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

Selecting crop models for decision making in wheat insurance

In crop insurance, the accuracy with which the insurer quantifies the actual risk is highly dependent on the availability on actual yield data. Crop models might be valuable tools to generate data on expected yields for risk assessment when no historical records are available. However, selecting a crop model for a specific objective, location and implementation scale is a difficult task. A look inside the different crop and soil modules to understand how outputs are obtained might facilitate model choice. The objectives of this paper were (i) to assess the usefulness of crop models to be used within a crop insurance analysis and design and (ii) to select the most suitable crop model for drought risk assessment in semi-arid regions in Spain. For that purpose first, a pre-selection of crop models simulating wheat yield under rainfed growing conditions at the field scale was made, and second, four selected models (Aquacrop, CERES- Wheat, CropSyst and WOFOST) were compared in terms of modelling approaches, process descriptions and model outputs. Outputs of the four models for the simulation of winter wheat growth are comparable when water is not limiting, but differences are larger when simulating yields under rainfed conditions. These differences in rainfed yields are mainly related to the dissimilar simulated soil water availability and the assumed linkages with dry matter formation. We concluded that for the simulation of winter wheat growth at field scale in such semi-arid conditions, CERES-Wheat and CropSyst are preferred. WOFOST is a satisfactory compromise between data availability and complexity when detail data on soil is limited. Aquacrop integrates physiological processes in some representative parameters, thus diminishing the number of input parameters, what is seen as an advantage when observed data is scarce. However, the high sensitivity of this model to low water availability limits its use in the region considered. Contrary to the use of ensembles of crop models, we endorse that efforts be concentrated on selecting or rebuilding a model that includes approaches that better describe the agronomic conditions of the regions in which they will be applied. The use of such complex methodologies as crop models is associated with numerous sources of uncertainty, although these models are the best tools available to get insight in these complex agronomic systems.

