Behavioural, physiological and molecular changes in alloparental caregivers may be responsible for selection response for female reproductive investment in honey bees

Reproductive investment is a central life history variable that influences all aspects of life. Hormones coordinate reproduction in multicellular organisms, but the mechanisms controlling the collective reproductive investment of social insects are largely unexplored. One important aspect of honey bee (Apis mellifera) reproductive investment consists of raising female-destined larvae into new queens by alloparental care of nurse bees in form of royal jelly provisioning. Artificial selection for commercial royal jelly production over 40 years has increased this reproductive investment by an order of magnitude. In a cross-fostering experiment, we establish that this shift in social phenotype is caused by nurse bees. We find no evidence for changes in larval signalling. Instead, the antennae of the nurse bees of the selected stock are more responsive to brood pheromones than control bees. Correspondingly, the selected royal jelly bee nurses are more attracted to brood pheromones than unselected control nurses. Comparative proteomics of the antennae from the selected and unselected stocks indicate putative molecular mechanisms, primarily changes in chemosensation and energy metabolism. We report expression differences of several candidate genes that correlate with the differences in reproductive investment. The functional relevance of these genes is supported by demonstrating that the corresponding proteins can competitively bind one previously described and one newly discovered brood pheromone. Thus, we suggest several chemosensory genes, most prominently OBP16 and CSP4, as candidate mechanisms controlling queen rearing, a key reproductive investment, in honey bees. These findings reveal novel aspects of pheromonal communication in honey bees and explain how sensory changes affect communication and lead to a drastic shift in colony-level resource allocation to sexual reproduction. Thus, pheromonal and hormonal communication may play similar roles for reproductive investment in superorganisms and multicellular organisms, respectively

Security in Cloud Computing: Evaluation and Integration

Au cours de la dernière décennie, le paradigme du Cloud Computing a révolutionné la manière dont nous percevons les services de la Technologie de l’Information (TI). Celui-ci nous a donné l’opportunité de répondre à la demande constamment croissante liée aux besoins informatiques des usagers en introduisant la notion d’externalisation des services et des données. Les consommateurs du Cloud ont généralement accès, sur demande, à un large éventail bien réparti d’infrastructures de TI offrant une pléthore de services. Ils sont à même de configurer dynamiquement les ressources du Cloud en fonction des exigences de leurs applications, sans toutefois devenir partie intégrante de l’infrastructure du Cloud. Cela leur permet d’atteindre un degré optimal d’utilisation des ressources tout en réduisant leurs coûts d’investissement en TI. Toutefois, la migration des services au Cloud intensifie malgré elle les menaces existantes à la sécurité des TI et en crée de nouvelles qui sont intrinsèques à l’architecture du Cloud Computing. C’est pourquoi il existe un réel besoin d’évaluation des risques liés à la sécurité du Cloud durant le procédé de la sélection et du déploiement des services. Au cours des dernières années, l’impact d’une efficace gestion de la satisfaction des besoins en sécurité des services a été pris avec un sérieux croissant de la part des fournisseurs et des consommateurs. Toutefois, l’intégration réussie de l’élément de sécurité dans les opérations de la gestion des ressources du Cloud ne requiert pas seulement une recherche méthodique, mais aussi une modélisation méticuleuse des exigences du Cloud en termes de sécurité. C’est en considérant ces facteurs que nous adressons dans cette thèse les défis liés à l’évaluation de la sécurité et à son intégration dans les environnements indépendants et interconnectés du Cloud Computing. D’une part, nous sommes motivés à offrir aux consommateurs du Cloud un ensemble de méthodes qui leur permettront d’optimiser la sécurité de leurs services et, d’autre part, nous offrons aux fournisseurs un éventail de stratégies qui leur permettront de mieux sécuriser leurs services d’hébergements du Cloud. L’originalité de cette thèse porte sur deux aspects : 1) la description innovatrice des exigences des applications du Cloud relativement à la sécurité ; et 2) la conception de modèles mathématiques rigoureux qui intègrent le facteur de sécurité dans les problèmes traditionnels du déploiement des applications, d’approvisionnement des ressources et de la gestion de la charge de travail au coeur des infrastructures actuelles du Cloud Computing. Le travail au sein de cette thèse est réalisé en trois phases.----------ABSTRACT: Over the past decade, the Cloud Computing paradigm has revolutionized the way we envision IT services. It has provided an opportunity to respond to the ever increasing computing needs of the users by introducing the notion of service and data outsourcing. Cloud consumers usually have online and on-demand access to a large and distributed IT infrastructure providing a plethora of services. They can dynamically configure and scale the Cloud resources according to the requirements of their applications without becoming part of the Cloud infrastructure, which allows them to reduce their IT investment cost and achieve optimal resource utilization. However, the migration of services to the Cloud increases the vulnerability to existing IT security threats and creates new ones that are intrinsic to the Cloud Computing architecture, thus the need for a thorough assessment of Cloud security risks during the process of service selection and deployment. Recently, the impact of effective management of service security satisfaction has been taken with greater seriousness by the Cloud Service Providers (CSP) and stakeholders. Nevertheless, the successful integration of the security element into the Cloud resource management operations does not only require methodical research, but also necessitates the meticulous modeling of the Cloud security requirements. To this end, we address throughout this thesis the challenges to security evaluation and integration in independent and interconnected Cloud Computing environments. We are interested in providing the Cloud consumers with a set of methods that allow them to optimize the security of their services and the CSPs with a set of strategies that enable them to provide security-aware Cloud-based service hosting. The originality of this thesis lies within two aspects: 1) the innovative description of the Cloud applications’ security requirements, which paved the way for an effective quantification and evaluation of the security of Cloud infrastructures; and 2) the design of rigorous mathematical models that integrate the security factor into the traditional problems of application deployment, resource provisioning, and workload management within current Cloud Computing infrastructures. The work in this thesis is carried out in three phases

