psi-Footprinting approach for the identification of protein synthesis inhibitor producers

Handel F, Kulik A, Wex KW, Berscheid A, Saur JS, Winkler A, Wibberg D, Kalinowski J, Broetz-Oesterhelt H, Mast Y (2022)
NAR: Genomics and Bioinformatics 4(3): lqac055.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Autor*in
Handel, Franziska; Kulik, Andreas; Wex, Katharina W.; Berscheid, Anne; Saur, Julian S.; Winkler, AnikaUniBi; Wibberg, DanielUniBi; Kalinowski, JörnUniBi; Broetz-Oesterhelt, Heike; Mast, Yvonne
Abstract / Bemerkung
Today, one of the biggest challenges in antibiotic research is a targeted prioritization of natural compound producer strains and an efficient dereplication process to avoid undesired rediscovery of already known substances. Thereby, genome sequence-driven mining strategies are often superior to wet-lab experiments because they are generally faster and less resource-intensive. In the current study, we report on the development of a novel in silico screening approach to evaluate the genetic potential of bacterial strains to produce protein synthesis inhibitors (PSI), which was termed the protein synthesis inhibitor ('psi') target gene footprinting approach = psi-footprinting. The strategy is based on the occurrence of protein synthesis associated self-resistance genes in genome sequences of natural compound producers. The screening approach was applied to 406 genome sequences of actinomycetes strains from the DSMZ strain collection, resulting in the prioritization of 15 potential PSI producer strains. For twelve of them, extract samples showed protein synthesis inhibitory properties in in vitro transcription/translation assays. For four strains, namely Saccharopolyspora flava DSM 44771, Micromonospora aurantiaca DSM 43813, Nocardioides albertanoniae DSM 25218, and Geodermatophilus nigrescens DSM 45408, the protein synthesis inhibitory substance amicoumacin was identified by HPLC-MS analysis, which proved the functionality of the in silico screening approach.
Erscheinungsjahr
2022
Zeitschriftentitel
NAR: Genomics and Bioinformatics
Band
4
Ausgabe
3
Art.-Nr.
lqac055
eISSN
2631-9268
Page URI
https://pub.uni-bielefeld.de/record/2964659

Zitieren

Handel F, Kulik A, Wex KW, et al. psi-Footprinting approach for the identification of protein synthesis inhibitor producers. NAR: Genomics and Bioinformatics . 2022;4(3): lqac055.
Handel, F., Kulik, A., Wex, K. W., Berscheid, A., Saur, J. S., Winkler, A., Wibberg, D., et al. (2022). psi-Footprinting approach for the identification of protein synthesis inhibitor producers. NAR: Genomics and Bioinformatics , 4(3), lqac055. https://doi.org/10.1093/nargab/lqac055
Handel, F., Kulik, A., Wex, K. W., Berscheid, A., Saur, J. S., Winkler, A., Wibberg, D., Kalinowski, J., Broetz-Oesterhelt, H., and Mast, Y. (2022). psi-Footprinting approach for the identification of protein synthesis inhibitor producers. NAR: Genomics and Bioinformatics 4:lqac055.
Handel, F., et al., 2022. psi-Footprinting approach for the identification of protein synthesis inhibitor producers. NAR: Genomics and Bioinformatics , 4(3): lqac055.
F. Handel, et al., “psi-Footprinting approach for the identification of protein synthesis inhibitor producers”, NAR: Genomics and Bioinformatics , vol. 4, 2022, : lqac055.
Handel, F., Kulik, A., Wex, K.W., Berscheid, A., Saur, J.S., Winkler, A., Wibberg, D., Kalinowski, J., Broetz-Oesterhelt, H., Mast, Y.: psi-Footprinting approach for the identification of protein synthesis inhibitor producers. NAR: Genomics and Bioinformatics . 4, : lqac055 (2022).
Handel, Franziska, Kulik, Andreas, Wex, Katharina W., Berscheid, Anne, Saur, Julian S., Winkler, Anika, Wibberg, Daniel, Kalinowski, Jörn, Broetz-Oesterhelt, Heike, and Mast, Yvonne. “psi-Footprinting approach for the identification of protein synthesis inhibitor producers”. NAR: Genomics and Bioinformatics 4.3 (2022): lqac055.

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