The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942.

Background: Nowadays, the reconstruction of genome scale metabolic models is a non-automatized and interactive process based on decision taking. This lengthy process usually requires a full year of one person's work in order to satisfactory collect, analyze and validate the list of all metabolic reactions present in a specific organism. In order to write this list, one manually has to go through a huge amount of genomic, metabolomic and physiological information. Currently, there is no optimal algorithm that allows one to automatically go through all this information and generate the models taking into account probabilistic criteria of unicity and completeness that a biologist would consider.Results: This work presents the automation of a methodology for the reconstruction of genome scale metabolic models for any organism. The methodology that follows is the automatized version of the steps implemented manually for the reconstruction of the genome scale metabolic model of a photosynthetic organism, Synechocystis sp. * daniel.gamermann@ucv.es PCC6803. The steps for the reconstruction are implemented in a computational platform (COPABI) that generates the models from the probabilistic algorithms that have been developed.Conclusions: For validation of the developed algorithm robustness, the metabolic models of several organisms generated by the platform have been studied together with published models that have been manually curated. Network properties of the models like connectivity and average shortest mean path of the different models have been compared and analyzed.

AIM:In the present study, antibody and peripheral b l o o d m o n o n u c l e a r c e l l s ( P B M C ) p r o l i fe ra t i ve responses against hepatitis C virus (HCV) antigens were evaluated in HCV chronically infected patients. ME THOD S : Pa i r e d s e r u m a n d P B M C s a m p l e s were taken six months apart from 34 individuals, either treated or not, and tested by enzyme-linked immunosorbent assay (ELISA) and carboxyfluorescein succinimidyl ester staining. RESULTS: Over 70% of the patients showed specific IgG and IgM against capsid, E1 and NS3, while HVR-1 was recognized by half of the patients. An increase in the levels of the anti-capsid IgM (P = 0.027) and IgG (P = 0.0006) was observed in six-month samples, compared to baseline. Similarly, a significantly higher percent of patients had detectable IgA reactivity to capsid (P = 0.017) and NS3 (P = 0.005) after six months, compared to baseline. Particularly, IgA against structural antigens positively correlated with hepatic damage (P = 0.036). IgG subclasses evaluation against capsid and NS3 revealed a positive recognition mediated by IgG1 in more than 80% of the individuals. On the contrary, less than 30% of the patients showed a positive proliferative response either of CD4+ or CD8+ T cells, being the capsid poorly recognized. CONCLUSION: These results confirm that while the cellular immune response is narrow and weak, a broad and vigorous humoral response occurs in HCV chronic infection. The observed correlation between IgA and hepatic damage may have diagnostic significance, although it warrants further confirmation.

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In this contribution, a design of a synthetic calibration genetic circuit to characterize the relative strength of different sensing promoters is proposed and its specifications and performance are analyzed via an effective mathematical model. Our calibrator device possesses certain novel and useful features like modularity (and thus the possibility of being used in many different biological contexts), simplicity, being based on a single cell, high sensitivity and fast response. To uncover the critical model parameters and the corresponding parameter domain at which the calibrator performance will be optimal, a sensitivity analysis of the model parameters was carried out over a given range of sensing protein concentrations (acting as input). Our analysis suggests that the half saturation constants for repression, sensing and difference in binding cooperativity (Hill coefficients) for repression are the key to the performance of the proposed device. They furthermore are determinant for the sensing speed of the device, showing that it is possible to produce deEmail address: daniel.gamermann@ucv.es (D. Gamermann) Preprint submitted to ElsevierJune 5, 2018 tectable differences in the repression protein concentrations and in turn in the corresponding fluorescence in less than two hours. This analysis paves the way for the design, experimental construction and validation of a new family of functional genetic circuits for the purpose of calibrating promoters.