MassIVE MSV000083784

Partial Public PXD013885

Fast and accurate bacterial species identification in biological samples using LC-MS/MS mass spectrometry and machine learning (DDA dataset)

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Description

We have developed a new strategy for identifying bacterial species in biological samples using specific LC-MS/MS peptidic signatures. In the first training step, deep proteome coverage of bacteria of interest is obtained in Data Independent Acquisition (DIA) mode, followed by the use of machine learning to define the peptides the most susceptible to distinguish each bacterial species from the others. Then, in the second step, this peptidic signature is monitored in biological samples using targeted proteomics. This method, which allows the bacterial identification from clinical specimens in less than 4h, has been applied to 15 species representing 84% of all Urinary Tract Infections (UTI). This dataset contains all the DDA files used to create bacterial spectral libraries prior to DIA analyses. [doi:10.25345/C5N928] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Bacterial identification ; Urine ; LC-MSMS ; DIA ; Machine Learning

Contact

Principal Investigators:
(in alphabetical order) 		Arnaud Droit, CHU de Quebec Universite Laval, Canada
Submitting User: Arno

Publications

Roux-Dalvai F., Gotti C., Leclercq M., Hélie MC., Boissinot M., Arrey T.N., Dauly C., Fournier F., Kelly I., Marcoux J., Bestman-Smith J., Bergeron M.G., Droit A.
Fast and accurate bacterial species identification in urine specimens using LC-MS/MS mass spectrometry and machine learning.
Mol Cell Proteomics. 2019 Oct 4. pii: mcp.TIR119.001559. doi: 10.1074/mcp.TIR119.001559.

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Identification Results
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Quantification Results
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Number of distinct conditions across all analyses (original submission and reanalyses) associated with this dataset.

Distinct condition labels are counted across all files submitted in the "Metadata" category having a "Condition" column in this dataset.

"N/A" means no results of this type were submitted.
Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

Distinct replicate labels are counted across all files submitted in the "Metadata" category having a "BioReplicate" or "Replicate" column in this dataset.

"N/A" means no results of this type were submitted.
Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

The technical replicate count is defined as the maximum number of times any one distinct combination of condition and biological replicate was analyzed across all files submitted in the "Metadata" category. In the case of fractionated experiments, only the first fraction is considered.

"N/A" means no results of this type were submitted.
Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

"N/A" means no results of this type were submitted.
Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

"N/A" means no results of this type were submitted.
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.

"N/A" means no results of this type were submitted.
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.

"N/A" means no results of this type were submitted.
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.