Specificity and complexity in bacterial quorum-sensing systems

Hawver, Lisa A.; Jung, Sarah; Ng, Wai‐Leung

doi:10.1093/femsre/fuw014

Cited by 246 publications

(174 citation statements)

References 189 publications

(302 reference statements)

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“…This process involves the production and detection of signaling molecules (called autoinducers) allowing bacterial communities to express genes collectively 102 . QS systems are different in Gram-negatives and Gram-positives, the signaling molecules are called acyl-homoserine-lactones (AHLs) in proteobacteria or cis-11-methyl-2-dodecanoic acid (also called diffusible signal factor – DSF) mainly in Xanthomonas and Xylella , gram negatives and gamma-butyrolactones in Streptomyces and peptides in Gram positives 103, 104…”

Section: Quorum Sensingmentioning

confidence: 99%

Microbial interactions: ecology in a molecular perspective

Braga

Dourado

Araújo

2016

Brazilian Journal of Microbiology

283

145

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The microorganism–microorganism or microorganism–host interactions are the key strategy to colonize and establish in a variety of different environments. These interactions involve all ecological aspects, including physiochemical changes, metabolite exchange, metabolite conversion, signaling, chemotaxis and genetic exchange resulting in genotype selection. In addition, the establishment in the environment depends on the species diversity, since high functional redundancy in the microbial community increases the competitive ability of the community, decreasing the possibility of an invader to establish in this environment. Therefore, these associations are the result of a co-evolution process that leads to the adaptation and specialization, allowing the occupation of different niches, by reducing biotic and abiotic stress or exchanging growth factors and signaling. Microbial interactions occur by the transference of molecular and genetic information, and many mechanisms can be involved in this exchange, such as secondary metabolites, siderophores, quorum sensing system, biofilm formation, and cellular transduction signaling, among others. The ultimate unit of interaction is the gene expression of each organism in response to an environmental (biotic or abiotic) stimulus, which is responsible for the production of molecules involved in these interactions. Therefore, in the present review, we focused on some molecular mechanisms involved in the microbial interaction, not only in microbial–host interaction, which has been exploited by other reviews, but also in the molecular strategy used by different microorganisms in the environment that can modulate the establishment and structuration of the microbial community.

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Section: Quorum Sensingmentioning

confidence: 99%

Microbial interactions: ecology in a molecular perspective

Braga

Dourado

Araújo

2016

Brazilian Journal of Microbiology

283

145

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“…The two-component system consists of a membrane-bound protein kinase that recognized AIP and activates the transcriptional regulator in the cytoplasm through its phosphorylation (for review, see Ref. [7]). …”

Section: Quorum Sensing and Chemical Signalsmentioning

confidence: 99%

Detection and Control of Indoor Airborne Pathogenic Bacteria by Biosensors Based on Quorum Sensing Chemical Language: Bio-Tools, Connectivity Apps and Intelligent Buildings

Ibacache-Quiroga¹,

Romo²,

Díaz-Viciedo³

et al. 2018

Biosensing Technologies for the Detection of Pathogens - A Prospective Way for Rapid Analysis

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Nowadays, lifestyles and climate change lead people to spend long periods in indoors spaces, where reduced ventilation and artificial light favor the concentration and spread of airborne pathogenic microorganisms. Current procedures for microbiological air evaluation are based on air sampling coupled to traditional microbiological culturedependent methods such as biochemical tests and molecular rDNA 16S sequencing. These techniques generate an important delay in the application of prevention and control measures. This chapter presents whole cell-based biosensors that are able to detect quorum sensing signaling molecules produced by airborne pathogenic bacteria as a tool for indoor air monitoring. Furthermore, a general biosensor model is proposed. In this model, in vivo biosensors technology can be connected to online applications (Apps), being part of intelligent buildings, in order to reduce airborne pathogenic bacteria concentration and dissemination.

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“…In particular, it is by now well established that real microbial communities are frequently characterized by the stable coexistence of several variant QS systems in the population [9][10][11]. AI molecules produced by cells with one QS variant tend to activate QS in related kin cells that also express that same variant, with the corresponding native cognate receptor.…”

mentioning

confidence: 99%

Mapping quorum sensing onto neural networks to understand collective decision making in heterogeneous microbial communities

Yusufaly¹,

Boedicker²

2017

Phys. Biol.

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Microbial communities frequently communicate via quorum sensing (QS), where cells produce, secrete, and respond to a threshold level of an autoinducer (AI) molecule, thereby modulating gene expression. However, the biology of QS remains incompletely understood in heterogeneous communities, where variant bacterial strains possess distinct QS systems that produce chemically unique AIs. AI molecules bind to 'cognate' receptors, but also to 'non-cognate' receptors found in other strains, resulting in inter-strain crosstalk. Understanding these interactions is a prerequisite for deciphering the consequences of crosstalk in real ecosystems, where multiple AIs are regularly present in the same environment. As a step towards this goal, we map crosstalk in a heterogeneous community of variant QS strains onto an artificial neural network model. This formulation allows us to systematically analyze how crosstalk regulates the community's capacity for flexible decision making, as quantified by the Boltzmann entropy of all QS gene expression states of the system. In a mean-field limit of complete cross-inhibition between variant strains, the model is exactly solvable, allowing for an analytical formula for the number of variants that maximize capacity as a function of signal kinetics and activation parameters. An analysis of previous experimental results on the Staphylococcus aureus two-component Agr system indicates that the observed combination of variant numbers, gene expression rates and threshold concentrations lies near this critical regime of parameter space where capacity peaks. The results are suggestive of a potential evolutionary driving force for diversification in certain QS systems.Multicellular communities of microbes frequently coordinate changes in group behavior, which requires cellto-cell communication via the exchange of extracellular signaling molecules called autoinducers (AI), a process known as quorum sensing (QS) [1]. Microbes produce AI molecules at a default basal rate, and if the local concentration of AI molecules accumulates beyond a certain threshold, the AI production rate is amplified to an activated level via a positive-feedback loop, simultaneously regulating the expression of QS-controlled genes. This two-state QS regulatory network controls a wide array of collective behaviors in microbial communities, such as the formation of biofilms, the regulation of virulence, or lateral gene transfer [1][2][3][4][5].Although quorum sensing has traditionally been viewed as a process associated with homogeneous populations, several results in recent years have called this conventional wisdom into question [6][7][8]. In particular, it is by now well established that real microbial communities are frequently characterized by the stable coexistence of several variant QS systems in the population [9][10][11]. AI molecules produced by cells with one QS variant tend to activate QS in related kin cells that also express that same variant, with the corresponding native cognate receptor. However, when multiple ...

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Specificity and complexity in bacterial quorum-sensing systems

Cited by 246 publications

References 189 publications

Microbial interactions: ecology in a molecular perspective

Microbial interactions: ecology in a molecular perspective

Detection and Control of Indoor Airborne Pathogenic Bacteria by Biosensors Based on Quorum Sensing Chemical Language: Bio-Tools, Connectivity Apps and Intelligent Buildings

Mapping quorum sensing onto neural networks to understand collective decision making in heterogeneous microbial communities

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