University of Veterinary Medicine Hannover

Patterns of parasitism in wild Verreaux’s sifakas (Propithecus verreauxi) at Kirindy Forest, Madagascar: Assessing the role of host behavior

Thesis Submitted in partial fulfillment of the requirements for the degree of Doctor of Veterinary Medicine - Doctor medicinae veterinariae - (Dr. med. vet.)

by Andrea Springer Hamburg

Hannover 2015 Academic supervision: Prof. Dr. med. vet. Franz-Josef Kaup Pathology Unit German Primate Center

1st referee: Prof. Dr. Franz-Josef Kaup 2nd referee: Prof. Prof. h. c. Dr. Ursula Siebert

Day of the oral examination: 13.11.2015

This study was funded by the German Primate Center and the German Research Foundation (Ka 1082/29-1).

II For the sifakas of Kirindy Forest

III The following parts of this thesis have been submitted for publication in peer-reviewed journals:

Chapter 6:

Andrea Springer, Alexander Mellmann, Claudia Fichtel and Peter M. Kappeler: “Sociality shapes inter-group transmission of Escherichia coli in a group-living wild primate, Verreaux’s sifaka” Submitted for publication to BMC Ecology (date of submission: 14.07.2015, in review)

Chapter 8:

Andrea Springer, Claudia Fichtel, Sébastien Calvignac-Spencer, Fabian H. Leendertz and Peter M. Kappeler (2015): “Hemoparasites in a wild primate: Plasmodium and Babesia interact in a lemur species” International Journal for Parasitology: Parasites and Wildlife, in press, doi:10.1016/j.ijppaw.2015.10.006.

Furthermore, results of this study have been publicly presented at the following conferences:

Ecology and Evolution of Infectious Diseases, May 26 – 29, 2015, Athens, GA, USA: “Hemoparasite infections in a wild primate: Parasite interaction shapes prevalence patterns” (poster), Springer A., Fichtel C., Calvignac-Spencer S., Leendertz F.H., Kappeler P. M.

EWDA student workshop “Human Impact on Wildlife Diseases”, March 26 – 30, 2015, Veyrier-du-Lac, France: “Social spread of Escherichia coli through a lemur population” (poster), Springer A., Mellmann A., Fichtel C., Kappeler P.M.

IV 10th topical meeting of the Ethological Society: “Causes and Consequences of Social Behavior”, February 11 – 14, 2015, Hamburg, Germany: “Environmental versus social transmission: How Escherichia coli spreads through a lemur population” (talk), Springer A., Fichtel C., Mellmann A., Kappeler P.M.

25th Congress of the International Primatological Society, August 11 – 16, 2014, Hanoi, Vietnam: “Investigating parasite spread through a lemur population” (talk), Springer A., Fichtel C., Leendertz F.H., Calvignac-Spencer S., Mellmann A., Nunn C.L., Kappeler P.M.

International Conference on Diseases of Zoo and Wild Animals, May 28 – June 01, 2014, Warsaw, Poland: “Investigating parasite spread through a lemur population” (talk), Springer A., Fichtel C., Leendertz F.H., Calvignac-Spencer S., Mellmann A., Nunn C.L., Kappeler P.M.

Göttinger Freilandtage, December 03 – 05, 2013, Göttingen, Germany: “Investigating parasite spread through a lemur population” (talk), Springer A., Fichtel C., Leendertz F.H., Calvignac-Spencer S., Mellmann A., Nunn C.L., Kappeler P.M.

International Prosimian Congress, August 05 – 11, 2013, Ranomafana, Madagascar: “Investigating parasite spread through a sifaka population” (talk), Springer A., Fichtel C., Leendertz F.H., Calvignac-Spencer S., Mellmann A., Nunn C.L., Kappeler P.M.

V VI Table of Contents

List of abbreviations……………………………………………………………………… X

Chapter 1 – Introduction………………………………………………………………..... 13 Parasitism – an ecological perspective……………………………………..... 13 Parasitism and behavior……………………………………………………… 13

Chapter 2 – Literature Review………………………………………………………….. 16 Parasitic infections – a major cost of sociality?...... 16 Benefits of living in groups………………………………………………. 16 Direct parasite transmission, animal density and social complexity……... 16 Sociality and vector-borne parasites……………………………………… 18 Behavioral adaptations against parasitism…………………………………… 18 Avoidance of fecal contamination………………………………………... 19 Social barriers to parasite transmission…………………………………… 20 Grooming……………………………………………………………...... 21

Linking theory with empirical data: Approaches to studying transmission in the wild………………………………………………………………………. 22

Verreaux’s sifakas as a study system………………………………………… 22 Behavioral ecology……………………………………………………….. 24 Parasites of Verreaux’s sifakas…………………………………………… 25

Chapter 3 – Objectives and Structure of this Thesis…………………………………… 27

Chapter 4 – Materials and Methods……………………………………………………... 29 Study site and study animals……………………………………………….... 29 Remote data collection………………………………………………………. 29 Calculation of home ranges and their overlaps…………………………… 30 Estimation of intergroup encounter rates………………………………..... 30 Behavioral observations……………………………………………………… 30 Invasive sampling…………………………………………………………..... 31 Noninvasive sampling……………………………………………………….. 32

VII Overview of data collection………………………………………………….. 33 Sample processing…………………………………………………………… 33 Microscopy of fecal samples…………………………………………….... 33 Fecal cultures and preparation of helminth larvae for PCR………………. 34 DNA extraction from fecal samples and PCRs…………………………… 35 Escherichia coli isolation and multi-locus sequence-typing……………… 37 Ectoparasites……………………………………………………………… 38 Analysis of blood samples and PCRs for hemoparasites………………..... 38 Phylogenetic analyses………………………………………………………... 40 Statistical analyses…………………………………………………………… 41 Ranging patterns and behavioral data…………………………………..... 41 Nematode infections……………………………………………………… 42 Escherichia coli type sharing……………………………………………... 42 Ectoparasite infections………………………………………………….... 44 Hemoparasite infections………………………………………………….. 44 Chapter 5 – Low diversity of intestinal parasites in an arboreal primate, Verreaux’s sifaka, at Kirindy Forest, Madagascar (Manuscript 1)……………………. 46

Chapter 6 – Sociality shapes inter-group transmission of Escherichia coli in a group- living wild primate, Verreaux’s sifaka (Manuscript 2)…………...... 66

Chapter 7 – Ectoparasites of a group-living wild lemur species, Verreaux’s sifaka: Does sociality influence infection risk? (Manuscript 3) ……...... 92

Chapter 8 – Hemoparasites in a wild primate: Plasmodium and Babesia interact in a lemur species (Manuscript 4)...... 111

Chapter 9 – General Discussion…………………………………………………………. 140 Arboreality: a strategy to avoid parasites?...... 142 Social behavior and directly transmitted infections…………………………. 146 Social group size and vector-borne infections………………………………. 151 Inter-specific parasite interactions: an important determinant of infection patterns………………………………………………………………………. 151

VIII Conclusions…………………………………………………………………... 153 Summary…………………………………………………………………………………... 155 Zusammenfassung……………………………………………………………...... 158 References…………………………………………………………………………………. 161 Acknowledgements………………………………………………………………………... 220 Erklärung………………………………………………………………………………….. 221

IX List of abbreviations

°C degree Celsius AIC Akaike Information Criterion ANOVA analysis of variance approx. approximately BLAST Basic Local Alignment Search Tool Bp bootstrapped pseudo-replicates bp basepairs CNFEREF Centre National de Formation, d’Etudes et de Recherche en Environnement et Foresterie cyt b cytochrome b df degrees of freedom DNA deoxyribonucleic acid E. coli Escherichia coli E. dispar Entamoeba dispar E. histolytica Entamoeba histolytica E. nuttalli Entamoeba nuttalli e.g. for example EMBL European Molecular Biology Laboratory ESBL extended-spectrum beta-lactamases EUCAST European Committee on Antimicrobial Susceptibility Testing F-EA formalin-ethylacetat FEC fecal egg count g gram GLMM generalized linear mixed model GPS global positioning system h hours ha hectare i.e. that means ID identity ITS internal transcribed spacer

LMM linear mixed model MALDI-ToF matrix-assisted laser desorption ionization time-of-flight mass-spectrometry MgCl2 magnesium chloride min minutes ml milliliter MLST multi-locus sequence typing mM millimolar MR-QAP multiple regression quadratic assignment procedure N sample size NLR neutrophil : lymphocyte ratio no. number p. page P. verreauxi Propithecus verreauxi PCR polymerase chain reaction PCV packed cell volume pp. pages rpm rounds per minute rRNA ribosomal ribonucleic acid s.s-1 substitutions per site SFV simian foamy virus SMS smart model selection sp. species spp. species (plural) ST sequence type TP total protein UDOI utilization distribution overlap index µl mikroliter µM mikromolar

XII

1. Introduction

Parasitism – an ecological perspective

Almost all organisms are affected by parasitism, be it as hosts or as parasites. Throughout this thesis, the term “parasite” will be used according to the ecological definition: “…any organism that lives on and draws nutrients from another organism (the host), usually to the host’s detriment” (Nunn and Altizer 2006). This definition encompasses a wide range of biological diversity in the form of viruses, bacteria, protozoa, fungi, helminths and arthropods. Parasites use their host both as a source of energy and as a habitat in a “prolonged and durable way” (Combes 2001), which gives rise to a system more complex than the sum of its parts. Parasites exhibit considerable morphological simplification and loss of genes while relying on the host to provide them with the corresponding functions (Combes 2001); a parasite is thus often reliant on the host in order to survive. Importantly, genes are lost only on one side of the relationship, in contrast to mutualism, where both partners profit from the relationship and there is bilateral dependence (Cheng 1991). In a parasitic relationship, the parasite profits, while the host may suffer substantial costs in the form of energy drainage, pathological damage, reduced survival and decreased reproductive fitness (e.g. Delahay et al. 1995; Milton 1996; Hudson et al. 1998; Hillegass et al. 2010). Thus, in parasitic associations each organism constitutes a separate unit of selection and reciprocal effects occur, leading to host-parasite arms races (e.g. Clayton et al. 1999; Schulte et al. 2010).

Parasitism and behavior

Regarding animal behavior, selection on the side of the host will favor behavioral strategies to avoid or get rid of parasites, summarized as the so-called “behavioral immune system” (Hart 1990; Schaller 2011), e. g. through avoidance of contact with feces (Freeland 1980; Ezenwa 2004b; Moe et al. 1999), grooming (Hart et al. 1987; Mooring et al. 1996; Akinyi et al. 2013) and self-medication (Carrai et al. 2003; Alfaro et al. 2012; Nakagawa et al. 2012), while parasites are selected to exploit, or even alter host behavior to increase transmissibility (Moore and Gotelli 1990). Alteration of host behavior occurs for example in Toxoplasma-

1. Introduction

infected mice, which become less fearful of predators (Webster 2007), or ants infected with metacercariae of Dicrocoelium sp., which attach to plants (Spindler et al. 1986), both facilitating uptake by the definitive host of the parasite. Exploitation of host behavior is especially apparent in sexually transmitted diseases, in which transmission is expected to increase with increasing promiscuity (Thrall et al. 2000; Nunn et al. 2014a). Other social interactions also represent opportunities for the spread of directly transmitted parasites and therefore transmission is expected to increase with animal density and group size (Freeland 1976; Anderson and May 1982; Anderson et al. 1986; Altizer et al. 2003). In addition, host gregariousness may influence environmental transmission of parasites, if increased host density leads to a higher degree of environmental contamination and contact with infectious parasite stages (Ezenwa 2004a; Chapman et al. 2005; Kappeler et al. 2015). Thus, gregarious animals face a trade-off between the advantages of living in groups and the disadvantage of increased parasite spread, which is regarded as one of the major costs of group-living (Alexander 1974; Hoogland 1979). Although social behavior has been widely incorporated into epidemiological modeling efforts (e.g. Griffin and Nunn 2012; Hamede et al. 2012; Carne et al. 2014; Gilbert et al. 2014), empirical evidence regarding the influence of social behavior on transmission remains limited in many host-parasite systems (but see Drewe 2010; VanderWaal et al. 2013b, 2014). Furthermore, parasite exposure and host susceptibility may be influenced by several other factors related to the biology of the host and the parasite, including host life style (arboreal vs. terrestrial) and ranging behavior (Benavides et al. 2012; Nunn et al. 2014b), body mass, sex, age and social and endocrine status (Zuk and McKean 1996; Nunn 2012; Habig and Archie 2015), interspecific interactions like co-infections (Pedersen and Fenton 2006; Telfer et al. 2010; Tompkins et al. 2011) and seasonality of the habitat (Altizer et al. 2006). In this context, the relative importance of different types of social contacts regarding transmission remains relatively unexplored (Drewe 2010; Kappeler et al. 2015), although such data may inform studies on the ecological and evolutionary impacts of parasites (Tompkins et al. 2011), epidemiological models (Nunn 2012) and the development of disease control strategies for emerging wildlife diseases (Anderson et al. 1986; Daszak et al. 2000; Leendertz et al. 2006). Thus, more empirical data need to be gathered on transmission characteristics of different infectious agents and their determinants in natural animal populations (Altizer et al. 2003;

1. Introduction

Nunn et al. 2011; Craft 2015; Kappeler et al. 2015). In this context, the aim of this study was to examine the links between host ecology, sociality and parasite infections in a wild population of group-living primates, Verreaux’s sifakas (Propithecus verreauxi).

2. Literature Review

Parasitic infections – a major cost of sociality?

The socio-ecological model introduced by Crook (1970) has provided the basis for identifying the ecological factors favoring the evolution of various types of social systems. Solitary life styles, pairs and groups have been identified as the main categories of primate social organization (Kappeler and van Schaik 2002), and predation, conflict and infectious disease as the main factors driving their evolution (Nunn and van Schaik 2000; Nunn and Altizer 2006).

Benefits of living in groups

Direct benefits of group-living include the increased ability to defend a territory and its resources, increased access to mating partners (e. g. Packer et al. 1990) and minimized predation risk (Jarman 1974; Molvar and Bowyer 1994). Furthermore, social relationships may have beneficial effects on health and disease resistance. In humans as well as animals, social integration may buffer against the negative effects of prolonged stress (Cohen and Janicki-Deverts 2009; Hennessy et al. 2009) and influence immune system functionality (Tung et al. 2012; Capitanio and Cole 2015), thus ultimately increasing fitness. In wild female baboons, for example, social bonding and levels of affiliative behavior were strong predictors of infant survival (Silk et al. 2003) and female longevity (Silk et al. 2010; Archie et al. 2014), while social isolation may impede wound healing in several mammal species (reviewed in Archie 2013).

Direct parasite transmission, animal density and social complexity

On the other side of the coin, transmission of directly and environmentally transmitted parasites is expected to increase with animal density and thus represent one of the major costs of group-living (Alexander 1974; Anderson and May 1982; Anderson et al. 1986; McCallum et al. 2001). Anderson and May (1982) proposed that the rate of direct parasite transmission is proportional to the rate of encounters between susceptible and infectious individuals, which they assumed to scale with population density. For environmentally transmitted parasites, the

2. Literature Review

so-called “fecal-exposure hypothesis” states that more intensive range use, i.e. a higher concentration of individuals in a specific area, will lead to more contact with contaminated substrates and thus an elevated exposure to parasites (Ezenwa 2004a). Indeed, it has been shown that gregarious salmonids harbor a greater diversity of parasites as compared to solitary species (Ranta 1992), and African ungulates display both an increase in parasite prevalence and infection intensity when living in groups and displaying territoriality (Ezenwa 2004a). A significant relationship between host density and parasite species richness could also be established across primate hosts (Nunn et al. 2003). However, host group size only partly explains variation in parasitism across species and effect sizes are generally low (Rifkin et al. 2012), indicating that further factors related to social complexity must play a role. Griffin and Nunn (2012) showed that increasing group size favors subgrouping in gregarious primates, which is associated with lower parasite richness and may thus represent an adaptive response to social transmission. This pattern of increased modularity in larger groups also held true in a cross-species analysis comprising 43 different mammal species, and reduced parasite prevalence in a theoretical model (Nunn et al. 2015). Thus, the structure of social networks and the nature of social relationships may be more important regarding parasite transmission than animal density per se. The social network approach, which derives from mathematical graph theory, recognizes that animals do not interact randomly but have distinct social relationships (Wey et al. 2008). Several studies have shown that incorporating realistic social network structures – rather than assuming random mixing of individuals – dramatically alters predictions of epidemiological models, especially with regard to threshold population sizes for disease invasion (Lloyd-Smith et al. 2005), transmission (Molina and Stone 2012; Carne et al. 2014) and mortality rates (Hamede et al. 2012). For example, a social network model simulating the spread of devil facial tumor disease predicted a lower epidemic threshold and faster extinction of Tasmanian devils (Sarcophilus harrisii) as compared to a model assuming random mixing (Hamede et al. 2012). In chimpanzees (Pan troglodytes schweinfurthii), however, a network model based on observed associations predicted lower final epidemic sizes (Carne et al. 2014), which indicates that social contacts in the population may have been more clustered than expected by chance.

17 2. Literature Review

In summary, increasing evidence suggests that specific features of animal sociality, namely range use patterns and social network structures, may be important determinants of parasite spread, and should be preferred in epidemiological models over the assumption of random-mixing. However, empirical evidence regarding the influence of specific social behaviors on transmission remains limited in many host-parasite systems (Altizer et al. 2003; Nunn et al. 2011; Craft 2015; Kappeler et al. 2015).

Sociality and vector-borne parasites

Finally, animal grouping may also influence the transmission of vector-borne parasites. It has been proposed that group-living may decrease the risk of exposure by means of an encounter- dilution effect, analogous to a decrease of predation risk (Freeland 1976; Mooring and Hart 1992; Kappeler et al. 2015). Empirical evidence for this effect is controversial, however. Decreased per capita attack rates of blood-sucking insects in larger host groups have been found in black grouse (Tetrao tetrix, Rätti et al. 2006) and domestic chicken (Gallus gallus, Foppa et al. 2011). Sentinel hosts caged inside large roosts of American robins (Turdus migratorius) seroconverted to West Nile Virus more slowly than those held outside of roosts, suggesting that exposure of individual hosts can indeed be reduced through group-formation (Krebs et al. 2014). However, larger groups may also attract more vectors. In a comparative study, colonially-breeding bird species showed both higher prevalences and higher species diversity of hemoparasites than solitarily breeding species (Tella 2002). Two studies on Neotropical primates found that prevalence of Plasmodium sp. increases with group size (Davies et al. 1991; Nunn and Heymann 2005), but studies on the effect of within-species variability of group size on vector-borne infections in primates are lacking.

Behavioral adaptations against parasitism

Parasites may impose substantial costs on their hosts, affecting survival and reproductive fitness considerably (e.g. Hudson et al. 1992; Milton 1996; Hudson et al. 1998; Hillegass et al. 2010). While the immune system is an intricate and powerful way of fighting parasites, it also comes with substantial energetic costs (Sheldon and Verhulst 1996). In humans,

18 2. Literature Review

activation of leucocytes can consume up to 30 % of the basal metabolic rate (Straub et al. 2010) and in chronic inflammatory diseases, the high level of energy allocation to the immune system, together with reduced caloric intake, often result in cachexia, anemia and osteopenia (Straub et al. 2010). In wild animals, trade-offs between energetic costs allocated to the immune system and to reproduction have been demonstrated (Martin et al. 2008): For example, lactating and pregnant Siberian hamsters (Phodopus sungorus) showed suppressed humoral immunity in comparison to nulliparous animals (Drazen et al. 2003), and an increase in the brood size of zebra finches (Taeniopygia guttata) resulted in decreased antibody responsiveness (Verhulst et al. 2005). Thus, proactive behaviors, which limit pathogen exposure, are expected to have strong adaptive value (Hart 1990; Stevenson et al. 2011). In this context, the term “behavioral immune system” has been coined (Schaller 2011). Behavioral adaptations against parasitic infections include selection of healthy mating partners with complementary immune genes, “sickness behaviors” which serve the function of supporting energy allocation to the immune system during infection, and behaviors that operate independent of and complementary to the immune system (Hart 1990). These can be proactive, limiting exposure to parasites, or reactive, facilitating their clearance from the host’s body, and include behaviors like deterring insects, avoiding physical contact with infectious agents, grooming and self-medication. In the following paragraphs, the most relevant examples for the context of this thesis will be discussed.

Avoidance of fecal contamination

Avoidance of contact with feces can limit exposure to infectious stages of gastro-intestinal parasites (Hart 1990). Three species of wild ungulates have been shown to selectively avoid feeding near concentrations of feces (Ezenwa 2004b), and the same behavior has been demonstrated in sheep (Ovis aries, Cooper et al. 2000) and eastern grey kangaroos (Macropus giganteus, Garnick et al. 2010). Freeland (1980) suggested that the movement patterns of mangabeys (Cercocebus albigena) were related to avoidance of fecal contamination: The animals ranged more extensively during dry weather, when fecal matter was more prone to remain on leaves, than on rainy days. In a theoretical model investigating the spread of fecal- orally transmitted parasites, Nunn et al. (2011) showed that ranging intensity was a strong

19 2. Literature Review

predictor of parasite prevalence, and more extensive ranging reduced exposure. Likewise, the alternation of sleeping sites by yellow baboons has been interpreted as a parasite avoidance strategy (Hausfater and Meade 1982). It has been proposed that a primarily arboreal lifestyle might limit exposure to intestinal parasites (Muehlenbein et al. 2003; Loudon and Sauther 2013). However, in a meta- analysis, Nunn et al. (2003) did not find an effect of arboreality vs. terrestriality on parasite species richness of primates. Nevertheless, lower prevalences of intestinal parasites in arboreal as compared to sympatric, more terrestrial primate species have been reported in several cases (e.g. Munene et al. 1998; Ekanayake et al. 2006; Mbora and McPeek 2009), indicating that arboreality may indeed be regarded as a strategy to avoid intestinal parasites in some cases.

Social barriers against parasite transmission

While territorial defense is usually regarded as a means of protecting resources, it could also serve to limit direct contact between animals and to avoid the introduction of parasites into an animal’s home range (Hart 1990). Many animals have evolved ways of solving territorial conflicts without physical contact, thus avoiding costly injuries and possible direct infections (Marler 1976; Loehle 1995). Freeland (1979) studied the intestinal protozoan faunas of several species of primates and found that all individuals within a particular social group exhibited an identical composition of the protozoan fauna, while there were differences between groups, making the groups effectively “biological islands”. Thus, social groups can be seen as discrete units that facilitate transmission between group members, but “social barriers” reduce spread to individuals of other units (Freeland 1976). A study on pneumonia epidemics in bighorn lambs (Ovis canadensis) confirmed the idea of social barriers. Lamb mortality during epidemics was largely localized to certain ewe nursery groups, while other parts of the population appeared to be protected, indicating that social structuring constrains epidemic size (Manlove et al. 2014). In addition to social structuring and territorial defense, xenophobia, i.e. aggression towards unfamiliar individuals, may also serve as a barrier against parasite transmission. This behavior has been reported in many group-living animals, especially in primates (e.g. Berkson 1977; Nishida and Hiraiwa-Hasegawa 1985; Goodall 1986; Goodall 1991), but also in other

20 2. Literature Review

mammals such as rodents (Rowe and Redfern 1969; O’Riain and Jarvis 1997). The lengthy and stressful process of admitting a stranger into a group could serve to reveal the possible presence of latent infections in that animal, as the occasional admittance of foreign individuals is necessary to prevent inbreeding (Freeland 1976).

Grooming

Grooming is a widely employed behavior to remove ectoparasites such as ticks, lice and fleas (Hawlena et al. 2007; Akinyi et al. 2013), and experimentally restraining (self-)grooming behavior may lead to an increase in ectoparasite loads (Mooring et al. 1996). Additionally, oral grooming may also reduce the number of microparasites present on the body surface, as the presence of antibacterial substances, immunoglobulins and inflammatory cells in saliva has been demonstrated (Mandel 1987; Hart 2011). Accordingly, post-copulatory genital grooming has been associated with prevention of sexually transmitted diseases (Hart et al. 1987; Nunn and Altizer 2004). In primates, this behavior is especially common in lemurs and lorises, but a correlation with the degree of promiscuity in a species, as would be expected, could not be shown (Nunn 2003). While grooming may serve to eliminate some ectoparasites, it may at the same time increase oral intake of viruses, bacteria and other infectious agents present in the fur, especially if the animals use an oral grooming strategy (Clough et al. 2010). Furthermore, ectoparasites which are ingested during grooming may serve as intermediate hosts for endoparasites (Gillespie 2006), e.g. fleas are intermediate hosts for the cestode Dypilidium caninum (Eckert et al. 2008). Therefore, it is unclear how the hygienic function relates to other important functions of social grooming in primates, most importantly social integration, social bonding, and exchange for benefits, such as tolerance or mating opportunities (Seyfarth 1977; Barrett and Henzi 2001; Lewis 2010).

21 2. Literature Review

Linking theory with empirical data: Approaches to studying transmission in the wild

To improve and validate epidemiological models, as well as to shed more light on the costs, benefits and the evolutionary causes of animal sociality, it is important to assess whether animal behaviors, including different types of social contacts, are indeed meaningful predictors of transmission for a certain parasite. This calls for data on animal behavior and infection patterns that have been collected in the same population (Craft 2015). For this purpose, behavioral predictors, including an individual’s position and connectedness within a social network, can be statistically linked to infection status for a certain pathogen. For example, Drewe (2010) was able to show that the type and direction rather than the frequency of social interactions between individual meerkats (Suricatta suricatta) had a significant impact on Mycobacterium bovis infection. MacIntosh et al. (2012) showed that centrality in a grooming network was correlated with higher probability of infection with the nematode Strongyloides fuelleborni in Japanese macaques (Macaca fuscata). Furthermore, microbial genetic markers represent a particularly useful tool to measure transmission, which can be inferred if two animals carry the same or a genetically similar isolate (Archie and Theis 2011; Craft 2015). Suitable organisms for this approach include Salmonella enterica (Bull et al. 2012; Cowled et al. 2012), simian foamy virus (Blasse et al. 2013) and Escherichia coli, which has been used to study cross-species transmission (Goldberg et al. 2008; Rwego et al. 2008; VanderWaal et al. 2014) and, recently, to establish a correlation between social association patterns and transmission within species (VanderWaal et al. 2013b; Blyton et al. 2014).

Verreaux’s sifakas as a study system

Nine Propithecus species occur in Madagascar, and all members of the genus are group-living and, being vertical clingers and leapers, primarily arboreal (Mittermeier et al. 2008). Verreaux’s sifakas (Propithecus verreauxi, family Indriidae) are diurnal, folivorous and frugivorous primates of 3 – 4 kg body mass, inhabiting dry forests of southern and south- western Madagascar (Mittermeier et al. 2008; Kappeler and Fichtel 2012; Figure 1).

22 2. Literature Review

Figure 1: Distribution of the nine different Propithecus species. The location of the Propithecus verreauxi population studied (Kirindy Forest) is highlighted with a rectangle. Map modified from Mittermeier et al. (2010).

23 2. Literature Review

Behavioral ecology

Social organization, life histories, mating tactics, home-range use and intergroup relations of Verreaux’s sifakas have been studied extensively (e.g. Richard 1985; Richard et al. 1991; Richard et al. 2002; Benadi et al. 2008; Kappeler and Schäffler 2008; Kappeler and Fichtel 2012). At Kirindy Forest in central western Madagascar, where the German Primate Centre has operated a field station since 1993, 10 groups of Verreaux’s sifakas are currently habituated to observers and individually marked (Figure 2). They live in stable multi-male, multi-female groups of varying size; most groups containing 1 to 3 adult males and an equal number of females (Kappeler and Fichtel 2012). Males disperse from their natal group at approximately 3 to 5 years of age and may transfer between groups several times during their lives, sometimes roaming between groups without exclusive group membership for months or even years (Richard 1985; Richard et al. 2000; Kappeler and Fichtel 2012). Territoriality involves a moderate amount of intergroup aggression due to resource competition, but home ranges partly overlap, and physical contact between members of different groups during encounters is rare (Richard 1985; Benadi et al. 2008). Scent-marking is assumed to play a role in the communication between groups. For this purpose, anogenital and, in the case of males, sternal scent glands are rubbed against the bark of trees (Benadi et al. 2008). Overmarking of these signals occurs frequently within and between groups (Lewis 2005; Benadi et al. 2008) and has been evoked as a route of transmission for gastro-intestinal parasites (Irwin and Raharison 2009). In lemurs and lorises, a modification of the lower incisors and canines, called a “toothcomb”, is commonly used in auto- and allogrooming (Barton 1987; Sauther et al. 2002), in contrast to other primates which groom manually. While potentially serving to reduce ectoparasite load, oral grooming may enhance fecal-oral transmission of infectious agents (Clough et al. 2010). Due to their stable social organization into small groups, which can be observed and sampled simultaneously, the presence of home range overlap and roaming individuals, Verreaux’s sifakas represent an excellent primate system to study social influences on parasite spread.

24 2. Literature Review

Parasites of Verreaux’s sifakas

Little was known about the parasites of Verreaux’s sifakas at the beginning of this study. Although some lemur species have been subject to long-term field studies (e. g. Jolly 2012; Kappeler and Fichtel 2012; Sussman et al. 2012), their parasite taxonomy and ecology remain generally understudied (Irwin and Raharison 2009). Previous parasitological studies on Verreaux’s sifakas in other regions of Madagascar found little or no intestinal parasites (Muehlenbein et al. 2003; Loudon and Sauther 2013; Rasambainarivo et al. 2014). Therefore, it has been argued that their arboreal lifestyle prevents contact with infectious stages in the soil (Muehlenbein et al. 2003). However, a high prevalence of strongylid parasites has been found in Verreaux’s sifakas in Kirindy Forest (Rambeloson et al. 2014). Apart from intestinal parasites, ectoparasites such as mites and lice have been found parasitizing Verreaux’s sifakas (Rasambainarivo et al. 2014), and microfilaria and Plasmodium sp. have been identified in blood samples (Pacheco et al. 2011; Rasambainarivo et al. 2014). Further investigations into the diversity and epidemiology of these parasites are lacking, however. Therefore, as a basis to examine social influences on parasite spread, a detailed investigation into the occurrence, species diversity and prevalence of different parasites in Verreaux’s sifakas at Kirindy Forest was necessary. Additionally, these baseline data may help to provide insights into the role of infectious diseases as possible conservation threats for this endangered primate species, and into their zoonotic potential (Leendertz et al. 2006; Smith et al. 2009).

25 2. Literature Review

Figure 2: Verreaux’s sifakas (Propithecus verreauxi) at Kirindy Forest. The male in this photograph is wearing a GPS unit (yellow), while the female is collared with a radio unit to facilitate the location of the group.

26 3. Objectives and Structure of this Thesis

3. Objectives and Structure of this Thesis

In this thesis, I examine the links between host ecology, sociality and parasite infections in a wild population of Verreaux’s sifakas (Propithecus verreauxi), with a particular emphasis on social behavior. Because the impact of behavior on parasitism may differ considerably depending on the parasite’s life cycle and transmission mode, 3 different modes of parasite transmission were investigated: fecal-oral / environmental, direct host-to-host contact and vector-borne.

The objectives of the study were the following: 1. To characterize the parasite community of a wild population of Verreaux’s sifakas in their natural habitat in Madagascar, including intestinal parasites, ectoparasites and hemoparasites, as a necessary foundation for all subsequent analyses. 2. To identify the factors shaping population prevalence and individual probability of infection with each of these parasites, considering host traits, host behaviors and environmental factors, according to the relevant hypotheses for each mode of transmission. 3. To assess the relative importance of social versus environmental transmission with regard to those parasites that can be transmitted via environmental reservoirs.

