12,907 research outputs found

    Impact of plant growth promoting rhizobacteria (PGPR) on stress resistance of winter wheat (Triticum aestivum L.)

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    Wheat is one of the worldwide most cultivated crop and highly contribute to secure food production in different world regions. Although, it grows almost ubiquitous, its production is severely vulnerable to drought. Soil and rhizosphere microbial communities associated to plants come more and more into the focus of modern agrobiology research, as a solution to maintain productivity under drought, and reinforce sustainable production. Whereas numerous studies on wheat production and the beneficial influence of the soil microbiome under drought have been performed in arid and semiarid regions of the world, comparable studies in Central Europe are rare. This might change due to the ongoing climate crisis and expected less frequent precipitations during the vegetation season. So far, most studies that focus on acclimatization of the wheat rhizobiome to water deficit mostly consider, at best, two interacting factors, and lack to consider other biotic or abiotic drivers of rhizosphere microbial communities structure and function. Therefore, the aim of this thesis was to combine complementary analytical approaches to investigate drought-induced structural and functional changes in wheat rhizosphere bacterial communities and individual species in dependency of soil type, farming system, wheat cultivar and plant development stage, and to determine how these changes affect wheat performance as a consequence of possible climate change scenarios in Central Germany. The presented thesis starts with a general introduction and presentation of the project, followed by three consecutive chapters containing the main findings published in peer-reviewed articles. Starting with an experiment performed in the greenhouse (Chapter 1) and then moving to a realistic climate scenario under field conditions (Chapter 2 and 3), the three chapters demonstrate the sole and interacting effects of drought and farming system (Chapter 1-3), soil type and wheat cultivar (Chapter 1), as well as plant growth stages (Chapter 2 and 3) on bacterial communities and individual taxa of the wheat rhizobiome. The methods used reach from traditional cultivation and in-vitro bioassays (Chapter 3), over extracellular enzyme activity potentials (Chapter 1 and 2) to more advanced technologies such as metabarcoding (Chapter 1 and 2) and computational tools (Chapter 1 and 2), addressing single bacterial taxa as well as community level. Finalizing the thesis, a concluding synopsis compiles and critically reviews the gained results and formulates future study perspectives. In Chapter 1, we evaluated the impact of soil type (loamy vs. sandy), farming management (conventional vs. organic), wheat cultivar (non-demanding vs. demanding), and the interacting effects of these factors on wheat rhizobacterial community composition and function under extreme drought conditions. Water deficit exerted a strong pressure on rhizobacterial communities, and interacted with soil type and farming management, but not with the wheat cultivar types. In the sandy soil, we observed a strong drought-induced shift in community composition, with a decrease in species diversity and extracellulare enzyme production, while changes by drought were less prominent in the fertile loamy soil. A particular exception from this pattern was found for enzyme activities involved in carbon cycling in the sandy soil suggesting a positive plant-soil-feedback on enzyme activities by drought conditioning. In Chapter 2, two individual, but interrelated aims were pursued. First, we used the platform of the Global Change Experimental Facility (GCEF) to explore the impact of two farming practices (conventional vs. organic) and two climate treatments (ambient vs. future) on bacterial community composition and activity profiles of extracellulare enzymes involved in C,N and P cycles in the wheat rhizosphere at two different plant growth stages. The climate treatment in the GCEF had no effect on the rhizobacterial communities. Rhizobacterial community composition and functions significantly differed between vegetative and mature growth stages of the plants, in both conventional and organic farming. In a second step, we reused the data to explore further the accuracy of computational approaches, like Tax4Fun and PanFP, to predict functional