Capturing protein communities by structural proteomics in a thermophilic eukaryote

Advances in spatial proteomics: Mapping proteome architecture from protein complexes to subcellular localizations

Proteins are responsible for most intracellular functions, which they perform as part of higher-order molecular complexes, located within defined subcellular niches. Localization is both dynamic and context specific and mislocalization underlies a multitude of diseases. It is thus vital to be able to measure the components of higher-order protein complexes and their subcellular location dynamically in order to fully understand cell biological processes. Here, we review the current range of highly complementary approaches that determine the subcellular organization of the proteome. We discuss the scale and resolution at which these approaches are best employed and the caveats that should be taken into consideration when applying them. We also look to the future and emerging technologies that are paving the way for a more comprehensive understanding of the functional roles of protein isoforms, which is essential for unraveling the complexities of cell biology and the development of disease treatments.

Disorder-to-order active site capping regulates the rate-limiting step of the inositol pathway

Myo-inositol-1-phosphate synthase (MIPS) catalyzes the NAD+-dependent isomerization of glucose-6-phosphate (G6P) into inositol-1-phosphate (IMP), controlling the rate-limiting step of the inositol pathway. Previous structural studies focused on the detailed molecular mechanism, neglecting large-scale conformational changes that drive the function of this 240 kDa homotetrameric complex. In this study, we identified the active, endogenous MIPS in cell extracts from the thermophilic fungus Thermochaetoides thermophila. By resolving the native structure at 2.48 Å (FSC = 0.143), we revealed a fully populated active site. Utilizing 3D variability analysis, we uncovered conformational states of MIPS, enabling us to directly visualize an order-to-disorder transition at its catalytic center. An acyclic intermediate of G6P occupied the active site in two out of the three conformational states, indicating a catalytic mechanism where electrostatic stabilization of high-energy intermediates plays a crucial role. Examination of all isomerases with known structures revealed similar fluctuations in secondary structure within their active sites. Based on these findings, we established a conformational selection model that governs substrate binding and eventually inositol availability. In particular, the ground state of MIPS demonstrates structural configurations regardless of substrate binding, a pattern observed across various isomerases. These findings contribute to the understanding of MIPS structure-based function, serving as a template for future studies targeting regulation and potential therapeutic applications.

Chemical cross-linking and mass spectrometry enabled systems-level structural biology

Structural information on protein-protein interactions (PPIs) is essential for improved understanding of regulatory interactome networks that confer various physiological and pathological responses. Additionally, maladaptive PPIs constitute desirable therapeutic targets due to inherently high disease state specificity. Recent advances in chemical cross-linking strategies coupled with mass spectrometry (XL-MS) have positioned XL-MS as a promising technology to not only elucidate the molecular architecture of individual protein assemblies, but also to characterize proteome-wide PPI networks. Moreover, quantitative in vivo XL-MS provides a new capability for the visualization of cellular interactome dynamics elicited by drug treatments, disease states, or aging effects. The emerging field of XL-MS based complexomics enables unique insights on protein moonlighting and protein complex remodeling. These techniques provide complimentary information necessary for in-depth structural interactome studies to better comprehend how PPIs mediate function in living systems.

Delineating organizational principles of the endogenous L-A virus by cryo-EM and computational analysis of native cell extracts

The high abundance of most viruses in infected host cells benefits their structural characterization. However, endogenous viruses are present in low copy numbers and are therefore challenging to investigate. Here, we retrieve cell extracts enriched with an endogenous virus, the yeast L-A virus. The determined cryo-EM structure discloses capsid-stabilizing cation-π stacking, widespread across viruses and within the Totiviridae, and an interplay of non-covalent interactions from ten distinct capsomere interfaces. The capsid-embedded mRNA decapping active site trench is supported by a constricting movement of two flexible opposite-facing loops. tRNA-loaded polysomes and other biomacromolecules, presumably mRNA, are found in virus proximity within the cell extract. Mature viruses participate in larger viral communities resembling their rare in-cell equivalents in terms of size, composition, and inter-virus distances. Our results collectively describe a 3D-architecture of a viral milieu, opening the door to cell-extract-based high-resolution structural virology.

Bridging structural and cell biology with cryo-electron microscopy

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.

Peripheral Linker Mediates Acyl Carrier Protein's Recognition of Dehydratase and Stabilizes Type-I Mycobacterium tuberculosis Fatty Acid Synthase

Incomplete structural details of Mycobacterium tuberculosis (Mtb) fatty acid synthase-I (FAS-I) at near-atomic resolution have limited our understanding of the shuttling mechanism of its mobile acyl carrier protein (ACP). Here, we have performed atomistic molecular dynamics simulation of Mtb FAS-I with a homology-modeled structure of ACP stalled at dehydratase (DH) and identified key residues that mediate anchoring of the recognition helix of ACP near DH. The observed distance between catalytic residues of ACP and DH agrees with that reported for fungal FAS-I. Further, the conformation of the peripheral linker is found to be crucial in stabilizing ACP near DH. Correlated interdomain motion is observed between DH, enoyl reductase, and malonyl/palmitoyl transferase, consistent with prior experimental reports of fungal and Mtb FAS-I.

DeepSLICEM: Clustering CryoEM particles using deep image and similarity graph representations

Finding the 3D structure of proteins and their complexes has several applications, such as developing vaccines that target viral proteins effectively. Methods such as cryogenic electron microscopy (cryo-EM) have improved in their ability to capture high-resolution images, and when applied to a purified sample containing copies of a macromolecule, they can be used to produce a high-quality snapshot of different 2D orientations of the macromolecule, which can be combined to reconstruct its 3D structure. Instead of purifying a sample so that it contains only one macromolecule, a process that can be difficult, time-consuming, and expensive, a cell sample containing multiple particles can be photographed directly and separated into its constituent particles using computational methods. Previous work, SLICEM, has separated 2D projection images of different particles into their respective groups using 2 methods, clustering a graph with edges weighted by pairwise similarities of common lines of the 2D projections. In this work, we develop DeepSLICEM, a pipeline that clusters rich representations of 2D projections, obtained by combining graphical features from a similarity graph based on common lines, with additional image features extracted from a convolutional neural network. DeepSLICEM explores 6 pretrained convolutional neural networks and one supervised Siamese CNN for image representation, 10 pretrained deep graph neural networks for similarity graph node representations, and 4 methods for clustering, along with 8 methods for directly clustering the similarity graph. On 6 synthetic and experimental datasets, the DeepSLICEM pipeline finds 92 method combinations achieving better clustering accuracy than previous methods from SLICEM. Thus, in this paper, we demonstrate that deep neural networks have great potential for accurately separating mixtures of 2D projections of different macromolecules computationally.

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

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

Enabling cryo-EM density interpretation from yeast native cell extracts by proteomics data and AlphaFold structures

In the cellular context, proteins participate in communities to perform their function. The detection and identification of these communities as well as in-community interactions has long been the subject of investigation, mainly through proteomics analysis with mass spectrometry. With the advent of cryogenic electron microscopy and the "resolution revolution," their visualization has recently been made possible, even in complex, native samples. The advances in both fields have resulted in the generation of large amounts of data, whose analysis requires advanced computation, often employing machine learning approaches to reach the desired outcome. In this work, we first performed a robust proteomics analysis of mass spectrometry (MS) data derived from a yeast native cell extract and used this information to identify protein communities and inter-protein interactions. Cryo-EM analysis of the cell extract provided a reconstruction of a biomolecule at medium resolution (∼8 Å (FSC = 0.143)). Utilizing MS-derived proteomics data and systematic fitting of AlphaFold-predicted atomic models, this density was assigned to the 2.6 MDa complex of yeast fatty acid synthase. Our proposed workflow identifies protein complexes in native cell extracts from Saccharomyces cerevisiae by combining proteomics, cryo-EM, and AI-guided protein structure prediction.

Identification and characterization of sugar-regulated promoters in Chaetomium thermophilum

The thermophilic fungus Chaetomium thermophilum has been used extensively for biochemical and high-resolution structural studies of protein complexes. However, subsequent functional analyses of these assemblies have been hindered owing to the lack of genetic tools compatible with this thermophile, which are typically suited to other mesophilic eukaryotic model organisms, in particular the yeast Saccharomyces cerevisiae. Hence, we aimed to find genes from C. thermophilum that are expressed under the control of different sugars and examine their associated 5' untranslated regions as promoters responsible for sugar-regulated gene expression. To identify sugar-regulated promoters in C. thermophilum, we performed comparative xylose- versus glucose-dependent gene expression studies, which uncovered a number of enzymes with induced expression in the presence of xylose but repressed expression in glucose-supplemented media. Subsequently, we cloned the promoters of the two most stringently regulated genes, the xylosidase-like gene (XYL) and xylitol dehydrogenase (XDH), obtained from this genome-wide analysis in front of a thermostable yellow fluorescent protein (YFP) reporter. With this, we demonstrated xylose-dependent YFP expression by both Western blotting and live-cell imaging fluorescence microscopy. Prompted by these results, we expressed the C. thermophilum orthologue of a well-characterized dominant-negative ribosome assembly factor mutant, under the control of the XDH promoter, which allowed us to induce a nuclear export defect on the pre-60S subunit when C. thermophilum cells were grown in xylose- but not glucose-containing medium. Altogether, our study identified xylose-regulatable promoters in C. thermophilum, which might facilitate functional studies of genes of interest in this thermophilic eukaryotic model organism.

High-resolution structural-omics of human liver enzymes

We applied raw human liver microsome lysate to a holey carbon grid and used cryo-electron microscopy (cryo-EM) to define its composition. From this sample we identified and simultaneously determined high-resolution structural information for ten unique human liver enzymes involved in diverse cellular processes. Notably, we determined the structure of the endoplasmic bifunctional protein H6PD, where the N- and C-terminal domains independently possess glucose-6-phosphate dehydrogenase and 6-phosphogluconolactonase enzymatic activity, respectively. We also obtained the structure of heterodimeric human GANAB, an ER glycoprotein quality-control machinery that contains a catalytic α subunit and a noncatalytic β subunit. In addition, we observed a decameric peroxidase, PRDX4, which directly contacts a disulfide isomerase-related protein, ERp46. Structural data suggest that several glycosylations, bound endogenous compounds, and ions associate with these human liver enzymes. These results highlight the importance of cryo-EM in facilitating the elucidation of human organ proteomics at the atomic level.

Structural biology of an organ

Su et al.1 use a build-and-retrieve approach to both identify and determine structures of ten macromolecular machines in the human liver. The authors' method will launch researchers forward in understanding the structural biology of the cell (or organ).

Structural analysis of an endogenous 4-megadalton succinyl-CoA-generating metabolon

The oxoglutarate dehydrogenase complex (OGDHc) participates in the tricarboxylic acid cycle and, in a multi-step reaction, decarboxylates α-ketoglutarate, transfers succinyl to CoA, and reduces NAD+. Due to its pivotal role in metabolism, OGDHc enzymatic components have been studied in isolation; however, their interactions within the endogenous OGDHc remain elusive. Here, we discern the organization of a thermophilic, eukaryotic, native OGDHc in its active state. By combining biochemical, biophysical, and bioinformatic methods, we resolve its composition, 3D architecture, and molecular function at 3.35 Å resolution. We further report the high-resolution cryo-EM structure of the OGDHc core (E2o), which displays various structural adaptations. These include hydrogen bonding patterns confining interactions of OGDHc participating enzymes (E1o-E2o-E3), electrostatic tunneling that drives inter-subunit communication, and the presence of a flexible subunit (E3BPo), connecting E2o and E3. This multi-scale analysis of a succinyl-CoA-producing native cell extract provides a blueprint for structure-function studies of complex mixtures of medical and biotechnological value.

Convolutional networks for supervised mining of molecular patterns within cellular context

Cryo-electron tomograms capture a wealth of structural information on the molecular constituents of cells and tissues. We present DeePiCt (deep picker in context), an open-source deep-learning framework for supervised segmentation and macromolecular complex localization in cryo-electron tomography. To train and benchmark DeePiCt on experimental data, we comprehensively annotated 20 tomograms of Schizosaccharomyces pombe for ribosomes, fatty acid synthases, membranes, nuclear pore complexes, organelles, and cytosol. By comparing DeePiCt to state-of-the-art approaches on this dataset, we show its unique ability to identify low-abundance and low-density complexes. We use DeePiCt to study compositionally distinct subpopulations of cellular ribosomes, with emphasis on their contextual association with mitochondria and the endoplasmic reticulum. Finally, applying pre-trained networks to a HeLa cell tomogram demonstrates that DeePiCt achieves high-quality predictions in unseen datasets from different biological species in a matter of minutes. The comprehensively annotated experimental data and pre-trained networks are provided for immediate use by the community.

Mono- and Intralink Filter (Mi-Filter) To Reduce False Identifications in Cross-Linking Mass Spectrometry Data

Cross-linking mass spectrometry (XL-MS) has become an indispensable tool for the emerging field of systems structural biology over the recent years. However, the confidence in individual protein-protein interactions (PPIs) depends on the correct assessment of individual inter-protein cross-links. In this article, we describe a mono- and intralink filter (mi-filter) that is applicable to any kind of cross-linking data and workflow. It stipulates that only proteins for which at least one monolink or intra-protein cross-link has been identified within a given data set are considered for an inter-protein cross-link and therefore participate in a PPI. We show that this simple and intuitive filter has a dramatic effect on different types of cross-linking data ranging from individual protein complexes over medium-complexity affinity enrichments to proteome-wide cell lysates and significantly reduces the number of false-positive identifications for inter-protein links in all these types of XL-MS data.

Cross-linking of the endolysosomal system reveals potential flotillin structures and cargo

Lysosomes are well-established as the main cellular organelles for the degradation of macromolecules and emerging as regulatory centers of metabolism. They are of crucial importance for cellular homeostasis, which is exemplified by a plethora of disorders related to alterations in lysosomal function. In this context, protein complexes play a decisive role, regulating not only metabolic lysosomal processes but also lysosome biogenesis, transport, and interaction with other organelles. Using cross-linking mass spectrometry, we analyze lysosomes and early endosomes. Based on the identification of 5376 cross-links, we investigate protein-protein interactions and structures of lysosome- and endosome-related proteins. In particular, we present evidence for a tetrameric assembly of the lysosomal hydrolase PPT1 and a heterodimeric structure of FLOT1/FLOT2 at lysosomes and early endosomes. For FLOT1-/FLOT2-positive early endosomes, we identify >300 putative cargo proteins and confirm eleven substrates for flotillin-dependent endocytosis, including the latrophilin family of adhesion G protein-coupled receptors.

Artificial Intelligence in Cryo-Electron Microscopy

Cryo-electron microscopy (cryo-EM) has become an unrivaled tool for determining the structure of macromolecular complexes. The biological function of macromolecular complexes is inextricably tied to the flexibility of these complexes. Single particle cryo-EM can reveal the conformational heterogeneity of a biochemically pure sample, leading to well-founded mechanistic hypotheses about the roles these complexes play in biology. However, the processing of increasingly large, complex datasets using traditional data processing strategies is exceedingly expensive in both user time and computational resources. Current innovations in data processing capitalize on artificial intelligence (AI) to improve the efficiency of data analysis and validation. Here, we review new tools that use AI to automate the data analysis steps of particle picking, 3D map reconstruction, and local resolution determination. We discuss how the application of AI moves the field forward, and what obstacles remain. We also introduce potential future applications of AI to use cryo-EM in understanding protein communities in cells.

The protein organization of a red blood cell

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

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.

An AI-assisted cryo-EM pipeline for structural studies of cellular extracts

Proteins, the building blocks of life, often form large assemblies to perform their function but are traditionally studied separately in structural biology. In this issue of Structure, Skalidis et al. (2022) present a workflow to identify members of intact protein communities and solve their structures de novo to near-atomic resolution.

Comparative Network Biology Discovers Protein Complexes That Underline Cellular Differentiation in Anabaena sp

The filamentous cyanobacterium Anabaena sp. PCC 7120 can differentiate into heterocysts to fix atmospheric nitrogen. During cell differentiation, cellular morphology and gene expression undergo a series of significant changes. To uncover the mechanisms responsible for these alterations, we built protein–protein interaction (PPI) networks for these two cell types by cofractionation coupled with mass spectrometry. We predicted 280 and 215 protein complexes, with 6322 and 2791 high-confidence PPIs in vegetative cells and heterocysts, respectively. Most of the proteins in both types of cells presented similar elution profiles, whereas the elution peaks of 438 proteins showed significant changes. We observed that some well-known complexes recruited new members in heterocysts, such as ribosomes, diflavin flavoprotein, and cytochrome c oxidase. Photosynthetic complexes, including photosystem I, photosystem II, and phycobilisome, remained in both vegetative cells and heterocysts for electron transfer and energy generation. Besides that, PPI data also reveal new functions of proteins. For example, the hypothetical protein Alr4359 was found to interact with FraH and Alr4119 in heterocysts and was located on heterocyst poles, thereby influencing the diazotrophic growth of filaments. The overexpression of Alr4359 suspended heterocyst formation and altered the pigment composition and filament length. This work demonstrates the differences in protein assemblies and provides insight into physiological regulation during cell differentiation.

•

PPIs in two types of cells of Anabaena sp. 7120 were systematically identified.

•

10,302 and 8557 high-confidence PPIs were obtained and over 80% were novel.

•

About 438 proteins showed significant changes in vegetative cells and heterocysts.

•

Protein Alr4359 was found to influence the diazotrophic growth of filaments.

Complexome Profiling-Exploring Mitochondrial Protein Complexes in Health and Disease

Complexome profiling (CP) is a state-of-the-art approach that combines separation of native proteins by electrophoresis, size exclusion chromatography or density gradient centrifugation with tandem mass spectrometry identification and quantification. Resulting data are computationally clustered to visualize the inventory, abundance and arrangement of multiprotein complexes in a biological sample. Since its formal introduction a decade ago, this method has been mostly applied to explore not only the composition and abundance of mitochondrial oxidative phosphorylation (OXPHOS) complexes in several species but also to identify novel protein interactors involved in their assembly, maintenance and functions. Besides, complexome profiling has been utilized to study the dynamics of OXPHOS complexes, as well as the impact of an increasing number of mutations leading to mitochondrial disorders or rearrangements of the whole mitochondrial complexome. Here, we summarize the major findings obtained by this approach; emphasize its advantages and current limitations; discuss multiple examples on how this tool could be applied to further investigate pathophysiological mechanisms and comment on the latest advances and opportunity areas to keep developing this methodology.

Label-free visual proteomics: Coupling MS- and EM-based approaches in structural biology

Combining diverse experimental structural and interactomic methods allows for the construction of comprehensible molecular encyclopedias of biological systems. Typically, this involves merging several independent approaches that provide complementary structural and functional information from multiple perspectives and at different resolution ranges. A particularly potent combination lies in coupling structural information from cryoelectron microscopy or tomography (cryo-EM or cryo-ET) with interactomic and structural information from mass spectrometry (MS)-based structural proteomics. Cryo-EM/ET allows for sub-nanometer visualization of biological specimens in purified and near-native states, while MS provides bioanalytical information for proteins and protein complexes without introducing additional labels. Here we highlight recent achievements in protein structure and interactome determination using cryo-EM/ET that benefit from additional MS analysis. We also give our perspective on how combining cryo-EM/ET and MS will continue bridging gaps between molecular and cellular studies by capturing and describing 3D snapshots of proteomes and interactomes.

Leveraging crosslinking mass spectrometry in structural and cell biology

Crosslinking mass spectrometry (crosslinking-MS) is a versatile tool providing structural insights into protein conformation and protein-protein interactions. Its medium-resolution residue-residue distance restraints have been used to validate protein structures proposed by other methods and have helped derive models of protein complexes by integrative structural biology approaches. The use of crosslinking-MS in integrative approaches is underpinned by progress in estimating error rates in crosslinking-MS data and in combining these data with other information. The flexible and high-throughput nature of crosslinking-MS has allowed it to complement the ongoing resolution revolution in electron microscopy by providing system-wide residue-residue distance restraints, especially for flexible regions or systems. Here, we review how crosslinking-MS information has been leveraged in structural model validation and integrative modeling. Crosslinking-MS has also been a key technology for cell biology studies and structural systems biology where, in conjunction with cryoelectron tomography, it can provide structural and mechanistic insights directly in situ.

Cryo-EM snapshots of a native lysate provide structural insights into a metabolon-embedded transacetylase reaction

Found across all kingdoms of life, 2-keto acid dehydrogenase complexes possess prominent metabolic roles and form major regulatory sites. Although their component structures are known, their higher-order organization is highly heterogeneous, not only across species or tissues but also even within a single cell. Here, we report a cryo-EM structure of the fully active Chaetomium thermophilum pyruvate dehydrogenase complex (PDHc) core scaffold at 3.85 Å resolution (FSC = 0.143) from native cell extracts. By combining cryo-EM with macromolecular docking and molecular dynamics simulations, we resolve all PDHc core scaffold interfaces and dissect the residing transacetylase reaction. Electrostatics attract the lipoyl domain to the transacetylase active site and stabilize the coenzyme A, while apolar interactions position the lipoate in its binding cleft. Our results have direct implications on the structural determinants of the transacetylase reaction and the role of flexible regions in the context of the overall 10 MDa PDHc metabolon architecture.

Cross-Linking Mass Spectrometry for Investigating Protein Conformations and Protein-Protein Interactions─A Method for All Seasons

Mass spectrometry (MS) has become one of the key technologies of structural biology. In this review, the contributions of chemical cross-linking combined with mass spectrometry (XL-MS) for studying three-dimensional structures of proteins and for investigating protein-protein interactions are outlined. We summarize the most important cross-linking reagents, software tools, and XL-MS workflows and highlight prominent examples for characterizing proteins, their assemblies, and interaction networks in vitro and in vivo. Computational modeling plays a crucial role in deriving 3D-structural information from XL-MS data. Integrating XL-MS with other techniques of structural biology, such as cryo-electron microscopy, has been successful in addressing biological questions that to date could not be answered. XL-MS is therefore expected to play an increasingly important role in structural biology in the future.

Structural features of nucleosomes in interphase and metaphase chromosomes

Structural heterogeneity of nucleosomes in functional chromosomes is unknown. Here, we devise the template-, reference- and selection-free (TRSF) cryo-EM pipeline to simultaneously reconstruct cryo-EM structures of protein complexes from interphase or metaphase chromosomes. The reconstructed interphase and metaphase nucleosome structures are on average indistinguishable from canonical nucleosome structures, despite DNA sequence heterogeneity, cell-cycle-specific posttranslational modifications, and interacting proteins. Nucleosome structures determined by a decoy-classifying method and structure variability analyses reveal the nucleosome structural variations in linker DNA, histone tails, and nucleosome core particle configurations, suggesting that the opening of linker DNA, which is correlated with H2A C-terminal tail positioning, is suppressed in chromosomes. High-resolution (3.4-3.5 Å) nucleosome structures indicate DNA-sequence-independent stabilization of superhelical locations ±0-1 and ±3.5-4.5. The linker histone H1.8 preferentially binds to metaphase chromatin, from which chromatosome cryo-EM structures with H1.8 at the on-dyad position are reconstituted. This study presents the structural characteristics of nucleosomes in chromosomes.

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.

Coupling proteomics and metabolomics for the unsupervised identification of protein-metabolite interactions in Chaetomium thermophilum

Protein-metabolite interactions play an important role in the cell's metabolism and many methods have been developed to screen them in vitro. However, few methods can be applied at a large scale and not alter biological state. Here we describe a proteometabolomic approach, using chromatography to generate cell fractions which are then analyzed with mass spectrometry for both protein and metabolite identification. Integrating the proteomic and metabolomic analyses makes it possible to identify protein-bound metabolites. Applying the concept to the thermophilic fungus Chaetomium thermophilum, we predict 461 likely protein-metabolite interactions, most of them novel. As a proof of principle, we experimentally validate a predicted interaction between the ribosome and isopentenyl adenine.

A proximity-dependent biotinylation map of a human cell

Compartmentalization is a defining characteristic of eukaryotic cells, and partitions distinct biochemical processes into discrete subcellular locations. Microscopy¹ and biochemical fractionation coupled with mass spectrometry^2-4 have defined the proteomes of a variety of different organelles, but many intracellular compartments have remained refractory to such approaches. Proximity-dependent biotinylation techniques such as BioID provide an alternative approach to define the composition of cellular compartments in living cells^5-7. Here we present a BioID-based map of a human cell on the basis of 192 subcellular markers, and define the intracellular locations of 4,145 unique proteins in HEK293 cells. Our localization predictions exceed the specificity of previous approaches, and enabled the discovery of proteins at the interface between the mitochondrial outer membrane and the endoplasmic reticulum that are crucial for mitochondrial homeostasis. On the basis of this dataset, we created humancellmap.org as a community resource that provides online tools for localization analysis of user BioID data, and demonstrate how this resource can be used to understand BioID results better.

Meta-analysis defines principles for the design and analysis of co-fractionation mass spectrometry experiments

Co-fractionation mass spectrometry (CF-MS) has emerged as a powerful technique for interactome mapping. However, there is little consensus on optimal strategies for the design of CF-MS experiments or their computational analysis. Here, we reanalyzed a total of 206 CF-MS experiments to generate a uniformly processed resource containing over 11 million measurements of protein abundance. We used this resource to benchmark experimental designs for CF-MS studies and systematically optimize computational approaches to network inference. We then applied this optimized methodology to reconstruct a draft-quality human interactome by CF-MS and predict over 700,000 protein-protein interactions across 27 eukaryotic species or clades. Our work defines new resources to illuminate proteome organization over evolutionary timescales and establishes best practices for the design and analysis of CF-MS studies.

Flexibility of Oxidized and Reduced States of the Chloroplast Regulatory Protein CP12 in Isolation and in Cell Extracts

In the chloroplast, Calvin–Benson–Bassham enzymes are active in the reducing environment created in the light by electrons from the photosystems. In the dark, these enzymes are inhibited, mainly caused by oxidation of key regulatory cysteine residues. CP12 is a small protein that plays a role in this regulation with four cysteine residues that undergo a redox transition. Using amide-proton exchange with solvent, measured by nuclear magnetic resonance (NMR) and mass-spectrometry, we confirmed that reduced CP12 is intrinsically disordered. Using real-time NMR, we showed that the oxidation of the two disulfide bridges is simultaneous. In oxidized CP12, the C₂₃–C₃₁ pair is in a region that undergoes a conformational exchange in the NMR-intermediate timescale. The C₆₆–C₇₅ pair is in the C-terminus that folds into a stable helical turn. We confirmed that these structural states exist in a physiologically relevant environment: a cell extract from Chlamydomonas reinhardtii. Consistent with these structural equilibria, the reduction is slower for the C₆₆–C₇₅ pair than for the C₂₃–C₃₁ pair. The redox mid-potentials for the two cysteine pairs differ and are similar to those found for glyceraldehyde 3-phosphate dehydrogenase and phosphoribulokinase, consistent with the regulatory role of CP12.

