Skip to main content
SpringerLink
Log in

Metaproteomics Study of the Gut Microbiome

  • Protocol
  • First Online:
Functional Proteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1871))

Abstract

Proteomics is a widely used method for defining the protein composition of a complex sample. As this approach allows for identification and quantification of proteins across a broad dynamic range as well as detection of post-translational modifications, proteomics is an ideal platform to investigate the gut microbiome at a functional level. The gut microbiome is a dynamic environment which is crucial for overall health and fitness. Imbalances in the gut microbiome can influence nutrient absorption, pathogen resistance, inflammation, and various human diseases. Metaproteomic analysis of the gut microbiome is currently being performed on bacteria isolated from (1) fecal samples (2) colonic lavage, or (3) colon biopsies. Investigation of the gut microbiome has demonstrated that within the colon, there are distinct communities based on spatial location, and separable from the gut microbiomes isolated from stool. In addition to expanding our understanding of host–bacterial interactions for human health and disease, gut microbiome analysis is being utilized for biomarker development to discriminate normal individuals and diseased (i.e., inflammatory bowel disease or colon cancer) patients as well as to monitor disease activity and prognosis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Frank DN, St Amand AL, Feldman RA et al (2007) Molecular-phylogenetic characterization of microbial community imbalances in human inflammatory bowel diseases. PNAS 104:13780–13785

    Article  CAS  Google Scholar 

  2. Cresci GA (2015) The gut microbiome: what we do and don’t know. Nutr Clin Pract 30:734–746

    Article  CAS  Google Scholar 

  3. Lynch SV, Pederson O (2016) The human intestinal microbiome in health and disease. N Engl J Med 375:2369–2379

    Article  CAS  Google Scholar 

  4. Tuddenham S, Sears CL (2015) The intestinal microbiome and health. Curr Opin Infect Dis 28:464–470

    Article  CAS  Google Scholar 

  5. Rakoff-Nahoum S, Paglino J, Eslami-Varzaneh F et al (2014) Recognition of commensal microflora by toll-like receptors is required for intestinal homeostasis. Cell 118:229–241

    Article  Google Scholar 

  6. Aagaard K, Ma J, Anthony K et al (2014) The placenta harbors a unique microbiome. Sci Transl Med 6:237ra65

    Article  Google Scholar 

  7. Urushiyama D, Suda W, Ohnishi E et al (2017) Microbiome profile of the amniotic fluid as a predictive biomarker of perinatal outcome. Sci Rep 7:12171

    Article  Google Scholar 

  8. DiGiulio DB, Romero R, Amogan HP et al (2008) Microbial prevalence, diversity and abundance in amniotic fluid during preterm labor: a molecular and culture-based investigation. PLoS One 3:e3056

    Article  Google Scholar 

  9. Milani C, Duranti S, Bottacini F et al (2017) The first microbial colonizers of the human gut: composition, activities, and health implications of the infant gut microbiota. Microbiol Mol Biol Rev. https://doi.org/10.1128/MMBR.00036-17

  10. Biasucci G, Rubini M, Riboni S et al (2010) Mode of delivery affects the bacterial community in the newborn gut. Early Hum Dev 86:13–15

    Article  Google Scholar 

  11. Hollister EB, Riehle K, Luna RA et al (2015) Structure and function of the healthy preadolescent pediatric gut microbiome. Microbiome 3:36

    Article  Google Scholar 

  12. Human Microbiome Project Consortium (2012) Structure, function and diversity of the healthy human microbiome. Nature 486:207–212

    Article  Google Scholar 

  13. Eckburg PB, Bik EM, Bernstein CN et al (2005) Diversity of the human intestinal microbial flora. Science 308:1635–1638

    Article  Google Scholar 

  14. Proctor LM, Sechi S, DiGiacomo ND et al (2014) The integrative human microbiome project: dynamic analysis of microbiome-host omics profiles during periods of human health and disease. Cell Host Microbe 16:276–289

    Article  CAS  Google Scholar 

  15. Tamboli CP, Neut C, Desreumaux P et al (2015) Dysbiosis in inflammatory bowel disease. Gut 53:1–4

    Article  Google Scholar 

  16. Ley RE, Turnbaugh PJ, Klein S et al (2006) Microbial ecology: human gut microbes associated with obesity. Nature 444:1022–1023

    Article  CAS  Google Scholar 

  17. Kolmeder CA, Ritari J, Verdam FJ et al (2015) Colonic metaproteomic signatures of active bacteria and the host in obesity. Proteomics 15:3544–3522

