The use of biomarkers to diagnose the ecological impact of pollutants in Mediterranean rivers

Um assunto que requer atenção é a avaliação ecológica da qualidade da água de ecossistemas de água doce. Uma abordagem que surge como promissora é a biomonitorização baseada em biomarcadores, porque pode avaliar a saúde dos organismos e obter sinais de alerta precoce acerca dos riscos ambientais. Até agora, porém, o uso de biomarcadores em espécies de invertebrados, para diagnosticar danos ecológicos nos rios, é escasso. Por essa razão, existe uma necessidade urgente de desenvolver biomarcadores nas principais espécies de macroinvertebrados dos ecossistemas fluviais que são alvo de estudo. Esta tese tem como objectivo averiguar se as respostas in situ, aliadas aos biomarcadores, podem ser um método viável para avaliar os danos ecológicos de contaminantes em ecossistemas de água doce. Numa primeira fase, os biomarcadores foram usados para averiguar os mecanismos fisiológicos de adaptação genética de clones de Daphnia magna ao pesticida organofosforado fenitrothion. Numa segunda fase, os biomarcadores foram usados como ferramentas de diagnóstico de poluição em zonas ribeirinhas. Estes estudos foram realizados com três espécies-chave de macroinvertebrados: Daphnia magna, Corbicula fluminea e Hydropsyche exocellata, nos rios Besós e Llobregat e no Delta do rio Ebro (NE Espanha). Além disso, foram realizados com animais capturados nos rios, ou com ensaios de transplantes, e foram complementados com índices biológicos de macroinvertebrados e análises químicas da água e dos animais. Como os contaminantes químicos têm vários modos toxicológicos de acção e, portanto, afectam várias respostas bioquímicas dos organismos, foram analisados nas três espécies um conjunto de biomarcadores pertencentes a diferentes vias metabólicas. A abordagem experimental indica que o uso combinado de biomarcadores e outras medidas, tais como índices biológicos e testes in situ, contribui para diagnosticar os efeitos prejudiciais de contaminantes nas comunidades ribeirinhas.

Pregnancy and newborns disorders followed by urine metabolomics

Chapter 1 introduces the scope of the work by identifying the clinically relevant prenatal disorders and presently available diagnostic methods. The methodology followed in this work is presented, along with a brief account of the principles of the analytical and statistical tools employed. A thorough description of the state of the art of metabolomics in prenatal research concludes the chapter, highlighting the merit of this novel strategy to identify robust disease biomarkers. The scarce use of maternal and newborn urine in previous reports enlightens the relevance of this work. Chapter 2 presents a description of all the experimental details involved in the work performed, comprising sampling, sample collection and preparation issues, data acquisition protocols and data analysis procedures. The proton Nuclear Magnetic Resonance (NMR) characterization of maternal urine composition in healthy pregnancies is presented in Chapter 3. The urinary metabolic profile characteristic of each pregnancy trimester was defined and a 21-metabolite signature found descriptive of the metabolic adaptations occurring throughout pregnancy. 8 metabolites were found, for the first time to our knowledge, to vary in connection to pregnancy, while known metabolic effects were confirmed. This chapter includes a study of the effects of non-fasting (used in this work) as a possible confounder. Chapter 4 describes the metabolomic study of 2nd trimester maternal urine for the diagnosis of fetal disorders and prediction of later-developing complications. This was achieved by applying a novel variable selection method developed in the context of this work. It was found that fetal malformations (FM) (and, specifically those of the central nervous system, CNS) and chromosomal disorders (CD) (and, specifically, trisomy 21, T21) are accompanied by changes in energy, amino acids, lipids and nucleotides metabolic pathways, with CD causing a further deregulation in sugars metabolism, urea cycle and/or creatinine biosynthesis. Multivariate analysis models´ validation revealed classification rates (CR) of 84% for FM (87%, CNS) and 85% for CD (94%, T21). For later-diagnosed preterm delivery (PTD), preeclampsia (PE) and intrauterine growth restriction (IUGR), it is found that urinary NMR profiles have early predictive value, with CRs ranging from 84% for PTD (11-20 gestational weeks, g.w., prior to diagnosis), 94% for PE (18-24 g.w. pre-diagnosis) and 94% for IUGR (2-22 g.w. pre-diagnosis). This chapter includes results obtained for an ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) study of pre-PTD samples and correlation with NMR data. One possible marker was detected, although its identification was not possible. Chapter 5 relates to the NMR metabolomic study of gestational diabetes mellitus (GDM), establishing a potentially predictive urinary metabolic profile for GDM, 2-21 g.w. prior to diagnosis (CR 83%). Furthermore, the NMR spectrum was shown to carry information on individual phenotypes, able to predict future insulin treatment requirement (CR 94%). Chapter 6 describes results that demonstrate the impact of delivery mode (CR 88%) and gender (CR 76%) on newborn urinary profile. It was also found that newborn prematurity, respiratory depression, large for gestational age growth and malformations induce relevant metabolic perturbations (CR 82-92%), as well as maternal conditions, namely GDM (CR 82%) and maternal psychiatric disorders (CR 91%). Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the value of maternal or newborn urine metabolomics for pregnancy monitoring and disease prediction, towards the development of new early and non-invasive diagnostic methods.

Concentration of tumor biomarkers using aqueous biphasic systems

According to the World Health Organization, around 8.2 million people die each year with cancer. Most patients do not perform routine diagnoses and the symptoms, in most situations, occur when the patient is already at an advanced stage of the disease, consequently resulting in a high cancer mortality. Currently, prostate cancer is the second leading cause of death among males worldwide. In Portugal, this is the most diagnosed type of cancer and the third that causes more deaths. Taking into account that there is no cure for advanced stages of prostate cancer, the main strategy comprises an early diagnosis to increase the successful rate of the treatment. The prostate specific antigen (PSA) is an important biomarker of prostate cancer that can be detected in biological fluids, including blood, urine and semen. However, the commercial kits available are addressed for blood samples and the commonly used analytical methods for their detection and quantification requires specialized staff, specific equipment and extensive sample processing, resulting in an expensive process. Thus, the aim of this MSc thesis consisted on the development of a simple, efficient and less expensive method for the extraction and concentration of PSA from urine samples using aqueous biphasic systems (ABS) composed of ionic liquids. Initially, the phase diagrams of a set of aqueous biphasic systems composed of an organic salt and ionic liquids were determined. Then, their ability to extract PSA was ascertained. The obtained results reveal that in the tested systems the prostate specific antigen is completely extracted to the ionic-liquid-rich phase in a single step. Subsequently, the applicability of the investigated ABS for the concentration of PSA was addressed, either from aqueous solutions or urine samples. The low concentration of this biomarker in urine (clinically significant below 150 ng/mL) usually hinders its detection by conventional analytical techniques. The obtained results showed that it is possible to extract and concentrate PSA, up to 250 times in a single-step, so that it can be identified and quantified using less expensive techniques.

Concentration of tumor biomarkers using aqueous biphasic systems

According to the World Health Organization, around 8.2 million people die each year with cancer. Most patients do not perform routine diagnoses and the symptoms, in most situations, occur when the patient is already at an advanced stage of the disease, consequently resulting in a high cancer mortality. Currently, prostate cancer is the second leading cause of death among males worldwide. In Portugal, this is the most diagnosed type of cancer and the third that causes more deaths. Taking into account that there is no cure for advanced stages of prostate cancer, the main strategy comprises an early diagnosis to increase the successful rate of the treatment. The prostate specific antigen (PSA) is an important biomarker of prostate cancer that can be detected in biological fluids, including blood, urine and semen. However, the commercial kits available are addressed for blood samples and the commonly used analytical methods for their detection and quantification requires specialized staff, specific equipment and extensive sample processing, resulting in an expensive process. Thus, the aim of this MSc thesis consisted on the development of a simple, efficient and less expensive method for the extraction and concentration of PSA from urine samples using aqueous biphasic systems (ABS) composed of ionic liquids. Initially, the phase diagrams of a set of aqueous biphasic systems composed of an organic salt and ionic liquids were determined. Then, their ability to extract PSA was ascertained. The obtained results reveal that in the tested systems the prostate specific antigen is completely extracted to the ionic-liquid-rich phase in a single step. Subsequently, the applicability of the investigated ABS for the concentration of PSA was addressed, either from aqueous solutions or urine samples. The low concentration of this biomarker in urine (clinically significant below 150 ng/mL) usually hinders its detection by conventional analytical techniques. The obtained results showed that it is possible to extract and concentrate PSA, up to 250 times in a single-step, so that it can be identified and quantified using less expensive techniques.