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Volume 11, Issue 5

Bioinformatic discovery of type 11 secretion system (T11SS) cargo across the Open Access

Graphical Abstract

Graphical Abstract

Abstract

Type 11 secretion systems (T11SS) are broadly distributed amongst , with more than 3,000 T11SS family outer membrane proteins (OMPs) comprising ten major sequence similarity network clusters. Of these, only seven, all from animal-associated cluster 1, have been experimentally verified as secretins of cargo, including adhesins, haemophores and metal-binding proteins. To identify novel cargo of a more diverse set of T11SS, we identified gene families co-occurring in gene neighbourhoods with either cluster 1 or marine microbe-associated cluster 3 T11SS OMP genes. We developed bioinformatic controls to ensure that perceived co-occurrences are specific to T11SS, and not general to OMPs. We found that both cluster 1 and cluster 3 T11SS OMPs frequently co-occur with single-carbon metabolism and nucleotide synthesis pathways, but that only cluster 1 T11SS OMPs had significant co-occurrence with metal and haem pathways, as well as with mobile genetic islands, potentially indicating the diversified function of this cluster. Cluster 1 T11SS co-occurrences included 2,556 predicted cargo proteins, unified by the presence of a C-terminal -barrel domain, which fall into 141 predicted UniRef50 clusters and approximately ten different architectures: four similar to known cargo and six uncharacterized types. We experimentally demonstrate T11SS-dependent secretion of an uncharacterized cargo type with homology to plasmin-sensitive protein. Unexpectedly, genes encoding marine cluster 3 T11SS OMPs only rarely co-occurred with the C-terminal -barrel domain and instead frequently co-occurred with DUF1194-containing genes. Overall, our results show that with sufficiently large-scale and controlled genomic data, T11SS-dependent cargo proteins can be accurately predicted.

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  • Accepted:
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Keyword(s): cargo detection , co-occurrence , DUF1194 , host association , plasmin-sensitive protein and T11SS
Funding
This study was supported by the:
  • University of Tennessee, Knoxville (Award David and Sandra White Endowment)
    • Principal Award Recipient: HeidiGoodrich-Blair
  • National Science Foundation (Award IOS-2128266)
    • Principal Award Recipient: HeidiGoodrich-Blair
© 2025 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
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2025-05-21
2026-04-14

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References

  1. Grossman AS, Mucci NC, Kauffman SJ, Rafi J, Goodrich-Blair H. Bioinformatic discovery of type 11 secretion system (T11SS) cargo across the proteobacteria supplemental data. Figshare. Online resource Epub ahead of print 5 March 2025 [View Article]
     [Google Scholar]
  2. Mistry J, Chuguransky S, Williams L, Qureshi M, Salazar GA et al. Pfam: the protein families database in 2021. Nucleic Acids Res 2021; 49:D412–D419 [View Article] [PubMed]
     [Google Scholar]
  3. Mudgal R, Sandhya S, Chandra N, Srinivasan N. De-DUFing the DUFs: deciphering distant evolutionary relationships of domains of unknown function using sensitive homology detection methods. Biol Direct 2015; 10:38 [View Article] [PubMed]
     [Google Scholar]
  4. Grossman AS, Mauer TJ, Forest KT, Goodrich-Blair H, Comstock L. A widespread bacterial secretion system with diverse substrates. mBio 2021; 12:e01956–21 [View Article]
     [Google Scholar]
  5. Huynh MS, Hooda Y, Li YR, Jagielnicki M, Lai CC-L et al. Reconstitution of surface lipoprotein translocation through the Slam translocon. elife 2022; 11:e72822 Epub ahead of print April 2022 [View Article] [PubMed]
     [Google Scholar]
  6. Shin HE, Pan C, Curran DM, Bateman TJ, Chong DHY et al. Prevalence of Slam-dependent hemophilins in Gram-negative bacteria. J Bacteriol 2024; 206:e0002724 [View Article] [PubMed]
     [Google Scholar]
  7. Hooda Y, Lai CCL, Moraes TF. Identification of a large family of Slam-dependent surface lipoproteins in Gram-negative bacteria. Front Cell Infect Microbiol 2017; 7:207 Epub ahead of print 2017 [View Article] [PubMed]
     [Google Scholar]
  8. Hooda Y, Lai CC-L, Judd A, Buckwalter CM, Shin HE et al. Slam is an outer membrane protein that is required for the surface display of lipidated virulence factors in Neisseria. Nat Microbiol 2016; 1:16009 Epub ahead of print 2016 [View Article] [PubMed]
     [Google Scholar]
  9. Cowles CE, Goodrich-Blair H. The Xenorhabdus nematophila nilABC genes confer the ability of Xenorhabdus spp. to colonize Steinernema carpocapsae nematodes. J Bacteriol 2008; 190:4121–4128 [View Article] [PubMed]
     [Google Scholar]
  10. Bateman TJ, Shah M, Ho TP, Shin HE, Pan C et al. A Slam-dependent hemophore contributes to heme acquisition in the bacterial pathogen Acinetobacter baumannii. Nat Commun 2021; 12:6270 [View Article] [PubMed]
     [Google Scholar]
  11. Latham RD, Torrado M, Atto B, Walshe JL, Wilson R et al. A heme-binding protein produced by Haemophilus haemolyticus inhibits non-typeable Haemophilus influenzae. Mol Microbiol 2020; 113:381–398 [View Article] [PubMed]
     [Google Scholar]
  12. Grossman AS, Gell DA, Wu DG, Carper DL, Hettich RL et al. Bacterial hemophilin homologs and their specific type eleven secretor proteins have conserved roles in heme capture and are diversifying as a family. J Bacteriol 2024; 206:e0044423 [View Article] [PubMed]
     [Google Scholar]
  13. Fulte S, Atto B, McCarty A, Horn KJ, Redzic JS et al. Heme sequestration by hemophilin from Haemophilus haemolyticus reduces respiratory tract colonization and infection with non-typeable Haemophilus influenzae. mSphere 2024; 9:e0000624 [View Article] [PubMed]
     [Google Scholar]
  14. Haft DH, Badretdin A, Coulouris G, DiCuccio M, Durkin AS et al. RefSeq and the prokaryotic genome annotation pipeline in the age of metagenomes. Nucleic Acids Res 2024; 52:D762–D769 [View Article] [PubMed]
     [Google Scholar]
  15. Rogozin IB, Makarova KS, Murvai J, Czabarka E, Wolf YI et al. Connected gene neighborhoods in prokaryotic genomes. Nucleic Acids Res 2002; 30:2212–2223 [View Article] [PubMed]
     [Google Scholar]
  16. Mahdavi MA, Lin Y-H. False positive reduction in protein-protein interaction predictions using gene ontology annotations. BMC Bioinf 2007; 8:262 [View Article] [PubMed]
     [Google Scholar]
  17. Tietz JI, Schwalen CJ, Patel PS, Maxson T, Blair PM et al. A new genome-mining tool redefines the lasso peptide biosynthetic landscape. Nat Chem Biol 2017; 13:470–478 [View Article] [PubMed]
     [Google Scholar]
  18. UniProt Consortium UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res 2021; 49:D480–D489 [View Article] [PubMed]
