Initiation and Prevention of Biological Damage by Radiation-Generated Protein Radicals

Ionizing radiations cause chemical damage to proteins. In aerobic aqueous solutions, the damage is commonly mediated by the hydroxyl free radicals generated from water, resulting in formation of protein radicals. Protein damage is especially significant in biological systems, because proteins are the most abundant targets of the radiation-generated radicals, the hydroxyl radical-protein reaction is fast, and the damage usually results in loss of their biological function. Under physiological conditions, proteins are initially oxidized to carbon-centered radicals, which can propagate the damage to other molecules. The most effective endogenous antioxidants, ascorbate, GSH, and urate, are unable to prevent all of the damage under the common condition of oxidative stress. In a promising development, recent work demonstrates the potential of polyphenols, their metabolites, and other aromatic compounds to repair protein radicals by the fast formation of less damaging radical adducts, thus potentially preventing the formation of a cascade of new reactive species.

GPRuler: Metabolic gene-protein-reaction rules automatic reconstruction

Metabolic network models are increasingly being used in health care and industry. As a consequence, many tools have been released to automate their reconstruction process de novo. In order to enable gene deletion simulations and integration of gene expression data, these networks must include gene-protein-reaction (GPR) rules, which describe with a Boolean logic relationships between the gene products (e.g., enzyme isoforms or subunits) associated with the catalysis of a given reaction. Nevertheless, the reconstruction of GPRs still remains a largely manual and time consuming process. Aiming at fully automating the reconstruction process of GPRs for any organism, we propose the open-source python-based framework GPRuler. By mining text and data from 9 different biological databases, GPRuler can reconstruct GPRs starting either from just the name of the target organism or from an existing metabolic model. The performance of the developed tool is evaluated at small-scale level for a manually curated metabolic model, and at genome-scale level for three metabolic models related to Homo sapiens and Saccharomyces cerevisiae organisms. By exploiting these models as benchmarks, the proposed tool shown its ability to reproduce the original GPR rules with a high level of accuracy. In all the tested scenarios, after a manual investigation of the mismatches between the rules proposed by GPRuler and the original ones, the proposed approach revealed to be in many cases more accurate than the original models. By complementing existing tools for metabolic network reconstruction with the possibility to reconstruct GPRs quickly and with a few resources, GPRuler paves the way to the study of context-specific metabolic networks, representing the active portion of the complete network in given conditions, for organisms of industrial or biomedical interest that have not been characterized metabolically yet.

Gene Deletion Algorithms for Minimum Reaction Network Design by Mixed-integer Linear Programming for Metabolite Production in Constraint-based Models: gDel_minRN

Background: Genome-scale constraint-based metabolic networks play an important role in the simulation of growth coupling, which means that cell growth and target metabolite production are simultaneously achieved. To achieve growth coupling, a minimal reaction-network-based design is known to be effective. However, the obtained reaction networks often fail to be realized by gene deletions due to conflicts with gene-protein-reaction relations.Results: Here, we developed gDel_minRN that determines gene deletion strategies using mixed-integer linear programming to achieve growth coupling by repressing the maximum number of reactions via gene-protein-reaction relations. Computational experiments were conducted in which gDel_minRN was applied to iML1515, a genome-scale model of Escherichia coli. The target metabolites were three vitamins that are highly valuable and require cost-effective bioprocesses for economics and the environment. gDel_minRN successfully calculated gene deletion strategies that achieve growth coupling for the production of biotin (vitamin B7), riboflavin (vitamin B2), and pantothenate (vitaminB5).Conclusion: Since gDel_minRN calculates a constraint-based model of the minimum number of gene-associated reactions without conflict with gene-protein-reaction relations, it helps biological analysis of the core parts essential for growth coupling for each target metabolite. The source codes are implemented in MATLAB, CPLEX, and COBRA Toolbox. The obtained data and source codes are available on https://github.com/taketam/gDel-minRN

