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First-principle metabolic modelling holds potential for designing microbial chassis that are resilient against phenotype reversal due to adaptive mutations. Yet, the theory of model-based chassis design has rarely been put to rigorous experimental test. Here, we report the development of Saccharomyces cerevisiae chassis strains for dicarboxylic acid production using genome-scale metabolic modelling. The chassis strains, albeit geared for higher flux towards succinate, fumarate and malate, do not appreciably secrete these metabolites. As predicted by the model, introducing product-specific TCA cycle disruptions resulted in the secretion of the corresponding acid. Adaptive laboratory evolution further improved production of succinate and fumarate, demonstrating the evolutionary robustness of the engineered cells. In the case of malate, multi-omics analysis revealed a flux bypass at peroxisomal malate dehydrogenase that was missing in the yeast metabolic model. In all three cases, flux balance analysis integrating transcriptomics, proteomics and metabolomics data confirmed the flux re-routing predicted by the model. Taken together, our modelling and experimental results have implications for the computer-aided design of microbial cell factories., We would like to acknowledge the support of R. Mattel and F. Stein from the Proteomics Core Facility and the Genomics Core Facility at the European Molecular Biology Laboratory (EMBL Heidelberg, Germany). This study was supported by national funds through FCT/MCTES (Portugal, Ref. ERA-IB-2/0003/2013) and BMBF (Germany, Grant number: 031A343A, Ref. ERA-IB-2/0003/2013). The Portuguese Foundation for Science and Technology (FCT) supported HL through grant ref. PD/BD/52336/2013. FCT also supported this study under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and through the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462). Open Access funding enabled and organized by Projekt DEAL., info:eu-repo/semantics/publishedVersion

In the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behavior at the tissue and multi-tissue level under different environmental conditions. Quercus suber, also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871), the first of a woody plant. The metabolic model comprises 7871 genes, 6231 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen, with specific biomass compositions. The tissue-specific models were merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyze the pathways associated with the synthesis of suberin monomers. Nevertheless, the models developed in this work can provide insights into other aspects of the metabolism of Q. suber, such as its secondary metabolism and cork formation.

Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.procbio.2020.11.013., In this study, adaptive laboratory evolution (ALE) was applied to isolate four strains of Clostridium saccharoperbutylacetonicum able to grow in the presence of hemicellulosic hydrolysate inhibitors unsupported by the parental strain. Among them, isolate RAC-25 presented the best fermentative performance, producing 22.1g/L of ABE and 16.7g/L of butanol. Genome sequencing revealed a deletion in the arabinose transcriptional repressor gene (araR) and a mutation in the anti-sigma factor I that promoted a downregulation of sigI. Gene expression analysis indicated high expression of genes related to H+-pumps (ATP synthases), proline biosynthesis (gamma phosphate reductase) and chaperonins (Grol), suggesting an integrated mechanism that is probably coordinated by the repression of sigI. Therefore, in addition to highlighting the power of ALE for selecting robust strains, our results suggest that sigI and araR may be interesting gene targets for increased tolerance toward inhibitor compounds relevant for lignocellulosic biofuels production., The authors would like to thank the Brazilian Center for Research in Energy and Materials (CNPEM) for providing access to the bioprocess facility of the Brazilian Biorenewables National Laboratory, and CNPq (400803/2013-5), FCT (UID/BIO/04469), BioTecNorte Operation (NORTE-01-0145-FEDER-000004) and Portuguese Biological Data Network” (ref. LISBOA-01-0145-FEDER-022231) for financial support., info:eu-repo/semantics/publishedVersion

The current survey aims to describe the main methodologies for extending the reconstruction and analysis of genome-scale metabolic models and phenotype simulation with Flux Balance Analysis mathematical frameworks, via the integration of Transcriptional Regulatory Networks and/or gene expression data. Although the surveyed methods are aimed at improving phenotype simulations obtained from these models, the perspective of reconstructing integrated genome-scale models of metabolism and gene expression for diverse prokaryotes is still an open challenge., This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04 469/2020 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 -Programa Operacional Regional do Norte. Fernando Cruz holds a doctoral fellowship (SFRH/BD/139198/2018) funded by the FCT. This study was supported by the European Commission through project SHIKIFACTORY100 -Modular cell factories for the production of 100 compounds from the shikimate pathway (Reference 814408). The submitted manuscript has been created by UChicago Argonne, LLC as Operator of Argonne National Laboratory (`Argonne') under Contract No. DE-AC02-06CH11357 with the U.S. Department of Energy. The U.S. Government retains for itself, and others acting on its behalf, a paid-up, nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan., info:eu-repo/semantics/publishedVersion

Candida albicans is one of the most impactful fungal pathogens and the most common cause of invasive candidiasis, which is associated with very high mortality rates. With the rise in the frequency of multidrug-resistant clinical isolates, the identification of new drug targets and new drugs is crucial in overcoming the increase in therapeutic failure. In this study, the first validated genome-scale metabolic model for Candida albicans, iRV781, is presented. The model consists of 1221 reactions, 926 metabolites, 781 genes, and four compartments. This model was reconstructed using the open-source software tool merlin 4.0.2. It is provided in the well-established systems biology markup language (SBML) format, thus, being usable in most metabolic engineering platforms, such as OptFlux or COBRA. The model was validated, proving accurate when predicting the capability of utilizing different carbon and nitrogen sources when compared to experimental data. Finally, this genome-scale metabolic reconstruction was tested as a platform for the identification of drug targets, through the comparison between known drug targets and the prediction of gene essentiality in conditions mimicking the human host. Altogether, this model provides a promising platform for global elucidation of the metabolic potential of C. albicans, possibly guiding the identification of new drug targets to tackle human candidiasis., “Fundação para a Ciência e a Tecnologia” (FCT) [Contract PTDC /BII-BIO/28216/2017] and by Programa Operacional Regional de Lisboa 2020 [LISBOA-01-0145-FEDER-022231], through the Biodata.pt Research Infrastructure. Funding received by iBB-Institute for Bioengineering and Biosciences from FCT [Contract UIDB/04565/2020], info:eu-repo/semantics/publishedVersion

Background Actinobacillus succinogenes is a promising bacterial catalyst for the bioproduction of succinic acid from low-cost raw materials. In this work, a genome-scale metabolic model was reconstructed and used to assess the metabolic capabilities of this microorganism under producing conditions. Results The model, iBP722, was reconstructed based on the functional reannotation of the complete genome sequence of A. succinogenes 130Z and manual inspection of metabolic pathways, covering 1072 enzymatic reactions associated with 722 metabolic genes that involve 713 metabolites. The highly curated model was effective in capturing the growth of A. succinogenes on various carbon sources, as well as the SA production under various growth conditions with fair agreement between experimental and predicted data. Calculated flux distributions under different conditions show that a number of metabolic pathways are affected by the activity of some metabolic enzymes at key nodes in metabolism, including the transport mechanism of carbon sources and the ability to fix carbon dioxide. Conclusions The established genome-scale metabolic model can be used for model-driven strain design and medium alteration to improve succinic acid yields., Financially supported by BRIGIT (KBBE-2012-6-311935, FP7 project Contract nr 311935) and by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684), in addition to the BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte., info:eu-repo/semantics/publishedVersion

Cigarette smoke is associated to pathological weakening of bone tissue, being considered an important playmaker in conditions such as osteoporosis and periodontal bone loss. In addition, it is also associated with an increased risk of failure in bone regeneration strategies. The present work aimed to characterize the effects of nicotine on human osteoclastogenesis over a hydroxyapatite substrate. Osteoclast precursors were maintained in the absence or presence of the osteoclastogenesis enhancers M-CSF and RANKL, and were further treated with nicotine levels representative of the concentrations observed in the plasma and saliva of smokers. It was observed that nicotine at low concentrations elicit an increase in osteoclast differentiation, but only in the presence of M-CSF and RANKL it was also able to significantly increase the resorbing ability of osteoclasts. A slight downregulation of NFkB pathway and an increase in the production of TNF-α and, particularly PGE2, were involved in the observed effects of nicotine. At high concentrations, nicotine revealed cytotoxic effects, causing a decrease in cell density. In conclusion, nicotine at levels found in the plasma of the smokers, has the ability to act directly on osteoclast precursors, inducing its osteoclastogenic differentiation. The stimulatory behavior appears to be dependent on the stage of osteoclastic differentiation of the precursor cells, which means, in the absence of M-CSF and RANKL, it only favors the initial stages of osteoclast differentiation, while in the presence of the growth factors, a significant increase in their resorbing ability is also achieved.

