990 resultados para EXPRESSION DYNAMICS


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BACKGROUND Foxi3 is a member of the large forkhead box family of transcriptional regulators, which have a wide range of biological activities including manifold developmental processes. Heterozygous mutation in Foxi3 was identified in several hairless dog breeds characterized by sparse fur coat and missing teeth. A related phenotype called hypohidrotic ectodermal dysplasia (HED) is caused by mutations in the ectodysplasin (Eda) pathway genes. RESULTS Expression of Foxi3 was strictly confined to the epithelium in developing ectodermal appendages in mouse embryos, but no expression was detected in the epidermis. Foxi3 was expressed in teeth and hair follicles throughout embryogenesis, but in mammary glands only during the earliest stages of development. Foxi3 expression was decreased and increased in Eda loss- and gain-of-function embryos, respectively, and was highly induced by Eda protein in embryonic skin explants. Also activin A treatment up-regulated Foxi3 mRNA levels in vitro. CONCLUSIONS Eda and activin A were identified as upstream regulators of Foxi3. Foxi3 is a likely transcriptional target of Eda in ectodermal appendage placodes suggesting that HED phenotype may in part be produced by compromised Foxi3 activity. In addition to hair and teeth, Foxi3 may have a role in nail, eye, and mammary, sweat, and salivary gland development.

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During development, the genome undergoes drastic reorganization within the nuclear space. To determine tridimensional genome folding, genome-wide techniques (damID/Hi-C) can be applied using cell populations, but these have to be calibrated using microscopy and single-cell analysis of gene positioning. Moreover, the dynamic behavior of chromatin has to be assessed on living samples. Combining fast stereotypic development with easy genetics and microscopy, the nematode C. elegans has become a model of choice in recent years to study changes in nuclear organization during cell fate acquisition. Here we present two complementary techniques to evaluate nuclear positioning of genes either by fluorescence in situ hybridization in fixed samples or in living worm embryos using the GFP-lacI/lacO chromatin-tagging system.

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cAMP-response element binding (CREB) proteins are involved in transcriptional regulation in a number of cellular processes (e.g., neural plasticity and circadian rhythms). The CREB family contains activators and repressors that may interact through positive and negative feedback loops. These loops can be generated by auto- and cross-regulation of expression of CREB proteins, via CRE elements in or near their genes. Experiments suggest that such feedback loops may operate in several systems (e.g., Aplysia and rat). To understand the functional implications of such feedback loops, which are interlocked via cross-regulation of transcription, a minimal model with a positive and negative loop was developed and investigated using bifurcation analysis. Bifurcation analysis revealed diverse nonlinear dynamics (e.g., bistability and oscillations). The stability of steady states or oscillations could be changed by time delays in the synthesis of the activator (CREB1) or the repressor (CREB2). Investigation of stochastic fluctuations due to small numbers of molecules of CREB1 and CREB2 revealed a bimodal distribution of CREB molecules in the bistability region. The robustness of the stable HIGH and LOW states of CREB expression to stochastic noise differs, and a critical number of molecules was required to sustain the HIGH state for days or longer. Increasing positive feedback or decreasing negative feedback also increased the lifetime of the HIGH state, and persistence of this state may correlate with long-term memory formation. A critical number of molecules was also required to sustain robust oscillations of CREB expression. If a steady state was near a deterministic Hopf bifurcation point, stochastic resonance could induce oscillations. This comparative analysis of deterministic and stochastic dynamics not only provides insights into the possible dynamics of CREB regulatory motifs, but also demonstrates a framework for understanding other regulatory processes with similar network architecture.

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cAMP-response element binding (CREB) proteins are involved in transcriptional regulation in a number of cellular processes (e.g., neural plasticity and circadian rhythms). The CREB family contains activators and repressors that may interact through positive and negative feedback loops. These loops can be generated by auto- and cross-regulation of expression of CREB proteins, via CRE elements in or near their genes. Experiments suggest that such feedback loops may operate in several systems (e.g., Aplysia and rat). To understand the functional implications of such feedback loops, which are interlocked via cross-regulation of transcription, a minimal model with a positive and negative loop was developed and investigated using bifurcation analysis. Bifurcation analysis revealed diverse nonlinear dynamics (e.g., bistability and oscillations). The stability of steady states or oscillations could be changed by time delays in the synthesis of the activator (CREB1) or the repressor (CREB2). Investigation of stochastic fluctuations due to small numbers of molecules of CREB1 and CREB2 revealed a bimodal distribution of CREB molecules in the bistability region. The robustness of the stable HIGH and LOW states of CREB expression to stochastic noise differs, and a critical number of molecules was required to sustain the HIGH state for days or longer. Increasing positive feedback or decreasing negative feedback also increased the lifetime of the HIGH state, and persistence of this state may correlate with long-term memory formation. A critical number of molecules was also required to sustain robust oscillations of CREB expression. If a steady state was near a deterministic Hopf bifurcation point, stochastic resonance could induce oscillations. This comparative analysis of deterministic and stochastic dynamics not only provides insights into the possible dynamics of CREB regulatory motifs, but also demonstrates a framework for understanding other regulatory processes with similar network architecture.

