To perform native mass spectrometry (MS) studies, there are a limited number of volatile and electrospray ionization (ESI)-MS compatible solutions, such as ammonium bicarbonate and ammonium acetate (AA). These solutions could induce the unfolding of proteins due to the formation of CO2 bubbles or induced acidification during ESI. Hence, it was important to introduce a buffer suitable to preserve the native form of proteins while simulating physiological conditions.

The 4-ethylmorpholinium/acetate (4EM/A) buffer was compared to AA for the analysis of proteins and protein complexes with mass ranges from 5 to 103 kDa and isoelectric points (pI) between 3 and 11. The evaluations were conducted by comparing the native-MS profiles, CCS values, arrival time distributions (ATDs), and proteins bioactivities. The human cardiac troponin complex (cTn complex) and its subunit cardiac troponin T (cTnT) were analyzed as proof of the applicability of this buffer for challenging proteins and protein complexes.

4EM/A led to lower charge states compared to AA, supporting the likelihood of preserving protein folding during nano-ESI and in a high vacuum environment of MS. Ion mobility measurements revealed that proteins in 4EM/A exhibit a lower degree of conformational variation compared to AA, suggesting enhanced conformational stability and potential retention of natural-like compactness. Additionally, testing the impact of 4EM/A on bioactivity, lysozyme showed increased biological activity in 4EM/A relative to AA, highlighting the buffer's potential for real-time assessment of protein interaction kinetics and bioactivity. The 4EM/A buffer enabled native-MS analysis of cTnT for the first time.

We introduced 4EM/A, with pKa of 7.72/4.76, as a promising buffer for native-MS studies to maintain protein and protein complex bioactivity and conformational integrity.

Antibodies are a major component of adaptive immunity against invading pathogens. Here, we explore possibilities for an analytical approach to characterize the antigen-specific antibody repertoire directly from the secreted proteins in convalescent serum. This approach aims to perform simultaneous antibody sequencing and epitope mapping using a combination of single particle cryo-electron microscopy (cryoEM) and bottom-up proteomics techniques based on mass spectrometry (LC-MS/MS). We evaluate the performance of the deep-learning tool ModelAngelo in determining de novo antibody sequences directly from reconstructed 3D volumes of antibody-antigen complexes. We demonstrate that while map quality is a critical bottleneck, it is possible to sequence antibody variable domains from cryoEM reconstructions with accuracies of up to 80-90%. While the rate of errors exceeds the typical levels of somatic hypermutation, we show that the ModelAngelo-derived sequences can be used to assign the used V-genes. This provides a functional guide to assemble de novo peptides from LC-MS/MS data more accurately and improves the tolerance to a background of polyclonal antibody sequences. Following this proof-of-principle, we discuss the feasibility and future directions of this approach to characterize antigen-specific antibody repertoires.

Human cells consist of a complex hierarchy of components, many of which remain unexplored1,2. Here we construct a global map of human subcellular architecture through joint measurement of biophysical interactions and immunofluorescence images for over 5,100 proteins in U2OS osteosarcoma cells. Self-supervised multimodal data integration resolves 275 molecular assemblies spanning the range of 10-8 to 10-5 m, which we validate systematically using whole-cell size-exclusion chromatography and annotate using large language models3. We explore key applications in structural biology, yielding structures for 111 heterodimeric complexes and an expanded Rag-Ragulator assembly. The map assigns unexpected functions to 975 proteins, including roles for C18orf21 in RNA processing and DPP9 in interferon signalling, and identifies assemblies with multiple localizations or cell type specificity. It decodes paediatric cancer genomes4, identifying 21 recurrently mutated assemblies and implicating 102 validated new cancer proteins. The associated Cell Visualization Portal and Mapping Toolkit provide a reference platform for structural and functional cell biology.

Protein complexes are essential for virtually all biological processes, yet their structural characterization remains a major challenge due to their heterogeneous, dynamic nature and the complexity of the proteome. Native top-down mass spectrometry (nTDMS) has emerged as a powerful tool for comprehensive structural characterization of purified protein complexes, but its application to endogenous protein complexes in the proteome is challenging and typically requires labor-intensive and time-consuming prefractionation. Here, for the first time, we develop a nondenaturing online two-dimensional liquid chromatography (2D-LC) method for native top-down proteomics (nTDP), enabling high-throughput structural analysis of endogenous protein complexes. The automated, online interfacing of size-exclusion and mixed-bed ion-exchange chromatography achieves high coverage of endogenous protein complexes. We further develop a multistage nTDMS approach that enables comprehensive structural characterization within the chromatographic timescale, capturing intact non-covalent complexes, released subunits/cofactors, and backbone fragments. Our analysis detected 133 native proteoforms and endogenous protein complexes (up to 350 kDa) from human heart tissue in less than two hours. Such technological leaps in high-throughput structural characterization of endogenous protein complexes will advance large-scale nTDP studies in health and disease.

Cryogenic electron microscopy single particle analysis (cryoEM-SPA) has evolved into a routine approach for determining macromolecule structures to near-atomic resolution. Cryogenic electron tomography subtomogram averaging (cryoET-STA) toward a similar resolution, in contrast, is still under active development. Here, we use the archeal chaperonin MmCpn as a model macromolecule to quantitatively investigate the resolution limiting factors of cryoET-STA in terms of cumulative electron dose, ice thickness, subtomogram numbers, and tilt angle ranges. By delineating the feasibility and experimental factors of attaining near atomic resolution structure with cryoET-STA, especially the effect of electron damage through the tilt series and inelastic scattering at various ice thickness, we encourage a customized tilt series collection strategy for efficient throughput. This study provides a biophysical basis for the application of cryoET-STA (for highly symmetric molecules like MmCpn) toward high resolution and the rationales in using cryoET-STA to achieve an efficient outcome at the desired resolution.

