Temporal dynamics of protein complex formation and dissociation during human cytomegalovirus infection

Salmonella infection impacts host proteome thermal stability

Intracellular bacterial pathogens hijack the protein machinery of infected host cells to evade their defenses and cultivate a favorable intracellular niche. The intracellular pathogen Salmonella enterica subsp. Typhimurium (STm) achieves this by injecting a cocktail of effector proteins into host cells that modify the activity of target host proteins. Yet, proteome-wide approaches to systematically map changes in host protein function during infection have remained challenging. Here we adapted a functional proteomics approach - Thermal-Proteome Profiling (TPP) - to systematically assess proteome-wide changes in host protein abundance and thermal stability throughout an STm infection cycle. By comparing macrophages treated with live or heat-killed STm, we observed that most host protein abundance changes occur independently of STm viability. In contrast, a large portion of host protein thermal stability changes were specific to infection with live STm. This included pronounced thermal stability changes in proteins linked to mitochondrial function (Acod1/Irg1, Cox6c, Samm50, Vdac1, and mitochondrial respiratory chain complex proteins), as well as the interferon-inducible protein with tetratricopeptide repeats, Ifit1. Integration of our TPP data with a publicly available STm-host protein-protein interaction database led us to discover that the secreted STm effector kinase, SteC, thermally destabilizes and phosphorylates the ribosomal preservation factor Serbp1. In summary, this work emphasizes the utility of measuring protein thermal stability during infection to accelerate the discovery of novel molecular interactions at the host-pathogen interface.

Differential Contributions of Interferon Classes to Host Inflammatory Responses and Restricting Virus Progeny Production

Fundamental to mammalian intrinsic and innate immune defenses against pathogens is the production of Type I and Type II interferons, such as IFN-β and IFN-γ, respectively. The comparative effects of IFN classes on the cellular proteome, protein interactions, and virus restriction within cell types that differentially contribute to immune defenses are needed for understanding immune signaling. Here, a multilayered proteomic analysis, paired with biochemical and molecular virology assays, allows distinguishing host responses to IFN-β and IFN-γ and associated antiviral impacts during infection with several ubiquitous human viruses. In differentiated macrophage-like monocytic cells, we classified proteins upregulated by IFN-β, IFN-γ, or pro-inflammatory LPS. Using parallel reaction monitoring, we developed a proteotypic peptide library for shared and unique ISG signatures of each IFN class, enabling orthogonal confirmation of protein alterations. Thermal proximity coaggregation analysis identified the assembly and maintenance of IFN-induced protein interactions. Comparative proteomics and cytokine responses in macrophage-like monocytic cells and primary keratinocytes provided contextualization of their relative capacities to restrict virus production during infection with herpes simplex virus type-1, adenovirus, and human cytomegalovirus. Our findings demonstrate how IFN classes induce distinct ISG abundance and interaction profiles that drive antiviral defenses within cell types that differentially coordinate mammalian immune responses.

Computational tools to predict context-specific protein complexes

Interactions between thousands of proteins define cells' protein-protein interaction (PPI) network. Some of these interactions lead to the formation of protein complexes. It is challenging to identify a protein complex in a haystack of protein-protein interactions, and it is even more difficult to predict all protein complexes of the complexome. Simulations and machine learning approaches try to crack these problems by looking at the PPI network or predicted protein structures. Clustering of PPI networks led to the first protein complex predictions, while most recently, atomistic models of protein complexes and deep-learning-based structure prediction methods have also emerged. The simulation of PPI level interactions even enables the quantitative prediction of protein complexes. These methods, the required data sources, and their potential future developments are discussed in this review.

Early signaling pathways in virus-infected cells

Virus infection activates specific pattern recognition receptors and immune signal transduction, resulting in pro-inflammatory cytokine production and activation of innate immunity. We describe here the molecular organization of early signaling pathways downstream of viral recognition, including conformational changes, post-translational modifications, formation of oligomers, and generation of small-molecule second messengers. Such molecular organization allows tight regulation of immune signal transduction, characterized by swift but transient responses, nonlinearity, and signal amplification. Pathologies of early immune signaling caused by genomic mutations illustrate the fine regulation of the immune transduction cascade.

Mapping protein-protein interactions by mass spectrometry

Protein-protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization and function of the proteome, and their perturbation is associated with various diseases, such as cancer, neurodegeneration, and infectious diseases. Recent advances in mass spectrometry (MS)-based protein interactomics have significantly expanded our understanding of the PPIs in cells, with techniques that continue to improve in terms of sensitivity, and specificity providing new opportunities for the study of PPIs in diverse biological systems. These techniques differ depending on the type of interaction being studied, with each approach having its set of advantages, disadvantages, and applicability. This review highlights recent advances in enrichment methodologies for interactomes before MS analysis and compares their unique features and specifications. It emphasizes prospects for further improvement and their potential applications in advancing our knowledge of PPIs in various biological contexts.

Tapioca: a platform for predicting de novo protein-protein interactions in dynamic contexts

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.

Experimental and data analysis advances in thermal proteome profiling

Method development for mass spectrometry (MS)-based thermal shift proteomic assays have advanced to probe small molecules with known and unknown protein-ligand interaction mechanisms and specificity, which is predominantly used in characterization of drug-protein interactions. In the discovery of target and off-target protein-ligand interactions, a thorough investigation of method development and their impact on the sensitivity and accuracy of protein-small molecule and protein-protein interactions is warranted. In this review, we discuss areas of improvement at each stage of thermal proteome profiling data analysis that includes processing of MS-based data, method development, and their effect on the overall quality of thermal proteome profiles. We also overview the optimization of experimental strategies and prioritization of an increased number of independent biological replicates over the number of evaluated temperatures.

Site-specific crosslinking reveals Phosphofructokinase-L inhibition drives self-assembly and attenuation of protein interactions

Phosphofructokinase is the central enzyme in glycolysis and constitutes a highly regulated step. The liver isoform (PFKL) compartmentalizes during activation and inhibition in vitro and in vivo, respectively. Compartmentalized PFKL is hypothesized to modulate metabolic flux consistent with its central role as the rate limiting step in glycolysis. PFKL tetramers self-assemble at two interfaces in the monomer (interface 1 and 2), yet how these interfaces contribute to PFKL compartmentalization and drive protein interactions remains unclear. Here, we used site-specific incorporation of noncanonical photocrosslinking amino acids to identify PFKL interactors at interface 1, 2, and the active site. Tandem mass tag-based quantitative interactomics reveals interface 2 as a hotspot for PFKL interactions, particularly with cytoskeletal, glycolytic, and carbohydrate derivative metabolic proteins. Furthermore, PFKL compartmentalization into puncta was observed in human cells using citrate inhibition. Puncta formation attenuated crosslinked protein-protein interactions with the cytoskeleton at interface 2. This result suggests that PFKL compartmentalization sequesters interface 2, but not interface 1, and may modulate associated protein assemblies with the cytoskeleton.

Improved in situ characterization of protein complex dynamics at scale with thermal proximity co-aggregation

Cellular activities are carried out vastly by protein complexes but large repertoire of protein complexes remains functionally uncharacterized which necessitate new strategies to delineate their roles in various cellular processes and diseases. Thermal proximity co-aggregation (TPCA) is readily deployable to characterize protein complex dynamics in situ and at scale. We develop a version termed Slim-TPCA that uses fewer temperatures increasing throughputs by over 3X, with new scoring metrics and statistical evaluation that result in minimal compromise in coverage and detect more relevant complexes. Less samples are needed, batch effects are minimized while statistical evaluation cost is reduced by two orders of magnitude. We applied Slim-TPCA to profile K562 cells under different duration of glucose deprivation. More protein complexes are found dissociated, in accordance with the expected downregulation of most cellular activities, that include 55S ribosome and respiratory complexes in mitochondria revealing the utility of TPCA to study protein complexes in organelles. Protein complexes in protein transport and degradation are found increasingly assembled unveiling their involvement in metabolic reprogramming during glucose deprivation. In summary, Slim-TPCA is an efficient strategy for characterization of protein complexes at scale across cellular conditions, and is available as Python package at https://pypi.org/project/Slim-TPCA/ .

Systematic thermal analysis of the Arabidopsis proteome: Thermal tolerance, organization, and evolution

Understanding the thermal stability of the plant proteome in the context of the native cellular environment would aid the design of crops with high thermal tolerance, but only limited such data are available. Here, we applied quantitative mass spectrometry to profile the thermal stability of the Arabidopsis proteome and identify thermo-sensitive and thermo-resilient protein networks in Arabidopsis, providing a basis for understanding heat-induced damage. We also show that the similarities of the protein-melting curves can be used as a proxy to evaluate system-wide protein-protein interactions in non-engineered plants and enable the identification of transient interactions exhibited by metabolons in the context of the cellular environment. Finally, we report a systematic comparison of the thermal stability of paralogs in Arabidopsis to aid the investigation and understanding of gene duplication and protein evolution. Taken together, our results could have broad implications for the fields of plant thermal tolerance, plant protein assemblies, and evolution.

Site-Specific Crosslinking Reveals Phosphofructokinase-L Inhibition Drives Self-Assembly and Attenuation of Protein Interactions

Phosphofructokinase is the central enzyme in glycolysis and constitutes a highly regulated step. The liver isoform (PFKL) compartmentalizes during activation and inhibition in vitro and in vivo respectively. Compartmentalized PFKL is hypothesized to modulate metabolic flux consistent with its central role as the rate limiting step in glycolysis. PFKL tetramers self-assemble at two interfaces in the monomer (interface 1 and 2), yet how these interfaces contribute to PFKL compartmentalization and drive protein interactions remains unclear. Here, we used site-specific incorporation of noncanonical photocrosslinking amino acids to identify PFKL interactors at interface 1, 2, and the active site. Tandem mass tag-based quantitative interactomics reveals interface 2 as a hotspot for PFKL interactions, particularly with cytoskeletal, glycolytic, and carbohydrate derivative metabolic proteins. Furthermore, PFKL compartmentalization into puncta was observed in human cells using citrate inhibition. Puncta formation attenuated crosslinked protein-protein interactions with the cytoskeleton at interface 2. This result suggests that PFKL compartmentalization sequesters interface 2, but not interface 1, and may modulate associated protein assemblies with the cytoskeleton.

Scaled-Down Thermal Profiling and Coaggregation Analysis of the Proteome for Drug Target and Protein Interaction Analysis

Thermal proteome profiling (TPP), an experimental technique combining the cellular thermal shift assay (CETSA) with quantitative protein mass spectrometry (MS), identifies interactions of drugs and chemicals with endogenous proteins. Thermal proximity coaggregation (TPCA) profiling extended TPP to study the intracellular dynamics of protein complexes. In TPP and TPCA, samples are subjected to multiple denaturing temperatures, each requiring over 100 μg of proteins, which restricts their applications for rare cells and precious clinical samples. We developed a workflow termed STASIS (scaled-down thermal profiling and coaggregation analysis with SISPROT) that scales down the required protein to as low as 1 μg per temperature. This is achieved by heating and centrifugation using the same PCR tube, processing samples with the SISPROT technology (simple and integrated spintip-based proteomics technology), and tip-based manual fractionation of TMT-labeled peptides. We evaluate the STASIS workflow with starting protein quantities of 10, 5, and 1 μg per temperature prior to heating, identifying between 4000 and 5000 proteins with 6 h of acquisition time. Importantly, we observed a high correlation in the Tm of proteins with minimal difference in TPCA performance for predicting protein complexes. Moreover, STASIS could identify the targets of methotrexate and panobinostat with high precision with 1 μg of proteins per temperature. In conclusion, STASIS is a robust cost-effective technique for target deconvolution and extended TPCA to rare primary cells and precious clinical samples for the analysis of protein complexes.

Obtaining Functional Proteomics Insights From Thermal Proteome Profiling Through Optimized Melt Shift Calculation and Statistical Analysis With InflectSSP

Thermal proteome profiling (TPP) is an invaluable tool for functional proteomics studies that has been shown to discover changes associated with protein-ligand, protein-protein, and protein-RNA interaction dynamics along with changes in protein stability resulting from cellular signaling. The increasing number of reports employing this assay has not been met concomitantly with new approaches leading to advancements in the quality and sensitivity of the corresponding data analysis. The gap between data acquisition and data analysis tools is important to fill as TPP findings have reported subtle melt shift changes related to signaling events such as protein posttranslational modifications. In this study, we have improved the Inflect data analysis pipeline (now referred to as InflectSSP, available at https://CRAN.R-project.org/package=InflectSSP) to increase the sensitivity of detection for both large and subtle changes in the proteome as measured by TPP. Specifically, InflectSSP now has integrated statistical and bioinformatic functions to improve objective functional proteomics findings from the quantitative results obtained from TPP studies through increasing both the sensitivity and specificity of the data analysis pipeline. InflectSSP incorporates calculation of a "melt coefficient" into the pipeline with production of average melt curves for biological replicate studies to aid in identification of proteins with significant melts. To benchmark InflectSSP, we have reanalyzed two previously reported datasets to demonstrate the performance of our publicly available R-based program for TPP data analysis. We report new findings following temporal treatment of human cells with the small molecule thapsigargin that induces the unfolded protein response as a consequence of inhibition of sarcoplasmic/endoplasmic reticulum calcium ATPase 2A. InflectSSP analysis of our unfolded protein response study revealed highly reproducible and statistically significant target engagement over a time course of treatment while simultaneously providing new insights into the possible mechanisms of action of the small molecule thapsigargin.

Next-generation proteomics for quantitative Jumbophage-bacteria interaction mapping

Host-pathogen interactions are pivotal in regulating establishment, progression, and outcome of an infection. While affinity-purification mass spectrometry has become instrumental in characterizing such interactions, it suffers from limitations in scalability and biological authenticity. Here we present the use of co-fractionation mass spectrometry for high throughput analysis of host-pathogen interactions from native viral infections of two jumbophages (ϕKZ and ϕPA3) in Pseudomonas aeruginosa. This approach enabled the detection of > 6000 unique host-pathogen interactions for each phage, encompassing > 50% of their respective proteomes. This deep coverage provided evidence for interactions between KZ-like phage proteins and the host ribosome, and revealed protein complexes for previously undescribed phage ORFs, including a ϕPA3 complex showing strong structural and sequence similarity to ϕKZ non-virion RNA polymerase. Interactome-wide comparison across phages showed similar perturbed protein interactions suggesting fundamentally conserved mechanisms of phage predation within the KZ-like phage family. To enable accessibility to this data, we developed PhageMAP, an online resource for network query, visualization, and interaction prediction ( https://phagemap.ucsf.edu/ ). We anticipate this study will lay the foundation for the application of co-fractionation mass spectrometry for the scalable profiling of host-pathogen interactomes and protein complex dynamics upon infection.

Altered Proteomic Profile of Exosomes Secreted from Vero Cells Infected with Porcine Epidemic Diarrhea Virus

Porcine epidemic diarrhea virus (PEDV) infection causes severe diarrhea in pigs and can be fatal in newborn piglets. Exosomes are extracellular vesicles secreted by cells that transfer biologically active proteins, lipids, and RNA to neighboring or distant cells. Herein, the morphology, particle size, and secretion of exosomes derived from a control and PEDV-infected group are examined, followed by a proteomic analysis of the exosomes. The results show that the exosomes secreted from the Vero cells had a typical cup-shaped structure. The average particle size of the exosomes from the PEDV-infected group was 112.4 nm, whereas that from the control group was 150.8 nm. The exosome density analysis and characteristic protein determination revealed that the content of exosomes in the PEDV-infected group was significantly higher than that in the control group. The quantitative proteomics assays revealed 544 differentially expressed proteins (DEPs) in the PEDV-infected group's exosomes compared with those in the controls, with 236 upregulated and 308 downregulated proteins. The DEPs were closely associated with cellular regulatory pathways, such as the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)-protein kinase B (Akt) signaling pathway, extracellular matrix-receptor interaction, focal adhesion, and cytoskeletal regulation. These findings provide the basis for further investigation of the pathogenic mechanisms of PEDV and the discovery of novel antiviral targets.

Orchestration of Mitochondrial Function and Remodeling by Post-Translational Modifications Provide Insight into Mechanisms of Viral Infection

The regulation of mitochondria structure and function is at the core of numerous viral infections. Acting in support of the host or of virus replication, mitochondria regulation facilitates control of energy metabolism, apoptosis, and immune signaling. Accumulating studies have pointed to post-translational modification (PTM) of mitochondrial proteins as a critical component of such regulatory mechanisms. Mitochondrial PTMs have been implicated in the pathology of several diseases and emerging evidence is starting to highlight essential roles in the context of viral infections. Here, we provide an overview of the growing arsenal of PTMs decorating mitochondrial proteins and their possible contribution to the infection-induced modulation of bioenergetics, apoptosis, and immune responses. We further consider links between PTM changes and mitochondrial structure remodeling, as well as the enzymatic and non-enzymatic mechanisms underlying mitochondrial PTM regulation. Finally, we highlight some of the methods, including mass spectrometry-based analyses, available for the identification, prioritization, and mechanistic interrogation of PTMs.

Intercellular communication within the virus microenvironment affects the susceptibility of cells to secondary viral infections

Communication between infected cells and cells in the surrounding tissue is a determinant of viral spread. However, it remains unclear how cells in close or distant proximity to an infected cell respond to primary or secondary infections. We establish a cell-based system to characterize a virus microenvironment, distinguishing infected, neighboring, and distal cells. Cell sorting, microscopy, proteomics, and cell cycle assays allow resolving cellular features and functional consequences of proximity to infection. We show that human cytomegalovirus (HCMV) infection primes neighboring cells for both subsequent HCMV infections and secondary infections with herpes simplex virus 1 and influenza A. Neighboring cells exhibit mitotic arrest, dampened innate immunity, and altered extracellular matrix. Conversely, distal cells are poised to slow viral spread due to enhanced antiviral responses. These findings demonstrate how infection reshapes the microenvironment through intercellular signaling to facilitate spread and how spatial proximity to an infection guides cell fate.

Next-generation interaction proteomics for quantitative Jumbophage-bacteria interaction mapping

Host-pathogen interactions (HPIs) are pivotal in regulating establishment, progression, and outcome of an infection. Affinity-purification mass spectrometry has become instrumental for the characterization of HPIs, however the targeted nature of exogenously expressing individual viral proteins has limited its utility to the analysis of relatively small pathogens. Here we present the use of co-fractionation mass spectrometry (SEC-MS) for the high-throughput analysis of HPIs from native viral infections of two jumbophages ( ϕ KZ and ϕ PA3) in Pseudomonas aeruginosa . This enabled the detection > 6000 unique host-pathogen and > 200 pathogen-pathogen interactions for each phage, encompassing > 50% of the phage proteome. Interactome-wide comparison across phages showed similar perturbed protein interactions suggesting fundamentally conserved mechanisms of phage predation within the KZ-like phage family. Prediction of novel ORFs revealed a ϕ PA3 complex showing strong structural and sequence similarity to ϕ KZ nvRNAp, suggesting ϕ PA3 also possesses two RNA polymerases acting at different stages of the infection cycle. We further expanded our understanding on the molecular organization of the virion packaged and injected proteome by identifying 23 novel virion components and 5 novel injected proteins, as well as providing the first evidence for interactions between KZ-like phage proteins and the host ribosome. To enable accessibility to this data, we developed PhageMAP, an online resource for network query, visualization, and interaction prediction ( https://phagemap.ucsf.edu/ ). We anticipate this study will lay the foundation for the application of co-fractionation mass spectrometry for the scalable profiling of hostpathogen interactomes and protein complex dynamics upon infection.

Proteomic analysis of antiviral innate immunity

The capacity of host cells to detect and restrict an infecting virus rests on an array of cell-autonomous antiviral effectors and innate immune receptors that can trigger inflammatory processes at tissue and organismal levels. Dynamic changes in protein abundance, subcellular localisation, post-translational modifications and interactions with other biomolecules govern these processes. Proteomics is therefore an ideal experimental tool to discover novel mechanisms of host antiviral immunity. Additional information can be gleaned both about host and virus by systematic analysis of viral immune evasion strategies. In this review, we summarise recent advances in proteomic technologies and their application to antiviral innate immunity.

Plasma proteome perturbation for CMV DNAemia in kidney transplantation

BACKGROUND

Cytomegalovirus (CMV) infection, either de novo or as reactivation after allotransplantation and chronic immunosuppression, is recognized to cause detrimental alloimmune effects, inclusive of higher susceptibility to graft rejection and substantive impact on chronic graft injury and reduced transplant survival. To obtain further insights into the evolution and pathogenesis of CMV infection in an immunocompromised host we evaluated changes in the circulating host proteome serially, before and after transplantation, and during and after CMV DNA replication (DNAemia), as measured by quantitative polymerase chain reaction (QPCR).

