Evolutionary Ecology of Lyme Borrelia T ⁎ Kayleigh R

Infection, Genetics and Evolution 85 (2020) 104570

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Infection, Genetics and Evolution

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Review Evolutionary ecology of Lyme Borrelia T ⁎ Kayleigh R. O'Keeffe , Zachary J. Oppler, Dustin Brisson

Department of Biology, University of Pennsylvania, Philadelphia, PA, USA

ARTICLE INFO ABSTRACT

Keywords: The bacterial genus, Borrelia, is comprised of vector-borne spirochete species that infect and are transmitted from Evolutionary ecology multiple host species. Some Borrelia species cause highly-prevalent diseases in humans and domestic animals. Borrelia Evolutionary, ecological, and molecular research on many Borrelia species have resulted in tremendous progress Transmission toward understanding the biology and natural history of these species. Yet, many outstanding questions, such as Ecological interactions how Borrelia populations will be impacted by climate and land-use change, will require an interdisciplinary approach. The evolutionary ecology research framework incorporates theory and data from evolutionary, eco logical, and molecular studies while overcoming common assumptions within each field that can hinder in tegration across these disciplines. Evolutionary ecology offers a framework to evaluate the ecological con sequences of evolved traits and to predict how present-day ecological processes may result in further evolutionary change. Studies of microbes with complex transmission cycles, like Borrelia, which interact with multiple vertebrate hosts and arthropod vectors, are poised to leverage the power of the evolutionary ecology framework to identify the molecular interactions involved in ecological processes that result in evolutionary change. Using existing data, we outline how evolutionary ecology theory can delineate how interactions with other species and the physical environment create selective forces or impact migration of Borrelia populations and result in micro-evolutionary changes. We further discuss the ecological and molecular consequences of those micro-evolutionary changes. While many of the currently outstanding questions will necessitate new experi mental designs and additional empirical data, many others can be addressed immediately by integrating existing molecular and ecological data within an evolutionary ecology framework.

1. Introduction interactions involved in ecological processes that result in evolutionary change within Borrelia and the ecological consequences of that evolu Zoonotic pathogens – those that transmit among wildlife and infect tionary change (Box 1). humans (Box 1)– are some of the most common causes of emerging and The evolutionary history and ecology of Borrelia have been in re-emerging infectious diseases in the world (Jones et al., 2008; Taylor vestigated extensively. Evolutionary studies of Borrelia have char et al., 2001). Many zoonotic bacterial and viral pathogens have com acterized within and between species diversity, genetic and phenotypic plex transmission cycles during which they must interact with multiple variation across space and among host species, and the intergenera natural host species and arthropod vectors (Taylor et al., 2001; Lloyd- tional processes underlying the observed variation (Graves et al., 2013; Smith et al., 2009; Higgs et al., 2019)(Box 1). The bacterial genus Dykhuizen et al., 2008; De Michelis et al., 2000; Coipan et al., 2018). Borrelia is comprised of vector-borne pathogens which infect and are These studies have resulted in the identification of molecular factors transmitted from multiple vertebrate host species and can cause several associated with host and vector specialization, diversification rates and highly-prevalent diseases in humans and domestic animals (Parker and processes, mechanisms of immune escape, and the importance of White, 1992; Burgdorfer et al., 1982; Pritt et al., 2016). While not fully virulence factors to the life cycle (Higgs et al., 2019; Tufts et al., 2019; resolved, the genus has three major evolutionary groups (Gofton et al., Hanincova et al., 2013; Walter et al., 2017; Becker et al., 2016; Estrada- 2018; Loh et al., 2016; Takano et al., 2010); the most well-studied of Peña et al., 2018; Råberg et al., 2017; Hanincová et al., 2003; Ogden these is the Lyme borreliosis clade (referred to here as the LB group), et al., 2010; Mukhacheva and Kovalev, 2014; Hoen et al., 2009; Kenedy the species of which are vectored exclusively by hard-bodied ticks in et al., 2012; Ogden et al., 2015; Neelakanta et al., 2007; Pal et al., 2001; the Ixodes genus. Here, we review research results on the LB group de Silva et al., 2009; Fingerle et al., 2007; Vollmer et al., 2011; Vollmer within an evolutionary ecology framework to explore the molecular et al., 2013). Similarly, ecological studies have provided critical

