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

The mycolic acid layer of the Mycobacterium tuberculosis cell wall is essential for viability and virulence, and the enzymes responsible for its synthesis are targets for antimycobacterial drug development. Polyketide synthase 13 (Pks13) is a module encoding several enzymatic and transport functions that carries out the condensation of two different long-chain fatty acids to produce mycolic acids. We determined structures by cryogenic-electron microscopy of dimeric multi-enzyme Pks13 purified from mycobacteria under normal growth conditions, captured with native substrates. Structures define the ketosynthase (KS), linker and acyl transferase (AT) domains at 1.8 Å resolution and two alternative locations of the N-terminal acyl carrier protein. These structures suggest intermediate states on the pathway for substrate delivery to the KS domain. Other domains, visible at lower resolution, are flexible relative to the KS-AT core. The chemical structures of three bound endogenous long-chain fatty acid substrates were determined by electrospray ionization mass spectrometry. Polyketide synthase 13 from mycobacteria was purified endogenously ‘in action’ with wild-type substrates bound. Structures by cryo-EM define multiple states of acyl carrier proteins in the final step of mycolic acid synthesis by a key drug target.

HIV, the virus that causes AIDS, heavily relies on the machinery of human cells to infect and replicate. Our study focuses on the host cell’s ubiquitination system which is crucial for numerous cellular processes. Many pathogens, including HIV, exploit this system to enhance their own replication and survival. E3 proteins are part of the ubiquitination pathway that are useful drug targets for host-directed therapies. We interrogated the 116 E3s found in human immune cells known as CD4+ T cells, since these are the target cells infected by HIV. Using CRISPR, a gene-editing tool, we individually removed each of these enzymes and observed the impact on HIV infection in human CD4+ T cells isolated from healthy donors. We discovered that 10 of the E3 enzymes had a significant effect on HIV infection. Two of them, TRAF2 and UHRF1, modulated HIV activity within the cells and triggered an increased release of HIV from previously dormant or “latent” cells in a new primary T cell assay. This finding could guide strategies to perturb hidden HIV reservoirs, a major hurdle to curing HIV. Our study offers insights into HIV-host interactions, identifies new factors that influence HIV infection in immune cells, and introduces a novel methodology for studying HIV infection and latency in human immune cells.

Ongoing social, political and ecological changes in the 21st century have placed more people at risk of life-threatening acute and chronic infections than ever before. The development of new diagnostic, prophylactic, therapeutic and curative strategies is critical to address this burden but is predicated on a detailed understanding of the immensely complex relationship between pathogens and their hosts. Traditional, reductionist approaches to investigate this dynamic often lack the scale and/or scope to faithfully model the dual and co-dependent nature of this relationship, limiting the success of translational efforts. With recent advances in large-scale, quantitative omics methods as well as in integrative analytical strategies, systems biology approaches for the study of infectious disease are quickly forming a new paradigm for how we understand and model host–pathogen relationships for translational applications. Here, we delineate a framework for a systems biology approach to infectious disease in three parts: discovery — the design, collection and analysis of omics data; representation — the iterative modelling, integration and visualization of complex data sets; and application — the interpretation and hypothesis-based inquiry towards translational outcomes.This Review outlines a broad, universal framework for systems biology applied to infectious disease research. From study design and omics data collection, analysis, visualization and interpretation to translational outcomes, the authors illustrate how systems biology can provide insights into host–pathogen relationships for the betterment of human health.

Understanding the effects of genetic variation is a fundamental problem in biology that requires methods to analyse both physical and functional consequences of sequence changes at systems-wide and mechanistic scales. To achieve a systems view, protein interaction networks map which proteins physically interact, while genetic interaction networks inform on the phenotypic consequences of perturbing these protein interactions. Until recently, understanding the molecular mechanisms that underlie these interactions often required biophysical methods to determine the structures of the proteins involved. The past decade has seen the emergence of new approaches based on coevolution, deep mutational scanning and genome-scale genetic or chemical–genetic interaction mapping that enable modelling of the structures of individual proteins or protein complexes. Here, we review the emerging use of large-scale genetic datasets and deep learning approaches to model protein structures and their interactions, and discuss the integration of structural data from different sources.Large-scale genetic datasets and deep learning approaches are being used to model the structures of proteins or protein complexes. This Review describes approaches based on coevolution, deep mutational scanning and genome-scale genetic or chemical–genetic interaction mapping and their application and integration to inform structural modelling.

In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array followed by rigorous biochemical verification with in vitro binding and kinase assays on wild-type and mutant proteins. Using this procedure, we found new 'D-site' class docking sites in previously known JNK substrates (hnRNP-K, PPM1J/PP2Czeta), as well as new JNK-interacting proteins (MLL4, NEIL1). Finally, we identified new D-site-dependent MAPK substrates, including the hedgehog-regulated transcription factors Gli1 and Gli3, suggesting that a direct connection between MAP kinase and hedgehog signaling may occur at the level of these key regulators. These results demonstrate that a genome-wide search for MAP kinase docking sites can be used to find new docking sites and substrates.

