Bacteria are infected by mobile genetic elements like plasmids and virulent phages, and those infections significantly impact bacterial ecology and evolution. Recent discoveries reveal that some plasmids carry anti-phage immune systems like CRISPR-Cas, suggesting that plasmids may participate in the coevolutionary arms race between virulent phages and bacteria. Intuitively, this seems reasonable as virulent phages kill the plasmid’s obligate host. However, the efficiency of CRISPR-Cas systems carried by plasmids can be expected to be lower than those carried by the chromosome due to continuous segregation loss, creating susceptible cells for phage amplification. To evaluate the anti-phage protection efficiency of CRISPR-Cas on plasmids, we develop a stochastic model describing the dynamics of a virulent phage infection against which a conjugative plasmid defends using CRISPR-Cas. We show that CRISPR-Cas on plasmids provides robust protection, except in limited parameter sets. In these cases, high segregation loss favours phage outbreaks by generating a population of defenceless cells on which the phage can evolve and escape CRISPR-Cas immunity. We show that the phage’s ability to exploit segregation loss depends strongly on the evolvability of both CRISPR-Cas and the phage itself.
Pathogens have evolved diverse strategies to maximize their transmission fitness. Here we investigate these strategies for directly transmitted pathogens using mathematical models of disease pathogenesis and transmission, modeling fitness as a function of within- and between-host pathogen dynamics. The within-host model includes realistic constraints on pathogen replication via resource depletion and cross-immunity between pathogen strains. We find three distinct types of infection emerge as maxima in the fitness landscape, each characterized by particular within-host dynamics, host population contact network structure, and transmission mode. These three infection types are associated with distinct non-overlapping ranges of levels of antigenic diversity, and well-defined patterns of within-host dynamics and between-host transmissibility. Fitness, quantified by the basic reproduction number, also falls within distinct ranges for each infection type. Every type is optimal for certain contact structures over a range of contact rates. Sexually transmitted infections and childhood diseases are identified as exemplar types for low and high contact rates, respectively. This work generates a plausible mechanistic hypothesis for the observed tradeoff between pathogen transmissibility and antigenic diversity, and shows how different classes of pathogens arise evolutionarily as fitness optima for different contact network structures and host contact rates. PMID: 19847288 Funding information This work was supported by: Medical Research Council, United Kingdom Howard Hughes Medical Institute, United States
Event Abstract Back to Event A global map of antimicrobial resistance in animals raised for food Thomas P. Van Boeckel1*, Joao Do Couto Pires1, Cheng Zhao1, Reshma Silvester2, Marius Gilbert3, Sebastian Bonhoeffer1, Ramanan Laxminarayan2, 4 and Julia Song4 1 ETH Zürich, Switzerland 2 Center for Disease Dynamics, Economics & Policy, United States 3 Free University of Brussels, Belgium 4 Princeton University, United States Background: Since the 1950s, the global increase in demand for meat and dairy has driven the use of antimicrobial drugs in agriculture. This practice has led to the development of antimicrobial resistance in animals and food products, with potentially harmful consequence for agricultural productivity, and human health. In low- and middle-income countries (LMICs), trends in AMR are poorly documented, and as a consequence the AMR status of LMICs remain largely unknow. On one hand, as in high-income countries, antimicrobials are used in LMICs to treat animals and as surrogates for poor hygiene on farms. AMR levels in LMICs could thus be exacerbated by lower biosecurity, less nutritious feed, and looser regulations on veterinary drugs. On the other hand, in LMICs, AMR levels may also be reduced by lower meat consumption and the very limited access to veterinary drugs in rural areas. Few works have attempted to disentangle the effect of those factors, and thus far, expert opinion has prevailed over an evidence-based assessment of the AMR status of LMICs. In this context, point prevalence surveys can be used as surrogates to systematic surveillance to provide a baseline of AMR levels, and guide interventions in LMICs. We extracted twelve thousand resistance rates from point prevalence surveys conducted in LMICs on common foodborne pathogens. Data on AMR was identified for Escherichia coli, non-Typhoidal Salmonella, Campylobacter spp., and Staphylococcus aureus. Resistance rates were manually extracted and curated across all the studies in a public database named RESBANK. We accounted for potential differences in accuracy of antimicrobial susceptibility testing between regions using the WHO External Quality Control System, as well as for temporal revisions of the breakpoints used for susceptibility testing. For each study, we calculated the proportion of drugs tested with resistance levels higher than 50% (P50), and used ensemble geospatial modelling (stacked generalization) to produced global maps of P50, at 10Km resolution. From 2000 to 2018, the proportion of antimicrobials with resistance higher than 50% increased twofold in chickens, and threefold in pigs. China, Northeast and South India represented the largest hotspots of resistance, while new hotspots are emerging in Central India, Brazil, and Kenya. Our maps suggest that worldwide a substantial proportion of chicken, cattle and pigs are raised in hotspots of AMR in 2013. Interpretations: We report a rapid but geographically heterogenous increase of AMR in animals in LMICs. These trends call for urgent actions to preserve the efficacy of existing drugs used in animal agriculture, limit the future economic burden of AMR on farmers. Our global maps of AMR provide a baseline to outline priorities for interventions in LMICs, and monitor their efficacy in the future. Acknowledgements The Swiss National Science Foundation The Branco Weiss Foundation The Bill and Melinda Gates Foundation. The Princeton University Health Ggand Challenges Program Keywords: maps, Species distribution models (SDM), Antimicrobial resistance (AMR), Low and Middle Income Countries, Kriging Conference: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019. Presentation Type: Regular oral presentation Topic: Spatio-temporal surveillance and modeling approaches Citation: Van Boeckel TP, Do Couto Pires J, Zhao C, Silvester R, Gilbert M, Bonhoeffer S, Laxminarayan R and Song J (2019). A global map of antimicrobial resistance in animals raised for food. Front. Vet. Sci. Conference Abstract: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data. doi: 10.3389/conf.fvets.2019.05.00092 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 09 Jun 2019; Published Online: 27 Sep 2019. * Correspondence: Prof. Thomas P Van Boeckel, ETH Zürich, Zurich, Switzerland, thomas.vanboeckel@env.ethz.ch Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Thomas P Van Boeckel Joao Do Couto Pires Cheng Zhao Reshma Silvester Marius Gilbert Sebastian Bonhoeffer Ramanan Laxminarayan Julia Song Google Thomas P Van Boeckel Joao Do Couto Pires Cheng Zhao Reshma Silvester Marius Gilbert Sebastian Bonhoeffer Ramanan Laxminarayan Julia Song Google Scholar Thomas P Van Boeckel Joao Do Couto Pires Cheng Zhao Reshma Silvester Marius Gilbert Sebastian Bonhoeffer Ramanan Laxminarayan Julia Song PubMed Thomas P Van Boeckel Joao Do Couto Pires Cheng Zhao Reshma Silvester Marius Gilbert Sebastian Bonhoeffer Ramanan Laxminarayan Julia Song Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.
Abstract Bacteria are infected by mobile genetic elements like plasmids and virulent phages, and those infections significantly impact bacterial ecology and evolution. Recent discoveries reveal that some plasmids carry anti-phage immune systems like CRISPR-Cas, suggesting that plasmids may participate in the coevolutionary arms-race between virulent phages and bacteria. Intuitively, this seems reasonable as virulent phages kill the plasmid’s obligate host. However, the efficiency of CRISPR-Cas systems carried by plasmids can be expected to be lower than those carried by the chromosome due to continuous segregation loss, creating susceptible cells for phage amplification. To evaluate the anti-phage protection efficiency of CRISPR-Cas on plasmids, we develop a stochastic model describing the dynamics of a virulent phage infection against which a conjugative plasmid defends using CRISPR-Cas. We show that CRISPR-Cas on plasmids provides robust protection, except in limited parameter-sets. In these cases, high segregation favours phage outbreaks by generating a population of defenceless cells on which the phage can evolve and escape CRISPR-Cas immunity. We show that the phage’s ability to exploit segregation loss depends strongly on the evolvability of both CRISPR-Cas and the phage itself.
Abstract While the Vibrio splendidus species is best known as an opportunistic pathogen in oysters, the Vibrio splendidus sp. 1A01 strain was first identified as an early colonizer of synthetic chitin particles incubated in seawater. To gain a better understanding of its metabolism, a genome-scale metabolic model (GSMM) of V. splendidus sp. 1A01 was reconstructed. GSMMs enable us to simulate all metabolic reactions in a bacterial cell using Flux Balance Analysis. A draft model was built using an automated pipeline from BioCyc. Manual curation was then performed based on experimental data, in part by gap-filling metabolic pathways and tailoring the model’s biomass reaction to V. splendidus sp. 1A01. The challenges of building a metabolic model for a marine microorganism like V. splendidus sp. 1A01 are described.
