Abstract-The occurrence of human and veterinary pharmaceuticals in the environment has been a subject of concern for the past decade because many of these emerging contaminants have been shown to persist in soil and water. Although recent studies indicate that pharmaceutical contaminants can pose long-term ecological risks, many of the investigations regarding risk assessment have only considered the ecotoxicity of the parent drug, with very little attention given to the potential contributions that metabolites may have. The scarcity of available environmental data on the human metabolites excreted into the environment or the microbial metabolites formed during environmental biodegradation of pharmaceutical residues can be attributed to the difficulty in analyzing trace amounts of previously unknown compounds in complex sample matrices. However, with the advent of highly sensitive and powerful analytical instrumentations that have become available commercially, it is likely that an increased number of pharmaceutical metabolites will be identified and included in environmental risk assessment. The present study will present a critical review of available literature on pharmaceutical metabolites, primarily focusing on their analysis and toxicological significance. It is also intended to provide an overview on the recent advances in analytical tools and strategies to facilitate metabolite identification in environmental samples. This review aims to provide insight on what future directions might be taken to help scientists in this challenging task of enhancing the available data on the fate, behavior, and ecotoxicity of pharmaceutical metabolites in the environment.

The rapid identification of novel plant metabolites and assignments of newly discovered substances to natural product classes present the main bottlenecks to defining plant specialized phenotypes. Although mass spectrometry provides powerful support for metabolite discovery by measuring molecular masses, ambiguities in elemental formulas often fail to reveal the biosynthetic origins of specialized metabolites detected using liquid chromatography-mass spectrometry. A promising approach for mining liquid chromatography-mass spectrometry metabolite profiling data for specific metabolite classes is achieved by calculating relative mass defects (RMDs) from molecular and fragment ions. This strategy enabled the rapid recognition of an extensive range of terpenoid metabolites in complex plant tissue extracts and is independent of retention time, abundance, and elemental formula. Using RMD filtering and tandem mass spectrometry data analysis, 24 novel elemental formulas corresponding to glycosylated sesquiterpenoid metabolites were identified in extracts of the wild tomato Solanum habrochaites LA1777 trichomes. Extensive isomerism was revealed by ultra-high-performance liquid chromatography, leading to evidence of more than 200 distinct sesquiterpenoid metabolites. RMD filtering led to the recognition of the presence of glycosides of two unusual sesquiterpenoid cores that bear limited similarity to known sesquiterpenes in the genus Solanum. In addition, RMD filtering is readily applied to existing metabolomics databases and correctly classified the annotated terpenoid metabolites in the public metabolome database for Catharanthus roseus.Plant metabolic networks generate amazing chemical diversity, but our understanding of the genetic factors responsible for plant chemistry remains primitive. The discovery and identification of metabolites has posed the greatest bottleneck in recent efforts to exploit metabolomics to address questions about the basis for biosynthetic diversity in the plant kingdom (Ji et al., 2009;Zhou et al., 2012). Since the specialized metabolism of nonmodel plants is taxonomically restricted, metabolite databases offer a poor representation of plant chemical diversity, and de novo recognition and discovery of metabolite chemistry is necessary. A common strategy for metabolite discovery has often started with the generation of tandem mass spectrometry (MS/MS) spectra, usually beginning with the most abundant metabolites, and uses characteristic fragment ions to assign metabolites to a particular class of compounds. Flavonoid identification from MS/MS spectra is often successful because most flavonoids yield MS/MS fragment ions characteristic of their flavonoid cores (Ma et al., 1997;Li et al., 2013). However, when MS/MS spectra fail to display classcharacteristic fragment ions, the recognition of a metabolite's structural class is less obvious.Specialized plant metabolites are often grouped as polyphenolic, terpenoid, alkaloid, polyketide, or fatty acid metabolites based upon the biosynthesis of their...

Background: Therapeutic values of Valeriana officinalis have been associated with sesquiterpenes whose biosynthetic origins have remained enigmatic. Results: A cyclobutenyl intermediate in the catalytic cascade of valerena-1,10-diene synthase is reported. Conclusion: A new class of sesquiterpene synthases for the biosynthesis of sesquiterpenes harboring isobutenyl functional groups is proposed. Significance: Similar catalytic mechanisms from evolutionarily diverse organisms are proposed and portend sources for sesquiterpene diversity.

Specialized compounds from photosynthetic organisms serve as rich resources for drug development. From aspirin to atropine, plant-derived natural products have had a profound impact on human health. Technological advances provide new opportunities to access these natural products in a metabolic context. Here, we describe a database and platform for storing, visualizing and statistically analyzing metabolomics data from fourteen medicinal plant species. The metabolomes and associated transcriptomes (RNAseq) for each plant species, gathered from up to twenty tissue/organ samples that have experienced varied growth conditions and developmental histories, were analyzed in parallel. Three case studies illustrate different ways that the data can be integrally used to generate testable hypotheses concerning the biochemistry, phylogeny and natural product diversity of medicinal plants. Deep metabolomics analysis of Camptotheca acuminata exemplifies how such data can be used to inform metabolic understanding of natural product chemical diversity and begin to formulate hypotheses about their biogenesis. Metabolomics data from Prunella vulgaris, a species that contains a wide range ofantioxidant, antiviral, tumoricidal and anti-inflammatory constituents, provide a case study of obtaining biosystematic and developmental fingerprint information from metabolite accumulation data in a little studied species. Digitalis purpurea, well known as a source of cardiac glycosides, is used to illustrate how integrating metabolomics and transcriptomics data can lead to identification of candidate genes encoding biosynthetic enzymes in the cardiac glycoside pathway. Medicinal Plant Metabolomics Resource (MPM) [1] provides a framework for generating experimentally testable hypotheses about the metabolic networks that lead to the generation of specialized compounds, identifying genes that control their biosynthesis and establishing a basis for modeling metabolism in less studied species. The database is publicly available and can be used by researchers in medicine and plant biology.

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