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Regulation of mitochondrial structure and function is a central component of infection with viruses, including human cytomegalovirus (HCMV), as a virus means to modulate cellular metabolism and immune responses. Here, we link the activity of the mitochondrial deacetylase SIRT3 and global mitochondrial acetylation status to host antiviral responses via regulation of both mitochondrial structural integrity and metabolism during HCMV infection. We establish that SIRT3 deacetylase activity is necessary for suppressing virus production, and that SIRT3 maintains mitochondrial pH and membrane potential during infection. By defining the temporal dynamics of SIRT3-substrate interactions during infection, and overlaying acetylome and proteome information, we find altered SIRT3 associations with the mitochondrial fusion factor OPA1 and acetyl-CoA acyltransferase 2 (ACAA2), concomitant with changes in their acetylation levels. Using mutagenesis, microscopy, and virology assays, we determine OPA1 regulates mitochondrial morphology of infected cells and inhibits HCMV production. OPA1 acetylation status modulates these functions, and we establish K834 as a site regulated by SIRT3. Control of SIRT3 protein levels or enzymatic activity is sufficient for regulating mitochondrial filamentous structure. Lastly, we establish a virus restriction function for ACAA2, an enzyme involved in fatty acid beta-oxidation. Altogether, we highlight SIRT3 activity as a regulatory hub for mitochondrial acetylation and morphology during HCMV infection and point to global acetylation as a reflection of mitochondrial health.

Protein–protein interactions (PPIs) drive cellular processes and responses to environmental cues, reflecting the cellular state. Here we develop Tapioca, an ensemble machine learning framework for studying global PPIs in dynamic contexts. Tapioca predicts de novo interactions by integrating mass spectrometry interactome data from thermal/ion denaturation or cofractionation workflows with protein properties and tissue-specific functional networks. Focusing on the thermal proximity coaggregation method, we improved the experimental workflow. Finely tuned thermal denaturation afforded increased throughput, while cell lysis optimization enhanced protein detection from different subcellular compartments. The Tapioca workflow was next leveraged to investigate viral infection dynamics. Temporal PPIs were characterized during the reactivation from latency of the oncogenic Kaposi’s sarcoma-associated herpesvirus. Together with functional assays, NUCKS was identified as a proviral hub protein, and a broader role was uncovered by integrating PPI networks from alpha- and betaherpesvirus infections. Altogether, Tapioca provides a web-accessible platform for predicting PPIs in dynamic contexts. Tapioca is an ensemble machine learning framework for studying protein–protein interactions (PPIs) that facilitates integration of curve-based dynamic PPI data from thermal proximity coaggregation, ion-based proteome-integrated solubility alteration or cofractionation mass spectrometry data with static interaction data to predict PPIs in dynamic contexts.

The co-evolution and co-existence of viral pathogens with their hosts for millions of years is reflected in dynamic virus-host protein-protein interactions (PPIs) that are intrinsic to the spread of infections. Here, we investigate the system-wide dynamics of protein complexes throughout infection with the herpesvirus, human cytomegalovirus (HCMV). Integrating thermal shift assays and mass spectrometry quantification with virology and microscopy, we monitor the temporal formation and dissociation of hundreds of functional protein complexes and the dynamics of host-host, virus-host, and virus-virus PPIs. We establish pro-viral roles for cellular protein complexes and translocating proteins. We show the HCMV receptor integrin beta 1 dissociates from extracellular matrix proteins, becoming internalized with CD63, which is necessary for virus production. Moreover, this approach facilitates characterization of essential viral proteins, such as pUL52. This study of temporal protein complex dynamics provides insights into mechanisms of HCMV infection and a resource for biological and therapeutic studies. Here, Hashimoto et al. apply mass spectrometry-based thermal proximity coaggregation to characterize the temporal dynamics of virus-host protein-protein interactions during human cytomegalovirus (HCMV) infection, uncovering proviral functions including the internalization of the HCMV receptor integrin beta 1 with CD63.

