Pathway Semantics: An Algebraic Data Driven Algorithm to Generate Hypotheses about Molecular Patterns Underlying Disease Progression

The overarching goal of the Pathway Semantics Algorithm (PSA) is to improve the in silico identification of clinically useful hypotheses about molecular patterns in disease progression. By framing biomedical questions within a variety of matrix representations, PSA has the flexibility to analyze combined quantitative and qualitative data over a wide range of stratifications. The resulting hypothetical answers can then move to in vitro and in vivo verification, research assay optimization, clinical validation, and commercialization. Herein PSA is shown to generate novel hypotheses about the significant biological pathways in two disease domains: shock / trauma and hemophilia A, and validated experimentally in the latter. The PSA matrix algebra approach identified differential molecular patterns in biological networks over time and outcome that would not be easily found through direct assays, literature or database searches. In this dissertation, Chapter 1 provides a broad overview of the background and motivation for the study, followed by Chapter 2 with a literature review of relevant computational methods. Chapters 3 and 4 describe PSA for node and edge analysis respectively, and apply the method to disease progression in shock / trauma. Chapter 5 demonstrates the application of PSA to hemophilia A and the validation with experimental results. The work is summarized in Chapter 6, followed by extensive references and an Appendix with additional material

Discovery of the Consistently Well-Performed Analysis Chain for SWATH-MS Based Pharmacoproteomic Quantification

Sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) has emerged as one of the most popular techniques for label-free proteome quantification in current pharmacoproteomic research. It provides more comprehensive detection and more accurate quantitation of proteins comparing with the traditional techniques. The performance of SWATH-MS is highly susceptible to the selection of processing method. Till now, ≥27 methods (transformation, normalization, and missing-value imputation) are sequentially applied to construct numerous analysis chains for SWATH-MS, but it is still not clear which analysis chain gives the optimal quantification performance. Herein, the performances of 560 analysis chains for quantifying pharmacoproteomic data were comprehensively assessed. Firstly, the most complete set of the publicly available SWATH-MS based pharmacoproteomic data were collected by comprehensive literature review. Secondly, substantial variations among the performances of various analysis chains were observed, and the consistently well-performed analysis chains (CWPACs) across various datasets were for the first time generalized. Finally, the log and power transformations sequentially followed by the total ion current normalization were discovered as one of the best performed analysis chains for the quantification of SWATH-MS based pharmacoproteomic data. In sum, the CWPACs identified here provided important guidance to the quantification of proteomic data and could therefore facilitate the cutting-edge research in any pharmacoproteomic studies requiring SWATH-MS technique

Multi-class gene expression biomarker panel identification for the diagnosis of paediatric febrile illness

Febrile illness in children can result from infections by diverse viral or bacterial pathogens as well as inflammatory conditions or cancer. The limitations of the existing diagnostic pipeline, which relies on clinical symptoms and signs, pathogen detection, empirical treatment and diagnoses of exclusion, contribute to missed or de- layed diagnosis and unnecessary antibiotic use. The potential of host gene expression biomarkers measured in blood has been demonstrated for simplified binary diagnostic questions however, the clinical reality is that multiple potential aetiologies must be considered and prioritised on the basis of likelihood and risks of severe disease. In order to identify a biomarker panel which better reflects this clinical reality, we applied a multi-class supervised learning approach to whole blood transcriptomic datasets from children with infectious and inflammatory disease. Three datasets were used for the analyses presented here, a single microarray dataset, a meta-analysis of 12 publicly available microarray datasets and a newly generated RNA-sequencing dataset. These were used for preliminary investigations of the approach, discovery of a multi-class biomarker panel of febrile illness and valida- tion of the biomarker panel respectively. In the merged microarray discovery dataset a two-stage approach to feature selection and classification, based on LASSO and Ridge penalised regression was applied to distinguish 18 disease classes. Cost-sensitivity was incorporated in the approach as aetiologies of febrile illness vary considerably in the risk of severe disease. The resulting 161 transcript biomarker panel could reliably distinguish bacterial, viral, inflammatory, tuberculosis and malarial disease as well as pathogen specific aetiologies. The panel was then validated in a newly generated RNA-Seq dataset and compared to previously published binary biomarker panels. The analyses presented here demonstrate that a single test for the diagnosis of acute febrile illness in children is possible using host RNA biomarkers. A test which could distinguish multiple aetiologies soon after presentation could be used to reduce unnecessary antibiotic use, improve targetting of antibiotics to bacterial species and reduce delays in the diagnosis of inflammatory diseases.Open Acces

