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Antibiotics
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How Far Are We from Predicting the Evolution of Antibiotic...
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How Far Are We from Predicting the Evolution of Antibiotic Resistance?

A special issue of Antibiotics (ISSN 2079-6382). This special issue belongs to the section "Mechanism and Evolution of Antibiotic Resistance".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 11627

Special Issue Editor

Dr. Dominique Schneider

E-Mail Website
Guest Editor
Laboratoire TIMC-IMAG, French National Center for Scientific Research, Université Grenoble Alpes, Institute Jean Roget, Grenoble, France
Interests: experimental evolution; microbial genomics; microbial genetics; regulation of gene expression; microbiology

Special Issue Information

Dear Colleagues,

Far from being a science of the past, microbial evolution is continuously impacting human health through the emergence of microbial drug resistance, new viral strains, and invasive species, as well as affecting biotechnological and industrial processes.

Currently, we are only able to monitor evolutionary changes after their occurrence. Improving the prediction of microbial evolution is essential for fighting diseases and pests, anticipating environmental changes, and avoiding the emergence of antibiotic resistance. Predictability is a long-standing dream of evolutionary biologists, and has now become an essential topic in medicine, including in the context of antibiotic resistance emergence.

The prediction of evolution is difficult, firstly, because it relies on random events and secondly, because of the high dimensionality of genomes and the multitude of interactions between genes, proteins, metabolites, and environmental factors, including resources. However, recent progress, based for instance on experimental evolution, genomics and modelling approaches, has been achieved in the potential prediction of the emergence of antibiotic resistance and the discovery of new molecules.

The Special Issue of Antibiotics aims to collect research or review papers which are relevant to the topic we mentioned above.

Dr. Dominique Schneider
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Antibiotics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • antibiotic resistance
  • experimental evolution
  • prediction of evolution
  • modelling
  • fitness cost
  • genomics

Published Papers (4 papers)

