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Abstract
The emerging antibiotic resistance in pathogenic bacteria is a key problem in modern
medicine that has led to a search for novel therapeutic strategies. A potential approach
for managing such bacteria involves the use of their natural killers, namely lytic
bacteriophages. Another effective method involves the use of metal nanoparticles with
antimicrobial properties. However, the use of lytic phages armed with nanoparticles
as an effective antimicrobial strategy, particularly with respect to biofilms, remains
unexplored. Here, we show that T7 phages armed with silver nanoparticles exhibit greater
efficacy in terms of controlling bacterial biofilm, compared with phages or nanoparticles
alone. We initially identified a novel silver nanoparticle-binding peptide, then constructed
T7 phages that successfully displayed the peptide on the outer surface of the viral
head. These recombinant, AgNP-binding phages could effectively eradicate bacterial
biofilm, even when used at low concentrations. Additionally, when used at concentrations
that could eradicate bacterial biofilm, T7 phages armed with silver nanoparticles
were not toxic to eukaryotic cells. Our results show that the novel combination of
lytic phages with phage-bound silver nanoparticles is an effective, synergistic and
safe strategy for the treatment of bacterial biofilms.
Summary Background Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen–drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date. Methods We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen–drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drug-resistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level. Findings On the basis of our predictive statistical models, there were an estimated 4·95 million (3·62–6·57) deaths associated with bacterial AMR in 2019, including 1·27 million (95% UI 0·911–1·71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27·3 deaths per 100 000 (20·9–35·3), and lowest in Australasia, at 6·5 deaths (4·3–9·4) per 100 000. Lower respiratory infections accounted for more than 1·5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000–1 270 000) deaths attributable to AMR and 3·57 million (2·62–4·78) deaths associated with AMR in 2019. One pathogen–drug combination, meticillin-resistant S aureus, caused more than 100 000 deaths attributable to AMR in 2019, while six more each caused 50 000–100 000 deaths: multidrug-resistant excluding extensively drug-resistant tuberculosis, third-generation cephalosporin-resistant E coli, carbapenem-resistant A baumannii, fluoroquinolone-resistant E coli, carbapenem-resistant K pneumoniae, and third-generation cephalosporin-resistant K pneumoniae. Interpretation To our knowledge, this study provides the first comprehensive assessment of the global burden of AMR, as well as an evaluation of the availability of data. AMR is a leading cause of death around the world, with the highest burdens in low-resource settings. Understanding the burden of AMR and the leading pathogen–drug combinations contributing to it is crucial to making informed and location-specific policy decisions, particularly about infection prevention and control programmes, access to essential antibiotics, and research and development of new vaccines and antibiotics. There are serious data gaps in many low-income settings, emphasising the need to expand microbiology laboratory capacity and data collection systems to improve our understanding of this important human health threat. Funding Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.
[1
]Department of Molecular Virology, Faculty of Biology, Institute of Microbiology,
University of Warsaw, (
https://ror.org/039bjqg32)
Miecznikowa 1, 02-096 Warsaw, Poland
[2
]GRID grid.413454.3, ISNI 0000 0001 1958 0162, Dioscuri Centre for Physics and Chemistry of Bacteria, Institute of Physical Chemistry,
, Polish Academy of Sciences, ; Kasprzaka 44/52, 01-224 Warsaw, Poland
[3
]GRID grid.413454.3, ISNI 0000 0001 1958 0162, Nalecz Institute of Biocybernetics and Biomedical Engineering, , Polish Academy of Sciences, ; Ks. Trojdena 4, 02-109 Warsaw, Poland
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History
Date
received
: 20
March
2023
Date
accepted
: 15
April
2024
Funding
Funded by: Narodowe Centrum Nauki (National Science Centre)
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