Quorum Sensing: Complexity in the bacterial world

Side, D. Delle; Giuffreda, E.; Tredici, Salvatore Maurizio; Talà, Adelfia; Pennetta, C.; Alifano, Pietro

doi:10.1016/j.chaos.2015.05.011

Cited by 5 publications

(7 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…the infectious dose for a pulmonary versus cutaneous or gastro-intestinal infection can be different and result in variation in values of β ). Parasite traits may also induce nonlinear effects: for example, quorum sensing among bacteria and yeast, which involves signalling between bacteria (or yeast cells) that requires threshold levels of autoinducer chemicals in interaction with bacterial density, in order for signalling to occur [ 38 ]. Such nonlinear quorum sensing can lead to biofilms which increase the probability of bacteria establishing infection [ 39 ].…”

Section: Sources Of Heterogeneity and Nonlinearitymentioning

confidence: 99%

Breaking beta: deconstructing the parasite transmission function

McCallum

Fenton

Hudson

et al. 2017

Phil. Trans. R. Soc. B

109

149

View full text Add to dashboard Cite

Transmission is a fundamental step in the life cycle of every parasite but it is also one of the most challenging processes to model and quantify. In most host–parasite models, the transmission process is encapsulated by a single parameter β. Many different biological processes and interactions, acting on both hosts and infectious organisms, are subsumed in this single term. There are, however, at least two undesirable consequences of this high level of abstraction. First, nonlinearities and heterogeneities that can be critical to the dynamic behaviour of infections are poorly represented; second, estimating the transmission coefficient β from field data is often very difficult. In this paper, we present a conceptual model, which breaks the transmission process into its component parts. This deconstruction enables us to identify circumstances that generate nonlinearities in transmission, with potential implications for emergent transmission behaviour at individual and population scales. Such behaviour cannot be explained by the traditional linear transmission frameworks. The deconstruction also provides a clearer link to the empirical estimation of key components of transmission and enables the construction of flexible models that produce a unified understanding of the spread of both micro- and macro-parasite infectious disease agents.This article is part of the themed issue ‘Opening the black box: re-examining the ecology and evolution of parasite transmission’.

show abstract

Section: Sources Of Heterogeneity and Nonlinearitymentioning

confidence: 99%

Breaking beta: deconstructing the parasite transmission function

McCallum

Fenton

Hudson

et al. 2017

Phil. Trans. R. Soc. B

109

149

View full text Add to dashboard Cite

show abstract

“…Even if the modeling approach is different, the underlying qualitative idea of this paper is similar to that discussed in paper [25]. In paper [28] a biophysical phenomenon known as Quorum Sensing (QS) is studied. QS is a very interesting example of social collective behaviour in bacteria, being the nonlinear interactions given here by the secretion and detection of some chemical signaling molecules or, as in this paper, of bioluminescence signals that are generated by bacteria through a chemical reaction.…”

Section: Complexity In Biological Systemsmentioning

confidence: 84%

“…Papers [26,27,28,29,30,31] are focused on the investigation of biological systems. Biology is probably the most intriguing research field from the point of view of complexity science.…”

Section: Complexity In Biological Systemsmentioning

confidence: 99%

The emergence of self-organization in complex systems–Preface

Paradisi

Kaniadakis

Scarfone

2015

Chaos, Solitons & Fractals

View full text Add to dashboard Cite

“…The connection of the experimental curve with the Gumbel function can be rationalized by observing that the bacterial growth curve is modelled by a Gompertz function, e.g. the integral of the Gumbel function [ 33 ].…”

Section: Discussionmentioning

confidence: 99%

“…Finally, we hypothesize that the number p ( t ) of photons emitted per second by the bioluminescent colony, which is eventually measured as the radiant flux in the climate chamber at nearly constant temperature and humidity [ 30 , 33 ], is simply proportional to that of bioluminescent bacteria a ( t ), as given by

The parameters involved are the enzyme copy number c e , the number of luciferase molecules expressed in a single bioluminescent bacterium and κ e , the luciferase turnover number in the photon emission reaction.…”

Section: A Simplified Model For Bioluminescence Onset and Quenchingmentioning

confidence: 99%

Bacterial bioluminescence onset and quenching: a dynamical model for aquorum sensing-mediated property

et al. 2017

View full text Add to dashboard Cite

We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of Vibrio jasicida, a luminescent bacterium belonging to the Harveyi clade, growing in a highly drying environment. A distinctive and novel feature of the proposed model is bioluminescence ‘quenching’ after a given time elapsed from activation. Using an advanced fitting procedure based on the simulated annealing algorithm, we are able to infer from the experimental observations the biochemical parameters used in the model. Such parameters are in good agreement with the literature data. As a further result, we find that, at least in our experimental conditions, light emission in bioluminescent bacteria appears to originate from a subtle balance between colony growth and quorum activation due to autoinducers diffusion, with the two phenomena occurring on the same time scale. This finding is consistent with a negative feedback mechanism previously reported for Vibrio harveyi.

show abstract

Quorum Sensing: Complexity in the bacterial world

Cited by 5 publications

References 30 publications

Breaking beta: deconstructing the parasite transmission function

Breaking beta: deconstructing the parasite transmission function

The emergence of self-organization in complex systems–Preface

Bacterial bioluminescence onset and quenching: a dynamical model for aquorum sensing-mediated property

Contact Info

Product

Resources

About