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While a remarkable continuity in smallholder agricultural production has been identified, the shift from subsistence orientation towards more wage dependence appears in a different light when analysed under a gender perspective. "Feminisation" has been a catchphrase to characterise some of these processes; however, the debate has been subject to overgeneralisation, and can only inadequately grasp the gender dynamics in what has been referred to as "new ruralities". Illustrated for high-value crop production as an expression of agricultural transition in the Global South, this contribution offers a critical account of the feminisation thesis. Instead of discarding the notion of feminisation, it advocates a reassessment of its potential as a comprehensive framework against which empirical findings can be reflected. While conventional uses of the feminisation thesis have, in their great majority, come up with the conclusion that for women it can always only get worse, I propose a perspective which reveals gains and risks and how they are shared between men and women as they engage in new agricultural labour markets. This perspective rests on a methodology for case-based, comparative studies developed in this paper as a contribution for assessing the nature of agricultural transition and to investigate the qualitative change associated with new ruralities. A distinctive appreciation of the substance of agricultural change for different members of the rural society – namely men and women, but also different men, and different women – is the premise for overcoming barriers to shared development, and for framing effective governance in the context of global development.

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As a consequence of artificial selection for specific traits, crop plants underwent considerable genotypic and phenotypic changes during the process of domestication. These changes may have led to reduced resistance in the cultivated plant due to shifts in resource allocation from defensive traits to increased growth rates and yield. Modern maize (Zea mays ssp. mays) was domesticated from its ancestor Balsas teosinte (Z. mays ssp. parviglumis) approximately 9000 years ago. Although maize displays a high genetic overlap with its direct ancestor and other annual teosintes, several studies show that maize and its ancestors differ in their resistance phenotypes with teosintes being less susceptible to herbivore damage. However, the underlying mechanisms are poorly understood. Here we addressed the question to what extent maize domestication has affected two crucial chemical and one physical defence traits and whether differences in their expression may explain the differences in herbivore resistance levels. The ontogenetic trajectories of 1,4-benzoxazin-3-ones, maysin and leaf toughness were monitored for different leaf types across several maize cultivars and teosinte accessions during early vegetative growth stages. We found significant quantitative and qualitative differences in 1,4-benzoxazin-3-one accumulation in an initial pairwise comparison, but we did not find consistent differences between wild and cultivated genotypes during a more thorough examination employing several cultivars/accessions. Yet, 1,4-benzoxazin-3-one levels tended to decline more rapidly with plant age in the modern maize cultivars. Foliar maysin levels and leaf toughness increased with plant age in a leaf-specific manner, but were also unaffected by domestication. Based on our findings we suggest that defence traits other than the ones that were investigated are responsible for the observed differences in herbivore resistance between teosinte and maize. Furthermore, our results indicate that single pairwise comparisons may lead to false conclusions regarding the effects of domestication on defensive and possibly other traits.

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To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

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To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

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Abstract The creation of atlases, or digital models where information from different subjects can be combined, is a field of increasing interest in biomedical imaging. When a single image does not contain enough information to appropriately describe the organism under study, it is then necessary to acquire images of several individuals, each of them containing complementary data with respect to the rest of the components in the cohort. This approach allows creating digital prototypes, ranging from anatomical atlases of human patients and organs, obtained for instance from Magnetic Resonance Imaging, to gene expression cartographies of embryo development, typically achieved from Light Microscopy. Within such context, in this PhD Thesis we propose, develop and validate new dedicated image processing methodologies that, based on image registration techniques, bring information from multiple individuals into alignment within a single digital atlas model. We also elaborate a dedicated software visualization platform to explore the resulting wealth of multi-dimensional data and novel analysis algo-rithms to automatically mine the generated resource in search of bio¬logical insights. In particular, this work focuses on gene expression data from developing zebrafish embryos imaged at the cellular resolution level with Two-Photon Laser Scanning Microscopy. Disposing of quantitative measurements relating multiple gene expressions to cell position and their evolution in time is a fundamental prerequisite to understand embryogenesis multi-scale processes. However, the number of gene expressions that can be simultaneously stained in one acquisition is limited due to optical and labeling constraints. These limitations motivate the implementation of atlasing strategies that can recreate a virtual gene expression multiplex. The developed computational tools have been tested in two different scenarios. The first one is the early zebrafish embryogenesis where the resulting atlas constitutes a link between the phenotype and the genotype at the cellular level. The second one is the late zebrafish brain where the resulting atlas allows studies relating gene expression to brain regionalization and neurogenesis. The proposed computational frameworks have been adapted to the requirements of both scenarios, such as the integration of partial views of the embryo into a whole embryo model with cellular resolution or the registration of anatom¬ical traits with deformable transformation models non-dependent on any specific labeling. The software implementation of the atlas generation tool (Match-IT) and the visualization platform (Atlas-IT) together with the gene expression atlas resources developed in this Thesis are to be made freely available to the scientific community. Lastly, a novel proof-of-concept experiment integrates for the first time 3D gene expression atlas resources with cell lineages extracted from live embryos, opening up the door to correlate genetic and cellular spatio-temporal dynamics. La creación de atlas, o modelos digitales, donde la información de distintos sujetos puede ser combinada, es un campo de creciente interés en imagen biomédica. Cuando una sola imagen no contiene suficientes datos como para describir apropiadamente el organismo objeto de estudio, se hace necesario adquirir imágenes de varios individuos, cada una de las cuales contiene información complementaria respecto al resto de componentes del grupo. De este modo, es posible crear prototipos digitales, que pueden ir desde atlas anatómicos de órganos y pacientes humanos, adquiridos por ejemplo mediante Resonancia Magnética, hasta cartografías de la expresión genética del desarrollo de embrionario, típicamente adquiridas mediante Microscopía Optica. Dentro de este contexto, en esta Tesis Doctoral se introducen, desarrollan y validan nuevos métodos de procesado de imagen que, basándose en técnicas de registro de imagen, son capaces de alinear imágenes y datos provenientes de múltiples individuos en un solo atlas digital. Además, se ha elaborado una plataforma de visualization específicamente diseñada para explorar la gran cantidad de datos, caracterizados por su multi-dimensionalidad, que resulta de estos métodos. Asimismo, se han propuesto novedosos algoritmos de análisis y minería de datos que permiten inspeccionar automáticamente los atlas generados en busca de conclusiones biológicas significativas. En particular, este trabajo se centra en datos de expresión genética del desarrollo embrionario del pez cebra, adquiridos mediante Microscopía dos fotones con resolución celular. Disponer de medidas cuantitativas que relacionen estas expresiones genéticas con las posiciones celulares y su evolución en el tiempo es un prerrequisito fundamental para comprender los procesos multi-escala característicos de la morfogénesis. Sin embargo, el número de expresiones genéticos que pueden ser simultáneamente etiquetados en una sola adquisición es reducido debido a limitaciones tanto ópticas como del etiquetado. Estas limitaciones requieren la implementación de estrategias de creación de atlas que puedan recrear un multiplexado virtual de expresiones genéticas. Las herramientas computacionales desarrolladas han sido validadas en dos escenarios distintos. El primer escenario es el desarrollo embrionario temprano del pez cebra, donde el atlas resultante permite constituir un vínculo, a nivel celular, entre el fenotipo y el genotipo de este organismo modelo. El segundo escenario corresponde a estadios tardíos del desarrollo del cerebro del pez cebra, donde el atlas resultante permite relacionar expresiones genéticas con la regionalización del cerebro y la formación de neuronas. La plataforma computacional desarrollada ha sido adaptada a los requisitos y retos planteados en ambos escenarios, como la integración, a resolución celular, de vistas parciales dentro de un modelo consistente en un embrión completo, o el alineamiento entre estructuras de referencia anatómica equivalentes, logrado mediante el uso de modelos de transformación deformables que no requieren ningún marcador específico. Está previsto poner a disposición de la comunidad científica tanto la herramienta de generación de atlas (Match-IT), como su plataforma de visualización (Atlas-IT), así como las bases de datos de expresión genética creadas a partir de estas herramientas. Por último, dentro de la presente Tesis Doctoral, se ha incluido una prueba conceptual innovadora que permite integrar los mencionados atlas de expresión genética tridimensionales dentro del linaje celular extraído de una adquisición in vivo de un embrión. Esta prueba conceptual abre la puerta a la posibilidad de correlar, por primera vez, las dinámicas espacio-temporales de genes y células.