Protein assembly into functional complexes is critical to life's processes. While complex assembly is classically described as occurring between fully synthesized proteins, recent work showed that co-translational assembly is prevalent in human cells. However, the biological basis for the existence of this process and the identity of protein pairs that assemble co-translationally remain unknown. We show that co-translational assembly is governed by structural characteristics of complexes and involves mutually stabilized subunits. Accordingly, co-translationally assembling subunits are unstable in isolation and exhibit synchronized proteostasis with their partner. By leveraging structural signatures and AlphaFold2-based predictions, we accurately predicted co-translational assembly, including pair identities, at proteome scale and across species. We validated our predictions by ribosome profiling, stoichiometry perturbations, and single-molecule RNA-fluorescence in situ hybridization (smFISH) experiments that revealed co-localized mRNAs. This work establishes a fundamental connection between protein structure and the translation process, highlighting the overarching impact of three-dimensional structure on gene expression, mRNA localization, and proteostasis.

Rapid structural analysis of purified proteins and their complexes has become increasingly common thanks to key methodological advances in cryo-electron microscopy (cryo-EM) and associated data processing software packages. In contrast, analogous structural analysis in cells via cryo-electron tomography (cryo-ET) remains challenging due to critical technical bottlenecks, including low-throughput sample preparation and imaging, and laborious data processing methods. Here, we describe a rapid in situ cryo-ET sample preparation and data analysis workflow that results in the routine determination of sub-nm resolution ribosomal structures. We apply this workflow to E. coli, producing a 5.8 Å structure of the 70S ribosome from cells in less than 10 days and facilitating the discovery of a minor population of 100S-like disomes. We envision our approach to be widely applicable to related bacterial samples.

Particle picking in cryo-electron tomograms (cryo-ET) is crucial for in situ structure detection of macromolecules and protein complexes. The traditional template-matching-based approaches for particle picking suffer from template-specific biases and have low throughput. Given these problems, learning-based solutions are necessary for particle picking. However, the paucity of annotated data for training poses substantial challenges for such learning-based approaches. Moreover, preparing extensively annotated cryo-ET tomograms for particle picking is extremely time-consuming and burdensome. Addressing these challenges, we present TomoPicker, an annotation-efficient particle-picking approach that can effectively pick particles when only a minuscule portion (~ 0.3 - 0.5%) of the total particles in a cellular cryo-ET dataset is provided for training. TomoPicker regards particle picking as a voxel classification problem and solves it with two different positive-unlabeled learning approaches. We evaluated our method on a benchmark cryo-ET dataset of eukaryotic cells, where we observed about 30% improvement by TomoPicker against the most recent state-of-the-art annotation efficient learning-based picking approaches.

The type 1 polyketide synthase (PKS) assembly line uses its modular structure to produce polyketide natural products that form the basis of many pharmaceuticals. Currently, several cryoelectron microscopy (cryo-EM) structures of a multidomain PKS module have been constructed, but much remains to be learned. Here we utilize ion-mobility mass spectrometry (IM-MS) to record size and shape information and detect different conformational states of a 207 kDa didomain dimer comprised of ketosynthase (KS) and acyl transferase (AT), excised from full-length module. Furthermore, gas-phase stability differences between these different conformations are captured by collision induced unfolding (CIU) technology. Additionally, through tracking these forms as a function of time, we elucidate a detailed disassembly pathway for KS-AT dimers for the first time.

Carotid stenosis is characterized by the progressive narrowing of the carotid arteries due to the formation of atherosclerotic plaque, which can lead to stroke and death as major complications. Numerous biomarkers allow for its study and characterization, particularly those related to "omics" sciences. Through the most common research databases, we report representative studies about carotid stenosis biomarkers based on genomics, transcriptomics, proteomics, and metabolomics in a narrative review. To establish a priority among studies based on their internal validity, we used a quality assessment tool, the Scale for the Assessment of Narrative Review Articles (SANRA). Genes, transcriptomes, proteins, and metabolites can diagnose the disease, define plaque connotations, predict consequences after revascularization interventions, and associate carotid stenosis with other patient comorbidities. It also emerged that many aspects determining the patient's psychological and social sphere are implicated in carotid disease. In conclusion, when taking the multidisciplinary approach that combines human sciences with biological sciences, it is possible to comprehensively define a patient's health and thus improve their clinical management through precision medicine.

The anaphase-promoting complex/cyclosome (APC/C) is a critical and tightly regulated E3 ligase that orchestrates the cellular life cycle by controlling the degradation of cell cycle regulators. An intriguing feature of this complex is an autoinhibition mechanism: an intrinsically disordered loop domain, Apc1-300L, blocks Cdc20 coactivator binding, yet phosphorylation of Apc1-300L counteracts this autoinhibition. Many such disordered loops within APC/C remain unexplored. Our systematic analysis of loop-deficient APC/C mutants uncovered a pivotal role for Apc8's C-terminal loop (Apc8-L) in mitotic activation. Apc8-L directly recruits the CDK adaptor protein, Xe-p9/Cks2, positioning the Xe-p9-CDK-CycB complex near Apc1-300L. This stimulates the phosphorylation and removal of Apc1-300L, prompting the formation of active APC/CCdc20. Strikingly, without both Apc8-L and Apc3-L, the APC/C is rendered inactive during mitosis, highlighting Apc8-L's synergistic role with other loops and kinases. This study broadens our understanding of the intricate dynamics in APC/C regulation and provides insights on the regulation of macromolecular complexes.

