Topology analysis and visualization of Potyvirus protein-protein interaction network

Adaptation of turnip mosaic virus to Arabidopsis thaliana involves rewiring of VPg-host proteome interactions

The outcome of a viral infection depends on a complex interplay between the host physiology and the virus, mediated through numerous protein-protein interactions. In a previous study, we used high-throughput yeast two-hybrid (HT-Y2H) to identify proteins in Arabidopsis thaliana that bind to the proteins encoded by the turnip mosaic virus (TuMV) genome. Furthermore, after experimental evolution of TuMV lineages in plants with mutations in defense-related or proviral genes, most mutations observed in the evolved viruses affected the VPg cistron. Among these mutations, D113G was a convergent mutation selected in many lineages across different plant genotypes, including cpr5-2 with constitutive expression of systemic acquired resistance. In contrast, mutation R118H specifically emerged in the jin1 mutant with affected jasmonate signaling. Using the HT-Y2H system, we analyzed the impact of these two mutations on VPg's interaction with plant proteins. Interestingly, both mutations severely compromised the interaction of VPg with the translation initiation factor eIF(iso)4E, a crucial interactor for potyvirus infection. Moreover, mutation D113G, but not R118H, adversely affected the interaction with RHD1, a zinc-finger homeodomain transcription factor involved in regulating DNA demethylation. Our results suggest that RHD1 enhances plant tolerance to TuMV infection. We also discuss our findings in a broad virus evolution context.

The 6-kilodalton peptide 1 in plant viruses of the family Potyviridae is a viroporin

Potyviridae, the largest family of plant RNA viruses, includes many important pathogens that significantly reduce the yields of many crops worldwide. In this study, we report that the 6-kilodalton peptide 1 (6K1), one of the least characterized potyviral proteins, is an endoplasmic reticulum-localized protein. AI-assisted structure modeling and biochemical assays suggest that 6K1 forms pentamers with a central hydrophobic tunnel, can increase the cell membrane permeability of Escherichia coli and Nicotiana benthamiana, and can conduct potassium in Saccharomyces cerevisiae. An infectivity assay showed that viral proliferation is inhibited by mutations that affect 6K1 multimerization. Moreover, the 6K1 or its homologous 7K proteins from other viruses of the Potyviridae family also have the ability to increase cell membrane permeability and transmembrane potassium conductance. Taken together, these data reveal that 6K1 and its homologous 7K proteins function as viroporins in viral infected cells.

Genetic basis of Arabidopsis thaliana responses to infection by naïve and adapted isolates of turnip mosaic virus

Plant viruses account for enormous agricultural losses worldwide, and the most effective way to combat them is to identify genetic material conferring plant resistance to these pathogens. Aiming to identify genetic associations with responses to infection, we screened a large panel of Arabidopsis thaliana natural inbred lines for four disease-related traits caused by infection by A. thaliana-naïve and -adapted isolates of the natural pathogen turnip mosaic virus (TuMV). We detected a strong, replicable association in a 1.5 Mb region on chromosome 2 with a 10-fold increase in relative risk of systemic necrosis. The region contains several plausible causal genes as well as abundant structural variation, including an insertion of a Copia transposon into a Toll/interleukin receptor (TIR-NBS-LRR) coding for a gene involved in defense, that could be either a driver or a consequence of the disease-resistance locus. When inoculated with TuMV, loss-of-function mutant plants of this gene exhibited different symptoms than wild-type plants. The direction and severity of symptom differences depended on the adaptation history of the virus. This increase in symptom severity was specific for infections with the adapted isolate. Necrosis-associated alleles are found worldwide, and their distribution is consistent with a trade-off between resistance during viral outbreaks and a cost of resistance otherwise, leading to negative frequency-dependent selection.

