Global atlas of predicted functional domains in Legionella pneumophila Dot/Icm translocated effectors

Legionella pneumophila utilizes the Dot/Icm type IVB secretion system to deliver hundreds of effector proteins inside eukaryotic cells to ensure intracellular replication. Our understanding of the molecular functions of the largest pathogenic arsenal known to the bacterial world remains incomplete....

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Veröffentlicht in:Molecular systems biology 2025-01, Vol.21 (1), p.59-89
Hauptverfasser: Patel, Deepak T, Stogios, Peter J, Jaroszewski, Lukasz, Urbanus, Malene L, Sedova, Mayya, Semper, Cameron, Le, Cathy, Takkouche, Abraham, Ichii, Keita, Innabi, Julie, Patel, Dhruvin H, Ensminger, Alexander W, Godzik, Adam, Savchenko, Alexei
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container_end_page 89
container_issue 1
container_start_page 59
container_title Molecular systems biology
container_volume 21
creator Patel, Deepak T
Stogios, Peter J
Jaroszewski, Lukasz
Urbanus, Malene L
Sedova, Mayya
Semper, Cameron
Le, Cathy
Takkouche, Abraham
Ichii, Keita
Innabi, Julie
Patel, Dhruvin H
Ensminger, Alexander W
Godzik, Adam
Savchenko, Alexei
description Legionella pneumophila utilizes the Dot/Icm type IVB secretion system to deliver hundreds of effector proteins inside eukaryotic cells to ensure intracellular replication. Our understanding of the molecular functions of the largest pathogenic arsenal known to the bacterial world remains incomplete. By leveraging advancements in 3D protein structure prediction, we provide a comprehensive structural analysis of 368  L. pneumophila effectors, representing a global atlas of predicted functional domains summarized in a database ( https://pathogens3d.org/legionella-pneumophila ). Our analysis identified 157 types of diverse functional domains in 287 effectors, including 159 effectors with no prior functional annotations. Furthermore, we identified 35 cryptic domains in 30 effector models that have no similarity with experimentally structurally characterized proteins, thus, hinting at novel functionalities. Using this analysis, we demonstrate the activity of thirteen functional domains, including three cryptic domains, predicted in L. pneumophila effectors to cause growth defects in the Saccharomyces cerevisiae model system. This illustrates an emerging strategy of exploring synergies between predictions and targeted experimental approaches in elucidating novel effector activities involved in infection. Synopsis Legionella pneumophila encodes the largest arsenal of eukaryotic host-manipulating proteins, called effectors. Leveraging high-throughput structural prediction tools, coupled with in cellulo assays, revealed previously unrecognized functional and cryptic domains in L. pneumophila effectors. Analysis revealed over 150 structurally diverse domains in 287 effectors, reflective of the diverse mechanisms required to modulate L. pneumophila ’s eukaryotic hosts ranging from protozoa to human alveolar macrophages. Over half of the predicted functional domains are present in only one effector, while cysteine proteases and kinases are the most prominent domain categories. An even larger presence of so-called tandem repeat structural motifs in effector proteins is suggested to facilitate protein-protein interactions. Over 30 identified domains, some of which are present in other pathogens, showed no structural similarity with characterized proteins, suggestive of novel biochemical activities. Legionella pneumophila encodes the largest arsenal of eukaryotic host-manipulating proteins, called effectors. Leveraging high-throughput structural prediction tools, coupled w
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Our understanding of the molecular functions of the largest pathogenic arsenal known to the bacterial world remains incomplete. By leveraging advancements in 3D protein structure prediction, we provide a comprehensive structural analysis of 368  L. pneumophila effectors, representing a global atlas of predicted functional domains summarized in a database ( https://pathogens3d.org/legionella-pneumophila ). Our analysis identified 157 types of diverse functional domains in 287 effectors, including 159 effectors with no prior functional annotations. Furthermore, we identified 35 cryptic domains in 30 effector models that have no similarity with experimentally structurally characterized proteins, thus, hinting at novel functionalities. Using this analysis, we demonstrate the activity of thirteen functional domains, including three cryptic domains, predicted in L. pneumophila effectors to cause growth defects in the Saccharomyces cerevisiae model system. This illustrates an emerging strategy of exploring synergies between predictions and targeted experimental approaches in elucidating novel effector activities involved in infection. Synopsis Legionella pneumophila encodes the largest arsenal of eukaryotic host-manipulating proteins, called effectors. Leveraging high-throughput structural prediction tools, coupled with in cellulo assays, revealed previously unrecognized functional and cryptic domains in L. pneumophila effectors. Analysis revealed over 150 structurally diverse domains in 287 effectors, reflective of the diverse mechanisms required to modulate L. pneumophila ’s eukaryotic hosts ranging from protozoa to human alveolar macrophages. Over half of the predicted functional domains are present in only one effector, while cysteine proteases and kinases are the most prominent domain categories. An even larger presence of so-called tandem repeat structural motifs in effector proteins is suggested to facilitate protein-protein interactions. Over 30 identified domains, some of which are present in other pathogens, showed no structural similarity with characterized proteins, suggestive of novel biochemical activities. Legionella pneumophila encodes the largest arsenal of eukaryotic host-manipulating proteins, called effectors. 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Our understanding of the molecular functions of the largest pathogenic arsenal known to the bacterial world remains incomplete. By leveraging advancements in 3D protein structure prediction, we provide a comprehensive structural analysis of 368  L. pneumophila effectors, representing a global atlas of predicted functional domains summarized in a database ( https://pathogens3d.org/legionella-pneumophila ). Our analysis identified 157 types of diverse functional domains in 287 effectors, including 159 effectors with no prior functional annotations. Furthermore, we identified 35 cryptic domains in 30 effector models that have no similarity with experimentally structurally characterized proteins, thus, hinting at novel functionalities. Using this analysis, we demonstrate the activity of thirteen functional domains, including three cryptic domains, predicted in L. pneumophila effectors to cause growth defects in the Saccharomyces cerevisiae model system. This illustrates an emerging strategy of exploring synergies between predictions and targeted experimental approaches in elucidating novel effector activities involved in infection. Synopsis Legionella pneumophila encodes the largest arsenal of eukaryotic host-manipulating proteins, called effectors. Leveraging high-throughput structural prediction tools, coupled with in cellulo assays, revealed previously unrecognized functional and cryptic domains in L. pneumophila effectors. Analysis revealed over 150 structurally diverse domains in 287 effectors, reflective of the diverse mechanisms required to modulate L. pneumophila ’s eukaryotic hosts ranging from protozoa to human alveolar macrophages. Over half of the predicted functional domains are present in only one effector, while cysteine proteases and kinases are the most prominent domain categories. An even larger presence of so-called tandem repeat structural motifs in effector proteins is suggested to facilitate protein-protein interactions. Over 30 identified domains, some of which are present in other pathogens, showed no structural similarity with characterized proteins, suggestive of novel biochemical activities. Legionella pneumophila encodes the largest arsenal of eukaryotic host-manipulating proteins, called effectors. 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Our understanding of the molecular functions of the largest pathogenic arsenal known to the bacterial world remains incomplete. By leveraging advancements in 3D protein structure prediction, we provide a comprehensive structural analysis of 368  L. pneumophila effectors, representing a global atlas of predicted functional domains summarized in a database ( https://pathogens3d.org/legionella-pneumophila ). Our analysis identified 157 types of diverse functional domains in 287 effectors, including 159 effectors with no prior functional annotations. Furthermore, we identified 35 cryptic domains in 30 effector models that have no similarity with experimentally structurally characterized proteins, thus, hinting at novel functionalities. Using this analysis, we demonstrate the activity of thirteen functional domains, including three cryptic domains, predicted in L. pneumophila effectors to cause growth defects in the Saccharomyces cerevisiae model system. This illustrates an emerging strategy of exploring synergies between predictions and targeted experimental approaches in elucidating novel effector activities involved in infection. Synopsis Legionella pneumophila encodes the largest arsenal of eukaryotic host-manipulating proteins, called effectors. Leveraging high-throughput structural prediction tools, coupled with in cellulo assays, revealed previously unrecognized functional and cryptic domains in L. pneumophila effectors. Analysis revealed over 150 structurally diverse domains in 287 effectors, reflective of the diverse mechanisms required to modulate L. pneumophila ’s eukaryotic hosts ranging from protozoa to human alveolar macrophages. Over half of the predicted functional domains are present in only one effector, while cysteine proteases and kinases are the most prominent domain categories. An even larger presence of so-called tandem repeat structural motifs in effector proteins is suggested to facilitate protein-protein interactions. Over 30 identified domains, some of which are present in other pathogens, showed no structural similarity with characterized proteins, suggestive of novel biochemical activities. Legionella pneumophila encodes the largest arsenal of eukaryotic host-manipulating proteins, called effectors. 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subjects Bacterial Effectors
Bacterial Proteins - chemistry
Bacterial Proteins - genetics
Bacterial Proteins - metabolism
Biomedical and Life Sciences
Cryptic Domains
EMBO10
EMBO23
EMBO40
Legionella pneumophila
Legionella pneumophila - genetics
Legionella pneumophila - metabolism
Life Sciences
Protein Domains
Protein Modeling
Saccharomyces cerevisiae - genetics
Saccharomyces cerevisiae - metabolism
Systems Biology
Type IV Secretion Systems - genetics
Type IV Secretion Systems - metabolism
Yeast Toxicity
title Global atlas of predicted functional domains in Legionella pneumophila Dot/Icm translocated effectors
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