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A gene expression atlas is an essential resource to quantify and understand the multiscale processes of embryogenesis in time and space. The automated reconstruction of a prototypic 4D atlas for vertebrate early embryos, using multicolor fluorescence in situ hybridization with nuclear counterstain, requires dedicated computational strategies. To this goal, we designed an original methodological framework implemented in a software tool called Match-IT. With only minimal human supervision, our system is able to gather gene expression patterns observed in different analyzed embryos with phenotypic variability and map them onto a series of common 3D templates over time, creating a 4D atlas. This framework was used to construct an atlas composed of 6 gene expression templates from a cohort of zebrafish early embryos spanning 6 developmental stages from 4 to 6.3 hpf (hours post fertilization). They included 53 specimens, 181,415 detected cell nuclei and the segmentation of 98 gene expression patterns observed in 3D for 9 different genes. In addition, an interactive visualization software, Atlas-IT, was developed to inspect, supervise and analyze the atlas. Match-IT and Atlas-IT, including user manuals, representative datasets and video tutorials, are publicly and freely available online. We also propose computational methods and tools for the quantitative assessment of the gene expression templates at the cellular scale, with the identification, visualization and analysis of coexpression patterns, synexpression groups and their dynamics through developmental stages.

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La embriogénesis es el proceso mediante el cual una célula se convierte en un ser un vivo. A lo largo de diferentes etapas de desarrollo, la población de células va proliferando a la vez que el embrión va tomando forma y se configura. Esto es posible gracias a la acción de varios procesos genéticos, bioquímicos y mecánicos que interaccionan y se regulan entre ellos formando un sistema complejo que se organiza a diferentes escalas espaciales y temporales. Este proceso ocurre de manera robusta y reproducible, pero también con cierta variabilidad que permite la diversidad de individuos de una misma especie. La aparición de la microscopía de fluorescencia, posible gracias a proteínas fluorescentes que pueden ser adheridas a las cadenas de expresión de las células, y los avances en la física óptica de los microscopios han permitido observar este proceso de embriogénesis in-vivo y generar secuencias de imágenes tridimensionales de alta resolución espacio-temporal. Estas imágenes permiten el estudio de los procesos de desarrollo embrionario con técnicas de análisis de imagen y de datos, reconstruyendo dichos procesos para crear la representación de un embrión digital. Una de las más actuales problemáticas en este campo es entender los procesos mecánicos, de manera aislada y en interacción con otros factores como la expresión genética, para que el embrión se desarrolle. Debido a la complejidad de estos procesos, estos problemas se afrontan mediante diferentes técnicas y escalas específicas donde, a través de experimentos, pueden hacerse y confrontarse hipótesis, obteniendo conclusiones sobre el funcionamiento de los mecanismos estudiados. Esta tesis doctoral se ha enfocado sobre esta problemática intentando mejorar las metodologías del estado del arte y con un objetivo específico: estudiar patrones de deformación que emergen del movimiento organizado de las células durante diferentes estados del desarrollo del embrión, de manera global o en tejidos concretos. Estudios se han centrado en la mecánica en relación con procesos de señalización o interacciones a nivel celular o de tejido. En este trabajo, se propone un esquema para generalizar el estudio del movimiento y las interacciones mecánicas que se desprenden del mismo a diferentes escalas espaciales y temporales. Esto permitiría no sólo estudios locales, si no estudios sistemáticos de las escalas de interacción mecánica dentro de un embrión. Por tanto, el esquema propuesto obvia las causas de generación de movimiento (fuerzas) y se centra en la cuantificación de la cinemática (deformación y esfuerzos) a partir de imágenes de forma no invasiva. Hoy en día las dificultades experimentales y metodológicas y la complejidad de los sistemas biológicos impiden una descripción mecánica completa de manera sistemática. Sin embargo, patrones de deformación muestran el resultado de diferentes factores mecánicos en interacción con otros elementos dando lugar a una organización mecánica, necesaria para el desarrollo, que puede ser cuantificado a partir de la metodología propuesta en esta tesis. La metodología asume un medio continuo descrito de forma Lagrangiana (en función de las trayectorias de puntos materiales que se mueven en el sistema en lugar de puntos espaciales) de la dinámica del movimiento, estimado a partir de las imágenes mediante métodos de seguimiento de células o de técnicas de registro de imagen. Gracias a este esquema es posible describir la deformación instantánea y acumulada respecto a un estado inicial para cualquier dominio del embrión. La aplicación de esta metodología a imágenes 3D + t del pez zebra sirvió para desvelar estructuras mecánicas que tienden a estabilizarse a lo largo del tiempo en dicho embrión, y que se organizan a una escala semejante al del mapa de diferenciación celular y con indicios de correlación con patrones de expresión genética. También se aplicó la metodología al estudio del tejido amnioserosa de la Drosophila (mosca de la fruta) durante el cierre dorsal, obteniendo indicios de un acoplamiento entre escalas subcelulares, celulares y supracelulares, que genera patrones complejos en respuesta a la fuerza generada por los esqueletos de acto-myosina. En definitiva, esta tesis doctoral propone una estrategia novedosa de análisis de la dinámica celular multi-escala que permite cuantificar patrones de manera inmediata y que además ofrece una representación que reconstruye la evolución de los procesos como los ven las células, en lugar de como son observados desde el microscopio. Esta metodología por tanto permite nuevas formas de análisis y comparación de embriones y tejidos durante la embriogénesis a partir de imágenes in-vivo. ABSTRACT The embryogenesis is the process from which a single cell turns into a living organism. Through several stages of development, the cell population proliferates at the same time the embryo shapes and the organs develop gaining their functionality. This is possible through genetic, biochemical and mechanical factors that are involved in a complex interaction of processes organized in different levels and in different spatio-temporal scales. The embryogenesis, through this complexity, develops in a robust and reproducible way, but allowing variability that makes possible the diversity of living specimens. The advances in physics of microscopes and the appearance of fluorescent proteins that can be attached to expression chains, reporting about structural and functional elements of the cell, have enabled for the in-vivo observation of embryogenesis. The imaging process results in sequences of high spatio-temporal resolution 3D+time data of the embryogenesis as a digital representation of the embryos that can be further analyzed, provided new image processing and data analysis techniques are developed. One of the most relevant and challenging lines of research in the field is the quantification of the mechanical factors and processes involved in the shaping process of the embryo and their interactions with other embryogenesis factors such as genetics. Due to the complexity of the processes, studies have focused on specific problems and scales controlled in the experiments, posing and testing hypothesis to gain new biological insight. However, methodologies are often difficult to be exported to study other biological phenomena or specimens. This PhD Thesis is framed within this paradigm of research and tries to propose a systematic methodology to quantify the emergent deformation patterns from the motion estimated in in-vivo images of embryogenesis. Thanks to this strategy it would be possible to quantify not only local mechanisms, but to discover and characterize the scales of mechanical organization within the embryo. The framework focuses on the quantification of the motion kinematics (deformation and strains), neglecting the causes of the motion (forces), from images in a non-invasive way. Experimental and methodological challenges hamper the quantification of exerted forces and the mechanical properties of tissues. However, a descriptive framework of deformation patterns provides valuable insight about the organization and scales of the mechanical interactions, along the embryo development. Such a characterization would help to improve mechanical models and progressively understand the complexity of embryogenesis. This framework relies on a Lagrangian representation of the cell dynamics system based on the trajectories of points moving along the deformation. This approach of analysis enables the reconstruction of the mechanical patterning as experienced by the cells and tissues. Thus, we can build temporal profiles of deformation along stages of development, comprising both the instantaneous events and the cumulative deformation history. The application of this framework to 3D + time data of zebrafish embryogenesis allowed us to discover mechanical profiles that stabilized through time forming structures that organize in a scale comparable to the map of cell differentiation (fate map), and also suggesting correlation with genetic patterns. The framework was also applied to the analysis of the amnioserosa tissue in the drosophila’s dorsal closure, revealing that the oscillatory contraction triggered by the acto-myosin network organized complexly coupling different scales: local force generation foci, cellular morphology control mechanisms and tissue geometrical constraints. In summary, this PhD Thesis proposes a theoretical framework for the analysis of multi-scale cell dynamics that enables to quantify automatically mechanical patterns and also offers a new representation of the embryo dynamics as experienced by cells instead of how the microscope captures instantaneously the processes. Therefore, this framework enables for new strategies of quantitative analysis and comparison between embryos and tissues during embryogenesis from in-vivo images.