    Article  CAS  Google Scholar 

  18. Kang Y, Cai Y (2017) Gut microbiota and hypertension: from pathogenesis to new therapeutic strategies. Clin Res Hepatol Gastroenterol. https://doi.org/10.1016/j.clinre.2017.09.006

    Article  CAS  Google Scholar 

  19. Turnbaugh PJ, Ridaura VK, Faith JJ et al (2009) The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci Transl Med 1:6ra14

    Article  Google Scholar 

  20. David LA, Maurice CF, Carmody RN et al (2014) Diet rapidly and reproducibly alters the human gut microbiome. Nature 505:559–563

    Article  CAS  Google Scholar 

  21. Yatsunenko T, Rey FE, Manary MJ et al (2012) Human gut microbiome viewed across age and geography. Nature 486:222–227

    Article  CAS  Google Scholar 

  22. Wright EK, Kamm MA, Teo SM et al (2015) Recent advances in characterizing the gastrointestinal microbiome in Crohn’s disease: a systematic review. Inflamm Bowel Dis 21:1219–1228

    Article  Google Scholar 

  23. Arthur JC, Perez-Chanona E, Myhlbauer M et al (2012) Intestinal inflammation targets cancer-inducing activity of the microbiota. Science 338:120–123

    Article  CAS  Google Scholar 

  24. Bullman S, Pedamallu CS, Sicinska E et al (2017) Analysis of Fusobacterium persistence and antibiotic response in colorectal cancer. Science. https://doi.org/10.1126/science.aal5240

    Article  CAS  Google Scholar 

  25. Karolewska-Bochenek K, Grzesiowski P, Banaszkiewicz A et al (2017) A two-week fecal microbiota transplantation course in pediatric patients with inflammatory bowel disease. Springer, Heidelberg, Boston, MA, pp 1–7

    Google Scholar 

  26. Fischer M, Sipe B, Cheng YW et al (2017) Fecal microbiota transplant in severe and severe-complicated Clostridium difficile: a promising treatment approach. Gut Microbes 8:289–302

    Article  CAS  Google Scholar 

  27. Wilmes P, Bond PL (2004) The application of two-dimensional polyacrylamide gel electrophoresis and downstream analyses to a mixed community of prokaryotic microorganisms. Env Microbiol 6:911–920

    Article  CAS  Google Scholar 

  28. Bastida F, Hernandez T, Garcia C (2014) Metaproteomics of soils from semiarid environment: functional and phylogenetic information obtained with different protein extraction methods. J Proteomics 101:31–42

    Article  CAS  Google Scholar 

  29. Maier TV, Lucio M, Lee H et al (2017) Impact of dietary resistant starch on the human gut microbiome, metaproteome, and metabolome. MBio 8:e01343–e01347

    Article  Google Scholar 

  30. Williams TJ, Cavicchioli R (2014) Marine metaproteomics: deciphering the microbial metabolic food web. Trends Microbiol 22:248–260

    Article  CAS  Google Scholar 

  31. Heyer R, Schallert K, Zoun R et al (2017) Challenges and perspectives of metaproteomic data analysis. J Biotechnol 261:24–36

    Article  CAS  Google Scholar 

  32. Zhang X, Li L, Mayne J et al (2017) Assessing the impact of protein extraction methods for human gut metaproteomics. J Proteome. https://doi.org/10.1016/j.jprot.2017.07.001

    Article  CAS  Google Scholar 

  33. Juste C, Kreil DP, Beauvallet C et al (2014) Bacterial protein signals are associated with Crohn’s disease. Gut 63:1566–1577

    Article  CAS  Google Scholar 

  34. Wilmes P, Heintz-Buschart A, Bond PL (2015) A decade of metaproteomics: where we stand and what the future holds. Proteomics 15:3409–3417

    Article  CAS  Google Scholar 

  35. Glatter T, Ahrne E, Schmidt A (2015) Comparison of different sample preparation protocols reveals lysis buffer-specific extraction biases in gram-negative bacteria and human cells. J Proteome Res 14:4472–4485

    Article  CAS  Google Scholar 

  36. Xiong W, Giannone RJ, Morowitz MJ et al (2015) Development of an enhanced metaproteomic approach for deepening the microbiome characterization of the human infant gut. J Proteome Res 14:133–141

    Article  CAS  Google Scholar 

  37. Erickson AR, Cantarel BL, Lamendella R et al (2012) Integrated metagenomics/metaproteomics reveals human host-microbiota signatures of Crohn’s disease. PLoS One 7:e49138

