Geometric diagnostics of complex patterns: Spiral defect chaos

Motivated by the observation of spiral patterns in a wide range of physical, chemical, and biological systems, we present an automated approach that aims at characterizing quantitatively spiral-like elements in complex stripelike patterns. The approach provides the location of the spiral tip and the size of the spiral arms in terms of their arc length and their winding number. In addition, it yields the number of pattern components (Betti number of order 1), as well as their size and certain aspects of their shape. We apply the method to spiral defect chaos in thermally driven Rayleigh- Bénard convection and find that the arc length of spirals decreases monotonically with decreasing Prandtl number of the fluid and increasing heating. By contrast, the winding number of the spirals is nonmonotonic in the heating. The distribution function for the number of spirals is significantly narrower than a Poisson distribution. The distribution function for the winding number shows approximately an exponential decay. It depends only weakly on the heating, but strongly on the Prandtl number. Large spirals arise only for larger Prandtl numbers. In this regime the joint distribution for the spiral length and the winding number exhibits a three-peak structure, indicating the dominance of Archimedean spirals of opposite sign and relatively straight sections. For small Prandtl numbers the distribution function reveals a large number of small compact pattern components.

Evaluation of the bioaccumulation kinetics of gold nanorods in vital mammalian organs by mean of TXRF spectrometry

This work presents the first application of total-reflection X-ray fluorescence (TXRF) spectrometry, a new and powerful alternative analytical method, to evaluation of the bioaccumulation kinetics of gold nanorods (GNRs) in various tissues upon intravenous administration in mice. The analytical parameters for developed methodology by TXRF were evaluated by means of the parallel analysis of bovine liver certified reference material samples (BCR-185R) doped with 10 μg/g gold. The average values (n = 5) achieved for gold measurements in lyophilized tissue weight were as follows: recovery 99.7%, expanded uncertainty (k = 2) 7%, repeatability 1.7%, detection limit 112 ng/g, and quantification limit 370 ng/g. The GNR bioaccumulation kinetics was analyzed in several vital mammalian organs such as liver, spleen, brain, and lung at different times. Additionally, urine samples were analyzed to study the kinetics of elimination of the GNRs by this excretion route. The main achievement was clearly differentiating two kinds of behaviors. GNRs were quickly bioaccumulated by highly vascular filtration organs such as liver and spleen, while GNRs do not show a bioaccumulation rates in brain and lung for the period of time investigated. In parallel, urine also shows a lack of GNR accumulation. TXRF has proven to be a powerful, versatile, and precise analytical technique for the evaluation of GNRs content in biological systems and, in a more general way, for any kind of metallic nanoparticles.

Rapid prototyping of multi-scale biomedical microdevices by combining additive manufacturing technologies

The possibility of designing and manufacturing biomedical microdevices with multiple length-scale geometries can help to promote special interactions both with their environment and with surrounding biological systems. These interactions aim to enhance biocompatibility and overall performance by using biomimetic approaches. In this paper, we present a design and manufacturing procedure for obtaining multi-scale biomedical microsystems based on the combination of two additive manufacturing processes: a conventional laser writer to manufacture the overall device structure, and a direct-laser writer based on two-photon polymerization to yield finer details. The process excels for its versatility, accuracy and manufacturing speed and allows for the manufacture of microsystems and implants with overall sizes up to several millimeters and with details down to sub-micrometric structures. As an application example we have focused on manufacturing a biomedical microsystem to analyze the impact of microtextured surfaces on cell motility. This process yielded a relevant increase in precision and manufacturing speed when compared with more conventional rapid prototyping procedures.

Diseño y desarrollo de un modelo booleano probabilístico de regulación genética en el simulador de colonias bacterianas GRO

Resulta interesante comprender como microorganismos sencillos como la bacteria Escherichia coli poseen mecanismos no tan simples para responder al entorno en el que está gestionada por complicadas redes de regulación formadas por genes y proteínas, donde cada elemento de la red genética debe tomar parte en armonía, en el momento justo y la cantidad adecuada para dar lugar a la respuesta celular apropiada. La biología sintética es un nuevo área de la biología y la tecnología que fusiona la biolog ía molecular, la ingeniería genética y las herramientas computacionales, para crear sistemas biológicos con funcionalidades novedosas. Los sistemas creados sintéticamente son ya una realidad, y cada vez se acumulan más trabajos alrededor del mundo que muestran su factibilidad. En este campo no solo se hacen pequeñas modificaciones en la información genética, sino que también se diseñan, manipulan e introducen circuitos genéticos a los organismos. Actualmente, se hace un gran esfuerzo para construir circuitos genéticos formados por numerosos genes y caracterizar la interacción de los mismos con otras moléculas, su regulaci ón, expresión y funcionalidad en diferentes organismos. La mayoría de los proyectos de biología sintética que se han desarrollado hasta ahora, se basan en el conocimiento actual del funcionamiento de los organismos vivos. Sin embargo, la información es numerosa y creciente, por lo que se requiere de herramientas computacionales y matem áticas para integrar y hacer manejable esta gran cantidad de información. El simulador de colonias bacterianas GRO posee la capacidad de representar las dinámicas más simples del comportamiento celular, tales como crecimiento, división y comunicación intercelular mediante conjugación, pero carece de la capacidad de simular el comportamiento de la colonia en presencia de un circuito genético. Para ello, se ha creado un nuevo módulo de regulación genética que maneja las interaciones entre genes y proteínas de cada célula ejecutando respuestas celulares específicas. Dado que en la mayoría de los experimentos intervienen colonias del orden de 105 individuos, es necesario un módulo de regulación genética simplificado que permita representar de la forma más precisa posible este proceso en colonias de tales magnitudes. El módulo genético integrado en GRO se basa en una red booleana, en la que un gen puede transitar entre dos estados, on (expresado) o off (reprimido), y cuya transición viene dada por una serie de reglas lógicas.---ABSTRACT---It is interesting to understand how simple organisms such as Escherichia coli do not have simple mechanisms to respond to the environment in which they find themselves. This response is managed by complicated regulatory networks formed by genes and proteins, where each element of the genetic network should take part in harmony, at the right time and with the right amount to give rise to the appropriate cellular response. Synthetic biology is a new area of biology and technology that combines molecular biology, genetic engineering and computational tools to create biological systems with novel features. The synthetically created systems are already a reality, and increasingly accumulate work around the world showing their feasibility. In this field not only minor changes are made in the genetic information but also genetic circuits designed, manipulated and introduced into the organisms. Currently, it takes great effort to build genetic circuits formed by numerous genes and characterize their interaction with other molecules, their regulation, their expression and their function in different organisms. Most synthetic biology projects that have been developed so far are based on the current knowledge of the functioning of living organisms. However, there is a lot of information and it keeps accumulating, so it requires computational and mathematical tools to integrate and manage this wealth of information. The bacterial colonies simulator, GRO, has the ability to represent the simplest dynamics of cell behavior, such as growth, division and intercellular communication by conjugation, but lacks the ability to simulate the behavior of the colony in the presence of a genetic circuit. To this end, a new genetic regulation module that handles interactions between genes and proteins for each cell running specific cellular responses has been created. Since most experiments involve colonies of about 105 individuals, a simplified genetic module which represent cell dynamics as accurately and simply as possible is needed. The integrated genetic GRO module is based on a Boolean network, in which a gene can be in either of two states, on (expressed) or off (repressed), and whose transition is given by a set of logical rules.