     [Google Scholar]
  19. Chen I-MA, Chu K, Palaniappan K, Ratner A, Huang J et al. The IMG/M data management and analysis system v.7: content updates and new features. Nucleic Acids Res 2023; 51:D723–D732 [View Article]
     [Google Scholar]
  20. Mukherjee S, Stamatis D, Li CT, Ovchinnikova G, Bertsch J et al. Twenty-five years of Genomes OnLine Database (GOLD): data updates and new features in v.9. Nucleic Acids Res 2023; 51:D957–D963 [View Article] [PubMed]
     [Google Scholar]
  21. Jumper J, Evans R, Pritzel A, Green T, Figurnov M et al. Highly accurate protein structure prediction with AlphaFold. Nature 2021; 596:583–589 [View Article]
     [Google Scholar]
  22. Mirdita M, Schütze K, Moriwaki Y, Heo L, Ovchinnikov S et al. ColabFold: making protein folding accessible to all. Nat Methods 2022; 19:679–682 [View Article] [PubMed]
     [Google Scholar]
  23. Abramson J, Adler J, Dunger J, Evans R, Green T et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 2024; 630:493–500 [View Article]
     [Google Scholar]
  24. Aramaki T, Blanc-Mathieu R, Endo H, Ohkubo K, Kanehisa M et al. KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold. Bioinformatics 2020; 36:2251–2252 [View Article] [PubMed]
     [Google Scholar]
  25. Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol 2016; 428:726–731 [View Article]
     [Google Scholar]
  26. Suzek BE, Huang H, McGarvey P, Mazumder R, Wu CH. UniRef: comprehensive and non-redundant UniProt reference clusters. Bioinformatics 2007; 23:1282–1288 [View Article] [PubMed]
     [Google Scholar]
  27. Buchan DWA, Jones DT. The PSIPRED protein analysis workbench: 20 years on. Nucleic Acids Res 2019; 47:W402–W407 [View Article] [PubMed]
     [Google Scholar]
  28. Bhasin A, Chaston JM, Goodrich-Blair H. Mutational analyses reveal overall topology and functional regions of NilB, a bacterial outer membrane protein required for host association in a model of animal-microbe mutualism. J Bacteriol 2012; 194:1763–1776 [View Article] [PubMed]
     [Google Scholar]
  29. Miroux B, Walker JE. Over-production of proteins in Escherichia coli: mutant hosts that allow synthesis of some membrane proteins and globular proteins at high levels. J Mol Biol 1996; 260:289–298 [View Article] [PubMed]
     [Google Scholar]
  30. Dumon-Seignovert L, Cariot G, Vuillard L. The toxicity of recombinant proteins in Escherichia coli: a comparison of overexpression in BL21(DE3), C41(DE3), and C43(DE3). Protein Expr Purif 2004; 37:203–206 [View Article] [PubMed]
     [Google Scholar]
  31. Orchard SS, Goodrich-Blair H. Identification and functional characterization of a Xenorhabdus nematophila oligopeptide permease. Appl Environ Microbiol 2004; 70:5621–5627 [View Article] [PubMed]
     [Google Scholar]
  32. Grossman AS, Escobar CA, Mans EJ, Mucci NC, Mauer TJ et al. A surface exposed, two-domain lipoprotein cargo of a type XI secretion system promotes colonization of host intestinal epithelia expressing glycans. Front Microbiol 2022; 13:800366 [View Article] [PubMed]
     [Google Scholar]
  33. Koontz L. Chapter one - TCA precipitation. In Lorsch JBT-M. eds Laboratory Methods in Enzymology Academic Press; pp 3–10 [View Article]
     [Google Scholar]
  34. Tukey JW. Comparing individual means in the analysis of variance. Biometrics 1949; 5:99–114 [PubMed]
     [Google Scholar]
  35. Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res 2017; 45:D353–D361 [View Article] [PubMed]