The composition of a cell in terms of macromolecular building blocks and other organic molecules underlies the metabolic needs and capabilities of a species. Although some core biomass components such as nucleic acids and proteins are evident for most species, the essentiality of the pool of other organic molecules, especially cofactors and prosthetic groups, is yet unclear. Here we integrate biomass compositions from 71 manually curated genome-scale models, 33 large-scale gene essentiality datasets, enzyme-cofactor association data and a vast array of publications, revealing universally essential cofactors for prokaryotic metabolism and also others that are specific for phylogenetic branches or metabolic modes. Our results revise predictions of essential genes in Klebsiella pneumoniae and identify missing biosynthetic pathways in models of Mycobacterium tuberculosis. This work provides fundamental insights into the essentiality of organic cofactors and has implications for minimal cell studies as well as for modeling genotype-phenotype relations in prokaryotic metabolic networks., J.C.X. was sponsored by Fundação para a Ciência e Tecnologia, Portugal [Grant SFRH/BD/81626/2011]. This study was supported by the European Molecular Biology Laboratory, the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, COMPETE 2020 (POCI-01–0145-FEDER-006684) and BioTecNorte operation (NORTE-01–0145-FEDER-000004) funded by European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. This project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant agreement no 686070.

Genome-scale metabolic models (GEMs) can be used to evaluate genotype-phenotype relationships and their application to microbial strain engineering is increasing in popularity. Some of the algorithms used to simulate the phenotypes of mutant strains require the determination of a wild-type flux distribution. However, the accuracy of this reference, when calculated with flux balance analysis, has not been studied in detail before. Here, the wild-type simulations of selected GEMs for Saccharomyces cerevisiae have been analysed and most of the models tested predicted erroneous fluxes in central pathways, especially in the pentose phosphate pathway. Since the problematic fluxes were mostly related to areas of the metabolism consuming or producing NADPH/NADH, we have manually curated all reactions including these cofactors by forcing the use of NADPH/NADP+ in anabolic reactions and NADH/NAD+ for catabolic reactions. The curated models predicted more accurate flux distributions and performed better in the simulation of mutant phenotypes., FCT -Fuel Cell Technologies Program(SFRH/BD/51111/2010)

Pythium irregulare is an oleaginous Oomycete able to accumulate large amounts of lipids, including Eicosapentaenoic acid (EPA). EPA is an important and expensive dietary supplement with a promising and very competitive market, which is dependent on fish-oil extraction. This has prompted several research groups to study biotechnological routes to obtain specific fatty acids rather than a mixture of various lipids. Moreover, microorganisms can use low cost carbon sources for lipid production, thus reducing production costs. Previous studies have highlighted the production of EPA by P. irregulare, exploiting diverse low cost carbon sources that are produced in large amounts, such as vinasse, glycerol, and food wastewater. However, there is still a lack of knowledge about its biosynthetic pathways, because no functional annotation of any Pythium sp. exists yet. The goal of this work was to identify key genes and pathways related to EPA biosynthesis, in P. irregulare CBS 494.86, by sequencing and performing an unprecedented annotation of its genome, considering the possibility of using wastewater as a carbon source., The genome sequencing, strain acquisition and preliminary experiments and data analysis were funded by the São Paulo Research Foundation (FAPESP) and Coordination for the Improvement of Higher Education Personnel (CAPES) (Grante: 2016/10562–4). The experiment performance, data collection, analysis and interpretation of data were supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of [UID/BIO/04469] unit and COMPETE 2020 [POCI01-0145-FEDER-006684] and BioTecNorte operation [NORTE-01-0145-FEDER000004] funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. The authors thank the project DD-DeCaF - Bioinformatics Services for Data-Driven Design of Cell Factories and Communities, Ref. H2020-LEIT-BIO-2015-1 686070–1, funded by the European Commission., info:eu-repo/semantics/publishedVersion

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb. 2019.01283/full#supplementary-material, A high-quality GSM model for Streptococcus pneumoniae R6 model strain (iDS372), comprising 372 genes and 529 reactions, was developed. The construction of this model involved performing a genome-wide reannotation to identify the metabolic capacity of the bacterium. A reaction representing the abstraction of the biomass composition was reconciled from several studies reported in the literature and previous models, and included in the model. The final model comprises two compartments and manifold automatically generated gene rules. The validation was performed with experimental data from recent studies, regarding the usability of carbon sources, the effect of the presence of oxygen and the requirement of amino acids for growth. This model can be used to better understand the metabolism of this major pathogen, provide clues regarding new drug targets and eventually design strategies for fighting infections by these bacteria., This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 – Programa Operacional Regional doNorte. This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreementno.686070., info:eu-repo/semantics/publishedVersion

Computational strain optimisation methods (CSOMs) have been successfully used to exploit genome-scale metabolic models, yielding strategies useful for allowing compound overproduction in metabolic cell factories. Minimal cut sets are particularly interesting since their definition allows searching for intervention strategies that impose strong growth-coupling phenotypes, and are not subject to optimality bias when compared with simulation-based CSOMs. However, since both types of methods have different underlying principles, they also imply different ways to formulate metabolic engineering problems, posing an obstacle when comparing their outputs., “DeYeastLibrary – Designer yeast strain library optimized for metabolic engineering applications”, Ref.ERA-IB-2/0003/2013, funded by national funds through FCT/MCTES, DD-DeCaf and SHIKIFACTORY100, both funded by the European Union through the Horizon 2020 research and innovation programme (grant agreements no. 686070 and 814408). This study was also supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2019 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. The authors acknowledge the use of computing facilities within the scope of the Search-ON2: Revitalization of HPC infrastructure of UMinho” project (NORTE-07-0162-FEDER-000086), co-funded by the North Portugal Regional Operational Programme (ON.2 – O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF). VV also thanks funding from FCT/MCTES for the PhD studentship with reference SFRH/BD/118657/2016., info:eu-repo/semantics/publishedVersion

Portugal presents the highest incidence of stage 5 chronic kidney disease in Europe. It is speculated that a high consumption of non-steroidal anti-inflammatory drugs (NSAIDS) may contribute to this high incidence. Our aim was to characterize the prescription of non-steroidal anti-inflammatory drugs to patients with diabetes mellitus in Portugal.We analyzed the national prescription database in triennium 2015 - 2017. In patients with diabetes mellitus, we evaluated the prescription of non-steroidal anti-inflammatory drugs according to age, gender and region of the patient and specialty of the prescribing physician. We evaluated the prescription of non-steroidal anti-inflammatory drugs in all patients with diabetes mellitus, in patients with presumed renal impairment, and in those with concomitant prescription of angiotensin converting enzyme inhibitors or angiotensin receptor antagonists.We analyzed 23 320 620 prescriptions, corresponding to 610 157 adults, including 104 306 patients with diabetes mellitus. The most prescribed non-steroidal anti-inflammatory drugs were ibuprofen (20.1%), metamizole (14.7%), and diclofenac (11.4%). The prescription of non-steroidal anti-inflammatory drugs was higher in females, in patients aged 51 - 70 years and in the Alentejo region. Non-steroidal anti-inflammatory drugs were prescribed to 70.6% of patients with diabetes mellitus, from which 10.6% were prescribed ≥ 10 packages during the three years. Among patients with diabetes mellitus on angiotensin converting enzyme inhibitors/angiotensin receptor antagonists and with presumed reduction in kidney function, 69.3% were prescribed non-steroidal anti-inflammatory drugs and 11.5% were prescribed ≥ 10 packages during the three years.The level of prescribing of non-steroidal anti-inflammatory drugs to patients with diabetes mellitus is high. The concern of reducing non-steroidal anti-inflammatory drugs prescription to patients already on angiotensin converting enzyme inhibitors/angiotensin receptor antagonists and/or decreased renal function does not seem to exist.In Portugal, the level of prescribing of non-steroidal anti-inflammatory drugs to patients with diabetes mellitus should be reduced, particularly in the subgroups identified with higher prescription and with higher risk of progression to stage 5 chronic kidney disease.Introdução: Portugal apresenta a incidência mais elevada de doença renal crónica estádio 5 na Europa. Especula-se que o elevado consumo de anti-inflamatórios não esteroides possa contribuir para esta incidência. O objetivo do presente estudo foi caracterizar a prescrição de anti-inflamatórios não esteroides a doentes com diabetes mellitus em Portugal. Material e Métodos: Na Base de Dados Nacional de Prescrições do Ministério da Saúde, triénio 2015 - 2017, analisámos a prescrição de anti-inflamatórios não esteroides em doentes com diabetes mellitus, de acordo com a idade, género e região do doente e a especialidade do médico prescritor. Avaliámos a prescrição de anti-inflamatórios não esteroides no total de doentes com diabetes mellitus, em doentes com diminuição presumida da função renal e naqueles com prescrição concomitante de inibidores da enzima de conversão da angiotensina ou antagonistas dos recetores da angiotensina. Resultados: Analisámos 23 320 620 prescrições, correspondendo a 610 157 adultos, dos quais 104 306 doentes com diabetes mellitus. Os anti-inflamatórios não esteroides mais prescritos foram ibuprofeno (20,1%), metamizol (14,7%) e diclofenac (11,4%). A prescrição foi mais frequente nas mulheres, nos doentes com 51 - 70 anos e no Alentejo. Foram prescritos anti-inflamatórios não esteroides a 70,6% dos doentes com diabetes mellitus, dos quais 10,6% receberam prescrições de ≥ 10 embalagens durante os três anos. Dos doentes com diabetes mellitus medicados com inibidores da enzima de conversão da angiotensina ou antagonistas dos receptores da angiotensina e com diminuição presumida da taxa de filtração glomerular, 69,3% receberam prescrição de anti-inflamatórios não esteroides e 11,5% receberam ≥ 10 embalagens durante os três anos. Discussão: A prescrição de anti-inflamatórios não esteroides na diabetes mellitus é elevada. Não parece existir uma preocupação na menor utilização de anti-inflamatórios não esteroides em doentes simultaneamente medicados com inibidores da enzima de conversão da angiotensina ou antagonistas dos recetores da angiotensina e/ou com diminuição da função renal. Conclusão: A prescrição de anti-inflamatórios não esteroides em Portugal a doentes com diabetes mellitus deverá ser reduzida, particularmente nos subgrupos identificados com prescrição mais elevada e com maior risco de progressão para doença renal crónica estádio 5.