⁎ Corresponding author. E-mail address: [email protected] (K.R. O'Keeffe). https://doi.org/10.1016/j.meegid.2020.104570 Received 26 June 2020; Received in revised form 21 September 2020; Accepted 22 September 2020 Available online 28 September 2020 1567-1348/ © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/). K.R. O'Keeffe, et al. Infection, Genetics and Evolution 85 (2020) 104570

Box 1 Glossary.

Complex transmission: Transmission that occurs through multiple hosts or vectors. Evolutionary ecology: A research framework that explicitly considers the evolutionary histories and the ecological interactions driving evolutionary change. Generalist pathogen: Pathogens that can successfully infect and transmit from a wide range of host species. Micro-evolution: The change in allele frequencies within populations or species caused by natural selection, gene flow, mutation or drift, including changes caused by horizontal gene or plasmid transfer within and between species (Casjens et al., 2018). Negative frequency-dependent selection: When the selective value of a variant (relative to other variants) is a function of the relative abundance the variant in a population. The fitness of a trait variant increases as the relative abundance, or frequency, of the variant decreases (Brisson, 2018; Wright, 1939). Niche: set of environmental conditions in which the members of a species can survive. Multiple niche polymorphism: Diversity within a population that is maintained because the strength and direction of natural selection on each trait variant is a function of its ability to exploit different environmental features in a heterogeneous habitat (Levene, 1953; Ravigné et al., 2004). This type of multi-niche selection can maintain multiple trait variants in a population if each variant has a selective advantage in some available habitats while other variants are superior in other habitats. Specialist pathogen: Pathogens that can successfully infect and transmit from only one or a small subset of possible species. Zoonotic pathogens: Pathogens naturally transmitted between animals and humans.

Table 1 Evolutionary Ecology Framework.

Ecology Evolutionary biology Evolutionary Ecology

Questions How does intraspecific diversity contribute How do pathogens co-evolve with How do ecological interactions create selective • to host-vector-pathogen interactions? • their vectors and hosts? • forces or impact migration rates to cause micro- How important are multiple infections in By what molecular mechanisms do evolutionary changes? • driving disease dynamics? • pathogens replicate and how does What are the ecological consequences – such as How do species interactions explain the that impact pathogen evolution? • changes in geographic, host or vector range, • distribution and abundance of different abundance, or virulence – of these micro- species? evolutionary changes? Assumptions Individuals within a species or group Constant/irrelevant population Distribution and variance of genetic variation is • considered identical • densities (Hartl and Clark 1989) • constant (Holt 2005) No evolutionary change (short timescales) Fitness in light of ecological • • interactions considered as constant Most evolution is neutral Necessary data & example Necessary Data: Measures of diversity (e.g. Necessary• Data: Sequencing (e.g. multi- Necessary Data: Sequencing (e.g. multi-locus markers, approaches phenotypes, genotypes, species counts, locus markers, whole genome sequencing, whole genome sequencing, reduced representation functional traits); Measures of disease reduced representation sequencing) sequencing); Measures of diversity (e.g. phenotypes, progression and transmission Examples: Brisson et al., 2010, Becker genotypes, species counts, functional traits); Examples: Devevey et al., 2015, Walter et al., et al., 2016 Examples: MacDonald et al., 2019, Becker and Han, 2016a 2020 advances in our understanding of the processes and interactions that evolutionary context. Such evaluations are critical for understanding, affect the abundance of some Borrelia species on short time scales, predicting, and managing disease epidemics. identifying environmental conditions and host communities that di Central to the evolutionary ecology of Borrelia species are two rectly influence year-to-year variations in Borrelia populations (Vuong questions: et al., 2017; Paul et al., 2016; Kilpatrick et al., 2017a). While both evolutionary and ecological studies have been instrumental to our un 1. How do intra- and interspecies interactions, or interactions with the derstanding of Borrelia, many outstanding questions can be addressed physical environment, create selective forces or impact migration only by transcending the assumption that ecological and evolutionary rates to cause micro-evolutionary changes? processes operate on different timescales (Table 1). 2. What are the ecological consequences – such as changes in geo An evolutionary ecology research framework integrates ecological graphic, host or vector range, abundance, or virulence – of these and evolutionary timescales, incorporating feedbacks between ecolo micro-evolutionary changes? gical interactions and evolutionary change (Turcotte et al., 2011) (Box 1). Ecological interactions, like those that Borrelia species experience Evolutionary ecology provides a particularly powerful investigatory throughout their transmission cycle, create evolutionary pressures that framework for infectious disease systems (Gilbert and Webb, 2007; select for traits that enhance specific omponents of the life cycles of Parker and Gilbert, 2004; Jarosz and Davelos, 1995; Alexander et al., Borrelia species (Barraclough, 2015). These evolutionary changes, in 1996). For example, an investigation of a plant pathogen system within turn, effect subsequent ecological interactions with hosts or vectors that an evolutionary ecology framework resulted in accurate identification create additional evolutionary pressures. Investigating Borrelia within of novel host species to which plant pathogens are likely to adapt an evolutionary ecology framework provides a foundation to evaluate (Gilbert and Parker, 2016). These predictions were made by con how ecological interactions result in micro-evolutionary change within sidering relatedness among hosts, their ecological traits, and their Borrelia populations and the ecological consequences of those changes. geographic distributions. Research into microbes with complex trans This evolutionary ecology framework can be used to address questions mission cycles, like those within the Borrelia genus, which interact with like why some Borrelia species are more host-specific than others or multiple hosts and environmental conditions, is particularly poised to why rates of gene flow are different among populations. While some of leverage the power derived from an evolutionary ecology framework to these questions have been addressed, further investigations within an identify ecological processes affecting evolutionary change. evolutionary ecology framework would provide new insights within an As Borrelia species are not free-living microbes, all molecular and

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Fig. 1. Why are some Borrelia species more host-specific than others? Along the generalist-specialist continuum, the generalist Borrelia species infect many vertebrate host species while the specialist species infect only one or a few host species. Considering the ecological interactions each Borrelia species experiences elucidates the selective pressures that led to the differences in host species specialization.A. The strength of natural selection is derived, in part, from the frequency of ecological interactions that a Borrelia species experiences with each possible host species. That is, selection on generalist species populations is impacted by the frequency of interactions with the wider vertebrate host community whereas selection on specialist species populations is determined primarily by interactions with the one species it can infect and from which it is regularly transmitted. B. The molecular mechanisms underlying successful infection vary between generalist and specialist species due to differing selective pressures. For example, the surface proteins of generalist species interact successfully but not ideally with the corre sponding receptors of multiple host species, C. resulting in sub-optimal infection or transmission success from many species; B. the surface proteins of specialist Borrelia species interact more effectively with the corresponding receptor of its one competent host C. resulting in optimal infection and transmission success from only one or a small number of host species. Thus, generalist species have less restricted ecological interactions with the vertebrate community but lower fitness in each host while specialist species are limited in their interactions to the vertebrate host species it can successfully infect and be transmitted from, but experience high fitness in that host. ecological interactions occur with or within a vector or a vertebrate Munro et al., 2019), and shape mutation rates and genetic drift (Brisson host. The web of interactions among Borrelia, vectors, and hosts creates et al., 2012), although the latter two evolutionary forces are difficult to selection pressures that drive Borrelia evolution (Haven et al., 2011; discern in natural populations. Here, we describe the impacts of eco Tsao, 2009), impact migration and geographic distributions of Borrelia logical interactions on micro-evolutionary change (Box 1) with Borrelia (Vollmer et al., 2011; Vollmer et al., 2013; Seifert et al., 2015; that can be deduced from independent studies of ecological interactions Khatchikian et al., 2015; Norte et al., 2020; Comstedt et al., 2011; and molecular interactions. We then discuss future directions that can