     [Google Scholar]
  36. Dobrindt U, Reidl J. Pathogenicity islands and phage conversion: evolutionary aspects of bacterial pathogenesis. Int J Med Microbiol 2000; 290:519–527 [View Article] [PubMed]
     [Google Scholar]
  37. Almagro Armenteros JJ, Tsirigos KD, Sønderby CK, Petersen TN, Winther O et al. SignalP 5.0 improves signal peptide predictions using deep neural networks. Nat Biotechnol 2019; 37:420–423 [View Article] [PubMed]
     [Google Scholar]
  38. Teufel F, Almagro Armenteros JJ, Johansen AR, Gíslason MH, Pihl SI et al. SignalP 6.0 predicts all five types of signal peptides using protein language models. Nat Biotechnol 2022; 40:1023–1025 [View Article] [PubMed]
     [Google Scholar]
  39. Skaf MS, Polikarpov I, Stanković IM. A linker of the proline-threonine repeating motif sequence is bimodal. J Mol Model 2020; 26:178 [View Article] [PubMed]
     [Google Scholar]
  40. Swearingen KE, Lindner SE, Shi L, Shears MJ, Harupa A et al. Interrogating the Plasmodium sporozoite surface: identification of surface-exposed proteins and demonstration of glycosylation on CSP and TRAP by mass spectrometry-based proteomics. PLoS Pathog 2016; 12:e1005606 [View Article] [PubMed]
     [Google Scholar]
  41. Sieber CMK, Paul BG, Castelle CJ, Hu P, Tringe SG et al. Unusual metabolism and hypervariation in the genome of a Gracilibacterium (BD1-5) from an oil-degrading community. mBio 2019; 10: [View Article]
     [Google Scholar]
  42. Calmettes C, Alcantara J, Yu R-H, Schryvers AB, Moraes TF. The structural basis of transferrin sequestration by transferrin-binding protein B. Nat Struct Mol Biol 2012; 19:358–360 [View Article] [PubMed]
     [Google Scholar]
  43. Ostberg KL, DeRocco AJ, Mistry SD, Dickinson MK, Cornelissen CN. Conserved regions of gonococcal TbpB are critical for surface exposure and transferrin iron utilization. Infect Immun 2013; 81:3442–3450 [View Article] [PubMed]
     [Google Scholar]
  44. Bleiziffer I, Eikmeier J, Pohlentz G, McAulay K, Xia G et al. The Plasmin-sensitive protein Pls in methicillin-resistant Staphylococcus aureus (MRSA) is a glycoprotein. PLoS Pathog 2017; 13:e1006110 [View Article] [PubMed]
     [Google Scholar]
  45. Savolainen K, Paulin L, Westerlund-Wikström B, Foster TJ, Korhonen TK et al. Expression of pls, a gene closely associated with the mecA gene of methicillin-resistant Staphylococcus aureus, prevents bacterial adhesion in vitro. Infect Immun 2001; 69:3013–3020 [View Article] [PubMed]
     [Google Scholar]
  46. Liang KYH, Orata FD, Boucher YF, Case RJ. Roseobacters in a sea of poly- and paraphyly: whole genome-based taxonomy of the family Rhodobacteraceae and the proposal for the split of the “Roseobacter Clade” into a novel family, Roseobacteraceae fam. nov. Front Microbiol 2021; 12:683109 Epub ahead of print 2021 [View Article] [PubMed]
     [Google Scholar]
  47. Crenn K, Serpin D, Lepleux C, Overmann J, Jeanthon C. Silicimonas algicola gen. nov., sp. nov., a member of the Roseobacter clade isolated from the cell surface of the marine diatom Thalassiosira delicatula. Int J Syst Evol Microbiol 2016; 66:4580–4588 [View Article] [PubMed]
     [Google Scholar]
  48. Kessner L, Spinard E, Gomez-Chiarri M, Rowley DC, Nelson DR. Draft genome sequence of Aliiroseovarius crassostreae CV919-312, the causative agent of Roseovarius Oyster Disease (formerly Juvenile Oyster Disease). Genome Announc 2016; 4:e00148-16 Epub ahead of print March 2016 [View Article] [PubMed]
