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Understanding and overcoming antibiotic resistance

* E-mail: [email protected]

Affiliation Public Library of Science, San Francisco, California, United States of America

• Lauren A. Richardson

Published: August 23, 2017

• https://doi.org/10.1371/journal.pbio.2003775
• Reader Comments

Citation: Richardson LA (2017) Understanding and overcoming antibiotic resistance. PLoS Biol 15(8): e2003775. https://doi.org/10.1371/journal.pbio.2003775

Copyright: © 2017 Lauren A. Richardson. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Competing interests: LR is a current paid employee at Public Library of Science.

Provenance: Written by editorial staff; not externally peer reviewed

Antibiotic drugs have revolutionized medicine and made our modern way of life possible. In addition to their essential role in the clinic, antibiotics are used in a huge array of non-medical applications, from promoting growth in livestock, to preserving building materials from contamination, to treating blight in orchards. However, overuse threatens their efficacy due to the promotion and spread of antibiotic resistant bacteria.

Antibiotics target and inhibit essential cellular processes, retarding growth and causing cell death. However, if bacteria are exposed to drugs below the dose required to kill all bacteria in a population (the minimum bactericidal concentration or MBC), they can mutate and resist antibiotic treatment via natural selection for resistance-conferring mutations. These genetic mutations can arise from the adoption of a plasmid encoding a resistance gene or by mutation to the bacterial chromosome itself.

The concern around the increasing prevalence of drug resistant bacteria is compounded by the fact that the discovery of new antibiotics is a fleeting rare event. Most classes of antibiotics on the market were discovered in the mid-to-late 20 th century. Thus, there is a limited arsenal of drugs to fight resistant bacteria, and bacteria can be resistant to multiple drugs at a time.

Given the importance of antibiotics to modern medicine, and the growing apprehension surrounding the threat of resistance, scientists are studying every aspect of antibiotic resistance. This Open Highlight features some of the cutting-edge research from the Open Access corpus on three major areas of focus: the cellular mechanisms of resistance, the evolution and spread of resistance, and techniques for combating resistance.

Mechanisms of Resistance

A common mechanism used by bacteria to minimize the effects of antibiotics is to acquire or increase the expression of drug efflux pumps. As the name implies, these pumps expel drugs from the cytoplasm, limiting their ability to access their target. In a PLOS Pathogens article, researchers investigated how efflux pump expression is regulated in the human pathogen Pseudomonas aeruginosa [ 1 ]. They found that the multifaceted transcription regulator CpxR regulates the expression of the major efflux pump in P . aeruginosa , and is involved in modulating resistance in clinical isolates.

Resistance-conferring mutations can be specific to a particular antibiotic or they can provide protection to multiple—often related—drugs. A recent eLife article described a surprising set of mutations in the genes encoding components of the ribosome of Mycobacterium smegmatis that confer resistance to numerous antibiotics that are not related structurally or mechanistically [ 2 ]. The authors find that these mutations cause extensive changes in the transcriptome and proteome of the bacterium, including alterations to several proteins known to impact resistance. Importantly, these mutations promote further evolution of the bacteria in a multi-drug environment in a drug-specific manner, thus they both provide resistance and spur further development of resistance.

Resistance is not just a property of an individual bacteria, resistance can also be a property of the microbial community. In a PLOS Biology article, scientists show that intracellular expression of an antibiotic-metabolizing enzyme in a non-pathogenic strain of bacteria can provide resistance to the pathogen Streptococcus pneumoniae when the two types of bacteria are grown together, both in vitro and in vivo [ 3 ]. The expression of the metabolizing enzyme in the non-pathogenic strain deactivates the drug in the immediate environment, despite its intracellular localization, allowing for the outgrowth of the drug-sensitive pathogenic strain ( Fig 1 ). This work highlights the importance of considering the microbial context during infectious disease.

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Still images of a time-lapse experiment show that the green-labeled drug-resistant strain of Staphylococcus aureus provides resistance for the non-labeled drug-sensitive strain of Streptococcus pneumoniae during antibiotic treatment. Image credit: doi: 10.1371/journal.pbio.2000631 .

https://doi.org/10.1371/journal.pbio.2003775.g001

Evolution and spread of resistance

Since antibiotic resistance is the result of natural selection for resistance-conferring mutations, it is important to understand the evolutionary processes underlying this selection. One interesting element to this puzzle is that bacteria acquire resistance to different antibiotics at different rates. In a PLOS Biology article, the authors sought to understand the properties that determine how quickly resistance will evolve [ 4 ]. They identified two properties, resistance variability and dose sensitivity, that could predict the rate of evolution in seven of eight of the drugs.

