ArticleMicrobiology spectrum2024
Real-time flow cytometry to assess qualitative and quantitative responses of oral pathobionts during exposure to antiseptics.
Article in Microbiology spectrum, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Antiseptics are widely used in oral healthcare to prevent or treat oral diseases, such as gingivitis and periodontitis. However, the incidence of bacteria being tolerant to standard antiseptics has sharply increased over the last few years. This stresses the urgency for surveillance against tolerant organisms, as well as the discovery of novel antimicrobials. Traditionally, susceptibility to antimicrobials is assessed by broth micro-dilution or disk diffusion assays, both of which are time-consuming, labor-intensive, and provide limited information on the mode of action of the antimicrobials. The abovementioned limitations highlight the need for the development of new methods to monitor and further understand antimicrobial susceptibility. In this study, we used real-time flow cytometry, combined with membrane permeability staining, as a quick and sensitive technology to study the quantitative and qualitative responses of two oral pathobionts to different concentrations of chlorhexidine (CHX), cetylpyridinium chloride (CPC), or triclosan. Apart from the real-time monitoring of cell damage, we further applied a phenotypic fingerprinting method to differentiate between the bacterial subpopulations that arose due to treatment. We quantified the pathobiont damage rate of different antiseptics at different concentrations within 15 minutes of exposure and identified the conditions under which the bacteria were most susceptible. Moreover, we detected species-specific and treatment-specific phenotypic subpopulations. This proves that real-time flow cytometry can provide information on the susceptibility of different microorganisms in a short time frame while differentiating between antiseptics and thus could be a valuable tool in the discovery of novel antimicrobial compound, while at the same time deciphering their mode of action. IMPORTANCE: With increasing evidence that microorganisms are becoming more tolerant to standard antimicrobials, faster and more accessible antimicrobial susceptibility testing methods are needed. However, traditional susceptibility assays are laborious and time-consuming. To overcome the abovementioned limitations, we introduce a novel approach to define antimicrobial susceptibility in a much shorter time frame with the use of real-time flow cytometry. Furthermore, phenotypic fingerprinting analysis can be applied on the data to study the way antiseptics affect the bacterial cell morphology over time and, thus, gain information on the mode of action of a certain compound.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.