The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Antibiotic resistance shaping multi-level population biology of bacteria
Open accessAbstract
Antibiotics have natural functions, mostly involving cell-to-cell signaling networks. The anthropogenic production of antibiotics, and its release in the microbiosphere results in a disturbance of these networks, antibiotic resistance tending to preserve its integrity. The cost of such adaptation is the emergence and dissemination of antibiotic resistance genes, and of all genetic and cellular vehicles in which these genes are located. Selection of the combinations of the different evolutionary units (genes, integrons, transposons, plasmids, cells, communities and microbiomes, hosts) is highly asymmetrical. Each unit of selection is a self-interested entity, exploiting the higher hierarchical unit for its own benefit, but in doing so the higher hierarchical unit might acquire critical traits for its spread because of the exploitation of the lower hierarchical unit. This interactive trade-off shapes the population biology of antibiotic resistance, a composed-complex array of the independent "population biologies." Antibiotics modify the abundance and the interactive field of each of these units. Antibiotics increase the number and evolvability of "clinical" antibiotic resistance genes, but probably also many other genes with different primary functions but with a resistance phenotype present in the environmental resistome. Antibiotics influence the abundance, modularity, and spread of integrons, transposons, and plasmids, mostly acting on structures present before the antibiotic era. Antibiotics enrich particular bacterial lineages and clones and contribute to local clonalization processes. Antibiotics amplify particular genetic exchange communities sharing antibiotic resistance genes and platforms within microbiomes. In particular human or animal hosts, the microbiomic composition might facilitate the interactions between evolutionary units involved in antibiotic resistance. The understanding of antibiotic resistance implies expanding our knowledge on multi-level population biology of bacteria.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Hidron, A. I., Edwards, J. R., Patel, J., Horan, T. C., Sievert, D. M., Pollock, D. A., Fridkin, S. K., & National Healthcare Safety Network Team and Participating National Healthcare Safety Network Facilities (2008) · Infection Control & Hospital Epidemiology · doi:10.1086/591861 · Cited by 3,724
Gut microbiota composition correlates with diet and health in the elderly
Claesson, M. J., Jeffery, I. B., Conde, S., Power, S. E., O’Connor, E. M., Cusack, S., Harris, H. M. B., Coakley, M., Lakshminarayanan, B., O’Sullivan, O., et al. (2012) · Nature · doi:10.1038/nature11319 · Cited by 3,314
Antibiotic resistance is ancient
D’Costa, V. M., King, C. E., Kalan, L., Morar, M., Sung, W. W. L., Schwarz, C., Froese, D., Zazula, G., Calmels, F., Debruyne, R., et al. (2011) · Nature · doi:10.1038/nature10388 · Cited by 2,720
Waves of resistance: Staphylococcus aureus in the antibiotic era
Chambers, H. F., & DeLeo, F. R. (2009) · Nature Reviews Microbiology · doi:10.1038/nrmicro2200 · Cited by 2,718
The shared antibiotic resistome of soil bacteria and human pathogens
Forsberg, K. J., Reyes, A., Wang, B., Selleck, E. M., Sommer, M. O. A., & Dantas, G. (2012) · Science · doi:10.1126/science.1220761 · Cited by 1,650
High-Fat Diet Determines the Composition of the Murine Gut Microbiome Independently of Obesity
Hildebrandt, M. A., Hoffmann, C., Sherrill–Mix, S. A., Keilbaugh, S. A., Hamady, M., Chen, Y., Knight, R., Ahima, R. S., Bushman, F., & Wu, G. D. (2009) · Gastroenterology · doi:10.1053/j.gastro.2009.08.042 · Cited by 1,576 · cited 2×
“For instance, a high-fat diet determines the composition of the murine gut microbiome independently of obesity, with an increase of Proteobacteria and Firmicutes, heavily involved in resistance gene mobilization (Hildebrandt et al., 2009; Tagliabue and Elli, 2012).”
BackgroundMicrobial co-occurrence relationships in the human microbiome
Faust, K., Sathirapongsasuti, J. F., Izard, J., Segata, N., Gevers, D., Raes, J., & Huttenhower, C. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002606 · Cited by 1,527
Functional characterization of the antibiotic resistance reservoir in the human microflora
Sommer, M. O. A., Dantas, G., & Church, G. M. (2009) · Science · doi:10.1126/science.1176950 · Cited by 878
Evolutionary consequences of niche construction and their implications for ecology
Laland, K. N., Odling-Smee, F. J., & Feldman, M. W. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.18.10242 · Cited by 624
Graessler, J., Qin, Y., Zhong, H., Zhang, J., Licinio, J., Wong, M.-L., Xu, A., Chavakis, T., Bornstein, A. B., Ehrhart-Bornstein, M., et al. (2013) · The Pharmacogenomics Journal · doi:10.1038/tpj.2012.43 · Cited by 428
Cited by
Tackling antibiotic resistance: the environmental framework
Berendonk, T. U., Manaia, C. M., Merlin, C., Fatta-Kassinos, D., Cytryn, E., Walsh, F., Bürgmann, H., Sørum, H., Norström, M., Pons, M.-N., et al. (2015) · Nature Reviews Microbiology · doi:10.1038/nrmicro3439 · Cited by 2,338
Self-citationEnvironmental factors influencing the development and spread of antibiotic resistance
Bengtsson-Palme, J., Kristiansson, E., & Larsson, D. G. J. (2018) · FEMS Microbiology Reviews · doi:10.1093/femsre/fux053 · Cited by 1,167
Mathers, A. J., Peirano, G., & Pitout, J. D. D. (2015) · Clinical Microbiology Reviews · doi:10.1128/cmr.00116-14 · Cited by 872
Carbapenemase-Producing Klebsiella pneumoniae, a Key Pathogen Set for Global Nosocomial Dominance
Pitout, J. D. D., Nordmann, P., & Poirel, L. (2015) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.01019-15 · Cited by 852
Antibiotic Resistance and the Biology of History
Landecker, H. (2016) · Body & Society · doi:10.1177/1357034x14561341 · Cited by 375
Metadata
- Authors
- Baquero, F., Tedim, A. P., & Coque, T. M.
- Venue
- Frontiers in Microbiology
- Publisher
- Frontiers Media SA
- Published
- 2013
- Volume
- 4
- Pages
- 15-15
- ISSN
- 1664-302X (ISSN-L)
- OpenAlex
- W2162161835
- Cited by
- 193
- References
- 13
- FWCI
- 8.58
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Antibiotic resistance shaping multi-level population biology of bacteria. https://app.cochat.ai/papers/10.3389/fmicb.2013.00015
- The paper
- Baquero, F., Tedim, A. P., & Coque, T. M. (2013). Antibiotic resistance shaping multi-level population biology of bacteria. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2013.00015
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
