Proteomic identification of nuclear processes manipulated by cytomegalovirus early during infection

Neutralizing antibodies with neurotropic factor treatment maintain neurodevelopmental gene expression upon exposure to human cytomegalovirus

IMPORTANCE

Human cytomegalovirus (HCMV) infection is the leading cause of non-heritable birth defects worldwide. HCMV readily infects the early progenitor cell population of the developing brain, and we have found that infection leads to significantly downregulated expression of key neurodevelopmental transcripts. Currently, there are no approved therapies to prevent or mitigate the effects of congenital HCMV infection. Therefore, we used human-induced pluripotent stem cell-derived organoids and neural progenitor cells to elucidate the glycoproteins and receptors used in the viral entry process and whether antibody neutralization was sufficient to block viral entry and prevent disruption of neurodevelopmental gene expression. We found that blocking viral entry alone was insufficient to maintain the expression of key neurodevelopmental genes, but neutralization combined with neurotrophic factor treatment provided robust protection. Together, these studies offer novel insight into mechanisms of HCMV infection in neural tissues, which may aid future therapeutic development.

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.

Human cytomegalovirus lytic infection inhibits replication-dependent histone synthesis and requires stem loop binding protein function

Until now, it was not known if, how, or why pathogenic human viruses might modulate the de novo production of the replication-dependent (RD) histone proteins that decorate their DNA genomes within infected cells. Our finding that human cytomegalovirus (HCMV) inhibits RD histone production affirms that a virus targets this fundamental cellular process. Furthermore, our revelation that HCMV induces, relocalizes, and then commandeers the stem loop–binding protein (SLBP) for a purpose other than RD histone synthesis to support productive replication illuminates the potential for other functions of this highly conserved protein. The critical nature of SLBP for HCMV infection and of RD histone synthesis for cellular DNA replication highlights this process as a target for future antiviral and chemotherapeutic interventions.

Replication-dependent (RD) histones are deposited onto human cytomegalovirus (HCMV) genomes at the start of infection. We examined how HCMV affects the de novo production of RD histones and found that viral infection blocked the accumulation of RD histone mRNAs that normally occurs during the S phase. Furthermore, RD histone mRNAs present in HCMV-infected cells did not undergo the unique 3′ processing required for their normal nuclear export and translation. The protein that orchestrates processing in the nucleus, stem loop–binding protein (SLBP), was found predominantly in the cytoplasm, and RD histone proteins were not de novo synthesized in HCMV-infected cells. Intriguingly, however, we found that SLBP was required for the efficient synthesis and assembly of infectious progeny virions. We conclude that HCMV infection attenuates RD histone mRNA accumulation and processing and the de novo protein synthesis of the RD histones, while utilizing SLBP for an alternative purpose to support infectious virion production.

ProteoSign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics

Bottom-up proteomics analyses have been proved over the last years to be a powerful tool in the characterization of the proteome and are crucial for understanding cellular and organism behaviour. Through differential proteomic analysis researchers can shed light on groups of proteins or individual proteins that play key roles in certain, normal or pathological conditions. However, several tools for the analysis of such complex datasets are powerful, but hard-to-use with steep learning curves. In addition, some other tools are easy to use, but are weak in terms of analytical power. Previously, we have introduced ProteoSign, a powerful, yet user-friendly open-source online platform for protein differential expression/abundance analysis designed with the end-proteomics user in mind. Part of Proteosign's power stems from the utilization of the well-established Linear Models For Microarray Data (LIMMA) methodology. Here, we present a substantial upgrade of this computational resource, called ProteoSign v2, where we introduce major improvements, also based on user feedback. The new version offers more plot options, supports additional experimental designs, analyzes updated input datasets and performs a gene enrichment analysis of the differentially expressed proteins. We also introduce the deployment of the Docker technology and significantly increase the speed of a full analysis. ProteoSign v2 is available at http://bioinformatics.med.uoc.gr/ProteoSign.

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.

TRANSPIRE: A Computational Pipeline to Elucidate Intracellular Protein Movements from Spatial Proteomics Data Sets

Protein localization is paramount to protein function, and the intracellular movement of proteins underlies the regulation of numerous cellular processes. Given advances in spatial proteomics, the investigation of protein localization at a global scale has become attainable. Also becoming apparent is the need for dedicated analytical frameworks that allow the discovery of global intracellular protein movement events. Here, we describe TRANSPIRE, a computational pipeline that facilitates TRanslocation ANalysis of SPatIal pRotEomics data sets. TRANSPIRE leverages synthetic translocation profiles generated from organelle marker proteins to train a probabilistic Gaussian process classifier that predicts changes in protein distribution. This output is then integrated with information regarding co-translocating proteins and complexes and enriched gene ontology associations to discern the putative regulation and function of movement. We validate TRANSPIRE performance for predicting nuclear-cytoplasmic shuttling events. Analyzing an existing data set of nuclear and cytoplasmic proteomes during Kaposi Sarcoma-associated herpesvirus (KSHV)-induced cellular mRNA decay, we confirm that TRANSPIRE readily discerns expected translocations of RNA binding proteins. We next investigate protein translocations during infection with human cytomegalovirus (HCMV), a β-herpesvirus known to induce global organelle remodeling. We find that HCMV infection induces broad changes in protein localization, with over 800 proteins predicted to translocate during virus replication. Evident are protein movements related to HCMV modulation of host defense, metabolism, cellular trafficking, and Wnt signaling. For example, the low-density lipoprotein receptor (LDLR) translocates to the lysosome early in infection in conjunction with its degradation, which we validate by targeted mass spectrometry. Using microscopy, we also validate the translocation of the multifunctional kinase DAPK3, a movement that may contribute to HCMV activation of Wnt signaling.