profiles of bacterial communities based on 16S rDNA abundance data. To this end, we compared the measured enzyme activities with respective gene abundances in the community under different climate and farming treatments, and at the two plant development stages. This analysis revealed qualitative, but not necessarily quantitative concordances, i.e. we found effects of the different treatments on the measured enzyme activities reflected in the gene abundances. Chapter 3 is a complementary approach to Chapter 2 with a focus on individual bacterial species level. Culture-dependent methods were used to specifically isolate strong P-solubilizing bacteria from the rhizosphere of wheat, which were tested for their in-vitro drought tolerance. Among the more than 800 isolated species, Phyllobacterium, Pseudomonas and Streptomyces species dominated. While farming management and climate treatment had only minor effects on composition and functions of the isolates, the wheat growth stages had an impact, whereby a dominance of Pseudomonas species at the vegetative growth phase was replaced by dominance of Phyllobacterium species at the mature growth phase. Since P-solubilizing potential was paralleled by a high in vitro drought tolerance, Phyllobacterium species were characterized as promising plant growth promoting rhizobacteria (PGPR) of wheat under future drought conditions. In the synopsis part, we evaluated the multifactorial and multidisciplinary approaches and investigated to what extent the adaptations of bacterial communities in field and pot experiments coincided or differed. Overall, we found common and distinct adaptation processes of bacterial communities and individual species in the rhizosphere of wheat to drought, whereby single factors, but also interacting effects exerted a strong impact on these processes. This study underlines the importance of multifactorial approaches to reveal community- or species-specific plant-soil-feedbacks.:Contents 3 Preface 5 Bibliographic description 6 Zusammenfassung 9 Summary 13 Introduction 16 When extreme events become the new normal 17 Feedback to agricultural production and need for management adaptation 20 Difficulties in exploring the soil microbiome and identification of plant beneficial microbial taxa 22 Our approach with wheat 24 Bibliography 27 ֎ Chapter 1 31 Interactions Between Soil Properties, Agricultural Management and Cultivar Type Drive Structural and Functional Adaptations of the Wheat Rhizosphere Microbiome To Drought 31 Supplemental Tables 51 Supplemental Figures 55 ╬ Chapter 2 59 Can We Estimate Functionality of Soil Microbial Communities from Structure-Derived Predictions? A Reality Test in Agricultural Soils 59 Supplementary Tables 79 Supplemental Figures 84 Supplemental Material 1: 87 Variation in edaphic parameters according to experimental factors 87 Supplemental Material 2 88 Effect of abiotic soil parameters on bacterial community structure and function 88 Supplemental Material 3 90 Indicator species analysis 90 ۝ Chapter 3 95 Shifts Between and Among Populations of Wheat Rhizosphere Pseudomonas, Streptomyces and Phyllobacterium Suggest Consistent Phosphate Mobilization at Different Wheat Growth Stages Under Abiotic Stress 95 Supplementary Figures 112 Supplementary Tables 117 Synopsis 152 Multidisciplinary approaches combine advantages of cultivation-based and high throughput community-based methods 155 Multifactorial approaches to gain a more holistic understanding of plant-microbe interactions in pot experiments 157 Transferability of findings gained in the pot experiment to field conditions 159 Towards a wheat core microbiome? 161 Study limitations and outlook 163 Bibliography 164 Acknowledgements 169 Curriculum Vitae 171 Personal details 171 Education 171 Work experience 172 Research and Mentoring experience 172 Extracurricular activities 173 List of publications and Presentations 174 Publications in peer-reviewed journals: 174 Oral Presentations: 175 Poster Presentations: 175 Statutory declaration 176 Eidesstattliche Erklärung 177 Author contributions 178Weizen ist eine der weltweit am häufigsten angebauten Kulturpflanzen und trägt zur Sicherung der Nahrungsmittelproduktion in verschiedenen Regionen der Welt bei. Obwohl er fast überall angebaut werden kann, ist die Produktion durch Trockenheit limitiert. Daher rücken mehr und mehr die mikrobiellen Gemeinschaften im Boden und in der Rhizosphäre in den Mittelpunkt der modernen agrarbiologischen Forschung, um