Algoritmos genéticos en control activo de ruido

Este proyecto se centra en la implementación de un sistema de control activo de ruido mediante algoritmos genéticos. Para ello, se ha tenido en cuenta el tipo de ruido que se quiere cancelar y el diseño del controlador, parte fundamental del sistema de control. El control activo de ruido sólo es eficaz a bajas frecuencias, hasta los 250 Hz, justo para las cuales los elementos pasivos pierden efectividad, y en zonas o recintos de pequeñas dimensiones y conductos. El controlador ha de ser capaz de seguir todas las posibles variaciones del campo acústico que puedan producirse (variaciones de fase, de frecuencia, de amplitud, de funciones de transferencia electro-acústicas, etc.). Su funcionamiento está basado en algoritmos FIR e IIR adaptativos. La elección de un tipo de filtro u otro depende de características tales como linealidad, causalidad y número de coeficientes. Para que la función de transferencia del controlador siga las variaciones que surgen en el entorno acústico de cancelación, tiene que ir variando el valor de los coeficientes del filtro mediante un algoritmo adaptativo. En este proyecto se emplea como algoritmo adaptativo un algoritmo genético, basado en la selección biológica, es decir, simulando el comportamiento evolutivo de los sistemas biológicos. Las simulaciones se han realizado con dos tipos de señales: ruido de carácter aleatorio (banda ancha) y ruido periódico (banda estrecha). En la parte final del proyecto se muestran los resultados obtenidos y las conclusiones al respecto. Summary. This project is focused on the implementation of an active noise control system using genetic algorithms. For that, it has been taken into account the noise type wanted to be canceled and the controller design, a key part of the control system. The active noise control is only effective at low frequencies, up to 250 Hz, for which the passive elements lose effectiveness, and in small areas or enclosures and ducts. The controller must be able to follow all the possible variations of the acoustic field that might be produced (phase, frequency, amplitude, electro-acoustic transfer functions, etc.). It is based on adaptive FIR and IIR algorithms. The choice of a kind of filter or another depends on characteristics like linearity, causality and number of coefficients. Moreover, the transfer function of the controller has to be changing filter coefficients value thought an adaptive algorithm. In this project a genetic algorithm is used as adaptive algorithm, based on biological selection, simulating the evolutionary behavior of biological systems. The simulations have been implemented with two signal types: random noise (broadband) and periodic noise (narrowband). In the final part of the project the results and conclusions are shown.

Diseño e implementación de un módulo de crecimiento bacteriano dependiente de nutrientes en el simulador GRO

Hace no más de una década que empezó a escucharse el término biología sintética. Este área de estudio emergente consiste en la ingeniería y programación de sistemas biológicos, tratando la biología como una tecnología programable a la que aplican los principios y metodologías de la ingeniería, con el fin de crear nuevas funcionalidades genéticas desde cero, procurando asÍ algún beneficio como por ejemplo, programar células bacterianas para producir biocombustibles. Sin embargo, para la creación de dichas funcionalidades es necesario conocer bien al organismo sobre el que se van a implantar. Por este motivo, los biólogos sintéticos emplean bacterias en sus estudios, ya que es la forma de vida más simple, está presente en prácticamente todos los nichos ecológicos, desempeña algunas de las funcionalidades vitales para los humanos y lo mas importante, se conoce prácticamente todo su material genético. Los experimentos son costosos en tiempo y dinero, siendo necesaria la ayuda de herramientas que faciliten esta labor, los simuladores. En PLASWIRES, proyecto europeo de biología sintética en el que se engloba este este trabajo, el simulador empleado es GRO. Sin embargo, en GRO el crecimiento de las bacterias ocurre de forma exponencial y sin restricciones, generando comportamientos poco realistas. Por ello, se ha considerado relevante en biología sintética, y en el simulador GRO en particular, disponer de un modelo de crecimiento bacteriano dependiente de los nutrientes. El desarrollo de este trabajo se centra en la implementación de un módulo de consumo de nutrientes en colonias de bacterias simuladas con GRO, introduciendo así la limitación de nutrientes y evitanto que las bacterias crezcan exponencialmente. Se han introducido nutrientes en el medio y la capacidad de consumirlos, con el objetivo de obtener un crecimiento ajustado al que ocurre en la naturaleza. Además, se ha desarrollado en GRO una nueva función de adquisición de volumen, que condiciona el volumen adquirido por cada bacteria en función de los nutrientes. La implentación de las dos aportaciones presentadas ha supuesto la adición de funcionalidad extra a GRO, convirtiéndolo en el único simulador de bacterias que tiene en cuenta el crecimiento bacteriano dependiente de nutrientes.---ABSTRACT---It has been in this last decade that the synthetic biology term began to be heard. This emergent area of study consists in the engineering and programming of biological systems, dealing with biology as a programable technology in which the engineering principles and methodologies are applied in order to create novel genetic functinalities from scratch, obtaining some advatages such as programmed bacteria in order to produce biofuels. However, to create this functionalities, it is necessary to know well the organisms in which they are going to be implemented. For this reason, synthetic biology researchers use bacteria, because it is the simplest life form, it can be found in almost all the ecological niche, it does some vital function to humans and, most important, almost all of its genetic information is known. Experiments are expensive in time and money, making it necessary to use tools to ease this task: the simulators. In PLASWIRES, the european synthetic biology project in which this work is included, the simulator used is GRO. However, the bacterial growth in GRO is exponential and it does not have restrictions, generating unrealistic behaviours. Therefore, it has been considered relevant in synthetic biology, and in a particular way in GRO, to provide a bacterial growth model dependent on nutrient. This work focuses on the implementation of a nutrient consumption module in bacteria colonies simulated with GRO, introducing a nuntrient limitation and avoiding the bacteria exponential growth. The module introduces nutrients and the capacity for bacteria to consume them, aiming to obtain realistic growth simulations that fit the observations made in nature. Moreover, an adquisition volumen function has been developed in GRO, determining the volumen depending on nutrients. This two contributions make GRO the only bacteria simulator that computes growth depending on nutrients

