Network inference : extension of linear programming model for time-series data

Dissertação de mestrado em Engenharia InformáticaWith the widespread availability of high-throughput technologies, it is now possible to study the behavior of dozens or even hundreds of gene/proteins through a single experiment. Still, these experiments provide only the gene/protein expression values, telling nothing about their interactions with each other. To understand these interactions, network inference methods need to be applied. By understanding such interactions, new light can be shed into biological processes and, in particular, into disease’s mechanisms of action, providing new insights for drug design: which genes/proteins should be targeted in order to cure/prevent a specific disease. In this thesis, we developed and tested two alternative extensions for a previously developed model based on linear programming. Such model infers signal transduction networks from perturbation steady-state data. The extensions now developed take advantage of perturbation time-series data, which further improves the resolution of causal relationships between genes/proteins. In a first phase, we use artificial networks with simulated data to test the performance of both extensions in different conditions. Additionally, we compare their performance to the original model and to a state-of-the-art model for perturbation timeseries data, DDEPN. Overall, our second extension exhibits a better performance, and significantly higher sensitivity. This extension assumes a given gene/protein can only influence its targets if it is in an active form. In a second phase, we use two experimental datasets related to ERBB signaling and evaluate the resulting networks: 1) by finding literature support for the inferred edges, and 2) by using a network assembled with Ingenuity IPA as true network to do a quantitative assessment. Our results are further compared to DDEPN and the original model in a quantitative way. Quantitatively, our second model extension is shown to perform better than both the original model and DDEPN. Qualitatively, we find literature support for most of the inferred edges in both datasets, while also inferring a few plausible edges for which no literature evidence was found.Com o uso generalizado de tecnologias de alto rendimento como os microarrays de ADN, torna-se comum estudar dezenas ou mesmo centenas de genes/proteínas numa única experiência. Contudo, estas experiências apenas nos permitem determinar a expressão dos genes/proteínas e nada nos dizem sobre as interações entre os mesmos. Assim, torna-se necessário o uso de métodos de inferência de redes, de modo a estudar as interações entre genes/proteínas. Ao perceber estas interações, não só é possível perceber melhor os processos biológicos em geral, como também o modo como actuam as doenças, de forma a desenvolver novos medicamentos. Nesta tese de mestrado, desenvolvemos e testámos duas extensões para um modelo baseado em programação linear. Este modelo infere redes de transdução de sinal a partir de experiências de RNAi em que as medidas são feitas após a perturbação, quando a rede se encontra em estado estacionário. Com as extensões desenvolvidas nesta tese é possível tirar partido de séries temporais de dados provenientes de experiências de RNAi, o que permite distinguir relações de causalidade entre proteínas. Numa primeira fase, usamos redes artificiais e dados simulados para testar a performance de ambas as extensões em diferentes condições. Além disso, comparamo-las com o modelo original e com um modelo recente, DDEPN, que usa séries temporais de dados de experiências em que a rede a inferir é perturbada. Em geral, a nossa segunda extensão obtém melhores resultados, principalmente em termos de sensibilidade. Esta extensão assume que só proteínas activas podem influenciar outras proteínas. Numa segunda fase, usamos dois conjuntos de dados experimentais e avaliamos os resultados obtidos: 1) procurando referências na literatura para as ligações inferidas, e 2) usando uma rede de referência para fazer uma avaliação quantitativa e estabelecer comparações com o modelo original e o DDEPN. Quantitativamente, a nossa segunda extensão obtém melhores resultados do que o modelo original e o DDEPN. Qualitativamente, encontrámos suporte na literatura para a maioria das ligações inferidas pela segunda extensão. Inferimos ainda algumas ligações bastante plausíveis, embora não tenhamos encontrado suporte para estas

Detrimental impact of a heatwave on male reproductive behaviour and fertility

Understanding how heatwaves impact on different aspects of mating behaviour and fertility is getting increasingly important. In this context, laboratory fertility and mating experiments involving manipulation and exposure of insects to different thermal conditions are common procedures. To conduct such experiments practical methods such as dyes are needed for an easy, non-invasive discrimination of individuals. We report here a study measuring the effect of an extended heat stress applied to males on several parameters of mating behaviour and fertility of laboratory populations of Drosophila subobscura derived from two distinct European locations. We found highly detrimental effects of heatwave on mating behaviour—with longer (courtship and copulation) latencies and lower mating occurrence but no changes in mating duration—and fertility, with reduced fecundity and reproductive success. Furthermore, we also tested the efficacy of food dye as a marker for individual discrimination and mating occurrence. While food dye did not allow to infer the occurrence of a mating based on a transfer of coloration from male to female, it did not affect mating and fertility, attesting its utility has a method for discriminating individuals within mating experiments in the context of thermal studies. Importantly, despite the fact that the heatwave was only applied in males, we observed an impact on behaviour of females that mated with stressed males, by often refusing their nuptial feeding. This opens possibilities for further integrated research on the changes of female and male mating behaviour and fertility under different thermal scenarios.info:eu-repo/semantics/publishedVersio

