Spatially resolved protein map of intact human cytomegalovirus virions

RawVegetable 2.0: Refining XL-MS Data Acquisition through Enhanced Quality Control

We present RawVegetable 2.0, a software tailored for assessing mass spectrometry data quality and fine-tuned for cross-linking mass spectrometry (XL-MS) applications. Building upon the capabilities of its predecessor, RawVegetable 2.0 introduces four main modules, each providing distinct and new functionalities: 1) Pair Finder, which identifies ion doublets characteristic of cleavable cross-linking experiments; 2) Diagnostic Peak Finder, which locates potential reporter ions associated with a specific cross-linker; 3) Precursor Signal Ratio, which computes the ratio between precursor intensity and the total signal in an MS/MS scan; and 4) Xrea, which evaluates spectral quality by analyzing the heterogeneity of peak intensities within a spectrum. These modules collectively streamline the process of optimizing mass spectrometry data acquisition for both Proteomics and XL-MS experiments. RawVegetable 2.0, along with a comprehensive tutorial is freely accessible for academic use at: http://patternlabforproteomics.org/rawvegetable2.

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.

Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes

While the primary sequences of human proteins have been cataloged for over a decade, determining how these are organized into a dynamic collection of multiprotein assemblies, with structures and functions spanning biological scales, is an ongoing venture. Systematic and data-driven analyses of these higher-order structures are emerging, facilitating the discovery and understanding of cellular phenotypes. At present, knowledge of protein localization and function has been primarily derived from manual annotation and curation in resources such as the Gene Ontology, which are biased toward richly annotated genes in the literature. Here, we envision a future powered by data-driven mapping of protein assemblies. These maps can capture and decode cellular functions through the integration of protein expression, localization, and interaction data across length scales and timescales. In this review, we focus on progress toward constructing integrated cell maps that accelerate the life sciences and translational research.

Structures of Epstein-Barr virus and Kaposi's sarcoma-associated herpesvirus virions reveal species-specific tegument and envelope features

Epstein-Barr virus (EBV) and Kaposi's sarcoma-associated herpesvirus (KSHV) are classified into the gammaherpesvirus subfamily of Herpesviridae , which stands out from its alpha- and betaherpesvirus relatives due to the tumorigenicity of its members. Although structures of human alpha- and betaherpesviruses by cryogenic electron tomography (cryoET) have been reported, reconstructions of intact human gammaherpesvirus virions remain elusive. Here, we structurally characterize extracellular virions of EBV and KSHV by deep learning-enhanced cryoET, resolving both previously known monomorphic capsid structures and previously unknown pleomorphic features beyond the capsid. Through subtomogram averaging and subsequent tomogram-guided sub-particle reconstruction, we determined the orientation of KSHV nucleocapsids from mature virions with respect to the portal to provide spatial context for the tegument within the virion. Both EBV and KSHV have an eccentric capsid position and polarized distribution of tegument. Tegument species span from the capsid to the envelope and may serve as scaffolds for tegumentation and envelopment. The envelopes of EBV and KSHV are less densely populated with glycoproteins than those of herpes simplex virus 1 and human cytomegalovirus, representative members of alpha- and betaherpesviruses, respectively. This population density of glycoproteins correlates with their relative infectivity against HEK293T cells. Also, we observed fusion protein gB trimers exist within triplet arrangements in addition to standalone complexes, which is relevant to understanding dynamic processes such as fusion pore formation. Taken together, this study reveals nuanced yet important differences in the tegument and envelope architectures among human herpesviruses and provides insights into their varied cell tropism and infection.

