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Large-scale label-free quantitative mapping of the sputum proteome

Large-scale label-free quantitative mapping of the sputum proteome
Large-scale label-free quantitative mapping of the sputum proteome
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 optimise the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMSE applied to 40 healthy non-smoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The “core” sputum proteome (proteins detected in ≥40 % of participants) was composed of 284 proteins and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimise the accuracy and consistency of measurement of sputum proteins and analyse the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMSE is influenced by several factors, with some proteins being measured in all participants’ samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high inter-individual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitisation. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance.
1535-3893
1997-2248
Schofield, James
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Burg, Dominic
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Brandsma, Joost
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Staykova, Doroteya kancheva K
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Bansal, Aruna
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Folisi, Caterina
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Bansal, Aruna
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Nicholas, Ben
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Rowe, Anthony
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Corfield, Julie
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Wilson, Susan
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Ward, Jonathan
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Lutter, Rene
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Fleming, Louise
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Shaw, Dominick E.
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Caruso, Massimo
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Dahlén, Sven-Erik
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Fowler, Stephen J.
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Hashimoto, Simone
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Horvath, Ildiko
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Howarth, Peter
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Krug, Norbert
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Montuschi, Paolo
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Sanak, Marek
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Sandstrom, Thomas
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Chung, Kian Fan
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Sterk, Peter J.
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Djukanovic, Ratko
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Skipp, Paul
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Schofield, James
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Burg, Dominic
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Brandsma, Joost
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Rowe, Anthony
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Corfield, Julie
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Wilson, Susan
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Ward, Jonathan
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Lutter, Rene
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Fleming, Louise
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Shaw, Dominick E.
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Dahlén, Sven-Erik
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Fowler, Stephen J.
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Hashimoto, Simone
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Howarth, Peter
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Krug, Norbert
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Montuschi, Paolo
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Sanak, Marek
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Sun, Kai
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Pandis, Ioannis
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Sousa, Ana R.
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Adcock, Ian M.
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Chung, Kian Fan
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Sterk, Peter J.
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Djukanovic, Ratko
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Skipp, Paul
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Schofield, James, Burg, Dominic, Brandsma, Joost, Staykova, Doroteya kancheva K, Bansal, Aruna, Nicholas, B.L., Folisi, Caterina, Bansal, Aruna, Nicholas, Ben, Xian, Yang, Rowe, Anthony, Corfield, Julie, Wilson, Susan, Ward, Jonathan, Lutter, Rene, Fleming, Louise, Shaw, Dominick E., Bakke, Per S., Caruso, Massimo, Dahlén, Sven-Erik, Fowler, Stephen J., Hashimoto, Simone, Horvath, Ildiko, Howarth, Peter, Krug, Norbert, Montuschi, Paolo, Sanak, Marek, Sandstrom, Thomas, Singer, Florian, Auffray, Charles, Sun, Kai, Pandis, Ioannis, Sousa, Ana R., Adcock, Ian M., Chung, Kian Fan, Sterk, Peter J., Djukanovic, Ratko and Skipp, Paul (2018) Large-scale label-free quantitative mapping of the sputum proteome. Journal of Proteome Research, 17 (6), 1997-2248. (doi:10.1021/acs.jproteome.8b00018).

Record type: Article

Abstract

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 optimise the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMSE applied to 40 healthy non-smoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The “core” sputum proteome (proteins detected in ≥40 % of participants) was composed of 284 proteins and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimise the accuracy and consistency of measurement of sputum proteins and analyse the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMSE is influenced by several factors, with some proteins being measured in all participants’ samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high inter-individual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitisation. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance.

Text
JSchofield_sputum proteome paper.pdf 10-05-2018 - Accepted Manuscript
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More information

Accepted/In Press date: 3 May 2018
e-pub ahead of print date: 8 May 2018
Published date: 1 June 2018

Identifiers

Local EPrints ID: 420876
URI: http://eprints.soton.ac.uk/id/eprint/420876
ISSN: 1535-3893
PURE UUID: ba5772a8-b0d8-442b-b470-cc06168c1d07
ORCID for Susan Wilson: ORCID iD orcid.org/0000-0003-1305-8271
ORCID for Jonathan Ward: ORCID iD orcid.org/0000-0002-9278-0002
ORCID for Ratko Djukanovic: ORCID iD orcid.org/0000-0001-6039-5612
ORCID for Paul Skipp: ORCID iD orcid.org/0000-0002-2995-2959

Catalogue record

Date deposited: 17 May 2018 16:30
Last modified: 22 Nov 2021 06:23

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Contributors

Author: James Schofield
Author: Dominic Burg
Author: Joost Brandsma
Author: Doroteya kancheva K Staykova
Author: Aruna Bansal
Author: B.L. Nicholas
Author: Caterina Folisi
Author: Aruna Bansal
Author: Ben Nicholas
Author: Yang Xian
Author: Anthony Rowe
Author: Julie Corfield
Author: Susan Wilson ORCID iD
Author: Jonathan Ward ORCID iD
Author: Rene Lutter
Author: Louise Fleming
Author: Dominick E. Shaw
Author: Per S. Bakke
Author: Massimo Caruso
Author: Sven-Erik Dahlén
Author: Stephen J. Fowler
Author: Simone Hashimoto
Author: Ildiko Horvath
Author: Peter Howarth
Author: Norbert Krug
Author: Paolo Montuschi
Author: Marek Sanak
Author: Thomas Sandstrom
Author: Florian Singer
Author: Charles Auffray
Author: Kai Sun
Author: Ioannis Pandis
Author: Ana R. Sousa
Author: Ian M. Adcock
Author: Kian Fan Chung
Author: Peter J. Sterk
Author: Paul Skipp ORCID iD

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