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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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 |
doi_str_mv | 10.1038/s44320-024-00076-z |
format | Article |
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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 with
in cellulo
assays, revealed previously unrecognized functional and cryptic domains in
L. pneumophila
effectors.</description><identifier>ISSN: 1744-4292</identifier><identifier>EISSN: 1744-4292</identifier><identifier>DOI: 10.1038/s44320-024-00076-z</identifier><identifier>PMID: 39562741</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>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</subject><ispartof>Molecular systems biology, 2025-01, Vol.21 (1), p.59-89</ispartof><rights>The Author(s) 2024</rights><rights>2024. The Author(s).</rights><rights>The Author(s) 2024 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c350t-86caecdc2c950da2372732d9c303b85034d796334940a47d23ecf77b57a298133</cites><orcidid>0000-0002-5256-9237 ; 0000-0003-0824-3704 ; 0009-0008-7885-7940 ; 0009-0002-1839-4282 ; 0009-0008-0850-3805 ; 0000-0003-3318-6270 ; 0000-0002-2425-852X ; 0000-0002-1121-2661 ; 0009-0007-3997-0265</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11696984/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11696984/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,27901,27902,41096,42165,51551,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39562741$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Patel, Deepak T</creatorcontrib><creatorcontrib>Stogios, Peter J</creatorcontrib><creatorcontrib>Jaroszewski, Lukasz</creatorcontrib><creatorcontrib>Urbanus, Malene L</creatorcontrib><creatorcontrib>Sedova, Mayya</creatorcontrib><creatorcontrib>Semper, Cameron</creatorcontrib><creatorcontrib>Le, Cathy</creatorcontrib><creatorcontrib>Takkouche, Abraham</creatorcontrib><creatorcontrib>Ichii, Keita</creatorcontrib><creatorcontrib>Innabi, Julie</creatorcontrib><creatorcontrib>Patel, Dhruvin H</creatorcontrib><creatorcontrib>Ensminger, Alexander W</creatorcontrib><creatorcontrib>Godzik, Adam</creatorcontrib><creatorcontrib>Savchenko, Alexei</creatorcontrib><title>Global atlas of predicted functional domains in Legionella pneumophila Dot/Icm translocated effectors</title><title>Molecular systems biology</title><addtitle>Mol Syst Biol</addtitle><addtitle>Mol Syst Biol</addtitle><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 with
in cellulo
assays, revealed previously unrecognized functional and cryptic domains in
L. pneumophila
effectors.</description><subject>Bacterial Effectors</subject><subject>Bacterial Proteins - chemistry</subject><subject>Bacterial Proteins - genetics</subject><subject>Bacterial Proteins - metabolism</subject><subject>Biomedical and Life Sciences</subject><subject>Cryptic Domains</subject><subject>EMBO10</subject><subject>EMBO23</subject><subject>EMBO40</subject><subject>Legionella pneumophila</subject><subject>Legionella pneumophila - genetics</subject><subject>Legionella pneumophila - metabolism</subject><subject>Life Sciences</subject><subject>Protein Domains</subject><subject>Protein Modeling</subject><subject>Saccharomyces cerevisiae - genetics</subject><subject>Saccharomyces cerevisiae - metabolism</subject><subject>Systems Biology</subject><subject>Type IV Secretion Systems - genetics</subject><subject>Type IV Secretion Systems - metabolism</subject><subject>Yeast Toxicity</subject><issn>1744-4292</issn><issn>1744-4292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>DOA</sourceid><recordid>eNp9kU1v1DAQhi0EomXhD3BAOXJJ66_Y8QmhQtuVVuLSni3Hnmy9SuxgJ0j01-NtStVeKlnyaOadZ8Z-EfpM8BnBrD3PnDOKa0x5jTGWor5_g06J5LzmVNG3z-IT9CHnAy5NpKXv0QlTjaCSk1MEV0PszFCZeTC5in01JXDezuCqfgl29jGUqouj8SFXPlQ72JccDIOppgDLGKc7X-IfcT7f2rGakwl5iNYcCdD3YOeY8kf0rjdDhk-P9wbdXv68ubiud7-uthffd7VlDZ7rVlgD1llqVYOdoUxSyahTlmHWtQ1m3EklGOOKY8OlowxsL2XXSENVSxjboO3KddEc9JT8aNJfHY3XD4mY9tqk2dsBNOW8cVISIozgquOt4h1RCrgRjYAya4O-raxp6UZwFkJ52_AC-rIS_J3exz-6IJVQLS-Er4-EFH8vkGc9-myPXxcgLlkzwnBbjpBFSlepTTHnBP3THIL10Wy9mq2L2frBbH1fmr483_Cp5b-7RcBWQS6lsIekD3FJxdD8GvYfIF-2IA</recordid><startdate>20250102</startdate><enddate>20250102</enddate><creator>Patel, Deepak T</creator><creator>Stogios, Peter J</creator><creator>Jaroszewski, Lukasz</creator><creator>Urbanus, Malene L</creator><creator>Sedova, Mayya</creator><creator>Semper, Cameron</creator><creator>Le, Cathy</creator><creator>Takkouche, Abraham</creator><creator>Ichii, Keita</creator><creator>Innabi, Julie</creator><creator>Patel, Dhruvin H</creator><creator>Ensminger, Alexander W</creator><creator>Godzik, Adam</creator><creator>Savchenko, Alexei</creator><general>Nature Publishing Group UK</general><general>Springer Nature</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-5256-9237</orcidid><orcidid>https://orcid.org/0000-0003-0824-3704</orcidid><orcidid>https://orcid.org/0009-0008-7885-7940</orcidid><orcidid>https://orcid.org/0009-0002-1839-4282</orcidid><orcidid>https://orcid.org/0009-0008-0850-3805</orcidid><orcidid>https://orcid.org/0000-0003-3318-6270</orcidid><orcidid>https://orcid.org/0000-0002-2425-852X</orcidid><orcidid>https://orcid.org/0000-0002-1121-2661</orcidid><orcidid>https://orcid.org/0009-0007-3997-0265</orcidid></search><sort><creationdate>20250102</creationdate><title>Global atlas of predicted functional domains in Legionella pneumophila Dot/Icm translocated effectors</title><author>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</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c350t-86caecdc2c950da2372732d9c303b85034d796334940a47d23ecf77b57a298133</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>Bacterial Effectors</topic><topic>Bacterial Proteins - chemistry</topic><topic>Bacterial Proteins - genetics</topic><topic>Bacterial Proteins - metabolism</topic><topic>Biomedical and Life Sciences</topic><topic>Cryptic Domains</topic><topic>EMBO10</topic><topic>EMBO23</topic><topic>EMBO40</topic><topic>Legionella pneumophila</topic><topic>Legionella pneumophila - genetics</topic><topic>Legionella pneumophila - metabolism</topic><topic>Life Sciences</topic><topic>Protein Domains</topic><topic>Protein Modeling</topic><topic>Saccharomyces cerevisiae - genetics</topic><topic>Saccharomyces cerevisiae - metabolism</topic><topic>Systems Biology</topic><topic>Type IV Secretion Systems - genetics</topic><topic>Type IV Secretion Systems - metabolism</topic><topic>Yeast Toxicity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Patel, Deepak T</creatorcontrib><creatorcontrib>Stogios, Peter J</creatorcontrib><creatorcontrib>Jaroszewski, Lukasz</creatorcontrib><creatorcontrib>Urbanus, Malene L</creatorcontrib><creatorcontrib>Sedova, Mayya</creatorcontrib><creatorcontrib>Semper, Cameron</creatorcontrib><creatorcontrib>Le, Cathy</creatorcontrib><creatorcontrib>Takkouche, Abraham</creatorcontrib><creatorcontrib>Ichii, Keita</creatorcontrib><creatorcontrib>Innabi, Julie</creatorcontrib><creatorcontrib>Patel, Dhruvin H</creatorcontrib><creatorcontrib>Ensminger, Alexander W</creatorcontrib><creatorcontrib>Godzik, Adam</creatorcontrib><creatorcontrib>Savchenko, Alexei</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Molecular systems biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Patel, Deepak T</au><au>Stogios, Peter J</au><au>Jaroszewski, Lukasz</au><au>Urbanus, Malene L</au><au>Sedova, Mayya</au><au>Semper, Cameron</au><au>Le, Cathy</au><au>Takkouche, Abraham</au><au>Ichii, Keita</au><au>Innabi, Julie</au><au>Patel, Dhruvin H</au><au>Ensminger, Alexander W</au><au>Godzik, Adam</au><au>Savchenko, Alexei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Global atlas of predicted functional domains in Legionella pneumophila Dot/Icm translocated effectors</atitle><jtitle>Molecular systems biology</jtitle><stitle>Mol Syst Biol</stitle><addtitle>Mol Syst Biol</addtitle><date>2025-01-02</date><risdate>2025</risdate><volume>21</volume><issue>1</issue><spage>59</spage><epage>89</epage><pages>59-89</pages><issn>1744-4292</issn><eissn>1744-4292</eissn><abstract>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 with
in cellulo
assays, revealed previously unrecognized functional and cryptic domains in
L. pneumophila
effectors.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>39562741</pmid><doi>10.1038/s44320-024-00076-z</doi><tpages>31</tpages><orcidid>https://orcid.org/0000-0002-5256-9237</orcidid><orcidid>https://orcid.org/0000-0003-0824-3704</orcidid><orcidid>https://orcid.org/0009-0008-7885-7940</orcidid><orcidid>https://orcid.org/0009-0002-1839-4282</orcidid><orcidid>https://orcid.org/0009-0008-0850-3805</orcidid><orcidid>https://orcid.org/0000-0003-3318-6270</orcidid><orcidid>https://orcid.org/0000-0002-2425-852X</orcidid><orcidid>https://orcid.org/0000-0002-1121-2661</orcidid><orcidid>https://orcid.org/0009-0007-3997-0265</orcidid><oa>free_for_read</oa></addata></record> |
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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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