Mass spectral libraries are collections of reference spectra, usually associated with specific analytes from which the spectra were generated, that are used for further downstream analysis of new spectra. There are many different formats used for encoding spectral libraries, but none have undergone a standardization process to ensure broad applicability to many applications. As part of the Human Proteome Organization Proteomics Standards Initiative (PSI), we have developed a standardized format for encoding spectral libraries, called mzSpecLib (https://psidev.info/mzSpecLib). It is primarily a data model that flexibly encodes metadata about the library entries using the extensible PSI-MS controlled vocabulary and can be encoded in and converted between different serialization formats. We have also developed a standardized data model and serialization for fragment ion peak annotations, called mzPAF (https://psidev.info/mzPAF). It is defined as a separate standard, since it may be used for other applications besides spectral libraries. The mzSpecLib and mzPAF standards are compatible with existing PSI standards such as ProForma 2.0 and the Universal Spectrum Identifier. The mzSpecLib and mzPAF standards have been primarily defined for peptides in proteomics applications with basic small molecule support. They could be extended in the future to other fields that need to encode spectral libraries for nonpeptidic analytes.

The rapid annotation and identification by mass spectrometry techniques of flavonoids remains a challenge, due to their structural diversity and the limited availability of reference standards. This study applies a workflow to characterize two isoflavonoids, the orobol-C-glycosides analogs, using high-energy collisional dissociation (HCD)- and collision-induced dissociation (CID)-type fragmentation patterns, and also to evaluate the antioxidant effects of these compounds by ferric reducing antioxidant power (FRAP), 2,2′-azino-bis(3-ethylbenzothiazolin acid) 6-sulfonic acid (ABTS), and 2,2-diphenyl-1-picrylhydrazyl (DPPH) methods. By the CID-type fragmentation, in positive mode and at all high-resolution mass spectrometry (HRMS) multiple stage, there were shown differences in the annotation of the compounds, mainly concerning some ratios of relative abundance. At CID-MS2 20 eV, the compounds could be efficiently characterized, because they present distinct base peaks [M + H]+ and [M + H–H2O]+ for the orobol-8-C- and orobol-6-C-glycoside, respectively. Similarly, by the HCD-type fragmentation, in HRMS2 stage, differences between orobol analogs in both mode of ionization were observed. However, the HR HCD-MS2 at 80 eV, in positive mode, generated more ions and each isomer presented different base peaks ions, [0,2X]+ for the orobol-8-C-glycoside and [0,3X]+ for the orobol-6-C-glycoside. By the DPPH, the 8-C-derivative showed a very close value compared with the standard rutin and, in the ABTS method, a higher radical-scavenging activity. In both methods, the EC50 of orobol-8-C-glycoside was almost twice better compared with orobol-6-C-glycoside. In FRAP, both C-glycosides showed a good capacity as Fe+3 reducing agents. We could realize that combined MS techniques, highlighting the positive mode of ionization, can be used to evaluate the isoflavones analogs being useful to differentiate between the isomeric flavones; therefore, these data are important to mass spectrometry dereplication studies become more efficient.

Mass spectrometry (MS) is one of the primary techniques used for large-scale analysis of small molecules in metabolomics studies. To date, there has been little data format standardization in this field, as different software packages export results in different formats represented in XML or plain text, making data sharing, database deposition, and reanalysis highly challenging. Working within the consortia of the Metabolomics Standards Initiative, Proteomics Standards Initiative, and the Metabolomics Society, we have created mzTab-M to act as a common output format from analytical approaches using MS on small molecules. The format has been developed over several years, with input from a wide range of stakeholders. mzTab-M is a simple tab-separated text format, but importantly, the structure is highly standardized through the design of a detailed specification document, tightly coupled to validation software, and a mandatory controlled vocabulary of terms to populate it. The format is able to represent final quantification values from analyses, as well as the evidence trail in terms of features measured directly from MS (e.g., LC-MS, GC-MS, DIMS, etc.) and different types of approaches used to identify molecules. mzTab-M allows for ambiguity in the identification of molecules to be communicated clearly to readers of the files (both people and software). There are several implementations of the format available, and we anticipate widespread adoption in the field.