Another critical element for understanding the evolution of resistance is the cost that resistance-conferring mutations have on bacterial fitness (i.e. growth rate). Most mutations have an associated cost, however bacteria can gain additional mutations, known as compensatory mutations, that offset those costs and help maintain resistance mutations in a population. A PLOS Biology paper describes how multi-drug resistant bacteria compensate, finding that their compensatory evolution is distinct from that of bacteria resistant to single drugs alone, due to the interaction between the resistance mutations [ 5 ].

Resistance to antibiotics is often acquired by the transfer of resistance-conferring genes between bacteria, and this acquisition is usually facilitated by a conjugative plasmid. These plasmids encode the genes necessary for two bacteria to pass the plasmid between them, and they can also encode resistance genes. But, as mentioned above, resistance comes at a cost, and a study published in Science Reports of the compensatory evolution of a large conjugative resistance plasmid showed that evolution follows common paths leading to plasmid stabilization and persistence of resistance [ 6 ].

Methicillin-resistant Staphylococcus aureus (MRSA) is the most common antibiotic resistant infection in humans, and the most frequent mechanism of resistance in MRSA is via the acquisition of mecA ( Fig 2 ). mecA is a member of the penicillin-binding protein family that doesn’t bind β-lactams (like penicillin) effectively and is thus immune to its effects. In a PLOS Genetics article, the scientists map the evolution of mecA from its original role cell wall biosynthesis [ 7 ]. They identify four mechanisms that have led to its new role in resistance, and most importantly, show that it was the use of antibiotics in medicine and in livestock feed that drove this evolution and spread of resistance.

Scanning electron micrograph of a human neutrophil ingesting MRSA (purple). Image credit : NIAID

https://doi.org/10.1371/journal.pbio.2003775.g002

Techniques for combating resistance

While we only have a limited set of antibiotics in our arsenal, there are better ways of dosing and combining drugs to increase efficacy and decrease resistance. One method is using a sequential regimen. Sequential regimens alternate the use of two (or more) drugs over time. The authors of a PLOS Biology article showed that they could design sequential regimens that eliminated bacteria at doses that would normally lead to resistance and treatment failure [ 8 ]. The key goal is to maximize collateral sensitivity–or when one drug sensitizes the bacteria to the second drug–while minimizing cross-resistance–where resistance to one drug confers resistance to the second drug.

A pair of synergistic antibiotics are more effective than the sum of the efficacies of each antibiotic when used alone and their dual action is thought to be more difficult overcome. Unfortunately, finding synergistic pairs is difficult and traditionally requires screening a huge number of drug combinations. In a PLOS Biology article, researchers utilized a technique originally developed for identifying novel antifungals [ 9 ]. The method uses previously generated chemical-genetic datasets and as a proof-of-concept, the researchers identified new synergistic combinations, including one with the classic antiviral, AZT.

Even in single-drug regimens, proper dosing is essential to minimize the development of resistance. Yet, finding the optimal dosing regimen is tricky and requires costly in vivo experiments. By modeling and understanding the kinetics of how the drug and target interaction, an article appearing in PLOS Computational Biology demonstrates that the best time and concentration parameters for an antibiotic dose can be predicted [ 10 ].

A critically important but often overlooked aspect of the treatment of antibiotic-resistant infections is the role of the immune system in clearance. In an article published in PLOS Computational Biology , the authors use mathematical modelling of within-host infection dynamics to understand the interaction between the host immune response and antibiotic treatment [ 11 ]. By comparing a standard fixed dose and duration treatment regime to dynamic regimes that account for pathogen load, they are able to identify treatments that promote synergy between the immune system and the antibiotics.

What if, instead of treating resistant bacteria with more drugs, we could instead make them sensitive to the original drug again? That is the question asked by the authors of a recent PLOS Biology article [ 12 ]. They show that resistant bacteria can be re-sensitized by treating with a specifically designed anti-sense oligonucleotide. This oligonucleotide, a peptide-conjugated phosphorodiamidate morpholino oligomer (PPMO), acts as an antisense mRNA translation inhibitor, and can be designed to target the mRNAs encoding resistance genes. They found that the most effective PPMOs target a constituent of the major drug efflux pump, and treatment with this PPMO can lead to a 2- to 40-fold increase in antibiotic efficacy.

For more detailed reading please see the associated PLOS Collection [ 13 ].