Análisis de la actividad neuronal y cerebral mediante técnicas de redes complejas

El cerebro humano es probablemente uno de los sistemas más complejos a los que nos enfrentamos en la actualidad, si bien es también uno de los más fascinantes. Sin embargo, la compresión de cómo el cerebro organiza su actividad para llevar a cabo tareas complejas es un problema plagado de restos y obstáculos. En sus inicios la neuroimagen y la electrofisiología tenían como objetivo la identificación de regiones asociadas a activaciones relacionadas con tareas especificas, o con patrones locales que variaban en el tiempo dada cierta actividad. Sin embargo, actualmente existe un consenso acerca de que la actividad cerebral tiene un carácter temporal multiescala y espacialmente extendido, lo que lleva a considerar el cerebro como una gran red de áreas cerebrales coordinadas, cuyas conexiones funcionales son continuamente creadas y destruidas. Hasta hace poco, el énfasis de los estudios de la actividad cerebral funcional se han centrado en la identidad de los nodos particulares que forman estas redes, y en la caracterización de métricas de conectividad entre ellos: la hipótesis subyacente es que cada nodo, que es una representación mas bien aproximada de una región cerebral dada, ofrece a una única contribución al total de la red. Por tanto, la neuroimagen funcional integra los dos ingredientes básicos de la neuropsicología: la localización de la función cognitiva en módulos cerebrales especializados y el rol de las fibras de conexión en la integración de dichos módulos. Sin embargo, recientemente, la estructura y la función cerebral han empezado a ser investigadas mediante la Ciencia de la Redes, una interpretación mecánico-estadística de una antigua rama de las matemáticas: La teoría de grafos. La Ciencia de las Redes permite dotar a las redes funcionales de una gran cantidad de propiedades cuantitativas (robustez, centralidad, eficiencia, ...), y así enriquecer el conjunto de elementos que describen objetivamente la estructura y la función cerebral a disposición de los neurocientíficos. La conexión entre la Ciencia de las Redes y la Neurociencia ha aportado nuevos puntos de vista en la comprensión de la intrincada anatomía del cerebro, y de cómo las patrones de actividad cerebral se pueden sincronizar para generar las denominadas redes funcionales cerebrales, el principal objeto de estudio de esta Tesis Doctoral. Dentro de este contexto, la complejidad emerge como el puente entre las propiedades topológicas y dinámicas de los sistemas biológicos y, específicamente, en la relación entre la organización y la dinámica de las redes funcionales cerebrales. Esta Tesis Doctoral es, en términos generales, un estudio de cómo la actividad cerebral puede ser entendida como el resultado de una red de un sistema dinámico íntimamente relacionado con los procesos que ocurren en el cerebro. Con este fin, he realizado cinco estudios que tienen en cuenta ambos aspectos de dichas redes funcionales: el topológico y el dinámico. De esta manera, la Tesis está dividida en tres grandes partes: Introducción, Resultados y Discusión. En la primera parte, que comprende los Capítulos 1, 2 y 3, se hace un resumen de los conceptos más importantes de la Ciencia de las Redes relacionados al análisis de imágenes cerebrales. Concretamente, el Capitulo 1 está dedicado a introducir al lector en el mundo de la complejidad, en especial, a la complejidad topológica y dinámica de sistemas acoplados en red. El Capítulo 2 tiene como objetivo desarrollar los fundamentos biológicos, estructurales y funcionales del cerebro, cuando éste es interpretado como una red compleja. En el Capítulo 3, se resumen los objetivos esenciales y tareas que serán desarrolladas a lo largo de la segunda parte de la Tesis. La segunda parte es el núcleo de la Tesis, ya que contiene los resultados obtenidos a lo largo de los últimos cuatro años. Esta parte está dividida en cinco Capítulos, que contienen una versión detallada de las publicaciones llevadas a cabo durante esta Tesis. El Capítulo 4 está relacionado con la topología de las redes funcionales y, específicamente, con la detección y cuantificación de los nodos mas importantes: aquellos denominados “hubs” de la red. En el Capítulo 5 se muestra como las redes funcionales cerebrales pueden ser vistas no como una única red, sino más bien como una red-de-redes donde sus componentes tienen que coexistir en una situación de balance funcional. De esta forma, se investiga cómo los hemisferios cerebrales compiten para adquirir centralidad en la red-de-redes, y cómo esta interacción se mantiene (o no) cuando se introducen fallos deliberadamente en la red funcional. El Capítulo 6 va un paso mas allá al considerar las redes funcionales como sistemas vivos. En este Capítulo se muestra cómo al analizar la evolución de la topología de las redes, en vez de tratarlas como si estas fueran un sistema estático, podemos caracterizar mejor su estructura. Este hecho es especialmente relevante cuando se quiere tratar de encontrar diferencias entre grupos que desempeñan una tarea de memoria, en la que las redes funcionales tienen fuertes fluctuaciones. En el Capítulo 7 defino cómo crear redes parenclíticas a partir de bases de datos de actividad cerebral. Este nuevo tipo de redes, recientemente introducido para estudiar las anormalidades entre grupos de control y grupos anómalos, no ha sido implementado nunca en datos cerebrales y, en este Capítulo explico cómo hacerlo cuando se quiere evaluar la consistencia de la dinámica cerebral. Para concluir esta parte de la Tesis, el Capítulo 8 se centra en la relación entre las propiedades topológicas de los nodos dentro de una red y sus características dinámicas. Como mostraré más adelante, existe una relación entre ellas que revela que la posición de un