Does host receptivity or host exposure drives dynamics of infectious diseases? The case of West Nile Virus in wild birds.

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Does host receptivity or host exposure drives dynamics of infectious diseases? The case of West Nile Virus in wild birds Benjamin Roche a,b,d,⇑, Serge Morand c,e, Eric Elguero b, Thomas Balenghien f,g, Jean-François Guégan b,d, Nicolas Gaidet e a

UMMISCO (UMI 209 IRD-UPMC), Bondy, France UMR MIVEGEC (IRD 224-CNRS 5290-UM1-UM2), Montpellier, France UMR ISEM (CNRS/IRD/UM2), Montpellier, France d Laboratoire d’Excellence Centre d’Etude de la Biodiversité Amazonienne, Montpellier, France e UPR AGIRS (CIRAD ES), Montpellier, France f CIRAD, UMR CMAEE, F-34398 Montpellier, France g INRA, UMR1309 CMAEE, F-34398 Montpellier, France b c

a r t i c l e

i n f o

Article history: Received 7 January 2015 Received in revised form 28 March 2015 Accepted 10 April 2015 Available online xxxx Keywords: Multi-host pathogen Infection process West Nile Receptivity Ecological factors

a b s t r a c t Infection is a complex biological process involving reciprocally both the intensity of host exposure to a pathogen as well as the host intrinsic ‘‘receptivity’’, or permissiveness to infection. Disentangling their respective contributions is currently seen as a fundamental gap in our knowledge. Here, we take the advantage of a rare semi-natural experiment context provided by the emergence of the West Nile Virus (WNV) in North America. Focusing on the pathogen emergence period, we combine datasets from (i) wild birds exposed to WNV in an urban zoo to evaluate the species intrinsic receptivity to WNV infection in an environment where exposure to WNV vectors can be assumed to be relatively homogenous for all captive species, and (ii) from free-ranging birds in their natural habitat where species ecological traits is expected to influence their exposure to WNV vectors. We show that ecological trait and intrinsic receptivity to infection both contribute similarly to the species variation in WNV seroprevalence, but considering only one of them can lead to erroneous conclusions. We then argue that degree of pathogen host specialization could be a fundamental factor for the respective contribution of species exposure and receptivity for numerous pathogens. Ó 2015 Elsevier B.V. All rights reserved.

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1. Introduction

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Zoonotic infectious diseases represent a current threat for public health and biodiversity (Daszak et al., 2000; Jones et al., 2008), especially in the current context of agriculture intensification and biodiversity erosion (Jones et al., 2013). Despite representing 62% of emerging infections (Jones et al., 2008), understanding epidemiological patterns of these mostly multi-host diseases (Woolhouse and Gowtage-Sequeria, 2005) remains a great challenge for ecologist and public health authorities. One reason of our inability to improve our understanding is the quantification of the respective contribution of the two scales involved in

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⇑ Corresponding author at: UMI IRD/UPMC 209 UMMISCO, 32, Avenue Henri Varagnat, 93143 Bondy Cedex, France. E-mail addresses: [email protected] (B. Roche), serge.morand@ univ-montp2.fr (S. Morand), [email protected] (E. Elguero), [email protected] (T. Balenghien), [email protected] (J.-F. Guégan), nicolas.gaidet-drapier@ cirad.fr (N. Gaidet).

pathogen transmission, namely exposure and receptivity (Combes, 2002). The first level will determine the probability for a given potential host species to be exposed to the circulating pathogen (i.e., ‘‘pathogen exposure’’), which is linked with host ecology (in a broad sense including behavioral ecology) that could increase the contact rate between host or between hosts and disease-source vectors (Carver et al., 2009; Gaidet et al., 2012). The role of host ecology on pathogen transmission has been increasingly recognized during the last decades (Collinge and Ray, 2006), mainly through statistical analyses of empirical data aimed understanding which ecological variables may explain the level of pathogen infection in wild host species (e.g., Gaidet et al., 2012; Garamszegi and Moller, 2007). The second level concerns the ‘‘receptivity’’ of a host species that includes its permissiveness for infection it has been exposed to and the capacity to replicate and transmit the pathogen to another host. Relatedness between host species is a factor that

http://dx.doi.org/10.1016/j.meegid.2015.04.011 1567-1348/Ó 2015 Elsevier B.V. All rights reserved.