     [Google Scholar]
  49. Kim Y-O, Park S, Nam B-H, Lee C, Park J-M et al. Ascidiaceihabitans donghaensis gen. nov., sp. nov., isolated from the golden sea squirt Halocynthia aurantium. Int J Syst Evol Microbiol 2014; 64:3970–3975 [View Article] [PubMed]
     [Google Scholar]
  50. Ivanova EP, Gorshkova NM, Sawabe T, Zhukova NV, Hayashi K et al. Sulfitobacter delicatus sp. nov. and Sulfitobacter dubius sp. nov., respectively from a starfish (Stellaster equestris) and sea grass (Zostera marina). Int J Syst Evol Microbiol 2004; 54:475–480 [View Article] [PubMed]
     [Google Scholar]
  51. Chen M-H, Sheu S-Y, Chen CA, Wang J-T, Chen W-M. Roseivivax isoporae sp. nov., isolated from a reef-building coral, and emended description of the genus Roseivivax. Int J Syst Evol Microbiol 2012; 62:1259–1264 [View Article] [PubMed]
     [Google Scholar]
  52. Alamos P, Tello M, Bustamante P, Gutiérrez F, Shmaryahu A et al. Functionality of tRNAs encoded in a mobile genetic element from an acidophilic bacterium. RNA Biol 2018; 15:518–527 [View Article] [PubMed]
     [Google Scholar]
  53. Baek M, DiMaio F, Anishchenko I, Dauparas J, Ovchinnikov S et al. Accurate prediction of protein structures and interactions using a three-track neural network. Science 2021; 373:871–876 [View Article]
     [Google Scholar]
  54. Bergelson JM, Hemler ME. Integrin-ligand binding. Do integrins use a “MIDAS touch” to grasp an Asp?. Curr Biol 1995; 5:615–617 [View Article] [PubMed]
     [Google Scholar]
  55. Cantí C, Nieto-Rostro M, Foucault I, Heblich F, Wratten J et al. The metal-ion-dependent adhesion site in the Von Willebrand factor-A domain of alpha2delta subunits is key to trafficking voltage-gated Ca2+ channels. Proc Natl Acad Sci USA 2005; 102:11230–11235 [View Article] [PubMed]
     [Google Scholar]
  56. Esch R, Merkl R. Conserved genomic neighborhood is a strong but no perfect indicator for a direct interaction of microbial gene products. BMC Bioinf 2020; 21:5 [View Article] [PubMed]
     [Google Scholar]
  57. Hantke K. Is the bacterial ferrous iron transporter FeoB a living fossil?. Trends Microbiol 2003; 11:192–195 [View Article] [PubMed]
     [Google Scholar]
  58. Ollis AA, Postle K. ExbD mutants define initial stages in TonB energization. J Mol Biol 2012; 415:237–247 [View Article] [PubMed]
     [Google Scholar]
  59. Levengood SK, Beyer WFJ, Webster RE. TolA: a membrane protein involved in colicin uptake contains an extended helical region. Proc Natl Acad Sci USA 1991; 88:5939–5943 [View Article] [PubMed]
     [Google Scholar]
  60. Tjalsma H, Kontinen VP, Prágai Z, Wu H, Meima R et al. The role of lipoprotein processing by signal peptidase II in the Gram-positive eubacterium Bacillus subtilis. Signal peptidase II is required for the efficient secretion of alpha-amylase, a non-lipoprotein. J Biol Chem 1999; 274:1698–1707 [View Article] [PubMed]
     [Google Scholar]
  61. Agrawal N, Lesley SA, Kuhn P, Kohen A. Mechanistic studies of a flavin-dependent thymidylate synthase. Biochemistry 2004; 43:10295–10301 [View Article]
     [Google Scholar]
  62. Dawadi S, Kordus SL, Baughn AD, Aldrich CC. Synthesis and analysis of bacterial folate metabolism intermediates and antifolates. Org Lett 2017; 19:5220–5223 [View Article] [PubMed]
     [Google Scholar]