The Expression Pattern and Clinical Significance of Lysyl Oxidase Family in Gliomas

LOX (Lysyl oxidase) family participates in the catalysis of collagen and elastin to maintain ECM homeostasis. Glioma is the most common primary brain tumor and LOX family has not been systemic studied in glioma. In this study, we found LOX family members are upregulated expressed in gliomas samples. A protein-protein interaction network (PPIN) was construct to visualize and understand the differential expression pattern, as well as functional annotation, for LOX family and their interacting proteins, which involved in collagen fibril organization and MAPK signaling pathway. Through subcellular localization distribution, the LOX family members distribute both intracellular and extracellular. All five LOX members are consistently significantly correlate with dendritic cell both in immune infiltrate of GBM and LGG. Survival analysis showed that high expression of LOX family is associated with a poor prognosis of gliomas patients. These analyses provide important clues to identify the potential biological roles for LOX family in gliomas, which might serve as diagnosis markers.

Soybean Mosaic Virus 6K1 Interactors Screening and GmPR4 and GmBI1 Function Characterization

Host proteins are essential during virus infection, and viral factors must target numerous host factors to complete their infectious cycle. The mature 6K1 protein of potyviruses is required for viral replication in plants. However, the interaction between 6K1 and host factors is poorly understood. The present study aims to identify the host interacting proteins of 6K1. Here, the 6K1 of Soybean mosaic virus (SMV) was used as the bait to screen a soybean cDNA library to gain insights about the interaction between 6K1 and host proteins. One hundred and twenty-seven 6K1 interactors were preliminarily identified, and they were classified into six groups, including defense-related, transport-related, metabolism-related, DNA binding, unknown, and membrane-related proteins. Then, thirty-nine proteins were cloned and merged into a prey vector to verify the interaction with 6K1, and thirty-three of these proteins were confirmed to interact with 6K1 by yeast two-hybrid (Y2H) assay. Of the thirty-three proteins, soybean pathogenesis-related protein 4 (GmPR4) and Bax inhibitor 1 (GmBI1) were chosen for further study. Their interactions with 6K1 were also confirmed by bimolecular fluorescence complementation (BiFC) assay. Subcellular localization showed that GmPR4 was localized to the cytoplasm and endoplasmic reticulum (ER), and GmBI1 was located in the ER. Moreover, both GmPR4 and GmBI1 were induced by SMV infection, ethylene and ER stress. The transient overexpression of GmPR4 and GmBI1 reduced SMV accumulation in tobacco, suggesting their involvement in the resistance to SMV. These results would contribute to exploring the mode of action of 6K1 in viral replication and improve our knowledge of the role of PR4 and BI1 in SMV response.

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.

Plant Virus Adaptation to New Hosts: A Multi-scale Approach

Viruses are studied at each level of biological complexity: from within-cells to ecosystems. The same basic evolutionary forces and principles operate at each level: mutation and recombination, selection, genetic drift, migration, and adaptive trade-offs. Great efforts have been put into understanding each level in great detail, hoping to predict the dynamics of viral population, prevent virus emergence, and manage their spread and virulence. Unfortunately, we are still far from this. To achieve these ambitious goals, we advocate for an integrative perspective of virus evolution. Focusing in plant viruses, we illustrate the pervasiveness of the above-mentioned principles. Beginning at the within-cell level, we describe replication modes, infection bottlenecks, and cellular contagion rates. Next, we move up to the colonization of distal tissues, discussing the fundamental role of random events. Then, we jump beyond the individual host and discuss the link between transmission mode and virulence. Finally, at the community level, we discuss properties of virus-plant infection networks. To close this review we propose the multilayer network theory, in which elements at different layers are connected and submit to their own dynamics that feed across layers, resulting in new emerging properties, as a way to integrate information from the different levels.

Overview of methods for characterization and visualization of a protein–protein interaction network in a multi-omics integration context

At the heart of the cellular machinery through the regulation of cellular functions, protein–protein interactions (PPIs) have a significant role. PPIs can be analyzed with network approaches. Construction of a PPI network requires prediction of the interactions. All PPIs form a network. Different biases such as lack of data, recurrence of information, and false interactions make the network unstable. Integrated strategies allow solving these different challenges. These approaches have shown encouraging results for the understanding of molecular mechanisms, drug action mechanisms, and identification of target genes. In order to give more importance to an interaction, it is evaluated by different confidence scores. These scores allow the filtration of the network and thus facilitate the representation of the network, essential steps to the identification and understanding of molecular mechanisms. In this review, we will discuss the main computational methods for predicting PPI, including ones confirming an interaction as well as the integration of PPIs into a network, and we will discuss visualization of these complex data.

