Semantic systems biology of prokaryotes : heterogeneous data integration to understand bacterial metabolism

The goal of this thesis is to improve the prediction of genotype to phenotypeassociations with a focus on metabolic phenotypes of prokaryotes. This goal isachieved through data integration, which in turn required the development ofsupporting solutions based on semantic web technologies. Chapter 1 providesan introduction to the challenges associated to data integration. Semantic webtechnologies provide solutions to some of these challenges and the basics ofthese technologies are explained in the Introduction. Furthermore, the ba-sics of constraint based metabolic modeling and construction of genome scalemodels (GEM) are also provided. The chapters in the thesis are separated inthree related topics: chapters 2, 3 and 4 focus on data integration based onheterogeneous networks and their application to the human pathogen M. tu-berculosis; chapters 5, 6, 7, 8 and 9 focus on the semantic web based solutionsto genome annotation and applications thereof; and chapter 10 focus on thefinal goal to associate genotypes to phenotypes using GEMs. Chapter 2 provides the prototype of a workflow to efficiently analyze in-formation generated by different inference and prediction methods. This me-thod relies on providing the user the means to simultaneously visualize andanalyze the coexisting networks generated by different algorithms, heteroge-neous data sets, and a suite of analysis tools. As a show case, we have ana-lyzed the gene co-expression networks of M. tuberculosis generated using over600 expression experiments. Hereby we gained new knowledge about theregulation of the DNA repair, dormancy, iron uptake and zinc uptake sys-tems. Furthermore, it enabled us to develop a pipeline to integrate ChIP-seqdat and a tool to uncover multiple regulatory layers. In chapter 3 the prototype presented in chapter 2 is further developedinto the Synchronous Network Data Integration (SyNDI) framework, whichis based on Cytoscape and Galaxy. The functionality and usability of theframework is highlighted with three biological examples. We analyzed thedistinct connectivity of plasma metabolites in networks associated with highor low latent cardiovascular disease risk. We obtained deeper insights froma few similar inflammatory response pathways in Staphylococcus aureus infec-tion common to human and mouse. We identified not yet reported regulatorymotifs associated with transcriptional adaptations of M. tuberculosis.In chapter 4 we present a review providing a systems level overview ofthe molecular and cellular components involved in divalent metal homeosta-sis and their role in regulating the three main virulence strategies of M. tu-berculosis: immune modulation, dormancy and phagosome escape. With theuse of the tools presented in chapter 2 and 3 we identified a single regulatorycascade for these three virulence strategies that respond to limited availabilityof divalent metals in the phagosome. The tools presented in chapter 2 and 3 achieve data integration throughthe use of multiple similarity, coexistence, coexpression and interaction geneand protein networks. However, the presented tools cannot store additional(genome) annotations. Therefore, we applied semantic web technologies tostore and integrate heterogeneous annotation data sets. An increasing num-ber of widely used biological resources are already available in the RDF datamodel. There are however, no tools available that provide structural overviewsof these resources. Such structural overviews are essential to efficiently querythese resources and to assess their structural integrity and design. There-fore, in chapter 5, I present RDF2Graph, a tool that automatically recoversthe structure of an RDF resource. The generated overview enables users tocreate complex queries on these resources and to structurally validate newlycreated resources. Direct functional comparison support genotype to phenotype predictions.A prerequisite for a direct functional comparison is consistent annotation ofthe genetic elements with evidence statements. However, the standard struc-tured formats used by the public sequence databases to present genome an-notations provide limited support for data mining, hampering comparativeanalyses at large scale. To enable interoperability of genome annotations fordata mining application, we have developed the Genome Biology OntologyLanguage (GBOL) and associated infrastructure (GBOL stack), which is pre-sented in chapter 6. GBOL is provenance aware and thus provides a consistentrepresentation of functional genome annotations linked to the provenance.The provenance of a genome annotation describes the contextual details andderivation history of the process that resulted in the annotation. GBOL is mod-ular in design, extensible and linked to existing ontologies. The GBOL stackof supporting tools enforces consistency within and between the GBOL defi-nitions in the ontology. Based on GBOL, we developed the genome annotation pipeline SAPP (Se-mantic Annotation Platform with Provenance) presented in chapter 7. SAPPautomatically predicts, tracks and stores structural and functional annotationsand associated dataset- and element-wise provenance in a Linked Data for-mat, thereby enabling information mining and retrieval with Semantic Webtechnologies. This greatly reduces the administrative burden of handling mul-tiple analysis tools and versions thereof and facilitates multi-level large scalecomparative analysis. In turn this can be used to make genotype to phenotypepredictions. The development of GBOL and SAPP was done simultaneously. Duringthe development we realized that we had to constantly validated the data ex-ported to RDF to ensure coherence with the ontology. This was an extremelytime consuming process and prone to error, therefore we developed the Em-pusa code generator. Empusa is presented in chapter 8. SAPP has been successfully used to annotate 432 sequenced Pseudomonas strains and integrate the resulting annotation in a large scale functional com-parison using protein domains. This comparison is presented in chapter 9.Additionally, data from six metabolic models, nearly a thousand transcrip-tome measurements and four large scale transposon mutagenesis experimentswere integrated with the genome annotations. In this way, we linked gene es-sentiality, persistence and expression variability. This gave us insight into thediversity, versatility and evolutionary history of the Pseudomonas genus, whichcontains some important pathogens as well some useful species for bioengi-neering and bioremediation purposes. Genome annotation can be used to create GEM, which can be used to betterlink genotypes to phenotypes. Bio-Growmatch, presented in chapter 10, istool that can automatically suggest modification to improve a GEM based onphenotype data. Thereby integrating growth data into the complete processof modelling the metabolism of an organism. Chapter 11 presents a general discussion on how the chapters contributedthe central goal. After which I discuss provenance requirements for data reuseand integration. I further discuss how this can be used to further improveknowledge generation. The acquired knowledge could, in turn, be used to de-sign new experiments. The principles of the dry-lab cycle and how semantictechnologies can contribute to establish these cycles are discussed in chapter11. Finally a discussion is presented on how to apply these principles to im-prove the creation and usability of GEM’s.</p