Please cite this article in press as: Roche, B., et al. Does host receptivity or host exposure drives dynamics of infectious diseases? The case of West Nile Virus in wild birds. Infect. Genet. Evol. (2015), http://dx.doi.org/10.1016/j.meegid.2015.04.011

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can potentially affect the capacity for a pathogen to infect and replicate in another host species since co-evolutionary process between host and pathogens may facilitate the infection in closely related host species (Longdon et al., 2011; Streicker et al., 2010). It thus can be assumed that the probability of successful transmission between host species may decline with increasing genetic distance between these species (Engelstadter et al., 2006). Despite recognized as an important scientific challenge a long time ago (Schrag and Wiener, 1995), attempts to disentangle the respective contribution of these exposure and receptivity on infectious disease transmission have been pretty rare (Garamszegi and Moller, 2007), especially for multi-host pathogens. Indeed, most of these studies suffer to focus only on empirical data from which the influences of receptivity and pathogen exposure are strongly raveled as well as shaped by another factors, especially the individual history of infection and the resulting acquired immunity that can modulate the host infectious response. Then, quantifying the respective contribution of exposure and receptivity is especially challenging on such empirical data (Plowright et al., 2008). Nevertheless, West Nile Virus (WNV) is a very relevant ecoepidemiological model to explore this issue. This mosquito-borne Flavivirus, with a positive-sense, single strand of RNA, infects mostly birds but also horses and humans among incidental host species (Granwehr et al., 2004). This virus is transmitted between birds mainly by ornithophilic mosquito species (mostly Culex species) (Komar, 2003). Evidence of WNV infection have been found in a broad range of wild bird species (Komar et al., 2003; Kilpatrick et al., 2007), resulting in a complex multi-host pathogen system (Roche et al., 2013). This system is especially relevant in North America since this area has witnessed an invasion wave of WNV started a decade ago, resulting in more than 200 human deaths every year (Gould and Fikrig, 2004) and a significant decrease in abundance for some bird species (Ladeau et al., 2007). Though WNV commonly infects human and bird populations in Africa, Middle East, Europe and Western Asia (Malkinson and Banet, 2002), the emerging nature of this pathogen in North America, where the bird populations have never been in contact with this virus before, allows to study a system where there have been no co-evolutionary dynamics between these local host species and this pathogen, nor acquired immunity in the host populations prior to the introduction of this novel pathogen. WNV invasion in North America has started in New York City (Lanciotti et al., 1999) where an unusually high morbidity and mortality was detected among the bird collection at the Bronx Zoo/Wildlife Conservation Park (BZ/WCP). The extensive serologic survey conducted at the BZ/WCP at that time in captive wild birds provides then a unique opportunity to study the ecology of WNV over a broad range of birds species immunologically naïve within the relatively confined area and controlled environment of a urban zoo (Ludwig et al., 2002). Following the rapid spread of WNV across North America, an extensive number of WNV serologic surveys were conducted on wild bird populations also immunologically naive. Such large and intense surveillance efforts in a large diversity of potential host species and ecosystems (Granwehr et al., 2004) offer a rare opportunity to investigate the drivers of host exposure to infectious vector and its consequences for variation in WNV infection rate. In this study, we aim to quantify the respective contribution of (i) the receptivity of avian host species to WNV infection estimated through the phylogenetic relatedness of bird families in BZ/WCP and (ii) the exposure to pathogen estimated through host ecological traits that can potentially influence the contact rate between hosts and vectors when considering their receptivity estimated on captive birds. Using the semi-natural experimental context of BZ/WCP where exposure to vectors can be assumed to be relatively

homogenous for all captive wild bird species, we estimate species receptivity by analyzing the relationship between species seroprevalence and species phylogenetic relatedness. Second, we study the role of pathogen exposure by analyzing the relationship between species variation in seroprevalence among free-ranging wild bird species measured in various regions of the USA during the invasion wave and various species ecological traits that can influence the contact rate between hosts and vectors. Finally, we evaluate the relative contribution of both receptivity and pathogen exposure by integrating the two previous steps within the latter model on free-ranging birds. We finally discuss on the implications of these findings for WNV and, more broadly for multi-host pathogens where we argue that the relative contribution of exposure and receptivity may depend on the pathogen host range.

