Strategies to combat antimicrobial resistance: anti-plasmid and plasmid curing

Buckner, Michelle M. C.; Ciusa, Maria Laura; Piddock, Laura J. V.

doi:10.1093/femsre/fuy031

Cited by 148 publications

(106 citation statements)

References 187 publications

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“…This can be further facilitated by the presence of resistance gene carrying plasmids that serve as a vehicle for gene transfer across species 67 , and were commonly found in the hospital environment (n=1400). The development and use of anti-plasmid agents 68,69 could thus be a complimentary strategy to reduce the spread of antibiotic resistance through hospital environments.…”

Section: Discussionmentioning

confidence: 99%

Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment

Chng

Bertrand

et al. 2019

Preprint

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There is growing attention surrounding hospital acquired infections (HAIs) due to high associated healthcare costs, compounded by the scourge of widespread multi-antibiotic resistance. Although hospital environment disinfection is well acknowledged to be key for infection control, an understanding of colonization patterns and resistome profiles of environment-dwelling microbes is currently lacking. We report the first extensive genomic characterization of microbiomes (355), common HAI-associated microbes (891) and transmissible drug resistance cassettes (1435) in a tertiary hospital environment based on a 2-timepoint sampling of 179 sites from 45 beds. Deep shotgun metagenomic sequencing unveiled two distinct ecological niches of microbes and antibiotic resistance genes characterized by biofilm-forming and human microbiome influenced environments that display corresponding patterns of divergence over space and time. To study common nosocomial pathogens that were typically present at low abundances, a combination of culture enrichment and long-read nanopore sequencing was used to obtain thousands of high contiguity genomes (2347) and closed plasmids (5910), a significant fraction of which (>58%) are not represented in current sequence databases. These high-quality assemblies and metadata enabled a rich characterization of resistance gene combinations, plasmid architectures, and the dynamic nature of hospital environment resistomes and their reservoirs. Phylogenetic analysis identified multidrug resistant clonal strains as being more widely disseminated and stably colonizing across hospital sites. Further genomic comparisons with clinical isolates across multiple species supports the hypothesis that multidrug resistant strains can persist in the hospital environment for extended periods (>8 years) to opportunistically infect patients. These findings highlight the importance of characterizing antibiotic resistance reservoirs in the hospital environment and establishes the feasibility of systematic genomic surveys to help target resources more efficiently for preventing HAIs.

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Section: Discussionmentioning

confidence: 99%

Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment

Chng

Bertrand

et al. 2019

Preprint

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“…Curing is a method to eliminate plasmids during bacteria replication. [ 14 ] Although there is no available technology reported to date, the use of nanomaterials as plasmid‐curing agents may be future targets for inhibition of conjugational transfer of antibiotic‐resistant plasmids and to decrease the spread of antibiotic resistance plasmids among bacteria present in pathogenic biofilms. Table 1 summarizes the major studies reporting the use of nanomaterials to combat antibiotic‐resistant and multidrug‐resistant bacteria over the past 5 years.…”

Section: Addressing Niches In Contemporary Antimicrobial Therapeuticsmentioning

confidence: 99%

Metal‐Based Nanomaterials in Biomedical Applications: Antimicrobial Activity and Cytotoxicity Aspects

Makvandi

Wang

Zare

et al. 2020

Adv Funct Materials

442

368

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Microbial colonization on material surfaces is ubiquitous. Biofilms derived from surface-colonized microbes pose serious problems to the society from both an economical perspective and a health concern. Incorporation of antimicrobial nanocompounds within or on the surface of materials, or by coatings, to prevent microbial adhesion or kill the microorganisms after their attachment to biofilms, represents an important strategy in an increasingly challenging field. Over the last decade, many studies have been devoted to preparing meta-based nanomaterials that possess antibacterial, antiviral, and antifungal activities to combat pathogen-related diseases. Herein, an overview on the state-of-the-art antimicrobial nanosized metal-based compounds is provided, including metal and metal oxide nanoparticles as well as transition metal nanosheets. The antimicrobial mechanism of these nanostructures and their biomedical applications such as catheters, implants, medical delivery systems, tissue engineering, and dentistry are discussed. Their properties as well as potential caveats such as cytotoxicity, diminishing efficacy, and induction of antimicrobial resistance of materials incorporating these nanostructures are reviewed to provide a backdrop for future research.

