PXD020607-1

PXD020607 is an original dataset announced via ProteomeXchange.

Title	The component parts of bacteriophage virions accurately defined by a new machine-learning approach built on evolutionary features.
Description	Klebsiella pneumoniae has risen to prominence as a major threat to human health, with hypervirulent and drug-resistant lineages spreading globally. Given their antimicrobial resistant phenotypes, new therapies are required for the treatment of these infections, and bacteriophages (phages) that kill Klebsiella are being identified for use in phage therapy. In order to circumvent the evolution of phage-resistance taking hold the way that drug-resistance has, clear and considered actions are needed in selecting the phages that would be used in therapeutic cocktails. It is known that annotation of phage genomes is poor, potentially obscuring those phages with the most therapeutic potential. Here we show that phages isolated from infrequently sampled environments have features of therapeutic potential and developed a computational tool called STEP3 to understand the evolutionary features that distinguish the component parts of diverse phages, features that proved particularly suitable to detection of virion proteins with only distantly related homologies. These features were integrated into an ensemble framework to achieve a stable and robust prediction performance by STEP3. Proteomics-based analysis of two phages validated the prediction accuracy of STEP3 and revealed the virions contain component parts that include DNA-binding factors, otherwise unrecognizable capsule degradation enzymes and membrane translocation factors.
HostingRepository	PRIDE
AnnounceDate	2021-04-30
AnnouncementXML	Submission_2021-04-30_03:01:16.467.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Cheng Huang
SpeciesList	scientific name: Klebsiella phage ST405-OXA48phi1.1; NCBI TaxID: 2516434;
ModificationList	No PTMs are included in the dataset
Instrument	Q Exactive

Revision	Datetime	Status	ChangeLog Entry
0	2020-07-28 04:59:26	ID requested
⏵ 1	2021-04-30 03:01:16	announced
2	2024-10-22 05:21:37	announced	2024-10-22: Updated project metadata.

Dataset with its publication pending

submitter keyword: machine learning, prediction, phage

Trevor Lithgow
contact affiliation	Infection & Immunity Program, Biomedicine Discovery Institute and Department of Microbiology, Monash University, Clayton, Australia
contact email	trevor.lithgow@monash.edu
lab head
Cheng Huang
contact affiliation	Monash University
contact email	cheng.huang@monash.edu
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/2021/04/PXD020607

PRIDE project URI

• PRIDE
  1. PXD020607
     1. Label: PRIDE project
     2. Name: The component parts of bacteriophage virions accurately defined by a new machine-learning approach built on evolutionary features.