What shapes template-matching performance in cryogenic electron tomography in situ?

The detection of specific biological macromolecules in cryogenic electron tomography data is frequently approached by applying cross-correlation-based 3D template matching. To reduce computational cost and noise, high binning is used to aggregate voxels before template matching. This remains a prevalent practice in both practical applications and methods development. Here, the relation between template size, shape and angular sampling is systematically evaluated to identify ribosomes in a ground-truth annotated data set. It is shown that at the commonly used binning, a detailed subtomogram average, a sphere and a heart emoji result in near-identical performance. These findings indicate that with current template-matching practices macromolecules can only be detected with high precision if their shape and size are sufficiently different from the background. Using theoretical considerations, the experimental results are rationalized and it is discussed why primarily low-frequency information remains at high binning and that template matching fails to be accurate because similarly shaped and sized macromolecules have similar low-frequency spectra. These challenges are discussed and potential enhancements for future template-matching methodologies are proposed.

ColabSeg: An interactive tool for editing, processing, and visualizing membrane segmentations from cryo-ET data.

Cellular cryo-electron tomography (cryo-ET) has emerged as a key method to unravel the spatial and structural complexity of cells in their near-native state at unprecedented molecular resolution. To enable quantitative analysis of the complex shapes and morphologies of lipid membranes, the noisy three-dimensional (3D) volumes must be segmented. Despite recent advances, this task often requires considerable user intervention to curate the resulting segmentations. Here, we present ColabSeg, a Python-based tool for processing, visualizing, editing, and fitting membrane segmentations from cryo-ET data for downstream analysis. ColabSeg makes many well-established algorithms for point-cloud processing easily available to the broad community of structural biologists for applications in cryo-ET through its graphical user interface (GUI). We demonstrate the usefulness of the tool with a range of use cases and biological examples. Finally, for a large Mycoplasma pneumoniae dataset of 50 tomograms, we show how ColabSeg enables high-throughput membrane segmentation, which can be used as valuable training data for fully automated convolutional neural network (CNN)-based segmentation.

Sensing their plasma membrane curvature allows migrating cells to circumvent obstacles.

To navigate through diverse tissues, migrating cells must balance persistent self-propelled motion with adaptive behaviors to circumvent obstacles. We identify a curvature-sensing mechanism underlying obstacle evasion in immune-like cells. Specifically, we propose that actin polymerization at the advancing edge of migrating cells is inhibited by the curvature-sensitive BAR domain protein Snx33 in regions with inward plasma membrane curvature. The genetic perturbation of this machinery reduces the cells' capacity to evade obstructions combined with faster and more persistent cell migration in obstacle-free environments. Our results show how cells can read out their surface topography and utilize actin and plasma membrane biophysics to interpret their environment, allowing them to adaptively decide if they should move ahead or turn away. On the basis of our findings, we propose that the natural diversity of BAR domain proteins may allow cells to tune their curvature sensing machinery to match the shape characteristics in their environment.

Visualizing the disordered nuclear transport machinery in situ.

The approximately 120 MDa mammalian nuclear pore complex (NPC) acts as a gatekeeper for the transport between the nucleus and cytosol1. The central channel of the NPC is filled with hundreds of intrinsically disordered proteins (IDPs) called FG-nucleoporins (FG-NUPs)2,3. Although the structure of the NPC scaffold has been resolved in remarkable detail, the actual transport machinery built up by FG-NUPs-about 50 MDa-is depicted as an approximately 60-nm hole in even highly resolved tomograms and/or structures computed with artificial intelligence4-11. Here we directly probed conformations of the vital FG-NUP98 inside NPCs in live cells and in permeabilized cells with an intact transport machinery by using a synthetic biology-enabled site-specific small-molecule labelling approach paired with highly time-resolved fluorescence microscopy. Single permeabilized cell measurements of the distance distribution of FG-NUP98 segments combined with coarse-grained molecular simulations of the NPC allowed us to map the uncharted molecular environment inside the nanosized transport channel. We determined that the channel provides-in the terminology of the Flory polymer theory12-a 'good solvent' environment. This enables the FG domain to adopt expanded conformations and thus control transport between the nucleus and cytoplasm. With more than 30% of the proteome being formed from IDPs, our study opens a window into resolving disorder-function relationships of IDPs in situ, which are important in various processes, such as cellular signalling, phase separation, ageing and viral entry.

Variable microtubule architecture in the malaria parasite.

Microtubules are a ubiquitous eukaryotic cytoskeletal element typically consisting of 13 protofilaments arranged in a hollow cylinder. This arrangement is considered the canonical form and is adopted by most organisms, with rare exceptions. Here, we use in situ electron cryo-tomography and subvolume averaging to analyse the changing microtubule cytoskeleton of Plasmodium falciparum, the causative agent of malaria, throughout its life cycle. Unexpectedly, different parasite forms have distinct microtubule structures coordinated by unique organising centres. In merozoites, the most widely studied form, we observe canonical microtubules. In migrating mosquito forms, the 13 protofilament structure is further reinforced by interrupted luminal helices. Surprisingly, gametocytes contain a wide distribution of microtubule structures ranging from 13 to 18 protofilaments, doublets and triplets. Such a diversity of microtubule structures has not been observed in any other organism to date and is likely evidence of a distinct role in each life cycle form. This data provides a unique view into an unusual microtubule cytoskeleton of a relevant human pathogen.

TriMem: A parallelized hybrid Monte Carlo software for efficient simulations of lipid membranes.

Lipid membranes are integral building blocks of living cells and perform a multitude of biological functions. Currently, molecular simulations of cellular-scale membrane remodeling processes at atomic resolution are extremely difficult, due to their size, complexity, and the large times-scales on which these processes occur. Instead, elastic membrane models are used to simulate membrane shapes and transitions between them and to infer their properties and functions. Unfortunately, an efficiently parallelized open-source simulation code to do so has been lacking. Here, we present TriMem, a parallel hybrid Monte Carlo simulation engine for triangulated lipid membranes. The kernels are efficiently coded in C++ and wrapped with Python for ease-of-use. The parallel implementation of the energy and gradient calculations and of Monte Carlo flip moves of edges in the triangulated membrane enable us to simulate large and highly curved membrane structures. For validation, we reproduce phase diagrams of vesicles with varying surface-to-volume ratios and area difference. We also compute the density of states to verify correct Boltzmann sampling. The software can be used to tackle a range of large-scale membrane remodeling processes as a step toward cell-scale simulations. Additionally, extensive documentation make the software accessible to the broad biophysics and computational cell biology communities.

AI-based structure prediction empowers integrative structural analysis of human nuclear pores.

INTRODUCTION The eukaryotic nucleus pro-tects the genome and is enclosed by the two membranes of the nuclear envelope. Nuclear pore complexes (NPCs) perforate the nuclear envelope to facilitate nucleocytoplasmic transport. With a molecular weight of ∼120 MDa, the human NPC is one of the larg-est protein complexes. Its ~1000 proteins are taken in multiple copies from a set of about 30 distinct nucleoporins (NUPs). They can be roughly categorized into two classes. Scaf-fold NUPs contain folded domains and form a cylindrical scaffold architecture around a central channel. Intrinsically disordered NUPs line the scaffold and extend into the central channel, where they interact with cargo complexes. The NPC architecture is highly dynamic. It responds to changes in nuclear envelope tension with conforma-tional breathing that manifests in dilation and constriction movements. Elucidating the scaffold architecture, ultimately at atomic resolution, will be important for gaining a more precise understanding of NPC function and dynamics but imposes a substantial chal-lenge for structural biologists. RATIONALE Considerable progress has been made toward this goal by a joint effort in the field. A synergistic combination of complementary approaches has turned out to be critical. In situ structural biology techniques were used to reveal the overall layout of the NPC scaffold that defines the spatial reference for molecular modeling. High-resolution structures of many NUPs were determined in vitro. Proteomic analysis and extensive biochemical work unraveled the interaction network of NUPs. Integra-tive modeling has been used to combine the different types of data, resulting in a rough outline of the NPC scaffold. Previous struc-tural models of the human NPC, however, were patchy and limited in accuracy owing to several challenges: (i) Many of the high-resolution structures of individual NUPs have been solved from distantly related species and, consequently, do not comprehensively cover their human counterparts. (ii) The scaf-fold is interconnected by a set of intrinsically disordered linker NUPs that are not straight-forwardly accessible to common structural biology techniques. (iii) The NPC scaffold intimately embraces the fused inner and outer nuclear membranes in a distinctive topol-ogy and cannot be studied in isolation. (iv) The conformational dynamics of scaffold NUPs limits the resolution achievable in structure determination. RESULTS In this study, we used artificial intelligence (AI)-based prediction to generate an exten-sive repertoire of structural models of human NUPs and their subcomplexes. The resulting models cover various domains and interfaces that so far remained structurally uncharac-terized. Benchmarking against previous and unpublished x-ray and cryo-electron micros-copy structures revealed unprecedented accu-racy. We obtained well-resolved cryo-electron tomographic maps of both the constricted and dilated conformational states of the hu-man NPC. Using integrative modeling, we fit-ted the structural models of individual NUPs into the cryo-electron microscopy maps. We explicitly included several linker NUPs and traced their trajectory through the NPC scaf-fold. We elucidated in great detail how mem-brane-associated and transmembrane NUPs are distributed across the fusion topology of both nuclear membranes. The resulting architectural model increases the structural coverage of the human NPC scaffold by about twofold. We extensively validated our model against both earlier and new experimental data. The completeness of our model has enabled microsecond-long coarse-grained molecular dynamics simulations of the NPC scaffold within an explicit membrane en-vironment and solvent. These simulations reveal that the NPC scaffold prevents the constriction of the otherwise stable double-membrane fusion pore to small diameters in the absence of membrane tension. CONCLUSION Our 70-MDa atomically re-solved model covers >90% of the human NPC scaffold. It captures conforma-tional changes that occur during dilation and constriction. It also reveals the precise anchoring sites for intrinsically disordered NUPs, the identification of which is a prerequisite for a complete and dy-namic model of the NPC. Our study exempli-fies how AI-based structure prediction may accelerate the elucidation of subcellular ar-chitecture at atomic resolution. [Figure: see text].

Membrane fusion and drug delivery with carbon nanotube porins.

Drug delivery mitigates toxic side effects and poor pharmacokinetics of life-saving therapeutics and enhances treatment efficacy. However, direct cytoplasmic delivery of drugs and vaccines into cells has remained out of reach. We find that liposomes studded with 0.8-nm-wide carbon nanotube porins (CNTPs) function as efficient vehicles for direct cytoplasmic drug delivery by facilitating fusion of lipid membranes and complete mixing of the membrane material and vesicle interior content. Fusion kinetics data and coarse-grained molecular dynamics simulations reveal an unusual mechanism where CNTP dimers tether the vesicles, pull the membranes into proximity, and then fuse their outer and inner leaflets. Liposomes containing CNTPs in their membranes and loaded with an anticancer drug, doxorubicin, were effective in delivering the drug to cancer cells, killing up to 90% of them. Our results open an avenue for designing efficient drug delivery carriers compatible with a wide range of therapeutics.

FAM134B-RHD Protein Clustering Drives Spontaneous Budding of Asymmetric Membranes.

Living cells constantly remodel the shape of their lipid membranes. In the endoplasmic reticulum (ER), the reticulon homology domain (RHD) of the reticulophagy regulator 1 (RETR1/FAM134B) forms dense autophagic puncta that are associated with membrane removal by ER-phagy. In molecular dynamics (MD) simulations, we find that FAM134B-RHD spontaneously forms clusters, driven in part by curvature-mediated attractions. At a critical size, as in a nucleation process, the FAM134B-RHD clusters induce the formation of membrane buds. The kinetics of budding depends sensitively on protein concentration and bilayer asymmetry. Our MD simulations shed light on the role of FAM134B-RHD in ER-phagy and show that membrane asymmetry can be used to modulate the kinetic barrier for membrane remodeling.

MDBenchmark: A toolkit to optimize the performance of molecular dynamics simulations.

Despite the impending flattening of Moore's law, the system size, complexity, and length of molecular dynamics (MD) simulations keep on increasing, thanks to effective code parallelization and optimization combined with algorithmic developments. Going forward, exascale computing poses new challenges to the efficient execution and management of MD simulations. The diversity and rapid developments of hardware architectures, software environments, and MD engines make it necessary that users can easily run benchmarks to optimally set up simulations, both with respect to time-to-solution and overall efficiency. To this end, we have developed the software MDBenchmark to streamline the setup, submission, and analysis of simulation benchmarks and scaling studies. The software design is open and as such not restricted to any specific MD engine or job queuing system. To illustrate the necessity and benefits of running benchmarks and the capabilities of MDBenchmark, we measure the performance of a diverse set of 23 MD simulation systems using GROMACS 2018. We compare the scaling of simulations with the number of nodes for central processing unit (CPU)-only and mixed CPU-graphics processing unit (GPU) nodes and study the performance that can be achieved when running multiple simulations on a single node. In all these cases, we optimize the numbers of message passing interface (MPI) ranks and open multi-processing (OpenMP) threads, which is crucial to maximizing performance. Our results demonstrate the importance of benchmarking for finding the optimal system and hardware specific simulation parameters. Running MD simulations with optimized settings leads to a significant performance increase that reduces the monetary, energetic, and environmental costs of MD simulations.

Structural basis of ER-associated protein degradation mediated by the Hrd1 ubiquitin ligase complex.

Misfolded luminal endoplasmic reticulum (ER) proteins undergo ER-associated degradation (ERAD-L): They are retrotranslocated into the cytosol, polyubiquitinated, and degraded by the proteasome. ERAD-L is mediated by the Hrd1 complex (composed of Hrd1, Hrd3, Der1, Usa1, and Yos9), but the mechanism of retrotranslocation remains mysterious. Here, we report a structure of the active Hrd1 complex, as determined by cryo-electron microscopy analysis of two subcomplexes. Hrd3 and Yos9 jointly create a luminal binding site that recognizes glycosylated substrates. Hrd1 and the rhomboid-like Der1 protein form two "half-channels" with cytosolic and luminal cavities, respectively, and lateral gates facing one another in a thinned membrane region. These structures, along with crosslinking and molecular dynamics simulation results, suggest how a polypeptide loop of an ERAD-L substrate moves through the ER membrane.

Phospholipid Scramblases Remodel the Shape of Asymmetric Membranes.

The cell membrane and many organellar membranes are asymmetric and highly curved. In experiments, it is challenging to reconstitute and characterize membranes that differ in the lipid composition of their leaflets. Here we use molecular dynamics simulations to study the large-scale membrane shape changes associated with lipid shuttling between asymmetric leaflets. We exploit leaflet asymmetry to create a stable, near-spherical vesicle bud connected to a flat bilayer under periodic boundary conditions. Then we demonstrate how the lipid scramblase nhTMEM16 relaxes the lipid-number asymmetry. By mediating the flipping of lipids, this transmembrane protein dissipates the mechanochemical gradient between the leaflets and drives a large-scale membrane reorganization, converting the vesicle bud into a flat membrane. Our procedure to exploit bilayer asymmetry for simulations of highly curved membranes can be used to study the function of other lipid transporters and membrane-shaping proteins.

Dynamic cluster formation determines viscosity and diffusion in dense protein solutions.

We develop a detailed description of protein translational and rotational diffusion in concentrated solution on the basis of all-atom molecular dynamics simulations in explicit solvent. Our systems contain up to 540 fully flexible proteins with 3.6 million atoms. In concentrated protein solutions (100 mg/mL and higher), the proteins ubiquitin and lysozyme, as well as the protein domains third IgG-binding domain of protein G and villin headpiece, diffuse not as isolated particles, but as members of transient clusters between which they constantly exchange. A dynamic cluster model nearly quantitatively explains the increase in viscosity and the decrease in protein diffusivity with protein volume fraction, which both exceed the predictions from widely used colloid models. The Stokes-Einstein relations for translational and rotational diffusion remain valid, but the effective hydrodynamic radius grows linearly with protein volume fraction. This increase follows the observed increase in cluster size and explains the more dramatic slowdown of protein rotation compared with translation. Baxter's sticky-sphere model of colloidal suspensions captures the concentration dependence of cluster size, viscosity, and rotational and translational diffusion. The consistency between simulations and experiments for a diverse set of soluble globular proteins indicates that the cluster model applies broadly to concentrated protein solutions, with equilibrium dissociation constants for nonspecific protein-protein binding in the Kd ≈ 10-mM regime.

PyContact: Rapid, Customizable, and Visual Analysis of Noncovalent Interactions in MD Simulations.

Molecular dynamics (MD) simulations have become ubiquitous in all areas of life sciences. The size and model complexity of MD simulations are rapidly growing along with increasing computing power and improved algorithms. This growth has led to the production of a large amount of simulation data that need to be filtered for relevant information to address specific biomedical and biochemical questions. One of the most relevant molecular properties that can be investigated by all-atom MD simulations is the time-dependent evolution of the complex noncovalent interaction networks governing such fundamental aspects as molecular recognition, binding strength, and mechanical and structural stability. Extracting, evaluating, and visualizing noncovalent interactions is a key task in the daily work of structural biologists. We have developed PyContact, an easy-to-use, highly flexible, and intuitive graphical user interface-based application, designed to provide a toolkit to investigate biomolecular interactions in MD trajectories. PyContact is designed to facilitate this task by enabling identification of relevant noncovalent interactions in a comprehensible manner. The implementation of PyContact as a standalone application enables rapid analysis and data visualization without any additional programming requirements, and also preserves full in-program customization and extension capabilities for advanced users. The statistical analysis representation is interactively combined with full mapping of the results on the molecular system through the synergistic connection between PyContact and VMD. We showcase the capabilities and scientific significance of PyContact by analyzing and visualizing in great detail the noncovalent interactions underlying the ion permeation pathway of the human P2X3 receptor. As a second application, we examine the protein-protein interaction network of the mechanically ultrastable cohesin-dockering complex.

Tracking of Fluorescently Labeled Polymer Particles Reveals Surface Effects during Shear-Controlled Aggregation.

Surface chemistry is believed to be the key parameter affecting the aggregation and breakage of colloidal suspensions when subjected to shear. To date, only a few works dealt with the understanding of the role of the physical and chemical properties of the particles' surface upon aggregation under shear. Previous studies suggested that surface modifications strongly affect polymer particles' adhesion, but it was very challenging to demonstrate this effect and monitor these alterations upon prolonged exposure to shear forces. More importantly, the mechanisms leading to these changes remain elusive. In this work, shear-induced aggregation experiments of polymer colloidal particles have been devised with the specific objective of highlighting material transfer and clarifying the role of the softness of the particle's surface. To achieve this goal, polymer particles with a core-shell structure comprising fluorescent groups have been prepared so that the surface's softness could be tuned by the addition of monomer acting as a plasticizer and the percentage of fluorescent particles could be recorded over time via confocal microscopy to detect eventual material transfer among different particles. For the first time, material exchange occurring on the soft surface of core-shell polymer microparticles upon aggregation under shear was observed and proved. More aptly, starting from a 50% labeled/nonlabeled mixture, an increase in the percentage of particles showing a fluorescent signature was recorded over time, reaching a fraction of 70% after 5 h.

Antimalarial Inhibitors Targeting Serine Hydroxymethyltransferase (SHMT) with in Vivo Efficacy and Analysis of their Binding Mode Based on X-ray Cocrystal Structures.

Target-based approaches toward new antimalarial treatments are highly valuable to prevent resistance development. We report several series of pyrazolopyran-based inhibitors targeting the enzyme serine hydroxymethyltransferase (SHMT), designed to improve microsomal metabolic stability and to identify suitable candidates for in vivo efficacy evaluation. The best ligands inhibited Plasmodium falciparum (Pf) and Arabidopsis thaliana (At) SHMT in target assays and PfNF54 strains in cell-based assays with values in the low nanomolar range (3.2-55 nM). A set of carboxylate derivatives demonstrated markedly improved in vitro metabolic stability (t1/2 > 2 h). A selected ligand showed significant in vivo efficacy with 73% of parasitemia reduction in a mouse model. Five new cocrystal structures with PvSHMT were solved at 2.3-2.6 Å resolution, revealing a unique water-mediated interaction with Tyr63 at the end of the para-aminobenzoate channel. They also displayed the high degree of conformational flexibility of the Cys364-loop lining this channel.