Comparative gene expression analysis based on RNA sequencing for the identification of host plant adaptation mechanisms in Chrysomelina leaf beetles

To study sequestration of defensive compounds and the adaptation of chemosensory proteins regarding host plant shift, the first focus of my thesis: De novo assembling the transcript libraries of three non-model insects (Phaedon cochleariae, Chrysomela populi and Chrysomela lapponica) by applying RNA-sequencing technology without genome information. Second focus is (re)identification and characterization of ATP-binding cassette transporters in C. populi, beta-glucosidase in three leaf beetles and chemosensory proteins in willow and birch populations of C. lapponica. Third focus is tissue expression profiling analysis of the above investigated genes. The comparison analysis among tissues or populations facilitates me to study the high expressed genes that may play an important role in the molecular process. The phylogenetic trees were calculated to characterize the relationships and propose a function for these beetle proteins

Exploiting cloud utility models for profit and ruin

A key characteristic that has led to the early adoption of public cloud computing is the utility pricing model that governs the cost of compute resources consumed. Similar to public utilities like gas and electricity, cloud consumers only pay for the resources they consume and only for the time they are utilized. As a result and pursuant to a Cloud Service Provider\u27s (CSP) Terms of Agreement, cloud consumers are responsible for all computational costs incurred within and in support of their rented computing environments whether these resources were consumed in good faith or not. While initial threat modeling and security research on the public cloud model has primarily focused on the confidentiality and integrity of data transferred, processed, and stored in the cloud, little attention has been paid to the external threat sources that have the capability to affect the financial viability of cloud-hosted services. Bounded by a utility pricing model, Internet-facing web resources hosted in the cloud are vulnerable to Fraudulent Resource Consumption (FRC) attacks. Unlike an application-layer DDoS attack that consumes resources with the goal of disrupting short-term availability, a FRC attack is a considerably more subtle attack that instead targets the utility model over an extended time period. By fraudulently consuming web resources in sufficient volume (i.e. data transferred out of the cloud), an attacker is able to inflict significant fraudulent charges to the victim. This work introduces and thoroughly describes the FRC attack and discusses why current application-layer DDoS mitigation schemes are not applicable to a more subtle attack. The work goes on to propose three detection metrics that together form the criteria for detecting a FRC attack from that of normal web activity and an attribution methodology capable of accurately identifying FRC attack clients. Experimental results based on plausible and challenging attack scenarios show that an attacker, without knowledge of the training web log, has a difficult time mimicking the self-similar and consistent request semantics of normal web activity necessary to carryout a successful FRC attack

