The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Strength of Selection Pressure Is an Important Parameter Contributing to the Complexity of Antibiotic Resistance Evolution
Open accessAbstract
Revealing the genetic changes responsible for antibiotic resistance can be critical for developing novel antibiotic therapies. However, systematic studies correlating genotype to phenotype in the context of antibiotic resistance have been missing. In order to fill in this gap, we evolved 88 isogenic Escherichia coli populations against 22 antibiotics for 3 weeks. For every drug, two populations were evolved under strong selection and two populations were evolved under mild selection. By quantifying evolved populations' resistances against all 22 drugs, we constructed two separate cross-resistance networks for strongly and mildly selected populations. Subsequently, we sequenced representative colonies isolated from evolved populations for revealing the genetic basis for novel phenotypes. Bacterial populations that evolved resistance against antibiotics under strong selection acquired high levels of cross-resistance against several antibiotics, whereas other bacterial populations evolved under milder selection acquired relatively weaker cross-resistance. In addition, we found that strongly selected strains against aminoglycosides became more susceptible to five other drug classes compared with their wild-type ancestor as a result of a point mutation on TrkH, an ion transporter protein. Our findings suggest that selection strength is an important parameter contributing to the complexity of antibiotic resistance problem and use of high doses of antibiotics to clear infections has the potential to promote increase of cross-resistance in clinics.
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Cites
Construction of Escherichia coli K‐12 in‐frame, single‐gene knockout mutants: the Keio collection
Baba, T., Ara, T., Hasegawa, M., Takai, Y., Okumura, Y., Baba, M., Datsenko, K. A., Tomita, M., Wanner, B. L., & Mori, H. (2006) · Molecular Systems Biology · doi:10.1038/msb4100050 · Cited by 7,858
Bacterial charity work leads to population-wide resistance
Lee, H. H., Molla, M. N., Cantor, C. R., & Collins, J. J. (2010) · Nature · doi:10.1038/nature09354 · Cited by 638
Chromosomal duplication is a transient evolutionary solution to stress
Yona, A. H., Manor, Y. S., Herbst, R. H., Romano, G. H., Mitchell, A., Kupiec, M., Pilpel, Y., & Dahan, O. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1211150109 · Cited by 376
Drug interactions and the evolution of antibiotic resistance
Yeh, P. J., Hegreness, M. J., Aiden, A. P., & Kishony, R. (2009) · Nature Reviews Microbiology · doi:10.1038/nrmicro2133 · Cited by 350
Self-citationNonoptimal microbial response to antibiotics underlies suppressive drug interactions
Bollenbach, T., Quan, S., Chait, R., & Kishony, R. (2009) · Cell · doi:10.1016/j.cell.2009.10.025 · Cited by 227
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Baym, M., Stone, L. K., & Kishony, R. (2016) · Science · doi:10.1126/science.aad3292 · Cited by 710
Evolution of high-level resistance during low-level antibiotic exposure
Wistrand-Yuen, E., Knopp, M., Hjort, K., Koskiniemi, S., Berg, O. G., & Andersson, D. I. (2018) · Nature Communications · doi:10.1038/s41467-018-04059-1 · Cited by 466
Alternating antibiotic treatments constrain evolutionary paths to multidrug resistance
Kim, S., Lieberman, T. D., & Kishony, R. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1409800111 · Cited by 264
Antibiotic resistance: turning evolutionary principles into clinical reality
Andersson, D. I., Balaban, N. Q., Baquero, F., Courvalin, P., Glaser, P., Gophna, U., Kishony, R., Molin, S., & Tønjum, T. (2020) · FEMS Microbiology Reviews · doi:10.1093/femsre/fuaa001 · Cited by 238
Antibiotic collateral sensitivity is contingent on the repeatability of evolution
Nichol, D., Rutter, J., Bryant, C., Hujer, A. M., Lek, S., Adams, M. D., Jeavons, P., Anderson, A. R. A., Bonomo, R. A., & Scott, J. G. (2019) · Nature Communications · doi:10.1038/s41467-018-08098-6 · Cited by 174
Metadata
- Authors
- Oz, T., Guvenek, A., Yildiz, S., Karaboga, E., Tamer, Y. T., Mumcuyan, N., Ozan, V. B., Senturk, G. H., Cokol, M., Yeh, P., & Toprak, E.
- Venue
- Molecular Biology and Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-06-24
- Volume
- 31
- Issue
- 9
- Pages
- 2387-2401
- ISSN
- 0737-4038 (ISSN-L)
- 1537-1719
- OpenAlex
- W2105560808
- Cited by
- 275
- References
- 5
- FWCI
- 11.29
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Oz, T., Guvenek, A., Yildiz, S., Karaboga, E., Tamer, Y. T., Mumcuyan, N., Ozan, V. B., Senturk, G. H., Cokol, M., Yeh, P., & Toprak, E. (2014). Strength of Selection Pressure Is an Important Parameter Contributing to the Complexity of Antibiotic Resistance Evolution. Molecular Biology and Evolution. https://doi.org/10.1093/molbev/msu191
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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