A strategy for dissecting the architectures of native macromolecular assemblies

Nanobodies: From High-Throughput Identification to Therapeutic Development

The camelid single-domain antibody fragment, commonly referred to as a nanobody, achieves the targeting power of conventional monoclonal antibodies (mAbs) at only a fraction of their size. Isolated from camelid species (including llamas, alpacas, and camels), their small size at ∼15 kDa, low structural complexity, and high stability compared with conventional antibodies have propelled nanobody technology into the limelight of biologic development. Nanobodies are proving themselves to be a potent complement to traditional mAb therapies, showing success in the treatment of, for example, autoimmune diseases and cancer, and more recently as therapeutic options to treat infectious diseases caused by rapidly evolving biological targets such as the SARS-CoV-2 virus. This review highlights the benefits of applying a proteomic approach to identify diverse nanobody sequences against a single antigen. This proteomic approach coupled with conventional yeast/phage display methods enables the production of highly diverse repertoires of nanobodies able to bind the vast epitope landscape of an antigen, with epitope sampling surpassing that of mAbs. Additionally, we aim to highlight recent findings illuminating the structural attributes of nanobodies that make them particularly amenable to comprehensive antigen sampling and to synergistic activity-underscoring the powerful advantage of acquiring a large, diverse nanobody repertoire against a single antigen. Lastly, we highlight the efforts being made in the clinical development of nanobodies, which have great potential as powerful diagnostic reagents and treatment options, especially when targeting infectious disease agents.

The molecular architecture of the nuclear basket

The nuclear pore complex (NPC) is the sole mediator of nucleocytoplasmic transport. Despite great advances in understanding its conserved core architecture, the peripheral regions can exhibit considerable variation within and between species. One such structure is the cage-like nuclear basket. Despite its crucial roles in mRNA surveillance and chromatin organization, an architectural understanding has remained elusive. Using in-cell cryo-electron tomography and subtomogram analysis, we explored the NPC's structural variations and the nuclear basket across fungi (yeast; S. cerevisiae), mammals (mouse; M. musculus), and protozoa (T. gondii). Using integrative structural modeling, we computed a model of the basket in yeast and mammals that revealed how a hub of nucleoporins (Nups) in the nuclear ring binds to basket-forming Mlp/Tpr proteins: the coiled-coil domains of Mlp/Tpr form the struts of the basket, while their unstructured termini constitute the basket distal densities, which potentially serve as a docking site for mRNA preprocessing before nucleocytoplasmic transport.

An IDR-dependent mechanism for nuclear receptor control of Mediator interaction with RNA polymerase II

The essential Mediator (MED) coactivator complex plays a well-understood role in regulation of basal transcription in all eukaryotes, but the mechanism underlying its role in activator-dependent transcription remains unknown. We investigated modulation of metazoan MED interaction with RNA polymerase II (RNA Pol II) by antagonistic effects of the MED26 subunit and the CDK8 kinase module (CKM). Biochemical analysis of CKM-MED showed that the CKM blocks binding of the RNA Pol II carboxy-terminal domain (CTD), preventing RNA Pol II interaction. This restriction is eliminated by nuclear receptor (NR) binding to CKM-MED, which enables CTD binding in a MED26-dependent manner. Cryoelectron microscopy (cryo-EM) and crosslinking-mass spectrometry (XL-MS) revealed that the structural basis for modulation of CTD interaction with MED relates to a large intrinsically disordered region (IDR) in CKM subunit MED13 that blocks MED26 and CTD interaction with MED but is repositioned upon NR binding. Hence, NRs can control transcription initiation by priming CKM-MED for MED26-dependent RNA Pol II interaction.

Mapping protein-protein interactions by mass spectrometry

Protein-protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization and function of the proteome, and their perturbation is associated with various diseases, such as cancer, neurodegeneration, and infectious diseases. Recent advances in mass spectrometry (MS)-based protein interactomics have significantly expanded our understanding of the PPIs in cells, with techniques that continue to improve in terms of sensitivity, and specificity providing new opportunities for the study of PPIs in diverse biological systems. These techniques differ depending on the type of interaction being studied, with each approach having its set of advantages, disadvantages, and applicability. This review highlights recent advances in enrichment methodologies for interactomes before MS analysis and compares their unique features and specifications. It emphasizes prospects for further improvement and their potential applications in advancing our knowledge of PPIs in various biological contexts.

The Molecular Architecture of the Nuclear Basket

The nuclear pore complex (NPC) is the sole mediator of nucleocytoplasmic transport. Despite great advances in understanding its conserved core architecture, the peripheral regions can exhibit considerable variation within and between species. One such structure is the cage-like nuclear basket. Despite its crucial roles in mRNA surveillance and chromatin organization, an architectural understanding has remained elusive. Using in-cell cryo-electron tomography and subtomogram analysis, we explored the NPC's structural variations and the nuclear basket across fungi (yeast; S. cerevisiae), mammals (mouse; M. musculus), and protozoa (T. gondii). Using integrative structural modeling, we computed a model of the basket in yeast and mammals that revealed how a hub of Nups in the nuclear ring binds to basket-forming Mlp/Tpr proteins: the coiled-coil domains of Mlp/Tpr form the struts of the basket, while their unstructured termini constitute the basket distal densities, which potentially serve as a docking site for mRNA preprocessing before nucleocytoplasmic transport.

CombFold: predicting structures of large protein assemblies using a combinatorial assembly algorithm and AlphaFold2

Deep learning models, such as AlphaFold2 and RosettaFold, enable high-accuracy protein structure prediction. However, large protein complexes are still challenging to predict due to their size and the complexity of interactions between multiple subunits. Here we present CombFold, a combinatorial and hierarchical assembly algorithm for predicting structures of large protein complexes utilizing pairwise interactions between subunits predicted by AlphaFold2. CombFold accurately predicted (TM-score >0.7) 72% of the complexes among the top-10 predictions in two datasets of 60 large, asymmetric assemblies. Moreover, the structural coverage of predicted complexes was 20% higher compared to corresponding Protein Data Bank entries. We applied the method on complexes from Complex Portal with known stoichiometry but without known structure and obtained high-confidence predictions. CombFold supports the integration of distance restraints based on crosslinking mass spectrometry and fast enumeration of possible complex stoichiometries. CombFold's high accuracy makes it a promising tool for expanding structural coverage beyond monomeric proteins.

