Integrated analytical and computer tools for structure elucidation in effect-directed analysis

Identification and Prioritization of Environmental Organic Pollutants: From an Analytical and Toxicological Perspective

Exposure to environmental organic pollutants has triggered significant ecological impacts and adverse health outcomes, which have been received substantial and increasing attention. The contribution of unidentified chemical components is considered as the most significant knowledge gap in understanding the combined effects of pollutant mixtures. To address this issue, remarkable analytical breakthroughs have recently been made. In this review, the basic principles on recognition of environmental organic pollutants are overviewed. Complementary analytical methodologies (i.e., quantitative structure-activity relationship prediction, mass spectrometric nontarget screening, and effect-directed analysis) and experimental platforms are briefly described. The stages of technique development and/or essential parts of the analytical workflow for each of the methodologies are then reviewed. Finally, plausible technique paths and applications of the future nontarget screening methods, interdisciplinary techniques for achieving toxicant identification, and burgeoning strategies on risk assessment of chemical cocktails are discussed.

Pesticide toxicity towards microalgae increases with environmental mixture complexity

Effect-directed analysis (EDA) aims at identifying the compound(s) responsible for toxicity in a complex environmental sample where several dozens of contaminants can be present. In this study, we used an environmental mixture extracted from the Polar Organic Chemical Integrative Sampler (POCIS) previously immersed downstream a landfill (River Ponteils, South West France), to perform an EDA approach using a microalgal bioassay based on the photosynthetic capacities of diatom (Nitzschia palea) cultures. Adverse effects on photosynthetic capacities were recorded when algae were exposed to the entire POCIS extract (> 85% inhibition at the highest concentration tested). This result was coherent with the detection of diuron and isoproturon, which were the 2 most concentrated herbicides in the extract. However, the EDA process did not allow pointing out the specific compound(s) responsible for the observed toxicity but rather suggested that multiple compounds were involved in the overall toxicity and caused mixture effects.

Suspect and non-target screening: the last frontier in environmental analysis

Suspect and non-target screening (SNTS) techniques are arising as new analytical strategies useful to disentangle the environmental occurrence of the thousands of exogenous chemicals present in our ecosystems. The unbiased discovery of the wide number of substances present over environmental analysis needs to find a consensus with powerful technical and computational requirements, as well as with the time-consuming unequivocal identification of discovered analytes. Within these boundaries, the potential applications of SNTS include the studies of environmental pollution in aquatic, atmospheric, solid and biological samples, the assessment of new compounds, transformation products and metabolites, contaminant prioritization, bioremediation or soil/water treatment evaluation, and retrospective data analysis, among many others. In this review, we evaluate the state of the art of SNTS techniques going over the normalized workflow from sampling and sample treatment to instrumental analysis, data processing and a brief review of the more recent applications of SNTS in environmental occurrence and exposure to xenobiotics. The main issues related to harmonization and knowledge gaps are critically evaluated and the challenges of their implementation are assessed in order to ensure a proper use of these promising techniques in the near future.

Sustainable microalgae-based technology for biotransformation of benzalkonium chloride in oil and gas produced water: A laboratory-scale study

Many countries have implemented stringent regulatory standards for discharging produced water (PW) from the oil and gas extraction process. Among the different chemical pollutants occurring in PW, surfactants are widely applied in the oil and gas industry to provide a barrier from metal corrosion. However, the release of these substances from the shale formation can pose serious hazardous impacts on the aquatic environment. In this study, a low-cost and eco-friendly microalgae laboratory-scale technology has been tested for biotransformation of benzalkonium chloride (BAC_C12 and BAC_C14) in seawater and PW during 14-days of treatment (spiked at 5 mg/L). From the eight microalgae strains selected, Tetraselmis suecica showed the highest removal rates of about 100% and 54% in seawater and PW, respectively. Suspect screening analysis using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) allowed the identification of 12 isomeric intermediates generated coming from biotransformation mechanisms. Among them, the intermediate [OH-BAC_C12] was found as the most intense compound generated from BAC_C12, while the intermediate [2OH-BAC_C14] was found as the most intense compound generated from BAC_C14. The suggested chemical structures demonstrated a high reduction on their amphiphilic properties, and thus, their tendency to be adsorbed into sediments after water discharge. In this study, Tetraselmis suecica was classified as the most successful specie to reduce the surfactant activity of benzalkonium chloride in treated effluents.

Effect-Based Identification of Hazardous Antibiotic Transformation Products after Water Chlorination

Antibiotic transformation products (TPs) generated during water treatment can be considered as an environmental concern, since they can retain part of the bioactivity of the parent compound. Effect-directed analysis (EDA) was applied for the identification of bioactive intermediates of azithromycin (AZI) and ciprofloxacin (CFC) after water chlorination. Fractionation of samples allowed the identification of bioactive intermediates by measuring the antibiotic activity and acute toxicity, combined with an automated suspect screening approach for chemical analysis. While the removal of AZI was in line with the decrease of bioactivity in chlorinated samples, an increase of bioactivity after complete removal of CFC was observed (at >0.5 mgCl₂/L). Principal component analysis (PCA) revealed that some of the CFC intermediates could contribute to the overall toxicity of the chlorinated samples. Fractionation of bioactive samples identified that the chlorinated TP296 (generated from the destruction of the CFC piperazine ring) maintained 41%, 44%, and 30% of the antibiotic activity of the parent compound in chlorinated samples at 2.0, 3.0, and 4.0 mgCl₂/L, respectively. These results indicate the spectrum of antibacterial activity can be altered by controlling the chemical substituents and configuration of the CFC structure with chlorine. On the other hand, the potential presence of volatile DBPs and fractionation losses do not allow for tentative confirmation of the main intermediates contributing to the acute toxic effects measured in chlorinated samples. Our results encourage further development of new and advanced methodologies to study the bioactivity of isolated unknown TPs to understand their hazardous effects in treated effluents.

Identification of acetylcholinesterase inhibitors in water by combining two-dimensional thin-layer chromatography and high-resolution mass spectrometry

Effect-directed analysis (EDA) is increasingly used in environmental monitoring to detect and identify key toxicants. High-performance thin-layer chromatography (HPTLC) has proven to be a very suitable fractionation technique for this purpose. However, HPTLC is limited in its separation efficiency. Thus, separated fractions could still contain many different components and identification of the effective substances remains difficult. Therefore, in this study a workflow for selective EDA with two-dimensional HPTLC in combination with high-performance liquid chromatography-high-resolution mass spectrometry (HPLC-HRMS) was developed. The aim of the workflow was the stepwise reduction of the sample complexity in order to reduce the number of signals that could be responsible for the measured effects. As a consequence, the identification of effective substances should be facilitated. The acetylcholinesterase inhibition assay (AChE assay) for the detection of potential neurotoxic compounds was applied for biotesting. The transfer of effective zones from the first to the second dimension and also to the mass spectrometric measurement was enabled by extraction. A proof of concept was performed by spiking six acetylcholinesterase inhibiting substances into three different water matrices that were investigated with the developed workflow. The successful prioritization of all spiked compounds confirmed the efficiency of the workflow, regardless of the sample matrix. Biotesting of different water samples resulted in numerous potentially neurotoxic effects, which overlapped strongly in the first separation dimension. The higher peak capacity reached by two-dimensional HPTLC, on the other hand, resulted in discrete effective zones and enabled the identification of several compounds. For the substances lumichrome, a derivate of riboflavin and paraxanthine as well as for linear alkylbenzene sulfonates that were applied as anionic surfactants in detergents, the inhibiting effect to the AChE could be confirmed.

Evaluating internal exposure of sea turtles as model species for identifying regional chemical threats in nearshore habitats of the Great Barrier Reef

Marine megafauna that forage in proximity to land can be exposed to a diverse mixture of chemicals that - individually or combined - have the potential to affect their health. Characterizing such complex exposure and examining associations with health still poses considerable challenges. The present study summarizes the development and application of novel approaches to identifying chemical hazards and their potential impacts on the health of coastal wildlife, using green sea turtles as model species. We used an epidemiological study approach to collect blood and keratinized scute samples from free-ranging turtles foraging in nearshore areas and an offshore control site. These were analyzed using a combination of non-targeted, effect-based and multi-chemical analytical screening approaches to assess internal exposure to a wide range of chemicals. The screening phase identified a suite of elements (essential and non-essential) as priority for further investigation. Many of these elements are not commonly analyzed in marine wildlife, illustrating that comprehensive screening is important where exposure is unknown or uncertain. In particular, cobalt was present at highly elevated concentrations, in the order of those known to elicit acute effects across other vertebrate species. Several trace elements, including cobalt, were correlated with clinical indicators of impaired turtle health. In addition, biomarkers of oxidative stress (e.g. 3-indolepropionic acid and lipid peroxidation products) identified in the blood of turtles showed significant correlations with clinical health markers (particularly alkaline phosphatase and total bilirubin), as well as with cobalt. To assist interpretation of trace element blood data in the absence of sufficient information on reptile toxicity, we established exposure reference intervals using a healthy control population. In addition, trace element exposure history was investigated by establishing temporal exposure indices using steady-state relationships between blood and scute. Overall, the data provide a strong argument for the notion that trace element exposure is having an impact on the health of coastal sea turtle populations.

UPLC-MS-IT-TOF Identification of Circumdatins Produced by Aspergillus ochraceus

A method based on the combined use of ultraperformance liquid chromatography coupled to mass spectrometry-ion trap-time-of-flight (UPLC-MS-IT-TOF) detection was employed to identify the metabolite production of Aspergillus ochraceus, which is the major cause of food and feed contamination due to ochratoxin A. Under the proposed chromatographic conditions, seven metabolites belonging to the family of circumdatins were separated and identified. Their initial identification was performed through the exact molecular formula, as a function of their accurate mass. Collision-induced dissociation was applied to predict precursor and product ions, and the elemental composition of each compound was obtained. The elimination of nitrogenous groups followed by successive losses of carbonyl groups is the common fragmentation pathway of circumdatins. With the fragmentation data obtained, an UPLC-MS/MS method was created and optimized to detect circumdatins in corn samples.

Integrated Framework for Identifying Toxic Transformation Products in Complex Environmental Mixtures

Complex environmental mixtures consist of hundreds to thousands of unknown and unregulated organic compounds that may have toxicological relevance, including transformation products (TPs) of anthropogenic organic pollutants. Non-targeted analysis and suspect screening analysis offer analytical approaches for potentially identifying these toxic transformation products. However, additional tools and strategies are needed in order to reduce the number of chemicals of interest and focus analytical efforts on chemicals that may pose risks to humans and the environment. This brief review highlights recent developments in this field and suggests an integrated framework that incorporates complementary instrumental techniques, computational chemistry, and toxicity analysis, for prioritizing and identifying toxic TPs in the environment.

The association of bacterial C9-based TTX-like compounds with Prorocentrum minimum opens new uncertainties about shellfish seafood safety

In 2012, Tetrodotoxin (TTX) was identified in mussels and linked to the presence of Prorocentrum minimum (P. minimum) in Greece. The connexion between TTX and P. minimum was further studied in this paper. First, the presence of TTX-producer bacteria, Vibrio and Pseudomonas spp, was confirmed in Greek mussels. In addition these samples showed high activity as inhibitors of sodium currents (I_Na). P. minimum was before associated with neurotoxic symptoms, however, the nature and structure of toxins produced by this dinoflagellate remains unknown. Three P. minimum strains, ccmp1529, ccmp2811 and ccmp2956, growing in different conditions of temperature, salinity and light were used to study the production of toxic compounds. Electrophysiological assays showed no effect of ccmp2811 strain on I_Na, while ccmp1529 and ccmp2956 strains were able to significantly reduce I_Na in the same way as TTX. In these samples two new compounds, m/z 265 and m/z 308, were identified and characterized by liquid chromatography tandem high-resolution mass spectrometry. Besides, two TTX-related bacteria, Roseobacter and Vibrio sp, were observed. These results show for the first time that P. minimum produce TTX-like compounds with a similar ion pattern and C9-base to TTX analogues and with the same effect on I_Na.