  63. Luk LYP, Javier Ruiz-Pernía J, Dawson WM, Roca M, Loveridge EJ et al. Unraveling the role of protein dynamics in dihydrofolate reductase catalysis. Proc Natl Acad Sci USA 2013; 110:16344–16349 [View Article]
     [Google Scholar]
  64. Mendel RR. The molybdenum cofactor. J Biol Chem 2013; 288:13165–13172 [View Article]
     [Google Scholar]
  65. Zhong Q, Kobe B, Kappler U. Molybdenum enzymes and how they support virulence in pathogenic bacteria. Front Microbiol 2020; 11:615860 [View Article] [PubMed]
     [Google Scholar]
  66. Van Bibber M, Bradbeer C, Clark N, Roth JR. A new class of cobalamin transport mutants (btuF) provides genetic evidence for A periplasmic binding protein in Salmonella typhimurium. J Bacteriol 1999; 181:5539–5541 [View Article] [PubMed]
     [Google Scholar]
  67. Peyvandi F, Garagiola I, Baronciani L. Role of von willebrand factor in the haemostasis. Blood Transfus 2011; 9 Suppl 2:s3–8 [View Article] [PubMed]
     [Google Scholar]
  68. Willebrand EAV. Hereditary pseudohaemophilia. Haemophilia 1999; 5:223–231 [View Article]
     [Google Scholar]
  69. Islam ST, Jolivet NY, Cuzin C, Belgrave AM, My L et al. Unmasking of the von Willebrand A-domain surface adhesin CglB at bacterial focal adhesions mediates myxobacterial gliding motility. Sci Adv 2023; 9:eabq0619 [View Article]
     [Google Scholar]
  70. Aravind L, Iyer LM, Burroughs AM. Discovering biological conflict systems through genome analysis: evolutionary principles and biochemical novelty. Annu Rev Biomed Data Sci 2022; 5:367–391 [View Article] [PubMed]
     [Google Scholar]
  71. Kaur G, Burroughs AM, Iyer LM, Aravind L. Highly regulated, diversifying NTP-dependent biological conflict systems with implications for the emergence of multicellularity. elife 2020; 9:e52696 [View Article] [PubMed]
     [Google Scholar]
  72. Lee C, Park C. Bacterial responses to glyoxal and methylglyoxal: reactive electrophilic species. Int J Mol Sci 2017; 18:169 Epub ahead of print January 2017 [View Article] [PubMed]
     [Google Scholar]
  73. Anaya-Sanchez A, Feng Y, Berude JC, Portnoy DA. Detoxification of methylglyoxal by the glyoxalase system is required for glutathione availability and virulence activation in Listeria monocytogenes. PLoS Pathog 2021; 17:e1009819 [View Article] [PubMed]
     [Google Scholar]
  74. Cao Y, Gao L, Zhang L, Zhou L, Yang J et al. Genome-wide screening of lipoproteins in Actinobacillus pleuropneumoniae identifies three antigens that confer protection against virulent challenge. Sci Rep 2020; 10:2343 [View Article] [PubMed]
     [Google Scholar]
  75. Schmidt MA, Riley LW, Benz I. Sweet new world: glycoproteins in bacterial pathogens. Trends Microbiol 2003; 11:554–561 [View Article]
     [Google Scholar]
  76. Tortorelli G, Rautengarten C, Bacic A, Segal G, Ebert B et al. Cell surface carbohydrates of symbiotic dinoflagellates and their role in the establishment of cnidarian-dinoflagellate symbiosis. ISME J 2022; 16:190–199 [View Article] [PubMed]
     [Google Scholar]
  77. Zhou M, Wu H. Glycosylation and biogenesis of a family of serine-rich bacterial adhesins. Microbiology 2009; 155:317–327 [View Article]
     [Google Scholar]
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Bioinformatic discovery of type 11 secretion system (T11SS) cargo across the Proteobacteria
M Gen 11, 001406 (2025); https://doi.org/10.1099/mgen.0.001406
/content/journal/mgen/10.1099/mgen.0.001406
/content/journal/mgen/10.1099/mgen.0.001406
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