Plant regeneration from an endangered valuable cork oak tree by somatic embryogenesis.

Among the several applications of in vitro tissue culture techniques, the conservation of plant germplasm is one of the most widely used. The cork oak is one of the principal tree species in the Western Mediterranean región. Within this área, the Balearic Islands are considered to be a glacial refuge, and therefore a reservoir of genetic resources. A singular tree has been found in the small Minorca Island population. The haplotype of this tree is of Tyrrhenian origin, showing a past link between Minorca and Sardinia. Moreover, this tree do not bear a deletion within an ITS from ribosimic nuclear DNA, which is fairly common in many populations of this species, and indicates that ir may be the descendant of a very ancient population. This tree is currently in a precarious condition, and it has not produced acorns in the last years. Hence there is a clear need of vegetative propagation to conserve this genotype. We have previously developed methods to clone adult cork oak tres by somatic embryogenesis, and therefore the aim of the present work was to clone this singular tree. There braches from the corwn were collected in November 2004, and methods previously described were carried out. By February 2005 somatic embryogenesis was obtained from leaves of the tree with percentages on induction ranging from 17 to 54% depending on the branch, which may show a novel source of variation that requires further study. Spontaneously matured somatic embryos germinated at 46% in average, and the first somatic seedlings from the Alfavaret's cork oak tree were obtained. Therefore, this study shows one of the most relevant applications of somatic embryogenesis: the plant regeneration of valuable genotypes for the in situ and ex situ conservation of forest genetic resources.

Improved walnut mass micropropagation through the combined use of phloroglucinol and FeEDDHA

Despite the socioeconomic importance of walnut trees, poor rooting and recalcitrance to in vitro culture have hampered the establishment of high-yield clonal plantations. To improve walnut micropropagation, we introduced several modifications to current methods and evaluated the effects on microshoot performance and acclimatization. Nine selected genotypes (13-year-old trees) of the commercial hybrid Juglans major 209 x J. regia were cultured in vitro on DKW-C medium supplemented with 4.4 µM BA and 50 µM IBA. A protocol was developed that relies on the use of 0.40 mM phloroglucinol during shoot multiplication, 0.20 mM previous root induction, and 6.81 mg/L Fe3+ (FeEDDHA). Moreover, the addition of 83.2 µM glucose during the root expression phase significantly improved plant survival during acclimatization. Phloroglucinol promoted microshoot elongation but inhibited rooting, especially at concentrations above 0.40 mM. Replacing FeEDTA by FeEDDHA diminished chlorotic symptoms and improved rooting, with up to 90% microshoots developing viable roots. Likewise, glucose was more efficient than sucrose or fructose in promoting plant survival. At the proposed working concentrations, neither glucose nor FeEDDHA caused any noticeable deleterious effect on walnut micropropagation. Microscopic analysis revealed the physical continuity between adventitious roots and stem pericycles. Analysis of leaf genomic DNA with eight polymorphic microsatellite markers was supportive of the clonal fidelity and genetic stability of the micropropagated material. Successful clonal plantations (over 5,800 ramets) have been established by applying this protocol.

Diseño y evaluación de un procedimiento on-line para la biorremediación de aguas radiactivas en centrales nucleares