METHODS

LC-MS-based proteomics was conducted on 168 serially banked plasma samples, from 62 propensity score-matched kidney transplant recipients. Patients were stratified by CMV replication status into 31 with CMV DNAemia and 31 without CMV DNAemia. Patients had blood samples drawn at protocol times of 3- and 12-months post-transplant. Additionally, blood samples were also drawn before and 1 week and 1 month after detection of CMV DNAemia. Plasma proteins were analyzed using an LCMS 8060 triple quadrupole mass spectrometer. Further, public transcriptomic data on time matched PBMCs samples from the same patients was utilized to evaluate integrative pathways. Data analysis was conducted using R and Limma.

RESULTS

Samples were segregated based on their proteomic profiles with respect to their CMV Dnaemia status. A subset of 17 plasma proteins was observed to predict the onset of CMV at 3 months post-transplant enriching platelet degranulation (FDR, 4.83E-06), acute inflammatory response (FDR, 0.0018), blood coagulation (FDR, 0.0018) pathways. An increase in many immune complex proteins were observed at CMV infection. Prior to DNAemia the plasma proteome showed changes in the anti-inflammatory adipokine vaspin (SERPINA12), copper binding protein ceruloplasmin (CP), complement activation (FDR = 0.03), and proteins enriched in the humoral (FDR = 0.01) and innate immune responses (FDR = 0.01).

CONCLUSION

Plasma proteomic and transcriptional perturbations impacting humoral and innate immune pathways are observed during CMV infection and provide biomarkers for CMV disease prediction and resolution. Further studies to understand the clinical impact of these pathways can help in the formulation of different types and duration of anti-viral therapies for the management of CMV infection in the immunocompromised host.

Thermal proteome profiling: Insights into protein modifications, associations, and functions

Tracking proteins' biophysical characteristics on a proteome-wide scale can provide valuable information on their functions and interactions. Thermal proteome profiling (TPP) is a multiplexed quantitative proteomics approach that measures changes in protein thermal stability-a key biophysical property-across different cellular states. Developed in 2014, as a target-deconvolution assay for drugs and other small molecules, TPP has since evolved to a system-level biochemical omics technique providing insights into context-dependent changes in protein states. In this review, we summarise key advances in the experimental and data analysis pipeline that have aided this transformation and discuss the recent developments and applications of TPP.

Overview of how HCMV manipulation of host cell intracellular trafficking networks can promote productive infection

Human cytomegalovirus (HCMV) is a significant cause of morbidity and mortality in the immunocompromised and developing fetuses. Infection has also been linked to chronic inflammatory diseases, cardiovascular disease, and the development of certain cancers. The wide range of pathologies associated with HCMV infection is attributable to the broad cellular tropism of the virus where infection affects every organ system. Like other viruses, HCMV must tailor host cells to support productive infection. In particular, HCMV dedicates many resources and various strategies to manipulate host intracellular trafficking networks to facilitate various aspects of infection across all infected cell types. The dysregulation of host intracellular trafficking networks allows the virus to translocate to the host cell nucleus for genome replication, facilitate nuclear import/export of viral proteins and immature virions, subvert the host immune response, form new organelles for progeny virion assembly, maturation and egress, and promote cellular migration and viral spread. However, due to their complex nature, many aspects of these processes are not well-studied. New research and omics-based technologies have recently begun to elucidate the extent to which HCMV dysregulates host cell trafficking machinery. Here we review the variety of strategies HCMV utilizes to dysregulate intracellular trafficking networks to promote productive infection.

In silico strategies to identify protein-protein interaction modulator in cell-to-cell transmission of SARS CoV2

RNA sequence data from SARS CoV2 patients helps to construct a gene network related to this disease. A detailed analysis of the human host response to SARS CoV2 with expression profiling by high-throughput sequencing has been accomplished with primary human lung epithelial cell lines. Using this data, the clustered gene annotation and gene network construction are performed with the help of the String database. Among the four clusters identified, only 1 with 44 genes could be annotated. Interestingly, this corresponded to basal cells with p = 1.37e - 05, which is relevant for respiratory tract infection. Functional enrichment analysis of genes present in the gene network has been completed using the String database and the Network Analyst tool. Among three types of cell-cell communication, only the anchoring junction between the basal cell membrane and the basal lamina in the host cell is involved in the virus transmission. In this junction point, a hemidesmosome structure plays a vital role in virus spread from one cell to basal lamina in the respiratory tract. In this protein complex structure, different integrin protein molecules of the host cell are used to promote the spread of virus infection into the extracellular matrix. So, small molecular blockers of different anchoring junction proteins, such as integrin alpha 3, integrin beta 1, can provide efficient protection against this deadly viral disease. ORF8 from SARS CoV2 virus can interact with both integrin proteins of human host. By using molecular docking technique, a ternary complex of these three proteins is modelled. Several oligopeptides are predicted as modulators for this ternary complex. In silico analysis of these modulators is very important to develop novel therapeutics for the treatment of SARS CoV2.

A network view of human immune system and virus-human interaction

The immune system is highly networked and complex, which is continuously changing as encountering old and new pathogens. However, reductionism-based researches do not give a systematic understanding of the molecular mechanism of the immune response and viral pathogenesis. Here, we present HUMPPI-2022, a high-quality human protein-protein interaction (PPI) network, containing > 11,000 protein-coding genes with > 78,000 interactions. The network topology and functional characteristics analyses of the immune-related genes (IRGs) reveal that IRGs are mostly located in the center of the network and link genes of diverse biological processes, which may reflect the gene pleiotropy phenomenon. Moreover, the virus-human interactions reveal that pan-viral targets are mostly hubs, located in the center of the network and enriched in fundamental biological processes, but not for coronavirus. Finally, gene age effect was analyzed from the view of the host network for IRGs and virally-targeted genes (VTGs) during evolution, with IRGs gradually became hubs and integrated into host network through bridging functionally differentiated modules. Briefly, HUMPPI-2022 serves as a valuable resource for gaining a better understanding of the composition and evolution of human immune system, as well as the pathogenesis of viruses.

Protein Interaction Networks of Catalytically Active and Catalytically Inactive PqsE in Pseudomonas aeruginosa

Pseudomonas aeruginosa is a human pathogen that relies on quorum sensing to establish infections. The PqsE quorum-sensing protein is required for P. aeruginosa virulence factor production and infection. PqsE has a reported enzymatic function in the biosynthesis of the quorum-sensing autoinducer called PQS. However, this activity is redundant because, in the absence of PqsE, this role is fulfilled by alternative thioesterases. Rather, PqsE drives P. aeruginosa pathogenic traits via a protein-protein interaction with the quorum-sensing receptor/transcription factor RhlR, an interaction that enhances the affinity of RhlR for target DNA sequences. PqsE catalytic activity is dispensable for interaction with RhlR. Thus, the virulence function of PqsE can be decoupled from its catalytic function. Here, we present an immunoprecipitation-mass spectrometry method employing enhanced green fluorescent protein-PqsE fusions to define the protein interactomes of wild-type PqsE and the catalytically inactive PqsE(D73A) variant in P. aeruginosa and their dependence on RhlR. Several proteins were identified to have specific interactions with wild-type PqsE while not forming associations with PqsE(D73A). In the ΔrhlR strain, an increased number of specific PqsE interactors were identified, including the partner autoinducer synthase for RhlR, called RhlI. Collectively, these results suggest that specific protein-protein interactions depend on PqsE catalytic activity and that RhlR may prevent proteins from interacting with PqsE, possibly due to competition between RhlR and other proteins for PqsE binding. Our results provide a foundation for the identification of the in vivo PqsE catalytic function and, potentially, new proteins involved in P. aeruginosa quorum sensing. IMPORTANCE Pseudomonas aeruginosa causes hospital-borne infections in vulnerable patients, including immunocompromised individuals, burn victims, and cancer patients undergoing chemotherapy. There are no effective treatments for P. aeruginosa infections, which are usually broadly resistant to antibiotics. Animal models show that, to establish infection and to cause illness, P. aeruginosa relies on an interaction between two proteins, namely, PqsE and RhlR. There could be additional protein-protein interactions involving PqsE, which, if defined, could be exploited for the design of new therapeutic strategies to combat P. aeruginosa. Here, we reveal previously unknown protein interactions in which PqsE participates, which will be investigated for potential roles in pathogenesis.

