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Multidimensionality in parasite-induced phenotypic alterations:
ultimate vs. proximate aspects
Frank Cézilly, Adrien Favrat and Marie-Jeanne Perrot-Minnot
Université de Bourgogne, Equipe Ecologie Evolutive, UMR CNRS 6282 Biogéosciences.
Running title: Multidimensionality in parasite-induced phenotypic alterations
Word count: 5898
In most cases, parasites alter more than one dimension in their host phenotype. Although
multidimensionality in parasite-induced phenotypic alterations (PIPA) seems to be the rule, it
has started to be addressed only recently. Here, we critically review some of the problems
associated with the definition, quantification and interpretation of multidimensionality in
PIPA. In particular, we confront ultimate and proximate accounts, and evaluate their own
limitations. We end up by introducing several suggestions for the development of future
research, including some practical guidelines for the quantitative analysis of
multidimensionality in PIPA.
Parasites can bring about various phenotypic alterations in their hosts that appear to increase
their own fitness at the expense of that of their hosts (Moore 2002, Thomas et al. 2005). In
particular, parasites with complex life cycles often modify the behaviour and or appearance of
their intermediate hosts, in ways that appear to increase trophic transmission to final hosts
(Moore 2002; but see Shirakashi and Goater 2005, Leung and Poulin 2006, Fermer et al.
2010). Such phenomena are regularly interpreted in relation to the concept of extended
phenotype introduced by Dawkins in his eponymous book. Thus, according to the ‘parasite
manipulation’ hypothesis, the ability of a parasite species to modify its host’s phenotype is the
product of natural selection acting on the genes of the parasite (Thomas et al. 2005; but see
Cézilly et al. 2010).
Early studies of the impact of parasites on the phenotype of their host typically
focused on one single phenotypic dimension at a time, such as modified behaviour (Bethel
and Holmes 1973), reduced fecundity (Skorping 1985), disrupted physiology (Rumpus &
Kennedy 1974), or altered appearance (Oetinger and Nickol 1981). Most often, however, a
single parasite species alters more than one phenotypic trait in its host. Recently, Cézilly and
Perrot (2005) coined the term "multidimensionality" to address this phenomenon.
Multidimensionality in parasite-induced phenotypic alterations (PIPA) is actually a
widespread, if not systematic, phenomenon, and stimulates a growing interest (Cézilly and
Perrot-Minnot 2005, 2010, Benesh et al. 2008, Thomas et al. 2010, 2012).
Multidimensionality in PIPA if of interest in evolutionary biology, in direct relation to the
evolution of complex life cycles, and also in ecology, in connection with the complex role of
parasites in ecosystems (Thomas et al. 1997).
The 'adaptationist' view regards the multiple phenotypic alterations caused by
parasites as effectively discrete, with each dimension that contributes to transmission being an
adaptation designed by natural selection (Thomas et al. 2010a, 2012). From a proximal point
of view, however, the various phenotypic alterations observed in infected hosts,
independently of their effect on trophic transmission, may find their origin in a single or a few
physiological processes, possibly linked to the crosstalk between the immune system and the
nervous system of the host (Adamo 2002, Cézilly & Perrot-Minnot 2010, Perrot-Minnot and
Cézilly 2012). Although the ultimate and proximate approaches to multidimensionality in
PIPA are not necessarily contradictory (Thomas et al. 2010b, 2012), their confrontation is
likely to improve our understanding of the evolution of host-parasite interactions.
In the present review, we first consider how multidimensionality manifests itself in
various host-parasite interactions, with a particular emphasis on one particular host-parasite
association for which several dimensions of the altered phenotype have been quantified.
Second, we present various adaptive explanations that can be put forward to account for
multidimensionality in PIPA, before discussing various kinds of limitations associated with
them. Third, we introduce a proximate perspective on multidimensionality in PIPA and argue
about its relevance to the question of adaptive manipulation of hosts by parasites. Finally, we
propose some directions for future research with the hope of promoting a more integrative
approach to PIPA.
