SIP-Metaproteomics: Linking Microbial Taxonomy, Function, and Activity

  • Martin TaubertEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 2046)


Stable isotope probing combined with metaproteomics enables the detection and characterization of active key species in microbial populations under near-natural conditions, which greatly helps to understand the metabolic functions of complex microbial communities. This is achieved by providing growth substrates labeled with heavy isotopes such as 13C, which will be assimilated into microbial biomass. After subsequent extraction of proteins and proteolytic cleavage into peptides, the heavy isotope enrichment can be detected by high-resolution mass spectrometric analysis, and linked to the functional and taxonomic characterization of these biomarkers. Here we provide protocols for obtaining isotopically labeled proteins and for downstream SIP-metaproteomics analysis.

Key words

Stable isotope probing Metaproteomics Microbial ecology Metabolic labeling Mass spectrometry 



I thank Nico Jehmlich for providing helpful inputs and for reviewing the manuscript.


  1. 1.
    Friedrich MW (2006) Stable-isotope probing of DNA: insights into the function of uncultivated microorganisms from isotopically labeled metagenomes. Curr Opin Biotech 17:59–66CrossRefGoogle Scholar
  2. 2.
    Neufeld JD, Dumont MG, Vohra J, Murrell JC (2007) Methodological considerations for the use of stable isotope probing in microbial ecology. Microb Ecol 53:435–442CrossRefGoogle Scholar
  3. 3.
    Neufeld JD, Vohra J, Dumont MG, Lueders T, Manefield M, Friedrich MW et al (2007) DNA stable-isotope probing. Nat Protoc 2:860–866CrossRefPubMedCentralGoogle Scholar
  4. 4.
    Whiteley AS, Thomson B, Lueders T, Manefield M (2007) RNA stable-isotope probing. Nat Protoc 2:838–844CrossRefGoogle Scholar
  5. 5.
    Boschker HTS, Nold SC, Wellsbury P, Bos D, de Graaf W, Pel R et al (1998) Direct linking of microbial populations to specific biogeochemical processes by C-13-labelling of biomarkers. Nature 392:801–805CrossRefGoogle Scholar
  6. 6.
    Jehmlich N, Schmidt F, Taubert M, Seifert J, Bastida F, von Bergen M et al (2010) Protein-based stable isotope probing. Nat Protoc 5:1957–1966CrossRefPubMedCentralGoogle Scholar
  7. 7.
    Huang WE, Stoecker K, Griffiths R, Newbold L, Daims H, Whiteley AS et al (2007) Raman-FISH: combining stable-isotope Raman spectroscopy and fluorescence in situ hybridization for the single cell analysis of identity and function. Environ Microbiol 9:1878–1889CrossRefGoogle Scholar
  8. 8.
    Musat N, Halm H, Winterholler B, Hoppe P, Peduzzi S, Hillion F et al (2008) A single-cell view on the ecophysiology of anaerobic phototrophic bacteria. Proc Natl Acad Sci U S A 105:17861–17866CrossRefPubMedCentralGoogle Scholar
  9. 9.
    Dumont MG, Radajewski SM, Miguez CB, McDonald IR, Murrell JC (2006) Identification of a complete methane monooxygenase operon from soil by combining stable isotope probing and metagenomic analysis. Environ Microbiol 8:1240–1250CrossRefGoogle Scholar
  10. 10.
    Dumont MG, Pommerenke B, Casper P (2013) Using stable isotope probing to obtain a targeted metatranscriptome of aerobic methanotrophs in lake sediment. Env Microbiol Rep 5:757–764Google Scholar
  11. 11.
    Taubert M, Vogt C, Wubet T, Kleinsteuber S, Tarkka MT, Harms H et al (2012) Protein-SIP enables time-resolved analysis of the carbon flux in a sulfate-reducing, benzene-degrading microbial consortium. ISME J 6:2291–2301CrossRefPubMedCentralGoogle Scholar
  12. 12.
    Jehmlich N, Kopinke FD, Lenhard S, Vogt C, Herbst FA, Seifert J et al (2012) Sulfur-36S stable isotope labeling of amino acids for quantification (SULAQ). Proteomics 12:37–42CrossRefGoogle Scholar
