Degradation of chlorinated nitroaromatic compounds

Chlorinated nitroaromatic compounds (CNAs) are persistent environmental pollutants that have been introduced into the environment due to the anthropogenic activities. Bacteria that utilize CNAs as the sole sources of carbon and energy have been isolated from different contaminated and non-contaminated sites. Microbial metabolism of CNAs has been studied, and several metabolic pathways for degradation of CNAs have been proposed. Detoxification and biotransformation of CNAs have also been studied in various fungi, actinomycetes and bacteria. Several physicochemical methods have been used for treatment of wastewater containing CNAs; however, these methods are not suitable for in situ bioremediation. This review describes the current scenario of the degradation of CNAs.     

Degradation of nitroaromatic compounds by microorganisms

Nitroaromatic compounds are abundantly present in nature, but are in most cases highly toxic to living organisms. Several microorganisms, however, are capable of mineralizing or converting these compounds. Until now four pathways for the complete degradation of nitroaromatics have been described, which start with either the oxygenolytic or reductive removal of the nitro group from the aromatic ring or with this removal by means of replacement reactions. Besides these conversions many organisms are able to reduce nitroaromatics. The degradation of nitroaromatic compounds does not only occur in pure cultures but also in situ, for example in soil, water and sewage. However, several problems are associated with the application of microorganisms in the bioremediation of contaminated sites, as nitroaromatics or their conversion products may chemically interact with soil particles and cells. Besides the possibilities of applying microorganisms in the cleaning of sites contaminated with nitroaromatics, the use of microorganisms or enzymes in the biocatalytic production of industrially valuable products from nitroaromatics is also discussed.     

Directed evolution of metabolic pathways

The modification of cellular metabolism is of biotechnological and commercial significance because naturally occurring metabolic pathways are the source of diverse compounds used in fields ranging from medicine to bioremediation. Directed evolution is the experimental improvement of biocatalysts or cellular properties through iterative genetic diversification and selection procedures. The creation of novel metabolic functions without disrupting the balanced intracellular pool of metabolites is the primary challenge of pathway manipulation. The introduction of coordinated changes across multiple genetic elements, in conjunction with functional selection, presents an integrated approach for the modification of metabolism with benign physiological consequences. Directed evolution formats take advantage of the dynamic structures of genomes and genomic sub-structures and their ability to evolve in multiple directions in response to external stimuli. The elucidation, design and application of genome-restructuring mechanisms are key elements in the directed evolution of cellular metabolic pathways.     

Benzoxazinoid biosynthesis,a model for evolution of secondary metabolic pathways in plants

Benzoxazinoids are secondary metabolites that are effective in defence and allelopathy. They are synthesised in two subfamilies of the Poaceae and sporadically found in single species of the dicots. The biosynthesis is fully elucidated in maize; here the genes encoding the enzymes of the pathway are in physical proximity. This “biosynthetic cluster” might facilitate coordinated gene regulation. Data from Zea mays, Triticum aestivum and Hordeum lechleri suggest that the pathway is of monophyletic origin in the Poaceae. The branchpoint from the primary metabolism (Bx1 gene) can be traced back to duplication and functionalisation of the alpha-subunit of tryptophan synthase (TSA). Modification of the intermediates by consecutive hydroxylation is catalysed by members of a cytochrome P450 enzyme subfamily (Bx2–Bx5). Glucosylation by an UDP-glucosyltransferase (UGT, Bx8, Bx9) is essential for the reduction of autotoxicity of the benzoxazinoids. In some species 2,4-dihydroxy-1,4-benzoxazin-3-one-glucoside (DIBOA-glc) is further modified by the 2-oxoglutarate-dependent dioxygenase BX6 and the O-methyltransferase BX7. In the dicots Aphelandra squarrosa, Consolida orientalis, and Lamium galeobdolon, benzoxazinoid biosynthesis is analogously organised: The branchpoint is established by a homolog of TSA, P450 enzymes catalyse hydroxylations and at least the first hydroxylation reaction is identical in dicots and Poaceae, the toxic aglucon is glucosylated by an UGT. Functionally, TSA and BX1 are indole-glycerolphosphate lyases (IGLs). Igl genes seem to be generally duplicated in angiosperms. Modelling and biochemical characterisation of IGLs reveal that the catalytic properties of the enzyme can easily be modified by mutation. Independent evolution can be assumed for the BX1 function in dicots and Poaceae.     

