Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

Analysis of bacterial-surface-specific antibodies in body fluids using bacterial flow cytometry

Abstract

Antibacterial antibody responses that target surfaces of live bacteria or secreted toxins are likely to be relevant in controlling bacterial pathogenesis. The ability to specifically quantify bacterial-surface-binding antibodies is therefore highly attractive as a quantitative correlate of immune protection. Here, binding of antibodies from various body fluids to pure-cultured live bacteria is made visible with fluorophore-conjugated secondary antibodies and measured by flow cytometry. We indicate the necessary controls for excluding nonspecific binding and also demonstrate a cross-adsorption technique for determining the extent of cross-reactivity. This technique has numerous advantages over standard ELISA and western blotting techniques because of its independence from scaffold binding, exclusion of cross-reactive elements from lysed bacteria and ability to visualize bacterial subpopulations. In addition, less than 105 bacteria and less than 10 μg of antibody are required per sample. The technique requires 3–4 h of hands-on experimentation and analysis. Moreover, it can be combined with automation and mutliplexing for high-throughput applications.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Overview of the protocol.
Figure 2: Detailed analysis of surface epitopes.
Figure 3: Increasing the target cell number is equivalent to increasing the dilution factor.
Figure 4: The effects of different contamination sources on acquired data.
Figure 5: Timing of serum IgG and IgA induction after confirmed K. pneumoniae sepsis secondary to a lung infection.
Figure 6: Bacterial flow cytometry with purified IgA from human breast milk and fecal water.
Figure 7: Effects of bacterial cryo-preservation and fixation on IgG binding.
Figure 8: Nonspecific antibody binding.
Figure 9: Use of irrelevant bacterial species and germ-free mice as negative controls in the murine system.
Figure 10: Controls in the human system.
Figure 11: Data analysis methods.
Figure 12: Vaccination with oral peracetic-acid-inactivated S. typhimurium and infection with live-attenuated S. typhimurium induce a similar magnitude of intestinal IgA response.
Figure 13: Bacterial flow cytometry reveals increased microbiota-specific serum antibodies in metabolic liver disease.

Similar content being viewed by others

References

  1. Slack, E. et al. Innate and adaptive immunity cooperate flexibly to maintain host-microbiota mutualism. Science 325, 617–620 (2009).

    Article  CAS  Google Scholar 

  2. Endt, K. et al. The microbiota mediates pathogen clearance from the gut lumen after non-typhoidal Salmonella diarrhea. PLoS Pathog. 6, e1001097 (2010).

    Article  Google Scholar 

  3. Hapfelmeier, S. et al. Reversible microbial colonization of germ-free mice reveals the dynamics of IgA immune responses. Science 328, 1705–1709 (2010).

    Article  CAS  Google Scholar 

  4. Haas, A. et al. Systemic antibody responses to gut commensal bacteria during chronic HIV-1 infection. Gut 60, 1506–1519 (2011).

    Article  CAS  Google Scholar 

  5. Seleznik, G.M. et al. Lymphotoxin β receptor signaling promotes development of autoimmune pancreatitis. Gastroenterology 143, 1361–1374 (2012).

    Article  CAS  Google Scholar 

  6. Balmer, M.L. et al. The liver may act as a firewall mediating mutualism between the host and its gut commensal microbiota. Sci. Transl. Med. 6, 237–266 (2014).

    Article  Google Scholar 

  7. Brown, J.S. et al. The classical pathway is the dominant complement pathway required for innate immunity to Streptococcus pneumoniae infection in mice. Proc. Natl. Acad. Sci. USA 99, 16969–16974 (2002).

    Article  CAS  Google Scholar 

  8. Hyams, C., Camberlein, E., Cohen, J.M., Bax, K. & Brown, J.S. The Streptococcus pneumoniae capsule inhibits complement activity and neutrophil phagocytosis by multiple mechanisms. Infect. Immun. 78, 704–715 (2010).

    Article  CAS  Google Scholar 

  9. Cohen, J.M., Wilson, R., Shah, P., Baxendale, H.E. & Brown, J.S. Lack of cross-protection against invasive pneumonia caused by heterologous strains following murine Streptococcus pneumoniae nasopharyngeal colonisation despite whole cell ELISAs showing significant cross-reactive IgG. Vaccine 31, 2328–2332 (2013).

    Article  CAS  Google Scholar 

  10. LeibundGut-Landmann, S. et al. Syk- and CARD9-dependent coupling of innate immunity to the induction of T helper cells that produce interleukin 17. Nat. Immunol. 8, 630–638 (2007).

    Article  CAS  Google Scholar 

  11. Maclennan, C.A. Antibodies and protection against invasive Salmonella disease. Front. Immunol. 5, 635 (2014).

    Article  Google Scholar 

  12. Slack, E., Balmer, M.L. & Macpherson, A.J.B . Cells as a critical node in the microbiota-host immune system network. Immunol. Rev. 260, 50–66 (2014).

    Article  CAS  Google Scholar 

  13. Lécuyer, E. et al. Segmented filamentous bacterium uses secondary and tertiary lymphoid tissues to induce gut IgA and specific T helper 17 cell responses. Immunity 40, 608–620 (2014).

    Article  Google Scholar 

  14. Porsch-Özcürümez, M. et al. Comparison of enzyme-linked immunosorbent assay, western blotting, microagglutination, indirect immunofluorescence assay, and flow cytometry for serological diagnosis of tularemia. Clin. Diagn. Lab. Immunol. 11, 1008–1015 (2004).

    PubMed  PubMed Central  Google Scholar 

  15. Macpherson, A.J. & Uhr, T. Induction of protective IgA by intestinal dendritic cells carrying commensal bacteria. Science 303, 1662–1665 (2004).

    Article  CAS  Google Scholar 

  16. Karlsson, M., Mollegard, I., Stiernstedt, G. & Wretlind, B. Comparison of western blot and enzyme-linked immunosorbent assay for diagnosis of Lyme borreliosis. Eur. J. Clin. Microbiol. Infect. Dis. 8, 871–877 (1989).

    Article  CAS  Google Scholar 

  17. Yutin, N., Puigbo, P., Koonin, E.V. & Wolf, Y.I. Phylogenomics of prokaryotic ribosomal proteins. PLoS One 7, e36972 (2012).

    Article  CAS  Google Scholar 

  18. Cooper, M.D., Wannemuehler, M.J., Miller, R.D. & Fedyk, M.F. Role of outer envelope contamination in protection elicited by ribosomal preparations against Neisseria gonorrhoeae infection. Infect. Immun. 32, 173–179 (1981).

    Article  CAS  Google Scholar 

  19. Smith, K., McCoy, K.D. & Macpherson, A.J. Use of axenic animals in studying the adaptation of mammals to their commensal intestinal microbiota. Semin. Immunol. 19, 59–69 (2007).

    Article  CAS  Google Scholar 

  20. Macpherson, A.J. & McCoy, K.D. Stratification and compartmentalisation of immunoglobulin responses to commensal intestinal microbes. Semin. Immunol. 25, 358–363 (2013).

    Article  CAS  Google Scholar 

  21. Bunker, J.J. et al. Innate and adaptive humoral responses coat distinct commensal bacteria with immunoglobulin A. Immunity 43, 541–553 (2015).

    Article  CAS  Google Scholar 

  22. Moor, K. et al. Peracetic acid treatment generates potent inactivated oral vaccines from a broad range of culturable bacterial species. Front. Immunol. 7, 34 (2016).

    Article  Google Scholar 

  23. Palm, N.W. et al. Immunoglobulin A coating identifies colitogenic bacteria in inflammatory bowel disease. Cell 158, 1000–1010 (2014).

    Article  CAS  Google Scholar 

  24. Cullender, T.C. et al. Innate and adaptive immunity interact to quench microbiome flagellar motility in the gut. Cell Host Microbe 14, 571–581 (2013).

    Article  CAS  Google Scholar 

  25. Bouvet, J.P. Immunoglobulin Fab fragment-binding proteins. Int. J. Immunopharmacol. 16, 419–424 (1994).

    Article  CAS  Google Scholar 

  26. Tashiro, M. & Montelione, G.T. Structures of bacterial immunoglobulin-binding domains and their complexes with immunoglobulins. Curr. Opin. Struct. Biol. 5, 471–481 (1995).

    Article  CAS  Google Scholar 

  27. Chimalapati, S. et al. Infection with conditionally virulent Streptococcus pneumoniae Δpab strains induces antibody to conserved protein antigens but does not protect against systemic iInfection with heterologous strains. Infect. Immun. 79, 4965–4976 (2011).

