Virus-host interactome: Putting the accent on how it changes

Tandem mass tag-based quantitative proteomics analysis reveals the new regulatory mechanism of progranulin in influenza virus infection

Progranulin (PGRN) plays an important role in influenza virus infection. To gain insight into the potential molecular mechanisms by which PGRN regulates influenza viral replication, proteomic analyzes of whole mouse lung tissue from wild-type (WT) versus (vs) PGRN knockout (KO) mice were performed to identify proteins regulated by the absence vs. presence of PGRN. Our results revealed that PGRN regulated the differential expression of ALOX15, CD14, CD5L, and FCER1g, etc., and also affected the lysosomal activity in influenza virus infection. Collectively these findings provide a panoramic view of proteomic changes resulting from loss of PGRN and thereby shedding light on the functions of PGRN in influenza virus infection.

A binary interaction map between turnip mosaic virus and Arabidopsis thaliana proteomes

Viruses are obligate intracellular parasites that have co-evolved with their hosts to establish an intricate network of protein-protein interactions. Here, we followed a high-throughput yeast two-hybrid screening to identify 378 novel protein-protein interactions between turnip mosaic virus (TuMV) and its natural host Arabidopsis thaliana. We identified the RNA-dependent RNA polymerase NIb as the viral protein with the largest number of contacts, including key salicylic acid-dependent transcription regulators. We verified a subset of 25 interactions in planta by bimolecular fluorescence complementation assays. We then constructed and analyzed a network comprising 399 TuMV-A. thaliana interactions together with intravirus and intrahost connections. In particular, we found that the host proteins targeted by TuMV are enriched in different aspects of plant responses to infections, are more connected and have an increased capacity to spread information throughout the cell proteome, display higher expression levels, and have been subject to stronger purifying selection than expected by chance. The proviral or antiviral role of ten host proteins was validated by characterizing the infection dynamics in the corresponding mutant plants, supporting a proviral role for the transcriptional regulator TGA1. Comparison with similar studies with animal viruses, highlights shared fundamental features in their mode of action.

A multitask transfer learning framework for the prediction of virus-human protein-protein interactions

BACKGROUND

Viral infections are causing significant morbidity and mortality worldwide. Understanding the interaction patterns between a particular virus and human proteins plays a crucial role in unveiling the underlying mechanism of viral infection and pathogenesis. This could further help in prevention and treatment of virus-related diseases. However, the task of predicting protein-protein interactions between a new virus and human cells is extremely challenging due to scarce data on virus-human interactions and fast mutation rates of most viruses.

RESULTS

We developed a multitask transfer learning approach that exploits the information of around 24 million protein sequences and the interaction patterns from the human interactome to counter the problem of small training datasets. Instead of using hand-crafted protein features, we utilize statistically rich protein representations learned by a deep language modeling approach from a massive source of protein sequences. Additionally, we employ an additional objective which aims to maximize the probability of observing human protein-protein interactions. This additional task objective acts as a regularizer and also allows to incorporate domain knowledge to inform the virus-human protein-protein interaction prediction model.

CONCLUSIONS

Our approach achieved competitive results on 13 benchmark datasets and the case study for the SARS-COV-2 virus receptor. Experimental results show that our proposed model works effectively for both virus-human and bacteria-human protein-protein interaction prediction tasks. We share our code for reproducibility and future research at https://git.l3s.uni-hannover.de/dong/multitask-transfer .

TMT-based quantitative proteomics analysis reveals the attenuated replication mechanism of Newcastle disease virus caused by nuclear localization signal mutation in viral matrix protein

Nuclear localization of cytoplasmic RNA virus proteins mediated by intrinsic nuclear localization signal (NLS) plays essential roles in successful virus replication. We previously reported that NLS mutation in the matrix (M) protein obviously attenuates the replication and pathogenicity of Newcastle disease virus (NDV), but the attenuated replication mechanism remains unclear. In this study, we showed that M/NLS mutation not only disrupted M's nucleocytoplasmic trafficking characteristic but also impaired viral RNA synthesis and transcription. Using TMT-based quantitative proteomics analysis of BSR-T7/5 cells infected with the parental NDV rSS1GFP and the mutant NDV rSS1GFP-M/NLSm harboring M/NLS mutation, we found that rSS1GFP infection stimulated much greater quantities and more expression changes of differentially expressed proteins involved in host cell transcription, ribosomal structure, posttranslational modification, and intracellular trafficking than rSS1GFP-M/NLSm infection. Further in-depth analysis revealed that the dominant nuclear accumulation of M protein inhibited host cell transcription, RNA processing and modification, protein synthesis, posttranscriptional modification and transport; and this kind of inhibition could be weakened when most of M protein was confined outside the nucleus. More importantly, we found that the function of M protein in the cytoplasm effected the inhibition of TIFA expression in a dose-dependent manner, and promoted NDV replication by down-regulating TIFA/TRAF6/NF-κB-mediated production of cytokines. It was the first report about the involvement of M protein in NDV immune evasion. Taken together, our findings demonstrate that NDV replication is closely related to the nucleocytoplasmic trafficking of M protein, which accelerates our understanding of the molecular functions of NDV M protein.

