DeepTracer-ID: De novo protein identification from cryo-EM maps

Structural diversity of axonemes across mammalian motile cilia

Reproduction, development and homeostasis depend on motile cilia, whose rhythmic beating is powered by a microtubule-based molecular machine called the axoneme. Although an atomic model of the axoneme is available for the alga Chlamydomonas reinhardtii1, structures of mammalian axonemes are incomplete1-5. Furthermore, we do not fully understand how molecular structures of axonemes vary across motile-ciliated cell types in the body. Here we use cryoelectron microscopy, cryoelectron tomography and proteomics to resolve the 96-nm modular repeat of axonemal doublet microtubules (DMTs) from both sperm flagella and epithelial cilia of the oviduct, brain ventricles and respiratory tract. We find that sperm DMTs are the most specialized, with epithelial cilia having only minor differences across tissues. We build a model of the mammalian sperm DMT, defining the positions and interactions of 181 proteins including 34 newly identified proteins. We elucidate the composition of radial spoke 3 and uncover binding sites of kinases associated with regeneration of ATP and regulation of ciliary motility. We discover a sperm-specific, axoneme-tethered T-complex protein ring complex (TRiC) chaperone that may contribute to construction or maintenance of the long flagella of mammalian sperm. We resolve axonemal dyneins in their prestroke states, illuminating conformational changes that occur during ciliary movement. Our results illustrate how elements of chemical and mechanical regulation are embedded within the axoneme, providing valuable resources for understanding the aetiology of ciliopathy and infertility, and exemplifying the discovery power of modern structural biology.

Cryo-EM-based discovery of a pathogenic parvovirus causing epidemic mortality by black wasting disease in farmed beetles

We use cryoelectron microscopy (cryo-EM) as a sequence- and culture-independent diagnostic tool to identify the etiological agent of an agricultural pandemic. For the past 4 years, American insect-rearing facilities have experienced a distinctive larval pathology and colony collapse of farmed Zophobas morio (superworm). By means of cryo-EM, we discovered the causative agent: a densovirus that we named Zophobas morio black wasting virus (ZmBWV). We confirmed the etiology of disease by fulfilling Koch's postulates and characterizing strains from across the United States. ZmBWV is a member of the family Parvoviridae with a 5,542 nt genome, and we describe intersubunit interactions explaining its expanded internal volume relative to human parvoviruses. Cryo-EM structures at resolutions up to 2.1 Å revealed single-strand DNA (ssDNA) ordering at the capsid inner surface pinned by base-binding pockets in the capsid inner surface. Also, we demonstrated the prophylactic potential of non-pathogenic strains to provide cross-protection in vivo.

Structural biology in cellulo: Minding the gap between conceptualization and realization

Recent technological advances have deepened our perception of cellular structure. However, most structural data doesn't originate from intact cells, limiting our understanding of cellular processes. Here, we discuss current and future developments that will bring us towards a structural picture of the cell. Electron cryotomography is the standard bearer, with its ability to provide in cellulo snapshots. Single-particle electron microscopy (of purified biomolecules and of complex mixtures) and covalent crosslinking combined with mass spectrometry also have significant roles to play, as do artificial intelligence algorithms in their many guises. To integrate these multiple approaches, data curation and standardisation will be critical - as is the need to expand efforts beyond our current protein-centric view to the other (macro)molecules that sustain life.

Two distinct archaeal type IV pili structures formed by proteins with identical sequence

Type IV pili (T4P) represent one of the most common varieties of surface appendages in archaea. These filaments, assembled from small pilin proteins, can be many microns long and serve diverse functions, including adhesion, biofilm formation, motility, and intercellular communication. Here, we determine atomic structures of two distinct adhesive T4P from Saccharolobus islandicus via cryo-electron microscopy (cryo-EM). Unexpectedly, both pili were assembled from the same pilin polypeptide but under different growth conditions. One filament, denoted mono-pilus, conforms to canonical archaeal T4P structures where all subunits are equivalent, whereas in the other filament, the tri-pilus, the same polypeptide exists in three different conformations. The three conformations in the tri-pilus are very different from the single conformation found in the mono-pilus, and involve different orientations of the outer immunoglobulin-like domains, mediated by a very flexible linker. Remarkably, the outer domains rotate nearly 180° between the mono- and tri-pilus conformations. Both forms of pili require the same ATPase and TadC-like membrane pore for assembly, indicating that the same secretion system can produce structurally very different filaments. Our results show that the structures of archaeal T4P appear to be less constrained and rigid than those of the homologous archaeal flagellar filaments that serve as helical propellers.

