Experimental-confirmation and functional-annotation of predicted proteins in the chicken genome

<p>Abstract</p> <p>Background</p> <p>The chicken genome was sequenced because of its phylogenetic position as a non-mammalian vertebrate, its use as a biomedical model especially to study embryology and development, its role as a source of human disease organisms and its importance as the major source of animal derived food protein. However, genomic sequence data is, in itself, of limited value; generally it is not equivalent to understanding biological function. The benefit of having a genome sequence is that it provides a basis for functional genomics. However, the sequence data currently available is poorly structurally and functionally annotated and many genes do not have standard nomenclature assigned.</p> <p>Results</p> <p>We analysed eight chicken tissues and improved the chicken genome structural annotation by providing experimental support for the <it>in vivo </it>expression of 7,809 computationally predicted proteins, including 30 chicken proteins that were only electronically predicted or hypothetical translations in human. To improve functional annotation (based on Gene Ontology), we mapped these identified proteins to their human and mouse orthologs and used this orthology to transfer Gene Ontology (GO) functional annotations to the chicken proteins. The 8,213 orthology-based GO annotations that we produced represent an 8% increase in currently available chicken GO annotations. Orthologous chicken products were also assigned standardized nomenclature based on current chicken nomenclature guidelines.</p> <p>Conclusion</p> <p>We demonstrate the utility of high-throughput expression proteomics for rapid experimental structural annotation of a newly sequenced eukaryote genome. These experimentally-supported predicted proteins were further annotated by assigning the proteins with standardized nomenclature and functional annotation. This method is widely applicable to a diverse range of species. Moreover, information from one genome can be used to improve the annotation of other genomes and inform gene prediction algorithms.</p

Ecological Adaptation of Diverse Honey Bee (Apis mellifera) Populations

BACKGROUND: Honey bees are complex eusocial insects that provide a critical contribution to human agricultural food production. Their natural migration has selected for traits that increase fitness within geographical areas, but in parallel their domestication has selected for traits that enhance productivity and survival under local conditions. Elucidating the biochemical mechanisms of these local adaptive processes is a key goal of evolutionary biology. Proteomics provides tools unique among the major 'omics disciplines for identifying the mechanisms employed by an organism in adapting to environmental challenges. RESULTS: Through proteome profiling of adult honey bee midgut from geographically dispersed, domesticated populations combined with multiple parallel statistical treatments, the data presented here suggest some of the major cellular processes involved in adapting to different climates. These findings provide insight into the molecular underpinnings that may confer an advantage to honey bee populations. Significantly, the major energy-producing pathways of the mitochondria, the organelle most closely involved in heat production, were consistently higher in bees that had adapted to colder climates. In opposition, up-regulation of protein metabolism capacity, from biosynthesis to degradation, had been selected for in bees from warmer climates. CONCLUSIONS: Overall, our results present a proteomic interpretation of expression polymorphisms between honey bee ecotypes and provide insight into molecular aspects of local adaptation or selection with consequences for honey bee management and breeding. The implications of our findings extend beyond apiculture as they underscore the need to consider the interdependence of animal populations and their agro-ecological context

Comprehensive Overview of Bottom-up Proteomics using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods to aid the novice and experienced researcher. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this work to serve as a basic resource for new practitioners in the field of shotgun or bottom-up proteomics

From spectrometric data to metabolic networks: an integrated view of cell metabolism