Structural insight into Pichia pastoris fatty acid synthase

Type I fatty acid synthases (FASs) are critical metabolic enzymes which are common targets for bioengineering in the production of biofuels and other products. Serendipitously, we identified FAS as a contaminant in a cryoEM dataset of virus-like particles (VLPs) purified from P. pastoris, an important model organism and common expression system used in protein production. From these data, we determined the structure of P. pastoris FAS to 3.1 Å resolution. While the overall organisation of the complex was typical of type I FASs, we identified several differences in both structural and enzymatic domains through comparison with the prototypical yeast FAS from S. cerevisiae. Using focussed classification, we were also able to resolve and model the mobile acyl-carrier protein (ACP) domain, which is key for function. Ultimately, the structure reported here will be a useful resource for further efforts to engineer yeast FAS for synthesis of alternate products.

Subcellular proteomics

The eukaryotic cell is compartmentalized into subcellular niches, including membrane-bound and membrane-less organelles. Proteins localize to these niches to fulfil their function, enabling discreet biological processes to occur in synchrony. Dynamic movement of proteins between niches is essential for cellular processes such as signalling, growth, proliferation, motility and programmed cell death, and mutations causing aberrant protein localization are associated with a wide range of diseases. Determining the location of proteins in different cell states and cell types and how proteins relocalize following perturbation is important for understanding their functions, related cellular processes and pathologies associated with their mislocalization. In this Primer, we cover the major spatial proteomics methods for determining the location, distribution and abundance of proteins within subcellular structures. These technologies include fluorescent imaging, protein proximity labelling, organelle purification and cell-wide biochemical fractionation. We describe their workflows, data outputs and applications in exploring different cell biological scenarios, and discuss their main limitations. Finally, we describe emerging technologies and identify areas that require technological innovation to allow better characterization of the spatial proteome.

Detecting Protein Communities in Native Cell Extracts by Machine Learning: A Structural Biologist's Perspective

Native cell extracts hold great promise for understanding the molecular structure of ordered biological systems at high resolution. This is because higher-order biomolecular interactions, dubbed as protein communities, may be retained in their (near-)native state, in contrast to extensively purifying or artificially overexpressing the proteins of interest. The distinct machine-learning approaches are applied to discover protein-protein interactions within cell extracts, reconstruct dedicated biological networks, and report on protein community members from various organisms. Their validation is also important, e.g., by the cross-linking mass spectrometry or cell biology methods. In addition, the cell extracts are amenable to structural analysis by cryo-electron microscopy (cryo-EM), but due to their inherent complexity, sorting structural signatures of protein communities derived by cryo-EM comprises a formidable task. The application of image-processing workflows inspired by machine-learning techniques would provide improvements in distinguishing structural signatures, correlating proteomic and network data to structural signatures and subsequently reconstructed cryo-EM maps, and, ultimately, characterizing unidentified protein communities at high resolution. In this review article, we summarize recent literature in detecting protein communities from native cell extracts and identify the remaining challenges and opportunities. We argue that the progress in, and the integration of, machine learning, cryo-EM, and complementary structural proteomics approaches would provide the basis for a multi-scale molecular description of protein communities within native cell extracts.

Protein identification from electron cryomicroscopy maps by automated model building and side-chain matching

Using single-particle electron cryo-microscopy (cryo-EM), it is possible to obtain multiple reconstructions showing the 3D structures of proteins imaged as a mixture. Here, it is shown that automatic map interpretation based on such reconstructions can be used to create atomic models of proteins as well as to match the proteins to the correct sequences and thereby to identify them. This procedure was tested using two proteins previously identified from a mixture at resolutions of 3.2 Å, as well as using 91 deposited maps with resolutions between 2 and 4.5 Å. The approach is found to be highly effective for maps obtained at resolutions of 3.5 Å and better, and to have some utility at resolutions as low as 4 Å.

Clamping, bending, and twisting inter-domain motions in the misfold-recognizing portion of UDP-glucose: Glycoprotein glucosyltransferase

UDP-glucose:glycoprotein glucosyltransferase (UGGT) flags misfolded glycoproteins for ER retention. We report crystal structures of full-length Chaetomium thermophilum UGGT (CtUGGT), two CtUGGT double-cysteine mutants, and its TRXL2 domain truncation (CtUGGT-ΔTRXL2). CtUGGT molecular dynamics (MD) simulations capture extended conformations and reveal clamping, bending, and twisting inter-domain movements. We name "Parodi limit" the maximum distance on the same glycoprotein between a site of misfolding and an N-linked glycan that can be reglucosylated by monomeric UGGT in vitro, in response to recognition of misfold at that site. Based on the MD simulations, we estimate the Parodi limit as around 70-80 Å. Frequency distributions of distances between glycoprotein residues and their closest N-linked glycosylation sites in glycoprotein crystal structures suggests relevance of the Parodi limit to UGGT activity in vivo. Our data support a "one-size-fits-all adjustable spanner" UGGT substrate recognition model, with an essential role for the UGGT TRXL2 domain.

First 3D-Structural Data of Full-Length Guanylyl Cyclase 1 in Rod-Outer-Segment Preparations of Bovine Retina by Cross-Linking/Mass Spectrometry

The rod-outer-segment guanylyl cyclase 1 (ROS-GC1) is a key transmembrane protein for retinal phototransduction. Mutations of ROS-GC1 correlate with different retinal diseases that often lead to blindness. No structural data are available for ROS-GC1 so far. We performed a 3D-structural analysis of native ROS-GC1 from bovine retina by cross-linking/mass spectrometry (XL-MS) and computational modeling. Absolute quantification and activity measurements of native ROS-GC1 were performed by MS-based assays directly in bovine retina samples. Our data present the first 3D-structural analysis of active, full-length ROS-GC1 derived from bovine retina. We propose a novel domain organization for the intracellular domain ROS-GC1. Our XL-MS data of native ROS-GC1 from rod-outer-segment preparations of bovine retina agree with a dimeric architecture. Our integrated approach can serve as a blueprint for conducting 3D-structural studies of membrane proteins in their native environment.

