISECT and processed them using CSPT to obtain a 3.6 Å resolution map where density for side chains is clearly resolved. These advances bring cryo-ET a step closer to becoming a high-throughput tool for in-situ structure determination at near-atomic resolution.