Chapter 5 investigates the prevalence and diversity of intestinal parasites in the study population, as determined by microscopy of fecal samples, genotyping of nematode larvae and polymerase chain reaction (PCR) to detect DNA of potentially pathogenic zoonotic protozoa. Intestinal parasites are usually environmentally transmitted, but can also be transmitted through direct host-to-host contact, if infectious stages are present in the animals’ fur. Potential seasonal variation of parasite prevalence is examined in relation to seasonal variation in host behavior, along with the impact of host-traits such as animal age and sex. In chapter 6, Escherichia coli is used as a model organism to trace fecal-oral transmission, which is inferred based on the genetic relatedness of E. coli isolates from known individuals, to assess the relative importance of the animals’ social structure for transmission in relation to host traits and transmission from environmental reservoirs. The potential of E.

27 3. Objectives and Structure of this Thesis

coli spillover from humans into the population is also investigated based on patterns of antibiotic resistance. In chapter 7, ectoparasites (mites and lice) infecting Verreaux’s sifakas in Kirindy Forest are described, which rely on direct contact between hosts for transmission. The roles of group size, body contact and grooming behavior are investigated as predictors of infection, in relation to host characteristics and seasonal influences. Additionally, ectoparasite infections are assessed as predictors of self-grooming activity, which may indicate irritation and shed light on potential costs associated with ectoparasitism. Finally, because group-size is expected to influence the probability of infection with vector-borne parasites by means of an encounter-dilution effect, patterns of hemoparasite infections and their drivers – including host age and sex, host group-size, seasonality and parasite community interactions – are investigated, as well as their potential clinical impact (chapter 8).

28 4. Materials and Methods

4. Materials and Methods

Study site and study animals

The study was carried out in Kirindy Forest, western Madagascar, located at approximately 44°39’E, 20°03’S. The 90-ha study area is part of a field station operated by the German Primate Center within a forestry concession managed by the Centre National de Formation, d’Etudes et de Recherche en Environnement et Foresterie (CNFEREF). Kirindy Forest is a dry deciduous forest and subject to pronounced seasonality, with a long dry season usually lasting from April to October and a hot, wet season from November to March (Kappeler and Fichtel 2012). Eight different lemur species occur in Kirindy Forest, two of which, Verreaux’s sifakas (Propithecus verreauxi) and redfronted lemurs (Eulemur rufifrons), are diurnal (Kappeler and Fichtel 2012). The principal study population consisted of 8 adjacent social groups of Verreaux’s sifakas, ranging in size from 3 – 7 individuals, resulting in a total of 45 study individuals during the course of one year. Invasive samples were also obtained from members of two groups living approximately 2 km away from the main study area. Data from these individuals were included in all analyses which did not involve behavioral data. As part of an ongoing long-term study (Kappeler and Fichtel 2012), which has been approved by the Ministère des Eaux et Forêts of Madagascar and by the Ethics Committee of the German Primate Center, the animals are habituated to human observers and individually marked with unique collars, including radio (Holohil Systems, Carp, Ontario, Canada) and GPS (e-obs, Grünwald, Germany) units. Censuses of group membership are carried out 2 – 3 times a week (Kappeler and Fichtel 2012). All necessary research permits were obtained from the respective Malagasy and German authorities.

Remote data collection

One adult animal in each of the 8 adjacent groups was equipped with a GPS collar. Collars were set to simultaneously record GPS coordinates every 15 min, from 04:00 - 20:00 h local time. GPS data were collected from August to December 2013 and from March to July 2014.

29 4. Materials and Methods

Batteries lasted for approximately 4 months and animals had to be immobilized again to remove collars. GPS data were not available for the 2 groups living outside of the principal study area.

Calculation of home ranges and their overlaps

95 % kernel home ranges and their overlaps were calculated for bi-weekly intervals using the adehabitatHR package (Calenge 2006) in R version 3.0.2. To quantify space-use sharing between the different groups, i.e. how much the animals actually use the overlap area, the utilization distribution overlap index (UDOI) was calculated (Fieberg et al., 2005).

Estimation of intergroup encounter rates

To derive intergroup encounter rates from GPS data, the linear movement model contained in the R package movementAnalysis was employed (Sijben, 2013), assuming linear movement between subsequent location measurements. An encounter was inferred if two groups were in < 42 m distance based on the interpolated trajectories. The 42 m distance threshold was derived by calculating the mean distance between the groups’ GPS locations during directly observed intergroup encounters, based on an extended dataset of observations and GPS data collection over the course of one year (Flávia Koch de Vasconcellos, personal communication). A new encounter was recorded if the two GPS-bearing individuals from different groups were at a distance > 42 m for at least 30 min, until this threshold was crossed again. Encounter rates were calculated as encounters per day for bi-weekly intervals.

Behavioral observations

Direct observations using the focal animal method (Altmann 1974) were conducted during two periods, from August to October 2013 and from February to May 2014, on each member of the 8 adjacent social groups, excluding dependent infants. For simplicity, behavioral data collected during the first period will be referred to as “dry season” data and data collected during the second period as “wet season” data, even though this period extended into the beginning of the dry season. Focal animal observations were carried out in an alternating

30 4. Materials and Methods

order for 3 h in the morning (between 07:30 and 10:30 am) and 3 h in the afternoon (between 02:00 and 05:00 pm). For each focal animal, morning and afternoon sessions together made up one statistical day (i.e. 6 h of observation). Each animal was observed for 4 statistical days (2 per season) resulting in the collection of 860 focal hours (August – October 2013: 418 h, February – May 2014: 442 h). During observations, social behaviors (grooming, body contact and proximity of < 1 m) as well as non-social behaviors (feeding, locomotion, resting, defecation, contact with the soil) were recorded in a continuous manner. As allogrooming is a directed behavior, we recorded the identity of groomer and groomee. In the case of intergroup encounters, the identities and proportion of participating animals, all close contacts (i.e. grooming, body contact or proximity of < 1 m) between members of different groups and their durations as well as the total duration of the encounter were recorded ad libitum.

Invasive sampling

As part of the ongoing long-term study (Kappeler and Fichtel 2012), animals are regularly anesthetized for biomedical sampling and the fixation of collars. During the course of this study, 39 Verreaux’s sifakas (12 females and 27 males) were captured using either the Göttinger Mixture II (Rensing 1999; containing Ketavet® 100, Pfizer Deutschland GmbH, Berlin, Germany, 100 mg/ml; Rompun®, Bayer AG, Leverkusen, Germany; 20 mg/ml; and Atropinum Sulfuricum®, WdT eG, Garbsen, Germany; 10 mg/ml); a combination of ketamine (ketamine hydrochloride, Umedica Laboratories, Mumbai, India; 50 mg/ml) and xylazine (Xyla®, Interchemie, AC Castenray, The Netherlands; 20 mg/ml) or a combination of tiletamine and zolazepame (Zoletil 100®, Virbac S.A., Carros, France; 100 mg/ml), delivered intramuscularly via remote injection by using blowpipes and two-chambered compressed gas darts (Telinject®, Veterinärmedizinische Spezialgeräte GmbH, Dudenhofen, Germany). Dosages based on estimated body weights were the following: 5 mg/kg ketamine, 1 mg/kg xylazine, and 0.01 mg/kg atropine (Göttinger Mixture II), 5 mg/kg ketamine and 0.5 mg/kg xylazine or 8.33 mg/kg Zoletil® (Springer et al. 2015). During immobilization, a clinical examination was conducted and samples were taken as detailed in Table 1. Blood was collected from the femoral vein. 7 animals were repeatedly sampled during the study period, a maximum of 3 times.

4. Materials and Methods

Table 1: Overview of samples taken during animal captures. Number of Sample Storage medium Sample analysis individuals sampled Examination of blood smears, EDTAa / 2.5 ml blood packed cell volume, total plasma 36 RNAlaterb protein, PCRs

Rectal swab Amies mediumc microbiological culture 39

Ectoparasites 70 % ethanold microscopy 39

Anogenital microscopy 70 % ethanold 39 adhesive tape (detection of helminth eggs / mites) aS-Monovette®, K-EDTA, 2.7 ml, Sarstedt AG & Co, Nümbrecht, Germany bprepared by the Robert-Koch-Institute, Berlin, Germany cTranswab® Amies, Medical Wire and Equipment, Corsham, Wiltshire, UK dVWR International GmbH, Darmstadt, Germany

Noninvasive sampling

Fecal samples were collected from the ground within 2 min of observed defecation during 3 sample collection periods (April 2013, August – October 2013 and March – May 2014). As sifaka droppings are usually very firm and small in size, collection of the sample from the inside of the fecal matter was impossible. Droppings were therefore collected in total and environmental contamination cannot be completely excluded. All fecal samples were stored in RNAlater (prepared by the Robert-Koch-Institute, Berlin, Germany) at -20°C until shipment to Germany and molecular analysis. Additionally, 81 samples were stored in 10 % formalin (VWR International GmbH, Darmstadt, Germany) for parasitological analysis using flotation / sedimentation techniques (48 samples from April 2013 (end of the rainy season); 33 from October 2013 (end of the dry season)).

4. Materials and Methods

Overview of data collection

Month Invasive sampling Fecal sample Behavioral GPS data (no. of individuals) collection observations collection

March / April 2013 14  - -

August 2013 11   

September 2013 -   

October 2013 -   

November 2013 - - - 

February 2014 - -  -

March 2014 6   

April 2014 18   

May 2014 -   

June 2014 - - - 

Sample processing

Microscopy of fecal samples

Fecal wet mounts were prepared from a subset of 44 fresh fecal samples (25 samples in October 2013; 19 samples in May 2014) within 2 – 6 hours of sample collection. A small amount of feces was diluted in a drop of 0.9 % sodium-chloride solution (B. Braun Melsungen AG, Melsungen, Germany) on a microscope slide. A drop of methylene blue (AppliChem GmbH, Darmstadt, Germany) was added in order to stain protozoan trophozoites. A cover slip was placed on the preparation and the slide was scanned for parasite stages using a Zeiss Primo Star microscope (Carl Zeiss AG, Oberkochen, Germany). Photographs were taken with a Zeiss AxioCam ERc 5s. Measurements were made using the Zeiss Zen lite 2012 software after calibration with a stage micrometer. Seventy-five formalin-stored fecal samples were processed using both a modification of the formalin ethyl-acetate (F-EA) sedimentation technique (Ash and Orihel 1991; Clough

4. Materials and Methods

2010) and a flotation centrifugation technique using Sheather’s sucrose solution (Dryden et al. 2005). The remaining 6 fecal samples were too small to perform both techniques and were only tested using F-EA sedimentation. Before the sedimentation and flotation procedures, each sample was well homogenized. For the F-EA sedimentation, approximately 1 g of feces was diluted in 3 ml of 10 % formalin and strained through a nylon sieve into a 15 ml conical centrifuge tube. Formalin was added until the total volume reached 10 ml. After adding 3 ml of ethyl-acetate (Merck KGaA, Darmstadt, Germany), the tube was capped and shook for 30 seconds, then centrifuged at 1800 rpm for 8 min in a Hettich EBA 20 centrifuge (Andreas Hettich GmbH u. Co.KG, Tuttlingen, Germany). After removing the tube from the centrifuge, the top layer of fat and debris was loosened and the supernatant was discarded. The remaining sediment was filled up with 10 % formalin to a volume of 1.5 ml. After shaking the tube to aim for an equal distribution of eggs, a 60 µl drop of the sediment was placed on a microscope slide, mixed with a drop of Lugol’s solution (VWR International GmbH, Darmstadt, Germany) to achieve an iodine stain and covered with a cover slip. Sheather’s solution was prepared by dissolving 454 g of household sugar in 355 ml of hot water. Approximately 1 g of homogenized feces was mixed with 10 ml of this solution, poured through a nylon sieve into a 15 ml centrifuge tube and filled up with Sheather’s solution until almost full. Tubes were capped and centrifuged for 10 min at 2200 rpm in a Hettich EBA 20 centrifuge (Andreas Hettich GmbH u. Co.KG, Tuttlingen, Germany). After centrifugation, flotation solution was added until a slight positive meniscus formed. A cover slip was placed on top of the tube and transferred to a microscope slide after a minimum of 20 min. Parasite stages were identified based on morphological criteria following the key in Irwin and Raharison (2009).

Fecal cultures and preparation of helminth larvae for PCR

Fecal cultures were prepared from 44 samples using the Harada-Mori filter paper method (Ash and Orihel 1991) in October 2013 and May 2014. If fecal samples were very firm, they were mixed with filtered drinking water before being spread on the filter paper strip. Up to 7 filariform larvae were isolated per culture after an incubation period of 9 to 10 days and individually stored in 70 % ethanol (VWR International GmbH, Darmstadt, Germany).

4. Materials and Methods

Thirty-nine nematode larvae from fecal cultures of 17 different animals representing all 8 social groups were prepared for PCR using a lysis solution comprising 3 % Proteinase K (recombinant) (Roche Diagnostics Deutschland GmbH, Mannheim, Germany) in DirectPCR (Tail) Lysis Reagent (Viagen Biotech Inc., Los Angeles, CA, U.S.A) as described in Bisset et al. (2014). Individual larvae were transferred directly from ethanol into 10 µl of the lysis solution and incubated at 55°C for 16 h and 90°C for 1 h before storage at 4°C, using a FlexCycler thermal cycler (Analytic Jena, Jena, Germany). Before being used as a template in the PCR, the samples were diluted 1:2 with PCR-grade water (Merck KGaA, Darmstadt, Germany).

DNA extraction from fecal samples and PCRs

DNA was extracted from 236 RNAlater-stored fecal samples (approximately 1 sample per individual per month, all sampling periods) using the Roboklon EURx Gene Matrix Stool DNA Purification Kit (Roboklon GmbH, Berlin, Germany) according to the manufacturer’s instructions. Details of primers and cycling conditions for amplification of protozoan and strongyle DNA are provided in Table 2. Primers for Entamoeba sp. were selected to amplify DNA of E. dispar, E. histolytica and E. nuttalli, while primers for Cryptosporidium sp. allowed amplification of DNA from all members of the genus. Negative and positive controls (DNA of Cryptosporidium parvum, Entamoeba histolytica and Litomosoides sigmodontis) were included in all PCRs. All 25 µl PCR reactions contained 1 µl of DNA-template, 2.5 µl of 10x PCR buffer (Invitrogen, Karlsruhe, Germany), 2 µl of 50 mM MgCl2 (Invitrogen, Karlsruhe, Germany), 2 µl of 2.5 mM deoxynucleotide triphosphates (Thermo Scientific Fermentas, St. Leon-Rot, Germany), 0.5 µl of each primer (10µM) and 0.25 µl of Platinum Taq polymerase (Invitrogen, Karlsruhe, Germany). PCRs were run in a FlexCycler thermal cycler (Analytic Jena, Jena, Germany) and amplification was detected by electrophoresis on 1.5 % agarose gels. PCR products of the corresponding size were purified from agarose gels using the JETQUICK Gel Extraction Spin Kit (Genomed, Löhne, Germany) and Sanger sequencing of both strands was performed by Seqlab Sequence Laboratories Göttingen GmbH (Göttingen, Germany). Sequences were analyzed using Geneious v6.1.6 (Biomatters Ltd., Auckland, New Zealand) and compared to publicly available sequences using BLAST (Altschul et al. 1990).

4. Materials and Methods

Strongylid larvae Entamoeba Cryptosporidium Organism 2 Table

: PCR conditions conditions and PCR primers:

sp.

ITS + ITS 18S 18S rRNA 18S gene Target rRNA

240 120 1000 (bp) amplification Length of

for amplification of and protozoan strongyle amplification for DNA.

forward: forward: 5’ NC2 reverse: 5’ 5’ reverse: 5’ 5’ reverse: 5’ Primer forward: NC16 ------TTAGTTTCTTTTCCTCCGCT GCATCTTATAGCGATCATGG GCATAAGTAAAGTTTCTAG TCGTAGTTGGATTTCTGTT AGTTCAATCGCAATGGCTT AAGCACTCTAATTTTCTCA

- - - 3’ - - 3’ 3’ 3’ 3’ -

3’

cycles 40 cycles 50 cycles 40 Thermoprofile

72 °C 72 °C 55 °C 94 °C 94 °C 72°C 72°C 52 °C 95 °C 95 °C 72 °C 72 °C 55 °C 94 °C 94 °C

5 min 5 min 1 30 sec 30 sec min 3 min 7 30 sec 20 sec 20 sec 10 min 10 min min 1 30 sec 30 sec min 2

Lott et al. (2012) Chilton et al. (2003) References (1993) al. et Gasser (2011) al. et Richter

4. Materials and Methods

Escherichia coli isolation and multi-locus sequence-typing

Pre-cultivation of bacteria was undertaken in the field laboratory to maximize E. coli recovery: Rectal swabs were streaked within 48 h onto MacConkey and Columbia blood agar and used to inoculate glucose-containing nutrient broth (agar and broth: Oxoid GmbH, Wesel, Germany). Broth and agar plates were incubated for 24 to 32 h at 37°C in a Cultura M Mini- Incubator (Almedica AG, Giffers, Switzerland). After this first incubation period, broth was streaked onto both MacConkey and Columbia blood agar and incubated for another 24 h. To maximize recovery of E. coli, colonies were randomly picked from all 4 agar plates, dissolved in sterile 0.9 % sodium chloride solution (B. Braun Melsungen AG, Melsungen, Germany) with an addition of 20 % glycerol (Spinnrad GmbH, Bad Segeberg, Germany) and frozen at -20°C until shipment and further processing. For all individuals from which a rectal swab was not available, fecal samples were used to inoculate glucose-containing nutrient broth. After incubation of 24 to 32 h, an aliquot of the broth was frozen at -20°C with an addition of 20 % glycerol. In the laboratory of the Institute of Hygiene, University Clinic of Münster, Germany, samples were streaked out onto MacConkey and Columbia blood agar. After an incubation period of 24 – 48 h, colonies typical for E. coli were isolated and subjected to species identification using matrix-assisted laser desorption ionization time-of-flight mass- spectrometry (MALDI-ToF MS; Bruker GmbH, Bremen, Germany). Antimicrobial susceptibility testing was done by agar disc diffusion as recommended by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) applying EUCAST clinical breakpoints for categorization of susceptible, intermediate and resistant isolates. All isolates were tested for multidrug resistance due to the production of extended-spectrum beta- lactamases (ESBL) using a chromogenic agar plate (chromID™ESBL; Bio Mérieux, Marcy l’Etoile, France). Isolates belonging to ST131 were additionally tested for resistance against the following antibiotics: Ampicillin, Piperacillin, Cefuroxim, Cefotaxim, Cefpodoxim, Ceftazidim, Cefepime, Piperacin/Tazobactam, Imipenem, Meropenem, Ertapenem, Trimethoprim/Sulfamethoxazol, Tigecyclin, Gentamicin, Amikacin, Ciprofloxacin, Fosfomycin and Nitrofurantoin. For molecular subtyping, each isolate was characterized using MLST (Maiden et al. 1998). This typing method relies on determination of the sequence of internal fragments of 7

4. Materials and Methods

housekeeping genes (Wirth et al. 2006) and STs were assigned according to the E. coli MLST website (http://mlst.warwick.ac.uk/mlst/dbs/Ecoli). Sequences were further analyzed using the SeqSphere+ software version 1 (Ridom GmbH, Münster, Germany). The minimum spanning tree based on the MLST was generated also using the SeqSphere+ software.

Ectoparasites

Ectoparasites were mounted on microscope slides in a drop of Berlese mixture (Waldeck GmbH & Co. KG, Münster, Germany), covered with a coverslip and examined under a compound microscope. Photographs were taken with a Zeiss AxioCam ERc 5s fitted to a Zeiss Primo Star microscope (Carl Zeiss AG, Oberkochen, Germany). Measurements were made using the Zeiss Zen lite 2012 software after calibration with a stage micrometer. Identification was based on morphological criteria and followed Uilenberg et al. (1979) and Rodriguez et al. (2012) for ticks, Stobbe (1913) and Ferris (1933) for chewing lice and Bochkov and OConnor (2006), Bochkov et al. (2010) and Bochkov et al. (2015) for mites.

Analysis of blood samples and PCRs for hemoparasites

Packed cell volume was determined by centrifuging EDTA blood in a microhematocrit capillary using a Sigma 1-14 centrifuge (Sigma Laborzentrifugen GmbH, Osterode am Harz, Germany) and total plasma protein was estimated using a hand-held refractometer. Two to 3 blood smears were prepared per individual, air dried, stained (Diff Quick stain, Eberhard Lehmann GmbH, Berlin, Germany) and preserved with mounting medium (Eukitt, FLUKA Analytics, Sigma-Aldrich Chemie Gmbh, Munich, Germany) and a cover slip. Blood smears were scanned for the presence of hemoparasites and used for a differential white blood cell count to assess the percentages of the following leukocyte categories: Neutrophils, banded neutrophils, lymphocytes, monocytes, eosinophils and basophils. Photographs were taken with a Zeiss AxioCam ERc 5s fitted to a Zeiss Primo Star microscope (Carl Zeiss AG, Oberkochen, Germany) and measurements were made using the Zeiss Zen lite 2012 software. An aliquot of blood was mixed with the same amount of RNAlater and frozen at -20°C until shipment to Germany and further analysis. DNA was extracted from RNAlater-

4. Materials and Methods

preserved blood samples using the QIAmp Blood Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. To test for the presence of Plasmodium spp. in blood samples, a semi-nested PCR was carried out targeting an approximately 1000 bp long fragment of the parasite’s cytochrome b gene. In the first amplification round, primers P.sp.cytB F1 (5’-TGC CTA GAC GTA TTC CTG ATT ATC CAG; Kaiser et al. (2010)) and P.sp.cytB R1 (5’- CTT GTG GTA ATT GAC ATC CWA TCC; Kaiser et al. (2010)) were used, followed by P.sp.cytB F2 (5’-ATT GGD TCA ACW ATG ACT TTA TTT GG) and P.sp.cytB R1 in the second round. The 25 µl reaction mixture contained1 µl of DNA-extract or PCR-product (diluted 1:40) from the first round, respectively, 2.5 µl 10x PCR buffer (Invitrogen, Karlsruhe, Germany), 2 µl of 50 mM MgCl2 (Invitrogen, Karlsruhe, Germany), 2 µl of 2.5 mM deoxynucleotide triphosphates (Thermo Scientific Fermentas, St. Leon-Rot, Germany), 0.5 µl of each primer (10µM) and 0.2 µl of Platinum Taq polymerase (Invitrogen, Karlsruhe, Germany). The thermal profile was the same for both rounds, with an initial denaturation step at 95°C for 5 minutes followed by 40 cycles of 95°C for 30 seconds, 58°C for 45 seconds and 72°C for 60 seconds, and a final elongation step at 72°C for 10 minutes. PCR for Babesia spp. was carried out using primers BJ1 (5'-GTC TTG TAA TTG GAA TGA TGG-3') and BN2 (5'-TAG TTT ATG GTT AGG ACT ACG-3'), targeting a 500 bp long fragment of the 18S rRNA gene (Casati et al. 2006). 5 µl of DNA-extract were used in a 25 µl reaction mixture containing the same quantities of reagents as stated above. The thermal profile consisted of an initial denaturation step at 94°C for 10 minutes followed by 40 cycles of 94°C for 60 seconds, 55°C for 60 seconds and 72°C for 2 minutes, and a final elongation step at 72°C for 5 minutes. To generate sequences for microfilaria observed in blood smears, a nested PCR was employed targeting an approximately 900 bp long fragment spanning part of the 18S rRNA gene, the internal transcribed spacer 1 (ITS1) and part of the 5.8S rRNA gene. Primers used were NF1 (5’-GGT GGT GCA TGG CCG TTC TTA GTT-3’) (Porazinska et al. 2009) and NC2 (5’-TTA GTT TCT TTT CCT CCG CT-3’) (Gasser et al. 1993; Chilton et al. 2003) in the first round and a modification of ITS1-F (5’- TTG ATT ACG TCC CTG CCC-3’) (Vrain et al. 1992; Bisset et al. 2014) and the filaria-specific Di5.8S-R (5’-ACC CTC AAC CAG ACG TAC-3’) (Nuchprayoon et al. 2003; Nuchprayoon et al. 2005) in the second round. The

4. Materials and Methods

25 µl reaction mixture contained 5 µl of DNA-extract in the first round and 1 µl PCR-product (diluted 1:40) in the second round, and the same quantities of reagents as in the other PCRs. The thermal profile of the first round consisted of an initial denaturation step at 95°C for 5 minutes followed by 35 cycles of 94°C for 60 seconds, 58°C for 30 seconds and 72°C for 60 seconds, and a final elongation step at 72°C for 10 minutes. The thermal profile of the second round consisted of an initial denaturation step at 94°C for 10 minutes followed by 35 cycles of 94°C for 30 seconds, 55°C for 30 seconds and 72°C for 60 seconds, and a final elongation step at 72°C for 10 minutes. PCRs were run in a FlexCycler thermal cycler (Analytic Jena, Jena, Germany) and amplification products were detected by electrophoresis on 1.5 % agarose gels. Positive and negative controls were included in all PCRs. PCR products of the corresponding size were purified from 2 % agarose gels using the JETQUICK Gel Extraction Spin Kit (Genomed, Löhne, Germany) and Sanger sequencing of both strands was performed by Seqlab Sequence Laboratories Göttingen GmbH (Göttingen, Germany). Sequences were analyzed using Geneious v6.1.6 (Biomatters Ltd., Auckland, New Zealand) and compared to publicly available sequences using BLAST (Altschul et al. 1990). New sequences were deposited in the EMBL Nucleotide Sequence Database (Kulikova et al. 2004), under accession numbers LN869519 - LN869522.

Phylogenetic analyses

For the sequence isolated from nematode larvae, a maximum likelihood phylogenetic tree containing the isolated sequence and all publicly available ITS+ sequences from members of the superfamily Trichostrongyloidea was constructed using PhyML v3 (Guindon et al. 2010), as implemented on the PhyML webserver (Guindon et al. 2005), with smart model selection (SMS) based on Akaike Information Criterion (AIC). Branch robustness was assessed through non-parametric bootstrapping (500 bootstrapped pseudo-replicates). For Plasmodium, the two unique sequences identified in this study were put together with the representative sequences selected by Pacheco et al. (2011), which include all sequences derived from lemur Plasmodium available to this date. jModelTest v2.1.4 was used to identify the model of nucleotide substitution with the best fit to the data (GTR+I+G4;

4. Materials and Methods

(Darriba et al. 2012). A maximum likelihood tree was then constructed under this model using PhyML v3. Branch robustness was assessed through non-parametric bootstrapping (500 bootstrapped pseudo-replicates). Patristic distances were calculated using Geneious v6.1.6 (Biomatters Ltd.).

Statistical analyses

All statistical analyses were performed in R version 3.0.2 (R Core Team 2013). Data distributions were assessed graphically by inspecting histograms and quantile-quantile-plots. Mean values and standard deviations were calculated where appropriate. Social network analyses were performed in UCINET version 6.523 (Analytic Technologies, Harvard, MA, USA).

Ranging patterns and behavioral data

To compare rates of ground contact between seasons, the Wilcoxon signed rank test for paired data was employed as the data violated assumptions for parametric tests. Only those animals were included in the analyses that were present during both seasons. To analyze seasonal variation in home range size, linear mixed models (LMM) were constructed, controlling for group as a random factor. Significance of the LMM was assessed by comparison to a null model containing only the random effect in a likelihood ratio test using the R-function ANOVA with the argument ‘test’ set to ‘Chisq’. Based on the social interaction data, a weighted and directed social network was created for each season based on body contact, ingrooming and outgrooming rates (in min/h) between dyads, respectively. Individual degree centrality was calculated as the sum of an individual’s ties, whereas individual strength centrality was calculated as the sum of the weights of these ties. Individual outgrooming strength (i.e. the rate an individual spent allogrooming) and ingrooming strength (i.e. the rate of being groomed) were calculated as the sum of an individual’s weighted in- or outgoing ties, respectively. To assess sex differences in centrality measures, node-level permutation-based t-tests were employed. The permutation-based approach is necessary as behavioral measures of

4. Materials and Methods

actors in social networks are non-independent and thus violate assumptions for standard statistical tests (Croft et al. 2011). Permutation-based tests account for the non-independence of data points by generating a sampling distribution: The scores for the independent variables are randomly assigned to the network measure of interest while keeping the network structure and thus the interdependence of connections intact. The P-value can then be calculated as the proportion of permutations that produce a result as or more extreme than the one observed. To assess sex-differences in autogrooming rates, a nonparametric Wilcoxon rank sum test was used as the data violated assumptions of parametric tests.

Nematode infections

To assess whether the 2 fecal concentration methods (F-EA sedimentation and Sheather’s flotation) yielded comparable results, a McNemar’s test was used. To test whether hatching success in fecal cultures was significantly different between seasons, a χ²-test was employed. To assess possible influences of season, animal age and sex on the probability of being infected with Trichostrongylidae, a general linear-mixed model (GLMM) with binomial error structure and logit link function was constructed, controlling for animal ID nested in group as a random effect. Significance of the GLMM was assessed by comparison to a null model containing only the random effect in a likelihood ratio test using the R-function ANOVA with the argument ‘test’ set to ‘Chisq’.

Escherichia coli type sharing

A χ²-test was employed to test for significant differences in E. coli recovery rate between the two sampling methods, rectal swab and fecal sample. I then tested whether the number of sequence types (STs) isolated from an individual was significantly correlated with the animals’ age, the size of its’ social group and sampling effort, i.e. the number of samples that were taken from this individual, using Spearman rank correlations. I tested for differences in the number of STs between adult males and adult females using a Wilcoxon rank sum test. Based on the results of MLST genotyping, an E. coli transmission network was constructed by assigning a link to a dyad if the two animals shared the same ST or if their types differed only by 1 of the 7 genes (single locus variant) and can thus be considered

4. Materials and Methods

closely related. Links were unweighted, i.e. we neither made a distinction between the number of types that animals shared nor whether they shared the same or a closely related ST, and undirected as no assumptions about the direction of transmission were made. Animals from which no isolate was obtained were not included. To determine which factors influenced the likelihood of a link occurring in the transmission network, multiple regression quadratic assignment procedures (MR-QAP) were performed, which represent one of the methods of choice to test hypotheses on social networks (Mantel 1967; Hubert 1987; Krackhardt 1988; Croft et al. 2011). Because of the non-independence of network data, statistical methods that assume data independence are not appropriate (Croft et al. 2011). MR-QAP accounts for the non-independence by implementing permutations to establish P-values. It performs standard logistic regression and then uses a Monte Carlo procedure to randomly permute rows and columns of the network matrix (Dekker et al. 2007); a regression coefficient is then calculated for each permuted matrix to generate a reference distribution. The P-value refers to the proportion of randomly generated values that are more extreme than the observed correlation. Using MR-QAP analysis with double Dekker semipartialling (Dekker et al. 2007) and 2000 permutations, I investigated in a multivariate model whether the following factors - belonging to the same sex, - being born in the same year, - being born in the same social group, - being a member of the same social group at the point of sampling, - having been sampled in the same month and - having been sampled by the same method (rectal swab or fecal sample) influenced a dyad’s log-odds of having the same or a closely related E. coli ST. Including only the 8 neighboring groups, I further tested whether UDOIs and intergroup encounter rates were significantly correlated with E. coli type sharing between dyads belonging to different groups, controlling for birth cohort, sex, natal group, sampling month and sampling method. For UDOIs as well as encounter rates, the arithmetic mean of all bi-weekly measurements was used to best represent the relation between the two groups throughout the study period. Separate models were constructed for these two predictors because of their strong correlation.

4. Materials and Methods

Ectoparasite infections

GLMMs with binomial error structure and logit link function were used to test the influence of several predictor variables on chewing louse and mite infections. The complete dataset of 39 sampled individuals was used to test whether animal sex, age and season of sampling (wet or dry) had an influence on infections with either parasite, controlling for social group as a random factor. For the subset of those animals for which both behavioral data and parasite samples were available (N = 28), additional binomial GLMMs were constructed for each parasite, including group size, body contact strength and ingrooming strength of the sampled individual during the season in which the samples were taken as fixed factors and social group as a random factor. Full models were compared to null models comprising only the random effect in a likelihood ratio test using the R-function ANOVA with the argument ‘test’ set to ‘Chisq’. Furthermore, the impact of infection status on autogrooming rates was assessed in this dataset using a LMM, controlling for social group as a random effect. Self-grooming rates were log-transformed and significance of the model was assessed by comparison to a null model containing only the random effect in a likelihood ratio test using the R-function ANOVA with the argument ‘test’ set to ‘Chisq’.