BOVINE STAPHYLOCOCCUS AUREUS MASTITIS: FROM THE MAMMARY IMMUNE RESPONSE TO THE BACTERIA VIRULENCE GENES

Staphylococcus aureus (S. aureus) is one of the most important bacteria in veterinary medicine. In dairy herds, it is a contagious bacterium responsible mainly for subclinical mastitis in cattle, which frequently gives rise to persistent and chronic infection. Mastitis cause considerable economic losses due to i) decreased milk production, (ii) reduced milk quality, and (iii) treatment costs. Mastitis is also a public health problem. Indeed, the strains isolated from infected glands could produce enterotoxins. Three factors interact in mastitis: the host, the pathogen and the environment. This thesis focuses on two main aspects: the host immune response and the virulence factor of S. aureus. The first chapter of the thesis focused on the development of a new mammary gland model to study the innate immune response bacterial infection. The mammary gland is a complex organ, and the immune response is a consequence of the different cell population interactions. Continuous or primary epithelial cell lines have been extensively used to study the mammary gland immune response, but they are composed of a single cell population. Previous studies explored the tissues of lactating cows, unconsidering the possibility of an already triggered immune response. To investigate the innate immune response of the bovine mammary gland, we used an explant of healthy heifer gland. This model allowed us to: i) exclude previous exposure of the udder to microorganisms, which might have damaged the cells and/or triggered an immune response, and ii) consider the interaction of the challenging microorganism with the tissue cell populations. Our aim was to test whether this innovative model might be a valid model to investigate the innate immune response to infection. The study was carried out on 2 mm3-sections of heifer udders, in 2 consecutive trials, using LPS or LTA in the first trial and two different concentrations of S. aureus in the second. Treated and untreated sections were collected after 1h, 3h and 6h incubation; in the first trial, a final time-point at 18h was considered. The mRNA expression of TNF\u3b1, IL-1\u3b2, IL-6, IL-8 and LAP was analyzed by quantitative real-time PCR. Histological examination showed well-preserved morphology of the tissue, and apoptosis only showed a slight, not significant increase throughout the experiment. IL-1\u3b2 and IL-6 were significantly up-regulated, in response to LPS or S. aureus, while TNF-\u3b1 and IL-8 significantly increased only under LPS treatment. LAP expression showed a significant late increase when stimulated by LPS. The immunochemical staining of the sections demonstrated a higher number of T lymphocytes within the alveolar epithelium, in comparison with interstitial localization. Since the explants belonged to pubertal non-pregnant heifers, T cells may be regarded as resident cells, suggesting their participation in the regulation of mammary homeostasis. Therefore, applying our model would give new insights in the investigation of udder pathophysiology. The second chapter of the thesis focused on S. aureus in bovine intrammary infections. Previous literature on the S. aureus-intrammamary suggested that infection might be related to a combination of S. aureus virulence factors beyond host factors. The present study considered 169 isolates from different Italian dairy herds that were classified into four groups based on the prevalence of S. aureus infection at the first testing: low prevalence ( 40 %; HP). We aimed to correlate the presence of virulence genes with the herd prevalence of intramammary infections in order to develop new strategies for the control of S. aureus mastitis. Microarray data were statistically evaluated using binary logistic regression and correspondence analysis to screen the risk factors and the relationship between prevalence group and gene. The analysis showed: (1) 24 genes at significant risk of being detected in all the herds with infection prevalence >5%, including genes belonging to microbial surface components recognizing adhesive matrix molecules (MSCRAMMs), immune evasion and serine proteases; and (2) a significant correlation coefficient between the genes interacting with the host immune response and HP isolates against LP ones. These results support the hypothesis that virulence factors, in addition to cow management, could be related to strain contagiousness, offering new insights into vaccine development