La biologia molecular ha avançat considerablement gràcies a importants progressos com la seqüenciació del ADN o la seva modificació per CRISPR. Tot i això, per entendre el metabolisme requerim estudiar els perfils metabòlics i les seves reaccions metabòliques. L™objectiu d™aquesta tesi és contribuir en aquest estudi del metabolism, el qual unifica dels camps de la proteòmica i la metabolòmica. Tradicionalment, l™anàlisi de dades òmiques es basa en el tractament independent de les diferents variables encara que està profundament establert que els mecanismes moleculars són controlats per la interacció de diferents molècules, i per tant seria més correcte tractar les dades de la mateixa manera. Avui dia, s™han descrit una gran quantitat de vies metabòliques, incluint els enzims responsables de les transformacions dels metabòlits que les formen, aquesta informació s™ha recopilat en bases de dades, que a la vegada poden ser utilitzades per a construir xarxes metabòliques. En aquesta tesi, s™han utilitzat xarxes metabòliques per a desenvolupar un algoritme que prediu metabòlits desregulats basant-se en el perfil d™expressió d™enzims gràcies a proteòmica quantitativa. Per a validar tals prediccions, és possible mesurar l™abundància d™aquests metabòlits, o el seu flux, o sigui la velocitat a la que s™han transformat, utilitzant experiments de marcatge amb isòtops estables, mesures completades mitjançant metabolòmica. Aqui, mostrem els productes del desenvolupament de dos mètodes per a l™anàlisi de dades de metabolòmica per a experiments amb isòtops estables: el primer per a la quantificació dirigida del flux en metabòlits del metabolisme central; i un segon, per la detecció no-dirigida de metabòlits marcats amb isòtops en altres vies metabòliques. Aquests mètodes han sigut provats en diferents estudis on han aportat resultats remarcables, revelant nous mecanismes moleculars en una complicació de la diabetes o en relació al metabolisme del càncer.La biología molecular ha avanzado considerablemente gracias a progresos como la secuenciación de ADN o su modificación por CRISPR. Sin embargo, para entender el metabolismo es indispensable estudiar los perfiles metabólicos y sus reacciones metabólicas. El objetivo de esta tesis es contribuir en el estudio del metabolismo, el cual implica los campos de la proteómica y la metabolómica. Tradicionalmente, el análisis de datos ómicas se basa en el tratamiento independiente de las diferentes variables aunque está profundamente aceptado que los mecanismos moleculares son controlados por la interacción de diferentes moléculas, y por lo tanto sería más correcto tratar los datos de esa manera. Hoy día, se han descrito una gran cantidad de vías metabólicas, incluyendo las enzimas responsables de las transformaciones de los metabolitos que las forman, esta información se ha recopilado en bases de datos, que a su vez pueden ser utilizadas para construir redes metabólicas . En esta tesis, se han utilizado redes metabólicas para desarrollar un algoritmo que predice metabolitos desregulados basándose en el perfil de expresión de enzimas por proteómica cuantitativa. Para validar tales predicciones, es posible medir la abundancia de estos metabolitos, o su flujo, o sea la velocidad a la que se han transformado, utilizando experimentos de marcado con isótopos estables, estas medidas se obtienen por metabolómica. Aquí, mostramos los productos del desarrollo de dos métodos para el análisis de datos de metabolómica para experimentos con isótopos estables: el primero para la cuantificación dirigida del flujo en metabolitos del metabolismo central; y un segundo, para la detección no-dirigida de metabolitos marcados con isótopos en otras vías metabólicas. Estos métodos han sido probados en diferentes estudios donde han aportado resultados interesantes, revelando nuevos mecanismos moleculares en una complicación de la diabetes o en relación al metabolismo del cáncer.Understanding the molecular basis of life has been in the spotlight of biochemistry research for more than a century already. Molecular biology has taken medicine forward thanks to technological breakthroughs like DNA sequencing and CRISPR editing. However, in order to understand metabolism we must rely on the study of metabolite profiles and metabolic reactions. The purpose of this thesis to contribute to this area, which unites the fields of proteomics and metabolomics. Traditionally, omics data analysis treats variables independently even if it is strongly settled that molecular mechanisms involve the interaction of diverse pathways, therefore data should be analyzed correspondingly. A vast amount of metabolic pathways have been described, together with enzymes that are responsible for metabolite transformations, this information has been assembled in databases that, in turn, can be used to build metabolic networks. In here, we use metabolic networks to predict metabolite dysregulation based on quantitative proteomics profiles. To validate the predictions, it is possible to measure the abundance of metabolites or their flux, namely the rate at which they are transformed, using stable isotope labelling experiments, both measurements can be performed by metabolomics. In this thesis, two different metabolomics-based stable isotope labelling approaches have been developed, one for the study of central carbon metabolites and one for the unbiased detection of deregulated fluxes in other metabolic pathways. These approaches have been tested on different datasets and have proven valuable to obtain remarkable results, unraveling molecular mechanisms in diabetes complications or novel metabolic hallmarks of cancer

TOMATO FLESHY FRUIT QUALITY IMPROVEMENT: CHARACTERIZATION OF GENES AND GENOMIC REGIONS ASSOCIATED TO SPECIALIZED METABOLISM IN TOMATO FLESHY FRUIT

