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Rahbé E, Glaser P, Opatowski L. Modeling the transmission of antibiotic-resistant Enterobacterales in the community: A systematic review. Epidemics 2024; 48:100783. [PMID: 38944024 DOI: 10.1016/j.epidem.2024.100783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 04/19/2024] [Accepted: 06/20/2024] [Indexed: 07/01/2024] Open
Abstract
BACKGROUND Antibiotic-resistant Enterobacterales (ARE) are a public health threat worldwide. Dissemination of these opportunistic pathogens has been largely studied in hospitals. Despite high prevalence of asymptomatic colonization in the community in some regions of the world, less is known about ARE acquisition and spread in this setting. As explaining the community ARE dynamics has not been straightforward, mathematical models can be key to explore underlying phenomena and further evaluate the impact of interventions to curb ARE circulation outside of hospitals. METHODS We conducted a systematic review of mathematical modeling studies focusing on the transmission of AR-E in the community, excluding models only specific to hospitals. We extracted model features (population, setting), formalism (compartmental, individual-based), biological hypotheses (transmission, infection, antibiotic impact, resistant strain specificities) and main findings. We discussed additional mechanisms to be considered, open scientific questions, and most pressing data needs. RESULTS We identified 18 modeling studies focusing on the human transmission of ARE in the community (n=11) or in both community and hospital (n=7). Models aimed at (i) understanding mechanisms driving resistance dynamics; (ii) identifying and quantifying transmission routes; or (iii) evaluating public health interventions to reduce resistance. To overcome the difficulty of reproducing observed ARE dynamics in the community using the classical two-strains competition model, studies proposed to include mechanisms such as within-host strain competition or a strong host population structure. Studies inferring model parameters from longitudinal carriage data were mostly based on models considering the ARE strain only. They showed differences in ARE carriage duration depending on the acquisition mode: returning travelers have a significantly shorter carriage duration than discharged hospitalized patient or healthy individuals. Interestingly, predictions across models regarding the success of public health interventions to reduce ARE rates depended on pathogens, settings, and antibiotic resistance mechanisms. For E. coli, reducing person-to-person transmission in the community had a stronger effect than reducing antibiotic use in the community. For Klebsiella pneumoniae, reducing antibiotic use in hospitals was more efficient than reducing community use. CONCLUSIONS This study raises the limited number of modeling studies specifically addressing the transmission of ARE in the community. It highlights the need for model development and community-based data collection especially in low- and middle-income countries to better understand acquisition routes and their relative contribution to observed ARE levels. Such modeling will be critical to correctly design and evaluate public health interventions to control ARE transmission in the community and further reduce the associated infection burden.
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Affiliation(s)
- Eve Rahbé
- Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Antimicrobials Evasion research unit, Paris, France; Université Paris-Saclay, UVSQ, Inserm, CESP, Anti-infective evasion and pharmacoepidemiology research team, Montigny-Le-Bretonneux, France.
| | - Philippe Glaser
- Institut Pasteur, Ecology and Evolution of Antibiotic Resistance research unit, Université Paris Cité, Paris, France
| | - Lulla Opatowski
- Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Antimicrobials Evasion research unit, Paris, France; Université Paris-Saclay, UVSQ, Inserm, CESP, Anti-infective evasion and pharmacoepidemiology research team, Montigny-Le-Bretonneux, France.
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Vincent J, Tenore A, Mattei MR, Frunzo L. Modelling Plasmid-Mediated Horizontal Gene Transfer in Biofilms. Bull Math Biol 2024; 86:63. [PMID: 38664322 DOI: 10.1007/s11538-024-01289-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 03/27/2024] [Indexed: 05/23/2024]
Abstract
In this study, we present a mathematical model for plasmid spread in a growing biofilm, formulated as a nonlocal system of partial differential equations in a 1-D free boundary domain. Plasmids are mobile genetic elements able to transfer to different phylotypes, posing a global health problem when they carry antibiotic resistance factors. We model gene transfer regulation influenced by nearby potential receptors to account for recipient-sensing. We also introduce a promotion function to account for trace metal effects on conjugation, based on literature data. The model qualitatively matches experimental results, showing that contaminants like toxic metals and antibiotics promote plasmid persistence by favoring plasmid carriers and stimulating conjugation. Even at higher contaminant concentrations inhibiting conjugation, plasmid spread persists by strongly inhibiting plasmid-free cells. The model also replicates higher plasmid density in biofilm's most active regions.
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Affiliation(s)
- Julien Vincent
- Department of Mathematics and Applications "Renato Caccioppoli", University of Naples Federico II, Via Cintia 26, 80126, Monte S. Angelo, Naples, Italy
- Microbial Ecology Laboratory, University of Galway, University Road, Galway, H91 TK33, Ireland
| | - Alberto Tenore
- Department of Mathematics and Applications "Renato Caccioppoli", University of Naples Federico II, Via Cintia 26, 80126, Monte S. Angelo, Naples, Italy
| | - Maria Rosaria Mattei
- Department of Mathematics and Applications "Renato Caccioppoli", University of Naples Federico II, Via Cintia 26, 80126, Monte S. Angelo, Naples, Italy.
| | - Luigi Frunzo
- Department of Mathematics and Applications "Renato Caccioppoli", University of Naples Federico II, Via Cintia 26, 80126, Monte S. Angelo, Naples, Italy
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3
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Liu F, Luo Y, Xu T, Lin H, Qiu Y, Li B. Current examining methods and mathematical models of horizontal transfer of antibiotic resistance genes in the environment. Front Microbiol 2024; 15:1371388. [PMID: 38638913 PMCID: PMC11025395 DOI: 10.3389/fmicb.2024.1371388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 03/11/2024] [Indexed: 04/20/2024] Open
Abstract
The increasing prevalence of antibiotic resistance genes (ARGs) in the environment has garnered significant attention due to their health risk to human beings. Horizontal gene transfer (HGT) is considered as an important way for ARG dissemination. There are four general routes of HGT, including conjugation, transformation, transduction and vesiduction. Selection of appropriate examining methods is crucial for comprehensively understanding characteristics and mechanisms of different HGT ways. Moreover, combined with the results obtained from different experimental methods, mathematical models could be established and serve as a powerful tool for predicting ARG transfer dynamics and frequencies. However, current reviews of HGT for ARG spread mainly focus on its influencing factors and mechanisms, overlooking the important roles of examining methods and models. This review, therefore, delineated four pathways of HGT, summarized the strengths and limitations of current examining methods, and provided a comprehensive summing-up of mathematical models pertaining to three main HGT ways of conjugation, transformation and transduction. Finally, deficiencies in current studies were discussed, and proposed the future perspectives to better understand and assess the risks of ARG dissemination through HGT.
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Affiliation(s)
- Fan Liu
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, China
| | - Yuqiu Luo
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, China
| | - Tiansi Xu
- School of Environment, Tsinghua University, Beijing, China
| | - Hai Lin
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, China
| | - Yong Qiu
- School of Environment, Tsinghua University, Beijing, China
| | - Bing Li
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, China
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4
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Tartik M. The priority of yeast to select among various DNA options to repair genome breaks by homologous recombination. Mol Biol Rep 2024; 51:99. [PMID: 38206425 DOI: 10.1007/s11033-023-09058-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 11/02/2023] [Indexed: 01/12/2024]
Abstract
BACKGROUND Horizontal gene transfer (HGT) is considered an important mechanism to contribute to the evolution of bacteria, plants, and animals by allowing the movement of genetic material between organisms, in difference to vertical inheritance. Thereby it can also play a significant role in spreading traits like antibiotic resistance among bacteria and virulence factors between pathogens. During the HGT, organisms take up free DNA from the environment and incorporate it into their genomes. Although HGT is known to be carried out by many organisms, there is limited information on how organisms select which genetic material for horizontal transfer. Here we have investigated the preference priority of Saccharomyces cerevisiae between different options of gene source presented under certain stress conditions to repair a double-strand break (DSB) in DNA via HR. RESULTS Each genetic module was designed with appropriate sequences being homologous for two sides of the DSB, which is important for yeast to repair the fracture with HR. S. cerevisiae made a random selection between two heterologous T1 (44%) and T2 (56%) modules to repair DSB. Interestingly, yeast corrected the DNA break only with the T3 module (almost 100%) when the homologous T3 module was an option for the selection. It seems that S. cerevisiae tends to prefer T3 over alternatives to fix DSBs when it exists among the options. CONCLUSIONS It seems that S. cerevisiae have a preference for priority to select a particular one under certain conditions when it has various DNA options to repair a DSB in its genome, further studies are required to support our findings.
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Affiliation(s)
- Musa Tartik
- Department of Molecular Biology and Genetics, Faculty of Arts and Sciences, Bingol University, 12000, Bingol, Turkey.
- Department of Life Sciences, Chalmers University of Technology, Kemivägen 10, 412 96, Gothenburg, Sweden.
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5
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Geoffroy F, Uecker H. Limits to evolutionary rescue by conjugative plasmids. Theor Popul Biol 2023; 154:102-117. [PMID: 37923145 DOI: 10.1016/j.tpb.2023.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 10/06/2023] [Accepted: 10/16/2023] [Indexed: 11/07/2023]
Abstract
Plasmids may carry genes coding for beneficial traits and thus contribute to adaptation of bacterial populations to environmental stress. Conjugative plasmids can horizontally transfer between cells, which a priori facilitates the spread of adaptive alleles. However, if the potential recipient cell is already colonized by another incompatible plasmid, successful transfer may be prevented. Competition between plasmids can thus limit horizontal transfer. Previous modeling has indeed shown that evolutionary rescue by a conjugative plasmid is hampered by incompatible resident plasmids in the population. If the rescue plasmid is a mutant variant of the resident plasmid, both plasmids transfer at the same rates. A high conjugation rate then has two, potentially opposing, effects - a direct positive effect on spread of the rescue plasmid and an increase in the fraction of resident plasmid cells. This raises the question whether a high conjugation rate always benefits evolutionary rescue. In this article, we systematically analyze three models of increasing complexity to disentangle the benefits and limits of increasing horizontal gene transfer in the presence of plasmid competition and plasmid costs. We find that the net effect can be positive or negative and that the optimal transfer rate is thus not always the highest one. These results can contribute to our understanding of the many facets of plasmid-driven adaptation and the wide range of transfer rates observed in nature.
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Affiliation(s)
- Félix Geoffroy
- Research group Stochastic Evolutionary Dynamics, Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany.
| | - Hildegard Uecker
- Research group Stochastic Evolutionary Dynamics, Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany
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6
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Dewan I, Uecker H. A mathematician's guide to plasmids: an introduction to plasmid biology for modellers. MICROBIOLOGY (READING, ENGLAND) 2023; 169:001362. [PMID: 37505810 PMCID: PMC10433428 DOI: 10.1099/mic.0.001362] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 07/03/2023] [Indexed: 07/29/2023]
Abstract
Plasmids, extrachromosomal DNA molecules commonly found in bacterial and archaeal cells, play an important role in bacterial genetics and evolution. Our understanding of plasmid biology has been furthered greatly by the development of mathematical models, and there are many questions about plasmids that models would be useful in answering. In this review, we present an introductory, yet comprehensive, overview of the biology of plasmids suitable for modellers unfamiliar with plasmids who want to get up to speed and to begin working on plasmid-related models. In addition to reviewing the diversity of plasmids and the genes they carry, their key physiological functions, and interactions between plasmid and host, we also highlight selected plasmid topics that may be of particular interest to modellers and areas where there is a particular need for theoretical development. The world of plasmids holds a great variety of subjects that will interest mathematical biologists, and introducing new modellers to the subject will help to expand the existing body of plasmid theory.
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Affiliation(s)
- Ian Dewan
- Research Group Stochastic Evolutionary Dynamics, Department of Theoretical Biology, Max Planck Institute for Evolutionary Biology, Plön, Germany
| | - Hildegard Uecker
- Research Group Stochastic Evolutionary Dynamics, Department of Theoretical Biology, Max Planck Institute for Evolutionary Biology, Plön, Germany
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7
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Pilosof S. Conceptualizing microbe-plasmid communities as complex adaptive systems. Trends Microbiol 2023:S0966-842X(23)00025-2. [PMID: 36822952 DOI: 10.1016/j.tim.2023.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 12/29/2022] [Accepted: 01/23/2023] [Indexed: 02/24/2023]
Abstract
Plasmids shape microbial communities' diversity, structure, and function. Nevertheless, we lack a mechanistic understanding of how community structure and dynamics emerge from local microbe-plasmid interactions and coevolution. Addressing this gap is challenging because multiple processes operate simultaneously at multiple levels of organization. For example, immunity operates between a plasmid and a cell, but incompatibility mechanisms regulate coexistence between plasmids. Conceptualizing microbe-plasmid communities as complex adaptive systems is a promising approach to overcoming these challenges. I illustrate how agent-based evolutionary modeling, extended by network analysis, can be used to quantify the relative importance of local processes governing community dynamics. These theoretical developments can advance our understanding of plasmid ecology and evolution, especially when combined with empirical data.