nodo dentro una red está íntimamente correlacionada con sus propiedades dinámicas. Finalmente, la última parte de esta Tesis Doctoral está compuesta únicamente por el Capítulo 9, el cual contiene las conclusiones y perspectivas futuras que pueden surgir de los trabajos expuestos. En vista de todo lo anterior, espero que esta Tesis aporte una perspectiva complementaria sobre uno de los más extraordinarios sistemas complejos frente a los que nos encontramos: El cerebro humano. ABSTRACT The human brain is probably one of the most complex systems we are facing, thus being a timely and fascinating object of study. Characterizing how the brain organizes its activity to carry out complex tasks is highly non-trivial. While early neuroimaging and electrophysiological studies typically aimed at identifying patches of task-specific activations or local time-varying patterns of activity, there has now been consensus that task-related brain activity has a temporally multiscale, spatially extended character, as networks of coordinated brain areas are continuously formed and destroyed. Up until recently, though, the emphasis of functional brain activity studies has been on the identity of the particular nodes forming these networks, and on the characterization of connectivity metrics between them, the underlying covert hypothesis being that each node, constituting a coarse-grained representation of a given brain region, provides a unique contribution to the whole. Thus, functional neuroimaging initially integrated the two basic ingredients of early neuropsychology: localization of cognitive function into specialized brain modules and the role of connection fibres in the integration of various modules. Lately, brain structure and function have started being investigated using Network Science, a statistical mechanics understanding of an old branch of pure mathematics: graph theory. Network Science allows endowing networks with a great number of quantitative properties, thus vastly enriching the set of objective descriptors of brain structure and function at neuroscientists’ disposal. The link between Network Science and Neuroscience has shed light about how the entangled anatomy of the brain is, and how cortical activations may synchronize to generate the so-called functional brain networks, the principal object under study along this PhD Thesis. Within this context, complexity appears to be the bridge between the topological and dynamical properties of biological systems and, more specifically, the interplay between the organization and dynamics of functional brain networks. This PhD Thesis is, in general terms, a study of how cortical activations can be understood as the output of a network of dynamical systems that are intimately related with the processes occurring in the brain. In order to do that, I performed five studies that encompass both the topological and the dynamical aspects of such functional brain networks. In this way, the Thesis is divided into three major parts: Introduction, Results and Discussion. In the first part, comprising Chapters 1, 2 and 3, I make an overview of the main concepts of Network Science related to the analysis of brain imaging. More specifically, Chapter 1 is devoted to introducing the reader to the world of complexity, specially to the topological and dynamical complexity of networked systems. Chapter 2 aims to develop the biological, topological and functional fundamentals of the brain when it is seen as a complex network. Next, Chapter 3 summarizes the main objectives and tasks that will be developed along the forthcoming Chapters. The second part of the Thesis is, in turn, its core, since it contains the results obtained along these last four years. This part is divided into five Chapters, containing a detailed version of the publications carried out during the Thesis. Chapter 4 is related to the topology of functional networks and, more specifically, to the detection and quantification of the leading nodes of the network: the hubs. In Chapter 5 I will show that functional brain networks can be viewed not as a single network, but as a network-of-networks, where its components have to co-exist in a trade-off situation. In this way, I investigate how the brain hemispheres compete for acquiring the centrality of the network-of-networks and how this interplay is maintained (or not) when failures are introduced in the functional network. Chapter 6 goes one step beyond by considering functional networks as living systems. In this Chapter I show how analyzing the evolution of the network topology instead of treating it as a static system allows to better characterize functional networks. This fact is especially relevant when trying to find differences between groups performing certain memory tasks, where functional networks have strong fluctuations. In Chapter 7 I define how to create parenclitic networks from brain imaging datasets. This new kind of networks, recently introduced to study abnormalities between control and anomalous groups, have not been implemented with brain datasets and I explain in this Chapter how to do it when evaluating the consistency of brain dynamics. To conclude with this part of the Thesis, Chapter 8 is devoted to the interplay between the topological properties of the nodes within a network and their dynamical features. As I will show, there is an interplay between them which reveals that the position of a node in a network is intimately related with its dynamical properties. Finally, the last part of this PhD Thesis is composed only by Chapter 9, which contains the conclusions and future perspectives that may arise from the exposed results. In view of all, I hope that reading this Thesis will give a complementary perspective of one of the most extraordinary complex systems: The human brain.