Sensitive analytical techniques that are capable of detecting and quantifying disease-associated biomolecules are indispensable in our efforts to understand disease mechanisms and guide therapeutic intervention through early detection, accurate diagnosis, and effective monitoring of disease. Parkinson's Disease (PD), for example, is one of the most prominent neurodegenerative disorders in the world, but the diagnosis of PD has primarily been based on the observation of clinical symptoms. The protein α-synuclein (α-syn) has emerged as a promising biomarker candidate for PD, but a lack of analytical methods to measure complex disease-associated variants of α-syn has prevented its widespread use as a biomarker. Antibody-based methods such as immunoassays and mass spectrometry-based approaches have been used to measure a limited number of α-syn forms; however, these methods fail to differentiate variants of α-syn that display subtle differences in only the sequence and structure. In this work, we developed a cyclic ion mobility-mass spectrometry method that combines multiple stages of activation and timed ion selection to quantify α-syn variants using both mass- and structure-based measurements. This method can allow for the quantification of several α-syn variants present at physiological levels in biological fluid. Taken together, this approach can be used to galvanize future efforts aimed at understanding the underlying mechanisms of PD and serves as a starting point for the development of future protein-structure-based diagnostics and therapeutic interventions.

Most life scientists would agree that understanding how cellular processes work requires structural knowledge about the macromolecules involved. For example, deciphering the double-helical nature of DNA revealed essential aspects of how genetic information is stored, copied and repaired. Yet, being reductionist in nature, structural biology requires the purification of large amounts of macromolecules, often trimmed off larger functional units. The advent of cryogenic electron microscopy (cryo-EM) greatly facilitated the study of large, functional complexes and generally of samples that are hard to express, purify and/or crystallize. Nevertheless, cryo-EM still requires purification and thus visualization outside of the natural context in which macromolecules operate and coexist. Conversely, cell biologists have been imaging cells using a number of fast-evolving techniques that keep expanding their spatial and temporal reach, but always far from the resolution at which chemistry can be understood. Thus, structural and cell biology provide complementary, yet unconnected visions of the inner workings of cells. Here we discuss how the interplay between cryo-EM and cryo-electron tomography, as a connecting bridge to visualize macromolecules in situ, holds great promise to create comprehensive structural depictions of macromolecules as they interact in complex mixtures or, ultimately, inside the cell itself.

Rapid structural analysis of purified proteins and their complexes has become increasingly common thanks to key methodological advances in cryo-electron microscopy (cryo-EM) and associated data processing software packages. In contrast, analogous structural analysis in cells via cryo-electron tomography (cryo-ET) remains challenging due to critical technical bottlenecks, including low-throughput sample preparation and imaging, and laborious data processing methods. Here, we describe the development of a rapid in situ cryo-ET sample preparation and data analysis workflow that results in the routine determination of sub-nm resolution ribosomal structures. We apply this workflow to E. coli, producing a 5.8 Å structure of the 70S ribosome from cells in less than 10 days, and we expect this workflow will be widely applicable to related bacterial samples.

Glioblastomas (GBMs) are the most lethal primary brain tumors with limited survival, even under aggressive treatments. The current therapeutics for GBMs are flawed due to the failure to accurately discriminate between normal proliferating cells and distinctive tumor cells. Mitochondria are essential to GBMs and serve as potential therapeutical targets. Here, we utilize cryo-electron tomography to quantitatively investigate nanoscale details of randomly sampled mitochondria in their native cellular context of GBM cells. Our results show that compared with cancer-free brain cells, GBM cells own more inter-mitochondrial junctions of several types for communications. Furthermore, our tomograms unveil microtubule-dependent mitochondrial nanotunnel-like bridges in the GBM cells as another inter-mitochondrial structure. These quantified inter-mitochondrial features, together with other mitochondria-organelle and intra-mitochondrial ones, are sufficient to distinguish GBM cells from cancer-free brain cells under scrutiny with predictive modeling. Our findings decipher high-resolution inter-mitochondrial structural signatures and provide clues for diagnosis and therapeutic interventions for GBM and other mitochondria-related diseases.

Determining the structure and mechanisms of all individual functional modules of cells at high molecular detail has often been seen as equal to understanding how cells work. Recent technical advances have led to a flush of high-resolution structures of various macromolecular machines, but despite this wealth of detailed information, our understanding of cellular function remains incomplete. Here, we discuss present-day limitations of structural biology and highlight novel technologies that may enable us to analyze molecular functions directly inside cells. We predict that the progression toward structural cell biology will involve a shift toward conceptualizing a 4D virtual reality of cells using digital twins. These will capture cellular segments in a highly enriched molecular detail, include dynamic changes, and facilitate simulations of molecular processes, leading to novel and experimentally testable predictions. Transferring biological questions into algorithms that learn from the existing wealth of data and explore novel solutions may ultimately unveil how cells work.

Understanding the dynamic processes involving virus structural components within host cells is crucial for comprehending viral infection, as viruses rely entirely on host cells for replication. Viral infection involves various intracellular stages, including cell entry, genome uncoating, replication, transcription and translation, assembly of new virus particles in a complex morphogenetic process, and the release of new virions from the host cell. These events are dynamic and scarce and can be obscured by other cellular processes, necessitating novel approaches for their in situ characterization. Among these methods, correlative microscopy integrates the labeling, localization, and functional characterization of events of interest through visible light microscopy, complemented by the structural insights provided by high-resolution imaging techniques. This correlative approach enables a comprehensive exploration of subcellular events within the cellular context, including those related to viral morphogenesis. This chapter provides an introduction to correlative three-dimensional imaging methods, specifically designed to study viral morphogenesis and other intracellular stages of the viral cycle under conditions closely resembling their native environment. The integration of whole-cell imaging and high-resolution structural biology techniques is emphasized as essential for unraveling the mechanisms by which viruses generate and disseminate their progeny.