The metabolomic response to severe thermal injury and the impact of age

Severe thermal injury results in a profound hypermetabolic response and is associated with increased morbidity, mortality and delayed rehabilitation of burn survivors. Serum 1H-NMR metabolomics was used to examine early global metabolic changes in the response to severe thermal injury (>15% TBSA) in young adults (16-64 years) and older adults (<15% TBSA). Early changes in the metabolome reflected hypoxic metabolism, hyperglycaemia, increased ketogenesis, peripheral lipolysis and increased energy production in both cohorts. Early metabolic profiles from the young adult group were used to construct OPLSDA models that could discriminate with high accuracy between outcome groups. Models from 0-24hrs serum samples predicted survival (AUC 0.92), whilst models from 24-96hrs samples predicted Multiple organ failure (MOF) (AUC 0.92) and sepsis (AUC 0.89). Untargeted LC-MS metabolomics was applied to study the longitudinal changes in the serum metabolome after severe thermal injury in 13 young adults, from admission until 6-months post-injury. Univariate ANOVA analysis revealed significant changes in 432 metabolite features, affecting 35 distinct classes, representing global metabolic disturbance. Changes in 300 lipid metabolite features may represent a ‘lipid storm’ in serum after severe thermal injury. Novel areas of metabolism and metabolites were identified as putative biomarkers warranting further targeted study

Insights on interspecies disease tolerance mechanisms through comparative and functional genomics

La sensibilité des primates aux pathogènes et aux maladies inflammatoires chroniques varie considérablement. Par exemple, les singes (tels que les humains et les chimpanzés) sont très sensibles à de très petites doses de lipopolysaccharide (LPS), une molécule mimétique d'agent pathogène, qui cause de graves lésions tissulaires en raison de l'immunopathologie tandis que les singes africains et asiatiques clades soeurs AAM (tels que les macaques et les babouins) sont beaucoup plus tolérants à des doses beaucoup plus élevées de LPS. Cet écart entre l'homme et les autres primates est connu pour être, au moins partiellement, dû à la différence interspécifique de la réponse immunitaire. Dans cette thèse, j'ai effectué une analyse comparative de la réponse immunitaire à travers différentes lignées de primates pour obtenir des informations supplémentaires sur l'évolution de la réponse immunitaire. J'ai trouvé que les singes provoquent une réponse immunitaire beaucoup plus forte aux stimulants (bactériens ou viraux) par rapport aux AMM. Une telle réponse plus élevée s'est également avérée corrélée avec la phylogénie du primate, la plus élevée chez le primate supérieur (humain) et la plus faible chez le primate basal (lémurien). Une réponse aussi élevée peut être bénéfique pour la médiation d'une destruction efficace des agents pathogènes, mais elle est probablement accompagnée de lésions tissulaires plus élevées, ce qui pourrait expliquer pourquoi les humains sont plus sensibles aux maladies immunopathologiques telles que la septicémie. J'ai également caractérisé le paysage réglementaire de la réponse immunitaire chez ces primates. J'ai trouvé que l'activité des éléments régulateurs était significativement différente entre les différentes espèces de primates après une stimulation immunitaire mettant en évidence le rôle de l'épigénétique dans la conduite du changement de la réponse immunitaire chez les primates. De plus, j'ai trouvé une signature d'évolution adaptative sur les régions actives associées aux gènes qui ont la réponse la plus élevée chez l'homme par rapport aux AMM révélant le rôle de la sélection naturelle sur le façonnement de la réponse immunitaire chez les primates.Primates vary remarkably in their disease susceptibility to pathogens and chronic inflammatory diseases. For instance, apes (such as humans and chimps) are highly sensitive to very small doses of lipopolysaccharide (LPS), a pathogen mimicry molecule, that causes severe tissue damage due to immunopathology while sister clade African and Asian monkeys AAMs (such as macaque and baboon) are far more tolerant to much higher doses of LPS. This discrepancy between humans and other primates is known to be, at least partially, due to interspecies differences of the immune response. In this dissertation, I performed comparative analyses of immune responses across different primate lineages to gain further insights on the evolution of immune response. I found that apes elicit a much stronger immune response to stimulants (bacterial or viral) relative to AMMs. Such a higher response was also found to be correlated with the primate phylogeny, highest in the higher primate (human) and lowest in the basal primate (lemur). Moreover, this high response may be beneficial in mediating effective pathogen killing but it is likely accompanied by higher tissue damage, which might explain why humans are more susceptible to immunopathological diseases such as sepsis. I also characterized the regulatory landscape of immune response across these primates. I found the regulatory elements activity to be significantly different between different primate species after immune stimulation highlighting the role of epigenetics in driving the immune response change across primates. In addition, I found a signature of adaptive evolution on active regions associated with genes that have the highest response in humans versus AMMs revealing the role of natural selection in shaping the immune response in primates

