PHYTOCHEMICAL PROFILE WITH ANTI-TUMOR ACTIVITY ESTIMATION OF CRUDE EXTRACT, ESSENTIAL OIL AND D-LIMONENE FROM CITRUS AURANTIUM L. AGAINST EHRLICH CARCINOMA

Objective: Plant based drugs have been a solution in the search for more cost-effective and less harmful drugs for the treatment of neoplasia. Citrus aurantium L. (Rutaceae) is abundant in Brazil and D-limonene, a monoterpene used in the prevention and treatment of neoplasia, was identified as a major compound in the oil of this specie. Objective of current study includes estimation of anti-tumor activity of Citrus aurantium L. (Rutaceae) (crude extract, essential oil and D-limonene) against Ehrlich carcinoma, as well as their phytochemical evaluation (D-limonene and essential oil). Methods: There was a randomized non-clinical trial in which were used adult male mice (Balb-C). Four groups of animals were used having 6 numbers of animal in each group. All groups were inoculated with the Ehrlich tumor and then received the treatment (control, crude extract, essential oil and D-limonene) by oral route daily (28 day treatment). Essential oil was obtained by hydro-distillation and analyzed by the means of GC (Gas Chromatography) that was attached to mass spectrometry. In last of the observations  hemogram was obtained. Results: Animals treated with the essential oil has shown no significant difference compared to the group treated with D-limonene. The group treated with crude extract had a growth inhibition close to the essential oil and D-limonene groups. Conclusion: It´s concluded that the essential oil and the crude extract of Citrus aurantium, L. (Rutaceae) can become therapeutic agents because of their anti-tumor activity with no toxicity to the blood cells and have low cost of production. Further studies are necessary, so they can be used in the treatment of neoplasia in humans. The chromatographic and spectrometric analyzes indicated the presence of other components in smaller amounts in the essential oil, which suggests that they could have a synergic activity to the D-limonene.                           Peer Review History: Received 2 June 2020; Revised 25 June; Accepted 4 July, Available online 15 July 2020 Academic Editor: Dr. Muhammad Zahid Iqbal, AIMST University, Malaysia, [email protected] UJPR follows the most transparent and toughest ‘Advanced OPEN peer review’ system. The identity of the authors and, reviewers will be known to each other. This transparent process will help to eradicate any possible malicious/purposeful interference by any person (publishing staff, reviewer, editor, author, etc) during peer review. As a result of this unique system, all reviewers will get their due recognition and respect, once their names are published in the papers. We expect that, by publishing peer review reports with published papers, will be helpful to many authors for drafting their article according to the specifications. Auhors will remove any error of their article and they will improve their article(s) according to the previous reports displayed with published article(s). The main purpose of it is ‘to improve the quality of a candidate manuscript’. Our reviewers check the ‘strength and weakness of a manuscript honestly’. There will increase in the perfection, and transparency. Received file:                Reviewer's Comments: Average Peer review marks at initial stage: 6.0/10 Average Peer review marks at publication stage: 8.0/10 Reviewer(s) detail: Ahmad Najib, Universitas Muslim Indonesia, Makassar, Indonesia, [email protected] Dr. Mohamed Said Fathy Al-Refaey, University of Sadat City, Menofia, Egypt, [email protected]  Similar Articles: CYTOTOXIC EFFECT AND PHYTOCHEMICAL STUDY OF PETROLEUM ETHER EXTRACT OF TILIA CORDATA MIL

Development of a framework for metabolic pathway analysis-driven strain optimization methods

Genome-scale metabolic models (GSMMs) have become important assets for rational design of compound overproduction using microbial cell factories. Most computational strain optimization methods (CSOM) using GSMMs, while useful in metabolic engineering, rely on the definition of questionable cell objectives, leading to some bias. Metabolic pathway analysis approaches do not require an objective function. Though their use brings immediate advantages, it has mostly been restricted to small scale models due to computational demands. Additionally, their complex parameterization and lack of intuitive tools pose an important challenge towards making these widely available to the community. Recently, MCSEnumerator has extended the scale of these methods, namely regarding enumeration of minimal cut sets, now able to handle GSMMs. This work proposes a tool implementing this method as a Java library and a plugin within the OptFlux metabolic engineering platform providing a friendly user interface. A standard enumeration problem and pipeline applicable to GSMMs is proposed, making use by the community simpler. To highlight the potential of these approaches, we devised a case study for overproduction of succinate, providing a phenotype analysis of a selected strategy and comparing robustness with a selected solution from a bi-level CSOM.The authors thank the project “DeYeastLibrary—Designer yeast strain library optimized for metabolic engineering applications”, Ref. ERA-IB-2/0003/2013, funded by national funds through “Fundação para a Ciência e Tecnologia / Ministério da Ciência, Tecnologia e Ensino Superior”.info:eu-repo/semantics/publishedVersio