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Affiliation(s)
- Shai Pilosof
- Department of Life Sciences, Ben-Gurion University of the Negev, Be'er-Sheva, Israel.
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8
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Leclerc QJ, Lindsay JA, Knight GM. Modelling the synergistic effect of bacteriophage and antibiotics on bacteria: Killers and drivers of resistance evolution. PLoS Comput Biol 2022; 18:e1010746. [PMID: 36449520 PMCID: PMC9744316 DOI: 10.1371/journal.pcbi.1010746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 12/12/2022] [Accepted: 11/17/2022] [Indexed: 12/05/2022] Open
Abstract
Bacteriophage (phage) are bacterial predators that can also spread antimicrobial resistance (AMR) genes between bacteria by generalised transduction. Phage are often present alongside antibiotics in the environment, yet evidence of their joint killing effect on bacteria is conflicted, and the dynamics of transduction in such systems are unknown. Here, we combine in vitro data and mathematical modelling to identify conditions where phage and antibiotics act in synergy to remove bacteria or drive AMR evolution. We adapt a published model of phage-bacteria dynamics, including transduction, to add the pharmacodynamics of erythromycin and tetracycline, parameterised from new in vitro data. We simulate a system where two strains of Staphylococcus aureus are present at stationary phase, each carrying either an erythromycin or tetracycline resistance gene, and where multidrug-resistant bacteria can be generated by transduction only. We determine rates of bacterial clearance and multidrug-resistant bacteria appearance, when either or both antibiotics and phage are present at varying timings and concentrations. Although phage and antibiotics act in synergy to kill bacteria, by reducing bacterial growth antibiotics reduce phage production. A low concentration of phage introduced shortly after antibiotics fails to replicate and exert a strong killing pressure on bacteria, instead generating multidrug-resistant bacteria by transduction which are then selected for by the antibiotics. Multidrug-resistant bacteria numbers were highest when antibiotics and phage were introduced simultaneously. The interaction between phage and antibiotics leads to a trade-off between a slower clearing rate of bacteria (if antibiotics are added before phage), and a higher risk of multidrug-resistance evolution (if phage are added before antibiotics), exacerbated by low concentrations of phage or antibiotics. Our results form hypotheses to guide future experimental and clinical work on the impact of phage on AMR evolution, notably for studies of phage therapy which should investigate varying timings and concentrations of phage and antibiotics.
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Affiliation(s)
- Quentin J. Leclerc
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Antimicrobial Resistance Centre, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Institute for Infection & Immunity, St George’s University of London, London, United Kingdom
- * E-mail: ,
| | - Jodi A. Lindsay
- Institute for Infection & Immunity, St George’s University of London, London, United Kingdom
| | - Gwenan M. Knight
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Antimicrobial Resistance Centre, London School of Hygiene and Tropical Medicine, London, United Kingdom
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9
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Ali A, Imran M, Sial S, Khan A. Effective antibiotic dosing in the presence of resistant strains. PLoS One 2022; 17:e0275762. [PMID: 36215219 PMCID: PMC9551627 DOI: 10.1371/journal.pone.0275762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 09/22/2022] [Indexed: 11/25/2022] Open
Abstract
Mathematical models can be very useful in determining efficient and successful antibiotic dosing regimens. In this study, we consider the problem of determining optimal antibiotic dosing when bacteria resistant to antibiotics are present in addition to susceptible bacteria. We consider two different models of resistance acquisition, both involve the horizontal transfer (HGT) of resistant genes from a resistant to a susceptible strain. Modeling studies on HGT and study of optimal antibiotic dosing protocols in the literature, have been mostly focused on transfer of resistant genes via conjugation, with few studies on HGT via transformation. We propose a deterministic ODE based model of resistance acquisition via transformation, followed by a model that takes into account resistance acquisition through conjugation. Using a numerical optimization algorithm to determine the 'best' antibiotic dosing strategy. To illustrate our optimization method, we first consider optimal dosing when all the bacteria are susceptible to the antibiotic. We then consider the case where resistant strains are present. We note that constant periodic dosing may not always succeed in eradicating the bacteria while an optimal dosing protocol is successful. We determine the optimal dosing strategy in two different scenarios: one where the total bacterial population is to be minimized, and the next where we want to minimize the bacterial population at the end of the dosing period. We observe that the optimal strategy in the first case involves high initial dosing with dose tapering as time goes on, while in the second case, the optimal dosing strategy is to increase the dosing at the beginning of the dose cycles followed by a possible dose tapering. As a follow up study we intend to look at models where 'persistent' bacteria may be present in additional to resistant and susceptible strain and determine the optimal dosing protocols in this case.
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Affiliation(s)
- Asgher Ali
- Department of Mathematics, Lahore University of Management Sciences, Lahore, Pakistan
- * E-mail:
| | - Mudassar Imran
- Department of Mathematics and Sciences, Ajman University, Ajman, UAE
| | - Sultan Sial
- Department of Mathematics, Lahore University of Management Sciences, Lahore, Pakistan
| | - Adnan Khan
- Department of Mathematics, Lahore University of Management Sciences, Lahore, Pakistan
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10
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Emergence and spread of antibiotic-resistant foodborne pathogens from farm to table. Food Sci Biotechnol 2022; 31:1481-1499. [PMID: 36065433 PMCID: PMC9435411 DOI: 10.1007/s10068-022-01157-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 07/26/2022] [Accepted: 08/17/2022] [Indexed: 11/13/2022] Open
Abstract
Antibiotics have been overused and misused for preventive and therapeutic purposes. Specifically, antibiotics are frequently used as growth promoters for improving productivity and performance of food-producing animals such as pigs, cattle, and poultry. The increasing use of antibiotics has been of great concern worldwide due to the emergence of antibiotic resistant bacteria. Food-producing animals are considered reservoirs for antibiotic resistance genes (ARGs) and residual antibiotics that transfer from the farm through the table. The accumulation of residual antibiotics can lead to additional antibiotic resistance in bacteria. Therefore, this review evaluates the risk of carriage and spread of antibiotic resistance through food chain and the potential impact of antibiotic use in food-producing animals on food safety. This review also includes in-depth discussion of promising antibiotic alternatives such as vaccines, immune modulators, phytochemicals, antimicrobial peptides, probiotics, and bacteriophages.