If we tried to list every known chemical reaction within an organismhuman, plant or even bacteriawe would get quite a long and confusing read. But when this information is represented in so-called genome-scale metabolic networks, we have the means to access computationally each of those reactions and their interconnections. Some parts of the network have alternatives, while others are unique and therefore can be essential for growth. Here, we simulate growth and compare essential reactions and genes for the simplest type of unicellular speciesprokaryotesto understand which parts of their metabolism are universally essential and potentially ancestral. We show that similar patterns of essential reactions echo phylogenetic relationships (this makes sense, as the genome provides the building plan for the enzymes that perform those reactions). Our computational predictions correlate strongly with experimental essentiality data. Finally, we show that a crucial step of protein synthesis (tRNA charging) and the synthesis and transformation of small molecules that enzymes require (cofactors) are the most essential and conserved parts of metabolism in prokaryotes. Our results are a step further in understanding the biology and evolution of prokaryotes but can also be relevant in applied studies including metabolic engineering and antibiotic design., This work was supported by grants from: the Fundac ¸ão para a Ciência e a Tecnologia (http:// www.fct.pt) with award number UID/BIO/04469/2013, the European Regional Development Fund (http://www.norte2020.pt) with award number NORTE-01-0145-FEDER-000004 (https://www. ceb.uminho.pt/Projects/Details/6040), Horizon 2020 (https://ec.europa.eu/programmes/ horizon2020) with award number 686070 (http:// dd-decaf.eu/) and COMPETE2020 with award number POCI-01-0145-FEDER-006684 to JCX and IR and the Fundação para a Ciência e a Tecnologia (http://www.fct.pt) with award number SFRH/BD/81626/2011 to JCX. The funders had no role in study design, data collectionand analysis, decision to publish, or preparation of the manuscript., info:eu-repo/semantics/publishedVersion

Mannosylglycerate (MG) is one of the most widespread compatible solutes among marine microorganisms adapted to hot environments. This ionic solute holds excellent ability to protect proteins against thermal denaturation, hence a large number of biotechnological and clinical applications have been put forward. However, the current prohibitive production costs impose severe constraints towards large-scale applications. All known microbial producers synthesize MG from GDP-mannose and 3-phosphoglycerate via a two-step pathway in which mannosyl-3-phosphoglycerate is the intermediate metabolite. In an early work, this pathway was expressed in Saccharomyces cerevisiae with the goal to confirm gene function (Empadinhas et al. in J Bacteriol 186:4075--4084, 2004), but the level of MG accumulation was low. Therefore, in view of the potential biotechnological value of this compound, we decided to invest further effort to convert S. cerevisiae into an efficient cell factory for MG production., This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684), BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte and also by project LISBOA-01-0145-FEDER-007660 (Microbiologia Molecular, Estrutural e Celular) funded by FEDER through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI). Cristiana Faria was supported by a Ph.D. Grant from FCT (Ref. SFRH/ BD/79552/2011)., info:eu-repo/semantics/publishedVersion

Sequence data from this article can be found in the GenBank/EMBL data libraries under accession numbers: KX262844.1 (RsUGT72B14, R. sachalinensis); AY547304.1 (RsUGT73B6. R. sachalinensis); NP_418458.1 (malE, E. coli); NP_415214.1 (pgm, E. coli); NP_415752.1 (galU, E. coli); NM_001180688.3 (aro10, S. cerevisiae), and NP_417484.1 (yqhD, E. coli)., Edible berries are considered to be among nature's treasure chests as they contain a large number of (poly)phenols with potentially health-promoting properties. However, as berries contain complex (poly)phenol mixtures, it is challenging to associate any interesting pharmacological activity with a single compound. Thus, identification of pharmacologically interesting phenols requires systematic analyses of berry extracts. Here, raspberry (Rubus idaeus, var. Prestige) extracts were systematically analyzed to identify bioactive compounds against pathological processes of neurodegenerative diseases. Berry extracts were tested on different Saccharomyces cerevisiae strains expressing disease proteins associated with Alzheimer's, Parkinson's, or Huntington's disease or amyotrophic lateral sclerosis. After identifying bioactivity against Huntington's disease, the extract was fractionated and the obtained fractions were tested in the yeast model, which revealed that salidroside, a glycosylated phenol, displayed significant bioactivity. Subsequently, a metabolic route to salidroside was reconstructed in S. cerevisiae and Corynebacterium glutamicum. The best-performing S. cerevisiae strain was capable of producing 2.1 mM (640 mg L-1) salidroside from glucose in shake flasks, whereas an engineered C. glutamicum strain could efficiently convert the precursor tyrosol to salidroside, accumulating up to 32 mM (9,700 mg L-1) salidroside in bioreactor cultivations (yield: 0.81 mol mol-1). Targeted yeast assays verified that salidroside produced by both organisms has the same positive effects as salidroside of natural origin., We express our gratitude to Dr. Rute Neves (Chr. Hansen A/S, Denmark), Prof. Dr. Jochen Förster and Dr. Alexey Dudnik (The Nova Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Denmark), who coordinated the BacHBerry project. We also thank Prof. Dr. Ian Macreadie (Centre of Excellence for Alzheimer’s Disease Research & Care, School of Exercise, Biomedical & Health Sciences, Edith Cowan University, WA, Australia) for providing p416_GPD-GFP_AB42; Prof. Dr. Tiago Outeiro (University Medical Center Gottingen, Department of Neurodegeneration and Restorative Research, Germany) for providing W303-1A_Syn and W303-1A TU; Prof. Dr. Flaviano Giorgini (Department of Genetics and Genome Biology, University of Leicester, UK) for providing p425GAL1_HTT103Q; and Prof. Dr. Greg Petsko (Department of Biochemistry and Chemistry, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, U.S.) for providing pYES_GAL1pr-FUS-GFP and pYES_CT., info:eu-repo/semantics/publishedVersion