Multidimensionality of phenotypic alterations in infected hosts
Infection with parasites generally induces the alteration of several phenotypic traits,
simultaneously or in succession. Simultaneous phenotypic alterations have been observed in a
large number of host-parasite associations, involving for instance crustacean and/or insect
intermediate hosts infected with acanthocephalans (Bakker et al. 1997, Fuller et al. 2003),
cestodes (Franceschi et al. 2007), or trematodes (Mc Curdy et al. 1999, Leung and Poulin
2006). However, the evidence for simultaneous multidimensionality in PIPA is most often
cumulative, as specific studies generally address only one or a few dimensions at a time. Still,
particular host-parasite interactions have received more attention than others, eventually
resulting through time in an impressive list of phenotypic alterations brought about by a single
parasite in a single host species. For instance, not less than 15 different phenotypic alterations
have been reported in the crustacean amphipod Gammarus pulex infected by the
acanthocephalan parasite Pomphorhynchus laevis (Table 1; see also Thomas et al. 2010a). It
is therefore likely that, in several cases, the number of PIPA known for a given host-parasite
association is more representative of the number of studies that addressed that association
than of the true number of phenotypic alterations induced by the parasite. This is problematic
to some extent, as it would make comparative studies based on literature surveys relatively
difficult to undertake. Still, it would be worth investigating at the interspecific level whether
some particular phenotypic alterations are co-occurring more often than by chance in infected
hosts, after controlling for the effect of phylogenetic inertia, and, eventually, if some
alterations preceded others historically (see Dubois et al. 1998, Pagel and Meade 2006).
There is, on the other hand, a risk that multidimensionality in PIPA is overestimated
when resulting from cumulative evidence collected from different populations of infected
hosts if the exact taxonomic of either the host or the parasite (or both) is not always correctly
established. For instance, Perrot-Minnot (2004) reported contrasted levels of altered reaction
to light induced by two closely-related, and previously confounded, species of
acanthocephalans in their common amphipod intermediate host. Symmetrically, the existence
of cryptic species in hosts (see Westram et al. 2011), eventually living in sympatry, may also
affect the assessment of multidimensionality in PIPA, since the effect of a parasite is known
to vary between closely-related species of intermediate hosts (Bauer et al. 2000, 2005, Tain et
al. 2007, Cornet et al. 2010). Ideally, then, such a study should be conducted in a single host-
parasite system, with the advantage of assessing whether all infected hosts express the same
combination of modified traits at the same intensity. However, the potentially large number of
PIPA in each host-parasite association might make such task a daunting one. Furthermore,
although hosts are often infected by several parasites, visual examination of hosts for the
presence of conspicuous macroparasites, such as acanthocephalans and cestodes, may
overlook the presence of more subtle parasites such as protists, rickettsia-like organisms and
microsporidian parasites (see Messick et al. 2004). However, there is evidence that such
parasitic organisms can affect the phenotype of their hosts and eventually interact with the
effects of macroparasites (Haine et al. 2005).
Sequential multidimensionality, the alteration of several phenotypic traits, in
succession, appears to occur more rarely, but is particularly interesting. It might be useful to
consider two types of sequential multidimensionality. In the cumulative sequential
multidimensionality, the various PIPA add to one another through time, such that the number
of altered dimensions in the host’s phenotype increases with time since infection. However,
the functional efficiency of one alteration does not appear to depend on the expression of
other alterations. For instance, in the amphipod G. insensibilis infected with the trematode
Microphallus papillorobustus, increased lipid content can be observed before the parasite
becomes infectious for its final host, at which stage the infected intermediate host also shows
altered reaction to light, negative geotaxis and aberrant escape behaviour (Ponton et al. 2005).
In the ordered sequential multidimensionality, the sequence of altered traits corresponds to
some kind of dormant fixed action pattern, organized as a fixed, stereotyped, temporal
sequence of behaviours, as suggested by Salwiczeck and Wickler (2009) in the case of
Formica ants infected by the trematode Dendrocelium dendriticum. According to Salwiczeck
and Wickler (2009), infected ants seek elevated places, crawling up twigs, and then use their
mandibles to fasten themselves, moving upward in the evening and downward in the morning.