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11
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Abstract
Bacteriophage (phage) are both predators and evolutionary drivers for bacteria, notably contributing to the spread of antimicrobial resistance (AMR) genes by generalized transduction. Our current understanding of this complex relationship is limited. We used an interdisciplinary approach to quantify how these interacting dynamics can lead to the evolution of multidrug-resistant bacteria. We cocultured two strains of methicillin-resistant Staphylococcus aureus, each harboring a different antibiotic resistance gene, with generalized transducing phage. After a growth phase of 8 h, bacteria and phage surprisingly coexisted at a stable equilibrium in our culture, the level of which was dependent on the starting concentration of phage. We detected double-resistant bacteria as early as 7 h, indicating that transduction of AMR genes had occurred. We developed multiple mathematical models of the bacteria and phage relationship and found that phage-bacteria dynamics were best captured by a model in which phage burst size decreases as the bacteria population reaches stationary phase and where phage predation is frequency-dependent. We estimated that one in every 108 new phage generated was a transducing phage carrying an AMR gene and that double-resistant bacteria were always predominantly generated by transduction rather than by growth. Our results suggest a shift in how we understand and model phage-bacteria dynamics. Although rates of generalized transduction could be interpreted as too rare to be significant, they are sufficient in our system to consistently lead to the evolution of multidrug-resistant bacteria. Currently, the potential of phage to contribute to the growing burden of AMR is likely underestimated. IMPORTANCE Bacteriophage (phage), viruses that can infect and kill bacteria, are being investigated through phage therapy as a potential solution to the threat of antimicrobial resistance (AMR). In reality, however, phage are also natural drivers of bacterial evolution by transduction when they accidentally carry nonphage DNA between bacteria. Using laboratory work and mathematical models, we show that transduction leads to evolution of multidrug-resistant bacteria in less than 8 h and that phage production decreases when bacterial growth decreases, allowing bacteria and phage to coexist at stable equilibria. The joint dynamics of phage predation and transduction lead to complex interactions with bacteria, which must be clarified to prevent phage from contributing to the spread of AMR.
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12
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A Chebyshev Collocation Approach to Solve Fractional Fisher–Kolmogorov–Petrovskii–Piskunov Equation with Nonlocal Condition. FRACTAL AND FRACTIONAL 2022. [DOI: 10.3390/fractalfract6030160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
We provide a detailed description of a numerical approach that makes use of the shifted Chebyshev polynomials of the sixth kind to approximate the solution of some fractional order differential equations. Specifically, we choose the fractional Fisher–Kolmogorov–Petrovskii–Piskunov equation (FFKPPE) to describe this method. We write our approximate solution in the product form, which consists of unknown coefficients and shifted Chebyshev polynomials. To compute the numerical values of coefficients, we use the initial and boundary conditions and the collocation technique to create a system of equations whose number matches the unknowns. We test the applicability and accuracy of this numerical approach using two examples.
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13
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Alderliesten JB, Zwart MP, de Visser JAGM, Stegeman A, Fischer EAJ. Second compartment widens plasmid invasion conditions: Two-compartment pair-formation model of conjugation in the gut. J Theor Biol 2022; 533:110937. [PMID: 34678229 DOI: 10.1016/j.jtbi.2021.110937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 10/12/2021] [Accepted: 10/13/2021] [Indexed: 11/20/2022]
Abstract
Understanding under which conditions conjugative plasmids encoding antibiotic resistance can invade bacterial communities in the gut is of particular interest to combat the spread of antibiotic resistance within and between animals and humans. We extended a one-compartment model of conjugation to a two-compartment model, to analyse how differences in plasmid dynamics in the gut lumen and at the gut wall affect the invasion of plasmids. We compared scenarios with one and two compartments, different migration rates between the lumen and wall compartments, and different population dynamics. We focused on the effect of attachment and detachment rates on plasmid dynamics, explicitly describing pair formation followed by plasmid transfer in the pairs. The parameter space allowing plasmid invasion in the one-compartment model is affected by plasmid costs and intrinsic conjugation rates of the transconjugant, but not by these characteristics of the donor. The parameter space allowing plasmid invasion in the two-compartment model is affected by attachment and detachment rates in the lumen and wall compartment, and by the bacterial density at the wall. The one- and two-compartment models predict the same parameter space for plasmid invasion if the conditions in both compartments are equal to the conditions in the one-compartment model. In contrast, the addition of the wall compartment widens the parameter space allowing invasion compared with the one-compartment model, if the density at the wall is higher than in the lumen, or if the attachment rate at the wall is high and the detachment rate at the wall is low. We also compared the pair-formation models with bulk-conjugation models that describe conjugation by instantaneous transfer of the plasmid at contact between cells, without explicitly describing pair formation. Our results show that pair-formation and bulk-conjugation models predict the same parameter space for plasmid invasion. From our simulations, we conclude that conditions at the gut wall should be taken into account to describe plasmid dynamics in the gut and that transconjugant characteristics rather than donor characteristics should be used to parameterize the models.
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Affiliation(s)
- Jesse B Alderliesten
- Department of Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands.
| | - Mark P Zwart
- Department of Microbial Ecology, The Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, the Netherlands.
| | - J Arjan G M de Visser
- Laboratory of Genetics, Wageningen University & Research, Wageningen, the Netherlands.
| | - Arjan Stegeman
- Department of Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands.
| | - Egil A J Fischer
- Department of Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands.
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14
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Baquero F, Martínez JL, F. Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance. Clin Microbiol Rev 2021; 34:e0005019. [PMID: 34190572 PMCID: PMC8404696 DOI: 10.1128/cmr.00050-19] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.
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Affiliation(s)
- F. Baquero
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - J. L. Martínez
- National Center for Biotechnology (CNB-CSIC), Madrid, Spain
| | - V. F. Lanza
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Central Bioinformatics Unit, Ramón y Cajal Institute for Health Research (IRYCIS), Madrid, Spain
| | - J. Rodríguez-Beltrán
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - J. C. Galán
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - A. San Millán
- National Center for Biotechnology (CNB-CSIC), Madrid, Spain
| | - R. Cantón
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - T. M. Coque
- Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Institute for Health Research (IRYCIS), Network Center for Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
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15
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Hernández-Beltrán JCR, San Millán A, Fuentes-Hernández A, Peña-Miller R. Mathematical Models of Plasmid Population Dynamics. Front Microbiol 2021; 12:606396. [PMID: 34803935 PMCID: PMC8600371 DOI: 10.3389/fmicb.2021.606396] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 10/14/2021] [Indexed: 11/24/2022] Open
Abstract
With plasmid-mediated antibiotic resistance thriving and threatening to become a serious public health problem, it is paramount to increase our understanding of the forces that enable the spread and maintenance of drug resistance genes encoded in mobile genetic elements. The relevance of plasmids as vehicles for the dissemination of antibiotic resistance genes, in addition to the extensive use of plasmid-derived vectors for biotechnological and industrial purposes, has promoted the in-depth study of the molecular mechanisms controlling multiple aspects of a plasmids' life cycle. This body of experimental work has been paralleled by the development of a wealth of mathematical models aimed at understanding the interplay between transmission, replication, and segregation, as well as their consequences in the ecological and evolutionary dynamics of plasmid-bearing bacterial populations. In this review, we discuss theoretical models of plasmid dynamics that span from the molecular mechanisms of plasmid partition and copy-number control occurring at a cellular level, to their consequences in the population dynamics of complex microbial communities. We conclude by discussing future directions for this exciting research topic.
