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:

iMAD, a genetic screening strategy for dissecting complex interactions between a pathogen and its host

Abstract

Insertional mutagenesis and depletion (iMAD) is a genetic screening strategy for dissecting complex interactions between two organisms. The simultaneous genetic manipulation of both organisms allows the identification of aggravating and alleviating genetic interactions between pairs of gene disruptions, one from each organism. Hierarchial clustering and genetic interaction networks are then used to identify common behavioral patterns among subsets of genes, which allow functional relationships between proteins and their component pathways to be elucidated. Here we present a protocol for dissecting the interaction between a pathogen (Legionella pneumophila) and its host (cultured Drosophila melanogaster cells) using bacterial mutagenesis and host RNAi. The key stages covered in the PROCEDURE include the design, execution and data analysis of an iMAD screen; details for determining the abundance of individual mutants by microarray analysis and next-generation sequencing are not included because detailed protocols have been published elsewhere. Adapting and optimizing iMAD to a specific experimental system can require 6–18 months. Once a bacterial mutant library, host cell factor depletion strategies and conditions to monitor the interaction are established, an iMAD screen can be completed in 4–8 weeks, depending on the organisms' growth rates, the duration of the interaction and the types of data analysis performed.

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: iMAD for examining host-pathogen interactions4.
Figure 2: Determining the number of host targets for RNAi.
Figure 3: Identifying functional relationships between bacterial virulence factors that promote disease.
Figure 4: Resolution of functional relationships using phenotype severity.

Similar content being viewed by others

References

  1. Typas, A. et al. High-throughput, quantitative analyses of genetic interactions in E. coli. Nat. Methods 5, 781–787 (2008).

    Article  CAS  Google Scholar 

  2. Schuldiner, M. et al. Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile. Cell 123, 507–519 (2005).

    Article  CAS  Google Scholar 

  3. Horn, T. et al. Mapping of signaling networks through synthetic genetic interaction analysis by RNAi. Nat. Methods 8, 341–346 (2011).

    Article  CAS  Google Scholar 

  4. O'Connor, T.J. et al. Aggravating genetic interactions allow a solution to redundancy in a bacterial pathogen. Science 338, 1440–1444 (2012).

    Article  CAS  Google Scholar 

  5. Huang, L. et al. The E Block motif is associated with Legionella pneumophila translocated substrates. Cell. Microbiol. 13, 227–245 (2011).

    Article  CAS  Google Scholar 

  6. Zhu, W. et al. Comprehensive identification of protein substrates of the Dot/Icm type IV transporter of Legionella pneumophila. PLoS ONE 6, e17638 (2011).

    Article  CAS  Google Scholar 

  7. Dorer, M.S. et al. RNA interference analysis of Legionella in Drosophila cells: exploitation of early secretory apparatus dynamics. PLoS Pathog. 2, e34 (2006).

    Article  Google Scholar 

  8. Sassetti, C.M. et al. Comprehensive identification of conditionally essential genes in mycobacteria. Proc. Natl. Acad. Sci. USA 98, 12712–12717 (2001).

    Article  CAS  Google Scholar 

  9. van Opijnen, T. et al. Tn-seq: high-throughput parallel sequencing for fitness and genetic interaction studies in microorganisms. Nat. Methods 6, 767–772 (2009).

    Article  CAS  Google Scholar 

  10. Goodman, A.L. et al. Identifying genetic determinants needed to establish a human gut symbiont in its habitat. Cell Host Microbe 6, 279–289 (2009).

    Article  CAS  Google Scholar 

  11. Langridge, G.C. et al. Simultaneous assay of every Salmonella typhi gene using one million transposon mutants. Genome Res. 19, 2308–2316 (2009).

    Article  CAS  Google Scholar 

  12. Gawronski, J.D. et al. Tracking insertion mutants within libraries by deep sequencing and a genome-wide screen for Haemophilus genes required in the lung. Proc. Natl. Acad. Sci. USA 106, 16422–16427 (2009).

    Article  CAS  Google Scholar 

  13. De Jesus, D.A. et al. Analysis of Legionella infection using RNA interference in Drosophila cells. Methods Mol. Biol. 954, 251–264 (2013).

    Article  CAS  Google Scholar 

  14. Wong, S.M. et al. High-throughput insertion tracking by deep sequencing for the analysis of bacterial mutants. Methods Mol. Biol. 733, 209–222 (2011).

    Article  CAS  Google Scholar 

  15. Murry, J.P. et al. Transposon site hybridization in Mycobacterium tuberculosis. Methods Mol. Biol. 416, 45–59 (2008).

