Parametric Sensitivity Analysis of the Most Recent Computational Models of Rabbit Cardiac Pacemaking

The cellular basis of cardiac pacemaking activity, and specifically the quantitative contributions of particular mechanisms, is still debated. Reliable computational models of sinoatrial nodal (SAN) cells may provide mechanistic insights, but competing models are built from different data sets and with different underlying assumptions. To understand quantitative differences between alternative models, we performed thorough parameter sensitivity analyses of the SAN models of Maltsev & Lakatta (2009) and Severi et al (2012). Model parameters were randomized to generate a population of cell models with different properties, simulations performed with each set of random parameters generated 14 quantitative outputs that characterized cellular activity, and regression methods were used to analyze the population behavior. Clear differences between the two models were observed at every step of the analysis. Specifically: (1) SR Ca2+ pump activity had a greater effect on SAN cell cycle length (CL) in the Maltsev model; (2) conversely, parameters describing the funny current (If) had a greater effect on CL in the Severi model; (3) changes in rapid delayed rectifier conductance (GKr) had opposite effects on action potential amplitude in the two models; (4) within the population, a greater percentage of model cells failed to exhibit action potentials in the Maltsev model (27%) compared with the Severi model (7%), implying greater robustness in the latter; (5) confirming this initial impression, bifurcation analyses indicated that smaller relative changes in GKr or Na+-K+ pump activity led to failed action potentials in the Maltsev model. Overall, the results suggest experimental tests that can distinguish between models and alternative hypotheses, and the analysis offers strategies for developing anti-arrhythmic pharmaceuticals by predicting their effect on the pacemaking activity.

Biomolecular studies in Alzheimer’s Disease models: investigations in vitro and in vivo

The Alzheimer’s disease (AD), the most prevalent form of age-related dementia, is a multifactorial and heterogeneous neurodegenerative disease. The molecular mechanisms underlying the pathogenesis of AD are yet largely unknown. However, the etiopathogenesis of AD likely resides in the interaction between genetic and environmental risk factors. Among the different factors that contribute to the pathogenesis of AD, amyloid-beta peptides and the genetic risk factor apoE4 are prominent on the basis of genetic evidence and experimental data. ApoE4 transgenic mice have deficits in spatial learning and memory associated with inflammation and brain atrophy. Evidences suggest that apoE4 is implicated in amyloid-beta accumulation, imbalance of cellular antioxidant system and in apoptotic phenomena. The mechanisms by which apoE4 interacts with other AD risk factors leading to an increased susceptibility to the dementia are still unknown. The aim of this research was to provide new insights into molecular mechanisms of AD neurodegeneration, investigating the effect of amyloid-beta peptides and apoE4 genotype on the modulation of genes and proteins differently involved in cellular processes related to aging and oxidative balance such as PIN1, SIRT1, PSEN1, BDNF, TRX1 and GRX1. In particular, we used human neuroblastoma cells exposed to amyloid-beta or apoE3 and apoE4 proteins at different time-points, and selected brain regions of human apoE3 and apoE4 targeted replacement mice, as in vitro and in vivo models, respectively. All genes and proteins studied in the present investigation are modulated by amyloid-beta and apoE4 in different ways, suggesting their involvement in the neurodegenerative mechanisms underlying the AD. Finally, these proteins might represent novel potential diagnostic and therapeutic targets in AD.

Comparison of immortalized bEnd5 and primary mouse brain microvascular endothelial cells as in vitro blood-brain barrier models for the study of T cell extravasation

Important insights into the molecular mechanism of T cell extravasation across the blood-brain barrier (BBB) have already been obtained using immortalized mouse brain endothelioma cell lines (bEnd). However, compared with bEnd, primary brain endothelial cells have been shown to establish better barrier characteristics, including complex tight junctions and low permeability. In this study, we asked whether bEnd5 and primary mouse brain microvascular endothelial cells (pMBMECs) were equally suited as in vitro models with which to study the cellular and molecular mechanisms of T cell extravasation across the BBB. We found that both in vitro BBB models equally supported both T cell adhesion under static and physiologic flow conditions, and T cell crawling on the endothelial surface against the direction of flow. In contrast, distances of T cell crawling on pMBMECs were strikingly longer than on bEnd5, whereas diapedesis of T cells across pMBMECs was dramatically reduced compared with bEnd5. Thus, both in vitro BBB models are suited to study T cell adhesion. However, because pMBMECs better reflect endothelial BBB specialization in vivo, we propose that more reliable information about the cellular and molecular mechanisms of T cell diapedesis across the BBB can be attained using pMBMECs.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