Native electrospray ionization mass spectrometry (ESI-MS) has emerged as a potent tool for examining the native-like structures of macromolecular complexes. Despite its utility, the predominant "buffer" used, ammonium acetate (AmAc) with pKa values of 4.75 for acetic acid and 9.25 for ammonium, provides very little buffering capacity within the physiological pH range of 7.0-7.4. ESI-induced redox reactions alter the pH of the liquid within the ESI capillary. This can result in protein unfolding or weakening of pH-sensitive interactions. Consequently, the discovery of volatile, ESI-compatible buffers, capable of effectively maintaining pH within a physiological range, is of high importance. Here, we demonstrate that 2,2-difluoroethylamine (DFEA) and 2,2,2-trifluoroethylamine (TFEA) offer buffering capacity at physiological pH where AmAc falls short, with pKa values of 7.2 and 5.5 for the conjugate acids of DFEA and TFEA, respectively. Native ESI-MS experiments on model proteins cytochrome c and myoglobin electrosprayed with DFEA and TFEA demonstrated the preservation of noncovalent protein-ligand complexes in the gas phase. Protein stability assays and collision-induced unfolding experiments further showed that neither DFEA nor TFEA destabilized model proteins in solution or in the gas phase. Finally, we demonstrate that multisubunit protein complexes such as alcohol dehydrogenase and concanavalin A can be studied in the presence of DFEA or TFEA using native ESI-MS. Our findings establish DFEA and TFEA as new ESI-compatible neutral pH buffers that promise to bolster the use of native ESI-MS for the analysis of macromolecular complexes, particularly those sensitive to pH fluctuations.

Biological function of macromolecules is closely tied to their cellular location, as well as to interactions with other molecules within the native environment of the cell. Therefore, to obtain detailed mechanistic insights into macromolecular functionality, one of the outstanding targets for structural biology is to produce an atomic-level understanding of the cell. One structural biology technique that has already been used to directly derive atomic models of macromolecules from cells, without any additional external information, is electron cryotomography (cryoET). In this perspective article, we discuss possible routes to chart the molecular landscape of the cell by advancing cryoET imaging as well as by embedding cryoET into correlative imaging workflows.

CAD is a large, 2225 amino acid multienzymatic protein required for de novo pyrimidine biosynthesis. Pathological CAD variants cause a developmental and epileptic encephalopathy which is highly responsive to uridine supplements. CAD deficiency is difficult to diagnose because symptoms are nonspecific, there is no biomarker, and the protein has over 1000 known variants. To improve diagnosis, we assessed the pathogenicity of 20 unreported missense CAD variants using a growth complementation assay that identified 11 pathogenic variants in seven affected individuals; they would benefit from uridine treatment. We also tested nine variants previously reported as pathogenic and confirmed the damaging effect of seven. However, we reclassified two variants as likely benign based on our assay, which is consistent with their long-term follow-up with uridine. We found that several computational methods are unreliable predictors of pathogenic CAD variants, so we extended the functional assay results by studying the impact of pathogenic variants at the protein level. We focused on CAD's dihydroorotase (DHO) domain because it accumulates the largest density of damaging missense changes. The atomic-resolution structures of eight DHO pathogenic variants, combined with functional and molecular dynamics analyses, provided a comprehensive structural and functional understanding of the activity, stability, and oligomerization of CAD's DHO domain. Combining our functional and protein structural analysis can help refine clinical diagnostic workflow for CAD variants in the genomics era.

Ion activation methods carried out at gas pressures compatible with ion mobility separations are not yet widely established. This limits the analytical utility of emerging tandem-ion mobility spectrometers that conduct multiple ion mobility separations in series. The present work investigates the applicability of collision-induced dissociation (CID) at 1 to 3 mbar in a tandem-trapped ion mobility spectrometer (tandem-TIMS) to study the architecture of protein complexes. We show that CID of the homotetrameric protein complexes streptavidin (53 kDa), neutravidin (60 kDa), and concanavalin A (110 kDa) provides access to all subunits of the investigated protein complexes, including structurally informative dimers. We report on an "atypical" dissociation pathway, which for concanavalin A proceeds via symmetric partitioning of the precursor charges and produces dimers with the same charge states that were previously reported from surface induced dissociation. Our data suggest a correlation between the formation of subunits by CID in tandem-TIMS/MS, their binding strengths in the native tetramer structures, and the applied activation voltage. Ion mobility spectra of in situ-generated subunits reveal a marked structural heterogeneity inconsistent with annealing into their most stable gas phase structures. Structural transitions are observed for in situ-generated subunits that resemble the transitions reported from collision-induced unfolding of natively folded proteins. These observations indicate that some aspects of the native precursor structure is preserved in the subunits generated from disassembly of the precursor complex. We rationalize our observations by an approximately 100-fold shorter activation time scale in comparison to traditional CID in a collision cell. Finally, the approach discussed here to conduct CID at elevated pressures appears generally applicable also for other types of tandem-ion mobility spectrometers.