BACterial Hosts for production of Bioactive phenolics from bERRY fruits (BacHBerry) was a 3-year project funded by the Seventh Framework Programme (FP7) of the European Union that ran between November 2013 and October 2016. The overall aim of the project was to establish a sustainable and economically-feasible strategy for the production of novel high-value phenolic compounds isolated from berry fruits using bacterial platforms. The project aimed at covering all stages of the discovery and pre-commercialization process, including berry collection, screening and characterization of their bioactive components, identification and functional characterization of the corresponding biosynthetic pathways, and construction of Gram-positive bacterial cell factories producing phenolic compounds. Further activities included optimization of polyphenol extraction methods from bacterial cultures, scale-up of production by fermentation up to pilot scale, as well as societal and economic analyses of the processes. This review article summarizes some of the key findings obtained throughout the duration of the project., The authors would like to thank the European Union’s Seventh Framework Programme (BacHBerry, Project No. FP7-613793, and FP7-PEOPLE2013-COFUND, Project No. FP7-609405) for the financial support. AD, RF, MHHN, PG, SGS, and JF would also like to acknowledge the Novo Nordisk Foundation. We express our gratitude to Dr. Martha Cyert (Stanford School of Medicine, EUA), Dr. Hitoshi Shimoi (National Research Institute of Brewing, Japan) and Dr. Yoshio Araki (Graduate School of Biosphere Science, Hiroshima University, Japan) for providing the yeast strain YAA5. We also thank Dr. Ian Macraedie, RMIT University, Australia) for providing the plasmid p416_GPDprGFP-A42., info:eu-repo/semantics/publishedVersion

© 2018 Elsevier B.V. All rights reserved., Background: Exposures to lead (Pb) during developmental phases can alter the normal course of development, with lifelong health consequences. Permanent Pb exposure leads to behavioral changes, cognitive impairment, sympathoexcitation, tachycardia, hypertension and autonomic dysfunction. However, the effects of an intermittent lead exposure are not yet studied. This pattern of exposure has been recently increasing due to migrations, implementation of school exchange programs and/or residential changes. Objective: To determine and compare lead effects on mammal’s behavior and physiology, using a rat model of intermittent and permanent Pb exposures. Methods: Fetuses were intermittently (PbI) or permanently (PbP) exposed to water containing lead acetate (0.2% w/v) throughout life until adulthood (28 weeks of age). A control group (CTL) without any exposure to lead was also used. Anxiety was assessed by elevated plus maze (EPM) and locomotor activity and exploration by open field test (OFT). Blood pressure (BP), electrocardiogram (ECG), heart rate (HR), respiratory frequency (RF), sympathetic and parasympathetic activity and baro- and chemoreceptor reflex profiles were evaluated. Immunohistochemistry protocol for the assessment of neuroinflammation, neuronal loss (NeuN), gliosis and synaptic alterations (Iba-1, GFAP, Syn), were performed at the hippocampus. One-way ANOVA with Tukey’s multiple comparison between means were used (significance p < 0.05) for statistical analysis. Results: The intermittent lead exposure produced a significant increase in diastolic and mean BP values, concomitant with a tendency to sympathetic overactivity (estimated by increased low-frequency power) and without significant changes in systolic BP, HR and RF. A chemoreceptor hypersensitivity and a baroreflex impairment were also observed, however, less pronounced when compared to the permanent exposure. Regarding behavioral changes, both lead exposure profiles showed an anxiety-like behavior without changes in locomotor and exploratory activity. Increase in GFAP and Iba-1 positive cells, without changes in NeuN positive cells were found in both exposed groups. Syn staining suffered a significant decrease in PbI group and a significant increase in PbP group. Conclusion: This study is the first to show that developmental Pb exposure since fetal period can cause lasting impairments in physiological parameters. The intermittent lead exposure causes adverse health effects, i.e, hypertension, increased respiratory frequency and chemoreflex sensitivity, baroreflex impairment, anxiety, decreased synaptic activity, neuroinflammation and reactive gliosis, in some ways similar to a permanent exposure, however some are lower-grade, due to the shorter duration of exposure. This study brings new insights on the environmental factors that influence autonomic and cardiovascular systems during development, which can help in creating public policy strategies to prevent and control the adverse effects of Pb toxicity., Vera Geraldes acknowledges the post-doctoral fellow given by the Fundação para a Ciência e Tecnologia (FCT) (Ref: SFRH/BPD/119315/ 2016).

The Metabolic Models Reconstruction Using Genome-Scale Information (merlin) tool is a user-friendly Java application that aids the reconstruction of genome-scale metabolic models for any organism that has its genome sequenced. It performs the major steps of the reconstruction process, including the functional genomic annotation of the whole genome and subsequent construction of the portfolio of reactions. Moreover, merlin includes tools for the identification and annotation of genes encoding transport proteins, generating the transport reactions for those carriers. It also performs the compartmentalisation of the model, predicting the organelle localisation of the proteins encoded in the genome and thus the localisation of the metabolites involved in the reactions promoted by such enzymes. The gene-proteins-reactions (GPR) associations are automatically generated and included in the model. Finally, merlin expedites the transition from genomic data to draft metabolic models reconstructions exported in the SBML standard format, allowing the user to have a preliminary view of the biochemical network, which can be manually curated within the environment provided by merlin., PhD grant to O. D. [SFRH /BD/47307/2008]; ERDF-European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness); National Funds through the FCT within the projects FCOMP-01-0124-FEDER-009707 (HeliSysBio-molecular Systems Biology in Helicobacter pylori) and FCOMP-01-0124-FEDER-015079 (ToMEGIM-Computational Tools for Metabolic Engineering using Genome-scale Integrated Models).

This work reports the nutritional profile and in vitro neuroprotective properties of leaves of Carpobrotus edulis L, a medicinal and edible succulent species native to the coast of South Africa. Biomass was evaluated for proximate composition and for contents in carotenoids, liposoluble pigments and minerals. Hexane, dichloromethane, ethyl acetate and methanol extracts were prepared by Soxhlet extraction from dried biomass and evaluated for in vitro inhibition of acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE), capacity to attenuate hydrogen peroxide (H2O2)-induced injury in the human dopaminergic cell line SH-SY5Y and for anti-neuroinflammatory potential on lipopolysaccharide (LPS)-stimulated microglia cells. Extracts were evaluated for antioxidant activity by four complementary methods, total content of phenolics, tannins and flavonoids. Finally the profile of the main phenolic compounds was determined by high performance liquid chromatography with diode array detection (HPLC-DAD). C edulis has a high moisture content, high levels of crude protein, fibre, ash, carotenoids, calcium and iron and a low fat level. The extracts were able to efficiently scavenge the free radical 2,2-diphenyl-1-picrylhydrazyl (DPPH), reduce iron and chelate copper and iron ions, and exhibited different levels of phenolic compounds in the order ethyl acetate > methanol > dichloromethane > hexane. The main compounds detected were gallic and salicylic acids and quercetin, all in the ethyl acetate extract. The extracts allowed a dual and potent inhibition of AChE and BuChE. The dichloromethane and methanol extracts had the strongest capacity to prevent cell death induced by H2O2, and the methanol extract had anti-neuronflammatory properties. All together our results suggest that consumption of leaves of C edulis can contribute for a balanced diet, and that they may add to the improvement of cognitive functions. It also suggests possible novel biotechnological applications of C. edulis such as source of molecules and/or products for the food and/or pharmaceutical industries. Studies aiming to the isolation and identification of the bioactive compounds are already in progress. (C) 2017 SAAB. Published by Elsevier B.V. All rights reserved. Portuguese National Budget XtremeGourmet project [ALG-01-0247-FEDER-017676] FCT Investigator Programme [IF/00049/2012] info:eu-repo/semantics/publishedVersion

Over the last 15 years, several genome-scale metabolic models (GSMMs) were developed for different yeast species, aiding both the elucidation of new biological processes and the shift toward a bio-based economy, through the design of in silico inspired cell factories. Here, an historical perspective of the GSMMs built over time for several yeast species is presented and the main inheritance patterns among the metabolic reconstructions are highlighted. We additionally provide a critical perspective on the overall genome-scale modeling procedure, underlining incomplete model validation and evaluation approaches and the quest for the integration of regulatory and kinetic information into yeast GSMMs. A summary of experimentally validated model-based metabolic engineering applications of yeast species is further emphasized, while the main challenges and future perspectives for the field are finally addressed, This work was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of a Ph.D. grant (PD/BD/52336/2013), of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01–0145FEDER-006684) and also in the context of the EU-funded initiative ERA-NET for Industrial Biotechnology (ERA-IB-2/0003/2013), in addition to the BioTecNorte operation (NORTE-01–0145FEDER-000004) funded by European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte., info:eu-repo/semantics/publishedVersion