Cryo-EM as a tool to study bacterial efflux systems and the membrane proteome

Antibiotic resistance is an emerging threat to global health. Current treatment regimens for these types of bacterial infections are becoming increasingly inadequate. Thus, new innovative technologies are needed to help identify and characterize novel drugs and drug targets which are critical in order to combat multidrug-resistant bacterial strains. Bacterial efflux systems have emerged as an attractive target for drug design, as blocking their export function significantly increases the potency of administered antibiotics. However, in order to develop potent and tolerable efflux pump inhibitors with high efficacy, detailed structural information is required for both the apo- and substrate-bound forms of these membrane proteins. The emergence of cryo-electron microscopy (cryo-EM) has greatly advanced the field of membrane protein structural biology. It has significantly enhanced the ability to solve large multi-protein complexes as well as extract meaningful data from a heterogeneous sample, such as identification of several assembly states of the bacterial ribosome, from a single data set. This technique can be expanded to solve the structures of substrate-bound efflux pumps and entire efflux systems from previously unusable membrane protein sample preparations. Subsequently, cryo-EM combined with other biophysical techniques has the potential to markedly advance the field of membrane protein structural biology. The ability to discern complete transport machineries, enzymatic signal transduction pathways, and other membrane-associated complexes will help us fully understand the complexities of the membrane proteome.

Protein Complexes Form a Basis for Complex Hybrid Incompatibility

Proteins are the workhorses of the cell and execute many of their functions by interacting with other proteins forming protein complexes. Multi-protein complexes are an admixture of subunits, change their interaction partners, and modulate their functions and cellular physiology in response to environmental changes. When two species mate, the hybrid offspring are usually inviable or sterile because of large-scale differences in the genetic makeup between the two parents causing incompatible genetic interactions. Such reciprocal-sign epistasis between inter-specific alleles is not limited to incompatible interactions between just one gene pair; and, usually involves multiple genes. Many of these multi-locus incompatibilities show visible defects, only in the presence of all the interactions, making it hard to characterize. Understanding the dynamics of protein-protein interactions (PPIs) leading to multi-protein complexes is better suited to characterize multi-locus incompatibilities, compared to studying them with traditional approaches of genetics and molecular biology. The advances in omics technologies, which includes genomics, transcriptomics, and proteomics can help achieve this end. This is especially relevant when studying non-model organisms. Here, we discuss the recent progress in the understanding of hybrid genetic incompatibility; omics technologies, and how together they have helped in characterizing protein complexes and in turn multi-locus incompatibilities. We also review advances in bioinformatic techniques suitable for this purpose and propose directions for leveraging the knowledge gained from model-organisms to identify genetic incompatibilities in non-model organisms.

Integrative structure of a 10-megadalton eukaryotic pyruvate dehydrogenase complex from native cell extracts

The pyruvate dehydrogenase complex (PDHc) is a giant enzymatic assembly involved in pyruvate oxidation. PDHc components have been characterized in isolation, but the complex's quaternary structure has remained elusive due to sheer size, heterogeneity, and plasticity. Here, we identify fully assembled Chaetomium thermophilum α-keto acid dehydrogenase complexes in native cell extracts and characterize their domain arrangements utilizing mass spectrometry, activity assays, crosslinking, electron microscopy (EM), and computational modeling. We report the cryo-EM structure of the PDHc core and observe unique features of the previously unknown native state. The asymmetric reconstruction of the 10-MDa PDHc resolves spatial proximity of its components, agrees with stoichiometric data (60 E2p:12 E3BP:∼20 E1p: ≤ 12 E3), and proposes a minimum reaction path among component enzymes. The PDHc shows the presence of a dynamic pyruvate oxidation compartment, organized by core and peripheral protein species. Our data provide a framework for further understanding PDHc and α-keto acid dehydrogenase complex structure and function.

A 'Build and Retrieve' methodology to simultaneously solve cryo-EM structures of membrane proteins

Single-particle cryo-electron microscopy (cryo-EM) has become a powerful technique in the field of structural biology. However, the inability to reliably produce pure, homogeneous membrane protein samples significantly hampers the progress of their structural determination. Here, we develop a bottom-up iterative method, designated “Build and Retrieve” (BaR), that allows us to identify and solve cryo-EM structures of a variety of inner and outer membrane proteins, including membrane protein complexes of different sizes and dimensions, from a heterogeneous, impure protein sample. We also employ the BaR methodology to elucidate structural information from E. coli K12 crude membrane and raw lysate. Our work demonstrates that it is possible to solve high-resolution structures of a number of relatively small (< 100 kDa) and less abundant (< 10%) unidentified membrane proteins within a single, heterogeneous sample. Importantly, these results highlight the potential of cryo-EM for systems structural proteomics.

John PC, Bomble YJ. Advances in integrative structural biology: Towards understanding protein complexes in their cellular context

Microorganisms rely on protein interactions to transmit signals, react to stimuli, and grow. One of the best ways to understand these protein interactions is through structural characterization. However, in the past, structural knowledge was limited to stable, high-affinity complexes that could be crystallized. Recent developments in structural biology have revolutionized how protein interactions are characterized. The combination of multiple techniques, known as integrative structural biology, has provided insight into how large protein complexes interact in their native environment. In this mini-review, we describe the past, present, and potential future of integrative structural biology as a tool for characterizing protein interactions in their cellular context.