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12 pages, 2003 KiB  
Article
Local and Global Protein Interactions Contribute to Residue Entrenchment in Beta-Lactamase TEM-1
by André Birgy, Mélanie Magnan, Claire Amaris Hobson, Matteo Figliuzzi, Karine Panigoni, Cyrielle Codde, Olivier Tenaillon and Hervé Jacquier
Antibiotics 2022, 11(5), 652; https://doi.org/10.3390/antibiotics11050652 - 13 May 2022
Cited by 2 | Viewed by 1631
Abstract
Due to their rapid evolution and their impact on healthcare, beta-lactamases, protein degrading beta-lactam antibiotics, are used as generic models of protein evolution. Therefore, we investigated the mutation effects in two distant beta-lactamases, TEM-1 and CTX-M-15. Interestingly, we found a site with a [...] Read more.
Due to their rapid evolution and their impact on healthcare, beta-lactamases, protein degrading beta-lactam antibiotics, are used as generic models of protein evolution. Therefore, we investigated the mutation effects in two distant beta-lactamases, TEM-1 and CTX-M-15. Interestingly, we found a site with a complex pattern of genetic interactions. Mutation G251W in TEM-1 inactivates the protein’s function, just as the reciprocal mutation, W251G, does in CTX-M-15. The phylogenetic analysis revealed that mutation G has been entrenched in TEM-1’s background: while rarely observed throughout the phylogeny, it is essential in TEM-1. Using a rescue experiment, in the TEM-1 G251W mutant, we identified sites that alleviate the deviation from G to W. While few of these mutations could potentially involve local interactions, most of them were found on distant residues in the 3D structure. Many well-known mutations that have an impact on protein stability, such as M182T, were recovered. Our results therefore suggest that entrenchment of an amino acid may rely on diffuse interactions among multiple sites, with a major impact on protein stability. Full article
(This article belongs to the Special Issue How Far Are We from Predicting the Evolution of Antibiotic Resistance?)
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16 pages, 3507 KiB  
Article
Evolution of Bacterial Persistence to Antibiotics during a 50,000-Generation Experiment in an Antibiotic-Free Environment
by Hugo Mathé-Hubert, Rafika Amia, Mikaël Martin, Joël Gaffé and Dominique Schneider
Antibiotics 2022, 11(4), 451; https://doi.org/10.3390/antibiotics11040451 - 27 Mar 2022
Cited by 2 | Viewed by 2970
Abstract
Failure of antibiotic therapies causes > 700,000 deaths yearly and involves both bacterial resistance and persistence. Persistence results in the relapse of infections by producing a tiny fraction of pathogen survivors that stay dormant during antibiotic exposure. From an evolutionary perspective, persistence is [...] Read more.
Failure of antibiotic therapies causes > 700,000 deaths yearly and involves both bacterial resistance and persistence. Persistence results in the relapse of infections by producing a tiny fraction of pathogen survivors that stay dormant during antibiotic exposure. From an evolutionary perspective, persistence is either a ‘bet-hedging strategy’ that helps to cope with stochastically changing environments or an unavoidable minimal rate of ‘cellular errors’ that lock the cells in a low activity state. Here, we analyzed the evolution of persistence over 50,000 bacterial generations in a stable environment by improving a published method that estimates the number of persister cells based on the growth of the reviving population. Our results challenged our understanding of the factors underlying persistence evolution. In one case, we observed a substantial decrease in persistence proportion, suggesting that the naturally observed persistence level is not an unavoidable minimal rate of ‘cellular errors’. However, although there was no obvious environmental stochasticity, in 11 of the 12 investigated populations, the persistence level was maintained during 50,000 bacterial generations. Full article
(This article belongs to the Special Issue How Far Are We from Predicting the Evolution of Antibiotic Resistance?)
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10 pages, 710 KiB  
Article
Idiosyncratic Fitness Costs of Ampicillin-Resistant Mutants Derived from a Long-Term Experiment with Escherichia coli
by Jalin A. Jordan, Richard E. Lenski and Kyle J. Card
Antibiotics 2022, 11(3), 347; https://doi.org/10.3390/antibiotics11030347 - 06 Mar 2022
Cited by 3 | Viewed by 2293
Abstract
Antibiotic resistance is a growing concern that has prompted a renewed focus on drug discovery, stewardship, and evolutionary studies of the patterns and processes that underlie this phenomenon. A resistant strain’s competitive fitness relative to its sensitive counterparts in the absence of drug [...] Read more.
Antibiotic resistance is a growing concern that has prompted a renewed focus on drug discovery, stewardship, and evolutionary studies of the patterns and processes that underlie this phenomenon. A resistant strain’s competitive fitness relative to its sensitive counterparts in the absence of drug can impact its spread and persistence in both clinical and community settings. In a prior study, we examined the fitness of tetracycline-resistant clones that evolved from five different Escherichia coli genotypes, which had diverged during a long-term evolution experiment. In this study, we build on that work to examine whether ampicillin-resistant mutants are also less fit in the absence of the drug than their sensitive parents, and whether the cost of resistance is constant or variable among independently derived lines. Like the tetracycline-resistant lines, the ampicillin-resistant mutants were often less fit than their sensitive parents, with significant variation in the fitness costs among the mutants. This variation was not associated with the level of resistance conferred by the mutations, nor did it vary across the different parental backgrounds. In our earlier study, some of the variation in fitness costs associated with tetracycline resistance was explained by the effects of different mutations affecting the same cellular pathway and even the same gene. In contrast, the variance among the ampicillin-resistant mutants was associated with different sets of target genes. About half of the resistant clones suffered large fitness deficits, and their mutations impacted major outer-membrane proteins or subunits of RNA polymerases. The other mutants experienced little or no fitness costs and with, one exception, they had mutations affecting other genes and functions. Our findings underscore the importance of comparative studies on the evolution of antibiotic resistance, and they highlight the nuanced processes that shape these phenotypes. Full article
(This article belongs to the Special Issue How Far Are We from Predicting the Evolution of Antibiotic Resistance?)
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8 pages, 833 KiB  
Opinion
Persistent Bacterial Infections, Antibiotic Treatment Failure, and Microbial Adaptive Evolution
by Ruggero La Rosa, Helle Krogh Johansen and Søren Molin
Antibiotics 2022, 11(3), 419; https://doi.org/10.3390/antibiotics11030419 - 21 Mar 2022
Cited by 12 | Viewed by 4047
Abstract
Antibiotic resistance is expected by the WHO to be the biggest threat to human health before 2050. In this overview, we argue that this prediction may in fact be too optimistic because it is often overlooked that many bacterial infections frequently ‘go under [...] Read more.
Antibiotic resistance is expected by the WHO to be the biggest threat to human health before 2050. In this overview, we argue that this prediction may in fact be too optimistic because it is often overlooked that many bacterial infections frequently ‘go under the radar’ because they are difficult to diagnose and characterize. Due to our lifestyle, persistent infections caused by opportunistic bacteria—well-known or emerging—show increasing success of infecting patients with reduced defense capacity, and often antibiotics fail to be sufficiently effective, even if the bacteria are susceptible, leaving small bacterial populations unaffected by treatment in the patient. The mechanisms behind infection persistence are multiple, and therefore very difficult to diagnose in the laboratory and to treat. In contrast to antibiotic resistance associated with acute infections caused by traditional bacterial pathogens, genetic markers associated with many persistent infections are imprecise and mostly without diagnostic value. In the absence of effective eradication strategies, there is a significant risk that persistent infections may eventually become highly resistant to antibiotic treatment due to the accumulation of genomic mutations, which will transform colonization into persistence. Full article
(This article belongs to the Special Issue How Far Are We from Predicting the Evolution of Antibiotic Resistance?)
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