Co-simulation Methodologies for Hybrid and Electric Vehicle Dynamics

In recent decades, full electric and hybrid electric vehicles have emerged as an alternative to conventional cars due to a range of factors, including environmental and economic aspects. These vehicles are the result of considerable efforts to seek ways of reducing the use of fossil fuel for vehicle propulsion. Sophisticated technologies such as hybrid and electric powertrains require careful study and optimization. Mathematical models play a key role at this point. Currently, many advanced mathematical analysis tools, as well as computer applications have been built for vehicle simulation purposes. Given the great interest of hybrid and electric powertrains, along with the increasing importance of reliable computer-based models, the author decided to integrate both aspects in the research purpose of this work. Furthermore, this is one of the first final degree projects held at the ETSII (Higher Technical School of Industrial Engineers) that covers the study of hybrid and electric propulsion systems. The present project is based on MBS3D 2.0, a specialized software for the dynamic simulation of multibody systems developed at the UPM Institute of Automobile Research (INSIA). Automobiles are a clear example of complex multibody systems, which are present in nearly every field of engineering. The work presented here benefits from the availability of MBS3D software. This program has proven to be a very efficient tool, with a highly developed underlying mathematical formulation. On this basis, the focus of this project is the extension of MBS3D features in order to be able to perform dynamic simulations of hybrid and electric vehicle models. This requires the joint simulation of the mechanical model of the vehicle, together with the model of the hybrid or electric powertrain. These sub-models belong to completely different physical domains. In fact the powertrain consists of energy storage systems, electrical machines and power electronics, connected to purely mechanical components (wheels, suspension, transmission, clutch…). The challenge today is to create a global vehicle model that is valid for computer simulation. Therefore, the main goal of this project is to apply co-simulation methodologies to a comprehensive model of an electric vehicle, where sub-models from different areas of engineering are coupled. The created electric vehicle (EV) model consists of a separately excited DC electric motor, a Li-ion battery pack, a DC/DC chopper converter and a multibody vehicle model. Co-simulation techniques allow car designers to simulate complex vehicle architectures and behaviors, which are usually difficult to implement in a real environment due to safety and/or economic reasons. In addition, multi-domain computational models help to detect the effects of different driving patterns and parameters and improve the models in a fast and effective way. Automotive designers can greatly benefit from a multidisciplinary approach of new hybrid and electric vehicles. In this case, the global electric vehicle model includes an electrical subsystem and a mechanical subsystem. The electrical subsystem consists of three basic components: electric motor, battery pack and power converter. A modular representation is used for building the dynamic model of the vehicle drivetrain. This means that every component of the drivetrain (submodule) is modeled separately and has its own general dynamic model, with clearly defined inputs and outputs. Then, all the particular submodules are assembled according to the drivetrain configuration and, in this way, the power flow across the components is completely determined. Dynamic models of electrical components are often based on equivalent circuits, where Kirchhoff’s voltage and current laws are applied to draw the algebraic and differential equations. Here, Randles circuit is used for dynamic modeling of the battery and the electric motor is modeled through the analysis of the equivalent circuit of a separately excited DC motor, where the power converter is included. The mechanical subsystem is defined by MBS3D equations. These equations consider the position, velocity and acceleration of all the bodies comprising the vehicle multibody system. MBS3D 2.0 is entirely written in MATLAB and the structure of the program has been thoroughly studied and understood by the author. MBS3D software is adapted according to the requirements of the applied co-simulation method. Some of the core functions are modified, such as integrator and graphics, and several auxiliary functions are added in order to compute the mathematical model of the electrical components. By coupling and co-simulating both subsystems, it is possible to evaluate the dynamic interaction among all the components of the drivetrain. ‘Tight-coupling’ method is used to cosimulate the sub-models. This approach integrates all subsystems simultaneously and the results of the integration are exchanged by function-call. This means that the integration is done jointly for the mechanical and the electrical subsystem, under a single integrator and then, the speed of integration is determined by the slower subsystem. Simulations are then used to show the performance of the developed EV model. However, this project focuses more on the validation of the computational and mathematical tool for electric and hybrid vehicle simulation. For this purpose, a detailed study and comparison of different integrators within the MATLAB environment is done. Consequently, the main efforts are directed towards the implementation of co-simulation techniques in MBS3D software. In this regard, it is not intended to create an extremely precise EV model in terms of real vehicle performance, although an acceptable level of accuracy is achieved. The gap between the EV model and the real system is filled, in a way, by introducing the gas and brake pedals input, which reflects the actual driver behavior. This input is included directly in the differential equations of the model, and determines the amount of current provided to the electric motor. For a separately excited DC motor, the rotor current is proportional to the traction torque delivered to the car wheels. Therefore, as it occurs in the case of real vehicle models, the propulsion torque in the mathematical model is controlled through acceleration and brake pedal commands. The designed transmission system also includes a reduction gear that adapts the torque coming for the motor drive and transfers it. The main contribution of this project is, therefore, the implementation of a new calculation path for the wheel torques, based on performance characteristics and outputs of the electric powertrain model. Originally, the wheel traction and braking torques were input to MBS3D through a vector directly computed by the user in a MATLAB script. Now, they are calculated as a function of the motor current which, in turn, depends on the current provided by the battery pack across the DC/DC chopper converter. The motor and battery currents and voltages are the solutions of the electrical ODE (Ordinary Differential Equation) system coupled to the multibody system. Simultaneously, the outputs of MBS3D model are the position, velocity and acceleration of the vehicle at all times. The motor shaft speed is computed from the output vehicle speed considering the wheel radius, the gear reduction ratio and the transmission efficiency. This motor shaft speed, somehow available from MBS3D model, is then introduced in the differential equations corresponding to the electrical subsystem. In this way, MBS3D and the electrical powertrain model are interconnected and both subsystems exchange values resulting as expected with tight-coupling approach.When programming mathematical models of complex systems, code optimization is a key step in the process. A way to improve the overall performance of the integration, making use of C/C++ as an alternative programming language, is described and implemented. Although this entails a higher computational burden, it leads to important advantages regarding cosimulation speed and stability. In order to do this, it is necessary to integrate MATLAB with another integrated development environment (IDE), where C/C++ code can be generated and executed. In this project, C/C++ files are programmed in Microsoft Visual Studio and the interface between both IDEs is created by building C/C++ MEX file functions. These programs contain functions or subroutines that can be dynamically linked and executed from MATLAB. This process achieves reductions in simulation time up to two orders of magnitude. The tests performed with different integrators, also reveal the stiff character of the differential equations corresponding to the electrical subsystem, and allow the improvement of the cosimulation process. When varying the parameters of the integration and/or the initial conditions of the problem, the solutions of the system of equations show better dynamic response and stability, depending on the integrator used. Several integrators, with variable and non-variable step-size, and for stiff and non-stiff problems are applied to the coupled ODE system. Then, the results are analyzed, compared and discussed. From all the above, the project can be divided into four main parts: 1. Creation of the equation-based electric vehicle model; 2. Programming, simulation and adjustment of the electric vehicle model; 3. Application of co-simulation methodologies to MBS3D and the electric powertrain subsystem; and 4. Code optimization and study of different integrators. Additionally, in order to deeply understand the context of the project, the first chapters include an introduction to basic vehicle dynamics, current classification of hybrid and electric vehicles and an explanation of the involved technologies such as brake energy regeneration, electric and non-electric propulsion systems for EVs and HEVs (hybrid electric vehicles) and their control strategies. Later, the problem of dynamic modeling of hybrid and electric vehicles is discussed. The integrated development environment and the simulation tool are also briefly described. The core chapters include an explanation of the major co-simulation methodologies and how they have been programmed and applied to the electric powertrain model together with the multibody system dynamic model. Finally, the last chapters summarize the main results and conclusions of the project and propose further research topics. In conclusion, co-simulation methodologies are applicable within the integrated development environments MATLAB and Visual Studio, and the simulation tool MBS3D 2.0, where equation-based models of multidisciplinary subsystems, consisting of mechanical and electrical components, are coupled and integrated in a very efficient way.

Mass spectrometry of ribosomes and ribosomal subunits

Nanoflow electrospray ionization has been used to introduce intact Escherichia coli ribosomes into the ion source of a mass spectrometer. Mass spectra of remarkable quality result from a partial, but selective, dissociation of the particles within the mass spectrometer. Peaks in the spectra have been assigned to individual ribosomal proteins and to noncovalent complexes of up to five component proteins. The pattern of dissociation correlates strongly with predicted features of ribosomal protein–protein and protein–RNA interactions. The spectra allow the dynamics and state of folding of specific proteins to be investigated in the context of the intact ribosome. This study demonstrates a potentially general strategy to probe interactions within complex biological assemblies.

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.

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.

Scanning electrochemical microscopy of living cells: Different redox activities of nonmetastatic and metastatic human breast cells

Electrochemical methods have been widely used to monitor physiologically important molecules in biological systems. This report describes the first application of the scanning electrochemical microscope (SECM) to probe the redox activity of individual living cells. The possibilities of measuring the rate and investigating the pathway of transmembrane charge transfer are demonstrated. By this approach, significant differences are detected in the redox responses given by nonmotile, nontransformed human breast epithelial cells, breast cells with a high level of motility (engendered by overexpression of protein kinase Cα), and highly metastatic breast cancer cells. SECM analysis of the three cell lines reveals reproducible differences with respect to the kinetics of charge transfer by several redox mediators.