Effects of Arbovirus Multi-Host Life Cycles on Dinucleotide and Codon Usage Patterns

Arthropod-borne viruses (arboviruses) of vertebrates including dengue, zika, chikungunya, Rift Valley fever, and blue tongue viruses cause extensive morbidity and mortality in humans, agricultural animals, and wildlife across the globe. As obligate intercellular pathogens, arboviruses must be well adapted to the cellular and molecular environment of both their arthropod (invertebrate) and vertebrate hosts, which are vastly different due to hundreds of millions of years of separate evolution. Here we discuss the comparative pressures on arbovirus RNA genomes as a result of a dual host life cycle, focusing on pressures that do not alter amino acids. We summarize what is currently known about arboviral genetic composition, such as dinucleotide and codon usage, and how cyclical infection of vertebrate and invertebrate hosts results in different genetic profiles compared with single-host viruses. To serve as a comparison, we compile what is known about arthropod tRNA, dinucleotide, and codon usages and compare this with vertebrates. Additionally, we discuss the potential roles of genetic robustness in arboviral evolution and how it may vary from other viruses. Overall, both arthropod and vertebrate hosts influence the resulting genetic composition of arboviruses, but a great deal remains to be investigated.

Time-Resolved Systems Medicine Reveals Viral Infection-Modulating Host Targets

Introduction: Drug-resistant infections are becoming increasingly frequent worldwide, causing hundreds of thousands of deaths annually. This is partly due to the very limited set of protein drug targets known for human-infecting viral genomes. The eleven influenza virus proteins, for instance, exploit host cell factors for replication and suppression of the antiviral immune responses. A systems medicine approach to identify relevant and druggable host factors would dramatically expand therapeutic options. Therapeutic target identification, however, has hitherto relied on static molecular networks, whereas in reality the interactome, in particular during an infection, is subject to constant change. Methods: We developed time-course network enrichment (TiCoNE), an expert-centered approach for discovering temporal response pathways. In the first stage of TiCoNE, time-series expression data is clustered in a human-augmented manner to identify groups of biological entities with coherent temporal responses. Throughout this process, the expert can add, remove, merge, or split temporal patterns. The resulting groups can then be mapped to an interaction network to identify enriched pathways and to analyze cross-talk enrichments and depletions between groups. Finally, temporal response groups of two experiments can be intersected, to identify condition-variant response patterns that represent promising drug-target candidates. Results: We applied TiCoNE to human gene expression data for influenza A virus infection and rhino virus infection, respectively. We then identified coherent temporal response patterns and employed our cross-talk analysis to establish two potential timelines of systems-level host responses for either infection. Next, we compared the two phenotypes and unraveled condition-variant temporal groups interacting on a networks level. The highest-ranking ones we then validated via literature search and wet-lab experiments. This not only confirmed many of our candidates as previously known, but we also identified phospholipid scramblase 1 (encoded by PLSCR1) as a previously not recognized host factor that is essential for influenza A virus infection. Conclusion: With TiCoNE we developed a novel approach for conjointly analyzing molecular networks with time-series expression data and demonstrated its power by identifying temporal drug-targets. We provide proof-of-concept that not only novel targets can be identified using our approach, but also that anti-infective drug target discovery can be enhanced by investigating temporal molecular networks of the host in response to viral infection.

Dual Analysis of Virus-Host Interactions: The Case of Ostreid herpesvirus 1 and the Cupped Oyster Crassostrea gigas

Dual analyses of the interactions between Ostreid herpesvirus 1 (OsHV-1) and the bivalve Crassostrea gigas during infection can unveil events critical to the onset and progression of this viral disease and can provide novel strategies for mitigating and preventing oyster mortality. Among the currently used “omics” technologies, dual transcriptomics (dual RNA-seq) coupled with the analysis of viral DNA in the host tissues has greatly advanced the knowledge of genes and pathways mostly contributing to host defense responses, expression profiles of annotated and unknown OsHV-1 open reading frames (ORFs), and viral genome variability. In addition to dual RNA-seq, proteomics and metabolomics analyses have the potential to add complementary information, needed to understand how a malacoherpesvirus can redirect and exploit the vital processes of its host. This review explores our current knowledge of “omics” technologies in the study of host-pathogen interactions and highlights relevant applications of these fields of expertise to the complex case of C gigas infections by OsHV-1, which currently threaten the mollusk production sector worldwide.

Comparative proteomic analysis reveals different responses in porcine lymph nodes to virulent and attenuated homologous African swine fever virus strains

African swine fever (ASF) is a pathology of pigs against which there is no treatment or vaccine. Understanding the equilibrium between innate and adaptive protective responses and immune pathology might contribute to the development of strategies against ASFV. Here we compare, using a proteomic approach, the course of the in vivo infection caused by two homologous strains: the virulent E75 and the attenuated E75CV1. Our results show a progressive loss of proteins by day 7 post-infection (pi) with E75, reflecting tissue destruction. Many signal pathways were affected by both infections but in different ways and extensions. Cytoskeletal remodelling and clathrin-endocytosis were affected by both isolates, while a greater number of proteins involved on inflammatory and immunological pathways were altered by E75CV1. 14-3-3 mediated signalling, related to immunity and apoptosis, was inhibited by both isolates. The implication of the Rho GTPases by E75CV1 throughout infection is also evident. Early events reflected the lack of E75 recognition by the immune system, an evasion strategy acquired by the virulent strains, and significant changes at 7 days post-infection (dpi), coinciding with the peak of infection and the time of death. The protein signature at day 31 pi with E75CV1 seems to reflect events observed at 1 dpi, including the upregulation of proteosomal subunits and molecules described as autoantigens (vimentin, HSPB1, enolase and lymphocyte cytosolic protein 1), which allow the speculation that auto-antibodies could contribute to chronic ASFV infections. Therefore, the use of proteomics could help understand ASFV pathogenesis and immune protection, opening new avenues for future research.

Protein Localization and Interaction Studies in Plants: Toward Defining Complete Proteomes by Visualization

Protein interaction and localization studies in plants are a fundamental component of achieving mechanistic understanding of virus:plant interactions at the systems level. Many such studies are conducted using transient expression assays in leaves of Nicotiana benthamiana, the most widely used experimental plant host in virology, examined by laser-scanning confocal microscopy. This chapter provides a workflow for protein interaction and localization experiments, with particular attention to the many control and supporting assays that may also need to be performed. Basic principles of microscopy are introduced to aid researchers in the early stages of adding imaging techniques to their experimental repertoire. Three major types of imaging-based experiments are discussed in detail: (i) protein localization using autofluorescent proteins, (ii) colocalization studies, and (iii) bimolecular fluorescence complementation, with emphasis on judicious interpretation of the data obtained from these approaches. In addition to establishing a general framework for protein localization experiments in plants, the need for proteome-scale localization projects is discussed, with emphasis on nuclear-localized proteins.

Prospects for engineering and improvement of cross-protective virus strains

Mild strain cross-protection is currently an important method for the production of high quality plant products; despite challenge from severe virus isolates the initial protecting strain precludes symptom development. The mechanism of cross-protection is not yet resolved as RNA silencing does not sufficiently explain the phenomenon. Six requirements have been put forward to ensure long-lasting protection. We propose two additional requirements for effective and durable mild strain cross-protection; mild strains based on knowledge of the mechanism and consideration of impacts to consumers. Future research on predicting phenotype from genotype and understanding virus-plant and virus-vector interactions will enable improvement of cross-protective strains. Shared international databases of whole ecosystem interactions across a wide range of virus patho- and symbiotic-systems will form the basis for making step-change advances towards our collective ability to engineer and improve mild strain cross-protection.

Genome sequence variation in the constricta strain dramatically alters the protein interaction and localization map of Potato yellow dwarf virus

The genome sequence of the constricta strain of Potato yellow dwarf virus (CYDV) was determined to be 12 792 nt long and organized into seven ORFs with the gene order 3'-N-X-P-Y-M-G-L-5', which encodes the nucleocapsid, phospho, movement, matrix, glyco, and RNA-dependent RNA polymerase proteins, respectively, except for X, which is of unknown function. Cloned ORFs for each gene, except L, were used to construct a protein interaction and localization map (PILM) for this virus, which shares greater than 80 % amino acid similarity in all ORFs except X and P with the sanguinolenta strain of this species (SYDV). Protein localization patterns and interactions unique to each viral strain were identified, resulting in strain-specific PILMs. Localization of CYDV and SYDV proteins in virus-infected cells mapped subcellular loci likely to be sites of replication, morphogenesis and movement.