Detection of Pathogens in Water Using Micro and Nano-Technology

Detection of Pathogens in Water Using Micro and Nano-Technology aims to promote the uptake of innovative micro and nano-technological approaches towards the development of an integrated, cost-effective nano-biological sensor useful for security and environmental assays.  The book describes the concerted efforts of a large European research project and the achievements of additional leading research groups. The reported knowledge and expertise should support in the innovation and integration of often separated unitary processes. Sampling, cell lysis and DNA/RNA extraction, DNA hybridisation detection micro- and nanosensors, microfluidics, together also with computational modelling and risk assessment can be integrated in the framework of the current and evolving European regulations and needs. The development and uptake of molecular methods is revolutionizing the field of waterborne pathogens detection, commonly performed with time-consuming cultural methods. The molecular detection methods are enabling the development of integrated instruments based on biosensor that will ultimately automate the full pathway of the microbiological analysis of water

Proceedings of the 35th International Workshop on Statistical Modelling : July 20- 24, 2020 Bilbao, Basque Country, Spain

466 p.The InternationalWorkshop on Statistical Modelling (IWSM) is a reference workshop in promoting statistical modelling, applications of Statistics for researchers, academics and industrialist in a broad sense. Unfortunately, the global COVID-19 pandemic has not allowed holding the 35th edition of the IWSM in Bilbao in July 2020. Despite the situation and following the spirit of the Workshop and the Statistical Modelling Society, we are delighted to bring you the proceedings book of extended abstracts

Proceedings of the 35th International Workshop on Statistical Modelling : July 20- 24, 2020 Bilbao, Basque Country, Spain

466 p.The InternationalWorkshop on Statistical Modelling (IWSM) is a reference workshop in promoting statistical modelling, applications of Statistics for researchers, academics and industrialist in a broad sense. Unfortunately, the global COVID-19 pandemic has not allowed holding the 35th edition of the IWSM in Bilbao in July 2020. Despite the situation and following the spirit of the Workshop and the Statistical Modelling Society, we are delighted to bring you the proceedings book of extended abstracts

Quantitative analysis of apoptotic decisions in single cells and cell populations

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2007.Includes bibliographical references.Apoptosis is a form of programmed cell death that is essential for the elimination of damaged or unneeded cells in multicellular organisms. Inactivation of apoptotic cell death is a necessary step in the development of cancer, while hypersensitivity to apoptosis is a factor in degenerative diseases. Many of the molecular components controlling apoptosis have been identified, including the central effectors of apoptosis, a family of proteases known as caspases that efficiently dismantle the cell when active. While many of the molecular details of apoptotic regulators are now understood, a major challenge is to integrate this information to understand quantitatively how sensitivity to apoptosis and the kinetics of death are determined, in both single cells and populations of cells. We have approached this problem with a combined experimental and computational approach. Using single-cell observations, genetic and pharmacological perturbations, and mechanistic mathematical modeling, we have dissected the mechanism by which cells make a binary decision between survival and apoptosis. We identified conditions under which the apoptotic decision system fails, allowing cells to survive with caspase-induced damage that may result in damage to the genome and oncogenesis.(cont.) We further used live-cell imaging to identify and characterize a kinetic threshold at which slow and variable upstream signals are converted into rapid and discrete downstream caspase activation. Lastly, we examined the integration of multiple pro-and apoptotic signal transduction pathways by constructing a principal component-based model that linked apoptotic phenotypes to a compendium of signaling measurements. This approach enabled the identification of the molecular signals most important in determining the level of apoptosis across a population of cells. Together, our findings provide insight into the molecular and kinetic mechanisms by which cells integrate diverse molecular signals to make a discrete cell fate decision.by John G. Albeck.Ph.D