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2. Materials and methods

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2.1. WNV seroprevalence data

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Our analysis relies on two data sets (Fig. 1). First, we consider results from the serologic survey conducted at the BZ/WCP in 1999 during the first WNV outbreak reported in North America (Ludwig et al., 2002). This extensive serologic survey revealed that WNV circulation was widespread among both captive and freeranging (indigenous) birds sampled in the park: a large proportion of birds tested (34%, n = 368 birds) were positive for antibody to WNV and seropositive birds were identified from about half the species tested (47%, n = 89 bird species) (Ludwig et al., 2002). No significant difference in seroprevalence was observed between captive and free-ranging birds sampled at the BZ/WCP (Ludwig et al., 2002), therefore they are considered together in our analysis (first dataset). All species housed in indoor enclosures are excluded from the analysis as mosquito exposure may vary between indoor and outdoor enclosures. In the second dataset, we compile seroprevalence measures from published WNV serologic surveys conducted in free-ranging wild birds in USA during the initial spread of WNV (1999–2003) from the East to the West–North American coasts (Table 1). Studies are restricted to serologic surveys conducted during the first year of WNV detection in wild birds for a given federal state to avoid potential confounding factors associated with the establishment of individual and population immunity.

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2.2. Bird phylogeny and ecological traits

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To investigate the relationship between seroprevalence and phylogeny, we use the latest bird phylogeny available to us (Hackett et al., 2008). Phylogeny of birds has been extensively studied (Hackett et al., 2008; Sibley and Ahlquist, 1991), nevertheless never deeper than at the family level when one considered the entire bird diversity. Second, we set up a database with a list of several ecological traits of bird species that have been previously proposed to influence the probability for a wild bird to be exposed to WNV vectors (Table 2). Each variable is defined as a two-class variable and was estimated using information from the ‘‘Birds of North America’’ online database (Poole, 2005), which provides detailed descriptions of behavioral and ecological traits for each species.

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2.3. Statistical analysis

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Our statistical procedure follows three steps. First, we explore the relationship between the phylogenetic relatedness among bird species at the family level and WNV seroprevalence measured on wild bird species at the BZ/WCP in order to evaluate the species

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Fig. 1. Distribution of captive and free-ranging wild bird families sampled at the BZ/WCP used in our analysis. (A) Number of observations for each family present in our study. (B) Phylogenetic position of these families within the birds phylogeny (Hackett et al., 2008). See main text for full description of our dataset.

Table 1 Summary of studies used to construct the database of seroprevalence in free-ranging wild bird species. Only serologic surveys conducted in free-ranging wild birds during the initial spread of WNV (1999–2003) across USA were considered. For studies conducted over several years, only data from the first year when a sero-conversion had been detected in wild birds were considered.

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References

Years

State

Number of species sampled (No. birds)

Mean WNV seroprevalence (%)

Diagnostic method

Infected mosquitoes observed

Bell et al. (2006) Beveroth et al. (2006) Gibbs et al. (2006) Godsey (2005)

2003–2005

Dakota

11

17.1

Epitope-blocking ELISA

Culex tarsalis

2002–2004

Illinois

37

5.4

Epitope-blocking ELISA

Culex pipiens

2000–2001

Georgia

57

0.05

Culex quiquefasciatus

2001

Florida

10

11

Komar (2001)

1999

18

33

Reisen (2009)

2004

New York California

27

NA

Ringia (2004)

2002

Illinois

19

5.3

Plaque reduction neutralization tests (PRNT) Plaque reduction neutralization tests (PRNT) Plaque reduction neutralization tests (PRNT) Plaque reduction neutralization tests (PRNT) Epitope-blocking ELISA

variation in receptivity to WNV infection. We did not assume any a priori about a particular bird family likely to have the highest (or lowest) receptivity to WNV infection, which could be tested as a reference family for investigating the influence of phylogenetic relatedness between bird families. We first measure the phylogenetic distances between the families of bird species present in the BZ/WCP Zoo dataset and each family present in the Hackett’s phylogeny (Hackett et al., 2008). We then investigate for the presence of a significant relationship between species seroprevalence measures and phylogenetic distances to one given reference family. We iteratively test for all families present in the Hackett’s phylogeny. We identify the reference families from which the phylogenetic relatedness is significantly related to species seroprevalence measures after Bonferonni correction. It is worth pointing out that phylogenetic distances are aggregated at the family level, thus two species belonging to the same family have a null phylogenetic distance despite variable seroprevalence measures. We have considered the different number of species and individuals for each family by weighting the observations through the number of individuals sampled. Second, we investigate the relationship between WNV seroprevalence measured in free-ranging wild bird species across USA and species ecological traits using Generalized Linear Mixed