Detection of pathogenic nucleic acids is essential for mammalian innate immunity. IFN-inducible protein IFI16 has emerged as a critical sensor for detecting pathogenic DNA, stimulating both type I IFN and proinflammatory responses. Despite being predominantly nuclear, IFI16 can unexpectedly sense pathogenic DNA in both the cytoplasm and the nucleus. However, the mechanisms regulating its localization and sensing ability remain uncharacterized. Here, we propose a two-signal model for IFI16 sensing. We first identify an evolutionarily conserved multipartite nuclear localization signal (NLS). Next, using FISH and immunopurification, we demonstrate that IFI16 detects HSV-1 DNA primarily in the nucleus, requiring a functional NLS. Furthermore, we establish a localization-dependent IFN-β induction mediated by IFI16 in response to HSV-1 infection or viral DNA transfection. To identify mechanisms regulating the secondary cytoplasmic localization, we explored IFI16 posttranslation modifications. Combinatorial MS analyses identified numerous acetylations and phosphorylations on endogenous IFI16 in lymphocytes, in which we demonstrate an IFI16-mediated IFN-β response. Importantly, the IFI16 NLS was acetylated in lymphocytes, as well as in macrophages. Mutagenesis and nuclear import assays showed that NLS acetylations promote cytoplasmic localization by inhibiting nuclear import. Additionally, broad-spectrum deacetylase inhibition triggered accumulation of cytoplasmic IFI16, and we identify the acetyltransferase p300 as a regulator of IFI16 localization. Collectively, these studies establish acetylation as a molecular toggle of IFI16 distribution, providing a simple and elegant mechanism by which this versatile sensor detects pathogenic DNA in a localization-dependent manner.

An elegant mathematical model supported by experiments in Escherichia coli demonstrates how clustering enzymes can efficiently channel intermediates from one enzyme to the next, facilitating rational engineering of metabolism. We present a quantitative model to demonstrate that coclustering multiple enzymes into compact agglomerates accelerates the processing of intermediates, yielding the same efficiency benefits as direct channeling, a well-known mechanism in which enzymes are funneled between enzyme active sites through a physical tunnel. The model predicts the separation and size of coclusters that maximize metabolic efficiency, and this prediction is in agreement with previously reported spacings between coclusters in mammalian cells. For direct validation, we study a metabolic branch point in Escherichia coli and experimentally confirm the model prediction that enzyme agglomerates can accelerate the processing of a shared intermediate by one branch, and thus regulate steady-state flux division. Our studies establish a quantitative framework to understand coclustering-mediated metabolic channeling and its application to both efficiency improvement and metabolic regulation.

At the core of organelle functions lies their ability and need to form dynamic organelle–organelle networks that drive intracellular communication and coordination of cellular pathways. These networks are facilitated by membrane contact sites (MCSs) that promote both intra-organelle and inter-organelle communication. Given their multiple functions, MCSs and the proteins that form them are commonly co-opted by viruses during infection to promote viral replication. This Essay discusses mechanisms acquired by diverse human viruses to regulate MCS functions in either proviral processes or host defense. It also examines techniques used for examining MCSs in the context of viral infections.

Persistent oncovirus infections account for 15–20% of the global cancer burden, driving multiple forms of human cancer. To maintain persistent infection and spread, oncoviruses drive alterations in host cell metabolism, immune signaling, and cell-to-cell communication throughout tumor microenvironments. Accumulating evidence has indicated that these alterations occur in conjunction with a range of organelle remodeling events that can differ between “dormant” viral latency and active lytic replication. Throughout each phase of infection, oncoviruses alter the morphology, composition, and function of organelles to promote cellular survival and proliferation, while periodically supporting viral replication. Here, we review oncovirus-driven organelle remodeling strategies across distinct infection states, including viral latency, reactivation from latency, and chronic active replication. We focus on the molecular mechanisms by which oncovirus-driven organelle remodeling promotes cellular transformation, impedes immune responses, and facilitates virion assembly and egress. We also draw parallels between remodeling strategies employed by oncogenic and oncomodulatory viruses, emphasizing broadly conserved mechanisms across cancer-associated infections. Lastly, we highlight how studies of oncovirus organelle remodeling are critical for discovering vulnerabilities in both oncogenic virus infection and viral oncogenesis, with therapeutic potential for multiple cancers.