Defects in Plant Immunity Modulate the Rates and Patterns of RNA Virus Evolution

It is assumed that host genetic variability for susceptibility to infection conditions virus evolution. Differences in host susceptibility can drive a virus to diversify into strains that track different defense alleles (e.g. antigenic diversity) or to infect only the most susceptible genotypes. Here, we have studied how variability in host defenses determines the evolutionary fate of a plant RNA virus. We performed evolution experiments with Turnip mosaic potyvirus in Arabidopsis thaliana mutants that had disruptions in infection-response signaling pathways or in genes whose products are essential for potyvirus infection. Plant genotypes were classified into five phenogroups according to their response to infection. We found that evolution proceeded faster in more restrictive hosts than in more permissive ones. Most of the phenotypic differences shown by the ancestral virus across host genotypes were removed after evolution, suggesting the combined action of selection and chance. When all evolved viral lineages were tested in all plant genotypes used in the experiments, we found compelling evidences that the most restrictive plant genotypes selected for more generalist viruses, while more permissive genotypes selected for more specialist viruses. Sequencing the genomes of the evolved viral lineages, we found that selection targeted the multifunctional genome-linked protein VPg in most host genotypes. Overall, this work illustrates how different host defenses modulate the rates and extent of virus evolution.

Phase transitions in virology

Viruses have established relationships with almost every other living organism on Earth and at all levels of biological organization: from other viruses up to entire ecosystems. In most cases, they peacefully coexist with their hosts, but in most relevant cases, they parasitize them and induce diseases and pandemics, such as the AIDS and the most recent avian influenza and COVID-19 pandemic events, causing a huge impact on health, society, and economy. Viruses play an essential role in shaping the eco-evolutionary dynamics of their hosts, and have been also involved in some of the major evolutionary innovations either by working as vectors of genetic information or by being themselves coopted by the host into their genomes. Viruses can be studied at different levels of biological organization, from the molecular mechanisms of genome replication, gene expression and encapsidation, to global pandemics. All these levels are different and yet connected through the presence of threshold conditions allowing for the formation of a capsid, the loss of genetic information or epidemic spreading. These thresholds, as occurs with temperature separating phases in a liquid, define sharp qualitative types of behaviour. Thesephase transitionsare very well known in physics. They have been studied by means of simple, but powerful models able to capture their essential properties, allowing us to better understand them. Can the physics of phase transitions be an inspiration for our understanding of viral dynamics at different scales? Here we review well-known mathematical models of transition phenomena in virology. We suggest that the advantages of abstract, simplified pictures used in physics are also the key to properly understanding the origins and evolution of complexity in viruses. By means of several examples, we explore this multilevel landscape and how minimal models provide deep insights into a diverse array of problems. The relevance of these transitions in connecting dynamical patterns across scales and their evolutionary and clinical implications are outlined.

Uncovering the mechanism of the effects of Paeoniae Radix Alba on iron-deficiency anaemia through a network pharmacology-based strategy

BACKGROUND

Paeoniae Radix Alba, the root of the plant Paeonia lactiflora Pall, is a common blood-enriching drug in traditional Chinese medicine. Its effectiveness in the clinical treatment of anaemia is remarkable, but its potential pharmacologic mechanism has not been clarified.

METHODS

In this study, the potential pharmacologic mechanism of Paeoniae Radix Alba in the treatment of iron-deficiency anaemia was preliminarily elucidated through systematic and comprehensive network pharmacology.

