LC-MS/MS DDA Method Optimization Natural Products
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Q Exactive HF
ORGANISM(S): Unknown Species
SUBMITTER: 
Daniel Petras
PROVIDER: MSV000088732 | MassIVE | Wed Jan 26 00:25:00 GMT 2022
REPOSITORIES: MassIVE
Similar Datasets
Project description:Untargeted-metabolomics LC-MS/MS analysis of commercial natural products pool, analyzed with different DDA settings with the objective to find the best one.
2022-01-26 | MSV000088732 | GNPS
Project description:DDA untargeted metabolomics of 3 different complex samples coming from river, ocean, and soil sources was used to obtain the best optimization setting.
2022-03-01 | MSV000088937 | MassIVE
Project description:In this study, a multi-residue analysis was developed for 32 compounds, including pesticides and metabolites, in five meat products using gas chromatography-tandem mass spectrometry (GC-MS/MS). The validation of the developed analytical method was also evaluated in accordance with Codex Alimentarius guidelines. Aminopropyl (NH2), C18, and florisil solid phase extraction (SPE) cartridges were used to evaluate and optimize the cleanup procedure of the tested samples prior to GC-MS/MS analysis. Based on the analytical performance, the C18 SPE cartridge was deemed to be the most suitable among the examined SPE cartridges. The optimized method demonstrated that 29 out of 32 tested compounds acquired good linearity (R2 ≥ 0.99), and 25 tested compounds displayed the method limit of quantification (MLOQ) ≤ 0.01 mg/kg. Out of the 32 tested compounds, only 21 compounds met the acceptable analytical criteria for the lard and tallow samples, compared to 27 compounds in the beef, pork, and chicken samples that falls within the acceptable standards for recovery (70–120%) and analytical precision (relative standard deviation RSD ≤ 20%). The average matrix effect was widely varied (20.1–64.8%) in the studied meat samples that were affected by either ion enhancement or suppression. In particular, in the lard sample, 13 compounds showed poor recovery and analytical precision due to ion suppression. Thus, the matrix effect (ME) was considered a critical factor during multi-residue pesticide analysis in different meat products. In conclusion, this developed analytical method can be used as a routine monitoring system for residual pesticide analysis in livestock products with acceptable analytical standards. Further meticulous analytical studies should be optimized and validated for multi-residue pesticide analysis in diversified meat products.
| S-EPMC9563028 | biostudies-literature
Project description:DDA untargeted metabolomics of 3 different complex samples coming from river, ocean, and soil sources was used to obtain the best optimization setting.
2022-03-01 | MSV000088937 | GNPS
Project description:Comparison of Data Dependent Acquisition MS/MS and All Ion Fragmentation of a mixture of known Natural Products.
2022-01-19 | MSV000088698 | MassIVE
Project description:A major problem in the discovery of new biologically active compounds from natural products is the reisolation of known compounds. Such reisolations waste time and resources, distracting chemists from more promising leads. To address this problem, dereplication strategies are needed that enable crude extracts to be screened for the presence of known compounds before isolation efforts are initiated. In a project to identify anticancer drug leads from filamentous fungi, a significant dereplication challenge arises, as the taxonomy of the source materials is rarely known, and, thus, the literature cannot be probed to identify likely known compounds. An ultraperformance liquid chromatography-photodiode array-high-resolution tandem mass spectrometric (UPLC-PDA-HRMS-MS/MS) method was developed for dereplication of fungal secondary metabolites in crude culture extracts. A database was constructed by recording HRMS and MS/MS spectra of fungal metabolites, utilizing both positive- and negative-ionization modes. Additional details, such as UV-absorption maxima and retention times, were also recorded. Small-scale cultures that showed cytotoxic activities were dereplicated before engaging in the scale-up or purification processes. Using these methods, approximately 50% of the cytotoxic extracts could be eliminated from further study after the confident identification of known compounds. The specific attributes of this dereplication methodology include a focus on bioactive secondary metabolites from fungi, the use of a 10 min chromatographic method, and the inclusion of both HRMS and MS/MS data.