Membrane contact sites (MCSs) link organelles to coordinate cellular functions across space and time. Although viruses remodel organelles for their replication cycles, MCSs remain largely unexplored during infections. Here, we design a targeted proteomics platform for measuring MCS proteins at all organelles simultaneously and define functional virus-driven MCS alterations by the ancient beta-herpesvirus human cytomegalovirus (HCMV). Integration with super-resolution microscopy and comparisons to herpes simplex virus (HSV-1), Influenza A, and beta-coronavirus HCoV-OC43 infections reveals time-sensitive contact regulation that allows switching anti- to pro-viral organelle functions. We uncover a stabilized mitochondria-ER encapsulation structure (MENC). As HCMV infection progresses, MENCs become the predominant mitochondria-ER contact phenotype and sequentially recruit the tethering partners VAP-B and PTPIP51, supporting virus production. However, premature ER-mitochondria tethering activates STING and interferon response, priming cells against infection. At peroxisomes, ACBD5-mediated ER contacts balance peroxisome proliferation versus membrane expansion, with ACBD5 impacting the titers of each virus tested. Membrane contact sites link organelles to coordinate cell functions. Comparing herpesvirus, influenza, and coronavirus infections, the authors define the virus-driven rewiring of organelle contact sites, uncovering ER-mitochondria encapsulation structures as well as a role for ER contacts in pro-viral peroxisome remodeling.

Interferon γ-inducible protein 16 (IFI16) and cGMP-AMP synthase (cGAS) have both been proposed to detect herpesviral DNA directly in herpes simplex virus (HSV)-infected cells and initiate interferon regulatory factor-3 signaling, but it has been unclear how two DNA sensors could both be required for this response. We therefore investigated their relative roles in human foreskin fibroblasts (HFFs) infected with HSV or transfected with plasmid DNA. siRNA depletion studies showed that both are required for the production of IFN in infected HFFs. We found that cGAS shows low production of cGMP-AMP in infected cells, but instead cGAS is partially nuclear in normal human fibroblasts and keratinocytes, interacts with IFI16 in fibroblasts, and promotes the stability of IFI16. IFI16 is associated with viral DNA and targets to viral genome complexes, consistent with it interacting directly with viral DNA. Our results demonstrate that IFI16 and cGAS cooperate in a novel way to sense nuclear herpesviral DNA and initiate innate signaling. Significance Interferon γ-inducible protein 16 (IFI16) and cGMP-AMP synthase (cGAS) have both been proposed to directly detect herpesviral DNA in herpes simplex virus (HSV)-infected cells and initiate interferon regulatory factor-3 signaling, but it has been unclear how two DNA sensors could both be required. Both are required in human fibroblasts for detection of HSV and transfected DNAs. We found evidence that IFI16 plays a direct role in HSV DNA sensing, whereas cGAS produces low amounts of cGAMP and promotes the stability of IFI16. Our results demonstrate a new function for cGAS in the maintenance of normal levels of IFI16 and provide an explanation for the multiple proposed DNA sensors.

Organisms are constantly exposed to microbial pathogens in their environments. When a pathogen meets its host, a series of intricate intracellular interactions shape the outcome of the infection. The understanding of these host–pathogen interactions is crucial for the development of treatments and preventive measures against infectious diseases. Over the past decade, proteomic approaches have become prime contributors to the discovery and understanding of host–pathogen interactions that represent anti‐ and pro‐pathogenic cellular responses. Here, we review these proteomic methods and their application to studying viral and bacterial intracellular pathogens. We examine approaches for defining spatial and temporal host–pathogen protein interactions upon infection of a host cell. Further expanding the understanding of proteome organization during an infection, we discuss methods that characterize the regulation of host and pathogen proteomes through alterations in protein abundance, localization, and post‐translational modifications. Finally, we highlight bioinformatic tools available for analyzing such proteomic datasets, as well as novel strategies for integrating proteomics with other omic tools, such as genomics, transcriptomics, and metabolomics, to obtain a systems‐level understanding of infectious diseases. Graphical Abstract This Review discusses the application of proteomics approaches to the analysis of host–pathogen interactions, including anti‐ and pro‐pathogenic cellular responses. It also highlights integrative omics methods for obtaining a systems‐level understanding of infectious diseases.