30 years of nanobodies - an ongoing success story of small binders in biological research

A milestone in the field of recombinant binding molecules was achieved 30 years ago with the discovery of single-domain antibodies from which antigen-binding variable domains, better known as nanobodies (Nbs), can be derived. Being only one tenth the size of conventional antibodies, Nbs feature high affinity and specificity, while being highly stable and soluble. In addition, they display accessibility to cryptic sites, low off-target accumulation and deep tissue penetration. Efficient selection methods, such as (semi-)synthetic/naïve or immunized cDNA libraries and display technologies, have facilitated the isolation of Nbs against diverse targets, and their single-gene format enables easy functionalization and high-yield production. This Review highlights recent advances in Nb applications in various areas of biological research, including structural biology, proteomics and high-resolution and in vivo imaging. In addition, we provide insights into intracellular applications of Nbs, such as live-cell imaging, biosensors and targeted protein degradation.

High-Efficiency Enrichment by Saturating Nanoliters of Protein Affinity Media

Affinity-purification mass spectrometry (AP-MS) is an established technique for identifying protein-protein interactions (PPIs). The basic technology involves immobilizing a high-specificity ligand to a solid-phase support (e.g., an agarose or magnetic bead) to pull down protein(s) of interest from cell lysates. Although these supports are engineered to minimize interactions with background protein, the conventional method recovers mostly nonspecific binders. The law of mass action for dilute solutions has taught us to use an excess of beads to capture all target proteins, especially weakly interacting ones. However, modern microbead technology presents a binding environment that is much different from a dilute solution. We describe a fluidic platform that captures and processes ultralow nanoliter quantities of magnetic particles, simultaneously increasing the efficiency of PPI detection and strongly suppressing nonspecific binding. We demonstrate the concept with synthetic mixtures of tagged protein and illustrate performance with a variety of AP-MS experiment types. These include a BioID experiment targeting lamin-A interactors from HeLa cells and pulldowns using GFP-tagged proteins associated with a double-strand DNA repair mechanism. We show that efficient extraction requires saturation of the solid-phase support and that <10 nL of beads is sufficient to generate comprehensive protein interaction maps.

A deep learning model for predicting optimal distance range in crosslinking mass spectrometry data

Macromolecular assemblies play an important role in all cellular processes. While there has recently been significant progress in protein structure prediction based on deep learning, large protein complexes cannot be predicted with these approaches. The integrative structure modeling approach characterizes multi-subunit complexes by computational integration of data from fast and accessible experimental techniques. Crosslinking mass spectrometry is one such technique that provides spatial information about the proximity of crosslinked residues. One of the challenges in interpreting crosslinking datasets is designing a scoring function that, given a structure, can quantify how well it fits the data. Most approaches set an upper bound on the distance between Cα atoms of crosslinked residues and calculate a fraction of satisfied crosslinks. However, the distance spanned by the crosslinker greatly depends on the neighborhood of the crosslinked residues. Here, we design a deep learning model for predicting the optimal distance range for a crosslinked residue pair based on the structures of their neighborhoods. We find that our model can predict the distance range with the area under the receiver-operator curve of 0.86 and 0.7 for intra- and inter-protein crosslinks, respectively. Our deep scoring function can be used in a range of structure modeling applications.

Circadian clocks are modulated by compartmentalized oscillating translation

Terrestrial organisms developed circadian rhythms for adaptation to Earth's quasi-24-h rotation. Achieving precise rhythms requires diurnal oscillation of fundamental biological processes, such as rhythmic shifts in the cellular translational landscape; however, regulatory mechanisms underlying rhythmic translation remain elusive. Here, we identified mammalian ATXN2 and ATXN2L as cooperating master regulators of rhythmic translation, through oscillating phase separation in the suprachiasmatic nucleus along circadian cycles. The spatiotemporal oscillating condensates facilitate sequential initiation of multiple cycling processes, from mRNA processing to protein translation, for selective genes including core clock genes. Depleting ATXN2 or 2L induces opposite alterations to the circadian period, whereas the absence of both disrupts translational activation cycles and weakens circadian rhythmicity in mice. Such cellular defect can be rescued by wild type, but not phase-separation-defective ATXN2. Together, we revealed that oscillating translation is regulated by spatiotemporal condensation of two master regulators to achieve precise circadian rhythm in mammals.

Spt6 directly interacts with Cdc73 and is required for Paf1 complex occupancy at active genes in Saccharomyces cerevisiae

The Paf1 complex (Paf1C) is a conserved transcription elongation factor that regulates transcription elongation efficiency, facilitates co-transcriptional histone modifications, and impacts molecular processes linked to RNA synthesis, such as polyA site selection. Coupling of the activities of Paf1C to transcription elongation requires its association with RNA polymerase II (Pol II). Mutational studies in yeast identified Paf1C subunits Cdc73 and Rtf1 as important mediators of Paf1C association with Pol II on active genes. While the interaction between Rtf1 and the general elongation factor Spt5 is relatively well-understood, the interactions involving Cdc73 have not been fully elucidated. Using a site-specific protein cross-linking strategy in yeast cells, we identified direct interactions between Cdc73 and two components of the Pol II elongation complex, the elongation factor Spt6 and the largest subunit of Pol II. Both of these interactions require the tandem SH2 domain of Spt6. We also show that Cdc73 and Spt6 can interact in vitro and that rapid depletion of Spt6 dissociates Paf1 from chromatin, altering patterns of Paf1C-dependent histone modifications genome-wide. These results reveal interactions between Cdc73 and the Pol II elongation complex and identify Spt6 as a key factor contributing to the occupancy of Paf1C at active genes in Saccharomyces cerevisiae.

Predicting structures of large protein assemblies using combinatorial assembly algorithm and AlphaFold2

Deep learning models, such as AlphaFold2 and RosettaFold, enable high-accuracy protein structure prediction. However, large protein complexes are still challenging to predict due to their size and the complexity of interactions between multiple subunits. Here we present CombFold, a combinatorial and hierarchical assembly algorithm for predicting structures of large protein complexes utilizing pairwise interactions between subunits predicted by AlphaFold2. CombFold accurately predicted (TM-score > 0.7) 72% of the complexes among the Top-10 predictions in two datasets of 60 large, asymmetric assemblies. Moreover, the structural coverage of predicted complexes was 20% higher compared to corresponding PDB entries. We applied the method on complexes from Complex Portal with known stoichiometry but without known structure and obtained high-confidence predictions. CombFold supports the integration of distance restraints based on crosslinking mass spectrometry and fast enumeration of possible complex stoichiometries. CombFold's high accuracy makes it a promising tool for expanding structural coverage beyond monomeric proteins.

