LOST IN TRANSMISSION Unravelling the mechanisms of parasite removal by non-hosts The research presented in this thesis was carried out at the Department of Coastal Systems, Royal Netherlands Institute for Sea Research (NIOZ), ‘t Horntje, Texel, The Netherlands. The research was financially supported by The Royal Netherlands Institute for Sea Research (NIOZ), ‘t Horntje, Texel, The Netherlands. The printing of theis was funded by The Royal Netherlands Institute for Sea Research (NIOZ), ‘t Horntje, Texel, The Netherlands and the Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. This Thesis should be cited as: Welsh, J. E. (2020) Lost in transmission: unravelling the mechanisms of parasite removal by non-hosts. PhD Thesis, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. Layout: Jennifer E. Welsh Cover Design: Joost Drijver - Degelijk Design Images adapted from Esper (1788), Herbst (1782), Audouin (1824) and Milne-Edwards, H. (1840). Cartoons and Photographs: Ilonka Koning-de Boer (cartoons pp. 50, 55, 61, 77, 91, 93, 113, 157, 169, 189, 203, 227 and 233) Jennifer E. Welsh (all photographs) Printed by: GVO Drukkers & Vormgevers, Ede. The Netherlands ISBN: 978-94-6332-613-1 © J. E. Welsh ([email protected]) Chapter 1 General Introduction Jennifer E. Welsh Community structure and disease risk In recent years the idea that an increase in biodiversity can reduce disease risk, a phenomenon which has been coined the “dilution effect” (Keesing et al. 2006, Clay et al. 2009, Pongsiri et al. 2009, Johnson et al. 2013, 2015a, Pfäffle et al. 2015), has gained a lot of attention. Originally, the dilution effect theory assumed that an increase in biodiversity (measured via species richness) would result in fewer highly susceptible or ‘competent’ host species being present in a given system and thus disease incidences would be reduced (van Buskirk and Ostfeld 1995). The idea is thought to derive from zooprophylaxis, whereby vectors containing infective disease agents are diverted from biting their target host (typically humans) and bite other organisms instead (World Health Organization 1982, Dobson et al. 2006), and thus zooprophylaxis and the original dilution theory primarily focused on vector-borne, human related diseases. However, differing interpretations of the dilution effect led Keesing et al. (2006) to expand on the original theory, defining it as ‘the net effect of species diversity reducing disease risk by any of a variety of mechanisms, and for both vector-borne and non- vector-borne diseases’. This new definition broadened the theory to include five key mechanisms in which changes in species diversity drive the reduction in disease risk. Susceptible host regulation occurs when compounding factors such as starvation and hunting regulate host populations and thus reduce the number of hosts available for infection. Infected host mortality, is when the death of the infected host leads to the death of the disease agent and thus its removal from the system. Recovery augmentation occurs when an increase in the recovery rate of the host results in them no longer being infected and potentially immune. Transmission reduction is the result of a reduction in successful transmission despite disease-host encounters. This thesis focuses on the fifth mechanism, encounter reduction, which occurs when changes in the diversity of non-host organisms result in a reduction in encounters between infective stages and uninfected host species. Since Keesing et al. (2006), results of studies testing the dilution theory have been contradictory, fueling an intense but valid debate on whether biodiversity does actually reduce disease risk (Randolph and Dobson 2012, Lafferty and Wood 2013, Ostfeld and Keesing 2013). The varying studies have shown that an increase in biodiversity can either decrease disease risk (Civitello et al. 2015), cause no effect, or may even amplify disease risk (‘amplification effect’; Randolph and Dobson 2012), thus the effects of biodiversity on disease may not be universal (Ostfeld and Keesing 2013). Mechanisms of encounter reduction Of the five types aforementioned mechanisms mentioned, encounter reduction has arguably received the most interest to date (Keesing et al. 2006, Clay et al. 2009). This is perhaps not surprising as all parasites, at one point or another, have a transmission stage when they move from one host to another. Many studies testing the effects of encounter reduction have focused on Lymes disease, a vector borne parasite which infects multiple different hosts. The Borrelia type bacterium which causes Lyme disease is not host specific and can infect multiple species, however some infected species are able to transmit the bacteria to the main vector, a tick, better than other infected species (highly competent and less competent hosts respectively; Johnson et al 2013; Wood and Lafferty 2013). The composition of the community in which the Borrelia type bacterium is present can affect the disease prevalence, that is, the composition of high and low competence hosts within a given system. If the community has a higher proportion of well distributed vectors and highly competent hosts (hosts which are efficient at transmitting the disease), then the chance of encounters between highly competent hosts and the subsequent spread of the bacteria is greater (Keesing et al. 2006, Levi et al. 2012; Fig. 1.1 A). In the Lyme disease system, host competency plays an important role and is a major factor in determining disease prevalence. Highly competent hosts allow propagation, maintenance and spread of the disease by transmitting the bacteria more easily and being geographically and temporally distributed in a way that enables host-to-host contact. Contrarily, low competency hosts are hosts which do not propagate, maintain and spread the disease as readily (Hatcher and Dunn 2011). Low competence host include hosts which are, in the case of Lyme disease, infected but the low competence host’s immunity kills the bacteria so that cannot be passed on to subsequent uninfected ticks (Gray 1998, Keesing et al. 2006, Hatcher and Dunn 2011). Therefore, the bacteria cannot go on to infect other hosts and thus, a more diverse system which contains a high proportion of low competency hosts compared to a low diversity system with fewer low competency hosts is expected to result in a lower disease prevalence (van Buskirk and Ostfeld 1995, Ostfeld and Keesing 2000, LoGiudice et al. 2003, Keesing et al. 2010). Differences in host competency also drive a second type of encounter reduction which does not include vector-borne diseases but, alternatively, non-vector borne diseases. The life strategy of non-vector borne diseases, such as helminth parasites, are typically complex with multi-stage life cycles containing free-living infective stages. The success of the parasite transmission is determined by the free-living stages infecting competent hosts and thus the community composition and ratio of highly competent to low competent hosts influences the success of infection (Fig. 1.1 B; Johnson et al. 2008, 2013, Hall et al. 2009). For example, the trematode parasite Ribeiroia ondatrae infects the larvae of a variety of freshwater amphibians leading to malformations in metamorphosed adult amphibians (Johnson and Sutherland 2003). Similar to the previous vector-borne example, some amphibian hosts are more competent than others (Johnson et al. 2008) and species poor communities, which have been shown to contain more highly competent amphibian hosts compared to species rich communities, result in 78.4% more successful Ribeiroia ondatrae infections and a higher percentages of malformations (Johnson et al. 2013). However, unlike the previous vector-borne example, host competency does not only affect disease prevalence (the proportion of infected individuals with in a system) but also infection intensity (the number of parasites within an infected host; Johnson et al. 2008). Infection intensity is important as the host is very rarely affected by a few parasites alone and host health only tends to be affected when infection intensity is high enough to deplete host resources or when combined with other factors such environmental stress (De Montaudouin et al. 1998, Wegeberg and Jensen 1999, Fredensborg et al. 2004, Kelly et al. 2010). In addition to encounter reduction effects caused by differential host susceptibility in vector-borne and non-vector-borne disease systems, there is a third mechanism which may also result in encounter reduction effects: transmission interference via parasite removal by non-hosts (Johnson and Thieltges 2010). Transmission interference occurs in non-vector borne diseases when organisms which do not serve as hosts for a pathogen or parasite (non-hosts) prevent infective stages from successfully transmitting from one host to another, resulting in a reduction in infection intensity in the downstream host. Non-host organisms can affect transmission via toxic excretions, physical barriers and predation (for review see Thieltges et al. 2008b). Thus, an increase in biodiversity is thought to increase the number of non-host organisms which cause transmission interference, specifically predators of parasites, resulting in more free-living infective stages being removed and therefore, and overall decrease in infection intensity in downstream hosts (Fig. 1.1 C). Until now, this third mechanism has been extremely understudied in regards to biodiversity effects on disease risk but is postulated to significantly