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Quorum sensing of pathogenic bacteria and quorum-sensing inhibitors

Authors: ZongHui YUAN; ZhenLi LIU; MengHong DAI; HaiHong HAO; GuYue CHENG;

Quorum sensing of pathogenic bacteria and quorum-sensing inhibitors

Abstract

The emergence of antibiotic-resistant and especially multidrug-resistant pathogenic bacteria intensifies the need to screen new drug targets and develop new antibacterial drugs. Bacteria coordinate their virulent behaviors in a cell density-dependent manner known as quorum sensing (QS). In this process, pathogenic bacteria exchange autoinducers (AIs) to regulate the expression of genes involved in processes such as virulence, adhesion, and biofilm formation. Different types of AIs mediate different QS systems. Preventing the accumulation of AIs or blocking their recognition by signal receptors can reduce the pathogenic processes under QS control. Therefore, quorum-sensing inhibitors (QSIs) may be an effective way to treat bacterial infections, especially those caused by antibiotic-resistant strains. QSIs can be categorized into three classes: nonpeptide small molecules, peptides, and proteins (including quorum-quenching enzymes and antibodies). In addition, competing bacteria and animal hosts can scavenge AIs, thus playing the role of QSIs. QSIs can be screened by natural QSI indicator strains, engineered bacteria, or computer simulation. The continuing study of QS-mediated pathogenic mechanisms will provide new targets for QSIs. The combined use of QSIs and traditional antimicrobials is expected to improve treatment and help prevent the further development of drug resistance.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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