die Produktivität bei Trockenheit aufrechtzuerhalten und eine nachhaltige Produktion zu fördern. Während bereits zahlreiche Studien über die Weizenproduktion und den positiven Einfluss des Bodenmikrobioms in ariden und semiariden Regionen der Welt durchgeführt wurden, sind vergleichbare Studien in Mitteleuropa selten. Dies könnte sich aufgrund der anhaltenden Klimakrise und der zu erwartenden ausbleibenden Sommerniederschläge ändern. Dabei haben die meisten Studien, die sich mit der Akklimatisierung des Weizenrhizobioms an Wasserdefizite befasst haben, bestenfalls den Einfluss von Trockenheit und ein oder zwei weiteren biotischen oder abiotischen Einflussfaktoren, die zudem miteinander interagieren können, auf die Struktur und Funktion der mikrobiellen Gemeinschaften in der Rhizosphäre untersucht. Ziel dieser Arbeit war es daher, verschiedene komplementäre Analysemethoden zu kombinieren, um trockenheitsbedingte strukturelle und funktionelle Veränderungen in den bakteriellen Gemeinschaften und auch einzelner Arten in der Weizenrhizosphäre, in Abhängigkeit von Bodentyp, Landnutzungssystem, Weizensorte und Pflanzenentwicklungsstadium zu untersuchen, und zu ermitteln, wie sich diese Veränderungen auf die Produktivität des Weizens als Folge möglicher Szenarien des Klimawandels in Mitteldeutschland auswirken. Die vorliegende Arbeit leitet mit einer allgemeinen Einführung und Vorstellung des Projekts ein, gefolgt von drei aufeinanderfolgenden Kapiteln, die die wichtigsten Ergebnisse enthalten, die in von Fachleuten begutachteten Artikeln veröffentlicht wurden. Beginnend mit einem Experiment im Gewächshaus (Kapitel 1) und weiterführend zu einem realistischen Klimaszenario unter Feldbedingungen (Kapitel 2 und 3), beschreiben die drei Kapitel die alleinigen und interagierenden Auswirkungen von Trockenheit und Anbausystem (Kapitel 1-3), Bodentyp und Weizensorte (Kapitel 1), sowie Pflanzenwachstumsstadien (Kapitel 2 und 3) auf Bakteriengemeinschaften und einzelne Taxa des Weizenrhizobioms. Die verwendeten Methoden reichen dabei von der traditionellen Kultivierung und In-vitro-Bioassays (Kapitel 3), über extrazelluläre Enzymaktivitätspotenziale (Kapitel 1 und 2), bis hin zu fortschrittlicheren Technologien, wie Metabarcoding (Kapitel 1 und 2) und computergestützten Vorhersagen (Kapitel 1 und 2). Zum Abschluss der Arbeit werden in einer abschließenden Synopsis die gewonnenen Ergebnisse zusammengetragen und kritisch betrachtet, sowie Ideen für zukünftige Studien formuliert. In Kapitel 1 untersuchten wir die Auswirkungen des Bodentyps (lehmig vs. sandig), der Bewirtschaftung (konventionell vs. ökologisch), der Weizensorte (anspruchslos vs. anspruchsvoll) und die Wechselwirkungen zwischen diesen Faktoren auf die Zusammensetzung und Funktion der Bakteriengemeinschaft in der Rhizosphäre von Weizen unter extremen Trockenheitsbedingungen. Das Wasserdefizit übte einen starken Druck auf die Rhizosphärenbakteriengemeinschaften aus und stand in Wechselwirkung mit dem Bodentyp und der Bewirtschaftung, nicht aber mit den Weizensorten. In den Sandböden beobachteten wir eine starke trockenheitsbedingte Veränderung der Zusammensetzung der Gemeinschaft mit einem Rückgang der Artenvielfalt und der extrazellulären Enzymproduktion, während die Veränderungen durch die Trockenheit in den fruchtbaren Lehmböden weniger stark ausgeprägt waren. Eine besondere Ausnahme von diesem Muster wurde für Enzymaktivitäten gefunden, die am Kohlenstoffkreislauf im Sandboden beteiligt sind, was auf eine positive Rückkopplung zwischen Pflanze und Bodengemeinschaften unter Trockenheit hindeutet. In Kapitel 2 wurden zwei einzelne, jedoch miteinander verknüpfte Ziele verfolgt. Erstens nutzten wir die Plattform der Global Change Experimental Facility (GCEF), um die Auswirkungen von zwei Anbaupraktiken (konventionell vs. ökologisch) und zwei Klimabehandlungen (ambient vs. zukünftig) auf die Zusammensetzung der Bakteriengemeinschaft und die Aktivitätsprofile extrazellulärer Enzyme, die an den C-, N- und P-Zyklen in der Rhizosphäre von Weizen beteiligt sind, in zwei verschiedenen Pflanzenwachstumsstadien zu untersuchen. Die Klimabehandlung in der GCEF hatte keinen Einfluss auf die Rhizosphärenbakteriengemeinschaften. Die Zusammensetzung und die Funktionen der Rhizosphärenbakteriengemeinschaften unterschieden sich signifikant zwischen dem vegetativen und dem generativen Wachstumsstadium der Pflanzen, sowohl im konventionellen als auch im ökologischen Landbau. In einem zweiten Schritt nutzten