Target and non-target identification of chemical components in Lamiophlomis rotata by liquid chromatography/quadrupole time-of-flight mass spectrometry using a three-step protocol

RATIONALE

As a herbal plant used in traditional Chinese medicine, Lamiophlomis rotata (Benth.) Kudo mainly displays its pharmacological effect by promoting blood circulation and hemostasis, dispelling wind, and acting as an analgesic. To identify the components contained in L. rotata, global detection and structural elucidation of both target and non-target components in the medicinal material was performed.

METHODS

L. rotata was ultrasonically extracted with methanol. Separation and analysis were achieved using liquid chromatography/quadrupole time-of-flight mass spectrometry (LC/QTOF-MS). A three-step protocol which included (1) potential components screening, (2) collection of qualitative information, and (3) database searching and structural elucidation was used for target and non-target identification.

RESULTS

A total of 42 components were tentatively identified, which included 12 iridoids (2 aglycones and 10 glucosides), 11 flavonoids (4 aglycones and 7 glucosides), and 13 phenylethanoid glycosides. Moreover, components of L. rotata extract belonging to the three main structural categories could be well separated in a 3D point plot according to their retention times, mass defects and degrees of unsaturation, facilitating the structural classification and identification in the subsequent studies.

CONCLUSIONS

The results provide a reasonable picture of the components contained in L. rotata extract and promote the further pharmacodynamic and/or pharmacokinetic characterization of this medical material, meanwhile demonstrating the utility of a universal methodology for the systematical study of herbal medicines. Copyright © 2016 John Wiley & Sons, Ltd.

Future water quality monitoring--adapting tools to deal with mixtures of pollutants in water resource management

Environmental quality monitoring of water resources is challenged with providing the basis for safeguarding the environment against adverse biological effects of anthropogenic chemical contamination from diffuse and point sources. While current regulatory efforts focus on monitoring and assessing a few legacy chemicals, many more anthropogenic chemicals can be detected simultaneously in our aquatic resources. However, exposure to chemical mixtures does not necessarily translate into adverse biological effects nor clearly shows whether mitigation measures are needed. Thus, the question which mixtures are present and which have associated combined effects becomes central for defining adequate monitoring and assessment strategies. Here we describe the vision of the international, EU-funded project SOLUTIONS, where three routes are explored to link the occurrence of chemical mixtures at specific sites to the assessment of adverse biological combination effects. First of all, multi-residue target and non-target screening techniques covering a broader range of anticipated chemicals co-occurring in the environment are being developed. By improving sensitivity and detection limits for known bioactive compounds of concern, new analytical chemistry data for multiple components can be obtained and used to characterise priority mixtures. This information on chemical occurrence will be used to predict mixture toxicity and to derive combined effect estimates suitable for advancing environmental quality standards. Secondly, bioanalytical tools will be explored to provide aggregate bioactivity measures integrating all components that produce common (adverse) outcomes even for mixtures of varying compositions. The ambition is to provide comprehensive arrays of effect-based tools and trait-based field observations that link multiple chemical exposures to various environmental protection goals more directly and to provide improved in situ observations for impact assessment of mixtures. Thirdly, effect-directed analysis (EDA) will be applied to identify major drivers of mixture toxicity. Refinements of EDA include the use of statistical approaches with monitoring information for guidance of experimental EDA studies. These three approaches will be explored using case studies at the Danube and Rhine river basins as well as rivers of the Iberian Peninsula. The synthesis of findings will be organised to provide guidance for future solution-oriented environmental monitoring and explore more systematic ways to assess mixture exposures and combination effects in future water quality monitoring.

Using model-based screening to help discover unknown environmental contaminants

Of the tens of thousands of chemicals in use, only a small fraction have been analyzed in environmental samples. To effectively identify environmental contaminants, methods to prioritize chemicals for analytical method development are required. We used a high-throughput model of chemical emissions, fate, and bioaccumulation to identify chemicals likely to have high concentrations in specific environmental media, and we prioritized these for target analysis. This model-based screening was applied to 215 organosilicon chemicals culled from industrial chemical production statistics. The model-based screening prioritized several recognized organosilicon contaminants and generated hypotheses leading to the selection of three chemicals that have not previously been identified as potential environmental contaminants for target analysis. Trace analytical methods were developed, and the chemicals were analyzed in air, sewage sludge, and sediment. All three substances were found to be environmental contaminants. Phenyl-tris(trimethylsiloxy)silane was present in all samples analyzed, with concentrations of ∼50 pg m(-3) in Stockholm air and ∼0.5 ng g(-1) dw in sediment from the Stockholm archipelago. Tris(trifluoropropyl)trimethyl-cyclotrisiloxane and tetrakis(trifluoropropyl)tetramethyl-cyclotetrasiloxane were found in sediments from Lake Mjøsa at ∼1 ng g(-1) dw. The discovery of three novel environmental contaminants shows that models can be useful for prioritizing chemicals for exploratory assessment.