The HIV-1 Nef protein suppresses multiple immune surveillance mechanisms to promote viral pathogenesis and is an attractive target for the development of novel therapeutics. A key function of Nef is to remove the CD4 receptor from the cell surface by hijacking clathrin- and adaptor protein complex 2 (AP2)-dependent endocytosis. However, exactly how Nef does this has been elusive. Here, we describe the underlying mechanism as revealed by a 3.0-Å crystal structure of a fusion protein comprising Nef and the cytoplasmic domain of CD4 bound to the tetrameric AP2 complex. An intricate combination of conformational changes occurs in both Nef and AP2 to enable CD4 binding and downregulation. A pocket on Nef previously identified as crucial for recruiting class I MHC is also responsible for recruiting CD4, revealing a potential approach to inhibit two of Nef’s activities and sensitize the virus to immune clearance.Crystallography and mutagenesis analyses examine how HIV-1 Nef interacts with AP2 to enable CD4 binding and downregulation and reveal the role of a Nef pocket that is also involved in downregulation of class I MHC.

Cell-surface tumor marker EpCAM plays a key role in proliferation, differentiation and adhesion processes in stem and epithelial cells. It is established as a cell-cell adhesion molecule, forming intercellular interactions through homophilic association. However, the mechanism by which such interactions arise has not yet been fully elucidated. Here, we first show that EpCAM monomers do not associate into oligomers that would resemble an inter-cellular homo-oligomer, capable of mediating cell-cell adhesion, by using SAXS, XL-MS and bead aggregation assays. Second, we also show that EpCAM forms stable dimers on the surface of a cell with pre-formed cell-cell contacts using FLIM-FRET; however, no inter-cellular homo-oligomers were detectable. Thus, our study provides clear evidence that EpCAM indeed does not function as a homophilic cell adhesion molecule and therefore calls for a significant revision of its role in both normal and cancerous tissues. In the light of this, we strongly support the previously suggested name Epithelial Cell Activating Molecule instead of the Epithelial Cell Adhesion Molecule.

Protein-protein interaction is one of the key regulatory mechanisms for controlling protein function in various cellular processes. Chemical cross-linking coupled with mass spectrometry has proven to be a powerful method not only for mapping protein-protein interactions of all natures, including weak and transient ones, but also for determining their interaction interfaces. One critical challenge remaining in this approach is how to effectively isolate and identify cross-linked products from a complex peptide mixture. In this work, we have developed a novel strategy using conjugation chemistry for selective enrichment of cross-linked products. An azide-tagged cross-linker along with two biotinylated conjugation reagents were designed and synthesized. Cross-linking of model peptides and cytochrome c as well as enrichment of the resulting cross-linked peptides has been assessed. Selective conjugation of azide-tagged cross-linked peptides has been demonstrated using two strategies: copper catalyzed cycloaddition and Staudinger ligation. While both methods are effective, Staudinger ligation is better suited for enriching the cross-linked peptides since there are fewer issues with sample handling. LC MS n analysis coupled with database searching using the Protein Prospector software package allowed identification of 58 cytochrome c cross-linked peptides after enrichment and affinity purification. The new enrichment strategy developed in this work provides useful tools for facilitating identification of cross-linked peptides in a peptide mixture by MS, thus presenting a step forward in future studies of protein-protein interactions of protein complexes by cross-linking and mass spectrometry. A novel Staudinger ligation-based enrichment strategy for selective isolation of cross-linked peptides from peptide mixtures using new reagents including azide-tagged cross-linker and biotin-phosphine.

Multiple genetic association studies have correlated a common allelic block linked to the BAG3 gene with a decreased incidence of heart failure, but the molecular mechanism remains elusive. In this study, we used induced pluripotent stem cells to test if the only coding variant in this allele block, BAG3 , alters protein and cellular function in human cardiomyocytes. Quantitative protein interaction analysis identified changes in BAG3 protein partners specific to cardiomyocytes. Knockdown of genes encoding for BAG3-interacting factors in cardiomyocytes followed by myofibrillar analysis revealed that BAG3 associates more strongly with proteins involved in the maintenance of myofibrillar integrity. Finally, we demonstrate that cardiomyocytes expressing the BAG3 variant have improved response to proteotoxic stress in a dose-dependent manner. This study suggests that BAG3 could be responsible for the cardioprotective effect of the haplotype block, by increasing cardiomyocyte protection from stress. Preferential binding partners of BAG3 may reveal potential targets for cardioprotective therapies.