The anatomical and cellular basis of immune surveillance in the central nervous system

The central nervous system (CNS) comprises the brain, spinal cord, optic nerves and retina, and contains post-mitotic, delicate cells. As the rigid coverings of the CNS render swelling dangerous and destructive, inflammatory reactions must be carefully controlled in CNS tissues. Nevertheless, effector immune responses that protect the host during CNS infection still occur in the CNS. Here, we describe the anatomical and cellular basis of immune surveillance in the CNS, and explain how this shapes the unique immunology of these tissues. The Review focuses principally on insights gained from the study of autoimmune responses in the CNS and to a lesser extent on models of infectious disease. Furthermore, we propose a new model to explain how antigen-specific T cell responses occur in the CNS.

Kinetic assessment of persistent halogenated xenobiotics in cell culture models: comparison of mono- and poly-halogenated compounds

We evaluated the suitability of single and multiple cell type cultures as model systems to characterise cellular kinetics of highly lipophilic compounds with potential ecotoxicological impact. Confluent mono-layers of human skin fibroblasts, rat astrocytoma C6 cells, non-differentiated and differentiated mouse 3T3 cells were kept in culture medium supplemented with 10% foetal calf serum. For competitive uptake experiments up to four different cell types, grown on glass sectors, were exposed for 3h to (14)C-labelled model compounds, dissolved either in organic solvents or incorporated into unilamellar lecithin liposomes. Bromo-, or chloro-benzenes, decabromodiphenylether (DBP), and dichlorodiphenyl ethylene (DDE) were tested in rather high concentration of 20 microM. Cellular toxicity was low. Compound levels were related to protein, DNA, and triglyceride contents. Cellular uptake was fast and dependent on physico-chemical properties of the compounds (lipophilicity, molecular size), formulation, and cell type. Mono-halogenated benzenes showed low and similar uptake levels (=low accumulation compounds). DBP and DDE showed much higher cellular accumulations (=high accumulation compounds) except for DBP in 3T3 cells. Uptake from liposomal formulations was mostly higher than if compounds were dissolved in organic solvents. The extent of uptake correlated with the cellular content of triglycerides, except for DBP. Uptake competition between different cell types was studied in a sectorial multi-cell culture model. For low accumulation compounds negligible differences were found among C6 cells and fibroblasts. Uptake of DDE was slightly and that of DBP highly increased in fibroblasts. Well-defined cell culture systems, especially the sectorial model, are appropriate to screen for bioaccumulation and cytotoxicity of (unknown) chemical entities in vitro.

Cellular and immunological basis of the host-parasite relationship during infection with Neospora caninum

Neospora caninum is an apicomplexan parasite that is closely related to Toxoplasma gondii, the causative agent of toxoplasmosis in humans and domestic animals. However, in contrast to T. gondii, N. caninum represents a major cause of abortion in cattle, pointing towards distinct differences in the biology of these two species. There are 3 distinct key features that represent potential targets for prevention of infection or intervention against disease caused by N. caninum. Firstly, tachyzoites are capable of infecting a large variety of host cells in vitro and in vivo. Secondly, the parasite exploits its ability to respond to alterations in living conditions by converting into another stage (tachyzoite-to-bradyzoite or vice versa). Thirdly, by analogy with T. gondii, this parasite has evolved mechanisms that modulate its host cells according to its own requirements, and these must, especially in the case of the bradyzoite stage, involve mechanisms that ensure long-term survival of not only the parasite but also of the host cell. In order to elucidate the molecular and cellular bases of these important features of N. caninum, cell culture-based approaches and laboratory animal models are being exploited. In this review, we will summarize the current achievements related to host cell and parasite cell biology, and will discuss potential applications for prevention of infection and/or disease by reviewing corresponding work performed in murine laboratory infection models and in cattle.