Effect-directed analysis of endocrine-disrupting compounds in multi-contaminated sediment: identification of novel ligands of estrogen and pregnane X receptors

Effect-directed analysis (EDA)-based strategies have been increasingly used in order to identify the causative link between adverse (eco-)toxic effects and chemical contaminants. In this study, we report the development and use of an EDA approach to identify endocrine-disrupting chemicals (EDCs) in a multi-contaminated river sediment. The battery of in vitro reporter cell-based bioassays, measuring estrogenic, (anti)androgenic, dioxin-like, and pregnane X receptor (PXR)-like activities, revealed multi-contamination profiles. To isolate active compounds of a wide polarity range, we established a multi-step fractionation procedure combining: (1) a primary fractionation step using normal phase-based solid-phase extraction (SPE), validated with a mixture of 12 non-polar to polar standard EDCs; (2) a secondary fractionation using reversed-phase-based high-performance liquid chromatography (RP-HPLC) calibrated with 33 standard EDCs; and (3) a purification step using a recombinant estrogen receptor (ER) affinity column. In vitro SPE and HPLC profiles revealed that ER and PXR activities were mainly due to polar to mid-polar compounds, while dioxin-like and anti-androgenic activities were in the less polar fractions. The overall procedure allowed final isolation and identification of new environmental PXR (e.g., di-iso-octylphthalate) and ER (e.g., 2,4-di-tert-butylphenol and 2,6-di-tert-butyl-α-methoxy-p-cresol) ligands by using gas chromatography coupled with mass spectrometry with full-scan mode acquisition in mid-polar fractions. In vitro biological activity of these chemicals was further confirmed using commercial standards, with di-iso-octylphthalate identified for the first time as a potent hPXR environmental agonist.

Post-incident monitoring to evaluate environmental damage from shipping incidents: chemical and biological assessments

Oil and chemical spills in the marine environment are an issue of growing concern. Oil exploration and exploitation is moving from the continental shelf to deeper waters, and to northern latitudes where the risk of an oil spill is potentially greater and may affect pristine ecosystems. Moreover, a growing number of chemical products are transported by sea and maritime incidents of hazardous and noxious substances (HNS) are expected to increase. Consequently, it seems timely to review all of the experience gained from past spills to be able to cope with appropriate response and mitigation strategies to combat future incidents. Accordingly, this overview is focused on the dissemination of the most successful approaches to both detect and assess accidental releases using chemical as well as biological approaches for spills of either oil or HNS in the marine environment. Aerial surveillance, sampling techniques for water, suspended particles, sediments and biota are reviewed. Early warning bioassays and biomarkers to assess spills are also presented. Finally, research needs and gaps in knowledge are discussed.

Metabolomics of human breast cancer: new approaches for tumor typing and biomarker discovery

Breast cancer is the most common cancer in women worldwide, and the development of new technologies for better understanding of the molecular changes involved in breast cancer progression is essential. Metabolic changes precede overt phenotypic changes, because cellular regulation ultimately affects the use of small-molecule substrates for cell division, growth or environmental changes such as hypoxia. Differences in metabolism between normal cells and cancer cells have been identified. Because small alterations in enzyme concentrations or activities can cause large changes in overall metabolite levels, the metabolome can be regarded as the amplified output of a biological system. The metabolome coverage in human breast cancer tissues can be maximized by combining different technologies for metabolic profiling. Researchers are investigating alterations in the steady state concentrations of metabolites that reflect amplified changes in genetic control of metabolism. Metabolomic results can be used to classify breast cancer on the basis of tumor biology, to identify new prognostic and predictive markers and to discover new targets for future therapeutic interventions. Here, we examine recent results, including those from the European FP7 project METAcancer consortium, that show that integrated metabolomic analyses can provide information on the stage, subtype and grade of breast tumors and give mechanistic insights. We predict an intensified use of metabolomic screens in clinical and preclinical studies focusing on the onset and progression of tumor development.

Current use of high-resolution mass spectrometry in the environmental sciences

During the last two decades, mass spectrometry (MS) has been increasingly used in the environmental sciences with the objective of investigating the presence of organic pollutants. MS has been widely coupled with chromatographic techniques, both gas chromatography (GC) and liquid chromatography (LC), because of their complementary nature when facing a broad range of organic pollutants of different polarity and volatility. A clear trend has been observed, from the very popular GC-MS with a single quadrupole mass analyser, to tandem mass spectrometry (MS-MS) and, more recently, high-resolution mass spectrometry (HRMS). For years GC has been coupled to HR magnetic sector instruments, mostly for dioxin analysis, although in the last ten years there has been growing interest in HRMS with time-of-flight (TOF) and Orbitrap mass analyzers, especially in LC-MS analysis. The increasing interest in the use of HRMS in the environmental sciences is because of its suitability for both targeted and untargeted analysis, owing to its sensitivity in full-scan acquisition mode and high mass accuracy. With the same instrument one can perform a variety of tasks: pre- and post-target analysis, retrospective analysis, discovery of metabolite and transformation products, and non-target analysis. All these functions are relevant to the environmental sciences, in which the analyst encounters thousands of different organic contaminants. Thus, wide-scope screening of environmental samples is one of the main applications of HRMS. This paper is a critical review of current use of HRMS in the environmental sciences. Needless to say, it is not the intention of the authors to summarise all contributions of HRMS in this field, as in classic descriptive reviews, but to give an overview of the main characteristics of HRMS, its strong potential in environmental mass spectrometry and the trends observed over the last few years. Most of the literature has been acquired since 2005, coinciding with the growth and popularity of HRMS in this field, with a few exceptions that deserve to be mentioned because of their relevance.

Linear Solvation Energy Relationships as classifiers in non-target analysis--a capillary liquid chromatography approach

For the identification of unknowns in environmental samples, Linear Solvation Energy Relationships (LSERs) are applied as classifiers for exclusion of candidate compounds with equal exact mass. By prediction of the Chromatographic Hydrophobicity Index (CHI) from retention time of the unknown compound on a gradient system using a C18 column and the description of interactions by LSER descriptors, an exclusion of isomers, with different retention behaviour and interaction terms is possible. The example of several isomers, with the empirical formula C₁₂H₁₀O₂, demonstrates the application as classifier and indicates limits of this prognosis.

Applying in-silico retention index and mass spectra matching for identification of unknown metabolites in accurate mass GC-TOF mass spectrometry

One of the major obstacles in metabolomics is the identification of unknown metabolites. We tested constraints for reidentifying the correct structures of 29 known metabolite peaks from GCT premier accurate mass chemical ionization GC-TOF mass spectrometry data without any use of mass spectral libraries. Correct elemental formulas were retrieved within the top-3 hits for most molecular ion adducts using the "Seven Golden Rules" algorithm. An average of 514 potential structures per formula was downloaded from the PubChem chemical database and in-silico-derivatized using the ChemAxon software package. After chemical curation, Kovats retention indices (RI) were predicted for up to 747 potential structures per formula using the NIST MS group contribution algorithm and corrected for contribution of trimethylsilyl groups using the Fiehnlib RI library. When matching the range of predicted RI values against the experimentally determined peak retention, all but three incorrect formulas were excluded. For all remaining isomeric structures, accurate mass electron ionization spectra were predicted using the MassFrontier software and scored against experimental spectra. Using a mass error window of 10 ppm for fragment ions, 89% of all isomeric structures were removed and the correct structure was reported in 73% within the top-5 hits of the cases.

Use of soft and hard ionization techniques for elucidation of unknown compounds by gas chromatography/time-of-flight mass spectrometry

Investigation of trace-level non-target compounds by gas chromatography/mass spectrometry (GC/MS) often is a challenging task that requires powerful software tools to detect the unknown components, to obtain the deconvoluted mass spectra, and to interpret the data if no acceptable library match is obtained. In this paper, the complementary use of electron ionization (EI) and chemical ionization (CI) is investigated in combination with GC/time-of-flight (TOF) MS for the elucidation of organic non-target (micro)contaminants in water samples. Based on accurate mass measurement of the molecular and fragment ions from the TOF MS, empirical formulae were calculated. Isotopic patterns, carbon number prediction filter and nitrogen rule were used to reduce the number of possible formulae. The candidate formulae were searched in databases to find possible chemical structures. Selection from possible structure candidates was achieved using information on substructures and observed neutral losses derived from the fragment ions. Four typical examples (bifenazate, boscalid, epoxiconazole, and fenhexamid) are used to illustrate the methodology applied and the various difficulties encountered in this process. Our results indicate that elucidation of unknowns cannot be achieved by following a standardized procedure, as both expertise and creativity are necessary in the process.

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12566-010-0015-9) contains supplementary material, which is available to authorized users.

HPLC/APCI-FTICR-MS as a tool for identification of partial polar mutagenic compounds in effect-directed analysis

Identification of unknown compounds remains one of the biggest challenges for the assignment of adverse effects of sediment contamination and other complex environmental mixtures to responsible toxicants by effect-directed analysis (EDA). The identification depends on information gained from biotesting, chromatographic separation, and mass spectrometric detection. Thus, a methodology is provided for non-target identification of partial polar mutagenic polyaromatic compounds in sediment extracts by using polymeric reversed-phase HPLC column, high-resolution mass spectrometry and PubChem database. After visualization and processing the chromatogram constituents by using deconvolution software, the unambiguous elemental compositions generated were used as input in PubChem database to find a possible identity for the suspected species. The retrieved structures from the database search were refined by characterized chromatographic and mass spectrometric classifiers based on 55 model compounds comprising eight different classes representing mutagenic substructures. The applicability of the method was demonstrated by positive and tentative identification of constituents of mutagenic sediment fractions similar to selected model compounds.

Application of preparative capillary gas chromatography (pcGC), automated structure generation and mutagenicity prediction to improve effect-directed analysis of genotoxicants in a contaminated groundwater

BACKGROUND, AIM AND SCOPE

The importance of groundwater for human life cannot be overemphasised. Besides fulfilling essential ecological functions, it is a major source of drinking water. However, in the industrial area of Bitterfeld, it is contaminated with a multitude of harmful chemicals, including genotoxicants. Therefore, recently developed methodologies including preparative capillary gas chromatography (pcGC), MOLGEN-MS structure generation and mutagenicity prediction were applied within effect-directed analysis (EDA) to reduce sample complexity and to identify candidate mutagens in the samples. A major focus was put on the added value of these tools compared to conventional EDA combining reversed-phase liquid chromatography (RP-LC) followed by GC/MS analysis and MS library search.

MATERIALS AND METHODS

We combined genotoxicity testing with umuC and RP-LC with pcGC fractionation to isolate genotoxic compounds from a contaminated groundwater sample. Spectral library information from the NIST05 database was combined with a computer-based structure generation tool called MOLGEN-MS for structure elucidation of unknowns. Finally, we applied a computer model for mutagenicity prediction (ChemProp) to identify candidate mutagens and genotoxicants.

RESULTS AND DISCUSSION

A total of 62 components were tentatively identified in genotoxic fractions. Ten of these components were predicted to be potentially mutagenic, whilst 2,4,6-trichlorophenol, 2,4-dichloro-6-methylphenol and 4-chlorobenzoic acid were confirmed as genotoxicants.

CONCLUSIONS AND PERSPECTIVES

The results suggest pcGC as a high-resolution fractionation tool and MOLGEN-MS to improve structure elucidation, whilst mutagenicity prediction failed in our study to predict identified genotoxicants. Genotoxicity, mutagenicity and carcinogenicity caused by chemicals are complex processes, and prediction from chemical structure still appears to be quite difficult. Progress in this field would significantly support EDA and risk assessment of environmental mixtures.