  13. 13.
    Justice NB, Li Z, Wang YF, Spaudling SE, Mosier AC, Hettich RL et al (2014) N-15- and H-2 proteomic stable isotope probing links nitrogen flow to archaeal heterotrophic activity. Environ Microbiol 16:3224–3237CrossRefGoogle Scholar
  14. 14.
    Taubert M, Stöckel S, Geesink P, Girnus S, Jehmlich N, von Bergen M et al (2018) Tracking active groundwater microbes with D2O labelling to understand their ecosystem function. Environ Microbiol 20:369–384CrossRefGoogle Scholar
  15. 15.
    Herbst FA, Bahr A, Duarte M, Pieper DH, Richnow HH, von Bergen M et al (2013) Elucidation of in situ polycyclic aromatic hydrocarbon degradation by functional metaproteomics (protein-SIP). Proteomics 13:2910–2920PubMedGoogle Scholar
  16. 16.
    Lünsmann V, Kappelmeyer U, Benndorf R, Martinez-Lavanchy PM, Taubert A, Adrian L et al (2016) In situ protein-SIP highlights Burkholderiaceae as key players degrading toluene by para ring hydroxylation in a constructed wetland model. Environ Microbiol 18:1176–1186CrossRefGoogle Scholar
  17. 17.
    Pan CL, Fischer CR, Hyatt D, Bowen BP, Hettich RL, Banfield JF (2011) Quantitative tracking of isotope flows in proteomes of microbial communities. Mol Cell Proteomics 10:M110.006049CrossRefPubMedCentralGoogle Scholar
  18. 18.
    Röst HL, Sachsenberg T, Aiche S, Bielow C, Weisser H, Aicheler F et al (2016) OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nat Methods 13:741–748CrossRefPubMedCentralGoogle Scholar
  19. 19.
    Tyanova S, Temu T, Cox J (2016) The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat Protoc 11:2301–2319CrossRefPubMedCentralGoogle Scholar
  20. 20.
    Muth T, Kohrs F, Heyer R, Benndorf D, Rapp E, Reichl U et al (2018) MPA portable: a stand-alone software package for analyzing metaproteome samples on the go. Anal Chem 90:685–689CrossRefPubMedCentralGoogle Scholar
  21. 21.
    Sachsenberg T, Herbst FA, Taubert M, Kermer R, Jehmlich N, von Bergen M et al (2015) MetaProSIP: automated inference of stable isotope incorporation rates in proteins for functional metaproteomics. J Proteome Res 14:619–627CrossRefPubMedCentralGoogle Scholar
  22. 22.
    Hoekman B, Breitling R, Suits F, Bischoff R, Horvatovich P (2012) msCompare: a framework for quantitative analysis of label-free LC-MS data for comparative candidate biomarker studies. Mol Cell Proteomics 11:M111.015974CrossRefPubMedCentralGoogle Scholar
  23. 23.
    Qian C, Hettich RL (2017) Optimized extraction method to remove humic acid interferences from soil samples prior to microbial proteome measurements. J Proteome Res 16:2537–2546CrossRefPubMedCentralGoogle Scholar
  24. 24.
    Taubert M, Grob C, Howat AM, Burns OJ, Chen Y, Neufeld JD et al (2016) Analysis of active methylotrophic communities: when DNA-SIP meets high-throughput technologies. Methods Mol Biol 1399:235–255CrossRefGoogle Scholar
  25. 25.
    Jehmlich N, Golatowski C, Murr A, Salazar G, Dhople VM, Hammer E et al (2014) Comparative evaluation of peptide desalting methods for salivary proteome analysis. Clin Chim Acta 434:16–20CrossRefGoogle Scholar
  26. 26.
    Muth T, Kolmeder CA, Salojärvi J, Keskitalo S, Varjosalo M, Verdam FJ et al (2015) Navigating through metaproteomics data: a logbook of database searching. Proteomics 15:3439–3453CrossRefGoogle Scholar
  27. 27.
    Seifert J, Taubert M, Jehmlich N, Schmidt F, Volker U, Vogt C et al (2012) Protein-based stable isotope probing (protein-SIP) in functional metaproteomics. Mass Spectrom Rev 31:683–697CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of Biological Sciences, Institute of BiodiversityFriedrich Schiller University JenaJenaGermany

Personalised recommendations