Phage resistance-mediated trade-offs with antibiotic resistance in Salmonella Typhimurium

Laure, Nana Nguefang; Ahn, Juhee

doi:10.1016/j.micpath.2022.105732

Cited by 8 publications

(3 citation statements)

References 67 publications

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“…Another aspect worthy of consideration is the observed ability of phages to increase vulnerability towards antibiotics, as was tested in Salmonella by Laure and Ahn ( 43 ) as well as Turner et al ( 44 ), who observed an increase in antibiotic sensitivity in P. aeruginosa after phage treatment. While we did not experimentally test whether our phages were capable of increasing susceptibility to antibiotics, it may certainly be interesting to follow up on this topic, using our library of phage-resistant mutants.…”

Section: Discussionmentioning

confidence: 99%

Optimizing bacteriophage treatment of resistant Pseudomonas

Ulrich,

Steiner,

Giez

et al. 2024

mSphere

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Phage therapy is increasing in relevance as an alternative treatment to combat antibiotic resistant bacteria. Phage cocktails are the state-of-the-art method of administering phages in clinical settings, preferred over monophage treatment because of their ability to eliminate multiple bacterial strains and reduce resistance formation. In our study, we compare monophage applications and phage cocktails to our chosen method of phage sequential treatments. To do so, we isolated four novel bacteriophages capable of infecting Pseudomonas alcaligenes T3, a close relative of P. aeruginosa , and characterized them using sequencing and transmission electron microscopy. While investigating monophage treatments, we observed that different phage concentrations had a strong impact on the timing and amount of resistance formation. When using phage cocktails, we observed that P. alcaligenes were capable of forming resistance in the same timespan it took them to become resistant to single phages. We isolated mutants resistant to each single phage as well as mutants exposed to phage cocktails, resulting in bacteria resistant to all four phages at once. Sequencing these mutants showed that different treatments yielded unique single nucleotide polymorphism mutation patterns. In order to combat resistance formation, we added phages one by one in intervals of 24 h, thus managing to delay resistance development and keeping bacterial growth significantly lower compared to phage cocktails. IMPORTANCE WHO declared antimicrobial resistance a top threat to global health; while antibiotics have stood at the forefront in the fight against bacterial infection, the increasing number of multidrug-resistant bacteria highlights a need to branch out in order to address the threat of antimicrobial resistance. Bacteriophages, viruses solely infecting bacteria, could present a solution due to their abundance, versatility, and adaptability. For this study, we isolated new phages infecting a fast-mutating Pseudomonas alcaligenes strain capable of forming resistance within 30 h. By using a sequential treatment approach of adding one phage after another, we were able to curb bacterial growth significantly more compared to state-of-the-art phage cocktails.

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Section: Discussionmentioning

confidence: 99%

Optimizing bacteriophage treatment of resistant Pseudomonas

Ulrich,

Steiner,

Giez

et al. 2024

mSphere

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“…In accordance with our hypothesis, we found that a fluorescent derivative of ciprofloxacin accumulates in individual B. thailandensis cells at significantly higher levels in the presence of ΦBp-AMP1 compared with in its absence. Noteworthy, previous studies using phage that have the efflux component TolC as a receptor, demonstrated that emergence of phage resistance in bacteria via tolC mutations led to increased antibiotic susceptibility 70,94,95 . Finally, it is conceivable that the phage-antibiotic interactions we observed are also due to phage and antibiotics targeting cells in different metabolic states as recently hypothesised 75 .…”

Section: Discussionmentioning

confidence: 99%

Phage-induced efflux down-regulation boosts antibiotic efficacy

Kraus,

Łapińska,

Chawla

et al. 2023

Preprint

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The interactions between a virus and its host vary in space and time and are affected by the presence of molecules that alter the physiology of either the host or the virus. Determining the dynamics of these interactions is paramount for predicting the fate of bacterial and phage populations and for designing rational phage-antibiotic therapies. We study the interactions between stationary phase Burkholderia thailandensis and the phage phi Bp-AMP1. Although heterogeneous genetic resistance to phage rapidly emerges in B. thailandensis, the presence of phage enhances the efficacy of three major antibiotic classes, the quinolones, the beta-lactams and the tetracyclines, but antagonizes tetrahydrofolate synthesis inhibitors. Enhanced antibiotic efficacy is underpinned by reduced antibiotic efflux in the presence of phage. This new phage-antibiotic therapy allows for eradication of stationary phase bacteria, whilst requiring reduced antibiotic concentrations, which is crucial for treating infections in sites where it is difficult to achieve high antibiotic concentrations.

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“…Garb et al, studied the defense-associated sirtuin (DSR) proteins in 2022, and found that SIR2 (N-terminal sirtuin) domain acts as NAD+ depletors and helps bacteria to abort phage adsorption and propagation [73]. One of the major findings by Laure et al, in 2022, on trade-off costs in Salmonella typhimurium was the increased β-lactamase activity of mutants obtained after phage and phage +ampicillin treatment [74]. Li et al, in 2022, investigated multiple mutant strains of P. aeruginosa and revealed major mutations in pilT and pilB (type IV pili) genes and chromosomal deletions of approximately 294 kb involving galU (UTP-glucose-1-phosphate uridylyltransferase) and hmgA (homogentisate 1,2-dioxygenase) [75].…”

Section: Mary Et Al 2023mentioning

confidence: 99%

Machine Learning Mediated Advanced Phage and Antimicrobial Therapy- A Futuristic Approach

Shanmugha Mary,

Manik Patil,

Kundu

et al. 2023

Highlights in BioScience

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The emergence of antimicrobial resistance (AMR) has overwhelmed the contemporary curatives and have turned into one of the major challenges in the biomedical sector. With increasing deaths being associated with AMR every year; early detection of pathogens and development of novel drugs and alternative therapies, have all become ad hoc in diagnosis, prognosis and patient survival. Bacteriophage therapy remains a viable strategy to counteract AMR, yet unduly restrained by phage resistance. Phage infection is a natural phenomenon and can be widely manipulated in vitro using advanced techniques including the CRISPR/Cas systems which renders phage therapy an upper hand in comparison to conventional drugs. Phage identification, host range detection, determination of phage-receptor binding efficiency, adsorption rate, phage genome analysis are crucial stages in phage selection and phage cocktail preparation and moreover pivotal in flourishing phage therapy. The ascent of translational research and omics has allowed the development of quick, reliable and precise strategies for phage-based diagnosis and treatment techniques. However, in vitro evaluation of AMR and phage factors as well as storing, processing and analyzing large laboratory data outputs are expensive, time-consuming and labor-intensive. Machine learning (ML) is a utilitarian strategy to organize, store, analyze data sets and more importantly allows prediction of certain features by recognizing patterns in the data sets. With the huge number of research been carried out around the globe and enormous data sets being published and stored in databases, ML can utilize the available data to perform and guide in developing alternative therapeutics. Several ML based tools have been developed to predict resistance in host, phage grouping for cocktail preparation, resistance and lysogenic genes detection, phage genomic evaluation and to understand phage-host interactions. ML also allows the in silico analysis of large samples (drug/phage) and reduces sample size for in vitro evaluation thereby reducing overall costs, time and labor. The present review summarizes the available ML algorithms and corresponding databases used in AMR and phage research. It also emphasizes the status quo of antimicrobial and phage resistance in the healthcare sector and analyses the role of ML in analyzing biological databases in order to predict possible phage/drug-host interaction patterns, phage susceptibility, suitability of phage strains for therapy and recommends the most efficient drug combinations and treatment strategies.

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Phage resistance-mediated trade-offs with antibiotic resistance in Salmonella Typhimurium

Cited by 8 publications

References 67 publications

Optimizing bacteriophage treatment of resistant Pseudomonas

Optimizing bacteriophage treatment of resistant Pseudomonas

Phage-induced efflux down-regulation boosts antibiotic efficacy

Machine Learning Mediated Advanced Phage and Antimicrobial Therapy- A Futuristic Approach

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