3 K.R. O'Keeffe, et al. Infection, Genetics and Evolution 85 (2020) 104570 maximize the utility of an evolutionary ecology framework to identify species by considering both how ecological interactions can cause additional ecological or molecular mechanisms that are key to the micro-evolutionary change and how that evolutionary change impacts Borrelia life-cycle. ecological interactions. Adaptations that cause Borrelia to complete their life cycles in only a 2. Borrelia-host interactions specialized subset of host species subsequently limit the frequency of interactions with other vertebrate species, thus limiting the selective 2.1. Generalism to specialism pressure they experience from these non-competent vertebrate species. Further, opportunities for genetic exchange between Borrelia species Ecological interactions between Borrelia and its vertebrate hosts decrease when different species are less likely to occupy the same host. select for evolutionarily-tuned molecular mechanisms within Borrelia Thus, genetic mutations that fix in Borrelia species that specialize on species to enhance their ability to colonize, disseminate to distal tissues, different host species are rarely shared through horizontal gene transfer evade host immune responses, and then transmit from the host to due to limited opportunities for genetic exchange (Bunikis et al., 2004; feeding ticks (Tufts et al., 2019; Kenedy et al., 2012; Ogden et al., Dykhuizen and Baranton, 2001; Jacquot et al., 2014) leading to con 2015). Sequence variation among Borrelia species in the proteins that tinuing evolutionary divergence among the Borrelia species. By con mediate these molecular mechanisms is shaped by natural selection to trast, horizontal gene transfer rates among genotypes within the same enhance the efficacy of interactions with host proteins that vary among Borrelia species are 50 times greater than rates of inter-species hor vertebrate host species (Tufts et al., 2019; Roberts et al., 1998; Hart izontal gene transfer, at least partially due to the increased opportunity et al., 2018). For example, variation in a complement regulator ac for transfer within co-infected hosts (Jacquot et al., 2014). Evolutionary quiring surface protein (CspA) among Borrelia species results in varia ecology provides a framework to investigate how eco-evolutionary tion in their ability to bind complement molecules in different verte feedback loops drive the high proportion of Borrelia species currently brate hosts and thus limits the host range of each Borrelia species (Hart displaying host associations. et al., 2018; Lin et al., 2020a; Bhide et al., 2009; Kurtenbach et al., Host-species associations are even apparent among genetically dis 2002; Wywial et al., 2009; Hammerschmidt et al., 2014; Lin et al., tinct strains, or genotypes, within some generalist Borrelia species 2020b). Ecological interactions with different host species cause each (Mechai et al., 2016; Hanincová et al., 2006; Kurtenbach et al., 2006) Borrelia species to experience unique selective pressures that result in (Box 1). Genotypes of B. burgdorferi sensu stricto (Bbss) appear to differ divergent micro-evolutionary trajectories (Table 1). This evolutionary in their ability to complete their infectious cycles in different vertebrate divergence has ecological consequences for Borrelia as it limits the hosts in nature (Barthold et al., 1991; Norris et al., 1995; Wang et al., subset of vertebrate hosts in which each Borrelia species can success 2002; Barbour et al., 2009; Baum et al., 2012; Chan et al., 2012). These fully complete its infectious cycle. A core component of evolutionary statistical associations have not been experimentally verified and are ecology is to assess these types of eco-evolutionary feedback loops. distinct, in both mechanism and strength, from those confirmed among Investigating these eco-evolutionary feedback loops could address European Borrelia species. Nevertheless, Bbss genotypes differ in their outstanding questions such as how the frequency and strength of se binding efficacy to host plasminogen and complement regulator mole lection on other Borrelia-host interactions are impacted by host spe cules from different host species due to molecular adaptations (i.e. OspC cialization or the mechanisms by which Borrelia species evolve to be and OspE) (Tufts et al., 2019; Önder et al., 2012; Lagal et al., 2006). come ever more specialized. Genotypes also differ in their abilities to survive and disseminate to Host associations, sometimes referred to as host specialization distal tissues in a range of vertebrate hosts (Anderson et al., 1990; (Mechai et al., 2016), determine the frequency and importance of Barthold et al., 1991; Norris et al., 1995; Wang et al., 2002; Barbour ecological interactions between each Borrelia species and each verte et al., 2009; Baum et al., 2012; Chan et al., 2012), both of which are brate species (Brisson and Dykhuizen, 2004; Bäumler and Fang, 2013). critical to the ability of Borrelia to transmit to ticks. Evolutionary The frequency of ecological interactions with each host species, in turn, ecology provides the research foundation to experimentally evaluate determines the strength of natural selection imposed by each host the mechanisms driving any existing host association differences among species on Borrelia (Tufts et al., 2019; Ripoche et al., 1988). For ex Bbss genotypes by focusing on eco-evolutionary feedbacks between ample, variation among host species in immune system components interactions with host species and the impacts of these interactions on imposes different selective regimes on invadingBorrelia species (Brisson micro-evolution. and Dykhuizen, 2004; Bäumler and Fang, 2013). The strength of these Variation among host species in plasminogen and complement selective regimes is determined by how frequently that Borrelia species regulator molecules may require Bbss genotypes to adapt to only a must evade the immune system of each host species and the host-to-tick subset of host species, resulting in interactions with molecules from transmission rate given a successful infection of that host (Tufts et al., other species that prevent successful infections (Ripoche et al., 1988). 2019; Ripoche et al., 1988). Further, adaptations that maximize sur For example, each Bbss genotype maintains a single OspC variant that vival and transmission from one host species often limit survival and interacts effectively with plasminogen from only a limited number of transmission from other hosts, leading to selection favoring host spe host species (Marconi et al., 1993; Livey et al., 1995; Casjens et al., cialism (Tufts et al., 2019; Anderson et al., 1990; Barthold et al., 1991; 2018). While expressing multiple OspC variants may increase the range Norris et al., 1995; Wang et al., 2002; Barbour et al., 2009; Baum et al., of host species that a Bbss genotype can infect, it may come at the cost 2012; Chan et al., 2012; Wang et al., 2001). This eco-evolutionary of increasing immune targeting (Tilly et al., 2006). OspC is targeted by feedback loop favors evolution toward greater host specialization (Box a fast and lethal immune response such that more targets could increase 1, Fig. 1). Host associations can even drive speciation events. For ex the probability of immune clearance before the bacterium can establish ample, the divergence between the sister species B. garinii and B. ba a long-lasting infection. The evolutionary ecology research framework variensis resulted from differential host species use;B. garinii specialized can be used to investigate if a tradeoff between host-range breadth and on bird species while B. bavariensis specialized on small mammals immune targeting imposes a barrier to the long-term maintenance of (Becker et al., 2016; Margos et al., 2009). Subsequent genetic differ host generalism in Borrelia genotypes. That being said, there is growing entiation among these specialized Borrelia species arose in response to evidence that the arrival of Borrelia in North America pre-dates the last the different selective regimes imposed by the different vertebrate hosts Ice Age (Walter et al., 2017; Hoen et al., 2009), and such a long evo with which they interact most frequently. An evolutionary ecology re lutionary history may suggest that generalism is being maintained. search framework can facilitate investigations into the molecular Future work within evolutionary ecology could elucidate the apparent changes within B. bavariensis that enabled it to use a different host discord.