Hemoparasite infections

GLMMs with binomial error structure and logit link function were used to analyze which factors influenced the probability of testing positive for each hemoparasite species. Sex, age, season (wet or dry) and size of the animal’s social group were included as fixed effects and individual identity nested in group as a random effect. Furthermore, a GLMM with Poisson error structure and log link function was employed to test influences on hemoparasite species richness, including the same fixed and random effects. Based on results of the GLMMs for Plasmodium and Babesia infections, another GLMM with binomial error structure was employed to test whether Babesia infection status had an effect on Plasmodium infection, again controlling for individual identity nested in group. To assess potential health impacts, I first tested whether age affected hematology values, using Spearman rank correlation, and then used LMMs to test influences of infection

4. Materials and Methods

with each hemoparasite and hemoparasite species richness on log-transformed packed cell volume, total plasma protein and the log-transformed neutrophil : lymphocyte ratio, controlling for animal age and individual identity nested in group as a random effect. Each full model was compared to a null model comprising only the random effect in a likelihood ratio test using the R-function ANOVA with the argument ‘test’ set to ‘Chisq’.

5. Manuscript 1: Intestinal Parasites

5. Manuscript 1:

Low diversity of intestinal parasites in an arboreal primate, Verreaux’s sifaka, at Kirindy Forest, Madagascar

Andrea Springera, Claudia Fichtela and Peter M. Kappelera,b

aBehavioral Ecology and Sociobiology Unit, German Primate Center, Kellnerweg 4, 37077 Göttingen, Germany bDepartment of Sociobiology and Anthropology, University of Göttingen, Kellnerweg 6, 30077 Göttingen, Germany

to be submitted

Keywords: intestinal parasites, Verreaux’s sifakas, Propithecus verreauxi, Trichostrongylidae, Cryptosporidium, Entamoeba, arboreality, parasite diversity, ITS+

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Abstract

Intestinal helminths and protozoa may impact health and reproductive fitness of wild animals substantially. Investigating patterns of parasite occurrence and prevalence in wild animal populations may enhance our insights into the ecological and evolutionary impacts these parasites have on their hosts, as well as into potential pathogen spillover events associated with anthropogenic influences. Prevalence patterns may be influenced by host traits impacting immune function, such as age and sex, as well as by seasonal differences in climatic conditions, host behavior and immunity, and seasonal birth pulses. Here, intestinal parasitism was investigated in a population of Verreaux’s sifakas (Propithecus verreauxi), an endangered, arboreal primate species living in a markedly seasonal habitat in western Madagascar. Microscopy of fecal samples from 45 individuals and two seasons was combined with genotyping of cultured nematode larvae to assess the species diversity of intestinal helminths. Additionally, fecal DNA extracts were tested for the presence of two potentially zoonotic protozoa, Cryptosporidium sp. and Entamoeba sp., by polymerase chain reaction (PCR). Only one species of helminths, belonging to the family Trichostrongylidae, was discovered, at high prevalence both during the dry and during the wet season. Neither animal age, sex nor season significantly influenced the probability of Trichostrongylidae infection, despite seasonal variation in climatic conditions as well as ranging behavior. Cryptosporidium sp. infections were not discovered, while only a small fraction of samples was positive for Entamoeba sp. The low diversity of intestinal parasites indicates that the predominantly arboreal lifestyle of Verreaux’s sifakas may protect them from environmentally transmitted parasites, while the high prevalence of Trichostrongylidae, which mature to infectiousness in the environment, despite low levels of ground contact suggests that social contact and oral grooming may play a role in the transmission of this parasite.

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Introduction

Intestinal helminths and protozoa may impact host health and reproductive fitness substantially (Hudson et al. 1992; Hudson et al. 1998; Hillegass et al. 2010). Prevalence patterns may be influenced by host traits impacting immune function, such as age and sex, as well as by seasonal differences in climatic conditions, host behavior and immunity, and seasonal birth pulses (Cattadori et al. 2005; Altizer et al. 2006; Martin et al. 2008). Understanding these patterns in wildlife may enhance our insight into the ecological and evolutionary impacts intestinal parasites have on their hosts (Tompkins et al. 2011), and may be critical in order to predict parasite abundance in response to climate change (Altizer et al. 2006). In addition, the presence of zoonotic pathogens may indicate potential cross-species transmission at the human-wildlife interface (Gillespie 2006; Leendertz et al. 2006). Once acquired, infections with intestinal helminths are usually chronic. In humans, prevalence increases from birth to adulthood as susceptible individuals become infected, and then reaches a plateau. Individual parasite burdens may then decrease with age due to the development of partial immunity (Woolhouse 1998; Hayes et al. 2004; Galvani 2005). Regarding intestinal protozoa, development of protective immunity may limit or prevent secondary infections (Okhuysen et al. 1998; da Silva et al. 2003; Haque et al. 2006; Gates and Nolan 2009) and therefore, prevalence is expected to be higher in juveniles than adults. Furthermore, sex differences in intestinal parasite infections have been noted in many mammal species (Klein 2004), and it has been proposed that males usually experience higher parasitism than females due to immunosuppressive effects of androgens as well as body mass differences (Poulin 1996; Zuk and McKean 1996; Klein 2004). Because environmental parasite stages usually develop and survive less well in dry and cold conditions (Banks et al. 1990; O’Connor et al. 2006; Ramos et al. 2013), hosts living in seasonal environments are expected to encounter more infective stages during warm and moist months than during dry seasons. Seasonally elevated parasite exposure may translate into seasonal peaks in incidence rates (Turner and Getz 2010). Seasonal rises in mortality, often tied to the wet season, have been reported for several primate species, and may in part be due to seasonally elevated parasite pressure (Gogarten et al. 2012). In addition to climatic factors, variation in host behavior may also mitigate seasonally increased parasite exposure, for example when hosts aggregate or adjust their ranging behavior in response to resource

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availability (Altizer et al. 2006; Altizer et al. 2011; Nunn et al. 2014b). Specifically, more intensive ranging has been related to higher prevalences and increased species-richness of fecal-orally transmitted parasites (Ezenwa 2004a; Nunn and Dokey 2006; Nunn et al. 2011). Furthermore, seasonal energy deprivation or trade-offs with reproduction may lead to the suppression of immune function (Martin et al. 2008), and seasonal reproduction may release pulses of susceptible animals into the population, thus decreasing herd immunity (Altizer et al. 2006). We investigated infections with intestinal parasites in relation to seasonal changes in animal behavior and ranging patterns in a wild population of lemurs, Verreaux’s sifakas (Propithecus verreauxi). These diurnal, predominantly folivorous primates inhabit highly seasonal habitats in southern and south-western Madagascar, where they reproduce seasonally (Brockman and Whitten 1996). They live in multi-male, multi-female groups of varying size and display territoriality with moderate home range overlap and frequent intergroup encounters (Richard 1985; Benadi et al. 2008). In previous studies at other study sites, little or no intestinal parasites have been found, leading to the hypothesis that the animals’ arboreal lifestyle limits contact with infectious parasite stages (Muehlenbein et al. 2003; Loudon and Sauther 2013). However, a previous study conducted at our study site has revealed a high prevalence of strongyle nematodes (Rambeloson et al. 2014). Here, we combined microscopy of fecal samples with genetic analyses to assess intestinal parasitism during two rainy and one dry season. Fecal samples were screened for parasite stages using direct wet mounts, sedimentation and flotation techniques and nematode larvae were cultured and genotyped to assess potential cryptic species diversity. Because the study population is subject to frequent visits of researchers, tourists and occasionally villagers and their livestock, fecal DNA extracts were additionally tested for the presence of potentially zoonotic Entamoeba histolytica / nuttalli and Cryptosporidium sp. using PCR, which is generally more sensitive for the detection of protozoa than conventional microscopy (Webster et al. 1996; Stensvold and Nielsen 2012). Both Entamoeba sp. and Cryptosporidium sp. may cause disease in captive sifakas (Charles-Smith et al. 2010; Williams 2015). The presence of Cryptosporidium sp. has recently been noted in wild lemurs, which might indicate pathogen spillover due to anthropogenic disturbance (Rasambainarivo et al. 2013).

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We expected prevalence of intestinal helminths to increase with age, while protozoa were expected to be more common in young animals than adults. Additionally, we expected prevalences to be higher during the wet season due to increased survival of environmental parasite stages. If sex influences parasite susceptibility, we expected males to harbor more parasites than females.

Materials and methods

Behavioral observations and GPS data collection

The study was carried out in Kirindy Forest, Western Madagascar, located at approximately 44°39’E, 20°03’S. The 90 ha study area is part of a field station operated by the German Primate Center within a forestry concession managed by the Centre National de Formation, d’Etudes et de Recherche en Environnement et Foresterie (CNFEREF). Kirindy Forest is a dry deciduous forest and subject to pronounced seasonality, with a long dry season usually lasting from April to October and a hot, wet season from November to March (Kappeler and Fichtel 2012). Eight adjacent social groups of Verreaux’s sifakas were studied, ranging in size from 3 to 7 individuals, comprising a total of 45 individuals during the course of one year. As part of an ongoing long-term study (Kappeler and Fichtel 2012), which has been approved by the Ministère des Eaux et Forêts of Madagascar and by the Ethics Committee of the German Primate Center, the animals are habituated to human observers and individually marked. All necessary research permits were obtained from the respective Malagasy and German authorities. Direct observations using the focal animal method were conducted during two periods, from August to October 2013 and from February to May 2014, on each member of the study population, excluding dependent infants. For simplicity, we will refer to behavioral data collected during the first period as “dry season” data and during the second period as “wet season” data, even though this period extended into the beginning of the dry season. Focal animal observations were carried out in an alternating order for 3 h in the morning (between 07:30 and 10:30 am) and 3 h in the afternoon (between 02:00 and 05:00 pm). For each focal

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animal, morning and afternoon sessions together made up one statistical day (i.e. 6 h of observation). We observed each animal for 4 statistical days (2 per season) resulting in the collection of 860 focal hours (August – October 2013: 418 h, February – May 2014: 442 h). During observations, we recorded social behaviors (grooming, body contact and proximity of one meter or less), as well as non-social behaviors (feeding, locomotion, resting, defecation, contact with the soil) in a continuous manner. To assess home range use, one animal in each of the 8 groups, usually the dominant male, was equipped with a GPS collar (e-obs GmbH, 82031 Grünwald, Germany). Collars were set to simultaneously record GPS coordinates every 15 minutes, starting at 04:00 am local time until 08:00 pm local time. As Verreaux’s sifakas remain stationary on their sleeping tree during the night, locations were not recorded between 08:00 pm and 04:00 am. Batteries lasted for approximately 4 months and animals had to be immobilized again to remove collars. GPS data were collected from August to December 2013 and from March to July 2014. Season was classified as “dry” until mid-October and as “wet” until mid-April. In order to assess temporal variation of space use, bi-weekly 95 % kernel home ranges were calculated using the adehabitatHR package (Calenge 2006) in R (R version 3.0.2, R Core Team 2013).

Sample collection, wet mounts and preparation of fecal cultures

Fecal samples were collected from the ground within 2 minutes of observed defecation during 3 sample collection periods (April 2013, August – October 2013 and March – May 2014). As sifaka droppings are usually very firm and small in size, collection of the sample from the inside of the fecal matter was impossible; droppings were therefore collected in total. All fecal samples were stored in RNAlater at -20°C until shipment to Germany and molecular analysis. Additionally, 81 samples were stored in 10 % formalin for parasitological analysis using flotation / sedimentation techniques (48 samples from April 2013 (end of the rainy season); 33 from October 2013 (end of the dry season)). Fecal wet mounts were prepared from a subset of 44 unpreserved fecal samples (25 samples in October 2013; 19 samples in May 2014) within 2 – 6 hours of sample collection. A small amount of feces was diluted in a drop of 0.9 % sodium-chloride solution on a microscope slide. A drop of methylene blue was added in order to stain protozoan

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trophozoites. A cover slip was placed on the preparation and the slide was scanned for parasites using a Zeiss Primo Star microscope (Carl Zeiss AG, Oberkochen, Germany). Photographs were taken with a Zeiss AxioCam ERc 5s. Measurements were made using the Zeiss Zen lite 2012 software after calibration with a stage micrometer. Fecal cultures were prepared from the same 44 samples using the Harada-Mori filter paper method (Ash and Orihel 1991). If fecal samples were very firm, they were mixed with filtered drinking water before being spread on the filter paper strip. Up to 7 filariform larvae were isolated per culture after an incubation period of 9 to 10 days and individually stored in 70 % ethanol. During routine animal captures, the perianal region of 39 anesthetized animals was sampled for oxyurid eggs using clear adhesive tape. The tape was examined microscopically on the day of sampling.

Sedimentation and flotation

Several flotation and sedimentation techniques exist for the diagnosis of parasite infections from non-invasively collected fecal samples. The formalin-ethyl acetate (F-EA) sedimentation technique is commonly used to recover helminth eggs from formalin-fixed fecal samples of wild primates (e.g. Clough 2010; Muehlenbein and Watts 2010; Pebsworth et al. 2012). This technique results in the sedimentation of eggs, larvae and protozoa on the bottom of the test tube during centrifugation (Ash and Orihel 1991). Among flotation solutions, Sheather’s solution has the highest specific gravity (1.27 - 1.3, Dryden et al. 2005) and should therefore allow most helminth eggs and protozoa to float, even if their specific gravity has been altered by formalin-storage (Baker 2008). Seventy-five formalin-stored fecal samples were processed using both a modification of the F-EA technique (Ash and Orihel 1991; Clough 2010) and a flotation centrifugation technique using Sheather’s solution (Dryden et al. 2005). The remaining 6 fecal samples were too small to perform both techniques and were only tested using F-EA. Before the sedimentation and flotation procedures, each sample was well homogenized.

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Formalin-ethyl acetate sedimentation

Approximately 1 g of feces was diluted in 3 ml of 10 % formalin and strained through a nylon sieve into a 15 ml conical centrifuge tube. Formalin was added until the total volume reached 10 ml. After adding 3 ml of ethyl-acetate, the tube was capped and shook for 30 seconds, then centrifuged at 1800 rpm for 8 min. After removing the tube from the centrifuge, the top layer of fat and debris was loosened and the supernatant was discarded. The remaining sediment was filled up with 10 % formalin to a volume of 1.5 ml. After shaking the tube to aim for an equal distribution of eggs, a 60 µl drop of the sediment was placed on a microscope slide, mixed with a drop of Lugol’s solution to achieve an iodine stain and covered with a cover slip.

Sheather’s flotation

Sheather’s solution was prepared by dissolving 454 g of sugar in 355 ml of hot water. Approximately 1 g of homogenized feces was mixed with 10 ml of this solution, poured through a nylon sieve into a 15 ml centrifuge tube and filled up with Sheather’s solution until almost full. Tubes were capped and centrifuged for 10 min at 2200 rpm. After centrifugation, flotation solution was added until a slight positive meniscus formed. A cover slip was placed on top of the tube and transferred to a microscope slide after a minimum of 20 min. Parasite stages were identified based on morphological criteria following the key in Irwin and Raharison (2009).

DNA extraction and PCRs

DNA was extracted from 236 fecal samples (approximately 1 sample per individual per month, all sampling periods) using the Roboklon EURx Gene Matrix Stool DNA Purification Kit (Roboklon GmbH, Berlin, Germany) according to the manufacturer’s instructions. Additionally, 39 nematode larvae from fecal cultures of 17 different animals representing all 8 social groups were prepared for PCR using a lysis solution comprising 3 % Proteinase K (recombinant) (Roche Diagnostics Deutschland GmbH, Mannheim, Germany) in DirectPCR (Tail) Lysis Reagent (Viagen Biotech Inc., Los Angeles, CA, U.S.A) as described in Bisset et al. (2014). Individual larvae were transferred directly from ethanol into 10 µl of the lysis

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solution and incubated at 55°C for 16 h and 90°C for 1 h before storage at 4°C, using a FlexCycler thermal cycler (Analytic Jena, Jena, Germany). Before being used as a template in the PCR, the samples were diluted 1:2 with PCR-grade water. Details of primers and cycling conditions for amplification of protozoan and strongyle DNA are provided in Table 1. Primers for Entamoeba sp. were selected to amplify DNA of E. dispar, E. histolytica and E. nuttalli, while primers for Cryptosporidium sp. allowed amplification of DNA from all members of the genus. Negative and positive controls (DNA of Cryptosporidium parvum, Entamoeba histolytica and Litomosoides sigmodontis) were included in all PCRs. All 25 µl PCR reactions contained 1 µl of DNA-template, 2.5 µl of 10x

PCR buffer (Invitrogen, Karlsruhe, Germany), 2 µl of 50 mM MgCl2 (Invitrogen, Karlsruhe, Germany), 2 µl of 2.5 mM deoxynucleotide triphosphates (Thermo Scientific Fermentas, St. Leon-Rot, Germany), 0.5 µl of each primer (10µM) and 0.25 µl of Platinum Taq polymerase (Invitrogen, Karlsruhe, Germany). PCRs were run in a FlexCycler thermal cycler (Analytic Jena, Jena, Germany) and amplification was detected by electrophoresis on 1.5 % agarose gels. PCR products of the corresponding size were purified from agarose gels using the JETQUICK Gel Extraction Spin Kit (Genomed, Löhne, Germany) and Sanger sequencing of both strands was performed by Seqlab Sequence Laboratories Göttingen GmbH (Göttingen, Germany). Sequences were analyzed using Geneious v6.1.6 (Biomatters Ltd., Auckland, New Zealand) and compared to publicly available sequences using BLAST (Altschul et al. 1990). For the sequence isolated from strongyle larvae, a maximum likelihood phylogenetic tree containing the isolated sequence and all publicly available ITS+ sequences from members of the superfamily Trichostrongyloidea was constructed using PhyML v3 (Guindon et al. 2010), as implemented on the PhyML webserver (Guindon et al. 2005), with smart model selection (SMS) based on Akaike Information Criterion (AIC). Branch robustness was assessed through non-parametric bootstrapping (500 bootstrapped pseudo-replicates).

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Richter et al. (2011) Gasser et al. (1993) References (2003) al. et Chilton (2012) al. et Lott

2 min 30 sec 30 sec 1 min 10 min 10 min 20 sec 20 sec 30 sec 7 min 3 min 30 sec 30 sec 1 min 5 min

94 °C 94 °C 55 °C 72 °C 72 °C 95 °C 95 °C 52 °C 72°C 72°C 94 °C 94 °C 55 °C 72 °C 72 °C

Thermoprofile 40 cycles 50 cycles 40 cycles

3’

- 3’ 3’ 3’ 3’ - - 3’ - - -

AAGCACTCTAATTTTCTCA AGTTCAATCGCAATGGCTT TCGTAGTTGGATTTCTGTT GCATAAGTAAAGTTTCTAG GCATCTTATAGCGATCATGG TTAGTTTCTTTTCCTCCGCT ------Primer 5’ reverse: 5’ 5’ reverse: 5’ NC16 forward: 5’ reverse: NC2 5’ forward: forward: for amplification of protozoan and strongyle DNA. for amplification strongyle protozoan and of

Length of of Length amplification (bp) 1000 120 240

Target gene 18S rRNA 18S rRNA ITS +

sp.

: primers PCRand conditions

Table 1 Organism Cryptosporidium Entamoeba larvae Strongylid

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Statistical analyses

To compare rates of ground contact between seasons, the Wilcoxon signed rank test for paired data was employed as the data violated assumptions for parametric tests. Only those animals were included in the analyses that were present during both seasons. To analyze seasonal variation in home range size, linear mixed models (LMM) were constructed, controlling for group as a random factor. To assess whether the two fecal concentration methods (F-EA sedimentation and Sheather’s flotation) yielded comparable results, a McNemar’s test was employed. To test whether hatching success in fecal cultures was significantly different between seasons, a χ²- test was employed. To assess possible influences of season, animal age and sex on the probability of being infected with Trichostrongylidae, a general linear-mixed model (GLMM) with binomial error structure and logit link function was constructed, controlling for animal ID nested in group as a random effect. Significance of LMMs and GLMMs was assessed by comparison to a null model containing only the random effect in a likelihood ratio test using the R-function ANOVA with the argument ‘test’ set to ‘Chisq’. All statistical analyses were performed in R v. 3.0.2 (R Core Team 2013). Because the relationship between fecal egg counts (FEC) and infection intensity is unclear in the study species, no statistical analyses using FEC were performed.

Results

Seasonal changes in animal behavior

Ground contact rates were low, ranging from 0 to 4.3 minutes per observational hour. During the wet season, only 9 of 38 animals were observed to go to the ground at all, while 19 of 36 animals had some ground contact during the dry season. Animals spent significantly more time on the ground during the dry season (Wilcoxon signed rank test for paired data, N = 32, P = 0.012). Bi-weekly 95 % kernel home ranges were significantly smaller during the dry season (LMM, χ² = 38.74, df = 1, P < 0.001, Table 2), indicating an increased ranging intensity.

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Table 2: Results of LMM testing the influence of season on bi-weekly 95 % kernel home ranges (ha). Significant P-values (< 0.05) are printed in bold.

Term Estimate Standard error df t P

Intercept 9.4 0.99 7.86 9.44 < 0.001

Season (wet) 3.65 0.52 79.04 7.02 < 0.001

Helminth infections

Most fecal samples were firm, except for 3 samples with soft consistency from March and April 2014. No parasites were macroscopically observed in feces. In fecal wet mounts, as well as after F-EA sedimentation and Sheather’s flotation, only strongylid eggs containing a morula or a larva (from 5 h after defecation on, Figure 1) were observed. Regarding presence of parasite eggs, both the flotation and the sedimentation technique resulted in almost the same rate of false-negatives (i.e. negative with one method, but positive with the other, 11 and 12 of 75 samples, respectively) and were thus equally sensitive (McNemar’s test: McNemar's χ² = 0, df = 1, N = 75, P = 1). To assess individual infection status, the results of both techniques were combined. Egg counts were low (1 – 7 eggs per 60 µl sediment, 1 – 28 eggs per slide using the flotation method). No oxyurid eggs were found attached to the perianal region of anesthetized individuals. In the dry season, larvae developed in only 9 of 25 fecal cultures, whereas in the rainy season, 13 of 19 fecal cultures yielded larvae after 10 days of incubation. However, this difference was not statistically significant (χ²-Test, χ² = 3.33, df= 1, P = 0.07). All larvae had a filariform phenotype. Filariform larvae were detected after as early as 4 days. All 39 larvae sequenced showed 99.9 % sequence identity and can thus be considered as belonging to the same species, which groups within the family Trichostrongylidae (Figure 2). No other sequences from Trichostrongylidae parasites recovered from lemurs have been publicly available to date, precluding any comparison or species identification. Prevalence of infection with Trichostrongylidae was 89 % in April 2013 and 96 % in October 2013. Neither season,

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nor animal age or sex significantly influenced infection status (GLMM, χ² = 4.65, df = 3, P = 0.19, Table 3).

Figure 1: Typical strongylid eggs discovered in fecal wet mounts of Verreaux’s sifakas at Kirindy Forest. Eggs contained a morula (left) or a larva (right, at > 5 hours after defecation).

Table 3: Results of GLMM testing the influence of animal age, sex and season on the probability of infection with Trichostrongylidae parasites. Significant P-values (< 0.05) are printed in bold.

Term Estimate Standard error z P

Intercept 3.48 1.73 2 0.045

Sex -0.21 1.04 -0.2 0.845

Age 0.1 0.12 0.9 0.37

Season (wet) -1.78 1.26 -1.41 0.158

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publicly available ITS+ (ITS, members publicly available of belonging 5.8S, sequences of ITS+ ITS2) tree likelihood Maximum 2: Figure with a inis Thediscovered this highlighted rectangle. sequence study Trichostrongyloidea. tosuperfamily the The scale is in substitutions per site. per substitutions in is scale The

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Protozoan infections

Two hundred and thirty-six fecal DNA extracts (approx. 1 sample per individual / month) were tested for the presence of Entamoeba sp. using PCR. 17 samples were positive for Entamoeba histolytica and / or Entamoeba nuttalli, which show 100 % sequence identity in the amplified region. DNA of non-pathogenic Entamoeba dispar was not detected. Only two samples from the dry season of 2013 were positive, and the same individuals were tested negative in subsequent samples from the dry season. The remaining positive samples were from March 2014, and belonged to individuals across all social groups and age-classes. Only one individual was tested positive twice. One hundred and thirty-two samples were tested for the presence of Cryptosporidium sp., and all of them were negative as sequences obtained from bands at the right height showed no significant similarity to publicly available Cryptosporidium sequences. Eight samples did not result in any PCR product, neither in the Entamoeba- nor in the Cryptosporidium-PCR, probably due to fecal PCR-inhibitors.

Discussion

In comparison to several sympatric lemur species, Verreaux’s sifakas in Kirindy Forest showed little intestinal parasitism: Only eggs of a strongylid morphotype were discovered in fecal samples, and genotyping of cultured third-stage larvae suggested that they belong to only one helminth species. In contrast, red-fronted lemurs (Eulemur rufifrons) from the same field site were found to shed 10 different morphotypes of intestinal parasites, including 6 nematodes, 1 trematode, 1 cestode, and 2 protozoans (Clough 2010), and sympatric mouse lemurs (Microcebus murinus) and fat-tailed dwarf lemurs (Cheirogeleus medius) show a similar parasite diversity (Schwensow et al. 2010). Oxyurid nematodes, which were detected in Verreaux’s sifakas at two other field sites in Madagascar (Loudon and Sauther 2013; Rasambainarivo et al. 2014), were not found in this study, neither in fecal samples nor attached to the perianal region of hosts. Parasitic protozoa have not been detected in fecal samples of wild sifakas before (Loudon and Sauther 2013; Rasambainarivo et al. 2013; Rasambainarivo et al. 2014) and the

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samples examined in this study were microscopically negative. PCR is regarded as a more sensitive method for the detection for protozoan infections (Webster et al. 1996; Stensvold and Nielsen 2012), and Entamoeba DNA was discovered in a small fraction of samples, almost exclusively from March 2014. Therefore, it is possible that potentially pathogenic Entamoeba infections, either with E. histolytica or E. nuttalli, were prevalent in the population during this month, affecting all social groups, but were then eliminated as all further samples from the same individuals were negative. Unfortunately, samples from November 2013 through February 2014 were not available, so that the possible duration of infections, their clinical impact and potential source could not be determined. In March 2014, all animals appeared clinically healthy and all samples tested had a firm consistency. At this stage, laboratory contamination as an alternative explanation for the presence of Entamoeba DNA cannot be excluded, as almost all positive samples were extracted on the same day, and the majority of samples from each individual was negative. Further studies are needed to confirm the occasional presence of Entamoeba in the population, and to determine whether the species in question is E. histolytica or E. nuttalli. These species do not differ in the genetic sequence analyzed here, and may both be pathogenic for primates (Tachibana et al. 2007). All samples tested were negative for Cryptosporidium DNA. As Cryptosporidium sp. causes high morbidity and may lead to mortality in captive sifakas (Charles-Smith et al. 2010), but all animals sampled appeared clinically healthy, this was not a surprise. We still tested for this parasite, because Cryptosporidium is prevalent in livestock as well as humans in Madagascar (Areeshi et al. 2008; Bodager et al. 2015), and Cryptosporidium-shedding wild lemurs have been found in another region of Madagascar (Rasambainarivo et al. 2013), although the sifakas (Propithecus edwardsi) tested were negative. It has been argued before that the arboreal lifestyle and folivory of sifakas may protect them from many intestinal parasites, including soil-born helminthiases and those transmitted by ingestion of intermediate hosts (Loudon and Sauther 2013). The transmission modes of Trichostrongylidae species parasitizing lemurs remain unknown (Irwin and Raharison 2009), but generally larvae of Trichostrongylidae hatch in the environment and need several days to develop into third-stage larvae, which are then infective (Bush 2001). Larvae in this study hatched after approximately 5 to 6 hours after defecation and developed into filariform larvae within 9 to 10 days. Although only one Trichostrongylidae species was discovered,

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prevalence of this single species was very high. Fecal-oral transmission of parasite stages between sifakas may be enhanced via oral grooming, which may explain the high prevalence despite little time spent on the ground. Sifakas, like all other lemurs, groom each other orally, making use of their toothcomb (Eaglen 1980). Infective parasite larvae may be present in the fur of one animal due to contact with the ground, and then spread within a social group via allogrooming. Motile larvae may be more likely to attach to the fur of hosts than helminth eggs because of active host seeking and “nictation behavior”, during which larvae raise their body in response to olfactory cues emitted by potential hosts (Lee 2010; Dillman et al. 2012; MacIntosh et al. 2012). Accordingly, in Japanese macaques a central position within a grooming network was a significant predictor of infection with two nematode species whose infectious stages are motile larvae, while infection with Trichuris sp., which is transmitted by ingestion of eggs, was not influenced by grooming behavior (MacIntosh et al. 2012). Active host seeking and attachment to fur, leading to social transmission, constitutes a likely explanation for the high prevalence of the Trichostrongylidae species discovered here, despite the arboreal behavior of Verreaux’s sifakas, while no other intestinal helminths were found. There were no effects of animal age or sex on nematode infections. Animals as young as one year were infected with Trichostrongylidae, and probably sustain a chronic infection, as expected. Because Verreaux’s sifakas do not display a sexual dimorphism in size and, like other lemurs with female dominance, exhibit smaller sex differences in androgen levels than other mammals (von Engelhard et al. 2000; Drea 2007), the absence of sex differences in parasite infections was also not surprising. We expected to find lower prevalences of nematode infections during the dry season as opposed to the wet season because hatching and survival of nematode larvae are generally favored by warm and moist conditions while they are sensitive to cold temperatures and desiccation (e.g. Banks et al. 1990; Besier and Dunsmore 1993; O’Connor et al. 2006; Ramos et al. 2013). Turner and Getz (2010) found strong seasonality for Strongylida infections in ungulates in Namibia, with more animals being infected during the wet season. In our study, a higher proportion of fecal cultures resulted in hatching of larvae in the wet season as compared to the dry season, although the difference was not statistically significant. However, we could not find a seasonal difference in prevalence of Trichostrongylidae in Verreaux’s sifakas. First of all, while parasite development might be facilitated during the

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wet season, animals spent significantly more time on the ground and constricted their home ranges during the dry season, potentially increasing contact with infectious parasite stages. Additionally, it has been shown for diademed sifakas (Propithecus diadema) that energy and macronutrient intake are reduced during the dry season (Irwin et al. 2014). Therefore, the effect of energy availability on the immune system might counter-balance the effect of parasite exposure: In the dry season, less infective parasite stages may be found, but animals are also likely to be relatively immune-suppressed and thus more susceptible, while in the wet season more infective stages are likely to be encountered, but hosts may also be more immunocompetent. Additionally, in some Trichostrongylidae, for example Ostertagia ostertagi in cattle, reactivation of hypobiotic parasite stages during periods of energy deprivation is common (Gibbs 1986). These parasite stages lie dormant in the wall of the digestive tract for months until they are reactivated when conditions are favorable. Furthermore, the exact life cycle and the prepatent period, i.e. the period from infection to shedding of parasite reproductive stages, of the Trichostrongylidae species recovered in this study are unknown. Prepatency of Trichostrongylidae usually ranges from 2 to 3 weeks in domestic animals, but may exceed several months in other Strongylida (e.g. Strongylus edentatus in horses: 11 months; Eckert et al. 2008). It is therefore possible that infections acquired during the wet season might only become apparent several weeks to months later, when adult parasite stages have developed within the host and begin to shed eggs. In this study, only absence or presence of nematode infection was analyzed. While estimation of individual parasite burdens might have allowed more fine-scaled analyses, this was not possible. Due to high intra-individual variation in fecal egg counts (FEC), e.g. due to time of day, fecal fiber content and fluctuations of egg output by female worms (e.g. Hall 1981; Anderson and Schad 1985; Melfi and Poyser 2007; Denwood et al. 2012), it is not recommended to infer parasite burdens from FEC in wild primates (Gillespie 2006). In addition, FEC was low in all cases, resulting in small inter-individual variation.

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Conclusions

In conclusion, the species diversity of intestinal parasites found in Verreaux’s sifakas in this study was considerably low, especially in comparison to previously determined parasite communities of sympatric lemur species. This confirms previous parasitological studies of Verreaux’s sifakas and may indicate that their arboreal lifestyle protects them from a variety of environmentally transmitted parasites, including potentially zoonotic protozoa. Further studies are required to confirm whether Entamoeba infections occur in this population, and whether the species in question is E. histolytica or E. nuttalli. The high prevalence of Trichostrongylidae despite low rates of ground contact indicates that social contacts and oral grooming may play a role in the transmission of this parasite.

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Author contributions

AS, CF and PMK designed the study. AS conducted the field work, analyzed the samples and drafted the manuscript. AS and CF performed the statistical analyses. All authors contributed to the final manuscript.

Acknowledgements

We thank the team of the Kirindy field station and the Malagasy Ministère de l’Environnement et des Eaux et Forêts, the Département Biologie Animale de l’Université d’Antananarivo, and the Centre National de Formation, d’Etudes et de Recherche en Environnement et Foresterie for supporting and authorizing our long-term research in Kirindy. We are grateful to members of the research group FOR 2136 “Sociality and health in primates” for discussion. This research was funded by the Deutsche Forschungsgemeinschaft (Ka 1082/29-1) and the German Primate Center.

6. Manuscript 2: Escherichia coli Transmission

6. Manuscript 2:

Sociality shapes inter-group transmission of Escherichia coli in a group-living wild primate, Verreaux’s sifaka

Andrea Springer* a, Alexander Mellmann b, Claudia Fichtel c and Peter M. Kappeler d

*Corresponding author aBehavioral Ecology and Sociobiology Unit, German Primate Center, Kellnerweg 4, 37077 Göttingen, Germany, [email protected] bInstitute of Hygiene, University Hospital of Münster, Robert-Koch-Straße 41, 48149 Münster, Germany, [email protected] cBehavioral Ecology and Sociobiology Unit, German Primate Center, Kellnerweg 4, 37077 Göttingen, Germany, [email protected] dDepartment of Sociobiology and Anthropology, University of Göttingen, Kellnerweg 6, 30077 Göttingen, Germany and

Behavioral Ecology and Sociobiology Unit, German Primate Center, Kellnerweg 4, 37077 Göttingen, Germany, [email protected]

Submitted for publication to BMC Ecology (date of submission: 14.07.2015)

Keywords: fecal-oral disease transmission, Verreaux’s sifakas, Propithecus verreauxi, Escherichia coli, multi-locus sequence-typing, scent-marking, social contacts, social network analysis, spillover

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Abstract

Background

Epidemiological models often use information on host social contacts to predict the potential impact of infectious diseases on host populations and the efficiency of control measures. It can be difficult, however, to determine whether social contacts are actually meaningful predictors of transmission. We investigated the role of host social structure in the transmission of Escherichia coli in a wild population of primates, Verreaux’s sifakas (Propithecus verreauxi). Using multi-locus sequence typing (MLST), we compared genetic similarities between isolates from different individuals and groups to infer transmission pathways.

Results

Correlation of social and transmission networks revealed that membership to the same group significantly predicted sharing of E. coli MLST types. Intergroup encounter rate and a measure of space-use sharing provided equally potent explanations for type sharing between social groups, whereas animal age, sex and dispersal history had no influence. No antibiotic resistance was found.

Conclusions

We show that patterns of E. coli transmission reflect the social structure of this group-living lemur species. We discuss our results in the light of the species’ ecology and propose scent- marking, a type of social contact not considered in previous epidemiological studies, as a likely route of transmission between groups. Because we found no antibiotic resistance, E. coli spillover from humans into this arboreal species seems to be low.

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Background

Pathogens and parasites – broadly defined as organisms that live on and draw nutrients from a host (Nunn and Altizer 2006) – may impact their hosts’ survival and fitness considerably (Milton 1996; Nunn and Altizer 2006; Hillegass et al. 2010), often leading to declines in wildlife populations (e.g. Packer et al. 1999; Bermejo et al. 2006; LaDeau et al. 2007). Epidemiological models predict the potential impact of infectious diseases on host populations and the efficiency of control measures. However, whereas most traditional models have assumed homogeneous mixing of individuals within a host population (McCallum et al. 2001), it is now recognized that heterogeneity in contact patterns arising from both the social behavior of individual hosts and the spatial structure of host populations affect pathogen transmission (Altizer et al. 2003; Ezenwa 2004a; Craft et al. 2011; Griffin and Nunn 2012). Epidemiological models accounting for these social contact heterogeneities yield predictions that differ dramatically from mean-field models assuming homogeneous mixing (Carne et al. 2014; Manlove et al. 2014), especially with regard to threshold population sizes for disease invasion (Lloyd-Smith et al. 2005) as well as transmission (Molina and Stone 2012) and mortality rates (Hamede et al. 2012). Therefore, increasing efforts are being made to accurately assess transmission-relevant social contact patterns in humans (Obadia et al. 2015) and wildlife (Craft 2015) through direct observations (MacIntosh et al. 2012), live-trapping (VanderWaal et al. 2013a) or the use of proximity loggers (Vander Wal et al. 2013; Obadia et al. 2015). It can be difficult, however, to establish whether the contact patterns that have been measured are meaningful for actual transmission (Obadia et al. 2015). Moreover, it remains a major goal in disease ecology to determine the relative importance of social pathogen transmission compared to uptake from environmental reservoirs (VanderWaal et al. 2013b; Chiyo et al. 2014; Kappeler et al. 2015). Escherichia coli is an ideal model organism to trace transmission of fecal-orally transmitted microorganisms (Archie et al. 2009). It is the main aerobic commensal colonizing the gastrointestinal tract of mammals and exhibits a clonal population structure that is little affected by genetic transfer and mutation (Tenaillon et al. 2010). Healthy humans and dogs usually carry one predominant, resident strain of E. coli, which is present for months to years, and one to several transient strains (Sears et al. 1950; Sears et al. 1956; Caugant et al. 1981). Thus, if 2 individuals carry the same or genetically very similar strains, it can be assumed that

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either direct transmission has occurred between them, or that they have been exposed to a common source of E. coli (Archie et al. 2009). Among wild mammals, concordance between contact networks and E. coli strain sharing networks has been demonstrated in the fission-fusion society of giraffes (VanderWaal et al. 2013b), in a multihost system of African ungulates (VanderWaal et al. 2014) and in solitary mountain brushtail possums (Blyton et al. 2014). A similar study in elephants has been hampered by the fact that E. coli survive in water sources, which can act as infection reservoirs, masking social transmission (Chiyo et al. 2014). Thus, social E. coli transmission in wild mammal populations with discrete adjacent groups, a common setting in epidemiological models (Bonnell et al. 2010; Nunn et al. 2011; Caillaud et al. 2013; Leslie et al. 2014), has not been investigated so far. We studied social determinants of E. coli transmission in 10 groups of Verreaux’s sifakas (Propithecus verreauxi), an endemic Malagasy primate. We investigated whether E. coli transmission, measured as multi-locus sequence type (MLST ST) sharing, is influenced by group membership, GPS-derived intergroup encounter rates and a measure of space-use sharing between groups, the Utilization Distribution Overlap Index (UDOI), while controlling for host sex, age and dispersal history. Verreaux’s sifakas are diurnal, folivorous lemurs that are strictly arboreal. They live in small stable, multi-male multi-female groups and defend core areas of their home range by scent-marking in overlap areas of regular intergroup encounters (Richard 1985; Benadi et al. 2008). Males disperse from their natal group at around 3 to 5 years of age (Kappeler and Fichtel 2012). In contrast to most other primates, the small group and home range size of sifakas permits simultaneous study of multiple neighboring groups (e.g. Richard 1985; Benadi et al. 2008), and thus a rare opportunity to study transmission within and between social groups of primates in a natural setting. If direct social contacts were important for E. coli transmission, we predicted that MLST ST sharing would be more prevalent within than between groups, and we expected intergroup encounter rates to better explain strain-sharing than joint space- use. Microorganisms can also be taken up directly from the environment or through contact with members of other species. Because Verreaux’s sifakas do not drink from waterholes, but

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rely on licking dew from trees as well as on the water content of their diet, E. coli transmission via environmental reservoirs is unlikely. Furthermore, environmental conditions in the habitat are considered unfavorable for E. coli survival during most of the year (Ottoson et al. 2011; van Elsas et al. 2011), as a long dry season is accompanied by high-amplitude daily temperature fluctuations, high levels of light exposure and low humidity (Kappeler and Fichtel 2012). However, the study population has been exposed to visits by several thousand tourists per year, which represent a potential source of pathogens. E. coli serves as an important indicator of potential microbial spillover from humans or livestock into wildlife populations (Rwego et al. 2008; Pesapane et al. 2013). It has been shown that other lemurs living in habitats frequented by tourists harbor pathogenic Enterobacteria, which do not occur in undisturbed populations (Bublitz et al. 2014). Although E. coli is most often a commensal, many pathogenic strains exist, causing severe intestinal and extra-intestinal disease (Nataro and Kaper 1998; Smith et al. 2007). Among these, multi-resistant, extended-spectrum beta-lactamase (ESBL)-producing strains have recently emerged worldwide as important causes of disease both in humans and animals (Oteo et al. 2010; Guenther et al. 2011). By testing for antibiotic resistance, we assess the risk of microbial spillover from humans to a species belonging to the most endangered group of mammals, the lemurs of Madagascar (Schwitzer et al. 2014).

Materials and methods

Study area and host population

The study was carried out in Kirindy Forest, Western Madagascar, located at 44°39’E, 20°03’S. The 90-ha study area is part of a field site operated by the German Primate Center, where lemurs are habituated and individually marked with unique collars, including radio (Holohil Systems, Carp, Ontario, Canada) and GPS (e-obs, Grünwald, Germany) units, as part of an ongoing long-term study (Kappeler and Fichtel 2012), which has been approved by the Ethics Committee of the German Primate Center and the Ministère des Eaux et Forêts of Madagascar. All necessary research permits were obtained from the respective Malagasy and German authorities.

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We studied 8 adjacent social groups of Verreaux’s sifakas, ranging in size from 3 to 7 individuals, comprising 36 to 38 animals in total. Censuses of group membership are carried out two to three times a week (Kappeler and Fichtel 2012). All members of these 8 groups were sampled for E. coli, and samples from 2 groups living about 2 km away from the principal study population were also included.

Estimation of home range size, home range overlap and intergroup encounter rates

One adult animal in each of the eight adjacent groups was equipped with a GPS collar. Collars were set to simultaneously record GPS coordinates every 15 min, from 04:00 - 20:00 h local time. GPS data were collected from August to December 2013 and from March to July 2014. GPS data were not available for the two groups living outside of the principal study area. We calculated 95 % kernel home ranges and their overlaps for bi-weekly intervals using the adehabitatHR package (Calenge 2006) in R version 3.0.2. To quantify space-use sharing between the different groups, i.e. how much the animals actually use the overlap area, we calculated the utilization distribution overlap index (UDOI) (Fieberg et al. 2005). To derive intergroup encounter rates from the GPS data, we used the linear movement model contained in the R package movementAnalysis (Sijben 2013), assuming linear movement between location measurements. An encounter was inferred if two groups were in <42 m distance based on the interpolated trajectories. The 42 m distance threshold was derived by calculating the mean distance between the groups’ GPS locations during directly observed intergroup encounters, based on an extended dataset of observations and GPS data collection over the course of one year (Flávia Koch de Vasconcellos, personal communication). A new encounter was recorded if the two GPS-bearing individuals from different groups were at a distance > 42 m for at least 30 min, until this threshold was crossed again. Encounter rates were calculated as encounters per day for bi-weekly intervals. We tested for correlation between UDOI and intergroup encounter rate using Spearman rank correlation.

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Direct observations

Focal animal observations were conducted on all members of the 8 adjacent groups during two periods, from August to October 2013 and from February to May 2014. Observations of 1 h per individual were carried out in an alternating order for 3 h in the morning and 3 h in the afternoon, resulting in 4 statistical days per individual, which amounted to a total of 860 h of focal animal observations. During intergroup encounters, the identities and proportion of participating animals, all close contacts (i.e. grooming, body contact or proximity of < 1m) between members of different groups and their durations as well as the total duration of the encounter were recorded ad libitum.

Sample collection, E. coli isolation and genotyping

Rectal swabs (Transwab® Amies, Medical Wire and Equipment, Corsham, Wiltshire, UK) were taken in the course of routine biomedical examinations of immobilized animals. Fecal samples were collected within 2 min of defecation from those individuals from whom rectal swabs could not be obtained. Samples were obtained during 3 periods: In March and April 2013 and in August 2013, we took rectal swabs from 14 and 11 individuals, respectively, and in March and April 2014, 24 rectal swabs and 15 fecal samples were taken, resulting in a total of 66 samples from 48 individuals. Sampling in each period was distributed over all groups (Additional file 1), to exclude the possibility that MLST sharing within groups could arise as an artifact of the time point of sampling. Four individuals were repeatedly sampled. Pre- cultivation of bacteria was undertaken in the field laboratory to maximize E. coli recovery: Rectal swabs were streaked within 48 h onto MacConkey and Columbia blood agar and used to inoculate glucose-containing nutrient broth (agar and broth: Oxoid GmbH, Wesel, Germany). Broth and agar plates were incubated for 24 to 32 h at 37°C. After this first incubation period, broth was streaked onto both MacConkey and Columbia blood agar and incubated for another 24 h. To maximize recovery of E. coli, we randomly picked colonies from all four agar plates, dissolved them in sterile 0.9 % sodium chloride solution with an addition of 20 % glycerol and froze them at -20°C until shipment and further processing. Fecal samples were used to inoculate glucose-containing nutrient broth. After incubation of 24 to 32 h, an aliquot of the broth was frozen at -20°C with an addition of 20 % glycerol.

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In the laboratory in Germany, samples were streaked out onto MacConkey and Columbia blood agar. After an incubation period of 24-48 h, colonies typical for E. coli were isolated and subjected to species identification using matrix-assisted laser desorption ionization time-of-flight mass-spectrometry (MALDI-ToF MS; Bruker GmbH, Bremen, Germany). Antimicrobial susceptibility testing was done by agar disc diffusion as recommended by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) applying EUCAST clinical breakpoints for categorization of susceptible, intermediate and resistant isolates. All isolates were tested for multidrug resistance due to the production of extended-spectrum beta-lactamases (ESBL) using a chromogenic agar plate (chromID™ESBL; Bio Mérieux, Marcy l’Etoile, France). Isolates belonging to ST131 were additionally tested for resistance against the following antibiotics: Ampicillin, Piperacillin, Cefuroxim, Cefotaxim, Cefpodoxim, Ceftazidim, Cefepime, Piperacin/Tazobactam, Imipenem, Meropenem, Ertapenem, Trimethoprim/Sulfamethoxazol, Tigecyclin, Gentamicin, Amikacin, Ciprofloxacin, Fosfomycin and Nitrofurantoin. These include, but are not limited to, the most prevalent resistance-causing antibiotics used in Madagascar (Randrianirina et al. 2014). For molecular subtyping, each isolate was characterized using MLST (Maiden et al. 1998). This typing method relies on determination of the sequence of internal fragments of 7 housekeeping genes (Wirth et al. 2006) and STs were assigned according to the E. coli MLST website (http://mlst.warwick.ac.uk/mlst/dbs/Ecoli). Sequences were further analyzed using the SeqSphere+ software version 1 (Ridom GmbH, Münster, Germany). The minimum spanning tree based on the MLST was generated also using the SeqSphere+ software.

Construction of the transmission network

We constructed an E. coli transmission network by assigning a link to a dyad if the two animals shared the same ST or if their types differed only by 1 of the 7 genes (single locus variant) and can thus be considered closely related. Links were unweighted, i.e. we neither made a distinction between the number of types that animals shared nor whether they shared the same or a closely related ST, and undirected as we did not make any assumptions about the direction of transmission. Animals from which we did not obtain any isolate were not included.

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Statistical analyses

We tested for significant differences in E. coli recovery rate between the two sampling methods, rectal swab and fecal sample, using a χ²-test. We then tested whether the number of STs isolated from an individual was significantly correlated with the animals’ age, the size of its’ social group and sampling effort, i.e. the number of samples that were taken from this individual, using Spearman rank correlations. Because adult males are expected to roam more than adult females, we tested for differences in the number of sequence types between adult males and adult females using a Wilcoxon rank sum test. We used nonparametric tests, because the data violated assumptions of generalized linear mixed models. To determine which factors influence the likelihood of a link occurring in the transmission network, we performed multiple regression quadratic assignment procedures (MR-QAP), which represent one of the methods of choice to test hypotheses on social networks (Mantel 1967; Hubert 1987; Krackhardt 1988; Croft et al. 2011). Because of the non-independence of network data, statistical methods that assume data independence are not appropriate (Croft et al. 2011). MR-QAP accounts for the non-independence by implementing permutations to establish P-values. It performs standard logistic regression and then uses a Monte Carlo procedure to randomly permute rows and columns of the network matrix (Dekker et al. 2007); a regression coefficient is then calculated for each permuted matrix to generate a reference distribution. The P-value refers to the proportion of randomly generated values that are more extreme than the observed correlation. In contrast to the ordinary least squares method, it is not possible to calculate degrees of freedom, statistical power, or effect sizes in MR-QAP regression (Ferrin et al. 2006) and R-squared values tend to have little meaning (Gibbons 2004; Zagenczyk et al. 2013). We thus report correlation coefficients and P-values, the primary statistic of interest in MR-QAP analysis (Zagenczyk et al. 2013). Using MR-QAP analysis with double Dekker semipartialling (Dekker et al. 2007) and 2000 permutations, we investigated in a multivariate model whether the following factors - belonging to the same sex, - being born in the same year, - being born in the same social group, - being a member of the same social group at the point of sampling, - having been sampled in the same month and

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- having been sampled by the same method (rectal swab or fecal sample) influenced a dyad’s log-odds of having the same or a closely related E. coli ST. Including only the 8 neighboring groups, we further tested whether UDOIs and intergroup encounter rates were significantly correlated with E. coli type sharing between dyads belonging to different groups. For UDOIs as well as encounter rates, we used the arithmetic mean of all bi-weekly measurements to best represent the relation between the two groups throughout the study period. We constructed separate models for these two predictors because of their strong correlation, and controlled for birth cohort, sex, natal group, sampling month and sampling method. All network analyses were performed in UCINET version 6.523 (Analytic Technologies, Harvard, MA, USA).

Results

Home range overlap and intergroup encounters

Mean bi-weekly 95 % kernel home ranges varied in size from 5.67 ha to 14.15 ha among groups, and the corresponding pair-wise home range overlap varied between 0.64 and 3.88 ha. Mean UDOIs of neighboring groups varied from 0.00017 to 0.098. Mean bi-weekly intergroup encounter rates estimated from GPS data varied from 0.005 to 0.7 encounters per day, and 49 intergroup encounters were directly observed. Mean duration (± SD) of intergroup encounters was 12.5 ± 11.5 min (range: 2 – 60 min). Scent-marking occurred in 75.5 % of observed encounters, while proximity < 1m between members of different groups occurred in 32.7 % and body contact and grooming only occurred during 16.3 and 12.2 % of encounters, respectively. Mean UDOIs and mean intergroup encounter rates between adjacent groups were strongly correlated (Spearman rank correlation, N = 14, S = 12, rho = 0.97, P < 0.001).

Recovery of E. coli types

We characterized 83 E. coli isolates, belonging to 39 individuals from 10 social groups. Twenty-nine individuals were natal to their social group, while 10 animals (1 female, 9 males) were immigrants. Isolation success did not differ statistically between rectal swabs and fecal

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samples (76.5 % of Nrectal = 51 vs. 60 % of Nfecal = 15, χ² = 0.78, P = 0.37). We isolated 24 distinct MLST STs, 13 of which (54.2 %) occurred in multiple hosts (Fig. 1). Previously unknown STs were deposited in the E. coli MLST database (http://mlst.warwick.ac.uk/mlst/dbs/Ecoli). Up to two different STs were obtained per sample and up to 4 different STs per individual host. Of the 4 animals that were sampled repeatedly, we only once found the same type twice in subsequent samples. All isolates were non-ESBL- producing. Further susceptibility tests on isolates of type ST131, an ST that is shared with the major antibiotic resistant E. coli lineage (Nicolas-Chanoine et al. 2008), revealed full susceptibility to all antimicrobial agents tested.

Figure 1: Minimum spanning tree based on the allelic profiles of the 24 MLST STs isolated. Node size is proportional to the frequency of sequence occurrence, numbers on connecting lines are the number of differing alleles in a pair-wise comparison, and colors indicate host social group.

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Predictors of individual ST richness and sharing

There was no significant correlation between the number of STs isolated from an individual and its age, the size of its social group, or the number of samples collected from an individual (Spearman rank correlation, rho = 0.05, P = 0.76; rho = -0.12, P = 0.42; rho = 0.25 and P = 0.08, respectively). Adult males did not harbor more STs than adult females (Wilcoxon rank sum test, W=183.5, P = 0.54). Density of the E. coli transmission network was 0.14 (Fig. 2), indicating that 14 % of all possible connections were present. A larger proportion of those dyads that were in the same group harbored the same or closely related STs than those that had home range overlap, but were not in the same group (Fig. 3). This proportion was smallest for animals belonging to non-neighboring groups. We tested whether several dyad-level attributes influenced the log- odds of a link occurring between two individuals, but the full E. coli transmission network was only significantly correlated with the group membership network; all other predictor variables were not statistically significant (Table 1, model A). Regarding links between social groups, UDOIs and intergroup encounter rates were equally strongly correlated with the intergroup transmission network (Table 1, models B and C), qualifying both as conduits of social transmission between different groups. Belonging to the same birth cohort was also significant, but the correlation coefficient was negative, indicating that in this data subset, animals born in the same year had a smaller chance of harboring the same E. coli strain than by chance. Having been sampled in the same month was a significant predictor in one of the two models, but not in the other, indicating that some temporal correlation between the isolated strains might exist.

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Figure 2: Networks including 10 social groups from 2 study areas based on a) group membership and home range overlap and b) E. coli ST sharing. Nodes are arranged by social groups, indicated by the different colors. In network a) thickness of lines is proportional to the degree of home range overlap (within-group overlap = 100 %) while in network b) lines indiscriminately indicate that two individuals share the same E. coli ST or that they harbor types which only differ by 1 of 7 loci.

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Figure 3: Proportion of dyads sharing the same E. coli sequence type in each of three association classes: 1) Belonging to the same group (N = 67), 2) belonging to adjacent groups whose ranges overlap (N = 224) and 3) belonging to non-adjacent groups (N = 443).

6. Manuscript 2: Escherichia coli Transmission

Table 1: MR-QAP models testing the influence of different predictors on the log-odds of E. coli type sharing.

Standardized correlation Model Predictor P-value coefficient A Same sex 0.18 -0.03 (P = 0.005) Same year of birth 0.2 -0.03

Same natal group 0.238 -0.04

Same group 0.016 0.12

Same sampling month 0.38 0.01

Same sampling method 0.366 0.02 B Mean Utilization Distribution 0.0005 0.15 (P < 0.001) Overlap Index (UDOI) Same sex 0.129 -0.03

Same year of birth 0.001 -0.09

Same natal group 0.375 0.009

Same sampling month 0.04 0.07

Same sampling method 0.479 0.004 C Mean intergroup encounter 0.0005 0.17 (P < 0.001) rate (encounters/day) Same sex 0.18 -0.01

Same year of birth 0.005 -0.09

Same natal group 0.521 -0.0007

Same sampling month 0.061 0.06

Same sampling method 0.413 0.01

Models B and C included only the 8 neighboring groups and excluded ties within the same social group. Significant P-values (< 0.05) are printed in bold. All models are significant after Bonferroni correction (P < 0.017).

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Discussion

Using E. coli as a model for other, potentially more harmful fecal-orally transmitted microorganisms, this study revealed that the social structure of a group-living primate, measured as group membership, intergroup encounter rates and space-use overlap, shapes transmission. These measures should therefore be considered in epidemiological modeling of fecal-orally transmitted infectious agents. In contrast, there was no evidence for E. coli spillover from humans, despite exposure to anthropogenic activities, including human defecation, in the study area. The strictly arboreal lifestyle of sifakas, in combination with reliance on ephemeral water sources, may therefore hamper environmental uptake of E. coli and other similarly transmitted microorganisms, although comparison with a sympatric lemur species that spends more time on the ground (Eulemur rufifrons) will be needed to confirm this hypothesis (cf. Clough et al. 2010). Extensive E. coli strain sharing has been documented in members of the same household, including pets (Johnson et al. 2008; Johnson et al. 2009), suggesting that households function as a microbiological unit. Our results show that wild groups mirror these microbiological units in Verreaux’s sifakas. Belonging to the same social group was the only significant predictor of E. coli ST sharing as compared to possible non-social influences such as host sex and age, which were important determinants of E. coli communities in elephants (Chiyo et al. 2014). Being born in the same group was also not significant, indicating that adult animals acquire the E. coli types of their new group after dispersal, and that their E. coli community is not static throughout life, but responds to changing social conditions, as in humans (Skurnik et al. 2008). Belonging to the same birth cohort even had a negative correlation with E. coli type sharing, likely because each cohort consists of only one to two animals per social group. It is possible that animals within a group only shared the same strains because they live in the same habitat. However, several factors make this explanation less likely than direct transmission via social interaction. First, while there is no empirical information on how long E. coli bacteria are able to survive on leaves and substrates used by sifakas, such as tree bark, a study investigating E. coli survival on lettuce revealed that exposure to sunlight reduced contamination by log 1 to 3 within 1 to 7 days (Ottoson et al. 2011). Light exposure in the dry deciduous Kirindy Forest is high, especially during the long dry season from April to October,

6. Manuscript 2: Escherichia coli Transmission

and is accompanied by high-amplitude temperature fluctuations and little rainfall (Kappeler and Fichtel 2012), conditions which are regarded hostile for E. coli survival (van Elsas et al. 2011). Conditions may be more favorable during the short wet season, however, which is characterized by more stable temperatures and regular rainfall. Transmission from water sources on the ground can be excluded because sifakas do not drink from water holes. This is in contrast to a wetland elephant population, where this environmental source of infection masked social factors (Chiyo et al. 2014). We recovered a maximum of 4 different STs from an individual and this number adequately represented within-host E. coli diversity found in humans (Sears et al. 1950) and other animals (Sears et al. 1956; VanderWaal et al. 2013b). One limitation of the study, however, is that we were unable to assess strain-turnover in individual hosts, as only 4 animals could be sampled more than once due to practical constraints of field work. In those animals, we only once recovered the same ST twice. Future research will have to reveal whether this was due to strain-turnover, variation in strain abundance within the host, or the fact that sometimes subdominant strains can be more easily cultured than the dominant, resident strain (de Muinck et al. 2011). However, E. coli strains have been shown to persist for 1 to 3 years in humans and their pets (Johnson et al. 2008). Furthermore, if strain-turnover in the population was indeed high, sampling during different periods should rather obscure any social signature than strengthen it, especially since sampling was equally distributed over all of the groups during each sampling window. To investigate whether our results were influenced by the different sampling periods or by the fact that we used both rectal swabs and fecal samples, we tested whether the probability of ST sharing was influenced by the animals being sampled in the same month or by the same method. Sampling method had no effect on the results, while being sampled in the same month was significant in one of the models investigating inter-group E. coli similarity. This indicates that there might have been a temporal correlation between strains isolated, but the social predictors had much larger correlation coefficients. Transmission of E. coli between social groups requires space-use sharing or direct contact during intergroup encounters. Both factors were equally correlated with the transmission network in the present study, making it impossible to decide whether transmission takes place predominantly through direct contact or through the subsequent use

6. Manuscript 2: Escherichia coli Transmission

of the same substrates. Because space sharing is a prerequisite for encounters to occur, encounter rate was expected and found to strongly correlate with our measure of range overlap, which takes into account the intensity of space use in the overlap area (UDOI). In contrast, association of individuals correlated with E. coli type sharing in giraffes, whereas home range overlap did not (VanderWaal et al. 2013b), but the intensity of use of the overlap area was not controlled for. Most observed sifaka intergroup encounters did not involve physical contact. We recorded members of different groups to be in a distance of < 1m in only 33 % of observed encounters, and body contact occurred in only 16 % of them. Alternatively, we propose that transmission might be mediated by scent-marking. Sifakas scent-mark by rubbing their anogenital region and chest glands (males only) on trees, and subsequent olfactory inspection of scent-marks and overmarking, i.e. placing a scent-mark directly on the scent-mark of another individual, are frequent behaviors in sifakas (Lewis 2005) and other lemurs (Kappeler 1998). Scent-marking has been shown to occur at higher rates in zones of home range overlap than in core areas (Benadi et al. 2008) and occurred during 75.5 % of observed encounters. Thus, olfactory communication involving signal inspection and overmarking, which are also common in other mammals (Ferkin 1999; Jordan et al. 2011), and potentially other types of indirect species-specific social contacts are worth considering as mechanisms of social pathogen transmission in future studies of many other mammals. Spillover of antimicrobial-resistant bacteria from humans into wildlife populations, which do not themselves come into contact with antimicrobial agents, has become an increasing concern, as these wild animal populations might constitute reservoirs for human infections (Guenther et al. 2011; Radhouani et al. 2014). ESBL-producing E. coli have been found in wildlife populations ranging from seagulls and birds of prey to rodents and wild boar (reviewed in Guenther et al. 2011). More recently, multidrug-resistant E. coli have been identified at high prevalence in banded mongoose living close to human settlements (Pesapane et al. 2013) and in a non-habituated gorilla living in a protected area (Janatova et al. 2014). Most E. coli isolates recovered in this study have not been described before in humans or domestic animals and were non-ESBL-producing. Thus, while we certainly did not sample the entire E. coli diversity harbored by sifakas, the data suggest that spillover of E. coli from

6. Manuscript 2: Escherichia coli Transmission

humans into this population might be low, even though the study area is frequented regularly by tourists, researchers and occasionally villagers and livestock. We did not investigate E. coli carriage in humans in this study, but a survey including human stool samples from all over Madagascar revealed that more than 80 % of E. coli isolates were resistant to the most widely used antibiotics, including those tested in our study (Randrianirina et al. 2014). Bublitz et al. (2014) recently found a higher prevalence of pathogenic Enterobacteria in lemurs living in habitats with frequent exposure to humans than in undisturbed forests. Lemurs found to be positive did not include Propithecus sp., however. Nonetheless, we did recover ST131 isolates in 3 individuals. The spread of a single clonal group with an ST131 profile has largely been responsible for the sudden increase in ESBL-producing E. coli during the last decades and today constitutes the predominant lineage among extraintestinal pathogenic E. coli worldwide (Rogers et al. 2010; Nicolas-Chanoine et al. 2014). ESBL-producing bacteria, including E. coli ST131, occur with high prevalence in the region of Antananarivo, the capital of Madagascar (Andriatahina et al. 2010; Herindrainy et al. 2011). The ST131 isolates which we recovered in this study were non-ESBL-producing, however. Additional susceptibility testing on all isolates belonging to this ST revealed full susceptibility to all antimicrobial agents tested. Along with some studies on humans, our results confirm that non-ESBL-producing, antibiotic-susceptible ST131 isolates exist (Leflon- Guibout et al. 2008; Brisse et al. 2012). Another type known for ESBL-production, ST101, was also isolated, but was also non-ESBL-producing.