Tesis por compendio[EN] Until recently, the genetic improvement of tomato (Solanum lycopersicum) was focused in agronomic traits, such as yield and biotic or abiotic stresses; therefore the interest in tomato fruit quality is relatively new. The tomato fruit surface can be considered both an agronomic trait as well as a quality trait, because it has an effect on consumer impression in terms of color and glossiness but also it underlies the resistance/sensitivity to cracking or water loss with consequences on fruit manipulation (e.g. transport and processing). The cuticle is deposited over the cell wall surrounding the epidermal cells and it is the first barrier in the plant-environment interface. The cuticle composition includes two main groups of metabolites: cuticular waxes and cutin. Other metabolites can be founded into the cuticle matrix, as triterpenoids and flavonoids. Those minor cuticular components are involved in the correct functionality of the cuticle. Understanding cuticle biosynthesis and genetic regulation requires the development of fast and simple analytical methodologies to study those specialized metabolites using large populations (e.g. mutant collections or introgression lines), together with the identification of genes and genomic regions responsible of their production. This thesis aims to contribute to our understanding of the molecular programs underlying tomato fruit quality by providing: i) a general protocol to profile cuticular waxes in different species, including tomato; ii) a QTL map for cuticular composition (i.e. cuticular waxes and cutin monomers) using the Solanum pennellii introgression line population; iii) a detailed protocol of the reverse genetic tool so-called Fruit-VIGS to assist in the study of gene function in tomato fruit; and iv) a thorough characterization of the first null allele for the transcription factor SlMYB12 (i.e. Slmyb12-pf) in tomato fruit which provides new insights into the regulation of the flavonoid biosynthetic pathway in the fruit peel by high resolution mass spectrometry and RNA-Seq approaches.[ES] Hasta hace poco, la mejora genética del cultivo del tomate (Solanum lycopersicum) había estado centrada principalmente en caracteres agronómicos, como la productividad y la resistencia a estreses, tanto bióticos como abióticos. Así, el interés en la calidad del fruto de tomate es relativamente reciente. La superficie del fruto del tomate puede considerarse tanto un carácter agronómico como de calidad, pues influye en la primera impresión de los consumidores en términos de color y brillo, así como también en los procesos de resistencia o sensibilidad a la rotura ('cracking') o a la pérdida de agua. Estos factores determinan el aspecto del fruto y condicionan atributos relacionados con su manipulación (transporte y procesado). La cutícula se deposita sobre la pared celular de las células epidérmicas y es la primera barrera que interacciona con el ambiente. Está constituida por dos grandes tipos de metabolitos: las ceras cuticulares y la cutina. Otros metabolitos pueden aparecer embebidos en la matriz cuticular, como es el caso de los triterpenoides y los flavonoides. Estos metabolitos contribuyen a la correcta funcionalidad de la cutícula. La compresión de la biosíntesis y regulación génica de la cutícula requiere del desarrollo de metodologías de análisis sencillas y rápidas para el estudio de estos metabolitos especializados en grandes poblaciones (colecciones de mutantes o líneas de introgresión), así como para la identificación de genes y regiones génicas responsables de la producción y acumulación de dichos compuestos, pudiendo ser muy útiles para implementar programas de mejora de la calidad del tomate. El objetivo de esta tesis es contribuir a la comprensión sobre los programas moleculares subyacentes a la calidad del fruto de tomate, proporcionando: i) un protocolo general de análisis del contenido de ceras cuticulares en diferentes especies, incluyendo el tomate; ii) un mapa de QTL de la composición cuticular (incluyendo ceras y monómeros de cutina) obtenido con la población de líneas de introgresión de Solanum pennellii; iii) un protocolo detallado de uso de la herramienta de genética reversa Fruit-VIGS con el que realizar estudios de funciones génicas en fruto de tomate; y iv) una minuciosa caracterización de un nuevo alelo nulo del factor de transcripción SlMYB12 (Slmyb12-pf) en fruto de tomate, proporcionando nueva información sobre la regulación de la ruta biosintética de los flavonoides en la piel del fruto, utilizando espectrometría de masas de alta resolución y de nuevas tecnologías de secuenciación.[CA] Fins fa poc de temps, la millora genètica de la tomata (Solanum lycopersicum) anava dirigida fonamentalment als caràcters de tipus agronòmic, com la productivitat i la tolerància a estressos biòtics o abiòtics, resultant que l'interés per la qualitat dels fruits és relativament nou. La superfície de la tomata pot ser considerada tant com un caràcter agronòmic com un de qualitat, ja que és l'aspecte de la superfície del fruit el que confereix al consumidor la primera impressió de color, brillantor, però és també la pell del fruit la responsable de la diferent susceptibilitat del fruit a desenvolupar clevills o que el fruit sofrisca més o menys pèrdues d'aigua, tot tenint importants conseqüències en la manipulació (i.e. transport i processament del fruit). La cutícula és dipositada per sobre de la paret cel·lular que envolta la capa de cèl·lules epidèrmiques i constitueix la primera barrera en la interfase planta-medi ambient. La composició de la cutícula presenta dos grups principals de metabòlits: les ceres i la cutina. També es poden trobar altres metabòlits els triterpenoids i el flavonoids. Aquests darrers components cuticulars menors són implicats en el correcte funcionament de la cutícula. Per tal de comprendre la biosíntesi i la regulació genètica de la cutícula cal desenvolupar tecnologies analítiques senzilles i rapides que permeten estudiar aquests metabòlits especialitzats en poblacions grans de plantes (i.e. Col·leccions de mutants o de línies d'introgressió), a més de la identificació de gens i regions genòmiques que són responsables de la seua producció. Aquesta tesi té com a objectiu contribuir a millorar la nostra comprensió dels programes moleculars que afecten determinats aspectes de la qualitat de la tomata mitjançant els següents objectius: i) proporcionar un protocol general per obtenir perfils de ceres cuticulars en diferents espècies, inclosa la tomata; ii) obtenir un mapa de QTL per a la composició cuticular (i.e. ceres cuticulars i monòmers de cutina) mitjançant la utilització de la població de línies d'introgressió de Solanum pennelli; iii) descriure amb detall el protocol d'una eina de revers genètica denominada Fruit-VIGS que resulta molt adequada per estudiar funció gènica a la tomata; y iv) fer una caracterització exhaustiva del primer al·lel nul del factor de transcripció SlMYB12 (ie. Slmyb12-pf) en tomata la qual proporciona informació nova sobre la regulació de la ruta de biosíntesi de flavonoides en la pell de la tomata mitjançant espectrometria de masses d'alta resolució i RNAseq.Fernández Moreno, JP. (2015). TOMATO FLESHY FRUIT QUALITY IMPROVEMENT: CHARACTERIZATION OF GENES AND GENOMIC REGIONS ASSOCIATED TO SPECIALIZED METABOLISM IN TOMATO FLESHY FRUIT [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/55505TESISPremios Extraordinarios de tesis doctoralesCompendi