GPRuler: metabolic Gene-Protein-Reaction rules automatic reconstruction

BackgroundMetabolic network models are increasingly being used in health care and industry. As a consequence, many tools have been released to automate their reconstruction process de novo. In order to enable gene deletion simulations and integration of gene expression data, these networks must include gene-protein-reaction (GPR) rules, which describe with a Boolean logic relationships between the gene products (e.g., enzyme isoforms or subunits) associated with the catalysis of a given reaction. Nevertheless, the reconstruction of GPRs still remains a largely manual and time consuming process. Aiming at fully automating the reconstruction process of GPRs for any organism, we propose the open-source python-based framework GPRuler.ResultsBy mining text and data from 9 different biological databases, GPRuler can reconstruct GPRs starting either from just the name of the target organism or from an existing metabolic model. The performance of the developed tool is evaluated at small-scale level for a manually curated metabolic model, and at genome-scale level for three metabolic models related to Homo sapiens and Saccharomyces cerevisiae organisms. By exploiting these models as benchmarks, the proposed tool shown its ability to reproduce the original GPR rules with a high level of accuracy. In all the tested scenarios, after a manual investigation of the mismatches between the rules proposed by GPRuler and the original ones, the proposed approach revealed to be in many cases more accurate than the original models.ConclusionsBy complementing existing tools for metabolic network reconstruction with the possibility to reconstruct GPRs quickly and with a few resources, GPRuler paves the way to the study of context-specific metabolic networks, representing the active portion of the complete network in given conditions, for organisms of industrial or biomedical interest that have not been characterized metabolically yet.

Nematicidal Streptomyces against Meloidogyne incognita by hydrosoluble macromolecules

Background: Although actinomycetes, which produce antibiotics, have been reported to produce nematicidal metabolites, macromolecules with nematicidal activities have rarely been described. Results: The culture filtrates of Streptomyces albogriseolus strain DN41 and S. fimicarius strain D153 presented 82.13 % and 86.96 % nematicidal activity against Meloidogyne incognita, respectively, after 12 h. A pot experiment highlighted that these culture filtrates were characterised by significant efficacy. The biocontrol efficiency of strain DN41 reached 61.68 % and that of strain D153 68.33 % after 30 days at a dose of 100 mL pot-1. The active metabolites produced by the two strains were hydrosoluble and sensitive to heat, with molecular weights above 8000 Da for DN41 and of 1000–8000 Da for D153. However, these metabolites were negative to protein reaction. A chemical characteristic test indicated that these active metabolites were polar polymers that contained a large amount of sugar and phenolic hydroxyl compounds. Conclusions: These results revealed S. albogriseolus strain DN41 and S. fimicarius strain D153 as potential agents for the control of root-knot nematodes, as hydrosoluble macromolecules have good compatibility and are convenient for practical application.

Conformation of the Intermediates in the Reaction Catalyzed by Protoporphyrinogen Oxidase: An In Silico Analysis

Protoporphyrinogen oxidase (PPO) is a critical enzyme across life as the last common step in the synthesis of many metalloporphyrins. The reaction mechanism of PPO was assessed in silico and the unstructured loop near the binding pocket was investigated. The substrate, intermediates, and product were docked in the catalytic domain of PPO using a modified Autodock method, introducing flexibility in the macrocycles. Sixteen PPO protein sequences across phyla were aligned and analyzed with Phyre2 and ProteinPredict to study the unstructured loop from residue 204–210 in the H. sapiens structure. Docking of the substrate, intermediates, and product all resulted in negative binding energies, though the substrate had a lower energy than the others by 40%. The α-H of C10 was found to be 1.4 angstroms closer to FAD than the β-H, explaining previous reports of the reaction occurring on the meso face of the substrate. A lack of homology in sequence or length in the unstructured loop indicates a lack of function for the protein reaction. This docking study supports a reaction mechanism proposed previously whereby all hydride abstractions occur on the C10 of the tetrapyrrole followed by tautomeric rearrangement to prepare the intermediate for the next reaction.

Silica nanoparticles induce unfolded protein reaction mediated apoptosis in spermatocyte cells

With increasing air pollution, silica nanoparticles (SiNPs), as a main inorganic member of PM2.5, have gained increasing attention to its reproductive toxicity. Most existing studies focused on the acute exposure, while data regarding the chronic effect of SiNPs on reproduction is limited. Therefore, this study was designed to evaluate the chronic toxicity of SiNPs on spermatocyte cells. The cells were continuously exposed to SiNPs for 1, 10, 20 and 30 generations at dose of 5 μg/ml SiNPs for 24 h per generation after attachment. The results showed that with the increasing generations of the exposure, SiNPs decreased the viability of spermatocyte cells, induced apoptosis and increased the level of reactive oxygen species in spermatocyte cells. Moreover, SiNPs increased the protein expression of GRP-78, p-PERK, IRE1α, ATF6 and Cleaved caspase-3 in spermatocyte cells, suggesting that SiNPs improved unfolded protein response (UPR) and apoptosis. The present results indicated that the long-term and low-dose exposure to SiNPs could induce apoptosis by triggering ROS-mediated UPR in spermatocyte cells.