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“…Plasmid transmission rates (the conjugation rates in our model) have been considered one of the main drivers of the spread of antibiotic resistance genes in natural bacterial populations (27). In fact, there is a line of research on ecology-evolution (eco-evo) drugs that seeks to develop plasmid conjugation inhibitors to reduce the burden of antibiotic resistance (48, 49). In our complex multilevel system and under the fixed conditions of the simulation, only high (10 −3 ) conjugation rates clearly influence the dissemination of plasmids and the resistances they contain.…”

Section: Discussionmentioning

confidence: 99%

Simulating the Influence of Conjugative Plasmids Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model

Campos

San-Milán

Sempere

et al. 2020

Preprint

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20Plasmids harboring antibiotic resistance genes differ in their kinetic values as plasmid 21 conjugation rate, segregation rate by incompatibility with related plasmids, rate of 22 stochastic loss during replication, cost reducing the host-cell fitness, and frequency of 23 compensatory mutations to reduce plasmid cost, depending on the cell mutation 24 frequency. How variation in these values influence the success of a plasmid and their 25 resistance genes in complex ecosystems, as the microbiota? Genes are located in 26 plasmids, plasmids in cells, cells in populations. These populations are embedded in 27 ensembles of species in different human hosts, are able to exchange between them 28 bacterial ensembles during cross-infection and are located in the hospital or the 29 community setting, under various levels of antibiotic exposure. Simulations using new 30 membrane computing methods help predict the influence of plasmid kinetic values on 31 such multilevel complex system. In our simulation, conjugation frequency needed to be 32 at least 10 -3 to clearly influence the dominance of a strain with a resistant plasmid. Host 33 strains able to stably maintain two copies of similar plasmids harboring different 34 resistances, coexistence of these resistances can occur in the population. Plasmid loss 35 rates of 10 -4 or 10 -5 or plasmid fitness costs ≥0.06 favor the plasmids located in the most 36 abundant species. The beneficial effect of compensatory mutations for plasmid fitness 37 cost is proportional to this cost, only at high mutation frequencies (10 -3 -10 -5 ). 38Membrane computing helps set a multilevel landscape to study the effect of changes in 39 plasmid kinetic values on the success of resistant organisms in complex ecosystems. 40 41 42 43 44 Plasmid kinetics are widely assumed to necessarily influence the spread of antibiotic 45 resistance genes in bacterial populations and ecosystems (1-10). The main parameters 46 that affect plasmid kinetics are: a) the rate of plasmid conjugation/transfer (the rate at 47 which a bacterial cell harboring a conjugative plasmid [donor] transfers this plasmid to 48 a recipient cell; b) the segregation rate due to plasmid incompatibility (considering the 49 number of plasmid genome copies that are stably maintained in a bacterial cell); c) the 50 rate of plasmid cost (the reduction imposed by the presence [and transfer] of a plasmid 51 in the growth rate of the host bacterial cell); d) the rate of plasmid cost compensation 52 (measuring the effect of mutations reducing plasmid cost); e) the frequency of 53 mutational events in the plasmid or bacterial genome; and f) the rate of plasmid loss (the 54 rate at which plasmids are lost during the bacterial replication process). 55 However, the effects of these changes on the kinetics of plasmid resistance genes among 56 bacterial populations are necessarily influenced by numerous other factors acting in 57 actual biological ecosystems, such as the intestinal microbiota. Of these factors, our 58 previously published studies...

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Strategies to combat antimicrobial resistance: anti-plasmid and plasmid curing

Cited by 148 publications

References 187 publications

Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment

Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment

Metal‐Based Nanomaterials in Biomedical Applications: Antimicrobial Activity and Cytotoxicity Aspects

Simulating the Influence of Conjugative Plasmids Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model

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