Antagonistic interactions between hosts and pathogens frequently result in arms races.
The host attempts to recognise the pathogen and inhibit its growth and spread, whereas
the pathogen tries to subvert recognition and suppress host responses. These antagonistic
interactions drive the evolution of ‘decoys’ in both hosts and pathogens. In host–pathogen
interactions, the term decoy describes molecules that mimic a component at the host–pathogen
interface that is manipulated during infection. Decoys undergo the same manipulation
as the component they mimic, but they serve the opposite role, either by preventing
manipulation of the component they mimic or by triggering a molecular recognition
event. At least three different types of decoy have been defined, described in detail
below. However, these different decoy models cause confusion on how they function
mechanistically. Here, we discuss the three different types of decoys with examples
and classify them according to two distinct mechanisms.
Receptor decoys: Mimics to absorb ligands
Some pathogens use ‘Receptor decoys’ to interfere with host immune signalling (Fig
1A). Examples of Receptor decoys are found in large DNA viruses. Some viruses have
acquired a diverse set of Receptor decoys through recombination events with the host
[1]. These Receptor decoys typically encode for viral versions of receptor homologs
of the host and bind chemokines or cytokines to prevent efficient immune signalling
in the host. For example, ectromelia virus (causative of mouse pox) encodes the Type
1-interferon binding protein (T1-IFNbp), a Receptor decoy that is essential for its
virulence [2]. T1-IFNbp mimics the interferon receptor and attaches to uninfected
cells close to the infection site in liver and spleen. By binding T1-IFN, T1-IFNbp
facilitates virus spread and impairs defence signalling [3]. Therefore, this virus-derived
Receptor decoy absorbs T1-IFN, a key signal in host immune signalling.
10.1371/journal.ppat.1006761.g001
Fig 1
Three types of decoys act through two distinct mechanisms.
Examples of Receptor (A), Bodyguard (B), and Sensing (C) decoys that act through either
Sponge (D) or Bait (E) mechanisms. Avr2, Avirulence gene-2; avrPto, avirulence gene
of Pseudomonas syringae pv. tomato; avrPtoB, avirulence gene B of Pseudomonas syringae
pv. tomato; CEACAM, epithelial Carcino-embryonic Antigen-related Adhesion Molecules;
CERK1, Chitin Elicitor Receptor Kinase-1; Cf-2, Cladosporium fulvum resistance gene-2;
ECP6, extracellular Protein-6; GIP1, Glucanase Inhibitor Protein-1; NLR, Nod-like
Receptor; OPA, opacity-associated membrane proteins; Pip1, Phytophthora-inhibited
protease-1; PopP2, Pseudomonas outer protein P2; Prf, Pseudomonas resistance and fenthion
sensitivity; Pto, Resistance to Pseudomonas syringae pv. tomato; Rcr3, Required for
Cladosporium resistance-3; RLK, receptor-like kinase; RRS1, Resistance to Ralstonia
solanacearum-1; T1-IFNbp, Type-1 interferon binding protein; TALE, Transcription Activator-like
Effector; WRKY, Transcription factor with WRKY motif; XEG1, xyloglucan-specific endoglucanase-1;
XLP1, XEG1-like protein-1.
A similar example of a pathogen-derived Receptor decoy is extracellular Protein-6
(Ecp6), a Lysin Motif (LysM)-containing effector that is secreted by the fungal pathogen
Cladosporium fulvum during infection of tomato plants. Ecp6 suppresses chitin recognition
and is therefore instrumental for C. fulvum virulence [4]. Chitin is an essential
component of fungal cell walls, and many plants can sense fungal chitin through LysM-containing
receptors such as Chitin Elicitor Receptor Kinase-1 (CERK1) and its homologs. Interestingly,
Ecp6 captures chitin oligomers with high affinity and is thought to outcompete the
LysM-based host immune receptor for chitin binding [5]. Therefore, Ecp6 mimics the
chitin-binding capacity of the receptor and acts as a Receptor decoy by binding chitin
to prevent recognition by the host. Interestingly, LysM-based effectors are widespread
amongst fungal plant pathogens, so chitin absorption by LysM effectors appears to
be a commonly used decoy strategy [6].