Culex quiquefasciatus, Culex nigripalpus, Culiseta melanura NA Culex quiquefasciatus, Culex pipiens Culex pipiens

Models (GLMM) with a binomial error distribution. Several wild bird species have been tested for WNV serology in the same study area, i.e., in similar environmental conditions, in each of the serologic survey that we have compiled in our second dataset. To avoid pseudo-replication we include the study area as a random effect in models. We run models with the ‘glmer’ function in the ‘lme4’ package in the R environment (R Development Core Team, 2011), using Laplace approximation of the maximum-likelihood and compare models using the Akaike information criterion (AIC). We first tested the potential association between ecological variables using correlation tests and Bonferroni correction. Multi-colinearity was high between two groups of explanatory variables (Table S1). We selected among these associated variables in each group by testing them alternatively in a two-variable model against seroprevalence data (i.e., one variable from each group of associated variables), retaining the two variables providing the lowest AIC within each group. As a final step, we use a model comparison approach to evaluate the relative ability of both phylogenetic relatedness and ecological traits to explain species variation in seroprevalence measured in free-ranging wild birds. We compare models that include either (i) the two ecological traits retained in our selection process plus the species phylogenetic distance to the reference family identified


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Table 2 List of species ecological traits tested to explain species variations in WNV seroprevalence measured in free-ranging wild birds across USA.

a b

Explanatory variables

Potential influence on WNV transmission

Definition

Scavenging

Direct (non-vector) transmission through ingestion may occur in birds scavenging on WNV infected carcasses (Hartemink et al., 2007)

Absent/accidental vs occasional/regular scavenging

Nocturnal gregariousness

Communal night-roosting or nocturnal flock-foraging in social birds may promote WNV transmission because of the nocturnal feeding behavior of Culex mosquitoes, the primary vectors of WNV (Diuk-Wasser et al., 2010)

Gregariousa vs solitary

Breeding sociality

Clustering of birds in nesting colonies may attract and concentrate the feeding activities of vectors hence promote WNV transmission (Carver et al., 2009; Reisen et al., 2009) Conversely solitary breeders may be more frequently fed on by mosquitoes through a concentration of mosquito bites on isolated individual in areas where mosquito-to-bird ratio is low.

Colonial vs solitary breeders

Nestling exposure

Altricial species may be more receptive to mosquito bites than precocial species due to minimal feather coverage and reduced defensive behavior of nestlings (Loss et al., 2009)

Altricial vs precocial

Wetland habitat use

The high density of mosquitoes in wetlands (i.e. breeding habitats for WNV-competent ornithophilic mosquito species) should promote contact between hosts and vectors (Hubálek and Halouzka, 1999)

Rare/irregular vs regular in wetland habitatb

Urban habitat use

Birds using in urban areas may be more exposed to WNV infection since the decrease in the diversity of avian hosts and the increase in the abundance of important mosquito vectors (Cx. pipiens and Cx. quinquefasciatus mostly) with urbanization may promote transmission (Kilpatrick, 2011)

Rare/irregular vs regular in urban or suburban areas

Exclude winter flocking (outside mosquito activity season). Exclude specific winter use of wetlands (outside mosquito activity season).

250

in the first step of the analysis, or (ii) only these two ecological traits or (iii) only the species phylogenetic distance to the reference family.

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3. Results

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3.1. Evaluation of the influence of phylogenetic relatedness among bird species

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In our first analysis on bird species at the BZ/WCP, we investigate the bird families from which the phylogenetic distance is a good predictor of species variation in WNV seroprevalence. After exploring the whole phylogenetic tree of bird families, we found a significant negative relationship between WNV seroprevalence and the phylogenetic distance to six families (Fig. 2): Cuculidae (cuckoos and allies), Aramidae (limpkin), Gruidae (cranes), Psophiidae (trumpeters), Rallidae (rails and gallinules), and Heliornithidae (finfoots). These families are all part of a single clade formed by the core Gruiformes (rails, cranes, and allies) and the Cuculiformes (cuckoos). This means that the seroprevalence significantly declines with increasing phylogenetic distance to these families. This is mostly a clade of terrestrial and arboreal taxa (Hackett et al., 2008) though it includes few aquatic bird groups (finfoots, coots, and gallinules). We also found a significant positive relationship between WNV seroprevalence and the relatedness to seven families, i.e. an increase in seroprevalence with increasing phylogenetic distance to these families: Hydrobatidae (storm petrels), Spheniscidae (penguins), Ciconiidae (storks), Fregatidae (frigatebirds), Phalacrocoracidae (cormorants), Anhingidae (darters), and Sulidae (gannets and boobies). All these families are classified within a cohesive waterbird clade (Hackett et al., 2008) including members of the Pelicaniformes (totipalmate birds), Ciconiiformes (storks and allies), Procellariiformes (tubenosed birds), Sphenisciformes (penguins), and Gaviiformes (loons).

Among all these families from which phylogenetic relatedness show a significant relationship (i.e., negative or positive) with WNV seroprevalence, the Ciconiidae provides the lowest AIC and is then kept as the reference family for the following part of our analysis. It is worth pointing out that we found that the phylogenetic relatedness to the reference family has no significant effect on species variation in WNV seroprevalence in the free-ranging wild birds in their natural habitats (Table 3).

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3.2. Contribution of species ecological traits on WNV seroprevalence in free-ranging wild birds

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Our selection process among associated ecological traits indicates that the variables ‘‘breeding sociality’’ and ‘‘nestling exposure’’ are the best predictors of WNV seroprevalence in freeranging birds according to AIC values between models including alternatively each variable from the two independent groups of variables. However, we found that these two species ecological traits are not significantly associated with the variation in WNV seroprevalence in free-ranging wild bird species when considered together (Table 3).

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3.3. Interplay between species ecological traits and phylogenetic relatedness

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In our last model we integrate the phylogenetic relatedness to Ciconiidae into the previous model including the variables breeding sociality and nestling exposure (Table 3). We found that this model received a much higher support from the data (DAIC > 20) than the model considering only the two species ecological traits or only the phylogenetic relatedness among species. In addition in this last model the variables nestling exposure and phylogenetic relatedness have a significant effect on species variations in WNV seroprevalence: altricial species showed a significantly higher prevalence than precocial birds in accordance with our initial

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Fig. 2. Bird reference families identified in our analysis of species variations in WNV seroprevalence in wild birds at the BZ/WCP. The positive (blue) and negative (red) roots represent families with whom phylogenetic distance is positively and negatively associated with seroprevalence in wild birds respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Table 3 Results from statistical models tested to explain species variations in WNV seroprevalence in wild birds. The first model relates variations in WNV seroprevalence only to phylogenetic distances among bird species, using the dataset on wild birds sampled in the BZ/WCP. The second model relates variations in WNV seroprevalence only to species ecological traits (summarized in Table 2) using the dataset on free-ranging birds sampled across USA (summarized in Table 1). The last model integrates both species ecological traits and phylogenetic relatedness to explain variations in WNV seroprevalence in the dataset on free-ranging birds. Number between brackets show coefficients values when variables have been normalized. Phylogenetic distance between Ciconiidae and nestling exposure are not associated together (p-value > 0.05). The full methodology is explained in the main text. Model

Variable

Model with phylogenetic relatedness

0.005842 0.319 Phylogenetic distance from Ciconiidae AIC = 149.5 Variance of random effect: 1.5822

Model with species ecological traits

Model with species ecological traits and phylogenetic relatedness

Slope coefficient

p-Value

Breeding 0.1403 0.4335 sociality Nestling 0.3288 0.0563 exposure AIC = 147.2 Variance of random effect: 1.5967 Breeding 0.01767 0.917 sociality ( 0.018) Nestling 1.55089 5.86e 07⁄⁄⁄ exposure (0.586) 0.04975 5.03e 06⁄⁄⁄ Phylogenetic (0.364) distance from Ciconiidae AIC = 126.1 Variance of random effect: 1.5663

prediction (Table 2); and seroprevalence significantly increases along phylogenetic distance to the Ciconiidae family in accordance with result from our first analysis on birds at the BZ/WCP.

