PXD020876

PXD020876 is an original dataset announced via ProteomeXchange.

Title	Deep learning neural network prediction method improves proteome profiling of vascular sap of grapevines during Pierces disease development
Description	Plant secretome studies have shown the importance of plant defense proteins in the vascular system against pathogens. Studies on Pierces disease of grapevines caused by the xylem-limited bacteria Xylella fastidiosa Xf have detected proteins and pathways associated to its pathobiology. Despite the biological importance of the secreted proteins in the extracellular space to plant survival and development, proteome studies are scarce due to technical and technological challenges. Prosit, a deep learning neural network prediction method can provide powerful tool for improving proteome profiling by data-independent acquisition DIA. We aimed to explore the potential of this strategy by combining it with in silico spectral library prediction tool to analyze the proteome of vascular leaf sap of grapevines with Pierces disease. The results demonstrate that the combination of DIA and Prosit increased the total number of identified proteins from 145 to 360 for grapevines and 18 to 90 for Xf. The new proteins increased the range of molecular weight, assisted on the identification of more exclusive peptides per protein, and increased the identification of low abundance proteins. These improvements allowed the identification of new functional pathways associated with cellular responses to oxidative stress to be further investigated.
HostingRepository	MassIVE
AnnounceDate	2020-09-18
AnnouncementXML	Submission_2020-09-18_09:01:10.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Brett Phinney
SpeciesList	scientific name: Vitis vinifera; common name: wine grape; NCBI TaxID: 29760; scientific name: Xylella fastidiosa Temecula1; NCBI TaxID: 183190;
ModificationList	Oxidation; Carbamidomethyl
Instrument	Orbitrap Fusion Lumos

Revision	Datetime	Status	ChangeLog Entry
0	2020-08-12 11:47:20	ID requested
⏵ 1	2020-09-18 09:01:11	announced

Helena Duarte Sagawa C, Zaini PA, de A B Assis R, Saxe H, Salemi M, Jacobson A, Wilmarth PA, Phinney BS, M Dandekar A, Deep Learning Neural Network Prediction Method Improves Proteome Profiling of Vascular Sap of Grapevines during Pierce's Disease Development. Biology (Basel), 9(9):(2020) [pubmed]

submitter keyword: predicted spectral library, quantitative proteomics, Prosit, apoplast, xylem sap, grapevine, Pierces Disease, secretome

Abhaya M. Dandekar
contact affiliation	1Department of Plant Sciences, University of California, Davis
contact email	amdandekar@ucdavis.edu
lab head
Brett Phinney
contact affiliation	UC Davis
contact email	brettsp@ucdavis.edu
dataset submitter

MassIVE dataset URI

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