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This data includes XL/MS and structural models for the Tetrahymena motile cilia interactome.

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.

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 and identified 1,225 intramolecular cross-links within the 100 best-sampled proteins to provide a benchmark of distance restraints obeyed by proteins in their native assemblies. The corresponding AlphaFold2 structure predictions were highly concordant, positioning 86.2% of cross-linked residues within Cα-to-Cα distances of 30 Å, consistent with the known cross-linker length. 43% of the proteins showed no violations. Most inconsistencies occurred in low-confidence regions or between domains of the structure prediction. For basal body protein BBC118, cross-links combined with the predicted structure revealed domain packing satisfying both data. Overall, AlphaFold2 predicted biological structures with low predicted aligned error corresponded to more correct native structures. However, we observe cases where rigid body domains are oriented incorrectly, suggesting that combining structure prediction with experimental information will better reveal biologically relevant conformations.

Advances in protein structure prediction have taken the biology community by storm with their promise of readily available, high-quality, atomic-level structural information. Because a major goal in structural biology is to understand proteins in their native biological contexts, we asked if AlphaFold2 predictions match native protein conformations. To answer this question, we chemically cross-linked proteins within intact Tetrahymena thermophila cilia and fractions enriched for endogenous protein complexes and identified cross-linked amino acids by mass spectrometry. Across the 100 best-sampled proteins, we measured 1,228 intramolecular cross-links, which serve as a benchmark of distance restraints to be obeyed by endogenous proteins. The corresponding AlphaFold2 structure predictions were highly concordant, positioning 86.0% of cross-linked lysine residues within 30 Å of each other (Cɑ-to-Cɑ), consistent with the known size of the cross-linker, and 92.2% within 40 Å of each other. A large fraction (43%) of the proteins showed no violations at all. Meanwhile, most inconsistencies occurred in low-confidence regions or not within confidently predicted rigid domains. For basal body EF-hand protein BBC118, the cross-links could be combined with the predicted structure to find domain packing satisfying both sets of data. Overall, AlphaFold2 performs well at predicting biologically relevant protein structures, with high confidence values corresponding to more correct native structures. However, we observe cases involving incorrect relative orientations of rigid domains, signifying the importance of combining structure prediction with experimental information to reveal biologically relevant structural conformations.

CRISPR (Clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated) systems are a type of adaptive immune response in bacteria and archaea that utilize crRNA (CRISPR RNA)-guided effector complexes to target complementary RNA or DNA for destruction. The prototypical type III-A and III-B CRISPR-Cas systems utilize multi-subunit effector complexes composed of individual proteins to cleave ssRNA targets at 6-nt intervals, as well as non-specifically degrading ssDNA and activating cyclic oligoadenylate (cOA) synthesis. Recent studies have shown that type III systems can contain subunit fusions yet maintain canonical type III RNA-targeting capabilities. To understand how a multi-subunit fusion effector functions, we determine structures of a variant type III-D effector and biochemically characterize how it cleaves RNA targets. These findings provide insights into how multi-subunit fusion proteins are tethered together and assemble into an active and programmable RNA endonuclease, how the effector utilizes a novel mechanism for target RNA seeding, and the structural basis for the evolution of type III effector complexes. Furthermore, our results provide a blueprint for fusing subunits in class 1 effectors for design of user-defined effector complexes with disparate activities.Important noteWhile this manuscript was in preparation, a manuscript describing the structure of the type III-E effector was published1. We reference these important findings; however, a careful comparison of the structures will follow once the coordinates have been released by the PDB.

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 (IMP) in order to build three-dimensional models of atomic structures into EM maps ranging from 10-14 a 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. This article is protected by copyright. All rights reserved.

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.

SUMMARYRed 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 defined 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 validated protein complexes through electron microscopy and chemical crosslinking, and with these data, built 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-link 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.

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 (IMP) 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.

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 cuboid transformation of 3D protein accessible surfaces on which molecular properties such as charge, hydrophobicity, and mutation 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 85 overall known protein complexes, we observed F1 scores (a weighted combination of precision and recall) of 19-34% at correctly identifying protein interaction surfaces, comparable to more computationally intensive 3D docking methods in the annual Critical Assessment of PRedicted Interactions. 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 RMSD. Thus, a cuboid transformation 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.

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.

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. Machine-accessible metadata file describing the reported data (ISA-Tab format)

Synthetic dispersants such as Corexit 9500A were used in large quantities (∼2 million gallons) to disperse the oil spilled in the ocean during the recent Deepwater Horizon event. These dispersant formulations contain a blend of surfactants in a base of organic solvent. Some concerns have been raised regarding the aquatic toxicity and environmental impact of these formulations. In an effort to create a safer dispersant, we have examined the ability of food-grade amphiphiles to disperse (emulsify) crude oil in seawater. Our studies show that an effective emulsifier is obtained by combining two such amphiphiles: lecithin (L), a phospholipid extracted from soybeans, and Tween 80 (T), a surfactant used in many food products including ice cream. Interestingly, we find that L/T blends show a synergistic effect, i.e., their combination is an effective emulsifier, but neither L or T is effective on its own. This synergy is maximized at a 60/40 weight ratio of L/T and is attributed to the following reasons: (i) L and T pack closely at the oil-water interface; (ii) L has a low tendency to desorb, which fortifies the interfacial film; and (iii) the large headgroup of T provides steric repulsions between the oil droplets and prevents their coalescence. A comparison of L/T with Corexit 9500A shows that the former leads to smaller oil droplets that remain stable to coalescence for a much longer time. The smaller size and stability of crude oil droplets are believed to be important to their dispersion and eventual microbial degradation in the ocean. Our findings suggest that L/T blends could potentially be a viable alternative for the dispersion of oil spills.