PXD006438

PXD006438 is an original dataset announced via ProteomeXchange.

Title	Quantitative label-free proteomic analysis of human urine to identify novel protein biomarkers for schistosomiasis
Description	Background: Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population, and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. Methodology: A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. Results: A total of 1306 proteins and 8752 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). Conclusion: These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis.
HostingRepository	PRIDE
AnnounceDate	2017-10-24
AnnouncementXML	Submission_2019-02-12_08:22:30.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Bridget Calder
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606; scientific name: Schistosoma haematobium; NCBI TaxID: 6185;
ModificationList	No PTMs are included in the dataset
Instrument	Q Exactive

Revision	Datetime	Status	ChangeLog Entry
0	2017-05-03 03:40:10	ID requested
1	2017-10-24 07:03:54	announced
⏵ 2	2019-02-12 08:22:31	announced	Updated publication reference for PubMed record(s): 29117212.

Onile OS, Calder B, Soares NC, Anumudu CI, Blackburn JM, Quantitative label-free proteomic analysis of human urine to identify novel candidate protein biomarkers for schistosomiasis. PLoS Negl Trop Dis, 11(11):e0006045(2017) [pubmed]

curator keyword: Biomedical

submitter keyword: schistosomiasis, Schistosoma haematobium, bladder cancer, QExactive, discovery proteomics, biomarkers

Jonathan Blackburn
contact affiliation	Department of Integrative Biomedical Sciences & Institute of Infectious Disease & Molecular Medicine Faculty of Health Sciences, University of Cape Town Anzio, Observatory Cape Town 7925 South Africa
contact email	jonathan.blackburn@uct.ac.za
lab head
Bridget Calder
contact affiliation	University of Cape Town
contact email	bridget.calder@uct.ac.za
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/2017/10/PXD006438

PRIDE project URI

• PRIDE
  1. PXD006438
     1. Label: PRIDE project
     2. Name: Quantitative label-free proteomic analysis of human urine to identify novel protein biomarkers for schistosomiasis