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Affiliation(s)
| | | | | | - Rafael Peña-Miller
- Center for Genomic Sciences, Universidad Nacional Autónoma de México, Cuernavaca, Mexico
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16
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Modeling the ecology of parasitic plasmids. THE ISME JOURNAL 2021; 15:2843-2852. [PMID: 33833414 PMCID: PMC8443676 DOI: 10.1038/s41396-021-00954-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 02/18/2021] [Accepted: 02/26/2021] [Indexed: 02/01/2023]
Abstract
Plasmids are autonomous genetic elements that can be exchanged between microorganisms via horizontal gene transfer (HGT). Despite the central role they play in antibiotic resistance and modern biotechnology, our understanding of plasmids' natural ecology is limited. Recent experiments have shown that plasmids can spread even when they are a burden to the cell, suggesting that natural plasmids may exist as parasites. Here, we use mathematical modeling to explore the ecology of such parasitic plasmids. We first develop models of single plasmids and find that a plasmid's population dynamics and optimal infection strategy are strongly determined by the plasmid's HGT mechanism. We then analyze models of co-infecting plasmids and show that parasitic plasmids are prone to a "tragedy of the commons" in which runaway plasmid invasion severely reduces host fitness. We propose that this tragedy of the commons is averted by selection between competing populations and demonstrate this effect in a metapopulation model. We derive predicted distributions of unique plasmid types in genomes-comparison to the distribution of plasmids in a collection of 17,725 genomes supports a model of parasitic plasmids with positive plasmid-plasmid interactions that ameliorate plasmid fitness costs or promote the invasion of new plasmids.
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17
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Smith DR, Temime L, Opatowski L. Microbiome-pathogen interactions drive epidemiological dynamics of antibiotic resistance: A modeling study applied to nosocomial pathogen control. eLife 2021; 10:68764. [PMID: 34517942 PMCID: PMC8560094 DOI: 10.7554/elife.68764] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 08/31/2021] [Indexed: 12/16/2022] Open
Abstract
The human microbiome can protect against colonization with pathogenic antibiotic-resistant bacteria (ARB), but its impacts on the spread of antibiotic resistance are poorly understood. We propose a mathematical modeling framework for ARB epidemiology formalizing within-host ARB-microbiome competition, and impacts of antibiotic consumption on microbiome function. Applied to the healthcare setting, we demonstrate a trade-off whereby antibiotics simultaneously clear bacterial pathogens and increase host susceptibility to their colonization, and compare this framework with a traditional strain-based approach. At the population level, microbiome interactions drive ARB incidence, but not resistance rates, reflecting distinct epidemiological relevance of different forces of competition. Simulating a range of public health interventions (contact precautions, antibiotic stewardship, microbiome recovery therapy) and pathogens (Clostridioides difficile, methicillin-resistant Staphylococcus aureus, multidrug-resistant Enterobacteriaceae) highlights how species-specific within-host ecological interactions drive intervention efficacy. We find limited impact of contact precautions for Enterobacteriaceae prevention, and a promising role for microbiome-targeted interventions to limit ARB spread.
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Affiliation(s)
- David Rm Smith
- Institut Pasteur, Epidemiology and Modelling of Antibiotic Evasion (EMAE), Paris, France.,Université Paris-Saclay, UVSQ, Inserm, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France.,Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire national des arts et métiers, Paris, France
| | - Laura Temime
- Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire national des arts et métiers, Paris, France.,PACRI unit, Institut Pasteur, Conservatoire national des arts et métiers, Paris, France
| | - Lulla Opatowski
- Institut Pasteur, Epidemiology and Modelling of Antibiotic Evasion (EMAE), Paris, France.,Université Paris-Saclay, UVSQ, Inserm, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France
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18
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Bier E, Nizet V. Driving to Safety: CRISPR-Based Genetic Approaches to Reducing Antibiotic Resistance. Trends Genet 2021; 37:745-757. [PMID: 33745750 DOI: 10.1016/j.tig.2021.02.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 02/23/2021] [Accepted: 02/23/2021] [Indexed: 02/07/2023]
Abstract
Bacterial resistance to antibiotics has reached critical levels, skyrocketing in hospitals and the environment and posing a major threat to global public health. The complex and challenging problem of reducing antibiotic resistance (AR) requires a network of both societal and science-based solutions to preserve the most lifesaving pharmaceutical intervention known to medicine. In addition to developing new classes of antibiotics, it is essential to safeguard the clinical efficacy of existing drugs. In this review, we examine the potential application of novel CRISPR-based genetic approaches to reducing AR in both environmental and clinical settings and prolonging the utility of vital antibiotics.
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Affiliation(s)
- Ethan Bier
- Tata Institute for Genetics and Society, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0349, USA; Section of Cell and Developmental Biology, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0349, USA.
| | - Victor Nizet
- Tata Institute for Genetics and Society, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0349, USA; Collaborative to Halt Antibiotic-Resistant Microbes, Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0687, USA; Skaggs School of Pharmacy & Pharmaceutical Sciences, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0687, USA
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19
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Roberts MG, Burgess S, Toombs-Ruane LJ, Benschop J, Marshall JC, French NP. Combining mutation and horizontal gene transfer in a within-host model of antibiotic resistance. Math Biosci 2021; 339:108656. [PMID: 34216634 DOI: 10.1016/j.mbs.2021.108656] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 06/17/2021] [Accepted: 06/18/2021] [Indexed: 11/25/2022]
Abstract
Antibiotics are used extensively to control infections in humans and animals, usually by injection or a course of oral tablets. There are several methods by which bacteria can develop antimicrobial resistance (AMR), including mutation during DNA replication and plasmid mediated horizontal gene transfer (HGT). We present a model for the development of AMR within a single host animal. We derive criteria for a resistant mutant strain to replace the existing wild-type bacteria, and for co-existence of the wild-type and mutant. Where resistance develops through HGT via conjugation we derive criteria for the resistant strain to be excluded or co-exist with the wild-type. Our results are presented as bifurcation diagrams with thresholds determined by the relative fitness of the bacteria strains, expressed in terms of reproduction numbers. The results show that it is possible that applying and then relaxing antibiotic control may lead to the bacterial load returning to pre-control levels, but with an altered structure with regard to the variants that comprise the population. Removing antimicrobial selection pressure will not necessarily reduce AMR and, at a population level, other approaches to infection prevention and control are required, particularly when AMR is driven by both mutation and mobile genetic elements.
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Affiliation(s)
- M G Roberts
- School of Natural & Computational Sciences, Massey University, Private Bag 102 904, North Shore Mail Centre, Auckland, 0745, New Zealand; New Zealand Institute for Advanced Study, Massey University, Private Bag 102 904, North Shore Mail Centre, Auckland, 0745, New Zealand; Infectious Disease Research Centre, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand.
| | - S Burgess
- Infectious Disease Research Centre, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand; School of Veterinary Sciences, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand; mEpilab, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand
| | - L J Toombs-Ruane
- Infectious Disease Research Centre, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand; School of Veterinary Sciences, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand; mEpilab, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand
| | - J Benschop
- Infectious Disease Research Centre, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand; School of Veterinary Sciences, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand; mEpilab, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand
| | - J C Marshall
- Infectious Disease Research Centre, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand; mEpilab, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand; School of Fundamental Sciences, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand
| | - N P French
- New Zealand Institute for Advanced Study, Massey University, Private Bag 102 904, North Shore Mail Centre, Auckland, 0745, New Zealand; Infectious Disease Research Centre, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand; mEpilab, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand; New Zealand Food Safety Science & Research Centre, Massey University, Private Bag 11-222, Palmerston North, 4442, New Zealand
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20
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Abstract
Although wastewater and sewage systems are known to be significant reservoirs of antibiotic-resistant bacterial populations and periodic outbreaks of drug-resistant infection, there is little quantitative understanding of the drivers behind resistant population growth in these settings. In order to fill this gap in quantitative understanding of the development of antibiotic-resistant infections in wastewater, we have developed a mathematical model synthesizing many known drivers of antibiotic resistance in these settings to help predict the growth of resistant populations in different environmental scenarios. A number of these drivers of drug-resistant infection outbreak, including antibiotic residue concentration, antibiotic interaction, chromosomal mutation, and horizontal gene transfer, have not previously been integrated into a single computational model. We validated the outputs of the model with quantitative studies conducted on the eVOLVER continuous culture platform. Our integrated model shows that low levels of antibiotic residues present in wastewater can lead to increased development of resistant populations and that the dominant mechanism of resistance acquisition in these populations is horizontal gene transfer rather than acquisition of chromosomal mutations. Additionally, we found that synergistic antibiotics at low concentrations lead to increased resistant population growth. These findings, consistent with recent experimental and field studies, provide new quantitative knowledge on the evolution of antibiotic-resistant bacterial reservoirs, and the model developed herein can be adapted for use as a prediction tool in public health policy making, particularly in low-income settings where water sanitation issues remain widespread and disease outbreaks continue to undermine public health efforts. IMPORTANCE The rate at which antimicrobial resistance (AMR) has developed and spread throughout the world has increased in recent years, and according to the Review on Antimicrobial Resistance in 2014, it is suggested that the current rate will lead to AMR-related deaths of several million people by 2050 (Review on Antimicrobial Resistance, Tackling a Crisis for the Health and Wealth of Nations, 2014). One major reservoir of resistant bacterial populations that has been linked to outbreaks of drug-resistant bacterial infections but is not well understood is in wastewater settings, where antibiotic pollution is often present. Using ordinary differential equations incorporating several known drivers of resistance in wastewater, we find that interactions between antibiotic residues and horizontal gene transfer significantly affect the growth of resistant bacterial reservoirs.
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21
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IBARGÜEN-MONDRAGÓN EDUARDO, PRIETO KERNEL, HIDALGO-BONILLA SANDRAPATRICIA. A MODEL ON BACTERIAL RESISTANCE CONSIDERING A GENERALIZED LAW OF MASS ACTION FOR PLASMID REPLICATION. J BIOL SYST 2021. [DOI: 10.1142/s0218339021400118] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Bacterial plasmids play a fundamental role in antibiotic resistance. However, a lack of knowledge about their biology is an obstacle in fully understanding the mechanisms and properties of plasmid-mediated resistance. This has motivated investigations of real systems in vitro to analyze the transfer and replication of plasmids. In this work, we address this issue with mathematical modeling. We formulate and perform a qualitative analysis of a nonlinear system of ordinary differential equations describing the competition dynamics between plasmids and sensitive and resistant bacteria. In addition, we estimated parameter values from empirical data. Our model predicts scenarios consistent with biological phenomena. The elimination or spread of infection depends on factors associated with bacterial reproduction and the transfer and replication of plasmids. From the estimated parameters, three bacterial growth experiments were analyzed in vitro. We determined the experiment with the highest bacterial growth rate and the highest rate of plasmid transfer. Moreover, numerical simulations were performed to predict bacterial growth.
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Affiliation(s)
| | - KERNEL PRIETO
- Instituto de Matemáticas, Universidad Nacional Autónoma de México, Cuernavaca, México
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22
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Lagerstrom KM, Hadly EA. The under-investigated wild side of Escherichia coli: genetic diversity, pathogenicity and antimicrobial resistance in wild animals. Proc Biol Sci 2021; 288:20210399. [PMID: 33849316 PMCID: PMC8059539 DOI: 10.1098/rspb.2021.0399] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 03/18/2021] [Indexed: 12/12/2022] Open
Abstract
A striking paucity of information exists on Escherichia coli in wild animals despite evidence that they harbour pathogenic and antimicrobial-resistant E. coli in their gut microbiomes and may even serve as melting pots for novel genetic combinations potentially harmful to human health. Wild animals have been implicated as the source of pathogenic E. coli outbreaks in agricultural production, but a lack of knowledge surrounding the genetics of E. coli in wild animals complicates source tracking and thus contamination curtailment efforts. As human populations continue to expand and invade wild areas, the potential for harmful microorganisms to transfer between humans and wildlife increases. Here, we conducted a literature review of the small body of work on E. coli in wild animals. We highlight the geographic and host taxonomic coverage to date, and in each, identify significant gaps. We summarize the current understanding of E. coli in wild animals, including its genetic diversity, host and geographic distribution, and transmission pathways within and between wild animal and human populations. The knowledge gaps we identify call for greater research efforts to understand the existence of E. coli in wild animals, especially in light of the potentially strong implications for global public health.