ProteoSign: an end-user online differential proteomics statistical analysis platform

Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a user-friendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ProteoSign.

Cytomegalovirus Late Protein pUL31 Alters Pre-rRNA Expression and Nuclear Organization during Infection

The replication cycle of human cytomegalovirus (CMV) leads to drastic reorganization of domains in the host cell nucleus. However, the mechanisms involved and how these domains contribute to infection are not well understood. Our recent studies defining the CMV-induced nuclear proteome identified several viral proteins of unknown functions, including a protein encoded by the UL31 gene. We set out to define the role of UL31 in CMV replication. UL31 is predicted to encode a 74-kDa protein, referred to as pUL31, containing a bipartite nuclear localization signal, an intrinsically disordered region overlapping arginine-rich motifs, and a C-terminal dUTPase-like structure. We observed that pUL31 is expressed with true late kinetics and is localized to nucleolin-containing nuclear domains. However, pUL31 is excluded from the viral nuclear replication center. Nucleolin is a marker of nucleoli, which are membrane-less regions involved in regulating ribosome biosynthesis and cellular stress responses. Other CMV proteins associate with nucleoli, and we demonstrate that pUL31 specifically interacts with the viral protein, pUL76. Coexpression of both proteins altered pUL31 localization and nucleolar organization. During infection, pUL31 colocalizes with nucleolin but not the transcriptional activator, UBF. In the absence of pUL31, CMV fails to reorganize nucleolin and UBF and exhibits a replication defect at a low multiplicity of infection. Finally, we observed that pUL31 is necessary and sufficient to reduce pre-rRNA levels, and this was dependent on the dUTPase-like motif in pUL31. Our studies demonstrate that CMV pUL31 functions in regulating nucleolar biology and contributes to the reorganization of nucleoli during infection.IMPORTANCE Nucleolar biology is important during CMV infection with the nucleolar protein, with nucleolin playing a role in maintaining the architecture of the viral nuclear replication center. However, the extent of CMV-mediated regulation of nucleolar biology is not well established. Proteins within nucleoli regulate ribosome biosynthesis and p53-dependent cellular stress responses that are capable of inducing cell cycle arrest and/or apoptosis, and they are proposed targets for cancer therapies. This study establishes that CMV protein pUL31 is necessary and sufficient to regulate nucleolar biology involving the reorganization of nucleolar proteins. Understanding these processes will help define approaches to stimulate cellular intrinsic stress responses that are capable of inhibiting CMV infection.

Proteomic Screen for Cellular Targets of the Vaccinia Virus F10 Protein Kinase Reveals that Phosphorylation of mDia Regulates Stress Fiber Formation

Vaccinia virus, a complex dsDNA virus, is unusual in replicating exclusively within the cytoplasm of infected cells. Although this prototypic poxvirus encodes >200 proteins utilized during infection, a significant role for host proteins and cellular architecture is increasingly evident. The viral B1 kinase and H1 phosphatase are known to target cellular proteins as well as viral substrates, but little is known about the cellular substrates of the F10 kinase. F10 is essential for virion morphogenesis, beginning with the poorly understood process of diversion of membranes from the ER for the purpose of virion membrane biogenesis. To better understand the function of F10, we generated a cell line that carries a single, inducible F10 transgene. Using uninduced and induced cells, we performed stable isotope labeling of amino acids in cell culture (SILAC) coupled with phosphopeptide analysis to identify cellular targets of F10-mediated phosphorylation. We identified 27 proteins that showed statistically significant changes in phosphorylation upon the expression of the F10 kinase: 18 proteins showed an increase in phosphorylation whereas 9 proteins showed a decrease in phosphorylation. These proteins participate in several distinct cellular processes including cytoskeleton dynamics, membrane trafficking and cellular metabolism. One of the proteins with the greatest change in phosphorylation was mDia, a member of the formin family of cytoskeleton regulators; F10 induction led to increased phosphorylation on Ser22 Induction of F10 induced a statistically significant decrease in the percentage of cells with actin stress fibers; however, this change was abrogated when an mDia Ser22Ala variant was expressed. Moreover, expression of a Ser22Asp variant leads to a reduction of stress fibers even in cells not expressing F10. In sum, we present the first unbiased screen for cellular targets of F10-mediated phosphorylation, and in so doing describe a heretofore unknown mechanism for regulating stress fiber formation through phosphorylation of mDia. Data are available via ProteomeXchange with identifier PXD005246.

Proteomics and integrative omic approaches for understanding host-pathogen interactions and infectious diseases

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.