Importance

Discovered in 1964, Epstein-Barr virus (EBV) is the first identified human oncogenic virus and the founding member of the gammaherpesvirus subfamily. In 1994, another cancer-causing virus was discovered in lesions of AIDS patients and later named Kaposi's sarcoma-associated herpesvirus (KSHV), the second human gammaherpesvirus. Despite the historical importance of EBV and KSHV, technical difficulties with isolating large quantities of these viruses and the pleiomorphic nature of their envelope and tegument layers have limited structural characterization of their virions. In this study, we employed the latest technologies in cryogenic electron microscopy (cryoEM) and tomography (cryoET) supplemented with an artificial intelligence-powered data processing software package to reconstruct 3D structures of the EBV and KSHV virions. We uncovered unique properties of the envelope glycoproteins and tegument layers of both EBV and KSHV. Comparison of these features with their non-tumorigenic counterparts provides insights into their relevance during infection.

Human cytomegalovirus deploys molecular mimicry to recruit VPS4A to sites of virus assembly

The AAA-type ATPase VPS4 is recruited by proteins of the endosomal sorting complex required for transport III (ESCRT-III) to catalyse membrane constriction and membrane fission. VPS4A accumulates at the cytoplasmic viral assembly complex (cVAC) of cells infected with human cytomegalovirus (HCMV), the site where nascent virus particles obtain their membrane envelope. Here we show that VPS4A is recruited to the cVAC via interaction with pUL71. Sequence analysis, deep-learning structure prediction, molecular dynamics and mutagenic analysis identify a short peptide motif in the C-terminal region of pUL71 that is necessary and sufficient for the interaction with VPS4A. This motif is predicted to bind the same groove of the N-terminal VPS4A Microtubule-Interacting and Trafficking (MIT) domain as the Type 2 MIT-Interacting Motif (MIM2) of cellular ESCRT-III components, and this viral MIM2-like motif (vMIM2) is conserved across β-herpesvirus pUL71 homologues. However, recruitment of VPS4A by pUL71 is dispensable for HCMV morphogenesis or replication and the function of the conserved vMIM2 during infection remains enigmatic. VPS4-recruitment via a vMIM2 represents a previously unknown mechanism of molecular mimicry in viruses, extending previous observations that herpesviruses encode proteins with structural and functional homology to cellular ESCRT-III components.

Harnessing the 14-3-3 protein-protein interaction network

Protein-protein interactions (PPIs) play a critical role in cellular signaling and represent interesting targets for therapeutic intervention. 14-3-3 proteins integrate many signaling targets via PPIs and are frequently implicated in disease, making them intriguing drug targets. Here, we review the recent advances in the 14-3-3 field. It will discuss the roles 14-3-3 proteins play within the cell, elucidation of their expansive interactome, and the complex mechanisms that underpin their function. In addition, the review will discuss significant advances in the development of molecular glues that target 14-3-3 PPIs. In particular, it will focus on novel drug discovery and development methodologies that have delivered selective, potent, and drug-like molecules that could open new avenues for the development of precision molecular tools and medicines.

Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topologies

The functions of cellular organelles and sub-compartments depend on their protein content, which can be characterized by spatial proteomics approaches. However, many spatial proteomics methods are limited in their ability to resolve organellar sub-compartments, profile multiple sub-compartments in parallel, and/or characterize membrane-associated proteomes. Here, we develop a cross-link assisted spatial proteomics (CLASP) strategy that addresses these shortcomings. Using human mitochondria as a model system, we show that CLASP can elucidate spatial proteomes of all mitochondrial sub-compartments and provide topological insight into the mitochondrial membrane proteome. Biochemical and imaging-based follow-up studies confirm that CLASP allows discovering mitochondria-associated proteins and revising previous protein sub-compartment localization and membrane topology data. We also validate the CLASP concept in synaptic vesicles, demonstrating its applicability to different sub-cellular compartments. This study extends the scope of cross-linking mass spectrometry beyond protein structure and interaction analysis towards spatial proteomics, and establishes a method for concomitant profiling of sub-organelle and membrane proteomes.