A thymidine triphosphate shape analog lacking Watson–Crick pairing ability is replicated with high sequence selectivity

Compound 1 (F), a nonpolar nucleoside analog that is isosteric with thymidine, has been proposed as a probe for the importance of hydrogen bonds in biological systems. Consistent with its lack of strong H-bond donors or acceptors, F is shown here by thermal denaturation studies to pair very poorly and with no significant selectivity among natural bases in DNA oligonucleotides. We report the synthesis of the 5′-triphosphate derivative of 1 and the study of its ability to be inserted into replicating DNA strands by the Klenow fragment (KF, exo− mutant) of Escherichia coli DNA polymerase I. We find that this nucleotide derivative (dFTP) is a surprisingly good substrate for KF; steady-state measurements indicate it is inserted into a template opposite adenine with efficiency (Vmax/Km) only 40-fold lower than dTTP. Moreover, it is inserted opposite A (relative to C, G, or T) with selectivity nearly as high as that observed for dTTP. Elongation of the strand past F in an F–A pair is associated with a brief pause, whereas that beyond A in the inverted A–F pair is not. Combined with data from studies with F in the template strand, the results show that KF can efficiently replicate a base pair (A–F/F–A) that is inherently very unstable, and the replication occurs with very high fidelity despite a lack of inherent base-pairing selectivity. The results suggest that hydrogen bonds may be less important in the fidelity of replication than commonly believed and that nucleotide/template shape complementarity may play a more important role than previously believed.

