EMERGE 2016 Autochamber Sites LC-MS


METHODS:
   Water soluble metabolites were extracted from peat by adding 7 mL of autoclaved milliQ water to 1g of peat in a sterile 15 mL Eppendorf tube. Tubes were vortexed twice for 30 seconds, and then the peat-water mixture was sonicated for 2 hours at 22˚C. Samples were then centrifuged to separate the supernatant, which served as the water extract. 
   
   Water extracted metabolites were thawed at room temperature and centrifuged again to remove any potential particles that formed after thawing. Next, each sample was split into two 2ml glass tube vials (1 ml each), one for hydrophilic interaction liquid chromatography (HILIC) and the other for reverse-phase (RP) liquid chromatography. Samples in both vials were then dried down completely on a Vacufuge plus (Eppendorf, USA).  Samples were resuspended in a solution of 50% Acetonitrile and 50% water for HILIC and a solution of 80% water and 20% HPLC grade methanol for RP.

A Thermo Scientific Vanquish Duo ultra-high performance liquid chromatography system (UHPLC) was used for the liquid chromatography step. Extracts were separated using a Waters ACQUITY HSS T3 C18 column for RP separation and a Waters ACQUITY BEH amide column for HILIC separation.

Samples were injected in a 1 μL volume on column and eluted as follows:  for RP the gradient went from 99% mobile phase A (0.1% formic acid in H2O) to 95% mobile phase B (0.1% formic acid in methanol) over 16 minutes. For HILIC the gradient went from 99% mobile phase A (0.1% formic acid, 10 mM ammonium acetate, 90% acetonitrile, 10% H¬2O) to 95% mobile phase B (0.1% formic acid, 10 mM ammonium acetate, 50% acetonitrile, 50% H2O).  Both columns were run at 45 °C with a flowrate of 300 μL/min.
A Thermo Scientific Orbitrap Exploris 480 was used for spectral data collection with a spray voltage of 3500 V for positive mode (for RP) and 2500 V for negative mode (for HILIC) using the H-ESI source. The ion transfer tube and vaporizer temperature were both 350 °C. Compounds were fragmented using data-dependent MS/MS with HCD collision energies of 20, 40, and 80.

The Compound Discoverer 3.2 software (Thermo Fisher Scientific) was used to analyze the data using the untargeted metabolomics workflow. Briefly, the spectra were first aligned followed by a peak picking step. Putative elemental compositions of unknown compounds were predicted using the exact mass, isotopic pattern, fine isotopic pattern, and MS/MS data using the built in HighChem Fragmentation Library of reference fragmentation mechanisms. Metabolite annotation was performed using spectral libraries and compound databases. First, fragmentation scans (MS2) searches in mzCloud were performed , which is a curated database of MSn spectra containing more than 9 million spectra and 20000 compounds.

   Second, predicted compositions were obtained based on mass error, matched isotopes, missing number of matched fragments, spectral similarity score (calculated by matching theoretical and measured isotope pattern), matched intensity percentage of the theoretical pattern, the relevant portion of MS, and the MS/MS scan. The mass tolerance used for estimating predicted composition was 5 ppm. Finally, annotation was complemented by searching MS1 scans on different online databases with ChemSpider (using either the exact mass or the predicted formula). Based on the annotation results, metabolites were divided into three categories: 1) full match on the three methods used (mzCloud, predicted composition, and ChemSpider), 2) full match by two methods (Predicted composition and ChemSpider) and 3) annotated only by one method (ChemSpider).


COLUMN DEFINITIONS:
For both files: 
Columns A-N : Annotation information
Columns O-P: KEGG pathway using molecular formula
Columns S-AW :  Normalized peak areas per sample

FUNDING:
This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070.
We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council’s grant 4.3-2021-00164.
This study was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0010580 and DE-SC0016440.