OptFlux: an open-source software platform for in silico metabolic engineering

<p>Abstract</p> <p>Background</p> <p>Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications.</p> <p>Results</p> <p><it>OptFlux </it>is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes.</p> <p><it>OptFlux </it>also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms.</p> <p>The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. <it>OptFlux </it>has a visualization module that allows the analysis of the model structure that is compatible with the layout information of <it>Cell Designer</it>, allowing the superimposition of simulation results with the model graph.</p> <p>Conclusions</p> <p>The <it>OptFlux </it>software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization algorithms and the final users. It is a valuable platform for researchers in the field that have available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community.</p> <p>Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean network based regulatory models.</p

Magnetic and structural properties of fcc/hcp bi-crystalline multilayer Co nanowire arrays prepared by controlled electroplating

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)We report on the structural and magnetic properties of crystalline bi-phase Co nanowires, electrodeposited into the pores of anodized alumina membranes, as a function of their length. Co nanowires present two different coexistent crystalline structures (fcc and hcp) that can be controlled by the time of pulsed electrodeposition. The fcc crystalline phase grows at the early stage and is present at the bottom of all the nanowires, strongly influencing their magnetic behavior. Both structural and magnetic characterizations indicate that the length of the fcc phase is constant at around 260-270 nm. X-ray diffraction measurements revealed a strong preferential orientation (texture) in the (1 0-1 0) direction for the hcp phase, which increases the nanowire length as well as crystalline grain size, degree of orientation, and volume fraction of oriented material. The first-order reversal curve (FORC) method was used to infer both qualitatively and quantitatively the complex magnetization reversal of the nanowires. Under the application of a magnetic field parallel to the wires, the magnetization reversal of each region is clearly distinguishable; the fcc phase creates a high coercive contribution without an interaction field, while the hcp phase presents a smaller coercivity and undergoes a strong antiparallel interaction field from neighboring wires. (C) 2011 American Institute of Physics. [doi:10.1063/1.3553865]1098Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Guggenheim FellowshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

An integrated network visualization framework towards metabolic engineering applications

Background Over the last years, several methods for the phenotype simulation of microorganisms, under specified genetic and environmental conditions have been proposed, in the context of Metabolic Engineering (ME). These methods provided insight on the functioning of microbial metabolism and played a key role in the design of genetic modifications that can lead to strains of industrial interest. On the other hand, in the context of Systems Biology research, biological network visualization has reinforced its role as a core tool in understanding biological processes. However, it has been scarcely used to foster ME related methods, in spite of the acknowledged potential. Results In this work, an open-source software that aims to fill the gap between ME and metabolic network visualization is proposed, in the form of a plugin to the OptFlux ME platform. The framework is based on an abstract layer, where the network is represented as a bipartite graph containing minimal information about the underlying entities and their desired relative placement. The framework provides input/output support for networks specified in standard formats, such as XGMML, SBGN or SBML, providing a connection to genome-scale metabolic models. An user-interface makes it possible to edit, manipulate and query nodes in the network, providing tools to visualize diverse effects, including visual filters and aspect changing (e.g. colors, shapes and sizes). These tools are particularly interesting for ME, since they allow overlaying phenotype simulation results or elementary flux modes over the networks. Conclusions The framework and its source code are freely available, together with documentation and other resources, being illustrated with well documented case studies.This work is partially funded 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 project ref. COMPETE FCOMP-01-0124-FEDER-015079 and the FCT Strategic Project PEst-OE/EQB/LA0023/2013. The work of PV is funded by PhD grant ref. SFRH/BDE/51442/2011

Iron, silicate, and light co-limitation of three Southern Ocean diatom species

The effect of combined iron, silicate, and light co-limitation was investigated in the three diatom species Actinocyclus sp. Ehrenberg, Chaetoceros dichaeta Ehrenberg, and Chaetoceros debilis Cleve, isolated from the Southern Ocean (SO). Growth of all species was co-limited by iron and silicate, reflected in a significant increase in the number of cell divisions compared to the control. Lowest relative Si uptake and drastic frustule malformation was found under iron and silicate co-limitation in C. dichaeta, while Si limitation in general caused cell elongation in both Chaetoceros species. Higher light intensities similar to SO surface conditions showed a negative impact on growth of C. dichaeta and Actinocyclus sp. and no effect on C. debilis. This is in contrast to the assumed light limitation of SO diatoms due to deep wind driven mixing. Our results suggest that growth and species composition of Southern Ocean diatoms is influenced by a sensitive interaction of the abiotic factors, iron, silicate, and light

What traits are carried on mobile genetic elements, and why?

Although similar to any other organism, prokaryotes can transfer genes vertically from mother cell to daughter cell, they can also exchange certain genes horizontally. Genes can move within and between genomes at fast rates because of mobile genetic elements (MGEs). Although mobile elements are fundamentally self-interested entities, and thus replicate for their own gain, they frequently carry genes beneficial for their hosts and/or the neighbours of their hosts. Many genes that are carried by mobile elements code for traits that are expressed outside of the cell. Such traits are involved in bacterial sociality, such as the production of public goods, which benefit a cell's neighbours, or the production of bacteriocins, which harm a cell's neighbours. In this study we review the patterns that are emerging in the types of genes carried by mobile elements, and discuss the evolutionary and ecological conditions under which mobile elements evolve to carry their peculiar mix of parasitic, beneficial and cooperative genes

Bacteriophages benefit from generalized transduction

Temperate phages are bacterial viruses that as part of their life cycle reside in the bacterial genome as prophages. They are found in many species including most clinical strains of the human pathogens, Staphylococcus aureus and Salmonella enterica serovar Typhimurium. Previously, temperate phages were considered as only bacterial predators, but mounting evidence point to both antagonistic and mutualistic interactions with for example some temperate phages contributing to virulence by encoding virulence factors. Here we show that generalized transduction, one type of bacterial DNA transfer by phages, can create conditions where not only the recipient host but also the transducing phage benefit. With antibiotic resistance as a model trait we used individual-based models and experimental approaches to show that antibiotic susceptible cells become resistant to both antibiotics and phage by i) integrating the generalized transducing temperate phages and ii) acquiring transducing phage particles carrying antibiotic resistance genes obtained from resistant cells in the environment. This is not observed for non-generalized transducing temperate phages, which are unable to package bacterial DNA, nor for generalized transducing virulent phages that do not form lysogens. Once established, the lysogenic host and the prophage benefit from the existence of transducing particles that can shuffle bacterial genes between lysogens and for example disseminate resistance to antibiotics, a trait not encoded by the phage. This facilitates bacterial survival and leads to phage population growth. We propose that generalized transduction can function as a mutualistic trait where temperate phages cooperate with their hosts to survive in rapidly-changing environments. This implies that generalized transduction is not just an error in DNA packaging but is selected for by phages to ensure their survival

Natural computation meta-heuristics for the in silico optimization of microbial strains

<p>Abstract</p> <p>Background</p> <p>One of the greatest challenges in Metabolic Engineering is to develop quantitative models and algorithms to identify a set of genetic manipulations that will result in a microbial strain with a desirable metabolic phenotype which typically means having a high yield/productivity. This challenge is not only due to the inherent complexity of the metabolic and regulatory networks, but also to the lack of appropriate modelling and optimization tools. To this end, Evolutionary Algorithms (EAs) have been proposed for <it>in silico </it>metabolic engineering, for example, to identify sets of gene deletions towards maximization of a desired physiological objective function. In this approach, each mutant strain is evaluated by resorting to the simulation of its phenotype using the Flux-Balance Analysis (FBA) approach, together with the premise that microorganisms have maximized their growth along natural evolution.</p> <p>Results</p> <p>This work reports on improved EAs, as well as novel Simulated Annealing (SA) algorithms to address the task of <it>in silico </it>metabolic engineering. Both approaches use a variable size set-based representation, thereby allowing the automatic finding of the best number of gene deletions necessary for achieving a given productivity goal. The work presents extensive computational experiments, involving four case studies that consider the production of succinic and lactic acid as the targets, by using <it>S. cerevisiae </it>and <it>E. coli </it>as model organisms. The proposed algorithms are able to reach optimal/near-optimal solutions regarding the production of the desired compounds and presenting low variability among the several runs.</p> <p>Conclusion</p> <p>The results show that the proposed SA and EA both perform well in the optimization task. A comparison between them is favourable to the SA in terms of consistency in obtaining optimal solutions and faster convergence. In both cases, the use of variable size representations allows the automatic discovery of the approximate number of gene deletions, without compromising the optimality of the solutions.</p