Doing so, they actually exhibit a phylogenetically old sleeping behaviour, usually observed on
non-social hymenoptera (Wickler 1976). Another example of dependent sequential
multidimensionality is provided by the work of Eberhard (2010) on the effect of the
ichneumonid wasp Polysphincta gufreundi on the web-building behaviour of its host, the orb-
weaving spider Allocyctosa bifurca. When infected by a larva of the parasitic wasp, the spider
modifies its web-builidng behaviour in a gradual manner, with several distinct steps occurring
in a consistent sequence. Interestingly, if the larva is experimentally removed, the spider
returns progressively to a normal web-building behaviour following the reverse order
(Eberhard 2010).
Adaptive explanations for multidimensionality in PIPA
Why should a parasite alter several dimensions in its host’s phenotype? One answer is that
some PIPA evolved in consequence of their direct benefits for the parasite’s fitness (at the
expense of that of its host), whereas some others might simply be pathological by-products of
infection (Thomas et al. 2010a, 2012). If this is true, how inducing multiple phenotypic
alterations in its host might benefit a parasite? Practically, as is often the case in behavioural
ecology, the answer to that question is essentially limited by one’s ability to build adaptive
scenarios.
A first possibility is simply that two is better than one, three better than two, etc.
Intermediate hosts most often rely on various sensory modalities, such as vision, olfaction and
sound and vibration detection to locate and avoid predators (Tikkanen et al. 1994, Wudkevich
et al., 1997, Abjörnsson et al., 2000, Popper et al. 2001). Modifying more than one sensory
modality may then increase the vulnerability of infected intermediate hosts to predation by
final hosts. Accordingly, Bakker et al. (1997) claimed that both modified appearance and
altered reaction to light in G. pulex infected with P. laevis act synergistically to increase
trophic transmission to fish final hosts (but see below).
In addition, the efficiency of a phenotypic alteration in enhancing trophic transmission
may vary according to local conditions. For instance, increasing the conspicuousness of the
intermediate host by modifying its visual appearance might be of little consequence in
environments with reduced light, such as, for instance, turbid waters. Similarly, modifying the
drift behaviour of aquatic intermediate hosts may have different consequences depending on
current velocity. Parasites with complex life cycles may thus benefit from altering several
dimensions in the phenotype of their hosts because multidimensionality ensures increased
trophic transmission in a large range of environments.
In that respect, the number of dimensions which are altered should represent some
optimal value, determined by the balance between the accrued benefits from
multidimensionality and its costs. Alternatively, a trade-off may exist between the number of
traits that are altered in the host and the efficiency with which each trait is altered. If this is
true, one would expect a lower variation between infected hosts in the intensity of each
alteration when only one or a few traits are altered, and a larger one when a large number of
traits are modified. To date, however, no empirical study, to our knowledge, has addressed the
question. One difficulty, though, might be to determine how many traits are actually modified
by one parasite in its host.
Multidimensionality might also be related to the range of definitive hosts that are
available to a parasite. For instance, P. laevis can use a very large range of fish species as
intermediate hosts, including Alburnus baliki (Aydogdu et al. 2011), Barbus barbus
(Djikanovic et al. 2010, Dezfuli et al. 2011), Capoeta antalyensis (Aydogdu et al. 2011),
Chondrostoma nasus (Jirsa et al. 2011), Leuciscus cephalus, Leuciscus souffia, Perca
fluviatilis (Perrot-Minnot, unpub. data) Neogobius melnostomus (Francova et al. 2011),
Phoxinus phoxinus (Dudinak and Spakulova 2003), Silurus glanis (Dezfuli et al. 2011)). This
large diversity of final hosts includes species feeding nocturnally or diurnally, as well as
being ambush or cruising predators. Altering more than one dimension in host phenotypes
may then expose it to larger range of definitive hosts, and, hence, speed up trophic
transmission. The idea may eventually be tested by comparing the extent of
multidimensionality in manipulation between parasites with trophic transmission differing in
their specificity for final hosts. However, multidimensionality might be beneficial even if the
parasite relies on a limited number of species as appropriate final hosts, when, for instance,
the behaviour of the latter shows some variation in predatory behaviour related to age (Graeb
2006, Takeuchi 2009).
A last possibility is that whereas some phenotypic alterations evolved as adaptations to
enhance trophic transmission to appropriate final hosts, some others actually evolved as
adaptations to decrease the vulnerability of hosts to predation by non-host species (Médoc &
Beisel 2011; but see below).
