dc.contributor.author
Recacha, Esther
dc.contributor.author
Kuropka, Benno
dc.contributor.author
Díaz-Díaz, Sara
dc.contributor.author
García-Montaner, Andrea
dc.contributor.author
González-Tortuero, Enrique
dc.contributor.author
Docobo-Pérez, Fernando
dc.contributor.author
Rodríguez-Rojas, Alexandro
dc.contributor.author
Rodríguez-Martínez, Jose Manuel
dc.date.accessioned
2024-05-06T08:21:53Z
dc.date.available
2024-05-06T08:21:53Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/43428
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-43145
dc.description.abstract
Introduction/objective: Suppression of the SOS response in combination with drugs damaging DNA has been proposed as a potential target to tackle antimicrobial resistance. The SOS response is the pathway used to repair bacterial DNA damage induced by antimicrobials such as quinolones. The extent of lexA-regulated protein expression and other associated systems under pressure of agents that damage bacterial DNA in clinical isolates remains unclear. The aim of this study was to assess the impact of this strategy consisting on suppression of the SOS response in combination with quinolones on the proteome profile of Escherichia coli clinical strains.
Materials and methods: Five clinical isolates of E. coli carrying different chromosomally- and/or plasmid-mediated quinolone resistance mechanisms with different phenotypes were selected, with E. coli ATCC 25922 as control strain. In addition, from each clinical isolate and control, a second strain was created, in which the SOS response was suppressed by deletion of the recA gene. Bacterial inocula from all 12 strains were then exposed to 1xMIC ciprofloxacin treatment (relative to the wild-type phenotype for each isogenic pair) for 1 h. Cell pellets were collected, and proteins were digested into peptides using trypsin. Protein identification and label-free quantification were done by liquid chromatography-mass spectrometry (LC–MS) in order to identify proteins that were differentially expressed upon deletion of recA in each strain. Data analysis and statistical analysis were performed using the MaxQuant and Perseus software.
Results: The proteins with the lowest expression levels were: RecA (as control), AphA, CysP, DinG, DinI, GarL, PriS, PsuG, PsuK, RpsQ, UgpB and YebG; those with the highest expression levels were: Hpf, IbpB, TufB and RpmH. Most of these expression alterations were strain-dependent and involved DNA repair processes and nucleotide, protein and carbohydrate metabolism, and transport. In isolates with suppressed SOS response, the number of underexpressed proteins was higher than overexpressed proteins.
Conclusion: High genomic and proteomic variability was observed among clinical isolates and was not associated with a specific resistant phenotype. This study provides an interesting approach to identify new potential targets to combat antimicrobial resistance.
en
dc.format.extent
10 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
SOS response
en
dc.subject
Escherichia coli
en
dc.subject
proteome profile
en
dc.subject
antimicrobial resistance
en
dc.subject
Enterobacteriaceae
en
dc.subject.ddc
500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie::570 Biowissenschaften; Biologie
dc.title
Impact of suppression of the SOS response on protein expression in clinical isolates of Escherichia coli under antimicrobial pressure of ciprofloxacin
dc.type
Wissenschaftlicher Artikel
dc.date.updated
2024-04-24T06:00:52Z
dcterms.bibliographicCitation.articlenumber
1379534
dcterms.bibliographicCitation.doi
10.3389/fmicb.2024.1379534
dcterms.bibliographicCitation.journaltitle
Frontiers in Microbiology
dcterms.bibliographicCitation.volume
15
dcterms.bibliographicCitation.url
https://doi.org/10.3389/fmicb.2024.1379534
refubium.affiliation
Biologie, Chemie, Pharmazie
refubium.affiliation.other
Institut für Chemie und Biochemie
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
1664-302X
refubium.resourceType.provider
DeepGreen