Masshunter metlin metabolomics database

The phytochemical screening of the orange B. ceiba stamen extracts was analyzed using LC-MS with a ZORBAX Eclipse Plus C18 Rapid Resolution HD column (2.1 × 150 mm, 1.8 μm), utilizing a Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry (LC-QTOF-MS) instrument (6545 LC/Q-TOF, Agilent Technology, Santa Clara, CA, USA), which consisted of a binary pump. The samples were dissolved in 70% methanol at a concentration of 1 mg/mL and passed through a 0.22 µm filter. The temperature was maintained at 35 °C, and the injection volume was 1 μL. Elution was performed for 21 minutes with a mobile-phase gradient system starting with 20% ACN and 80% water (0.1% formic acid), with a flow rate of 0.2 mL/min. The MS conditions involved an electrospray ionization (ESI) probe in the negative mode. MassHunter Qualitative Analysis Software (Agilent MassHunter Workstation Qualitative Analysis version 10.0, CA, USA) was used to evaluate the ion’s match with the database, and this was carried out by comparing the measured mass to the exact mass of the molecular formula and the predicted isotope pattern, utilizing the find-by-formula search of the Agilent MassHunter METLIN Metabolomics Database. The chemical characteristics of the compounds were obtained using the Medlin library [60 (link)].

Significantly altered metabolites were imported into Mass Profiler Professional (MPP, Version 15.0) ID Browser (version 10.0). Tentative metabolite IDs (25 (link)) were assigned using the Agilent MassHunter METLIN Metabolomics Database (curated in Agilent PCDL Manager, version B.08.00). Compounds were annotated in the first instance by Library/Database search, and by formula generation when there were no Library/Database hits. LC/MS tolerances for precursor ion m/z were ± 10ppm + 2mDa. Identification parameter (Database search, Molecular Formula Generation score) score weights were all evenly set to 40. Search results were limited to the 10 best hits per compound and scores above 70 were considered reliable. Features were annotated with tentative metabolite IDs assigned based on 1) score, 2) the presence of a commercialised standard, and 3) brief literature review to determine likelihood of metabolite’s impact on human monocyte function. Endogenous metabolites (as listed in HMDB) were preferred. Where no metabolite IDs or formulae were available, metabolite features were annotated by their mass and RT values (e.g., 601.2048@4.95).