Although little is known about their nutritional composition, Sarcocornia perennis subsp. perennis, S. perennis subsp. alpini and Salicornia ramosissima (Salicorniaceae) as well as Arthrocnemum macro-stachyum (Amaranthaceae) are consumed in gourmet cuisine. In spite of belonging to different families, these halophytes share morphological and organoleptic characteristics. This work explored the nutritional properties and the antioxidant potential of these species using five integrative methods. All species had a nutritional profile suitable for human consumption with high levels of protein (5.20-13.2 g/100 g dw) and n-3 polyunsaturated fatty acids (FA), particularly or alpha-linolenic acid (19.3-25.9% of total FA), and low concentration of toxic metals (below the limits imposed by the European Commission). These halophytes are also a good source of minerals, particularly sodium (64.1-109 mg/gdw), and S. ramosissima is an excellent source of manganese (204 mu g/g dw). However, due care should be taken not to exceed the legal limits for sodium ingestion. These plants showed also significant antioxidant potential, with high radical scavenging activity (RSA), iron reducing power and total phenolics content (20.5-49.2 mg GAE/g). A. macrostachyum had the highest RSA (lC(50-DPPH) = 0.84 mg/mL; IC50-NO = 0.60 mg/mL), and iron reducing potential (IC50= 0.84 mg/mL) along with high levels of alpha- and gamma-tocopherol (8.74 and 4.71 mg/100 g dw, respectively). (C) 2017 Elsevier Inc. All rights reserved. XtremeBio project - Portuguese Foundation for Science and Technology (FCT) [PTDC/MAR-EST/4346/2012] XtremeGourmet project from the Portuguese National Budget [ALG-01-0247-FEDER-017676] FCT Investigator Programme [IF/00049/2012] FCT project [CCMAR/Multi/04326/2013] [FCTFRH/BD/105541/2014] info:eu-repo/semantics/publishedVersion

Myocardial infarction (MI) is a high prevalence cardiovascular disease with a tendency to increase. Although MI therapy has increased its effectiveness, the loss of myocardial function in consequence of MI is still responsible for major subsequent complications as rhythm changes and heart failure. In human hearts, MI is characterized by cardiomyocyte death and fibrin deposition, which is later replaced by scar tissue. In opposition, zebrafish heart undergoes minimal scaring and cardiac tissue can undergo full functionally regeneration in 60 to 120 days. Therefore, this animal model has been used in cardiovascular research as a model for studying mechanisms of cardiac regeneration. The hearts of zebrafish is anatomically different from the human heart, though the electrocardiogram (ECG) pattern and the critical conduction pathways are comparable to the human's. The objective of our full project is the implementation of an ECG recording system with 3 orthogonal electrodes in 2 planes, in order to create a 4D recording of the zebrafish cardiac electrical activity. Here we present our preliminary work related to a non-invasive ECG monitoring with two electrodes.

Usually, transport reactions are added to genome-scale metabolic models (GSMMs) based on experimental data and literature. This approach does not allow associating specific genes with transport reactions, which impairs the ability of the model to predict effects of gene deletions. Novel methods for systematic genome-wide transporter functional annotation and their integration into GSMMs are therefore necessary. In this work, an automatic system to detect and classify all potential membrane transport proteins for a given genome and integrate the related reactions into GSMMs is proposed, based on the identification and classification of genes that encode transmembrane proteins. The Transport Reactions Annotation and Generation (TRIAGE) tool identifies the metabolites transported by each transmembrane protein and its transporter family. The localization of the carriers is also predicted and, consequently, their action is confined to a given membrane. The integration of the data provided by TRIAGE with highly curated models allowed the identification of new transport reactions. TRIAGE is included in the new release of merlin, a software tool previously developed by the authors, which expedites the GSMM reconstruction processes., This work was partially supported by a PhD grant (SFRH /BD/47307/2008) and by the ERDF—European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness), and National Funds through the FCT within the projects FCOMP-01-0124-FEDER-009707 (HeliSysBio—molecular Systems Biology in Helicobacter pylori) and PTDC/EIAEIA/115176/2009. The authors would also like to thank the FCT Strategic Project PEst-OE/EQB/LA0023/2013 and the Projects “BioInd - Biotechnology and Bioengineering for improved Industrial and Agro-Food processes”, REF. NORTE-07-0124-FEDER-000028 and “PEM – Metabolic Engineering Platform”, project number 23060 , both cofunded by the Programa Operacional Regional do Norte (ON.2 – O Novo Norte), QREN, FEDER., info:eu-repo/semantics/publishedVersion

We report a case of a patient with recurrent syncope and paroxysmal atrial fibrillation whose clinical status greatly improved after a period of orthostatic training. The potential efficacy of this non-pharmacological measure in modulating the autonomic tone is discussed below.

Bacterial lipids have relevant applications in the production of renewable fuels and biobased oleochemicals. The genus Rhodococcus is one of the most relevant lipid producers due to its capability to accumulate those compounds, mainly triacylglycerols (TAG), when cultivated on different defined substrates, namely sugars, organic acids and hydrocarbons but also on complex carbon sources present in industrial wastes. In this work, the production of storage lipids by Rhodococcus opacus B4 using glucose, acetate and hexadecane is reported for the first time and its productivity compared with Rhodococcus opacus PD630, the best TAG producer bacterium reported. Both strains accumulated mainly TAG from all carbon sources, being influenced by the carbon source itself and by the duration of the accumulation period. R. opacus B4 produced 0.09 and 0.14 g L1 at 24 and 72 h, with hexadecane as carbon source, which was 2 and 3.3 fold higher than the volumetric production obtained by R. opacus PD630. Both strains presented similar fatty acids (FA) profiles in intact cells while in TAG produced fraction, R. opacus B4 revealed a higher variability in fatty acid composition than R. opacus PD630, when both strains were cultivated on hexadecane. The obtained results open new perspectives for the use of R. opacus B4 to produce TAG, in particular using oily (alkane-contaminated) waste and wastewater as cheap raw-materials. Combining TAG production with hydrocarbons degradation is a promising strategy to achieve environmental remediation while producing added value compounds., This work was financially supported by the Portuguese Science Foundation (FCT) and European Social Fund (ESF, POPH-QREN) through the Grant given to A.R. Castro (SFRH/BD/64500/2009), the FCT Strategic Project of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462).

Since the metabolic network reconstruction of Haemophilus influenzae was published in 1999, many other researchers have followed this trend. The possibilities and potential of having an in silico metabolic network for a specific organism is gaining emphasis among researchers that see the promise that the new era of genome-scale metabolic models could bring to the scientific scene. Enterococcus faecalis is a Gram positive bacterium from the lactic acid group that inhabits commensally the gut of humans and warm-blooded animals. Although it is normally known for its influence in the medical panorama it is also gaining relevance in different fields namely in the food industry and more specifically in the process of ripening and aroma development in certain types of cheese. Nevertheless, it is still more prominent in the medical scenery as the main cause of nosocomial infections in hospital environments and the reason behind multiple diseases, namely urinary tract infections, endocarditis, meningitis, to name a few. In this work the first genome-scale model of Enterococcus faecalis, has been reconstructed to serve as a valuable tool to predict and better understand the phenotypic behaviour and its metabolism., (undefined)

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb.2016.01819/full#supplementary-material, Understanding gene function and regulation is essential for the interpretation prediction and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets Atomic Regulons ARs represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems. Here we describe an approach for inferring ARs that leverages large-scale expression data sets gene context and functional relationships among genes. We computed ARs for Escherichia coli based on 907 gene expression experiments and compared our results with gene clusters produced by two prevalent data-driven methods: hierarchical clustering and k-means clustering. We compared ARs and purely data-driven gene clusters to the curated set of regulatory interactions for E. coli found in RegulonDB showing that ARs are more consistent with gold standard regulons than are data-driven gene clusters. We further examined the consistency of ARs and data-driven gene clusters in the context of gene interactions predicted by Context Likelihood of Relatedness CLR analysis finding that the ARs show better agreement with CLR predicted interactions. We determined the impact of increasing amounts of expression data on AR construction and find that while more data improve ARs it is not necessary to use the full set of gene expression experiments available for E. coli to produce high quality ARs. In order to explore the conservation of co-regulated gene sets across different organisms we computed ARs for Shewanella oneidensis Pseudomonas aeruginosa Thermus thermophilus and Staphylococcus aureus each of which represents increasing degrees of phylogenetic distance from E. coli. Comparison of the organism-specific ARs showed that the consistency of AR gene membership correlates with phylogenetic distance but there is clear variability in the regulatory networks of closely related organisms. As large scale expression data sets become increasingly common for model and non-model organisms comparative analyses of atomic regulons will provide valuable insights into fundamental regulatory modules used across the bacterial domain., JF acknowledges funding from [SFRH/BD/70824/2010] of the FCT (Portuguese Foundation for Science and Technology) PhD program. CH and PW were supported by the National Science Foundation under grant number EFRI-MIKS-1137089. RT was supported by the Genomic Science Program (GSP), Office of Biological and Environmental Research (OBER), U.S. Department of Energy(DOE),and his work is a contribution of the Pacific North west National Laboratory (PNNL) Foundational Scientific Focus Area. This work was partially supported by an award from the National Science Foundation to MD, AB, NT, and RO (NSFABI-0850546). This work was also supported by the United States National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Service [Contract No. HHSN272201400027C].

