Transcriptomic responses to antibiotic exposure in Mycobacterium tuberculosis
Transcriptional responses in bacteria following antibiotic exposure offer insights into antibiotic mechanism of action, bacterial responses, and characterization of antimicrobial resistance. We aimed to define the transcriptional antibiotic response (TAR) in (Mtb) isolates for clinically relevant dr...
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| Veröffentlicht in: | Antimicrobial agents and chemotherapy 2024-05, Vol.68 (5), p.e0118523 |
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| container_title | Antimicrobial agents and chemotherapy |
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| creator | Poonawala, Husain Zhang, Yu Kuchibhotla, Sravya Green, Anna G Cirillo, Daniela Maria Di Marco, Federico Spitlaeri, Andrea Miotto, Paolo Farhat, Maha R |
| description | Transcriptional responses in bacteria following antibiotic exposure offer insights into antibiotic mechanism of action, bacterial responses, and characterization of antimicrobial resistance. We aimed to define the transcriptional antibiotic response (TAR) in
(Mtb) isolates for clinically relevant drugs by pooling and analyzing Mtb microarray and RNA-seq data sets. We generated 99 antibiotic transcription profiles across 17 antibiotics, with 76% of profiles generated using 3-24 hours of antibiotic exposure and 49% within one doubling of the WHO antibiotic critical concentration. TAR genes were time-dependent, and largely specific to the antibiotic mechanism of action. TAR signatures performed well at predicting antibiotic exposure, with the area under the receiver operating curve (AUC) ranging from 0.84-1.00 (TAR 6 hours of antibiotic exposure) for upregulated genes and 0.57-0.90 and 0.87-1.00, respectfully, for downregulated genes. This work desmonstrates that transcriptomics allows for the assessment of antibiotic activity in Mtb within 6 hours of exposure. |
| doi_str_mv | 10.1128/aac.01185-23 |
| format | Article |
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(Mtb) isolates for clinically relevant drugs by pooling and analyzing Mtb microarray and RNA-seq data sets. We generated 99 antibiotic transcription profiles across 17 antibiotics, with 76% of profiles generated using 3-24 hours of antibiotic exposure and 49% within one doubling of the WHO antibiotic critical concentration. TAR genes were time-dependent, and largely specific to the antibiotic mechanism of action. TAR signatures performed well at predicting antibiotic exposure, with the area under the receiver operating curve (AUC) ranging from 0.84-1.00 (TAR <6 hours of antibiotic exposure) and 0.76-1.00 (>6 hours of antibiotic exposure) for upregulated genes and 0.57-0.90 and 0.87-1.00, respectfully, for downregulated genes. This work desmonstrates that transcriptomics allows for the assessment of antibiotic activity in Mtb within 6 hours of exposure.</description><identifier>ISSN: 0066-4804</identifier><identifier>ISSN: 1098-6596</identifier><identifier>EISSN: 1098-6596</identifier><identifier>DOI: 10.1128/aac.01185-23</identifier><identifier>PMID: 38587412</identifier><language>eng</language><publisher>United States: American Society for Microbiology</publisher><subject>Anti-Bacterial Agents - pharmacology ; Antitubercular Agents - pharmacology ; Computational Biology ; Gene Expression Profiling - methods ; Gene Expression Regulation, Bacterial - drug effects ; Humans ; Mechanisms of Resistance ; Microbial Sensitivity Tests ; Mycobacterium tuberculosis - drug effects ; Mycobacterium tuberculosis - genetics ; Transcriptome - genetics</subject><ispartof>Antimicrobial agents and chemotherapy, 2024-05, Vol.68 (5), p.e0118523</ispartof><rights>Copyright © 2024 American Society for Microbiology.</rights><rights>Copyright © 2024 American Society for Microbiology. 2024 American Society for Microbiology.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a338t-41692c6cb2f07870164a0a99da21d0aa0e4d5219804e5ceb80d81ad12191a1a03</cites><orcidid>0000-0003-4334-7226 ; 0000-0003-0376-1342 ; 0000-0003-4610-2427 ; 0000-0002-3871-5760 ; 0000-0001-6415-1535</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/PMC11064486/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11064486/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,27903,27904,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38587412$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Wasserman, Sean</contributor><creatorcontrib>Poonawala, Husain</creatorcontrib><creatorcontrib>Zhang, Yu</creatorcontrib><creatorcontrib>Kuchibhotla, Sravya</creatorcontrib><creatorcontrib>Green, Anna G</creatorcontrib><creatorcontrib>Cirillo, Daniela Maria</creatorcontrib><creatorcontrib>Di Marco, Federico</creatorcontrib><creatorcontrib>Spitlaeri, Andrea</creatorcontrib><creatorcontrib>Miotto, Paolo</creatorcontrib><creatorcontrib>Farhat, Maha R</creatorcontrib><title>Transcriptomic responses to antibiotic exposure in Mycobacterium tuberculosis</title><title>Antimicrobial agents and chemotherapy</title><addtitle>Antimicrob Agents Chemother</addtitle><addtitle>Antimicrob Agents Chemother</addtitle><description>Transcriptional responses in bacteria following antibiotic exposure offer insights into antibiotic mechanism of action, bacterial responses, and characterization of antimicrobial resistance. We aimed to define the transcriptional antibiotic response (TAR) in
(Mtb) isolates for clinically relevant drugs by pooling and analyzing Mtb microarray and RNA-seq data sets. We generated 99 antibiotic transcription profiles across 17 antibiotics, with 76% of profiles generated using 3-24 hours of antibiotic exposure and 49% within one doubling of the WHO antibiotic critical concentration. TAR genes were time-dependent, and largely specific to the antibiotic mechanism of action. TAR signatures performed well at predicting antibiotic exposure, with the area under the receiver operating curve (AUC) ranging from 0.84-1.00 (TAR <6 hours of antibiotic exposure) and 0.76-1.00 (>6 hours of antibiotic exposure) for upregulated genes and 0.57-0.90 and 0.87-1.00, respectfully, for downregulated genes. This work desmonstrates that transcriptomics allows for the assessment of antibiotic activity in Mtb within 6 hours of exposure.</description><subject>Anti-Bacterial Agents - pharmacology</subject><subject>Antitubercular Agents - pharmacology</subject><subject>Computational Biology</subject><subject>Gene Expression Profiling - methods</subject><subject>Gene Expression Regulation, Bacterial - drug effects</subject><subject>Humans</subject><subject>Mechanisms of Resistance</subject><subject>Microbial Sensitivity Tests</subject><subject>Mycobacterium tuberculosis - drug effects</subject><subject>Mycobacterium tuberculosis - genetics</subject><subject>Transcriptome - genetics</subject><issn>0066-4804</issn><issn>1098-6596</issn><issn>1098-6596</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kc1PFjEQxhsigVfg5tnsURIXZ9put3syhqCSQLzAuZnt9sWS3e3ado3891RfJHrgNJmZX575eBh7g3CGyPUHInsGiLqpudhjG4RO16rp1Cu2AVCqlhrkIXud0j2UvOnggB0K3ehWIt-w65tIc7LRLzlM3lbRpSXMyaUqh4rm7Hsfcqm7X0tIa3SVn6vrBxt6stlFv05VXnsX7TqG5NMx29_SmNzJUzxit58vbs6_1lffvlyef7qqSQida4mq41bZnm-h1S2gkgTUdQNxHIAInBwajl3Z3DXW9RoGjTRgKSEhgThiH3e6y9pPbrBuzpFGs0Q_UXwwgbz5vzP77-Yu_DSIoKTUqii8e1KI4cfqUjaTT9aNI80urMkIELJtFddY0Pc71MaQUnTb5zkI5rcFplhg_lhguCj46Q6nNHFzH9Y4l1e8xL79945n4b_-iEdBhZDW</recordid><startdate>20240502</startdate><enddate>20240502</enddate><creator>Poonawala, Husain</creator><creator>Zhang, Yu</creator><creator>Kuchibhotla, Sravya</creator><creator>Green, Anna G</creator><creator>Cirillo, Daniela Maria</creator><creator>Di Marco, Federico</creator><creator>Spitlaeri, Andrea</creator><creator>Miotto, Paolo</creator><creator>Farhat, Maha R</creator><general>American Society for Microbiology</general><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><orcidid>https://orcid.org/0000-0003-4334-7226</orcidid><orcidid>https://orcid.org/0000-0003-0376-1342</orcidid><orcidid>https://orcid.org/0000-0003-4610-2427</orcidid><orcidid>https://orcid.org/0000-0002-3871-5760</orcidid><orcidid>https://orcid.org/0000-0001-6415-1535</orcidid></search><sort><creationdate>20240502</creationdate><title>Transcriptomic responses to antibiotic exposure in Mycobacterium tuberculosis</title><author>Poonawala, Husain ; 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We aimed to define the transcriptional antibiotic response (TAR) in
(Mtb) isolates for clinically relevant drugs by pooling and analyzing Mtb microarray and RNA-seq data sets. We generated 99 antibiotic transcription profiles across 17 antibiotics, with 76% of profiles generated using 3-24 hours of antibiotic exposure and 49% within one doubling of the WHO antibiotic critical concentration. TAR genes were time-dependent, and largely specific to the antibiotic mechanism of action. TAR signatures performed well at predicting antibiotic exposure, with the area under the receiver operating curve (AUC) ranging from 0.84-1.00 (TAR <6 hours of antibiotic exposure) and 0.76-1.00 (>6 hours of antibiotic exposure) for upregulated genes and 0.57-0.90 and 0.87-1.00, respectfully, for downregulated genes. This work desmonstrates that transcriptomics allows for the assessment of antibiotic activity in Mtb within 6 hours of exposure.</abstract><cop>United States</cop><pub>American Society for Microbiology</pub><pmid>38587412</pmid><doi>10.1128/aac.01185-23</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0003-4334-7226</orcidid><orcidid>https://orcid.org/0000-0003-0376-1342</orcidid><orcidid>https://orcid.org/0000-0003-4610-2427</orcidid><orcidid>https://orcid.org/0000-0002-3871-5760</orcidid><orcidid>https://orcid.org/0000-0001-6415-1535</orcidid></addata></record> |
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| subjects | Anti-Bacterial Agents - pharmacology Antitubercular Agents - pharmacology Computational Biology Gene Expression Profiling - methods Gene Expression Regulation, Bacterial - drug effects Humans Mechanisms of Resistance Microbial Sensitivity Tests Mycobacterium tuberculosis - drug effects Mycobacterium tuberculosis - genetics Transcriptome - genetics |
| title | Transcriptomic responses to antibiotic exposure in Mycobacterium tuberculosis |
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