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: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:2,5-diketopiperazines are cyclic dipeptides found, among others, in chocolate. Although those compounds are contributing greatly to its pleasant bitterness, they can also be seen as interesting markers of cocoa beans processing. To evaluate the influence of bean variety and processing technology on the quantity of 2,5-diketopiperazines formed in chocolates, HPLC-MS/MS analyses were conducted, and a molecular network was built with the MS2 data. This approach eases the identification of 2,5-diketopiperazines within complex datasets and allows to visualize the chemical diversity of all samples. Using this methodology, 33 dark chocolates were analysed. 18 different diketopiperazine were identified and quantified. Among them, cyclo(L-ile-L-val), cyclo(L-leu-L-ile) and cyclo(L-phe-L-phe) were, to the best of our knowledge, detected for the first time in chocolate. The molecular network allows the clear visualization of differences between samples. The principal component analysis revealed the clustering of small batch chocolate samples according to bean variety, suggesting that bean genotype has a strong influence on the 2,5-diketopiperazines content of bean-to-bar chocolates, regardless of the degree of roasting or the technological process used by the small producers. The presence of two unique diastereoisomers in the classical chocolates bought in the supermarket indicates that the beans have probably undergone a more intense heat treatment. This study proposes the use of 2,5-diketopiperazines as potential markers of cocoa beans variety, as well as an indicator of post-harvest processing and processing technology, and highlights the potential of the molecular networks in the field of food and drink innovation as a promising tool to understand the complex chemistry of flavours.
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.