Biological Significance of Dual Mutations A494D and E495K of the Genotype III Newcastle Disease Virus Hemagglutinin-Neuraminidase In Vitro and In Vivo

As a multifunctional protein, the hemagglutinin-neuraminidase (HN) protein of Newcastle disease virus (NDV) is involved in various biological functions. A velogenic genotype III NDV JS/7/05/Ch evolving from the mesogenic vaccine strain Mukteswar showed major amino acid (aa) mutations in the HN protein. However, the precise biological significance of the mutant HN protein remains unclear. This study sought to investigate the effects of the mutant HN protein on biological activities in vitro and in vivo. The mutant HN protein (JS/7/05/Ch-type HN) significantly enhanced the hemadsorption (HAd) and fusion promotion activities but impaired the neuraminidase (NA) activity compared with the original HN protein (Mukteswar-type HN). Notably, A494D and E495K in HN exhibited a synergistic role in regulating biological activities. Moreover, the mutant HN protein, especially A494D and E495K in HN, enhanced the F protein cleavage level, which can contribute to the activation of the F protein. In vitro infection assays further showed that NDVs bearing A494D and E495K in HN markedly impaired the cell viability. Simultaneously, A494D and E495K in HN enhanced virus replication levels at the early stage of infection but weakened later in infection, which might be associated with the attenuated NA activity and cell viability. Furthermore, the animal experiments showed that A494D and E495K in HN enhanced case fatality rates, virus shedding, virus circulation, and histopathological damages in NDV-infected chickens. Overall, these findings highlight the importance of crucial aa mutations in HN in regulating biological activities of NDV and expand the understanding of the enhanced pathogenicity of the genotype III NDV.

Intermittent bulk release of human cytomegalovirus

Human Cytomegalovirus (HCMV) can infect a variety of cell types by using virions of varying glycoprotein compositions. It is still unclear how this diversity is generated, but spatio-temporally separated envelopment and egress pathways might play a role. So far, one egress pathway has been described in which HCMV particles are individually enveloped into small vesicles and are subsequently exocytosed continuously. However, some studies have also found enveloped virus particles inside multivesicular structures but could not link them to productive egress or degradation pathways. We used a novel 3D-CLEM workflow allowing us to investigate these structures in HCMV morphogenesis and egress at high spatio-temporal resolution. We found that multiple envelopment events occurred at individual vesicles leading to multiviral bodies (MViBs), which subsequently traversed the cytoplasm to release virions as intermittent bulk pulses at the plasma membrane to form extracellular virus accumulations (EVAs). Our data support the existence of a novel bona fide HCMV egress pathway, which opens the gate to evaluate divergent egress pathways in generating virion diversity.

Zika Virus Strains and Dengue Virus Induce Distinct Proteomic Changes in Neural Stem Cells and Neurospheres

Brain abnormalities and congenital malformations have been linked to the circulating strain of Zika virus (ZIKV) in Brazil since 2016 during the microcephaly outbreak; however, the molecular mechanisms behind several of these alterations and differential viral molecular targets have not been fully elucidated. Here we explore the proteomic alterations induced by ZIKV by comparing the Brazilian (Br ZIKV) and the African (MR766) viral strains, in addition to comparing them to the molecular responses to the Dengue virus type 2 (DENV). Neural stem cells (NSCs) derived from induced pluripotent stem (iPSCs) were cultured both as monolayers and in suspension (resulting in neurospheres), which were then infected with ZIKV (Br ZIKV or ZIKV MR766) or DENV to assess alterations within neural cells. Large-scale proteomic analyses allowed the comparison not only between viral strains but also regarding the two- and three-dimensional cellular models of neural cells derived from iPSCs, and the effects on their interaction. Altered pathways and biological processes were observed related to cell death, cell cycle dysregulation, and neurogenesis. These results reinforce already published data and provide further information regarding the biological alterations induced by ZIKV and DENV in neural cells.

RANBP2 and USP9x regulate nuclear import of adenovirus minor coat protein IIIa

As intracellular parasites, viruses exploit cellular proteins at every stage of infection. Adenovirus outbreaks are associated with severe acute respiratory illnesses and conjunctivitis, with no specific antiviral therapy available. An adenoviral vaccine based on human adenovirus species D (HAdV-D) is currently in use for COVID-19. Herein, we investigate host interactions of HAdV-D type 37 (HAdV-D37) protein IIIa (pIIIa), identified by affinity purification and mass spectrometry (AP-MS) screens. We demonstrate that viral pIIIa interacts with ubiquitin-specific protease 9x (USP9x) and Ran-binding protein 2 (RANBP2). USP9x binding did not invoke its signature deubiquitination function but rather deregulated pIIIa-RANBP2 interactions. In USP9x-knockout cells, viral genome replication and viral protein expression increased compared to wild type cells, supporting a host-favored mechanism for USP9x. Conversely, RANBP2-knock down reduced pIIIa transport to the nucleus, viral genome replication, and viral protein expression. Also, RANBP2-siRNA pretreated cells appeared to contain fewer mature viral particles. Transmission electron microscopy of USP9x-siRNA pretreated, virus-infected cells revealed larger than typical paracrystalline viral arrays. RANBP2-siRNA pretreatment led to the accumulation of defective assembly products at an early maturation stage. CRM1 nuclear export blockade by leptomycin B led to the retention of pIIIa within cell nuclei and hindered pIIIa-RANBP2 interactions. In-vitro binding analyses indicated that USP9x and RANBP2 bind to C-terminus of pIIIa amino acids 386–563 and 386–510, respectively. Surface plasmon resonance testing showed direct pIIIa interaction with recombinant USP9x and RANBP2 proteins, without competition. Using an alternative and genetically disparate adenovirus type (HAdV-C5), we show that the demonstrated pIIIa interaction is also important for a severe respiratory pathogen. Together, our results suggest that pIIIa hijacks RANBP2 for nuclear import and subsequent virion assembly. USP9x counteracts this interaction and negatively regulates virion synthesis. This analysis extends the scope of known adenovirus-host interactions and has potential implications in designing new antiviral therapeutics.