Limits to the adaptationist approach
Thomas et al. (2010a,b) suggested that the term “multidimensionality” should be restricted to
PIPA that directly contributes to completion of the parasite’s life cycle at the expense of its
host’s fitness. Considering PIPA as adaptations comes however with three major problems
that have been partly overlooked and, thus, need addressing. A first one in directly linked to
the limitations of the adaptationist program as first emphasize by Stephen Jay Gould and
Richard Lewontin in the famous “spandrels” paper (Gould and Lewontin 1979). A second
one, of practical concern, is linked to the very possibility of demonstrating a causal
relationship between increased probability of life-cycle completion and a single PIPA. The
third and last one is directly related to reductionism, the definition of what constitutes a
phenotypic trait and the existence of genes ‘for’ phenotypes (Kaplan and Pigliucci 2001).
In its more extreme version, the adaptationist program is “an attempt to explain the
existence and the particular forms of any phenotypic trait as the results of natural selection”
(Pigliucci and Kaplan 2000, Forber 2009). When applied to multidimensionality in PIPA, the
adaptationist view is not so extreme, but rather considers that some traits are “true”
adaptations”, while others are should be regarded as mere pathological consequences of
infection (Thomas et al. 2010a). Still the distinction between the two types of traits is not
straightforward, as the most ardent defenders of the “host-manipulation” hypothesis tend to
consider that « if pathology is linked to transmission, then it is highly likely that natural
selection has not been blind to that pathology» (Thomas et al. 2005).
The confusion here circles around the distinction between three types of traits
(Thomas et al. 2005). The first one corresponds to traits which are coincidental with infection
but do not seem to play any part in increased transmission (or completion of the life cycle).
The second kind of traits, are traits which are coincidental with infection, appear to contribute
to transmission, but do not appear to have been specially designed to that aim. A general
decrease in stamina in infected hosts fits perfectly this category. Traits belonging to the third
kind are coincidental with infection, appear to contribute to transmission, and are suggestive
of “purposive design” (sensu Poulin 1995). Precisely, the limits of the adaptationist stance lie
in the possibility to infer the selective forces that historically shaped one trait from its
apparent current utility (Gould and Lewontin 1979, Pigliucci and Kaplan 2000).
Showing that a given PIPA contributes effectively to enhance transmission is no proof
that the set of genes that presently confer to the parasite the ability to induce such an alteration
has evolved at any time in relation to this advantage. A more moderate claim consists in
resorting to the concept of “exaptation” (Gould and Vrba 1982), as suggested by Combes
(2005) and Beisel and Médoc (2010). Broadly speaking, an exaptation refers to a shift in
function during the evolution of a trait (Gould and Vrba 1982). According to Beisel and
Médoc (2010), the tendency of amhipods infected with the bird acanthocephalan
Polymorphus minutus to show reverse geotaxis compared to uninfected individuals is an
example of exaptation as it would find its origin in the benefit accruing from avoiding
predation by non-hosts species (“historical genesis”), before favouring trophic transmission to
avian definitive hosts (“current utility”). However, this is only shifting the problem, not
solving it, as the avoidance of predation by non-hosts is another “just-so story”, particularly as
specificity in transmission does not appear to have much influence on the evolution of PIPA
(Cézilly et al. 2010). A more parsimonious view might be that reversed geotaxis first
appeared as a by-product of the infection at the time the ancestors of P. minutus had a simple
life cycle, thus increasing predation by aquatic birds, and hence favouring their later inclusion
as a second and definitive host in the life cycle of the parasite (Cézilly et al. 2010).