MRIT, a novel death-effector domain-containing protein, interacts with caspases and BclXL and initiates cell death

Activation of the cascade of proteolytic caspases has been identified as the final common pathway of apoptosis in diverse biological systems. We have isolated a gene, termed MRIT, that possesses overall sequence homology to FLICE (MACH), a large prodomain caspase that links the aggregated complex of the death domain receptors of the tumor necrosis factor receptor family to downstream caspases. However, unlike FLICE, the C-terminal domain of MRIT lacks the caspase catalytic consensus sequence QAC(R/Q)G. Nonetheless MRIT activates caspase-dependent death. Using yeast two-hybrid assays, we demonstrate that MRIT associates with caspases possessing large and small prodomains (FLICE, and CPP32/YAMA), as well as with the adaptor molecule FADD. In addition, MRIT simultaneously and independently interacts with BclXL and FLICE in mammalian cells. Thus, MRIT is a mammalian protein that interacts simultaneously with both caspases and a Bcl-2 family member.

Altered phosphorylation and intracellular distribution of a (CUG)n triplet repeat RNA-binding protein in patients with myotonic dystrophy and in myotonin protein kinase knockout mice

Myotonic dystrophy (DM) is associated with expansion of CTG repeats in the 3′-untranslated region of the myotonin protein kinase (DMPK) gene. The molecular mechanism whereby expansion of the (CUG)n repeats in the 3′-untranslated region of DMPK gene induces DM is unknown. We previously isolated a protein with specific binding to CUG repeat sequences (CUG-BP/hNab50) that possibly plays a role in mRNA processing and/or transport. Here we present evidence that the phosphorylation status and intracellular distribution of the RNA CUG-binding protein, identical to hNab50 protein (CUG-BP/hNab50), are altered in homozygous DM patient and that CUG-BP/hNab50 is a substrate for DMPK both in vivo and in vitro. Data from two biological systems with reduced levels of DMPK, homozygous DM patient and DMPK knockout mice, show that DMPK regulates both phosphorylation and intracellular localization of the CUG-BP/hNab50 protein. Decreased levels of DMPK observed in DM patients and DMPK knockout mice led to the elevation of the hypophosphorylated form of CUG-BP/hNab50. Nuclear concentration of the hypophosphorylated CUG-BP/hNab50 isoform is increased in DMPK knockout mice and in homozygous DM patient. DMPK also interacts with and phosphorylates CUG-BP/hNab50 protein in vitro. DMPK-mediated phosphorylation of CUG-BP/hNab50 results in dramatic reduction of the CUG-BP2, hypophosphorylated isoform, accumulation of which was observed in the nuclei of DMPK knockout mice. These data suggest a feedback mechanism whereby decreased levels of DMPK could alter phosphorylation status of CUG-BP/hNab50, thus facilitating nuclear localization of CUG-BP/hNab50. Our results suggest that DM pathophysiology could be, in part, a result of sequestration of CUG-BP/hNab50 and, in part, of lowered DMPK levels, which, in turn, affect processing and transport of specific subclass of mRNAs.

Computation, prediction, and experimental tests of fitness for bacteriophage T7 mutants with permuted genomes

We created a simulation based on experimental data from bacteriophage T7 that computes the developmental cycle of the wild-type phage and also of mutants that have an altered genome order. We used the simulation to compute the fitness of more than 105 mutants. We tested these computations by constructing and experimentally characterizing T7 mutants in which we repositioned gene 1, coding for T7 RNA polymerase. Computed protein synthesis rates for ectopic gene 1 strains were in moderate agreement with observed rates. Computed phage-doubling rates were close to observations for two of four strains, but significantly overestimated those of the other two. Computations indicate that the genome organization of wild-type T7 is nearly optimal for growth: only 2.8% of random genome permutations were computed to grow faster, the highest 31% faster, than wild type. Specific discrepancies between computations and observations suggest that a better understanding of the translation efficiency of individual mRNAs and the functions of qualitatively “nonessential” genes will be needed to improve the T7 simulation. In silico representations of biological systems can serve to assess and advance our understanding of the underlying biology. Iteration between computation, prediction, and observation should increase the rate at which biological hypotheses are formulated and tested.