    Article  CAS  Google Scholar 

  38. Tanca A, Palomba A, Pisanu S et al (2014) A straightforward and efficieint analytical pipeline for metaproteome characterization. Microbiome 2:49

    Article  Google Scholar 

  39. Durban A, Abellan JJ, Jimenez-Hernandez N et al (2011) Assessing gut microbial diversity from feces and rectal mucosa. Microb Ecol 61:123–133

    Article  Google Scholar 

  40. Verberkmoes NC, Russell AL, Shah M et al (2009) Shotgun metaproteomics of the human distal gut microbiota. ISME J 3:179–189

    Article  CAS  Google Scholar 

  41. Zoetendal EG, von Wright A, Vilpponen-Salmela T et al (2002) Mucosa-associated bacteria in the human gastrointestinal tract are uniformly distributed along the colon and differ from the community recovered from feces. Appl Environ Microbiol 68:3401–3407

    Article  CAS  Google Scholar 

  42. Li X, LeBlanc J, Truong A et al (2011) A metaproteomic approach to study human-microbial ecosystems at the mucosal luminal interface. PLoS One 6:e26542

    Article  CAS  Google Scholar 

  43. Choo JM, Leong LEX, Rogers GB (2015) Sample storage conditions significantly influence faecal microbiome profiles. Sci Rep 5:16350

    Article  CAS  Google Scholar 

  44. Chapman JD, Goodlett DR, Masselon CD (2014) Mulitplexed and data-independent tandem mass spectrometry for global proteome profiling. Mass Spec Rev 33:452–470

    Article  CAS  Google Scholar 

  45. Nigjeh EN, Chen R, Allen-Tamura Y et al (2017) Spectral library-based glycopeptide analysis--detection of circulating galectin-3 binding protein in pancreatic cancer. Proteomics Clin Appl 11:1700064

    Article  Google Scholar 

  46. Rosenberger G, Liu Y, Rost HL et al (2017) Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS. Nat Biotechnol 35:781–788

    Article  CAS  Google Scholar 

  47. Rost HL, Aebersold R, Schubert OT (2017) Automated SWATH data analysis using targeted extraction of ion chromatograms. Methods Mol Biol 1550:289–307

    Article  CAS  Google Scholar 

  48. Alispahic M, Hummel K, Jandreski-Cvetkovic D et al (2010) Species-specific identification and differentiation of Arcobacter, Helicobacter, and Campylobacter by full-spectral matrix-associated laser desorption/ionization time of flight mass spectrometry analysis. J Med Microbiol 59:295–301

    Article  CAS  Google Scholar 

  49. Cheng K, Ning Z, Zhang X et al (2017) MetaLab: an automated pipeline for metaproteomic data analysis. Microbiome 5:157

    Article  Google Scholar 

  50. Tang H, Li S, Ye Y (2016) A graph-centric approach for metagenome-guided peptide and protein identification in metaproteomics. PLoS Comput Biol 12:e1005224

    Article  Google Scholar 

  51. Mesuere B, Devreese B, Debyser G et al (2012) Unipept: tryptic peptide-based biodiversity analysis of metaproteome samples. J Proteome Res 11:5773–5780

    Article  CAS  Google Scholar 

  52. Mesuere B, Van der Jeugt F, Willems T et al (2018) High-throughput metaprotomics data analysis with Unipept: a tutorial. J Proteome 171:11–22

    Article  CAS  Google Scholar 

  53. Zhang X, Ning Z, Moore JI et al (2016) Meta-Pro-IQ: a universal metaproteomic approach to studying human and mouse gut microbiota. Microbiome 4:31

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Medicine, University of Washington, Seattle, WA, USA

    Lisa A. Lai, Zachary Tong & Ru Chen

  2. Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA

    Sheng Pan

Authors
  1. Lisa A. Lai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zachary Tong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ru Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sheng Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sheng Pan .

Editor information

Editors and Affiliations

  1. Array Bridge Inc., St. Louis, MO, USA

    Xing Wang

  2. Biotech Support Group LLC, Monmouth Junction, NJ, USA

    Matthew Kuruc

Rights and permissions

Reprints and permissions

Copyright information

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

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Lai, L.A., Tong, Z., Chen, R., Pan, S. (2019). Metaproteomics Study of the Gut Microbiome. In: Wang, X., Kuruc, M. (eds) Functional Proteomics. Methods in Molecular Biology, vol 1871. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8814-3_8

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-8814-3_8

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-8813-6

  • Online ISBN: 978-1-4939-8814-3

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation