Skip to main content

Identification of Protein Secretion Systems in Bacterial Genomes Using MacSyFinder

  • Protocol
  • First Online:
Bacterial Protein Secretion Systems

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1615))

Abstract

Protein secretion systems are complex molecular machineries that translocate proteins through the outer membrane, and sometimes through multiple other barriers. They have evolved by co-option of components from other envelope-associated cellular machineries, making them sometimes difficult to identify and discriminate. Here, we describe how to identify protein secretion systems in bacterial genomes using MacSyFinder. This flexible computational tool uses the knowledge stemming from experimental studies to identify homologous systems in genome data. It can be used with a set of predefined models—“TXSScan”—to identify all major secretion systems of diderm bacteria (i.e., with inner and with LPS-containing outer membranes). For this, it identifies and clusters colocalized components of secretion systems using sequence similarity searches with hidden Markov model protein profiles. Finally, it checks whether the genetic content and organization of clusters satisfy the constraints of the model. TXSScan models can be customized to search for variants of known systems. The models can also be built from scratch to identify novel systems. In this chapter, we describe a complete pipeline of analysis, including the identification of a reference set of experimentally studied systems, the identification of components and the construction of their protein profiles, the definition of the models, their optimization, and, finally, their use as tools to search genomic data.

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

Access this chapter

Institutional subscriptions

References

  1. Kanonenberg K, Schwarz CK, Schmitt L (2013) Type I secretion systems—a story of appendices. Res Microbiol 164(6):596–604

    Article  CAS  PubMed  Google Scholar 

  2. Campos M, Cisneros DA, Nivaskumar M, Francetic O (2013) The type II secretion system—a dynamic fiber assembly nanomachine. Res Microbiol 164(6):545–555

    Article  CAS  PubMed  Google Scholar 

  3. Korotkov KV, Sandkvist M, Hol WG (2012) The type II secretion system: biogenesis, molecular architecture and mechanism. Nat Rev Microbiol 10(5):336–351

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Galan JE, Lara-Tejero M, Marlovits TC, Wagner S (2014) Bacterial type III secretion systems: specialized nanomachines for protein delivery into target cells. Annu Rev Microbiol 68:415–438

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Alvarez-Martinez CE, Christie PJ (2009) Biological diversity of prokaryotic type IV secretion systems. Microbiol Mol Biol Rev 73:775–808

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. van Ulsen P, Rahman S, Jong WS, Daleke-Schermerhorn MH, Luirink J (2014) Type V secretion: from biogenesis to biotechnology. Biochim Biophys Acta 1843(8):1592–1611

    Article  CAS  PubMed  Google Scholar 

  7. Zoued A, Brunet YR, Durand E, Aschtgen MS, Logger L, Douzi B, Journet L, Cambillau C, Cascales E (2014) Architecture and assembly of the Type VI secretion system. Biochim Biophys Acta 1843(8):1664–1673

    Article  CAS  PubMed  Google Scholar 

  8. McBride MJ, Nakane D (2015) Flavobacterium gliding motility and the type IX secretion system. Curr Opin Microbiol 28:72–77

    Article  CAS  PubMed  Google Scholar 

  9. Abby SS, Cury J, Guglielmini J, Néron B, Touchon M, Rocha EPC (2016) Identification of protein secretion systems in bacterial genomes. Sci Rep 6:23080

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Ginocchio CC, Olmsted SB, Wells CL, Galan JE (1994) Contact with epithelial cells induces the formation of surface appendages on Salmonella typhimurium. Cell 76(4):717–724

    Article  CAS  PubMed  Google Scholar 

  11. Peabody CR, Chung YJ, Yen MR, Vidal-Ingigliardi D, Pugsley AP, Saier MH Jr (2003) Type II protein secretion and its relationship to bacterial type IV pili and archaeal flagella. Microbiology 149(Pt 11):3051–3072

    Article  CAS  PubMed  Google Scholar 

  12. Abby SS, Rocha EP (2012) The non-flagellar type III secretion system evolved from the bacterial flagellum and diversified into host-cell adapted systems. PLoS Genet 8(9):e1002983

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Holland IB, Schmitt L, Young J (2005) Type 1 protein secretion in bacteria, the ABC-transporter dependent pathway. Mol Membr Biol 22(1–2):29–39

    Article  CAS  PubMed  Google Scholar 

  14. Paulsen IT, Park JH, Choi PS, Saier MH Jr (1997) A family of gram-negative bacterial outer membrane factors that function in the export of proteins, carbohydrates, drugs and heavy metals from gram-negative bacteria. FEMS Microbiol Lett 156(1):1–8

    Article  CAS  PubMed  Google Scholar 

  15. Abby SS, Neron B, Menager H, Touchon M, Rocha EP (2014) MacSyFinder: a program to mine genomes for molecular systems with an application to CRISPR-Cas systems. PLoS One 9(10):e110726

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Christie PJ (2004) Type IV secretion: the Agrobacterium VirB/D4 and related conjugation systems. Biochim Biophys Acta 1694(1–3):219–234