Long‐chain ferulic acid esters, such as eicosyl ferulate (1), show a complex and analytically valuable fragmentation behavior under negative‐ion electrospay collision‐induced dissociation ((‐)‐ESI‐CID) mass spectrometry, as studied by use of a high‐resolution (Orbitrap) mass spectrometer. In a strong contrast to the very simple fragmentation of the [M + H]+ ion, which is discussed briefly, the deprotonated molecule, [M ‐ H]‐, exhibits a rich secondary fragmentation chemistry. It first loses a methyl radical (MS2) and the ortho‐quinoid [M ‐ H ‐ Me]‐• radical anion thus formed then dissociates by loss of an extended series of neutral radicals, CnH2n+1• (n = 0‐16) from the long alkyl chain, in competition with the expulsion of CO and CO2 (MS3). The further fragmentation (MS4) of the [M ‐ H ‐ Me ‐ C3H7]‐ ion, discussed as an example, and the highly specific losses of alkyl radicals from the [M ‐ H ‐ Me ‐ CO]‐• and [M ‐ H ‐ Me ‐ CO2]‐• ions provide some mechanistic and structural insights.

Metabolic fingerprinting is a powerful analytical technique, giving access to high-throughput identification and relative quantification of multiple metabolites. Because of short analysis times, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is the preferred instrumental platform for fingerprinting, although its power in analysis of free fatty acids (FFAs) is limited. However, these metabolites are the biomarkers of human pathologies and indicators of food quality. Hence, a high-throughput method for their fingerprinting is required. Therefore, here we propose a MALDI-TOF-MS method for identification and relative quantification of FFAs in biological samples of different origins. Our approach relies on formation of monomolecular Langmuir films (LFs) at the interphase of aqueous barium acetate solution, supplemented with low amounts of 2,5-dihydroxybenzoic acid, and hexane extracts of biological samples. This resulted in detection limits of 10–13–10–14 mol and overall method linear dynamic range of at least 4 orders of magnitude with accuracy and precision within 2 and 17%, respectively. The method precision was verified with eight sample series of different taxonomies, which indicates a universal applicability of our approach. Thereby, 31 and 22 FFA signals were annotated by exact mass and identified by tandem MS, respectively. Among 20 FFAs identified in Fucus algae, 14 could be confirmed by gas chromatography-mass spectrometry.

Identification and structural determination of small molecules by mass spectrometry is an important step in chemistry and biochemistry. However, the chemically realistic annotation of a fragment ion spectrum can be a difficult challenge. We developed ChemFrag, for the detection of fragmentation pathways and the annotation of fragment ions with chemically reasonable structures. ChemFrag combines a quantum chemical with a rule‐based approach. For different doping substances as test instances, ChemFrag correctly annotates fragment ions. In most cases, the predicted fragments are chemically more realistic than those from purely combinatorial approaches, or approaches based on machine learning. The annotation generated by ChemFrag often coincides with spectra that have been manually annotated by experts. This is a major advance in peak annotation and allows a more precise automatic interpretation of mass spectra.

NMR is a widely used analytical technique with a growing number of repositories available. As a result, demands for a vendor-agnostic, open data format for long-term archiving of NMR data have emerged with the aim to ease and encourage sharing, comparison, and reuse of NMR data. Here we present nmrML, an open XML-based exchange and storage format for NMR spectral data. The nmrML format is intended to be fully compatible with existing NMR data for chemical, biochemical, and metabolomics experiments. nmrML can capture raw NMR data, spectral data acquisition parameters, and where available spectral metadata, such as chemical structures associated with spectral assignments. The nmrML format is compatible with pure-compound NMR data for reference spectral libraries as well as NMR data from complex biomixtures, i.e., metabolomics experiments. To facilitate format conversions, we provide nmrML converters for Bruker, JEOL and Agilent/Varian vendor formats. In addition, easy-to-use Web-based spectral viewing, processing, and spectral assignment tools that read and write nmrML have been developed. Software libraries and Web services for data validation are available for tool developers and end-users. The nmrML format has already been adopted for capturing and disseminating NMR data for small molecules by several open source data processing tools and metabolomics reference spectral libraries, e.g., serving as storage format for the MetaboLights data repository. The nmrML open access data standard has been endorsed by the Metabolomics Standards Initiative (MSI), and we here encourage user participation and feedback to increase usability and make it a successful standard.

Representative compounds with a 1,3‐dihydroxybenzene substructure belonging to different important polyphenol classes (stilbenes, flavones, isoflavones, flavonols, flavanones, flavanols, phloroglucinols, anthraquinones and bisanthraquinones) were investigated based on detailed high‐resolution tandem mass spectrometry measurements with an Orbitrap system under negative ion electrospray conditions. The mass spectral behaviour of these compound classes was compared among each other not only with respect to previously described losses of CO, CH2CO and C3O2 but also concerning the loss of CO2 and successive specific fragmentations. Furthermore, some unusual fragmentations such as the loss of a methyl radical during mass spectral decomposition are discussed. The obtained results demonstrate both similarities and differences in their mass spectral fragmentation under MSn conditions, allowing a characterization of the corresponding compound type.

The identification of metabolites by mass spectrometry constitutes a major bottleneck which considerably limits the throughput of metabolomics studies in biomedical or plant research. Here, we present a novel approach to analyze metabolomics data from untargeted, data-independent LC-MS/MS measurements. By integrated analysis of MS1 abundances and MS/MS spectra, the identification of regulated metabolite families is achieved. This approach offers a global view on metabolic regulation in comparative metabolomics. We implemented our approach in the web application “MetFamily”, which is freely available at http://msbi.ipb-halle.de/MetFamily/. MetFamily provides a dynamic link between the patterns based on MS1-signal intensity and the corresponding structural similarity at the MS/MS level. Structurally related metabolites are annotated as metabolite families based on a hierarchical cluster analysis of measured MS/MS spectra. Joint examination with principal component analysis of MS1 patterns, where this annotation is preserved in the loadings, facilitates the interpretation of comparative metabolomics data at the level of metabolite families. As a proof of concept, we identified two trichome-specific metabolite families from wild-type tomato Solanum habrochaites LA1777 in a fully unsupervised manner and validated our findings based on earlier publications and with NMR.

Demands in research investigating small molecules by applying untargeted approaches have been a key motivator for the development of repositories for mass spectrometry spectra and automated tools to aid compound identification. Comparatively little attention has been afforded to using retention times (RTs) to distinguish compounds and for liquid chromatography there are currently no coordinated efforts to share and exploit RT information. We therefore present PredRet; the first tool that makes community sharing of RT information possible across laboratories and chromatographic systems (CSs). At http://predret.org, a database of RTs from different CSs is available and users can upload their own experimental RTs and download predicted RTs for compounds which they have not experimentally determined in their own experiments. For each possible pair of CSs in the database, the RTs are used to construct a projection model between the RTs in the two CSs. The number of compounds for which RTs can be predicted and the accuracy of the predictions are dependent upon the compound coverage overlap between the CSs used for construction of projection models. At the moment, it is possible to predict up to 400 RTs with a median error between 0.01 and 0.28 min depending on the CS and the median width of the prediction interval ranging from 0.08 to 1.86 min. By comparing experimental and predicted RTs, the user can thus prioritize which isomers to target for further characterization and potentially exclude some structures completely. As the database grows, the number and accuracy of predictions will increase.