Biosynthetic potentials of metabolites and their hierarchical organization

A major challenge in systems biology is to understand how complex and highly connected metabolic networks are organized. The structure of these networks is investigated here by identifying sets of metabolites that have a similar biosynthetic potential. We measure the biosynthetic potential of a particular compound by determining all metabolites than can be produced from it and, following a terminology introduced previously, call this set the scope of the compound. To identify groups of compounds with similar scopes, we apply a hierarchical clustering method. We find that compounds within the same cluster often display similar chemical structures and appear in the same metabolic pathway. For each cluster we define a consensus scope by determining a set of metabolites that is most similar to all scopes within the cluster. This allows for a generalization from scopes of single compounds to scopes of a chemical family. We observe that most of the resulting consensus scopes overlap or are fully contained in others, revealing a hierarchical ordering of metabolites according to their biosynthetic potential. Our investigations show that this hierarchy is not only determined by the chemical complexity of the metabolites, but also strongly by their biological function. As a general tendency, metabolites which are necessary for essential cellular processes exhibit a larger biosynthetic potential than those involved in secondary metabolism. A central result is that chemically very similar substances with different biological functions may differ significantly in their biosynthetic potentials. Our studies provide an important step towards understanding fundamental design principles of metabolic networks determined by the structural and functional complexity of metabolites.     

Towards inference of a biochemical ontology from a metabolic database

In order to predict the metabolic fate of an arbitrary compound based solely on structure, it is useful to be able to identify substructural 'functional groups' that are biochemically reactive. These functional groups are the substructural elements that can be removed and replaced to transform one compound into another. This problem of identifying functional groups is related to the problem of classifying compounds. The research presented here discusses the state of the art in biochemical databases and how these sources may be applied to the problem of classifying compounds based solely on structure. We describe a biochemical informatics system for processing molecular data and describe how 100 255 compositional (hasA) relationships are inferred between 835 abstractions and 9500 metabolites from the KEGG Ligand database. Specifically, we focus on the identification of amino acids and consider ways in which the inference of biochemical ontologies for metabolites will be improved in the future.     

Metabolome searcher: a high throughput tool for metabolite identification and metabolic pathway mapping directly from mass spectrometry and using genome restriction

Background

Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism’s genome as a database restricts metabolite identification to only those compounds that the organism can produce.

Results

To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment’s MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis.

Conclusions

Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome.     

In vitro bone marrow granulocyte-macrophage progenitor cultures in the assessment of hematotoxic potential of the new drugs

In pharmaceutical research, in vitro toxicity tests, for assessing the potential toxicity of new chemical entities are necessary in the early stages of the developmental process, when no information is available about the metabolism or even the target organ toxicity of the compounds to be tested. In vitro specific organ toxicity tests, such as the granulocyte-macrophage colony-forming unit (CFU-GM) clonogenic assay, are useful tools for predicting the adverse effects of new compounds on the blood-forming system, provided that some reference points are available, e.g., toxicological information about compounds belonging to the same chemical class and structure-activity relationship data. Furthermore, when no information is available about metabolism, the in vitro system should cover as many possibilities as possible, to avoid false positive or false negative results. In fact, while many compounds are metabolized to a variety of inactive chemical species, some undergo bioactivation to form more active metabolites. The addition of a metabolic activation system to the CFU-GM assay enables assessment of direct and metabolism-mediated toxicity. The regulatory agencies and industry value the concept of assays performed with and without metabolic activation, since they often have to take decisions about compounds with unknown mechanisms of action. CFU-GM assay, designed in this way, is an example of such a mechanism-naive assay. It has been suggested that, for new compounds, metabolites should be generated and tested both in the presence and in the absence of the parent compound itself, to identify the possible contribution of metabolites to the hematotoxicity observed, and to determine whether there is any synergistic or antagonistic effect between metabolites and the parent compound that might affect hematotoxicity in vivo. Various approaches can be used to obtain such information.     

Hierarchy of metabolic compounds based on their synthesising capacity

The concept of scopes is applied to analyse large metabolic networks. Scopes are defined as sets of metabolites that can be synthesised by a metabolic network when it is provided with given seeds (Sets of initial metabolic compounds). Thus, scopes represent synthesising capacities of the seeds in the network. A hierarchy is discussed in the sense that compounds, which are part of the scope of another compound, possess scopes themselves that are subsets of the former scope. This hierarchy is analysed by means of a directed acyclic graph. Using a simple chemical model, it is found that this hierarchy contains specific structures that can, to a large extent, be explained by the chemical composition of the participating compounds. In this way, it represents a new kind of map of metabolic networks, arranging the metabolic compounds according to their chemical capacity.     

Mass spectrometric identification of urinary and plasma metabolites of 9-hydroxy-19,20-bis-nor-prostanoic acid (rosaprostol)

9-Hydroxy-19,20-bis-nor-prostanoic acid (Rosaprostol) is an antiulcer compound with antisecretory and cytoprotective action. We studied the metabolites of Rosaprostol found in human plasma and in human and rat urine. Sixteen different metabolites were tentatively identified on the basis of their mass spectra. Two presumed metabolites were synthesized. To clarify the identities of some of them, deuterated Rosaprostol was administered to rats and mass spectra of the deuterated and protonated metabolites were examined. Rosaprostol is metabolized following three metabolic pathways leading, combined, to oxidized compounds with a lower number of carbons than the parent drug.     

Novel nuclear magnetic resonance spectroscopy methods demonstrate preferential carbon source utilization by Acinetobacter calcoaceticus.

Novel nuclear magnetic resonance spectroscopy techniques, designated metabolic observation, were used to study aromatic compound degradation by the soil bacterium Acinetobacter calcoaceticus. Bacteria which had been rendered spectroscopically invisible by growth with deuterated (2H) medium were used to inoculate cultures in which natural-abundance 1H hydrogen isotopes were provided solely by aromatic carbon sources in an otherwise 2H medium. Samples taken during the incubation of these cultures were analyzed by proton nuclear magnetic resonance spectroscopy, and proton signals were correlated with the corresponding aromatic compounds or their metabolic descendants. This approach allowed the identification and quantitation of metabolites which accumulated during growth. This in vivo metabolic monitoring facilitated studies of catabolism in the presence of multiple carbon sources, a topic about which relatively little is known. A. calcoaceticus initiates aromatic compound dissimilation by forming catechol or protocatechuate from a variety of substrates. Degradation proceeds via the beta-ketoadipate pathway, comprising two discrete branches that convert catechol or protocatechuate to tricarboxylic acid cycle intermediates. As shown below, when provided with several carbon sources simultaneously, all degraded via the beta-ketoadipate pathway, A. calcoaceticus preferentially degraded specific compounds. For example, benzoate, degraded via the catechol branch, was consumed in preference to p-hydroxybenzoate, degraded via the protocatechuate branch, when both compounds were present. To determine if this preference were governed by metabolites unique to catechol degradation, pathway mutants were constructed. Studies of these mutants indicated that the product of catechol ring cleavage, cis,cis-muconate, inhibited the utilization of p-hydroxybenzoate in the presence of benzoate. The accumulation of high levels of cis,cis-muconate also appeared to be toxic to the cells.     

MMT--a pathway modeling tool for data from rapid sampling experiments

The identification of metabolic regulation is a major concern in metabolic engineering. Metabolic regulation phenomena depend on intracellular compounds such as enzymes, metabolites and cofactors. A complete understanding of metabolic regulation requires quantitative information about these compounds under in vivo conditions. This quantitative knowledge in combination with the known network of metabolic pathways allows the construction of mathematical models that describe the dynamic changes in metabolite concentrations over time. Rapid sampling combined with pulse experiments is a useful tool for the identification of metabolic regulation owing to the transient data they provide. Enzymatic tests in combination with ESI-LC-MS (Electrospray Ionization Liquid Chromatographic Tandem Mass Spectrometry) and HPLC measurements have been used to identify up to 30 metabolites and nucleotides from rapid sampling experiments. A metabolic modeling tool (MMT) that is built on a relational database was developed specifically for analysis of rapid sampling experiments. The tool allows to construct complex pathway models with information stored in the relational database. Parameter fitting and simulation algorithms for the resulting system of Ordinary Differential Equations (ODEs) are part of MMT. Additionally explicit sensitivity functions are calculated. The integration of all necessary algorithms in one tool allows fast model analysis and comparison. Complex models have been developed to describe the central metabolic pathways of Escherichia coli during a glucose pulse experiment.     

Peltate glandular trichomes of Colquhounia seguinii harbor new defensive clerodane diterpenoids

Glandular trichomes produce a wide variety of secondary metabolites that are considered as major defen-sive chemicals against herbivore attack. The morphology and secondary metabolites of the peltate g...     

Encoding microbial metabolic logic: predicting biodegradation

Prediction of microbial metabolism is important for annotating genome sequences and for understanding the fate of chemicals in the environment. A metabolic pathway prediction system (PPS) has been developed that is freely available on the world wide web (), recognizes the organic functional groups found in a compound, and predicts transformations based on metabolic rules. These rules are designed largely by examining reactions catalogued in the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD) and are generalized based on metabolic logic. The predictive accuracy of the PPS was tested: (1) using a 113-member set of compounds found in the database, (2) against a set of compounds whose metabolism was predicted by human experts, and (3) for consistency with experimental microbial growth studies. First, the system correctly predicted known metabolism for 111 of the 113 compounds containing C and H, O, N, S, P and/or halides that initiate existing pathways in the database, and also correctly predicted 410 of the 569 known pathway branches for these compounds. Second, computer predictions were compared to predictions by human experts for biodegradation of six compounds whose metabolism was not described in the literature. Third, the system predicted reactions liberating ammonia from three organonitrogen compounds, consistent with laboratory experiments showing that each compound served as the sole nitrogen source supporting microbial growth. The rule-based nature of the PPS makes it transparent, expandable, and adaptable.     

Comprehensive metabolic fingerprinting of Withania somnifera leaf and root extracts

Profiling of metabolites is a rapidly expanding area of research for resolving metabolic pathways. Metabolic fingerprinting in medicinally important plants is critical to establishing the quality of herbal medicines. In the present study, metabolic profiling of crude extracts of leaf and root of Withania somnifera (Ashwagandha), an important medicinal plant of Indian system of medicine (ISM) was carried out using NMR and chromatographic (HPLC and GC-MS) techniques. A total of 62 major and minor primary and secondary metabolites from leaves and 48 from roots were unambiguously identified. Twenty-nine of these were common to the two tissues. These included fatty acids, organic acids, amino acids, sugars and sterol based compounds. Eleven bioactive sterol-lactone molecules were also identified. Twenty-seven of the identified metabolites were quantified. Highly significant qualitative and quantitative differences were noticed between the leaf and root tissues, particularly with respect to the secondary metabolites.     

Identification of 11-dehydro-TXB2 as a suitable parameter for monitoring thromboxane production in the human

In order to identify suitable parameters for measurement of thromboxane production in vivo, the metabolism of TXB2 was studied in the human. [3H8]-TXB2 was given intravenously to a healthy human volunteer. Blood samples were collected for 50 min after the injection, and urine was collected for 24 hours. The urinary and blood metabolic profiles were visualized by the use of two-dimensional TLC and autoradiography. Identification of metabolites was achieved with GC/MS and in some cases by cochromatography with reference compounds in TLC and GC. In blood, unmetabolized TXB2 was the dominating compound during the first 30 min. Three less polar metabolites appeared, two of which were identified as 11-dehydro-TXB2 and 11,15-didehydro-13,14-dihydro-TXB2, respectively. The third compound was tentatively identified as 15-dehydro-13,14-dihydro-TXB2. Since 11-dehydro-TXB2 was one of the major metabolites in blood as well as urine, it was deemed suitable as target for measurement of thromboxane production in vivo. The advantages of 11-dehydro-TXB2 over its parent compound, TXB2, were demonstrated in experiments where unlabeled TXB2 was injected i.v. to a human volunteer, and the blood and urinary levels of both compounds were then followed by radioimmunoassay. Measured levels of 11-dehydro-TXB2 were found to give a more reliable picture of metabolic events than TXB2, the latter compound to a large extent reflecting technical difficulties during blood sample collection.     

Inferring meaningful pathways in weighted metabolic networks

An approach is presented for computing meaningful pathways in the network of small molecule metabolism comprising the chemical reactions characterized in all organisms. The metabolic network is described as a weighted graph in which all the compounds are included, but each compound is assigned a weight equal to the number of reactions in which it participates. Path finding is performed in this graph by searching for one or more paths with lowest weight. Performance is evaluated systematically by computing paths between the first and last reactions in annotated metabolic pathways, and comparing the intermediate reactions in the computed pathways to those in the annotated ones. For the sake of comparison, paths are computed also in the un-weighted raw (all compounds and reactions) and filtered (highly connected pool metabolites removed) metabolic graphs, respectively. The correspondence between the computed and annotated pathways is very poor (<30%) in the raw graph; increasing to approximately 65% in the filtered graph; reaching approximately 85% in the weighted graph. Considering the best-matching path among the five lightest paths increases the correspondence to 92%, on average. We then show that the average distance between pairs of metabolites is significantly larger in the weighted graph than in the raw unfiltered graph, suggesting that the small-world properties previously reported for metabolic networks probably result from irrelevant shortcuts through pool metabolites. In addition, we provide evidence that the length of the shortest path in the weighted graph represents a valid measure of the "metabolic distance" between enzymes. We suggest that the success of our simplistic approach is rooted in the high degree of specificity of the reactions in metabolic pathways, presumably reflecting thermodynamic constraints operating in these pathways. We expect our approach to find useful applications in inferring metabolic pathways in newly sequenced genomes.     

Anthracycline metabolites of tetracenomycin C-nonproducing Streptomyces glaucescens mutants.

Mutants of Streptomyces glaucescens GLA.0 which are blocked in the production of tetracenomycin C (compound 1), an anthracycline antibiotic having significant antitumor activity, accumulated several new anthracycline metabolites structurally related to compound 1 and to intermediates of its biosynthetic pathway. Through chemical and spectroscopic comparisons with the known anthracycline metabolites of the wild-type strain, we identified the two regioisomers of tetracenomycin B2 (compounds 7a and 7b), 8-demethyltetracenomycin C (compound 12), tetracenomycin D2 (compound 11), tetracenomycin E (compound 13), and the 12-naphthacenone forms of compounds 7a, 7b, and 2 (tetracenomycin D1). A hypothetical biosynthetic pathway to compound 1 is presented that is consistent with the occurrence of compounds 7b, 13, and 5 (tetracenomycin A2) and with the cosynthetic behavior of tetracenomycin C-nonproducing mutants (H. Motamedi, E. Wendt-Pienkowski, and C. R. Hutchinson, J. Bacteriol. 167:575-580, 1986).     

Development of an <Emphasis Type="Italic">in vitro</Emphasis> assay for the investigation of metabolism-induced drug hepatotoxicity

In a number of adverse drug reactions leading to hepatotoxicity drug metabolism is thought to be involved by generation of reactive metabolites from nontoxic drugs. In this study, an in vitro assay was developed for measurement of the impact of metabolic activation of compound on the cytotoxicity toward a human hepatic cell line. HepG2 cells were treated for 6 h with compound in the presence or absence of rat liver S9-mix, and the viability was measured using the MTT test. The cytotoxicity of cyclophosphamide was substantially increased by S9-mix in the presence of NADPH. Three NADPH sources were tested: NADPH (1 mmol/L) or NADPH regenerating system with either NADP⁺/glucose 6-phosphate (G6P) or NADP⁺/isocitrate. All three NADPH sources increased the cytotoxicity of cyclophosphamide to a similar extent. Eight test compounds known to cause hepatotoxicity were tested. For these, only the cytotoxicity of diclofenac was increased by S9 enzymes when an NADPH regenerating system was used. The increased toxicity was NADPH dependent. Reactive drug metabolites of diclofenac, formed by NADPH-dependent metabolism, were identified by LC-MS. Furthermore, an increase in toxicity, not related to enzymatic activity but to G6P, was observed for diclofenac and minocycline. Tacrine and amodiaquine displayed decreased toxicity with S9-mix, and carbamazepine, phenytoin, bromfenac and troglitazone were nontoxic at all tested concentrations, with or without S9-mix. The results show that this method, with measurement of the cytotoxicity of a compound in the presence of an extracellular metabolizing system, may be useful in the study of cytotoxicity of drug metabolites.     

High-performance liquid chromatographic method for the detection and quantitation of haloperidol and seven of its metabolites in microsomal preparations

An isocratic high-performance liquid chromatographic (HPLC) system was developed to analyze haloperidol and its potential metabolites. These compounds included 4-(4-chlorophenyl)-4-hydroxypiperidine (CPHP), haloperidol N-oxide (HNO), reduced haloperidol (RHAL), the 1,2,3,6-tetrahydropyridine analogue and its N-oxide, and the pyridinium ion from haloperidol (HP⁺). The HPLC system comprised a Hypersil CPS5 column with a mobile phase of acetonitrile (67%) and ammonium acetate (final concentration 10 mM) which was adjusted to pH 5.4 by acetic acid. The solvent was delivered at 1 ml/min. RHAL and CPHP were determined by an ultraviolet detector at 220 nm with a detection limit of 1 nmol/ml. All other compounds were determined at 245 nm and had a detection limit of 0.3 nmol/ml. This system was used to analyze a microsomal metabolic mixture of haloperidol. It was found that all above compounds except HNO were metabolites of haloperidol. In addition, two other metabolites were also well separated in this HPLC system which are proposed to be oxygenated haloperidol and the pyridone analogue of haloperidol. The HPLC system was used to carry out quantitative metabolic studies of haloperidol. It was found that the metabolism of haloperidol exhibits large inter-species differences. The apparent enzyme kinetic parameters were also determined using mice microsomes.     

Studies on the metabolism and toxicological detection of the new designer drug 4'-methyl-alpha-pyrrolidinobutyrophenone (MPBP) in rat urine using gas chromatography-mass spectrometry

The aim of the presented study was to identify the metabolites of the new designer drug 4'-methyl-alpha-pyrrolidinobutyrophenone (MPBP) in rat urine using GC-MS techniques. After enzymatic hydrolysis, extraction and various derivatizations, seven metabolites of MPBP could be identified suggesting the following metabolic steps: oxidation of the 4'-methyl group to the corresponding alcohol and further oxidation to the respective carboxy compound, hydroxylation of the pyrrolidine ring followed by dehydrogenation to the corresponding lactam or reduction of the keto group to the 1-dihydro compound. A previously published GC-MS-based screening procedure for pyrrolidinophenones involving enzymatic hydrolysis and mixed-mode solid-phase extraction of urine samples allowed detection of MPBP metabolites. Assuming similar metabolism and dosages in humans, an intake of MPBP should be detectable via its metabolites in urine.     

Influence of methoxy and nitro groups in the oxidative metabolism of naphtho[2,1-b]furan.

In the present study, we have investigated the role of methoxy and nitro groups in the oxidative metabolism of naphtho[2,1-b]furan. Hepatic microsomes were used to investigate the aerobic metabolism of naphtho[2,1-b]furan (compound A), 2-nitro-naphtho[2,1-b]furan (compound B) and 7-methoxy-naphtho [2,1-b]furan (compound C) and comparison of the metabolites formed was made using HPCL analysis and NMR, mass and UV-visible spectrometry. The different metabolic pathways investigated were compared with the previously reported metabolism of 7-methoxy-2-nitro-naphtho[2,1-b]furan (compound D). Naphtho[2,1-b]furan yield metabolites of both the furan and benzene rings, while metabolites formed from 7-methoxy-naphtho[2,1-b]furan and 2-nitro-naphtho [2,1-b]furan were derived entirely as a result of enzymic attack on the first benzene ring.