Recientemente se ha demostrado la existencia de microorganismos en las piscinas de almacenamiento de combustible nuclear gastado en las centrales nucleares utilizando técnicas convencionales de cultivo en el laboratorio. Estudios posteriores han puesto de manifiesto que los microorganismos presentes eran capaces de colonizar las paredes de acero inoxidable de las piscinas formando biopelículas. Adicionalmente se ha observado la capacidad de estas biopelículas de retener radionúclidos, lo que hace pensar en la posibilidad de utilizarlas en la descontaminación de las aguas radiactivas de las piscinas. En la presente tesis se plantea conocer más profundamente la biodiversidad microbiana de las biopelículas utilizando técnicas de biología molecular como la clonación, además de desarrollar un sistema de descontaminación a escala piloto con el objetivo de valorar si el proceso podría resultar escalable a nivel industrial. Para ello se diseñaron y fabricaron dos biorreactores en acero inoxidable compatibles con las condiciones específicas de seguridad sísmica y protección frente a la radiación en la zona controlada de una central nuclear. Los biorreactores se instalaron en la Central Nuclear de Cofrentes (Valencia) en las proximidades de las piscinas de almacenamiento de combustible nuclear gastado y precediendo a las resinas de intercambio iónico, de forma que reciben el agua de las piscinas permitiendo el análisis in situ de la radiación eliminada del agua de las mismas. Se conectó una lámpara de luz ultravioleta a uno de los biorreactores para poder comparar el desarrollo de bipelículas y la retención de radiactividad en ambas condiciones. En estos biorreactores se introdujeron ovillos de acero inoxidable y de titanio que se extrajeron a diversos tiempos, hasta 635 días para los ovillos de acero inoxidable y hasta 309 días para los ovillos de titanio. Se analizaron las biopelículas desarrolladas sobre los ovillos por microscopía electrónica de barrido y por microscopía de epifluorescencia. Se extrajo el ADN de las biopelículas y, tras su clonación, se identificaron los microorganismos por técnicas independientes de cultivo. Asimismo se determinó por espectrometría gamma la capacidad de las biopelículas para retener radionúclidos. Los microorganismos radiorresistentes identificados pertenecen a los grupos filogenéticos Alpha-proteobacteria, Gamma-proteobacteria, Actinobacteria, Deinococcus-Thermus y Bacteroidetes. Las secuencias de estos microorganismos se han depositado en el GenBank con los números de acceso KR817260-KR817405. Se ha observado una distribución porcentual ligeramente diferente en relación con el tipo de biorreactor. Las biopelículas han retenido fundamentalmente radionúclidos de activación. La suma de Co-60 y Mn-54 ha llegado en ocasiones al 97%. Otros radionúclidos retenidos han sido Cr-51, Co-58, Fe-59, Zn-65 y Zr-95. Se sugiere un mecanismo del proceso de retención de radionúclidos relacionado con el tiempo de formación y desaparición de las biopelículas. Se ha valorado que el proceso escalable puede ser económicamente rentable. ABSTRACT The existence of microorganisms in spent nuclear fuel pools has been demonstrated recently in nuclear power plants by using conventional microbial techniques. Subsequent studies have revealed that those microorganisms were able to colonize the stainless steel pool walls forming biofilms. Additionally, it has been observed the ability of these biofilms to retain radionuclides, which suggests the possibility of using them for radioactive water decontamination purposes. This thesis presents deeper knowledge of microbial biofilms biodiversity by using molecular biology techniques such as cloning, and develops a decontamination system on a pilot scale, in order to assess whether the process could be scalable to an industrial level. Aiming to demonstrate this was feasible, two stainless steel bioreactors were designed and manufactured, both were compatible with seismic and radiation protection standards in the controlled zone of a nuclear plant. These bioreactors were installed in the Cofrentes Nuclear Power Plant (Valencia) next to the spent nuclear fuel pools and preceding (upstream) ion exchange resins. This configuration allowed the bioreactors to receive water directly from the pools allowing in situ analysis of radiation removal. One ultraviolet lamp was connected to one of the bioreactors to compare biofilms development and radioactivity retention in both conditions. Stainless steel and titanium balls were introduced into these bioreactors and were removed after different time periods, up to 635 days for stainless steel balls and up to 309 days for titanium. Biofilms developed on the balls were analyzed by scanning electron microscopy and epifluorescence microscopy. DNA was extracted from the biofilms, was cloned and then the microorganisms were identified by independent culture techniques. Biofilms ability to retain radionuclides was also determined by gamma spectrometry. The identified radioresistant organisms belong to the phylogenetic groups Alphaproteobacteria, Gamma-proteobacteria, Actinobacteria, Deinococcus-Thermus and Bacteroidetes. The sequences of these microorganisms have been deposited in GenBank (access numbers KR817260-KR817405). A different distribution of microorganisms was observed in relation to the type of bioreactor. Biofilms have essentially retained activation radionuclides. Sometimes the sum of Co-60 and Mn-54 reached 97%. Cr-51, Co-58, Fe-59, Zn-65 and Zr-95 have also been retained. A radionuclide retention process mechanism related to biofilms formation and disappearance time is suggested. It has been assessed that the scalable process can be economically profitable.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.