RESULTS

Specifically, we obtained 15 candidate active ingredients from among 146 chemical components in Paeoniae Radix Alba. The ingredients were predicted to target 77 genes associated with iron-deficiency anaemia. In-depth analyses of these targets revealed that they were mostly associated with energy metabolism, cell proliferation, and stress responses, suggesting that Paeoniae Radix Alba helps alleviate iron-deficiency anaemia by affecting these processes. In addition, we conducted a core target analysis and a cluster analysis of protein-protein interaction (PPI) networks. The results showed that four pathways, the p53 signalling pathway, the IL-17 signalling pathway, the TNF signalling pathway and the AGE-RAGE signalling pathway in diabetic complications, may be major pathways associated with the ameliorative effects of Paeoniae Radix Alba on iron-deficiency anaemia. Moreover, molecular docking verified the credibility of the network for molecular target prediction.

CONCLUSIONS

Overall, this study predicted the functional ingredients in Paeoniae Radix Alba and their targets and uncovered the mechanism of action of this drug, providing new insights for advanced research on Paeoniae Radix Alba and other traditional Chinese medicines.

P3N-PIPO Interacts with P3 via the Shared N-Terminal Domain To Recruit Viral Replication Vesicles for Cell-to-Cell Movement

P3N-PIPO, the only dedicated movement protein (MP) of potyviruses, directs cylindrical inclusion (CI) protein from the cytoplasm to the plasmodesma (PD), where CI forms conical structures for intercellular movement. To better understand potyviral cell-to-cell movement, we further characterized P3N-PIPO using Turnip mosaic virus (TuMV) as a model virus. We found that P3N-PIPO interacts with P3 via the shared P3N domain and that TuMV mutants lacking the P3N domain of either P3N-PIPO or P3 are defective in cell-to-cell movement. Moreover, we found that the PIPO domain of P3N-PIPO is sufficient to direct CI to the PD, whereas the P3N domain is necessary for localization of P3N-PIPO to 6K2-labeled vesicles or aggregates. Finally, we discovered that the interaction between P3 and P3N-PIPO is essential for the recruitment of CI to cytoplasmic 6K2-containing structures and the association of 6K2-containing structures with PD-located CI inclusions. These data suggest that both P3N and PIPO domains are indispensable for potyviral cell-to-cell movement and that the 6K2 vesicles in proximity to PDs resulting from multipartite interactions among 6K2, P3, P3N-PIPO, and CI may also play an essential role in this process.IMPORTANCE Potyviruses include numerous economically important viruses that represent approximately 30% of known plant viruses. However, there is still limited information about the mechanism of potyviral cell-to-cell movement. Here, we show that P3N-PIPO interacts with and recruits CI to the PD via the PIPO domain and interacts with P3 via the shared P3N domain. We further report that the interaction of P3N-PIPO and P3 is associated with 6K2 vesicles and brings the 6K2 vesicles into proximity with PD-located CI structures. These results support the notion that the replication and cell-to-cell movement of potyviruses are processes coupled by anchoring viral replication complexes at the entrance of PDs, which greatly increase our knowledge of the intercellular movement of potyviruses.

Identifying Early Warning Signals for the Sudden Transition from Mild to Severe Tobacco Etch Disease by Dynamical Network Biomarkers

Complex systems exhibit critical thresholds at which they transition among alternative phases. Complex systems theory has been applied to analyze disease progression, distinguishing three stages along progression: (i) a normal noninfected state; (ii) a predisease state, in which the host is infected and responds and therapeutic interventions could still be effective; and (iii) an irreversible state, where the system is seriously threatened. The dynamical network biomarker (DNB) theory sought for early warnings of the transition from health to disease. Such DNBs might range from individual genes to complex structures in transcriptional regulatory or protein-protein interaction networks. Here, we revisit transcriptomic data obtained during infection of tobacco plants with tobacco etch potyvirus to identify DNBs signaling the transition from mild/reversible to severe/irreversible disease. We identified genes showing a sudden transition in expression along disease categories. Some of these genes cluster in modules that show the properties of DNBs. These modules contain both genes known to be involved in response to pathogens (e.g., ADH2, CYP19, ERF1, KAB1, LAP1, MBF1C, MYB58, PR1, or TPS5) and other genes not previously related to biotic stress responses (e.g., ABCI6, BBX21, NAP1, OSM34, or ZPN1).

Uncovering the mechanism of Maxing Ganshi Decoction on asthma from a systematic perspective: A network pharmacology study

Maxing Ganshi Decoction (MXGSD) is used widely for asthma over thousands of years, but its underlying pharmacological mechanisms remain unclear. In this study, systematic and comprehensive network pharmacology was utilized for the first time to reveal the potential pharmacological mechanisms of MXGSD on asthma. Specifically, we collected 141 bioactive components from the 600 components in MXGSD, which shared 52 targets common to asthma-related ones. In-depth network analysis of these 52 common targets indicated that asthma might be a manifestation of systemic neuro-immuno-inflammatory dysfunction in the respiratory system, and MXGSD could treat asthma through relieving airway inflammation, improving airway remodeling, and increasing drug responsiveness. After further cluster and enrichment analysis of the protein-protein interaction network of MXGSD bioactive component targets and asthma-related targets, we found that the neurotrophin signaling pathway, estrogen signaling pathway, PI3K-Akt signaling pathway, and ErbB signaling pathway might serve as the key points and principal pathways of MXGSD gene therapy for asthma from a systemic and holistic perspective, and also provides a novel idea for the development of new drugs for asthma.

In silico-prediction of protein-protein interactions network about MAPKs and PP2Cs reveals a novel docking site variants in Brachypodium distachyon

Protein-protein interactions (PPIs) underlie the molecular mechanisms of most biological processes. Mitogen-activated protein kinases (MAPKs) can be dephosphorylated by MAPK-specific phosphatases such as PP2C, which are critical to transduce extracellular signals into adaptive and programmed responses. However, the experimental approaches for identifying PPIs are expensive, time-consuming, laborious and challenging. In response, many computational methods have been developed to predict PPIs. Yet, these methods have inherent disadvantages such as high false positive and negative results. Thus, it is crucial to develop in silico approaches for predicting PPIs efficiently and accurately. In this study, we identified PPIs among 16 BdMAPKs and 86 BdPP2Cs in B. distachyon using a novel docking approach. Further, we systematically investigated the docking site (D-site) of BdPP2C which plays a vital role for recognition and docking of BdMAPKs. D-site analysis revealed that there were 96 pairs of PPIs including all BdMAPKs and most BdPP2Cs, which indicated that BdPP2C may play roles in other signaling networks. Moreover, most BdPP2Cs have a D-site for BdMAPKs in our prediction results, which suggested that our method can effectively predict PPIs, as confirmed by their 3D structure. In addition, we validated this methodology with known Arabidopsis and yeast phosphatase-MAPK interactions from the STRING database. The results obtained provide a vital research resource for exploring an accurate network of PPIs between BdMAPKs and BdPP2Cs.

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

Protein-protein interaction networks and different clustering analysis in Burkitt's lymphoma

OBJECTIVE

Burkitt's lymphoma (BL) is a highly aggressive malignant lymphoma, its molecular biological mechanism has not been fully investigated. The construction of protein-protein interaction (PPI) networks and the identification of complexes through a cluster analysis are important research directions in the post-genome era. However, different cluster analysis algorithms have their own characteristics, and a single analysis has some limitations. In this study, we obtained the target and pathway information of BL using different clustering analyses.

MATERIAL AND METHODS

First, we obtained 50 BL genes by screening the Online Mendelian Inheritance in Man (OMIM) database; their related genes were further extracted from the literature. The PPI network was constructed with the Search Tool for Retrieval of Interacting Genes/Proteins (STRING). Afterward, the interaction data were input in Cytoscape3.4.0 software and related plug-ins were used to implement topology analysis and clustering analysis. Functional analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were used to characterize the biological importance of the clusters.

RESULTS

We constructed a PPI network consisting of 459 nodes (proteins) and 1399 sides (interactions), 12 genes and 8 signaling pathways were found to be closely related to BL.