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4. Discussion of results and conclusion

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Our study context based on the seroprevalence of an emerging pathogen (to control for immunity) on captive birds (to control for variation in pathogen exposure) has allowed us to evaluate the influence of species relatedness on the probability of infection. We have then included the phylogenetic distance between species – estimated on captive birds as a proxy of species receptivity to WNV infection – in our analysis of species variation in WNV seroprevalence in free-ranging wild bird species, which has yielded an improved quality of our model. This two step statistical procedure has also highlighted that relatedness between host species, inferred by phylogenetic distance to the bird family Ciconiidae, as well a pathogen exposure, surrogated by nestling exposure, have both a significant and similar effect on species variation in WNV seroprevalence (Table 3). Compared to the current knowledge on WNV, we could have expected to find a an increase in seroprevalence with increasing distance to endemic bird families of the New World that have been biogeographically isolated from WNV exposure because they are more distantly related to the natural WNV hosts of the OldWorld (Longdon et al., 2011). Conversely, two endemic bird families of the New World (Aramidae and Psophiidae) were found to be families from which distance was negatively related to WNV seroprevalence in captive birds. Such counter-intuitive pattern may suggest that the virus could be adapted to a broad range of

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host species. In such a case, some host species that have never coevolved with the pathogen may have incidentally a good receptivity. A misplacement of these reference families, inherent to the uncertainty about the bird phylogeny, is also possible, like in any kind of study involving phylogeny at large scale. From an ecological point of view, recent evidences for an increase in the incidence of WNV infection in humans (Brown, 2008) and in WNV seroprevalence in wild birds (Bradley et al., 2008) with urbanization and agriculture have been proposed to be related to the increase in the abundance of the main WNV competent vectors (e.g. Culex pipiens, Culex quinquefasciatus, Culex restuans, Culex tarsalis) and the key amplification hosts (e.g., American robin Turdus migratorius) in human-modified habitats (Kilpatrick, 2011). In this study, we found that nestling exposure was a better predictor than the variable characterizing urban habitat use (see Supplementary Materials) .The higher seroprevalence found in altricial species compared to precocial species is consistent with the hypothesis than altricial nestlings are more exposed to vectors due to a minimal feather coverage and reduced defensive movements (Loss et al., 2009). 4.1. Contribution of host receptivity and host exposure: Is host spectrum the missing ingredient? Our model comparison approach revealed the relative ability of phylogenetic relatedness and ecological traits to explain species variation in WNV seroprevalence. First, inclusion of both phylogenetic measures and ecological traits received a much higher support from the data than models considering each component separately. Second, phylogenetic relatedness to a reference bird family and ecological traits associated with an increased exposure to vector are significant in the global model, but are not when considered separately. It suggests that excluding host exposure or receptivity may lead to wrong prediction about the contribution of the different factors. Finally, normalizing factors shows that nestling exposure has a contribution 60% greater than host receptivity (Table 3). Without considering this proportion as an accurate estimation, it nevertheless suggests that both host receptivity and exposure contribute similarly and significantly to the infection process. This latter point is especially insightful to figure out the complex processes involved in zoonotic diseases and its validity needs to be discussed for a broader range of pathogens. Indeed, the relative contribution of host exposure and receptivity can remain valid for pathogen with a similar host spectrum (the range of potential receptive hosts). However, this spectrum varies greatly among infectious diseases (Woolhouse and Gowtage-Sequeria, 2005) with some pathogens showing a high host specificity (specialist pathogen) whereas others have low or no host specificity (generalist pathogen). The West Nile Virus, used here as a case study, is especially insightful because its host spectrum is intermediate between the extreme cases of specialist and generalist pathogens. One can expect that for a pathogen with such an intermediate host range the contribution of host receptivity and exposure to the pathogen will be relatively equivalent. Beyond this intermediate point one can hypothesized what could be the relative contributions of host receptivity and exposure for other pathogens along a gradient between specialist and generalist pathogens (Fig. 3). In order to be more consistent and to offer hypotheses to be tested, we present below a framework of predictions for pathogens associated with infectious diseases for same kind of hosts (birds) or others (rodents). While WNV has a large host range among viruses infecting wild birds (Thomas et al., 2007), some other avian pathogens show a more restricted host range. For instance, duck plague, a contagious