    Article  CAS  Google Scholar 

  28. Avraham, R. et al. Pathogen cell-to-cell variability drives heterogeneity in host immune responses. Cell 162, 1309–1321 (2015).

    Article  CAS  Google Scholar 

  29. van der Woude, M.W. Phase variation: how to create and coordinate population diversity. Curr. Opin. Microbiol. 14, 205–211 (2011).

    Article  CAS  Google Scholar 

  30. Mouslim, C. & Hughes, K.T. The effect of cell growth phase on the regulatory cross-talk between flagellar and Spi1 virulence gene expression. PLoS Pathog. 10, e1003987 (2014).

    Article  Google Scholar 

  31. Goodman, A.L. et al. Extensive personal human gut microbiota culture collections characterized and manipulated in gnotobiotic mice. Proc. Natl Acad. Sci. USA 108, 6252–6257 (2011).

    Article  CAS  Google Scholar 

  32. Saletti, G., Çuburu, N., Yang, J.S., Dey, A. & Czerkinsky, C. Enzyme-linked immunospot assays for direct ex vivo measurement of vaccine-induced human humoral immune responses in blood. Nat. Protoc. 8, 1073–1087 (2013).

    Article  Google Scholar 

  33. Liu, B. et al. Structural diversity in Salmonella O antigens and its genetic basis. FEMS Microbiol. Rev. 38, 56–89 (2014).

    Article  CAS  Google Scholar 

  34. Pack, T.D. Purification of human IgA. Curr. Protoc. Immunol. Chapter 2 Unit 2.10B (10.1002/0471142735) (2001).

  35. Koch, C., Günther, S., Desta, A.F., Hübschmann, T. & Müller, S. Cytometric fingerprinting for analyzing microbial intracommunity structure variation and identifying subcommunity function. Nat. Protoc. 8, 190–202 (2013).

    Article  CAS  Google Scholar 

  36. Speers, A.M., Cologgi, D.L. & Reguera, G. (Current Protocols in Microbiology. John Wiley & Sons, 2005).

  37. Schulthess, B., Bloemberg, G.V., Zbinden, R., Böttger, E.C. & Hombach, M. Evaluation of the Bruker MALDI Biotyper for identification of Gram-positive rods: development of a diagnostic algorithm for the clinical laboratory. J. Clin. Microbiol. 52, 1089–1097 (2014).

    Article  Google Scholar 

  38. Szaloki, G. & Goda, K. Compensation in multicolor flow cytometry. Cytom. A 87, 982–985 (2015).

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge J. Doré and C. Juste (Institut National de la Recherche Agronomique (INRA), UMR1319 Micalis, Jouy en Josas, France) for access to well-characterized bacterial strains, and C. Parizot and D. Gouas for technical help during initial experimental setup. The authors also acknowledge the following funders: M.L. was supported by the Institut national de la santé et de la recherche médicale (Inserm), Agence Nationale de la Recherche (MetAntibody, ANR-14-CE14-0013) and Fondation pour l'Aide a la Recherche sur la Sclerose En Plaques (ARSEP). E.S. was supported by an SNF Ambizione fellowship (PZ00P3_136742) and an ETH research grant (ETH-33 12-2).

Author information

Authors and Affiliations

Authors

Contributions

K.M., J.F., A.T. and D.S. generated the data shown in Figures 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11. M.L.B. generated the data shown in Figure 13. A.J.M. provided support during the development of the method and reviewed the manuscript. G.G. provided support for adaption of the method to clinical scenarios and reviewed the manuscript. M.L. further developed the method for application to human research, generated data shown in Figures 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and wrote the manuscript. E.S. established the methodology and analysis protocols, generated data shown in Figures 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 and wrote the manuscript.

Corresponding authors

Correspondence to Martin Larsen or Emma Slack.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Data

Raw data and calculations for graphs shown in Figures 11 and 12 (XLSX 343 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Moor, K., Fadlallah, J., Toska, A. et al. Analysis of bacterial-surface-specific antibodies in body fluids using bacterial flow cytometry. Nat Protoc 11, 1531–1553 (2016). https://doi.org/10.1038/nprot.2016.091

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2016.091

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing