Type III secretion system effectors form robust and flexible intracellular virulence networks

Infections with many Gram-negative pathogens, including , , , and , rely on type III secretion system (T3SS) effectors. We hypothesized that while hijacking processes within mammalian cells, the effectors operate as a robust network that can tolerate substantial contractions. This was tested in vivo...

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Veröffentlicht in:Science (American Association for the Advancement of Science) Jg. 371; H. 6534
Hauptverfasser: Ruano-Gallego, David, Sanchez-Garrido, Julia, Kozik, Zuzanna, Núñez-Berrueco, Elena, Cepeda-Molero, Massiel, Mullineaux-Sanders, Caroline, Naemi Baghshomali, Yasaman, Slater, Sabrina L, Wagner, Naama, Glegola-Madejska, Izabela, Roumeliotis, Theodoros I, Pupko, Tal, Fernández, Luis Ángel, Rodríguez-Patón, Alfonso, Choudhary, Jyoti S, Frankel, Gad
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 12.03.2021
Schlagworte:
Animals
Bacterial Proteins - genetics
Bacterial Proteins - metabolism
Citrobacter rodentium - genetics
Citrobacter rodentium - pathogenicity
Enterobacteriaceae Infections - immunology
Enterobacteriaceae Infections - microbiology
Female
Gene Deletion
Immunity
Metabolic Networks and Pathways
Mice
Mice, Inbred C57BL
Proteolysis
Type III Secretion Systems - genetics
Type III Secretion Systems - metabolism
Virulence
ISSN:1095-9203, 1095-9203
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Zusammenfassung:Infections with many Gram-negative pathogens, including , , , and , rely on type III secretion system (T3SS) effectors. We hypothesized that while hijacking processes within mammalian cells, the effectors operate as a robust network that can tolerate substantial contractions. This was tested in vivo using the mouse pathogen (encoding 31 effectors). Sequential gene deletions showed that effector essentiality for infection was context dependent and that the network could tolerate 60% contraction while maintaining pathogenicity. Despite inducing very different colonic cytokine profiles (e.g., interleukin-22, interleukin-17, interferon-γ, or granulocyte-macrophage colony-stimulating factor), different networks induced protective immunity. Using data from >100 distinct mutant combinations, we built and trained a machine learning model able to predict colonization outcomes, which were confirmed experimentally. Furthermore, reproducing the human-restricted enteropathogenic effector repertoire in was not sufficient for efficient colonization, which implicates effector networks in host adaptation. These results unveil the extreme robustness of both T3SS effector networks and host responses.
Bibliographie:ObjectType-Article-1
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ISSN:1095-9203
1095-9203
DOI:10.1126/science.abc9531