Development of computational methods for metabolic network analysis based on metabolomics data

The baker';s yeast, Saccharomyces cerevisiae, is a simple eukaryotic organism with approximately 6000 genes. Saccharomyces cerevisiae is an ideal model organism for large-scale functional studies and provides a system in which genes can be systematically inactivated by way of gene-knockout methods. A substantial fraction of the 6000 genes in Saccharomyces cerevisiae encode proteins for which currently we do not know any confirmed or putative function. Prediction of the functional role of these proteins is a challenging problem in systems biology, especially as many of these genes have no overt phenotypes. In our study, we aim at a better understanding of the underlying functional relationships between genes working across diverse metabolic pathways using intracellular metabolite profiling studies. We applied bioinformatics methods and statistical analysis techniques in combination with metabolic profiling to understand the function and the regulatory mechanisms of specific genes involved in central carbon metabolism and amino acid biosynthesis. The experimental work was carried out by the group of Prof. Elmar Heinzle (Biochemical Engineering, Saarland University), our collaboration partner. 13C stable isotope substrates can be used as tracers to generate detailed metabolic profiles of gene knockouts. Detailed and quantitative information on the physiological cellular states is measured by 13C -metabolic profiling of cultures grown on novel high throughput oxygen sensor microtiter plates. In this dissertation, we worked towards developing systematic approaches for study of Saccharomyces cerevisiae genes of unknown function based on the metabolic profiles of knockout mutants under varied environmental conditions. In the first step, we have developed a software tool called CalSpec for automation of Gas Chromatography Mass Spectrometry data acquisition and analysis routine, as this is a bottleneck in the metabolic profiling studies. In the next step, we worked on large scale statistical analysis of metabolic profiling data. We applied various algorithms for finding closely related mutants which show similar metabolic profiles. According to our hypothesis, similarity in the metabolic profiles can be used to find functionally linked genes. Saccharomyces cerevisiae is known to be robust to majority of genetic perturbations. In these cases where the mutants show no overt 4 phenotypes, we developed a sensitive outlier detection method to detect those subsets of metabolic profile features which are most differentiating (outliers) for all mutants. The second part of this dissertation involves developing computational tools for metabolic pathway analysis on the basis of genome scale metabolic models, as well as integration of various newly emerging experimental techniques. In recent years, genome scale metabolic models have been and are continuing to be assembled for various organisms. In the year 2003, first comprehensive genome scale metabolic model for yeast became publicly available. With the emergence of system biology area of research, diverse computational approaches have been developed. In this work, we developed a new webserver called MetaModel, for analysis of genome scale metabolic networks of eukaryotic organisms

Novel concepts for lipid identification from shotgun mass spectra using a customized query language

Lipids are the main component of semipermeable cell membranes and linked to several important physiological processes. Shotgun lipidomics relies on the direct infusion of total lipid extracts from cells, tissues or organisms into the mass spectrometer and is a powerful tool to elucidate their molecular composition. Despite the technical advances in modern mass spectrometry the currently available software underperforms in several aspects of the lipidomics pipeline. This thesis addresses these issues by presenting a new concept for lipid identification using a customized query language for mass spectra in combination with efficient spectra alignment algorithms which are implemented in the open source kit “LipidXplorer”