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Combination of Pseudo-LC-NMR and HRMS/MS-Based Molecular Networking for the Rapid Identification of Antimicrobial Metabolites From Fusarium petroliphilum

ABSTRACT: An endophytic fungal strain isolated from a seagrass endemic to the Mediterranean Sea (Posidonia oceanica) was studied in order to identify its antimicrobial constituents and further characterize the composition of its metabolome. It was identified as Fusarium petroliphilum by in-depth phylogenetic analyses. The ethyl acetate extract of that strain exhibited antimicrobial activities and an ability to inhibit quorum sensing of Staphylococcus aureus. To perform this study with a few tens of mg of extract, an innovative one-step generic strategy was devised. On one side, the extract was analyzed by UHPLC-HRMS/MS molecular networking for dereplication. On the other side, semi-preparative HPLC using a similar gradient profile was used for a single-step high-resolution fractionation. All fractions were systematically profiled by 1H-NMR. The data were assembled into a 2D contour map, which we call “pseudo-LC-NMR,” and combined with those of UHPLC-HRMS/MS. This further highlighted the connection within structurally related compounds, facilitated data interpretation, and provided an unbiased quantitative profiling of the main extract constituents. This innovative strategy led to an unambiguous characterization of all major specialized metabolites of that extract and to the localization of its bioactive compounds. Altogether, this approach identified 22 compounds, 13 of them being new natural products and six being inhibitors of the quorum sensing mechanism of S. aureus and Pseudomonas aeruginosa. Minor analogues were also identified by annotation propagation through the corresponding HRMS/MS molecular network, which enabled a consistent annotation of 27 additional metabolites. This approach was designed to be generic and applicable to natural extracts of the same polarity range.

SUBMITTER: Alfattani A

PROVIDER: S-EPMC8569130 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:In order to undertake an epidemiologic study relating levels of parent estrogens (estrone and estradiol) and estrogen metabolites (EMs) to other breast cancer risk factors, we have optimized methods for EM quantification with ultra high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). A two-step approach was adopted; the first step comprised method development and evaluation of the method performance. The second step consisted of applying this method to quantify estrogens in postmenopausal women and determine if the observed patterns are consistent with the existing literature and prior knowledge of estrogen metabolism. First, 1-methylimidazole-2-sulfonyl chloride (MIS) was used to derivatize endogenous estrogens and estrogen metabolites in urine from study participants. Since C18 reversed phase columns have not been able to separate all the structurally related EMs, we used a C18-pentafluorophenyl (PFP) column. The parent estrogens and EMs were baseline resolved with distinct retention times on this C18-PFP column using a 30 min gradient. This method was used to quantify the parent estrogens and 13 EMs in urine samples collected in an initial pilot study involving males as well as pre- and peri-menopausal females to assess a range of EM levels in urine samples and enable comparison to the previous literature for assay evaluation. Detection limits ranged from 1 - 20 pg/mL depending on the EM. We evaluated matrix effects and interference as well as the intra- and inter-batch reproducibility including hydrolysis, extraction, derivatization and LC-MS analysis using charcoal-stripped human urine as a matrix. Methods were then applied to the measurement of estrogens in urine samples from 169 postmenopausal women enrolled in an epidemiological study to examine relationships between breast cancer risk, the intestinal microbiome, and urinary EMs. The results from our cohort are comparable to previous reports on urinary EMs in postmenopausal women and enabled thorough evaluation of the method.

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Combination of Pseudo-LC-NMR and HRMS/MS-Based Molecular Networking for the Rapid Identification of Antimicrobial Metabolites From Fusarium petroliphilum

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