Membrane Protein Binding Interactions Studied in Live Cells via Diethylpyrocarbonate Covalent Labeling Mass Spectrometry

Membrane proteins are vital in the human proteome for their cellular functions and make up a majority of drug targets in the U.S. However, characterizing their higher-order structures and interactions remains challenging. Most often membrane proteins are studied in artificial membranes, but such artificial systems do not fully account for the diversity of components present in cell membranes. In this study, we demonstrate that diethylpyrocarbonate (DEPC) covalent labeling mass spectrometry can provide binding site information for membrane proteins in living cells using membrane-bound tumor necrosis factor α (mTNFα) as a model system. Using three therapeutic monoclonal antibodies that bind TNFα, our results show that residues that are buried in the epitope upon antibody binding generally decrease in DEPC labeling extent. Additionally, serine, threonine, and tyrosine residues on the periphery of the epitope increase in labeling upon antibody binding because of a more hydrophobic microenvironment that is created. We also observe changes in labeling away from the epitope, indicating changes to the packing of the mTNFα homotrimer, compaction of the mTNFα trimer against the cell membrane, and/or previously uncharacterized allosteric changes upon antibody binding. Overall, DEPC-based covalent labeling mass spectrometry offers an effective means of characterizing structure and interactions of membrane proteins in living cells.

Electron microscopy holdings of the Protein Data Bank: the impact of the resolution revolution, new validation tools, and implications for the future

As a discipline, structural biology has been transformed by the three-dimensional electron microscopy (3DEM) "Resolution Revolution" made possible by convergence of robust cryo-preservation of vitrified biological materials, sample handling systems, and measurement stages operating a liquid nitrogen temperature, improvements in electron optics that preserve phase information at the atomic level, direct electron detectors (DEDs), high-speed computing with graphics processing units, and rapid advances in data acquisition and processing software. 3DEM structure information (atomic coordinates and related metadata) are archived in the open-access Protein Data Bank (PDB), which currently holds more than 11,000 3DEM structures of proteins and nucleic acids, and their complexes with one another and small-molecule ligands (~ 6% of the archive). Underlying experimental data (3DEM density maps and related metadata) are stored in the Electron Microscopy Data Bank (EMDB), which currently holds more than 21,000 3DEM density maps. After describing the history of the PDB and the Worldwide Protein Data Bank (wwPDB) partnership, which jointly manages both the PDB and EMDB archives, this review examines the origins of the resolution revolution and analyzes its impact on structural biology viewed through the lens of PDB holdings. Six areas of focus exemplifying the impact of 3DEM across the biosciences are discussed in detail (icosahedral viruses, ribosomes, integral membrane proteins, SARS-CoV-2 spike proteins, cryogenic electron tomography, and integrative structure determination combining 3DEM with complementary biophysical measurement techniques), followed by a review of 3DEM structure validation by the wwPDB that underscores the importance of community engagement.

The Magic of Linking Rings: Discovery of a Unique Photoinduced Fluorescent Protein Crosslink

Fluorosubstituted tryptophans serve as valuable probes for fluorescence and nuclear magnetic resonance (NMR) studies of proteins. Here, we describe an unusual photoreactivity introduced by replacing the single tryptophan in cyclophilin A with 7-fluoro-tryptophan. UV exposure at 282 nm defluorinates 7-fluoro-tryptophan and crosslinks it to a nearby phenylalanine, generating a bright fluorophore. The crosslink-containing fluorescent protein possesses a large quantum yield of ∼0.40 with a fluorescence lifetime of 2.38 ns. The chemical nature of the crosslink and the three-dimensional protein structure were determined by mass spectrometry and NMR spectroscopy. To the best of our knowledge, this is the first report of a Phe–Trp crosslink in a protein. Our finding may break new ground for developing novel fluorescence probes and for devising new strategies to exploit aromatic crosslinks in proteins.

Characterizing Endogenous Protein Complexes with Biological Mass Spectrometry

Biological mass spectrometry (MS) encompasses a range of methods for characterizing proteins and other biomolecules. MS is uniquely powerful for the structural analysis of endogenous protein complexes, which are often heterogeneous, poorly abundant, and refractive to characterization by other methods. Here, we focus on how biological MS can contribute to the study of endogenous protein complexes, which we define as complexes expressed in the physiological host and purified intact, as opposed to reconstituted complexes assembled from heterologously expressed components. Biological MS can yield information on complex stoichiometry, heterogeneity, topology, stability, activity, modes of regulation, and even structural dynamics. We begin with a review of methods for isolating endogenous complexes. We then describe the various biological MS approaches, focusing on the type of information that each method yields. We end with future directions and challenges for these MS-based methods.

Highly synergistic combinations of nanobodies that target SARS-CoV-2 and are resistant to escape

The emergence of SARS-CoV-2 variants threatens current vaccines and therapeutic antibodies and urgently demands powerful new therapeutics that can resist viral escape. We therefore generated a large nanobody repertoire to saturate the distinct and highly conserved available epitope space of SARS-CoV-2 spike, including the S1 receptor binding domain, N-terminal domain, and the S2 subunit, to identify new nanobody binding sites that may reflect novel mechanisms of viral neutralization. Structural mapping and functional assays show that indeed these highly stable monovalent nanobodies potently inhibit SARS-CoV-2 infection, display numerous neutralization mechanisms, are effective against emerging variants of concern, and are resistant to mutational escape. Rational combinations of these nanobodies that bind to distinct sites within and between spike subunits exhibit extraordinary synergy and suggest multiple tailored therapeutic and prophylactic strategies.

New system for archiving integrative structures

Structures of many complex biological assemblies are increasingly determined using integrative approaches, in which data from multiple experimental methods are combined. A standalone system, called PDB-Dev, has been developed for archiving integrative structures and making them publicly available. Here, the data standards and software tools that support PDB-Dev are described along with the new and updated components of the PDB-Dev data-collection, processing and archiving infrastructure. Following the FAIR (Findable, Accessible, Interoperable and Reusable) principles, PDB-Dev ensures that the results of integrative structure determinations are freely accessible to everyone.