The compact genomes of viruses must code for proteins with multiple functions, including those that assist with cell entry, replication, and escape from the host immune defenses. Viruses succeed in every stage of this process by hijacking critical cellular proteins for their propagation. Hence, identifying virus-host protein interactions may permit identifying therapeutic applications that restrict viral processes. Human adenovirus structural proteins link together to produce infectious virions. Protein IIIa is required to assemble fully packaged virions, but its interactions with host factors are unknown. Here, we identify novel host protein interactions of pIIIa with cellular RANBP2 and USP9x. We demonstrate that by interacting with cellular RANBP2, viral pIIIa gains entry to the nucleus for subsequent virion assembly and replication. Reduced RANBP2 expression inhibited pIIIa entry into the nucleus, minimized viral replication and viral protein expression, and led to accumulation of defective assembly products in the infected cells. As a defense against viral infection, USP9x reduces the interaction between pIIIa and RANBP2, resulting in decreased viral propagation. We also show that the identified pIIIa-host interactions are crucial in two disparate HAdV types with diverse disease implications.

The unconventional way out-Egress of HCMV through multiviral bodies

Human cytomegalovirus (HCMV) is a ubiquitous herpesvirus and the leading cause of congenital disabilities as well as a significant cause of disease in immunocompromised patients. The envelopment and egress of HCMV particles is an essential step of the viral life cycle as it determines viral spread and potentially tropism. Here we review the current literature on HCMV envelopment and egress with a particular focus on the role of virus-containing multivesicular body-like vesicles for virus egress and spread. We discuss the difficulties of determining the cellular provenance of these structures in light of viral redistribution of cellular marker proteins and provide potential paths to illuminate their genesis. Finally, we discuss how divergent egress pathways could result in virions of different tropisms.

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.

ProSAP: a GUI software tool for statistical analysis and assessment of thermal stability data

The Cellular Thermal Shift Assay (CETSA) plays an important role in drug-target identification, and statistical analysis is a crucial step significantly affecting conclusion. We put forward ProSAP (Protein Stability Analysis Pod), an open-source, cross-platform and user-friendly software tool, which provides multiple methods for thermal proteome profiling (TPP) analysis, nonparametric analysis (NPA), proteome integral solubility alteration and isothermal shift assay (iTSA). For testing the performance of ProSAP, we processed several datasets and compare the performance of different algorithms. Overall, TPP analysis is more accurate with fewer false positive targets, but NPA methods are flexible and free from parameters. For iTSA, edgeR and DESeq2 identify more true targets than t-test and Limma, but when it comes to ranking, the four methods show not much difference. ProSAP software is available at https://github.com/hcji/ProSAP and https://zenodo.org/record/5763315.

Dynamics of huntingtin protein interactions in the striatum identifies candidate modifiers of Huntington disease

Huntington disease (HD) is a monogenic neurodegenerative disorder with one causative gene, huntingtin (HTT). Yet, HD pathobiology is multifactorial, suggesting that cellular factors influence disease progression. Here, we define HTT protein-protein interactions (PPIs) perturbed by the mutant protein with expanded polyglutamine in the mouse striatum, a brain region with selective HD vulnerability. Using metabolically labeled tissues and immunoaffinity purification-mass spectrometry, we establish that polyglutamine-dependent modulation of HTT PPI abundances and relative stability starts at an early stage of pathogenesis in a Q140 HD mouse model. We identify direct and indirect PPIs that are also genetic disease modifiers using in-cell two-hybrid and behavioral assays in HD human cell and Drosophila models, respectively. Validated, disease-relevant mHTT-dependent interactions encompass mediators of synaptic neurotransmission (SNAREs and glutamate receptors) and lysosomal acidification (V-ATPase). Our study provides a resource for understanding mHTT-dependent dysfunction in cortico-striatal cellular networks, partly through impaired synaptic communication and endosomal-lysosomal system. A record of this paper's Transparent Peer Review process is included in the supplemental information.

Virus-host protein interactions as footprints of human cytomegalovirus replication

Human cytomegalovirus (HCMV) is a pervasive β-herpesvirus that causes lifelong infection. The lytic replication cycle of HCMV is characterized by global organelle remodeling and dynamic virus-host interactions, both of which are necessary for productive HCMV replication. With the advent of new technologies for investigating protein-protein and protein-nucleic acid interactions, numerous critical interfaces between HCMV and host cells have been identified. Here, we review temporal and spatial virus-host interactions that support different stages of the HCMV replication cycle. Understanding how HCMV interacts with host cells during entry, replication, and assembly, as well as how it interfaces with host cell metabolism and immune responses promises to illuminate processes that underlie the biology of infection and the resulting pathologies.

Prediction of Non-canonical Routes for SARS-CoV-2 Infection in Human Placenta Cells

The SARS-CoV-2 is the causative agent of the COVID-19 pandemic. The data available about COVID-19 during pregnancy have demonstrated placental infection; however, the mechanisms associated with intrauterine transmission of SARS-CoV-2 is still debated. Intriguingly, while canonical SARS-CoV-2 cell entry mediators are expressed at low levels in placental cells, the receptors for viruses that cause congenital infections such as the cytomegalovirus and Zika virus are highly expressed in these cells. Here we analyzed the transcriptional profile (microarray and single-cell RNA-Seq) of proteins potentially interacting with coronaviruses to identify non- canonical mediators of SARS-CoV-2 infection and replication in the placenta. Despite low levels of the canonical cell entry mediators ACE2 and TMPRSS2, we show that cells of the syncytiotrophoblast, villous cytotrophoblast, and extravillous trophoblast co-express high levels of the potential non-canonical cell-entry mediators DPP4 and CTSL. We also found changes in the expression of DAAM1 and PAICS genes during pregnancy, which are translated into proteins also predicted to interact with coronaviruses proteins. These results provide new insight into the interaction between SARS-CoV-2 and host proteins that may act as non-canonical routes for SARS-CoV-2 infection and replication in the placenta cells.

Target Discovery for Host-Directed Antiviral Therapies: Application of Proteomics Approaches

Current epidemics, such as AIDS or flu, and the emergence of new threatening pathogens, such as the one causing the current coronavirus disease 2019 (COVID-19) pandemic, represent major global health challenges. While vaccination is an important part of the arsenal to counter the spread of viral diseases, it presents limitations and needs to be complemented by efficient therapeutic solutions. Intricate knowledge of host-pathogen interactions is a powerful tool to identify host-dependent vulnerabilities that can be exploited to dampen viral replication. Such host-directed antiviral therapies are promising and are less prone to the development of drug-resistant viral strains. Here, we first describe proteomics-based strategies that allow the rapid characterization of host-pathogen interactions. We then discuss how such data can be exploited to help prioritize compounds with potential host-directed antiviral activity that can be tested in preclinical models.

