Analytical and Bioanalytical Chemistry

, Volume 407, Issue 20, pp 5965–5976 | Cite as

Differential proteomic analysis of mouse macrophages exposed to adsorbate-loaded heavy fuel oil derived combustion particles using an automated sample-preparation workflow

  • Tamara Kanashova
  • Oliver Popp
  • Jürgen Orasche
  • Erwin Karg
  • Horst Harndorf
  • Benjamin Stengel
  • Martin Sklorz
  • Thorsten Streibel
  • Ralf Zimmermann
  • Gunnar DittmarEmail author
Research Paper
Part of the following topical collections:
  1. Aerosols and Health


Ship diesel combustion particles are known to cause broad cytotoxic effects and thereby strongly impact human health. Particles from heavy fuel oil (HFO) operated ships are considered as particularly dangerous. However, little is known about the relevant components of the ship emission particles. In particular, it is interesting to know if the particle cores, consisting of soot and metal oxides, or the adsorbate layers, consisting of semi- and low-volatile organic compounds and salts, are more relevant. We therefore sought to relate the adsorbates and the core composition of HFO combustion particles to the early cellular responses, allowing for the development of measures that counteract their detrimental effects. Hence, the semi-volatile coating of HFO-operated ship diesel engine particles was removed by stepwise thermal stripping using different temperatures. RAW 264.7 macrophages were exposed to native and thermally stripped particles in submersed culture. Proteomic changes were monitored by two different quantitative mass spectrometry approaches, stable isotope labeling by amino acids in cell culture (SILAC) and dimethyl labeling. Our data revealed that cells reacted differently to native or stripped HFO combustion particles. Cells exposed to thermally stripped particles showed a very differential reaction with respect to the composition of the individual chemical load of the particle. The cellular reactions of the HFO particles included reaction to oxidative stress, reorganization of the cytoskeleton and changes in endocytosis. Cells exposed to the 280 °C treated particles showed an induction of RNA-related processes, a number of mitochondria-associated processes as well as DNA damage response, while the exposure to 580 °C treated HFO particles mainly induced the regulation of intracellular transport. In summary, our analysis based on a highly reproducible automated proteomic sample-preparation procedure shows a diverse cellular response, depending on the soot particle composition. In particular, it was shown that both the molecules of the adsorbate layer as well as particle cores induced strong but different effects in the exposed cells.


SILAC Dimethyl labeling Ship diesel exhaust particles Polycyclic aromatic hydrocarbons Oxidative stress Mitochondria 



Dimethyl labeling


Gas chromatography


Gene ontology


Heavy fuel oil


Heavy fuel oil, 280 °C treatment


Heavy fuel oil, 580 °C treatment


Limit of detection


Polycyclic aromatic hydrocarbons


Particulate matter


Stable isotope labeling by amino acids in cell culture



This work was supported by funds of the Helmholtz virtual institute for complex Molecular Systems in Environmental Health (HICE). We thank Hanns Paur from the KIT, Karlsruhe, Germany for the loan of the CAROLA electrostatic precipitator and Patrick Beaudette as well as Daniel Perez-Hernandez for carefully reading the paper and fruitful discussions. We thank CTC and the Axel Semrau GmbH for the close collaboration in adapting the automation procedures for the CTC-PAL/Chronos setup.

Conflict of Interest

The authors declare no conflict of interest.

Supplementary material

216_2015_8595_MOESM1_ESM.pdf (256 kb)
ESM 1 (PDF 255 kb)