disease caused by a herpesvirus transmitted via direct contact between individuals or through contaminated environment, has been reported almost exclusively in waterfowl (ducks, geese and swans), while non-waterfowl species have been found to be resistant to infection (Thomas et al., 2007). One could expect a stronger host barrier to the transmission of this relatively specialist virus among the wild bird community, and a larger contribution of the phylogenetic relatedness with the main host family (Anatidae) in explaining the species variation in infection (Fig. 3). Conversely all species of birds probably can be infected with Newcastle Disease virus (Thomas et al., 2007), a paramyxovirus also transmitted directly among susceptible birds via contaminated environment. The ecological traits associated with host exposure could be expected to explain most of the species variation in infection with such a pathogen widespread among different taxonomic groups of wild birds (Fig. 3). Among mammals, rodents are known to be hosts for a considerable number of infectious diseases (Meerburg et al., 2009). A comparable example of WNV in rodent pathogens could be Hantaviruses, which form a group of rodent/shrew-borne RNA viruses, with a variety of human pathogenic strains. Hantaviruses are thought to share co-phylogeny with their rodent hosts, although some recent findings of multiple new hantaviruses pose some problems for the co-phylogeny paradigm (Henttonen et al., 2008). Each hantavirus species or lineage is, however, hosted predominantly by a single rodent species, with some spill-over infections into other species occurring (Zou et al., 2008). Transmission of hantaviruses among their rodent hosts is then depending on both host receptivity (host phylogenetic relatedness) and host exposure (host ecological traits). Indeed, several studies have emphasized the importance of the composition and structure of rodent communities on the overall prevalence of hantaviruses (Suzán et al., 2009). As hantaviruses are environmentally transmitted through aerosol, the host ecological factors (such as host habitat use) associated with host exposure (behavior and social interactions) are also important components of the transmission ecology (Bordes et al., 2013). At one side of the gradient for mammals, fungus of the genus Pneumocystis showed a quite high specificity toward their hosts and the importance of co-evolution in the host-parasite interaction has been emphasized (Aliouat-Denis et al., 2008). Pneumocystis carinii and Pneumocystis wakefieldiae were found mainly in Rattus norvegicus, the Norway rat, in which they are observed in high prevalence. These fungi are transmitted among individuals through aerosol, and the host ecological traits (except the sex), habitat use and whatever the origins of the rats (laboratory or wild) have little influence on the prevalence of the infection (Chabe et al., 2010). At the other side of the gradient, bacteria of the genus Leptospira can infect almost all rodents (McBride et al., 2005). Until now, no host specificity has been observed (Ivanova et al., 2012). Leptospirosis is transmitted via the water-environment through the excretion of the bacteria by reservoirs (and among them, rodents) (Levett, 2001). Several studies showed the importance of the host ecological traits, and particularly the habitat use, has the major factor associated with the exposure to this environmentally transmitted disease (Bordes et al., 2013; Ivanova et al., 2012). We made several assumptions in our study that deserve to be discussed here. First we assumed that the bird exposure to infectious mosquitoes across the BZ/WCP was relatively homogenous for all species of captive (out-door) and free-ranging (indigenous) birds. According the homogenous nature (Ludwig et al., 2002) and the small surface (265-acre/1 km2) of this urban park, it is nevertheless reasonable to assume a relatively homogeneous and abundant distribution of C. pipiens mosquitoes within this area. This assumption is supported by the findings that some


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Fig. 3. Conceptual framework of respective contribution of host receptivity and exposure according to the degree of pathogen host specialization. We found for West Nile Virus a similar contribution of host exposure and host exposure. Thus, pathogens with larger host spectra should exhibit a stronger influence of host exposure while host receptivity is expected to have greater contribution for specialist pathogens.