Electron microscopy of high pressure frozen samples: bridging the gap between cellular ultrastructure and atomic resolution

Transmission electron microscopy has provided most of what is known about the ultrastructural organization of tissues, cells, and organelles. Due to tremendous advances in crystallography and magnetic resonance imaging, almost any protein can now be modeled at atomic resolution. To fully understand the workings of biological "nanomachines" it is necessary to obtain images of intact macromolecular assemblies in situ. Although the resolution power of electron microscopes is on the atomic scale, in biological samples artifacts introduced by aldehyde fixation, dehydration and staining, but also section thickness reduces it to some nanometers. Cryofixation by high pressure freezing circumvents many of the artifacts since it allows vitrifying biological samples of about 200 mum in thickness and immobilizes complex macromolecular assemblies in their native state in situ. To exploit the perfect structural preservation of frozen hydrated sections, sophisticated instruments are needed, e.g., high voltage electron microscopes equipped with precise goniometers that work at low temperature and digital cameras of high sensitivity and pixel number. With them, it is possible to generate high resolution tomograms, i.e., 3D views of subcellular structures. This review describes theory and applications of the high pressure cryofixation methodology and compares its results with those of conventional procedures. Moreover, recent findings will be discussed showing that molecular models of proteins can be fitted into depicted organellar ultrastructure of images of frozen hydrated sections. High pressure freezing of tissue is the base which may lead to precise models of macromolecular assemblies in situ, and thus to a better understanding of the function of complex cellular structures.

Investigating within-canopy variation of functional traits and cellular structure of sugar maple (Acer saccharum) leaves

Patterns of increasing leaf mass per area (LMA), area-based leaf nitrogen (Narea), and carbon isotope composition (δ13C) with increasing height in the canopy have been attributed to light gradients or hydraulic limitation in tall trees. Theoretical optimal distributions of LMA and Narea that scale with light maximize canopy photosynthesis; however, sub-optimal distributions are often observed due to hydraulic constraints on leaf development. Using observational, experimental, and modeling approaches, we investigated the response of leaf functional traits (LMA, density, thickness, and leaf nitrogen), leaf carbon isotope composition (δ13C), and cellular structure to light availability, height, and leaf water potential (Ψl) in an Acer saccharum forest to tease apart the influence of light and hydraulic limitations. LMA, leaf and palisade layer thickness, and leaf density were greater at greater light availability but similar heights, highlighting the strong control of light on leaf morphology and cellular structure. Experimental shading decreased both LMA and area-based leaf nitrogen (Narea) and revealed that LMA and Narea were more strongly correlated with height earlier in the growing season and with light later in the growing season. The supply of CO2 to leaves at higher heights appeared to be constrained by stomatal sensitivity to vapor pressure deficit (VPD) or midday leaf water potential, as indicated by increasing δ13C and VPD and decreasing midday Ψl with height. Model simulations showed that daily canopy photosynthesis was biased during the early growing season when seasonality was not accounted for, and was biased throughout the growing season when vertical gradients in LMA and Narea were not accounted for. Overall, our results suggest that leaves acclimate to light soon after leaf expansion, through an accumulation of leaf carbon, thickening of palisade layers and increased LMA, and reduction in stomatal sensitivity to Ψl or VPD. This period of light acclimation in leaves appears to optimize leaf function over time, despite height-related constraints early in the growing season. Our results imply that vertical gradients in leaf functional traits and leaf acclimation to light should be incorporated in canopy function models in order to refine estimates of canopy photosynthesis.

Antitumor effect of SIRT1 inhibition in human HCC tumor models in vitro and in vivo

Sirtuins (SIRT1-7) are a highly conserved family of NAD(+)-dependent enzymes that control the activity of histone and nonhistone regulatory proteins. SIRT1 is purposed to promote longevity and to suppress the initiation of some cancers. Nevertheless, SIRT1 is reported to function as a tumor suppressor as well as an oncogenic protein. Our data show that compared with normal liver or surrounding tumor tissue, SIRT1 is strongly overexpressed in human hepatocellular carcinoma (HCC). In addition, human HCC cell lines (Hep3B, HepG2, HuH7, HLE, HLF, HepKK1, skHep1) were screened for the expression of the sirtuin family members and only SIRT1 was consistently overexpressed compared with normal hepatocytes. To determine its effect on HCC growth, SIRT1 activity was inhibited either with lentiviruses expressing short hairpin RNAs or with the small molecule inhibitor, cambinol. Knockdown or inhibition of SIRT1 activity had a cytostatic effect, characterized by an altered morphology, impaired proliferation, an increased expression of differentiation markers, and cellular senescence. In an orthotopic xenograft model, knockdown of SIRT1 resulted in 50% fewer animals developing tumors and cambinol treatment resulted in an overall lower tumor burden. Taken together, our data show that inhibition of SIRT1 in HCC cells impairs their proliferation in vitro and tumor formation in vivo. These data suggest that SIRT1 expression positively influences the growth of HCC and support further studies aimed to block its activity alone or in combination as a novel treatment strategy.

Cellular dynamic simulator: an event driven molecular simulation environment for cellular physiology.

In this paper, we present the Cellular Dynamic Simulator (CDS) for simulating diffusion and chemical reactions within crowded molecular environments. CDS is based on a novel event driven algorithm specifically designed for precise calculation of the timing of collisions, reactions and other events for each individual molecule in the environment. Generic mesh based compartments allow the creation / importation of very simple or detailed cellular structures that exist in a 3D environment. Multiple levels of compartments and static obstacles can be used to create a dense environment to mimic cellular boundaries and the intracellular space. The CDS algorithm takes into account volume exclusion and molecular crowding that may impact signaling cascades in small sub-cellular compartments such as dendritic spines. With the CDS, we can simulate simple enzyme reactions; aggregation, channel transport, as well as highly complicated chemical reaction networks of both freely diffusing and membrane bound multi-protein complexes. Components of the CDS are generally defined such that the simulator can be applied to a wide range of environments in terms of scale and level of detail. Through an initialization GUI, a simple simulation environment can be created and populated within minutes yet is powerful enough to design complex 3D cellular architecture. The initialization tool allows visual confirmation of the environment construction prior to execution by the simulator. This paper describes the CDS algorithm, design implementation, and provides an overview of the types of features available and the utility of those features are highlighted in demonstrations.

Mechanical constraints imposed by 3D cellular geometry and arrangement modulate growth patterns in the Arabidopsis embryo

Morphogenesis occurs in 3D space over time and is guided by coordinated gene expression programs. Here we use postembryonic development in Arabidopsis plants to investigate the genetic control of growth. We demonstrate that gene expression driving the production of the growth-stimulating hormone gibberellic acid and downstream growth factors is first induced within the radicle tip of the embryo. The center of cell expansion is, however, spatially displaced from the center of gene expression. Because the rapidly growing cells have very different geometry from that of those at the tip, we hypothesized that mechanical factors may contribute to this growth displacement. To this end we developed 3D finite-element method models of growing custom-designed digital embryos at cellular resolution. We used this framework to conceptualize how cell size, shape, and topology influence tissue growth and to explore the interplay of geometrical and genetic inputs into growth distribution. Our simulations showed that mechanical constraints are sufficient to explain the disconnect between the experimentally observed spatiotemporal patterns of gene expression and early postembryonic growth. The center of cell expansion is the position where genetic and mechanical facilitators of growth converge. We have thus uncovered a mechanism whereby 3D cellular geometry helps direct where genetically specified growth takes place.

Tumor heterogeneity dictates sensitivity to gefitinib (Iressa(TM)/ZD1839) in solid tumor models

The epidermal growth factor receptor (EGFR) and its ligands are overexpressed in many human tumors, including bladder and pancreas, correlating with a more aggressive tumor phenotype and poor patient prognosis. We initiated the present study to characterize the heterogeneity of gefitinib responsiveness in a panel of human bladder and pancreatic cancer cell lines in order to identify the biological characteristics of EGFR-dependent proliferation that could be used to prospectively identify drug-sensitive tumors. A second objective was to elucidate how to best exploit these results by utilizing gefitinib in combination therapy. To these ends, we examined the effects of the EGFR antagonist gefitinib on proliferation and apoptosis in a panel of 18 human bladder cancer cell lines and 9 human pancreatic cancer cell lines. Our data confirmed the existence of marked heterogeneity in Iressa responsiveness with less than half of the cell lines displaying significant growth inhibition by clinically relevant concentrations of the drug. Gefitinib responsiveness was found to be p27 kip1 dependent as DNA synthesis was restored following exposure to p27siRNA. Unfortunately, Iressa responsiveness was not closely linked to surface EGFR or TGF-α expression in the bladder cancer cells, however, cellular TGF-α expression correlated directly with Iressa sensitivity in the pancreatic cancer cell lines. These findings provide the potential for prospectively identifying patients with drug-sensitive tumors. ^ Further studies aimed at exploiting gefitinib-mediated cell cycle effects led us to investigate if gefitinib-mediated TRAIL sensitization correlated with increased p27kip1 accumulation. We observed that increased TRAIL sensitivity following gefitinib exposure was not dependent on p27 kip1 expression. Additional studies initiated to examine the role(s) of Akt and Erk signaling demonstrated that exposure to PI3K or MEK inhibitors significantly enhanced TRAIL-induced apoptosis at concentrations that block target phosphorylation. Furthermore, combinations of TRAIL and the PI3K or MEK inhibitors increased procaspase-8 processing above levels observed with TRAIL alone, indicating that the effects were exerted at the level of caspase-8 activation, considered the earliest step in the TRAIL pathway. ^

The mechanism of action of a novel benzo[c]phenanthridine alkaloid, NK314 and the cellular responses

NK314 is a novel synthetic benzo[c]phenanthridine alkaloid that is currently in clinical trials as an antitumor compound, based on impressive activities in preclinical models. However, its mechanism of action is unknown. The present investigations were directed at determining the mechanism of action of this agent and cellular responses to NK314. My studies demonstrated that NK314 intercalated into DNA, trapped topoisomerase IIα in its cleavage complex intermediate, and inhibited the ability of topoisomerase IIα to relax super-coiled DNA. CEM/VM1 cells, which are resistant to etoposide due to mutations in topoisomerase IIα, were cross-resistant to NK314. However, CEM/C2 cells, which are resistant to camptothecin due to mutations in topoisomerase I, retained sensitivity. This indicates topoisomerase IIα is the target of NK314 in the cells. NK314 caused phosphorylation of the histone variant, H2AX, which is considered a marker of DNA double-strand breaks. DNA double-strand breaks were also evidenced by pulsed-field gel electrophoresis and visualized as chromosomal aberrations after cells were treated with NK314 and arrested in mitosis. Cell cycle checkpoints are activated following DNA damage. NK314 induced significant G2 cell cycle arrest in several cell lines, independent of p53 status, suggesting the existence of a common mechanism of checkpoint activation. The Chk1-Cdc25C-Cdk1 G2 checkpoint pathway was activated in response to NK314, which can be abrogated by the Chk1 inhibitor UCN-01. Cell cycle checkpoint activation may be a defensive mechanism that provides time for DNA repair. DNA double-strand breaks are repaired either through ATM-mediated homologous recombination or DNA-PK-mediated non-homologous end-joining repair pathways. Clonogenic assays demonstrated a significant decrease of colony formation in both ATM deficient and DNA-PK deficient cells compared to ATM repleted and DNA-PK wild type cells respectively, indicating that both ATM and DNA-PK play important roles in the survival of the cells in response to NK314. The DNA-PK specific inhibitor NU7441 also significantly sensitized cells to NK314. In conclusion, the major mechanism of NK314 is to intercalate into DNA, trap and inhibit topoisomerase IIα, an action that leads to the generation of double-strand DNA breaks, which activate ATM and DNA-PK mediated DNA repair pathways and Chk1 mediated G2 checkpoint pathway. ^