    Article  CAS  Google Scholar 

  16. Goodman, A.L. et al. Identifying microbial fitness determinants by insertion sequencing using genome-wide transposon mutant libraries. Nat. Protoc. 6, 1969–1980 (2011).

    Article  CAS  Google Scholar 

  17. Lampe, D.J. et al. A purified mariner transposase is sufficient to mediate transposition in vitro. EMBO J. 15, 5470–5479 (1996).

    Article  CAS  Google Scholar 

  18. O'Connor, T.J. et al. Minimization of the Legionella pneumophila genome reveals chromosomal regions involved in host range expansion. Proc. Natl. Acad. Sci. USA 108, 14733–14740 (2011).

    Article  CAS  Google Scholar 

  19. Chiang, S.U. et al. Construction of a mariner-based transposon for epitope-tagging and genomic targeting. Gene 296, 179–185 (2002).

    Article  CAS  Google Scholar 

  20. Crimmins, G.T. et al. Identification of MrtAB, an ABC transporter specifically required for Yersinia pseudotuberculosis to colonize the mesenteric lymph nodes. PLoS Pathog. 8, e1002828 (2012).

    Article  CAS  Google Scholar 

  21. Bassik, M.C. et al. A systematic mammalian genetic interaction map reveals pathways underlying ricin susceptibility. Cell 152, 909–922 (2013).

    Article  CAS  Google Scholar 

  22. Kim, H.S. et al. Systematic identification of molecular subtype-selective vulnerabilities in non-small-cell lung cancer. Cell 155, 552–566 (2013).

    Article  CAS  Google Scholar 

  23. Roguev, A. et al. Quantitative genetic-interaction mapping in mammalian cells. Nat. Methods 10, 432–437 (2013).

    Article  CAS  Google Scholar 

  24. Carette, J.E. et al. Haploid genetic screens in human cells identify host factors used by pathogens. Science 326, 1231–1235 (2009).

    Article  CAS  Google Scholar 

  25. Xu, M. et al. Down-regulation of ribosomal protein S15A mRNA with a short hairpin RNA inhibits human hepatic cancer cell growth in vitro. Gene 536, 84–89 (2014).

    Article  CAS  Google Scholar 

  26. Tang, F.C. et al. Stable suppression of gene expression in murine embryonic stem cells by RNAi directed from DNA vector-based short hairpin RNA. Stem Cells 22, 93–99 (2004).

    Article  CAS  Google Scholar 

  27. Livak, K.J. & Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(–ΔΔCT) method. Methods 25, 402–408 (2001).

    Article  CAS  Google Scholar 

  28. US Centers for Disease Control and Prevention. Biosafety in Microbiological and Biomedical Laboratories (BMBL), 5th edn. http://www.cdc.gov/biosafety/publications/bmbl5/ (2009).

  29. van Opijnen, T. & Camilli, A. Transposon insertion sequencing: a new tool for systems-level analysis of microorganisms. Nat. Rev. Microbiol. 11, 435–442 (2013).

    Article  CAS  Google Scholar 

  30. Drees, B.L. et al. Derivation of genetic interaction networks from quantitative phenotype data. Genome Biol. 6, R38 (2005).

    Article  Google Scholar 

  31. St. Onge, R.P. et al. Systematic pathway analysis using high-resolution fitness profiling of combinatorial gene deletions. Nat. Genet. 39, 199–206 (2007).

    Article  CAS  Google Scholar 

  32. Eisen, M.B. et al. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14863–14868 (1998).

    Article  CAS  Google Scholar 

  33. Tong, A.H. et al. Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science 294, 2364–2368 (2001).

    Article  CAS  Google Scholar 

  34. Shannon, P. Cytoscape: a software environment for integrate models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).

    Article  CAS  Google Scholar 

  35. Tong, A.H. et al. Global mapping of the yeast genetic interaction network. Science 303, 808–813 (2004).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by the Howard Hughes Medical Institute and a Natalie Zucker Fellowship to T.J.O. R.R.I. is a Howard Hughes Investigator.

Author information

Authors and Affiliations

Authors

Contributions

Both authors wrote the paper and designed the experiments. T.J.O. conducted the experiments.

Corresponding author

Correspondence to Ralph R Isberg.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

O'Connor, T., Isberg, R. iMAD, a genetic screening strategy for dissecting complex interactions between a pathogen and its host. Nat Protoc 9, 1916–1930 (2014). https://doi.org/10.1038/nprot.2014.133

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2014.133

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 Microbiology

Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research, free to your inbox weekly.

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