A resource of high-quality and versatile nanobodies for drug delivery

Therapeutic and diagnostic efficacies of small biomolecules and chemical compounds are hampered by suboptimal pharmacokinetics. Here, we developed a repertoire of robust and high-affinity antihuman serum albumin nanobodies (NbHSA) that can be readily fused to small biologics for half-life extension. We characterized the thermostability, binding kinetics, and cross-species reactivity of NbHSAs, mapped their epitopes, and structurally resolved a tetrameric HSA-Nb complex. We parallelly determined the half-lives of a cohort of selected NbHSAs in an HSA mouse model by quantitative proteomics. Compared to short-lived control nanobodies, the half-lives of NbHSAs were drastically prolonged by 771-fold. NbHSAs have distinct and diverse pharmacokinetics, positively correlating with their albumin binding affinities at the endosomal pH. We then generated stable and highly bioactive NbHSA-cytokine fusion constructs "Duraleukin" and demonstrated Duraleukin's high preclinical efficacy for cancer treatment in a melanoma model. This high-quality and versatile Nb toolkit will help tailor drug half-life to specific medical needs.

Targeted in situ cross-linking mass spectrometry and integrative modeling reveal the architectures of three proteins from SARS-CoV-2

Atomic structures of several proteins from the coronavirus family are still partial or unavailable. A possible reason for this gap is the instability of these proteins outside of the cellular context, thereby prompting the use of in-cell approaches. In situ cross-linking and mass spectrometry (in situ CLMS) can provide information on the structures of such proteins as they occur in the intact cell. Here, we applied targeted in situ CLMS to structurally probe Nsp1, Nsp2, and nucleocapsid (N) proteins from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and obtained cross-link sets with an average density of one cross-link per 20 residues. We then employed integrative modeling that computationally combined the cross-linking data with domain structures to determine full-length atomic models. For the Nsp2, the cross-links report on a complex topology with long-range interactions. Integrative modeling with structural prediction of individual domains by the AlphaFold2 system allowed us to generate a single consistent all-atom model of the full-length Nsp2. The model reveals three putative metal binding sites and suggests a role for Nsp2 in zinc regulation within the replication-transcription complex. For the N protein, we identified multiple intra- and interdomain cross-links. Our integrative model of the N dimer demonstrates that it can accommodate three single RNA strands simultaneously, both stereochemically and electrostatically. For the Nsp1, cross-links with the 40S ribosome were highly consistent with recent cryogenic electron microscopy structures. These results highlight the importance of cellular context for the structural probing of recalcitrant proteins and demonstrate the effectiveness of targeted in situ CLMS and integrative modeling.

IMProv: A Resource for Cross-link-Driven Structure Modeling that Accommodates Protein Dynamics

Proteomics methodology has expanded to include protein structural analysis, primarily through cross-linking mass spectrometry (XL-MS) and hydrogen-deuterium exchange mass spectrometry (HX-MS). However, while the structural proteomics community has effective tools for primary data analysis, there is a need for structure modeling pipelines that are accessible to the proteomics specialist. Integrative structural biology requires the aggregation of multiple distinct types of data to generate models that satisfy all inputs. Here, we describe IMProv, an app in the Mass Spec Studio that combines XL-MS data with other structural data, such as cryo-EM densities and crystallographic structures, for integrative structure modeling on high-performance computing platforms. The resource provides an easily deployed bundle that includes the open-source Integrative Modeling Platform program (IMP) and its dependencies. IMProv also provides functionality to adjust cross-link distance restraints according to the underlying dynamics of cross-linked sites, as characterized by HX-MS. A dynamics-driven conditioning of restraint values can improve structure modeling precision, as illustrated by an integrative structure of the five-membered Polycomb Repressive Complex 2. IMProv is extensible to additional types of data.

Protein interaction landscapes revealed by advanced in vivo cross-linking-mass spectrometry

Defining protein-protein interactions (PPIs) in their native environment is crucial to understanding protein structure and function. Cross-linking-mass spectrometry (XL-MS) has proven effective in capturing PPIs in living cells; however, the proteome coverage remains limited. Here, we have developed a robust in vivo XL-MS platform to facilitate in-depth PPI mapping by integrating a multifunctional MS-cleavable cross-linker with sample preparation strategies and high-resolution MS. The advancement of click chemistry-based enrichment significantly enhanced the detection of cross-linked peptides for proteome-wide analyses. This platform enabled the identification of 13,904 unique lysine-lysine linkages from in vivo cross-linked HEK 293 cells, permitting construction of the largest in vivo PPI network to date, comprising 6,439 interactions among 2,484 proteins. These results allowed us to generate a highly detailed yet panoramic portrait of human interactomes associated with diverse cellular pathways. The strategy presented here signifies a technological advancement for in vivo PPI mapping at the systems level and can be generalized for charting protein interaction landscapes in any organisms.

Transiently structured head domains control intermediate filament assembly

Assembly of intermediate filaments (IFs) is reliant upon amino-terminal head domains. These head domains are of low sequence complexity and are assumed to function in the absence of structural order. Herein, we provide evidence that the head domains of the desmin and neurofilament light (NFL) IF proteins self-associate via the formation of labile but structurally specific cross-β interaction. Disease-causing mutations in the head domains of both proteins cause enhanced cross-β interactions. By assembling desmin and NFL IFs bearing isotopically labeled head domains, we provide evidence of structural order in properly assembled biological filaments. We propose that these observations on IF head domains may be instructive to the function of low complexity domains operative in other aspects of cell biology.

Low complexity (LC) head domains 92 and 108 residues in length are, respectively, required for assembly of neurofilament light (NFL) and desmin intermediate filaments (IFs). As studied in isolation, these IF head domains interconvert between states of conformational disorder and labile, β-strand–enriched polymers. Solid-state NMR (ss-NMR) spectroscopic studies of NFL and desmin head domain polymers reveal spectral patterns consistent with structural order. A combination of intein chemistry and segmental isotope labeling allowed preparation of fully assembled NFL and desmin IFs that could also be studied by ss-NMR. Assembled IFs revealed spectra overlapping with those observed for β-strand–enriched polymers formed from the isolated NFL and desmin head domains. Phosphorylation and disease-causing mutations reciprocally alter NFL and desmin head domain self-association yet commonly impede IF assembly. These observations show how facultative structural assembly of LC domains via labile, β-strand–enriched self-interactions may broadly influence cell morphology.

In-Cell Labeling and Mass Spectrometry for Systems-Level Structural Biology

Biological systems have evolved to utilize proteins to accomplish nearly all functional roles needed to sustain life. A majority of biological functions occur within the crowded environment inside cells and subcellular compartments where proteins exist in a densely packed complex network of protein-protein interactions. The structural biology field has experienced a renaissance with recent advances in crystallography, NMR, and CryoEM that now produce stunning models of large and complex structures previously unimaginable. Nevertheless, measurements of such structural detail within cellular environments remain elusive. This review will highlight how advances in mass spectrometry, chemical labeling, and informatics capabilities are merging to provide structural insights on proteins, complexes, and networks that exist inside cells. Because of the molecular detection specificity provided by mass spectrometry and proteomics, these approaches provide systems-level information that not only benefits from conventional structural analysis, but also is highly complementary. Although far from comprehensive in their current form, these approaches are currently providing systems structural biology information that can uniquely reveal how conformations and interactions involving many proteins change inside cells with perturbations such as disease, drug treatment, or phenotypic differences. With continued advancements and more widespread adaptation, systems structural biology based on in-cell labeling and mass spectrometry will provide an even greater wealth of structural knowledge.

Facilitating In Situ Cross-Linking and Mass Spectrometry by Antibody-Based Protein Enrichment

Cross-linking of living cells followed by mass spectrometry identification of cross-linked peptides (in situ CLMS) is an emerging technology to study protein structures in their native environment. One of the inherent difficulties of this technology is the high complexity of the samples following cell lysis. Currently, this difficulty largely limits the identification of cross-links to the more abundant proteins in the cell. Here, we describe a targeted approach in which an antibody is used to purify a specific protein-of-interest out of the cell lysate. Mass spectrometry analysis of the protein material that binds to the antibody can then identify considerably more cross-links on the target protein. By using an antibody against the CCT chaperonin, we identified over 200 cross-links that provide in situ evidence for the subunit arrangement of the CCT particle and its interactions with prefoldin. Similar targeting with an antibody against tubulin provided in situ evidence for the structure of the microtubule. Finally, the approach was also successful in identifying cross-links within a protein that expresses at a low level. These results demonstrate the general utility of antibody-based sample simplification for in situ CLMS and greatly expand the scope of protein systems that are amenable to in situ structural studies.

Integrative proteomics identifies thousands of distinct, multi-epitope, and high-affinity nanobodies

The antibody immune response is essential for the survival of mammals. However, we still lack a systematic understanding of the antibody repertoire. Here, we developed a proteomic strategy to survey, at an unprecedented scale, the landscape of antigen-engaged, circulating camelid heavy-chain antibodies, whose minimal binding fragments are called VHH antibodies or nanobodies. The sensitivity and robustness of this approach were validated with three antigens spanning orders of magnitude in immune responses; thousands of distinct, high-affinity nanobody families were reliably identified and quantified. Using high-throughput structural modeling, cross-linking mass spectrometry, mutagenesis, and deep learning, we mapped and analyzed the epitopes of >100,000 antigen-nanobody complexes. Our results revealed a surprising diversity of ultrahigh-affinity camelid nanobodies for specific antigen binding on various dominant epitope clusters. Nanobodies utilize both shape and charge complementarity to enable highly selective antigen binding. Interestingly, we found that nanobody-antigen binding can mimic conserved intracellular protein-protein interactions. A record of this paper's Transparent Peer Review process is included in the Supplemental information.

Ubiquitination-mediated degradation of TRDMT1 regulates homologous recombination and therapeutic response

The RNA methyltransferase TRDMT1 has recently emerged as a key regulator of homologous recombination (HR) in the transcribed regions of the genome, but how it is regulated and its relevance in cancer remain unknown. Here, we identified that TRDMT1 is poly-ubiquitinated at K251 by the E3 ligase TRIM28, removing TRDMT1 from DNA damage sites and allowing completion of HR. Interestingly, K251 is adjacent to G155 in the 3D structure, and the G155V mutation leads to hyper ubiquitination of TRDMT1, reduced TRDMT1 levels and impaired HR. Accordingly, a TRDMT1 G155V mutation in an ovarian cancer super responder to platinum treatment. Cells expressing TRDMT1-G155V are sensitive to cisplatin in vitro and in vivo. In contrast, high expression of TRDMT1 in patients with ovarian cancer correlates with platinum resistance. A potent TRDMT1 inhibitor resensitizes TRDMT1-high tumor cells to cisplatin. These results suggest that TRDMT1 is a promising therapeutic target to sensitize ovarian tumors to platinum therapy.

The active DNA-PK holoenzyme occupies a tensed state in a staggered synaptic complex

In the non-homologous end-joining (NHEJ) of a DNA double-strand break, DNA ends are bound and protected by DNA-PK, which synapses across the break to tether the broken ends and initiate repair. There is little clarity surrounding the nature of the synaptic complex and the mechanism governing the transition to repair. We report an integrative structure of the synaptic complex at a precision of 13.5 Å, revealing a symmetric head-to-head arrangement with a large offset in the DNA ends and an extensive end-protection mechanism involving a previously uncharacterized plug domain. Hydrogen/deuterium exchange mass spectrometry identifies an allosteric pathway connecting DNA end-binding with the kinase domain that places DNA-PK under tension in the kinase-active state. We present a model for the transition from end-protection to repair, where the synaptic complex supports hierarchical processing of the ends and scaffold assembly, requiring displacement of the catalytic subunit and tension release through kinase activity.

From integrative structural biology to cell biology

Integrative modeling is an increasingly important tool in structural biology, providing structures by combining data from varied experimental methods and prior information. As a result, molecular architectures of large, heterogeneous, and dynamic systems, such as the ∼52-MDa Nuclear Pore Complex, can be mapped with useful accuracy, precision, and completeness. Key challenges in improving integrative modeling include expanding model representations, increasing the variety of input data and prior information, quantifying a match between input information and a model in a Bayesian fashion, inventing more efficient structural sampling, as well as developing better model validation, analysis, and visualization. In addition, two community-level challenges in integrative modeling are being addressed under the auspices of the Worldwide Protein Data Bank (wwPDB). First, the impact of integrative structures is maximized by PDB-Development, a prototype wwPDB repository for archiving, validating, visualizing, and disseminating integrative structures. Second, the scope of structural biology is expanded by linking the wwPDB resource for integrative structures with archives of data that have not been generally used for structure determination but are increasingly important for computing integrative structures, such as data from various types of mass spectrometry, spectroscopy, optical microscopy, proteomics, and genetics. To address the largest of modeling problems, a type of integrative modeling called metamodeling is being developed; metamodeling combines different types of input models as opposed to different types of data to compute an output model. Collectively, these developments will facilitate the structural biology mindset in cell biology and underpin spatiotemporal mapping of the entire cell.

Versatile and multivalent nanobodies efficiently neutralize SARS-CoV-2

Cost-effective, efficacious therapeutics are urgently needed to combat the COVID-19 pandemic. In this study, we used camelid immunization and proteomics to identify a large repertoire of highly potent neutralizing nanobodies (Nbs) to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein receptor binding domain (RBD). We discovered Nbs with picomolar to femtomolar affinities that inhibit viral infection at concentrations below the nanograms-per-milliliter level, and we determined a structure of one of the most potent Nbs in complex with the RBD. Structural proteomics and integrative modeling revealed multiple distinct and nonoverlapping epitopes and indicated an array of potential neutralization mechanisms. We bioengineered multivalent Nb constructs that achieved ultrahigh neutralization potency (half-maximal inhibitory concentration as low as 0.058 ng/ml) and may prevent mutational escape. These thermostable Nbs can be rapidly produced in bulk from microbes and resist lyophilization and aerosolization.

Versatile, Multivalent Nanobody Cocktails Efficiently Neutralize SARS-CoV-2

The outbreak of COVID-19 has severely impacted global health and the economy. Cost-effective, highly efficacious therapeutics are urgently needed. Here, we used camelid immunization and proteomics to identify a large repertoire of highly potent neutralizing nanobodies (Nbs) to the SARS-CoV-2 spike (S) protein receptor-binding domain (RBD). We discovered multiple elite Nbs with picomolar to femtomolar affinities that inhibit viral infection at sub-ng/ml concentration, more potent than some of the best human neutralizing antibodies. We determined a crystal structure of such an elite neutralizing Nb in complex with RBD. Structural proteomics and integrative modeling revealed multiple distinct and non-overlapping epitopes and indicated an array of potential neutralization mechanisms. Structural characterization facilitated the bioengineering of novel multivalent Nb constructs into multi-epitope cocktails that achieved ultrahigh neutralization potency (IC50s as low as 0.058 ng/ml) and may prevent mutational escape. These thermostable Nbs can be rapidly produced in bulk from microbes and resist lyophilization, and aerosolization. These promising agents are readily translated into efficient, cost-effective, and convenient therapeutics to help end this once-in-a-century health crisis.

Software Requirements for the Analysis and Interpretation of Native Ion Mobility Mass Spectrometry Data

The past few years have seen a dramatic increase in applications of native mass and ion mobility spectrometry, especially for the study of proteins and protein complexes. This increase has been catalyzed by the availability of commercial instrumentation capable of carrying out such analyses. As in most fields, however, the software to process the data generated from new instrumentation lags behind. Recently, a number of research groups have started addressing this by developing software, but further improvements are still required in order to realize the full potential of the data sets generated. In this perspective, we describe practical aspects as well as challenges in processing native mass spectrometry (MS) and ion mobility-MS data sets and provide a brief overview of currently available tools. We then set out our vision of future developments that would bring the community together and lead to the development of a common platform to expedite future computational developments, provide standardized processing approaches, and serve as a location for the deposition of data for this emerging field. This perspective has been written by members of the European Cooperation in Science and Technology Action on Native MS and Related Methods for Structural Biology (EU COST Action BM1403) as an introduction to the software tools available in this area. It is intended to serve as an overview for newcomers and to stimulate discussions in the community on further developments in this field, rather than being an in-depth review. Our complementary perspective (http://dx.doi.org/10.1021/acs.analchem.9b05791) focuses on computational approaches used in this field.

Coarse-grained (hybrid) integrative modeling of biomolecular interactions

The computational modeling field has vastly evolved over the past decades. The early developments of simplified protein systems represented a stepping stone towards establishing more efficient approaches to sample intricated conformational landscapes. Downscaling the level of resolution of biomolecules to coarser representations allows for studying protein structure, dynamics and interactions that are not accessible by classical atomistic approaches. The combination of different resolutions, namely hybrid modeling, has also been proved as an alternative when mixed levels of details are required. In this review, we provide an overview of coarse-grained/hybrid models focusing on their applicability in the modeling of biomolecular interactions. We give a detailed list of ready-to-use modeling software for studying biomolecular interactions allowing various levels of coarse-graining and provide examples of complexes determined by integrative coarse-grained/hybrid approaches in combination with experimental information.

Integrative structure and function of the yeast exocyst complex

Exocyst is an evolutionarily conserved hetero-octameric tethering complex that plays a variety of roles in membrane trafficking, including exocytosis, endocytosis, autophagy, cell polarization, cytokinesis, pathogen invasion, and metastasis. Exocyst serves as a platform for interactions between the Rab, Rho, and Ral small GTPases, SNARE proteins, and Sec1/Munc18 regulators that coordinate spatial and temporal fidelity of membrane fusion. However, its mechanism is poorly described at the molecular level. Here, we determine the molecular architecture of the yeast exocyst complex by an integrative approach, based on a 3D density map from negative-stain electron microscopy (EM) at ~16 Å resolution, 434 disuccinimidyl suberate and 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride cross-links from chemical-crosslinking mass spectrometry, and partial atomic models of the eight subunits. The integrative structure is validated by a previously determined cryo-EM structure, cross-links, and distances from in vivo fluorescence microscopy. Our subunit configuration is consistent with the cryo-EM structure, except for Sec5. While not observed in the cryo-EM map, the integrative model localizes the N-terminal half of Sec3 near the Sec6 subunit. Limited proteolysis experiments suggest that the conformation of Exo70 is dynamic, which may have functional implications for SNARE and membrane interactions. This study illustrates how integrative modeling based on varied low-resolution structural data can inform biologically relevant hypotheses, even in the absence of high-resolution data.

High-density chemical cross-linking for modeling protein interactions

Detailed mechanistic understanding of protein complex function is greatly enhanced by insights from its 3-dimensional structure. Traditional methods of protein structure elucidation remain expensive and labor-intensive and require highly purified starting material. Chemical cross-linking coupled with mass spectrometry offers an alternative that has seen increased use, especially in combination with other experimental approaches like cryo-electron microscopy. Here we report advances in method development, combining several orthogonal cross-linking chemistries as well as improvements in search algorithms, statistical analysis, and computational cost to achieve coverage of 1 unique cross-linked position pair for every 7 amino acids at a 1% false discovery rate. This is accomplished without any peptide-level fractionation or enrichment. We apply our methods to model the complex between a carbonic anhydrase (CA) and its protein inhibitor, showing that the cross-links are self-consistent and define the interaction interface at high resolution. The resulting model suggests a scaffold for development of a class of protein-based inhibitors of the CA family of enzymes. We next cross-link the yeast proteasome, identifying 3,893 unique cross-linked peptides in 3 mass spectrometry runs. The dataset includes 1,704 unique cross-linked position pairs for the proteasome subunits, more than half of them intersubunit. Using multiple recently solved cryo-EM structures, we show that observed cross-links reflect the conformational dynamics and disorder of some proteasome subunits. We further demonstrate that this level of cross-linking density is sufficient to model the architecture of the 19-subunit regulatory particle de novo.

RNA Exosomes and Their Cofactors

The RNA exosome is a ribonucleolytic multiprotein complex that is conserved and essential in all eukaryotes. Although we tend to speak of "the" exosome complex, it should be more correctly viewed as several different subtypes that share a common core. Subtypes of the exosome complex are present in the cytoplasm, the nucleus and the nucleolus of all eukaryotic cells, and carry out the 3'-5' processing and/or degradation of a wide range of RNA substrates.Because the substrate specificity of the exosome complex is determined by cofactors, the system is highly adaptable, and different organisms have adjusted the machinery to their specific needs. Here, we present an overview of exosome complexes and their cofactors that have been described in different eukaryotes.

Chemical Cross-Linking and Mass Spectrometric Analysis of the Endogenous Yeast Exosome Complexes

Chemical cross-linking and mass spectrometric readout (CX-MS) has become a useful toolkit for structural analysis of protein complexes. CX-MS enables rapid detection of a larger number of cross-link peptides from the chemically cross-linked protein assembly, providing invaluable cross-link spatial restraints to understand the architecture of the complex. Since CX-MS is complementary with other structural and computational modeling tools, it can be used for integrative structural determination of large native protein assemblies. However, due to technical limitations, current CX-MS applications have still been predominantly confined to complexes reconstituted from recombinant proteins where large amount of purified materials are available. Cross-linking and hybrid structural proteomic analysis of endogenous protein complexes remains a challenge. In this chapter, we present a protocol that efficiently couples affinity capture of endogenous complexes with sensitive CX-MS analysis, with particular application to the yeast RNA processing exosome complexes.

Cryo-Electron Microscopy of Endogenous Yeast Exosomes

The RNA exosome is a multisubunit complex typically composed of a catalytically inactive core and the Rrp44 protein, which contains 3'-to-5' exo- and endo-RNase activities. With assistance from nuclear or cytoplasmic cofactors, functional studies implicated the exosome as a critical player in the turnover of almost all RNA species, including mRNAs, rRNA, tRNAs, and other noncoding RNAs. Here, we describe the purification of the yeast 10-subunit exosome and 11-subunit Exosome-Ski7, as well as subsequent sample screening by negative staining EM and structural analysis by cryo-EM.

The RNA Exosome and Human Disease

The evolutionarily conserved RNA exosome is a multisubunit ribonuclease complex that processes and/or degrades numerous RNAs. Recently, mutations in genes encoding both structural and catalytic subunits of the RNA exosome have been linked to human disease. Mutations in the structural exosome gene EXOSC2 cause a distinct syndrome that includes retinitis pigmentosa, hearing loss, and mild intellectual disability. In contrast, mutations in the structural exosome genes EXOSC3 and EXOSC8 cause pontocerebellar hypoplasia type 1b (PCH1b) and type 1c (PCH1c), respectively, which are related autosomal recessive, neurodegenerative diseases. In addition, mutations in the structural exosome gene EXOSC9 cause a PCH-like disease with cerebellar atrophy and spinal motor neuronopathy. Finally, mutations in the catalytic exosome gene DIS3 have been linked to multiple myeloma, a neoplasm of plasma B cells. How mutations in these RNA exosome genes lead to distinct, tissue-specific diseases is not currently well understood. In this chapter, we examine the role of the RNA exosome complex in human disease and discuss the mechanisms by which mutations in different exosome subunit genes could impair RNA exosome function and give rise to diverse diseases.

Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures

Structures of biomolecular systems are increasingly computed by integrative modeling. In this approach, a structural model is constructed by combining information from multiple sources, including varied experimental methods and prior models. In 2019, a Workshop was held as a Biophysical Society Satellite Meeting to assess progress and discuss further requirements for archiving integrative structures. The primary goal of the Workshop was to build consensus for addressing the challenges involved in creating common data standards, building methods for federated data exchange, and developing mechanisms for validating integrative structures. The summary of the Workshop and the recommendations that emerged are presented here.

Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities

New technologies have enabled the investigation of biology and human health at an unprecedented scale and in multiple dimensions. These dimensions include myriad properties describing genome, epigenome, transcriptome, microbiome, phenotype, and lifestyle. No single data type, however, can capture the complexity of all the factors relevant to understanding a phenomenon such as a disease. Integrative methods that combine data from multiple technologies have thus emerged as critical statistical and computational approaches. The key challenge in developing such approaches is the identification of effective models to provide a comprehensive and relevant systems view. An ideal method can answer a biological or medical question, identifying important features and predicting outcomes, by harnessing heterogeneous data across several dimensions of biological variation. In this Review, we describe the principles of data integration and discuss current methods and available implementations. We provide examples of successful data integration in biology and medicine. Finally, we discuss current challenges in biomedical integrative methods and our perspective on the future development of the field.

The ALFA-tag is a highly versatile tool for nanobody-based bioscience applications

Specialized epitope tags are widely used for detecting, manipulating or purifying proteins, but often their versatility is limited. Here, we introduce the ALFA-tag, a rationally designed epitope tag that serves a remarkably broad spectrum of applications in life sciences while outperforming established tags like the HA-, FLAG®- or myc-tag. The ALFA-tag forms a small and stable α-helix that is functional irrespective of its position on the target protein in prokaryotic and eukaryotic hosts. We characterize a nanobody (NbALFA) binding ALFA-tagged proteins from native or fixed specimen with low picomolar affinity. It is ideally suited for super-resolution microscopy, immunoprecipitations and Western blotting, and also allows in vivo detection of proteins. We show the crystal structure of the complex that enabled us to design a nanobody mutant (NbALFA^PE) that permits efficient one-step purifications of native ALFA-tagged proteins, complexes and even entire living cells using peptide elution under physiological conditions.

Epitope tags are widely used in various applications, but often lack versatility. Here, the authors introduce a small, alpha helical tag, which is recognized by a high affinity nanobody and can be used in a range of different applications, from protein purification to super-resolution imaging and in vivo detection of proteins.

Archiving and disseminating integrative structure models

Limitations in the applicability, accuracy, and precision of individual structure characterization methods can sometimes be overcome via an integrative modeling approach that relies on information from all available sources, including all available experimental data and prior models. The open-source Integrative Modeling Platform (IMP) is one piece of software that implements all computational aspects of integrative modeling. To maximize the impact of integrative structures, the coordinates should be made publicly available, as is already the case for structures based on X-ray crystallography, NMR spectroscopy, and electron microscopy. Moreover, the associated experimental data and modeling protocols should also be archived, such that the original results can easily be reproduced. Finally, it is essential that the integrative structures are validated as part of their publication and deposition. A number of research groups have already developed software to implement integrative modeling and have generated a number of structures, prompting the formation of an Integrative/Hybrid Methods Task Force. Following the recommendations of this task force, the existing PDBx/mmCIF data representation used for atomic PDB structures has been extended to address the requirements for archiving integrative structural models. This IHM-dictionary adds a flexible model representation, including coarse graining, models in multiple states and/or related by time or other order, and multiple input experimental information sources. A prototype archiving system called PDB-Dev ( https://pdb-dev.wwpdb.org ) has also been created to archive integrative structural models, together with a Python library to facilitate handling of integrative models in PDBx/mmCIF format.

Role of integrative structural biology in understanding transcriptional initiation

Integrative structural biology combines data from multiple experimental techniques to generate complete structural models for the biological system of interest. Most commonly cross-linking data sets are employed alongside electron microscopy maps, crystallographic structures, and other data by computational methods that integrate all known information and produce structural models at a level of resolution that is appropriate to the input data. The precision of these modelled solutions is limited by the sparseness of cross-links observed, the length of the cross-linking reagent, the ambiguity arisen from the presence of multiple copies of the same protein, and structural and compositional heterogeneity. In recent years integrative structural biology approaches have been successfully applied to a range of RNA polymerase II complexes. Here we will provide a general background to integrative structural biology, a description of how it should be practically implemented and how it has furthered our understanding of the biology of large transcriptional assemblies. Finally, in the context of recent breakthroughs in microscope and direct electron detector technology, where increasingly EM is capable of resolving structural features directly without the aid of other structural techniques, we will discuss the future role of integrative structural techniques.

Miniaturised interaction proteomics on a microfluidic platform with ultra-low input requirements

Essentially all cellular processes are orchestrated by protein-protein interactions (PPIs). In recent years, affinity purification coupled to mass spectrometry (AP-MS) has been the preferred method to identify cellular PPIs. Here we present a microfluidic-based AP-MS workflow, called on-chip AP-MS, to identify PPIs using minute amounts of input material. By using this automated platform we purify the human Cohesin, CCC and Mediator complexes from as little as 4 micrograms of input lysate, representing a 50─100-fold downscaling compared to regular microcentrifuge tube-based protocols. We show that our platform can be used to affinity purify tagged baits as well as native cellular proteins and their interaction partners. As such, our method holds great promise for future biological and clinical AP-MS applications in which sample amounts are limited.

Evaluation of Different Stationary Phases in the Separation of Inter-Cross-Linked Peptides

Chemical cross-linking coupled with mass spectrometry (MS) is becoming a routinely and widely used technique for depicting and constructing protein structures and protein interaction networks. One major challenge for cross-linking/MS is the determination of informative low-abundant inter-cross-linked products, generated within a sample of high complexity. A C18 stationary phase is the conventional means for reversed-phase (RP) separation of inter-cross-linked peptides. Various RP stationary phases, which provide different selectivities and retentions, have been developed as alternatives to C18 stationary phases. In this study, two phenyl-based columns, biphenyl and fluorophenyl, were investigated and compared with a C18 phase for separating BS³ (bis(sulfosuccinimidyl)suberate) cross-linked bovine serum albumin (BSA) and myoglobin by bottom-up proteomics. Fractions from the three columns were collected and analyzed in a linear ion trap (LIT) mass spectrometer for improving detection of low abundant inter-cross-linked peptides. Among these three columns, the fluorophenyl column provides additional ion-exchange interaction and exhibits unique retention in separating the cross-linked peptides. The fractioned data was analyzed in pLink, showing the fluorophenyl column consistently obtained more inter-cross-linked peptide identifications than both C18 and biphenyl columns. For the BSA cross-linked sample, the identified inter-cross-linked peptide numbers of the fluorophenyl to C18 column are 136 to 102 in "low confident" results and 11 to 6 in "high confident" results. The fluorophenyl column could potentially be a better alternative for targeting the low stoichiometric inter-cross-linked peptides.

The Nuclear RNA Exosome and Its Cofactors

The RNA exosome is a highly conserved ribonuclease endowed with 3'-5' exonuclease and endonuclease activities. The multisubunit complex resides in both the nucleus and the cytoplasm, with varying compositions and activities between the two compartments. While the cytoplasmic exosome functions mostly in mRNA quality control pathways, the nuclear RNA exosome partakes in the 3'-end processing and complete decay of a wide variety of substrates, including virtually all types of noncoding (nc) RNAs. To handle these diverse tasks, the nuclear exosome engages with dedicated cofactors, some of which serve as activators by stimulating decay through oligoA addition and/or RNA helicase activities or, as adaptors, by recruiting RNA substrates through their RNA-binding capacities. Most nuclear exosome cofactors contain the essential RNA helicase Mtr4 (MTR4 in humans). However, apart from Mtr4, nuclear exosome cofactors have undergone significant evolutionary divergence. Here, we summarize biochemical and functional knowledge about the nuclear exosome and exemplify its cofactor variety by discussing the best understood model organisms-the budding yeast Saccharomyces cerevisiae, the fission yeast Schizosaccharomyces pombe, and human cells.

Mechanisms of opening and closing of the bacterial replicative helicase

Assembly of bacterial ring-shaped hexameric replicative helicases on single-stranded (ss) DNA requires specialized loading factors. However, mechanisms implemented by these factors during opening and closing of the helicase, which enable and restrict access to an internal chamber, are not known. Here, we investigate these mechanisms in the Escherichia coli DnaB helicase•bacteriophage λ helicase loader (λP) complex. We show that five copies of λP bind at DnaB subunit interfaces and reconfigure the helicase into an open spiral conformation that is intermediate to previously observed closed ring and closed spiral forms; reconfiguration also produces openings large enough to admit ssDNA into the inner chamber. The helicase is also observed in a restrained inactive configuration that poises it to close on activating signal, and transition to the translocation state. Our findings provide insights into helicase opening, delivery to the origin and ssDNA entry, and closing in preparation for translocation.