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Biology subjects

Chaillet, M. L.

Publications and source records attributed to Chaillet, M. L..

2 recordsLinked to original sources

Structure of an oxygen-induced tubular nanocompartment in Pyrococcus furiosus

Reactive oxygen species (ROS) pose a significant threat to biological molecules, prompting organisms to develop systems that buffer oxidative stress and contain iron, which otherwise amplifies ROS production. Understanding oxidative stress responses requires identifying the key proteins involved and their cellular organization. Here, we combined proteomics and cryo-EM to investigate the response of the anaerobic hyperthermophilic archaeon Pyrococcus furiosus to oxygen exposure. Proteome analysis revealed a significant upregulation of the oxidoreductase Rubrerythrin (Rbr) under oxidative stress. Cryo-electron tomograms showed the formation of prominent oxidative stress-induced tubules (OSITs). Single-particle cryo-EM and mass spectrometry of enriched OSITs identified them as stacked rings of Rbr homotetramers. The 3.3 [A] structure demonstrates that rubredoxin-like domains mediate homotetramer assembly, suggesting that their oxidation drives OSIT formation. Within OSITs, we discovered virus-like particles formed by a ferritin-like/encapsulin fusion protein with iron hydroxide cores, uncovering a sophisticated organelle that protects P. furiosus from ROS through advanced compartmentalization.

molecular biology↗

pytom-match-pick: a tophat-transform constraint for automated classification in template matching

Template matching (TM) in cryo-electron tomography (cryo-ET) enables in situ detection and localization of known macromolecules. However, TM faces challenges such as interfering features with a high signal-to-noise ratio and the need for manual curation of results. To address these challenges, we introduce pytom-match-pick, a GPU-accelerated, open-source command line interface for enhanced TM in cryo-ET. Using pytom-match-pick, we first quantify the effects of point spread function (PSF) weighting and show that a tilt-weighted PSF outperforms a binary wedge with a single defocus estimate. We also assess previously introduced background normalization methods for classification performance. This indicates that phase randomization is more effective than spectrum whitening in reducing false positives. Furthermore, a novel application of the tophat transform on score maps, combined with a dual-constraint thresholding strategy, reduces false positives and improves precision. We benchmarked pytom-match-pick on public datasets, demonstrating improved classification and localization of macromolecules like ribosomal subunits and proteasomes that led to fewer artifacts in subtomogram averages. This tool promises to advance visual proteomics by improving the efficiency and accuracy of macromolecule detection in cellular contexts.

molecular biology↗