TomoFlow: Analysis of continuous conformational variability of macromolecules in cryogenic subtomograms based on 3D dense optical flow

Mohamad Harastani (1) , Mikhail Eltsov (2) , Amélie Leforestier (3) , Slavica Jonic (1)

1 IMPMC - Institut de minéralogie, de physique des matériaux et de cosmochimie
2 IGBMC - Institut de Génétique et de Biologie Moléculaire et Cellulaire
3 LPS - Laboratoire de Physique des Solides

Cryogenic Electron Tomography (cryo-ET) allows structural and dynamics studies of macromolecules in situ. Averaging different copies of imaged macromolecules is commonly used to obtain their structure at higher resolution and discrete classification to analyze their dynamics. Instrumental and data processing developments are progressively equipping cryo-ET studies with the ability to escape the trap of classification into a complete continuous conformational variability analysis. In this work, we propose TomoFlow, a method for analyzing macromolecular continuous conformational variability in cryo-ET subtomograms based on a three-dimensional dense optical flow (OF) approach. The resultant lower-dimensional conformational space allows generating movies of macromolecular motion and obtaining subtomogram averages by grouping conformationally similar subtomograms. The animations and the subtomogram group averages reveal accurate trajectories of macromolecular motion based on a novel mathematical model that makes use of OF properties. This paper describes TomoFlow with tests on simulated datasets generated using different techniques, namely Normal Mode Analysis and Molecular Dynamics Simulation. It also shows an application of TomoFlow on a dataset of nucleosomes in situ, which provided promising results coherent with previous findings using the same dataset but without imposing any prior knowledge on the analysis of the conformational variability. The method is discussed with its potential uses and limitations.

Mots clés: Cryogenic electron tomography (cryo-ET); continuous conformational variability analysis; optical flow; nucleosomes in situ; TomoFlow

Domaines: Biologie structurale [q-bio.BM]; Traitement du signal et de l'image [eess.SP]; Vision par ordinateur et reconnaissance de formes [cs.CV]

Mohamad Harastani, Mikhail Eltsov, Amélie Leforestier, Slavica Jonic. TomoFlow: Analysis of continuous conformational variability of macromolecules in cryogenic subtomograms based on 3D dense optical flow. Journal of Molecular Biology, 2022, 434 (2), pp.167381. ⟨10.1016/j.jmb.2021.167381⟩. ⟨hal-03452809⟩