The bacterial RelA-dependent stringent response exerts a strong influence over various processes. In this work, the impact of the relA gene mutation in Escherichia coli cells was evaluated by a quantitative proteomics analysis, employing stable-isotope labeling and high-resolution mass spectrometry. Chemostat cultures of E. coli W3110 and ΔrelA mutant strains were performed at two dilution rates (0.1 and 0.2 h−1) to assess the influence of the relA gene mutation in steady-state protein levels. A total of 121 proteins showed significant alterations in their abundance when comparing the proteome of mutant to wild-type cells. The relA gene mutation induced changes on key cellular processes, including the amino acids and nucleotide biosynthesis, the lipid metabolism, transport activities, transcription and translation processes, and responses to stress. Furthermore, some of those changes were more pronounced under specific growth conditions, as the most significant differences in protein ratios were observed at one of the dilution rates. An effect of the relA gene mutation in the acetate overflow was also observed, which confers interesting characteristics to this mutant strain that could be useful in the production of recombinant proteins. Overall, these results provide a valuable insight into the E. coli stringent response under defined steady-state conditions, suggesting that this stress response might influence multiple metabolic processes like the acetate overflow or the catabolite repression., This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684)

Given that Newcastle disease (ND) is one of the major threats for the poultry industry, testing of Newcastle disease virus (NDV) has been carried out since 2010 in cases of mortality in wild birds (passive surveillance) in Catalonia. The objective is to provide an early warning system to prevent the infection of poultry. Since 2010, 35 episodes of mortality in wild birds were attributed to NDV infection. Throughout this period there was a progressive expansion of NDV to new areas, with an increase in the episodes of mortality, although it is not clear whether they were the result of the spread of the virus, or of the improvement of the surveillance. Phylogenetic analyses indicate that two distinct sublineages of NDV, 4a and 4b, were circulating in Catalonia. Both sublineages seem to be endemic in the wild bird population, affecting mainly Eurasian-collared doves, with a clear pattern in relation to its spatial distribution (coincident with the distribution of this species), and its temporal distribution (with the majority of cases between September and February). So far, endemicity in wild birds has not resulted in ND outbreaks in poultry. However, there are still many uncertainties about, for example, whether NDV may expand to new areas of Catalonia (with higher poultry density), or about the threat that the apparently more novel sublineage 4a may represent. Hence, efforts should be made so that measures to prevent infection of poultry farms (particularly in high-risk areas and periods) are encouraged, and surveillance is maintained.

Context Marine macroalgae contain several bioactive molecules that may be developed as functional foods, but information about their neuroprotective potential is scarce. Objective The objective of this study is to determine the in vitro antioxidant and neuroprotective features of marine algae from the southern coast of Portugal and to assess the total content of different types of bioactives. Materials and methods Methanol extracts from 21 macroalgal species from the southern Portugal were evaluated for in vitro antioxidant and acetylcholinesterase (AChE) inhibition. Active extracts were further evaluated for inhibitory activity against butyrylcholinesterase (BuChE) and tyrosinase (TYRO), and for their ability to attenuate hydrogen peroxide (H2O2)-induced toxicity in SH-SY5Y cells. The total contents of different phenolic groups were determined for the most active extracts. Results Cystoseira tamariscifolia (Hudson) Papenfuss (Sargassaceae) had the highest antiradical activity (92%, 1 mg/mL). Cystoseira nodicaulis (Withering) M. Roberts (Sargassaceae) (75%) and Cystoseira humilis Schousboe ex Kützing (Sargassaceae) (70%) had the highest iron-chelating activity at 10 mg/mL. Cystoseira baccata (S.G. Gmelin) P.C. Silva (Sargassaceae) was more active towards copper (66%, 10 mg/mL). Cystoseira tamariscifolia had the highest AChE inhibitory capacity (85%, 10 mg/mL). Cystoseira tamariscifolia and C. nodicaulis were also active against BuChE and TYRO, and were able to protect SH-SY5Y cells against oxidative stress induced by H2O2. Cystoseira tamariscifolia had the highest content of all the groups of phenolics, and was particularly enriched in hydroxycinnamic acids (106 mg CAE/g DW). Discussion and conclusion Results indicate that C. tamariscifolia and C. nodicaulis are important sources of nutraceutical compounds and may be considered functional foods that could improve cognitive functions.

Given the huge potential impact of the growing number of complete genome-scale metabolic network reconstructions of organisms, it is necessary to use bioinformatics tools to simplify and accelerate the course of knowledge in this field. One essential component of genome-scale metabolic model is biomass equation, whose maximization is one of the most common objective functions used in Flux Balance Analysis formulations. Some components of biomass, such as amino acids and nucleotides, can be estimated from genome information. In this work it is proposed a Java tool that estimates biomass composition in amino acids and nucleotides, from genome and transcriptomic information, using as input files sequences in FASTA format and files with transcriptomic data in csv format. This application allows to obtain the results rapidly and is also a user-friendly tool since facilitates its use by users with any or little background in informatics., Project DeYeastLibrary - Designer yeast strain library optimized for metabolic engineering applications, Ref. ERA-IB-2/0003/2013, funded by national funds through FCT/MCTES

While the stoichiometry of metabolism is probably the best studied cellular level, the dynamics in metabolism can still not be well described, predicted and, thus, engineered. Unknowns in the metabolic flux behavior arise from kinetic interactions, especially allosteric control mechanisms. While the stoichiometry of enzymes is preserved in vitro, their activity and kinetic behavior differs from the in vivo situation. Next to this challenge, it is infeasible to test the interaction of each enzyme with each intracellular metabolite in vitro exhaustively. As a consequence, the whole interacting metabolome has to be studied in vivo to identify the relevant enzymes properties. In this review we discuss current approaches for in vivo perturbation experiments, that is, stimulus response experiments using different setups and quantitative analytical approaches, including dynamic carbon tracing. Next to reliable and informative data, advanced modeling approaches and computational tools are required to identify kinetic mechanisms and their parameters., The authors EV, AT, KN, IR, MO, DM and AW are part of the ERA-IB funded consortium DYNAMICS (ERA-IB-14-081, NWO 053.80.724).

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00275, We introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of B. subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, we reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches and small regulatory RNAs. Overall, regulatory information is included in the model for approximately 2500 of the ~4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same ON and OFF gene expression profiles across multiple samples of experimental data. We show how atomic regulons for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how atomic regulons can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome expression metadata relating to experimental conditions, gaining insights into novel biology., AG and VF acknowledge funding from the European Union Basynthecproject(BaSynthecFP7-244093).

Metabolite profiling of E. coli W3110 and the isogenic ∆relA mutant cells was used to characterize the RelA-dependent stringent control of metabolism under different growth conditions. Metabolic profiles were obtained by gas chromatography–mass spectrometry (GC-MS) analysis and revealed significant differences between E. coli strains grown at different conditions. Major differences between the two strains were assessed in the levels of amino acids and fatty acids and their precursor metabolites, especially when growing at the lower dilution rates, demonstrating differences in their metabolic behavior. Despite the fatty acid biosynthesis being the most affected due to the lack of the RelA activity, other metabolic pathways involving succinate, lactate and threonine were also affected. Overall, metabolite profiles indicate that under nutrient-limiting conditions the RelA-dependent stringent response may be elicited and promotes key changes in the E. coli metabolism., The authors thank to Raphael Aggio for assisting in the automatic refinement and correction of the GC-MS data, Katie Smart for performing acetate analyses and Clark Ehlers for his support with the bioreactor set up. This work was supported by the Portuguese FCT (Fundacao para a Ciencia e Tecnologia) funded MIT-Portugal Program in Bioengineering (MIT-Pt/BS-BB/0082/2008) and by ERDF-European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within the project FCOMP-01-0124-FEDER-009707 (HeliSysBio. molecular Systems Biology in Helicobacter pylori). The work was also supported by a PhD grant from FCT (ref. SFRH/BD/22863/2005).

