DOI: 10.6084/m9.figshare.28543700.v2
title: Untargeted <i>In Vitro</i> Metabolomics data from <i>Burkholderia cenocepacia </i>J2315, H111 and <i>Staphylococcus aureus </i>NRS77 Biofilm Supernatant

description: Here, we offer a metabolomics dataset generated via high-performance-liquid chromatography and high-resolution mass spectrometry analysis of <i>in vitro</i> biofilm supernatant harvested from the human pathogens <i>Burkholderia cenocepacia</i> H111 & J2315 and <i>Staphylococcus aureus</i> NRS77. Polar metabolites from uninoculated media (LB+1% glucose, 150 mM MOPS) is also included as a control condition.<br><br><b>METHODS</b><br><b>Sample Collection</b><br>B. cenocepacia or Staphylococcus strains were inoculated into T LB Lennox + 1% glucose + 150 mM MOPS at 10^6 CFU/mL and incubated at 37 °C for 3 days in replicate wells of a 96-well PVC plate. After 7 days, the biofilm supernatants were removed via a micropipette, centrifuged at 21,130 x g for 1 min, and filter-sterilized through a 0.45 µm syringe filter (VWR 28145-505).<br><b>Extraction</b><br>Sterile supernatant was collected for each sample and frozen at -80 °C for 2 h or overnight, then freeze dried in a LabConco 2.5L Benchtop Freeze Dryer. Dried sample was reconstituted into 2 mL 50% acetonitrile and transferred into an autosampler injection vial after filtered with a 0.22 µm filter.<br><b>Chromatography</b>All samples were run on a Thermo DIONEX UltiMate 3000 HPLC system (Thermo Fisher Scientific, Waltham, MA, USA). The LC system was equipped with a reversed phase column (RPC, a Waters Acquity UPLC HSS T3 column, 2.1 x 150 mm, 1.8 µm) and hydrophilic interaction chromatography column (HILIC, a Millipore SeQuant ZIC-cHILIC column, 2.1 x 150 mm, 3 µm). The two LC columns were configured in parallel, and each column was connected with a 2-μL sample loop. The column temperature was set to 40 °C. For separation on the RPC column, water with 0.1% formic acid and acetonitrile with 0.1% formic acid were mobile phase A and B, respectively. The flow rate was 0.35 mL/min. The solvent gradient was set as 0-6 min 0% B, 6-14 min increased from 0% to 28% B, 14-16 min increased from 28% to 50% B, 16-20 min increased from 50% to 100% B, 21-33 min back to 0% B. For separation on the HILIC column, 10 mM ammonium acetate (pH=3.25) and acetonitrile with 0.1% formic acid were mobile phase A and B, respectively. The flow rate was 0.3 mL/min. The solvent gradient was set to 0-1.3 min 95% B, 1.3-8.3 min decreased from 95% to 0% B, 8.3-11 min kept 0% B, 11.5-33 min kept 95% B<br><br><b>Mass Spectrometry</b><br>All samples were run on a Thermo Q Exactive HF Hybrid Quadrupole-Orbitrap Mass Spectrometer. All samples were randomly analyzed in positive (+) and negative (-) modes to obtain full MS data for metabolite quantification. For the metabolite identification, the pooled sample was analyzed by 2D LC-MS/MS in positive and negative modes at three collision energies, 20, 40 and 60 eV.<br><br><b>Data Transformation</b><br>The raw data was converted mzML format using the MSCovert software, and XCMS software was used for spectrum deconvolution[1] and MetSign software for metabolite identification, cross-sample peak list alignment, normalization and statistical analysis[2][3].<br>Refs:<br>[1] Tautenhahn, R., Patti, G.J., Rinehart, D., and Siuzdak, G. (2012). XCMS On-line: a web-based platform to process untargeted metabolomic data. Anal Chem 84, 5035-5039. 10.1021/ac300698c.<br>[2] Wei, X., Shi, X., Kim, S., Patrick, J.S., Binkley, J., Kong, M., McClain, C., and Zhang, X. (2014). Data dependent peak model based spectrum deconvolution for analysis of high resolution LC-MS data. Anal Chem 86, 2156-2165. 10.1021/ac403803a.<br>[3] He, L., Li, F., Yin, X., Bohman, P., Kim, S., McClain, C.J., Feng, W., and Zhang, X. (2019). Profiling of Polar Metabolites in Mouse Feces Using Four Analytical Platforms to Study the Effects Of Cathelicidin-Related Antimicrobial Peptide in Alcoholic Liver Disease. J Proteome Res 18, 2875-2884. 10.1021/acs.jproteome.9b00181.<br><b>Metabolite Identification</b><br>To identify metabolites, 2D LC-MS/MS data was first matched to our own proprietary database that contains parent ion m/z, MS/MS spectra and retention time of 363 authentic standards. Thresholds were set as spectral similarity ≥ 0.4, retention time difference ≤ 0.15 and m/z variation window ≤ 5 ppm. 2D LC-MS/MS data without a match with the metabolites in the proprietary database were further analyzed using Compound Discoverer software (v 2.0, Thermo Fisher Scientific, Germany), where MS/MS spectra similarity score threshold was set ≥ 40 with a maximum score of 100. The suite of databases utilized though Compound Discoverer v3.1 software are as follows: E. coli Metabolome Database; Fecal Metabolome database; KEGG; Saliva Metabolome Database; Urine Metabolome Database; Compound Classes/Therapeutics/Prescription Drugs (including only the Endogenous Metabolites; Natural Products/Medicines; Natural Toxins; Small Molecule Chemicals; Steroids/Vitamins/Hormones; and Therapeutics/Prescription Drugs groups).<br>