RNA targeting and cleavage by the type III-Dv CRISPR effector complex.

CRISPR-Cas are adaptive immune systems in bacteria and archaea that utilize CRISPR RNA-guided surveillance complexes to target complementary RNA or DNA for destruction1-5. Target RNA cleavage at regular intervals is characteristic of type III effector complexes6-8. Here, we determine the structures of the Synechocystis type III-Dv complex, an apparent evolutionary intermediate from multi-protein to single-protein type III effectors9,10, in pre- and post-cleavage states. The structures show how multi-subunit fusion proteins in the effector are tethered together in an unusual arrangement to assemble into an active and programmable RNA endonuclease and how the effector utilizes a distinct mechanism for target RNA seeding from other type III effectors. Using structural, biochemical, and quantum/classical molecular dynamics simulation, we study the structure and dynamics of the three catalytic sites, where a 2'-OH of the ribose on the target RNA acts as a nucleophile for in line self-cleavage of the upstream scissile phosphate. Strikingly, the arrangement at the catalytic residues of most type III complexes resembles the active site of ribozymes, including the hammerhead, pistol, and Varkud satellite ribozymes. Our work provides detailed molecular insight into the mechanisms of RNA targeting and cleavage by an important intermediate in the evolution of type III effector complexes.

Integrating cellular electron microscopy with multimodal data to explore biology across space and time.

Biology spans a continuum of length and time scales. Individual experimental methods only glimpse discrete pieces of this spectrum but can be combined to construct a more holistic view. In this Review, we detail the latest advancements in volume electron microscopy (vEM) and cryo-electron tomography (cryo-ET), which together can visualize biological complexity across scales from the organization of cells in large tissues to the molecular details inside native cellular environments. In addition, we discuss emerging methodologies for integrating three-dimensional electron microscopy (3DEM) imaging with multimodal data, including fluorescence microscopy, mass spectrometry, single-particle analysis, and AI-based structure prediction. This multifaceted approach fills gaps in the biological continuum, providing functional context, spatial organization, molecular identity, and native interactions. We conclude with a perspective on incorporating diverse data into computational simulations that further bridge and extend length scales while integrating the dimension of time.

An amino acid-resolution interactome for motile cilia illuminates the structure and function of ciliopathy protein complexes.

Motile cilia are ancient, evolutionarily conserved organelles whose dysfunction underlies motile ciliopathies, a broad class of human diseases. Motile cilia contain myriad different proteins that assemble into an array of distinct machines, so understanding the interactions and functional hierarchies among them presents an important challenge. Here, we defined the protein interactome of motile axonemes using cross-linking mass spectrometry (XL/MS) in Tetrahymena thermophila. From over 19,000 XLs, we identified 4,757 unique amino acid interactions among 1,143 distinct proteins, providing both macromolecular and atomic-scale insights into diverse ciliary machines, including the Intraflagellar Transport system, axonemal dynein arms, radial spokes, the 96 nm ruler, and microtubule inner proteins, among others. Guided by this dataset, we used vertebrate multiciliated cells to reveal novel functional interactions among several poorly-defined human ciliopathy proteins. The dataset therefore provides a powerful resource for studying the basic biology of an ancient organelle and the molecular etiology of human genetic disease.

Integrated modeling of the Nexin-dynein regulatory complex reveals its regulatory mechanism.

Cilia are hairlike protrusions that project from the surface of eukaryotic cells and play key roles in cell signaling and motility. Ciliary motility is regulated by the conserved nexin-dynein regulatory complex (N-DRC), which links adjacent doublet microtubules and regulates and coordinates the activity of outer doublet complexes. Despite its critical role in cilia motility, the assembly and molecular basis of the regulatory mechanism are poorly understood. Here, using cryo-electron microscopy in conjunction with biochemical cross-linking and integrative modeling, we localize 12 DRC subunits in the N-DRC structure of Tetrahymena thermophila. We also find that the CCDC96/113 complex is in close contact with the DRC9/10 in the linker region. In addition, we reveal that the N-DRC is associated with a network of coiled-coil proteins that most likely mediates N-DRC regulatory activity.

Type III CRISPR-Cas complexes act as protein-assisted ribozymes during target RNA cleavage.

CRISPR-Cas systems are an adaptive immune system in bacteria and archaea that utilize CRISPR RNA-guided surveillance complexes to target complementary RNA or DNA for destruction1-5. Target RNA cleavage at regular intervals is characteristic of type III effector complexes; however, the mechanism has remained enigmatic6,7. Here, we determine the structures of the Synechocystis type III-Dv complex, an evolutionary intermediate in type III effectors8,9, in pre- and post-cleavage states, which show metal ion coordination in the active sites. Using structural, biochemical, and quantum/classical molecular dynamics simulation, we reveal the structure and dynamics of the three catalytic sites, where a 2'-OH of the ribose on the target RNA acts as a nucleophile for in line self-cleavage of the upstream scissile phosphate. Strikingly, the arrangement at the catalytic residues of most type III complexes resembles the active site of ribozymes, including the hammerhead, pistol, and Varkud satellite ribozymes. Thus, type III CRISPR-Cas complexes function as protein-assisted ribozymes, and their programmable nature has important implications for how these complexes could be repurposed for applications.

Native doublet microtubules from Tetrahymena thermophila reveal the importance of outer junction proteins.

Cilia are ubiquitous eukaryotic organelles responsible for cellular motility and sensory functions. The ciliary axoneme is a microtubule-based cytoskeleton consisting of two central singlets and nine outer doublet microtubules. Cryo-electron microscopy-based studies have revealed a complex network inside the lumen of both tubules composed of microtubule-inner proteins (MIPs). However, the functions of most MIPs remain unknown. Here, we present single-particle cryo-EM-based analyses of the Tetrahymena thermophila native doublet microtubule and identify 42 MIPs. These data shed light on the evolutionarily conserved and diversified roles of MIPs. In addition, we identified MIPs potentially responsible for the assembly and stability of the doublet outer junction. Knockout of the evolutionarily conserved outer junction component CFAP77 moderately diminishes Tetrahymena swimming speed and beat frequency, indicating the important role of CFAP77 and outer junction stability in cilia beating generation and/or regulation.

Does AlphaFold2 model proteins' intracellular conformations? An experimental test using cross-linking mass spectrometry of endogenous ciliary proteins.

A major goal in structural biology is to understand protein assemblies in their biologically relevant states. Here, we investigate whether AlphaFold2 structure predictions match native protein conformations. We chemically cross-linked proteins in situ within intact Tetrahymena thermophila cilia and native ciliary extracts, identifying 1,225 intramolecular cross-links within the 100 best-sampled proteins, providing a benchmark of distance restraints obeyed by proteins in their native assemblies. The corresponding structure predictions were highly concordant, positioning 86.2% of cross-linked residues within Cɑ-to-Cɑ distances of 30 Å, consistent with the cross-linker length. 43% of proteins showed no violations. Most inconsistencies occurred in low-confidence regions or between domains. Overall, AlphaFold2 predictions with lower predicted aligned error corresponded to more correct native structures. However, we observe cases where rigid body domains are oriented incorrectly, as for ciliary protein BBC118, suggesting that combining structure prediction with experimental information will better reveal biologically relevant conformations.

Integrative modeling reveals the molecular architecture of the intraflagellar transport A (IFT-A) complex.

Intraflagellar transport (IFT) is a conserved process of cargo transport in cilia that is essential for development and homeostasis in organisms ranging from algae to vertebrates. In humans, variants in genes encoding subunits of the cargo-adapting IFT-A and IFT-B protein complexes are a common cause of genetic diseases known as ciliopathies. While recent progress has been made in determining the atomic structure of IFT-B, little is known of the structural biology of IFT-A. Here, we combined chemical cross-linking mass spectrometry and cryo-electron tomography with AlphaFold2-based prediction of both protein structures and interaction interfaces to model the overall architecture of the monomeric six-subunit IFT-A complex, as well as its polymeric assembly within cilia. We define monomer-monomer contacts and membrane-associated regions available for association with transported cargo, and we also use this model to provide insights into the pleiotropic nature of human ciliopathy-associated genetic variants in genes encoding IFT-A subunits. Our work demonstrates the power of integration of experimental and computational strategies both for multi-protein structure determination and for understanding the etiology of human genetic disease.

The protein organization of a red blood cell.

Red blood cells (RBCs) (erythrocytes) are the simplest primary human cells, lacking nuclei and major organelles and instead employing about a thousand proteins to dynamically control cellular function and morphology in response to physiological cues. In this study, we define a canonical RBC proteome and interactome using quantitative mass spectrometry and machine learning. Our data reveal an RBC interactome dominated by protein homeostasis, redox biology, cytoskeletal dynamics, and carbon metabolism. We validate protein complexes through electron microscopy and chemical crosslinking and, with these data, build 3D structural models of the ankyrin/Band 3/Band 4.2 complex that bridges the spectrin cytoskeleton to the RBC membrane. The model suggests spring-like compression of ankyrin may contribute to the characteristic RBC cell shape and flexibility. Taken together, our study provides an in-depth view of the global protein organization of human RBCs and serves as a comprehensive resource for future research.

Improving integrative 3D modeling into low- to medium-resolution electron microscopy structures with evolutionary couplings.

Electron microscopy (EM) continues to provide near-atomic resolution structures for well-behaved proteins and protein complexes. Unfortunately, structures of some complexes are limited to low- to medium-resolution due to biochemical or conformational heterogeneity. Thus, the application of unbiased systematic methods for fitting individual structures into EM maps is important. A method that employs co-evolutionary information obtained solely from sequence data could prove invaluable for quick, confident localization of subunits within these structures. Here, we incorporate the co-evolution of intermolecular amino acids as a new type of distance restraint in the integrative modeling platform in order to build three-dimensional models of atomic structures into EM maps ranging from 10-14 Å in resolution. We validate this method using four complexes of known structure, where we highlight the conservation of intermolecular couplings despite dynamic conformational changes using the BAM complex. Finally, we use this method to assemble the subunits of the bacterial holo-translocon into a model that agrees with previous biochemical data. The use of evolutionary couplings in integrative modeling improves systematic, unbiased fitting of atomic models into medium- to low-resolution EM maps, providing additional information to integrative models lacking in spatial data.

Simplified geometric representations of protein structures identify complementary interaction interfaces.

Protein-protein interactions are critical to protein function, but three-dimensional (3D) arrangements of interacting proteins have proven hard to predict, even given the identities and 3D structures of the interacting partners. Specifically, identifying the relevant pairwise interaction surfaces remains difficult, often relying on shape complementarity with molecular docking while accounting for molecular motions to optimize rigid 3D translations and rotations. However, such approaches can be computationally expensive, and faster, less accurate approximations may prove useful for large-scale prediction and assembly of 3D structures of multi-protein complexes. We asked if a reduced representation of protein geometry retains enough information about molecular properties to predict pairwise protein interaction interfaces that are tolerant of limited structural rearrangements. Here, we describe a reduced representation of 3D protein accessible surfaces on which molecular properties such as charge, hydrophobicity, and evolutionary rate can be easily mapped, implemented in the MorphProt package. Pairs of surfaces are compared to rapidly assess partner-specific potential surface complementarity. On two available benchmarks of 185 overall known protein complexes, we observe predictions comparable to other structure-based tools at correctly identifying protein interaction surfaces. Furthermore, we examined the effect of molecular motion through normal mode simulation on a benchmark receptor-ligand pair and observed no marked loss of predictive accuracy for distortions of up to 6 Å Cα-RMSD. Thus, a shape reduction of protein surfaces retains considerable information about surface complementarity, offers enhanced speed of comparison relative to more complex geometric representations, and exhibits tolerance to conformational changes.

Structural Biology in the Multi-Omics Era.

Rapid developments in cryogenic electron microscopy have opened new avenues to probe the structures of protein assemblies in their near native states. Recent studies have begun applying single -particle analysis to heterogeneous mixtures, revealing the potential of structural-omics approaches that combine the power of mass spectrometry and electron microscopy. Here we highlight advances and challenges in sample preparation, data processing, and molecular modeling for handling increasingly complex mixtures. Such advances will help structural-omics methods extend to cellular-level models of structural biology.

Correction: Global computational mutagenesis provides a critical stability framework in protein structures.

[This corrects the article DOI: 10.1371/journal.pone.0189064.].

Global computational mutagenesis provides a critical stability framework in protein structures.

A protein's amino acid sequence dictates the folds and final structure the macromolecule will form. We propose that by identifying critical residues in a protein's atomic structure, we can select a critical stability framework within the protein structure essential to proper protein folding. We use global computational mutagenesis based on the unfolding mutation screen to test the effect of every possible missense mutation on the protein structure to identify the residues that cannot tolerate a substitution without causing protein misfolding. This method was tested using molecular dynamics to simulate the stability effects of mutating critical residues in proteins involved in inherited disease, such as myoglobin, p53, and the 15th sushi domain of complement factor H. In addition we prove that when the critical residues are in place, other residues may be changed within the structure without a stability loss. We validate that critical residues are conserved using myoglobin to show that critical residues are the same for crystal structures of 6 different species and comparing conservation indices to critical residues in 9 eye disease-related proteins. Our studies demonstrate that by using a selection of critical elements in a protein structure we can identify a critical protein stability framework. The frame of critical residues can be used in genetic engineering to improve small molecule binding for drug studies, identify loss-of-function disease-causing missense mutations in genetics studies, and aide in identifying templates for homology modeling.

Dataset of eye disease-related proteins analyzed using the unfolding mutation screen.

A number of genetic diseases are a result of missense mutations in protein structure. These mutations can lead to severe protein destabilization and misfolding. The unfolding mutation screen (UMS) is a computational method that calculates unfolding propensities for every possible missense mutation in a protein structure. The UMS validation demonstrated a good agreement with experimental and phenotypical data. 15 protein structures (a combination of homology models and crystal structures) were analyzed using UMS. The standard and clustered heat maps, and patterned protein structure from the analysis were stored in a UMS library. The library is currently composed of 15 protein structures from 14 inherited eye diseases including retina degenerations, glaucoma, and cataracts, and contains data for 181,110 mutations. The UMS protein library introduces 13 new human models of eye disease related proteins and is the first collection of the consistently calculated unfolding propensities, which could be used as a tool for the express analysis of novel mutations in clinical practice, next generation sequencing, and genotype-to-phenotype relationships in inherited eye disease.

In silico Mapping of Protein Unfolding Mutations for Inherited Disease.

The effect of disease-causing missense mutations on protein folding is difficult to evaluate. To understand this relationship, we developed the unfolding mutation screen (UMS) for in silico evaluation of the severity of genetic perturbations at the atomic level of protein structure. The program takes into account the protein-unfolding curve and generates propensities using calculated free energy changes for every possible missense mutation at once. These results are presented in a series of unfolding heat maps and a colored protein 3D structure to show the residues critical to the protein folding and are available for quick reference. UMS was tested with 16 crystal structures to evaluate the unfolding for 1391 mutations from the ProTherm database. Our results showed that the computational accuracy of the unfolding calculations was similar to the accuracy of previously published free energy changes but provided a better scale. Our residue identity control helps to improve protein homology models. The unfolding predictions for proteins involved in age-related macular degeneration, retinitis pigmentosa, and Leber's congenital amaurosis matched well with data from previous studies. These results suggest that UMS could be a useful tool in the analysis of genotype-to-phenotype associations and next-generation sequencing data for inherited diseases.