wir die gewonnenen Daten, um die Genauigkeit rechnerischer Ansätze wie Tax4Fun und PanFP zur Vorhersage funktioneller Profile von Bakteriengemeinschaften auf der Grundlage von 16S rDNA-Daten zu überprüfen. Zu diesem Zweck verglichen wir die gemessenen Enzymaktivitäten mit den jeweiligen Genhäufigkeiten in der Gemeinschaft unter verschiedenen Klima- und Anbaubedingungen und in den beiden Entwicklungsstadien der Pflanzen. Diese Analyse ergab qualitative, aber nicht unbedingt quantitative Übereinstimmungen, d. h. wir fanden Auswirkungen der verschiedenen Behandlungen auf die gemessenen Enzymaktivitäten, die sich auch in den Genhäufigkeiten widerspiegeln. Kapitel 3 stellt einen ergänzenden Ansatz zu Kapitel 2 dar, wobei der Schwerpunkt auf einzelnen Bakterienarten liegt. Mit kulturabhängigen Methoden wurden gezielt stark Phosphat-solubilisierende Bakterien aus der Rhizosphäre von Weizen isoliert und auf ihre In-vitro-Trockenheitstoleranz getestet. Unter den mehr als 800 isolierten Arten dominierten Phyllobacterium-, Pseudomonas- und Streptomyces-Arten. Während Anbaumanagement und Klimabehandlung nur geringe Auswirkungen hatten, wirkten sich die Wachstumsstadien des Weizens signifikant auf die Zusammensetzung und Funktionen der Isolate aus, wobei eine Dominanz von Pseudomonas-Arten in der vegetativen Wachstumsphase durch eine Dominanz von Phyllobacterium-Arten in der generativen Wachstumsphase ersetzt wurde. Da das Potenzial zur P-Solubilisierung mit einer hohen in vitro-Trockenheitstoleranz einherging, wurden Phyllobacterium-Arten als vielversprechende pflanzenwachstumsfördernde Rhizobakterien (PGPR) für Weizen unter zukünftigen Trockenheitsbedingungen charakterisiert. In der Synopsis dieser Arbeit bewerteten wir die multifaktoriellen und multidisziplinären Ansätze, und untersuchten, inwieweit die Anpassungen der Bakteriengemeinschaften in Feld- und Topfversuchen übereinstimmen oder sich unterscheiden. Insgesamt fanden wir allgemeine, aber auch differenzielle Anpassungsprozesse von Bakteriengemeinschaften und einzelnen Arten in der Rhizosphäre von Weizen an die Trockenheit, wobei einzelne Faktoren, aber auch interagierende Effekte einen starken Einfluss auf diese Prozesse ausübten. Diese Studie unterstreicht damit die Bedeutung multifaktorieller Ansätze, um gemeinschafts- oder artspezifische Rückkopplungen zwischen Pflanze und Boden zu untersuchen.:Contents 3 Preface 5 Bibliographic description 6 Zusammenfassung 9 Summary 13 Introduction 16 When extreme events become the new normal 17 Feedback to agricultural production and need for management adaptation 20 Difficulties in exploring the soil microbiome and identification of plant beneficial microbial taxa 22 Our approach with wheat 24 Bibliography 27 ֎ Chapter 1 31 Interactions Between Soil Properties, Agricultural Management and Cultivar Type Drive Structural and Functional Adaptations of the Wheat Rhizosphere Microbiome To Drought 31 Supplemental Tables 51 Supplemental Figures 55 ╬ Chapter 2 59 Can We Estimate Functionality of Soil Microbial Communities from Structure-Derived Predictions? A Reality Test in Agricultural Soils 59 Supplementary Tables 79 Supplemental Figures 84 Supplemental Material 1: 87 Variation in edaphic parameters according to experimental factors 87 Supplemental Material 2 88 Effect of abiotic soil parameters on bacterial community structure and function 88 Supplemental Material 3 90 Indicator species analysis 90 ۝ Chapter 3 95 Shifts Between and Among Populations of Wheat Rhizosphere Pseudomonas, Streptomyces and Phyllobacterium Suggest Consistent Phosphate Mobilization at Different Wheat Growth Stages Under Abiotic Stress 95 Supplementary Figures 112 Supplementary Tables 117 Synopsis 152 Multidisciplinary approaches combine advantages of cultivation-based and high throughput community-based methods 155 Multifactorial approaches to gain a more holistic understanding of plant-microbe interactions in pot experiments 157 Transferability of findings gained in the pot experiment to field conditions 159 Towards a wheat core microbiome? 161 Study limitations and outlook 163 Bibliography 164 Acknowledgements 169 Curriculum Vitae 171 Personal details 171 Education 171 Work experience 172 Research and Mentoring experience 172 Extracurricular activities 173 List of publications and Presentations 174 Publications in peer-reviewed journals: 174 Oral Presentations: 175 Poster Presentations: 175 Statutory declaration 176 Eidesstattliche Erklärung 177 Author contributions 17

    NALCN is a potential biomarker and therapeutic target in human cancers

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    Background: Sodium leak channel non-selective (NALCN), known as a voltage-independent Na+ channel, is increasingly considered to play vital roles in tumorigenesis and metastasis of human cancers. However, no comprehensive pan-cancer analysis of NALCN has been conducted. Our study aims to explore the potential diagnostic, prognostic and therapeutic value of NALCN in human cancers.Methods: Through comprehensive application of datasets from Human Protein Atlas (HPA), The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), Enhanced Version of Tumor Immune Estimation Resource (TIMER2.0), Tumor and Immune System Interaction Database (TISIDB), The University of Alabama at Birmingham Cancer data analysis Portal (UALCAN), cBioPortal, GeneMANIA and Search Tool for the Retrieval of Interaction Gene/Proteins (STRING) databases, we explored the potential roles of NALCN in different cancers. The differential expression, prognostic implications, pathological stages and grades, molecular and immune subtypes, diagnostic accuracy, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR) genes, immune checkpoint genes, chemokine genes, major histocompatibility complex (MHC)-related genes, tumor-infiltrating immune cells (TIICs), promoter methylation, mutations, copy number alteration (CNA), and functional enrichment related to NALCN were analyzed.Results: Most cancers lowly expressed NALCN. Upregulated NALCN expression was associated with poor or better prognosis in different cancers. Moreover, NALCN was correlated with clinicopathological features in multiple cancers. NALCN showed high diagnostic accuracy in 5 caner types. NALCN is highly linked with immune-related biomarkers, immune-related genes and TIICs. Significant methylation changes and genetic alteration of NALCN can be observed in many cancers. Enrichment analysis showed that NALCN is closely related to multiple tumor-related signaling pathways.Conclusion: Our study revealed the vital involvement of NALCN in cancer. NALCN can be used as a prognostic biomarker for immune infiltration and clinical outcomes, and has potential diagnostic and therapeutic implications

    Salinity stress endurance of the plants with the aid of bacterial genes

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    The application of plant growth-promoting bacteria (PGPB) is vital for sustainable agriculture with continuous world population growth and an increase in soil salinity. Salinity is one of the severe abiotic stresses which lessens the productivity of agricultural lands. Plant growth-promoting bacteria are key players in solving this problem and can mitigate salinity stress. The highest of reported halotolerant Plant growth-promoting bacteria belonged to Firmicutes (approximately 50%), Proteobacteria (40%), and Actinobacteria (10%), respectively. The most dominant genera of halotolerant plant growth-promoting bacteria are Bacillus and Pseudomonas. Currently, the identification of new plant growth-promoting bacteria with special beneficial properties is increasingly needed. Moreover, for the effective use of plant growth-promoting bacteria in agriculture, the unknown molecular aspects of their function and interaction with plants must be defined. Omics and meta-omics studies can unreveal these unknown genes and pathways. However, more accurate omics studies need a detailed understanding of so far known molecular mechanisms of plant stress protection by plant growth-promoting bacteria. In this review, the molecular basis of salinity stress mitigation by plant growth-promoting bacteria is presented, the identified genes in the genomes of 20 halotolerant plant growth-promoting bacteria are assessed, and the prevalence of their involved genes is highlighted. The genes related to the synthesis of indole acetic acid (IAA) (70%), siderophores (60%), osmoprotectants (80%), chaperons (40%), 1-aminocyclopropane-1-carboxylate (ACC) deaminase (50%), and antioxidants (50%), phosphate solubilization (60%), and ion homeostasis (80%) were the most common detected genes in the genomes of evaluated halotolerant plant growth-promoting and salinity stress-alleviating bacteria. The most prevalent genes can be applied as candidates for designing molecular markers for screening of new halotolerant plant growth-promoting bacteria

    HuCoPIA: An Atlas of Human vs. SARS-CoV-2 Interactome and the Comparative Analysis with Other Coronaviridae Family Viruses

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    SARS-CoV-2, a novel betacoronavirus strain, has caused a pandemic that has claimed the lives of nearly 6.7M people worldwide. Vaccines and medicines are being developed around the world to reduce the disease spread, fatality rates, and control the new variants. Understanding the protein-protein interaction mechanism of SARS-CoV-2 in humans, and their comparison with the previous SARS-CoV and MERS strains, is crucial for these efforts. These interactions might be used to assess vaccination effectiveness, diagnose exposure, and produce effective biotherapeutics. Here, we present the HuCoPIA database, which contains approximately 100,000 protein-protein interactions between humans and three strains (SARS-CoV-2, SARS-CoV, and MERS) of betacoronavirus. The interactions in the database are divided into common interactions between all three strains and those unique to each strain. It also contains relevant functional annotation information of human proteins. The HuCoPIA database contains SARS-CoV-2 (41,173), SARS-CoV (31,997), and MERS (26,862) interactions, with functional annotation of human proteins like subcellular localization, tissue-expression, KEGG pathways, and Gene ontology information. We believe HuCoPIA will serve as an invaluable resource to diverse experimental biologists, and will help to advance the research in better understanding the mechanism of betacoronaviruses

    Estudo da remodelagem reversa miocárdica através da análise proteómica do miocárdio e do líquido pericárdico

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    Valve replacement remains as the standard therapeutic option for aortic stenosis patients, aiming at abolishing pressure overload and triggering myocardial reverse remodeling. However, despite the instant hemodynamic benefit, not all patients show complete regression of myocardial hypertrophy, being at higher risk for adverse outcomes, such as heart failure. The current comprehension of the biological mechanisms underlying an incomplete reverse remodeling is far from complete. Furthermore, definitive prognostic tools and ancillary therapies to improve the outcome of the patients undergoing valve replacement are missing. To help abridge these gaps, a combined myocardial (phospho)proteomics and pericardial fluid proteomics approach was followed, taking advantage of human biopsies and pericardial fluid collected during surgery and whose origin anticipated a wealth of molecular information contained therein. From over 1800 and 750 proteins identified, respectively, in the myocardium and in the pericardial fluid of aortic stenosis patients, a total of 90 dysregulated proteins were detected. Gene annotation and pathway enrichment analyses, together with discriminant analysis, are compatible with a scenario of increased pro-hypertrophic gene expression and protein synthesis, defective ubiquitinproteasome system activity, proclivity to cell death (potentially fed by complement activity and other extrinsic factors, such as death receptor activators), acute-phase response, immune system activation and fibrosis. Specific validation of some targets through immunoblot techniques and correlation with clinical data pointed to complement C3 β chain, Muscle Ring Finger protein 1 (MuRF1) and the dual-specificity Tyr-phosphorylation regulated kinase 1A (DYRK1A) as potential markers of an incomplete response. In addition, kinase prediction from phosphoproteome data suggests that the modulation of casein kinase 2, the family of IκB kinases, glycogen synthase kinase 3 and DYRK1A may help improve the outcome of patients undergoing valve replacement. Particularly, functional studies with DYRK1A+/- cardiomyocytes show that this kinase may be an important target to treat cardiac dysfunction, provided that mutant cells presented a different response to stretch and reduced ability to develop force (active tension). This study opens many avenues in post-aortic valve replacement reverse remodeling research. In the future, gain-of-function and/or loss-of-function studies with isolated cardiomyocytes or with animal models of aortic bandingdebanding will help disclose the efficacy of targeting the surrogate therapeutic targets. Besides, clinical studies in larger cohorts will bring definitive proof of complement C3, MuRF1 and DYRK1A prognostic value.A substituição da válvula aórtica continua a ser a opção terapêutica de referência para doentes com estenose aórtica e visa a eliminação da sobrecarga de pressão, desencadeando a remodelagem reversa miocárdica. Contudo, apesar do benefício hemodinâmico imediato, nem todos os pacientes apresentam regressão completa da hipertrofia do miocárdio, ficando com maior risco de eventos adversos, como a insuficiência cardíaca. Atualmente, os mecanismos biológicos subjacentes a uma remodelagem reversa incompleta ainda não são claros. Além disso, não dispomos de ferramentas de prognóstico definitivos nem de terapias auxiliares para melhorar a condição dos pacientes indicados para substituição da válvula. Para ajudar a resolver estas lacunas, uma abordagem combinada de (fosfo)proteómica e proteómica para a caracterização, respetivamente, do miocárdio e do líquido pericárdico foi seguida, tomando partido de biópsias e líquidos pericárdicos recolhidos em ambiente cirúrgico. Das mais de 1800 e 750 proteínas identificadas, respetivamente, no miocárdio e no líquido pericárdico dos pacientes com estenose aórtica, um total de 90 proteínas desreguladas foram detetadas. As análises de anotação de genes, de enriquecimento de vias celulares e discriminativa corroboram um cenário de aumento da expressão de genes pro-hipertróficos e de síntese proteica, um sistema ubiquitina-proteassoma ineficiente, uma tendência para morte celular (potencialmente acelerada pela atividade do complemento e por outros fatores extrínsecos que ativam death receptors), com ativação da resposta de fase aguda e do sistema imune, assim como da fibrose. A validação de alguns alvos específicos através de immunoblot e correlação com dados clínicos apontou para a cadeia β do complemento C3, a Muscle Ring Finger protein 1 (MuRF1) e a dual-specificity Tyr-phosphoylation regulated kinase 1A (DYRK1A) como potenciais marcadores de uma resposta incompleta. Por outro lado, a predição de cinases a partir do fosfoproteoma, sugere que a modulação da caseína cinase 2, a família de cinases do IκB, a glicogénio sintase cinase 3 e da DYRK1A pode ajudar a melhorar a condição dos pacientes indicados para intervenção. Em particular, a avaliação funcional de cardiomiócitos DYRK1A+/- mostraram que esta cinase pode ser um alvo importante para tratar a disfunção cardíaca, uma vez que os miócitos mutantes responderam de forma diferente ao estiramento e mostraram uma menor capacidade para desenvolver força (tensão ativa). Este estudo levanta várias hipóteses na investigação da remodelagem reversa. No futuro, estudos de ganho e/ou perda de função realizados em cardiomiócitos isolados ou em modelos animais de banding-debanding da aorta ajudarão a testar a eficácia de modular os potenciais alvos terapêuticos encontrados. Além disso, estudos clínicos em coortes de maior dimensão trarão conclusões definitivas quanto ao valor de prognóstico do complemento C3, MuRF1 e DYRK1A.Programa Doutoral em Biomedicin