The test-trace-isolate-quarantine (TTIQ) strategy, where confirmed-positive pathogen carriers are isolated from the community and their recent close contacts are identified and pre-emptively quarantined, is used to break chains of transmission during a disease outbreak. The protocol is frequently followed after an individual presents with disease symptoms, at which point they will be tested for the pathogen. This TTIQ strategy, along with hygiene and social distancing measures, make up the non-pharmaceutical interventions that are utilised to suppress the ongoing COVID-19 pandemic. Here we develop a tractable mathematical model of disease transmission and the TTIQ intervention to quantify how the probability of detecting and isolating a case following symptom onset, the fraction of contacts that are identified and quarantined, and the delays inherent to these processes impact epidemic growth. In the model, the timing of disease transmission and symptom onset, as well as the frequency of asymptomatic cases, is based on empirical distributions of SARS-CoV-2 infection dynamics, while the isolation of confirmed cases and quarantine of their contacts is implemented by truncating their respective infectious periods. We find that a successful TTIQ strategy requires intensive testing: the majority of transmission is prevented by isolating symptomatic individuals and doing so in a short amount of time. Despite the lesser impact, additional contact tracing and quarantine increases the parameter space in which an epidemic is controllable and is necessary to control epidemics with a high reproductive number. TTIQ could remain an important intervention for the foreseeable future of the COVID-19 pandemic due to slow vaccine rollout and highly-transmissible variants with the potential for vaccine escape. Our results can be used to assess how TTIQ can be improved and optimised, and the methodology represents an improvement over previous quantification methods that is applicable to future epidemic scenarios.
The use of structured treatment interruption (STI) in human immunodeficiency virus (HIV)–infected subjects is currently being studied as an alternative therapeutic strategy for HIV-1. The potential risk for selection of drug-resistant HIV-1 variants during STI is unknown and remains a concern. Therefore, the emergence of drug resistance in sequential plasma samples obtained from 28 subjects with chronic HIV infection was studied. They underwent 4 cycles of 2-week STI, followed by 8-week retreatment with highly active antiretroviral therapy identical to that used before STI, and they had never failed treatment before undergoing STI. At week 40, treatment was stopped for a longer period. Minor populations of drug-resistant variants were detected by quantitative real-time polymerase chain reaction, by use of allele-discriminating oligonucleotides for 2 key resistance mutations: L90M (protease) and M184V (reverse transcriptase). The approximate discriminative power was 0.1%. In 14 of 25 and in 3 of 25 subjects, the M184V and the L90M mutations, respectively, were detected as minor populations, at different times during STI. Overall, these results indicate that, in subjects undergoing multiple STIs, HIV-1 variants carrying drug-resistance mutations can emerge during periods of increased HIV-1 replication
When and under which conditions antibiotic combination therapy decelerates rather than accelerates resistance evolution is not well understood. We examined the effect of combining antibiotics on within-patient resistance development across various bacterial pathogens and antibiotics.We searched CENTRAL, EMBASE and PubMed for (quasi)-randomised controlled trials (RCTs) published from database inception to November 24th, 2022. Trials comparing antibiotic treatments with different numbers of antibiotics were included. A patient was considered to have acquired resistance if, at the follow-up culture, a resistant bacterium was detected that had not been present in the baseline culture. We combined results using a random effects model and performed meta-regression and stratified analyses. The trials' risk of bias was assessed with the Cochrane tool.42 trials were eligible and 29, including 5054 patients, were qualified for statistical analysis. In most trials, resistance development was not the primary outcome and studies lacked power. The combined odds ratio (OR) for the acquisition of resistance comparing the group with the higher number of antibiotics with the comparison group was 1.23 (95% CI 0.68-2.25), with substantial between-study heterogeneity (I2 =77%). We identified tentative evidence for potential beneficial or detrimental effects of antibiotic combination therapy for specific pathogens or medical conditions.The evidence for combining a higher number of antibiotics compared to fewer from RCTs is scarce and overall, is compatible with both benefit or harm. Trials powered to detect differences in resistance development or well-designed observational studies are required to clarify the impact of combination therapy on resistance.
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