Dataset Information

Large-scale HDMSE mapping of the normal sputum proteome

ABSTRACT: Severe asthma is a collection of disease entities with varying pathophysiological characteristics that result in symptoms of cough, wheeze and breathlessness, with frequent exacerbations. To address the problem of phenotypic difference and heterogeneity, the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project was set up as a public-private partnership within the framework of the Innovative Medicines Initiative (IMI), engaging academia, the pharmaceutical industry and patient groups. The goal of this investigation was to identify proteomic fingerprints in induced sputum that characterize patients with severe asthma and to determine whether subgroups of severe asthmatics can be identified. Furthermore, we were interested in elucidating the biological pathways that showed differences between subgroups. This dataset is a description of the normal sputum proteome.

INSTRUMENT(S): Synapt MS

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Sputum

SUBMITTER: Paul Skipp

LAB HEAD: Paul J S Skipp

PROVIDER: PXD005949 | Pride | 2018-05-14

REPOSITORIES: Pride

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Publications

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome.

Burg Dominic D Schofield James P R JPR Brandsma Joost J Staykova Doroteya D Folisi Caterina C Bansal Aruna A Nicholas Ben B Xian Yang Y Rowe Anthony A Corfield Julie J Wilson Susan S Ward Jonathan J Lutter Rene R Fleming Louise L Shaw Dominick E DE Bakke Per S PS Caruso Massimo M Dahlen Sven-Erik SE Fowler Stephen J SJ Hashimoto Simone S Horváth Ildikó I Howarth Peter P Krug Norbert N Montuschi Paolo P Sanak Marek M Sandström Thomas T Singer Florian F Sun Kai K Pandis Ioannis I Auffray Charles C Sousa Ana R AR Adcock Ian M IM Chung Kian Fan KF Sterk Peter J PJ Djukanović Ratko R Skipp Paul J PJ The U-Biopred Study Group

Journal of proteome research 20180523 6

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. ...[more]

PMID: 29737851

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Project description:MicroRNAs (miRNAs) have been shown to play an important role in many different cellular, developmental, and physiological processes. Accordingly, numerous methods have been established to identify and quantify miRNAs. The shortness of miRNA sequence results in a high dynamic range of melting temperatures and, moreover, impedes a proper selection of detection probes or optimized PCR primers. While miRNA microarrays allow for massive parallel and accurate relative measurement of all known miRNAs, they have so far been less useful as an assay for absolute quantification. Here, we present a microarray based approach for global and absolute quantification of miRNAs. The method relies on an equimolar pool of about 1000 synthetic miRNAs of known concentration which is used as an universal reference and labeled and hybridized in a dual colour approach on the same array as the sample of interest. Each single miRNA is quantified with respect to the universal reference outbalancing bias related to sequence, labeling, hybridization or signal detection method. We demonstrate the accuracy of the method by various spike in experiments. Further, we quantified miRNA copy numbers in liver samples and CD34(+)CD133(-) hematopoietic stem cells. The RNA extracted from 7 x 10^ 5 to 1 x 10^ 6 CD34(+)/CD133(-) cells of three different donors was analyzed. 1 µg of respective total RNA was mixed with 2.5 fmol of each of 18 RNA oligonucleotides reverse complement to miRControl 3 probes and subsequently fluorescently labelled by 3’ ligation. Total RNA mix was hybridized in a dual colour approach to microarrays versus a second labelled synthetic miRNA pool. The synthetic miRNA pool consisted of 2.5 fmol of each of 954 non redundant miRNAs sequences and miRControl 3 sequences. The array data was normalized by calculating the median of the miRControl 3 present in the CD34(+)/CD133(-) and UR sample. The miRNA amount was calculated with respect to the corresponding miRNA in the UR.

Dataset Information

Large-scale HDMSE mapping of the normal sputum proteome

Publications

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome.

Similar Datasets

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