Oscillatory genetic circuits: new designs and mathematical models

Introduction and motivation: A wide variety of organisms have developed in-ternal biomolecular clocks in order to adapt to cyclic changes of the environment. Clock operation involves genetic networks. These genetic networks have to be mod¬eled in order to understand the underlying mechanism of oscillations and to design new synthetic cellular clocks. This doctoral thesis has resulted in two contributions to the fields of genetic clocks and systems and synthetic biology, generally. The first contribution is a new genetic circuit model that exhibits an oscillatory behav¬ior through catalytic RNA molecules. The second and major contribution is a new genetic circuit model demonstrating that a repressor molecule acting on the positive feedback of a self-activating gene produces reliable oscillations. First contribution: A new model of a synthetic genetic oscillator based on a typical two-gene motif with one positive and one negative feedback loop is pre¬sented. The originality is that the repressor is a catalytic RNA molecule rather than a protein or a non-catalytic RNA molecule. This catalytic RNA is a ribozyme that acts post-transcriptionally by binding to and cleaving target mRNA molecules. This genetic clock involves just two genes, a mRNA and an activator protein, apart from the ribozyme. Parameter values that produce a circadian period in both determin¬istic and stochastic simulations have been chosen as an example of clock operation. The effects of the stochastic fluctuations are quantified by a period histogram and autocorrelation function. The conclusion is that catalytic RNA molecules can act as repressor proteins and simplify the design of genetic oscillators. Second and major contribution: It is demonstrated that a self-activating gene in conjunction with a simple negative interaction can easily produce robust matically validated. This model is comprised of two clearly distinct parts. The first is a positive feedback created by a protein that binds to the promoter of its own gene and activates the transcription. The second is a negative interaction in which a repressor molecule prevents this protein from binding to its promoter. A stochastic study shows that the system is robust to noise. A deterministic study identifies that the oscillator dynamics are mainly driven by two types of biomolecules: the protein, and the complex formed by the repressor and this protein. The main conclusion of this study is that a simple and usual negative interaction, such as degradation, se¬questration or inhibition, acting on the positive transcriptional feedback of a single gene is a sufficient condition to produce reliable oscillations. One gene is enough and the positive transcriptional feedback signal does not need to activate a second repressor gene. At the genetic level, this means that an explicit negative feedback loop is not necessary. Unlike many genetic oscillators, this model needs neither cooperative binding reactions nor the formation of protein multimers. Applications and future research directions: Recently, RNA molecules have been found to play many new catalytic roles. The first oscillatory genetic model proposed in this thesis uses ribozymes as repressor molecules. This could provide new synthetic biology design principles and a better understanding of cel¬lular clocks regulated by RNA molecules. The second genetic model proposed here involves only a repression acting on a self-activating gene and produces robust oscil¬lations. Unlike current two-gene oscillators, this model surprisingly does not require a second repressor gene. This result could help to clarify the design principles of cellular clocks and constitute a new efficient tool for engineering synthetic genetic oscillators. Possible follow-on research directions are: validate models in vivo and in vitro, research the potential of second model as a genetic memory, investigate new genetic oscillators regulated by non-coding RNAs and design a biosensor of positive feedbacks in genetic networks based on the operation of the second model Resumen Introduccion y motivacion: Una amplia variedad de organismos han desarro-llado relojes biomoleculares internos con el fin de adaptarse a los cambios ciclicos del entorno. El funcionamiento de estos relojes involucra redes geneticas. El mo delado de estas redes geneticas es esencial tanto para entender los mecanismos que producen las oscilaciones como para diseiiar nuevos