Sensing of Antibiotic–Bacteria Interactions

Baranova, Anna A.; Tyurin, Anton P.; Korshun, Vladimir A.; Alferova, Vera A.

doi:10.3390/antibiotics12081340

Cited by 4 publications

(2 citation statements)

References 159 publications

(215 reference statements)

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“…Over the past 12 years, advancements in the application of BCP and similar methods in antibiotic research have received only brief mention in review articles covering other topics [6,26,27]. That is why we consider it necessary to conduct a more comprehensive and critical examination of the accumulated data.…”

Section: Fig 2 Main Steps Of Bacterial Cytological Profilingmentioning

confidence: 99%

“…The main problem with this approach is precisely the lack of information about the mechanism underlying the observed phenotypic changes. To solve this problem, various approaches have been developed to elucidate the mechanism of action, both newly developed [3,[6][7][8] and conventional, or "classical" ones. The "gold standard" for establishing the mechanism of action of an antibiotic is a macromolecular synthesis assay utilizing radioactively labeled precursors [9,10] (Fig.…”

Section: Introductionmentioning

confidence: 99%

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Imaging-based profiling for elucidation of antibacterial mechanisms of action

Baranova,

Alferova,

Korshun

et al. 2024

Preprint

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In this review, we aim to summarize experimental data and approaches to identifying cellular targets or mechanisms of action of antibacterials based on imaging techniques. Imaging-based profiling methods such as bacterial cytological profiling, dynamic bacterial morphology imaging and others have become a useful research tool for mechanistic studies of new antibiotics as well as combinations with conventional ones and other therapeutic options. The main methodological, experimental details and obtained results are summarized and discussed. The review covers the literature up to Feb 2024.

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Section: Fig 2 Main Steps Of Bacterial Cytological Profilingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Imaging-based profiling for elucidation of antibacterial mechanisms of action

Baranova,

Alferova,

Korshun

et al. 2024

Preprint

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Imaging‐based profiling for elucidation of antibacterial mechanisms of action

Baranova,

Alferova,

Korshun

et al. 2024

Biotech and App Biochem

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In this review, we aim to summarize experimental data and approaches to identifying cellular targets or mechanisms of action of antibacterials based on imaging techniques. Imaging‐based profiling methods, such as bacterial cytological profiling, dynamic bacterial morphology imaging, and others, have become a useful research tool for mechanistic studies of new antibiotics as well as combinations with conventional ones and other therapeutic options. The main methodological and experimental details and obtained results are summarized and discussed. The review covers the literature up to February 2024.

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Early prediction of the bactericidal and bacteriostatic effect of imipenem and doxycycline using tabletop scanning electron microscopy

Zmerli,

Hodzic,

Bellali

et al. 2024

Front. Cell. Infect. Microbiol.

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IntroductionOur work aims at establishing a proof-of-concept for a method that allows the early prediction of the bactericidal and bacteriostatic effects of antibiotics on bacteria using scanning electron microscopy (SEM) as compared to traditional culture-based methods.MethodsWe tested these effects using Imipenem (bactericidal) and Doxycycline (bacteriostatic) with several strains of sensitive and resistant Escherichia coli. We developed a SEM-based predictive score based on three main criteria: Bacterial Density, Morphology/Ultrastructure, and Viability. We determined the results for each of these criteria using SEM micrographs taken with the TM4000Plus II-Tabletop-SEM (Hitachi, Japan) following an optimized, rapid, and automated acquisition and analysis protocol. We compared our method with the traditional culture colony counting gold standard method and classic definitions of the two effects. ResultsOur method revealed total agreement with the CFU method and classic definition by visualizing the effect of the antibiotic at 60 minutes and 120 minutes using SEM. DiscussionThis early prediction allows a rapid and early identification of the bactericidal and bacteriostatic effects as compared to culture that would take a minimum of 18 hours. This has several future applications in the development of SEM-automated assays coupled to machine learning models that identify the antibiotic effect and facilitate determination of bacterial susceptibility.

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Sensing of Antibiotic–Bacteria Interactions

Cited by 4 publications

References 159 publications

Imaging-based profiling for elucidation of antibacterial mechanisms of action

Imaging-based profiling for elucidation of antibacterial mechanisms of action

Imaging‐based profiling for elucidation of antibacterial mechanisms of action

Early prediction of the bactericidal and bacteriostatic effect of imipenem and doxycycline using tabletop scanning electron microscopy

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