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Cryo-electron tomography (cryo-ET) and subtomogram averaging (STA) can resolve protein complexes at near atomic resolution, and when combined with focused ion beam (FIB) milling, macromolecules can be observed within their native context. Unlike single particle acquisition (SPA), cryo-ET can be slow, which may reduce overall project throughput. We here propose a fast, multi-position tomographic acquisition scheme based on beam-tilt corrected beam-shift imaging along the tilt axis, which yields sub-nanometer in situ STA averages.

Background and ObjectiveCryo-electron tomography (cryo-ET) is an imaging technique that enables 3D visualization of the native cellular environment at sub-nanometer resolution, providing unpreceded insights into the molecular organization of cells. However, cryo-electron tomograms suffer from low signal-to-noise ratios and anisotropic resolution, which makes subsequent image analysis challenging. In particular, the automated detection of membrane-embedded proteins is a problem still lacking satisfactory solutions.MethodsWe present MemBrain – a new deep learning-based pipeline that automatically detects membrane-bound protein complexes in cryo-electron tomograms. After subvolumes are sampled along a segmented membrane, each subvolume is assigned a score using a convolutional neural network (CNN), and protein positions are extracted by a clustering algorithm. Incorporating rotational subvolume normalization and using a tiny receptive field simplify the task of protein detection and thus facilitate the network training.ResultsMemBrain requires only a small quantity of training labels and achieves excellent performance with only a single annotated membrane (F1 score: 0.88). A detailed evaluation shows that our fully trained pipeline outperforms existing classical computer vision-based and CNN-based approaches by a large margin (F1 score: 0.92 vs. max. 0.63). Furthermore, in addition to protein center positions, MemBrain can determine protein orientations, which has not been implemented by any existing CNN-based method to date. We also show that a pre-trained MemBrain program generalizes to tomograms acquired using different cryo-ET methods and depicting different types of cells.ConclusionsMemBrain is a powerful and label-efficient tool for the detection of membrane protein complexes in cryo-ET data, with the potential to be used in a wide range of biological studies. It is generalizable to various kinds of tomograms, making it possible to use pretrained models for different tasks. Its efficiency in terms of required annotations also allows rapid training and fine-tuning of models. The corresponding code, pretrained models, and instructions for operating the MemBrain program can be found at: https://github.com/CellArchLab/MemBrain

Cryogenic electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at nanometer resolution inside native cells. However, automated identification of macromolecules inside cellular tomograms is challenged by noise and reconstruction artifacts, as well as the presence of many molecular species in the crowded volumes. Here, we present DeepFinder, a computational procedure that uses artificial neural networks to simultaneously localize multiple classes of macromolecules. Once trained, the inference stage of DeepFinder is faster than template matching and performs better than other competitive deep learning methods at identifying macromolecules of various sizes in both synthetic and experimental datasets. On cellular cryo-ET data, DeepFinder localized membrane-bound and cytosolic ribosomes (roughly 3.2 MDa), ribulose 1,5-bisphosphate carboxylase–oxygenase (roughly 560 kDa soluble complex) and photosystem II (roughly 550 kDa membrane complex) with an accuracy comparable to expert-supervised ground truth annotations. DeepFinder is therefore a promising algorithm for the semiautomated analysis of a wide range of molecular targets in cellular tomograms. DeepFinder is a deep learning-based tool for identifying macromolecules in cellular cryo-electron tomograms. DeepFinder performs with an accuracy comparable to expert-supervised ground truth annotations on multiple experimental datasets.

Ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco) is present in all photosynthetic organisms and is a key enzyme for photosynthesis-driven life on Earth. Its most prominent form is a hetero-oligomer in which small subunits (SSU) stabilize the core of the enzyme built from large subunits (LSU), yielding, after a chaperone-assisted multistep assembly process, an LSU8SSU8 hexadecameric holoenzyme. Here we use Chlamydomonas reinhardtii and a combination of site-directed mutants to dissect the multistep biogenesis pathway of Rubisco in vivo. We identify assembly intermediates, in two of which LSU are associated with the RAF1 chaperone. Using genetic and biochemical approaches we further unravel a major regulation process during Rubisco biogenesis, in which LSU translation is controlled by its ability to assemble with the SSU, via the mechanism of control by epistasy of synthesis (CES). Altogether this leads us to propose a model whereby the last assembly intermediate, an LSU8-RAF1 complex, provides the platform for SSU binding to form the Rubisco enzyme, and when SSU is not available, converts to a key regulatory form that exerts negative feedback on the initiation of LSU translation.

Ribulose 1,5-bisphosphate Carboxylase/Oxygenase (Rubisco) is a key enzyme for photosynthesis-driven life on Earth. While present in all photosynthetic organisms, its most prominent form is a hetero-oligomer in which a Small Subunit (SSU) stabilizes the core of the enzyme built from Large Subunits (LSU), yielding, after a chaperone-assisted multistep assembly, a LSU8SSU8hexadecameric holoenzyme. Here we useChlamydomonas reinhardtii, and a combination of site-directed mutants, to dissect the multistep biogenesis pathway of Rubiscoin vivo. We identify assembly intermediates, in two of which LSU is associated with the RAF1 chaperone. Using genetic and biochemical approaches we further unravel a major regulation process during Rubisco biogenesis which places translation of its large subunit under the control of its ability to assemble with the small subunit, by a mechanism of Control by Epistasy of Synthesis (CES). Altogether this leads us to propose a model where the last assembly intermediate, an octameric LSU8-RAF1 complex which delivers LSU to SSU to form the Rubisco enzyme, converts to a key regulator form able to exert a negative feed-back on the initiation of translation of LSU, when SSU is not available.

Filamentous enzymes have been found in all domains of life, but the advantage of filamentation is often elusive

Vesicle-inducing protein in plastids (VIPP1) is essential for the biogenesis and maintenance of thylakoid membranes, which transform light into life. However, it is unknown how VIPP1 performs its vital membrane-shaping function. Here, we use cryo-electron microscopy to determine structures of cyanobacterial VIPP1 rings, revealing how VIPP1 monomers flex and interweave to form basket-like assemblies of different symmetries. Three VIPP1 monomers together coordinate a non-canonical nucleotide binding pocket that is required for VIPP1 oligomerization. Inside the ring’s lumen, amphipathic helices from each monomer align to form large hydrophobic columns, enabling VIPP1 to bind and curve membranes. In vivo point mutations in these hydrophobic surfaces cause extreme thylakoid swelling under high light, indicating an essential role of VIPP1 lipid binding in resisting stress-induced damage. Our study provides a structural basis for understanding how the oligomerization of VIPP1 drives the biogenesis of thylakoid membranes and protects these life-giving membranes from environmental stress.

Summary Vesicle-inducing protein in plastids 1 (VIPP1) is essential for the biogenesis and maintenance of thylakoid membranes, which transform light into life. However, it is unknown how VIPP1 performs its vital membrane-remodeling functions. Here, we use cryo-electron microscopy to determine structures of cyanobacterial VIPP1 rings, revealing how VIPP1 monomers flex and interweave to form basket-like assemblies of different symmetries. Three VIPP1 monomers together coordinate a non-canonical nucleotide binding pocket on one end of the ring. Inside the ring’s lumen, amphipathic helices from each monomer align to form large hydrophobic columns, enabling VIPP1 to bind and curve membranes. In vivo mutations in these hydrophobic surfaces cause extreme thylakoid swelling under high light, indicating an essential role of VIPP1 lipid binding in resisting stress-induced damage. Using cryo-correlative light and electron microscopy (cryo-CLEM), we observe oligomeric VIPP1 coats encapsulating membrane tubules within the Chlamydomonas chloroplast. Our work provides a structural foundation for understanding how VIPP1 directs thylakoid biogenesis and maintenance.