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Franco IS, Shuman HA, Charpentier X (2009) The perplexing functions and surprising origins of Legionella pneumophila type IV secretion effectors. Cell Microbiol 11(10):1435–1443

    Article  CAS  PubMed  Google Scholar 

  18. Gillespie JJ, Brayton KA, Williams KP, Diaz MA, Brown WC, Azad AF, Sobral BW (2010) Phylogenomics reveals a diverse Rickettsiales type IV secretion system. Infect Immun 78(5):1809–1823

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL (2009) BLAST+: architecture and applications. BMC Bioinformatics 10:421

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Eddy SR (2011) Accelerated profile HMM searches. PLoS Comput Biol 7(10):e1002195

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Katoh K, Toh H (2010) Parallelization of the MAFFT multiple sequence alignment program. Bioinformatics 26(15):1899–1900

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Gouy M, Guindon S, Gascuel O (2010) SeaView version 4: a multiplatform graphical user interface for sequence alignment and phylogenetic tree building. Mol Biol Evol 27(2):221–224

    Article  CAS  PubMed  Google Scholar 

  24. Waterhouse AM, Procter JB, Martin DM, Clamp M, Barton GJ (2009) Jalview Version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics 25(9):1189–1191

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Miele V, Penel S, Duret L (2011) Ultra-fast sequence clustering from similarity networks with SiLiX. BMC Bioinformatics 12:116

    Article  PubMed  PubMed Central  Google Scholar 

  26. Enright AJ, Van Dongen S, Ouzounis CA (2002) An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res 30(7):1575–1584

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Mitchell A, Chang HY, Daugherty L, Fraser M, Hunter S, Lopez R, McAnulla C, McMenamin C, Nuka G, Pesseat S, Sangrador-Vegas A, Scheremetjew M, Rato C, Yong SY, Bateman A, Punta M, Attwood TK, Sigrist CJ, Redaschi N, Rivoire C, Xenarios I, Kahn D, Guyot D, Bork P, Letunic I, Gough J, Oates M, Haft D, Huang H, Natale DA, Wu CH, Orengo C, Sillitoe I, Mi H, Thomas PD, Finn RD (2015) The InterPro protein families database: the classification resource after 15 years. Nucleic Acids Res 43(Database issue):D213–D221

    Article  PubMed  Google Scholar 

  28. Shrivastava A, Johnston JJ, van Baaren JM, McBride MJ (2013) Flavobacterium johnsoniae GldK, GldL, GldM, and SprA are required for secretion of the cell surface gliding motility adhesins SprB and RemA. J Bacteriol 195(14):3201–3212

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. McBride MJ, Zhu Y (2013) Gliding motility and Por secretion system genes are widespread among members of the phylum Bacteroidetes. J Bacteriol 195(2):270–278

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Zhu Y, McBride MJ (2014) Deletion of the Cytophaga hutchinsonii type IX secretion system gene sprP results in defects in gliding motility and cellulose utilization. Appl Microbiol Biotechnol 98(2):763–775

    Article  CAS  PubMed  Google Scholar 

  31. Kharade SS, McBride MJ (2015) Flavobacterium johnsoniae PorV is required for secretion of a subset of proteins targeted to the type IX secretion system. J Bacteriol 197(1):147–158

    Article  CAS  PubMed  Google Scholar 

  32. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215:403–410

    Article  CAS  Google Scholar 

  33. Boyer F, Fichant G, Berthod J, Vandenbrouck Y, Attree I (2009) Dissecting the bacterial type VI secretion system by a genome wide in silico analysis: what can be learned from available microbial genomic resources? BMC Genomics 10:104

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Finn RD, Tate J, Mistry J, Coggill PC, Sammut SJ, Hotz HR, Ceric G, Forslund K, Eddy SR, Sonnhammer EL, Bateman A (2008) The Pfam protein families database. Nucleic Acids Res 36(Database issue):D281–D288

    PubMed  CAS  Google Scholar 

  35. Haft DH, Selengut JD, Richter RA, Harkins D, Basu MK, Beck E (2013) TIGRFAMs and Genome Properties in 2013. Nucleic Acids Res 41(Database issue):D387–D395

    PubMed  CAS  Google Scholar 

  36. Quevillon E, Silventoinen V, Pillai S, Harte N, Mulder N, Apweiler R, Lopez R (2005) InterProScan: protein domains identifier. Nucleic Acids Res 33(Web Server issue):W116–W120

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sophie S. Abby .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media LLC

About this protocol

Cite this protocol

Abby, S.S., Rocha, E.P.C. (2017). Identification of Protein Secretion Systems in Bacterial Genomes Using MacSyFinder. In: Journet, L., Cascales, E. (eds) Bacterial Protein Secretion Systems. Methods in Molecular Biology, vol 1615. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7033-9_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-7033-9_1

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7031-5

  • Online ISBN: 978-1-4939-7033-9

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics