Cryo-Electron Tomography of Chlamydomonas reinhardtii: Leveraging Electron Event Representation (EER) Image Format in Visual Proteomics

This is the authors' abstract. We don't add key points for this paper.

Cryo-electron tomography (cryo-ET) and subtomogram averaging, combined with cryo-focused ion beam (cryo-FIB) milling, provide a groundbreaking approach to explore biomolecules within their native environment. Referred to as visual proteomics, this method enables visualization of biomolecular complexes within cells [1], unlike traditional structural biology methods reliant on solutions or crystals. Our pilot study with Chlamydomonas reinhardtii [2], a unicellular green alga, aims to unravel high-resolution cellular structures, inspiring large-scale studies across species. Cryo-ET faces challenges, affecting attainable resolution [3]. These include a very low dose per image leading to a low signal-to-noise ratio and increased motion during imaging compared to single particle analysis (SPA). Furthermore, its low throughput nature emphasizes the critical importance of data quality. The TFS-exclusive Electron Event Representation (EER) image format preserves the full time and spatial resolution of the detector [4], offering the highest possible data quality. In this work, we assess the key benefits of the EER format for cryo-ET and subtomogram averaging (STA). We are currently testing our data pre-processing pipeline using EER against conventional TIFF format. Preliminary results suggest improvement in local resolution of ribosome structure determined by STA, as measured by Fourier shell correlation. Furthermore, we plan to compare EER and TIFF-based data processing by two metrics: ultimate attainable resolution and B-factor, i.e. dependence of resolution on dataset size. If the benefit is convincingly demonstrated, this would make a compelling case for wider adoption of EER in the cryo-ET community. The significance of this study goes beyond scientific discovery, acting as a catalyst for advancements in cryo-ET methodologies. We have also created an open access database for C. reinhardtii tomograms [5] to accelerate annotation and curation, enable further cell biology research, and develop new computational tools for in situ cryo-ET. By unlocking the potential of visual proteomics, we pave the way for transformative impacts on future in situ structural biology studies.