As emphasized by Poulin (1995), one point of crucial importance to evaluate the
current utility of PIPA is to show that it directly contributes to enhance completion of the life
cycle. Such evidence is however lacking for most PIPA that have been qualified as
“manipulative” (Cézilly et al. 2010). It is indeed a far cry between showing that the presence
of a phenotypic alteration coincides with, for instance, increased predation by final hosts and
providing evidence for a causal relationship between the two phenomenons, as a mere
correlation can be firm evidence for causality. We will argue that relying on an apparent
logical relationship between the design of an alteration and its potential consequences (or
“purposive design”) is not a reliable criteria, and can even be misleading. For instance, Lagrue
et al. (2006) observed that differences in genetic drift between P. laevis-infected and
uninfected G. pulex was in itself sufficient to account for selective predation by bullheads,
Cottus gobio, under field conditions. Indeed the difference in proportions between infected
and uninfected individuals in the stomach contents of bullheads did not differ significantly
from that that was measured in the drift. This suggests that others PIPA known in the same
host-parasite association and that “logically” appear to enhance trophic transmission, such s
reversed reaction to light (Cézilly et al. 2000) and reversed reaction to olfactory cues from
fish predators (Kaldonski et al. 2008; see also Perrot-Minnot et al. 2007), assessed under lab
conditions, may not play much role in trophic transmission under natural ones. Actually,
recent experimental evidence (Perrot-Minnot et al. submitted) indicates that reversed reaction
to light is no causally linked to increased vulnerability to fish predation in P. laevis-infected
G. pulex. Clearly, evidence for a causative link between enhanced transmission and PIPA,
beyond any logical guess, is badly needed in most systems in which parasitic “manipulation”
has been advocated. The need is even more obvious in the case of multidimensionality if, as
recommended by Thomas et al. (2010) we must restrict the use of that term to PIPA that
effectively contribute to transmission. Let alone the problem of partitioning the variance in
increased transmission between several PIPA and their interactions (see below).
Ultimately, the adaptationist view on PIPA critically depends on the validity of the
concept of “extended phenotype” (Dawkins 1982), according to which particular alleles or
combinations of alleles have been selected in parasites during the course of evolution in direct
consequence of their effect on the ability of “manipulative” parasite to induce particular
phenotypic alteration in their hosts. However, the existence of genes “for” particular abilities
is not always straightforward (Kaplan and Pigliucci 2001) and requires some evidence that the
trait is causally linked to the gene and that the prevalence of the gene in the population results
from a process of natural selection. Arguably, we know very little, if anything, on parasite
genes involved in “manipulation” in any of the major host-parasite systems studied so far.
Worse, standard QTL methods of investigation of the relationship between genes and
phenotype (Lange and Whittaker 2001, Guo and Nelson 2008) might be of limited use in the
framework of the study of PIPA, if only for the difficulty of obtaining measures of the ability
to induce PIPA in two consecutive generations of parasites. Similarly, the use of gene
knockout or knock-down methods might be of limited value if the pleiotropy of mutations
(which is more relevant to evolutionary change) rather than that of the gene is involved in
multidimensionality (see Wagner and Zhang 2011).
Besides, deciding which altered traits are adaptive and which ones are not is
contingent on the definition of what a “trait” is. A phenotypic trait is generally regarded as
the final product of several processes taking place at the molecular and biochemical levels.
But what makes a phenotypic character en entity in itself is not a trivial question (Wagner &
Zhang 2011). Imagine for instance that in a species of amphipod, individuals infected by a
given fish acanthocephalan shows both reduced photophobia and decreased use of refuges
compared to uninfected one, with the intensities of the two behaviours being highly correlated
(Fig 1a). Imagine further that the use of refuge is shown not to be a direct consequence of
altered photophobia, based on the evidence that uninfected amphipods make a more intense
use of translucid refuges than infected ones (thus implying a role for thigmotactism in refuge
use). Such an evidence for multidimensionality could be countered on mathematical grounds
by the possibility of defining a new coordinate system in which one dimension would be
defined as the summation of the two behaviours. Rotating the axis (Fig. 1b) leads to an
equally correct representation of the phenotypic space (see Wagner and Zhang 2011), thus
questioning the measurement of multidimensionality. Although a behavioural ecologist may
see the two behaviours considered separately as more natural dimensions of the phenotype,
there is no firm ground on which to prefer one representation of the phenotypic space to the
other.
As emphasized by Cézilly et al. (2010), however, hosts traits are not under selection to
enhance trophic transmission, only the ability of parasites to alter them in that way is
supposed to be. Therefore, one essential question, largely unanswered, is at which stage in its
development is a trait altered by a parasite. Two main possibilities exist and are relevant to
the question of adaptive multidimensionality. First, a parasite may directly regulate the
expression of some genes in its host, eventually regulating the production of various
neuromodulators that influence behaviour (Hoek et al. 1997). Such a mode of action may
eventually interact with the pleiotropic effects of such genes (see however Wagner and Zhang
2011) and contribute to the observed multidimensionality in PIPA. However, several traits
that are known to be modified by parasites in their hosts are likely to be polygenic.