It is widely acknowledged that the human-associated microbial community influences host physiology, systemic health, disease progression, and even behavior. There is currently an increased interest in the oral microbiome, which occupies the entryway to much of what the human initially encounters from the environment. In addition to the dental pathology that results from a dysbiotic microbiome, microbial activity within the oral cavity exerts significant systemic effects. The composition and activity of the oral microbiome is influenced by (1) host-microbial interactions, (2) the emergence of niche-specific microbial "ecotypes," and (3) numerous microbe-microbe interactions, shaping the underlying microbial metabolic landscape. The oral streptococci are central players in the microbial activity ongoing in the oral cavity, due to their abundance and prevalence in the oral environment and the many interspecies interactions in which they participate. Streptococci are major determinants of a healthy homeostatic oral environment. The metabolic activities of oral Streptococci, particularly the metabolism involved in energy generation and regeneration of oxidative resources vary among the species and are important factors in niche-specific adaptations and intra-microbiome interactions. Here we summarize key differences among streptococcal central metabolic networks and species-specific differences in how the key glycolytic intermediates are utilized.

Native ion mobility (IM) mass spectrometry (MS) is used to probe the size, shape, and assembly of biomolecular complexes. IM-IM-MS can increase the amount of information available in structural studies by isolating subpopulations of structures for further analysis. Previously, IM-IM-MS has been implemented using the Structures for Lossless Ion Manipulations (SLIM) architecture to probe the structural stability of gas-phase protein ions. Here, a new multidimensional IM instrument constructed from SLIM devices is characterized using multiple operational modes. In this new design, modular devices are used to perform all ion manipulations, including initial accumulation, injection, separation, selection, and trapping. Using single-dimension IM, collision cross section (Ω) values are determined for a set of native-like ions. These Ω values are within 3% of those reported previously based on measurements using RF-confining drift cells. Tandem IM experiments are performed on a sample of ubiquitin ions that contains both compact and partially unfolded structures, demonstrating that this platform can isolate subpopulations of structures. Finally, additional modes of analysis, including multiplexed IM and inverse IM, are demonstrated using this platform. The ability of this platform to quickly switch between different modes of IM analysis makes it a highly flexible tool for studying protein structures and dynamics.

Proteins are essential molecular building blocks of life, responsible for most biological functions as a result of their specific molecular interactions. However, predicting their  binding  interfaces remains a challenge. In this study, we present a geometric transformer that acts directly on atomic coordinates labeled only with element names. The resulting model-the Protein Structure Transformer, PeSTo-surpasses the current state of the art in predicting protein-protein interfaces and can also predict and differentiate between interfaces involving nucleic acids, lipids, ions, and small molecules with high confidence. Its low computational cost enables processing high volumes of structural data, such as molecular dynamics ensembles allowing for the discovery of interfaces that remain otherwise inconspicuous in static experimentally solved structures. Moreover, the growing foldome provided by de novo structural predictions can be easily analyzed, providing new opportunities to uncover unexplored biology.

The investigation of macromolecular biomolecules with ion mobility mass spectrometry (IM-MS) techniques has provided substantial insights into the field of structural biology over the past two decades. An IM-MS workflow applied to a given target analyte provides mass, charge, and conformation, and all three of these can be used to discern structural information. While mass and charge are determined in mass spectrometry (MS), it is the addition of ion mobility that enables the separation of isomeric and isobaric ions and the direct elucidation of conformation, which has reaped huge benefits for structural biology. In this review, where we focus on the analysis of proteins and their complexes, we outline the typical features of an IM-MS experiment from the preparation of samples, the creation of ions, and their separation in different mobility and mass spectrometers. We describe the interpretation of ion mobility data in terms of protein conformation and how the data can be compared with data from other sources with the use of computational tools. The benefit of coupling mobility analysis to activation via collisions with gas or surfaces or photons photoactivation is detailed with reference to recent examples. And finally, we focus on insights afforded by IM-MS experiments when applied to the study of conformationally dynamic and intrinsically disordered proteins.

The Spindle Assembly Abnormal Protein 6 (SAS-6) forms dimers, which then self-assemble into rings that are critical for the nine-fold symmetry of the centriole organelle. It has recently been shown experimentally that the self-assembly of SAS-6 rings is strongly facilitated on a surface, shifting the reaction equilibrium by four orders of magnitude compared to the bulk. Moreover, a fraction of non-canonical symmetries (i.e., different from nine) was observed. In order to understand which aspects of the system are relevant to ensure efficient self-assembly and selection of the nine-fold symmetry, we have performed Brownian dynamics computer simulation with patchy particles and then compared our results with the experimental ones. Adsorption onto the surface was simulated by a grand canonical Monte Carlo procedure and random sequential adsorption kinetics. Furthermore, self-assembly was described by Langevin equations with hydrodynamic mobility matrices. We find that as long as the interaction energies are weak, the assembly kinetics can be described well by coagulation-fragmentation equations in the reaction-limited approximation. By contrast, larger interaction energies lead to kinetic trapping and diffusion-limited assembly. We find that the selection of nine-fold symmetry requires a small value for the angular interaction range. These predictions are confirmed by the experimentally observed reaction constant and angle fluctuations. Overall, our simulations suggest that the SAS-6 system works at the crossover between a relatively weak binding energy that avoids kinetic trapping and a small angular range that favors the nine-fold symmetry.

Faster-growing cells must synthesize proteins more quickly. Increased ribosome abundance only partly accounts for increases in total protein synthesis rates. The productivity of individual ribosomes must increase too, almost doubling by an unknown mechanism. Prior models point to diffusive transport as a limiting factor but raise a paradox: faster-growing cells are more crowded, yet crowding slows diffusion. We suspected that physical crowding, transport, and stoichiometry, considered together, might reveal a more nuanced explanation. To investigate, we built a first-principles physics-based model of Escherichia coli cytoplasm in which Brownian motion and diffusion arise directly from physical interactions between individual molecules of finite size, density, and physiological abundance. Using our microscopically detailed model, we predicted that physical transport of individual ternary complexes accounts for ~80% of translation elongation latency. We also found that volumetric crowding increases during faster growth even as cytoplasmic mass density remains relatively constant. Despite slowed diffusion, we predicted that improved proximity between ternary complexes and ribosomes wins out, illustrating a simple physics-based mechanism for how individual elongating ribosomes become more productive. We speculate that crowding imposes a physical limit on growth rate and undergirds cellular behavior more broadly. Unfitted colloidal-scale modeling offers systems biology a complementary "physics engine" for exploring how cellular-scale behaviors arise from physical transport and reactions among individual molecules. IMPORTANCE Ribosomes are the factories in cells that synthesize proteins. When cells grow faster, there are not enough ribosomes to keep up with the demand for faster protein synthesis without individual ribosomes becoming more productive. Yet, faster-growing cells are more crowded, seemingly making it harder for each ribosome to do its work. Our computational model of the physics of translation elongation reveals the underlying mechanism for how individual ribosomes become more productive: proximity and stoichiometry of translation molecules overcome crowding. Our model also suggests a universal physical limitation of cell growth rates.

The baculovirus expression vector systems (BEVS) have been widely used for the recombinant production of proteins in insect cells and with high insert capacity. However, baculovirus does not replicate in mammalian cells; thus, the BacMam system, a heterogenous expression system that can infect certain mammalian cells, was developed. Since then, the BacMam system has enabled transgene expression via mammalian-specific promoters in human cells, and later, the MultiBacMam system enabled multi-protein expression in mammalian cells. In this review, we will cover the continual development of the BEVS in combination with CRPISPR-Cas technologies to drive genome-editing in mammalian cells. Additionally, we highlight the use of CRISPR-Cas in glycoengineering to potentially produce a new class of glycoprotein medicines in insect cells. Moreover, we anticipate CRISPR-Cas9 to play a crucial role in the development of protein expression systems, gene therapy, and advancing genome engineering applications in the future.

Improvements in cryo-electron tomography sample preparation, electron-microscopy instrumentations, and image processing algorithms have advanced the structural analysis of macromolecules in situ. Beyond such analyses of individual macromolecules, the study of their interactions with functionally related neighbors in crowded cellular habitats, i.e. 'molecular sociology', is of fundamental importance in biology. Here we present a NEighboring Molecule TOpology Clustering (NEMO-TOC) algorithm. We optimized this algorithm for the detection and profiling of polyribosomes, which play both constitutive and regulatory roles in gene expression. Our results suggest a model where polysomes are formed by connecting multiple nonstochastic blocks, in which translation is likely synchronized.

In-cell NMR spectroscopy is a powerful tool to investigate protein behavior in physiologically relevant environments. Although proven valuable for disordered proteins, we show that in commonly used ¹ H-¹⁵ N HSQC spectra of globular proteins, interactions with cellular components often broaden resonances beyond detection. This contrasts ¹⁹ F spectra in mammalian cells, in which signals are readily observed. Using several proteins, we demonstrate that surface charges and interaction with cellular binding partners modulate linewidths and resonance frequencies. Importantly, we establish that ¹⁹ F paramagnetic relaxation enhancements using stable, rigid Ln(III) chelate pendants, attached via non-reducible thioether bonds, provide an effective means to obtain accurate distances for assessing protein conformations in the cellular milieu.

Protein-protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein-protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein-protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein-protein interface.

Tubulin is a conserved protein that polymerizes into different forms of filamentous structures in Toxoplasma gondii, an obligate intracellular parasite in the phylum Apicomplexa. Two key tubulin-containing cytoskeletal components are subpellicular microtubules (SPMTs) and conoid fibrils (CFs). The SPMTs help maintain shape and gliding motility, while the CFs are implicated in invasion. Here, we use cryogenic electron tomography to determine the molecular structures of the SPMTs and CFs in vitrified intact and detergent-extracted parasites. Subvolume densities from detergent-extracted parasites yielded averaged density maps at subnanometer resolutions, and these were related back to their architecture in situ. An intralumenal spiral lines the interior of the 13-protofilament SPMTs, revealing a preferred orientation of these microtubules relative to the parasite's long axis. Each CF is composed of nine tubulin protofilaments that display a comma-shaped cross-section, plus additional associated components. Conoid protrusion, a crucial step in invasion, is associated with an altered pitch of each CF. The use of basic building blocks of protofilaments and different accessory proteins in one organism illustrates the versatility of tubulin to form two distinct types of assemblies, SPMTs and CFs.

Cryo-electron tomography is uniquely suited to provide insights into the molecular architecture of cells and tissue in the native state. While frozen hydrated specimens tolerate sufficient electron doses to distinguish different types of particles in a tomogram, the accumulating beam damage does not allow resolving their detailed molecular structure individually. Statistical methods for subtomogram averaging and classification that coherently enhance the signal of particles corresponding to copies of the same type of macromolecular allow obtaining much higher resolution insights into macromolecules. Here, I review the developments in subtomogram analysis at Wolfgang Baumeister's laboratory that make the dream of structural biology in the native cell become reality.

Predicting and designing systems with dynamic self-assembly properties in a spatiotemporal fashion is an important research area across disciplines ranging from understanding the fundamental non-equilibrium features of life to the fabrication of next-generation materials with life-like properties. Herein, we demonstrate a spatiotemporal dynamics pattern in the self-assembly behavior of a surfactant from an unorganized assembly, induced by adenosine triphosphate (ATP) and enzymes responsible for the degradation or conversion of ATP. We report the different behavior of two enzymes, alkaline phosphatase (ALP) and hexokinase (HK), towards adenosine triphosphate (ATP)-driven surfactant assembly, which also results in contrasting spatiotemporal dynamic assembly behavior. Here, ALP acts antagonistically, resulting in transient self-assemblies, whereas HK shows agonistic action with the ability to sustain the assemblies. This dynamic assembly behavior was then used to program the time-dependent emergence of a self-assembled structure in a two-dimensional space by maintaining concentration gradients of the enzymes and surfactant at different locations, demonstrating a new route for obtaining 'spatial' organizational adaptability in a self-organized system of interacting components for the incorporation of programmed functionality.