Conclusions

In conclusion, our results provide further evidence for transmission of potentially pathogenic microorganisms as a cost of group-living through direct and indirect social contacts within and between wild groups of primates. While E. coli is usually a commensal, severely pathogenic strains exist (Nataro and Kaper 1998; Smith et al. 2007), which have been shown to cause disease in captive lemurs (Williams 2015). We could show that E. coli strain-sharing is most prevalent within groups of wild lemurs and that spatial association explains group-to- group transmission. Species-specific patterns of scent-marking and overmarking might constitute a likely route of social transmission, especially between groups. The absence of

6. Manuscript 2: Escherichia coli Transmission

antibiotic resistance indicates that E. coli spillover into the population might be low, despite relatively high human impact, although spillover of other pathogens cannot be excluded. More detailed genetic analyses will be needed to clarify the extent to which the ST131 isolates discovered in this study are related to disease-causing human ST131 isolates.

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List of abbreviations

E. coli = Escherichia coli

ESBL = extended-spectrum beta-lactamase

EUCAST = European Committee on Antimicrobial Susceptibility Testing

GPS = global positioning system h = hours ha = hectare km = kilometer

MALDI-ToF MS = matrix-assisted laser desorption ionization time-of-flight mass- spectrometry min = minutes

MLST = multi-locus sequence typing

MR-QAP = multiple regression quadratic assignment procedure

ST = sequence type

UDOI = utilization distribution overlap index

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Competing interests

The authors declare that they have no competing interests.

Author contributions

AS, AM, CF and PMK designed the research. AS conducted the field work, performed the statistical analyses and drafted the manuscript. AM performed E. coli isolation, genotyping and analyses. PMK and CF analyzed data and contributed to manuscript writing. All authors read and approved the final manuscript.

Acknowledgements

We thank the team of the Kirindy field station and the Malagasy Ministère de l’Environnement et des Eaux et Forêts, the Département Biologie Animale de l’Université d’Antananarivo, and the Centre National de Formation, d’Etudes et de Recherche en Environnement et Foresterie for supporting and authorizing our long-term research in Kirindy. We are grateful to C. L. Nunn and F. Leendertz for valuable comments on an earlier version of this manuscript and members of the research group FOR 2136 “Sociality and health in primates” for discussion. This research was funded by the Deutsche Forschungsgemeinschaft (Ka 1082/29-1) and the German Primate Center.

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recAEc 25 82 82 82 82 82 4 4 99 26 26 26 28 15 15 82 4 82 82 82 96 96

purAEc 37 14 14 14 14 14 5 5 5 11 11 14 68 14 36 14 5 14 14 14 11 11

mdhEc 16 30 30 30 30 30 37 37 5 17 17 23 17 17 17 30 37 30 30 30 17 17

icdEc 13 36 36 36 36 36 27 27 6 13 13 36 13 22 22 36 27 36 36 36 36 36

gyrBEc 50 19 19 19 19 19 2 2 131 9 9 19 30 13 13 19 2 377 377 377 121 121

fumCEc 39 39 39 39 39 39 132 132 160 39 39 103 39 21 21 39 132 39 39 39 14 14

adkEc 13 13 13 13 13 13 35 35 126 13 13 88 38 13 13 13 35 13 13 13 76 76

ST 135 491 491 491 491 491 501 501 714 4009 4009 4567 4569 28 121 491 501 4011 4011 4011 4177 4177

2014

in this with information study, together isolates recovered

Collection Date 2014 11, Apr 2014 11, Apr 2013 20, Aug 2013 20, Aug 2013 Mar 25, 2013 Mar 25, 2013 20, Aug 2013 20, Aug 2014 Mar 13, 2014 30, Apr 2014 Mar 13, 11, Apr 2014 11, Apr 2013 Mar 25, 2013 16, Apr 2014 2, Apr 2013 20, Aug 2014 Mar 12, 2014 Mar 12, 2013 Mar 28, 2013 10, Sept 2013 10, Sept E. coli E.

natal natal natal natal natal natal natal natal natal natal natal natal natal Status

immigrant immigrant immigrant immigrant immigrant immigrant immigrant immigrant immigrant

E E E E E E E E E C C C C C C C C C C C C C Group

verreauxi verreauxi

Host Species Propithecus Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi

Individual Tenali Betioky Bochum Bochum Manombo Manombo Bochum Bochum Bochum Beroboka Bochum Tenali Betioky Wagga Melbourne Brisbane Melbourne Augusta Augusta Sissy Augusta Augusta

dditional file file dditional 1 Sample ID LB359533#1 LB359534#1 LB336903#b LB336912#b LB309303#1 LB309340#1 LB336903#a LB336912#a LB359528#1 LB359569#1 LB359584#1 LB359588#1 LB359589#1 LB309341#1 LB309320#1 LB359532#1 LB336905 LB359526#1 LB359582#1 LB309353#1 LB336910 LB336918 on their hosts, sampling date, and MLST profile. MLST hosts,profile. and on their sampling date, A the of all including table A characteristics”: host and “Isolates 88

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82 96 96 4 6 4 4 4 4 25 25 165 165 29 29 4 4 26 26 4 2 15 15 25 82 82 4 26

14 11 11 16 8 5 5 5 5 30 30 2 2 28 28 16 16 11 11 16 2 14 36 25 14 14 5 11

30 17 17 67 9 37 37 37 37 17 17 196 196 36 36 67 67 17 17 67 367 17 17 17 30 30 37 17

36 36 36 87 16 27 27 27 27 425 425 479 479 13 13 87 87 13 13 87 480 487 22 37 36 36 27 13

377 121 121 39 3 2 2 2 2 190 190 6 6 47 47 39 39 9 9 39 75 13 13 19 19 19 2 9

39 14 14 36 19 132 132 132 132 13 13 186 186 40 40 36 36 39 39 36 586 21 21 43 39 39 132 39

13 76 76 384 6 35 35 35 35 76 76 80 80 53 53 34 34 13 13 384 6 13 13 13 13 13 35 13

4011 4177 4177 4571 196 501 501 501 501 4010 4010 4570 4570 131 131 349 349 4009 4009 4571 4572 4601 121 126 491 491 501 4009

2013 Mar 28, 2013 10, Sept 2013 10, Sept 2013 Mar 25, 2014 Mar 12, 2014 11, Apr 2014 11, Apr 2013 Mar 26, 2013 Mar 26, 2013 Mar 25, 2013 Mar 25, 2014 4, May 2014 4, May 2014 14, Apr 2014 14, Apr 2013 20, Aug 2013 20, Aug 2013 Mar 26, 2013 Mar 26, 2014 30, Apr 2014 11, Apr 2014 11, Apr 2013 16, Apr 2014 11, Apr 2014 1, May 2014 1, May 2014 11, Apr 2014 11, Apr

natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal

immigrant immigrant immigrant immigrant immigrant immigrant

F F F F F F F F F E E E E G G G H H H H H H F1 F1 F1 F1 F1 F1

Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi

Sissy Augusta Augusta Wagga Francisco Fresno Fresno Helena Helena Columbus Columbus Marojejy Marojejy Kansas Kansas Lincoln Lincoln Savannah Savannah Niagara Nova Nova Sapporo Davos Geneva Geneva Sapporo Davos

LB309353#1 LB336910 LB336918 LB309304#1 LB359527#1 LB359535#1 LB359590#1 LB309308#1 LB309345#1 LB309305#1 LB309342#1 LB359575#1 LB359621#1 LB359553#1 LB359608#1 LB336908 LB336916 LB309309#1 LB309346#1 LB359617#1 LB359598#1 LB359543#1 LB309321#1 LB359537#1 LB359571#1 LB359619#1 LB359591#1 LB359592#1 Additional file 1 continued Additional file

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4 4 6 6 6 6 25 25 36 26 96 96 4 4 4 4 29 29 26 26 165 165 29 82 82 82 82 14

16 16 7 7 7 7 25 25 37 11 11 11 16 16 16 16 28 28 11 11 2 2 28 14 14 14 14 8

67 67 11 11 11 11 17 17 17 17 17 17 67 67 67 67 36 36 17 17 196 196 36 30 30 30 30 9

87 87 18 18 18 18 37 37 46 13 36 36 87 87 87 87 13 13 13 13 479 479 13 36 36 36 36 16

39 39 15 15 15 15 19 19 10 9 121 121 39 39 39 39 47 47 9 9 6 6 47 19 19 19 19 14

36 36 41 41 41 41 43 43 24 39 14 14 36 36 36 36 40 40 39 39 186 186 40 39 39 39 39 29

384 384 43 43 43 43 13 13 15 13 76 76 384 384 384 384 53 53 13 13 80 80 53 13 13 13 13 6

4571 4571 101 101 101 101 126 126 583 4009 4177 4177 4571 4571 4571 4571 131 131 4009 4009 4570 4570 131 491 491 491 491 2005

2013

2014 11, Apr 2013 22, Aug Mar 26, 2013 Mar 26, 2014 29, Apr 2014 29, Apr 2014 11, Apr 2014 11, Apr 2014 Mar 13, 2014 Mar 13, 2013 20, Aug 2013 20, Aug 2014 29, Apr 2014 29, Apr 2014 11, Apr 2014 11, Apr 2013 Mar 26, 2013 Mar 26, 2014 12, Apr 2013 22, Aug 2014 23, Apr 2014 23, Apr 2014 14, Apr 2013 Mar 25, 2013 Mar 25, 2013 Mar 25, 2013 Mar 25, 2014 14, Apr

natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal natal

immigrant immigrant immigrant immigrant immigrant immigrant

J J J J J J J J J J J J J J L L L L L L

H H S2 S2 S2 S2 S2 S2

verreauxi

Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi

1 continued

Sapporo Sapporo Kamikaze Kamikaze Knuta Montreal Yokohama Yokohama Sendai Sendai Ichino Ichino Yokohama Yokohama Yono Yono Goa Goa Gaya Mafybe Gandhi Gandhi Swansea Glasgow Glasgow Glasgow Glasgow Swansea

LB359536#1 LB371747 LB309311#1 LB309348#1 LB359614#1 LB359615#1 LB359539#1 LB359594#1 LB359585#1 LB359529#1 LB336906 LB336914 LB359566#1 LB359616#1 LB359538#1 LB359593#1 LB309312#1 LB309349#1 LB359599#1 LB371746 LB359562#1 LB359613#1 LB359554#1 LB309306#1 LB309307#1 LB309344#1 LB309344#2 LB359609#1 Additional file file Additional

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4 4 26 26 26 26

5 5 11 11 11 11

37 37 17 17 17 17

27 27 13 13 13 13

2 2 9 9 9 9

132 132 39 39 39 39

35 35 13 13 13 13

501 501 4009 4009 4009 4009

15, 2014 15,

2014 13, Apr 2014 13, Apr Apr 2014 15, Apr 2014 13, Apr 2014 13, Apr

natal natal immigrant immigrant immigrant immigrant

S3 S3 S3 S3 S3 S3

Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi Propithecus verreauxi

1 continued Born Born Gouda Gouda Venlo Venlo

LB359552#1 LB359607#1 LB359556#1 LB359611#1 LB359551#1 LB359606#1 file Additional

7. Manuscript 3: Ectoparasites

7. Manuscript 3:

Ectoparasites of a group-living wild lemur species, Verreaux’s sifaka: Does sociality influence infection risk?

Andrea Springera, Claudia Fichtela and Peter M. Kappelera,b

to be submitted

Keywords: ectoparasites, Verreaux’s sifakas, Propithecus verreauxi, grooming, Makialginae

7. Manuscript 3: Ectoparasites

Abstract

Host social behavior is expected to mediate exposure to directly transmitted parasites, but other factors related to the biology of the host or the parasite may also shape prevalence patterns. Stationary ectoparasites are transmitted via direct host-to-host contact and can be removed via grooming, thus representing an ideal system to study the impact of host social behavior on infection. We investigated the impact of host social group size and the amount of allogrooming received, in relation to host age, sex and season, on ectoparasite infections in a wild population of Malagasy lemurs, Verreaux’s sifakas (Propithecus verreauxi), comprising 39 animals in 10 social groups. The animals were co-infected with several species of psoroptid mites and one species of chewing louse, while ticks were only recovered on two animals. We did not find any effect of social group size, amount of body contact, amount of grooming received, host age, sex or season on the probability of infection with mites or chewing lice. However, chewing louse infections showed a clustered pattern of occurrence, suggesting that the animals’ social structure may limit spread of the infection and that dispersal may be the most likely route of inter-group transmission. Increased autogrooming rates in mite-infected animals may indicate that mites cause irritation and thus impose costs on their hosts, but more data are needed to confirm this hypothesis. In conclusion, evidence for the potential costs and consequences of social behavior in terms of ectoparasitism remains weak, while host traits and seasonality also do not seem to influence ectoparasite prevalences in Verreaux’s sifakas.

93 7. Manuscript 3: Ectoparasites

Introduction

Host behavior, especially in the social domain, can mediate parasite transmission (Hart 1990; Barnard 2002; Altizer et al. 2003; Kappeler et al. 2015). On the one hand, parasites often exploit host social contacts for transmission, and thus parasitism is expected to increase with group size (Freeland 1976; Anderson and May 1982; Anderson et al. 1986; Altizer et al. 2003). On the other hand, hosts are expected to show adaptive behaviors to avoid or get rid of parasites, e.g. grooming (Hart 1990; Nunn and Altizer 2006). However, parasite exposure and host susceptibility are also influenced by several other factors, including host sex, age, social and endocrine status (Zuk and McKean 1996; Nunn and Altizer 2006; Habig and Archie 2015), and seasonality of the habitat (Altizer et al. 2006). In this context, the relative importance of social behaviors regarding individual infection risks remains relatively unexplored (Drewe 2010; Kappeler et al. 2015). Stationary ectoparasites, like mites and lice, usually require direct contact between hosts for transmission (Wall and Shearer 2001), while they can be removed via auto- or allogrooming (Hawlena et al. 2007; Akinyi et al. 2013). Social behaviors should therefore directly impact ectoparasite infections. However, empirical evidence regarding the influence of host social group size and patterns of direct social contacts on ectoparasite infections remains limited to mainly rodents and bats (Arnold and Lichtenstein 1993; Van Vuren 1996; Hillegass et al. 2008; Zhang et al. 2010). Although most primates are highly social, similar investigations in wild primates are scarce (but see Sánchez-Villagra et al. 1998; Akinyi et al. 2013). This might be due to the fact that measuring ectoparasitism requires animal capture, which is not always possible, and primatologists often struggle with low sample sizes. While grooming behavior has been extensively studied in primates (e.g. Seyfarth 1977; Silk 1982; Barrett and Henzi 2001; Schino and Aureli 2008; Port et al. 2009), the function of grooming with regard to ectoparasite removal has usually been inferred from the body parts groomed (Hutchins and Barash 1976; Barton 1985; Zamma 2002), rather than by directly relating grooming patterns to ectoparasite infections. We investigated social group size and grooming as predictors of ectoparasitism, in relation to host sex, age and seasonality, in a wild population of primates, Verreaux’s sifakas (Propithecus verreauxi), comprising 10 social groups. These folivorous lemurs inhabit dry deciduous forests of southern and south-western Madagascar, where they are subject to

7. Manuscript 3: Ectoparasites

pronounced seasonality (Kappeler and Fichtel 2012). They live in small multi-male, multi- female social groups, which display territoriality, although home ranges partly overlap (Benadi et al. 2008). Like other lemurs, sifakas auto- and allogroom orally, making use of their toothcomb (Eaglen 1980). We predicted that animals which live in larger groups, and thus have body contact with more individuals, would have a higher likelihood of infection, as well as individuals which spend more time in body contact with conspecifics, while individuals which receive more grooming would have a lower probability of infection due to ectoparasite removal. We also tested the hypothesis that infected animals groom themselves more than non-infected animals due to irritation caused by ectoparasites. With regard to animal sex, we expected that males would have higher probabilities of infection. Sex-biased patterns of parasitism, probably due to differences in hormone levels, are common (Zuk and McKean 1996; Klein 2004), and higher ectoparasite loads in males than females have been found in raccoons (Monello and Gompper 2010), African ground squirrels (Hillegass et al. 2008) and marmots (Wey and Blumstein 2012), for example. In addition, males are the dispersing sex in sifakas, and a history of dispersal has been linked to higher measures of ectoparasitism (Van Vuren 1996). Controversial patterns have been found regarding age-distributions of ectoparasite infections. Some studies report an increase with age (Krasnov et al. 2006; Hillegass et al. 2008), while others describe greater ectoparasite abundance on juveniles than adults (Zhang et al. 2010), or an age-sex interaction, with age affecting ectoparasitism in one sex, but not the other (Hillegass et al. 2008; Monello and Gompper 2009; Le Coeur et al. 2015; Webber et al. 2015). We expected the probability of ectoparasite infection to increase with age, due to cumulative exposure and a decline in immune function in aged individuals. Seasonality of the environment may influence ectoparasite prevalence if animals show increased aggregation during a specific season, leading to increased parasite exposure (Altizer et al. 2006), or if host immune responsiveness decreases seasonally due to energetic constraints (Martin et al. 2008). Therefore, we expected prevalence of ectoparasite infection to be higher during the dry season, when energy availability for folivorous sifakas is low (Lewis and Kappeler 2005; Irwin 2008). In addition, birth and lactation fall into this season, increasing energy demand for female sifakas.

7. Manuscript 3: Ectoparasites

Materials and methods

Study site

Sample collection

39 Verreaux’s sifakas (12 females, 27 males) belonging to 10 different social groups from two study areas, were routinely anaesthetized between March 2013 and May 2014 (dry season: 9 animals, wet season: 30 animals) as part of an ongoing long-term study (Kappeler and Fichtel 2012). This long-term study has been approved by the Ethics Committee of the German Primate Center and the Ministère des Eaux et Forêts of Madagascar. All necessary research permits were obtained from the respective Malagasy and German authorities. During clinical examination, ectoparasites were removed from their hosts with the help of tweezers in case of ticks and chewing lice and clear adhesive tape in the case of mites. Both were stored in 70 % ethanol. In Germany, they were mounted on microscope slides in a drop of Berlese mixture (Waldeck GmbH & Co. KG, Münster, Germany), covered with a coverslip and examined under a compound microscope. Photographs were taken with a Zeiss AxioCam ERc 5s fitted to a Zeiss Primo Star microscope (Carl Zeiss AG, Oberkochen, Germany). Measurements were made using the Zeiss Zen lite 2012 software after calibration with a stage micrometer. Identification was based on morphological criteria and followed Uilenberg et al. (1979) and Rodriguez et al. (2012) for ticks, Stobbe (1913) and Ferris (1933) for chewing lice and Bochkov and OConnor (2006), Bochkov et al. (2010) and Bochkov et al. (2015) for mites.

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Behavioral observations

Focal animal observations were conducted during two periods, from August to October 2013 and from February to May 2014, on each member of 8 adjacent social groups of Verreaux’s sifakas (N = 42), excluding dependent infants. For simplicity, we will refer to behavioral data collected during the first period as “dry season” data and during the second period as “wet season” data, even though this period extended into the beginning of the dry season. Focal animal observations of 1 h per individual were carried out in an alternating order for 3 h in the morning (between 07:30 and 10:30 am) and 3 h in the afternoon (between 02:00 and 05:00 pm). For each focal animal, morning and afternoon sessions together made up one statistical day (i.e. 6 h of observation). We observed each animal for two statistical days in each observation period, resulting in the collection of 860 focal hours (August – October 2013: 418 h, February – May 2014: 442 h). During observations, we recorded social behaviors, such as allogrooming, body contact and proximity of < 1 m and the identities of conspecifics involved (group members as well as roaming individuals), as well as individual behaviors (e.g. feeding, locomotion, resting, autogrooming) continuously. As allogrooming is a directed behavior, we recorded the identity of groomer and groomee.

Social network analysis

Based on the behavioral data, a weighted and directed network was created for each season based on body contact, ingrooming and outgrooming rates (in min/h) between dyads, respectively. Individual degree centrality was calculated as the sum of an individual’s ties, whereas individual strength centrality was calculated as the sum of the weights of these ties. Individual outgrooming strength (i.e. the rate an individual spent allogrooming) and ingrooming strength (i.e. the rate of being groomed) were calculated as the sum of an individual’s weighted in- or outgoing ties, respectively.

Statistical analyses

To assess sex differences in centrality measures, we used node-level permutation-based t-tests using the program UCINET (Borgatti et al. 2002). The permutation-based approach is

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necessary as behavioral measures of actors in social networks are non-independent and thus violate assumptions for standard statistical tests (Croft et al. 2011). Permutation-based tests account for the non-independence of data points by generating a sampling distribution: The scores for the independent variables are randomly assigned to the network measure of interest while keeping the network structure and thus the interdependence of connections intact. The P-value can then be calculated as the proportion of permutations that produce a result as or more extreme than the one observed. To assess sex-differences in autogrooming rates, we used a nonparametric Wilcoxon rank sum test as the data violated assumptions of parametric tests. We then used generalized linear mixed models (GLMMs) with binomial error structure and logit link function to test the influence of several predictor variables on chewing louse and mite infections. We used the complete dataset of 39 sampled individuals to test whether animal sex, age and season of sampling (wet or dry) had an influence on infections with either parasite, controlling for social group as a random factor. For the subset of those animals for which both behavioral data and parasite samples were available (N = 28), we constructed additional binomial GLMMs for each parasite, including group size, body contact strength and ingrooming strength of the sampled individual during the season in which the samples were taken, and social group as a random factor. Full models were compared to null models comprising only the random effect in a likelihood ratio test using the R-function ANOVA with the argument ‘test’ set to ‘Chisq’. Furthermore, we assessed the impact of infection status on autogrooming rates in this dataset using linear mixed models (LMM), controlling for social group as a random effect. Self-grooming rates were log-transformed and significance of the model was assessed by comparison to a null model containing only the random effect in a likelihood ratio test using the R-function ANOVA with the argument ‘test’ set to ‘Chisq’.

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Results

Ectoparasite infections

In total, 5 species of ectoparasites were identified, including 3 species of psoroptid mites, one chewing louse species and one tick species. Prevalence of mites was 79.5 %. These parasites were predominantly found in the inguinal and perianal regions, in the ears and in the arm pits. The following species from the subfamily Makialginae (Acariformes: Psoroptidae) were morphologically identified: Lemuralges intermedius, Gaudalges propitheci and Gaudalges caparti (Figure 1). Only female specimens of G. caparti were found. In many cases, only larvae / nymphs or fragments of mites could be recovered, thus species identification could not always be made. We therefore used only absence / presence of mites for statistical analyses. However, co-infections with at least two different Makialginae species were confirmed in 5 of 35 positive individuals (14.3 %), belonging to different social groups. Mite infection was associated with focal alopecia in 6 cases (19.3 % of infected animals) and with red-colored crusts in the inguinal region in two cases (5.7 %). Chewing lice were located in the skin-folds at the back of the knee, on the chest and in the armpits. They were identified as Trichophilopterus babakotophilus (Ischnocera: Philopteridae; Figure 2). A minimum of 57 % of animals were sampled from each group. Mite-infections were present in all social groups, whereas chewing lice were found on only 43.6 % of animals, and in only 7 of 10 social groups (Figure 3). Neither season, age nor sex had a significant influence on mite infection (GLMM: χ² = 1.39, df = 3, P = 0.71; Table 1) or chewing lice infection (GLMM: χ² = 2.57, df = 3, P = 0.46; Table 1). Ticks were found on only two individuals. Furthermore, these specimens were not attached, but found crawling through the fur. They were identified as nymphs of the species Haemaphysalis (H.) lemuris (Figure 4). No ticks were found in the nostrils, which seem to be a preferred attachment site of H. lemuris in another sifaka species (Klompen et al. 2015).

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Figure 1: Makialginae mites collected from Verreaux’s sifakas at Kirindy Forest, Madagascar, and features used for species identification: Lemuralges intermedius (a.: male, b.: female; 1. distinctly developed opisthosomal lobes with clefts, 2. pretarsi III and IV longer than the

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(Figure 1 continued) respective tarsi, 3. epigynum situated between coxal fields I, 4. Setae h2 longer or equal to setae h3), Gaudalges propitheci (c.: male, d.: female; 5. distinctly developed opisthosomal lobes without clefts, 6. epigynum arch-like, situated between coxal fields II, 7. distinctly developed spurs of tibiae and tarsi III-IV) and Gaudalges caparti (e.: female, f.: detail; 8. pretarsi III and IV shorter than respective tarsi, 9. epigynum situated between levels of coxal fields I and II, 10. ventral spurs of coxal fields I and II present).

Figure 2: Specimen of the chewing louse Trichophilopterus babakotophilus collected from Verreaux’s sifakas at Kirindy Forest, Madagascar.

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Figure 3: Distribution of mite and lice infections among 10 groups of Verreaux’s sifakas in Kirindy Forest. Lines indicate group membership and the spatial arrangement of groups reflects the location of their home ranges. Dashed lines indicate dispersal events that took place the year before or during the study. Notice the clustered pattern of chewing lice infections, with high prevalences in some, but absence of infections in other social groups.

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Figure 4: Nymph of Haemaphysalis lemuris collected from Verreaux’s sifakas at Kirindy Forest, Madagascar.

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Table 1: Results of GLMMs testing the influence of age, sex and season on the probability of being infected with Makialginae mites and the chewing louse Trichophilopterus babakotophilus. Significant P-values are printed in bold.

Term Estimate Std. Error Z-Value P-value Mite infection

Intercept -0.16 1.4 -0.12 0.908

Age 0.1 0.09 1.04 0.295

Sex 0.75 0.91 0.82 0.411

Season 0.59 1.02 0.58 0.56

T. babakotophilus infection

Intercept -2.1 2.15 -0.98 0.327

Age 0.1 0.09 1.06 0.29

Sex 1.53 1.4 1.09 0.277

Season -0.05 1.19 -0.04 0.969

Ectoparasites and animal behavior

Individual body contact strength ranged between 0.1 and 7.8 min/h. We found no sex differences in centrality measures in the body contact network (permutation-based t-test, Table 2). Individual outgrooming and ingrooming strength was low, ranging from 0 to 0.86 min/h and 0 to 0.9 min/h, respectively. Females received significantly more grooming during the dry season, but sex differences in ingrooming strength during the wet season were not significant (permutation-based t-test, Table 2). Furthermore, males had a significantly higher outgrooming degree, i.e. they groomed significantly more partners than females, irrespective of season (permutation-based t-test, Table 2). We did not find any significant influence of ingrooming strength, body contact strength or group size, neither on mite nor on chewing lice

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infections (GLMM, χ² = 6.89, df = 3, P = 0.07 and χ² = 0.96, df = 3, P = 0.81, respectively; Table 3). Autogrooming rates ranged from 0.17 – 1.64 min/h. There was no sex-difference in autogrooming rates (Wilcoxon rank sum test, Nmale = 20, Nfemale = 8, W = 93, P = 0.52). Mite- infected animals groomed themselves significantly more than their non-infected conspecifics, but infection with chewing lice had no influence on autogrooming rates (LMM, χ² = 7.59, df = 2, P = 0.022; Table 4).

Table 2: Results of node-level permutation-based t-tests to assess sex differences in degree and strength centrality in the body contact and grooming networks generated during two seasons. Tests were carried out in UCINET and based on 10,000 permutations. Significant P- values (< 0.05) are printed in bold.

Mean ± standard deviation Network measure P-value males females

Dry season (N = 34): (N = 20) (N=14) Outgrooming degree 2.45 ± 1.07 1.43 ± 1.05 0.016 Ingrooming degree 1.75 ± 0.7 2.36 ± 1.17 0.113 Outgrooming strength 0.27 ± 0.217 0.08 ± 0.1 0.006 Ingrooming strength 0.11 ± 0.12 0.28 ± 0.25 0.009 Body contact degree 3.4 ± 0.92 3.36 ± 0.97 0.999 Body contact strength 2.12 ± 1.96 2.64 ± 1.57 0.433 Wet season (N = 38): (N = 24) (N = 14) Outgrooming degree 2.79 ± 1.04 1.64 ± 0.97 0.003 Ingrooming degree 2.25 ± 0.97 2.71 ± 1.1 0.21 Outgrooming strength 0.29 ± 0.25 0.12 ± 0.1 0.023 Ingrooming strength 0.25 ± 0.23 0.18 ± 0.13 0.304 Body contact degree 3.92 ± 1.29 3.41 ± 0.98 0.272 Body contact strength 1.73 ± 1.54 2.15 ± 2.0 0.489

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Table 3: Results of GLMMs testing the influence of group size and ingrooming strength on the probability of being infected with Makialginae mites and the chewing louse Trichophilopterus babakotophilus.

Term Estimate Std. Error Z-Value P-value Mite infection

Intercept 8.85 4.72 1.87 0.061

Group size at sampling -1.23 0.74 -1.68 0.094

Body contact strength (min / hour) -0.77 0.42 -1.86 0.063

Grooming instrength (min / hour) 5.22 4.22 1.24 0.216

T. babakotophilus infection

Intercept 2.22 3.01 0.74 0.46

Group size at sampling -0.4 0.57 -0.71 0.478

Body contact strength (min / hour) -0.24 0.36 -0.67 0.506

Grooming instrength (min / hour) 1.88 3.2 0.59 0.556

Table 4: Result of LMM testing the influence of ectoparasite infection status on log- transformed autogrooming rates.

Term Estimate Std. Error df t-value P-value

Intercept -1.35 0.3 22.87 -4.49 <0.001 Mite infection 0.92 0.32 22.3 2.91 0.008 Trichophilopterus inf. -0.28 0.28 24.02 -1.01 0.322

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Discussion

We found 5 species of ectoparasites co-infecting Verreaux’s sifakas in Kirindy Forest. Psoroptid mites showed a high prevalence of 79.5 %, while chewing lice were present on 43 % of sampled individuals. We tested whether these infections were influenced by social group size, amount of body contact and the amount of grooming received, as well as host sex, age and seasonality. Because sifakas live in relatively small groups (3 – 7 individuals in this study), social group size is highly correlated with the number of body contact partners. We expected animals living in larger groups to have a higher likelihood of infection due to a greater variety of potential sources for infection, as well as animals which spent more time in body contact, while animals which received more grooming were expected to exhibit a smaller probability of being infected with ectoparasites. However, we could not demonstrate an effect of these social parameters on ectoparasite infection, which is in line with previous results on other gregarious mammals (Arnold and Lichtenstein 1993; Van Vuren 1996; Hillegass et al. 2008; Zhang et al. 2010). Indeed, a previous study on Verreaux’s sifakas concluded that grooming may serve a social rather than a hygienic function in lemurs (Lewis 2010). However, ectoparasites were found predominantly in regions which are difficult to groom – skin folds, ears and armpits – indicating that they may be removed from other body parts via auto- or allogrooming. Although we could not demonstrate a direct effect of social contacts on infection patterns, it is noteworthy that in 3 of 10 social groups, chewing lice infections were not detected, while prevalences ranged from 25 % to 100 % of sampled individuals in the other 7 groups. We were not able to sample all individuals from each group (Figure 2), thus it remains unclear whether these 3 groups were really free from infection. However, if they were, this would indicate that between-group spread of this ectoparasite is limited. Physical contact during intergroup encounters of sifakas is rare (Springer et al., unpublished; Chapter 6 of this thesis) and may not be sufficient for effective transmission. Dispersal would thus represent the most likely route of intergroup transmission. Because lice of the suborder Ischnocera are specialized for life on the host (Johnson and Clayton 2003), environmental factors related to the home ranges of the different groups are unlikely to contribute to this pattern. However, some groups may be more susceptible to infection than others based on dietary differences. These hypotheses remain to be tested on a larger dataset, however.

