Download Acyl-Homoserine Lactone Quorum Sensing: From Evolution to

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V I E W
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Acyl-Homoserine Lactone
Quorum Sensing: From
Evolution to Application
Martin Schuster,1 D. Joseph Sexton,1
Stephen P. Diggle,2 and E. Peter Greenberg3
1
Department of Microbiology, Oregon State University, Corvallis, Oregon 97331;
email: [email protected], [email protected]
2
School of Molecular Medical Sciences, University of Nottingham, Nottingham NG7 2RD,
United Kingdom; email: [email protected]
3
Department of Microbiology, University of Washington, Seattle, Washington 98195;
email: [email protected]
Annu. Rev. Microbiol. 2013. 67:43–63
Keywords
The Annual Review of Microbiology is online at
micro.annualreviews.org
Pseudomonas, cooperation, cheating, public good, QS inhibition
This article’s doi:
10.1146/annurev-micro-092412-155635
Abstract
c 2013 by Annual Reviews.
Copyright All rights reserved
Quorum sensing (QS) is a widespread process in bacteria that employs
autoinducing chemical signals to coordinate diverse, often cooperative
activities such as bioluminescence, biofilm formation, and exoenzyme
secretion. Signaling via acyl-homoserine lactones is the paradigm for QS
in Proteobacteria and is particularly well understood in the opportunistic
pathogen Pseudomonas aeruginosa. Despite thirty years of mechanistic
research, empirical studies have only recently addressed the benefits of
QS and provided support for the traditional assumptions regarding its
social nature and its role in optimizing cell-density-dependent group
behaviors. QS-controlled public-goods production has served to investigate
principles that explain the evolution and stability of cooperation, including
kin selection, pleiotropic constraints, and metabolic prudence. With
respect to medical application, appreciating social dynamics is pertinent
to understanding the efficacy of QS-inhibiting drugs and the evolution of
resistance. Future work will provide additional insight into the foundational
assumptions of QS and relate laboratory discoveries to natural ecosystems.
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Contents
INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
MODEL SYSTEMS AND COMMON THEMES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The Vibrio fischeri Paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Pseudomonas aeruginosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Common Themes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
EVOLUTIONARY CONSIDERATIONS OF QUORUM SENSING . . . . . . . . . . . . .
Foundational Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Sociality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Social Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Density Dependence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
QS-Independent Cooperation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
QUORUM SENSING AS AN ANTIVIRULENCE DRUG TARGET:
SOCIAL INTERACTIONS AND RESISTANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The Potential of Antivirulence Drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
QS-Inhibiting Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
How Likely Is the Evolution of Resistance? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
QSI Resistance and the Quorum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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INTRODUCTION
Quorum sensing
(QS): a mechanism of
chemical cell-cell
communication that
permits coordination
of gene expression as a
function of the local
population density
Cooperation: a
behavior that benefits
another individual (the
recipient) and is
maintained (at least
partially) because of its
beneficial effect on the
recipient
44
Although bacteria were long thought to be individual cells acting alone, we now accept that they
are social organisms capable of acting together to exhibit a range of cooperative activities (14,
116). Many of these activities are involved in virulence and for this reason have been studied in the
context of pathogenesis, but microbial social behaviors are important in a variety of other contexts
(24). One type of social trait that has been studied extensively at the molecular level is the ability
of bacteria to communicate with one another by using chemical signals. Bacterial communication
can coordinate a wide range of activities in different bacterial species as a function of population
density (118). This type of communication is called quorum sensing (QS) (33). At least in some
cases it is clear that QS controls social behaviors (24, 94, 120).
If one strives to understand bacteria, and the wide variety of ecological and environmental
niches they occupy, social aspects of their biology cannot be ignored. Although the field of sociomicrobiology is very young, we see two reasons why it is critical to study QS and the control
of social activities in bacteria. (a) Bacteria have become powerful tools with which to study fundamental questions about the costs and benefits of cooperation, the selective pressures that lead to
the evolution and maintenance of cooperative traits, and the advantages of controlling cooperative behaviors by cell-cell communication systems such as QS. With fast growth rates and ease of
genetic manipulations, evolutionary questions that cannot possibly be addressed with higher organisms can be addressed with bacteria. (b) The central role QS plays in regulating many relevant
microbial behaviors has not gone unnoticed. There is currently high interest in manipulating QS
systems for diverse human applications such as ecological control in agriculture and antivirulence
in medicine (4, 54, 77, 78).
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O
O
O
C4-HSL
N
H
O
O
O
O
3OC6-HSL
N
H
O
O
O
O
3OC12-HSL
N
H
O
O
O
pC-HSL
N
H
HO
Figure 1
Some examples of AHL quorum-sensing signals. The structures and corresponding names are shown. The
Pseudomonas aeruginosa signal synthase RhlI produces C4-HSL and LasI produces 3OC12-HSL. The Vibrio
fischeri signal synthase LuxI produces 3OC6-HSL, and the Rhodopseudomonas palustris signal synthase RpaI
produces pC-HSL. In all, dozens of different AHL signals have been described. Abbreviations: AHL,
acyl-homoserine lactone; C4-HSL, butanoyl-homoserine lactone; 3OC12-HSL, 3-oxo-dodecanoylhomoserine lactone; 3OC6-HSL, 3-oxo-hexanoyl-homoserine lactone; pC-HSL,
para-coumaroyl-homoserine lactone.
MODEL SYSTEMS AND COMMON THEMES
The Vibrio fischeri Paradigm
In the late 1960s and early 1970s, there was a very modest literature describing pheromone
production and activity in bacteria (26, 108). It was not until the early 1980s that work on gene
regulation in marine luminescent bacteria led to some understanding of how an intercellular
communication system could coordinate group activities. Only in the 1990s did we begin to
understand the prevalence of QS in bacteria. Now we know there are many different types of
bacterial QS systems. Our review focuses on acyl-homoserine lactone (AHL) QS systems, which
are prevalent but not universal among the Proteobacteria and for which the term QS was first
introduced (33). Generally, AHL signals are synthesized by LuxI family enzymes and detected by
LuxR family signal receptor–transcriptional regulators. There are related but chemically distinct
signals that are specific to particular systems (Figure 1).
AHL signaling was first discovered in the marine bacterium Vibrio fischeri, which uses QS to
control a small set of approximately 25 genes, including genes for light production, by LuxR and
3-oxo-hexanoyl-homoserine lactone (3OC6-HSL), which is produced by the luxI gene product
(3, 27, 28) (Figure 2a). V. fischeri is a mutualistic symbiont of specific marine animals in which it
colonizes the light organs and produces light. Like other AHLs, 3OC6-HSL moves in and out of
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AHL:
acyl-homoserine
lactone
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a
b
luxI
luxR
LuxI
LuxR
qscR
lasI
lasR
rhIR
rhII
LasI
LasR
RhIR
RhII
LasR
RhIR
LasR
regulon
RhlR
regulon
QscR
AHL
AHL
ACTIVE
Lux regulon
QscR
regulon
AHL
Figure 2
AHL signaling in (a) Vibrio fischeri and (b) Pseudomonas aeruginosa. AHL signals are made by members of the
LuxI family of signal synthases and specifically interact with LuxR family transcription factors. At high cell
density, AHLs accumulate and interact with LuxR homologs. AHL binding controls activity of LuxR family
members. (a) In V. fischeri, LuxI and LuxR produce and respond to 3OC6-HSL, respectively. (b) In
P. aeruginosa, the LasIR system produces and responds to 3OC12-HSL, and the RhlR system produces and
responds to C4-HSL. QscR is an orphan LuxR receptor that is not linked to a luxI synthase gene. QscR
responds to 3OC12-HSL produced by LasI. Each quorum-sensing regulon is shown as a distinct entity, but
in reality there is overlapping regulation among the controlled genes. Figure adapted from Reference 71.
Abbreviations: AHL, acyl-homoserine lactone; 3OC6-HSL, 3-oxo-hexanoyl-homoserine lactone;
3OC12-HSL, 3-oxo-dodecanoyl-homoserine lactone; C4-HSL, butanoyl-homoserine lactone.
cells by passive diffusion (55). In this way the environmental signal concentration is a reflection
of cell density and the diffusion potential of the habitat. This QS system allows V. fischeri to
discriminate between its free-living, low-density lifestyle in seawater and its high-density, hostassociated lifestyle in animal light organs. The luxI gene itself is controlled by QS; it is activated by
3OC6-HSL-bound LuxR (28). This positive autoregulation provides hysteresis to the system. The
population density required to activate quorum-controlled genes is much higher than the density
required to shut down an activated system. Furthermore, once the system is induced, it would
require an enormous increase in diffusivity to shut the system off. Once the system is induced,
the environmental AHL concentration increases very rapidly. Finally, we view luminescence as
a cooperative activity. Single cells do not emit enough light for biological detection, but the
light produced by groups of cells can easily be seen with the naked eye. This is in fact the basis
for isolation of luminous marine bacteria. One can plate bacteria from a source enriched for
luminous bacteria on a seawater-based medium and isolate colonies producing blue light in a dark
room. The ease with which luminescence can be observed and measured has facilitated the use of
V. fischeri as a model for understanding QS.
Pseudomonas aeruginosa
In addition to V. fischeri, the gammaproteobacterium Pseudomonas aeruginosa has also emerged
as an important model organism for QS research. Equipped with a large genome, P. aeruginosa
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is metabolically versatile and capable of occupying a range of different habitats (101). It is also an
opportunistic pathogen capable of infecting different host species, including plants, insects, and
mammals (69). Immunocompromised humans, including those with burn wounds or the genetic
disorder cystic fibrosis (CF), are particularly vulnerable to infection with P. aeruginosa (69). The
relative ease with which P. aeruginosa can be handled in the laboratory, along with its medical
relevance, has led to an extensive body of work that includes a detailed picture of the complex
P. aeruginosa QS network. There are two complete AHL circuits, LasR-LasI and RhlR-RhlI; each
is composed of a LuxR-type receptor and a LuxI-type synthase (96, 121) (Figure 2b). LasI produces
3-oxo-dodecanoyl-homoserine lactone (3OC12-HSL), and RhlI produces butanoyl-homoserine
lactone (C4-HSL). The LasRI circuit is hierarchically positioned to regulate the RhlRI circuit.
Together both circuits control the activation of more than 300 genes (48, 97, 114). Genes coding
for production of extracellular products such as exoenzymes and phenazine pigments are grossly
overrepresented in the quorum-controlled regulon (36, 96). Many such extracellular products are
considered virulence factors because they damage host tissue and promote infection. The importance of P. aeruginosa QS for establishing acute and chronic infections has been demonstrated in
several animal models (83, 91, 122). In addition to the LasRI and RhlRI systems, there is a 3OC12HSL-responsive orphan receptor, QscR, which controls its own set of genes and also represses
many LasRI- and RhlRI-dependent genes (65, 66). Another layer of complexity is added by the
Pseudomonas quinolone signal (PQS) system, which is intertwined with the AHL signaling circuitry
(44).
CF: cystic fibrosis
Regulon: the
collection of genes
controlled by an
individual
transcription factor
EPS: extracellular
polysaccharide
Common Themes
Despite the diverse applications and mechanisms of QS, common themes relate these systems.
Many of the controlled factors fall into several general groups that are conserved. Some of the most
common types are toxins (e.g., virulence factors and antimicrobials), exoenzymes (e.g., proteases),
and biofilm components (e.g., extracellular polysaccharides, EPS). Such activities are interesting
because they may represent forms of cooperation. For example, biofilms consist of heterogeneous bacterial groups that organize on surfaces (14). Bacteria in biofilms secrete EPS and other
biofilm matrix components that surround and protect the group, but this may be a wasteful process
for an isolated individual. The common thread of cooperation suggests the evolutionary forces
shaping AHL-mediated QS in P. aeruginosa may also be pertinent to even phylogenetically distinct QS systems, such as the peptide signaling and response systems in gram-positive bacteria
(57).
That said, AHL QS systems are often required but not sufficient to activate a particular gene.
In the current vernacular of synthetic biology, the QS circuit is often part of an AND logic gate.
An excellent example can be drawn from the plant pathogen Agrobacterium tumefaciens, which uses
AHL QS to regulate conjugal transfer of the Ti plasmid. The QS system itself requires activation by small molecules produced only by infected plants (113). Thus, a sufficient A. tumefaciens
density is required and the bacteria must be in the plant host. Another example is the regulation of QS gene expression by starvation in P. aeruginosa. The stringent response, the hallmark
response to slow growth in bacteria, can trigger increased signal synthesis and thus lower the
quorum threshold for target gene induction (111). This feature may prove beneficial, for example,
if QS-dependent exoenzymes are required for nutrient acquisition at relatively low cell density.
The integration of environmentally specific cues into QS circuits is common. Therefore, although
this review discusses the foundational and common evolutionary forces of QS systems, extrapolating these principles to other systems requires consideration of mechanistic and ecological
peculiarities.
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WHAT MAKES A QUORUM-SENSING SIGNAL A SIGNAL?
It is widely accepted among microbiologists that QS represents signaling within species, between species, and
between prokaryotes and eukaryotes. Indeed, it is common in the literature to define any molecule produced by one
individual that elicits a response in another to be a signal. Broad use of the term signal can be misleading, and this
can obscure the true nature of the biological interaction between individuals. For example, QS molecules could also
act as biological cues or be used for coercion or chemical manipulation of other individuals (23, 56). Specifically,
signaling occurs when the production of substance X from individual A has evolved because of its effect on individual
B and is effective because the response in individual B has also evolved. This is distinct from a cue, in which the
production of substance X by individual A has not evolved because of its effect on individual B. Finally, a coercion
or chemical manipulation is when the production of substance X by individual A forces a costly response from
individual B. Here the production has evolved because of the benefit to the sender and not the receiver (73). This
matters because determining whether bacterial cells are interacting via signal, cue, or coercion, allows us to make
very different predictions as to how interactions within and between species evolve and are maintained in nature.
Such distinctions will become increasingly important as microbiologists begin to unravel the nature of multispecies
interactions.
EVOLUTIONARY CONSIDERATIONS OF QUORUM SENSING
Foundational Assumptions
A large volume of literature describes QS at the molecular level, and this has unraveled the genetic
mechanisms and pathways of QS systems. The molecular focus of this work has led to general
assumptions about QS upon which the entire research field is based, namely that QS is a social
trait performed by individual cells for the good of the group, and that QS is most beneficial at high
cell densities. Not until recently has empirical work directly tested these ideas (described in detail
below). A third assumption that QS represents signaling between individuals is briefly touched
upon in the sidebar, What Makes a Quorum-Sensing Signal a Signal?, and has been discussed in
detail elsewhere (23).
Sociality
Public good: a
resource that is costly
to produce and
provides a benefit to
all the individuals in
the local group or
population
48
In 2002, Redfield (87) challenged the notion that QS is social. She pointed out that the need for
group action or the selective conditions required for its evolution had not been experimentally
demonstrated (87). Redfield argued that the chief function of autoinducer signal molecules is to
enable an individual cell to sense how rapidly secreted molecules diffuse away into the surrounding
environment. By producing a metabolically inexpensive molecule such as an AHL, individual cells
could first use this to assess the diffusive properties of their environment to determine whether it
was beneficial to produce a more costly public good such as an extracellular protease. This idea
was termed diffusion sensing (DS) and suggests QS need not be a social behavior but rather a
nonsocial trait, which matters to an individual cell whether or not it is in a group (87). We note
that DS and QS are not mutually exclusive. The efficiency sensing hypothesis made an attempt to
formally unify the two ideas (45), although its utility has recently come under contention (117).
Redfield’s work raises an important question: How can we know whether a bacterial behavior is
social? Answering this question requires an experimental approach. It is key to determine whether
benefits are shared with other cells or enjoyed only by the producer. In microbes, extracellular
products may indeed be available to other members of the group once secreted from the cell.
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If they are costly for the individual but provide a benefit to the group, they can be classified as
public goods (116). With QS, two levels of potential social behavior must be distinguished: first,
the QS circuit, composed of a signal and cognate receptor, which enables communication and
coordination of cooperative behaviors, and second, the actual, generally more costly cooperative
behaviors controlled by QS.
The first step in testing whether a microbial trait is social is to examine whether the relative
costs and benefits of the trait vary with the social environment. Specifically, if exofactors are shared
socially between cells, then one would predict that (a) populations of cells that do produce the
exofactors should grow better than populations that do not. (b) When grown in mixed populations,
nonproducing mutants should be able to exploit producing cells (i.e., they should be able to
cheat) and hence increase in frequency. With respect to QS, we can further predict that signalblind (LuxR-type) mutants should be favored over signal-negative (LuxI-type) mutants, given the
different costs associated with signal production and signal response. (c) If an exofactor is important
for growth in natural environments, then one would be able to isolate natural cheats. If the benefit
of exofactors flowed only to the cell that produced them and was not social, we would make the
first prediction but not the second or third. Understanding this will then allow us to begin to
determine how and why cooperative behaviors evolve and are maintained in natural populations.
Empirical studies using P. aeruginosa have tested the first and second predictions and have shown
that QS-controlled public-goods production is both costly and exploitable by cheats. Using a synthetic QS growth medium with a protein carbon source (casein or bovine serum albumin) that requires QS-dependent exoprotease secretion, researchers have demonstrated that wild-type populations grow well in monocultures whereas populations of QS mutants do not (24, 94, 120). However,
crucially, in mixed culture, signal-blind (lasR-negative) cheats have a fitness advantage because they
exploit the exoprotease production of wild-type cells, displaying a trend of negative-frequencydependent fitness (24, 120). Simply put, when there are fewer cheats in the population there are
more cooperators to exploit, resulting in an increased cheat fitness (88). Signal-blind but not signalnegative cheats emerge when wild-type P. aeruginosa is grown in QS medium over a number of
selection rounds (94). Signal-blind cheats invade cooperating populations to a greater extent when
the cost of cooperation is increased by altering the nutritional composition of the QS medium (17).
The studies cited above were performed with well-mixed cultures of planktonic bacteria,
although similar results were obtained with laboratory biofilms of P. aeruginosa (84). This result
is surprising as it contrasts with previous theory, which suggests that growth in structured
environments such as biofilms should lead to a segregation of cooperators and cheats, reducing
the ability of cheats to exploit cooperators (62, 124).
If QS is social, our third prediction suggests that social cheats should be present in real-world
microbial communities. It is now well established that QS-negative (primarily lasR-negative)
mutants are common in certain human infections, including CF lung infections, and in other
environments (10, 20, 41, 52, 53, 93, 95, 99, 100, 102, 105, 109, 119, 126, 127). Empirical
evidence demonstrating why such QS mutants emerge during infection is sparse. One explanation
for their emergence in the CF lung is that they are better adapted to this unique environment and
therefore have a selective advantage. In support of this, it has been shown that lasR mutants have
an intrinsic growth advantage on particular carbon and nitrogen sources that could contribute to
selection in a CF lung environment (16). An alternative explanation is that lasR mutants behave
as social cheats in a mixed population, exploiting the social behaviors of cooperating strains.
To date, no experimental evidence has demonstrated social cheating in the CF lung. However,
in a mouse infection model, QS cheats invade a burn wound within days, displaying negativefrequency-dependent fitness (89). By comparing monoculture and mixed infections, the study
addressed and confirmed the first and second predictions. This finding suggests that during in vivo
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Cheat: an individual
who does not
cooperate (or
cooperates less than
his fair share) but can
potentially gain the
benefit from others
cooperating; also
called freeloader
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Pleiotropic
constraint: prevents
the origination of
cheaters if the
mutation conferring a
cheater phenotype is
linked to a cost of
cheating
Pleiotropy: the
phenomenon of a
single gene, e.g., a
global regulatory gene,
affecting multiple
distinct phenotypic
traits
Private good: a
resource that is costly
to produce and
provides a benefit only
to the producer
Metabolic constraint:
a specific case of
pleiotropy in which
QS control of both
public and private
nutrient acquisition
constrains cheating
Metabolic prudence:
mechanism that
stabilizes public-goods
cooperation by
initiating their
production only when
the fitness cost is low
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infections, QS cheats can exploit public goods and resources produced by a cooperating population
in a manner similar to that seen in previous studies using planktonic cultures (89). Another study
has demonstrated that during infections in human intubated patients, a mix of QS cooperating
cells and QS cheats resulted in a milder infection (59). The overall implication is that the spread of
cheats within a population can significantly reduce virulence due to a breakdown in cooperation.
In summary, experiments performed in test tubes, biofilms, and infection models have begun
to show that QS and at least some of the traits regulated by QS are social in nature. However, it is
important that we do not automatically regard all QS-regulated traits as social. A key challenge for
the future is to determine which traits are social and which are nonsocial. Empirically doing so will
require identifying the distribution of fitness benefits with steps similar to those outlined above.
Social Stability
With the assumption of sociality strongly supported, the maintenance or evolutionary stability of
QS must also be addressed. Explaining the stability of cooperative behaviors such as QS remains
one of the greatest problems for evolutionary biologists (115). Why would an individual carry out
a cooperative behavior that is costly to perform and primarily benefits other individuals or the
local group? Doing so threatens the stability of cooperative behaviors because it is vulnerable to
cheats that do not perform the cooperative act but reap the benefits from the cooperation of others
(115, 116). This problem is well known in the fields of economics and human morality, where it
is termed the tragedy of the commons (42). The tragedy is that in a group, individuals would do
better to cooperate, but this is not stable because each individual gains by selfishly pursuing its
own short-term interests (42). Yet cooperation clearly exists. In general, genes can be favored by
natural selection if they increase the reproductive success of their bearer (direct fitness) and also
increase the reproductive success of other related individuals that carry the same gene (indirect
fitness) (39, 40). Strategies that stabilize cooperative behaviors can therefore be categorized on
the basis of whether the benefits are direct or indirect.
If there is a direct fitness benefit to the individual performing the behavior, cooperation can
be maintained by processes that enforce cooperation and limit the spread of cheats by removing
the advantage of cheating. This can involve mechanisms to repress cheating such as policing and
sanctions (30, 110, 115). Empirical evidence demonstrating the existence of such processes in
microbes is sparse; however, some recent studies highlight that they might be widespread. One
described mechanism that may be pertinent to QS is pleiotropic constraint, in which behaviors
with high individual fitness benefits are coregulated with cooperative behaviors (17, 31). Adopting
a cheat strategy by mutation in a regulatory gene may therefore be accompanied by the loss of
another important function. Pleiotropy may specifically contribute to the stability of the LasRI
QS circuit in P. aeruginosa through the control of both public and private goods (17, 120). LasR
controls not only public, extracellular products but also certain private, cell-associated factors,
one of which is a periplasmic enzyme that metabolizes adenosine (50). During passage of wildtype cells in QS medium with casein and adenosine as carbon sources, LasR cheats do not invade
when adenosine is in excess because they do not receive the direct fitness benefit associated with
adenosine utilization (17). This mechanism has been termed metabolic constraint (17). Pleiotropy
may also contribute to the evolutionary stability of the rhl QS circuit. In casein medium that solely
favors QS-dependent public goods secretion, rhlR mutants do not invade wild-type populations,
possibly because the derepression of PQS synthesis, which is negatively regulated by rhlR, imposes
a metabolic burden (120).
Another stabilizing mechanism that involves regulatory control is metabolic prudence (125).
The concept has been derived from studying cooperative swarming motility in P. aeruginosa.
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Costly biosurfactant production is required for swarming, and theory suggests that this should be
exploitable by cheats. However, metabolic prudence results in the inability of cheats to invade a
swarm. Cooperators secrete QS-controlled biosurfactants only when the cost of production and
the impact on individual fitness are low. This regulation prevents nonsecretors from gaining an
evolutionary advantage. On the mechanistic level, this is achieved through the coregulation of
biosurfactant production by nitrogen availability (21, 97). These carbon-rich polymers are only
produced when active growth is limited or prevented by nitrogen starvation, and the cost of
production is low because carbon is not limiting.
A third property that affects the stability of public-goods cooperation is the durability of the
good itself. This has been shown for bacterial siderophores, iron-scavenging molecules that are
not only very stable but are also reused multiple times (63). Through facultative regulation, costly
siderophore production can thus be restricted to a brief growth period during iron starvation,
providing cheats with less opportunity to invade.
In addition to strategies that increase direct fitness, the evolutionary stability of QS may also
be supported by indirect fitness benefits, or kin selection (39, 40). The most common reason for
two individuals to share genes is for them to be genealogical relatives (kin), and so this process is
often termed kin selection, although it was originally called inclusive fitness (61). Kin selection is
discussed in detail elsewhere (34). Briefly, relatedness (r) is a measure of genetic similarity (85). In
microorganisms, r is measured at the locus or loci that control the social behavior being studied.
Cooperative individuals carrying an intact locus are related (r = 1), whereas those carrying a
mutation are unrelated to the cooperators (r = 0) (22, 116). Kin selection is likely to be highly
important for behaviors such as QS because of clonal reproduction and relatively local interactions (116). Empirical tests of the kin selection hypothesis in culture and in an infection model
revealed that QS is favored in conditions of high relatedness, whereas a lasR cheat is favored under
conditions of low relatedness. This is because in high-relatedness conditions, the QS wild-type
or the lasR mutant grew in separate test tubes or mice, and the greater fitness of the wild-type
led to an increase in wild-type frequency, which resulted in maintenance of QS. In contrast, in
low-relatedness populations, composed of mixtures of cooperators and cheats, the cheats are able
to exploit cooperators and this does not favor QS (24, 92).
Kin selection: a
process by which traits
are favored because of
their beneficial effects
on the fitness of
relatives
Density Dependence
In addition to questioning the sociality of QS, DS as a hypothesis is important because it challenges
a second major assumption of QS, namely that density matters. The general consensus in the
literature describes QS as the production, release, and detection of signaling molecules by cells.
Signal detection triggers the production of a range of extracellular factors, which are secreted from
cells and have various uses, including nutrient scavenging for growth and toxin production for
virulence. This regulatory mechanism results in an increase in the production of QS-controlled
factors at high cell densities, which is generally further accelerated and stabilized by the positive
autoregulation of signal production. This important assumption implies that the QS circuitry itself
is a mechanism that optimizes cooperation by delaying expression of a social behavior until the
cost balances the benefit.
Despite the huge amount of research on QS, there is very little work testing the idea that QS provides a benefit at high density. It is therefore crucial to compare individual and population benefits
of inducing QS at high and low densities (Figure 3). Two separate studies recently tested the idea
that QS provides the greatest benefit at high cell densities. The first study focused on the enzymatic
breakdown of public goods in the external environment and showed that QS can provide social
benefits to other cells and that the fitness benefits of QS are greater at higher cell densities, when
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a
b
Public good
External volume per cell
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Private good
Cell with fitness benefit
Cell with no fitness benefit
Figure 3
Density, microenvironment, and the fitness benefits of producing (a) public and (b) private goods. Assuming
constitutive production, private goods, which are utilized within a cell, confer direct fitness benefits to
individuals, thus allowing growth at both low and high cell densities. In contrast, public goods confer both
direct and indirect fitness benefits to individuals and neighboring cells, but their production is most efficient
at high cell densities. Therefore, QS optimizes the costs and benefits of public goods by restricting public
goods production to high densities (18, 80). Costs and benefits are equivalent from the perspective of a single
cell (81). As the microenvironment or external volume per cell decreases (depicted as a dark blue dashed
circle in the bottom images), the benefit from public goods production increases, whereas the benefit from
private goods production remains the same.
cells are better able to interact (18) (Figure 3a). Here the authors independently manipulated population density and the induction of and response to a QS signal in P. aeruginosa. They found that
the benefit of QS was greater at higher population densities because QS-dependent extracellular
public goods were used more efficiently. The experimental design also considered QS-controlled
private goods, in this case adenosine metabolism, in which benefits are retained by the individual
and not shared with the population (Figure 3b). Here the benefits do not vary with cell density.
The second, related study was conducted with a synthetic QS system engineered in Escherichia coli,
which controls the synthesis of a costly but beneficial exoenzyme public good (80). By using this
system, the authors demonstrated that exoenzyme production is beneficial at high cell densities but
that the optimal benefit only occurs if QS is initiated at a sufficiently high density. Overall, these
results support the assumption that QS improves the efficiency of cooperative behaviors through
activation at high density. An analogous scenario in which metabolically cheap QS invades and
helps stabilize more costly cooperative behaviors was modeled by Czaran & Hoekstra (15).
Laboratory experiments on QS have traditionally been performed with high-volume planktonic
batch cultures, in which cells can reach very high numbers. These include the aforementioned
studies on the relationship between density and QS efficiency. There is an increasing body of work
examining QS at low population sizes or even at the single-cell level. For example, the confinement
of individual P. aeruginosa cells in small volumes using microfluidic devices initiates high-density
QS target gene expression (7, 13), as does the confinement of individual Staphylococcus aureus
cells inside the phagosome of eukaryotic cells (98). Similarly, the quorum size of Pseudomonas
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syringae is very small when grown in non-water-saturated environments such as plant leaves (25).
Ultrasensitive AHL QS circuits have also recently been described in two members of the genus
Bradyrhizobium, which respond to signal levels at orders of magnitude lower than that described for
model QS systems (68). Such examples refute the notion held by some that QS requires millions
of cells (7), although the original definition of QS never discounted the possibility that even a
single cell in a small-enough volume would constitute a quorum (43) (Figure 3).
A useful quantitative concept in this context is the sensing potential, introduced by Pai & You
(81). It quantifies the ability of a single cell to sense the dimensions of its microenvironment. The
approach is similar to that of DS but does not consider diffusion limitations in the environment.
The sensing potential therefore intuitively relates QS of an individual cell to the population-level
phenotype (Figure 3).
PVD: pyoverdine
QS-Independent Cooperation
Although the control of costly cooperative behaviors by QS is advantageous, the production of
some public goods appears to be largely independent of QS. One such example is the production of
the siderophore pyoverdine (PVD) in P. aeruginosa. A QS-negative strain still produces PVD with
only an approximately twofold decrease under conditions of iron stringency (106). In contrast,
pathways that directly sense iron starvation activate PVD biosynthetic genes ten- to several
hundredfold (79). Why would PVD expression not be more strongly coregulated by QS? Insights
into the molecular properties of PVD and mechanisms of regulation offer some clues. PVDs are
structurally distinct between different species and sometimes even between closely related strains
of the same species (75, 76). Such structural diversity provides specificity and hence excludability,
as each distinct PVD type can only be utilized by a cell carrying a complementary receptor. This
mechanism is referred to as kin discrimination, as it permits an individual to distinguish relatives
from nonrelatives and preferentially direct aid toward relatives (39, 40). Importantly, the structural specificity of PVD is also exploited for signaling purposes. PVD expression is significantly
augmented by the detection of PVD itself (64). Recognition of PVD, specifically Fe-bound PVD,
by an outer membrane receptor initiates a transition from basal to high expression levels. In
a fashion somewhat analogous to QS, PVD acts as an autoinducer and perhaps independently
achieves the primary benefits QS has to offer. PVD signaling differs from QS in that it serves both
as the signal and as the public good, and that it is more costly to produce than an AHL signal,
which is used solely for the purpose of signaling. The specificity in PVD reception is exploited
in a way not possible with most other public goods and directly conveys information about the
utility of PVD production, namely the ability to chelate and deliver iron, as it is the Fe-bound
form of PVD that is sensed (38). Therefore, further integration of PVD into a QS circuit seems
redundant, although no studies have pursued this question from a social evolution perspective.
Although we have made an attempt here to rationalize QS-dependent versus QS-independent
production of a public good in an individual species, we note that specific public goods are not
controlled identically in different species. Clearly, prevailing environmental conditions have a
large role in the evolution of regulatory networks. Unfortunately, these conditions remain largely
unknown, particularly for opportunistic pathogens with primarily nonparasitic life histories.
QUORUM SENSING AS AN ANTIVIRULENCE DRUG TARGET:
SOCIAL INTERACTIONS AND RESISTANCE
The Potential of Antivirulence Drugs
Antimicrobial agents, first discovered a century ago, have significantly eased the burden of infectious disease, but this achievement has been endangered by the emergence of antibiotic resistance.
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A promising new strategy is to target virulence (5, 11, 12, 86). Whereas conventional antibiotics
target in vitro viability, antivirulence drugs target functions required for infection, thereby essentially disarming the bacteria. It is thought that this tips the balance in favor of the host, allowing
the immune system to clear the infection. This approach potentially has several advantages, including exerting less selective pressure toward resistance, preserving the endogenous microflora,
and of course expanding the repertoire of bacterial targets. In addition, antivirulence drugs could
be administered in combination with conventional antibiotics to enhance their efficacy.
QS-Inhibiting Compounds
The regulatory mechanisms that govern virulence gene expression are thought to be an attractive
target for antivirulence drugs, in particular small-molecule-mediated cell-cell communication.
In principle, one could interfere with QS by inhibiting signal production, accelerating signal
degradation, or inhibiting signal reception (Figure 4a). Most of the work to date has focused
on inhibiting signal binding by QS receptors. A number of structural AHL analogs and other
small molecules have been shown to inhibit the expression of QS-controlled genes and biofilm
formation in P. aeruginosa (35, 78, 103). The halogenated furanones have been investigated in
greatest detail (6, 46) (Figure 4b). Administration of halogenated furanones promotes clearance
of P. aeruginosa from the lungs of infected mice (48, 123) and increases the survival time of mice
in a lethal lung infection model (123).
The initial halogenated furanone compound was isolated from the seaweed Delisea pulchra
(37), although derivatives with more potent anti-QS activity have been synthesized (72). Work
with V. fischeri LuxR protein suggests that halogenated furanones exert their inhibitory effect by
accelerating receptor protein turnover (72). Analysis of LuxR mutants with substitutions at the
AHL binding pocket indicates that halogenated furanones, in contrast to some signal analogs,
inhibit in a nonagonist fashion (58). In P. aeruginosa, halogenated furanones inhibit production
of numerous virulence factors and increase the susceptibility of biofilms to antibiotic treatment
(47, 48). Microarray analysis showed that they inhibit 85% of all QS-induced genes (48).
Despite initial promise, halogenated furanones are not optimally suited for therapeutic use
because of their high reactivity. Other potentially more promising compounds have recently
been identified (Figure 4b). One example is a structurally unrelated triphenyl mimic of
P. aeruginosa 3OC12-HSL that is a potent, specific LasR agonist (77) and serves as a scaffold for
the synthesis of more stable and less toxic QS inhibitors (QSIs). One antagonist that effectively
inhibits P. aeruginosa AHL-QS, termed TP-5, has been derived from this compound (77).
Another example is a compound with a phenyl group and a 12-carbon alkyl tail that broadly
inhibits LasR-dependent gene expression (78). Neither TP-5 nor the phenyl compound has been
tested in animal infection models.
How Likely Is the Evolution of Resistance?
Widespread bacterial resistance to virtually every clinically significant conventional antibiotic
has evolved rapidly (12). The question is whether such rapid resistance to antivirulence drugs,
specifically QSIs, might also evolve (19). In general, there are two prerequisites for the evolution of
resistance to occur, namely mutability and selective pressure. Mutability is essentially already met
by the natural mutation rate, permitting genetic change. In the case of QS, this is further augmented
by considerable variation in the QS regulatory circuitry among different strains of the same species.
This includes the presence of QS-deficient isolates in natural P. aeruginosa populations (10, 16,
32, 49, 51, 102, 107). QSI resistance can also easily be obtained through genetic engineering:
A point mutation in the LuxR signal binding site, L42A, renders the receptor insensitive to
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Enzymes
Antibodies
a
Cl
b
Br
O
O
O
LuxI
LuxR
O
Cl
C-30
TP-5
Small-molecule inhibitors
H
N
V-06-018
QSI targets
cooperative behavior
N
H
Br
AHL
c
NH
O
O
QSI targets
noncooperative behavior
QS-controlled enzyme
Nutrient
QSI-resistant cell
QSI-sensitive cell
Figure 4
QS as an antivirulence drug target. (a) Potential targets of QSI strategies within the AHL signaling circuitry.
Small molecules may interact with receptor or synthase to inhibit signal binding or generation, respectively.
Extracellular AHL may also be enzymatically degraded or be sequestered by antibodies. (b) Selected smallmolecule QSIs. (c) Social interactions and resistance evolution. Outcomes of two scenarios, QS inhibition of
cooperative and noncooperative behaviors, are shown. The cooperative behavior is extracellular degradation
of a complex nutrient (e.g., casein) by a secreted enzyme. The noncooperative behavior is intracellular
degradation of a nutrient (e.g., adenosine) by a cell-associated enzyme. For clarity, details on nutrient
utilization depicted in the top panels are omitted in the bottom images. Abbreviations: AHL,
acyl-homoserine lactone; QS, quorum sensing; QSI, QS inhibitor.
synthetic antagonist N-(propylsulfanylacetyl)-L-homoserine lactone while only modestly reducing
sensitivity to activation by the natural signal, 3-oxo-C8-homoserine lactone (58). In addition,
overexpression of the LuxR homolog TraR in A. tumefaciens overcomes inhibition by synthetic
AHL analogs (128).
Understanding the selective forces at work is a more complicated matter. Because QS disruption
does not affect bacterial growth in standard laboratory media, it has generally been assumed that
there is no selective pressure for the evolution of resistance. However, the situation is significantly
different in vivo. Numerous animal infection studies have shown that P. aeruginosa QS is important
for infection (67, 83, 91, 122). Reduced virulence is probably due to the decreased ability of
QS mutants to colonize and disseminate in a given host, and to the increased clearance of QS
mutants by the host immune system. It is also possible that the AHL signals themselves act as
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immunomodulators (90). In either case, our considerations thus far suggest that a strain resistant
to QS inhibition would have a selective advantage over a sensitive strain during QSI treatment of
an infection. As with opportunistic pathogens such as P. aeruginosa, the selective forces outside the
host are less clear, and there is mounting evidence that virulence factors are maintained, at least
in part, because of advantages in nonparasitic contexts (8).
Bacterial social interactions add another layer of complexity. Theoretical work suggests that
social conflict may prevent or at least slow the evolution of QSI resistance (1). Conceptually, a
single cell or a small subpopulation of cells harboring QSI resistance will initially exist within a
larger population of cells sensitive to the QSI. Treatment with a QSI will lead to a tragedy of the
commons: The QSI-resistant cells will behave as cooperators capable of producing QS-controlled
public goods. The QSI-sensitive majority, unable to produce these goods themselves, will benefit
from this expenditure and effectively behave as cheats (Figure 4c). Given the growth advantage
that cheats generally enjoy over cooperators, QSI resistance should not evolve. This prediction
was experimentally tested in a lab microcosm with P. aeruginosa QSI-sensitive and QSI-resistant
mimics, represented by signal receptor (lasR rhlR) mutant and wild-type strains, respectively (74).
Two separate synthetic growth media were designed with either casein or adenosine as the sole
carbon source to create environments where either QS-controlled public-goods production or
QS-controlled private goods production was favored. Corroborating the theoretical work, QSI
resistant mimics do not have a growth advantage when public-goods cooperation is favored. They
do have a growth advantage when private goods production is favored because they do not share the
good nor the benefit derived from it (Figure 4c). Of course, the use of mimics has its limitations, as
QSI resistance may also occur via QSI degradation, limited uptake, or increased efflux, in addition
to target modification.
These in vitro studies also neglect several other factors pertinent to an infection, such as spatial
structuring and selective pressures imposed by the host immune system. Nevertheless, results from
experimental infection of mice with P. aeruginosa support the outcomes obtained from modeling
QS-controlled public-goods cooperation. A mixed infection with wild-type and lasR mutant strains
results in reduced virulence, compared with a wild-type-only infection (89). The two strains again
act as a cooperator and cheat pair that can be considered QSI-resistant and QSI-sensitive mimics,
respectively. Intriguingly, given their potential to attenuate infection, cheat strains themselves
have also been proposed as antivirulence therapeutics (9).
Although the evidence cited thus far suggests that QS-dependent cooperative behaviors represent a viable antivirulence drug target, one study cautions that this approach may also bear
certain epidemiological risks. QSI treatment of a fully susceptible, QS-proficient P. aeruginosa
population disfavors invasion by true QS-deficient cheats, thereby increasing the prevalence of
the QS-proficient, virulent strain (60).
As mentioned above, QSI resistance is expected to evolve when QS controls a noncooperative
behavior, such as growth on adenosine as the sole carbon source. Wood and colleagues (70)
provided further evidence for this with an in vitro evolution experiment in which P. aeruginosa
was cultured in adenosine medium containing a halogenated furanone as a QSI. They isolated
partially QSI-resistant mutants that exhibited increased efflux of the furanone compound, imparted
by a loss-of-function mutation in a repressor of the MexAB-OprM multidrug resistance efflux
pump. The ecological context of bacterial adenosine utilization is not entirely clear (49), although
adenosine, in response to injury and inflammation, can reach high levels in certain host tissues (82).
Nevertheless, bacterial consumption of this or other private nutrients in the natural environment
is predicted to accelerate the evolution of QSI resistance.
Although the aforementioned studies have identified social conflict as a major constraint
to the emergence of QSI resistance, in vitro evolution experiments have also shown that this
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constraint can be overcome under certain conditions. When P. aeruginosa lasR deletion mutants are
starvation-selected in growth medium that requires las-dependent proteolysis, second-site mutants
emerge that regain the ability to produce certain QS-controlled factors including exoproteases
(112). These mutants appear to be resistant to exploitation by cheats, similar to the “Phoenix”
variant of the fruiting bacterium Myxococcus xanthus (29), but it is not known whether they are also
fully virulent. If they were fully virulent because of compensation by the rhl system, then a potent
QSI that targets both las and rhl QS would be needed clinically to avoid the rapid development
of resistance through this mechanism. It seems obvious that more fundamental knowledge about
genetic regulatory circuits is needed if we hope to develop QSI therapeutics for P. aeruginosa.
QSI Resistance and the Quorum
If QSI resistance evolves from a single clone or at least from a small subpopulation, what about the
quorum? Would QS-controlled traits in the presence of QSI be expressed at all? This complex
question likely depends on a multitude of factors and relates to the fundamental issue of the
infective dose. The dynamics of colonization and killing, and the role of QS in active growth versus
preventing clearance by the immune system, is not well understood. If QS was strictly required
for growth in vivo, it is unlikely that a single or a few QSI-resistant bacteria would constitute
a quorum to express QS-controlled factors. However, if there was some growth in vivo in the
presence of QSI, then a small cluster of QSI-resistant bacteria could possibly cross the quorum
threshold and produce QS products to acquire nutrients or fight the immune system, which in
turn would enhance their fitness. An increase in the colonization ability of QS-proficient strains,
compared with deficient strains, is already seen for fairly small inocula (for example, 1,000 bacteria
in an acute pneumonia mouse model) (2, 104). This finding suggests that a quorum can be achieved
with a fairly small number of bacteria, presumably modulated by population structuring (limited
diffusion) in the respective colonization site and by bacterial starvation, which can significantly
lower the quorum threshold (111).
CONCLUSIONS
The past three decades have provided remarkable insight into the mechanisms of bacterial communication and cooperation, but the evolutionary and ecological assumptions about these behaviors
have been empirically tested only in recent years. Here emphasis has shifted from merely confirming general evolutionary theory with microbes to actually understanding the evolution of
microbial sociality in its own right. Various novel -omics tools in microbial ecology will further
accelerate discovery.
Research thus far strongly supports the notion that QS represents a social behavior and that it
can offer density-dependent fitness advantages. QS-controlled cooperation is favored through kin
selection and specific mechanisms that help constrain cheating, including pleiotropy and metabolic
prudence. More specifically, QS signaling optimizes other, more costly cooperative behaviors and
thereby helps stabilize these behaviors. As QS circuits often control virulence factors, there is high
interest in interfering with QS. Preliminary evidence suggests that social interactions in bacterial
populations can slow the evolution of resistance to QSIs.
SUMMARY POINTS
1. Microbial social interactions are now known to be both common and important.
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2. A few key model systems in the Proteobacteria have been particularly useful in understanding the mechanisms and, more recently, the evolution of QS.
3. Recent empirical work supports the traditional assumptions of QS, namely that QS is a
social behavior and that QS provides a cell-density-dependent benefit.
4. The assumption that QS is a social behavior is supported by the demonstration of social
cheating in test tubes, biofilms, and infections and is consistent with the presence of
QS-negative strains in natural populations.
5. QS-controlled public-goods cooperation is stabilized by several forces and mechanisms,
including kin selection, pleiotropy (metabolic constraint), and metabolic prudence.
6. QS optimizes more costly cooperative behaviors by restricting their production to when
they are beneficial.
7. QSIs are appealing alternatives to traditional antibiotics. Theory and proof-of-concept
data from a lab microcosm and an infection model suggest that social conflict reduces
the potential for QSI resistance to evolve.
FUTURE ISSUES
1. An important task for the future will be to carry research from the laboratory to the natural
environment. What are the roles, costs, and benefits of QS in these environments, and
what is the spatiotemporal structure of natural QS populations? Are the selective forces
that shape social behaviors identical to those in lab microcosms?
2. Additional questions concern the nature and stability of the various social behaviors in
bacteria. Which behaviors are social and why? Why are some behaviors controlled by
QS, whereas others are not? What mechanisms help stabilize these behaviors, and specifically, what is the role of accessory mechanisms that coregulate QS and QS-controlled
behaviors?
3. Preliminary findings on the contribution of bacterial social interactions to the evolution
of resistance to QSIs and to other antivirulence drugs require further testing in structured
communities such as biofilms and in animal infection models.
DISCLOSURE STATEMENT
The authors are not aware of any affiliations, memberships, funding, or financial holdings that
might be perceived as affecting the objectivity of this review.
ACKNOWLEDGMENTS
Work on this review was supported by the National Science Foundation (grant 1158553 to M.S.),
the Royal Society (to S.D.), and the National Institutes of Health (grants GM-59026 and P30 DK
89507 to E.P.G.).
LITERATURE CITED
1. André J-B, Godelle B. 2005. Multicellular organization in bacteria as a target for drug therapy. Ecol. Lett.
8:800–10
58
Schuster et al.
MI67CH03-Greenberg
ARI
4 May 2013
14:58
2. Allewelt M, Coleman FT, Grout M, Priebe GP, Pier GB. 2000. Acquisition of expression of the
Pseudomonas aeruginosa ExoU cytotoxin leads to increased bacterial virulence in a murine model of acute
pneumonia and systemic spread. Infect. Immun. 68:3998–4004
3. Antunes LC, Schaefer AL, Ferreira RB, Qin N, Stevens AM, et al. 2007. Transcriptome analysis of the
Vibrio fischeri LuxR-LuxI regulon. J. Bacteriol. 189:8387–91
4. Banin E, Lozinski A, Brady KM, Berenshtein E, Butterfield PW, et al. 2008. The potential of
desferrioxamine-gallium as an anti-Pseudomonas therapeutic agent. Proc. Natl. Acad. Sci. USA 105:16761–
66
5. Barczak AK, Hung DT. 2009. Productive steps toward an antimicrobial targeting virulence. Curr. Opin.
Microbiol. 12:490–96
6. Bjarnsholt T, Givskov M. 2007. Quorum-sensing blockade as a strategy for enhancing host defences
against bacterial pathogens. Philos. Trans. R. Soc. Lond. B 362:1213–22
7. Boedicker JQ, Vincent ME, Ismagilov RF. 2009. Microfluidic confinement of single cells of bacteria in
small volumes initiates high-density behavior of quorum sensing and growth and reveals its variability.
Angew. Chem. Int. Ed. 48:5908–11
8. Brown SP, Cornforth DM, Mideo N. 2012. Evolution of virulence in opportunistic pathogens: generalism, plasticity, and control. Trends Microbiol. 20:336–42
9. Brown SP, West SA, Diggle SP, Griffin AS. 2009. Social evolution in microorganisms and a Trojan
horse approach to medical intervention strategies. Philos. Trans. R. Soc. Lond. B 364:3157–68
10. Cabrol S, Olliver A, Pier GB, Andremont A, Ruimy R. 2003. Transcription of quorum-sensing system
genes in clinical and environmental isolates of Pseudomonas aeruginosa. J. Bacteriol. 185:7222–30
11. Cegelski L, Marshall GR, Eldridge GR, Hultgren SJ. 2008. The biology and future prospects of antivirulence therapies. Nat. Rev. Microbiol. 6:17–27
12. Clatworthy AE, Pierson E, Hung DT. 2007. Targeting virulence: a new paradigm for antimicrobial
therapy. Nat. Chem. Biol. 3:541–48
13. Connell JL, Wessel AK, Parsek MR, Ellington AD, Whiteley M, Shear JB. 2010. Probing prokaryotic
social behaviors with bacterial “lobster traps”. mBio 1:e00202–10
14. Costerton JW, Stewart PS, Greenberg EP. 1999. Bacterial biofilms: a common cause of persistent
infections. Science 284:1318–22
15. Czaran T, Hoekstra RF. 2009. Microbial communication, cooperation and cheating: Quorum
sensing drives the evolution of cooperation in bacteria. PLoS ONE 4:e6655
16. D’Argenio DA, Wu M, Hoffman LR, Kulasekara HD, Deziel E, et al. 2007. Growth phenotypes of
Pseudomonas aeruginosa lasR mutants adapted to the airways of cystic fibrosis patients. Mol. Microbiol.
64:512–33
17. Dandekar AA, Chugani S, Greenberg EP. 2012. Bacterial quorum sensing and metabolic incentives to cooperate. Science 338:264–66
18. Darch SE, West SA, Winzer K, Diggle SP. 2012. Density-dependent fitness benefits in quorumsensing bacterial populations. Proc. Natl. Acad. Sci. USA 109:8259–63
19. Defoirdt T, Boon N, Bossier P. 2010. Can bacteria evolve resistance to quorum sensing disruption? PLoS
Pathog. 6:e1000989
20. Denervaud V, TuQuoc P, Blanc D, Favre-Bonte S, Krishnapillai V, et al. 2004. Characterization of cellto-cell signaling-deficient Pseudomonas aeruginosa strains colonizing intubated patients. J. Clin. Microbiol.
42:554–62
21. Desai JD, Banat IM. 1997. Microbial production of surfactants and their commercial potential. Microbiol.
Mol. Biol. Rev. 61:47–64
22. Diggle SP. 2010. Microbial communication and virulence: lessons from evolutionary theory. Microbiology
156:3503–12
23. Diggle SP, Gardner A, West SA, Griffin AS. 2007. Evolutionary theory of bacterial quorum sensing:
When is a signal not a signal? Philos. Trans. R. Soc. Lond. B 362:1241–49
24. Diggle SP, Griffin AS, Campbell GS, West SA. 2007. Cooperation and conflict in quorum-sensing
bacterial populations. Nature 450:411–14
25. Dulla G, Lindow SE. 2008. Quorum size of Pseudomonas syringae is small and dictated by water availability
on the leaf surface. Proc. Natl. Acad. Sci. USA 105:3082–87
www.annualreviews.org • Acyl-Homoserine Lactone Quorum Sensing
15. Modeling shows
how communicationbased cooperation such
as QS can both evolve
and subsequently
persist.
17. QS regulation of
private goods such as
adenosine provides
metabolic incentive to
cooperate rather than
cheat.
18. The fitness benefits
provided by QS at high
densities is empirically
demonstrated with
P. aeruginosa.
24. QS cheats have a
relative fitness
advantage when QS is
favored, and kin
selection stabilizes QS.
59
MI67CH03-Greenberg
ARI
4 May 2013
14:58
26. Eberhard A. 1972. Inhibition and activation of bacterial luciferase synthesis. J. Bacteriol. 109:1101–5
27. Eberhard A, Burlingame AL, Eberhard C, Kenyon GL, Nealson KH, Oppenheimer NJ. 1981. Structural
identification of autoinducer of Photobacterium fischeri luciferase. Biochemistry 20:2444–49
28. Engebrecht J, Nealson K, Silverman M. 1983. Bacterial bioluminescence: isolation and genetic analysis
of functions from Vibrio fischeri. Cell 32:773–81
29. Fiegna F, Yu YT, Kadam SV, Velicer GJ. 2006. Evolution of an obligate social cheater to a superior
cooperator. Nature 441:310–14
30. Foster KR, Parkinson K, Thompson CR. 2007. What can microbial genetics teach sociobiology? Trends
Genet. 23:74–80
31. Foster KR, Shaulsky G, Strassmann JE, Queller DC, Thompson CR. 2004. Pleiotropy as a mechanism
to stabilize cooperation. Nature 431:693–96
32. Fothergill JL, Panagea S, Hart CA, Walshaw MJ, Pitt TL, Winstanley C. 2007. Widespread pyocyanin
over-production among isolates of a cystic fibrosis epidemic strain. BMC Microbiol. 7:45
33. Fuqua WC, Winans SC, Greenberg EP. 1994. Quorum sensing in bacteria: the LuxR-LuxI family of
cell density-responsive transcriptional regulators. J. Bacteriol. 176:269–75
34. Gardner A, West SA, Wild G. 2011. The genetical theory of kin selection. J. Evol. Biol. 24:1020–43
35. Geske GD, Wezeman RJ, Siegel AP, Blackwell HE. 2005. Small molecule inhibitors of bacterial quorum
sensing and biofilm formation. J. Am. Chem. Soc. 127:12762–63
36. Gilbert KB, Kim TH, Gupta R, Greenberg EP, Schuster M. 2009. Global position analysis of the
Pseudomonas aeruginosa quorum-sensing transcription factor LasR. Mol. Microbiol. 73:1072–85
37. Givskov M, de Nys R, Manefield M, Gram L, Maximilien R, et al. 1996. Eukaryotic interference with
homoserine lactone-mediated prokaryotic signalling. J. Bacteriol. 178:6618–22
38. Greenwald J, Zeder-Lutz G, Hagege A, Celia H, Pattus F. 2008. The metal dependence of pyoverdine
interactions with its outer membrane receptor FpvA. J. Bacteriol. 190:6548–58
39. Hamilton WD. 1964. The genetical evolution of social behaviour. I. J. Theor. Biol. 7:1–16
40. Hamilton WD. 1964. The genetical evolution of social behaviour. II. J. Theor. Biol. 7:17–52
41. Hamood AN, Griswold J, Colmer J. 1996. Characterization of elastase-deficient clinical isolates of
Pseudomonas aeruginosa. Infect. Immunity 64:3154–60
42. Hardin G. 1968. The tragedy of the commons. Science 162:1243–48
43. Hastings JW. 2010. Quorum sensing is not a misnomer. Microbe 5:189
44. Heeb S, Fletcher MP, Chhabra SR, Diggle SP, Williams P, Camara M. 2011. Quinolones: from antibiotics to autoinducers. FEMS Microbiol. Rev. 35:247–74
45. Hense BA, Kuttler C, Muller J, Rothballer M, Hartmann A, Kreft JU. 2007. Does efficiency sensing
unify diffusion and quorum sensing? Nat. Rev. Microbiol. 5:230–39
46. Hentzer M, Givskov M. 2003. Pharmacological inhibition of quorum sensing for the treatment of chronic
bacterial infections. J. Clin. Invest. 112:1300–7
47. Hentzer M, Riedel K, Rasmussen TB, Heydorn A, Andersen JB, et al. 2002. Inhibition of quorum sensing
in Pseudomonas aeruginosa biofilm bacteria by a halogenated furanone compound. Microbiology 148:87–102
48. Hentzer M, Wu H, Andersen JB, Riedel K, Rasmussen TB, et al. 2003. Attenuation of Pseudomonas
aeruginosa virulence by quorum sensing inhibitors. EMBO J. 22:3803–15
49. Heurlier K, Denervaud V, Haas D. 2006. Impact of quorum sensing on fitness of Pseudomonas aeruginosa.
Int. J. Med. Microbiol. 296:93–102
50. Heurlier K, Denervaud V, Haenni M, Guy L, Krishnapillai V, Haas D. 2005. Quorum-sensing-negative
(lasR) mutants of Pseudomonas aeruginosa avoid cell lysis and death. J. Bacteriol. 187:4875–83
51. Hoffman LR, Kulasekara HD, Emerson J, Houston LS, Burns JL, et al. 2009. Pseudomonas aeruginosa
lasR mutants are associated with cystic fibrosis lung disease progression. J. Cyst. Fibros. 8:66–70
52. Huse HK, Kwon T, Zlosnik JEA, Speert DP, Marcotte EM, Whiteley M. 2010. Parallel evolution in
Pseudomonas aeruginosa over 39,000 generations in vivo. mBio 1(4):e00199–10
53. Joelsson A, Liu Z, Zhu J. 2006. Genetic and phenotypic diversity of quorum-sensing systems in clinical
and environmental isolates of Vibrio cholerae. Infect. Immun. 74:1141–47
54. Kalia VC, Purohit HJ. 2011. Quenching the quorum sensing system: potential antibacterial drug targets.
Crit. Rev. Microbiol. 37:121–40
60
Schuster et al.
MI67CH03-Greenberg
ARI
4 May 2013
14:58
55. Kaplan HB, Greenberg EP. 1985. Diffusion of autoinducer is involved in regulation of the Vibrio fischeri
luminescence system. J. Bacteriol. 163:1210–14
56. Keller L, Surette MG. 2006. Communication in bacteria: an ecological and evolutionary perspective.
Nat. Rev. Microbiol. 4:249–58
57. Kleerebezem M, Quadri LE, Kuipers OP, de Vos WM. 1997. Quorum sensing by peptide pheromones
and two-component signal-transduction systems in gram-positive bacteria. Mol. Microbiol. 24:895–904
58. Koch B, Liljefors T, Persson T, Nielsen J, Kjelleberg S, Givskov M. 2005. The LuxR receptor: the sites
of interaction with quorum-sensing signals and inhibitors. Microbiology 151:3589–602
59. Kohler T, Buckling A, van Delden C. 2009. Cooperation and virulence of clinical Pseudomonas
aeruginosa populations. Proc. Natl. Acad. Sci. USA 106:6339–44
60. Kohler T, Perron GG, Buckling A, van Delden C. 2010. Quorum sensing inhibition selects for virulence
and cooperation in Pseudomonas aeruginosa. PLoS Pathog. 6:e1000883
61. Koulman A, Lee TV, Fraser K, Johnson L, Arcus V, et al. 2012. Identification of extracellular siderophores
and a related peptide from the endophytic fungus Epichloë festucae in culture and endophyte-infected
Lolium perenne. Phytochemistry 75:128–39
62. Kreft JU. 2004. Biofilms promote altruism. Microbiology 150:2751–60
63. Kuemmerli R, Brown SP. 2010. Molecular and regulatory properties of a public good shape the evolution
of cooperation. Proc. Natl. Acad. Sci. USA 107:18921–26
64. Lamont IL, Beare PA, Ochsner U, Vasil AI, Vasil ML. 2002. Siderophore-mediated signaling regulates
virulence factor production in Pseudomonas aeruginosa. Proc. Natl. Acad. Sci. USA 99:7072–77
65. Lee JH, Lequette Y, Greenberg EP. 2006. Activity of purified QscR, a Pseudomonas aeruginosa orphan
quorum-sensing transcription factor. Mol. Microbiol. 59:602–9
66. Lequette Y, Lee JH, Ledgham F, Lazdunski A, Greenberg EP. 2006. A distinct QscR regulon in the
Pseudomonas aeruginosa quorum-sensing circuit. J. Bacteriol. 188:3365–70
67. Lesprit P, Faurisson F, Join-Lambert O, Roudot-Thoraval F, Foglino M, et al. 2003. Role of the quorumsensing system in experimental pneumonia due to Pseudomonas aeruginosa in rats. Am. J. Respir. Crit. Care
Med. 167:1478–82
68. Lindemann A, Pessi G, Schaefer AL, Mattmann ME, Christensen QH, et al. 2011. Isovaleryl-homoserine
lactone, an unusual branched-chain quorum-sensing signal from the soybean symbiont Bradyrhizobium
japonicum. Proc. Natl. Acad. Sci. USA 108:16765–70
69. Lyczak JB, Cannon CL, Pier GB. 2000. Establishment of Pseudomonas aeruginosa infection: lessons from
a versatile opportunist. Microbes Infect. 2:1051–60
70. Maeda T, Garcia-Contreras R, Pu M, Sheng L, Garcia LR, et al. 2012. Quorum quenching quandary:
resistance to antivirulence compounds. ISME J. 6:493–501
71. Majerczyk CD, Greenberg EP, Chandler JR. 2013. Quorum sensing in Burkholderia. In Regulation of
Bacterial Virulence, ed. ML Vasil, AJ Darwin. Washington, DC: ASM Press. In press
72. Manefield M, Rasmussen TB, Henzter M, Andersen JB, Steinberg P, et al. 2002. Halogenated furanones
inhibit quorum sensing through accelerated LuxR turnover. Microbiology 148:1119–27
73. Maynard-Smith J, Harper D. 2003. Animal Signals. Oxford, UK: Oxford Univ. Press
74. Mellbye B, Schuster M. 2011. The sociomicrobiology of antivirulence drug resistance: a proof
of concept. mBio 2(5):e00131–11
75. Meyer JM, Geoffroy VA, Baida N, Gardan L, Izard D, et al. 2002. Siderophore typing, a powerful tool for
the identification of fluorescent and nonfluorescent pseudomonads. Appl. Environ. Microbiol. 68:2745–53
76. Meyer JM, Stintzi A, DeVos D, Cornelis P, Tappe R, et al. 1997. Use of siderophores to type pseudomonads: the three Pseudomonas aeruginosa pyoverdine systems. Microbiology 143:35–43
77. Muh U, Hare BJ, Duerkop BA, Schuster M, Hanzelka BL, et al. 2006. A structurally unrelated mimic
of a Pseudomonas aeruginosa acyl-homoserine lactone quorum-sensing signal. Proc. Natl. Acad. Sci. USA
103:16948–52
78. Muh U, Schuster M, Heim R, Singh A, Olson ER, Greenberg EP. 2006. Novel Pseudomonas aeruginosa
quorum-sensing inhibitors identified in an ultra-high-throughput screen. Antimicrob. Agents Chemother.
50:3674–79
www.annualreviews.org • Acyl-Homoserine Lactone Quorum Sensing
59. Analysis of clinical
populations indicates
social conflict can drive
the emergence of QS
mutants in human
infections.
74. A P. aeruginosa
laboratory model
suggests social
dynamics hinders
evolution of QSI
resistance.
61
MI67CH03-Greenberg
ARI
4 May 2013
80. A synthetic QS
circuit in E. coli
demonstrates optimal
benefits of QS at high
densities.
89. QS cheats have a
relative fitness
advantage in
experimental infection
of mice with
Pseudomonas aeruginosa.
94. QS cheats emerge
during in vitro evolution
of P. aeruginosa under
conditions that favor
QS.
62
14:58
79. Ochsner UA, Wilderman PJ, Vasil AI, Vasil ML. 2002. GeneChip expression analysis of the iron
starvation response in Pseudomonas aeruginosa: identification of novel pyoverdine biosynthesis genes.
Mol. Microbiol. 45:1277–87
80. Pai A, Tanouchi Y, You L. 2012. Optimality and robustness in quorum sensing (QS)-mediated
regulation of a costly public good enzyme. Proc. Natl. Acad. Sci. USA 109:19810–15
81. Pai A, You L. 2009. Optimal tuning of bacterial sensing potential. Mol. Syst. Biol. 5:286
82. Patel NJ, Zaborina O, Wu L, Wang Y, Wolfgeher DJ, et al. 2007. Recognition of intestinal epithelial
HIF-1α activation by Pseudomonas aeruginosa. Am. J. Physiol. Gastrointest. Liver Physiol. 292:G134–42
83. Pearson JP, Feldman M, Iglewski BH, Prince A. 2000. Pseudomonas aeruginosa cell-to-cell signaling is
required for virulence in a model of acute pulmonary infection. Infect. Immun. 68:4331–34
84. Popat R, Crusz SA, Messina M, Williams P, West SA, Diggle SP. 2012. Quorum-sensing and cheating
in bacterial biofilms. Proc. R. Soc. B 279:4765–71
85. Queller DC, Goodnight KF. 1989. Estimating relatedness using genetic markers. Evolution 43:258–75
86. Rasko DA, Sperandio V. 2010. Anti-virulence strategies to combat bacteria-mediated disease. Nat. Rev.
Drug Discov. 9:117–28
87. Redfield RJ. 2002. Is quorum sensing a side effect of diffusion sensing? Trends Microbiol. 10:365–70
88. Ross-Gillespie A, Gardner A, West SA, Griffin AS. 2007. Frequency dependence and cooperation: theory
and a test with bacteria. Am. Nat. 170:331–42
89. Rumbaugh KP, Diggle SP, Watters CM, Ross-Gillespie A, Griffin AS, West SA. 2009. Quorum
sensing and the social evolution of bacterial virulence. Curr. Biol. 19:341–45
90. Rumbaugh KP, Griswold JA, Hamood AN. 2000. The role of quorum sensing in the in vivo virulence
of Pseudomonas aeruginosa. Microbes Infect. 2:1721–31
91. Rumbaugh KP, Griswold JA, Iglewski BH, Hamood AN. 1999. Contribution of quorum sensing to the
virulence of Pseudomonas aeruginosa in burn wound infections. Infect. Immun. 67:5854–62
92. Rumbaugh KP, Trivedi U, Watters C, Burton-Chellew MN, Diggle SP, West SA. 2012. Kin selection,
quorum sensing and virulence in pathogenic bacteria. Proc. R. Soc. B 279:3584–88
93. Salunkhe P, Smart CHM, Morgan JAW, Panagea S, Walshaw MJ, et al. 2005. A cystic fibrosis epidemic
strain of Pseudomonas aeruginosa displays enhanced virulence and antimicrobial resistance. J. Bacteriol.
187:4908–20
94. Sandoz KM, Mitzimberg SM, Schuster M. 2007. Social cheating in Pseudomonas aeruginosa
quorum sensing. Proc. Natl. Acad. Sci. USA 104:15876–81
95. Schaber JA, Carty NL, McDonald NA, Graham ED, Cheluvappa R, et al. 2004. Analysis of quorum
sensing-deficient clinical isolates of Pseudomonas aeruginosa. J. Med. Microbiol. 53:841–53
96. Schuster M, Greenberg EP. 2006. A network of networks: quorum-sensing gene regulation in
Pseudomonas aeruginosa. Int. J. Med. Microbiol. 296:73–81
97. Schuster M, Lostroh CP, Ogi T, Greenberg EP. 2003. Identification, timing, and signal specificity of
Pseudomonas aeruginosa quorum-controlled genes: a transcriptome analysis. J. Bacteriol. 185:2066–79
98. Shompole S, Henon KT, Liou LE, Dziewanowska K, Bohach GA, Bayles KW. 2003. Biphasic intracellular expression of Staphylococcus aureus virulence factors and evidence for Agr-mediated diffusion sensing.
Mol. Microbiol. 49:919–27
99. Shopsin B, Drlica-Wagner A, Mathema B, Adhikari RP, Kreiswirth BN, Novick RP. 2008. Prevalence
of agr dysfunction among colonizing Staphylococcus aureus strains. J. Infect. Dis. 198:1171–74
100. Shopsin B, Eaton C, Wasserman GA, Mathema B, Adhikari RP, et al. 2010. Mutations in agr do not
persist in natural populations of methicillin-resistant Staphylococcus aureus. J. Infect. Dis. 202:1593–99
101. Silby MW, Winstanley C, Godfrey SAC, Levy SB, Jackson RW. 2011. Pseudomonas genomes: diverse
and adaptable. FEMS Microbiol. Rev. 35:652–80
102. Smith EE, Buckley DG, Wu Z, Saenphimmachak C, Hoffman LR, et al. 2006. Genetic adaptation by
Pseudomonas aeruginosa to the airways of cystic fibrosis patients. Proc. Natl. Acad. Sci. USA 103:8487–92
103. Smith KM, Bu Y, Suga H. 2003. Induction and inhibition of Pseudomonas aeruginosa quorum sensing by
synthetic autoinducer analogs. Chem. Biol. 10:81–89
104. Smith RS, Harris SG, Phipps R, Iglewski B. 2002. The Pseudomonas aeruginosa quorum-sensing molecule
N-(3-oxododecanoyl)homoserine lactone contributes to virulence and induces inflammation in vivo.
J. Bacteriol. 184:1132–39
Schuster et al.
MI67CH03-Greenberg
ARI
4 May 2013
14:58
105. Sokurenko EV, Tchesnokova V, Yeung AT, Oleykowski CA, Trintchina E, et al. 2001. Detection of
simple mutations and polymorphisms in large genomic regions. Nucleic Acids Res. 29:e111
106. Stintzi A, Evans K, Meyer JM, Poole K. 1998. Quorum-sensing and siderophore biosynthesis in
Pseudomonas aeruginosa: lasR/lasI mutants exhibit reduced pyoverdine biosynthesis. FEMS Microbiol. Lett.
166:341–45
107. Tingpej P, Smith L, Rose B, Zhu H, Conibear T, et al. 2007. Phenotypic characterization of clonal
and nonclonal Pseudomonas aeruginosa strains isolated from lungs of adults with cystic fibrosis. J. Clin.
Microbiol. 45:1697–704
108. Tomasz A. 1965. Control of the competent state in Pneumococcus by a hormone-like cell product: an
example for a new type of regulatory mechanism in bacteria. Nature 208:155–59
109. Traber KE, Lee E, Benson S, Corrigan R, Cantera M, et al. 2008. agr function in clinical Staphylococcus
aureus isolates. Microbiology 154:2265–74
110. Travisano M, Velicer GJ. 2004. Strategies of microbial cheater control. Trends Microbiol. 12:72–78
111. van Delden C, Comte R, Bally AM. 2001. Stringent response activates quorum sensing and modulates
cell density-dependent gene expression in Pseudomonas aeruginosa. J. Bacteriol. 183:5376–84
112. van Delden C, Pesci EC, Pearson JP, Iglewski BH. 1998. Starvation selection restores elastase and
rhamnolipid production in a Pseudomonas aeruginosa quorum-sensing mutant. Infect. Immun. 66:4499–
502
113. von Bodman SB, Bauer WD, Coplin DL. 2003. Quorum sensing in plant-pathogenic bacteria. Annu.
Rev. Phytopathol. 41:455–82
114. Wagner VE, Bushnell D, Passador L, Brooks AI, Iglewski BH. 2003. Microarray analysis of Pseudomonas
aeruginosa quorum-sensing regulons: effects of growth phase and environment. J. Bacteriol. 185:2080–95
115. West SA, Griffin AS, Gardner A. 2007. Evolutionary explanations for cooperation. Curr. Biol. 17:R661–
72
116. West SA, Griffin AS, Gardner A, Diggle SP. 2006. Social evolution theory for microorganisms.
Nat. Rev. Microbiol. 4:597–607
117. West SA, Winzer K, Gardner A, Diggle SP. 2012. Quorum sensing and the confusion about diffusion.
Trends Microbiol. 20:586–94
118. Whitehead NA, Barnard AM, Slater H, Simpson NJ, Salmond GP. 2001. Quorum-sensing in gramnegative bacteria. FEMS Microbiol. Rev. 25:365–404
119. Wilder CN, Allada G, Schuster M. 2009. Instantaneous within-patient diversity of Pseudomonas aeruginosa
quorum-sensing populations from cystic fibrosis lung infections. Infect. Immun. 77:5631–39
120. Wilder CN, Diggle SP, Schuster M. 2011. Cooperation and cheating in Pseudomonas aeruginosa: the roles
of the las, rhl, and pqs quorum-sensing systems. ISME J. 5:1332–43
121. Williams P, Camara M. 2009. Quorum sensing and environmental adaptation in Pseudomonas aeruginosa:
a tale of regulatory networks and multifunctional signal molecules. Curr. Opin. Microbiol. 12:182–91
122. Wu H, Song Z, Givskov M, Doring G, Worlitzsch D, et al. 2001. Pseudomonas aeruginosa mutations in
lasI and rhlI quorum sensing systems result in milder chronic lung infection. Microbiology 147:1105–13
123. Wu H, Song Z, Hentzer M, Andersen JB, Molin S, et al. 2004. Synthetic furanones inhibit quorumsensing and enhance bacterial clearance in Pseudomonas aeruginosa lung infection in mice. J. Antimicrob.
Chemother. 53:1054–61
124. Xavier JB, Foster KR. 2007. Cooperation and conflict in microbial biofilms. Proc. Natl. Acad. Sci. USA
104:876–81
125. Xavier JB, Kim W, Foster KR. 2011. A molecular mechanism that stabilizes cooperative secretions in Pseudomonas aeruginosa. Mol. Microbiol. 79:166–79
126. Zhu H, Bandara R, Conibear TCR, Thuruthyil SJ, Rice SA, et al. 2004. Pseudomonas aeruginosa with LasI
quorum-sensing deficiency during corneal infection. Investig. Ophthalmol. Visual Sci. 45:1897–903
127. Zhu H, Thuruthyil SJ, Willcox MDP. 2002. Determination of quorum-sensing signal molecules and
virulence factors of Pseudomonas aeruginosa isolates from contact lens-induced microbial keratitis. J. Med.
Microbiol. 51:1063–70
128. Zhu J, Beaber JW, Moré MI, Fuqua C, Eberhard A, Winans SC. 1998. Analogs of the autoinducer 3-oxooctanoyl-homoserine lactone strongly inhibit activity of the TraR protein of
Agrobacterium tumefaciens. J. Bacteriol. 180:5398–405
www.annualreviews.org • Acyl-Homoserine Lactone Quorum Sensing
125. Cooperative
secretions are
evolutionarily stabile if
prudently regulated to
minimize fitness costs.
63