Salivary proteomics and peptidomics of type 1 diabetes Mellitus

A Diabetes Mellitus (DM) compreende um conjunto de desordens metabólicas comuns caracterizadas por hiperglicemia, que afeta diferentes órgãos do organismo. Ao longo do tempo, ocorrem danos microvasculares no glomérulo renal, retina e nervos periféricos, bem como doença macrovascular nas artérias. A composição da saliva também é afetada pela DM, com consequências na homeostasia oral. No entanto, o proteoma e o peptidoma salivar têm sido pouco explorados na DM tipo 1 e nas suas complicações crónicas. Tendo em conta o crescente interesse na saliva como fluido diagnóstico, o objetivo principal deste trabalho foi avaliar os eventos proteolíticos subjacentes à DM tipo 1 e às suas complicações microvasculares, bem como, caracterizar as alterações induzidas pela DM tipo 1 no proteoma e peptidoma salivar. A DM tipo 1 e particularmente as complicações microvasculares associadas modulam o perfil proteolítico dos fluidos biológicos, com diferenças significativas de atividade observadas na urina e saliva, atribuídas principalmente ao complexo Metaloproteinase da Matriz (MMP)-9/lipocalina associada à gelatinase de neutrófilos, aminopeptidase N, azurocidina e calicreína 1. O aumento da atividade proteolítica observado na saliva total dos diabéticos resultou no aumento da percentagem de péptidos, principalmente de um número acrescido de fragmentos de colagénio do tipo I, refletindo possivelmente um estado inflamatório crónico dos tecidos orais e periodontais. O peptidoma também corrobora uma maior suscetibilidade das proteínas salivares, especificamente, das proteínas ricas em prolina básicas (bPRP) 1, bPRP2 e proteínas ricas em prolina ácidas (aPRP) à proteólise, evidenciando a geração de fragmentos de proteínas associadas à ligação a bactérias. A análise do proteoma salivar baseada em iTRAQ mostrou uma sobre-expressão de L-plastina, fator do adenocarcinoma do pâncreas e das proteínas S100-A8 e S100-A9, enfatizando a importância do sistema imune inato na patogénese da DM tipo 1 e das complicações microvasculares associadas. A análise integrada de todas as proteínas expressas diferencialmente entre os pacientes diabéticos com ou sem complicações microvasculares e indivíduos saudáveis foi realizada com o STRING, onde se observam três conjuntos funcionalmente ligados, um compreende a interação entre o colagénio tipo I, colagénio tipo II e MMP-9, um segundo conjunto envolve a MMP-2 e o colagénio de tipo I e um terceiro conjunto composto por proteínas salivares e inflamatórias. Estes conjuntos estão associados com as vias Kegg de interação recetor-matriz extracelular, de adesão focal e migração transendotelial dos leucócitos. Por outro lado, a análise do proteoma e peptidoma salivar destacou potenciais biomarcadores para o diagnóstico e prognóstico da DM tipo 1 e das suas complicações.

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.

Identification of protein complexes in Alzheimer's disease

A Doença de Alzheimer (AD) é a maior doença neurodegenerativa a nível mundial, e a principal causa de demência na população idosa. O processamento da proteína precursora de amilóide (APP) pelas β- e g- secretases origina o peptídeo Aβ, que agrega em oligómeros neurotóxicos e em placas senis. Estes são eventos-chave na patogénese da DA que levam à rutura da neurotransmissão sináptica, morte neuronal e inflamação neuronal do hipocampo e córtex cerebral, causando perda de memória disfunção cognitiva geral. Apesar dos grandes avanços no conhecimento do papel do processamento da APP na DA, a sua função fisiológica ainda não foi totalmente elucidada. Os mapas de interações proteína-proteína (PPI) humanos têm desempenhado um papel importante na investigação biomédica, em particular no estudo de vias de sinalização e de doenças humanas. O método dois-híbrido em levedura (YTH) consiste numa plataforma para a produção rápida de redes de PPI em larga-escala. Neste trabalho foram realizados vários rastreios YTH com o objetivo de identificar proteínas específicas de cérebro humano que interagissem com a APP, ou com o seu domínio intracelular (AICD), tanto o tipo selvagem como com os mutantes Y687F, que mimetizam o estado desfosforilado do resíduo Tyr-687. De facto, a endocitose da APP e a produção de Aβ estão dependentes do estado de fosforilação da Tyr-687. Os rastreios YTH permitiram assim obter de redes proteínas que interagem com a APP, utilizando como “isco” a APP, APPY687F e AICDY687F. Os clones positivos foram isolados e identificados através de sequenciação do cDNA. A maior parte dos clones identificados, 118, correspondia a sequências que codificam para proteínas conhecidas, resultando em 31 proteínas distintas. A análise de proteómica funcional das proteínas identificadas neste estudo e em dois projetos anteriores (AICDY687E, que mimetiza a fosforilação, e AICD tipo selvagem), permitiram avaliar a relevância da fosforilação da Tyr-687. Três clones provenientes do rastreio YTH com a APPY687F foram identificados como um novo transcrito da proteína Fe65, resultante de splicing alternativo, a Fe65E3a (GenBank Accession: EF103274), que codifica para a isoforma p60Fe65. A p60Fe65 está enriquecida no cérebro e os seus níveis aumentam durante a diferenciação neuronal de células PC12, evidenciando o potencial papel que poderá desempenhar na patologia da DA. A RanBP9 é uma proteína nuclear e citoplasmática envolvida em diversas vias de sinalização celulares. Neste trabalho caracterizou-se a nova interação entre a RanBP9 e o AICD, que pode ser regulada pela fosforilação da Tyr-687. Adicionalmente, foi identificada uma nova interação entre a RanBP9 e a acetiltransferase de histonas Tip60. Demonstrou-se ainda que a RanBP9 tem um efeito de regulação inibitório na transcrição mediada por AICD, através da interação com a Tip60, afastando o AICD dos locais de transcrição ativos. O estudo do interactoma da APP/AICD, modelado pela fosforilação da Tyr-687, revela que a APP poderá estar envolvida em novas vias celulares, contribuindo não só para o conhecimento do papel fisiológico da APP, como também auxilia a revelar as vias que levam à agregação de Aβ e neurodegeneração. A potencial relevância deste trabalho relaciona-se com a descoberta de algumas interações proteicas/vias de sinalização que podem que podem ser relevantes para o desenvolvimento de novas estratégias terapêuticas na DA.

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.