PXD026634

PXD026634 is an original dataset announced via ProteomeXchange.

Title	Identification of antibiotic resistance proteins via MiCId's augmented workflow. A mass spectrometry-based proteomics approach
Description	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.
HostingRepository	PRIDE
AnnounceDate	2022-06-09
AnnouncementXML	Submission_2022-06-09_04:56:37.126.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Gelio Alves
SpeciesList	scientific name: Escherichia coli; NCBI TaxID: 562; scientific name: Klebsiella pneumoniae; NCBI TaxID: 573; scientific name: Pseudomonas aeruginosa; NCBI TaxID: 287;
ModificationList	No PTMs are included in the dataset
Instrument	Q Exactive HF

Revision	Datetime	Status	ChangeLog Entry
0	2021-06-10 22:33:00	ID requested
⏵ 1	2022-06-09 04:56:37	announced

Alves G, Ogurtsov A, Karlsson R, Ja, é, n-Luchoro D, Pi, ñ, eiro-Iglesias B, Salv, à, -Serra F, Andersson B, Moore ERB, Yu YK, Identification of Antibiotic Resistance Proteins via MiCId's Augmented Workflow. A Mass Spectrometry-Based Proteomics Approach. J Am Soc Mass Spectrom, 33(6):917-931(2022) [pubmed]

submitter keyword: Identification of antibiotic resistance proteins, Bacteria identification, Mass spectrometry

Roger Karlsson
contact affiliation	Department of Clinical Microbiology, Sahlgrenska University Hospital, Gothenburg, Sweden
contact email	roger.karlsson@vgregion.se
lab head
Gelio Alves
contact affiliation	CBB
contact email	alves@ncbi.nlm.nih.gov
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2022/06/PXD026634

PRIDE project URI

• PRIDE
  1. PXD026634
     1. Label: PRIDE project
     2. Name: Identification of antibiotic resistance proteins via MiCId's augmented workflow. A mass spectrometry-based proteomics approach