Adaptive evolution of metabolic pathways in Drosophila

The adaptive significance of enzyme variation has been of central interest in population genetics. Yet, how natural selection operates on enzymes in the larger context of biochemical pathways has not been broadly explored. A basic expectation is that natural selection on metabolic phenotypes will target enzymes that control metabolic flux, but how adaptive variation is distributed among enzymes in metabolic networks is poorly understood. Here, we use population genetic methods to identify enzymes responding to adaptive selection in the pathways of central metabolism in Drosophila melanogaster and Drosophila simulans. We report polymorphism and divergence data for 17 genes that encode enzymes of 5 metabolic pathways that converge at glucose-6-phosphate (G6P). Deviations from neutral expectations were observed at five loci. Of the 10 genes that encode the enzymes of glycolysis, only aldolase (Ald) deviated from neutrality. The other 4 genes that were inconsistent with neutral evolution (glucose-6-phosphate dehydrogenase [G6pd]), phosphoglucomutase [Pgm], trehalose-6-phosphate synthetase [Tps1], and glucose-6phosphatase [G6pase] encode G6P branch point enzymes that catalyze reactions at the entry point to the pentose-phosphate, glycogenic, trehalose synthesis, and gluconeogenic pathways. We reconcile these results with population genetics theory and existing arguments on metabolic regulation and propose that the incidence of adaptive selection in this system is related to the distribution of flux control. The data suggest that adaptive evolution of G6P branch point enzymes may have special significance in metabolic adaptation.     

Degradation of 2,4-dinitrophenol and selected nitroaromatic compounds by Sphingomonas sp. UG30

Sphingomonas strain UG30 mineralizes both p-nitrophenol (PNP) and pentachlorophenol (PCP). Our current studies showed that UG30 oxidatively metabolized certain other p-substituted nitrophenols, i.e., p-nitrocatechol, 2,4-dinitrophenol (2,4-DNP), and 4,6-dinitrocresol with liberation of nitrite. 2,6-DNP, o- or m-nitrophenol, picric acid, or the herbicide dinoseb were not metabolized. Studies using 14C-labelled 2,4-DNP indicated that in glucose-glutamate broth cultures of UG30, greater than 90% of 103 microM 2,4-DNP was transformed to other compounds, while 8-19% of the 2,4-DNP was mineralized within 5 days. A significant portion (20-50%) of the 2,4-DNP was metabolized to highly polar metabolite(s) with one major unidentified metabolite accumulating from 5 to 25% of the initial radioactivity. The amounts of 2,4-DNP mineralized and converted to polar metabolites was affected by glutamate concentration in the medium. Nitrophenolic compounds metabolized by UG30 were also suitable substrates for the UG30 PCP-4-monooxygenase (pcpB gene expressed in Escherichia coli) which is likely central to degradation of these compounds. The wide substrate range of UG30 could render this strain useful in bioremediation of some chemically contaminated soils.     

Enzymatic dehalogenation of chlorinated nitroaromatic compounds

4-Chlorobenzoate dehalogenase from Pseudomonas sp. strain CBS3 converted 4-chloro-3,5-dinitrobenzoate to 3,5-dinitro-4-hydroxybenzoate and 1-chloro-2,4-dinitrobenzene to 2,4-dinitrophenol. The activities were 0.13 mU/mg of protein for 4-chloro-3,5-dinitrobenzoate and 0.16 mU/mg of protein for 1-chloro-2,4-dinitrobenzene compared with 0.5 mU/mg of protein for 4-chlorobenzoate.     

Enzymatic dehalogenation of chlorinated nitroaromatic compounds.

4-Chlorobenzoate dehalogenase from Pseudomonas sp. strain CBS3 converted 4-chloro-3,5-dinitrobenzoate to 3,5-dinitro-4-hydroxybenzoate and 1-chloro-2,4-dinitrobenzene to 2,4-dinitrophenol. The activities were 0.13 mU/mg of protein for 4-chloro-3,5-dinitrobenzoate and 0.16 mU/mg of protein for 1-chloro-2,4-dinitrobenzene compared with 0.5 mU/mg of protein for 4-chlorobenzoate.     

PathwayBooster: a tool to support the curation of metabolic pathways

Background

Despite several recent advances in the automated generation of draft metabolic reconstructions, the manual curation of these networks to produce high quality genome-scale metabolic models remains a labour-intensive and challenging task.

Results

We present PathwayBooster, an open-source software tool to support the manual comparison and curation of metabolic models. It combines gene annotations from GenBank files and other sources with information retrieved from the metabolic databases BRENDA and KEGG to produce a set of pathway diagrams and reports summarising the evidence for the presence of a reaction in a given organism’s metabolic network. By comparing multiple sources of evidence within a common framework, PathwayBooster assists the curator in the identification of likely false positive (misannotated enzyme) and false negative (pathway hole) reactions. Reaction evidence may be taken from alternative annotations of the same genome and/or a set of closely related organisms.

Conclusions

By integrating and visualising evidence from multiple sources, PathwayBooster reduces the manual effort required in the curation of a metabolic model. The software is available online at http://www.theosysbio.bio.ic.ac.uk/resources/pathwaybooster/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0447-2) contains supplementary material, which is available to authorized users.     

MMG: a probabilistic tool to identify submodules of metabolic pathways

Motivation: A fundamental task in systems biology is the identificationof groups of genes that are involved in the cellular responseto particular signals. At its simplest level, this often reducesto identifying biological quantities (mRNA abundance, enzymeconcentrations, etc.) which are differentially expressed intwo different conditions. Popular approaches involve using t-teststatistics, based on modelling the data as arising from a mixturedistribution. A common assumption of these approaches is thatthe data are independent and identically distributed; however,biological quantities are usually related through a complex(weighted) network of interactions, and often the more pertinentquestion is which subnetworks are differentially expressed,rather than which genes. Furthermore, in many interesting cases(such as high-throughput proteomics and metabolomics), onlyvery partial observations are available, resulting in the needfor efficient imputation techniques. Results: We introduce Mixture Model on Graphs (MMG), a novelprobabilistic model to identify differentially expressed submodulesof biological networks and pathways. The method can easily incorporateinformation about weights in the network, is robust againstmissing data and can be easily generalized to directed networks.We propose an efficient sampling strategy to infer posteriorprobabilities of differential expression, as well as posteriorprobabilities over the model parameters. We assess our methodon artificial data demonstrating significant improvements overstandard mixture model clustering. Analysis of our model resultson quantitative high-throughput proteomic data leads to theidentification of biologically significant subnetworks, as wellas the prediction of the expression level of a number of enzymes,some of which are then verified experimentally. Availability: MATLAB code is available from http://www.dcs.shef.ac.uk/~guido/software.html Contact: guido{at}dcs.shef.ac.uk Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Jonathan Wren     

Flavonoids: a colorful model for the regulation and evolution of biochemical pathways

For more than a century, the biosynthesis of flavonoid pigments has been a favorite of scientists to study a wide variety of biological processes, such as inheritance and transposition, and has become one of the best-studied pathways in nature. The analysis of pigmentation continues to provide insights into new areas, such as the channeling and intracellular transport of metabolites, regulation of gene expression and RNA interference. Moreover, because pigmentation is studied in a variety of species, it provides unique molecular insights into the evolution of biochemical pathways and regulatory networks.     

A markov classification model for metabolic pathways

Background  

This paper considers the problem of identifying pathways through metabolic networks that relate to a specific biological response. Our proposed model, HME3M, first identifies frequently traversed network paths using a Markov mixture model. Then by employing a hierarchical mixture of experts, separate classifiers are built using information specific to each path and combined into an ensemble prediction for the response.     

A mathematical model of metabolic insulin signaling pathways

We develop a mathematical model that explicitly represents many of the known signaling components mediating translocation of the insulin-responsive glucose transporter GLUT4 to gain insight into the complexities of metabolic insulin signaling pathways. A novel mechanistic model of postreceptor events including phosphorylation of insulin receptor substrate-1, activation of phosphatidylinositol 3-kinase, and subsequent activation of downstream kinases Akt and protein kinase C-zeta is coupled with previously validated subsystem models of insulin receptor binding, receptor recycling, and GLUT4 translocation. A system of differential equations is defined by the structure of the model. Rate constants and model parameters are constrained by published experimental data. Model simulations of insulin dose-response experiments agree with published experimental data and also generate expected qualitative behaviors such as sequential signal amplification and increased sensitivity of downstream components. We examined the consequences of incorporating feedback pathways as well as representing pathological conditions, such as increased levels of protein tyrosine phosphatases, to illustrate the utility of our model for exploring molecular mechanisms. We conclude that mathematical modeling of signal transduction pathways is a useful approach for gaining insight into the complexities of metabolic insulin signaling.     

Specificity space,the structure and evolution of metabolic pathways: Part II of a general theory

Biomolecular structures are interacting in terms of their force fields. These force fields define the specificity surfaces of the molecules. Specificity surfaces are represented by specificity vectors in a multidimensional specificity space. A quantitative analytical expression is developed for biochemical reactions and the evolution of metabolic pathways in the specificity space. This leads to detailed identification of various biomolecular processes with individual terms in the equation. This theoretical analysis permits defining detailed function and resolution requirement of enzymes, as well as, how these fit into the overall metabolic pattern of the cell. This paper is Part II of a general theory of the physical basis of the biological state of matter.     

Social evolution: pathways to ant unicoloniality

Unicolonial ant species live in interlinked populations known as super-colonies, where workers and queens move freely. New research suggests that low intra-specific resource competition leads to an absence of inter-colony aggression.     

Evolution of novel metabolic pathways for the degradation of chloroaromatic compounds

Chlorobenzenes are substrates not easily metabolized by existing bacteria in the environment. Specific strains, however, have been isolated from polluted environments or in laboratory selection procedures that use chlorobenzenes as their sole carbon and energy source. Genetic analysis indicated that these bacteria have acquired a novel combination of previously existing genes. One of these gene clusters contains the genes for an aromatic ring dioxy-genase and a dihydrodiol dehydrogenase. The other contains the genes for a chlorocatechol oxidative pathway. Comparison of such gene clusters with those from other aromatics degrading bacteria reveals that this process of recombining or assembly of existing genetic material must have occurred in many of them. Similarities of gene functions between pathways suggest that incorporation of existing genetic material has been the most important mechanism of expanding a metabolic pathway. Only in a few cases a horizontal expansion, that is acqui sition of gene functions to accomodate a wider range of substrates which are then all transformed in one central pathway, is observed on the genetic level. Evidence is presented indicating that the assembly process may trigger a faster divergence of nearby gene sequences. Further fine-tuning, for example by developing a proper regulation, is then the next step in the adaptation.     

Insight into trichomonas vaginalis genome evolution through metabolic pathways comparison

Trichomonas vaginalis causes the trichomoniasis, in women and urethritis and prostate cancer in men. Its genome draft published by TIGR in 2007 presents many unusual genomic and biochemical features like, exceptionally large genome size, the presence of hydrogenosome, gene duplication, lateral gene transfer mechanism and the presence of miRNA. To understand some of genomic features we have performed a comparative analysis of metabolic pathways of the T. vaginalis with other 22 significant common organisms. Enzymes from the biochemical pathways of T. vaginalis and other selected organisms were retrieved from the KEGG metabolic pathway database. The metabolic pathways of T. vaginalis common in other selected organisms were identified. Total 101 enzymes present in different metabolic pathways of T. vaginalis were found to be orthologous by using BLASTP program against the selected organisms. Except two enzymes all identified orthologous enzymes were also identified as paralogous enzymes. Seventy-five of identified enzymes were also identified as essential for the survival of T. vaginalis, while 26 as non-essential. The identified essential enzymes also represent as good candidate for novel drug targets. Interestingly, some of the identified orthologous and paralogous enzymes were found playing significant role in the key metabolic activities while others were found playing active role in the process of pathogenesis. The N-acetylneuraminate lyase was analyzed as the candidate of lateral genes transfer. These findings clearly suggest the active participation of lateral gene transfer and gene duplication during evolution of T. vaginalis from the enteric to the pathogenic urogenital environment.