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Antibiotic resistance: Time of synthesis in a post-genomic age
Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Neverthe...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8181582/ https://www.ncbi.nlm.nih.gov/pubmed/34141134 http://dx.doi.org/10.1016/j.csbj.2021.05.034 |
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author | Gil-Gil, Teresa Ochoa-Sánchez, Luz Edith Baquero, Fernando Martínez, José Luis |
author_facet | Gil-Gil, Teresa Ochoa-Sánchez, Luz Edith Baquero, Fernando Martínez, José Luis |
author_sort | Gil-Gil, Teresa |
collection | PubMed |
description | Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions. |
format | Online Article Text |
id | pubmed-8181582 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-81815822021-06-16 Antibiotic resistance: Time of synthesis in a post-genomic age Gil-Gil, Teresa Ochoa-Sánchez, Luz Edith Baquero, Fernando Martínez, José Luis Comput Struct Biotechnol J Review Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions. Research Network of Computational and Structural Biotechnology 2021-05-21 /pmc/articles/PMC8181582/ /pubmed/34141134 http://dx.doi.org/10.1016/j.csbj.2021.05.034 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Gil-Gil, Teresa Ochoa-Sánchez, Luz Edith Baquero, Fernando Martínez, José Luis Antibiotic resistance: Time of synthesis in a post-genomic age |
title | Antibiotic resistance: Time of synthesis in a post-genomic age |
title_full | Antibiotic resistance: Time of synthesis in a post-genomic age |
title_fullStr | Antibiotic resistance: Time of synthesis in a post-genomic age |
title_full_unstemmed | Antibiotic resistance: Time of synthesis in a post-genomic age |
title_short | Antibiotic resistance: Time of synthesis in a post-genomic age |
title_sort | antibiotic resistance: time of synthesis in a post-genomic age |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8181582/ https://www.ncbi.nlm.nih.gov/pubmed/34141134 http://dx.doi.org/10.1016/j.csbj.2021.05.034 |
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