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Acyl-Homoserine Lactone Quorum Sensing: From Evolution to

Application

Article in Annual review of microbiology · May 2013

DOI: 10.1146/annurev-micro-092412-155635 · Source: PubMed

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MI67CH03-Greenberg ARI 5 August 2013 13:51

Acyl-Homoserine LactoneQuorum Sensing: FromEvolution to ApplicationMartin Schuster,1 D. Joseph Sexton,1

Stephen P. Diggle,2 and E. Peter Greenberg3

1Department of Microbiology, Oregon State University, Corvallis, Oregon 97331;email: [email protected], [email protected] of Life Sciences, University of Nottingham, Nottingham NG7 2RD, United Kingdom;email: [email protected] of Microbiology, University of Washington, Seattle, Washington 98195;email: [email protected]

Annu. Rev. Microbiol. 2013. 67:43–63

First published online as a Review in Advance onMay 15, 2013

The Annual Review of Microbiology is online atmicro.annualreviews.org

This article’s doi:10.1146/annurev-micro-092412-155635

Copyright c© 2013 by Annual Reviews.All rights reserved

Keywords

Pseudomonas, cooperation, cheating, public good, QS inhibition

Abstract

Quorum sensing (QS) is a widespread process in bacteria that employsautoinducing chemical signals to coordinate diverse, often cooperativeactivities such as bioluminescence, biofilm formation, and exoenzymesecretion. Signaling via acyl-homoserine lactones is the paradigm for QSin Proteobacteria and is particularly well understood in the opportunisticpathogen Pseudomonas aeruginosa. Despite thirty years of mechanisticresearch, empirical studies have only recently addressed the benefits ofQS and provided support for the traditional assumptions regarding itssocial nature and its role in optimizing cell-density-dependent groupbehaviors. QS-controlled public-goods production has served to investigateprinciples that explain the evolution and stability of cooperation, includingkin selection, pleiotropic constraints, and metabolic prudence. Withrespect to medical application, appreciating social dynamics is pertinentto understanding the efficacy of QS-inhibiting drugs and the evolution ofresistance. Future work will provide additional insight into the foundationalassumptions of QS and relate laboratory discoveries to natural ecosystems.

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Quorum sensing(QS): a mechanism ofchemical cell-cellcommunication thatpermits coordinationof gene expression as afunction of the localpopulation density

Cooperation: abehavior that benefitsanother individual (therecipient) and ismaintained (at leastpartially) because of itsbeneficial effect on therecipient

Contents

INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44MODEL SYSTEMS AND COMMON THEMES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

The Vibrio fischeri Paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45Pseudomonas aeruginosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46Common Themes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

EVOLUTIONARY CONSIDERATIONS OF QUORUM SENSING . . . . . . . . . . . . . 48Foundational Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48Sociality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48Social Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50Density Dependence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51QS-Independent Cooperation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

QUORUM SENSING AS AN ANTIVIRULENCE DRUG TARGET:SOCIAL INTERACTIONS AND RESISTANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53The Potential of Antivirulence Drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53QS-Inhibiting Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54How Likely Is the Evolution of Resistance? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54QSI Resistance and the Quorum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

INTRODUCTION

Although bacteria were long thought to be individual cells acting alone, we now accept that theyare 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 thecontext 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 abilityof bacteria to communicate with one another by using chemical signals. Bacterial communicationcan coordinate a wide range of activities in different bacterial species as a function of populationdensity (118). This type of communication is called quorum sensing (QS) (33). At least in somecases it is clear that QS controls social behaviors (24, 94, 120).

If one strives to understand bacteria, and the wide variety of ecological and environmentalniches they occupy, social aspects of their biology cannot be ignored. Although the field of so-ciomicrobiology is very young, we see two reasons why it is critical to study QS and the controlof social activities in bacteria. (a) Bacteria have become powerful tools with which to study funda-mental questions about the costs and benefits of cooperation, the selective pressures that lead tothe evolution and maintenance of cooperative traits, and the advantages of controlling coopera-tive behaviors by cell-cell communication systems such as QS. With fast growth rates and ease ofgenetic manipulations, evolutionary questions that cannot possibly be addressed with higher or-ganisms can be addressed with bacteria. (b) The central role QS plays in regulating many relevantmicrobial behaviors has not gone unnoticed. There is currently high interest in manipulating QSsystems for diverse human applications such as ecological control in agriculture and antivirulencein medicine (4, 54, 77, 78).

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OO

O

N

C4-HSL

3OC6-HSL

3OC12-HSL

pC-HSL

H

OO

OO

NH

OO

OO

NH

OO

O

NH

HO

Figure 1Some examples of AHL quorum-sensing signals. The structures and corresponding names are shown. ThePseudomonas aeruginosa signal synthase RhlI produces C4-HSL and LasI produces 3OC12-HSL. The Vibriofischeri signal synthase LuxI produces 3OC6-HSL, and the Rhodopseudomonas palustris signal synthase RpaIproduces 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-dodecanoyl-homoserine lactone; 3OC6-HSL, 3-oxo-hexanoyl-homoserine lactone; pC-HSL,para-coumaroyl-homoserine lactone.

AHL:acyl-homoserinelactone

MODEL SYSTEMS AND COMMON THEMES

The Vibrio fischeri Paradigm

In the late 1960s and early 1970s, there was a very modest literature describing pheromoneproduction and activity in bacteria (26, 108). It was not until the early 1980s that work on generegulation in marine luminescent bacteria led to some understanding of how an intercellularcommunication system could coordinate group activities. Only in the 1990s did we begin tounderstand the prevalence of QS in bacteria. Now we know there are many different types ofbacterial QS systems. Our review focuses on acyl-homoserine lactone (AHL) QS systems, whichare prevalent but not universal among the Proteobacteria and for which the term QS was firstintroduced (33). Generally, AHL signals are synthesized by LuxI family enzymes and detected byLuxR family signal receptor–transcriptional regulators. There are related but chemically distinctsignals that are specific to particular systems (Figure 1).

AHL signaling was first discovered in the marine bacterium Vibrio fischeri, which uses QS tocontrol a small set of approximately 25 genes, including genes for light production, by LuxR and3-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 itcolonizes the light organs and produces light. Like other AHLs, 3OC6-HSL moves in and out of

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luxR

LuxR

ACTIVE

Lux regulon

qscR

QscR

QscRregulon

lasI

LasI

AHL

rhII

RhII

AHL

luxI

a b

LuxI

AHL

lasR

LasR

LasR

LasRregulon

rhIR

RhIR

RhIR

RhlRregulon

Figure 2AHL signaling in (a) Vibrio fischeri and (b) Pseudomonas aeruginosa. AHL signals are made by members of theLuxI family of signal synthases and specifically interact with LuxR family transcription factors. At high celldensity, AHLs accumulate and interact with LuxR homologs. AHL binding controls activity of LuxR familymembers. (a) In V. fischeri, LuxI and LuxR produce and respond to 3OC6-HSL, respectively. (b) InP. aeruginosa, the LasIR system produces and responds to 3OC12-HSL, and the RhlR system produces andresponds to C4-HSL. QscR is an orphan LuxR receptor that is not linked to a luxI synthase gene. QscRresponds to 3OC12-HSL produced by LasI. Each quorum-sensing regulon is shown as a distinct entity, butin 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 reflectionof cell density and the diffusion potential of the habitat. This QS system allows V. fischeri todiscriminate between its free-living, low-density lifestyle in seawater and its high-density, host-associated lifestyle in animal light organs. The luxI gene itself is controlled by QS; it is activated by3OC6-HSL-bound LuxR (28). This positive autoregulation provides hysteresis to the system. Thepopulation density required to activate quorum-controlled genes is much higher than the densityrequired to shut down an activated system. Furthermore, once the system is induced, it wouldrequire 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 asa cooperative activity. Single cells do not emit enough light for biological detection, but thelight produced by groups of cells can easily be seen with the naked eye. This is in fact the basisfor isolation of luminous marine bacteria. One can plate bacteria from a source enriched forluminous bacteria on a seawater-based medium and isolate colonies producing blue light in a darkroom. The ease with which luminescence can be observed and measured has facilitated the use ofV. fischeri as a model for understanding QS.

Pseudomonas aeruginosa

In addition to V. fischeri, the gammaproteobacterium Pseudomonas aeruginosa has also emergedas an important model organism for QS research. Equipped with a large genome, P. aeruginosa

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CF: cystic fibrosis

Regulon: thecollection of genescontrolled by anindividualtranscription factor

EPS: extracellularpolysaccharide

is metabolically versatile and capable of occupying a range of different habitats (101). It is also anopportunistic pathogen capable of infecting different host species, including plants, insects, andmammals (69). Immunocompromised humans, including those with burn wounds or the geneticdisorder cystic fibrosis (CF), are particularly vulnerable to infection with P. aeruginosa (69). Therelative ease with which P. aeruginosa can be handled in the laboratory, along with its medicalrelevance, has led to an extensive body of work that includes a detailed picture of the complexP. aeruginosa QS network. There are two complete AHL circuits, LasR-LasI and RhlR-RhlI; eachis composed of a LuxR-type receptor and a LuxI-type synthase (96, 121) (Figure 2b). LasI produces3-oxo-dodecanoyl-homoserine lactone (3OC12-HSL), and RhlI produces butanoyl-homoserinelactone (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 codingfor production of extracellular products such as exoenzymes and phenazine pigments are grosslyoverrepresented in the quorum-controlled regulon (36, 96). Many such extracellular products areconsidered virulence factors because they damage host tissue and promote infection. The impor-tance of P. aeruginosa QS for establishing acute and chronic infections has been demonstrated inseveral animal models (83, 91, 122). In addition to the LasRI and RhlRI systems, there is a 3OC12-HSL-responsive orphan receptor, QscR, which controls its own set of genes and also repressesmany LasRI- and RhlRI-dependent genes (65, 66). Another layer of complexity is added by thePseudomonas quinolone signal (PQS) system, which is intertwined with the AHL signaling circuitry(44).

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 mostcommon types are toxins (e.g., virulence factors and antimicrobials), exoenzymes (e.g., proteases),and biofilm components (e.g., extracellular polysaccharides, EPS). Such activities are interestingbecause they may represent forms of cooperation. For example, biofilms consist of heteroge-neous bacterial groups that organize on surfaces (14). Bacteria in biofilms secrete EPS and otherbiofilm matrix components that surround and protect the group, but this may be a wasteful pro-cess for an isolated individual. The common thread of cooperation suggests the evolutionaryforces shaping AHL-mediated QS in P. aeruginosa may also be pertinent to phylogenetically dis-tinct 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 usesAHL QS to regulate conjugal transfer of the Ti plasmid. The QS system itself requires activa-tion by small molecules produced only by infected plants (113). Thus, a sufficient A. tumefaciensdensity is required and the bacteria must be in the plant host. Another example is the regula-tion of QS gene expression by starvation in P. aeruginosa. The stringent response, the hallmarkresponse to slow growth in bacteria, can trigger increased signal synthesis and thus lower thequorum 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, althoughthis review discusses the foundational and common evolutionary forces of QS systems, extrap-olating these principles to other systems requires consideration of mechanistic and ecologicalpeculiarities.


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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, andbetween prokaryotes and eukaryotes. Indeed, it is common in the literature to define any molecule produced by oneindividual that elicits a response in another to be a signal. Broad use of the term signal can be misleading, and thiscan obscure the true nature of the biological interaction between individuals. For example, QS molecules could alsoact 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 individualB and is effective because the response in individual B has also evolved. This is distinct from a cue, in which theproduction of substance X by individual A has not evolved because of its effect on individual B. Finally, a coercion orchemical manipulation is when the production of substance X by individual A forces a costly response from individualB. Here the production has evolved because of the benefit to the sender and not the receiver (73). This mattersbecause determining whether bacterial cells are interacting via signal, cue, or coercion allows us to make very differentpredictions as to how interactions within and between species evolve and are maintained in nature. Such distinctionswill become increasingly important as microbiologists begin to unravel the nature of multispecies interactions.

Public good: aresource that is costlyto produce andprovides a benefit toall the individuals inthe local group orpopulation

EVOLUTIONARY CONSIDERATIONS OF QUORUM SENSING

Foundational Assumptions

A large volume of literature describes QS at the molecular level, and this has unraveled the geneticmechanisms and pathways of QS systems. The molecular focus of this work has led to generalassumptions about QS upon which the entire research field is based, namely that QS is a socialtrait performed by individual cells for the good of the group, and that QS is most beneficial at highcell densities. Not until recently has empirical work directly tested these ideas (described in detailbelow). A third assumption that QS represents signaling between individuals is briefly touchedupon in the sidebar, What Makes a Quorum-Sensing Signal a Signal?, and has been discussed indetail elsewhere (23).

Sociality

In 2002, Redfield (87) challenged the notion that QS is social. She pointed out that the need forgroup action or the selective conditions required for its evolution had not been experimentallydemonstrated (87). Redfield argued that the chief function of autoinducer signal molecules is toenable an individual cell to sense how rapidly secreted molecules diffuse away into the surroundingenvironment. By producing a metabolically inexpensive molecule such as an AHL, individual cellscould first use this to assess the diffusive properties of their environment to determine whether itwas beneficial to produce a more costly public good such as an extracellular protease. This ideawas termed diffusion sensing (DS) and suggests QS need not be a social behavior but rather anonsocial trait, which matters to an individual cell whether or not it is in a group (87). We notethat DS and QS are not mutually exclusive. The efficiency sensing hypothesis made an attempt toformally 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 issocial? Answering this question requires an experimental approach. It is key to determine whetherbenefits are shared with other cells or enjoyed only by the producer. In microbes, extracellularproducts may indeed be available to other members of the group once secreted from the cell.If they are costly for the individual but provide a benefit to the group, they can be classified as

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Cheat: an individualwho does notcooperate (orcooperates less thanhis fair share) but canpotentially gain thebenefit from otherscooperating; alsocalled freeloader

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 andcoordination of cooperative behaviors, and second, the actual, generally more costly cooperativebehaviors controlled by QS.

The first step in testing whether a microbial trait is social is to examine whether the relativecosts and benefits of the trait vary with the social environment. Specifically, if exofactors areshared socially between cells, then one would predict the following: (a) Populations of cells that doproduce the exofactors should grow better than populations that do not. (b) When grown in mixedpopulations, nonproducing mutants should be able to exploit producing cells (i.e., they should beable to cheat) and hence increase in frequency. With respect to QS, we can further predict thatsignal-blind (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 isimportant for growth in natural environments, then one would be able to isolate natural cheats. Ifthe benefit of exofactors flowed only to the cell that produced them and was not social, we wouldmake the first prediction but not the second or third. Understanding this will then allow us to beginto 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 shownthat QS-controlled public-goods production is both costly and exploitable by cheats. Using syn-thetic QS growth medium with a protein carbon source (casein or bovine serum albumin) that re-quires QS-dependent exoprotease secretion, researchers have demonstrated that wild-type popula-tions 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 theyexploit the exoprotease production of wild-type cells, displaying a trend of negative-frequency-dependent fitness (24, 120). Simply put, when there are fewer cheats in the population there aremore cooperators to exploit, resulting in an increased cheat fitness (88). Signal-blind but not signal-negative cheats emerge when wild-type P. aeruginosa is grown in QS medium over a number ofselection rounds (94). Signal-blind cheats invade cooperating populations to a greater extent whenthe cost of cooperation is increased by altering the nutritional composition of 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 resultis surprising as it contrasts with previous theory, which suggests that growth in structuredenvironments such as biofilms should lead to a segregation of cooperators and cheats, reducingthe ability of cheats to exploit cooperators (62, 124).

If QS is social, our third prediction suggests that social cheats should be present in real-worldmicrobial 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 otherenvironments (10, 20, 41, 52, 53, 93, 95, 99, 100, 102, 105, 109, 119, 126, 127). Empiricalevidence demonstrating why such QS mutants emerge during infection is sparse. One explanationfor their emergence in the CF lung is that they are better adapted to this unique environment andtherefore have a selective advantage. In support of this, it has been shown that lasR mutants havean intrinsic growth advantage on particular carbon and nitrogen sources that could contribute toselection in a CF lung environment (16). An alternative explanation is that lasR mutants behaveas 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 negative-frequency-dependent fitness (89). By comparing monocultures and mixed infections, the studyaddressed and confirmed the first and second predictions. This finding suggests that during in vivoinfections, QS cheats can exploit public goods and resources produced by a cooperating population


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Pleiotropicconstraint: preventsthe origination ofcheaters if themutation conferring acheater phenotype islinked to a cost ofcheating

Pleiotropy: thephenomenon of asingle gene, e.g., aglobal regulatory gene,affecting multipledistinct phenotypictraits

Private good: aresource that is costlyto produce andprovides a benefit onlyto the producer

Metabolic constraint:a specific case ofpleiotropy in whichQS control of bothpublic and privatenutrient acquisitionconstrains cheating

Metabolic prudence:mechanism thatstabilizes public-goodscooperation byinitiating theirproduction only whenthe fitness cost is low

in a manner similar to that seen in previous studies using planktonic cultures (89). Another studyhas demonstrated that during infections in human intubated patients, a mix of QS cooperatingcells and QS cheats resulted in a milder infection (59). The overall implication is that the spread ofcheats 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 begunto show that QS and at least some of the traits regulated by QS are social in nature. However, it isimportant that we do not automatically regard all QS-regulated traits as social. A key challenge forthe future is to determine which traits are social and which are nonsocial. Empirically doing so willrequire 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 ofQS must also be addressed. Explaining the stability of cooperative behaviors such as QS remainsone of the greatest problems for evolutionary biologists (115). Why would an individual carry outa cooperative behavior that is costly to perform and primarily benefits other individuals or thelocal group? Doing so threatens the stability of cooperative behaviors because it is vulnerable tocheats 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 itis termed the tragedy of the commons (42). The tragedy is that in a group, individuals would dobetter to cooperate, but this is not stable because each individual gains by selfishly pursuing itsown short-term interests (42). Yet cooperation clearly exists. In general, genes can be favored bynatural selection if they increase the reproductive success of their bearer (direct fitness) and alsoincrease the reproductive success of other related individuals that carry the same gene (indirectfitness) (39, 40). Strategies that stabilize cooperative behaviors can therefore be categorized onthe basis of whether the benefits are direct or indirect.

If there is a direct fitness benefit to the individual performing the behavior, cooperation canbe maintained by processes that enforce cooperation and limit the spread of cheats by removingthe advantage of cheating. This can involve mechanisms to repress cheating such as policing andsanctions (30, 110, 115). Empirical evidence demonstrating the existence of such processes inmicrobes is sparse; however, some recent studies highlight that they might be widespread. Onedescribed mechanism that may be pertinent to QS is pleiotropic constraint, in which behaviorswith high individual fitness benefits are coregulated with cooperative behaviors (17, 31). Adoptinga cheat strategy by mutation in a regulatory gene may therefore be accompanied by the loss ofanother important function. Pleiotropy may specifically contribute to the stability of the LasRIQS circuit in P. aeruginosa through the control of both public and private goods (17, 120). LasRcontrols 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 wild-type cells in QS medium with casein and adenosine as carbon sources, LasR cheats do not invadewhen adenosine is in excess because they do not receive the direct fitness benefit associated withadenosine utilization (17). This mechanism has been termed metabolic constraint (17). Pleiotropymay also contribute to the evolutionary stability of the rhl QS circuit. In casein medium that solelyfavors 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, imposesa 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.Costly biosurfactant production is required for swarming, and theory suggests that this should be

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Kin selection: aprocess by which traitsare favored because oftheir beneficial effectson the fitness ofrelatives

exploitable by cheats. However, metabolic prudence results in the inability of cheats to invade aswarm. Cooperators secrete QS-controlled biosurfactants only when the cost of production andthe impact on individual fitness are low. This regulation prevents nonsecretors from gaining anevolutionary advantage. On the mechanistic level, this is achieved through the coregulation ofbiosurfactant production by QS and nitrogen availability (21, 97). These carbon-rich polymersare only produced when active growth is limited or prevented by nitrogen starvation, and the costof production is low because carbon is not limiting.

A third property that affects the stability of public-goods cooperation is the durability of thegood itself. This has been shown for bacterial siderophores, iron-scavenging molecules that arenot only very stable but are also reused multiple times (63). Through facultative regulation, costlysiderophore 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 alsobe supported by indirect fitness benefits, or kin selection (39, 40). The most common reason fortwo individuals to share genes is for them to be genealogical relatives (kin), and so this process isoften termed kin selection, although it was originally called inclusive fitness (61). Kin selection isdiscussed in detail elsewhere (34). Briefly, relatedness (r) is a measure of genetic similarity (85). Inmicroorganisms, 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 amutation are unrelated to the cooperators (r = 0) (22, 116). Kin selection is likely to be highlyimportant for behaviors such as QS because of clonal reproduction and relatively local interac-tions (116). Empirical tests of the kin selection hypothesis in culture and in an infection modelrevealed that QS is favored in conditions of high relatedness, whereas a lasR cheat is favored underconditions of low relatedness. This is because in high-relatedness conditions, the QS wild-typeor the lasR mutant grew in separate test tubes or mice, and the greater fitness of the wild-typeled to an increase in wild-type frequency, which resulted in maintenance of QS. In contrast, inlow-relatedness populations, composed of mixtures of cooperators and cheats, the cheats are ableto exploit cooperators and this does not favor QS (24, 92).

Density Dependence

In addition to questioning the sociality of QS, DS as a hypothesis is important because it challengesa second major assumption of QS, namely that density matters. The general consensus in theliterature 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 fromcells and have various uses, including nutrient scavenging for growth and toxin production forvirulence. This regulatory mechanism results in an increase in the production of QS-controlledfactors at high cell densities, which is generally further accelerated and stabilized by the positiveautoregulation of signal production. This important assumption implies that the QS circuitry itselfis a mechanism that optimizes cooperation by delaying expression of a social behavior until thecost balances the benefit.

Despite the huge amount of research on QS, there is very little work testing the idea that QSprovides a benefit at high density. It is therefore crucial to compare individual and populationbenefits of inducing QS at high and low densities (Figure 3). Two separate studies recently testedthe idea that QS provides the greatest benefit at high cell densities. The first study focused on theenzymatic breakdown of public goods in the external environment and showed that QS can providesocial benefits to other cells and that the fitness benefits of QS are greater at higher cell densities,when cells are better able to interact (18) (Figure 3a). Here the authors independently manipulated


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a b

Public good

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Figure 3Density, microenvironment, and the fitness benefits of producing (a) public and (b) private goods. Assumingconstitutive production, private goods, which are utilized within a cell, confer direct fitness benefits toindividuals, thus allowing growth at both low and high cell densities. In contrast, public goods confer bothdirect and indirect fitness benefits to individuals and neighboring cells, but their production is most efficientat high cell densities. Therefore, QS optimizes the costs and benefits of public goods by restricting publicgoods production to high densities (18, 80). Costs and benefits are equivalent from the perspective of a singlecell (81). As the microenvironment or external volume per cell decreases (depicted as a dark blue dashedcircle in the bottom images), the benefit from public goods production increases, whereas the benefit fromprivate goods production remains the same.

population density and the induction of and response to a QS signal in P. aeruginosa. Theyfound that the benefit of QS was greater at higher population densities because QS-dependentextracellular public goods were used more efficiently. The experimental design also consideredQS-controlled private goods, in this case adenosine metabolism, in which benefits are retainedby the individual and not shared with the population (Figure 3b). Here the benefits do notvary with cell density. The second, related study was conducted with a synthetic QS systemengineered in Escherichia coli, which controls the synthesis of a costly but beneficial exoenzymepublic good (80). By using this system, the authors demonstrated that exoenzyme productionis beneficial at high cell densities but that the optimal benefit only occurs if QS is initiated ata sufficiently high density. Overall, these results support the assumption that QS improves theefficiency of cooperative behaviors through activation at high density. An analogous scenario inwhich metabolically cheap QS invades and helps stabilize more costly cooperative behaviors wasmodeled by Czaran & Hoekstra (15).

Laboratory experiments on QS have traditionally been performed with high-volume planktonicbatch cultures, in which cells can reach very high numbers. These include the aforementionedstudies on the relationship between density and QS efficiency. There is an increasing body of workexamining QS at low population sizes or even at the single-cell level. For example, the confinementof individual P. aeruginosa cells in small volumes using microfluidic devices initiates high-densityQS target gene expression (7, 13), as does the confinement of individual Staphylococcus aureuscells inside the phagosome of eukaryotic cells (98). Similarly, the quorum size of Pseudomonassyringae is very small when grown in non-water-saturated environments such as plant leaves (25).

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PVD: pyoverdine

Ultrasensitive AHL QS circuits have also recently been described in two members of the genusBradyrhizobium, which respond to signal levels at orders of magnitude lower than that described formodel QS systems (68). Such examples refute the notion held by some that QS requires millionsof cells (7), although the original definition of QS never discounted the possibility that even asingle 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. Theapproach 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-levelphenotype (Figure 3).

QS-Independent Cooperation

Although the control of costly cooperative behaviors by QS is advantageous, the production ofsome public goods appears to be largely independent of QS. One such example is the productionof the siderophore pyoverdine (PVD) in P. aeruginosa. A QS-negative strain still produces PVDwith only an approximately twofold decrease under conditions of iron stringency (106). In con-trast, pathways that directly sense iron starvation activate PVD biosynthetic genes ten- to severalhundredfold (79). Why would PVD expression not be more strongly coregulated by QS? Insightsinto the molecular properties of PVD and mechanisms of regulation offer some clues. PVDs arestructurally distinct between different species and sometimes even between closely related strainsof 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. Thismechanism is referred to as kin discrimination, as it permits an individual to distinguish relativesfrom nonrelatives and preferentially direct aid toward relatives (39, 40). Importantly, the structuralspecificity of PVD is also exploited for signaling purposes. PVD expression is significantly aug-mented by the detection of PVD itself (64). Recognition of PVD, specifically Fe-bound PVD, byan outer membrane receptor initiates a transition from basal to high expression levels. In a fashionsomewhat analogous to QS, PVD acts as an autoinducer and perhaps independently achieves theprimary benefits QS has to offer. PVD differs from an AHL signal in that it is more costly to pro-duce and that it is not solely used for the purpose of signaling. The specificity in PVD reception isexploited in a way not possible with most other public goods and directly conveys information aboutthe utility of PVD production, namely the ability to chelate and deliver iron, as it is the Fe-boundform of PVD that is sensed (38). Therefore, further integration of PVD into a QS circuit seemsredundant, 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-independentproduction of a public good in an individual species, we note that specific public goods are notcontrolled identically in different species. Clearly, prevailing environmental conditions have alarge role in the evolution of regulatory networks. Unfortunately, these conditions remain largelyunknown, 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 infec-tious disease, but this achievement has been endangered by the emergence of antibiotic resistance.A promising new strategy is to target virulence (5, 11, 12, 86). Whereas conventional antibiotics


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QSI: quorum-sensinginhibitor

target in vitro viability, antivirulence drugs target functions required for infection, thereby essen-tially disarming the bacteria. It is thought that this tips the balance in favor of the host, allowingthe immune system to clear the infection. This approach potentially has several advantages, in-cluding exerting less selective pressure toward resistance, preserving the endogenous microflora,and of course expanding the repertoire of bacterial targets. In addition, antivirulence drugs couldbe 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 attractivetarget for antivirulence drugs, in particular small-molecule-mediated cell-cell communication.In principle, one could interfere with QS by inhibiting signal production, accelerating signaldegradation, or inhibiting signal reception (Figure 4a). Most of the work to date has focusedon inhibiting signal binding by QS receptors. A number of structural AHL analogs and othersmall molecules have been shown to inhibit the expression of QS-controlled genes and biofilmformation in P. aeruginosa (35, 78, 103). The halogenated furanones have been investigated ingreatest detail (6, 46) (Figure 4b). Administration of halogenated furanones promotes clearanceof P. aeruginosa from the lungs of infected mice (48, 123) and increases the survival time of micein 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). Workwith V. fischeri LuxR protein suggests that halogenated furanones exert their inhibitory effect byaccelerating receptor protein turnover (72). Analysis of LuxR mutants with substitutions at theAHL binding pocket indicates that halogenated furanones, in contrast to some signal analogs,inhibit in a nonagonist fashion (58). In P. aeruginosa, halogenated furanones inhibit productionof 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 usebecause of their high reactivity. Other potentially more promising compounds have recentlybeen identified (Figure 4b). One example is a structurally unrelated triphenyl mimic ofP. aeruginosa 3OC12-HSL that is a potent, specific LasR agonist (77) and serves as a scaffold forthe synthesis of more stable and less toxic QS inhibitors (QSIs). One antagonist that effectivelyinhibits 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 broadlyinhibits LasR-dependent gene expression (78). Neither TP-5 nor the phenyl compound has beentested in animal infection models.

How Likely Is the Evolution of Resistance?

Widespread bacterial resistance to virtually every clinically significant conventional antibiotichas 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 ofresistance to occur, namely mutability and selective pressure. Mutability is essentially already metby the natural mutation rate, permitting genetic change. In the case of QS, this is further augmentedby 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 tosynthetic antagonist N-(propylsulfanylacetyl)-L-homoserine lactone while only modestly reducing

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AHL

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Figure 4QS 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 small-molecule QSIs. (c) Social interactions and resistance evolution. Outcomes of two scenarios, QS inhibition ofcooperative and noncooperative behaviors, are shown. The cooperative behavior is extracellular degradationof a complex nutrient (e.g., casein) by a secreted enzyme. The noncooperative behavior is intracellulardegradation of a nutrient (e.g., adenosine) by a cell-associated enzyme. For clarity, details on nutrientutilization depicted in the top panels are omitted in the bottom images. Abbreviations: AHL,acyl-homoserine lactone; QS, quorum sensing; QSI, QS inhibitor.

sensitivity to activation by the natural signal, 3OC6-HSL (58). In addition, overexpression of theLuxR 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 disruptiondoes not affect bacterial growth in standard laboratory media, it has generally been assumed thatthere is no selective pressure for the evolution of resistance. However, the situation is significantlydifferent in vivo. Numerous animal infection studies have shown that P. aeruginosa QS is importantfor infection (67, 83, 91, 122). Reduced virulence is probably due to the decreased ability ofQS mutants to colonize and disseminate in a given host, and to the increased clearance of QSmutants by the host immune system. It is also possible that the AHL signals themselves act asimmunomodulators (90). In either case, our considerations thus far suggest that a strain resistantto QS inhibition would have a selective advantage over a sensitive strain during QSI treatment of


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an infection. As with opportunistic pathogens such as P. aeruginosa, the selective forces outside thehost are less clear, and there is mounting evidence that virulence factors are maintained, at leastin part, because of advantages in nonparasitic contexts (8).

Bacterial social interactions add another layer of complexity. Theoretical work suggests thatsocial conflict may prevent or at least slow the evolution of QSI resistance (1). Conceptually, asingle cell or a small subpopulation of cells harboring QSI resistance will initially exist within alarger population of cells sensitive to the QSI. Treatment with a QSI will lead to a tragedy of thecommons: The QSI-resistant cells will behave as cooperators capable of producing QS-controlledpublic goods. The QSI-sensitive majority, unable to produce these goods themselves, will benefitfrom this expenditure and effectively behave as cheats (Figure 4c). Given the growth advantagethat cheats generally enjoy over cooperators, QSI resistance should not evolve. This predictionwas experimentally tested in a lab microcosm with P. aeruginosa QSI-sensitive and QSI-resistantmimics, 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 solecarbon source to create environments where either QS-controlled public-goods production orQS-controlled private goods production was favored. Corroborating the theoretical work, QSIresistant 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 shareneither the good nor the benefit derived from it (Figure 4c). Of course, the use of mimics has itslimitations, as QSI resistance may also occur via QSI degradation, limited uptake, or increasedefflux, in addition to target modification.

These in vitro studies also neglect several other factors pertinent to an infection, such as spatialstructuring and selective pressures imposed by the host immune system. Nevertheless, results fromexperimental infection of mice with P. aeruginosa support the outcomes obtained from modelingQS-controlled public-goods cooperation. A mixed infection with wild-type and lasR mutant strainsresults in reduced virulence, compared with a wild-type-only infection (89). The two strains againact 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 themselveshave also been proposed as antivirulence therapeutics (9).

Although the evidence cited thus far suggests that QS-dependent cooperative behaviors rep-resent a viable antivirulence drug target, one study cautions that this approach may also bearcertain epidemiological risks. QSI treatment of a fully susceptible, QS-proficient P. aeruginosapopulation disfavors invasion by true QS-deficient cheats, thereby increasing the prevalence ofthe QS-proficient, virulent strain (60).

As mentioned above, QSI resistance is expected to evolve when QS controls a noncoopera-tive behavior, such as growth on adenosine as the sole carbon source. Wood and colleagues (70)provided evidence for this with an in vitro evolution experiment in which P. aeruginosa was cul-tured in adenosine medium containing a halogenated furanone as a QSI. They isolated partiallyQSI-resistant mutants that exhibited increased efflux of the furanone compound, imparted by aloss-of-function mutation in a repressor of the MexAB-OprM multidrug resistance efflux pump.Similar mutations are also found among clinical isolates (129). The ecological context of bacte-rial adenosine utilization is not entirely clear (49), although adenosine, in response to injury andinflammation, can reach high levels in certain host tissues (82). Bacterial consumption of this orother QS-dependent private nutrients in the natural environment is predicted to accelerate theevolution of QSI resistance.

Although the aforementioned studies have identified social conflict as a major constraintto the emergence of QSI resistance, in vitro evolution experiments have also shown that thisconstraint can be overcome under certain conditions. When P. aeruginosa lasR deletion mutants are

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starvation-selected in growth medium that requires las-dependent proteolysis, second-site mutantsemerge 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 alsofully virulent. If they were fully virulent because of compensation by the rhl system, then a potentQSI that targets both las and rhl QS would be needed clinically to avoid the rapid developmentof resistance through this mechanism. It seems obvious that more fundamental knowledge aboutgenetic 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 thequorum? Would QS-controlled traits in the presence of QSI be expressed at all? This complexquestion likely depends on a multitude of factors and relates to the fundamental issue of theinfective dose. The dynamics of colonization and killing, and the role of QS in active growth versuspreventing clearance by the immune system, is not well understood. If QS was strictly requiredfor growth in vivo, it is unlikely that a single or a few QSI-resistant bacteria would constitutea quorum to express QS-controlled factors. However, if there was some growth in vivo in thepresence of QSI, then a small cluster of QSI-resistant bacteria could possibly cross the quorumthreshold and produce QS products to acquire nutrients or fight the immune system, which inturn 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 bacteriain an acute pneumonia mouse model) (2, 104). This finding suggests that a quorum can be achievedwith a fairly small number of bacteria, presumably modulated by population structuring (limiteddiffusion) in the respective colonization site and by bacterial starvation, which can significantlylower the quorum threshold (111).

CONCLUSIONS

The past three decades have provided remarkable insight into the mechanisms of bacterial commu-nication and cooperation, but the evolutionary and ecological assumptions about these behaviorshave been empirically tested only in recent years. Here emphasis has shifted from merely con-firming general evolutionary theory with microbes to actually understanding the evolution ofmicrobial sociality in its own right. Various novel -omics tools in microbial ecology will furtheraccelerate discovery.

Research thus far strongly supports the notion that QS represents a social behavior and that itcan offer density-dependent fitness advantages. QS-controlled cooperation is favored through kinselection and specific mechanisms that help constrain cheating, including pleiotropy and metabolicprudence. More specifically, QS signaling optimizes other, more costly cooperative behaviors andthereby helps stabilize these behaviors. As QS circuits often control virulence factors, there is highinterest in interfering with QS. Preliminary evidence suggests that social interactions in bacterialpopulations can slow the evolution of resistance to QSIs.

SUMMARY POINTS

1. Microbial social interactions are now known to be both common and important.

2. A few key model systems in the Proteobacteria have been particularly useful in understand-ing the mechanisms and, more recently, the evolution of QS.


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3. Recent empirical work supports the traditional assumptions of QS, namely that QS is asocial 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 socialcheating in test tubes, biofilms, and infections and is consistent with the presence ofQS-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 whenthey are beneficial.

7. QSIs are appealing alternatives to traditional antibiotics. Theory and proof-of-conceptdata from a lab microcosm and an infection model suggest that social conflict reducesthe 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 naturalenvironment. What are the roles, costs, and benefits of QS in these environments, andwhat is the spatiotemporal structure of natural QS populations? Are the selective forcesthat shape social behaviors identical to those in lab microcosms?

2. Additional questions concern the nature and stability of the various social behaviors inbacteria. Which behaviors are social and why? Why are some behaviors controlled byQS, whereas others are not? What mechanisms help stabilize these behaviors, and specif-ically, what is the role of accessory mechanisms that coregulate QS and QS-controlledbehaviors?

3. Preliminary findings on the contribution of bacterial social interactions to the evolutionof resistance to QSIs and to other antivirulence drugs require further testing in structuredcommunities such as biofilms and in animal infection models.

DISCLOSURE STATEMENT

The authors are not aware of any affiliations, memberships, funding, or financial holdings thatmight 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.P.D.), and the National Institutes of Health (grants GM-59026 and P30DK 89507 to E.P.G.).

LITERATURE CITED

1. Andre J-B, Godelle B. 2005. Multicellular organization in bacteria as a target for drug therapy. Ecol. Lett.8:800–10

2. Allewelt M, Coleman FT, Grout M, Priebe GP, Pier GB. 2000. Acquisition of expression of thePseudomonas aeruginosa ExoU cytotoxin leads to increased bacterial virulence in a murine model of acutepneumonia and systemic spread. Infect. Immun. 68:3998–4004

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MI67-FrontMatter ARI 12 August 2013 12:26

Annual Review ofMicrobiology

Volume 67, 2013 Contents

Fifty Years Fused to LacJonathan Beckwith � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 1

3′ Cap-Independent Translation Enhancers of Plant VirusesAnne E. Simon and W. Allen Miller � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �21

Acyl-Homoserine Lactone Quorum Sensing: From Evolutionto ApplicationMartin Schuster, D. Joseph Sexton, Stephen P. Diggle, and E. Peter Greenberg � � � � � � � � �43

Mechanisms of Acid Resistance in Escherichia coliUsheer Kanjee and Walid A. Houry � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �65

The Biology of the PmrA/PmrB Two-Component System: The MajorRegulator of Lipopolysaccharide ModificationsH. Deborah Chen and Eduardo A. Groisman � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �83

Transcription Regulation at the Core: Similarities Among Bacterial,Archaeal, and Eukaryotic RNA PolymerasesKimberly B. Decker and Deborah M. Hinton � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 113

Bacterial Responses to Reactive Chlorine SpeciesMichael J. Gray, Wei-Yun Wholey, and Ursula Jakob � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 141

It Takes a Village: Ecological and Fitness Impactsof Multipartite MutualismElizabeth A. Hussa and Heidi Goodrich-Blair � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 161

Electrophysiology of BacteriaAnne H. Delcour � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 179

Microbial Contributions to Phosphorus Cycling in Eutrophic Lakesand WastewaterKatherine D. McMahon and Emily K. Read � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 199

Structure and Operation of Bacterial Tripartite PumpsPhilip Hinchliffe, Martyn F. Symmons, Colin Hughes, and Vassilis Koronakis � � � � � � � � � 221

Plasmodium Nesting: Remaking the Erythrocyte from the Inside OutJustin A. Boddey and Alan F. Cowman � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 243

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The Algal Past and Parasite Present of the ApicoplastGiel G. van Dooren and Boris Striepen � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 271

Hypoxia and Gene Expression in Eukaryotic MicrobesGeraldine Butler � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 291

Wall Teichoic Acids of Gram-Positive BacteriaStephanie Brown, John P. Santa Maria Jr., and Suzanne Walker � � � � � � � � � � � � � � � � � � � � � � 313

Archaeal Biofilms: The Great UnexploredAlvaro Orell, Sabrina Frols, and Sonja-Verena Albers � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 337

An Inquiry into the Molecular Basis of HSV Latency and ReactivationBernard Roizman and Richard J. Whitley � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 355

Molecular Bacteria-Fungi Interactions: Effects on Environment, Food,and MedicineKirstin Scherlach, Katharina Graupner, and Christian Hertweck � � � � � � � � � � � � � � � � � � � � � � � 375

Fusarium PathogenomicsLi-Jun Ma, David M. Geiser, Robert H. Proctor, Alejandro P. Rooney,

Kerry O’Donnell, Frances Trail, Donald M. Gardiner, John M. Manners,and Kemal Kazan � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 399

Biological Consequences and Advantages of AsymmetricBacterial GrowthDavid T. Kysela, Pamela J.B. Brown, Kerwyn Casey Huang, and Yves V. Brun � � � � � � � 417

Archaea in Biogeochemical CyclesPierre Offre, Anja Spang, and Christa Schleper � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 437

Experimental Approaches for Defining Functional Roles of Microbesin the Human GutGautam Dantas, Morten O.A. Sommer, Patrick H. Degnan,

and Andrew L. Goodman � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 459

Plant Cell Wall Deconstruction by Ascomycete FungiN. Louise Glass, Monika Schmoll, Jamie H.D. Cate, and Samuel Coradetti � � � � � � � � � � � � 477

Cnidarian-Microbe Interactions and the Origin of InnateImmunity in MetazoansThomas C.G. Bosch � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 499

On the Biological Success of VirusesBrian R. Wasik and Paul E. Turner � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 519

Prions and the Potential Transmissibility of ProteinMisfolding DiseasesAllison Kraus, Bradley R. Groveman, and Byron Caughey � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 543

Contents vii

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The Wonderful World of Archaeal VirusesDavid Prangishvili � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 565

Tip Growth in Filamentous Fungi: A Road Trip to the ApexMeritxell Riquelme � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 587

A Paradigm for Endosymbiotic Life: Cell Differentiation of RhizobiumBacteria Provoked by Host Plant FactorsEva Kondorosi, Peter Mergaert, and Attila Kereszt � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 611

Neutrophils Versus Staphylococcus aureus: A Biological Tug of WarAndras N. Spaan, Bas G.J. Surewaard, Reindert Nijland,

and Jos A.G. van Strijp � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 629

Index

Cumulative Index of Contributing Authors, Volumes 63–67 � � � � � � � � � � � � � � � � � � � � � � � � � � � 651

Errata

An online log of corrections to Annual Review of Microbiology articles may be found athttp://micro.annualreviews.org/

viii Contents

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ANNUAL REVIEWSIt’s about time. Your time. It’s time well spent.

Now Available from Annual Reviews:Annual Review of Virologyvirology.annualreviews.org • Volume 1 • September 2014

Editor: Lynn W. Enquist, Princeton UniversityThe Annual Review of Virology captures and communicates exciting advances in our understanding of viruses of animals, plants, bacteria, archaea, fungi, and protozoa. Reviews highlight new ideas and directions in basic virology, viral disease mechanisms, virus-host interactions, and cellular and immune responses to virus infection, and reinforce the position of viruses as uniquely powerful probes of cellular function.

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Graham F. Hatfull, Vincent Racaniello• Viruses and the Microbiota, Christopher M. Robinson, Julie K. Pfeiffer• Role of the Vector in Arbovirus Transmission, Michael J. Conway,

Tonya M. Colpitts, Erol Fikrig• Balance and Stealth: The Role of Noncoding RNAs in the Regulation

of Virus Gene Expression, Jennifer E. Cox, Christopher S. Sullivan• Thinking Outside the Triangle: Replication Fidelity of the Largest RNA

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of Acute Hepatitis, Zongdi Feng, Asuka Hirai-Yuki, Kevin L. McKnight, Stanley M. Lemon

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Discoveries in Virology, Todd M. Greco, Benjamin A. Diner, Ileana M. Cristea

• Viruses and the DNA Damage Response: Activation and Antagonism, Micah A. Luftig

Complimentary online access to the first volume will be available until September 2015.

ANNUAL REVIEWS | Connect With Our ExpertsTel: 800.523.8635 (us/can) | Tel: 650.493.4400 | Fax: 650.424.0910 | Email: [email protected]

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Editor: Stephen E. Fienberg, Carnegie Mellon UniversityAssociate Editors: Nancy Reid, University of Toronto

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Complimentary online access to the first volume will be available until January 2015. table of contents:•What Is Statistics? Stephen E. Fienberg•A Systematic Statistical Approach to Evaluating Evidence

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Access this and all other Annual Reviews journals via your institution at www.annualreviews.org.

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