| S-EPMC3856222 | biostudies-literature
Project description:In its fourth year, the CASMI 2016 contest was organized to evaluate current chemical structure identification strategies for 19 natural products using high-resolution LC-MS and LC-MS/MS challenge datasets using automated methods with or without the combination of other tools. These natural products originate from plants, fungi, marine sponges, algae, or micro-algae. Every compound annotation workflow must start with determination of elemental compositions. Of these 19 challenges, one was excluded by the organizers after submission. For the remaining 18 challenges, three software programs were used. MS-FINDER version 1.62 was able to correctly identify 89% of the molecular formulas using an internal database that comprised of 13 metabolomics repositories with 45,181 formulas. SIRIUS correctly identified 61% compositions using PubChem formulas and Seven Golden Rules correctly identified 83% by using the Dictionary of Natural Products as a targeted database. Next, we performed structural dereplication for which we used the consensus formula from the three software programs. We submitted two solution sets for these challenges. In the first solution set, avaniya001, we only used the internal MS-FINDER functions for predicting and ranking structures, correctly identifying 53% of the structures as top-hit, 72% within the top-3 structures, and 78% within the top-10 hits. For our second set, avaniya002, we used both MS-FINDER predictions as well as MS/MS queries against the commercial NIST 14, METLIN, and the public MassBank of North America libraries. Here we correctly identified 78% of the structures as top-hit and 83% within the top-3 hits. Three challenge spectra remained unidentified in either of our submissions within the top-10 hits.
| S-EPMC6771281 | biostudies-other
Project description:Introduction Stable isotope tracer studies are increasingly applied to explore metabolism from the detailed analysis of tracer incorporation into metabolites. Untargeted LC/MS approaches have recently emerged and provide potent methods for expanding the dimension and complexity of the metabolic networks that can be investigated. A number of software tools have been developed to process the highly complex MS data collected in such studies; however, a method to optimize the extraction of valuable isotopic data is lacking. Objectives To develop and validate a method to optimize automated data processing for untargeted MS-based isotopic tracing investigations of metabolism. Methods The method is based on the application of a suitable reference material to rationally perform parameter optimization throughout the complete data processing workflow. It was applied in the context of 13C-labelling experiments and with two different software, namely geoRge and X13CMS. It was illustrated with the study of a E. coli mutant impaired for central metabolism. Results The optimization methodology provided significant gain in the number and quality of extracted isotopic data, independently of the software considered. Pascal triangle samples are well suited for such purpose since they allow both the identification of analytical issues and optimization of data processing at the same time. Conclusion The proposed method maximizes the biological value of untargeted MS-based isotopic tracing investigations by revealing the full metabolic information that is encoded in the labelling patterns of metabolites. Supplementary Information The online version contains supplementary material available at 10.1007/s11306-022-01897-5.
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Project description:Inhibitors of quinone reductase-2 (NQO2; QR-2) can have antimalarial activity and antitumor activities or can function as chemoprevention agents by preventing the metabolic activation of toxic quinones such as menadione. To expedite the search for new natural product inhibitors of QR-2, we developed a screening assay based on ultrafiltration liquid chromatography-mass spectrometry that is compatible with complex samples such as bacterial or botanical extracts. Human QR-2 was prepared recombinantly, and the known QR-2 inhibitor, resveratrol, was used as a positive control and as a competitive ligand to eliminate false positives. Ultrafiltration LC-MS screening of extracts of marine sediment bacteria resulted in the discovery of tetrangulol methyl ether as an inhibitor of QR-2. When applied to the screening of hop extracts from the botanical, Humulus lupulus L., xanthohumol and xanthohumol D were identified as ligands of QR-2. Inhibition of QR-2 by these ligands was confirmed using a functional enzyme assay. Furthermore, binding of xanthohumol and xanthohumol D to the active site of QR-2 was confirmed using X-ray crystallography. Ultrafiltration LC-MS was shown to be a useful assay for the discovery of inhibitors of QR-2 in complex matrixes such as extracts of bacteria and botanicals.
| S-EPMC3034444 | biostudies-literature
Project description:Six piglets (age 2-4 days) suffering from pseudorabies virus were identified during at outbreak at a commercial farm. RNA was extracted from lung (n=4) and brain (n=6) of the infected pigs, and compared to lung/brain RNA from a control pool of three uninfected piglets. Expression profiling used a human oligonucleotide geneset.
2009-10-02 | E-MEXP-2376 | biostudies-arrayexpress