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
German Primate Center
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streferee:
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ndreferee:
Prof. Dr. Franz-Josef Kaup
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
Prof. Prof. h. c. Dr. Ursula Siebert
III
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.
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“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.
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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
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
Zusammenfassung………... 158
References………. 161
Acknowledgements………... 220
Erklärung……….. 221
IX
°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
X
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
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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-
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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;
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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).
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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
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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 groupsize 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.
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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,
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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
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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
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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).
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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).
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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).
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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.
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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).
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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.
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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.
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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).
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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.
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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
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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.
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Table 1: Overview of samples taken during animal captures.
Sample Storage medium Sample analysis Number of
individuals sampled
2.5 ml blood EDTAa / RNAlaterb
Examination of blood smears, packed cell volume, total plasma protein, PCRs
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Rectal swab Amies mediumc microbiological culture 39
Ectoparasites 70 % ethanold microscopy 39
Anogenital
adhesive tape 70 % ethanold microscopy
(detection of helminth eggs / mites) 39
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)).
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Overview of data collection
Month Invasive sampling
(no. of individuals)
Fecal sample collection
Behavioral observations
GPS data 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
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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).
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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).
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Table 2: PCR conditions and primers for amplification of protozoan and strongyle DNA.
OrganismTarget
gene Length of
amplification(bp) PrimerThermoprofileReferences
Cryptosporidium sp. 18S rRNA120forward:94 °C2 minRichter et al. (2011)
5’-TCGTAGTTGGATTTCTGTT-3’94 °C30 secreverse:40 cycles55 °C30 sec
5’-AAGCACTCTAATTTTCTCA-3’72 °C1 min
72 °C10 min
Entamoeba sp. 18S rRNA240forward:95 °C10 min
5’-GCATAAGTAAAGTTTCTAG-3’95 °C20 secreverse:50 cycles52 °C20 sec
5’-GCATCTTATAGCGATCATGG-3’72°C30 sec
72°C7 min
Strongylid larvaeITS +1000forward: NC1694 °C3 minGasser et al. (1993)
5’-AGTTCAATCGCAATGGCTT-3’94 °C30 secChilton et al. (2003) reverse: NC240 cycles55 °C30 secLott et al. (2012)
5’-TTAGTTTCTTTTCCTCCGCT-3’72 °C1 min
72 °C5 min
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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
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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-
38
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
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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;
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