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• 13. In PLOS Collections. Available: http://collections.plos.org/open-highlights-antibiotic-resistance

Prevention of antibiotic resistance - an epidemiological scoping review to identify research categories and knowledge gaps

Affiliation.

• 1 Department of Epidemiology and Global Health, Umeå University , Umeå, Sweden.
• PMID: 32475304
• PMCID: PMC7782542
• DOI: 10.1080/16549716.2020.1756191

Background: Antibiotics have become the cornerstone for the treatment of infectious diseases and contributed significantly to the dramatic global health development during the last 70 years. Millions of people now survive what were previously life-threatening infections. But antibiotics are finite resources and misuse has led to antibiotic resistance and reduced efficacy within just a few years of introduction of each new antibiotic. The World Health Organization rates antibiotic resistance as a 'global security threat' impacting on global health, food security and development and as important as terrorism and climate change.

Objectives: This paper explores, through a scoping review of the literature published during the past 20 years, the magnitude of peer-reviewed and grey literature that addresses antibiotic resistance and specifically the extent to which "prevention" has been at the core. The ultimate aim is to identify know-do gaps and strategies to prevent ABR.

Methods: The review covers four main data bases, Web of Science, Medline, Scopus and Ebsco searched for 2000-17. The broader research field "antibiotic OR antimicrobial resistance" gave 431,335 hits. Narrowing the search criteria to "Prevention of antibiotic OR antimicrobial resistance" resulted in 1062 remaining titles. Of these, 622 were unique titles. After screening of the 622 titles for relevance, 420 abstracts were read, and of these 282 papers were read in full. An additional 53 references were identified from these papers, and 64 published during 2018 and 2019 were also included. The final scoping review database thus consisted of 399 papers.

Results: A thematic structure emerged when categorizing articles in different subject areas, serving as a proxy for interest expressed from the research community. The research area has been an evolving one with about half of the 399 papers published during the past four years of the study period. Epidemiological modelling needs strengthening and there is a need for more and better surveillance systems, especially in lower- and middle-income countries. There is a wealth of information on the local and national uses and misuses of antibiotics. Educational and stewardship programmes basically lack evidence. Several studies address knowledge of the public and prescribers. The lessons for policy are conveyed in many alarming reports from national and international organizations.

Conclusions: Descriptive rather than theoretical ambitions have characterized the literature. If we want to better understand and explain the antibiotic situation from a behavioural perspective, the required approaches are lacking. A framework for an epidemiological causal web behind ABR is suggested and may serve to identify entry points for potential interventions.

Keywords: Antibiotic resistance; Antimicrobial Resistance; antimicrobial resistance; behaviour; drug resistance; global threat; health policy; prevention.

Publication types

• Systematic Review
• Anti-Bacterial Agents / pharmacology*
• Drug Resistance, Microbial*
• Global Health
• World Health Organization
• Anti-Bacterial Agents

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• Review Article
• Published: 30 April 2024

Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance

• Matthew J. Shepherd   ORCID: orcid.org/0000-0002-3283-9930 1 ,
• Taoran Fu   ORCID: orcid.org/0000-0003-4683-2171 1 ,
• Niamh E. Harrington 2 ,
• Anastasia Kottara 1 ,
• Kendall Cagney 2 ,
• James D. Chalmers 3 ,
• Steve Paterson   ORCID: orcid.org/0000-0002-1307-2981 2 ,
• Joanne L. Fothergill 2 &
• Michael A. Brockhurst   ORCID: orcid.org/0000-0003-0362-820X 1  

Nature Reviews Microbiology ( 2024 ) Cite this article

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• Antimicrobial resistance
• Bacterial infection

The ecological and evolutionary mechanisms of antimicrobial resistance (AMR) emergence within patients and how these vary across bacterial infections are poorly understood. Increasingly widespread use of pathogen genome sequencing in the clinic enables a deeper understanding of these processes. In this Review, we explore the clinical evidence to support four major mechanisms of within-patient AMR emergence in bacteria: spontaneous resistance mutations; in situ horizontal gene transfer of resistance genes; selection of pre-existing resistance; and immigration of resistant lineages. Within-patient AMR emergence occurs across a wide range of host niches and bacterial species, but the importance of each mechanism varies between bacterial species and infection sites within the body. We identify potential drivers of such differences and discuss how ecological and evolutionary analysis could be embedded within clinical trials of antimicrobials, which are powerful but underused tools for understanding why these mechanisms vary between pathogens, infections and individuals. Ultimately, improving understanding of how host niche, bacterial species and antibiotic mode of action combine to govern the ecological and evolutionary mechanism of AMR emergence in patients will enable more predictive and personalized diagnosis and antimicrobial therapies.

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The authors thank members of Microbial Evolution Research Manchester for discussion of the ideas in this manuscript. They gratefully acknowledge funding from the Wellcome Trust (Collaborative Award in Science 220243/Z/20/Z).

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M.J.S. researched data for the article, substantially contributed to discussion of content, wrote the article, and reviewed and edited the article. M.A.B., N.E.H. and J.L.F. substantially contributed to discussion of content, wrote the article, and reviewed and edited the article. A.K., K.C. and S.P. substantially contributed to discussion of content, and reviewed and edited the article. T.F. researched data for the article and substantially contributed to discussion of content. J.D.C. reviewed and edited the article.

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An antibiotic is an agent that is used against bacteria and can be classified as bactericidal (kills bacteria) or bacteriostatic (inhibits bacterial growth).

(AMR). The ability of microorganisms — bacteria, viruses, fungi or parasites — to withstand the effects of drugs that would normally inhibit or kill them. This phenomenon occurs when these organisms adapt and develop resistance mechanisms against antimicrobial agents, rendering previously effective treatments ineffective. Clinically, AMR is defined as when the minimum inhibitory concentration of the antimicrobial required to halt growth of a bacterium exceeds the clinical breakpoint, which is the highest concentration of that antimicrobial that can be given to a patient.

The ability of a population of microorganisms to survive transient exposure to a microbicidal agent. It differs from resistance in that the agent remains effective against the microorganism as measured by the minimum inhibitory concentration but requires more prolonged treatment to successfully eliminate the infection.

When a subpopulation of bacteria has a much higher tolerance to an antibiotic than the majority, that population is described as persistent. When the pressure of the antibiotic is removed, this persistent community can re-emerge, leading to recurrent infection despite antibiotic treatment.

Antimicrobial resistance that evolves through adaptation to another antimicrobial agent. This can occur when evolution of resistance to one agent confers resistance to another, typically due to a resistance mechanism that equally affects the action of all drugs within a class or to a nonspecific mechanism such as multidrug efflux pumps.

The reciprocal interactions and feedback between ecological processes and evolutionary changes in populations over short time scales. Ecological shifts promote adaptation of populations to their changing environments, and the resulting evolutionary changes can in turn shape ecological interactions. In the context of infections — the within-patient niche ecology will shape the evolution of antibiotic resistance, which can then affect the ecology of the infection itself through failure to clear the infection, disease progression and loss of sensitive strains and microflora.

The physiological or energetic cost of an advantage in reproductive success (fitness). For example, the fitness benefit of resistance to an antibiotic may come at the cost of a reduced growth rate. Importantly, this trade-off becomes a disadvantage when the antibiotic is absent.

The state in which a genetic variant becomes the only variant present for that specific locus. All individuals within the population share that same allele.

The change in frequency of an allele owing to random chance. The impact of such random effects is stronger at smaller population sizes. Newly generated random mutations present at very low frequency must escape random loss due to genetic drift even if they provide a benefit before becoming established at a higher frequency in the population.

(HGT). The process by which microorganisms may exchange genetic material that bypasses vertical transmission from parent to offspring.

A microbial strain with an unusually high mutation rate, often caused by deficiencies in DNA repair mechanisms. Under selection pressure from an antimicrobial agent, this rapid accumulation of spontaneous genetic mutations may accelerate the process of selection and thus evolution of antimicrobial resistance by increasing the likelihood of a mutation-conferring resistance to occur.

The process by which genetic variations within a population become more prevalent because they confer traits that influence the fitness of the organisms in their environment. In the context of antimicrobial therapy, selection refers to the survival and growth of resistant strains and the loss of sensitive ones during treatment.

An evolutionary event whereby a highly advantageous mutation rapidly increases in frequency owing to strong positive selective pressure. As it does, the genetic diversity in the region of the mutation decreases, creating a detectable signature of reduced allele frequency.

Also known as de novo mutations. Heritable alterations in the genome of a microorganism that arise spontaneously during replication or repair and were not previously present in the population or acquired from external sources of genetic material.

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Shepherd, M.J., Fu, T., Harrington, N.E. et al. Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance. Nat Rev Microbiol (2024). https://doi.org/10.1038/s41579-024-01041-1

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DOI : https://doi.org/10.1038/s41579-024-01041-1

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