The Funil water reservoir, located in the Paraiba do Sul River Valley in the municipality of Resende (Rio de Janeiro State, Brazil), has become eutrophic during the last two decades and undergone recurrent blooms of cyanobacteria. This study presents temporal series of physical, chemical and biological data from the reservoir encompassing an overall period of four years (from June/02 to March/06). Monthly, measurements of conductivity, transparency, temperature, pH, dissolved oxygen, and water samples for the analyses of nutrients (N and P), chlorophyll-a, phytoplankton and zooplankton composition and cyanotoxins in seston and in net plankton were performed. Toxicity tests with native and temperate cladocerans species were also performed. The results showed that the high input of N and P favored the persistent dominance of cyanobacteria. A temporal pattern was observed mainly related to changes in water temperature, characterizing two distinct periods: a warm-wet period with cyanobacterial bloom, and a cold-dry period with general reduced biomass. Cyanobacteria included potential hepatotoxins (microcystins) producers like Microcystis spp., and potential neurotoxins (saxitoxins) producers like Anabaena circinalis and Cylindrospermopsis raciborskii. In fact, elevated concentrations of microcystins and saxitoxins were found in the phytoplankton, and high levels of microcystins in the zooplankton, suggesting that these toxins may be transferred through the food chain. The toxicity tests revealed that the cyanobacterial blooms had toxic effects on cladocerans, causing death, reduction in the rate of population increase (r), and paralysis, in agreement with the mechanism of action of the cyanotoxins present.

The development of monitoring methods for assessing the physiological state of microorganisms during recombinant fermentation processes has been encouraged by the need to evaluate the influence of processing conditions in recombinant protein production. In this work, a technique based on microscopy and image analysis was developed that allows the simultaneous quantification of parameters associated with viability and fluorescent protein production in recombinant Escherichia coli fermentations. Images obtained from light microscopy with phase contrast are used to assess the total number of cells in a given sample and, from epifluorescence microscopy, both protein producing and injured cells are evaluated using two different fluorochromes: propidium iodide and enhanced yellow fluorescent protein. This technique revealed the existence of different cell populations in the recombinant E. coli fermentation broth that were evaluated along four batch fermentations, complementing information obtained with standard techniques to study the effects of the temperature and induction time in recombinant protein production processes., Fundação para a Ciência e a Tecnologia (FCT) - POCI/BIO/60139/2004

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed., The work of P.M. was supported by the Portuguese Science Foundation (FCT) through Ph.D. grant SFRH/BD/61465/2009. We thank the FCT Strategic Project of UID/BIO/04469/2013 unit, the project RECI/BBB-EBI/0179/201 (FCOMP-01-0124-FEDER-027462) and the project “BioInd-Biotechnology and Bioengineering for Improved Industrial and Agro-Food Processes,” (NORTE-07-0124-FEDER-000028) cofunded by the Programa Operacional Regional do Norte (ON.2-O Novo Norte), QREN, FEDER, and the project “DeYeastLib-Designer Yeast Strain Library Optimized for Metabolic Engineering Applications” (ERA-IB-2/0003/2013) funded by national funds through FCT/MCTES.

Live attenuated strains of Salmonella typhimurium have been extensively investigated as vaccines for a number of infectious diseases. However, there is still little information available concerning aspects of their metabolism. S. typhimurium and Escherichia coli show a high degree of similarity in terms of their genome contents and metabolic networks. However, this work presents experimental evidence showing that significant differences exist in their abilities to direct carbon fluxes to biomass and energy production. It is important to study the metabolism of Salmonella in order to elucidate the formation of acetate and other metabolites involved in optimizing the production of biomass, essential for the development of recombinant vaccines. The metabolism of Salmonella under aerobic conditions was assessed using continuous cultures performed at dilution rates ranging from 0.1 to 0.67 h1, with glucose as main substrate. Acetate assimilation and glucose metabolism under anaerobic conditions were also investigated using batch cultures. Chemostat cultivations showed deviation of carbon towards acetate formation, starting at dilution rates above 0.1 h1. This differed from previous findings for E. coli, where acetate accumulation was only detected at dilution rates exceeding 0.4 h1, and was due to the lower rate of acetate assimilation by S. typhimurium under aerobic conditions. Under anaerobic conditions, both microorganisms mainly produced ethanol, acetate, and formate. A genome-scale metabolic model, reconstructed for Salmonella based on an E. coli model, provided a poor description of the mixed fermentation pattern observed during Salmonella cultures, reinforcing the different patterns of carbon utilization exhibited by these closely related bacteria. This article is protected by copyright. All rights reserved., Special thanks to Amadeus Azevedo for the HPLC analyses and technical assistance. The authors acknowledge the national funding received from CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico, Brazil), the international cooperation project CAPES-FCT (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior/Brazil-Fundacao para a Ciencia e a Tecnologia/Portugal-Process 315/11), CAPES (Atracao de Jovens Talentos-Process 064922/2014-01) and to Fundacao para a Ciencia e Tecnologia the strategic funding of UID/BIO/04469/2013 unit.

Alternative biofuels to petroleum-derived compounds are in high demand nowadays. Ethanol has played an important role in the picture as the major biofuel currently produced [1], [2]. However, advances in technology and the current search for alternatives biofuels, brought butanol into the scenario. The characteristics of this primary alcohol make it an interesting alternative to ethanol as it can directly replace gasoline without the need of engine adaptation. Moreover, it is an excellent diluent and solvent for manufacturing intermediates of chemical industry augmenting the potential of this compound. With the most recent Genome-scale Model (GEM) of C. acetobutylicum available, new in silico strategies can be further explored to improve butanol production. By modeling clostridial metabolism, new insights on the acidogenic-solventogenic metabolism are debated in this work.

Modeling cellular metabolism is fundamental for many biotechnological applications, including drug discovery and rational cell factory design. Central carbon metabolism (CCM) is particularly important as it provides the energy and precursors for other biological processes. However, the complex regulation of CCM pathways has still not been fully unraveled and recent studies have shown that CCM is mostly regulated at post-transcriptional levels. In order to better understand the role of allosteric regulation in controlling the metabolic phenotype, we expand the reconstruction of CCM in Escherichia coli with allosteric interactions obtained from relevant databases. This model is used to integrate multi-omics datasets and analyze the coordinated changes in enzyme, metabolite, and flux levels between multiple experimental conditions. We observe cases where allosteric interactions have a major contribution to the metabolic flux changes. Inspired by these results, we develop a constraint-based method (arFBA) for simulation of metabolic flux distributions that accounts for allosteric interactions. This method can be used for systematic prediction of potential allosteric regulation under the given experimental conditions based on experimental data. We show that arFBA allows predicting coordinated flux changes that would not be predicted without considering allosteric regulation. The results reveal the importance of key regulatory metabolites, such as fructose-1,6-bisphosphate, in controlling the metabolic flux. Accounting for allosteric interactions in metabolic reconstructions reveals a hidden topology in metabolic networks, improving our understanding of cellular metabolism and fostering the development of novel simulation methods that account for this type of regulation., (undefined)

SUMMARYThe fatty-acid composition and botanical origin of 14 honey bee (Apis mellifera) pollen load samples acquired in shops and apiaries in Minas Gerais and Sao Paulo states, Brazil, were determi...

There is considerable controversy concerning the origin of Iberian populations of the Mediterranean chameleon, Chamaeleo chamaeleon. Current opinion dictates that Spanish populations result from introductions during the 18th and 19th centuries, with subsequent translocations from the original populations to other parts of Spain. The Portugese population in the Algarve is believed to have been introduced from Africa or Spain during the 1920s. However, Holocene remains of chameleons suggest that the Malaga population at least could have a much older origin. Analysis of sequences from the mitochondrial 16S ribosomal RNA gene of samples from the Iberian Peninsula and North Africa revealed a double origin for the Iberian population. The Mediterranean Iberian (Malaga) population is closely related to Mediterranean North African populations, with Atlantic Iberian populations more closely related to populations of the Atlantic coast of North Africa. The overall genetic differentiation and diversity observed was very low, preventing precise dating of the colonization events. However this low level of differentiation is not consistent with Plio-Pleistocene colonization, the assumed timing for a natural colonization event and suggests that chameleons were probably introduced twice by man in the recent past.

BACKGROUND:Ashbya gossypii is an industrially relevant microorganism traditionally used for riboflavin production. Despite the high gene homology and gene order conservation comparatively with Saccharomyces cerevisiae, it presents a lower level of genomic complexity. Its type of growth, placing it among filamentous fungi, questions how close it really is from the budding yeast, namely in terms of metabolism, therefore raising the need for an extensive and thorough study of its entire metabolism. This work reports the first manual enzymatic genome-wide re-annotation of A. gossypii as well as the first annotation of membrane transport proteins.RESULTS:After applying a developed enzymatic re-annotation pipeline, 847 genes were assigned with metabolic functions. Comparatively to KEGG's annotation, these data corrected the function for 14% of the common genes and increased the information for 52 genes, either completing existing partial EC numbers or adding new ones. Furthermore, 22 unreported enzymatic functions were found, corresponding to a significant increase in the knowledge of the metabolism of this organism. The information retrieved from the metabolic re-annotation and transport annotation was used for a comprehensive analysis of A. gossypii's metabolism in comparison to the one of S. cerevisiae (post-WGD - whole genome duplication) and Kluyveromyces lactis (pre-WGD), suggesting some relevant differences in several parts of their metabolism, with the majority being found for the metabolism of purines, pyrimidines, nitrogen and lipids. A considerable number of enzymes were found exclusively in A. gossypii comparatively with K. lactis (90) and S. cerevisiae (13). In a similar way, 176 and 123 enzymatic functions were absent on A. gossypii comparatively to K. lactis and S. cerevisiae, respectively, confirming some of the well-known phenotypes of this organism.CONCLUSIONS:This high quality metabolic re-annotation, together with the first membrane transporters annotation and the metabolic comparative analysis, represents a new important tool for the study and better understanding of A. gossypii's metabolism., Research described in this article was financially supported by FEDER and "Fundacao para a Ciencia e a Tecnologia" (FCT): Project AshByofactory (PTDC/EBB-EBI/101985/2008 - FCOMP-01-0124-FEDER-009701), Strategic Project PEst-OE/EQB/LA0023/2013, Project "BioInd - Biotechnology and Bioengineering for improved Industrial and Agro-Food processes, REF.NORTE-07-0124-FEDER-000028" Co-funded by the Programa Operacional Regional do Norte (ON.2 - O Novo Norte), QREN, FEDER and the PhD grant to DG (SFRH/BD/88623/2012).

We describe here the first genome-scale metabolic model of Kluyveromyces lactis, iOD907. It is partially compartmentalized (4 compartments), composed of 1867 reactions and 1476 metabolites. The iOD907 model performed well when assessing the positive growth of K. lactis to Biolog experiments and to an online catalogue of strains that provides information on carbon sources in which K. lactis is able to grow. Chemostat experiments were used to adjust non-growth-associated energy requirements, and the model proved accurate when predicting the biomass, oxygen and carbon dioxide yields. In silico knockouts predicted in vivo phenotypes accurately when compared to published experiments. The iOD907 genome-scale metabolic model complies with the MIRIAM standards for the annotation of enzymes, transporters, metabolites and reactions. Moreover, it contains direct links to KEGG (for enzymes, metabolites and reactions) and to TCDB for transporters, allowing easy comparisons to other models. Furthermore, this model is provided in the well-established SBML format, which means that it can be used in most metabolic engineering platforms, such as OptFlux or Cobra. The model is able to predict the behavior of K. lactis under different environmental conditions and genetic perturbations. Furthermore, it can also be important in the design of minimal media and will allow insights on the milk yeast's metabolism, as well as identifying metabolic engineering targets for the improvement of the production of products of interest by performing simulations and optimizations., The authors thank strategic Project PEst-OE/EQB/LA0023/2013 and project "BioInd - Biotechnology and Bioengineering for improved Industrial and Agro-Food processes, REF. NORTE-07-0124-FEDER-000028" co-funded by the Programa Operacional Regional do Norte (ON.2 - O Novo Norte), QREN, FEDER. The authors would also like to acknowledge Steve Sheridan for proof reading this manuscript.

Advances in sequencing technology are resulting in the rapid emergence of large numbers of complete genome sequences. High throughput annotation and metabolic modeling of these genomes is now a reality. The high throughput reconstruction and analysis of genome-scale transcriptional regulatory networks represents the next frontier in microbial bioinformatics. The fruition of this next frontier will depend upon the integration of numerous data sources relating to mechanisms, components, and behavior of the transcriptional regulatory machinery, as well as the integration of the regulatory machinery into genome-scale cellular models. Here we review existing repositories for different types of transcriptional regulatory data, including expression data, transcription factor data, and binding site locations, and we explore how these data are being used for the reconstruction of new regulatory networks. From template network based methods to de novo reverse engineering from expression data, we discuss how regulatory networks can be reconstructed and integrated with metabolic models to improve model predictions and performance. Finally, we explore the impact these integrated models can have in simulating phenotypes, optimizing the production of compounds of interest or paving the way to a whole-cell model., J.P.F. acknowledges funding from [SFRH/BD/70824/2010] of the FCT (Portuguese Foundation for Science and Technology) PhD program. The work was supported in part by the ERDF—European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness), National Funds through the FCT within projects [FCOMP-01-0124-FEDER015079] (ToMEGIM—Computational Tools for Metabolic Engineering using Genome-scale Integrated Models) and FCOMP-01-0124-FEDER009707 (HeliSysBio—molecular Systems Biology in Helicobacter pylori), the U.S. Department of Energy under contract [DE-ACO2-06CH11357] and the National Science Foundation under [0850546].

In this work, a simple chromatographic method is proposed and in-house validated for the quantification of total and individual fructooligossacharides (e.g., 1-kestose, nystose, and 1F-fructofuranosylnystose). It was shown that a high-performance liquid chromatography with refractive index detector could be used to monitor the dynamic of fructooligossacharides production via sucrose fermentation using Aspergillus aculeatus. This analytical technique may be easily implemented at laboratorial or industrial scale for fructooligossacharides mass-production monitoring allowing also controlling the main substrate (sucrose) and the secondary by-products (glucose and fructose). The proposed chromatographic method had a satisfactory intra- and inter-day variability (in general, with a relative standard deviation lower than 5%), high sensitivity for each sugar (usually, with a relative error lower than 5%), and low detection (lower than 0.06 ± 0.04 g/L) and quantification (lower than 0.2 ± 0.1 g/L) limits. The correct quantification of fructooligossacharides in fermentative media may allow a more precise nutritional formulation of new functional foods, since it is reported that different fructooligossacharides exhibit different biological activities and effects., This work was partially co-financed by FCT and FEDER under Program COMPETE (Project PEst-C/EQB/LA0020/2013), by the Strategic Project PEst-OE/EQB/LA0023/2013 and by the project ref. RECI/BBB-EBI/0179/2012 (project number FCOMP 01-0124-FEDER-027462) funded by Fundação para a Ciência e a Tecnologia.

The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells., J.C.X. is sponsored by grant SFRH/BD/81626/2011 from the Fundacao para a Ciencia e Tecnologia, Portugal.

In silico cell simulation approaches based in the use of genome-scale metabolic models (GSMMs) and constraint-based methods such as Flux Balance Analysis are gaining importance, but methods to integrate these approaches with omics data are still greatly needed. In this work, the focus relies on fluxomics data that provide valuable information on the intracellular fluxes, although in many cases in an indirect, incomplete and noisy way. The proposed framework enables the integration of fluxomics data, in the form of 13C labeling distribution for metabolite fragments, with GSMMs enriched with carbon atom transition maps. The algorithms implemented allow to infer labeling distributions for fragments/metabolites not measured and to build expressions for the relevant flux ratios that can be then used to enrich constraint-based methods for flux determination. This approach does not require any assumptions on the metabolic network and reaction reversibility, allowing to compute ratios originating from coupled joint points of the network. Also, when enough data do not exist, the system tries to infer ratio bounds from the measurements.