MassIVE MSV000100842

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Soil microbiome pH perturbation metabolomics - LC

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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. For data generated, confident metabolite identifications are made using Thermo Compound Discoverer 3.3. For RP and HILIC positive and negative mode, spectra are aligned using an adaptive curve with a maximum of 0.3 or 0.6 RT shift respectively and a 3 ppm mass tolerance. Peaks are selected based on a minimum intensity of 1e6 and a chromatographic S/N of 3. Detected features are grouped based on a mass tolerance of 3 ppm and a RT tolerance of 0.3. Features are then filtered out depending on the number of samples. Compounds are assigned based on Isotopic pattern, RT, MS1, and/or MS2. All identifications and integrated peaks are manually validated and exported for statistical analysis. We provide, on average, four levels of identification starting from the most to least confidence: 1. Match with MS1, MS2, AND RT; 2. Match with MS2 only; 3. Match with MS1 and RT; 4. Match primarily with MS1 and partial MS2 match. [doi:10.25345/C5VH5CX9B] [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 biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

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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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.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

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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This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.