Wojciech Wietrzyñski

This study identifies three photoprotective mechanisms in diatoms under light stress: detachment of oxygen-evolving complex proteins, NPQ in the antenna, and energy spillover between photosystems.

This study shows that far-red light induces structural changes in cyanobacterial thylakoids, reorganizing antenna-photosystem complexes and revealing persistent membrane heterogeneity.

MemBrain v2 couples a generalist U-Net cryo-ET membrane segmenter, a mesh-based picker reaching 91% F1 for photosystem II from one annotated membrane, and geodesic particle statistics.

This study shows that the lateral distribution of cytochrome b6f in thylakoid membranes affects photosynthetic electron transfer efficiency in Chlamydomonas reinhardtii.

The paper shows that mature Arabidopsis thylakoid membranes can reversibly transition from lamellar to gyroid cubic structures without losing photosystem II function.

The paper introduces an Advanced Mobile Laboratory (AML) for field-based microbial ecology and cell biology, enabling multiscale analysis of environmental samples directly at the sampling site.

Automated cryogenic plasma-focused ion beam milling and cryo-electron tomography of Chlamydomonas reinhardtii yield 1,829 annotated cellular tomograms and sub-nanometer in situ structures of six macromolecular complexes.

This study uses cryo-ET and AI-based methods to analyze thylakoid membrane organization in spinach chloroplasts, revealing similarities to green algae despite differences in 3D architecture.

This study identifies a protein shell surrounding diatom pyrenoids that enhances CO2 fixation efficiency and reveals its structural and functional role through in vivo and in vitro analyses.

This paper introduces a fast multi-position tomographic acquisition method for subtomogram averaging, achieving sub-nanometer resolution in situ.

MemBrain detects membrane proteins in cryo-ET data using a deep learning pipeline, achieving high accuracy with minimal labels and generalizing across different cell types and imaging methods.

This paper introduces DeepFinder, a deep learning method that improves macromolecule identification in 3D cellular cryo-ET data by localizing multiple species with high accuracy.