Dataset Information

A pro-drug approach for selective modulation of AI-2-mediated bacterial cell-to-cell communication.

ABSTRACT: The universal quorum sensing autoinducer, AI-2, is utilized by several bacteria. Analogs of AI-2 have the potential to modulate bacterial behavior. Selectively quenching the communication of a few bacteria, in the presence of several others in an ecosystem, using analogs of AI-2 is non-trivial due to the ubiquity of AI-2 processing receptors in many bacteria that co-exist. Herein, we demonstrate that when an AI-2 analog, isobutyl DPD (which has been previously shown to be a quorum sensing, QS, quencher in both Escherichia coli and Salmonella typhimurium) is modified with ester groups, which get hydrolyzed once inside the bacterial cells, only QS in E. coli, but not in S. typhimurium, is inhibited. The origin of this differential QS inhibition could be due to differences in analog permeation of the bacterial membranes or ester hydrolysis rates. Such differences could be utilized to selectively target QS in specific bacteria amongst a consortium of other species that also use AI-2 signaling.

SUBMITTER: Guo M

PROVIDER: S-EPMC3376627 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A pro-drug approach for selective modulation of AI-2-mediated bacterial cell-to-cell communication.

Guo Min M Gamby Sonja S Nakayama Shizuka S Smith Jacqueline J Sintim Herman O HO

Sensors (Basel, Switzerland) 20120321 3

The universal quorum sensing autoinducer, AI-2, is utilized by several bacteria. Analogs of AI-2 have the potential to modulate bacterial behavior. Selectively quenching the communication of a few bacteria, in the presence of several others in an ecosystem, using analogs of AI-2 is non-trivial due to the ubiquity of AI-2 processing receptors in many bacteria that co-exist. Herein, we demonstrate that when an AI-2 analog, isobutyl DPD (which has been previously shown to be a quorum sensing, QS, q ...[more]

PMID: 22737036

Similar Datasets

Project description:The extracellular signaling molecule indole plays a pivotal role in biofilm formation by the enteric gammaproteobacterium Escherichia coli; this process is particularly correlated with the extracellular indole concentration. Using the indole-biodegrading betaproteobacterium Burkholderia unamae, we examined the mechanism by which these two bacteria modulate biofilm formation in an indole-dependent manner. We quantified the spatial organization of cocultured microbial communities at the micrometer scale through computational image analysis, ultimately identifying how bidirectional cell-to-cell communication modulated the physical relationships between them. Further analysis allowed us to determine the mechanism by which the B. unamae-derived signaling diketopiperazine cyclo(Pro-Tyr) considerably upregulated indole biosynthesis and enhanced E. coli biofilm formation. We also determined that the presence of unmetabolized indole enhanced the production of cyclo(Pro-Tyr). Thus, bidirectional cell-to-cell communication that occurred via interspecies signaling molecules modulated the formation of a mixed-species biofilm between indole-producing and indole-consuming species. IMPORTANCE Indole is a relatively stable N-heterocyclic aromatic compound that is widely found in nature. To date, the correlations between indole-related bidirectional cell-to-cell communications and interspecies communal organization remain poorly understood. In this study, we used an experimental model, which consisted of indole-producing and indole-degrading bacteria, to evaluate how bidirectional cell-to-cell communication modulated interspecies biofilm formation via intrinsic and environmental cues. We identified a unique spatial patterning of indole-producing and indole-degrading bacteria within mixed-species biofilms. This spatial patterning was an active process mediated by bidirectional physicochemical interactions. Our findings represent an important step in gaining a more thorough understanding of the process of polymicrobial biofilm formation and advance the possibility of using indole-degrading bacteria to address biofilm-related health and industry issues.

Project description:BackgroundSince the mid-2010s, use of conversational artificial intelligence (AI; chatbots) in health care has expanded significantly, especially in the context of increased burdens on health systems and restrictions on in-person consultations with health care providers during the COVID-19 pandemic. One emerging use for conversational AI is to capture evolving questions and communicate information about vaccines and vaccination.ObjectiveThe objective of this systematic review was to examine documented uses and evidence on the effectiveness of conversational AI for vaccine communication.MethodsThis systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, Web of Science, PsycINFO, MEDLINE, Scopus, CINAHL Complete, Cochrane Library, Embase, Epistemonikos, Global Health, Global Index Medicus, Academic Search Complete, and the University of London library database were searched for papers on the use of conversational AI for vaccine communication. The inclusion criteria were studies that included (1) documented instances of conversational AI being used for the purpose of vaccine communication and (2) evaluation data on the impact and effectiveness of the intervention.ResultsAfter duplicates were removed, the review identified 496 unique records, which were then screened by title and abstract, of which 38 were identified for full-text review. Seven fit the inclusion criteria and were assessed and summarized in the findings of this review. Overall, vaccine chatbots deployed to date have been relatively simple in their design and have mainly been used to provide factual information to users in response to their questions about vaccines. Additionally, chatbots have been used for vaccination scheduling, appointment reminders, debunking misinformation, and, in some cases, for vaccine counseling and persuasion. Available evidence suggests that chatbots can have a positive effect on vaccine attitudes; however, studies were typically exploratory in nature, and some lacked a control group or had very small sample sizes.ConclusionsThe review found evidence of potential benefits from conversational AI for vaccine communication. Factors that may contribute to the effectiveness of vaccine chatbots include their ability to provide credible and personalized information in real time, the familiarity and accessibility of the chatbot platform, and the extent to which interactions with the chatbot feel "natural" to users. However, evaluations have focused on the short-term, direct effects of chatbots on their users. The potential longer-term and societal impacts of conversational AI have yet to be analyzed. In addition, existing studies do not adequately address how ethics apply in the field of conversational AI around vaccines. In a context where further digitalization of vaccine communication can be anticipated, additional high-quality research will be required across all these areas.

Dataset Information

A pro-drug approach for selective modulation of AI-2-mediated bacterial cell-to-cell communication.

Publications

A pro-drug approach for selective modulation of AI-2-mediated bacterial cell-to-cell communication.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets