Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.

Protein homology reveals new targets for bioactive small molecules.

MOTIVATION: The functional impact of small molecules is increasingly being assessed in different eukaryotic species through large-scale phenotypic screening initiatives. Identifying the targets of these molecules is crucial to mechanistically understand their function and uncover new therapeutically relevant modes of action. However, despite extensive work carried out in model organisms and human, it is still unclear to what extent one can use information obtained in one species to make predictions in other species. RESULTS: Here, for the first time, we explore and validate at a large scale the use of protein homology relationships to predict the targets of small molecules across different species. Our results show that exploiting target homology can significantly improve the predictions, especially for molecules experimentally tested in other species. Interestingly, when considering separately orthology and paralogy relationships, we observe that mapping small molecule interactions among orthologs improves prediction accuracy, while including paralogs does not improve and even sometimes worsens the prediction accuracy. Overall, our results provide a novel approach to integrate chemical screening results across multiple species and highlight the promises and remaining challenges of using protein homology for small molecule target identification. AVAILABILITY AND IMPLEMENTATION: Homology-based predictions can be tested on our website http://www.swisstargetprediction.ch. CONTACT: david.gfeller@unil.ch or vincent.zoete@isb-sib.ch. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Cardiac cell fate control by the imidazoline I1 receptor/nischarin : application in cardiac pathology

La moxonidine, un médicament antihypertenseur sympatholytique de type imidazolinique, agit au niveau de la médulla du tronc cérébral pour diminuer la pression artérielle, suite à l’activation sélective du récepteur aux imidazolines I1 (récepteur I1, aussi nommé nischarine). Traitement avec de la moxonidine prévient le développement de l’hypertrophie du ventricule gauche chez des rats hypertendus (SHR), associé à une diminution de la synthèse et une élévation transitoire de la fragmentation d’ADN, des effets antiprolifératifs et apoptotiques. Ces effets se présentent probablement chez les fibroblastes, car l’apoptose des cardiomyocytes pourrait détériorer la fonction cardiaque. Ces effets apparaissent aussi avec des doses non hypotensives de moxonidine, suggérant l’existence d’effets cardiaques directes. Le récepteur I1 se trouvé aussi dans les tissus cardiaques; son activation ex vivo par la moxonidine stimule la libération de l’ANP, ce qui montre que les récepteurs I1 cardiaques sont fonctionnels malgré l’absence de stimulation centrale. Sur la base de ces informations, en plus du i) rôle des peptides natriurétiques comme inhibiteurs de l’apoptose cardiaque et ii) des études qui lient le récepteur I1 avec la maintenance de la matrix extracellulaire, on propose que, à part les effets sympatholytiques centrales, les récepteurs I1 cardiaques peuvent contrôler la croissance-mort cellulaire. L’activation du récepteur I1 peut retarder la progression des cardiopathies vers la défaillance cardiaque, en inhibant des signaux mal adaptatifs de prolifération et apoptose. Des études ont été effectuées pour : 1. Explorer les effets in vivo sur la structure et la fonction cardiaque suite au traitement avec moxonidine chez le SHR et le hamster cardiomyopathique. 2. Définir les voies de signalisation impliquées dans les changements secondaires au traitement avec moxonidine, spécifiquement sur les marqueurs inflammatoires et les voies de signalisation régulant la croissance et la survie cellulaire (MAPK et Akt). 3. Explorer les effets in vitro de la surexpression et l’activation du récepteur I1 sur la survie cellulaire dans des cellules HEK293. 4. Rechercher la localisation, régulation et implication dans la croissance-mort cellulaire du récepteur I1 in vitro (cardiomyocytes et fibroblastes), en réponse aux stimuli associés au remodelage cardiaque : norépinephrine, cytokines (IL-1β, TNF-α) et oxydants (H2O2). Nos études démontrent que la moxonidine, en doses hypotensives et non-hypotensives, améliore la structure et la performance cardiaque chez le SHR par des mécanismes impliquant l’inhibition des cytokines et des voies de signalisation p38 MAPK et Akt. Chez le hamster cardiomyopathique, la moxonidine améliore la fonction cardiaque, module la réponse inflammatoire/anti-inflammatoire et atténue la mort cellulaire et la fibrose cardiaque. Les cellules HEK293 surexprimant la nischarine survivent et prolifèrent plus en réponse à la moxonidine; cet effet est associé à l’inhibition des voies ERK, JNK et p38 MAPK. La surexpression de la nischarine protège aussi de la mort cellulaire induite par le TNF-α, l’IL-1β et le H2O2. En outre, le récepteur I1 s’exprime dans les cardiomyocytes et fibroblastes, son activation inhibe la mort des cardiomyocytes et la prolifération des fibroblastes induite par la norépinephrine, par des effets différentiels sur les MAPK et l’Akt. Dans des conditions inflammatoires, la moxonidine/récepteur aux imidazolines I1 protège les cardiomyocytes et facilite l’élimination des myofibroblastes par des effets contraires sur JNK, p38 MAPK et iNOS. Ces études démontrent le potentiel du récepteur I1/nischarine comme cible anti-hypertrophique et anti-fibrose à niveau cardiaque. L’identification des mécanismes cardioprotecteurs de la nischarine peut amener au développement des traitements basés sur la surexpression de la nischarine chez des patients avec hypertrophie ventriculaire. Finalement, même si l’effet antihypertenseur des agonistes du récepteur I1 centraux est salutaire, le développement de nouveaux agonistes cardiosélectifs du récepteur I1 pourrait donner des bénéfices additionnels chez des patients non hypertendus.

Strategies for Inverse Profiling of Two Dimensional Dielectric Scatterers Using Electromagnetic Illumination

Electromagnetic tomography has been applied to problems in nondestructive evolution, ground-penetrating radar, synthetic aperture radar, target identification, electrical well logging, medical imaging etc. The problem of electromagnetic tomography involves the estimation of cross sectional distribution dielectric permittivity, conductivity etc based on measurement of the scattered fields. The inverse scattering problem of electromagnetic imaging is highly non linear and ill posed, and is liable to get trapped in local minima. The iterative solution techniques employed for computing the inverse scattering problem of electromagnetic imaging are highly computation intensive. Thus the solution to electromagnetic imaging problem is beset with convergence and computational issues. The attempt of this thesis is to develop methods suitable for improving the convergence and reduce the total computations for tomographic imaging of two dimensional dielectric cylinders illuminated by TM polarized waves, where the scattering problem is defmed using scalar equations. A multi resolution frequency hopping approach was proposed as opposed to the conventional frequency hopping approach employed to image large inhomogeneous scatterers. The strategy was tested on both synthetic and experimental data and gave results that were better localized and also accelerated the iterative procedure employed for the imaging. A Degree of Symmetry formulation was introduced to locate the scatterer in the investigation domain when the scatterer cross section was circular. The investigation domain could thus be reduced which reduced the degrees of freedom of the inverse scattering process. Thus the entire measured scattered data was available for the optimization of fewer numbers of pixels. This resulted in better and more robust reconstructions of the scatterer cross sectional profile. The Degree of Symmetry formulation could also be applied to the practical problem of limited angle tomography, as in the case of a buried pipeline, where the ill posedness is much larger. The formulation was also tested using experimental data generated from an experimental setup that was designed. The experimental results confirmed the practical applicability of the formulation.

Integrative views on dual-task costs

In this paper, we introduce a special issue about unique and shared mechanisms underlying the performance limitations observed in dual tasks. In particular, the relationship between task-switching costs, the attentional-blink effect, and the psychological refractory period effect is reviewed. These costs are traditionally attributed to fixed and unique capacity limitations for task set reconfiguration, target identification, and response selection, respectively However, we argue that more global attentional processes play a role that cuts across these paradigms. This is reason for a more paradigm-independent approach to processing limitations in dual tasks.

Echinococcus metacestodes as laboratory models for the screening of drugs against cestodes and trematodes

Among the cestodes, Echinococcus granulosus, Echinococcus multilocularis and Taenia solium represent the most dangerous parasites. Their larval stages cause the diseases cystic echinococcosis (CE), alveolar echinococcosis (AE) and cysticercosis, respectively, which exhibit considerable medical and veterinary health concerns with a profound economic impact. Others caused by other cestodes, such as species of the genera Mesocestoides and Hymenolepis, are relatively rare in humans. In this review, we will focus on E. granulosus and E. multilocularis metacestode laboratory models and will review the use of these models in the search for novel drugs that could be employed for chemotherapeutic treatment of echinococcosis. Clearly, improved therapeutic drugs are needed for the treatment of AE and CE, and this can only be achieved through the development of medium-to-high throughput screening approaches. The most recent achievements in the in vitro culture and genetic manipulation of E. multilocularis cells and metacestodes, and the accessability of the E. multilocularis genome and EST sequence information, have rendered the E. multilocularis model uniquely suited for studies on drug-efficacy and drug target identification. This could lead to the development of novel compounds for the use in chemotherapy against echinococcosis, and possibly against diseases caused by other cestodes, and potentially also trematodes.

Application of MFBD Algorithms to Image Reconstruction Under Anisoplanatic Conditions

All optical systems that operate in or through the atmosphere suffer from turbulence induced image blur. Both military and civilian surveillance, gun-sighting, and target identification systems are interested in terrestrial imaging over very long horizontal paths, but atmospheric turbulence can blur the resulting images beyond usefulness. My dissertation explores the performance of a multi-frame-blind-deconvolution technique applied under anisoplanatic conditions for both Gaussian and Poisson noise model assumptions. The technique is evaluated for use in reconstructing images of scenes corrupted by turbulence in long horizontal-path imaging scenarios and compared to other speckle imaging techniques. Performance is evaluated via the reconstruction of a common object from three sets of simulated turbulence degraded imagery representing low, moderate and severe turbulence conditions. Each set consisted of 1000 simulated, turbulence degraded images. The MSE performance of the estimator is evaluated as a function of the number of images, and the number of Zernike polynomial terms used to characterize the point spread function. I will compare the mean-square-error (MSE) performance of speckle imaging methods and a maximum-likelihood, multi-frame blind deconvolution (MFBD) method applied to long-path horizontal imaging scenarios. Both methods are used to reconstruct a scene from simulated imagery featuring anisoplanatic turbulence induced aberrations. This comparison is performed over three sets of 1000 simulated images each for low, moderate and severe turbulence-induced image degradation. The comparison shows that speckle-imaging techniques reduce the MSE 46 percent, 42 percent and 47 percent on average for low, moderate, and severe cases, respectively using 15 input frames under daytime conditions and moderate frame rates. Similarly, the MFBD method provides, 40 percent, 29 percent, and 36 percent improvements in MSE on average under the same conditions. The comparison is repeated under low light conditions (less than 100 photons per pixel) where improvements of 39 percent, 29 percent and 27 percent are available using speckle imaging methods and 25 input frames and 38 percent, 34 percent and 33 percent respectively for the MFBD method and 150 input frames. The MFBD estimator is applied to three sets of field data and the results presented. Finally, a combined Bispectrum-MFBD Hybrid estimator is proposed and investigated. This technique consistently provides a lower MSE and smaller variance in the estimate under all three simulated turbulence conditions.

Cue salience in multiple cue attentional capture

The predominant use of single element cues in visual attentional capture research motivated examination using dual capture cues. Participants in these studies viewed computer screens briefly displaying sequences of feature-defined positional cues and targets, with target identification response time recorded. Five initial experiments utilising the features of colour (purple) and intensity (bold font), and reported at EPC 2005, revealed contingent capture influences and suggested capture by colour cues may be more powerful than single cue literature has indicated. Three follow-up experiments manipulated displays and defining features to see if the conclusions remained. Experiments 6 and 7 investigated whether target identification in the initial series was based on a featural or singleton search. Experiment 8 then tested "onset' versus "purple" under the condition of specific attentional set, a featural change that appeared to remove purple colour dominance evidenced in the initial experimental series. Overall, outcomes of both experimental series suggest strong salience involvement with overtones of contingent capture for specific featural selections. The novel multi-cue approach revealed the significance of relative salience within these selections.

Application of genomics, proteomics and metabolomics in drug discovery, development and clinic

Genomics, proteomics and metabolomics are three areas that are routinely applied throughout the drug-development process as well as after a product enters the market. This review discusses all three 'omics, reporting on the key applications, techniques, recent advances and expectations of each. Genomics, mainly through the use of novel and next-generation sequencing techniques, has advanced areas of drug discovery and development through the comparative assessment of normal and diseased-state tissues, transcription and/or expression profiling, side-effect profiling, pharmacogenomics and the identification of biomarkers. Proteomics, through techniques including isotope coded affinity tags, stable isotopic labeling by amino acids in cell culture, isobaric tags for relative and absolute quantification, multidirectional protein identification technology, activity-based probes, protein/peptide arrays, phage displays and two-hybrid systems is utilized in multiple areas through the drug development pipeline including target and lead identification, compound optimization, throughout the clinical trials process and after market analysis. Metabolomics, although the most recent and least developed of the three 'omics considered in this review, provides a significant contribution to drug development through systems biology approaches. Already implemented to some degree in the drug-discovery industry and used in applications spanning target identification through to toxicological analysis, metabolic network understanding is essential in generating future discoveries.

Application of genomics, proteomics and metabolomics in drug discovery, development and clinic

Genomics, proteomics and metabolomics are three areas that are routinely applied throughout the drug-development process as well as after a product enters the market. This review discusses all three 'omics, reporting on the key applications, techniques, recent advances and expectations of each. Genomics, mainly through the use of novel and next-generation sequencing techniques, has advanced areas of drug discovery and development through the comparative assessment of normal and diseased-state tissues, transcription and/or expression profiling, side-effect profiling, pharmacogenomics and the identification of biomarkers. Proteomics, through techniques including isotope coded affinity tags, stable isotopic labeling by amino acids in cell culture, isobaric tags for relative and absolute quantification, multidirectional protein identification technology, activity-based probes, protein/peptide arrays, phage displays and two-hybrid systems is utilized in multiple areas through the drug development pipeline including target and lead identification, compound optimization, throughout the clinical trials process and after market analysis. Metabolomics, although the most recent and least developed of the three 'omics considered in this review, provides a significant contribution to drug development through systems biology approaches. Already implemented to some degree in the drug-discovery industry and used in applications spanning target identification through to toxicological analysis, metabolic network understanding is essential in generating future discoveries.

Classification of Southern Ocean krill and icefish echoes using random forests

Acknowledgements The authors thank the crews, fishers, and scientists who conducted the various surveys from which data were obtained. This work was supported by the Government of South Georgia and South Sandwich Islands. Additional logistical support provided by The South Atlantic Environmental Research Institute, with thanks to Paul Brickle. PF receives funding from the MASTS pooling initiative (TheMarine Alliance for Science and Technology for Scotland), and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. SF is funded by the Natural Environment Research Council, and data were provided from the British Antarctic Survey Ecosystems Long-term Monitoring and Surveys programme as part of the BAS Polar Science for Planet Earth Programme. The authors also thank the anonymous referees for their helpful suggestions on an earlier version of this manuscript.

Applications of network-based approaches in drug research

Recent research trends in computer-aided drug design have shown an increasing interest towards the implementation of advanced approaches able to deal with large amount of data. This demand arose from the awareness of the complexity of biological systems and from the availability of data provided by high-throughput technologies. As a consequence, drug research has embraced this paradigm shift exploiting approaches such as that based on networks. Indeed, the process of drug discovery can benefit from the implementation of network-based methods at different steps from target identification to drug repurposing. From this broad range of opportunities, this thesis is focused on three main topics: (i) chemical space networks (CSNs), which are designed to represent and characterize bioactive compound data sets; (ii) drug-target interactions (DTIs) prediction through a network-based algorithm that predicts missing links; (iii) COVID-19 drug research which was explored implementing COVIDrugNet, a network-based tool for COVID-19 related drugs. The main highlight emerged from this thesis is that network-based approaches can be considered useful methodologies to tackle different issues in drug research. In detail, CSNs are valuable coordinate-free, graphically accessible representations of structure-activity relationships of bioactive compounds data sets especially for medium-large libraries of molecules. DTIs prediction through the random walk with restart algorithm on heterogeneous networks can be a helpful method for target identification. COVIDrugNet is an example of the usefulness of network-based approaches for studying drugs related to a specific condition, i.e., COVID-19, and the same ‘systems-based’ approaches can be used for other diseases. To conclude, network-based tools are proving to be suitable in many applications in drug research and provide the opportunity to model and analyze diverse drug-related data sets, even large ones, also integrating different multi-domain information.

Identification Of Target Genes Using Gene Expression Profile Of Granulocytes From Patients With Chronic Myeloid Leukemia Treated With Tyrosine Kinase Inhibitors.

Differential gene expression analysis by suppression subtractive hybridization with correlation to the metabolic pathways involved in chronic myeloid leukemia (CML) may provide a new insight into the pathogenesis of CML. Among the overexpressed genes found in CML at diagnosis are SEPT5, RUNX1, MIER1, KPNA6 and FLT3, while PAN3, TOB1 and ITCH were decreased when compared to healthy volunteers. Some genes were identified and involved in CML for the first time, including TOB1, which showed a low expression in patients with CML during tyrosine kinase inhibitor treatment with no complete cytogenetic response. In agreement, reduced expression of TOB1 was also observed in resistant patients with CML compared to responsive patients. This might be related to the deregulation of apoptosis and the signaling pathway leading to resistance. Most of the identified genes were related to the regulation of nuclear factor κB (NF-κB), AKT, interferon and interleukin-4 (IL-4) in healthy cells. The results of this study combined with literature data show specific gene pathways that might be explored as markers to assess the evolution and prognosis of CML as well as identify new therapeutic targets.

Identification and validation of candidate Myb target genes

While a considerable number of candidate Myb target genes have been reported to date, most of these are likely to play little or no role in transformation by myb oncogenes. Here we have used a conditionally myb-transformed myeloid cell line (ERMYB) to further examine Myb regulation of one candidate target gene-c-myc-that has the potential to affect cell proliferation. It was found that the major influence on c-myc expression was the presence of cytokine (GM-CSF) rather than Myb activity. We also describe the application of PCR-based subtractive hybridization and low-density cDNA array screening, in conjunction with the ERMYB line, to the identification of additional Myb target genes. Preliminary identification of a number of candidates is reported; these include myeloperoxidase, which is known to have essential Myb-binding sites in its regulatory region. (C) 2001 Academic Press.