MassIVE MSV000100841

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Soil microbiome pH perturbation metabolomics - GC

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Description

Examined soil microbiome microcosms to determine the effect of changing pH on the production of lignocellulolytic enzymes. Soil from a Prosser, Washington field site was incubated in mesh bags on top of a soil interfacing glass bead matrix with MOPS minimal media amended with or without carboxymethyl cellulose at three different pH levels. After incubation, 2 mL of media solution was collected, centrifuged, and filtered to remove cells prior to preparing supernatant for metabolomics. GC-MS raw data files are processed using the Metabolite Detector (MD) software. Retention indices (RI) of detected metabolites are calculated based on the analysis of the FAMEs mixture, followed by their chromatographic alignment across all analyses after deconvolution. Compound detection is done on MD with a minimum peak threshold of 10.0 and deconvolution width of 8.0. Settings for compound matching and identification are delta RI of 20.0, a required S/N of 5.0, and the scoring method combines the RI and mass spectra. Metabolites are identified by matching experimental spectra to a PNNL augmented version of Agilent GC-MS metabolomics Library, containing spectra and validated RI for over 1200 metabolites. All metabolite identifications and quantification ions are manually confirmed to reduce deconvolution errors during automated data-processing and to eliminate false identifications. The NIST20 and Wiley11 GC-MS libraries are also used to cross-validate the spectral matching scores obtained using the PNNL augmented library. The unknown peaks are additionally matched with the NIST20 and Wiley11 GC-MS libraries and reported as tentative identifications only if the MS score is high. Additionally, the MS-DIAL website provides various types of public GC-MS databases, so they were converted to MSL database format, and unknown peaks can be searched with them using ChemStation. [doi:10.25345/C50863K3V] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: soil microbiome ; DatasetType:Metabolomics

Contact

Principal Investigators:
(in alphabetical order) 		Nicholas J. Reichart, Pacific Northwest National Laboratory, United States
Ryan S. McClure, Pacific Northwest National Laboratory, United States
Submitting User: alchemistmatt
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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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