Positive and negative regulation of endogenous genes by designed transcription factors

Gene regulation by imposed localization was studied by using designed zinc finger proteins that bind 18-bp DNA sequences in the 5′ untranslated regions of the protooncogenes erbB-2 and erbB-3. Transcription factors were generated by fusion of the DNA-binding proteins to repression or activation domains. When introduced into cells these transcription factors acted as dominant repressors or activators of, respectively, endogenous erbB-2 or erbB-3 gene expression. Significantly, imposed regulation of the two genes was highly specific, despite the fact that the transcription factor binding sites targeted in erbB-2 and erbB-3 share 15 of 18 nucleotides. Regulation of erbB-2 gene expression was observed in cells derived from several species that conserve the DNA target sequence. Repression of erbB-2 in SKBR3 breast cancer cells inhibited cell-cycle progression by inducing a G1 accumulation, suggesting the potential of designed transcription factors for cancer gene therapy. These results demonstrate the willful up- and down-regulation of endogenous genes, and provide an additional means to alter biological systems.

Quantitative, chemically specific imaging of selenium transformation in plants

Quantitative, chemically specific images of biological systems would be invaluable in unraveling the bioinorganic chemistry of biological tissues. Here we report the spatial distribution and chemical forms of selenium in Astragalus bisulcatus (two-grooved poison or milk vetch), a plant capable of accumulating up to 0.65% of its shoot dry biomass as Se in its natural habitat. By selectively tuning incident x-ray energies close to the Se K-absorption edge, we have collected quantitative, 100-μm-resolution images of the spatial distribution, concentration, and chemical form of Se in intact root and shoot tissues. To our knowledge, this is the first report of quantitative concentration-imaging of specific chemical forms. Plants exposed to 5 μM selenate for 28 days contained predominantly selenate in the mature leaf tissue at a concentration of 0.3–0.6 mM, whereas the young leaves and the roots contained organoselenium almost exclusively, indicating that the ability to biotransform selenate is either inducible or developmentally specific. While the concentration of organoselenium in the majority of the root tissue was much lower than that of the youngest leaves (0.2–0.3 compared with 3–4 mM), isolated areas on the extremities of the roots contained concentrations of organoselenium an order of magnitude greater than the rest of the root. These imaging results were corroborated by spatially resolved x-ray absorption near-edge spectra collected from selected 100 × 100 μm2 regions of the same tissues.

Sulfur K-edge x-ray absorption spectroscopy: A spectroscopic tool to examine the redox state of S-containing metabolites in vivo

The sulfur K-edge x-ray absorption spectra for the amino acids cysteine and methionine and their corresponding oxidized forms cystine and methionine sulfoxide are presented. Distinct differences in the shape of the edge and the inflection point energy for cysteine and cystine are observed. For methionine sulfoxide the inflection point energy is 2.8 eV higher compared with methionine. Glutathione, the most abundant thiol in animal cells, also has been investigated. The x-ray absorption near-edge structure spectrum of reduced glutathione resembles that of cysteine, whereas the spectrum of oxidized glutathione resembles that of cystine. The characteristic differences between the thiol and disulfide spectra enable one to determine the redox status (thiol to disulfide ratio) in intact biological systems, such as unbroken cells, where glutathione and cyst(e)ine are the two major sulfur-containing components. The sulfur K-edge spectra for whole human blood, plasma, and erythrocytes are shown. The erythrocyte sulfur K-edge spectrum is similar to that of fully reduced glutathione. Simulation of the plasma spectrum indicated 32% thiol and 68% disulfide sulfur. The whole blood spectrum can be simulated by a combination of 46% disulfide and 54% thiol sulfur.