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Affiliation(s)
| | - Elizabeth A. Hadly
- Department of Biology, Stanford University, Stanford, CA, USA
- Stanford Woods Institute for the Environment, Stanford University, Stanford, CA, USA
- Center for Innovation in Global Health, Stanford University, Stanford, CA, USA
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23
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Zwanzig M. The ecology of plasmid-coded antibiotic resistance: a basic framework for experimental research and modeling. Comput Struct Biotechnol J 2020; 19:586-599. [PMID: 33510864 PMCID: PMC7807137 DOI: 10.1016/j.csbj.2020.12.027] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 12/16/2020] [Accepted: 12/20/2020] [Indexed: 12/27/2022] Open
Abstract
Many antibiotic resistance genes are associated with plasmids. The ecological success of these mobile genetic elements within microbial communities depends on varying mechanisms to secure their own propagation, not only on environmental selection. Among the most important are the cost of plasmids and their ability to be transferred to new hosts through mechanisms such as conjugation. These are regulated by dynamic control systems of the conjugation machinery and genetic adaptations that plasmid-host pairs can acquire in coevolution. However, in complex communities, these processes and mechanisms are subject to a variety of interactions with other bacterial species and other plasmid types. This article summarizes basic plasmid properties and ecological principles particularly important for understanding the persistence of plasmid-coded antibiotic resistance in aquatic environments. Through selected examples, it further introduces to the features of different types of simulation models such as systems of ordinary differential equations and individual-based models, which are considered to be important tools to understand these complex systems. This ecological perspective aims to improve the way we study and understand the dynamics, diversity and persistence of plasmids and associated antibiotic resistance genes.
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Affiliation(s)
- Martin Zwanzig
- Faculty of Environmental Sciences, Technische Universität Dresden, Pienner Str. 8, D-01737 Tharandt, Germany
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24
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Abstract
Conjugative plasmids can mediate the spread and maintenance of diverse traits and functions in microbial communities. This role depends on the plasmid's ability to persist in a population. However, for a community consisting of multiple populations transferring multiple plasmids, the conditions underlying plasmid persistence are poorly understood. Here, we describe a plasmid-centric framework that makes it computationally feasible to analyze gene flow in complex communities. Using this framework, we derive the 'persistence potential': a general, heuristic metric that predicts the persistence and abundance of any plasmids. We validate the metric with engineered microbial consortia transferring mobilizable plasmids and with quantitative data available in the literature. We believe that our framework and the resulting metric will facilitate a quantitative understanding of natural microbial communities and the engineering of microbial consortia.
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Affiliation(s)
- Teng Wang
- Department of Biomedical Engineering, Duke University, Durham, NC, 27708, USA
| | - Lingchong You
- Department of Biomedical Engineering, Duke University, Durham, NC, 27708, USA.
- Center for Genomic and Computational Biology, Duke University, Durham, NC, 27708, USA.
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, 27708, USA.
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25
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Hooban B, Joyce A, Fitzhenry K, Chique C, Morris D. The role of the natural aquatic environment in the dissemination of extended spectrum beta-lactamase and carbapenemase encoding genes: A scoping review. WATER RESEARCH 2020; 180:115880. [PMID: 32438141 DOI: 10.1016/j.watres.2020.115880] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 04/22/2020] [Accepted: 04/23/2020] [Indexed: 06/11/2023]
Abstract
The natural aquatic environment is a significant contributor to the development and circulation of clinically significant antibiotic resistance genes (ARGs). The potential for the aquatic environment to act as a reservoir for ARG accumulation in areas receiving anthropogenic contamination has been thoroughly researched. However, the emergence of novel ARGs in the absence of external influences, as well as the capacity of environmental bacteria to disseminate ARGs via mobile genetic elements remain relatively unchallenged. In order to address these knowledge gaps, this scoping literature review was established focusing on the detection of two important and readily mobile ARGs, namely, extended spectrum beta-lactamase (ESBL) and carbapenemase genes. This review included 41 studies from 19 different countries. A range of different water bodies including rivers (n = 26), seawaters (n = 6) and lakes (n = 3), amongst others, were analysed in the included studies. ESBL genes were reported in 29/41 (70.7%) studies, while carbapenemase genes were reported in 13/41 (31.7%), including joint reporting in 9 studies. The occurrence of mobile genetic elements was evaluated, which included the detection of integrons (n = 22), plasmids (n = 18), insertion sequences (n = 4) and transposons (n = 3). The ability of environmental bacteria to successfully transfer resistance genes via conjugation was also examined in 11 of the included studies. The findings of this scoping review expose the presence of clinically significant ARGs in the natural aquatic environment and highlights the potential ability of environmental isolates to disseminate these genes among different bacterial species. As such, the results presented demonstrate how anthropogenic point discharges may not act as the sole contributor to the development and spread of clinically significant antibiotic resistances. A number of critical knowledge gaps in current research were also identified. Key highlights include the limited number of studies focusing on antibiotic resistance in uncontaminated aquatic environments as well as the lack of standardisation among methodologies of reviewed investigations.
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Affiliation(s)
- Brigid Hooban
- Antimicrobial Resistance and Microbial Ecology Group, School of Medicine, National University of Ireland Galway, Ireland; Centre for One Health, Ryan Institute, National University of Ireland Galway, Ireland.
| | - Aoife Joyce
- Antimicrobial Resistance and Microbial Ecology Group, School of Medicine, National University of Ireland Galway, Ireland; Centre for One Health, Ryan Institute, National University of Ireland Galway, Ireland
| | - Kelly Fitzhenry
- Antimicrobial Resistance and Microbial Ecology Group, School of Medicine, National University of Ireland Galway, Ireland; Centre for One Health, Ryan Institute, National University of Ireland Galway, Ireland
| | - Carlos Chique
- School of Biological, Earth and Environmental Science (BEES), University College Cork, Ireland; Environmental Research Institute, University College Cork, Ireland
| | - Dearbháile Morris
- Antimicrobial Resistance and Microbial Ecology Group, School of Medicine, National University of Ireland Galway, Ireland; Centre for One Health, Ryan Institute, National University of Ireland Galway, Ireland
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26
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Simulating the Influence of Conjugative-Plasmid Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model. Antimicrob Agents Chemother 2020; 64:AAC.00593-20. [PMID: 32457104 PMCID: PMC7526830 DOI: 10.1128/aac.00593-20] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 05/15/2020] [Indexed: 12/17/2022] Open
Abstract
Bacterial plasmids harboring antibiotic resistance genes are critical in the spread of antibiotic resistance. It is known that plasmids differ in their kinetic values, i.e., conjugation rate, segregation rate by copy number incompatibility with related plasmids, and rate of stochastic loss during replication. They also differ in cost to the cell in terms of reducing fitness and in the frequency of compensatory mutations compensating plasmid cost. However, we do not know how variation in these values influences the success of a plasmid and its resistance genes in complex ecosystems, such as the microbiota. Genes are in plasmids, plasmids are in cells, and cells are in bacterial populations and microbiotas, which are inside hosts, and hosts are in human communities at the hospital or the community under various levels of cross-colonization and antibiotic exposure. Differences in plasmid kinetics might have consequences on the global spread of antibiotic resistance. New membrane computing methods help to predict these consequences. In our simulation, conjugation frequency of at least 10-3 influences the dominance of a strain with a resistance plasmid. Coexistence of different antibiotic resistances occurs if host strains can maintain two copies of similar plasmids. Plasmid loss rates of 10-4 or 10-5 or plasmid fitness costs of ≥0.06 favor plasmids located in the most abundant species. The beneficial effect of compensatory mutations for plasmid fitness cost is proportional to this cost at high mutation frequencies (10-3 to 10-5). The results of this computational model clearly show how changes in plasmid kinetics can modify the entire population ecology of antibiotic resistance in the hospital setting.
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27
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Emamalipour M, Seidi K, Zununi Vahed S, Jahanban-Esfahlan A, Jaymand M, Majdi H, Amoozgar Z, Chitkushev LT, Javaheri T, Jahanban-Esfahlan R, Zare P. Horizontal Gene Transfer: From Evolutionary Flexibility to Disease Progression. Front Cell Dev Biol 2020; 8:229. [PMID: 32509768 PMCID: PMC7248198 DOI: 10.3389/fcell.2020.00229] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 03/17/2020] [Indexed: 12/11/2022] Open
Abstract
Flexibility in the exchange of genetic material takes place between different organisms of the same or different species. This phenomenon is known to play a key role in the genetic, physiological, and ecological performance of the host. Exchange of genetic materials can cause both beneficial and/or adverse biological consequences. Horizontal gene transfer (HGT) or lateral gene transfer (LGT) as a general mechanism leads to biodiversity and biological innovations in nature. HGT mediators are one of the genetic engineering tools used for selective introduction of desired changes in the genome for gene/cell therapy purposes. HGT, however, is crucial in development, emergence, and recurrence of various human-related diseases, such as cancer, genetic-, metabolic-, and neurodegenerative disorders and can negatively affect the therapeutic outcome by promoting resistant forms or disrupting the performance of genome editing toolkits. Because of the importance of HGT and its vital physio- and pathological roles, here the variety of HGT mechanisms are reviewed, ranging from extracellular vesicles (EVs) and nanotubes in prokaryotes to cell-free DNA and apoptotic bodies in eukaryotes. Next, we argue that HGT plays a role both in the development of useful features and in pathological states associated with emerging and recurrent forms of the disease. A better understanding of the different HGT mediators and their genome-altering effects/potentials may pave the way for the development of more effective therapeutic and diagnostic regimes.
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Affiliation(s)
- Melissa Emamalipour
- Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Khaled Seidi
- Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | | | | | - Mehdi Jaymand
- Nano Drug Delivery Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Hasan Majdi
- Department of Medical Nanotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Zohreh Amoozgar
- Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - L T Chitkushev
- Department of Computer Science, Metropolitan College, Boston University, Boston, MA, United States.,Health Informatics Lab, Metropolitan College, Boston University, Boston, MA, United States
| | - Tahereh Javaheri
- Health Informatics Lab, Metropolitan College, Boston University, Boston, MA, United States
| | - Rana Jahanban-Esfahlan
- Department of Medical Biotechnology, School of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Peyman Zare
- Faculty of Medicine, Cardinal Stefan Wyszyński University in Warsaw, Warsaw, Poland.,Dioscuri Center of Chromatin Biology and Epigenomics, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
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28
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Evans DR, Griffith MP, Sundermann AJ, Shutt KA, Saul MI, Mustapha MM, Marsh JW, Cooper VS, Harrison LH, Van Tyne D. Systematic detection of horizontal gene transfer across genera among multidrug-resistant bacteria in a single hospital. eLife 2020; 9:53886. [PMID: 32285801 PMCID: PMC7156236 DOI: 10.7554/elife.53886] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2019] [Accepted: 03/14/2020] [Indexed: 12/16/2022] Open
Abstract
Multidrug-resistant bacteria pose a serious health threat, especially in hospitals. Horizontal gene transfer (HGT) of mobile genetic elements (MGEs) facilitates the spread of antibiotic resistance, virulence, and environmental persistence genes between nosocomial pathogens. We screened the genomes of 2173 bacterial isolates from healthcare-associated infections from a single hospital over 18 months, and identified identical nucleotide regions in bacteria belonging to distinct genera. To further resolve these shared sequences, we performed long-read sequencing on a subset of isolates and generated highly contiguous genomes. We then tracked the appearance of ten different plasmids in all 2173 genomes, and found evidence of plasmid transfer independent from bacterial transmission. Finally, we identified two instances of likely plasmid transfer within individual patients, including one plasmid that likely transferred to a second patient. This work expands our understanding of HGT in healthcare settings, and can inform efforts to limit the spread of drug-resistant pathogens in hospitals.
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Affiliation(s)
- Daniel R Evans
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, United States.,Department of Infectious Diseases and Microbiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, United States
| | - Marissa P Griffith
- Microbial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, United States
| | - Alexander J Sundermann
- Microbial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, United States
| | - Kathleen A Shutt
- Microbial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, United States
| | - Melissa I Saul
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, United States
| | - Mustapha M Mustapha
- Microbial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, United States
| | - Jane W Marsh
- Microbial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, United States
| | - Vaughn S Cooper
- Department of Microbiology and Molecular Genetics, and Center for Evolutionary Biology and Medicine, University of Pittsburgh, Pittsburgh, United States
| | - Lee H Harrison
- Microbial Genomic Epidemiology Laboratory, Infectious Diseases Epidemiology Research Unit, University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh, United States
| | - Daria Van Tyne
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, United States
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