Proteomics

Dataset Information

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Identification of antibiotic resistance proteins via MiCId's augmented workflow. A mass spectrometry-based proteomics approach


ABSTRACT: Fast and accurate identification of pathogenic bacteria along with the identification of antibiotic resistance proteins is of paramount importance for the treatment of patients and public health. While mass spectrometry has become an important technique for these purposes there is a lack of mass spectrometry workflow offering this capability. To meet this need we have augmented the previously published Microorganism Classification Identification (MiCId) workflow with this capability. Evaluation results showed that MiCId's workflow has a sensitivity value around 86% and a precision greater than 95% in the identification of antibiotic resistance proteins. Futhermore, we showed that MiCId's workflow is fast. It is capable of providing microorganismal identification, protein identification, sample biomass estimation, and antibiotic resistance protein identification in about 6-17 minutes using computer resources that are available in most desktop and laptop computers making it highly portable workflow. The newly augmented MiCId is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Escherichia Coli Pseudomonas Aeruginosa Klebsiella Pneumoniae

SUBMITTER: Gelio Alves  

LAB HEAD: Roger Karlsson

PROVIDER: PXD026634 | Pride | 2022-06-09

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
MSMS_DataFiles_Sample_Key.xlsx.gz Xlsx
QEHF_190228_42.raw.AntiMicrobialResistance_Id Raw
QEHF_190228_42.raw.MiCId.Species Raw
QEHF_190228_42.raw.Protein_Peptide_Id Raw
QEHF_190228_42.raw.gz Raw
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Publications

Identification of Antibiotic Resistance Proteins via MiCId's Augmented Workflow. A Mass Spectrometry-Based Proteomics Approach.

Alves Gelio G   Ogurtsov Aleksey A   Karlsson Roger R   Jaén-Luchoro Daniel D   Piñeiro-Iglesias Beatriz B   Salvà-Serra Francisco F   Andersson Björn B   Moore Edward R B ERB   Yu Yi-Kuo YK  

Journal of the American Society for Mass Spectrometry 20220502 6


Fast and accurate identifications of pathogenic bacteria along with their associated antibiotic resistance proteins are of paramount importance for patient treatments and public health. To meet this goal from the mass spectrometry aspect, we have augmented the previously published <i>Mi</i>croorganism <i>C</i>lassification and <i>Id</i>entification (MiCId) workflow for this capability. To evaluate the performance of this augmented workflow, we have used MS/MS datafiles from samples of 10 antibio  ...[more]

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