Geminivirus Rep Protein Interferes with the Plant DNA Methylation Machinery and Modifies the Host Epigenome

The apparent simplicity of viruses hides the complexity of their interactions with their hosts. Viruses are masters at circumventing host defenses and manipulating the cellular environment for their own benefit. The replication of the largest known family of single-stranded DNA viruses, Geminiviridae, is impaired by DNA methylation and Arabidopsis mutants affected in cytosine methylation are hypersusceptible to geminivirus infection. This implies that plants might use methylation as a defense against geminiviruses and that the viral genome is a target for plant DNA methyltransferases. We have found a novel counter-defense strategy used by geminiviruses, that reduces the expression of the plant maintenance DNA methyltransferases, MET1 and CMT3, in both, locally and systemically infected tissues. Furthermore, we demonstrated that the virus-mediated repression of these two maintenance DNA methyltransferases is widely spread among different geminivirus species. Additionally, we identified Rep as the geminiviral protein responsible for the repression of MET1 and CMT3, and another viral protein, C4, as an ancillary player in MET1 downregulation. The presence of Rep, suppresses TGS of an Arabidopsis transgene and of host loci whose expression is strongly controlled by CG methylation. Bisulfite sequencing analyses showed that the expression of Rep caused a substantial reduction in the levels of DNA methylation at CG sites. Our findings suggest that Rep, the only viral protein essential for geminiviral replication, displays TGS suppressor activity through a mechanism distinct from the one thus far described for geminiviruses.

The Associations Between the Maladaptive Personality Dimensions of Neediness and Self-Criticism, Defense Styles, Selfobject Needs, and Attachment Styles in an Iranian Sample

The present study extends previous findings by examining whether defense styles, selfobject needs, attachment styles relate to Neediness and Self-Criticism, as maladaptive personality dimensions focused, respectively, on relatedness and self-definition in an Iranian sample. Three hundred and fifty two participants completed a socio-demographic questionnaire as well as the Persian forms of the Depressive Experiences Questionnaire, Experience of Close Relationships-Revised, Defense Style Questionnaire, Beck Depression Inventory–II and Selfobject Needs Inventory. Two Multiple Linear Regression Analyses, entering Self-criticism and Neediness as criterion variables, were computed. According to the results high Attachment anxiety, high Immature defenses, high depressive symptoms, and high need for idealization were related to self-criticism, and explained 47% of its variance. In addition, high attachment anxiety, low mature defenses, high neurotic defenses, high avoidance of mirroring, and low avoidance of idealization/twinship were related to neediness, and explained 40% of its variance. A Principal Component Analysis was performed, entering all the studied variables. Three factors emerged; one describing a maladaptive form of psychological functioning and two describing more mature modes of psychological functioning. The results are discussed in their implications for the understanding of neediness and self-criticism as maladaptive personality dimensions focused, respectively, on relatedness and self-definition.

Genome-wide analysis of G-type lectin genes in Fragaria vesca and functional characterization of FaMBL1 gene in defense response of F. × ananassa to fungal pathogens

Strawberry (Fragaria × ananassa) is an important soft fruit but easily to be infected by pathogens. Anthracnose and gray mold are two of the most destructive diseases of strawberry which lead to serious fruit rot. The first chapter introduced strawberry anthracnose caused by Colletotrichum acutatum. The infection strategy, disease cycle and management of C. acutatum on strawberry were reported. Likewise, the second chapter summarized the infection strategy of Botrytis cinerea and the defense responses of strawberry. As we already know white unripe strawberry fruits are more resistant to C. acutatum than red ripe fruits. During the interaction between strawberry white/red fruit and C. acutaum, a mannose binding lectin gene, FaMBL1, was found to be the most up-regulated gene and induced exclusively in white fruit. FaMBL1 belongs to the G-type lectin family which has important roles in plant development and defense process. To get insight into the role of FaMBL1, genome-wide identification was carried out on G-type lectin gene family in Fragaria vesca and the results were showed in chapter 3. G-type lectin genes make up a large family in F. vesca. Active expression upon biotic/abiotic stresses suggested a potential role of G-lectin genes in strawberry defenses. Hence, stable transgenic strawberry plants with FaMBL1 gene overexpressed were generated. Transformed strawberry plants were screened and identified. The results were showed in chapter 4, content of disease-related phytohormone, jasmonic acid, was found decreased in overexpressing lines compared with wild type (WT). Petioles inoculated by C. fioriniae of overexpressing lines had lower disease incidence than WT. Leaves of overexpressing lines challenged by B. cinerea showed remarkably smaller lesion diameters compared with WT. The chitinase 2-1 (FaChi2-1) showed higher expression in overexpressing lines than in WT during the interaction with B. cinerea, which could be related with the lower susceptibility of overexpressing lines.

Security enhancements and flaws of emerging communication technologies

The multi-faced evolution of network technologies ranges from big data centers to specialized network infrastructures and protocols for mission-critical operations. For instance, technologies such as Software Defined Networking (SDN) revolutionized the world of static configuration of the network - i.e., by removing the distributed and proprietary configuration of the switched networks - centralizing the control plane. While this disruptive approach is interesting from different points of view, it can introduce new unforeseen vulnerabilities classes. One topic of particular interest in the last years is industrial network security, an interest which started to rise in 2016 with the introduction of the Industry 4.0 (I4.0) movement. Networks that were basically isolated by design are now connected to the internet to collect, archive, and analyze data. While this approach got a lot of momentum due to the predictive maintenance capabilities, these network technologies can be exploited in various ways from a cybersecurity perspective. Some of these technologies lack security measures and can introduce new families of vulnerabilities. On the other side, these networks can be used to enable accurate monitoring, formal verification, or defenses that were not practical before. This thesis explores these two fields: by introducing monitoring, protections, and detection mechanisms where the new network technologies make it feasible; and by demonstrating attacks on practical scenarios related to emerging network infrastructures not protected sufficiently. The goal of this thesis is to highlight this lack of protection in terms of attacks on and possible defenses enabled by emerging technologies. We will pursue this goal by analyzing the aforementioned technologies and by presenting three years of contribution to this field. In conclusion, we will recapitulate the research questions and give answers to them.

Asymmetries in Adversarial Settings

Even without formal guarantees of their effectiveness, adversarial attacks against Machine Learning models frequently fool new defenses. We identify six key asymmetries that contribute to this phenomenon and formulate four guidelines to build future-proof defenses by preventing such asymmetries. We also prove that attacking a classifier is NP-complete, while defending from such attacks is Sigma_2^P-complete. We then introduce Counter-Attack (CA), an asymmetry-free metadefense that determines whether a model is robust on a given input by estimating its distance from the decision boundary. Under specific assumptions CA can provide theoretical detection guarantees. Additionally, we prove that while CA is NP-complete, fooling CA is Sigma_2^P-complete. Even when using heuristic relaxations, we show that our method can reliably identify non-robust points. As part of our experimental evaluation, we introduce UG100, a new dataset obtained by applying a provably optimal attack to six limited-scale networks (three for MNIST and three for CIFAR10), each trained in three different manners.