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As a caveat, we were only able to test our predictions regarding absence / presence of infection. Because chewing lice load was low in all cases and the psoroptid mites in question are not always visible to the naked eye (except adult males), we were not able to assess the influence of our predictors on parasite loads, which might have been more informative. Furthermore, species identification of mites was not always possible. Therefore, infections with different mite species were lumped into the same category, which might have contributed to the overall high prevalence of mite infections and obscured patterns related to ectoparasite species richness. Keeping these limitations in mind, we did not find any significant influences of host sex, age and season on the probability of being infected with either chewing lice or mites. The absence of a sex difference may reflect the absence of sex differences in body mass in Verreaux’s sifakas (Lewis and Kappeler 2005) as well as smaller sex differences in hormone levels in lemurs as compared to other mammals (von Engelhard et al. 2000). Both of these factors are believed to correlate with higher parasitism in males (Moore and Wilson 2002; Klein 2004). Specifically, the immunomodulatory effects of testosterone may underlie increased parasite susceptibility in males (Klein 2004). The absence of a sex difference despite significant differences in grooming behavior between males and females also indicates that grooming probably does not result in effective ectoparasite control. The absence of an age-related infection pattern indicates that young animals can be infected early in life, and that the development of protective immunity is unlikely. Unlike reported in a previous study on rainforest-living diademed sifakas (Propithecus diadema) (Klompen et al. 2015), we did not find any influence of season on ectoparasite infections. However, our data were biased towards the rainy season, with only 9 of 39 animals sampled during the dry season. Ectoparasites may have profound health effects on their hosts. Psoroptid mites cause psoroptic mange in domestic animals (Fain and Hyland 1985), characterized by dermatitis with pruritus, exudation, crust-formation and alopecia (Wall and Shearer 2001), accompanied by eosinophilia and antibody formation (e.g. Stromberg and Guillot 1987; O'Brien et al. 1995; Van Den Broek et al. 2000). In wild primates, psoroptid mites have been reported as the cause of mange-like pathological lesions in howler monkeys (Santa Cruz et al. 2000) and tufted capuchins (Guerim et al. 2001). Focal alopecia, pruritus, crust-formation and excoriation can

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also be symptoms of chewing lice infections of domestic animals, e.g. with Werneckiella equi (e.g. Larsen et al. 2005) and Bovicola bovis (Wall and Shearer 2001). We found focal alopecia in only 6 and crusts in only two of 39 animals, however. These lesions were always associated with mite infection, but not all of these animals were infected with chewing lice. No symptoms related exclusively to chewing lice infections were found. Mite-infected animals also groomed themselves significantly more than non-infected individuals, but this result should be interpreted with caution as there were few non-infected animals in the analysis due to the high prevalence of mite infections. Nevertheless, it may indicate that mites cause pruritus, whereas chewing lice infection had no influence on autogrooming rates. Thus, mite infections may indeed be costly for Verreaux’s sifakas, as increased grooming activity may lead to less vigilance (Cords 1995) and less time spent feeding or resting (Hawlena et al. 2007). We did not find any ticks attached to Verreaux’s sifakas, which seems surprising given the high levels of tick infestation that have been found in another sifaka species in rainforest habitats (Klompen et al. 2015). The dryer climate in Kirindy Forest may be less favorable for tick development, or ticks may prefer other host species in this habitat. However, indirect evidence suggests that Verreaux’s sifakas must be hosts to ticks in Kirindy Forest, as they show a high prevalence of infection with Babesia sp., which are transmitted by ticks (Springer et al., unpublished; Chapter 8 of this thesis).

Conclusions

Verreaux’s sifakas in Kirindy Forest were co-infected with several species of psoroptid mites and one chewing louse species, while ticks were almost absent. We did not find any effects of social group size, the amount of body contact and the amount of grooming received on the probability of infection, nor were animal age, sex or season significant predictors. However, the clustered pattern of chewing louse infections suggests that the animals’ social structure may limit spread of the infection and that dispersal may play a role, which remains to be confirmed on a larger dataset. Likewise, more data are needed to confirm the pattern of increased autogrooming rates due to mite infection, which could suggest that mites cause pruritus and are indeed costly to their hosts.

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Author contributions

Acknowledgements

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8. Manuscript 4:

International Journal of Parasitology: Parasites and Wildlife, in press, doi:10.1016/j.ijppaw.2015.10.006

Hemoparasites in a wild primate: Plasmodium and Babesia interact in a lemur species

Andrea Springera, Claudia Fichtela, Sébastien Calvignac-Spencerb, Fabian H. Leendertzb and Peter M. Kappelera,c

aBehavioral Ecology and Sociobiology Unit, German Primate Center, Kellnerweg 4, 37077 Göttingen, Germany bProject Group “Epidemiology of Highly Pathogenic Microorganisms”, Robert-Koch-Institut, Nordufer 20, 13353 Berlin, Germany cDepartment of Sociobiology and Anthropology, University of Göttingen, Kellnerweg 6, 30077 Göttingen, Germany

Corresponding author: Andrea Springer, Behavioral Ecology and Sociobiology Unit, German Primate Center, Kellnerweg 4, 37077 Göttingen, Germany, Tel.: +49 551 3851 377, [email protected]

Note: Nucleotide sequence data reported in this paper are available in the GenBank™ , EMBL and DDBJ databases under the accession number(s) LN869519 - LN869522.

Key words: Verreaux’s sifakas, Propithecus verreauxi, Plasmodium sp., Babesia sp., hemoparasites, cross-immunity, parasite community

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Abstract

Hemoparasites can cause serious morbidity in humans and animals and often involve wildlife reservoirs. Understanding patterns of hemoparasite infections in natural populations can therefore inform about emerging disease risks, especially in the light of climate change and human disruption of natural ecosystems. We investigated the effects of host age, sex, host group size and season on infection patterns of Plasmodium sp., Babesia sp. and filarial nematodes in a population of wild Malagasy primates, Verreaux’s sifakas (Propithecus verreauxi), as well as the effects of these infections on hematological variables. We tested 45 blood samples from 36 individuals and identified two species of Plasmodium, one species of Babesia and two species of filarial nematodes. Plasmodium spp. and Babesia sp. infections showed opposite patterns of age-dependency, with babesiosis being prevalent among young animals, while older animals were infected with Plasmodium sp. In addition, Babesia sp. infection was a statistically significant negative predictor of Plasmodium sp. infection. These results suggest that Plasmodium and Babesia parasites may interact within the host, either through cross-immunity or via resource competition, so that Plasmodium infections can only establish after babesiosis has resolved. We found no effects of host sex, host group size and season on hemoparasite infections. Infections showed high prevalences and did not influence hematological variables. This preliminary evidence supports the impression that the hosts and parasites considered in this study appear to be well-adapted to each other, resulting in persistent infections with low pathogenic and probably low zoonotic potential. Our results illustrate the crucial role of biodiversity in host-parasite relationships, specifically how within-host pathogen diversity may regulate the abundance of parasites.

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1. Introduction

Vector-borne hemoparasites, including the apicomplexan protozoa Babesia sp. and Plasmodium sp., trypanosomes and filarial nematodes, are important pathogens in humans and domestic animals, causing babesiosis, malaria, sleeping sickness, lymphatic filariasis and canine heartworm disease. Endemic as well as introduced hemoparasites may also impact health and fitness of wildlife (e.g. Custer and Pence 1981; Atkinson et al. 2000; Garvin et al. 2003; Donahoe et al. 2015). Furthermore, babesiosis is an emerging zoonosis worldwide, with wildlife reservoirs playing a particular role in its epidemiology (Gray et al. 2010; Yabsley and Shock 2013). Thus, characterizing hemoparasite infections in wildlife and understanding patterns of prevalence can potentially reveal emerging disease risks, especially in the light of ecological instabilities as a result of human encroachment into wildlife habitats (Daszak et al. 2001; Keesing et al. 2010) and climate change (Daszak et al. 2000; Barrett et al. 2013; Kronefeld et al. 2014). Wild primate populations are of particular interest in this context, because nonhuman primates have played a major role in the emergence of human diseases, including malaria, in the past (Wolfe et al. 2007; Pedersen and Davies 2009; Pacheco et al. 2011). Age, sex or seasonal effects may have an influence on exposure and susceptibility to infection with many parasites. Age effects have been demonstrated for Plasmodium sp. infections in chimpanzees and humans (Doolan et al. 2009; De Nys et al. 2013) and for Babesia sp. infections in dogs and cattle (Boozer and Macintire 2003; Bock et al. 2004), with decreasing prevalence in older animals being most likely due to the development of an effective adaptive immune response (Frölich et al. 2012). Additionally, the innate immune system is an important controlling factor of apicomplexan parasite infectivity (Frölich et al. 2012) and variation in immune responsiveness may thus influence infection patterns. Sex differences in hemoparasite infections have been found in several vertebrates, including higher prevalences in male penguins (Merkel et al. 2007), lizards (Schall et al. 2000) and lions (Sherman 2010). These sex differences could either be due to physiological differences, e.g. immunosuppression caused by higher testosterone levels in males (Klein 2004; Roberts et al. 2004), or due to differences in parasite exposure. For example, a sex-bias in vector feeding rates towards males was recently demonstrated in birds (Burkett-Cadena et al. 2014). Although hemoparasite infections have been investigated in several wild primate

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species (De Thoisy et al. 2001; Maamun et al. 2011; De Nys et al. 2013; Thurber et al. 2013), no sex-differences in prevalence have been reported so far. Furthermore, it has been proposed that group-living may decrease the risk of infection with vector-borne pathogens by means of an encounter-dilution effect, analogous to a decrease of predation risk (Freeland 1976; Mooring and Hart 1992; Kappeler et al. 2015). Empirical evidence for this effect is controversial, however. Krebs et al. (2014) recently demonstrated that sentinel hosts caged inside large roosts of American robins seroconverted to West Nile Virus more slowly than those held outside of roosts, suggesting that exposure of individual hosts can indeed be reduced through group-formation. However, larger groups may also be more conspicuous, and thus attract more vectors. In a comparative study, colonially- breeding bird species were shown to experience both higher prevalences and higher species diversity of blood parasites than solitarily breeding species (Tella 2002). Two studies on Neotropical primates found that prevalence of Plasmodium sp. increases with group size (Davies et al. 1991; Nunn and Heymann 2005), but studies on the effect of within-species variability of group size on hemoparasite infections in primates are lacking. Furthermore, infections with vector-borne parasites are likely to covary with environmental conditions (Altizer et al. 2006). Rainfall and temperature affect mosquito abundance, biting rates and parasite development within mosquitoes (Altizer et al. 2006; Galardo et al. 2009; Mohammed and Chadee 2011). Additionally, dry, cold conditions as well as frequent temperature fluctuations can reduce the abundance of host-seeking ticks (Sutherst and Bourne 2006; Swai et al. 2006; Herrmann and Gern 2013). Despite this seasonality in vector biology, empirical evidence regarding seasonal variation in host infection rates is contradictory and mainly limited to malaria in humans (Smith et al. 1993; Koram et al. 2003; Mabaso et al. 2007). If transmission results in persistent infections, little seasonal variation in prevalence can be expected (Govender et al. 2011). Finally, in natural systems co-infections with multiple parasites are common, potentially resulting in complex interspecific interactions. It has been shown that parasite community interactions may explain more variation in infection risk than the effects associated with host and environmental factors. For example, in field voles (Microtus agrestis) chronic infection with Babesia microti reduces susceptibility to Bartonella spp. bacteria by 85 % as compared to uninfected individuals (Telfer et al. 2010). Parasites may

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directly affect the fitness of co-infecting species through interference competition, they may compete for the same resources within a host, or affect each other’s abundance via interaction with the host’s immune system (Pedersen and Fenton 2006). Cross-immunity between co- infecting parasite species might limit prevalence at the population level, whereas parasite- induced immunosuppression may lead to synergistic effects (Cox 2001; Telfer et al. 2008). We present the first study which systematically characterizes infections with several co-occurring hemoparasites in a population of Malagasy primates, Verreaux’s sifakas (Propithecus verreauxi). Madagascar faces acute risks of species extinctions as well as disease emergence in humans and wildlife due to intense human disruption of natural ecosystems (Harper et al. 2007; Junge 2007; Barrett et al. 2013; Ratsimbazafy et al. 2013; Schwitzer et al. 2014). Verreaux’s sifakas are diurnal, sexually monomorphic lemurs which live in multi-male multi-female groups of varying size in seasonal habitats, in which mosquitoes are virtually absent for several months of the year, in western and southern Madagascar (Kappeler and Fichtel 2012). The life expectancy of sifakas in the wild can exceed 20 years (Richard et al. 2002; Kappeler and Fichtel 2012). We used samples collected from members of all age classes from 10 adjacent groups ranging in size from 2 to 7 individuals during annual captures to detect infections with Plasmodium sp., Babesia sp. and filarial nematodes using a combination of a PCR-based approach and microscopical examination of blood smears. These parasites have previously been reported to occur in blood samples of sifakas (Uilenberg et al. 1972; Junge and Louis 2005; Duval et al. 2010; Pacheco et al. 2011; Rasambainarivo et al. 2014), but systematic investigations of infection patterns are lacking. The potential vectors for Plasmodium spp. and Babesia spp., anopheline mosquitos and haemaphysaline ticks, are present in the study region (Davidson 1966; Rodriguez et al. 2012), whereas the vectors for filarial parasites of lemurs are unknown (Irwin and Raharison 2009). To illuminate natural drivers of infection patterns, we tested the influence of host age and sex, host group size and seasonality on individual infection status and hemoparasite species richness in our study population. To assess possible health consequences, we also tested the influence of these infections on packed cell volume, to assess possible anemia, and total plasma protein as well as the neutrophil-lymphocyte ratio, which are usually increased during inflammatory processes (Thrall et al. 2006). Based on results of previous studies with

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other vertebrates, we predicted that infection probabilities would decrease with age and that males would harbor more hemoparasites than females. Furthermore, we predicted that group size would negatively affect the probability of testing positive for each hemoparasite, as well as individual hemoparasite species richness, in case of an encounter-dilution effect. Alternatively, we predicted that group size would have a positive effect on these measures if larger groups attract more vectors. We also expected to find lower prevalences of hemoparasite infections during the dry season than during the hot, wet season.

2. Materials and methods

2.1. Sample collection

The study was carried out in Kirindy Forest, Western Madagascar, located at approximately 44°39’E, 20°03’S. The study area is part of a field site operated by the German Primate Center (DPZ) since 1993 and is situated within a forestry concession managed by the Centre National de Formation, d’Etudes et de Recherche en Environnement et Foresterie (CNFEREF). Kirindy Forest is a dry deciduous forest and subject to pronounced seasonality, with a dry season from April to October and a hot, wet season from November to March (Kappeler and Fichtel 2012). As part of an ongoing long-term study (Kappeler and Fichtel 2012), several social groups of Verreaux’s sifakas have been habituated to human observers and individually marked with microchips and unique collars. A total of 45 blood samples were taken from 36 individual Verreaux’s sifakas belonging to 10 social groups during routine immobilization procedures in April 2013, August 2013, March 2014 and April 2014. Group sizes ranged from 2 to 7 individuals, and a minimum of 43 % of individuals were sampled from each group. Seven animals were repeatedly sampled at intervals of 4 to 5 months, resulting in a maximum of 3 samples per individual (Table 1). Blood was collected from the femoral vein into anti-coagulant EDTA tubes. Packed cell volume was determined by centrifuging EDTA blood in a microhematocrit capillary using a Sigma 1-14 centrifuge (Sigma Laborzentrifugen GmbH, Osterode am Harz, Germany) and total plasma protein was estimated using a hand-held refractometer. Two to 3 blood smears were prepared per individual, air dried, stained (Diff Quick stain, Eberhard

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Lehmann GmbH, Berlin, Germany) and preserved with mounting medium (Eukitt, FLUKA Analytics, Sigma-Aldrich Chemie Gmbh, Munich, Germany) and a cover slip. Blood smears were scanned for the presence of hemoparasites and used for a differential white blood cell count to assess the percentages of the following leukocyte categories: Neutrophils, banded neutrophils, lymphocytes, monocytes, eosinophils and basophils. Photographs were taken with a Zeiss AxioCam ERc 5s fitted to a Zeiss Primo Star microscope (Carl Zeiss AG, Oberkochen, Germany). Measurements were made using the Zeiss Zen lite 2012 software (Carl Zeiss AG) after calibration with a stage micrometer. An aliquot of blood was mixed with the same amount of RNAlater and frozen at -20°C until shipment to Germany and further analysis. All necessary research permits were obtained from the Malagasy and German authorities and the study was approved by the Ethics Committee of the German Primate Center.

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Table 1: Details of sampling and infection patterns. Individuals are ordered by age. X denotes a positive infection, while -- denotes a negative sample.

ID age sex group group size sampling date season Plasmodium Babesia Onchocercidae (years) sp. 1 sp. 2 Bet 1 m C 4 11-Apr -14 wet ------Buf 1 m F1 6 26-Mar-13 wet -- X -- -- Col 1 m F 5 25-Mar-13 wet ------Dav 1 m H 4 11-Apr-14 wet -- X -- -- Fre 1 m F 6 11-Apr-14 wet -- X -- -- Gay 1 f L 4 12-Apr-14 wet -- X -- -- Kam 1 f J 7 26-Mar-13 wet -- X -- -- Man 1 m C 4 25-Mar-13 wet -- X -- -- Win 1 m G 6 11-Apr-14 wet -- X -- -- Yon 1 m J 7 11-Apr-14 wet -- X -- -- Zwo 1 m S3 7 25-Mar-13 wet -- X -- -- Gan 4 m L 4 23-Apr-14 wet -- X X -- Ich 4 m J 6 20-Aug-13 dry -- X -- -- Mor 4 m H 4 19-Mar-14 wet -- X X X Aug 5 f E 4 10-Sep-13 dry -- X X -- Aug 6 f E 4 12-Mar-14 wet -- X X -- Hel 5 f F 5 26-Mar-13 wet -- -- X X Hon 5 m G 4 21-Aug-13 dry ------X Nov 5 f G 6 11-Apr-14 wet -- X X -- Ven 5 m S3 6 13-Apr-14 wet ------Bor 6 m S3 6 13-Apr-14 wet X -- X X Kan 6 m F1 3 14-Apr-14 wet -- X -- X Kyu 6 m G 6 11-Apr-14 wet X X X -- Lin 6 m F1 5 20-Aug-13 dry -- X -- -- Sen 6 m J 6 21-Aug-13 dry X -- -- X Sen 7 m J 7 13-Mar-14 wet X X X X Ten 7 m C 4 11-Apr-14 wet -- X X -- Zur 9 m G 5 16-Apr-13 wet -- -- X X Zur 9 m G 4 21-Aug-13 dry X -- X X Zur 10 m G 5 13-Mar-14 wet X -- X X Goa 10 f L 3 26-Mar-13 wet -- -- X X Mel 10 m E 6 16-Apr-13 wet X -- X -- Mel 10 m E 5 20-Aug-13 dry X -- X X Sis 11 f E 6 28-Mar-13 wet X X X X Fra 12 m F 5 21-Aug-13 dry X -- X -- Fra 12 m F 6 12-Mar-14 wet X -- X -- Boc 13 m C 4 20-Aug-13 dry X -- X X Boc 14 m C 4 13-Mar-14 wet X -- X X Sav 14 f F1 6 26-Mar-13 wet X ------Swa 14 f S2 2 14-Apr-14 wet X -- X --

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Table 1 continued

ID age sex group group size sampling date season Plasmodium Babesia Onchocercidae (years) sp. 1 sp. 2 Maf 16 m L 3 22-Aug -13 dry X -- X -- Sap 19 m H 3 16-Apr-13 wet X -- X -- Sap 19 m H 3 22-Aug-13 dry X ------Sap 20 m H 4 11-Apr-14 wet X -- X -- Yok 21 f J 7 11-Apr-14 wet X -- -- X

2.2. DNA extraction, PCRs and sequence analyses

DNA was extracted from RNAlater-preserved blood samples using the QIAmp Blood Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. To test for the presence of Plasmodium spp. in blood samples, a semi-nested PCR was carried out targeting an approximately 1000 bp long fragment of the parasite’s cytochrome b gene. In the first amplification round, primers P.sp.cytB F1 (5’-TGC CTA GAC GTA TTC CTG ATT ATC CAG; Kaiser et al. (2010)) and P.sp.cytB R1 (5’- CTT GTG GTA ATT GAC ATC CWA TCC; Kaiser et al. (2010)) were used, followed by P.sp.cytB F2 (5’-ATT GGD TCA ACW ATG ACT TTA TTT GG) and P.sp.cytB R1 in the second round. The 25 µl reaction mixture contained1 µl of DNA-extract or PCR-product (diluted 1:40) from the first round, respectively, 2.5 µl 10x PCR buffer (Invitrogen, Karlsruhe, Germany), 2 µl of 50 mM

MgCl2 (Invitrogen, Karlsruhe, Germany), 2 µl of 2.5 mM deoxynucleotide triphosphates (Thermo Scientific Fermentas, St. Leon-Rot, Germany), 0.5 µl of each primer (10µM) and 0.2 µl of Platinum Taq polymerase (Invitrogen, Karlsruhe, Germany). The thermal profile was the same for both rounds, with an initial denaturation step at 95°C for 5 minutes followed by 40 cycles of 95°C for 30 seconds, 58°C for 45 seconds and 72°C for 60 seconds, and a final elongation step at 72°C for 10 minutes. We tested for Babesia spp. using primers BJ1 (5'-GTC TTG TAA TTG GAA TGA TGG-3') and BN2 (5'-TAG TTT ATG GTT AGG ACT ACG-3'), targeting a 500 bp long fragment of the 18S rRNA gene (Casati et al. 2006). We used 5 µl of DNA-extract in a 25 µl reaction mixture containing the same quantities of reagents as stated above. The thermal profile consisted of an initial denaturation step at 94°C for 10 minutes followed by 40 cycles

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of 94°C for 60 seconds, 55°C for 60 seconds and 72°C for 2 minutes, and a final elongation step at 72°C for 5 minutes. To generate sequences for microfilaria observed in blood smears, we employed a nested PCR targeting an approximately 900 bp long fragment spanning part of the 18S rRNA gene, the internal transcribed spacer 1 (ITS1) and part of the 5.8S rRNA gene. Primers used were NF1 (5’-GGT GGT GCA TGG CCG TTC TTA GTT-3’) (Porazinska et al. 2009) and NC2 (5’-TTA GTT TCT TTT CCT CCG CT-3’) (Gasser et al. 1993; Chilton et al. 2003) in the first round and a modification of ITS1-F (5’- TTG ATT ACG TCC CTG CCC-3’) (Vrain et al. 1992; Bisset et al. 2014) and the filaria-specific Di5.8S-R (5’-ACC CTC AAC CAG ACG TAC-3’) (Nuchprayoon et al. 2003; Nuchprayoon et al. 2005) in the second round. The 25 µl reaction mixture contained 5 µl of DNA-extract in the first round and 1 µl PCR-product (diluted 1:40) in the second round, and the same quantities of reagents as in the other PCRs. The thermal profile of the first round consisted of an initial denaturation step at 95°C for 5 minutes followed by 35 cycles of 94°C for 60 seconds, 58°C for 30 seconds and 72°C for 60 seconds, and a final elongation step at 72°C for 10 minutes. The thermal profile of the second round consisted of an initial denaturation step at 94°C for 10 minutes followed by 35 cycles of 94°C for 30 seconds, 55°C for 30 seconds and 72°C for 60 seconds, and a final elongation step at 72°C for 10 minutes. PCRs were run in a FlexCycler thermal cycler (Analytic Jena, Jena, Germany) and amplification products were detected by electrophoresis on 1.5 % agarose gels. Positive and negative controls were included in all PCRs. PCR products of the corresponding size were purified from 2 % agarose gels using the JETQUICK Gel Extraction Spin Kit (Genomed, Löhne, Germany) and Sanger sequencing of both strands was performed by Seqlab Sequence Laboratories Göttingen GmbH (Göttingen, Germany). Sequences were analysed using Geneious v6.1.6 (Biomatters Ltd., Auckland, New Zealand) and compared to publicly available sequences using BLAST (Altschul et al. 1990). New sequences were deposited in the EMBL Nucleotide Sequence Database (Kulikova et al. 2004), under accession numbers LN869519 - LN869522. For Plasmodium sequences, we also performed phylogenetic analyses. The two unique sequences identified in this study were put together with the representative sequences selected by Pacheco et al. (2011), which includes all sequences derived from lemur Plasmodium

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available to this date. We used jModelTest v2.1.4 to identify the model of nucleotide substitution with the best fit to the data (GTR+I+G4; (Darriba et al. 2012). We then reconstructed a maximum likelihood tree under this model using PhyML v3 (Guindon et al. 2010), as implemented on the PhyML webserver (Guindon et al. 2005). Branch robustness was assessed through non-parametric bootstrapping (500 bootstrapped pseudo-replicates; Bp). Patristic distances were calculated using Geneious v6.1.6 (Biomatters Ltd.).

2.3. Statistical analyses

We used generalized linear-mixed models (GLMMs) with binomial error structure and logit link function to analyse which factors influenced the probability of testing positive for each parasite species. We included sex, age, season (wet or dry) and size of the animal’s social group as fixed effects and individual identity nested in group as a random effect. Furthermore, we ran a GLMM with Poisson error structure and log link function to test influences on hemoparasite species richness, including the same fixed and random effects. Based on results of the GLMMs for Plasmodium and Babesia infections, we used another GLMM with binomial error structure to test whether Babesia infection status had an effect on Plasmodium infection, again controlling for individual identity nested in group. To assess potential health impacts, we first tested whether age affected hematology values, using Spearman rank correlation, and then used linear mixed models (LMMs) to test influences of infection with each hemoparasite and hemoparasite species richness on log-transformed packed cell volume, total plasma protein and the log-transformed neutrophil : lymphocyte ratio, controlling for animal age and individual identity nested in group as a random effect. We compared each full model to a null model comprising only the random effect in a likelihood ratio test using the R- function ANOVA with the argument ‘test’ set to ‘Chisq’.

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3. Results

3.1. Plasmodium infections

Thirteen of 36 individuals tested PCR-positive for Plasmodium spp. infection. Seven individuals were tested more than once, and repeated sampling at different times of the year almost always gave identical results for these animals. Only results for one animal (age 9) switched from negative to positive during the study period. Population prevalence is thus estimated at 36 %. We did not observe any parasite stages in Diff-quick®-stained blood smears. Only two unique sequences were amplified in this study, which showed 95 to 100 % sequence identity to publicly available Plasmodium sequences. Most sequences could be unambiguously assigned to Plasmodium sp. LLD-2010 which has previously been found in Verreaux’s sifakas (Duval et al. 2010). Two animals carried a different parasite (EMBL accession no.: LN869522), which unambiguously nested within the clade of malaria parasites infecting lemurs (Bp 100; Figure 1). This parasite appeared as most closely related to Plasmodium sp. C-MAP-2012 (which has been found in Hapalemur griseus (Pacheco et al. 2011)), although the statistical support for this association was moderate (Bp 59; Figure 1). The patristic distance between these two sequences was 0.21 substitution per site (s.s-1), which is both higher than the 0.17 s.s-1 observed between the two most closely related lemur parasite sequences known to date (Plasmodium sp. B-MAP.2012 and E-MAP-2011) and higher than the maximum 0.14 s.s-1 observed between P. reichenowii (clade C1, infecting chimpanzees) and P. praefalciparum sequences (clade G1, infecting gorillas; Rayner et al. 2011). Coinfections with both lemur malaria parasites were not observed. Age seemed to affect Plasmodium spp. test outcome, with older animals being more likely to test positive (Figure 2). In fact, none of the animals up to the age of 5 years were infected (n = 18), 50 % of animals between age 6 and 10 were infected (n = 10) and all animals over the age of 10 tested positive (n = 8). However, in the GLMM including age as well as sex, season and group size as fixed factors, age only tended to have a statistically significant effect (Table 2). Sex, season and group size had no significant effect on Plasmodium spp. infection status.

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50. The 50. is inscale

on Tree continues next page.

bstitution site.bstitution per tree of malaria parasite cytochrome b sequences. The clade formed by lemur malaria parasites is blue. The two two The blue. is parasites malaria lemur by formed clade The sequences. b cytochrome parasite malaria likelihood of tree Maximum 1: Figure > when branches above reported are values Bootstrap rectangles. grey with are highlighted study in this detected sequences su

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The clade formed by lemur malaria parasites is blue. The two sequences detected in this study are highlighted with grey grey with are highlighted study this in detected sequences two The blue. is parasites malaria lemur by formed clade The

continued. continued. Figure 1 rectangles.

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Figure 2: Age-dependence of Babesia sp. infections (grey) and Plasmodium sp. infections (black). The lines represent the predicted values according to the two different GLMMs.

Table 2: Results of GLMM testing the influence of different predictor variables on the probability of being infected with Plasmodium spp. Significant P-values are printed in bold. Likelihood ratio test comparing the full model to a null model containing only the random effect: χ² = 37.2, df = 4, P < 0.001. Significant P-values are printed in bold.

Term Estimate Standard error z P

Intercept -28.59 16.76 -1.71 0.088 Sex 0.06 2.99 0.02 0.98 Age 1.86 0.98 1.89 0.059 Group size 3.3 2.3 1.43 0.153 Season -2.68 2.41 -1.11 0.267

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3.2. Babesia infections and potential Plasmodium – Babesia interaction

Prevalence of Babesia infections was 55.6 %. Again, test results for only 1 individual (age 7) changed from negative to positive during the study period. The Babesia sequence amplified (EMBL accession no. LN869519) was the same in all samples and showed 94 % identity to different Babesia canis isolates. We did not microscopically observe any Babesia parasite stages in Diff-quick®-stained blood smears. Only age significantly affected Babesia sp. test outcome, but contrary to the Plasmodium sp. infections, young animals were more likely to test positive (Table 3, Figure 2). Only 3 animals (6, 7 and 11 years old) were co-infected with Plasmodium sp. and Babesia sp. Based on this complementary age pattern, the low number of co-infections, and because neither age, sex, season nor group size influenced Plasmodium spp. infections, we tested Babesia infection status as a predictor of Plasmodium infection, and found a highly significant negative effect (Table 4).

Table 3: Results of GLMM testing the influence of different predictor variables on the probability of being infected with Babesia sp. Significant P-values are printed in bold. Likelihood ratio test comparing the full model to a null model containing only the random effect: χ² = 23.7, df = 4, P < 0.001.

Term Estimate Standard error z P Intercept 1.08 2.72 0.4 0.692 Sex -1.51 1.29 -1.16 0.244 Age -0.49 0.22 -2.2 0.028 Group size 0.35 0.5 0.71 0.479 Season 1.7 1.49 1.14 0.254

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Table 4: Results of GLMM testing the influence of Babesia sp. infection on the probability of being infected with Plasmodium spp. Significant P-values are printed in bold. Likelihood ratio test comparing the full model to a null model containing only the random effect: χ² = 9.21, df = 1, P = 0.002.

Term Estimate Standard error z P Intercept 9.14 2.89 3.17 0.002 Babesia infection -19.52 5.16 -3.78 <0.001

3.3. Filarial nematode infections

Two different filarial nematode species could be differentiated morphologically as well as genetically. Two to 3 blood smears per sample were scanned for microfilaria and on average 4.2 microfilaria were measured per sample. Microfilaria of species 1 were 268 ± 10.1 µm long with the nerve ring located at 53 ± 4.5 µm from the anterior end. Microfilaria of species 2 were considerably shorter, 222 ± 18.6 µm, with the nerve ring located at 43 ± 5.4 µm. Sequencing of PCR products confirmed the presence of two different species. Species 1 produced a shorter band of about 850 bp and species 2 produced a longer band of about 900 bp. The bands could be separated out using 2 % agarose gels, and individually sequenced. The sequences (EMBL accession no. LN869520 and LN869521) showed 99 – 100 % sequence identity to different filarial nematodes such as Mansonella sp., Dirofilaria sp. and Onchocerca sp. in the conserved 18S and 5.8S regions, but only 84 – 90 % similarity to other filarial nematodes in the variable ITS1 region. In 33 of 45 samples, the PCR results exactly confirmed the morphological diagnosis (negative sample, presence of one or both species). In 7 cases, a species was morphologically identified but not detected by PCR, while in 5 cases an infection was revealed by PCR only. Thus, neither method seems to be 100 % sensitive. For statistical analyses, we considered an infection present if it was detected by one of the methods. Prevalence of species 1 was 50 %, while species 2 was found in 33.3% of animals. Nine animals (25 %) were co-infected with both species. No filarial nematode infections were

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detected in animals under the age of one year. Probability of infection with species 1 significantly increased with age (Table 5). We did not find any significant influences on infection with the second species (Table 5).