How phenotypic convergence arises in experimental evolution

Evolutionary convergence is a core issue in the study of adaptive evolution, as well as a highly debated topic at present. Few studies have analyzed this issue using a "real-time" or evolutionary trajectory approach. Do populations that are initially differentiated converge to a similar adaptive state when experiencing a common novel environment? Drosophila subobscura populations founded from different locations and years showed initial differences and variation in evolutionary rates in several traits during short-term (∼20 generations) laboratory adaptation. Here, we extend that analysis to 40 more generations to analyze (1) how differences in evolutionary dynamics among populations change between shorter and longer time spans, and (2) whether evolutionary convergence occurs after 60 generations of evolution in a common environment. We found substantial variation in longer term evolutionary trajectories and differences between short- and longer term evolutionary dynamics. Although we observed pervasive patterns of convergence toward the character values of long-established populations, populations still remain differentiated for several traits at the final generations analyzed. This pattern might involve transient divergence, as we report in some cases, indicating that more generations should lead to final convergence. These findings highlight the importance of longer term studies for understanding convergent evolution.info:eu-repo/semantics/publishedVersio

Predictable phenotypic, but not karyotypic, evolution of populations with contrasting initial history

This study was financed by Portuguese National Funds through FCT - ‘Fundação para a Ciência e Tecnologia’ within the projects PTDC/BIA-BEC/098213/2008, PTDC/BIA-BIC/2165/2012 and cE3c Unit FCT funding UID/BIA/00329/2013. I.F. had a PhD grant (SFRH/BD/60734/2009), P.S. has a Post Doc grant (SFRH/BPD/86186/2012) and S.G.S. has a Post Doc grant (SFRH/BPD/108413/2015) from FCT. M.S. is funded by grant CGL2013-42432-P from the Ministerio de Economía y Competitividad (Spain) and grant 2014 SGR 1346 from Generalitat de Catalunya. The datasets generated during and/or analysed during the current study are available in the figshare repository, at https://doi.org/10.6084/m9.figshare.4797550.The relative impact of selection, chance and history will determine the predictability of evolution. There is a lack of empirical research on this subject, particularly in sexual organisms. Here we use experimental evolution to test the predictability of evolution. We analyse the real-time evolution of Drosophila subobscura populations derived from contrasting European latitudes placed in a novel laboratory environment. Each natural population was sampled twice within a three-year interval. We study evolutionary responses at both phenotypic (life-history, morphological and physiological traits) and karyotypic levels for around 30 generations of laboratory culture. Our results show (1) repeatable historical effects between years in the initial state, at both phenotypic and karyotypic levels; (2) predictable phenotypic evolution with general convergence except for body size; and (3) unpredictable karyotypic evolution. We conclude that the predictability of evolution is contingent on the trait and level of organization, highlighting the importance of studying multiple biological levels with respect to evolutionary patterns.Publisher PDFPeer reviewe

Circulating Cell-Free DNA in Dogs with Mammary Tumors: Short and Long Fragments and Integrity Index

Circulating cell-free DNA (cfDNA) has been considered an interesting diagnostic/prognostic plasma biomarker in tumor-bearing subjects. In cancer patients, cfDNA can hypothetically derive from tumor necrosis/apoptosis, lysed circulating cells, and some yet unrevealed mechanisms of active release. This study aimed to preliminarily analyze cfDNA in dogs with canine mammary tumors (CMTs). Forty-four neoplastic, 17 non-neoplastic disease-bearing, and 15 healthy dogs were recruited. Necrosis and apoptosis were also assessed as potential source of cfDNA on 78 CMTs diagnosed from the 44 dogs. The cfDNA fragments and integrity index significantly differentiated neoplastic versus non-neoplastic dogs (P<0.05), and allowed the distinction between benign and malignant lesions (P<0.05). Even if without statistical significance, the amount of cfDNA was also affected by tumor necrosis and correlated with tumor size and apoptotic markers expression. A significant (P<0.01) increase of Bcl-2 in malignant tumors was observed, and in metastatic CMTs the evasion of apoptosis was also suggested. This study, therefore, provides evidence that cfDNA could be a diagnostic marker in dogs carrying mammary nodules suggesting that its potential application in early diagnostic procedures should be further investigated

Prediction of Antibacterial Activity from Physicochemical Properties of Antimicrobial Peptides

Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM), which conciliates the two types of observations

Thermochemical and Theoretical Studies of Dimethylpyridine-2,6-dicarboxylate and Pyridine-2,3-, Pyridine-2,5-, and Pyridine-2,6-dicarboxylic Acids

Article discussing thermochemical and theoretical studies of dimethylpyridine-2,6-dicarboxylate and pyridine-2,3-, pyridine-2,5- and pyridine-2,6-dicarboxylic acids