Evolutionary computation for predicting optimal reaction knockouts and enzyme modulation strategies

One of the main purposes of Metabolic Engineering is the quantitative prediction of cell behaviour under selected genetic modifications. These methods can then be used to support adequate strain optimization algorithms in a outer layer. The purpose of the present study is to explore methods in which dynamical models provide for phenotype simulation methods, that will be used as a basis for strain optimization algorithms to indicate enzyme under/over expression or deletion of a few reactions as to maximize the production of compounds with industrial interest. This work details the developed optimization algorithms, based on Evolutionary Computation approaches, to enhance the production of a target metabolite by finding an adequate set of reaction deletions or by changing the levels of expression of a set of enzymes. To properly evaluate the strains, the ratio of the flux value associated with the target metabolite divided by the wild-type counterpart was employed as a fitness function. The devised algorithms were applied to the maximization of Serine production by Escherichia coli, using a dynamic kinetic model of the central carbon metabolism. In this case study, the proposed algorithms reached a set of solutions with higher quality, as compared to the ones described in the literature using distinct optimization techniques.This work is funded by National Funds through the FCT - Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) within project PEst-OE/EEI/UI0752/2011. The work is also partially funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT within project ref. COMPETE FCOMP-01-0124- FEDER-015079. PEs work is supported by a PhD grant FCT SFRH/BD/51016/2010 from the Portuguese FCT

Implementing metaheuristic optimization algorithms with JECoLi

This work proposes JECoLi - a novel Java-based library for the implementation of metaheuristic optimization algorithms with a focus on Genetic and Evolutionary Computation based methods. The library was developed based on the principles of flexibility, usability, adaptability, modularity, extensibility, transparency, scalability, robustness and computational efficiency. The project is opensource, so JECoLi is made available under the GPL license, together with extensive documentation and examples, all included in a community Wiki-based web site (http://darwin.di.uminho.pt/jecoli). JECoLi has been/is being used in several research projects that helped to shape its evolution, ranging application fields from Bioinformatics, to Data Mining and Computer Network optimization

Immune cell changes in swimmers : response to acute exercise and training

O treino competitivo envolve exercício intenso e prolongado, capaz de modular o número e actividade das células imunitárias. Quando demasiado exigente poderá induzir fadiga e aumentar a susceptibilidade a doenças. Esta dissertação apresenta três estudos desenvolvidos no âmbito da Imunologia do Exercício, considerando a análise da resposta celular imunitária sistémica aguda e crónica ao exercício aplicada em situações reais do treino competitivo de natação, controlando factores passíveis de influenciar esta resposta. Pretendeu-se avaliar a resposta imunitária a uma sessão de treino prolongada e intensa, durante as 24h de recuperação (Estudo 1) e a uma época de treino com sete meses (Estudo 2), e estudar a influência de um macrociclo de treino de quatro meses sobre a resposta imunitária à mesma sessão de treino e período de recuperação (Estudo 3), controlando sexo, fases do ciclo menstrual, maturidade, escalão, especialidade, performance, cargas de treino e sintomas respiratórios superiores (URS). A sessão de treino induziu a diminuição da vigilância imunitária adquirida imediatamente e, pelo menos nas 2h seguintes. Juvenis e seniores recuperaram totalmente 24h depois, mas não os juniores, reforçando a ideia da existência de uma janela aberta para a infecção após exercícios prolongados e intensos e sugerindo uma recuperação menos eficiente para os juniores. No período de treino mais intenso da época observou-se uma imunodepressão e maior prevalência de URS. No final da época, a imunidade inata diminuiu aparentando maior sensibilidade aos efeitos cumulativos da carga de treino, enquanto a imunidade adquirida parece ter recuperado após o taper. O macrociclo de treino atenuou a resposta imunitária à sessão de treino e aumentou o período de janela aberta às infecções (efeitos mais acentuados nos adolescentes). Os resultados evidenciam a importância de controlar alterações imunitárias durante a época competitiva, especialmente em períodos de treino intenso e quando se realizam sessões de treino intensas consecutivas com recuperações inferiores a 24h.Competitive training demands strenuous prolonged exercise that may modulate the number and activity of circulating immune cells. Over demanding programs can lead to fatigue and increased risk of infection and susceptibility to diseases. This dissertation presents three studies developed within the Exercise Immunology scope, considering the analysis of acute and chronic systemic immune cell responses to exercise applied in real situations of competitive training, controlling for factors that may affect immune responses. We aimed to evaluate the immune response to a high intensity prolonged swimming training session (Study 1) and to a 7-month swimming training season (Study 2), and the influence of a 4-month training macrocycle on the immune response to a swimming session (Study 3). Subjects characteristics, namely sex, menstrual cycle phase, maturity, swimming age group, and distance specialty were controlled, and training load, performance improvements and Upper Respiratory Symptoms (URS) were monitored. The swimming session induced an impaired acquired immune surveillance immediately and at least throughout 2h post-exercise, however, 24h after, senior and youth swimmers had totally recovered but not juniors. This supports the idea of an open window to infection after prolonged intense exercise, suggesting also a more difficult recovery of juniors. During the season’s high intensity training periods immune depression and higher URS prevalence were observed. When the season ended, innate immunity was decreased, appearing to have been more affected by cumulative training loads, while acquired immunity seemed to have adapted and recovered efficiently after the taper period. The training season induced an overall attenuation of the immune system’s ability to respond to the swimming session, and a subsequent longer open window period of susceptibility to infection (more accentuated in adolescents). These findings enhance the importance of controlling immune alterations throughout the season, especially in heavy training periods and when performing consecutive intense training sessions without 24h of recovery

Using graphene oxide as means of improvement of concrete: a brief review

Este trabalho foi financiado pelo Concurso Anual para Projetos de Investigação, Desenvolvimento, Inovação e Criação Artística (IDI&CA) 2018 do Instituto Politécnico de Lisboa. Código de referência IPL/2018/Nanomortar_ISELThe use of nanomaterials (NM) to improve the performance of cement and concrete matrixes nowadays appears as a potential alternative to the exclusive use of Portland cement (PC). Similarly, there is currently no doubt in the construction industry (CI) about the pressing need to reduce consumption of PC. The CI represents the world's third-largest industrial energy consumer, and the component related to the production of PC alone represents 7% of the carbon dioxide (CO2) emissions globally (OECD, 2018). PC is undoubtedly the most used material in construction in terms of its relative volume. Raw materials for PC production are generally plentiful and are available throughout the world. It is possible to state that there is, at this moment, no other material, with the same availability as the PC, that is able to fulfil the construction’s technical requirements as the concrete’s main component. In this sense, it is imperative that the cement industry obtains viable technical solutions that allow the reduction of PC consumption. That reduction can be achieved either by its direct replacement with another material (as for example with the use of fly ash), or by improving the cement and concrete matrix performance with the addition of new materials such as NM. This second option is quite interesting since it allows, for example, to maintain the cement and concrete matrix properties/characteristics, reducing PC consumption by adding a tiny amount of a NM.info:eu-repo/semantics/publishedVersio

Novel approaches for dynamic modelling of E. coli and their application in Metabolic Engineering

PhD thesis in BioengineeringOne of the trends of modern societies is the replacement of chemical processes by biochemical ones, with new compounds being synthesized by engineered microorganisms, while some waste products are also being degraded by biotechnological means. Biotechnology holds the promise of creating a more profitable and environmental friendly industry, with a reduced number of waste products, when contrasted with the traditional chemical industry. However, in an era in which genomes are sequenced at a faster pace than ever before, and with the advent omic measurements, this information is not directly translated into the targeted design of new microorganisms, or biological processes. These experimental data in isolation do not explain how the different cell constituents interact. Reductionist approaches that dominated science in the last century study cellular entities in isolation as separate chunks, without taking into consideration interactions with other molecules. This leads to an incomplete view of biological processes, which compromises the development of new knowledge. To overcome these hurdles, a formal systems approach to Biology has been surging in the last thirty years. Systems biology can be defined as the conjugation of different fields (such as Mathematics, Computer Science, Biology), to describe formally and non-ambiguously the behavior of the different cellular systems and their interactions, using to models and simulations. Metabolic Engineering takes advantage of these formal specifications, using mathematically based methods to derive strategies to optimize the microbial metabolism, in order to achieve a desired goal, such as the increase of the production of a relevant industrial compound. In this work, we develop a mechanistic dynamic model based on ordinary differential equations, comprised by elementary mass action descriptions of each reaction, from an existing model of Escherichia coli in the literature. We also explore different calibration processes for these reaction descriptions. We also contribute to the field of strain design by utilizing evolutionary algorithms with a new representation scheme that allows to search for enzyme modulations, in continuous or discrete scales, as well as reaction knockouts, in existing dynamic metabolic models, aiming at the maximization of product yields. In the bioprocess optimization field, we extended the Dynamic Flux Balance Analysis formulation to incorporate the possibility to simulate fed-batch bioprocesses. This formulation is also enhanced with methods that possess the capacity to design feed profiles to attain a specific goal, such as maximizing the bioprocess yield or productivity. All the developed methods involved some form of sensitivity and identifiability analysis, to identify how model outputs are affected by their parameters. All the work was constructed under a modular software framework (developed during this thesis), that permits the interaction of distinct algorithms and languages, being a flexible tool to utilize in a cluster environment. The framework is available as an open-source software package, and has appeal to systems biologists describing biological processes with ordinary differential equations.Uma das tendências na nossa sociedade actual é a substituição de processos químicos por processos bioquímicos, e a síntese de novos compostos por microrganismos, bem como a degradação de resíduos por meios biotecnológicos. A Biotecnologia tem, assim, a promessa de criar uma indústria mais rentavél e mais amiga do ambiente, com um número reduzido de resíduos, contrastando com a indústria química. No entanto, numa era em que os genomas são sequenciados a um ritmo nunca visto, assim como as medições de dados ómicos, esta informação não é diretamente traduzida no desenho de estirpes microbianas ou processos biológicos. Estes dados experimentais em isolamento não explicam como os diferentes componentes celulares interagem. As abordagens reducionistas que dominaram a ciência no século passado, estudam os constituintes celulares em isolamento, como pedaços isolados, sem tomar em consideração as interacções com outras moléculas, o que traduz uma visão incompleta do mundo, que compromete o desenvolvimento de novo conhecimento. Para superar estes obstáculos, uma nova abordagem à Biologia tem emergido nos últimos trinta anos. A Biologia de Sistemas pode ser definida como a conjugação de diferentes áreas (como a Matemática, Ciência da Computação, Biologia), para descrever formalmente e de forma não ambígua o comportamento dos diferentes sistemas celulares e as suas interações utilizando a modelação. A Engenharia Metabólica tira partido destas especificações formais, utilizando métodos matemáticos para derivar estratégias tendo em vista a optimização do metabolismo de microrganismos, de forma a atingir um objetivo definido como por exemplo o aumento da produção de um composto relevante a nível industrial. Neste trabalho, desenvolvemos um modelo dinâmico mecanístico baseado em equações diferenciais ordinárias, composto por descrições ação de massas elementares para cada reacção, partindo de um modelo já existente da Escherichia coli na literatura. Utilizamos também algoritmos evolucionários com um novo esquema de representação que permite pesquisar por modulações enzimáticas, numa escala contínua ou discreta, assim como eliminar reações em modelos metabólicos existentes de forma a maximizar o rendimento ou a produtividade. Todos os métodos desenvolvidos envolveram alguma forma de análise de sensibilidade ou identifiabilidade, de forma a verificar como as saídas do modelo são afetados pelos parâmetros. Todo o trabalho foi construído de acordo com uma plataforma de software modular (desenvolvida durante esta tese) que permite a interação de algoritmos e linguagens distintos, sendo uma ferramenta flexível para utilizar em ambientes de cluster. A plataforma encontra-se disponível como um pacote de software de código aberto e tem utilidade para biólogos de sistemas que pretendam descrever processos com equações diferencias ordinárias

A software tool for the simulation and optimization of dynamic metabolic models

In Systems Biology, there is a growing need for simulation and optimization tools for the prediction of the phenotypical behavior of microorganisms. In this paper, an open-source software platform is proposed to provide support for research in Metabolic Engineering, by implementing tools that enable the simulation and optimization of dynamic metabolic models using ordinary differential equations. Its main functionalities are related with (i) phenotype simulation of both wild type and mutant strains under given environmental conditions and (ii) strain optimization tackling tasks such as gene knockout selection or the definition of the optimal level of enzyme expression, given appropriate objective functions. The central carbon metabolism of E. coli was used as a case study, to illustrate the main features of the software

Evolutionary approaches for strain optimization using dynamic models under a metabolic engineering perspective

One of the purposes of Systems Biology is the quantitative modeling of biochemical networks. In this effort, the use of dynamical mathematical models provides for powerful tools in the prediction of the phenotypical behavior of microorganisms under distinct environmental conditions or subject to genetic modifications. The purpose of the present study is to explore a computational environment where dynamical models are used to support simulation and optimization tasks. These will be used to study the effects of two distinct types of modifications over metabolic models: deleting a few reactions (knockouts) and changing the values of reaction kinetic parameters. In the former case, we aim to reach an optimal knockout set, under a defined objective function. In the latter, the same objective function is used, but the aim is to optimize the values of certain enzymatic kinetic coefficients. In both cases, we seek for the best model modifications that might lead to a desired impact on the concentration of chemical species in a metabolic pathway. This concept was tested by trying to maximize the production of dihydroxyacetone phosphate, using Evolutionary Computation approaches. As a case study, the central carbon metabolism of Escherichia coli is considered. A dynamical model based on ordinary differential equations is used to perform the simulations. The results validate the main features of the approach

Structural Unemployment in Brazil in the Neoliberal Era

The Brazilian economy is historically characterized by an unequal economic and social structure. Over the years, given this economic and social structure, the Brazilian economy developed without solving its main problems. This has created barriers to both stable economic growth and improvements in the living conditions of the population. Even though the industrial sector between 1930 and 1970 increased its investment, growth and output rates, reinforcing its structure and proportion in the gross domestic product, unemployment and income inequality have remained as structural characteristics of the Brazilian economy. The crisis in the 1980s and the neoliberal policies in the 1990s strengthened these problems, especially through the increase in the unemployment rate and in the informal sector, and with the deregulation of the labor laws. The Brazilian government only started to pay attention to those problems from the Lula government onwards, implementing public policies to promote improvements in the labor market. However, high unemployment rates, low wages and income inequality still remain as structural problems in the Brazilian economy. Based on these aspects, the article will analyze structural unemployment in Brazil over the last ten years, pointing out and trying to understand the problems and trends. The discussion developed by Karl Marx in Capital concerning the relative surplus population and the reserve army will be the theoretical approach on which that analysis will be based

A JUSTIÇA TERAPÊUTICA E O CONTEÚDO IDEOLÓGICO DA CRIMINALIZAÇÃO DO USO DE DROGAS NO BRASIL

O processo de criminalização do uso de drogas ilícitas no Brasil começou já no período colonial. Desde então, várias medidas têm sido aplicadas na tentativa de conter o consumo, restando infrutíferas sob o aspecto da contenção do consumo, mas eficazes sob o aspecto da criminalização de classes sociais economicamente desfavorecidas e (ou) estigmatizadas. A proposta da “justiça terapêutica” hoje é adotada em alguns estados brasileiros como uma “nova” solução, mas como o histórico da política criminal brasileira revela, tal proposta não passa da reformulação cíclica de uma antiga posição que reforça o binômio “doença-crime” e atende aos interesses das classes hegemônicas como eficaz instrumento de controle social