Cryo-electron microscopy of cholinesterases, present and future

Acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) exist in a variety of oligomeric forms, each with defined cellular and subcellular distributions. Although crystal structures of AChE and BChE have been available for many years, structures of the physiologically relevant ChE tetramer were only recently solved by cryo‐electron microscopy (cryo‐EM) single‐particle analysis. Here, we briefly review how these structures contribute to our understanding of cholinesterase oligomerization, highlighting the advantages of using cryo‐EM to resolve structures of protein assemblies that cannot be expressed recombinantly. We argue that the next frontier in cholinesterase structural biology is to image membrane‐anchored ChE oligomers directly in their native environment—the cell.

EMPAS: Electron Microscopy Screening for Endogenous Protein Architectures

In cells, proteins form macromolecular complexes to execute their own unique roles in biological processes. Conventional structural biology methods adopt a bottom-up approach starting from defined sets of proteins to investigate the structures and interactions of protein complexes. However, this approach does not reflect the diverse and complex landscape of endogenous molecular architectures. Here, we introduce a top-down approach called Electron Microscopy screening for endogenous Protein ArchitectureS (EMPAS) to investigate the diverse and complex landscape of endogenous macromolecular architectures in an unbiased manner. By applying EMPAS, we discovered a spiral architecture and identified it as AdhE. Furthermore, we performed screening to examine endogenous molecular architectures of human embryonic stem cells (hESCs), mouse brains, cyanobacteria and plant leaves, revealing their diverse repertoires of molecular architectures. This study suggests that EMPAS may serve as a tool to investigate the molecular architectures of endogenous macromolecular proteins.

Shotgun EM of mycobacterial protein complexes during stationary phase stress

There is little structural information about the protein complexes conferring resistance in Mycobacterium tuberculosis (Mtb) to anti-microbial oxygen and nitrogen radicals in the phagolysosome. Here, we expose the model Mycobacterium, Mycobacterium smegmatis, to simulated oxidative-stress conditions and apply a shotgun EM method for the structural detection of the resulting protein assemblies. We identified: glutamine synthetase I, essential for Mtb virulence; bacterioferritin A, critical for Mtb iron regulation; aspartyl aminopeptidase M18, a protease; and encapsulin, which produces a cage-like structure to enclose cargo proteins. After further investigation, we found that encapsulin carries dye-decolourising peroxidase, a protein antioxidant, as its primary cargo under the conditions tested.

In-cell architecture of an actively transcribing-translating expressome

Structural biology studies performed inside cells can capture molecular machines in action within their native context. In this work, we developed an integrative in-cell structural approach using the genome-reduced human pathogen Mycoplasma pneumoniae We combined whole-cell cross-linking mass spectrometry, cellular cryo-electron tomography, and integrative modeling to determine an in-cell architecture of a transcribing and translating expressome at subnanometer resolution. The expressome comprises RNA polymerase (RNAP), the ribosome, and the transcription elongation factors NusG and NusA. We pinpointed NusA at the interface between a NusG-bound elongating RNAP and the ribosome and propose that it can mediate transcription-translation coupling. Translation inhibition dissociated the expressome, whereas transcription inhibition stalled and rearranged it. Thus, the active expressome architecture requires both translation and transcription elongation within the cell.

Unstructured regions of large enzymatic complexes control the availability of metabolites with signaling functions

Metabolites produced via traditional biochemical processes affect intracellular communication, inflammation, and malignancy. Unexpectedly, acetyl-CoA, α-ketoglutarate and palmitic acid, which are chemical species of reactions catalyzed by highly abundant, gigantic enzymatic complexes, dubbed as "metabolons", have broad "nonmetabolic" signaling functions. Conserved unstructured regions within metabolons determine the yield of these metabolites. Unstructured regions tether functional protein domains, act as spatial constraints to confine constituent enzyme communication, and, in the case of acetyl-CoA production, tend to be regulated by intricate phosphorylation patterns. This review presents the multifaceted roles of these three significant metabolites and describes how their perturbation leads to altered or transformed cellular function. Their dedicated enzymatic systems are then introduced, namely, the pyruvate dehydrogenase (PDH) and oxoglutarate dehydrogenase (OGDH) complexes, and the fatty acid synthase (FAS), with a particular focus on their structural characterization and the localization of unstructured regions. Finally, upstream metabolite regulation, in which spatial occupancy of unstructured regions within dedicated metabolons may affect metabolite availability and subsequently alter cell functions, is discussed. Video abstract.

Structural analysis of 70S ribosomes by cross-linking/mass spectrometry reveals conformational plasticity

The ribosome is not only a highly complex molecular machine that translates the genetic information into proteins, but also an exceptional specimen for testing and optimizing cross-linking/mass spectrometry (XL-MS) workflows. Due to its high abundance, ribosomal proteins are frequently identified in proteome-wide XL-MS studies of cells or cell extracts. Here, we performed in-depth cross-linking of the E. coli ribosome using the amine-reactive cross-linker disuccinimidyl diacetic urea (DSAU). We analyzed 143 E. coli ribosomal structures, mapping a total of 10,771 intramolecular distances for 126 cross-link-pairs and 3,405 intermolecular distances for 97 protein pairs. Remarkably, 44% of intermolecular cross-links covered regions that have not been resolved in any high-resolution E. coli ribosome structure and point to a plasticity of cross-linked regions. We systematically characterized all cross-links and discovered flexible regions, conformational changes, and stoichiometric variations in bound ribosomal proteins, and ultimately remodeled 2,057 residues (15,794 atoms) in total. Our working model explains more than 95% of all cross-links, resulting in an optimized E. coli ribosome structure based on the cross-linking data obtained. Our study might serve as benchmark for conducting biochemical experiments on newly modeled protein regions, guided by XL-MS. Data are available via ProteomeXchange with identifier PXD018935.