Table 5: Results of GLMMs testing the influence of different predictor variables on the probability of being infected with two different filaria species (family Onchocercidae). Significant P-values are printed in bold. Likelihood ratio tests comparing full models to null models containing only the random effect: Onchocercidae sp. 1: χ² = 12.07, df = 4, P = 0.016; Onchocercidae sp. 2: χ² = 1.63, df = 4, P = 0.802.

Term Estimate Standard error z P Onchocercidae sp. 1 Intercept -0.67 2.4 -0.28 0.78 Sex 0.02 0.97 0.03 0.98 Age 0.24 0.1 2.48 0.013 Group size -0.38 0.39 -0.96 0.338 Season 1.36 1.06 1.28 0.202

Onchocercidae sp. 2 Intercept -3.88 10.88 -0.36 0.721 Sex -0.25 4.41 -0.06 0.956 Age -0.14 0.43 -0.33 0.739 Group size -0.69 1.84 -0.38 0.707 Season -3.68 4.59 -0.8 0.422

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3.4. Hemoparasite species richness

We tested whether host age, sex, season or group size affected the number of hemoparasite species found in each individual, but we did not find any statistically significant influences (Table 6).

Table 6: Results of GLMM testing the influence of different predictor variables on hemoparasite species richness. Likelihood ratio test comparing the full model to a null model containing only the random effect: χ² = 3.7, df = 4, P = 0.45.

Term Estimate Standard error z P Intercept 0.1 0.59 0.18 0.859 Sex -0.03 0.25 -0.13 0.897 Age 0.04 0.02 1.92 0.054 Group size 0.04 0.09 0.45 0.65 Season 0.07 0.26 0.27 0.79

3.5. Hematologic values

Hematology results are summarized in Table 7. Packed cell volume and total plasma protein were significantly positively correlated with the animals’ age (Spearman rank correlation, N = 44, ρ = 0.44, P = 0.003, and N = 43, ρ = 0.4, P = 0.008, respectively) and the ratio of neutrophils to lymphocytes tended to be positively correlated with age (Spearman rank correlation, N = 45, ρ = 0.26, P = 0.08). Controlling for age, we did not find any significant influences of infection with any single parasite species on packed cell volume (PCV; Table 8), and hemoparasite richness also did not influence PCV (Table 9). Likewise, total plasma protein (TP) was neither significantly influenced by infection with any single parasite species (Table 8), nor by hemoparasite species richness (Table 9).

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The ratio of neutrophils to lymphocytes (NLR) was 0.47 ± 0.22 (range: 0.15 – 1.25). No single infection influenced log-transformed NLR values (Table 8) and hemoparasite richness was also not a significant predictor (Table 9). The percentage of eosinophils was 0.96 ± 0.91 (range: 0 – 4.5), which is in the range of published values for Propithecus sp. (Bergeron and Buettner-Janusch 1970; Junge and Louis 2005; Irwin et al. 2010; Rasambainarivo et al. 2014). We thus concluded that no eosinophilia was present.

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40 max 1 7.4 43

81.5 2.5 0.5 - 20.67

0 -

0 - 0 - 29 - 5.4 - 49 - 12.5 - min 1.5 -

0.29 0.54 9.98 5.27 3.44 0.87 0.14 11.66 4 year olds (N = 14) 4 = (N olds year

- 1 standard deviation standard

mean 0.14 6.39 8.35 1.06 0.06 65.72 25.16 35.14

max 49

- 2 7.6 47 1 20.3 4.5 76.5 0 - 0 - 39.5 - 35 - 0 - min 6.2 - 17.5 - 1.5 -

0.53 7.78 8.51 0.38 4.37 2.74 0.91 0.19 Adults (N = (N 31) Adults standard deviation standard

mean 0.41 6.83 7.36 39.4 1.07 0.05 28.88 62.37

max 81.5 2 49 7.8 47

4.5 0.5 - 20.67 0 - 0 - 0 - 14 - 29 -

5.4 - min 39.5 - 1.5 -

9.95 0.49 4.75 8.88 0.49 0.91 3.58 0.18 All animals (N = 45) = (N animals All standard deviation standard

mean 0.33 7.77 6.68 0.96 0.05 63.37 27.64 38.05

Lymphocytes Lymphocytes (%) Monocytes (%) Monocytes Neutrophilic Neutrophilic granulocytes, (%) segmented Neutrophilic granulocytes, banded (%) Eosinophilic Eosinophilic granulocytes (%) Total plasma plasma Total protein (g/dl) Table 7: Hematology results for Verreaux’s sifakas captured at Kirindy Forest, Madagascar. Forest, Kirindy at captured sifakas Verreaux’s for results 7: Hematology Table cell Packed (%) volume Basophilic granulocytes (%)

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Table 8: Results of LMMs testing the influence of infection with each parasite species on hematology results. Packed cell volume and the neutrophil : lymphocyte ratio were log- transformed. Significant P-values are printed in bold. Likelihood ratio tests comparing full models to null models containing only the random effect: PCV: χ² = 7.9, df = 5, P = 0.16; TP: χ² = 9.3, df = 5, P = 0.1; NLR: χ² = 7.6, df = 5, P = 0.18.

Standard Term Estimate df t P error Packed cell volume Intercept 3.55 0.04 33.45 85.86 <0.001 Plasmodium 0.004 0.04 28.54 0.09 0.929 Babesia 0.04 0.04 35.34 1.05 0.303 Filaria 1 0.01 0.03 26.95 0.47 0.64 Filaria 2 -0.02 0.03 33.91 -0.53 0.603 Age 0.008 0.005 36.93 1.77 0.085 Total plasma protein Intercept 6.6 0.21 32.3 31.05 <0.001 Plasmodium 0.09 0.23 32.31 0.39 0.698 Babesia -0.22 0.19 36.07 -1.15 0.258 Filaria 1 0.27 0.16 33.64 1.68 0.101 Filaria 2 -0.02 0.17 32.02 -0.11 0.911 Age 0.002 0.02 29.52 0.11 0.912 Neutrophil : lymphocyte ratio Intercept -1.01 0.21 34.87 -4.7 <0.001 Plasmodium 0.15 0.19 32.31 0.76 0.452 Babesia -0.05 0.18 36.23 -0.29 0.776 Filaria 1 -0.02 0.16 38.97 -0.15 0.885 Filaria 2 -0.03 0.15 27.77 -0.22 0.829 Age 0.02 0.02 26.56 0.92 0.366

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Table 9: Results of LMMs testing the influence of hemoparasite species richness on hematology results. Packed cell volume and the neutrophil : lymphocyte ratio were log- transformed. Significant P-values are printed in bold. Likelihood ratio tests comparing full models to null models containing only the random effect: PCV: χ² = 6.06, df = 2, P = 0.05; TP: χ² = 6.1, df = 2, P = 0.047, χ² = 6.7, df = 2, P = 0.036.

Standard Term Estimate df t P error Packed cell volume (PCV) Intercept 3.57 0.03 36.12 115.45 <0.001 Hemoparasite 0.01 0.02 33.12 0.75 0.46 species richness Age 0.006 0.003 30.43 1.87 0.072 Total plasma protein (TP) Intercept 6.39 0.17 30.81 38.26 <0.001 Hemoparasite 0.06 0.08 35.76 0.82 0.42 species richness Age 0.03 0.01 22.06 1.89 0.072 Neutrophil : lymphocyte ratio (NLR) Intercept -1.07 0.16 30.02 -6.64 <0.001 Hemoparasite 0.0003 0.07 32.66 0.004 0.997 species richness Age 0.03 0.01 18.74 2.49 0.022

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4. Discussion

We identified 5 putative species of hemoparasites in Verreaux’s sifakas in Kirindy Forest: 2 species of malaria parasites, only one of which has been previously identified in Verreaux’s sifakas by means of PCR (Duval et al. 2010), the other one likely standing for a yet undetected and undescribed species; one species of Babesia; and 2 species of filarial nematodes. As sequences of Babesia parasites and filarial nematodes from Madagascar are not publicly available to date, we could not assign species names to our sequences. Morphological descriptions of microfilaria found in lemurs were ambiguous (Irwin and Raharison 2009). Of the 4 species described in lemurs, which all belong to the family Onchocercidae, species 1 could either be Dipetalonema petteri or Protofilaria furcata, while measurements for species 2 fall into the range described for Paulianfilaria pauliani. We did not recover any adult worms, as dissections of animals were not possible in this study, and the insufficient quality of blood smears did not allow us to use further microfilaria characteristics for identification. However, genetic analyses confirmed the presence of two different filaria species in the population. We found high prevalence of infection with Babesia sp. in wild Verreaux’s sifakas under the age of 5, while infections with Plasmodium sp. were absent from this age class, although most, but not all individuals of this age class were sampled during the wet season, when mosquitoes are abundant. This is unusual, as it has been found in humans and chimpanzees that younger animals usually have higher Plasmodium sp. prevalences and that prevalence decreases with age, possibly due to naturally acquired immunity (Doolan et al. 2009; De Nys et al. 2013). We found no indication of age-related immunity to Plasmodium sp. in Verreaux’s sifakas. In our study, animals older than approximately 10 years showed 100 % Plasmodium sp. prevalence, but no Babesia sp. infections. Only 3 animals (6, 7 and 11 years old) were co-infected with both parasites, and Babesia sp. infection was a statistically significant negative predictor for Plasmodium sp. infection. Juveniles under the age of one year were never PCR-positive for filarial nematodes, nor were microfilaria observed in their blood-smears. However, we cannot exclude the possibility that these animals were already infected, as the prepatent period of filarial nematodes, i.e. the period from infection to appearance of reproductive parasite stages in the

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blood, may span several months (Bowman and Georgi 2009). Therefore, the result that age significantly affects filarial infections should be treated with caution. An additional caveat concerning filarial infections should be kept in mind. Neither PCR nor microscopic examinations of blood smears seem to be sensitive enough to reliably detect filarial infections in all cases, so we combined the results of both methods. In cases of low parasitemia, PCRs produced some false-negatives although single microfilaria were identified in the corresponding blood smears, and species differentiation based on microfilaria morphology only is difficult, because the length ranges of both species may potentially overlap. This could have led us to misdiagnose infections in some cases and we might have missed statistically significant effects on filaria infections or hemoparasite species richness, as well as the effects of those on hematology values. Sex did not influence infection with any single species, nor species richness, indicating that males are neither more susceptible to infections nor more exposed. Although sex-biased patterns of parasitism, including the parasite taxa examined in this study, seem to exist in many mammals (Klein 2004), this effect does not seem to be universal (Kiffner et al. 2013). Specifically, sifakas do not display sexual size dimorphism (Kappeler 1990), which has been proposed to relate to sex differences in parasite susceptibility in general (Moore and Wilson 2002), while larger bodied hosts may also attract more vectors (Davies et al. 1991). Furthermore, male and female sifakas, like other lemurs with female dominance, exhibit smaller differences in androgen levels than other mammals (von Engelhard et al. 2000; Drea 2007), indicating that sex-specific endocrine-immune interactions may be less pronounced. We tested whether host social group size influenced infection with each single hemoparasite species as well as hemoparasite species richness, but we did not find any significant effect. Group sizes in this study ranged from 3 to 7 individuals, and this range may have been too small to detect any differences, although small group-size differences should have a more pronounced effect on individual infection risk in small groups. Thus, our data do not support the encounter-dilution hypothesis, nor the opposing prediction that larger groups attract more vectors, which was supported by two studies of Plasmodium sp. prevalences across Neotropical primates with group sizes ranging from 3 to 29 individuals (Davies et al. 1991; Nunn and Heymann 2005).

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We also did not find any effect of seasonality, neither on Plasmodium sp. infections nor on infections with any of the other parasites, although fewer mosquitoes are present during the dry season. This indicates that infections are persistent for at least several months. Persistent infections as well as long developmental times of the parasite within the host, as might be the case for filarial nematodes, may mask seasonal effects. Because of the opposite patterns of age-dependency of Plasmodium and Babesia infections, and because Babesia sp. infections were a significant negative predictor for Plasmodium sp. infections, we suggest that infection with Babesia sp. may be a natural protectant against Plasmodium sp. in this lemur species. As sifakas in Kirindy give birth during the dry season, when almost no mosquitoes are present, juveniles likely acquire Babesia sp. infections via tick-bites, probably of Haemaphysaline ticks, which occur in western Madagascar (Rodriguez et al. 2012) and have been detected on sifakas during animal captures, before they become exposed to Plasmodium sp. Until babesiosis resolves, e.g. due to antibody-mediated immunity (Frolich et al. 2012), they seem to be naturally protected against Plasmodium sp. infections. The suppression of malaria infections in the course of ongoing babesiosis has been investigated in rhesus macaques (Macaca mulatta) in laboratory settings (van Duivenvoorde et al. 2010), after it was found that a macaque infected with a Babesia microti-like parasite showed a suppressed Plasmodium cynomolgi infection (Wel et al. 2008). Heterologous immunity between the two parasites has also been observed in mice (Cox 1978; Zivkovic et al. 1984). It has been proposed that the cross-protection is most likely due to immune responses such as the activation of a distinct class of pro-inflammatory monocytes, release of pro-inflammatory cytokines, and increased C-reactive protein levels, which potentially play an important protective role in malaria infections (Clark 2001; Ansar et al. 2006; van Duivenvoorde et al. 2010). It has also been proposed that this heterologous immunity might be exploited for the development of malaria vaccines. However, an interaction between Plasmodium and Babesia could also arise due to resource competition within the host. In fact, in humans it has been shown that co-infecting parasites mostly interact in this way (Griffiths et al. 2014). Both parasites invade and replicate in erythrocytes and both of them modify the erythrocytic membrane to achieve higher permeability, but do so using different mechanisms and at different time points after invasion

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(Alkhalil et al. 2007). Changes in membrane permeability induced by Babesia infection may thus make subsequent infection with Plasmodium sp. impossible and lead to a competitive advantage for Babesia sp. However, B. microti parasites suppressed P. cynomolgi parasitemia without altering the induction of initial anemia in rhesus macaques, suggesting the malaria parasites could enter erythrocytes during an infection with Babesia (van Duivenvoorde et al. 2010). The lack of positive microscopic observation of both Babesia and Plasmodium stages in the blood smears of infected individuals may partially result from technical limitations, but probably also indicates that parasitemia was generally low. This may suggest that if competition occurs, the parasites only compete for a narrow erythrocyte subset. While the precise mechanism of interaction remains unclear, the pattern found in our study provides the first indication of a possible protective effect of babesiosis on malaria infections in a wild population of primates naturally infected with both parasites, thus adding external validity to the above observation. Finally, we did not find any signs of morbidity caused by the parasites tested in this study. Only animal age affected hematology values, a common pattern also in primates (McPherson 2013). Packed cell volume was not significantly affected by infection with any single hemoparasite species nor by hemoparasite species richness, indicating that these parasites do not cause clinically relevant anemia. The absence of anemia may be explained by the long coevolutionary history between hemoparasites and their hosts, leading to a complete dependence of the parasite on the host for survival, which favours long-lasting asymptomatic infections with low parasitemia (Chauvin et al. 2009; Frölich et al. 2012). Furthermore, evidence has been found that co-infection with filarial nematodes may attenuate anemia associated with clinical malaria in humans (Dolo et al. 2012). We did not detect signs of inflammation, either. Total plasma protein and the neutrophil-lymphocyte ratio were not affected in a statistically significant way. Acute inflammation usually causes an increase in plasma globulin concentrations, which may reflect in increased total plasma protein levels, as well as an increase in neutrophilic granulocytes (Thrall et al. 2006). However, the neutrophil-lymphocyte ratio may be affected in both directions by an excitement response with epinephrine release due to animal capture, as leucocytes are released from the marginal into the circulating pool (Thrall et al. 2006), which may have masked effects due to parasitism. Eosinophils typically show an increase as a

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response to helminth infection (Nutman 2007), and high values have been measured in the course of filarial infections in dogs and humans (Mackenzie 1980; Niwetpathomwat et al. 2007). Elevations may also occur in the course of babesiosis (Vercammen et al. 1997). The relative counts of eosinophils were not markedly elevated in any of the animals in this study, judging by comparison with previously reported values from both captive and wild Propithecus sp. populations (Bergeron and Buettner-Janusch 1970; Junge and Louis 2005; Irwin et al. 2010; Rasambainarivo et al. 2014). However, this conclusion remains preliminary as we were not able to obtain absolute leucocyte counts due to restrictions of fieldwork.

Conclusions

In conclusion, prevalences of hemoparasite infections in Verreaux’s sifakas in Kirindy Forest, Madagascar, are significantly related to host age, probably shaped by interaction between Babesia sp. and Plasmodium sp., but independent of host sex, host group size and season. The possible cross-protection between Babesia sp. and Plasmodium sp. is a prime example of how biodiversity may affect the ecology of infectious diseases. Increasing evidence has accumulated that biodiversity may have a buffering role on disease transmission, while biodiversity loss is thought to increase transmission, disease incidence and disease emergence (Daszak et al. 2001; Ostfeld 2009; Keesing et al. 2010; Vourc’h et al. 2012). In this case, the presence of tick-borne babesiosis seems to reduce Plasmodium sp. prevalence in a natural system, illustrating how within-host pathogen diversity may regulate the abundance of parasites. Infection status did not influence hematology values, suggesting that the parasites considered in this study do not cause clinically relevant anemia or inflammation, but that hosts and parasites are well-adapted to each other, resulting in persistent infections with low pathogenic potential.

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Acknowledgements

We thank the team of the Kirindy field station, especially Rodin Rasoloarison and Léonard Razafimanantsoa, and the Malagasy Ministère de l’Environnement et des Eaux et Forêts, the Département Biologie Animale de l’Université d’Antananarivo, and the Centre National de Formation, d’Etudes et de Recherche en Environnement et Foresterie for supporting and authorizing and our long-term research in Kirindy. We are grateful to J. Hirzmann for valuable advice on PCR protocols and for providing positive controls for filarial nematodes and to M. Sakowsky for help with microscopic measurement of microfilaria. This research was funded by the Deutsche Forschungsgemeinschaft (Ka 1082/29-1) and the German Primate Center and has profited from numerous discussions in the research group “Sociality and Health in Primates” (FOR 2136).

Author contributions

AS, CF, FHL, SCS and PMK designed the study. AS conducted the field work, analyzed the samples and drafted the manuscript. AS and CF performed the statistical analyses. SCS performed the phylogenetic analysis. All authors contributed to and approved the final manuscript.

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Parasites, defined here as “any organism that lives on and draws nutrients from another organism (the host)” (Nunn and Altizer 2006), may impose substantial costs on their hosts, be it in the form of energy-drainage, pathological lesions or even death. Increasing evidence suggests that the characteristics of parasite spread in wild animal populations are affected by their behavior, and that incorporation of these aspects into epidemiological models may dramatically alter model predictions. However, empirical evidence regarding the impact of animal behavior on patterns of parasitism, in relation to other influences, like host traits and seasonality, remain limited in many host-parasite systems, although this information is needed in order to improve and validate model predictions. Furthermore, assessing the impact of animal behavior in general, and animal social structure in particular, on parasite transmission may shed light on the evolutionary causes for these behaviors, and their costs and benefits. Here, a wild population of a group-living, arboreal primate species, Verreaux’s sifaka, was chosen as a study system to investigate the impact of host behavior on parasite spread under natural conditions, in relation to host traits and seasonality. Parasites with 3 different transmission modes were investigated, because the impact of a certain behavior on transmission may be parasite-specific, depending on the parasite’s transmission mode and biological characteristics. Furthermore, baseline data about parasites naturally infecting wild animals are needed in order to fuel comparative studies (Altizer et al. 2003), as well as to provide insights into the role of infectious diseases as possible conservation threats and into their zoonotic potential, especially in the light of anthropogenic change (Leendertz et al. 2006; Smith et al. 2009). This study has thus added valuable information on the occurrence of different parasites in a species belonging to the most endangered group of mammals, the lemurs of Madagascar (Schwitzer et al. 2014). However, this assessment of parasite occurrence could not be exhaustive during the duration of this study. Several other infectious agents are worth investigating, which might be present in the population, for example due to contact with humans or livestock, but were not included here due to time limitations. This would also help to further assess the risks of parasite spillover into this endangered primate species (Andriaholinirina et al. 2014).

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Here, fecal-orally transmitted infectious agents were studied as well as ectoparasites and vector-borne hemoparasites. In total, 11 parasite taxa were identified, including one intestinal helminth species, one tick species, 3 species of psoroptid mites, one chewing louse species, two Plasmodium species, one Babesia species and 2 filarial nematodes. Entamoeba sp. may have been present in the population for a short time-period, but this needs to be confirmed in future studies. Not all parasites could be identified to the species level, as comparative genetic sequences from parasites of lemurs were not available, and, in the case of nematodes, no adult parasite stages were discovered. Furthermore, the Diff Quick® staining method of blood smears did not allow the use of morphologic characteristics to identify hemoparasites to the species level. The majority of infections appeared to be asymptomatic. All animals seemed to be in good health and fecal samples were firm in the majority of cases, including those tested positive for Entamoeba sp. The dominating cause of death for sifakas at Kirindy Forest is predation by Madagascar’s largest carnivore, the fossa (Cryptoprocta ferox, Kappeler and Fichtel 2012). As a consequence, corpses are rarely found at this study site, and necropsies including histological examinations to demonstrate pathologic lesions associated with endoparasites could not be conducted during the study period. Among ectoparasites, only mite infections were associated with focal alopecia in 19.3 % and crusts in 5.7 % of infected animals. Mite-infected individuals also groomed themselves significantly more than the few non-infected individuals, indicating that psoroptid mites may cause pruritus in Verreaux’s sifakas, potentially reducing vigilance and time spent resting or feeding. Hemoparasite infections were not associated with changes in hematological values indicative of anemia or inflammation, suggesting that these parasites and their hosts are well-adapted to each other, resulting in asymptomatic, long-term persistence, which can be advantageous for parasites in order to achieve efficient transmission (Chauvin et al. 2009). Still, further investigations into the costs associated with parasites of Verreaux’s sifakas are needed. Even if a single infection appears to be of low virulence, the cumulative effect of parasites on their host may be substantial and decrease lifespan and lifetime reproductive success (Nunn and Altizer 2006). Here, data on individual life histories and pedigrees, which are collected during the ongoing long-term study on Verreaux’s sifakas at Kirindy Forest, will be useful to relate measures of parasitism to individual fitness.

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In addition to the parasites mentioned above, Escherichia coli, which is a common member of the gut microbiome in most mammals, but may also be a pathogen (Tenaillon et al. 2010), was used as a model organism to study the influence of social structure on fecal- oral transmission. In a pilot-study, detection of viruses was also attempted. Because of rapid evolutionary dynamics, simian foamy viruses (SFVs) represent useful model organisms to link animal social relationships with transmission histories (Blasse et al. 2013). However, no SFVs were found in the 12 blood samples of Verreaux’s sifakas initially tested by polymerase chain reaction (PCR). Therefore, this approach was not pursued further and the results of this assay are not included in the present thesis. Likewise, detection of polyomaviruses from skin swabs and adenoviruses from fecal samples was attempted using established PCR methods, but was equally unpromising. Nonetheless, in the previous chapters several factors influencing patterns of parasitism in Verreaux’s sifakas could be identified: the animals’ arboreal lifestyle, their social structure, and host age in combination with possible parasite community interactions. In this chapter, the principal results will be discussed in a broader context, and their implications beyond the study system will be highlighted. Limitations of the current study will be assessed, leading to suggestions for future research.

Arboreality: a strategy to avoid parasites?

In previous studies of wild sifakas, few or no intestinal parasite stages were discovered in fecal samples (Muehlenbein et al. 2003; Rasambainarivo et al. 2014), and comparison with more terrestrial, sympatric lemur species suggested that the genus’ primarily arboreal lifestyle may act as a buffer against environmentally transmitted infectious agents (Loudon 2009). Additionally, Verreaux’s sifakas do not drink from terrestrial water bodies, but rely entirely on the water content of their diet and the dew present on vegetation, a behavior which may limit contact with water-borne infectious agents. This ecological particularity might make the genus also less vulnerable to pathogen spillover from domestic animals and humans via this route. Spillover of pathogens into wildlife populations represents an emerging threat to biodiversity, as well as to human and domestic animal health, because new disease reservoirs may be created from which spillback events can occur (Daszak et al. 2000; Thompson 2013).

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In this study, Verreaux’s sifakas from Kirindy Forest exhibited little diversity of intestinal parasites, and little indication of successful pathogen spillover via environmental transmission. During microscopic analysis of unpreserved fecal samples as well as formalin- fixed fecal samples subjected to sedimentation and flotation, only eggs of a strongylid morphotype were discovered. Therefore, cultured third-stage larvae were genotyped to investigate potential cryptic species diversity. This approach has previously been used to reveal co-infections with multiple strongylid species in wild primates (Ghai et al. 2014; Metzger 2015). However, sequencing of the ITS+ region including both the internal transcribed spacer 1 and 2, which are commonly used to distinguish helminth species (Lott et al. 2012; McLean et al. 2012; Bisset et al. 2014), revealed no cryptic diversity. Thus, the animals seemed to harbor only one intestinal helminth species, belonging to the family Trichostrongylidae, at high prevalence both during the dry and the wet season. Because the population is subject to anthropogenic influences in the form of research, tourism and occasionally presence of local people and their livestock, the presence of potentially zoonotic protozoa was investigated using PCR, although no protozoans were microscopically observed. PCR is regarded as the most sensitive detection method (Webster et al. 1996; Stensvold and Nielsen 2012). Only 17 of 228 samples were positively tested for Entamoeba histolytica / nuttalli, and at the moment the possibility cannot be excluded that these positive results were due to laboratory contamination. Alternatively, infections may have been prevalent during March 2014, affecting all 8 social groups, but were then eliminated by the hosts, as all subsequent samples from the same individuals were negative. Unfortunately, neither samples nor behavioral observations were available from November 2013 through February 2014, so that the possible duration of infections, their clinical impact, as well as their potential source, could not be determined. Further samples need to be tested to clarify whether Entamoeba sp. infections do indeed occur in the population, and whether the species in question is Entamoeba histolytica or E. nuttalli, which do not differ in the genetic sequence amplified here and which may both be pathogenic for primates (Tachibana et al. 2007). Cryptosporidium sp., which would be of concern due to high morbidity and potential mortality of the corresponding infections in captive sifakas (Charles-Smith et al. 2010), were not detected in the 132 samples tested. Cryptosporidium sp. has been found in lemurs near

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Ranomafana National Park in eastern Madagascar, greater bamboo lemurs (Prolemur simus) and eastern rufous mouse lemurs (Microcebus rufus) (Rasambainarivo et al. 2013), but the Mile-Edward’s sifakas (Propithecus edwardsi) tested were negative. Furthermore, the presence of antimicrobial resistance in zoonotic bacteria isolated from wildlife may be regarded as an indicator of pathogen spillover, since wildlife rarely comes into direct contact with antimicrobials (Rwego et al. 2008; Guenther et al. 2011). Escherichia coli isolates recovered from wild sifakas in this study predominantly belonged to novel, yet undescribed multi-locus sequence types (MLSTs), and did not show multidrug resistance due to production of extended-spectrum beta-lactamases (ESBLs), although ESBL- producing E. coli are prevalent in the human population in Madagascar (Rakotonirina et al. 2013). This resistance mechanism has been on a worldwide rise in E. coli isolated from humans as well as domestic animals during the last decades and has been discovered in wildlife E. coli from 2006 on (Guenther et al. 2011). Further antibiotic susceptibility testing, including the most widely used resistance-causing substances in Madagascar (Randrianirina et al. 2014), on isolates belonging to a potentially zoonotic MLST type of major clinical importance in humans, ST131, showed full susceptibility. Thus, it seems unlikely that human E. coli have successfully spread to Verreaux’s sifakas at this study site, although comparison with E. coli isolates from humans who regularly visit the area, e.g. research staff and tourist guides, would be needed to further strengthen this preliminary conclusion. Two studies on another sifaka species also indicate lower levels of successful pathogen spillover as compared to sympatric, more terrestrial lemurs. Milne-Edward’s sifakas at Ranomafana National Park have been tested for zoonotic enteropathogenic bacteria (Bublitz et al. 2014) and diarrhea-associated viruses (Zohdy et al. 2015). They were negative for bacteria like Shigella spp., Yersinia spp. and Salmonella enterica, in contrast to some of the other lemur species studied, and harbored only 3 of 5 viral groups tested, while sympatric, more terrestrial brown lemurs (Eulemur rubriventer and Eulemur rufifrons) harbored all 5 viral groups. Regarding both bacteria and viruses, mouse lemurs (Microcebus rufus) showed the highest prevalences. Both Eulemur sp. and Microcebus sp. also occur in sympatry with Verreaux’s sifakas in Kirindy Forest, where they harbor a high diversity of intestinal helminths (Clough 2010; Schwensow et al. 2010).

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Taken together, these results indicate 1.) that ecological differences may result in differences in parasite exposure between arboreal and terrestrial species and 2.) that cross- species transmission via the fecal-oral route between these lemur species may be limited, although they share the same habitat. In this study, only samples from Verreaux’s sifakas were investigated, however. To further test these hypotheses, it would be required to take samples from multiple terrestrial and arboreal species in the same area and to investigate a variety of enteric parasites and pathogens to which all species should in principle be susceptible. Other mainly arboreal lemurs sympatric with Verreaux’s sifakas at Kirindy Forest include sportive lemurs (Lepilemur ruficaudatus) and fork-marked lemurs (Phaner pallescens), whose parasite communities remain unexplored. Further pathogens of interest include diarrhea-associated viruses and enteropathogenic bacteria, as found in lemurs of Ranomafana National Park (Bublitz et al. 2014; Zohdy et al. 2015). Investigating these pathogens would at the same time serve to evaluate risks of pathogen spillover into the ecosystem, especially since redfronted lemurs (Eulemur rufifrons) occasionally come into contact with human feces (Claudia Fichtel, personal communication). Furthermore, MLST- genotyping of E. coli, as detailed in Chapter 6, could serve here to elucidate cross-species transmission. Evidence from other ecosystems also indicates that arboreality might indeed act as a buffer against soil- and water-borne infectious agents. Exclusively arboreal mammals showed significantly lower levels of Toxoplasma gondii seroprevalence than sympatric terrestrial species in French Guiana (de Thoisy et al. 2003), and highly arboreal purple-faced langurs (Semnopithecus vetulus) were found to be negative for Cryptosporidium sp., in contrast to other, more terrestrial primates in the same study area in Sri Lanka (Ekanayake et al. 2006). Habitat fragmentation and habitat loss seemed to have different effects on parasite prevalence and richness in arboreal Tana river red colobus (Procolobus rufomitratus) compared to more terrestrial mangabeys (Cercocebus galeritus galeritus) in coastal forests in east Africa, with a smaller effect on parasitism in red colobus (Mbora and McPeek 2009). However, care should be taken before this observation is generalized and used to set conservation priorities. Across primate species, Nunn et al. (2003) could not find a significant effect of substrate use on helminth parasite species richness, indicating that it might depend on the ecosystem and the biology of the parasites in question whether arboreality has a

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protective effect on the risk of helminth infection. Verreaux’s sifakas in Kirindy Forest had a high prevalence of Trichostrongylidae, which develop in the environment, despite low rates of ground contact. This may be due to the fact that infectious larvae cling to the fur of some animals, are then spread within a social group via body contact, and ingested during oral grooming. Furthermore, the seasonal variation in the degree of arboreality – the animals spent significantly more time on the ground during the dry season – did not translate into higher prevalence or species richness of intestinal parasites during the dry season. Thus, arboreality alone probably cannot account for the low species richness of intestinal parasites, and further aspects need to be studied. For example, it remains unclear why intestinal parasites detected in Verreaux’s sifakas at other study sites, e.g. Oxyuridae (Rasambainarivo et al. 2014) which do not require a maturation period in the environment but can be transmitted directly from host to host, were absent in this population. Another factor responsible for the low diversity of intestinal parasites in Verreaux’s sifakas in comparison to sympatric lemurs might be their folivorous diet. In contrast to sifakas, Microcebus sp. regularly feed on arthropods (Atsalis 1999; Dammhahn and Kappeler 2008), which may serve as intermediate hosts for helminths or as vectors for other infectious agents, and Eulemur sp. do so at least occasionally (Schnoell and Fichtel 2013). Nunn et al. (2003) did not find a significant effect of insectivory on parasite species richness across primates, however, but their meta-analysis excluded lemurs and lorises, a major group of insectivorous primates. In summary, arboreality seems to shape intestinal parasitism in Verreaux’s sifakas, which is characterized by low species richness of intestinal parasites and little indication of parasite spillover, including the absence of antibiotic-resistant Escherichia coli strains found in this study. However, other aspects related to the biology of the host and the ecosystem likely contribute to this phenomenon.