CONCLUSION

In this study, the use of combined algorithms to analyse gene interactions provides a new perspective for network-based analysis. The results of this study reveal new insights into the molecular mechanisms underlying BL, which may be novel therapeutic targets for disease management and may provide a bioinformatic basis for the further understanding of BL.

The Potyvirus Particle Recruits the Plant Translation Initiation Factor eIF4E by Means of the VPg covalently Linked to the Viral RNA

The viral protein genome-linked (VPg) of potyviruses is a protein covalently linked to the 5' end of viral RNA. It interacts with eIF4E, a component of the cellular translation initiation complex. It has been suggested that the 5' RNA-linked VPg could mimic the cellular mRNA cap, promoting synthesis of viral proteins. Here, we report evidence for recruitment of the plant eIF4E by Lettuce mosaic virus (LMV, potyvirus) particles via the 5' RNA-linked VPg. Analysis of the viral population was performed by enzyme-linked immunosorbent assay-based tests, either with crude extracts of LMV-infected tissues or purified viral particles. In both cases, LMV-VPg and LMV-eIF4E subpopulations could be detected. After reaching a maximum within the first 2 weeks postinoculation, these populations decreased and very few labeled particles were found later than 3 weeks postinoculation. The central domain of VPg (CD-VPg) was found to be exposed at the surface of the particles. Using a purified recombinant lettuce eIF4E and CD-VPg-specific antibodies, we demonstrate that the plant factor binds to the VPg via its central domain. Moreover, the plant eIF4E factor could be imaged at one end of the particles purified from LMV plant extracts, by immunoredox atomic force microscopy coupled to scanning electrochemical microscopy. We discuss the biological significance of these results.

Engineering resistance to virus transmission

Engineering plants for resistance to virus transmission by invertebrate vectors has lagged behind other forms of plant protection. Vectors typically transmit more than one virus. Thus, vector resistance could provide a wider range of protection than defenses directed solely against one virus or virus group. We discuss current knowledge of vector-host-virus interactions, the roles of viral gene products in host and vector manipulation, and the effects of semiochemicals on host-vector interactions, and how this knowledge could be employed to disrupt transmission dynamics. We also discuss how resistance to vectors could be generated through genetic engineering or gene editing or indirectly through use of biocontrol using plant-resident viruses that infect vectors.

Fusion of genomic, proteomic and phenotypic data: the case of potyviruses

Data fusion has been widely applied to analyse different sources of information, combining all of them in a single multivariate model. This methodology is mandatory when different omic data sets must be integrated to fully understand an organism using a systems biology approach. Here, a data fusion procedure is presented to combine genomic, proteomic and phenotypic data sets gathered for Tobacco etch virus (TEV). The genomic data correspond to random mutations inserted in most viral genes. The proteomic data represent both the effect of these mutations on the encoded proteins and the perturbation induced by the mutated proteins to their neighbours in the protein-protein interaction network (PPIN). Finally, the phenotypic trait evaluated for each mutant virus is replicative fitness. To analyse these three sources of information a Partial Least Squares (PLS) regression model is fitted in order to extract the latent variables from data that explain (and relate) the significant variables to the fitness of TEV. The final output of this methodology is a set of functional modules of the PPIN relating topology and mutations with fitness. Throughout the re-analysis of these diverse TEV data, we generated valuable information on the mechanism of action of certain mutations and how they translate into organismal fitness. Results show that the effect of some mutations goes beyond the protein they directly affect and spreads on the PPIN to neighbour proteins, thus defining functional modules.

Interaction network of tobacco etch potyvirus NIa protein with the host proteome during infection

BACKGROUND

The genomes of plant viruses have limited coding capacity, and to complete their infectious cycles, viral factors must target, direct or indirectly, many host elements. However, the interaction networks between viruses and host factors are poorly understood. The genus Potyvirus is the largest group of plus-strand RNA viruses infecting plants. Potyviral nuclear inclusion a (NIa) plays many roles during infection. NIa is a polyprotein consisting of two domains, viral protein genome-linked (VPg) and protease (NIaPro), separated by an inefficiently utilized self-proteolytic site. To gain insights about the interaction between potyviral NIa and the host cell during infection, we constructed Tobacco etch virus (TEV, genus Potyvirus) infectious clones in which the VPg or the NIaPro domains of NIa were tagged with the affinity polypeptide Twin-Strep-tag and identified the host proteins targeted by the viral proteins by affinity purification followed by mass spectrometry analysis (AP-MS).

RESULTS

We identified 232 different Arabidopsis thaliana proteins forming part of complexes in which TEV NIa products were also involved. VPg and NIaPro specifically targeted 89 and 76 of these proteins, respectively, whereas 67 proteins were targeted by both domains and considered full-length NIa targets. Taking advantage of the currently known A. thaliana interactome, we constructed a protein interaction network between TEV NIa domains and 516 host proteins. The most connected elements specifically targeted by VPg were G-box regulating factor 6 and mitochondrial ATP synthase δ subunit; those specifically targeted by NIaPro were plasma membrane aquaporin PIP2;7 and actin 7, whereas those targeted by full-length NIa were heat shock protein 70-1 and photosystem protein LHCA3. Moreover, a contextualization in the global A. thaliana interactome showed that NIa targets are not more connected with other host proteins than expected by chance, but are in a position that allows them to connect with other host proteins in shorter paths. Further analysis of NIa-targeted host proteins revealed that they are mainly involved in response to stress, metabolism, photosynthesis, and localization. Many of these proteins are connected with the phytohormone ethylene.

CONCLUSIONS

Potyviral NIa targets many host elements during infection, establishing a network in which information is efficiently transmitted.

The impact of high-order epistasis in the within-host fitness of a positive-sense plant RNA virus

RNA viruses are the main source of emerging infectious diseases because of the evolutionary potential bestowed by their fast replication, large population sizes and high mutation and recombination rates. However, an equally important property, which is usually neglected, is the topography of the fitness landscape. How many fitness maxima exist and how well they are connected is especially interesting, as this determines the number of accessible evolutionary pathways. To address this question, we have reconstructed a region of the fitness landscape of tobacco etch potyvirus constituted by mutations observed during the experimental adaptation of the virus to the novel host Arabidopsis thaliana. Fitness was measured for many genotypes and showed the existence of multiple peaks and holes in the landscape. We found prevailing epistatic effects between mutations, with cases of reciprocal sign epistasis being common among pairs of mutations. We also found that high-order epistasis was as important as pairwise epistasis in their contribution to fitness. Therefore, results suggest that the landscape was rugged due to the existence of holes caused by lethal genotypes, that a very limited number of potential neutral paths exist and that it contained a single adaptive peak.

Biotechnological strategies and tools for Plum pox virus resistance: trans-, intra-, cis-genesis, and beyond

Plum pox virus (PPV) is the etiological agent of sharka, the most devastating and economically important viral disease affecting Prunus species. It is widespread in most stone fruits producing countries even though eradication and quarantine programs are in place. The development of resistant cultivars and rootstocks remains the most ecologically and economically suitable approach to achieve long-term control of sharka disease. However, the few PPV resistance genetic resources found in Prunus germplasm along with some intrinsic biological features of stone fruit trees pose limits for efficient and fast breeding programs. This review focuses on an array of biotechnological strategies and tools, which have been used, or may be exploited to confer PPV resistance. A considerable number of scientific studies clearly indicate that robust and predictable resistance can be achieved by transforming plant species with constructs encoding intron-spliced hairpin RNAs homologous to conserved regions of the PPV genome. In addition, we discuss how recent advances in our understanding of PPV biology can be profitably exploited to develop viral interference strategies. In particular, genetic manipulation of host genes by which PPV accomplishes its infection cycle already permits the creation of intragenic resistant plants. Finally, we review the emerging genome editing technologies based on ZFN, TALEN and CRISPR/Cas9 engineered nucleases and how the knockout of host susceptibility genes will open up next generation of PPV resistant plants.