    Deciphering Regulation in Escherichia coli: From Genes to Genomes

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    Advances in DNA sequencing have revolutionized our ability to read genomes. However, even in the most well-studied of organisms, the bacterium Escherichia coli, for ≈ 65% of promoters we remain ignorant of their regulation. Until we crack this regulatory Rosetta Stone, efforts to read and write genomes will remain haphazard. We introduce a new method, Reg-Seq, that links massively-parallel reporter assays with mass spectrometry to produce a base pair resolution dissection of more than 100 E. coli promoters in 12 growth conditions. We demonstrate that the method recapitulates known regulatory information. Then, we examine regulatory architectures for more than 80 promoters which previously had no known regulatory information. In many cases, we also identify which transcription factors mediate their regulation. This method clears a path for highly multiplexed investigations of the regulatory genome of model organisms, with the potential of moving to an array of microbes of ecological and medical relevance.</p

    Omics measures of ageing and disease susceptibility

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    While genomics has been a major field of study for decades due to relatively inexpensive genotyping arrays, the recent advancement of technology has also allowed the measure and study of various “omics”. There are now numerous methods and platforms available that allow high throughput and high dimensional quantification of many types of biological molecules. Traditional genomics and transcriptomics are now joined by proteomics, metabolomics, glycomics, lipidomics and epigenomics. I was lucky to have access to a unique resource in the Orkney Complex Disease Study (ORCADES), a cohort of individuals from the Orkney Islands that are extremely deeply annotated. Approximately 1000 individuals in ORCADES have genomics, proteomics, lipidomics, glycomics, metabolomics, epigenomics, clinical risk factors and disease phenotypes, as well as body composition measurements from whole body scans. In addition to these cross-sectional omics and health related measures, these individuals also have linked electronic health records (EHR) available, allowing the assessment of the effect of these omics measures on incident disease over a ~10-year follow up period. In this thesis I use this phenotype rich resource to investigate the relationship between multiple types of omics measures and both ageing and health outcomes. First, I used the ORCADES data to construct measures of biological age (BA). The idea that there is an underlying rate at which the body deteriorates with age that varies between individuals of the same chronological age, this biological age, would be more indicative of health status, functional capacity and risk of age-related diseases than chronological age. Previous models estimating BA (ageing clocks) have predominantly been built using a single type of omics assay and comparison between different omics ageing clocks has been limited. I performed the most exhaustive comparison of different omics ageing clocks yet, with eleven clocks spanning nine different omics assays. I show that different omics clocks overlap in the information they provide about age, that some omics clocks track more generalised ageing while others track specific disease risk factors and that omics ageing clocks are prognostic of incident disease over and above chronological age. Second, I assessed whether individually or in multivariable models, omics measures are associated with health-related risk factors or prognostic of incident disease over 10 years post-assessment. I show that 2,686 single omics biomarkers are associated with 10 risk factors and 44 subsequent incident diseases. I also show that models built using multiple biomarkers from whole body scans, metabolomics, proteomics and clinical risk factors are prognostic of subsequent diabetes mellitus and that clinical risk factors are prognostic of incident hypertensive disorders, obesity, ischaemic heart disease and Framingham risk score. Third, I investigated the genetic architecture of a subset of the proteomics measures available in ORCADES, specifically 184 cardiovascular-related proteins. Combining genome-wide association (GWAS) summary statistics from ORCADES and 17 other cohorts from the SCALLOP Consortium, giving a maximum sample size of 26,494 individuals, I performed 184 genome-wide association meta-analyses (GWAMAs) on the levels of these proteins circulating in plasma. I discovered 592 independent significant loci associated with the levels of at least one protein. I found that between 8-37% of these significant loci colocalise with known expression quantitative trait loci (eQTL). I also find evidence of causal associations between 11 plasma protein levels and disease susceptibility using Mendelian randomisation, highlighting potential candidate drug targets