Bodyguard decoys: Protecting secreted virulence factors
Some pathogens employ ‘Bodyguard decoys’ to protect virulence factors [7]. Bodyguard
decoys are inactive mimics of secreted virulence factors. They accompany these virulence
factors and efficiently bind host-derived defence proteins that aim to suppress these
virulence factors (Fig 1B). For instance, soybean secretes inhibitor GmGIP1 that strongly
inhibits the xyloglucan-specific endoglucanase PsXEG1 of the soybean oomycete pathogen
Phytophthora sojae [8]. PsXEG1 is an important virulence factor that probably acts
on the host cell wall during infection. P. sojae, however, protects PsXEG1 by cosecreting
the Bodyguard decoy PsXLP1, a truncated paralog of PsXEG1 with no known enzymatic
activity [8]. PsXLP1 has a higher binding affinity for GmGIP1 and acts as a Bodyguard
decoy by outcompeting the inhibition of PsXEG1.
A similar Bodyguard decoy concept has been proposed for truncated versions of Transcription
Activator-like Effectors (TALEs) that are secreted by the bacterial plant pathogen
Xanthomonas [7]. TALEs trans-activate host genes in the plant cell nucleus to facilitate
bacterial infection and therefore have a major role in virulence. Some host plants
carry Nod-like Receptor (NLR) proteins that confer recognition of TALEs and trigger
immune responses. Remarkably, a recently discovered class of truncated TALEs named
‘iTALEs’ [9] or ‘truncTALEs’ [10] with N- and C-terminal deletions can suppress TALE
recognition by these NLRs, possibly by binding the NLR without activating it. Therefore,
these truncated TALEs may act as a Bodyguard decoy to prevent NLR activation through
full-length TALEs that act as virulence factors.
Sensing decoys: Mimics of effector targets acting as coreceptors
The decoy concept has also been frequently used to explain the indirect recognition
mechanisms through products of disease resistance genes in plants [11]. The usual
interpretation is that these resistance genes monitor the modification of a decoy
that mimics the target of a pathogen-derived effector. These ‘Sensing decoys’ act
as coreceptors with resistance gene products (Fig 1C).
A classic example of a Sensing decoy is the tomato resistance gene product Pto. Pto
is a serine/threonine (Ser/Thr) kinase that confers resistance to strains of the bacterial
pathogen Pseudomonas syringae secreting the Type-III effectors AvrPto and AvrPtoB
[12,13]. AvrPto and AvrPtoB target receptor-like kinases (RLKs) involved in immune
signalling by inhibiting or ubiquitinating them, respectively. Pto mimics these RLKs
and confers recognition of AvrPto and AvrPtoB together with its binding partner Pseudomonas
resistance and fenthion sensitivity (Prf), an NLR that triggers immune signalling.
PBS1 is a similar Sensing decoy in the model plant Arabidopsis thaliana [14]. As with
Pto, PBS1 is a Ser/Thr kinase that detects AvrPphB, a Type-III effector of P. syringae.
AvrPphB is a cysteine protease that cleaves the kinase domain of immune-related RLKs.
PBS1 is a Sensing decoy that mimics the target of AvrPphB and confers recognition
of this effector by activating its binding partner Resistance to Pseudomonas syringae-5
(RPS5), an NLR that triggers immune signalling [14].
It was recently discovered that many plant NLRs may carry a Sensing decoy within themselves.
For instance, the NLR Resistance to Ralstonia solanacearum-1 (RRS1) from A. thaliana
carries like a WRKY-DNA–binding domain [15], and the NLRs RGA5 and Pik-1 in rice contain
a heavy metal–associated (HMA) domain related to ATX1 (RATX1) [16,17]. These domains
seem to mimic targets of effectors and enable pathogen detection. Therefore, they
were named ‘Integrated decoys’ [18]. However, given that the specific biochemical
activities of the ancestral effector targets and their NLR-integrated counterparts
are generally unknown, they could be sensor domains retaining their biochemical activity
as an extraneous domain within a classic NLR architecture [19].
Not all Sensing decoys associate with NLRs. A classic example comes from a study of
the Cladosporium fulvum resistance gene-2 (Cf-2) resistance gene of tomato, which
encodes a transmembrane receptor-like protein. Cf-2 confers recognition of the avirulence
2 (Avr2) effector secreted by the fungal tomato pathogen C. fulvum. Avr2 contributes
to virulence by inhibiting Phytophthora-inhibited protease-1 (Pip1) and other extracellular
papain-like Cys proteases of tomato. Cf-2 perceives Avr2 through its coreceptor Required
for Cladosporium resistance-3 (Rcr3), a paralog of Pip1, which acts as a Sensing decoy
to confer Avr2 recognition [20].
Likewise, human epithelial carcinoembryonic antigen-related adhesion molecules 3 (CEACAM3)
can be considered to be a Sensing decoy that acts during gonorrhoea infection. To
facilitate close attachment to epithelial cells in the human urogenital tract, the
bacterial pathogen Neisseria gonorrhoeae expresses opacity-associated (Opa) membrane
proteins [21]. Opas interact with a different human CEACAM, and this Opa–CEACAM interaction
triggers bacterial engulfment and transcytosis and thereby facilitates infection [22].
However, some Opas also bind to the decoy CEACAM3, and this Opa–CEACAM3 interaction
triggers efficient phagocytosis of the bacteria and recruitment and downstream activation
of the neutrophils’ antimicrobial responses, including degranulation and oxidative
burst [23]. Therefore, CEACAM3 acts as a Sensing decoy that allows the capture and
killing of CEACAM-targeting microbes.
The concept of Sensing decoy can be extended beyond proteins. TALEs such as AvrBs3
from X. campestris and AvrHah1 from X. gardneri reprogram the host by binding and
activating promoters of upa (up-regulated by AvrBs3) and other genes in the host [24,25].
The promotor of the pepper resistance gene Bs3 (pBs3) mimics the targets of these
TALEs and transcriptionally activates the Bs3 gene product, leading to a localised
cell death response that stops further pathogen growth. Therefore, pBs3 acts as a
nonprotein Sensing decoy to trick AvrBs3 and AvrHah1 into a recognition event [25,26].
Two decoy mechanisms: Sponge and bait
The above examples of Receptor, Bodyguard, and Sensing decoys illustrate that the
decoy concept is discussed frequently in host–pathogen interactions. This, however,
causes confusion in the field because not all these decoys are mechanistically the
same.
Receptor decoys are expected to have a higher affinity and/or abundance when compared
to the receptor they mimic, to prevent the ligands from reaching the receptors and
inducing immune signalling. Likewise, Bodyguard decoys must have a higher affinity
and/or abundance when compared to the acting virulence factor to prevent the virulence
factor from being inactivated or recognised. Therefore, both Receptor and Bodyguard
decoys act as a sponge to absorb (Fig 1D). The ligand or virulence factor, respectively,
is ‘trapped’ because it cannot reach its operative target as it is captured by the
Sponge mechanism.
In contrast, all Sensing decoys act like a bait. These baits are not necessarily preventing
the interaction of the effector with its operative target. The response to recognition
can simply overrule the benefits of the effector manipulating its operative target.
Therefore, in the Bait mechanism, the effector is ‘tricked’ by the Sensing decoy that
prompts a recognition event (Fig 1E). Indeed, there is no evidence that Sensing decoys
like Pto, PBS1, HMA, Rcr3, CEACAM3, and pBs3 prevent the interaction of the sensed
effector with its operative target.
Further thoughts
Sponge and Bait mechanisms occur frequently at the host–pathogen interface. By its
definition, decoys are thought to have no additional role, e.g., in development, disease
or resistance. Hypothetically, however, because of their crucial role, decoys can
become an attractive target for manipulation and can evolve into a target. In addition,
also outside of that specific host–pathogen interaction, decoys may play a role. Therefore,
it is important to use decoy terminology when the decoy acts in conjunction with the
component they mimic.
Interestingly, the presented examples indicate a trend: all Sponge mechanisms that
we define here are pathogen derived, while Bait mechanisms are host derived. There
is, however, no reason to exclude the existence of host-derived Sponge mechanisms.
For instance, the absorbance of pathogen-derived toxins to prevent them from reaching
their target in the host is likely to occur. Bait mechanisms may only be host-derived
because invading pathogens are more likely to sense the host in a direct way, not
least because receptors that recognize the host are also under selection pressure
and coevolve with the host. Because some pathogenic organisms may become a host themselves,
it is conceivable that they may also have decoys that act as a bait.
While both types of decoy mechanisms have been described in the literature, much remains
to be discovered. The discovery of more decoy examples will help us to find novel
drug targets as well as new possibilities to improve host immunity. The latter is
illustrated by a broader resistance spectrum upon decoy engineering of PBS1 in Arabidopsis
plants [27].