Structural determination and modeling of ciliary microtubules

The axoneme, a microtubule-based array at the center of every cilium, has been the subject of structural investigations for decades, but only recent advances in cryo-EM and cryo-ET have allowed a molecular-level interpretation of the entire complex to be achieved. The unique properties of the nine doublet microtubules and central pair of singlet microtubules that form the axoneme, including the highly decorated tubulin lattice and the docking of massive axonemal complexes, provide opportunities and challenges for sample preparation, 3D reconstruction and atomic modeling. Here, the approaches used for cryo-EM and cryo-ET of axonemes are reviewed, while highlighting the unique opportunities provided by the latest generation of AI-guided tools that are transforming structural biology.

Automated model building and protein identification in cryo-EM maps

Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs1,2. Here we present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality to those generated by human experts. For nucleotides, ModelAngelo builds backbones with similar accuracy to those built by humans. By using its predicted amino acid probabilities for each residue in hidden Markov model sequence searches, ModelAngelo outperforms human experts in the identification of proteins with unknown sequences. ModelAngelo will therefore remove bottlenecks and increase objectivity in cryo-EM structure determination.

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 extensive disulfide bond network prevents tail contraction in Agrobacterium tumefaciens phage Milano

A contractile sheath and rigid tube assembly is a widespread apparatus used by bacteriophages, tailocins, and the bacterial type VI secretion system to penetrate cell membranes. In this mechanism, contraction of an external sheath powers the motion of an inner tube through the membrane. The structure, energetics, and mechanism of the machinery imply rigidity and straightness. The contractile tail of Agrobacterium tumefaciens bacteriophage Milano is flexible and bent to varying degrees, which sets it apart from other contractile tail-like systems. Here, we report structures of the Milano tail including the sheath-tube complex, baseplate, and putative receptor-binding proteins. The flexible-to-rigid transformation of the Milano tail upon contraction can be explained by unique electrostatic properties of the tail tube and sheath. All components of the Milano tail, including sheath subunits, are crosslinked by disulfides, some of which must be reduced for contraction to occur. The putative receptor-binding complex of Milano contains a tailspike, a tail fiber, and at least two small proteins that form a garland around the distal ends of the tailspikes and tail fibers. Despite being flagellotropic, Milano lacks thread-like tail filaments that can wrap around the flagellum, and is thus likely to employ a different binding mechanism.

Cryo-EM of a heterogeneous biochemical fraction elucidates multiple protein complexes from a multicellular thermophilic eukaryote

Biomolecular complexes and their interactions govern cellular structure and function. Understanding their architecture is a prerequisite for dissecting the cell's inner workings, but their higher-order assembly is often transient and challenging for structural analysis. Here, we performed cryo-EM on a single, highly heterogeneous biochemical fraction derived from Chaetomium thermophilum cell extracts to visualize the biomolecular content of the multicellular eukaryote. After cryo-EM single-particle image processing, results showed that a simultaneous three-dimensional structural characterization of multiple chemically diverse biomacromolecules is feasible. Namely, the thermophilic, eukaryotic complexes of (a) ATP citrate-lyase, (b) Hsp90, (c) 20S proteasome, (d) Hsp60 and (e) UDP-glucose pyrophosphorylase were characterized. In total, all five complexes have been structurally dissected in a thermophilic eukaryote in a total imaged sample area of 190.64 μm2, and two, in particular, 20S proteasome and Hsp60, exhibit side-chain resolution features. The C. thermophilum Hsp60 near-atomic model was resolved at 3.46 Å (FSC = 0.143) and shows a hinge-like conformational change of its equatorial domain, highly similar to the one previously shown for its bacterial orthologue, GroEL. This work demonstrates that cryo-EM of cell extracts will greatly accelerate the structural analysis of cellular complexes and provide unprecedented opportunities to annotate architectures of biomolecules in a holistic approach.

Automated model building and protein identification in cryo-EM maps

Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention. We present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality as those generated by human experts. For nucleotides, ModelAngelo builds backbones with similar accuracy as humans. By using its predicted amino acid probabilities for each residue in hidden Markov model sequence searches, ModelAngelo outperforms human experts in the identification of proteins with unknown sequences. ModelAngelo will thus remove bottlenecks and increase objectivity in cryo-EM structure determination.

Neck and capsid architecture of the robust Agrobacterium phage Milano

Large gaps exist in our understanding of how bacteriophages, the most abundant biological entities on Earth, assemble and function. The structure of the "neck" region, where the DNA-filled capsid is connected to the host-recognizing tail remains poorly understood. We describe cryo-EM structures of the neck, the neck-capsid and neck-tail junctions, and capsid of the Agrobacterium phage Milano. The Milano neck 1 protein connects the 12-fold symmetrical neck to a 5-fold vertex of the icosahedral capsid. Comparison of Milano neck 1 homologs leads to four proposed classes, likely evolved from the simplest one in siphophages to more complex ones in myo- and podophages. Milano neck is surrounded by the atypical collar, which covalently crosslinks the tail sheath to neck 1. The Milano capsid is decorated with three types of proteins, a minor capsid protein (mCP) and two linking proteins crosslinking the mCP to the major capsid protein. The extensive network of disulfide bonds within and between neck, collar, capsid and tail provides an exceptional structural stability to Milano.

Novel Artificial Intelligence-Based Approaches for Ab Initio Structure Determination and Atomic Model Building for Cryo-Electron Microscopy

Single particle cryo-electron microscopy (cryo-EM) has emerged as the prevailing method for near-atomic structure determination, shedding light on the important molecular mechanisms of biological macromolecules. However, the inherent dynamics and structural variability of biological complexes coupled with the large number of experimental images generated by a cryo-EM experiment make data processing nontrivial. In particular, ab initio reconstruction and atomic model building remain major bottlenecks that demand substantial computational resources and manual intervention. Approaches utilizing recent innovations in artificial intelligence (AI) technology, particularly deep learning, have the potential to overcome the limitations that cannot be adequately addressed by traditional image processing approaches. Here, we review newly proposed AI-based methods for ab initio volume generation, heterogeneous 3D reconstruction, and atomic model building. We highlight the advancements made by the implementation of AI methods, as well as discuss remaining limitations and areas for future development.

Two dramatically distinct archaeal type IV pili structures formed by the same pilin

Type IV pili (T4P) represent one of the most common varieties of surface appendages in archaea. These filaments, assembled from relatively small pilin proteins, can be many microns long and serve diverse functions, including adhesion, biofilm formation, motility, and intercellular communication. Using cryo-electron microscopy (cryo-EM), we determined atomic structures of two dramatically different T4P from Saccharolobus islandicus REY15A. Unexpectedly, both pili were assembled from the same pilin protein but under different growth conditions. One filament, denoted mono-pilus, conforms to canonical archaeal T4P structures where all subunits are equivalent, whereas in the other filament, the tri-pilus, the same protein exists in three different conformations. The three conformations involve different orientations of the outer immunoglobulin (Ig)-like domains, mediated by a very flexible linker, and all three of these conformations are very different from the single conformation found in the mono-pilus. Remarkably, the outer domains rotate nearly 180° between the mono- and tri-pilus conformations, formally similar to what has been shown for outer domains in bacterial flagellar filaments, despite lack of homology between bacterial flagella and archaeal T4P. Interestingly, both forms of pili require the same ATPase and TadC-like membrane pore for assembly, indicating that the same secretion system can produce structurally very different filaments. However, the expression of the ATPase and TadC genes was significantly different under the conditions yielding mono- and tri-pili. While archaeal T4P are homologs of archaeal flagellar filaments, our results show that in contrast to the rigid supercoil that the flagellar filaments must adopt to serve as helical propellers, archaeal T4P are likely to have fewer constraints on their structure and enjoy more internal degrees of freedom.

The evolution of archaeal flagellar filaments

Flagellar motility has independently arisen three times during evolution: in bacteria, archaea, and eukaryotes. In prokaryotes, the supercoiled flagellar filaments are composed largely of a single protein, bacterial or archaeal flagellin, although these two proteins are not homologous, while in eukaryotes, the flagellum contains hundreds of proteins. Archaeal flagellin and archaeal type IV pilin are homologous, but how archaeal flagellar filaments (AFFs) and archaeal type IV pili (AT4Ps) diverged is not understood, in part, due to the paucity of structures for AFFs and AT4Ps. Despite having similar structures, AFFs supercoil, while AT4Ps do not, and supercoiling is essential for the function of AFFs. We used cryo-electron microscopy to determine the atomic structure of two additional AT4Ps and reanalyzed previous structures. We find that all AFFs have a prominent 10-strand packing, while AT4Ps show a striking structural diversity in their subunit packing. A clear distinction between all AFF and all AT4P structures involves the extension of the N-terminal α-helix with polar residues in the AFFs. Additionally, we characterize a flagellar-like AT4P from Pyrobaculum calidifontis with filament and subunit structure similar to that of AFFs which can be viewed as an evolutionary link, showing how the structural diversity of AT4Ps likely allowed for an AT4P to evolve into a supercoiling AFF.

Structural specializations of the sperm tail

Sperm motility is crucial to reproductive success in sexually reproducing organisms. Impaired sperm movement causes male infertility, which is increasing globally. Sperm are powered by a microtubule-based molecular machine-the axoneme-but it is unclear how axonemal microtubules are ornamented to support motility in diverse fertilization environments. Here, we present high-resolution structures of native axonemal doublet microtubules (DMTs) from sea urchin and bovine sperm, representing external and internal fertilizers. We identify >60 proteins decorating sperm DMTs; at least 15 are sperm associated and 16 are linked to infertility. By comparing DMTs across species and cell types, we define core microtubule inner proteins (MIPs) and analyze evolution of the tektin bundle. We identify conserved axonemal microtubule-associated proteins (MAPs) with unique tubulin-binding modes. Additionally, we identify a testis-specific serine/threonine kinase that links DMTs to outer dense fibers in mammalian sperm. Our study provides structural foundations for understanding sperm evolution, motility, and dysfunction at a molecular level.

Extracellular cytochrome nanowires appear to be ubiquitous in prokaryotes

Electrically conductive appendages from the anaerobic bacterium Geobacter sulfurreducens, recently identified as extracellular cytochrome nanowires (ECNs), have received wide attention due to numerous potential applications. However, whether other organisms employ similar ECNs for electron transfer remains unknown. Here, using cryoelectron microscopy, we describe the atomic structures of two ECNs from two major orders of hyperthermophilic archaea present in deep-sea hydrothermal vents and terrestrial hot springs. Homologs of Archaeoglobus veneficus ECN are widespread among mesophilic methane-oxidizing Methanoperedenaceae, alkane-degrading Syntrophoarchaeales archaea, and in the recently described megaplasmids called Borgs. The ECN protein subunits lack similarities in their folds; however, they share a common heme arrangement, suggesting an evolutionarily optimized heme packing for efficient electron transfer. The detection of ECNs in archaea suggests that filaments containing closely stacked hemes may be a common and widespread mechanism for long-range electron transfer in both prokaryotic domains of life.

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.

AlphaFold2 and its applications in the fields of biology and medicine

AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind that can predict three-dimensional (3D) structures of proteins from amino acid sequences with atomic-level accuracy. Protein structure prediction is one of the most challenging problems in computational biology and chemistry, and has puzzled scientists for 50 years. The advent of AF2 presents an unprecedented progress in protein structure prediction and has attracted much attention. Subsequent release of structures of more than 200 million proteins predicted by AF2 further aroused great enthusiasm in the science community, especially in the fields of biology and medicine. AF2 is thought to have a significant impact on structural biology and research areas that need protein structure information, such as drug discovery, protein design, prediction of protein function, et al. Though the time is not long since AF2 was developed, there are already quite a few application studies of AF2 in the fields of biology and medicine, with many of them having preliminarily proved the potential of AF2. To better understand AF2 and promote its applications, we will in this article summarize the principle and system architecture of AF2 as well as the recipe of its success, and particularly focus on reviewing its applications in the fields of biology and medicine. Limitations of current AF2 prediction will also be discussed.

Ring-stacked capsids of white spot syndrome virus and structural transitions with genome ejection

White spot syndrome virus (WSSV) is one of the largest DNA viruses and the major pathogen responsible for white spot syndrome in crustaceans. The WSSV capsid is critical for genome encapsulation and ejection and exhibits the rod-shaped and oval-shaped structures during the viral life cycle. However, the detailed architecture of the capsid and the structural transition mechanism remain unclear. Here, using cryo-electron microscopy (cryo-EM), we obtained a cryo-EM model of the rod-shaped WSSV capsid and were able to characterize its ring-stacked assembly mechanism. Furthermore, we identified an oval-shaped WSSV capsid from intact WSSV virions and analyzed the structural transition mechanism from the oval-shaped to rod-shaped capsids induced by high salinity. These transitions, which decrease internal capsid pressure, always accompany DNA release and mostly eliminate the infection of the host cells. Our results demonstrate an unusual assembly mechanism of the WSSV capsid and offer structural insights into the pressure-driven genome release.

Archaeal DNA-import apparatus is homologous to bacterial conjugation machinery

Conjugation is a major mechanism of horizontal gene transfer promoting the spread of antibiotic resistance among human pathogens. It involves establishing a junction between a donor and a recipient cell via an extracellular appendage known as the mating pilus. In bacteria, the conjugation machinery is encoded by plasmids or transposons and typically mediates the transfer of cognate mobile genetic elements. Much less is known about conjugation in archaea. Here, we determine atomic structures by cryo-electron microscopy of three conjugative pili, two from hyperthermophilic archaea (Aeropyrum pernix and Pyrobaculum calidifontis) and one encoded by the Ti plasmid of the bacterium Agrobacterium tumefaciens, and show that the archaeal pili are homologous to bacterial mating pili. However, the archaeal conjugation machinery, known as Ced, has been 'domesticated', that is, the genes for the conjugation machinery are encoded on the chromosome rather than on mobile genetic elements, and mediates the transfer of cellular DNA.

Smart de novo Macromolecular Structure Modeling from Cryo-EM Maps

The study of macromolecular structures has expanded our understanding of the amazing cell machinery and such knowledge has changed how the pharmaceutical industry develops new vaccines in recent years. Traditionally, X-ray crystallography has been the main method for structure determination, however, cryogenic electron microscopy (cryo-EM) has increasingly become more popular due to recent advancements in hardware and software. The number of cryo-EM maps deposited in the EMDataResource (formerly EMDatabase) since 2002 has been dramatically increasing and it continues to do so. De novo macromolecular complex modeling is a labor-intensive process, therefore, it is highly desirable to develop software that can automate this process. Here we discuss our automated, data-driven, and artificial intelligence approaches including map processing, feature extraction, modeling building, and target identification. Recently, we have enabled DNA/RNA modeling in our deep learning-based prediction tool, DeepTracer. We have also developed DeepTracer-ID, a tool that can identify proteins solely based on the cryo-EM map. In this paper, we will present our accumulated experiences in developing deep learning-based methods surrounding macromolecule modeling applications.