Social behavior and directly transmitted infections

Because many parasites exploit host social behavior for transmission, increased exposure to parasites has been proposed as one of the major costs of sociality, scaling with population density (Alexander 1974; Anderson and May 1982; Anderson et al. 1986). In recent years,

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however, it has become evident that the structure of social networks and the nature of social relationships may be more important for transmission than animal density per se (e.g. Altizer et al. 2003; Griffin and Nunn 2012; Rifkin et al. 2012; Manlove et al. 2014). Therefore, it was an initial goal of this project to link specific social behaviors, like body contact and grooming, to parasite infection probabilities. For example, it has been shown in Japanese macaques (Macaca fuscata) that grooming relationships affect the probability of infection with the nematode Strongyloides fuelleborni (MacIntosh et al. 2012). To this end, direct observations were conducted in the study population at Kirindy Forest to construct social networks with regard to body contact and grooming. However, the low species richness of intestinal parasites and the high prevalence of around 90 % of Trichostrongylidae sp. precluded linking these networks to nematode infection probabilities, because there was almost no variability in the response. Egg-counts were not used, because the relationship between fecal egg count and infection intensity is not well established in primates, and considerable intra-individual variation may occur, for example with respect to time of day (Melfi and Poyser 2007). In principle, ectoparasitic mites and lice represent ideal candidate parasites to study the impact of social behavior on transmission, because they can only be transmitted via direct host-to-host contact, and may be removed via grooming. Three different species of psoroptid mites and one species of chewing louse were found in the population, but due to the small size of mites and the fact that only larval stages were recovered from some individuals, individual ectoparasite species richness and ectoparasite loads could not be determined. Infections with different mite species were lumped into the same category and only the probability of being infected with mites and with chewing lice was analyzed, and this was neither significantly influenced by animal age, sex and season, nor by social group size, amount of body contact or amount of grooming received. Thus, a direct influence of these social behaviors on parasite transmission could not be shown. However, support was found for social structure and intergroup relationships as important determinants of infection patterns. The pattern of evidence from Verreaux’s sifakas presented in this thesis lends support to the social barrier hypothesis, according to which social groups can be regarded as “biological islands” with distinct parasite communities, whereas intergroup transmission is limited (Freeland 1979; Loehle 1995). Multi-locus sequence typing (MLST) was used to infer transmission pathways of enteric bacteria based on

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the genetic similarity of Escherichia coli isolates from different individuals. The distribution of E. coli MLST sharing in the population has provided a clear indication that fecal-oral parasite transmission is shaped by social structure in these group-living primates. Sharing of MLST types was most prevalent within groups, so that social groups can be regarded as microbiological units. Although it could not be statistically distinguished whether between- group spread of E. coli is mediated by intergroup encounters or by environmental transmission in zones of home-range overlap, the low rates of direct contact during encounters, together with the low rates of ground contact and avoidance of terrestrial water sources, leading to a generally low potential for environmental transmission as detailed above, indicate that anogenital scent-marking may play a role here. Scent-marking has already been evoked as a transmission route for oxyurid nematodes in lemurs (Irwin and Raharison 2009). Scent-marking, olfactory inspection of scent-marks and overmarking are important means of social communication in lemurs (Kappeler 1998), as well as New World primates (Heymann 2006) and other mammals (e.g. voles: Ferkin 1999; mongooses: Jordan et al. 2011). Thus, this type of indirect social contact deserves more attention with regard to transmission processes, and detection of infectious agents from scent- marks should be attempted in future studies. During direct observations, swabs could be taken from the scent-marking sites of sifakas and subjected to microbiological culture. Taking a sequence of samples from the same spot could also help to clarify for how long enteric microorganisms remain viable after deposition of the scent-mark, and, thus, whether home range overlap, overmarking or direct social contact constitutes the most likely route of transmission between social groups. In addition to fecal-orally transmitted microorganisms, the spread of ectoparasites might also be affected by social structure in Verreaux’s sifakas, although this inference is based on relatively weak data and needs to be investigated further with additional data. Occurrence of chewing lice, which are transmitted only by direct host-to-host contact, was limited to 7 of 10 social groups, while no infections were recorded in the other 3, although more than 50 % of animals from each group were sampled. This clumped pattern may indicate that between-group spread of this parasite, too, is limited by low rates and brief durations of direct contact during intergroup encounters. Dispersing animals would thus represent the most likely route of intergroup chewing lice transmission. While movement of

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animals between herds has long been identified as a major risk factor for infectious disease spread in livestock (e.g. Gilbert et al. 2005; Ortiz-Pelaez et al. 2006), evidence for dispersal as a transmission mechanism in natural host-parasite systems is limited. However, dispersal has been linked to ectoparasite spread in cliff swallows (Petrochelidon pyrrhonota, Brown and Brown 2004) and to increased incidence of bovine tuberculosis in badgers (Meles meles, Vicente et al. 2007). During the data collection period for this project, only two animals transferred between study groups, and an additional animal dispersed into an unmarked group adjacent to the study population. This small dataset unfortunately precluded any analysis of the role of dispersers for parasite spread in this study. To what extent intergroup relationships may influence the magnitude of epidemic disease spread is illustrated by outbreaks of Ebola virus infection in wild populations of great apes: Mortality rates from Ebola differed between chimpanzees (Pan troglodytes) and gorillas (Gorilla gorilla) from the same study region; chimpanzees showed a mortality rate of 86 %, while it reached 96 % for gorillas (Walsh et al. 2009). Walsh et al. (2009) suggested that differences in the social structure of these ape populations might have been responsible for the observed differences in mortality rates, rather than differences in disease susceptibility or contact with reservoir hosts. The spatial pattern and time-scale of die-offs suggested that chimpanzees, which live in fission-fusion societies, are highly territorial and have little intergroup social contacts, maintained less chains of transmission, while high-rates of inter-group contacts in gorillas may have facilitated disease spread. Social barriers may on the one hand constrain the size of disease outbreaks, but depending on the characteristics of the disease, socially mediated transmission may on the other hand also be detrimental for the population. If group sizes are independent of population size, then animals that remain after the death of group-mates are expected to form new groups or join existing ones, creating new transmission chains and causing disease invasion thresholds based on animal density to disappear (Manlove et al. 2014). For example, group break-ups have been witnessed in Verreaux’s sifakas after predation events, with remaining animals joining neighboring groups within a matter of weeks (Kappeler and Fichtel 2012). In this sense, increased population susceptibility to infectious diseases can indeed be regarded as a cost of living in groups, but this cost seems to depend not only on the transmission mode of

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the disease, but also on other disease characteristics, like the duration of the infectious period and mortality rate. Therefore, it is crucial to know whether the spread of certain diseases is influenced by social structure in the light of species conservation; and information on the social structure of hosts, the stability of social groups and inter-group relationships should be incorporated into epidemiological models. Theoretical models are useful tools to explore the characteristics of disease spread under different scenarios and evaluate intervention strategies (Hethcote 2009). Data gathered on social contacts and ranging behavior in this population of Verreaux’s sifakas could be used to parameterize an epidemiological model and answer further questions, for example how dispersal events might affect parasite spread, or under which conditions introduced pathogens, like Cryptosporidium sp., which causes severe disease in captive sifakas (Charles-Smith et al. 2010) but has not yet been detected in wild members of the genus, might establish in the population. Finally, it has to be considered that this study focused on animal behavior as a mediator of parasite exposure, and potential differences in host susceptibility were only taken into account with regard to host traits like age and sex. However, social variables may also influence host susceptibility to parasites, and may have masked patterns of increased exposure. Specifically, the role of social stress, reflected in altered patterns of glucocorticoid hormone secretion, needs to be addressed in future investigations. Changes in glucocorticoid hormone regulation due to social stressors are known to affect health and immune system functionality in humans and other mammals (Capitanio et al. 1998; Miller et al. 2002; Cavigelli and Caruso 2015), but empirical data on the relationship between social behavior, glucocorticoid hormone levels and parasite infections in wildlife remains equivocal (e.g. Hoby et al. 2006; Muehlenbein 2006; MacIntosh et al. 2012). Glucocorticoid hormone metabolites have successfully been measured in fecal samples of Verreaux’s sifakas in the past and linked to social and environmental influences (Fichtel et al. 2007), as a next step their role regarding susceptibility to parasites should be assessed, for example by relating them to individual parasite species richness. In summary, support was found for social structure and intergroup social contacts as an important determinant of direct parasite transmission, exemplified by the spread of Escherichia coli, in this system. Given that transmission via environmental reservoirs seems

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to be less likely, this indicates that gregariousness may indeed come with the cost of direct parasite transmission in group-living, arboreal primates.

Social group size and vector-borne infections

In addition to directly transmitted infections, sociality may also influence vector-borne infections by either reducing or enhancing attack rates of arthropod vectors (Mooring and Hart 1992; Tella 2002; Nunn and Heymann 2005). In this study, social group size could not be related to infection probabilities with vector-borne parasites, however. Neither probability of infection with any single hemoparasite species nor hemoparasite species richness decreased with increasing social group size, as would have been expected under the “encounter-dilution hypothesis” (Mooring and Hart 1992). A positive relationship with group size was also not observed, which would have been expected if larger groups attract more vectors, a pattern which has been found in a comparative phylogenetic study across New World primates (Nunn and Heymann 2005). Thus, living in groups seems to be neither costly nor beneficial with regard to hemoparasite infections in Verreaux’s sifakas, which live in relatively small groups of 2 – 9 individuals. In conclusion, it seems likely that increased attraction of vectors, or encounter-dilution effects, only occur in larger groups, consistent with the fact that effect sizes of animal group size on overall parasite species richness increased with maximum group sizes in a meta-analysis (Rifkin et al. 2012).

Inter-specific parasite interactions: an important determinant of infection patterns

In natural systems, hosts are usually infected by more than one parasite species at a time, and it should not be forgotten that these co-infecting parasites can influence one another. For example, the presence of one parasite species can positively or negatively affect the fitness of another via resource competition, cross-immunity, immunosuppression or a shift in the Th1- Th2-response (Pedersen and Fenton 2006). In this study, hemoparasites were investigated because a link between social group size and risk of infection with vector-borne parasites has been proposed (Mooring and Hart

151 9. General Discussion

1992). Five different species of hemoparasites were detected, including two Plasmodium, one Babesia and two filarial nematode species. An effect of group size on infection patterns was not found, but the infection patterns of Babesia and Plasmodium could be explained best by negative interaction between these two parasite taxa. Only 3 animals were co-infected, Babesia and Plasmodium infections showed opposite patterns of age-dependency and Babesia infection was a statistically significant negative predictor of Plasmodium infection probability. Whether this potential interaction is due to cross-immunity, as suggested by an experimental co-infection study in rhesus macaques (Macaca mulatta, van Duivenvoorde et al. 2010), or resource competition remains speculative and should be the subject of future research. Thus, last but not least, interactions between co-occurring parasites may be important determinants of prevalence patterns and should be taken into account when interpreting them. These interactions may mask other factors influencing parasite exposure or susceptibility, like group size in this case. Furthermore, this example illustrates the important role biodiversity may play in the ecology of infectious diseases. Biodiversity loss has been recognized as one of the driving forces of disease emergence and increased disease prevalence (Daszak et al. 2001; Ostfeld 2009; Keesing et al. 2010; Vourc’h et al. 2012), and the pattern found in the present study illustrates how parasite diversity may limit prevalences of individual parasites in an intact ecosystem. Although both Babesia and Plasmodium seemed to be little pathogenic in this case, as hematological parameters indicative of anemia or inflammation were not significantly influenced by infection status, the consequences should one of the players in this interaction be removed – e.g. due to disappearance of the vector – cannot be foreseen. For example, Plasmodium might be more virulent in young, immunologically naive individuals, which currently seem to be protected from Plasmodium establishment due to the presence of Babesia, than in adults. Thus, although parasites are often regarded as something detrimental, they often play important regulatory roles in natural systems. They may allow several species to coexist in an ecosystem by regulating host abundance (Hudson et al. 2006; Nunn and Altizer 2006), they drive host genetic diversity (Spurgin and Richardson 2010) and they may exert regulatory forces on other parasites, as illustrated by the Plasmodium-Babesia-example. From this point

152 9. General Discussion

of view, it should be of concern that a loss of parasite species has been recognized in threatened as compared to non-threatened primates (Altizer et al. 2007).

Conclusions

This study was undertaken to characterize parasitic infections in wild Verreaux’s sifakas and to identify the relative roles of host behavior and social structure, host traits and seasonal climatic conditions regarding infection patterns. Eleven parasite taxa were identified, including one intestinal helminth species, 5 ectoparasite and 5 hemoparasite species; and the animals’ arboreal lifestyle, their social structure and host age in combination with potential parasite community interactions were identified as the main factors shaping this parasite community. Arboreality likely results in lower exposure to environmentally transmitted parasites as compared to sympatric, more terrestrial species, which was reflected by the low species richness of intestinal helminths and the absence of antibiotic-resistant Escherichia coli strains. A comparative analysis of more environmentally transmitted infectious agents in sifakas and sympatric lemur species, as well as data from comparative systems, would help to confirm this notion. Further studies are also needed to confirm the potential presence of Entamoeba histolytica / nuttalli in the ecosystem. Furthermore, support was found for social structure as an important determinant of fecal-oral transmission, exemplified by the spread of Escherichia coli, in this system. Here, direct and indirect social contacts seem to be more important than transmission via environmental reservoirs, indicating that gregariousness may indeed come with the cost of parasite transmission in this system. For between-group transmission, scent-marking and subsequent overmarking may play a previously underestimated role, a hypothesis which needs to be tested explicitly in future studies. In contrast, sociality does not seem to influence vector-borne infections in this system. Animal group sizes had no significant influence on infections with hemoparasites, indicating that group-living in sifakas neither represents a cost nor a benefit in this context. Finally, the fact that Plasmodium sp. infections seemed to be negatively influenced by Babesia infection status highlights that parasitic infections should not be examined in

153 9. General Discussion

isolation, as concomitant infections may have a major impact on patterns of prevalence, potentially masking effects due to individual differences in susceptibility or exposure. Future studies are needed to continue describing the parasite community of these lemurs and to assess further influences on individual susceptibility to infection, like patterns of glucocorticoid hormone secretion. Continued investigations are also necessary to monitor the risks of pathogen spillover into this population of endangered primates, which is continuously exposed to anthropogenic influences.

154 Summary

Summary

Patterns of parasitism in wild Verreaux’s sifakas (Propithecus verreauxi) at Kirindy Forest, Madagascar: Assessing the role of host behavior

Andrea Springer

Parasites, including viruses, microorganisms, arthropods and helminths, may impose substantial costs on their hosts. Increasing evidence suggests that the characteristics of parasite spread in wild animal populations are affected by host behavior, and that incorporation of these aspects into epidemiological models may dramatically alter model predictions. However, empirical evidence regarding the impact of animal behavior on patterns of parasitism, in relation to other influences, e.g. host traits and seasonality, remain limited in many host-parasite systems, although this information is needed in order to improve and validate model predictions. Furthermore, assessing the impact of animal behavior in general, and animal social structure in particular, on parasite transmission may shed light on the evolutionary causes for these behaviors, and their costs and benefits. Additionally, baseline data on parasites of wildlife are needed to assess risks of transmission at the wildlife-human- livestock interface. For this study, a wild population of a group-living, primarily arboreal primate species, Verreaux’s sifaka (Propithecus verreauxi), was chosen as a study system to investigate the impact of host behavior on parasite spread under natural conditions, in relation to host traits and seasonality. Verreaux’s sifakas are diurnal, folivorous lemurs inhabiting dry forests of southern and south-western Madagascar, where they are annually subjected to a long dry and a short wet season. They live in multi-male, multi-female groups ranging in size from 2 – 9 individuals. Home ranges overlap and intergroup encounters occur frequently. In Kirindy Forest in western Madagascar, a population of Verreaux’s sifakas comprising 10 social groups was studied during 3 periods, covering two rainy and one dry season. Eight adjacent groups were equipped with GPS collars to track group movement and thus assess home range overlap and intergroup encounter rates, while direct observations during two three-month periods (one dry season and one rainy season) provided the raw data to construct social networks and assess the influence of animal contact rates on transmission.

155 Summary

Invasive and noninvasive samples were taken to investigate parasites with 3 different transmission modes, because the impact of a certain behavior on transmission may depend on the parasite’s transmission mode and biological characteristics. Fecal samples were collected non-invasively, while blood samples, mucosal swabs and ectoparasites were collected during routine immobilization procedures from members of all 10 groups. To assess diversity of intestinal parasites, ecto- and hemoparasites, microscopy was combined with genetic analyses. In total, 11 parasite taxa were identified, including one intestinal helminth species (Trichostrongylidae sp.), one tick species (Haemaphysalis lemuris), 3 species of psoroptid mites (Gaudalges propitheci, Gaudalges caparti and Lemuralges intermedius), one chewing louse species (Trichophilopterus babakotophilus), two Plasmodium species, one Babesia species and 2 filarial nematodes (Onchocercidae spp.). Additionally, Escherichia coli, which is a common member of the gut microbiome in most mammals, but may also be a pathogen, was used as a model organism to study the influence of social structure on fecal-oral transmission. The animals’ arboreal lifestyle, their social structure and host age in combination with potential parasite community interactions were identified as the main factors shaping this parasite community. Arboreality likely results in low exposure to environmentally transmitted parasites, which was reflected by the fact that only one intestinal helminth species, belonging to the family Trichostrongylidae, was found parasitizing the study animals. Additionally, little indication of parasite spillover from humans via this route was found. Escherichia coli isolates did not show antibiotic resistance, and infections with Cryptosporidium sp., which have been found in lemurs subjected to human influence at another study site in Madagascar, were absent. Furthermore, support was found for social structure as an important determinant of fecal-oral transmission, exemplified by the spread of Escherichia coli, in this system. Multi- locus sequence-typing (MLST) was used to infer transmission pathways based on the genetic similarity of Escherichia coli isolates from different individuals. Sharing of MLST types was most prevalent within groups, so that social groups can be regarded as microbiological units. Although it could not be distinguished statistically whether home range overlap or intergroup encounter rates mediate intergroup E. coli transmission, anogenital scent-marking and

156 Summary

subsequent overmarking may play a previously underestimated role, a hypothesis which needs to be tested explicitly in future studies. In addition to directly transmitted infections, sociality may also influence vector-borne infections by either reducing or enhancing attack rates of arthropod vectors. However, sociality did not seem to influence vector-borne infections in this system. Animal group sizes had no significant influence on infections with hemoparasites, indicating that group-living in sifakas neither represents a cost nor a benefit in this context. Finally, interactions between co-occurring parasites may be important determinants of prevalence patterns. Here, Plasmodium sp. infections seemed to be negatively influenced by Babesia infection status. These infections showed opposite patterns of age-dependency and Babesia infection was a statistically significant negative predictor of Plasmodium infection, which highlights that parasitic infections should not be examined in isolation. In conclusion, this study has provided evidence for social structure as an important determinant of direct parasite transmission in arboreal, group-living wild primates, which indicates that gregariousness may be costly, and has implications for epidemiological modeling. In addition, the arboreal behavior of the host and parasite community interactions had an equally strong influence on patterns of parasitism in this system. Future studies are needed to continue describing the parasite community of these lemurs, to assess further influences on individual susceptibility to infection, and to monitor the risks of pathogen spillover into this population of endangered primates.

157

Deutsche Zusammenfassung

Zusammenfassung

Parasiten-Infektionsmuster bei wildlebenden Verreaux’s Larvensifakas (Propithecus verreauxi) im Kirindy-Wald, Madagaskar: Zur Rolle des Wirtsverhaltens

Andrea Springer

Parasiten, einschließlich Viren, Mikroorganismen, Arthropoden und Helminthen, können eine erhebliche Belastung für ihren Wirt darstellen. Zunehmend legen Untersuchungen nahe, dass die Ausbreitung von Parasiten in Wildtierpopulationen vom Verhalten der Wirte beeinflusst wird, und dass eine Einbeziehung dieser Aspekte in epidemiologische Modelle deren Voraussagen dramatisch verändern kann. Dennoch sind empirische Belege für den Einfluss des Wirtsverhaltens auf Parasiten-Infektionsmuster, im Verhältnis zu anderen Einflüssen, wie z. B. Wirtsmerkmalen und Saisonalität, für viele Wirt-Parasit-Beziehungen nur eingeschränkt vorhanden, obwohl diese Informationen zur Verbesserung und Validierung von Modell- Vorhersagen notwendig sind. Weiterhin erlaubt eine Einschätzung der Auswirkung von Tierverhalten im Allgemeinen, und von Sozialstrukturen im Besonderen, auf Parasiten- Übertragung einen Einblick in die evolutionären Ursachen dieser Verhaltensweisen, sowie ihre Vor- und Nachteile. Zudem sind Daten zu Parasiteninfektionen bei Wildtieren notwendig, um Übertragungsrisiken zwischen Wildtieren, Menschen und Haustieren einzuschätzen. Für diese Studie wurde eine wildlebende Population einer in Gruppen und primär auf Bäumen lebenden Primaten-Spezies, Verreaux’s Larvensifaka (Propithecus verreauxi), als Untersuchungssystem ausgewählt, um den Einfluss des Wirtsverhaltens auf Parasiten- Übertragung, im Verhältnis zu Wirtsmerkmalen und Saisonalität, unter natürlichen Bedingungen zu untersuchen. Verreaux’s Larvensifakas sind tagaktive, blätterfressende Lemuren, die in Trockenwäldern im Süden und Südwesten Madagaskars leben, wo sie jährlich einer langen Trockenzeit und einer kurzen Regenzeit ausgesetzt sind. Sie leben in Gruppen aus mehreren Männchen und Weibchen, deren Größe zwischen 2 und 9 Tieren beträgt. Die Territorien der einzelnen Gruppen überlappen sich und Gruppenbegegnungen finden regelmäßig statt. Im Kirindy-Wald im Westen Madagaskars wurde eine Population von Verreaux’s Larvensifakas, bestehend aus 10 Gruppen, während dreier Feldaufenthalte untersucht, sodass zwei Regen- und eine Trockenzeit abgedeckt wurden. Acht benachbarte Gruppen wurden mit

158 Deutsche Zusammenfassung

GPS-Halsbändern ausgestattet, um Gruppenbewegungen und damit Territorien- Überlappungen und Zwischengruppenbegegnungen zu erfassen. Direkte Beobachtungen während zwei drei-monatiger Feldzeiten (eine Regen- und eine Trockenzeit) lieferten die Rohdaten, um soziale Netzwerke zu erstellen und den Einfluss von Kontaktraten auf Übertragungsprozesse zu untersuchen. Invasive und nicht-invasive Proben wurden gesammelt, um Parasiten mit drei verschiedenen Übertragungswegen zu untersuchen, da der Einfluss eines speziellen Verhaltens auf Erregerausbreitung vom Übertragungsweg und den biologischen Merkmalen des Parasiten abhängen kann. Kotproben wurden nicht-invasiv gesammelt, während Blutproben, Schleimhautabstriche und Ektoparasiten während regelmäßiger Immobilisationen von Mitgliedern aller 10 Gruppen entnommen wurden. Um die Artenvielfalt intestinaler Parasiten, Ekto- und Blutparasiten zu untersuchen, wurden mikroskopische Verfahren mit genetischen Analysen kombiniert. Insgesamt wurden 11 Parasiten-Taxa nachgewiesen: eine intestinale Helminthen-Art (Trichostrongylidae sp.), eine Zecken-Art (Haemaphysalis lemuris), drei Psoroptidae-Milben (Gaudalges propitheci, Gauldalges caparti und Lemuralges intermedius), eine Haarling-Art (Trichophilopterus babakotophilus), zwei Plasmodien-, eine Babesien- und zwei Filarien- Arten (Onchocercidae sp.). Zusätzlich wurde Escherichia coli, ein regulärer Bestandteil der intestinalen Mikroflora der meisten Säugetiere, aber auch potentiell ein Pathogen, als Modellorganismus genutzt, um den Einfluss der Sozialstruktur auf fäkal-orale Übertragung zu untersuchen. Als wesentliche, diese Parasiten-Artengemeinschaft formende Faktoren wurden die Lebensweise auf Bäumen, die Sozialstruktur der Tiere und ihr Alter in Verbindung mit potentiellen Interaktionen zwischen unterschiedlichen Parasiten erkannt. Das Leben auf Bäumen führt wahrscheinlich zu einer geringen Exposition mit über die Umwelt übertragenen Parasiten, was sich in der Tatsache widerspiegelte, dass nur eine Helminthen-Art, zur Familie Trichostrongylidae gehörend, bei den Tieren gefunden wurde. Zusätzlich waren die Hinweise auf eine Übertragung von zoonotischen Erregern über diesen Übertragungsweg gering. Escherichia coli-Isolate zeigten keine Antibiotika-Resistenzen. Infektionen mit Cryptosporidium, welche bei Lemuren in einem anderen, von Menschen beeinflussten Gebiet Madagaskars gefunden wurden, lagen nicht vor.

159

Deutsche Zusammenfassung

Weiterhin wurde die Sozialstruktur, am Beispiel der Übertragung von Escherichia coli, als ein wichtiger Einflussfaktor auf fäkal-orale Übertragung in diesem System erkannt. Multi-Lokus Sequenz-Typisierung (MLST) wurde genutzt, um basierend auf der genetischen Ähnlichkeit der E. coli-Isolate von verschiedenen Tieren Übertragungswege herzuleiten. Übereinstimmende MLST-Typen fanden sich allem innerhalb von sozialen Gruppen, sodass diese als mikrobiologische Einheiten angesehen werden können. Obwohl nicht statistisch unterschieden werden konnte, ob die Übertragung zwischen sozialen Gruppen von der Territorien-Überlappung oder der Rate an Zwischengruppen-Begegnungen abhängt, scheinen das Setzen von Duftmarken mittels anogenitaler Duftdrüsen und anschließendes Übermarkieren eine derzeit unterschätzte Rolle als Übertragungsweg zu spielen. Diese Hypothese sollte in zukünftigen Studien explizit überprüft werden. Zusätzlich zu direkt übertragenen Parasiten kann das Sozialverhalten über die Angriffsraten von Arthropoden auch vektoren-übertragene Infektionen beeinflussen. In diesem System scheint Sozialität jedoch keinen Einfluss auf vektoren-übertragene Infektionen zu haben. Die Größe der Tiergruppen hatte keinen signifikanten Einfluss auf Infektionen mit Blutparasiten, was darauf schließen lässt, dass das Leben in Gruppen in diesem Kontext weder einen Vor- noch einen Nachteil darstellt. Letztlich können auch Interaktionen zwischen gleichzeitig auftretenden Parasiten als wichtige Einflussfaktoren Prävalenz-Muster formen. In dieser Studie schienen Plasmodien- Infektionen negativ vom Babesien-Infektionsstatus beeinflusst zu sein. Diese Infektionen zeigten gegensätzliche Altersverteilungen und die Infektion mit Babesien war ein statistisch signifikanter negativer Einflussfaktor auf die Wahrscheinlichkeit, mit Plasmodien infiziert zu sein. Dies zeigt, dass einzelne Infektionen nicht in Isolation betrachtet werden sollten. Abschließend lässt sich sagen, dass in dieser Studie die Sozialstruktur als wesentliche Determinante für direkte Parasiten-Übertragung bei baum- und gruppenlebenden, wilden Primaten erkannt wurde, was darauf hinweist, dass das Leben in Gruppen nachteilig sein kann, und Implikationen für epidemiologische Modelle beinhaltet. Zusätzlich hatten die Lebensweise überwiegend auf Bäumen, sowie Interaktionen zwischen unterschiedlichen Parasiten einen ebenso starken Einfluss auf die Parasiten-Infektionsmuster in diesem System. Zukünftige Studien sind notwendig, um die Parasiten dieser Lemuren weiter zu charakterisieren, weitere Einflussfaktoren auf die Empfänglichkeit der Tiere gegenüber

160 Deutsche Zusammenfassung

Infektionen zu erkennen, und die Risiken eines Eintrags von Pathogenen in diese Population gefährdeter Primaten zu überwachen.

161 References

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219 Acknowledgements

Acknowledgements

I would like to express my sincere gratitude to Prof. Franz-Josef Kaup and Prof. Peter M. Kappeler for their academic supervision and for giving me the opportunity to work with wild lemurs in Madagascar, a dream come true!

I am grateful to Dr. Claudia Fichtel for her patience and help with statistical analyses and to Dr. Fabian H. Leendertz and Dr. Sébastien Calvignac-Spencer for hosting me at the Robert- Koch-Institute and giving valuable advice.

Without the help of Léonard Razafimanantsoa, Rodin Rasoloarison, Patrique Solondrainy and the other assistants at the field station in Kirindy Forest this work would not have been possible.

Another big thank you goes to Andreas Kues and Christina Glaschke from the German Primate Center and to Kevin Merkel from the Robert-Koch-Institute for their valuable support in the lab.

I thank Dr. J. Hirzmann, JLU Gießen, and Prof. E. Tannich, Bernard-Nocht-Institute, for providing positive controls for PCR reactions and giving scientific advice on PCR protocols.

I am grateful to all past and present members of the Behavioral Ecology and Sociobiology Unit of the German Primate Center as well as to all members of the Research Group “Sociality and Health in Primates” for numerous fruitful discussions during seminars, workshops and coffee breaks.

I thank my family, Angelika and Jürgen Springer, Christian Springer and Felix Fitting for their enthusiasm and support concerning all my foreign adventures, and for following me to the other side of the world.

220 Erklärung

Erklärung

Hiermit erkläre ich, dass ich die Dissertation

Patterns of parasitism in wild Verreaux’s sifakas (Propithecus verreauxi) at Kirindy Forest, Madagascar: Assessing the role of host behavior selbstständig verfasst habe. Bei der Anfertigung wurden folgende Hilfen Dritter in Anspruch genommen:

Akademische Betreuung: Prof. Franz-Josef Kaup und Prof. Peter M. Kappeler Hilfe bei statistischer Auswertung: Dr. Claudia Fichtel

Ich habe keine entgeltliche Hilfe von Vermittlungs- bzw. Beratungsdiensten (Promotionsberater oder anderer Personen) in Anspruch genommen. Niemand hat von mir unmittelbar oder mittelbar entgeltliche Leistungen für Arbeiten erhalten, die im Zusammenhang mit dem Inhalt der vorgelegten Dissertation stehen.

Ich habe die Dissertation an folgenden Institutionen angefertigt:

Deutsches Primatenzentrum, Göttingen

Die Dissertation wurde bisher nicht für eine Prüfung oder Promotion oder für einen ähnlichen Zweck zur Beurteilung eingereicht.

Ich versichere, dass ich die vorstehenden Angaben nach bestem Wissen vollständig und der Wahrheit entsprechend gemacht habe.

Göttingen, den 03.09. 2015

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