Controlling such polygenic traits in a way that ensures fine-tuned manipulation of the host
phenotype may require an ability to control the regulation of several genes simultaneously.
Alternatively, the parasite may secrete compounds that disrupt or interfere with the
physiology of its host. Such compounds may be then specific enough to alter a single trait in
the host. Indentifying the mechanisms behind PIPA is therefore of paramount importance to
understand multidimensionality.
A proximate view on multidimensionality in PIPA
Very little is known at present on the mechanisms underlying PIPA, and even less so about
the mechanisms underlying multidimensionality. Identifying such mechanisms is however
essential to evaluate if the various dimensions with are altered are independent of each other
or are actually related at the proximate level. For instance, in proposing to include exclusively
PIPA with obvious consequences for transmission under the umbrella of multidimensionality,
Thomas et al. (2010a) exclude one conspicuous alteration which is commonly observed in
hosts infected with parasites with complex life-cycles, i.e. partial or total castration (Bollache
et al. 2001, 2002). The problem here is not to decide whether castration, though forcing the
host to reallocate resources to growth and maintenance, and thus contributing directly to the
development of the parasite, should be considered as enhancing completion of the life cycle
or not. It consists in estimating what are the chances that the physiological mechanisms that
lie behind castration are in one way or another functionally linked to other PIPA, such as, for
instance, behavioural alterations that appear to contribute to enhance transmission.
Cézilly and Perrot-Minnot (2010) proposed that infection with parasites could result in
a series of symptoms organized as an “infection syndrome”, and which are all the
consequences of some major dysregulation in the host’s physiology. The latter phenomenon
could arise as a consequence of the subversion of the host’s immune system by the parasite,
given the existence of a cross-talk between the immune and the nervous system in both
vertebrates and invertebrates (see Adamo 2002, Scharsack et al. 2007). Indeed, it has been
shown in various host-parasite systems (see Perrot-Minnot and Cézilly 2012) that infection
can affect various neuromodulators, such as, for instance, serotonin (5-HT). For instance, an
increase in brain 5-HT immunoreactivity has been observed in amphipods infected with fish
acanthocephalans (Tain et al. 2006, 2007) and injection with 5-HT mimics the reversed
photophobia observed in amphipods naturally infected with fish acanthocephalans.
Interestingly, infection with fish acanthocephalans induces partial castration in female
amphipods, whereas 5-HT is known to affect ovarian development in crustaceans (Makkapan
et al. 2011). Furthermore, 5-HT also controls the release of the crustacean hyperglycemic
hormone (Escamilla-Chimal et al., 2002, Sathyanandam et al., 2008), and, correspondingly,
altered levels of glycogen have been observed in amphipods infected with acanthocephalans
(Plaistow et al. 2001). Obviously, such observations may just reflect the polyvalence of
biogenic amines in the regulation of the physiology of host species. Still, they suggest that the
investigation of multiple consequences of the alteration of the regulation of some key
neuromodulator may shed some light on multidimensionality in PIPA (see Perrot-Minnot and
Cézilly 2012).
A further possibility is that multidimensionality in PIPA is related, in one way or
another, to the existence of behavioural syndromes. Behavioural syndromes correspond to a
suite of correlated behaviours expressed either within a given behavioural context or across
different contexts and are supposed to reflect differences in so-called personality between
individuals (Sih et al. 2004, David et al. 2011). The existence of behavioural syndromes has
now been evidence in large range of species including both vertebrates and invertebrates,
including taxonomic groups that serve as intermediate hosts to “manipulative” parasites
(Briffa et al. 2008, Lihoreau et al. 2008, Dzieweczynski, and Crovo 2011, Hojesjo et al.
2011). According to Barber and Dingemanse (2010), behaviours which are altered following
infection with “manipulative” parasites often correspond to major personality axes in
behavioural studies. Indeed, considerations about animal personality have often revolved
around the shy-bold continuum, of particular relevance to inter-individual variation in anti-
predator behaviour (Pellegrini et al. 2010, Jones and Godin 2010). Parallel to this, several
studies have shown that hosts infected with parasites with complex life-cycles often show
marked alterations of their anti-predatory behaviour (Libersat & Moore 2000, Perrot-Minnot
et al. 2007, Kaldonski et al. 2008). Barber and Dingemanse (2010; see also Kortet et al. 2010)
further suggest that infection with parasites with complex life cycles could “decouple”
normally correlated behaviours which evolved in hosts as adaptations to local environments,
and that such a decoupling effect would be positively selected through its effect on the
vulnerability of infected hosts to predation. Similarly, Poulin (2010) considered that
behavioural syndromes could be the targets of manipulation by parasites. However, the
precise mechanisms by which such a decoupling effect can work are still elusive.
Alternatively, individuals with different coping styles and, hence, different behavioural
syndromes may show different susceptibility to infection by parasites (see Blanchet et al.
2009), resulting in apparent multidimensionality in PIPA, although this latter hypothesis is
less likey.
Some suggestions for future research
So far, to our knowledge, only a few studies (Cornet et al. 2008, Benesh et al. 2009, Coats et
al 2010) have examined multidimensionality in PIPA. Such studies have essentially
investigated co-variation between a few PIPA, under the assumption that positive correlations
would provide evidence for the existence of a mechanistic link between various dimensions.
Benesh et al. (2009), for instance, quantified five different traits in isopods infected with
acanthocephalans: hiding, activity, substrate colour preference, body coloration and
abdominal colour. Although infected individuals were darker and hid less than uninfected
individuals, no relationship was found between the two traits among infected individuals.
However, as emphasized by Cézilly and Perrot-Minnot (2010), the absence of correlation
between two PIPA does not necessarily demonstrate their functional independence. Indeed,
the two PIPA might be regulated by the same neuromodulator, but with different dose-
dependent effects.
Future studies of multidimensionality in PIPA would certainly benefit from adopting a
common methodology. This would be particularly useful when attempting to make
comparisons between studies. We therefore propose here some simple recommendations for
the measurement and analysis of PIPA, with the hope that they will help researchers to obtain
reliable and comparable quantitative measures of the phenomenon.
As indicated before, assessing the total number of phenotypic dimensions altered by
one parasite in its host, whether at the individual, population, or species level, might be out of
reach. Therefore, providing a number of phenotypic dimensions which are altered by a given
parasite in its hosts makes little sense because it clearly depends on the number of traits that
have been investigated in a study. Assessing multidimensionality from the percentage of
phenotypic characters which are altered by infection among all characters that have been
studied might be preferable, as it would be more comparable between studies. Still, in most
cases, a researcher will consider that a dimension is not altered if the difference between
uninfected and infected individuals is not significant at some arbitrary chosen alpha level.
Thus with only moderate sample size, traits which are only slightly altered by infection would
not be included in the calculation of multidimensionality. However, when a large number of
dimensions can be measured, even on a limited number of individuals, it might be more
relevant to consider multidimensionality as a measure of the distribution of effect sizes across
traits. It should then be possible to estimate the shape of the distribution of effect sizes of
infection on all measured traits. If this distribution is close to a normal one, then the standard
deviation of the effect size distribution could provide a rigorous measure of the level of
multidimensionality.
Researchers may also want to appreciate to what extent one alteration in one
dimension might be more intense than in another one, or compare the intensity of the same
alteration between two different host-parasite associations, or two different populations of the
same host-parasite association. However, the metric used to quantify phenotypic alterations
may largely vary between traits. For instance, developmental stability of infected hosts might
be measured from fluctuating asymmetry (Alibert et al. 2002), whereas photophobia might be
assessed from an index of time spent in a dark area versus a lighted one (Cézilly et al. 2000).
In addition, the baseline behaviour of uninfected individuals may differ between populations.
We therefore propose to use the following index, Ia, as a standardized value of alteration in a
given dimension d, with:
Ia (d) = [x _(d)i – x _(d)u] / IQR
where x _(d)i denotes the median value of dimension d in infected individuals, x _(d)u denotes
the median value of dimension d in uninfected individuals, and IQR is the interquartile range
of the distribution of d in uninfected individuals, equal to the difference between the upper
and lower quartiles (IQR = Q3 _ Q1).
We recommend the use of non-parametric estimators as, most often, the frequency
distributions of PIPA does not conform to a normal distribution. However, in the case where
measurements conform to the normal distribution, the same index can be computed as the
difference between the mean value for infected individuals and that for uninfected ones,
divided by the standard deviation for uninfected individuals.
One important line of investigation for the future is to provide direct rather than
correlational evidence that one phenotypic alteration effectively contributes to enhance
transmission. This can be achieved through combining refined experimental design with
phenotypic engineering. Furthermore, such experiments will allow one to estimate whether
the effects of altered traits on enhanced transmission are additive or interactive. If traits are
highly redundant, then their summation should explain better the increased vulnerability to
predation. If they are not, their summation should not improve the prediction of vulnerability
for a given predator but would eventually for a series of predators, under the assumption that
multidimensionality is adaptive (see above). On the other hand, multiplication would do better
if one poorly manipulated dimension is sufficient to decrease the overall effect on trophic
transmission. Analyzing the results experiments combining predation trials with phenotypic
engineering of both infected and uninfected hosts (Bakker et al. 2007, Kaldonski et al. 2009,
Perrot-Minnot et al. submitted) using multiple regression techniques might provide interesting
insights in that respect.
Information is also missing on the genetic and physiological determinism of traits
which are altered by infection. Future research may then benefit from addressing the
mechanistic basis of traits in uninfected individuals, and also to attempt to establish whether
traits which are altered by infection are polygenic or not.
We would like to end this review with a friendly note of caution. Too much (naïve)
adaptationism may kill adaptationism. Although we do not deny that the study of host-paarsite
interactions benefits a great deal from an evolutionary approach, it might be time for
evolutionary parasitologists to reconsider the extended phenotype framework and include in
their reflexion modern views on the relationship between genes and phenotype (Pigliucci
2003, Dalziel et al. 2009, Wagner and Zhang 2011). In particular, a better integration of
proximate mechanisms with ecological aspects might be, in our opinion, a much more
valuable advance in our understanding of the evolution of PIPA that the endless formulation
of ad-hoc adaptive scenarios for which, most often, no critical test is available.
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Table 1. Multidmensionality in the phenotypic alteration induced by the acanthocephalan
Pomphorhynchus laevis in its amphipod intermediate host Gammarus pulex.
Phenotypic trait
Alteration (relative to
uninfected individuals)
Source
Response to olfactory predator
cues
Inversion
Baldauf et al. (2007),
Kaldonski et al. (2007)
Reaction to light
Inversion
Cézilly et al. (2000)
Activity
Augmentation
Dezfuli et al. (2003)
Drift
Augmentation
McCahon et al. (1991)
Lagrue et al. (2007)
Carbohydrate titres in
haemolymph
Augmentation
Bentley and Hurd (1996)
Pairing success
Diminution
Bollache et al. (2001, 2002)
Female fecundity
Diminution
Bollache et al. (2001, 2002)
Fluctuating asymmetry
Augmentation
Alibert et al. (2002)
Oxygen consumption
Diminution
Rumpus and Kennedy (1974)
Immunocompetence
Diminution
Rigaud and Moret (2003)
Cornet et al. (2009)
Brain serotonergic activity
Augmentation
Tain et al. (2006, 2007)
Appearance
Increased
conspicuousness
Bakker et al. (1997),
Kaldonski et al. (2009)
Glycogen level
Augmentation
Plaistow et al. (2001)
Total protein content of the
midgut gland
Diminution
Bentley & Hurd (1995)
midgut gland
Copper content of the midgut
gland
Diminution
Bentley & Hurd (1995)
Caption for figure
Figure 1. Multidimensionality depends on the definition of phenotypic traits. A. Bi-
dimensional effect of a parasitic infection affecting both photophobia and refuge use in a
correlated way (with both variables being standardized). B. This estimate of
multidimensionality is arbitrary because we can switch to another coordinate system in which
one dimension is defined as “PhotRef” which corresponds to the sum of the effect of infection
on each of the two behaviours. A rotation of the coordinate axis leads to an equally valid
representation of the phenotypic space. The dimensionality of the manipulation depends on
the coordinate system (adapted from Wagner and Zhang 2011).
Cézilly and Perrot-Minnot Figure 1
Photophobia
Refuge use
PhotRef
A B