Progress Identifying and Analyzing the Human Proteome: 2021 Metrics from the HUPO Human Proteome Project

The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) of the 19 778 predicted proteins coded in the human genome, a gain of 483 since 2020 from reports throughout the world reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 478 to 1421. This represents remarkable progress on the proteome parts list. The utilization of proteomics in a broad array of biological and clinical studies likewise continues to expand with many important findings and effective integration with other omics platforms. We present highlights from the Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, Musculo-Skeletal, Liver, and Cancers B/D-HPP teams and from the Knowledgebase, Mass Spectrometry, Antibody Profiling, and Pathology resource pillars, as well as ethical considerations important to the clinical utilization of proteomics and protein biomarkers.

Integration of Mass Spectrometry Data for Structural Biology

Mass spectrometry (MS) is increasingly being used to probe the structure and dynamics of proteins and the complexes they form with other macromolecules. There are now several specialized MS methods, each with unique sample preparation, data acquisition, and data processing protocols. Collectively, these methods are referred to as structural MS and include cross-linking, hydrogen-deuterium exchange, hydroxyl radical footprinting, native, ion mobility, and top-down MS. Each of these provides a unique type of structural information, ranging from composition and stoichiometry through to residue level proximity and solvent accessibility. Structural MS has proved particularly beneficial in studying protein classes for which analysis by classic structural biology techniques proves challenging such as glycosylated or intrinsically disordered proteins. To capture the structural details for a particular system, especially larger multiprotein complexes, more than one structural MS method with other structural and biophysical techniques is often required. Key to integrating these diverse data are computational strategies and software solutions to facilitate this process. We provide a background to the structural MS methods and briefly summarize other structural methods and how these are combined with MS. We then describe current state of the art approaches for the integration of structural MS data for structural biology. We quantify how often these methods are used together and provide examples where such combinations have been fruitful. To illustrate the power of integrative approaches, we discuss progress in solving the structures of the proteasome and the nuclear pore complex. We also discuss how information from structural MS, particularly pertaining to protein dynamics, is not currently utilized in integrative workflows and how such information can provide a more accurate picture of the systems studied. We conclude by discussing new developments in the MS and computational fields that will further enable in-cell structural studies.

Drug Target Identification in Tissues by Thermal Proteome Profiling

Drug target deconvolution can accelerate the drug discovery process by identifying a drug's targets (facilitating medicinal chemistry efforts) and off-targets (anticipating toxicity effects or adverse drug reactions). Multiple mass spectrometry-based approaches have been developed for this purpose, but thermal proteome profiling (TPP) remains to date the only one that does not require compound modification and can be used to identify intracellular targets in living cells. TPP is based on the principle that the thermal stability of a protein can be affected by its interactions. Recent developments of this approach have expanded its applications beyond drugs and cell cultures to studying protein-drug interactions and biological phenomena in tissues. These developments open up the possibility of studying drug treatment or mechanisms of disease in a holistic fashion, which can result in the design of better drugs and lead to a better understanding of fundamental biology. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Bioinformatic Analysis of Temporal and Spatial Proteome Alternations During Infections

Microbial pathogens have evolved numerous mechanisms to hijack host's systems, thus causing disease. This is mediated by alterations in the combined host-pathogen proteome in time and space. Mass spectrometry-based proteomics approaches have been developed and tailored to map disease progression. The result is complex multidimensional data that pose numerous analytic challenges for downstream interpretation. However, a systematic review of approaches for the downstream analysis of such data has been lacking in the field. In this review, we detail the steps of a typical temporal and spatial analysis, including data pre-processing steps (i.e., quality control, data normalization, the imputation of missing values, and dimensionality reduction), different statistical and machine learning approaches, validation, interpretation, and the extraction of biological information from mass spectrometry data. We also discuss current best practices for these steps based on a collection of independent studies to guide users in selecting the most suitable strategies for their dataset and analysis objectives. Moreover, we also compiled the list of commonly used R software packages for each step of the analysis. These could be easily integrated into one's analysis pipeline. Furthermore, we guide readers through various analysis steps by applying these workflows to mock and host-pathogen interaction data from public datasets. The workflows presented in this review will serve as an introduction for data analysis novices, while also helping established users update their data analysis pipelines. We conclude the review by discussing future directions and developments in temporal and spatial proteomics and data analysis approaches. Data analysis codes, prepared for this review are available from https://github.com/BabuLab-UofR/TempSpac, where guidelines and sample datasets are also offered for testing purposes.

Recent progress in mass spectrometry-based strategies for elucidating protein-protein interactions

Protein-protein interactions are fundamental to various aspects of cell biology with many protein complexes participating in numerous fundamental biological processes such as transcription, translation and cell cycle. MS-based proteomics techniques are routinely applied for characterising the interactome, such as affinity purification coupled to mass spectrometry that has been used to selectively enrich and identify interacting partners of a bait protein. In recent years, many orthogonal MS-based techniques and approaches have surfaced including proximity-dependent labelling of neighbouring proteins, chemical cross-linking of two interacting proteins, as well as inferring PPIs from the co-behaviour of proteins such as the co-fractionating profiles and the thermal solubility profiles of proteins. This review discusses the underlying principles, advantages, limitations and experimental considerations of these emerging techniques. In addition, a brief account on how MS-based techniques are used to investigate the structural and functional properties of protein complexes, including their topology, stoichiometry, copy number and dynamics, are discussed.

Quantitative Temporal Viromics

The abundance, localization, modifications, and protein-protein interactions of many host cell and virus proteins can change dynamically throughout the course of any viral infection. Studying these changes is critical for a comprehensive understanding of how viruses replicate and cause disease, as well as for the development of antiviral therapeutics and vaccines. Previously, we developed a mass spectrometry-based technique called quantitative temporal viromics (QTV), which employs isobaric tandem mass tags (TMTs) to allow precise comparative quantification of host and virus proteomes through a whole time course of infection. In this review, we discuss the utility and applications of QTV, exemplified by numerous studies that have since used proteomics with a variety of quantitative techniques to study virus infection through time. Expected final online publication date for the Annual Review of Virology, Volume 8 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Systematic profiling of protein complex dynamics reveals DNA-PK phosphorylation of IFI16 en route to herpesvirus immunity

Dynamically shifting protein-protein interactions (PPIs) regulate cellular responses to viruses and the resulting immune signaling. Here, we use thermal proximity coaggregation (TPCA) mass spectrometry to characterize the on-off behavior of PPIs during infection with herpes simplex virus 1 (HSV-1), a virus with an ancient history of coevolution with hosts. Advancing the TPCA analysis to infer associations de novo, we build a time-resolved portrait of thousands of host-host, virus-host, and virus-virus PPIs. We demonstrate that, early in infection, the DNA sensor IFI16 recruits the active DNA damage response kinase, DNA-dependent protein kinase (DNA-PK), to incoming viral DNA at the nuclear periphery. We establish IFI16 T149 as a substrate of DNA-PK upon viral infection or DNA damage. This phosphorylation promotes IFI16-driven cytokine responses. Together, we characterize the global dynamics of PPIs during HSV-1 infection, uncovering the co-regulation of IFI16 and DNA-PK functions as a missing link in immunity to herpesvirus infection.

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.

