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Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study

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Abstract

Metabolomics protocols are used to comprehensively characterize the metabolite content of biological samples by exploiting cutting-edge analytical platforms, such as gas chromatography (GC) or liquid chromatography (LC) coupled to mass spectrometry (MS) assays, as well as nuclear magnetic resonance (NMR) assays. We have developed novel sample preparation procedures combined with GC-MS, LC-MS, and NMR metabolomics profiling for analyzing bronchial wash (BW) and bronchoalveolar lavage (BAL) fluid from 15 healthy volunteers following exposure to biodiesel exhaust and filtered air. Our aim was to investigate the responsiveness of metabolite profiles in the human lung to air pollution exposure derived from combustion of biofuels, such as rapeseed methyl ester biodiesel, which are increasingly being promoted as alternatives to conventional fossil fuels. Our multi-platform approach enabled us to detect the greatest number of unique metabolites yet reported in BW and BAL fluid (82 in total). All of the metabolomics assays indicated that the metabolite profiles of the BW and BAL fluids differed appreciably, with 46 metabolites showing significantly different levels in the corresponding lung compartments. Furthermore, the GC-MS assay revealed an effect of biodiesel exhaust exposure on the levels of 1-monostearylglycerol, sucrose, inosine, nonanoic acid, and ethanolamine (in BAL) and pentadecanoic acid (in BW), whereas the LC-MS assay indicated a shift in the levels of niacinamide (in BAL). The NMR assay only identified lactic acid (in BW) as being responsive to biodiesel exhaust exposure. Our findings demonstrate that the proposed multi-platform approach is useful for wide metabolomics screening of BW and BAL fluids and can facilitate elucidation of metabolites responsive to biodiesel exhaust exposure.

Graphical abstract illustrating the study workflow. NMR Nuclear Magnetic Resonance, LC-TOFMS Liquid chromatography-Time Of Flight Mass Spectrometry, GC Gas Chromatography-Mass spectrometry

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Abbreviations

AUC:

Area under the curve

CV-ANOVA:

Cross-validation-analysis of variance

GC-MS:

Gas chromatography-mass spectrometry

LC-MS:

Liquid chromatography-mass spectrometry

MVA:

Multivariate analysis

NMR:

Nucleic magnetic resonance

OPLS:

Orthogonal projections to latent structures

OPLS-DA:

Orthogonal projections to latent structures-discriminant analysis

PCA:

Principal component analysis

RME:

Rapeseed methyl ester

ROC:

Receiver operating characteristic

RSD:

Relative standard deviations

SMC:

Swedish Metabolomics Centre

UPSC:

Umeå Plant Science Centre

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Acknowledgments

Financial support from The Swedish Research Council Formas, the Swedish Heart Lung Foundation, Västerbotten County Council (Spjutspetsmedel), AFA-Insurance, and the Kempe Foundation is gratefully acknowledged. The Swedish Metabolomics Centre (www.swedishmetabolomicscentre.se) is acknowledged for outstanding assistance with the analyses.

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    Authors and Affiliations

    1. Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 901 87, Umeå, Sweden

      Izabella Surowiec, Masoumeh Karimpour, Sandra Gouveia-Figueira, Junfang Wu, Johan Trygg & Malin L. Nording

    2. Department of Public Health and Clinical Medicine, Division of Medicine/Respiratory Medicine, Umeå University, 901 87, Umeå, Sweden

      Jon Unosson, Jenny A. Bosson, Anders Blomberg, Jamshid Pourazar, Thomas Sandström & Annelie F. Behndig

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    1. Izabella Surowiec
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    Correspondence to Malin L. Nording.

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    Izabella Surowiec and Masoumeh Karimpour contributed equally to this work.

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    Surowiec, I., Karimpour, M., Gouveia-Figueira, S. et al. Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study. Anal Bioanal Chem 408, 4751–4764 (2016). https://doi.org/10.1007/s00216-016-9566-0

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