Emergence of new viral agents is driven by evolution of interactions between viral proteins and host targets. For instance, increased infectivity of SARS-CoV-2 compared to SARS-CoV-1 arose in part through rapid evolution along the interface between the spike protein and its human receptor ACE2, leading to increased binding affinity. To facilitate broader exploration of how pathogen-host interactions might impact transmission and virulence in the ongoing COVID-19 pandemic, we performed state-of-the-art interface prediction followed by molecular docking to construct a three-dimensional structural interactome between SARS-CoV-2 and human. We additionally carried out downstream meta-analyses to investigate enrichment of sequence divergence between SARS-CoV-1 and SARS-CoV-2 or human population variants along viral-human protein-interaction interfaces, predict changes in binding affinity by these mutations/variants and further prioritize drug repurposing candidates predicted to competitively bind human targets. We believe this resource ( http://3D-SARS2.yulab.org ) will aid in development and testing of informed hypotheses for SARS-CoV-2 etiology and treatments.

Recent advancements place a comprehensive catalog of protein structure, oligomeric state, sequence, and modification status tentatively within reach, thus providing an unprecedented roadmap to therapies for many human diseases. To achieve this goal, revolutionary technologies capable of bridging key gaps in our ability to simultaneously measure protein composition and structure must be developed. Much of the current progress in this area has been catalyzed by mass spectrometry (MS) tools, which have become an indispensable resource for interrogating the structural proteome. For example, methods associated with native proteomics seek to comprehensively capture and quantify the endogenous assembly states for all proteins within an organism. Such technologies have often been partnered with ion mobility (IM) separation, from which collision cross section (CCS) information can be rapidly extracted to provide protein size information. IM technologies are also being developed that utilize CCS values to enhance the confidence of protein identification workflows derived from liquid chromatography-IM-MS analyses of enzymatically produced peptide mixtures. Such parallel advancements in technology beg the question: can CCS values prove similarly useful for the identification of intact proteins and their complexes in native proteomics? In this perspective, I examine current evidence and technology trends to explore the promise and limitations of such CCS information for the comprehensive analysis of multiprotein complexes from cellular mixtures.

Self-assembly of supramolecular complexes such as viral capsids occurs prominently in nature. Nonetheless, the mechanisms underlying these processes remain poorly understood. Here, we uncover the assembly pathway of hepatitis B virus (HBV), applying fluorescence optical tweezers and high-speed atomic force microscopy. This allows tracking the assembly process in real time with single-molecule resolution. Our results identify a specific, contact-rich pentameric arrangement of HBV capsid proteins as a key on-path assembly intermediate and reveal the energy balance of the self-assembly process. Real-time nucleic acid packaging experiments show that a free energy change of ~1.4 k_BT per condensed nucleotide is used to drive protein oligomerization. The finding that HBV assembly occurs via contact-rich energy minima has implications for our understanding of the assembly of HBV and other viruses and also for the development of new antiviral strategies and the rational design of self-assembling nanomaterials.

The predictive power of simulation has become embedded in the infrastructure of modern economies. Computer-aided design is ubiquitous throughout industry. In aeronautical engineering, built infrastructure and materials manufacturing, simulations are routinely used to compute the performance of potential designs before construction. The ability to predict the behaviour of products is a driver of innovation by reducing the cost barrier to new designs, but also because radically novel ideas can be piloted with relatively little risk. Accurate weather forecasting is essential to guide domestic and military flight paths, and therefore the underpinning simulations are critical enough to have implications for national security. However, in the pharmaceutical and biotechnological industries, the application of computer simulations remains limited by the capabilities of the technology with respect to the complexity of molecular biology and human physiology. Over the last 30 years, molecular-modelling tools have gradually gained a degree of acceptance in the pharmaceutical industry. Drug discovery has begun to benefit from physics-based simulations. While such simulations have great potential for improved molecular design, much scepticism remains about their value. The motivations for such reservations in industry and areas where simulations show promise for efficiency gains in preclinical research are discussed. In this, the first of two complementary papers, the scientific and technical progress that needs to be made to improve the predictive power of biomolecular simulations, and how this might be achieved, is firstly discussed (Part 1). In Part 2, the status of computer simulations in pharma is contrasted with aerodynamics modelling and weather forecasting, and comments are made on the cultural changes needed for equivalent computational technologies to become integrated into life-science industries.

The de Rham-Hodge theory is a landmark of the 20^th Century's mathematics and has had a great impact on mathematics, physics, computer science, and engineering. This work introduces an evolutionary de Rham-Hodge method to provide a unified paradigm for the multiscale geometric and topological analysis of evolving manifolds constructed from a filtration, which induces a family of evolutionary de Rham complexes. While the present method can be easily applied to close manifolds, the emphasis is given to more challenging compact manifolds with 2-manifold boundaries, which require appropriate analysis and treatment of boundary conditions on differential forms to maintain proper topological properties. Three sets of unique evolutionary Hodge Laplacians are proposed to generate three sets of topology-preserving singular spectra, for which the multiplicities of zero eigenvalues correspond to exactly the persistent Betti numbers of dimensions 0, 1 and 2. Additionally, three sets of non-zero eigenvalues further reveal both topological persistence and geometric progression during the manifold evolution. Extensive numerical experiments are carried out via the discrete exterior calculus to demonstrate the potential of the proposed paradigm for data representation and shape analysis of both point cloud data and density maps. To demonstrate the utility of the proposed method, the application is considered to the protein B-factor predictions of a few challenging cases for which existing biophysical models break down.

Gene regulation requires the dynamic coordination of hundreds of regulatory factors at precise genomic and RNA targets. Although many regulatory factors have specific affinity for their nucleic acid targets, molecular diffusion and affinity models alone cannot explain many of the quantitative features of gene regulation in the nucleus. One emerging explanation for these quantitative properties is that DNA, RNA and proteins organize within precise, 3D compartments in the nucleus to concentrate groups of functionally related molecules. Recently, nucleic acids and proteins involved in many important nuclear processes have been shown to engage in cooperative interactions, which lead to the formation of condensates that partition the nucleus. In this Review, we discuss an emerging perspective of gene regulation, which moves away from classic models of stoichiometric interactions towards an understanding of how spatial compartmentalization can lead to non-stoichiometric molecular interactions and non-linear regulatory behaviours. We describe key mechanisms of nuclear compartment formation, including emerging roles for non-coding RNAs in facilitating their formation, and discuss the functional role of nuclear compartments in transcription regulation, co-transcriptional and post-transcriptional RNA processing, and higher-order chromatin regulation. More generally, we discuss how compartmentalization may explain important quantitative aspects of gene regulation.

Traditionally, structural biologists approach the complexity of cellular proteomes in a reductionist manner. Proteomes are fractionated, their molecular components purified and studied one-by-one using the experimental methods for structure determination at their disposal. Visual proteomics aims at obtaining a holistic picture of cellular proteomes by studying them in situ, ideally in unperturbed cellular environments. The method that enables doing this at highest resolution is cryo-electron tomography. It allows to visualize cellular landscapes with molecular resolution generating maps or atlases revealing the interaction networks which underlie cellular functions in health and in disease states. Current implementations of cryo ET do not yet realize the full potential of the method in terms of resolution and interpretability. To this end, further improvements in technology and methodology are needed. This review describes the state of the art as well as measures which we expect will help overcoming current limitations.

The baculovirus expression vector system (BEVS) delivers high yield heterologous protein expression and is widely used in academic and industrial R&D. The proteins produced enable many applications including structure/function analysis, drug screening and manufacture of protein therapeutics. Vital cellular functions are controlled by multi-protein complexes, MultiBac, a BEVS specifically designed for heterologous multigene delivery and expression, has unlocked many of these machines to atomic resolution studies. Baculovirus can accommodate very large foreign DNA cargo for faithful delivery into a target host cell, tissue or organism. Engineered MultiBac variants exploit this valuable feature for delivery of customized multifunctional DNA circuitry in mammalian cells and for production of virus-like particles for vaccines manufacture. Here, latest developments and applications of the MultiBac system are reviewed.

Characterizing the three-dimensional structure of macromolecules is central to understanding their function. Traditionally, structures of proteins and their complexes have been determined using experimental techniques such as X-ray crystallography, NMR, or cryo-electron microscopy-applied individually or in an integrative manner. Meanwhile, however, computational methods for protein structure prediction have been improving their accuracy, gradually, then suddenly, with the breakthrough advance by AlphaFold2, whose models of monomeric proteins are often as accurate as experimental structures. This breakthrough foreshadows a new era of computational methods that can build accurate models for most monomeric proteins. Here, we envision how such accurate modeling methods can combine with experimental structural biology techniques, enhancing integrative structural biology. We highlight the challenges that arise when considering multiple structural conformations, protein complexes, and polymorphic assemblies. These challenges will motivate further developments, both in modeling programs and in methods to solve experimental structures, towards better and quicker investigation of structure-function relationships.

The modeling of protein assemblies at the atomic level remains a central issue in structural biology, as protein interactions play a key role in numerous cellular processes. This problem is traditionally addressed using docking tools, where the quality of the models is based on their similarity to a single reference experimental structure. However, using a static reference does not take into account the dynamic quality of the protein interface. Here, we used all-atom classical Molecular Dynamics simulations to investigate the stability of the reference interface for three complexes that previously served as targets in the CAPRI competition. For each one of these targets, we also ran MD simulations for ten models that are distributed over the High, Medium and Acceptable accuracy categories. To assess the quality of these models from a dynamic perspective, we set up new criteria which take into account the stability of the reference experimental protein interface. We show that, when the protein interfaces are allowed to evolve along time, the original ranking based on the static CAPRI criteria no longer holds as over 50% of the docking models undergo a category change (which can be either toward a better or a lower accuracy group) when reassessing their quality using dynamic information.

The study of enzymes from extremophiles arouses interest in Protein Science because of the amazing solutions these proteins adopt to cope with extreme conditions. Recently solved, the structure of the psychrophilic acyl aminoacyl peptidase from Sporosarcina psychrophila (SpAAP) pinpoints a mechanism of dimerization unusual for this class of enzymes. The quaternary structure of SpAAP relies on a domain-swapping mechanism involving the N-terminal A1 helix. The A1 helix is conserved among homologous mesophilic and psychrophilic proteins and its deletion causes the formation of a monomeric enzyme, which is inactive and prone to aggregate. Here, we investigate the dimerization mechanism of SpAAP through the analysis of chimeric heterodimers where a protomer lacking the A1 helix combines with a protomer carrying the inactivated catalytic site. Our results indicate that the two active sites are independent, and that a single A1 helix is sufficient to partially recover the quaternary structure and the activity of chimeric heterodimers. Since catalytically competent protomers are unstable and inactive unless they dimerize, SpAAP reveals as an "obligomer" for both structural and functional reasons.