Evaluation of Ion Mobility Spectrometry for Improving Constitutional Assignment in Natural Product Mixtures

Systematic analysis of post-blast organic traces in soil, application of color tests, TLC, GC-MS, and ITMS

The post-blast trace analysis of explosives is inherently complex, requiring the separation and identification of multiple unknown compounds within contaminated matrices. The study explores modified methods for the extraction, analysis, and detection of post-explosion residues, of the three main organic explosives groups, focusing on key explosives such as NC (Nitrocellulose), NG (Nitroglycerin), Tetryl, TNT, RDX, PETN, as well as sheet and plastic explosives. A comprehensive protocol was developed, involving sample extraction, filtration, and clean-up processes, followed by analysis using a range of analytical techniques. The study introduces an optimized spot test scheme and proposes novel TLC mobile phases for improved separation and characterization of explosives. In addition, a new GC/EI-MS method was developed for the selective detection of PETN, overcoming common thermal degradation issues. The presented GC-MS findings of this study demonstrate the significant advancements made in overcoming these obstacles, providing a clearer understanding of the analytical improvements enabling its reliable detection. Ion Trap Mobility Spectrometry (ITMS) was employed for evaluating the concentration-time decay of explosive residues on hand swabs, revealing that NG exhibited higher persistence than TNT. The study determined the Minimum Detection Limits (MDL) to be 2 ng for TNT, 3 ng for RDX and NG, and 4 ng for PETN. The research underscores that the effectiveness of explosive detection methods depends on aligning techniques with the physical and chemical properties of the analytes. Results also emphasize the importance of using confirmatory techniques beyond TLC and spot tests, as these methods are presumptive analyses and insufficient for independent compound identification. The proposed TLC mobile phases achieved significant resolution of the studied explosives, achieving significantly improved Rf values for a wide range of explosives across different groups, confirming their suitability for forensic applications. This study establishes that GC/EI-MS with its basic set, can be used for PETN analysis, while ITMS offers a fast and reliable approach for field detection and persistence studies. Collectively, these findings contribute to the analytical protocols for forensic explosive residue analysis.

Metabolite profiling and characterization of potential anticancer constituents from Garcinia subfalcata using UPLC-IMS-QTOF-MS

Garcinia subfalcata, an edible species endemic to China, has limited research on its chemical composition and biological effects. This study aimed to analyze metabolites in different plant parts and identify potential anticancer constituents. Using UPLC-IMS-QTOF-MS-based metabolomics, a total of 124 compounds were identified, with xanthones, flavonoids and phloroglucinols being the predominant compounds. PCA and PLS-DA analyses revealed significant metabolite differences among plant parts, identifying 28 differential metabolites, including bronianone and (±)-fukugiside. Antiproliferative assays showed varying bioactivities, with bark exhibiting the highest cytotoxicity against A549, HeLa and HGC-27 cells (IC50: 2.72-5.71 μg/mL). Mechanism studies indicated that the bark inhibited cell proliferation by inducing apoptosis and disrupting mitochondrial membrane potential. S-plot models revealed 23 potential anticancer constituents, including (-)-epicatechin and 1,7-dihydroxyxanthone. These findings highlight G. subfalcata's potential as a source of functional food supplements and medicinal agents and indicate the efficacy of UPLC-IMS-QTOF-MS-based metabolomics in exploring bioactive components within Garcinia.

LC-MS/DIA-based strategy for comprehensive flavonoid profiling: an Ocotea spp. applicability case

We introduce a liquid chromatography - mass spectrometry with data-independent acquisition (LC-MS/DIA)-based strategy, specifically tailored to achieve comprehensive and reliable glycosylated flavonoid profiling. This approach facilitates in-depth and simultaneous exploration of all detected precursors and fragments during data processing, employing the widely-used open-source MZmine 3 software. It was applied to a dataset of six Ocotea plant species. This framework suggested 49 flavonoids potentially newly described for these plant species, alongside 45 known features within the genus. Flavonols kaempferol and quercetin, both exhibiting O-glycosylation patterns, were particularly prevalent. Gas-phase fragmentation reactions further supported these findings. For the first time, the apigenin flavone backbone was also annotated in most of the examined Ocotea species. Apigenin derivatives were found mainly in the C-glycoside form, with O. porosa displaying the highest flavone : flavonol ratio. The approach also allowed an unprecedented detection of kaempferol and quercetin in O. porosa species, and it has underscored the untapped potential of LC-MS/DIA data for broad and reliable flavonoid profiling. Our study annotated more than 50 flavonoid backbones in each species, surpassing the current literature.