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The cAMP response element-binding protein (CREB) is an activity-dependent transcription factor that is involved in neural plasticity. The kinetics of CREB phosphorylation have been suggested to be important for gene activation, with sustained phosphorylation being associated with downstream gene expression. If so, the duration of CREB phosphorylation might serve as an indicator for time-sensitive plastic changes in neurons. To screen for regions potentially involved in dopamine-mediated plasticity in the basal ganglia, we used organotypic slice cultures to study the patterns of dopamine- and calcium-mediated CREB phosphorylation in the major subdivisions of the striatum. Different durations of CREB phosphorylation were evoked in the dorsal and ventral striatum by activation of dopamine D1-class receptors. The same D1 stimulus elicited (i) transient phosphorylation (≤15 min) in the matrix of the dorsal striatum; (ii) sustained phosphorylation (≤2 hr) in limbic-related structures including striosomes, the nucleus accumbens, the fundus striati, and the bed nucleus of the stria terminalis; and (iii) prolonged phosphorylation (up to 4 hr or more) in cellular islands in the olfactory tubercle. Elevation of Ca2+ influx by stimulation of L-type Ca2+ channels, NMDA, or KCl induced strong CREB phosphorylation in the dorsal striatum but not in the olfactory tubercle. These findings differentiate the response of CREB to dopamine and calcium signals in different striatal regions and suggest that dopamine-mediated CREB phosphorylation is persistent in limbic-related regions of the neonatal basal ganglia. The downstream effects activated by persistent CREB phosphorylation may include time-sensitive neuroplasticity modulated by dopamine.

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A hierarchical order of gene expression has been proposed to control developmental events in hematopoiesis, but direct demonstration of the temporal relationships between regulatory gene expression and differentiation has been difficult to achieve. We modified a single-cell PCR method to detect 2-fold changes in mRNA copies per cell (dynamic range, 250–250,000 copies/cell) and used it to sequentially quantitate gene expression levels as single primitive (CD34+,CD38−) progenitor cells underwent differentiation to become erythrocytes, granulocytes, or monocyte/macrophages. Markers of differentiation such as CD34 or cytokine receptor mRNAs and transcription factors associated with their regulation were assessed. All transcription factors tested were expressed in multipotent progenitors. During lineage-specific differentiation, however, distinct patterns of expression emerged. SCL, GATA-2, and GATA-1 expression sequentially extinguished during erythroid differentiation. PU.1, AML1B, and C/EBPα expression profiles and their relationship to cytokine receptor expression in maturing granulocytes could be distinguished from similar profiles in monocytic cells. These data characterize the dynamics of gene expression accompanying blood cell development and define a signature gene expression pattern for specific stages of hematopoietic differentiation.

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We demonstrate, by using mathematical modeling of cell division cycle (CDC) dynamics, a potential mechanism for precisely controlling the frequency of cell division and regulating the size of a dividing cell. Control of the cell cycle is achieved by artificially expressing a protein that reversibly binds and inactivates any one of the CDC proteins. In the simplest case, such as the checkpoint-free situation encountered in early amphibian embryos, the frequency of CDC oscillations can be increased or decreased by regulating the rate of synthesis, the binding rate, or the equilibrium constant of the binding protein. In a more complex model of cell division, where size-control checkpoints are included, we show that the same reversible binding reaction can alter the mean cell mass in a continuously dividing cell. Because this control scheme is general and requires only the expression of a single protein, it provides a practical means for tuning the characteristics of the cell cycle in vivo.

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Although human and rodent telomeres have been studied extensively, very little is known about telomere dynamics in other vertebrates. Moreover, our current dependence on mice as a model for human tumorigenesis and aging poses a problem because human and mouse telomere biology is very different. To explore whether chickens might provide a more useful model, we have examined telomerase activity and telomere length in chicken tissues as well as in primary cell cultures. Although chicken telomeres resemble human telomeres in that they are 8–20 kb in length, the distribution of telomerase activity in chickens resembles what is found in mice. Active enzyme is present in germline tissue as well as in a wide range of somatic tissues. Because chicken cells exhibit extremely low rates of spontaneous immortalization, this finding indicates that constitutive telomerase expression does not necessarily lead to an increased immortalization frequency. Finally, we found that telomerase activity is greatly down-regulated when primary cultures are established from chicken embryos. Although this down-regulation explains the telomere loss and replicative senescence that we observed in fibroblast cultures, it raises questions concerning how relevant studies of senescence in primary cell cultures are to aging in whole animals.