Cryo-electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at nanometer resolution inside native cells. While this label-free cryogenic imaging technology produces data containing rich structural information, automated identification of macromolecules inside cellular tomograms is challenged by noise and reconstruction artifacts, as well as the presence of many molecular species in the crowded volumes. Here, we present a computational procedure that uses artificial neural networks to simultaneously localize with a multi-class strategy several macromolecular species in cellular cryo-electron tomograms. Once trained, the inference stage of DeepFinder is significantly faster than template matching, and performs better than other competitive deep learning methods at identifying macromolecules of various sizes in both synthetic and experimental datasets. On cellular cryo-ET data, DeepFinder localized membrane-bound and cytosolic ribosomes (~3.2 MDa), Rubisco (~540 kDa soluble complex), and photosystem II (~550 kDa membrane complex) with comparable accuracy to expert-supervised ground truth annotations. Furthermore, we show that DeepFinder is flexible and can be combined with template matching to localize the missing macromolecules not found by one or the other method. The DeepFinder algorithm is therefore very promising for the semi-automated analysis of a wide range of molecular targets in cellular tomograms, including macromolecules with weights of 500-600 kDa and membrane proteins.

Thylakoid membranes scaffold an assortment of large protein complexes that work together to harness the energy of light. It has been a longstanding challenge to visualize how the intricate thylakoid network organizes these protein complexes to finely tune the photosynthetic reactions. Previously, we used in situ cryo-electron tomography to reveal the native architecture of thylakoid membranes (Engel et al., 2015). Here, we leverage technical advances to resolve the individual protein complexes within these membranes. Combined with a new method to visualize membrane surface topology, we map the molecular landscapes of thylakoid membranes inside green algae cells. Our tomograms provide insights into the molecular forces that drive thylakoid stacking and reveal that photosystems I and II are strictly segregated at the borders between appressed and non-appressed membrane domains. This new approach to charting thylakoid topology lays the foundation for dissecting photosynthetic regulation at the level of single protein complexes within the cell.

Upon first exposure to light, plants initiate the synchronized biogenesis of chlorophyll and thylakoid membranes. Two new studies have revealed a molecular view of the light-dependent step of chlorophyll synthesis within the membranes of developing angiosperm chloroplasts.

Vesicle-inducing protein in plastids (VIPP1) is essential for the biogenesis and maintenance of thylakoid membranes, which transform light into life. However, it is unknown how VIPP1 performs its vital membrane-shaping function. Here, we use cryo-electron microscopy to determine structures of cyanobacterial VIPP1 rings, revealing how VIPP1 monomers flex and interweave to form basket-like assemblies of different symmetries. Three VIPP1 monomers together coordinate a non-canonical nucleotide binding pocket that is required for VIPP1 oligomerization. Inside the ring’s lumen, amphipathic helices from each monomer align to form large hydrophobic columns, enabling VIPP1 to bind and curve membranes. In vivo point mutations in these hydrophobic surfaces cause extreme thylakoid swelling under high light, indicating an essential role of VIPP1 lipid binding in resisting stress-induced damage. Our study provides a structural basis for understanding how the oligomerization of VIPP1 drives the biogenesis of thylakoid membranes and protects these life-giving membranes from environmental stress.

Thylakoid membranes scaffold an assortment of large protein complexes that work together to harness the energy of light. It has been a longstanding challenge to visualize how the intricate thylakoid network organizes these protein complexes to finely tune the photosynthetic reactions. Previously, we used in situ cryo-electron tomography to reveal the native architecture of thylakoid membranes (Engel et al., 2015). Here, we leverage technical advances to resolve the individual protein complexes within these membranes. Combined with a new method to visualize membrane surface topology, we map the molecular landscapes of thylakoid membranes inside green algae cells. Our tomograms provide insights into the molecular forces that drive thylakoid stacking and reveal that photosystems I and II are strictly segregated at the borders between appressed and non-appressed membrane domains. This new approach to charting thylakoid topology lays the foundation for dissecting photosynthetic regulation at the level of single protein complexes within the cell.

Thylakoid membranes scaffold an assortment of large protein complexes that work together to harness the energy of light to produce oxygen, NADPH, and ATP. It has been a longstanding challenge to visualize how the intricate thylakoid network organizes these protein complexes to finely tune the photosynthetic reactions. Using cryo-electron tomography to analyze membrane surface topology, we have mapped the native molecular landscape of thylakoid membranes within green algae cells. Our tomograms provide insights into the molecular forces that drive thylakoid stacking and reveal that photosystems I and II are strictly segregated at the borders between appressed and non-appressed membrane domains. This new approach to charting thylakoid topology lays the foundation for dissecting photosynthetic regulation at the level of single protein complexes within the cell.