The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Plasmid Classification in an Era of Whole-Genome Sequencing: Application in Studies of Antibiotic Resistance Epidemiology
Open accessAbstract
Plasmids are extra-chromosomal genetic elements ubiquitous in bacteria, and commonly transmissible between host cells. Their genomes include variable repertoires of ‘accessory genes’, such as antibiotic resistance genes, as well as ‘backbone’ loci which are largely conserved within plasmid families, and often involved in key plasmid-specific functions (e.g. replication, stable inheritance, mobility). Classifying plasmids into different types according to their phylogenetic relatedness provides insight into the epidemiology of plasmid-mediated antibiotic resistance. Current typing schemes exploit backbone loci associated with replication (replicon typing), or plasmid mobility (MOB typing). Conventional PCR-based methods for plasmid typing remain widely used. With the emergence of whole-genome sequencing (WGS), large datasets can be analyzed using in silico plasmid typing methods. However, short reads from popular high-throughput sequencers can be challenging to assemble, so complete plasmid sequences may not be accurately reconstructed. Therefore, localizing resistance genes to specific plasmids may be difficult, limiting epidemiological insight. Long-read sequencing will become increasingly popular as costs decline, especially when resolving accurate plasmid structures is the primary goal. This review discusses the application of plasmid classification in WGS-based studies of antibiotic resistance epidemiology; novel in silico plasmid analysis tools are highlighted. Due to the diverse and plastic nature of plasmid genomes, current typing schemes do not classify all plasmids, and identifying conserved, phylogenetically concordant genes for subtyping and phylogenetics is challenging. Analyzing plasmids as nodes in a network that represents gene-sharing relationships between plasmids provides a complementary way to assess plasmid diversity, and allows inferences about horizontal gene transfer to be made.
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Cites
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066
Identification of acquired antimicrobial resistance genes
Zankari, E., Hasman, H., Cosentino, S., Vestergaard, M., Rasmussen, S., Lund, O., Aarestrup, F. M., & Larsen, M. V. (2012) · Journal of Antimicrobial Chemotherapy · doi:10.1093/jac/dks261 · Cited by 4,980
How to apply de Bruijn graphs to genome assembly
Compeau, P. E. C., Pevzner, P. A., & Tesler, G. (2011) · Nature Biotechnology · doi:10.1038/nbt.2023 · Cited by 673
Cited by
Mobile Genetic Elements Associated with Antimicrobial Resistance
Partridge, S. R., Kwong, S. M., Firth, N., & Jensen, S. O. (2018) · Clinical Microbiology Reviews · doi:10.1128/cmr.00088-17 · Cited by 2,751
Antibiotic resistance in microbes: History, mechanisms, therapeutic strategies and future prospects
Uddin, T. M., Chakraborty, A. J., Khusro, A., Zidan, B. R. M., Mitra, S., Emran, T. B., Dhama, K., Ripon, M. K. H., Gajdács, M., Sahibzada, M. U. K., et al. (2021) · Journal of Infection and Public Health · doi:10.1016/j.jiph.2021.10.020 · Cited by 1,311
Rapid Diagnosis of Lower Respiratory Infection using Nanopore-based Clinical Metagenomics
Charalampous, T., Richardson, H., Kay, G. L., Baldan, R., Jeanes, C., Rae, D., Grundy, S., Turner, D. J., Wain, J., Leggett, R. M., et al. (2018) · doi:10.1101/387548 · Cited by 37
Metadata
- Authors
- Orlek, A., Stoesser, N., Anjum, M. F., Doumith, M., Ellington, M. J., Peto, T., Crook, D., Woodford, N., Walker, A. S., Phan, H., & Sheppard, A. E.
- Venue
- Frontiers in Microbiology
- Publisher
- Frontiers Media SA
- Published
- 2017-02-09
- Volume
- 8
- Pages
- 182-182
- ISSN
- 1664-302X (ISSN-L)
- OpenAlex
- W2587678577
- Cited by
- 215
- References
- 3
- FWCI
- 7.49
- Type
- journal article
- Language
- en
- Open access
- gold
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- The paper
- Orlek, A., Stoesser, N., Anjum, M. F., Doumith, M., Ellington, M. J., Peto, T., Crook, D., Woodford, N., Walker, A. S., Phan, H., & Sheppard, A. E. (2017). Plasmid Classification in an Era of Whole-Genome Sequencing: Application in Studies of Antibiotic Resistance Epidemiology. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2017.00182
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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).
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