Nature-inspired algorithms for solving some hard numerical problems

Optimisation is a branch of mathematics that was developed to find the optimal solutions, among all the possible ones, for a given problem. Applications of optimisation techniques are currently employed in engineering, computing, and industrial problems. Therefore, optimisation is a very active research area, leading to the publication of a large number of methods to solve specific problems to its optimality. This dissertation focuses on the adaptation of two nature inspired algorithms that, based on optimisation techniques, are able to compute approximations for zeros of polynomials and roots of non-linear equations and systems of non-linear equations. Although many iterative methods for finding all the roots of a given function already exist, they usually require: (a) repeated deflations, that can lead to very inaccurate results due to the problem of accumulating rounding errors, (b) good initial approximations to the roots for the algorithm converge, or (c) the computation of first or second order derivatives, which besides being computationally intensive, it is not always possible. The drawbacks previously mentioned served as motivation for the use of Particle Swarm Optimisation (PSO) and Artificial Neural Networks (ANNs) for root-finding, since they are known, respectively, for their ability to explore high-dimensional spaces (not requiring good initial approximations) and for their capability to model complex problems. Besides that, both methods do not need repeated deflations, nor derivative information. The algorithms were described throughout this document and tested using a test suite of hard numerical problems in science and engineering. Results, in turn, were compared with several results available on the literature and with the well-known Durand–Kerner method, depicting that both algorithms are effective to solve the numerical problems considered.A Optimização é um ramo da matemática desenvolvido para encontrar as soluções óptimas, de entre todas as possíveis, para um determinado problema. Actualmente, são várias as técnicas de optimização aplicadas a problemas de engenharia, de informática e da indústria. Dada a grande panóplia de aplicações, existem inúmeros trabalhos publicados que propõem métodos para resolver, de forma óptima, problemas específicos. Esta dissertação foca-se na adaptação de dois algoritmos inspirados na natureza que, tendo como base técnicas de optimização, são capazes de calcular aproximações para zeros de polinómios e raízes de equações não lineares e sistemas de equações não lineares. Embora já existam muitos métodos iterativos para encontrar todas as raízes ou zeros de uma função, eles usualmente exigem: (a) deflações repetidas, que podem levar a resultados muito inexactos, devido ao problema da acumulação de erros de arredondamento a cada iteração; (b) boas aproximações iniciais para as raízes para o algoritmo convergir, ou (c) o cálculo de derivadas de primeira ou de segunda ordem que, além de ser computacionalmente intensivo, para muitas funções é impossível de se calcular. Estas desvantagens motivaram o uso da Optimização por Enxame de Partículas (PSO) e de Redes Neurais Artificiais (RNAs) para o cálculo de raízes. Estas técnicas são conhecidas, respectivamente, pela sua capacidade de explorar espaços de dimensão superior (não exigindo boas aproximações iniciais) e pela sua capacidade de modelar problemas complexos. Além disto, tais técnicas não necessitam de deflações repetidas, nem do cálculo de derivadas. Ao longo deste documento, os algoritmos são descritos e testados, usando um conjunto de problemas numéricos com aplicações nas ciências e na engenharia. Os resultados foram comparados com outros disponíveis na literatura e com o método de Durand–Kerner, e sugerem que ambos os algoritmos são capazes de resolver os problemas numéricos considerados

Temperature- and host-dependent transcriptional responses in the entomopathogenic bacterium, Yersinia entomophaga MH96 : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Genetics at Massey University, Albany Campus, New Zealand

Yersinia entomophaga MH96 is a virulent pathogenic bacterium that is infective towards a broad range of insects and is under development as a biopesticide. MH96 produces insecticidal toxin complex called Yen-TC that is secreted at temperatures of 25 °C and below and has been shown to be the primary virulence factor (VF) during per os challenge against the New Zealand grass grub, Costelytra giveni and other agricultural pests (Hurst et al., 2011a, 2019). New insights into the pathobiology of MH96 during insect infection were gained from the in vivo transcriptome, including identification of a core secreted weaponry of co-expressed/co-secreted VFs, including Yen-TC and other exoenzymes; however, many other diverse types of VFs, including toxins, effectors, fimbriae, secretion systems, efflux pumps, iron acquisition, stress response and metabolic adaptation were also identified as highly expressed under in vivo conditions. A small DNA-binding protein, Yen6, was shown to be under thermoregulation at the transcriptional level and host-dependent-regulation at the post-transcriptional level and contributed to virulence during intrahemocoelic infection of Galleria mellonella at 37 °C. The in vivo transcriptome of Δyen6 and in vitro DNA-binding specificity analysis provided evidence that Yen6 is a novel LytTR-containing regulator that activates a ribose uptake/metabolism gene cluster, rbsD-xylG-rbsC-xylF-rbsK-ccpA, and represses a fructose uptake/metabolism gene cluster, IIA-fruK-IIB and a gene for RNA-binding protein yhbY during infection at 37 °C. Another small DNA-binding protein, Yen7, was also implicated as a potential temperature-dependent activator of Yen-TC component genes and over-expression of yen7 resulted in restored secretion by MH96 at 37 °C; however, deletion of yen7 did not abrogate Yen-TC production. Experimental investigations into potential regulatory linkages between Yen6 and yen7 were undertaken, and evidence to date does not support Yen6 as transcriptional repressor of yen7. A 17.5 Kb unstable element within the genome of MH96 with linkages to Yen-TC and toxin secretion, motility and cell shape was identified. Overall the findings presented in this thesis represent the most detailed investigation of MH96 pathogenesis to date, reinforcing MH96 as one of the most highly entomopathogenic bacteria known to humankind; yet suggesting MH96 has possibly maintained at least one core thermoregulatory mechanism more typical of an opportunistic pathogen