Crystal structure of the tegument protein UL82 (pp71) from human cytomegalovirus

Human cytomegalovirus (HCMV) is an opportunistic pathogen that infects a majority of the world population. It may cause severe disease in immunocompromised people and lead to pregnancy loss or grave disabilities of the fetus upon congenital infection. For effective replication and lifelong persistence in its host, HCMV relies on diverse functions of its tegument protein UL82, also known as pp71. Up to now, little is known about the molecular mechanisms underlying the multiple functions of this crucial viral protein. Here, we describe the X-ray structure of full-length UL82 to a resolution of 2.7 Å. A single polypeptide chain of 559 amino acids mainly folds into three ß-barrels. We show that UL82 forms a dimer in the crystal as well as in solution. We identify point mutations that disturb the dimerization interface and show that the mutant protein is monomeric in solution and upon expression in human cells. On the basis of the three-dimensional structure, we identify structural homologs of UL82 from other herpesviruses and analyze whether their functions are preserved in UL82. We demonstrate that UL82, despite its structural homology to viral deoxyuridinetriphosphatases (dUTPases), does not possess dUTPase activity. Prompted by the structural homology of UL82 to the ORF10 protein of murine herpesvirus 68 (MHV68), which is known to interact with the RNA export factor ribonucleic acid export 1 (Rae1), we performed coimmunoprecipitations and demonstrated that UL82 indeed interacts with Rae1. This suggests that HCMV UL82 may play a role in mRNA export from the nucleus similar to ORF10 encoded by the gammaherpesviruses MHV68.

The incredible bulk: Human cytomegalovirus tegument architectures uncovered by AI-empowered cryo-EM

The compartmentalization of eukaryotic cells presents considerable challenges to the herpesvirus life cycle. The herpesvirus tegument, a bulky proteinaceous aggregate sandwiched between herpesviruses' capsid and envelope, is uniquely evolved to address these challenges, yet tegument structure and organization remain poorly characterized. We use deep-learning-enhanced cryogenic electron microscopy to investigate the tegument of human cytomegalovirus virions and noninfectious enveloped particles (NIEPs; a genome packaging-aborted state), revealing a portal-biased tegumentation scheme. We resolve atomic structures of portal vertex-associated tegument (PVAT) and identify multiple configurations of PVAT arising from layered reorganization of pUL77, pUL48 (large tegument protein), and pUL47 (inner tegument protein) assemblies. Analyses show that pUL77 seals the last-packaged viral genome end through electrostatic interactions, pUL77 and pUL48 harbor a head-linker-capsid-binding motif conducive to PVAT reconfiguration, and pUL47/48 dimers form 45-nm-long filaments extending from the portal vertex. These results provide a structural framework for understanding how herpesvirus tegument facilitates and evolves during processes spanning viral genome packaging to delivery.

The 2023 Report on the Proteome from the HUPO Human Proteome Project

Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1-4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.

Multi-modal features-based human-herpesvirus protein-protein interaction prediction by using LightGBM

The identification of human-herpesvirus protein-protein interactions (PPIs) is an essential and important entry point to understand the mechanisms of viral infection, especially in malignant tumor patients with common herpesvirus infection. While natural language processing (NLP)-based embedding techniques have emerged as powerful approaches, the application of multi-modal embedding feature fusion to predict human-herpesvirus PPIs is still limited. Here, we established a multi-modal embedding feature fusion-based LightGBM method to predict human-herpesvirus PPIs. In particular, we applied document and graph embedding approaches to represent sequence, network and function modal features of human and herpesviral proteins. Training our LightGBM models through our compiled non-rigorous and rigorous benchmarking datasets, we obtained significantly better performance compared to individual-modal features. Furthermore, our model outperformed traditional feature encodings-based machine learning methods and state-of-the-art deep learning-based methods using various benchmarking datasets. In a transfer learning step, we show that our model that was trained on human-herpesvirus PPI dataset without cytomegalovirus data can reliably predict human-cytomegalovirus PPIs, indicating that our method can comprehensively capture multi-modal fusion features of protein interactions across various herpesvirus subtypes. The implementation of our method is available at https://github.com/XiaodiYangpku/MultimodalPPI/.