A 2-4 keV multilayer mirrored channel for the NIF Dante system

During inertial confinement fusion experiments at the National Ignition Facility (NIF), a capsule filled with deuterium and tritium (DT) gas, surrounded by a DT ice layer and a high-density carbon ablator, is driven to the temperature and densities required to initiate fusion. In the indirect method, 2 MJ of NIF laser light heats the inside of a gold hohlraum to a radiation temperature of 300 eV; thermal x rays from the hohlraum interior couple to the capsule and create a central hotspot at tens of millions degrees Kelvin and a density of 100-200 g/cm³. During the laser interaction with the gold wall, m-band x rays are produced at ∼2.5 keV; these can penetrate into the capsule and preheat the ablator and DT fuel. Preheat can impact instability growth rates in the ablation front and at the fuel-ablator interface. Monitoring the hohlraum x-ray spectrum throughout the implosion is, therefore, critical; for this purpose, a Multilayer Mirror (MLM) with flat response in the 2-4 keV range has been installed in the NIF 37° Dante calorimeter. Precision engineering and x-ray calibration of components mean the channel will report 2-4 keV spectral power with an uncertainty of ±8.7%.

The five line-of-sight neutron time-of-flight (nToF) suite on the National Ignition Facility (NIF)

Measurement of the neutron spectrum from inertial confinement fusion implosions is one of the primary diagnostics of implosion performance. Analysis of the spectrum gives access to quantities such as neutron yield, hot-spot velocity, apparent ion temperature, and compressed fuel ρr through measurement of the down-scatter ratio. On the National Ignition Facility, the neutron time-of-flight suite has been upgraded to include five independent, collimated lines of sight, each comprising a high dynamic range bibenzyl/diphenylacetylene-stilbene scintillator [R. Hatarik et al., Plasma Fusion Res. 9, 4404104 (2014)] and high-speed fused silica Cherenkov detectors [A. S. Moore et al., Rev. Sci. Instrum. 89, 10I120 (2018)].

Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation

The extensive heterogeneity of biological data poses challenges to analysis and interpretation. Construction of a large-scale mechanistic model of Escherichia coli enabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various groups over decades. We identified inconsistencies with functional consequences across the data, including that the total output of the ribosomes and RNA polymerases described by data are not sufficient for a cell to reproduce measured doubling times, that measured metabolic parameters are neither fully compatible with each other nor with overall growth, and that essential proteins are absent during the cell cycle-and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.

Pulse dilation gas Cherenkov detector for ultra-fast gamma reaction history at the NIF (invited)

The Cherenkov mechanism used in Gas Cherenkov Detectors (GCDs) is exceptionally fast. However, the temporal resolution of GCDs, such as the Gamma Reaction History diagnostic at the National Ignition Facility (NIF), has been limited by the current state-of-the-art photomultiplier tube technology to ∼100 ps. The soon-to-be deployed Pulse Dilation Photomultiplier Tube (PD-PMT) at NIF will allow for temporal resolution comparable to that of the gas cell or ∼10 ps. Enhanced resolution will contribute to the quest for ignition in a crucial way through precision measurements of reaction history and ablator areal density (ρR) history, leading to better constrained models. Features such as onset of alpha heating, shock reverberations, and burn truncation due to dynamically evolving failure modes may become visible for the first time. Test measurements of the PD-PMT at Atomic Weapons Establishment confirmed that design goals have been met. The PD-PMT provides dilation factors of 2 to 40× in 6 increments. The GCD-3 recently deployed at the NIF has been modified for coupling to a PD-PMT and will soon be making ultrafast measurements.

Progress on next generation gamma-ray Cherenkov detectors for the National Ignition Facility

Fusion reaction history and ablator areal density measurements for Inertial Confinement Fusion experiments at the National Ignition Facility are currently conducted using the Gamma Reaction History diagnostic (GRH_6m). Future Gas Cherenkov Detectors (GCDs) will ultimately provide ∼100x more sensitivity, reduce the effective temporal response from ∼100 to ∼10 ps, and lower the energy threshold from 2.9 to 1.8 MeV, relative to GRH_6m. The first phase toward next generation GCDs consisted of inserting the existing coaxial GCD-3 detector into a reentrant well which puts it within 4 m of the implosion. Reaction history and ablator gamma measurement results from this Phase I are discussed here. These results demonstrate viability for the follow-on Phases of (II) the use of a revolutionary new pulse-dilation photomultiplier tube to improve the effective measurement bandwidth by >10x relative to current PMT technology; and (III) the design of a NIF-specific "Super" GCD which will be informed by the assessment of the radiation background environment within the well described here.

Modulation of Intracellular O2 Concentration in Escherichia coli Strains Using Oxygen Consuming Devices

The use of cell factories for the production of bulk and value-added compounds is nowadays an advantageous alternative to the traditional petrochemical methods. Nevertheless, the efficiency and productivity of several of these processes can improve with the implementation of micro-oxic or anoxic conditions. In the industrial setting, laccases are appealing catalysts that can oxidize a wide range of substrates and reduce O₂ to H₂O. In this work, several laccase-based devices were designed and constructed to modulate the intracellular oxygen concentration in bacterial chassis. These oxygen consuming devices (OCDs) included Escherichia coli's native laccase (CueO) and three variants of this protein obtained by directed evolution. The OCDs were initially characterized in vitro using E. coli DH5α protein extracts and subsequently using extracts obtained from other E. coli strains and in vivo. Upon induction of the OCDs, no major effect on growth was observed in four of the strains tested, and analysis of the cell extract protein profiles revealed increased levels of laccase. Moreover, oxygen consumption associated with the OCDs occurred under all of the conditions tested, but the performance of the devices was shown to be strain-dependent, highlighting the importance of the genetic background even in closely related strains. One of the laccase variants showed 13- and 5-fold increases in oxidase activity and O₂ consumption rate, respectively. Furthermore, it was also possible to demonstrate O₂ consumption in vivo using l-DOPA as the substrate, which represents a proof of concept that these OCDs generate an intracellular oxygen sink, thereby manipulating the redox status of the cells. In addition, the modularity and orthogonality principles used for the development of these devices allow easy reassembly and fine-tuning, foreseeing their introduction into other chassis/systems.

Why Build Whole-Cell Models?

Our ability to build computational models that account for all known gene functions in a cell has increased dramatically. But why build whole-cell models, and how can they best be used? In this forum, we enumerate several areas in which whole-cell modeling can significantly impact research and technology.

Would a two-stage N-removal be a suitable technology to implement at full scale the use of anammox for sewage treatment?

Sewage treatment with anammox could be implemented through a two-step reactor system, where the first reactor would be devoted to partial nitritation. A process design was sketched including control loops. The control strategy regulates the flow-rate of the rich ammonium sidestream produced after dewatering the digested sludge, to keep the ammonium concentration at a set point in the partial nitritation reactor by DOsing the SIde Stream (DOSIS). A second control loop manages the ammonium concentration set point based on the measurement of the total nitrogen in the partial nitritation reactor. A mathematical model was developed to assess the amount of sidestream required. Even in the case of a strong diurnal variability, simulations show how the control strategy is correctly performing, demonstrating the potential of the proposed technology.

An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli

Given the vast behavioral repertoire and biological complexity of even the simplest organisms, accurately predicting phenotypes in novel environments and unveiling their biological organization is a challenging endeavor. Here, we present an integrative modeling methodology that unifies under a common framework the various biological processes and their interactions across multiple layers. We trained this methodology on an extensive normalized compendium for the gram-negative bacterium Escherichia coli, which incorporates gene expression data for genetic and environmental perturbations, transcriptional regulation, signal transduction, and metabolic pathways, as well as growth measurements. Comparison with measured growth and high-throughput data demonstrates the enhanced ability of the integrative model to predict phenotypic outcomes in various environmental and genetic conditions, even in cases where their underlying functions are under-represented in the training set. This work paves the way toward integrative techniques that extract knowledge from a variety of biological data to achieve more than the sum of their parts in the context of prediction, analysis, and redesign of biological systems.

[Surgical treatment of giant congenital melanocytic nevi: a change of aim]

OBJECTIVE

To review the surgical experience in Giant Congenital Melanocytic Nevi (GCMN).

MATERIAL AND METHODS

Review of GCMN cases consulting at the Department of Pediatric Surgery since 1994. Data registered were: year and age at 1st consultation, type of treatment, number of surgical procedures and complications, histology, central nervous system MRI and follow-up.

RESULTS

Eleven patients with GCMN > 10% of body surface consulted at ages ranging from newborn to 8 years. All of them had multiple surgical procedures (2-19), from nevus removal to only biopsies. Eight patients had tissue expansion, completed in 3 of them with skin grafts on dermal substitute. Six patients had complications: 4 expander extrusions, 5 infections, 3 flap necrosis and 1 dehiscence. In 6 children a total or subtotal resection of the nevus was achieved; in 2 the treatment was interrupted, remaining 20% and 50% of the initial nevus; three patients had not had nevus treatment. None of the patients presented cutaneous melanoma; one died from intracranial melanoma; another one has leptomeningeal melanosis. The first 4 patients underwent an average of 16 surgical procedures each, the last 7 patients only 5.

CONCLUSIONS

The aim of GCNM management has changed: GCNM treatment is now surgically conservative. Complete excision is now not the aim when technically unfeasible in few procedures; multiple surgical procedures with poor cosmetical results are not acceptable. The gravity is determined by CNS involvement.

Automated design of bacterial genome sequences

Background

Organisms have evolved ways of regulating transcription to better adapt to varying environments. Could the current functional genomics data and models support the possibility of engineering a genome with completely rearranged gene organization while the cell maintains its behavior under environmental challenges? How would we proceed to design a full nucleotide sequence for such genomes?

Results

As a first step towards answering such questions, recent work showed that it is possible to design alternative transcriptomic models showing the same behavior under environmental variations than the wild-type model. A second step would require providing evidence that it is possible to provide a nucleotide sequence for a genome encoding such transcriptional model. We used computational design techniques to design a rewired global transcriptional regulation of Escherichia coli, yet showing a similar transcriptomic response than the wild-type. Afterwards, we “compiled” the transcriptional networks into nucleotide sequences to obtain the final genome sequence. Our computational evolution procedure ensures that we can maintain the genotype-phenotype mapping during the rewiring of the regulatory network. We found that it is theoretically possible to reorganize E. coli genome into 86% fewer regulated operons. Such refactored genomes are constituted by operons that contain sets of genes sharing around the 60% of their biological functions and, if evolved under highly variable environmental conditions, have regulatory networks, which turn out to respond more than 20% faster to multiple external perturbations.

Conclusions

This work provides the first algorithm for producing a genome sequence encoding a rewired transcriptional regulation with wild-type behavior under alternative environments.

A meta-analysis reveals the commonalities and differences in Arabidopsis thaliana response to different viral pathogens

Understanding the mechanisms by which plants trigger host defenses in response to viruses has been a challenging problem owing to the multiplicity of factors and complexity of interactions involved. The advent of genomic techniques, however, has opened the possibility to grasp a global picture of the interaction. Here, we used Arabidopsis thaliana to identify and compare genes that are differentially regulated upon infection with seven distinct (+)ssRNA and one ssDNA plant viruses. In the first approach, we established lists of genes differentially affected by each virus and compared their involvement in biological functions and metabolic processes. We found that phylogenetically related viruses significantly alter the expression of similar genes and that viruses naturally infecting Brassicaceae display a greater overlap in the plant response. In the second approach, virus-regulated genes were contextualized using models of transcriptional and protein-protein interaction networks of A. thaliana. Our results confirm that host cells undergo significant reprogramming of their transcriptome during infection, which is possibly a central requirement for the mounting of host defenses. We uncovered a general mode of action in which perturbations preferentially affect genes that are highly connected, central and organized in modules.

Fine-tuning tomato agronomic properties by computational genome redesign

Considering cells as biofactories, we aimed to optimize its internal processes by using the same engineering principles that large industries are implementing nowadays: lean manufacturing. We have applied reverse engineering computational methods to transcriptomic, metabolomic and phenomic data obtained from a collection of tomato recombinant inbreed lines to formulate a kinetic and constraint-based model that efficiently describes the cellular metabolism from expression of a minimal core of genes. Based on predicted metabolic profiles, a close association with agronomic and organoleptic properties of the ripe fruit was revealed with high statistical confidence. Inspired in a synthetic biology approach, the model was used for exploring the landscape of all possible local transcriptional changes with the aim of engineering tomato fruits with fine-tuned biotechnological properties. The method was validated by the ability of the proposed genomes, engineered for modified desired agronomic traits, to recapitulate experimental correlations between associated metabolites.

Perspectives on the automatic design of regulatory systems for synthetic biology

Automatic design is based on computational modeling and optimization methods to provide prototype designs to targeted problems in an unsupervised manner. For biological circuits, we need to produce quantitative predictions of cell behavior for a given genotype as consequence of the different molecular interactions. Automatic design techniques aim at solving the inverse problem of finding the sequences of nucleotides that better fit a targeted behavior. In the post-genomic era, our molecular knowledge and modeling capabilities have allowed to start using such methodologies with success. Herein, we describe how the emergence of this new type of tools could enable novel synthetic biology applications. We highlight the essential elements to develop automatic design procedures for synthetic biology pointing out their advantages and bottlenecks. We discuss in detail the experimental difficulties to overcome in the in vivo implementation of designed networks. The use of automatic design to engineer biological networks is starting to emerge as a new technique to perform synthetic biology, which should not be neglected in the future.

Computational design of synthetic regulatory networks from a genetic library to characterize the designability of dynamical behaviors

The engineering of synthetic gene networks has mostly relied on the assembly of few characterized regulatory elements using rational design principles. It is of outmost importance to analyze the scalability and limits of such a design workflow. To analyze the design capabilities of libraries of regulatory elements, we have developed the first automated design approach that combines such elements to search the genotype space associated to a given phenotypic behavior. Herein, we calculated the designability of dynamical functions obtained from circuits assembled with a given genetic library. By designing circuits working as amplitude filters, pulse counters and oscillators, we could infer new mechanisms for such behaviors. We also highlighted the hierarchical design and the optimization of the interface between devices. We dissected the functional diversity of a constrained library and we found that even such libraries can provide a rich variety of behaviors. We also found that intrinsic noise slightly reduces the designability of digital circuits, but it increases the designability of oscillators. Finally, we analyzed the robust design as a strategy to counteract the evolvability and noise in gene expression of the engineered circuits within a cellular background, obtaining mechanisms for robustness through non-linear negative feedback loops.

A systems biology approach to the evolution of plant-virus interactions

Omic approaches to the analysis of plant-virus interactions are becoming increasingly popular. These types of data, in combination with models of interaction networks, will aid in revealing not only host components that are important for the virus life cycle, but also general patterns about the way in which different viruses manipulate host regulation of gene expression for their own benefit and possible mechanisms by which viruses evade host defenses. Here, we review studies identifying host genes regulated by viruses and discuss how these genes integrate in host regulatory and interaction networks, with a particular focus on the physical properties of these networks.

Empirical model and in vivo characterization of the bacterial response to synthetic gene expression show that ribosome allocation limits growth rate

Synthetic biology uses modeling to facilitate the design of new genetic constructions. In particular, it is of utmost importance to model the reaction of the cellular chassis when expressing heterologous systems. We constructed a mathematical model for the response of a bacterial cell chassis under heterologous expression. For this, we relied on previous characterization of the growth-rate dependence on cellular resource availability (in this case, DNA and RNA polymerases and ribosomes). Accordingly, we estimated the maximum capacities of the cell for heterologous expression to be 46% of the total RNA and the 33% of the total protein. To experimentally validate our model, we engineered two genetic constructions that involved the constitutive expression of a fluorescent reporter in a vector with a tunable origin of replication. We performed fluorescent measurements using population and single-cell fluorescent measurements. Our model predicted cell growth for several heterologous constructions under five different culture conditions and various plasmid copy numbers with significant accuracy, and confirmed that ribosomes act as the limiting resource. Our study also confirmed that the bacterial response to synthetic gene expression could be understood in terms of the requirement for cellular resources and could be predicted from relevant cellular parameters.

Optimal viral strategies for bypassing RNA silencing

The RNA silencing pathway constitutes a defence mechanism highly conserved in eukaryotes, especially in plants, where the underlying working principle relies on the repressive action triggered by the intracellular presence of double-stranded RNAs. This immune system performs a post-transcriptional suppression of aberrant mRNAs or viral RNAs by small interfering RNAs (siRNAs) that are directed towards their target in a sequence-specific manner. However, viruses have evolved strategies to escape from silencing surveillance while promoting their own replication. Several viruses encode suppressor proteins that interact with different elements of the RNA silencing pathway and block it. The different suppressors are not phylogenetically nor structurally related and also differ in their mechanism of action. Here, we adopt a model-driven forward-engineering approach to understand the evolution of suppressor proteins and, in particular, why viral suppressors preferentially target some components of the silencing pathway. We analysed three strategies characterized by different design principles: replication in the absence of a suppressor, suppressors targeting the first protein component of the pathway and suppressors targeting the siRNAs. Our results shed light on the question of whether a virus must opt for devoting more time into transcription or into translation and on which would be the optimal step of the silencing pathway to be targeted by suppressors. In addition, we discussed the evolutionary implications of such designing principles.

Robust dynamical pattern formation from a multifunctional minimal genetic circuit

BACKGROUND

A practical problem during the analysis of natural networks is their complexity, thus the use of synthetic circuits would allow to unveil the natural mechanisms of operation. Autocatalytic gene regulatory networks play an important role in shaping the development of multicellular organisms, whereas oscillatory circuits are used to control gene expression under variable environments such as the light-dark cycle.