circuitos sinteticos en celulas. Esta tesis doctoral ha dado lugar a dos contribuciones dentro de los campos de los circuitos geneticos en particular, y biologia de sistemas y sintetica en general. La primera contribucion es un nuevo modelo de circuito genetico que muestra un comportamiento oscilatorio usando moleculas de ARN cataliticas. La segunda y principal contribucion es un nuevo modelo de circuito genetico que demuestra que una molecula represora actuando sobre el lazo de un gen auto-activado produce oscilaciones robustas. Primera contribucion: Es un nuevo modelo de oscilador genetico sintetico basado en una tipica red genetica compuesta por dos genes con dos lazos de retroa-limentacion, uno positivo y otro negativo. La novedad de este modelo es que el represor es una molecula de ARN catalftica, en lugar de una protefna o una molecula de ARN no-catalitica. Este ARN catalitico es una ribozima que actua despues de la transcription genetica uniendose y cortando moleculas de ARN mensajero (ARNm). Este reloj genetico involucra solo dos genes, un ARNm y una proteina activadora, aparte de la ribozima. Como ejemplo de funcionamiento, se han escogido valores de los parametros que producen oscilaciones con periodo circadiano (24 horas) tanto en simulaciones deterministas como estocasticas. El efecto de las fluctuaciones es-tocasticas ha sido cuantificado mediante un histograma del periodo y la función de auto-correlacion. La conclusion es que las moleculas de ARN con propiedades cataliticas pueden jugar el misnio papel que las protemas represoras, y por lo tanto, simplificar el diseno de los osciladores geneticos. Segunda y principal contribucion: Es un nuevo modelo de oscilador genetico que demuestra que un gen auto-activado junto con una simple interaction negativa puede producir oscilaciones robustas. Este modelo ha sido estudiado y validado matematicamente. El modelo esta compuesto de dos partes bien diferenciadas. La primera parte es un lazo de retroalimentacion positiva creado por una proteina que se une al promotor de su propio gen activando la transcription. La segunda parte es una interaction negativa en la que una molecula represora evita la union de la proteina con el promotor. Un estudio estocastico muestra que el sistema es robusto al ruido. Un estudio determinista muestra que la dinamica del sistema es debida principalmente a dos tipos de biomoleculas: la proteina, y el complejo formado por el represor y esta proteina. La conclusion principal de este estudio es que una simple y usual interaction negativa, tal como una degradation, un secuestro o una inhibition, actuando sobre el lazo de retroalimentacion positiva de un solo gen es una condition suficiente para producir oscilaciones robustas. Un gen es suficiente y el lazo de retroalimentacion positiva no necesita activar a un segundo gen represor, tal y como ocurre en los relojes actuales con dos genes. Esto significa que a nivel genetico un lazo de retroalimentacion negativa no es necesario de forma explicita. Ademas, este modelo no necesita reacciones cooperativas ni la formation de multimeros proteicos, al contrario que en muchos osciladores geneticos. Aplicaciones y futuras lineas de investigacion: En los liltimos anos, se han descubierto muchas moleculas de ARN con capacidad catalitica. El primer modelo de oscilador genetico propuesto en esta tesis usa ribozimas como moleculas repre¬soras. Esto podria proporcionar nuevos principios de diseno en biologia sintetica y una mejor comprension de los relojes celulares regulados por moleculas de ARN. El segundo modelo de oscilador genetico propuesto aqui involucra solo una represion actuando sobre un gen auto-activado y produce oscilaciones robustas. Sorprendente-mente, un segundo gen represor no es necesario al contrario que en los bien conocidos osciladores con dos genes. Este resultado podria ayudar a clarificar los principios de diseno de los relojes celulares naturales y constituir una nueva y eficiente he-rramienta para crear osciladores geneticos sinteticos. Algunas de las futuras lineas de investigation abiertas tras esta tesis son: (1) la validation in vivo e in vitro de ambos modelos, (2) el estudio del potential del segundo modelo como circuito base para la construction de una memoria genetica, (3) el estudio de nuevos osciladores geneticos regulados por ARN no codificante y, por ultimo, (4) el rediseno del se¬gundo modelo de oscilador genetico para su uso como biosensor capaz de detectar genes auto-activados en redes geneticas.