Niels Volkmann, PhD. : Computational Tools for Macromolecular Structure Discovery in Multimodal Cryogenic Imaging

Special Seminar - Niels Volkmann, Ph.D.

This seminar speaker will present in-person and the seminar will be broadcasted online via Zoom. 

Zoom will open after the host has joined at the start of each seminar. You can ask questions through the chat forum and by raising your "hand" and the speaker will call on you. 

Speaker - Niels Volkmann

Monday, May 16, 2022 | 2 PM Elings Hall 1601, or join us virtually on Zoom!

Tuesday, May 17, 2022 | 10 AM BIOE 3001, or join us virtually on Zoom!

RSVP with info@bioengineering.ucsb.edu

Seminar Abstract

Recent technical advances in cryogenic electron microscopy (cryo-EM) offer now the possibility not only to solve the structures of ever larger macromolecular assemblies at atomic resolution, but also to create three-dimensional mappings of entire proteomes in cryogenically preserved cells and tissues. In particular, cryogenic electron tomography (cryo-ET), the technique that allows three-dimensional investigation of arbitrary volumes in their native state at nanometer resolution, is gaining significant traction. When combined with additional data from biophysical and engineering approaches as well as other imaging modalities, these methods can potentially revolutionize our understanding of biological processes and how they are modulated by perturbations in their environment.

However, the task of imaging cells at near-atomic resolution not only involves processing massive quantities of data, but also dealing with tremendous data complexity. Even with the current technological limits that restrict us to study smaller regions of the cell, currently about 2 x 2 x 0.5 microns, each volume represents ~20 GB of data and contains ~5 million protein molecules. Though the basic cryo-ET technique has been used for several decades, the technology is being revolutionized by recent advances in hardware, direct electron detection technology, and automatic data collection, leading to the ability to collect extraordinarily large numbers of raw tomographic data sets. These advances translate to a nominal increase of two orders of magnitude in data throughput. Thus, rapid data processing and quantitative analysis are quickly becoming the primary bottleneck in cryo-EM and cryo-ET. It has indeed become abundantly clear that only automated or at least semi-automated processing and analysis can keep up with the increasing flow of data.

To address these challenges, Dr. Volkmann is developing and applying innovative new automated computational, artificial intelligence, and data science tools. Additional efforts in his lab are targeting the quantitative integration of structural information from cryo-EM and cryo-ET with other biophysical techniques, imaging modalities, mathematical modeling, molecular dynamics, and engineering approaches. These efforts bridge information between the atomic and cellular scales, covering more than six orders of magnitude from Ångstroms to tens of microns. Taken together, Dr. Volkmann’s approach enables automated or at semi-automated direct nanometer scale definition of molecular assemblies and higher-order structures in their native environmental and functional context, allowing to derive more detailed and holistic hypotheses about the behavior of these nanomachines within cells. Furthermore, the approach allows probing of cellular behavior in response to perturbations including addition of chemicals/drugs or using engineered systems emulating specific cellular and extracellular environments or external forces.

About the Speaker

I was originally educated as a Physicist and Biophysicist. During my postdoctoral training, I expanded my knowledge first to macromolecular X-ray crystallography and then to electron cryo-microscopy (cryo-EM), image processing and data mining. Cryo-EM and the associated data analysis are rapidly developing fields with no formal curriculum available. Over the last 20 years, I developed and applied many innovative data mining algorithms primarily targeting the interpretation of data from in-situ cellular cryo-tomography but also for high-resolution structure determination of reconstituted systems of varying complexity unraveling basic rules such as those underlying self-assembly of cytoskeletal elements on the basis of statistics and quantification.

My research focuses on the development and application of innovative new computational, artificial intelligence, and data science tools to bridge information between the atomic and cellular scales, covering more than six orders of magnitude from Ångstroms to tens of microns. To this end, I am leading efforts targeting the analysis and interpretation of reconstructions from cryo-EM) and cellular cryo-ET and their correlation with other biophysical techniques and imaging modalities.