Characterizing and visualizing the direct injection of hydrogen into high-pressure argon and nitrogen environments

Using argon as the working fluid in an internal combustion engine holds the potential of substantially enhancing thermal efficiency because of its high specific heat ratio. Burning hydrogen, not with air but with pure oxygen, in a closed-loop argon power cycle would lead to an emission-free exhaust composition, effectively containing only water and argon, which can be separated by condensation. One of the current challenges is the high-pressure direct injection of both fuel and oxidizer, which directly controls the combustion process. To support the development of such an injection strategy, high-pressure injections of hydrogen into pressurized argon and nitrogen are investigated using high-speed Schlieren and pressure transducers in a non-heated constant-volume chamber at varying conditions. In this work it is shown that hydrogen mass flow increases linearly with injection pressure and that it is unaffected by chamber pressure as expected based on choked flow theory, while jet penetration and cone angle are determined by the pressure ratio between the fuel line and the ambient. A correlation is presented between jet penetration and pressure ratio for argon or nitrogen environments at room temperature

Supervisor idea adoption scale:Construction, reliability and initial validity evidence

Despite the importance of workplace innovation, the adoption of creative ideas at workplace level has received little attention due to a lack of measures for idea adoption. The purpose of this study was to develop and validate a scale that measures employees’ perceptions of the process of idea adoption. Specifically, the scale assesses employee perceptions of their supervisor's behavior in terms of idea openness, selection and application. Three studies were conducted to develop the supervisor idea adoption scale and investigate the scale scores’ psychometric properties (Study 1, n = 326); concurrent, convergent and divergent validity (Study 2, n = 333); and test–retest reliability over a three month period (Study 3, n = 189). The findings indicated good psychometric properties: the 3-factor structure was supported, and the scales scores showed internal consistency and retest reliability. Furthermore, the scale scores’ associations with other variables provided initial evidence for concurrent, convergent and divergent validity. Several recommendations are made for the application of the scale in research and practice.</p

Principles of Flow and Transport in Turfgrass Profiles, and consequences for management