  1. 1.
    Frampton MW (2001) Systemic and cardiovascular effects of airway injury and inflammation: ultrafine particle exposure in humans. Environ Health Perspect 109(4):529–532CrossRefGoogle Scholar
  2. 2.
    Gan WQ, Man SFP, Senthilselvan A, Sin DD (2004) Association between chronic obstructive pulmonary disease and systemic inflammation: a systematic review and a meta-analysis. Thorax 59(7):574–580CrossRefGoogle Scholar
  3. 3.
    Capaldo KP, Corbett JJ, Kasibhatla P, Fischbeck P, Pandis S-N (1999) Effects of ship emissions on sulphur cycling and radiative climate forcing over the ocean. Nature 400:743–74CrossRefGoogle Scholar
  4. 4.
    Corbett JJ, Fischbeck PS, Pandis SN (1999) Global nitrogen and sulfur emissions inventories for oceangoing ships. J Geophys Res 104(D3):3457–3470CrossRefGoogle Scholar
  5. 5.
    Corbett JJ, Fischbeck PS (2000) Emissions from waterborne commerce in United States continental and inland waters. Environ Sci Technol 34(15):3254–3260CrossRefGoogle Scholar
  6. 6.
    Wang C, Corbett JJ, Firestone J (2007) Modeling energy use and emissions from North American shipping: application of the ship traffic, energy, and environment model. Environ Sci Technol 41(9):3226–3232CrossRefGoogle Scholar
  7. 7.
    Streets D-G, Guttikunda SK, Carmichae G-R (2000) The growing contribution of sulfur emissions from ships in Asian waters 1988–1995. Atmos Environ 34(26):4425–4439CrossRefGoogle Scholar
  8. 8.
    Streets DG, Bond TC, Carmichael GR, Fernandes SD, Fu Q, He D, Klimont Z, Nelson SM, Tsai NY, Wang MQ, Woo JH, Yarber KF (2003) An inventory of gaseous and primary aerosol emissions in Asia in the year 2000. J Geophys Res 108(D21)Google Scholar
  9. 9.
    Quantification of emissions from ships associated with ship movements between ports in the European Community (2002) FS 13881; European Commission: Brussels, BelgiumGoogle Scholar
  10. 10.
    Cofala J, Amann M, Heyes C, Klimont Z, Posch M, Schöpp W, Tarasson L, Jonson JE, Whall C, Stavrakaki A (2007) Final report: analysis of policy measures to reduce ship emissions in the context of the revision of the national emissions ceilings directive. International Institute for Applied Systems Analysis, Laxenburg, p 74Google Scholar
  11. 11.
    Corbett JJ, Winebrake JJ, Green EH, Kasibhatla P, Eyring V et al (2007) Mortality from ship emissions: a global assessment. Environ Sci Technol 41:8512–8518CrossRefGoogle Scholar
  12. 12.
    Salvi S, Holgate S-T (1999) Mechanisms of particulate matter toxicity. Clin Exp Allergy 29(9):1187–1194CrossRefGoogle Scholar
  13. 13.
    Donaldson K, Stone V (2011) Current hypotheses on the mechanisms of toxicity of ultrafine particles. Ann Ist Super Sanita 39(3):405–410Google Scholar
  14. 14.
    Kelly FJ, Fussell JC (2011) Air pollution and airway disease. Clin Exp Allergy 41(8):1059–1071CrossRefGoogle Scholar
  15. 15.
    Ristovski ZD, Miljevic B, Surawski N-C (2012) Respiratory health effects of diesel particulate matter. Respirology 17(2):201–212CrossRefGoogle Scholar
  16. 16.
    Donaldson K, Stone V, Seaton A, MacNee W (2001) Ambient particle inhalation and the cardiovascular system: potential mechanisms. Environ Health Perspect 109(4):523–527CrossRefGoogle Scholar
  17. 17.
    Emmendoerffer A, Hecht M, Boeker T, Mueller M, Heinrich U (2000) Role of inflammation in chemical-induced lung cancer. Toxicol Lett 112–113:185–191CrossRefGoogle Scholar
  18. 18.
    Reda AA, Schnelle-Kreis J, Orasche J, Abbaszade G, Lintelmann J, Arteaga-Salas JM, Stengel B, Rabe R, Harndorf H, Sippula O, Streibel T, Zimmermann R (2014) Gas phase carbonyl compounds in ship emissions: differences between diesel fuel and heavy fuel oil operation. Atmos Environ 94:467–478. doi: 10.1016/j.atmosenv.2014.05.053 CrossRefGoogle Scholar
  19. 19.
    Popovicheva O, Kireeva E, ShonijaN ZN, PersiantsevaN TV, DemirdjianB MJ, Mogilnikov V (2009) Ship particulate pollutants: characterization in terms of environmental implication. J Environ Monit 11:2077–2086CrossRefGoogle Scholar
  20. 20.
    Sippula O, Stengel B, Sklorz M, Streibel T, Rabe R, Orasche J, Lintelmann J, Michalke B, Abbaszade G, Radischat C, Gröger T, Schnelle-Kreis J, Harndorf H, Zimmermann R (2014) Particle emissions from a marine engine: chemical composition and aromatic emission profiles under various operating conditions. Environ Sci Technol 48(19):11721–9CrossRefGoogle Scholar
  21. 21.
    Korell J, Paur H-R, Seifert H, Andersson S (2009) Simultaneous removal of mercury, PCDD/F, and fine particles from flue gas. Environ Sci Technol 43:8308–8314. doi: 10.1021/es901289g CrossRefGoogle Scholar
  22. 22.
    Bologa AM, Paur HR, Seifert H, Wascher T (2005) Pilot-plant testing of a novel electrostatic collector for submicrometer particles. Ind Appl IEEE Trans 41:882–890. doi: 10.1109/TIA.2005.851017 CrossRefGoogle Scholar
  23. 23.
    Paur H-R, Bologa A, Koerber R (2012) Electrostatic precipitator of fine particles from biomass combustion facilities. Karlsruhe Institute of Technology. Accessed 15 Nov 2014
  24. 24.
    Schnelle-Kreis J, Orasche J, Abbaszade G, Schäfer K, Harlos D, Hansen A, Zimmermann R (2011) Application of direct thermal desorption gas chromatography time-of-flight mass spectrometry for determination of nonpolar organics in low-volume samples from ambient particulate matter and personal samplers. Anal Bioanal Chem 401(10):3083–3094CrossRefGoogle Scholar
  25. 25.
    Orasche J, Schnelle-Kreis J, Abbaszade G, Zimmermann R (2011) Technical Note: In-situ derivatization thermal desorption GC-TOFMS for direct analysis of particle-bound non-polar and polar organic species. Atmos Chem Phys 2011(11):8977–8993CrossRefGoogle Scholar
  26. 26.
    DFG, Polycyclic aromatic hydrocarbons (PAH) [MAK Value Documentation, 2012] (2002) In The MAK-Collection for Occupational Health and Safety, Wiley-VCH Verlag GmbH & Co. KGaAGoogle Scholar
  27. 27.
    Ong SE, Mann M (2006) A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC). Nat Protoc 1(6):2650–2660CrossRefGoogle Scholar
  28. 28.
    Sapcariu SC, Kanashova T, Weindl D, Ghelfi J, Dittmar G, and Hiller K (2014) Simultaneous extraction of proteins and metabolites from cells in culture. MethodsXGoogle Scholar
  29. 29.
    Rappsilber J, Mann M, Ishihama Y (2007) Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat Protoc 2(8):1896–906CrossRefGoogle Scholar
  30. 30.
    Boersema PJ, Raijmakers R, Lemeer S, Mohammed S, Heck AJ (2009) Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics. Nat Protoc 4(4):484–94. doi: 10.1038/nprot.2009.21 CrossRefGoogle Scholar
  31. 31.
    Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized ppb-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26(12):1367–1372CrossRefGoogle Scholar
  32. 32.
    R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: Accessed 15 Nov 2014
  33. 33.
    Huang DW, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4:44–57CrossRefGoogle Scholar
  34. 34.
    Ong S-E, Mann M (2005) Mass spectrometry-based proteomics turns quantitative. Nat Chem Biol 2005(1):252–262CrossRefGoogle Scholar
  35. 35.
    Lau HT, Suh HW, Golkowski M, Ong SE (2014) Comparing SILAC- and stable isotope dimethyl-labeling approaches for quantitative proteomics. J Proteome Res 13(9):4164–74. doi: 10.1021/pr500630a CrossRefGoogle Scholar
  36. 36.
    Garçon G, Dagher Z, Zerimech F, Ledoux F, Courcot D, Aboukais A, Puskaric E, Shirali P (2006) Dunkerque City air pollution particulate matter-induced cytotoxicity, oxidative stress and inflammation in human epithelial lung cells (L132) in culture. Toxicol Vitro Int J Publ Assoc Bibra 20:519–528CrossRefGoogle Scholar
  37. 37.
    Cachona BF, Firmin S, Verdin A, Ayi-Fanou L, Billet S, Cazier F, Martin PJ, Aissi F, Courcot D, Sanni A, Shirali P (2013) Proinflammatory effects and oxidative stress within human bronchial epithelial cells exposed to atmospheric particulate matter (PM2.5 and PM > 2.5) collected from Cotonou, Benin. Environ Pollut 185:340–351CrossRefGoogle Scholar
  38. 38.
    Schwarze PE, Totlandsdal AI, Lag M, Refsnes M, Holme JA, Ovrevik J (2013) Inflammation-related effects of diesel engine exhaust particles: studies on lung cells in vitro. Biomed Res Int 685142:1–13CrossRefGoogle Scholar
  39. 39.
    Baulig A, Garlatti M, Bonvallot V (2003) Involvement of reactive oxygen species in the metabolic pathways triggered by diesel exhaust particles in human airway epithelial cells. Am J Physiol 285(3):L671–L679Google Scholar
  40. 40.
    Bonvallot V, Baeza-Squiban A, Baulig A (2001) Organic compounds from diesel exhaust particles elicit a proinflammatory response in human airway epithelial cells and induce cytochrome p450 1A1 expression. Am J Respir Cell Mol Biol 25(4):515–521CrossRefGoogle Scholar
  41. 41.
    Bladt H, Ivleva NP, Niessner R (2014) Internally mixed multicomponent soot: Impact of different salts on soot structure and thermo-chemical properties. J Aerosl Sci 70:26–35CrossRefGoogle Scholar
  42. 42.
    Grabowsky J, Streibel T, Sklorz M, Chow JC, Watson JG, Mamakos A, Zimmermann R (2011) Hyphenation of a carbon analyzer to photo-ionization mass spectrometry to unravel the organic composition of particulate matter on a molecular level. Anal Bioanal Chem 401(10):3153–3164CrossRefGoogle Scholar
  43. 43.
    Bladt H, Schmid J, Kireeva ED, Popovicheva OB, Perseantseva NM, Timofeev MA, Heister K, Uihlein J, Ivleve NP, Niessner R (2012) Impact of fe content in laboratory-produced soot aerosol on its composition, structure, and thermo-chemical properties. Aerosol Sci Technol 46:1337–1348CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Tamara Kanashova
    • 1
    • 5
  • Oliver Popp
    • 1
  • Jürgen Orasche
    • 2
    • 5
  • Erwin Karg
    • 2
    • 4
  • Horst Harndorf
    • 4
    • 5
  • Benjamin Stengel
    • 4
    • 5
  • Martin Sklorz
    • 2
  • Thorsten Streibel
    • 2
    • 4
  • Ralf Zimmermann
    • 2
    • 3
    • 5
  • Gunnar Dittmar
    • 1
    • 5
    Email author
  1. 1.Mass spectrometryMax-Delbrück Center for molecular medicineBerlinGermany
  2. 2.Joint Mass Spectrometry CentreUniversity of RostockRostockGermany
  3. 3.Comprehensive Molecular AnalyticsHelmholtz Zentrum München – German Research Center for Environmental Health GmbHOberschleißheimGermany
  4. 4.Chair of Piston Machines and Internal Combustion EnginesUniversity of RostockRostockGermany
  5. 5.HICE – Helmholtz Virtual Institute of Complex Molecular Systems in Environmental HealthNeuherbergGermany

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