Digital image processing technology under backpropagation neural network and K-Means Clustering algorithm on nitrogen utilization rate of Chinese cabbages

The purposes are to monitor the nitrogen utilization efficiency of crops and intelligently evaluate the absorption of nutrients by crops during the production process. The research object is Chinese cabbage. The Chinese cabbage population with different agricultural parameters is constructed through different densities and nitrogen fertilizer application rates based on digital image processing technology, and an estimation NC (Nitrogen Content) model is established. The population is classified through the K-Means Clustering algorithm using the feature extraction method, and the Chinese cabbage population quality BPNN (Backpropagation Neural Network) model is constructed. The nonlinear mapping relationship between different agricultural parameters and population quality, and the contribution rate of each indicator, are studied. The nitrogen utilization of Chinese cabbage is monitored effectively. Results demonstrate that the proposed NC estimation model has correlation coefficients above 0.70 in different growth stages. This model can accurately estimate the NC of the Chinese cabbage population. The results of the Chinese cabbage population quality BPNN model show that the population planting density based on the seedling number is reasonable. The constructed population quality evaluation model has a high R2 value and a comparatively low RMSE (Root Mean Square Error) value for the quality evaluation of Chinese cabbage in different periods, showing that it applies to evaluate the population quality of Chinese cabbage in different growth stages. The constructed nitrogen utilization model and quality evaluation model can monitor the nutrient utilization of crops in different growth stages, ascertain the agricultural characteristics of other yield groups in different growth stages, and clarify the performance of agricultural parameters in different growth stages. The above results can provide some ideas for crop growth intelligent detection.

TMEM2 binds to CSNK2A3 to inhibit HBV infection via activation of the JAK/STAT pathway

To investigate mechanisms that TMEM2 activation inhibits hepatitis B virus (HBV) infection in hepatocarcinoma (HCC) cells, co-immunoprecipitation (Co-IP) and mass spectrometry were used in screening interacting proteins for TMEM2. Levels of casein kinase 2 subunit α3 (CSNK2A3) in HCC cells were found to be inhibited or overexpressed using siRNAs and pcDNA3.1-CSNK2A3, respectively. Effect of CSNK2A3 expression on cell proliferation was analyzed using MTS, while its effect on HBV infection was measured using ddPCR and IHC. Western blotting and JAK inhibitor ruxolitinib were also used to determine whether TMEM2-regulated CSNK2A3 expression and HBV infection were affected by JAK-STAT signaling. Co-IP and mass spectrometry results showed that CSNK2A3 interacts with TMEM2. Moreover, overexpression of CSNK2A3 significantly inhibited cell proliferation, while inhibition of CSNK2A3 promoted proliferation of HCC cells. In addition, overexpression of CSNK2A3 was observed to significantly enhance HBV infection, while siRNA knockdown of CSNK2A3 inhibited HBV infection. Notably, effect of CSNK2A3 overexpression on HBV infection was suppressed by TMEM2 overexpression. Further mechanistic analyses have revealed that TMEM2 could antagonize the effects of CSNK2A3 on cell proliferation and HBV infection via JAK-STAT pathway activation. In conclusion, TMEM2 has been determined to bind to CSNK2A3 to inhibit HBV infection via activation of the JAK-STAT pathway.

SARS-CoV-2 infection remodels the host protein thermal stability landscape

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global threat to human health and has compromised economic stability. In addition to the development of an effective vaccine, it is imperative to understand how SARS-CoV-2 hijacks host cellular machineries on a system-wide scale so that potential host-directed therapies can be developed. In situ proteome-wide abundance and thermal stability measurements using thermal proteome profiling (TPP) can inform on global changes in protein activity. Here we adapted TPP to high biosafety conditions amenable to SARS-CoV-2 handling. We discovered pronounced temporal alterations in host protein thermostability during infection, which converged on cellular processes including cell cycle, microtubule and RNA splicing regulation. Pharmacological inhibition of host proteins displaying altered thermal stability or abundance during infection suppressed SARS-CoV-2 replication. Overall, this work serves as a framework for expanding TPP workflows to globally important human pathogens that require high biosafety containment and provides deeper resolution into the molecular changes induced by SARS-CoV-2 infection.

Evolution of Protein Structure and Stability in Global Warming

This review focuses on the molecular signatures of protein structures in relation to evolution and survival in global warming. It is based on the premise that the power of evolutionary selection may lead to thermotolerant organisms that will repopulate the planet and continue life in general, but perhaps with different kinds of flora and fauna. Our focus is on molecular mechanisms, whereby known examples of thermoresistance and their physicochemical characteristics were noted. A comparison of interactions of diverse residues in proteins from thermophilic and mesophilic organisms, as well as reverse genetic studies, revealed a set of imprecise molecular signatures that pointed to major roles of hydrophobicity, solvent accessibility, disulfide bonds, hydrogen bonds, ionic and π-electron interactions, and an overall condensed packing of the higher-order structure, especially in the hydrophobic regions. Regardless of mutations, specialized protein chaperones may play a cardinal role. In evolutionary terms, thermoresistance to global warming will likely occur in stepwise mutational changes, conforming to the molecular signatures, such that each "intermediate" fits a temporary niche through punctuated equilibrium, while maintaining protein functionality. Finally, the population response of different species to global warming may vary substantially, and, as such, some may evolve while others will undergo catastrophic mass extinction.

Comparative Multiplexed Interactomics of SARS-CoV-2 and Homologous Coronavirus Nonstructural Proteins Identifies Unique and Shared Host-Cell Dependencies

Human coronaviruses (hCoVs) have become a threat to global health and society, as evident from the SARS outbreak in 2002 caused by SARS-CoV-1 and the most recent COVID-19 pandemic caused by SARS-CoV-2. Despite a high sequence similarity between SARS-CoV-1 and -2, each strain has a distinctive virulence. A better understanding of the basic molecular mechanisms mediating changes in virulence is needed. Here, we profile the virus-host protein-protein interactions of two hCoV nonstructural proteins (nsps) that are critical for virus replication. We use tandem mass tag-multiplexed quantitative proteomics to sensitively compare and contrast the interactomes of nsp2 and nsp4 from three betacoronavirus strains: SARS-CoV-1, SARS-CoV-2, and hCoV-OC43-an endemic strain associated with the common cold. This approach enables the identification of both unique and shared host cell protein binding partners and the ability to further compare the enrichment of common interactions across homologues from related strains. We identify common nsp2 interactors involved in endoplasmic reticulum (ER) Ca2+ signaling and mitochondria biogenesis. We also identify nsp4 interactors unique to each strain, such as E3 ubiquitin ligase complexes for SARS-CoV-1 and ER homeostasis factors for SARS-CoV-2. Common nsp4 interactors include N-linked glycosylation machinery, unfolded protein response associated proteins, and antiviral innate immune signaling factors. Both nsp2 and nsp4 interactors are strongly enriched in proteins localized at mitochondria-associated ER membranes suggesting a new functional role for modulating host processes, such as calcium homeostasis, at these organelle contact sites. Our results shed light on the role these hCoV proteins play in the infection cycle, as well as host factors that may mediate the divergent pathogenesis of OC43 from SARS strains. Our mass spectrometry workflow enables rapid and robust comparisons of multiple bait proteins, which can be applied to additional viral proteins. Furthermore, the identified common interactions may present new targets for exploration by host-directed antiviral therapeutics.