RESULTS

We propose a new mechanism to generate developmental patterns and oscillations using a minimal number of genes. For this, we design a synthetic gene circuit with an antagonistic self-regulation to study the spatio-temporal control of protein expression. Here, we show that our minimal system can behave as a biological clock or memory, and it exhibites an inherent robustness due to a quorum sensing mechanism. We analyze this property by accounting for molecular noise in an heterogeneous population. We also show how the period of the oscillations is tunable by environmental signals, and we study the bifurcations of the system by constructing different phase diagrams.

CONCLUSIONS

As this minimal circuit is based on a single transcriptional unit, it provides a new mechanism based on post-translational interactions to generate targeted spatio-temporal behavior.

Geochemical and environmental controls on the genesis of soluble efflorescent salts in coastal mine tailings deposits: a discussion based on reactive transport modeling

Water-soluble efflorescent salts often form on tailings in hyperarid climates. Their high solubility together with the high risk of human exposure to heavy metals such as Cu, Ni, Zn, etc., makes this occurrence a serious environmental problem. Understanding their formation (genesis) is therefore key to designing prevention and remediation strategies. A significant amount of these efflorescences has been described on the coastal area of Chañaral (Chile). There, highly soluble salts such as halite (NaCl) and eriochalcite (CuCl(2).2H(2)O) form on 4km(2) of marine shore tailings. Natural occurrence of eriochalcite is rare: its formation requires extreme environmental and geochemical conditions such as high evaporation rate and low relative air humidity, and continuous Cl and Cu supply from groundwater, etc. Its formation was examined by means of reactive transport modeling. A scenario is proposed involving sea water and subsequently a mixture of sea water/freshwater in the groundwater composition in the formation of these efflorescences. The strong competition from other halides (i.e. halite and silvite (KCl)) for the Cl may inhibit the precipitation of eriochalcite. Therefore, the Cl/Na ratio trend >1 is a key parameter in its formation. Cation-exchange between Na(+) and other major ions such as K(+), Ca(2+), Mg(2+) and Cu(2+) in the clay fraction of tailings is proposed to account for realistic Cl/Na ratios. With regard to preventing the formation of eriochalcite, a capillary barrier on the tailings surface is proposed as a suitable alternative. Its efficiency as a barrier is also tested by means of reactive transport models.

Reverse-engineering the Arabidopsis thaliana transcriptional network under changing environmental conditions

An Arabidopsis thaliana transcriptional network reveals regulatory mechanisms for the control of genes related to stress adaptation.

Background

Understanding the molecular mechanisms plants have evolved to adapt their biological activities to a constantly changing environment is an intriguing question and one that requires a systems biology approach. Here we present a network analysis of genome-wide expression data combined with reverse-engineering network modeling to dissect the transcriptional control of Arabidopsis thaliana. The regulatory network is inferred by using an assembly of microarray data containing steady-state RNA expression levels from several growth conditions, developmental stages, biotic and abiotic stresses, and a variety of mutant genotypes.

Results

We show that the A. thaliana regulatory network has the characteristic properties of hierarchical networks. We successfully applied our quantitative network model to predict the full transcriptome of the plant for a set of microarray experiments not included in the training dataset. We also used our model to analyze the robustness in expression levels conferred by network motifs such as the coherent feed-forward loop. In addition, the meta-analysis presented here has allowed us to identify regulatory and robust genetic structures.

Conclusions

These data suggest that A. thaliana has evolved high connectivity in terms of transcriptional regulation among cellular functions involved in response and adaptation to changing environments, while gene networks constitutively expressed or less related to stress response are characterized by a lower connectivity. Taken together, these findings suggest conserved regulatory strategies that have been selected during the evolutionary history of this eukaryote.

Towards the automated engineering of a synthetic genome

The development of the technology to synthesize new genomes and to introduce them into hosts with inactivated wild-type chromosome opens the door to new horizons in synthetic biology. Here it is of outmost importance to harness the ability of using computational design to predict and optimize a synthetic genome before attempting its synthesis. The methodology to computationally design a genome is based on an optimization that computationally mimics genome evolution. The biggest bottleneck lies on the use of an appropriate fitness function. This fitness function, usually cell growth, relies on the ability to quantitatively model the biochemical networks of the cell at the genome scale using parameters inferred from high-throughput data. Computational methods integrating such models in a common multilayer design platform can be used to automatically engineer synthetic genomes under physiological specifications. We describe the current state-of-the-art on automated methods for engineering or re-engineering synthetic genomes. We restrict ourselves to global models of metabolism, transcription and DNA structure. Although we are still far from the de novo computational genome design, it is important to collect all relevant work towards this goal. Finally, we discuss future perspectives about the practicability of an automated methodology for such computational design of synthetic genomes.

Model-based redesign of global transcription regulation

Synthetic biology aims to the design or redesign of biological systems. In particular, one possible goal could be the rewiring of the transcription regulation network by exchanging the endogenous promoters. To achieve this objective, we have adapted current methods to the inference of a model based on ordinary differential equations that is able to predict the network response after a major change in its topology. Our procedure utilizes microarray data for training. We have experimentally validated our inferred global regulatory model in Escherichia coli by predicting transcriptomic profiles under new perturbations. We have also tested our methodology in silico by providing accurate predictions of the underlying networks from expression data generated with artificial genomes. In addition, we have shown the predictive power of our methodology by obtaining the gene profile in experimental redesigns of the E. coli genome, where rewiring the transcriptional network by means of knockouts of master regulators or by upregulating transcription factors controlled by different promoters. Our approach is compatible with most network inference methods, allowing to explore computationally future genome-wide redesign experiments in synthetic biology.

DESHARKY: automatic design of metabolic pathways for optimal cell growth

MOTIVATION

The biological solution for synthesis or remediation of organic compounds using living organisms, particularly bacteria and yeast, has been promoted because of the cost reduction with respect to the non-living chemical approach. In that way, computational frameworks can profit from the previous knowledge stored in large databases of compounds, enzymes and reactions. In addition, the cell behavior can be studied by modeling the cellular context.

RESULTS

We have implemented a Monte Carlo algorithm (DESHARKY) that finds a metabolic pathway from a target compound by exploring a database of enzymatic reactions. DESHARKY outputs a biochemical route to the host metabolism together with its impact in the cellular context by using mathematical models of the cell resources and metabolism. Furthermore, we provide the sequence of amino acids for the enzymes involved in the route closest phylogenetically to the considered organism. We provide examples of designed metabolic pathways with their genetic load characterizations. Here, we have used Escherichia coli as host organism. In addition, our bioinformatic tool can be applied for biodegradation or biosynthesis and its performance scales with the database size.

AVAILABILITY

Software, a tutorial and examples are freely available and open source at http://soft.synth-bio.org/desharky.html

Changes in the gene expression profile of Arabidopsis thaliana after infection with Tobacco etch virus

BACKGROUND

Tobacco etch potyvirus (TEV) has been extensively used as model system for the study of positive-sense RNA virus infecting plants. TEV ability to infect Arabidopsis thaliana varies among ecotypes. In this study, changes in gene expression of A. thaliana ecotype Ler infected with TEV have been explored using long-oligonucleotide arrays. A. thaliana Ler is a susceptible host that allows systemic movement, although the viral load is low and syndrome induced ranges from asymptomatic to mild. Gene expression profiles were monitored in whole plants 21 days post-inoculation (dpi). Microarrays contained 26,173 protein-coding genes and 87 miRNAs.

RESULTS

Expression analysis identified 1727 genes that displayed significant and consistent changes in expression levels either up or down, in infected plants. Identified TEV-responsive genes encode a diverse array of functional categories that include responses to biotic (such as the systemic acquired resistance pathway and hypersensitive responses) and abiotic stresses (droughtness, salinity, temperature, and wounding). The expression of many different transcription factors was also significantly affected, including members of the R2R3-MYB family and ABA-inducible TFs. In concordance with several other plant and animal viruses, the expression of heat-shock proteins (HSP) was also increased. Finally, we have associated functional GO categories with KEGG biochemical pathways, and found that many of the altered biological functions are controlled by changes in basal metabolism.

CONCLUSION

TEV infection significantly impacts a wide array of cellular processes, in particular, stress-response pathways, including the systemic acquired resistance and hypersensitive responses. However, many of the observed alterations may represent a global response to viral infection rather than being specific of TEV.

Asmparts: assembly of biological model parts

We propose a new computational tool to produce models of biological systems by assembling models from biological parts. Our software not only takes advantage of modularity, but it also enforces standardisation in part characterisation by considering a model of each part. We have used model parts in SBML to design transcriptional networks. Our software is open source, it works in linux and windows platforms, and it could be used to automatically produce models in a server. Our tool not only facilitates model design, but it will also help to promote the establishment of a registry of model parts.

Competitive technology approaches for electronic hybridization detection in a microsystem with microfluidics for diagnosis genetic tests

This paper is presenting competitive technology alternatives for the electronic hybridization detection in a microsystem with microfluidics for diagnosis genetic tests that are carried out by two competitive research projects. The technologies developed are a photosensor, a capacitive sensor and an optical real-time affinity biosensor. The performance of those biosensors will be evaluated but also their manufacturability and cost will define the appropriateness of each one for industrialization and their integration on a microsystem for diagnosis genetic testing.

Estimation of recharge from floods in disconnected stream-aquifer systems

Stream-aquifer interaction has been the subject of much research for cases of good hydraulic connection (continuous saturated zone) between a river and an aquifer. Under these conditions, floods do not represent a very large net input to the aquifer because most of the water that enters the aquifer during the flood returns to the river when its stage recedes. The situation is different in disconnected stream-aquifer systems, where the streambed lies above the water level in the aquifer, thus preventing return flow from the aquifer. Under these conditions, floods may represent large, but hard to quantify, water inputs. Here, we present a methodology to estimate recharge from floods for disconnected stream-aquifer systems. Recharge is estimated as the product of a flood time function (dependent on the streamflow) and an unknown factor, which is obtained from calibrating a ground water flow model to aquifer heads. The approach can also benefit from concentration data, which can be very informative when river water concentrations vary over time. This methodology is applied to a field situation where recharge from river flooding is found to amount to nearly 15 million m(3)/year on the average, which represents 40% of the total aquifer inputs. Recharge from flooding helps explain major head recoveries, suggesting that basin water management programs should allow some floods to occur.

Genetdes: automatic design of transcriptional networks

MOTIVATION

The rational design of biological networks with prescribed functions is limited to gene circuits of a few genes. Larger networks involve complex interactions with many parameters and the use of automated computational tools can be very valuable. We propose a new tool to design transcriptional networks with targeted behavior that could be used to better understand the design principles of genetic circuits.

RESULTS

We have implemented a Simulated Annealing optimization algorithm that explores throughout the space of transcription networks to obtain a specific behavior. The software outputs a transcriptional network with all the corresponding kinetic parameters in SBML format. We provide examples of transcriptional circuits with logical and oscillatory behaviors. Our tool can also be applied to design networks with multiple external input and output genes.

AVAILABILITY

The software, a tutorial manual, parameter sets and examples are freely available at http://synth-bio.yi.org/genetdes.html.

Model-based design of a control strategy for optimal start-up of a high-strength nitrification system

The objective of this study was to define an automatic control loop for the start-up of a high-strength nitrification system to achieve a rich nitrifying biomass from a poor nitrifying sludge by means of simulation tools. The used model considered the nitrification as a two-step model with substrate and non-competitive inhibitions. Two control strategies (on-off controller and proportional-integral (PI) controller) were designed, simulated and compared. The measured variable in the control loops was the sum of ammonium and nitrite concentrations in the effluent and the manipulated variable was the inflow. The objective in the optimisation of both controllers was to increase the inflow of the system as fast as possible without exceeding the maximum ammonium and nitrite concentrations allowed in the effluent. The optimised controllers parameters were used to simulate a 40 days start-up. The results obtained with both strategies were similar, although, the best strategy was the PI controller since it was less oscillatory and the biomass growth was slightly faster.

Phenol wastewater remediation: advanced oxidation processes coupled to a biological treatment

Nowadays, there are increasingly stringent regulations requiring more and more treatment of industrial effluents to generate product waters which could be easily reused or disposed of to the environment without any harmful effects. Therefore, different advanced oxidation processes were investigated as suitable precursors for the biological treatment of industrial effluents containing phenol. Wet air oxidation and Fenton process were tested batch wise, while catalytic wet air oxidation and H2O2-promoted catalytic wet air oxidation processes were studied in a trickle bed reactor, the last two using over activated carbon as catalyst. Effluent characterisation was made by means of substrate conversion (using high liquid performance chromatography), chemical oxygen demand and total organic carbon. Biodegradation parameters (i.e. maximum oxygen uptake rate and oxygen consumption) were obtained from respirometric tests using activated sludge from an urban biological wastewater treatment plant (WWTP). The main goal was to find the proper conditions in terms of biodegradability enhancement, so that these phenolic effluents could be successfully treated in an urban biological WWTP. Results show promising research ways for the development of efficient coupled processes for the treatment of wastewater containing toxic or biologically non-degradable compounds.

Feasibility of pegfilgrastim as haematopoietic support for dose-dense every-2-week adjuvant chemotherapy in breast cancer

18606

Background: Dose-dense sequential chemotherapy has been safety supported with Filgrastim (F). Pegfilgrastim (PEGF) is a pegylated recombinant human granulocyte colony-stimulating factor (G-CSF) that has a long half-life, a fact that facilitates a less frequent dosing. Its safety and efficacy has been established in 21- and 28-days schedules. Methods: We have performed a retrospective analysis of medical records of 2 cohort of patients (n=38) treated at our institution between December 2003 and November 2005. All patients received Adriamicin 60 mg/m2 plus Ciclophosphamide 600 mg/m2 q2w for 4 cycles followed by Paclitaxel 175 mg/m2 q2w for 4 cycles. As G-CSF support, in Cohort A (n=29) PEGF was administered 6 mg on day 2 of each cycle and in Cohort B (n=9) F days 3 to 10 at 5 μg/kg. The primary end point was to explore the feasibility and safety in terms of febrile neutropenia (FN) events, number of treatment delays (TD), incidence of neutropenia grade 3 (NPG3) and 4 (NPG4) and mean absolute neutrophil count (ANC) on day 14 of cycle 1 to 7 for both groups. Indirect comparisons have been performed. Results: Patients characteristics in both cohorts were well balanced, except for age in cohort A compared with cohort B (44,89 versus 52,5, p = 0,02). FN events and TD were increased in cohort B compared with cohort A (22% versus 0%, p=0.051, both comparisons). No statistically significant difference in number of episodes of NPG3 and NPG4 was observed. Median ANC on day 14 for each treatment cycle was significantly greater for Cohort A than Cohort B, except for cycle 6. Conclusions: PEGF is very safe and efficacy in patients treated with dose-dense sequential adjuvant chemotherapy for breast cancer. It could be even more efficient than F in preventing febrile neutropenia events.

[Table: see text]

Improving the start-up of an EBPR system using OUR to control the aerobic phase length: a simulation study

The enhanced biological phosphorus removal (EBPR) process is based on enriching the sludge with polyphosphate accumulating organisms (PAO) which are scarce in conventional non-EBPR wastewater treatment plant sludge. Hence, the start-up of EBPR systems (i.e. enriching the sludge with PAO) can be very slow and complex. A simulation study of a possible improvement of the start-up of an EBPR system in a sequencing batch reactor is presented in this work. The improvement is based on reducing the length of the aerobic phase so that it coincides with the depletion of orthophosphate from the medium. This improvement, though verified by simulation to be very successful, requires a good on-line orthophosphate sensor. To avoid this technical limitation, a link between oxygen uptake rate (OUR) measurements and orthophosphate presence is proposed. This link allows the control of the aerobic phase length with OUR as a measured variable and, consequently, a considerable improvement with respect to the conventional fixed aerobic phase length operation. An improvement of 95% in the ratio of PAO to heterotrophs and an increase of 30% in the final amount of PAO in sludge is achieved with this control strategy. The kinetic mod for simulations was a modification of the Activated Sludge Model 2d.

Observation and mathematical description of the acceleration phenomenon in batch respirograms associated with ammonium oxidation

Two-step nitrification models are generally calibrated using short-term respirometric batch experiments. Important discrepancies appear between model predictions and experimental observations just after the pulse addition since a fast transient in the OUR profile is experimentally observed. Acceleration of the OUR appears ongoing between the substrate addition and attainment of the maximum OUR value. Among the several phenomena that could contribute to this observation, the most probable cause is the limitation of reducing equivalents required for maximal ammonia monooxygenase activity at the time of substrate addition. Ignoring acceleration would result in large parameter estimation errors from respirometric batch experiments. This work proposes a simple methodology to successfully describe (not to explain) the acceleration phenomenon estimating only two parameters. This methodology consists of introducing a Gaussian-like expression in the model.

Limitations of ASM1 and ASM3: a comparison based on batch oxygen uptake rate profiles from different full-scale wastewater treatment plants

The two most popular models for the description of the biological COD removal are ASM1 and ASM3. However, some numerical inconsistencies arise when using these models to interpret the data obtained in short-term respirometric batch experiments. In this study, both models are fitted to four different respirometric batch profiles obtained with biomass from different WWTP. The parameter estimation results and the practical (local) identifiability are analysed, and the limitations of both models are discussed. The growth yield obtained by fitting ASM1 to the short-term respirometric batch profiles is higher than the default one, as well as the storage yield obtained by fitting ASM3 is lower than the default one. Based on these values, possible improvements to the modelling of the biological COD removal, such as the inclusion of simultaneous growth and storage on external substrate, are proposed.