Description: Ultrahigh-resolution Fourier transform tandem mass spectrometry was employed to reveal novel structural detail of the natural complex mixture dissolved organic matter (DOM) that is found ubiquitously in soils and rivers. We developed and evaluated a novel approach to decipher the structural detail that is encrypted in DOM. One DOM sample from a spruce forest (Wetzstein, Germany, 50° 27' 13" N; 11° 27' 27" E; 785 meter above sea level) and Suwannee River Natural Organic Matter (SRNOM, purchased from International Humic Substances Society as isolate 2R101N; details given in Green et al. 2015, Environm Eng Sci 32, 1) were used as representative biodegraded DOM mixtures of high complexity and measured by direct-injection tandem mass spectrometry (DI-ESI-Orbitrap-MS/MS). The unknowns in DOM were then compared with indicative tandem MS features (mass differences, "dm" features, written with greek letter delta instead of d) from known standard compounds (14 phenolic standard substances measured in parallel, and 11477 library mass spectra available from the java-based software framework SIRIUS which included nearly 18000 unique molecular structures) and natural product and in-silico structure suggestions. The dataset consists of seven subsets (Data Set S1 - S7), all of which are xlsx files. "Data Set S1", contains the standard compound data and fragmentation sensitivities (14 phenolic standards) and general information on the analyzed parts of the DOM mass spectrum (molecular indices, number of precursors, number of product ions). Data Sets S2 through S5 contain the aligned DOM molecular composition data obtained at different collision energies for four mass windows ("Data Set S2", m/z 241; "Data Set S3", m/z 301; "Data Set S4", m/z 361; "Data Set S5", m/z 417) and include mass difference matching results (non-indicative dm features, standard compound (14 phenolics) dm features, and SIRIUS library spectra Δm features). "Data Set S6" contains the full dm feature lists and several data tables on individual DOM precursor properties (for example, aggregated matching results for indicative dm features (incl. N- and S-containing precursors), DOM precursor fragmentation sensitivity data, two-way clustering data of precursors and dm features, and structure suggestions classified into broader structural families ("scaffolds"). "Data Set S7" contains the results of a two-way clustering analysis using 725 SIRIUS-annotated dm features. In this dataset, the dm data is used to estimate structural compositions of individual DOM precursor ions. More details can be found in the related manuscript by the same authors.

Description: Ultrahigh-resolution Fourier transform tandem mass spectrometry was employed to reveal novel structural detail of the natural complex mixture dissolved organic matter (DOM) that is found ubiquitously in soils and rivers. We developed and evaluated a novel approach to decipher the structural detail that is encrypted in DOM. A DOM sample from a spruce forest (Wetzstein, Germany, 50° 27' 13" N; 11° 27' 27" E; 785 meter above sea level) was used as a representative biodegraded DOM mixture of high complexity and measured by direct-injection tandem mass spectrometry (DI-ESI-Orbitrap-MS/MS). The unknowns in DOM were then compared with indicative tandem MS features (mass differences, "Δm" features) from known standard compounds (14 phenolic standard substances measured in parallel, and 11280 library mass spectra available from the java-based software framework SIRIUS) and natural product and in-silico structure suggestions. The dataset consists of six subsets (Data Set ds01 - ds06), all of which are xlsx files.

Description: n our daily lives, we consume foods that have been transported, stored, prepared, cooked, or otherwise processed by ourselves or others. Food storage and preparation have drastic effects on the chemical composition of foods. Untargeted mass spectrometry analysis of food samples has the potential to increase our chemical understanding of these processes by detecting a broad spectrum of chemicals. We performed a time-based analysis of the chemical changes in foods during common preparations, such as fermentation, brewing, and ripening, using untargeted mass spectrometry and molecular networking. The data analysis workflow presented implements an approach to study changes in food chemistry that can reveal global alterations in chemical profiles, identify changes in abundance, as well as identify specific chemicals and their transformation products. The data generated in this study are publicly available, enabling the replication and re-analysis of these data in isolation, and serve as a baseline dataset for future investigations.

Description: The Estremadura Spur pockmarks are a unique and unexplored ecosystem located in the North Atlantic, off the coast of Portugal. A total of 85 marine-derived actinomycetes were isolated and cultured from sediments collected from this ecosystem at a depth of 200 to 350 m. Nine genera, Streptomyces, Micromonospora, Saccharopolyspora, Actinomadura, Actinopolymorpha, Nocardiopsis, Saccharomonospora, Stackebrandtia, and Verrucosispora were identified by 16S rRNA gene sequencing analyses, from which the first two were the most predominant. Non-targeted LC-MS/MS, in combination with molecular networking, revealed high metabolite diversity, including several known metabolites, such as surugamide, antimycin, etamycin, physostigmine, desferrioxamine, ikarugamycin, piericidine, and rakicidin derivatives, as well as numerous unidentified metabolites. Taxonomy was the strongest parameter influencing the metabolite production, highlighting the different biosynthetic potentials of phylogenetically related actinomycetes; the majority of the chemical classes can be used as chemotaxonomic markers, as the metabolite distribution was mostly genera-specific. The EtOAc extracts of the actinomycete isolates demonstrated antimicrobial and antioxidant activity. Altogether, this study demonstrates that the Estremadura Spur is a source of actinomycetes with potential applications for biotechnology. It highlights the importance of investigating actinomycetes from unique ecosystems, such as pockmarks, as the metabolite production reflects their adaptation to this habitat.

Description: We report a novel hybrid, molecular and elemental mass spectrometry (MS) setup for the absolute quantification of snake venom proteomes shown here for two desert black cobra species within the genus Walterinnesia, Walterinnesia aegyptia and Walterinnesia morgani. The experimental design includes the decomplexation of the venom samples by reverse-phase chromatography independently coupled to four mass spectrometry systems: the combined bottom-up and top-down molecular MS for protein identification and a parallel reverse-phase microbore high-performance liquid chromatograph (RP-μHPLC) on-line to inductively coupled plasma (ICP-MS/MS) elemental mass spectrometry and electrospray ionization quadrupole time-of-flight mass spectrometry (ESI-QToF MS). This allows to continuously record the absolute sulfur concentration throughout the chromatogram and assign it to the parent venom proteins separated in the RP-μHPLC-ESI-QToF parallel run via mass profiling. The results provide a locus-resolved and quantitative insight into the three desert black cobra venom proteome samples. They also validate the units of measure of our snake venomics strategy for the relative quantification of snake venom proteomes as % of total venom peptide bonds as a proxy for the % by weight of the venom toxins/toxin families. In a more general context, our work may pave the way for broader applications of hybrid elemental/molecular MS setups in diverse areas of proteomics.