Automated Structure Annotation and Curation for MassBank: Potential and Pitfalls

<p>The European MassBank server (<a href="http://www.massbank.eu/">www.massbank.eu</a>) was founded in 2012 by the NORMAN Network (<a href="http://www.norman-network.net/">www.norman-network.net</a>) to provide open access to mass spectra of substances of environmental interest contributed by NORMAN members. The automated workflow RMassBank was developed as a part of this effort (<a href="https://github.com/MassBank/RMassBank/">https://github.com/MassBank/RMassBank/</a>). This workflow included automated processing of the mass spectral data, as well as automated annotation using the SMILES, Names and CAS numbers provided by the user. Cheminformatics toolkits (e.g. Open Babel, rcdk) and web services (e.g. the CACTUS Chemical Identifier Resolver, Chemical Translation Services (CTS), ChemSpider, PubChem) were then used to convert and/or retrieve the remaining information for completion of the MassBank records (additional names, InChIs, InChIKeys, several database identifiers, mol files), to avoid excessive burden on the users and reduce the chance of errors. To date, approximately 16,000 MS/MS spectra (61 % of all open data as of Nov. 2016) corresponding with 1,269 (18 %) unique chemicals have been uploaded to MassBank.EU via RMassBank. Curating the MassBank.EU records, as part of efforts to provide EPA CompTox Dashboard identifiers (DTXSIDs) for each record, revealed several conflicts in the chemical metadata arising from varying sources. In addition, the representation of “ambiguous substances”, for example complex surfactant mixtures of various chain lengths and branching or incompletely-defined structures of transformaton products, is an ongoing challenge. In this work, we report on proof-of-concept solutions for “ambiguous structure” representation, currently unavailable in the majority of cheminformatics tools. This presentation reflects on the effectiveness of the original RMassBank concept but also identifies pitfalls that automated structure annotation with open resources offers to streamline spectra contributions from external laboratories and users with widely ranging cheminformatics experience. <i>Note: this work does not necessarily reflect U.S. EPA policy.</i></p

Pooled egg and tadpole depositions placed by parental <i>Ranitomeya variabilis</i> in cups with clean or treated water.

<p>Treated water contains different fractions (or a total mix) of chemical substances from <i>R</i>. <i>variabilis</i> (V) or <i>H</i>. <i>azureiventris</i> (A), tested in 2012 (marked with numbers) and 2013 (marked with the according numbers of 2012 and additional letters), respectively. Deposition frequencies are compared by a G-test.</p><p>* A_total was only tested in 2012</p><p>** A_4-13 is the only fraction that in 2013 is the same fraction as in 2012 (and it is therefore assigned with a number instead of a letter), but it is missing some cues that could not be found again in 2013.</p><p>Pooled egg and tadpole depositions placed by parental <i>Ranitomeya variabilis</i> in cups with clean or treated water.</p

Decoding and Discrimination of Chemical Cues and Signals: Avoidance of Predation and Competition during Parental Care Behavior in Sympatric Poison Frogs

<div><p>The evolution of chemical communication and the discrimination between evolved functions (signals) and unintentional releases (cues) are among the most challenging issues in chemical ecology. The accurate classification of inter- or intraspecific chemical communication is often puzzling. Here we report on two different communication systems triggering the same parental care behavior in the poison frog <i>Ranitomeya variabilis</i>. This species deposits its tadpoles and egg clutches in phytotelmata and chemically recognizes and avoids sites with both predatory conspecific and non-predatory heterospecific tadpoles (of the species <i>Hyloxalus azureiventris</i>). Combining chemical analyses with in-situ bioassays, we identified the molecular formulas of the chemical compounds triggering this behavior. We found that both species produce distinct chemical compound combinations, suggesting two separate communication systems. Bringing these results into an ecological context, we classify the conspecific <i>R</i>. <i>variabilis</i> compounds as chemical cues, advantageous only to the receivers (the adult frogs), not the emitters (the tadpoles). The heterospecific compounds, however, are suggested to be chemical signals (or cues evolving into signals), being advantageous to the emitters (the heterospecific tadpoles) and likely also to the receivers (the adult frogs). Due to these assumed receiver benefits, the heterospecific compounds are possibly synomones which are advantageous to both emitter and receiver ‒ a very rare communication system between animal species, especially vertebrates.</p></div

Results of the preliminary trials to find a sorbent to extract the active tadpole compounds.

<p>Ratio (in percent) of offspring depositions in clean water (grey narrow bars) and water used by tadpoles and treated with sorbents afterwards (black narrow bars). The expected distribution (50:50) is shown in lighter shades of grey in the background. V and A refer to <i>R</i>. <i>variabilis</i> and <i>H</i>. <i>azureiventris</i>, respectively. When frogs showed a significant preference for the clean water we assumed that the treated water still contained tadpole compounds, i.e. the sorbents did not filter them sufficiently out of the water to end the avoidance behavior. Only after the treatment with DSC-18 did frogs not show avoidance of tadpole-treated water. * <i>p</i> < 0.05, ** <i>p</i> < 0.01, *** <i>p</i> < 0.001.</p

Compounds found in fractions avoided in the bioassays by <i>Ranitomeya variabilis</i>.

<p>V and A stand for <i>R</i>. <i>variabilis</i> and <i>H</i>. <i>azureiventris</i> respectively. Compounds marked with a * were found in fractions of both species; nd = no detection.</p><p>Compounds found in fractions avoided in the bioassays by <i>Ranitomeya variabilis</i>.</p

Overview of methods.

<p>Steps are numbered in accordance with the text (a—f). V and A stand for fractions of <i>R</i>. <i>variabilis</i> and <i>H</i>. <i>azureiventris</i>, respectively. Structural formulas shown in (f) are only examples.</p

Bioassay results after offering the fractionated compounds of the tadpoles to the frogs.

<p>The ratio of offspring depositions in clean water (grey narrow bars) and in water treated with chemically processed (A) <i>R</i>. <i>variabilis</i> and (B) <i>H</i>. <i>azureiventris</i> substances (black narrow bars) is shown in percent. V and A stand for <i>R</i>. <i>variabilis</i> and <i>H</i>. <i>azureiventris</i>, respectively. The distribution of the total samples (V_total and A_total) is shown with lighter grey shades in the background. Connecting lines leading from results from 2012 to 2013 show which fractions were further processed in 2013 and contain identical compounds. * <i>p</i> < 0.05, ** <i>p</i> < 0.01, *** <i>p</i> < 0.001.</p

DataSheet_1_S1PR4 deficiency results in reduced germinal center formation but only marginally affects antibody production.pdf

IntroductionSplenic B cells exhibit a high expression of the G protein-coupled sphingosine-1-phosphate (S1P) receptor type 4 (S1PR4). Little is known about the functional relevance of S1PR4 expression on those cells.MethodsIn this study, S1PR4-deficient mice were used to study the role of S1PR4-mediated S1P signaling in B cell motility in vitro and for the maintenance of the splenic architecture under steady state conditions as well as in polymicrobial abdominal sepsis in vivo. Finally, the impact of S1PR4 deficiency on antibody production after immunization with T cell dependent antigens was assessed.ResultsLoss of S1PR4 resulted in minor alterations of the splenic architecture concerning the presence of B cell follicles. After sepsis induction, the germinal center response was severely impaired in S1PR4-deficient animals. Splenic B cells showed reduced motility in the absence of S1PR4. However, titres of specific antibodies showed only minor reductions in S1PR4-deficient animals.DiscussionThese observations suggest that S1P signaling mediated by S1PR4 modifies chemokine-induced splenic B cell chemotaxis, thus modulating splenic microarchitecture, GC formation and T-cell dependent antibody production.</p

Screening of Pesticide and Biocide Patterns As Risk Drivers in Sediments of Major European River Mouths: Ubiquitous or River Basin-Specific Contamination?

Pesticides and biocides (PaB) are ubiquitously present in aquatic ecosystems due to their widespread application and have been detected in rivers at concentrations that may cause distress to aquatic life. Many of these compounds accumulate in sediments acting as long-term source for aquatic ecosystems. However, data on sediment contamination with current-use PaB in Europe are scarce. Thus, in this study, we elucidated PaB patterns and associated risks in sediments of seven major European rivers focusing on their last stretch as an integrative sink of particles transported by these rivers. Sediments were extracted with pressurized liquid extraction (PLE) using a broad-spectrum method recovering many compound classes with a wide range of physicochemical properties. Altogether 126 compounds were analyzed and 81 of them were detected with LC-HRMS and GC-NCI-MS/MS at least in one of the sediments. The highest number of compounds was detected (59) in River Elbe sediments close to Cuxhaven with outstanding concentrations ranging from 0.8 to 1691 mg/g organic carbon. Multivariate analysis identified a cluster with 3 ubiquitous compounds (cyhalothrin, carbendazim, fenpropimorph) and three clusters of chemicals with higher variability within and between rivers. Risk assessment indicates an acute toxic risk to benthic crustaceans at all investigated sites with the pyrethroids tefluthrin and cyfluthrin together with the fungicide carbendazim as the main drivers. Risks to algae were driven at most sites almost exclusively by photosynthesis inhibitors with estuary-specific herbicide mixtures, while in the rivers Po and Gironde cell division inhibitors played an important role at some sites. Mixtures of specific concern have been defined and suggested for integration in future monitoring programs

Consensus Structure Elucidation Combining GC/EI-MS, Structure Generation, and Calculated Properties

This article explores consensus structure elucidation on the basis of GC/EI-MS, structure generation, and calculated properties for unknown compounds. Candidate structures were generated using the molecular formula and substructure information obtained from GC/EI-MS spectra. Calculated properties were then used to score candidates according to a consensus approach, rather than filtering or exclusion. Two mass spectral match calculations (MOLGEN-MS and MetFrag), retention behavior (Lee retention index/boiling point correlation, NIST Kovat’s retention index), octanol–water partitioning behavior (log <i>K</i>_ow), and finally steric energy calculations were used to select candidates. A simple consensus scoring function was developed and tested on two unknown spectra detected in a mutagenic subfraction of a water sample from the Elbe River using GC/EI-MS. The top candidates proposed using the consensus scoring technique were purchased and confirmed analytically using GC/EI-MS and LC/MS/MS. Although the compounds identified were not responsible for the sample mutagenicity, the structure-generation-based identification for GC/EI-MS using calculated properties and consensus scoring was demonstrated to be applicable to real-world unknowns and suggests that the development of a similar strategy for multidimensional high-resolution MS could improve the outcomes of environmental and metabolomics studies