Cycloheximide in the nanomolar range inhibits seed germination of Orobanche minor

From the 992 samples of culture extracts of microorganisms isolated from soil in Japan, we found that the extract of Streptomyces sp. no. 226 inhibited Orobanche minor seed germination without significantly affecting the seed germination of Trifolium pratense and the growth of Aspergillus oryzae and Escherichia coli. Using ESI-MS, 1H-NMR, and 13C-NMR, we identified the active compound as cycloheximide. Cycloheximide had half-maximum inhibitory concentrations of 2.6 ng/mL for the inhibition of seed germination of O. minor and 2.5 µg/mL for that of the conidial germination of A. oryzae. Since cycloheximide is known to inhibit translation by interacting with ribosomal protein L28 (RPL28) in yeast, we investigated whether RPL protein of O. minor plays a critical role in the inhibition of O. minor seed germination. Our data suggested that O. minor RPL27A was not sensitive to cycloheximide by comparing it to the strain expressing S. cerevisiae RPL28. These findings suggest the presence of an unidentified mechanism by which cycloheximide hinders O. minor seed germination.

Integrative open workflow for confident annotation and molecular networking of metabolomics MSE/DIA data

Liquid chromatography coupled with high-resolution mass spectrometry data-independent acquisition (LC-HRMS/DIA), including MSE, enable comprehensive metabolomics analyses though they pose challenges for data processing with automatic annotation and molecular networking (MN) implementation. This motivated the present proposal, in which we introduce DIA-IntOpenStream, a new integrated workflow combining open-source software to streamline MSE data handling. It provides 'in-house' custom database construction, allows the conversion of raw MSE data to a universal format (.mzML) and leverages open software (MZmine 3 and MS-DIAL) all advantages for confident annotation and effective MN data interpretation. This pipeline significantly enhances the accessibility, reliability and reproducibility of complex MSE/DIA studies, overcoming previous limitations of proprietary software and non-universal MS data formats that restricted integrative analysis. We demonstrate the utility of DIA-IntOpenStream with two independent datasets: dataset 1 consists of new data from 60 plant extracts from the Ocotea genus; dataset 2 is a publicly available actinobacterial extract spiked with authentic standard for detailed comparative analysis with existing methods. This user-friendly pipeline enables broader adoption of cutting-edge MS tools and provides value to the scientific community. Overall, it holds promise for speeding up metabolite discoveries toward a more collaborative and open environment for research.

Natural Products Dereplication: Databases and Analytical Methods

The development of efficient methods for dereplication has been critical in the re-emergence of the research in natural products as a source of drug leads. Current dereplication workflows rapidly identify already known bioactive secondary metabolites in the early stages of any drug discovery screening campaign based on natural extracts or enriched fractions. Two main factors have driven the evolution of natural products dereplication over the last decades. First, the availability of both commercial and public large databases of natural products containing the key annotations against which the biological and chemical data derived from the studied sample are searched for. Second, the considerable improvement achieved in analytical technologies (including instrumentation and software tools) employed to obtain robust and precise chemical information (particularly spectroscopic signatures) on the compounds present in the bioactive natural product samples. This chapter describes the main methods of dereplication, which rely on the combined use of large natural product databases and spectral libraries, alongside the information obtained from chromatographic, UV-Vis, MS, and NMR spectroscopic analyses of the samples of interest.

Advanced Methods for Natural Products Discovery: Bioactivity Screening, Dereplication, Metabolomics Profiling, Genomic Sequencing, Databases and Informatic Tools, and Structure Elucidation

Natural Products (NP) are essential for the discovery of novel drugs and products for numerous biotechnological applications. The NP discovery process is expensive and time-consuming, having as major hurdles dereplication (early identification of known compounds) and structure elucidation, particularly the determination of the absolute configuration of metabolites with stereogenic centers. This review comprehensively focuses on recent technological and instrumental advances, highlighting the development of methods that alleviate these obstacles, paving the way for accelerating NP discovery towards biotechnological applications. Herein, we emphasize the most innovative high-throughput tools and methods for advancing bioactivity screening, NP chemical analysis, dereplication, metabolite profiling, metabolomics, genome sequencing and/or genomics approaches, databases, bioinformatics, chemoinformatics, and three-dimensional NP structure elucidation.