    Statistical Learning for Gene Expression Biomarker Detection in Neurodegenerative Diseases

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    In this work, statistical learning approaches are used to detect biomarkers for neurodegenerative diseases (NDs). NDs are becoming increasingly prevalent as populations age, making understanding of disease and identification of biomarkers progressively important for facilitating early diagnosis and the screening of individuals for clinical trials. Advancements in gene expression profiling has enabled the exploration of disease biomarkers at an unprecedented scale. The work presented here demonstrates the value of gene expression data in understanding the underlying processes and detection of biomarkers of NDs. The value of novel approaches to previously collected -omics data is shown and it is demonstrated that new therapeutic targets can be identified. Additionally, the importance of meta-analysis to improve power of multiple small studies is demonstrated. The value of blood transcriptomics data is shown in applications to researching NDs to understand underlying processes using network analysis and a novel hub detection method. Finally, after demonstrating the value of blood gene expression data for investigating NDs, a combination of feature selection and classification algorithms were used to identify novel accurate biomarker signatures for the diagnosis and prognosis of Parkinson’s disease (PD) and Alzheimer’s disease (AD). Additionally, the use of feature pools based on previous knowledge of disease and the viability of neural networks in dimensionality reduction and biomarker detection is demonstrated and discussed. In summary, gene expression data is shown to be valuable for the investigation of ND and novel gene biomarker signatures for the diagnosis and prognosis of PD and AD

    Clinico-pathologic and molecular analysis of myxofibrosarcoma of the extremities.

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    AIM The aim of this study was to perform a molecular analysis and to identify class of risk, in terms of local recurrence and survival, in patients affected by myxofibrosarcoma (MFS) of the extremities. MATERIALS AND METHODS A total of 166 patients (>18 years) affected by primary MFS of the extremities were included. Immunohistochemistry expression of MET, RET, p53 and Rb1 was evaluated on tissue MicroArray (TMA) in the whole series. Next generation sequencing (NGS) analysis was performed on 20 samples. Differences in p53 mutations were observed among relapsed and not relapsed cases. Thus, Sanger sequencing was performed on a total of 83 samples. Somatic copy number variations (CNV) of analyzed genes were hypothesized based on allelic frequencies observed. A digital assay of p53 and Met was therefore performed to confirm and characterize them as amplifications or deletions. RESULTS HIC was positive for MET protein in 81.9% and positive for p53 in 19.3%. Point mutations in Tp53 were observed in 25.3%.ses. Point mutations alone were observed in only two cases (2.3%), whereas in 19 (22.9%) they were associated with a gene deletion. Most of the cases (52, 61.9%) presented a Tp53 gene deletion. Cases with overexpression of MET had a higher risk of local recurrence (LR) (p=0.047), Tp53 point mutations increased the risk of LR (p=0.032). CONCLUSIONS We confirm that Tp53 and MET are frequently altered genes in MFS of the extremities. Both CNV and point mutations appear to play important roles in MFS tumorigenesis. Point mutations in Tp53 seem to influence the risk of both local recurrence and survival
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