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http://dx.doi.org/10.18419/opus-10852
Autor(en): | Ullrich, Timo Weirich, Sara Jeltsch, Albert |
Titel: | Development of an epigenetic tetracycline sensor system based on DNA methylation |
Erscheinungsdatum: | 2020 |
Dokumentart: | Zeitschriftenartikel |
Seiten: | 17, 11 |
Erschienen in: | PLOS ONE 15 (2020), No. 5, e0232701 |
URI: | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-108692 http://elib.uni-stuttgart.de/handle/11682/10869 http://dx.doi.org/10.18419/opus-10852 |
ISSN: | 1932-6203 |
Zusammenfassung: | Bacterial live cell sensors are potentially powerful tools for the detection of environmental toxins. In this work, we have established and validated a flow cytometry readout for an existing bacterial arabinose sensor system with DNA methylation based memory function (Maier et al., 2017, Nat. Comm., 8:15336). Flow cytometry readout is convenient and enables a multiparameter analysis providing information about single-cell variability, which is beneficial for further development of sensor systems of this type in the future. We then designed a tetracycline sensor system, because of the importance of antibiotics pollution in the light of multi-resistant pathogens. To this end, a tetracycline trigger plasmid was constructed by replacing the araC repressor gene and the ara operator of the arabinose trigger plasmid with the tetR gene coding for the tetracycline repressor and the tet operon. After combination with the memory plasmid, the tetracycline sensor system was shown to be functional in E. coli allowing to detect and memorize the presence of tetracycline. Due to a positive feedback between the trigger and memory systems, the combined whole-cell biosensor showed a very high sensitivity for tetracycline with a detection threshold at 0.1 ng/ml tetracycline, which may be a general property of sensors of this type. Moreover, acute presence of tetracycline and past exposure can be detected by this sensor using the dual readout of two reporter fluorophores. |
Enthalten in den Sammlungen: | 03 Fakultät Chemie |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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Ullrich_PLOSone_2020.pdf | Article | 2,45 MB | Adobe PDF | Öffnen/Anzeigen |
tetsensor_suppl_rev2_1.pdf | Supplementary information | 1,09 MB | Adobe PDF | Öffnen/Anzeigen |
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