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seropositive birds were detected in about half the species sampled across the zoo suggesting a widespread exposure to infectious mosquitoes. Similarly, the use of serology and associated detection tests comes with some limits because it does not inform on the magnitude and duration of viremia produced by a given species and therefore consequently on its relative role in virus transmission. Moreover, the potential influence of cross-protection by antibodies from other flaviviruses present in North America (SLEV) may have reduced the rate of sero-conversion to WNV in some bird species or in some geographic areas (Kilpatrick, 2011). Nevertheless, it is worth to point out that such measure, which is in our case equivalent to an accumulated prevalence during the season, was the only opportunity to study bird exposure without the scrambling effect of a potential herd immunity that may arise. We have tried to account for the potential effect of differences in the local environmental conditions – i.e. climate, diversity and abundance of vectors and birds species – by including the study site as a random effect in all our models. We assumed that the differences in mosquito pressure and bird species assemblages between study sites (Table 1) do not confuse the pattern of species variation in WNV transmission. While bird species richness or vector competence can play an important role in WNV transmission (Roche et al., 2013), these effects are expected to be more influent on established pathogens rather than on emerging ones like WNV. However, one factor that can potentially affect the vector-host contact rates is the feeding preferences of mosquito vectors of WNV for certain species of birds, which could be due to a myriad of factors (Balenghien et al., 2011), irrespective to the bird species local abundance (Simpson et al., 2012). While this may bias our capacity to predict the contribution of various bird species to WNV transmission from their ecological-associated traits of exposure to vectors, we nevertheless hope that including sites as random factor combined with the high number of different sites we consider may have overcome this additional variability. In this study, we have adopted a different approach than the classic methods used in phylogenetic comparative methods, such

as Phylogenetically Independent Contrasts (PIC) (Felsenstein, 1985). We use this different approach because these comparative methods aim to control for relatedness between species when comparing the influence of a given species attribute on a given ecological characteristic. Conversely, we aim to evaluate the relative contribution of such relatedness on species seroprevalence and to link it with co-evolutionary history between host species and the pathogen, as discussed previously. This different approach also allowed us to take the advantage of the semi-natural experiment in BZ/WCP where species relatedness could be considered as the only influencing factor on seroprevalence. Nevertheless, while dataset on BZ/WCP could also be used to quantify the robustness of new Phylogenetic Comparative methods, we believe that our approach could be applied to other pathogen system where immunity is not permanent and environmental conditions correctly controlled. The goal of our study was to disentangle the respective role of ecologically-related risk factors of exposure to infectious vectors and the phylogenetically-related receptivity to infection in a wide range of avian host species. Here, we do not aim at identifying the main ecological drivers or the most important bird species or families of WNV transmission in North America. Despite the quantification of each component cannot be used as an accurate estimation, we nevertheless shown that each component plays a significant role within its context: (i) we successfully related phylogenetic relatedness among host bird families to species heterogeneity in pathogen infection in accordance to the hypothesis of the difference in evolutionary history among host species and the pathogen, (ii) the ecological/behavioral components associated with exposure to vectors seem to have a strong weight on pathogen transmission in natural ecosystems. It is also important to underline that the two types of environments that we studied, i.e., a urban zoo and different natural ecosystems throughout United States, are somewhat extreme on the gradient of zoonosis environments. Indeed, suburb areas seem to be the most common playground of emerging pathogens, especially West Nile (Magori


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et al., 2011). Such environments are situated within a gradient between an extreme of captive host species in zoo and the other extreme of free ranging host species in natural environment. The exact contribution of receptivity and ecology should take this into account in the future.

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Acknowledgments

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We sincerely acknowledge different colleagues which reviewed this manuscript and help to its improvement. B.R. is sponsored by Institut de Recherche pour le Développement and Université Pierre et Marie Curie. E.G. and J.F.G. are sponsored by both Institut de Recherche pour le Développement and the Centre National de la Recherche Scientifique. S.M. is sponsored by Centre National de la Recherche Scientifique. NG and TB are sponsored by the Centre de coopération internationale en recherche agronomique pour le Développement. B.R., J.F.G., S.M. and N.G. are supported by the EDEN project (EU Grant GOCE2003010284 EDEN). This work has benefited from an Investissements d’Avenir grant managed by Agence Nationale de la Recherche (CEBA, ref. ANR-10-LABX-2501) for B.R. and J.F.G. S.M. was also supported by ANR CP&ES (Grant ANR 11 CPEL 002) BiodivHealthSEA. The contents of this publication are the sole responsibility of the authors and don’t necessarily reflect the views of the European Commission.

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Appendix A. Supplementary data

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Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.meegid.2015.04. 011.

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