Sport turfs require specific soil and water management strategies to achieve optimal sport turf performance and grass quality. In this study the know-how of flow and transport mechanisms in turfgrass porous media is highlighted under drought conditions when water repellency cause preferential flow. An illustration is given of the principles that cause soil water repellency and dry spots for the Ouddorp site in the Netherlands, and ways to prevent or alleviate dry spots. The concept of the critical soil water content is discussed and illustrated with field observations and with computer simulation results. Furthermore, an integrated monitoring and management system is proposed aiming at optimizing soil and water management strategies for sport turfgrass systems. The system is based on the integrated knowledge of soil profile characteristics, the actual soil water content status, and short-term weather expectations

Regulation of three virulence strategies of Mycobacterium tuberculosis : A success story

Tuberculosis remains one of the deadliest diseases. Emergence of drug-resistant and multidrug-resistant M. tuberculosis strains makes treating tuberculosis increasingly challenging. In order to develop novel intervention strategies, detailed understanding of the molecular mechanisms behind the success of this pathogen is required. Here, we review recent literature to provide a systems level overview of the molecular and cellular components involved in divalent metal homeostasis and their role in regulating the three main virulence strategies of M. tuberculosis: immune modulation, dormancy and phagosomal rupture. We provide a visual and modular overview of these components and their regulation. Our analysis identified a single regulatory cascade for these three virulence strategies that respond to limited availability of divalent metals in the phagosome

Cannabis-opioid interaction in the treatment of fibromyalgia pain: an open-label, proof of concept study with randomization between treatment groups: cannabis, oxycodone or cannabis/oxycodone combination-the SPIRAL study

Background Opioids continue to be widely prescribed for chronic noncancer pain, despite the awareness that opioids provide only short-time pain relief, lead to dose accumulation, have numerous adverse effects, and are difficult to wean. As an alternative, we previously showed advantages of using pharmaceutical-grade cannabis in a population of chronic pain patients with fibromyalgia. It remains unknown whether combining an opioid with pharmaceutical-grade cannabis has advantages, such as fewer side effects from lesser opioid consumption in chronic pain.Methods Trial design: a single-center, randomized, three-arm, open-label, exploratory trial.Trial population: 60 patients with fibromyalgia according to the 2010 definition of the American College of Rheumatologists.Intervention: Patients will be randomized to receive up to 4 daily 5 mg oral oxycodone sustained release (SR) tablet, up to 5 times 150 mg inhaled cannabis (Bediol (R), containing 6.3% delta(9)-tetrahydrocannabinol and 8% cannabidiol), or the combination of both treatments. Treatment is aimed at self-titration with the daily maximum doses given. Treatment will continue for 6 weeks, after which there is a 6-week follow-up period.Main trial endpoint: The number of side effects observed during the course of treatment using a composite adverse effect score that includes the following 10 symptoms: dizziness (when getting up), sleepiness, insomnia, headache, nausea, vomiting, constipation, drug high, hallucinations, and paranoia.Secondary and tertiary endpoints include pain relief and number of oxycodone doses and cannabis inhalations.Discussion The trial is designed to determine whether self-titration of oxycodone and cannabis will reduce side effects in chronic pain patients with fibromyalgia.Perioperative Medicine: Efficacy, Safety and Outcome (Anesthesiology/Intensive Care

“The Mystery of the Raddlesham Mumps”: a Case Study for Combined Storytelling in a Theatre Play and Virtual Reality

“The Mystery of the Raddlesham Mumps” is a poem by Murray Lachlan Young, aimed at both children and adults. This poem has been adapted as a theatre play with a short prequel as a Virtual Reality (VR) / tablet app. We used this unique combination to explore the potential interaction between these different media elements for the level of “presence” and “immersion” in the story (i.e. the level to which one can imagine oneself within the story at the expense of the sense of physical time and space). The theatre audience had the opportunity to play the VR / tablet app in the foyer before the performance started. After the performance, a questionnaire measured participants' level of immersion and presence in the theatre play and their enjoyment of both play and app. The results showed that people of all ages interacted with and liked the app. Ratings for the play were also high and did not depend on prior engagement with the app. However, the play was liked more by adults than children, and the reverse was true for the app, suggesting a potential generation shift in multimedia story telling