Project description:data files used to produce Figure 1B and Figure 2 (left). cosine similarity score was set to 0.65, and analyses were conducted using LC-MS (Waters Acquity connected to Thermo LTQ Orbitrap XL).
Project description:Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.
Project description:Botanical medicines have been utilized for centuries, but it remains challenging to identify bioactive constituents from complex botanical extracts. Bioassay-guided fractionation is often biased toward abundant or easily isolatable compounds. To comprehensively evaluate active botanical mixtures, methods that allow for the prioritization of active compounds are needed. To this end, a method integrating bioassay-guided fractionation, biochemometric selectivity ratio analysis, and molecular networking was devised and applied to Angelica keiskei to comprehensively evaluate its antimicrobial activity against Staphylococcus aureus. This approach enabled the identification of putative active constituents early in the fractionation process and provided structural information for these compounds. A subset of chalcone analogs were prioritized for isolation, yielding 4-hydroxyderricin (1, minimal inhibitory concentration [MIC] ≤ 4.6 µM, IC50 = 2.0 µM), xanthoangelol (2, MIC ≤ 4.0 µM, IC50 = 2.3) and xanthoangelol K (4, IC50 = 168 µM). This approach allowed for the identification of a low-abundance compound (xanthoangelol K) that has not been previously reported to possess antimicrobial activity and facilitated a more comprehensive understanding of the compounds responsible for A. keiskei's antimicrobial activity.
Project description:Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.
Project description:Ginkgo biloba L. stands as one of the oldest living tree species, exhibiting a diverse range of biological activities, including antioxidant, neuroprotective, anti-inflammatory, and cardiovascular activities. As part of our ongoing discovery of novel bioactive components from natural sources, we directed our focus toward the investigation of potential bioactive compounds from G. biloba fruit. The profiles of its chemical compounds were examined using a Global Natural Products Social (GNPS)-based molecular networking analysis. Guided by this, we successfully isolated and characterized 11 compounds from G. biloba fruit, including (E)-coniferin (1), syringin (2), 4-hydroxybenzoic acid 4-O-β-D-glucopyranoside (3), vanillic acid 4-O-β-D-glucopyranoside (4), syringic acid 4-O-β-D-glucopyranoside (5), (E)-ferulic acid 4-O-β-D-glucoside (6), (E)-sinapic acid 4-O-β-D-glucopyranoside (7), (1'R,2'S,5'R,8'S,2'Z,4'E)-dihydrophaseic acid 3'-O-β-D-glucopyranoside (8), eucomic acid (9), rutin (10), and laricitrin 3-rutinoside (11). The structural identification was validated through a comprehensive analysis involving nuclear magnetic resonance (NMR) spectroscopic data and LC/MS analyses. All isolated compounds were evaluated using an E-screen assay for their estrogen-like effects in MCF-7 cells. As a result, compounds 2, 3, 4, 8, and 9 promoted cell proliferation in MCF-7 cells, and these effects were mitigated by the ER antagonist, ICI 182,780. In particular, cell proliferation increased most significantly to 140.9 ± 6.5% after treatment with 100 µM of compound 2. The mechanism underlying the estrogen-like effect of syringin (2) was evaluated using a Western blot analysis to determine the expression of estrogen receptor α (ERα). We found that syringin (2) induced an increase in the phosphorylation of ERα. Overall, these experimental results suggest that syringin (2) can potentially aid the control of estrogenic activity during menopause.
Project description:This study presents an innovative cloud-based approach, using Pixian Douban, a well-known Chinese fermented seasoning, as a case study, to improve the identification of umami peptides and explore their interactions with the T1R1/T1R3 receptor. A feature-based molecular networking method was utilized to rapidly identify a total of eighteen peptides, including seven previously unrecorded ones. Notably, the umami threshold of QIVK in an aqueous solution was determined to be 0.3215 mmol/L, surpassing the majority of peptides reported in the past three years. Molecular docking analysis further revealed the strong binding of QIVK to T1R3 receptor residues through hydrogen bonds, as well as interactions via salt bridges and electrostatic attractions. As a result, this research significantly contributes to the efficient screening of umami peptides and the elucidation of the molecular basis of umami sensory perception in complex food systems.
Project description:Identifying novel phytochemical secondary metabolites following classical pharmacognostic investigations is tedious and often involves repetitive chromatographic efforts. During the past decade, Ultra-High Performance Liquid Chromatography-Quadrupole Time of Flight-Tandem Mass Spectrometry (UHPLC-QToF-MS/MS), in combination with molecular networking, has been successfully demonstrated for the rapid dereplication of novel natural products in complex mixtures. As a logical application of such innovative tools in botanical research, more than 40 unique 3-oxy-, 3, 6-dioxy-, and 3, 6, 27-trioxy-steroidal saponins were identified in aerial parts and rhizomes of botanically verified Smilax sieboldii. Tandem mass diagnostic fragmentation patterns of aglycones, diosgenin, sarsasapogenin/tigogenin, or laxogenin were critical to establishing the unique nodes belonging to six groups of nineteen unknown steroidal saponins identified in S. sieboldii. Mass fragmentation analysis resulted in the identification of 6-hydroxy sapogenins, believed to be key precursors in the biogenesis of characteristic smilaxins and sieboldins, along with other saponins identified within S. sieboldii. These analytes' relative biodistribution and characteristic molecular networking profiles were established by analyzing the leaf, stem, and root/rhizome of S. sieboldii. Deducing such profiles is anticipated to aid the overall product integrity of botanical dietary supplements while avoiding tedious pharmacognostic investigations and helping identify exogenous components within the finished products.
| S-EPMC10380369 | biostudies-literature
Project description:A Sphingomonas sp. used to produce exopolysaccharides
Project description:Data used to produce Figure 2D from "A multifaceted gradient in human cerebellum of structural and functional development." Shotgun proteomic analysis from tissue samples taken from lobules 1-4 and crus 2 of the human cerebellum. Single subject, 3yo female.
Project description:A major goal in natural product discovery programs is to rapidly dereplicate known entities from complex biological extracts. We demonstrate here that molecular networking, an approach that organizes MS/MS data based on chemical similarity, is a powerful complement to traditional dereplication strategies. Successful dereplication with molecular networks requires MS/MS spectra of the natural product mixture along with MS/MS spectra of known standards, synthetic compounds, or well-characterized organisms, preferably organized into robust databases. This approach can accommodate different ionization platforms, enabling cross correlations of MS/MS data from ambient ionization, direct infusion, and LC-based methods. Molecular networking not only dereplicates known molecules from complex mixtures, it also captures related analogues, a challenge for many other dereplication strategies. To illustrate its utility as a dereplication tool, we apply mass spectrometry-based molecular networking to a diverse array of marine and terrestrial microbial samples, illustrating the dereplication of 58 molecules including analogues.