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2.2. Interactions with the vertebrate immune system the impact of genetic drift leading to further differentiation among subpopulations. Interactions between Borrelia species and the vertebrate adaptive Host species diversity can select for the maintenance of genetic di immune system impose strong selective pressures on Borrelia. These versity within Borrelia populations. Multiple genotypes of Bbss coexist interactions result in an evolutionary arms race between host immune within geographic locations when the environment is heterogeneous responses and molecular mechanisms that enable immune evasion (i.e. a diverse vertebrate community) and none of the genotypes have within Borrelia species (Tufts et al., 2019). The vlsE locus in all Borrelia the highest fitness in all host species (Brisson and Dykhuizen, 2004; species encodes an immunodominant surface protein that undergoes Cobey and Lipsitch, 2012). Molecular variation among genotypes extensive and rapid antigenic variation during vertebrate infection in within Borrelia species determines the transmission success of anti order to evade antibodies (Graves et al., 2013; Zhang and Norris, 1998; genically distinct genotypes in each host species resulting in niche se Coutte et al., 2009; Norris, 2015). Novel vlsE protein sequences that are paration (Vuong et al., 2017; Mechai et al., 2016; Brisson and unrecognized by circulating antibodies are generated by recombination Dykhuizen, 2004; Hanincová et al., 2006; Brisson, 2018) (Box 1). The between the vlsE expression site and one or more of the unexpressed, presence of multiple host species at individual locations permits an highly-variable vls cassettes. The conservation of highly-mutable array of genetically distinct genotypes to be simultaneously maintained. tandem repeat structures across the otherwise highly-diverged cassettes As vertebrate communities have been and continue to be impacted by suggests that the host immune system imposes a strong selective pres land use change (Kilpatrick et al., 2017b), evolutionary ecology will sure to maintain evolvability at this locus and results in ongoing micro- provide a framework to predict how changes in vertebrate host com evolutionary change in the vls antigenic variation system (Graves et al., munities will impact the diversity of Borrelia populations. 2013). Acquired immunity can also create negative frequency dependent 3. Borrelia-vector interactions selection processes that maintain genetic variation within Borrelia po pulations (Box 1). Differences among host individuals in their history of 3.1. Vector specialization, vector switches, and Borrelia distribution antigen exposure can result in acquired immunity to specific Borrelia genotypes, thus reducing the proportion of hosts susceptible to the All Borrelia species require at least one tick species to complete their more common Borrelia genotypes. Therefore, rare Borrelia genotypes to life cycle. Similar to the molecular interactions between Borrelia and its which few hosts have been exposed would have a selective advantage vertebrate hosts, interactions between Borrelia and its vectors select for over the more common genotypes to which many hosts have mounted molecules that enable successful uptake by feeding ticks, persistence an immune response. Experimental studies have also shown that gen within the tick midgut throughout the tick molt and subsequent otype-specific antibodies are maternally inherited such that selection questing, and migration to the salivary glands and transmission to a against common genotypes may last across generations (Gomez- subsequent host (Kenedy et al., 2012; Neelakanta et al., 2007; Pal et al., Chamorro et al., 2019). Although fluctuating frequencies of genotypes 2001; de Silva et al., 2009; Fingerle et al., 2007). For example, Outer are often associated with negative frequency dependent selection, ospC- Surface Protein A (OspA) in Borrelia must bind to the tick midgut re major groups do not appear to fluctuate cyclically in natural popula ceptor, TROSPA, in order to colonize and persist within the tick (Battisti tions (Durand et al., 2017a). Contrary to most textbook examples, et al., 2008; Pal et al., 2004). Genes involved in interactions with ticks however, negative frequency dependent selection on multi-strain pa generally have little variation within Borrelia species (Wilske et al., thogens can produce a variety of dynamics in addition to cyclical fre 1993), but there is substantial variation between Borrelia species quency fluctuations. For example, as discussed in Durand et al. 2017a, (Konnai et al., 2012). The among-species variation observed at these the host immune system could cause pathogen populations to organize genes is likely caused by differences in binding efficiency to tick pro into communities of serotypes that minimize cross-reactive acquired teins (i.e. TROSPA receptors) that likely differ among tick species immunity whose frequencies remain stable over long periods of time (Konnai et al., 2012). Past natural selection has resulted in molecular (Gupta and Anderson, 1999; Gupta et al., 1998; Gupta et al., 1996). The specialization to maximize efficacy in one or a few tick species resulting exact mechanisms underlying this somewhat counterintuitive popula in the observed differences in vector competence and vector speciali tion dynamic under negative frequency dependent selection can be zation among Borrelia species (Couper et al., 2020). Future evolutionary further explored within an evolutionary ecology research framework. ecology research can determine how the frequency and strength of se lection on other molecular interactions is impacted by vector speciali 2.3. Borrelia distribution and genetic structure is shaped by host zation and evaluate the ecological consequences caused by the resulting associations micro-evolution. Specialization to one or a few vector species impacts the geographic The geographic distribution and population genetic structure of range and migration rates of Borrelia species (Margos et al., 2011; Borrelia species is shaped, in part, by the migration patterns of infected Margos et al., 2019), primarily through the mobility and range of the vertebrate hosts. Borrelia species associated with highly-mobile hosts vertebrate species commonly parasitized by the vector. Some vectors, (i.e. birds) tend to have limited population genetic structure as hosts like I. dentatus, prefer mobile hosts like birds (Sonenshine, 1979), while maintain genetic cohesion over large geographic ranges (Vollmer et al., others, like I. spinipalpis, feed primarily on rodents with smaller geo 2011; Vollmer et al., 2013; Norte et al., 2020; Comstedt et al., 2011; graphic ranges (Maupin et al., 1994; Burkot et al., 2000). As expected, Munro et al., 2019). By contrast, species associated with less mobile Borrelia associated with vectors that feed on more mobile hosts have hosts (i.e. small mammals) tend to show much stronger population less population genetic structure due to the high rates of migration genetic structure, with different selective environments in different among locations (Vollmer et al., 2011; Norte et al., 2020; Margos et al., geographic areas and few opportunities for horizontal gene transfer 2011). In contrast, Borrelia species in vectors parasitizing less-mobile among isolated populations (Vollmer et al., 2011; Norte et al., 2020; hosts tend to have greater genetic divergence among geographically Vitorino et al., 2008). For example, population genetic structure can be separated populations due to both neutral evolution and natural se detected only at very large (inter-continental) scales in bird-associated lection favoring specialization, despite experiencing limited ecological species like B. garinii and B. valaisiana while the rodent-associated interactions within their restricted location (Hoen et al., 2009; species like B. afzelii shows extensive spatial structuring even at fine Humphrey et al., 2010). Differences inBorrelia population structure can spatial scales (Vollmer et al., 2011; Vollmer et al., 2013; Gómez-Díaz stem from both direct associations with vertebrates, as discussed in the et al., 2012). Highly disconnected populations limit horizontal gene Borrelia-host section, or indirectly through associations with vectors transfer and reduces effective population sizes, which in turn, amplifies that differently associate with different vertebrate species. Evolutionary

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Fig. 2. Diversification of Borrelia garinii and Borrelia bavariensis in Eurasia demonstrates how evolutionary changes impact ecological interactions. A. The sister species B. garinii and B. bavariensis diverged at node i as a result of specialization on different sets of host species, with B. garinii specializing on bird species and B. bavariensis specializing on small mammals. Subsequent B. bavariensis divergence into two populations at node ii occurred due to adaptation to a novel vector, Ixodes ricinus, allowing B. bavariensis to invaded western Europe. B. The distributions of I. ricinus (blue) and I. persulcatus (yellow) overlap in eastern Europe (green) where the eastern B. bavariensis population predominates. The host and vector switches that have occurred during the evolutionary history of these Borrelia species have facilitated range expansion and increased the diversity of their ecological interactions. (Species ranges as described in Stanek et al. (Stanek et al., 2012). Adapted from the European Concerted Action on Lyme Borreliosis. Available at: http://www.eucalb.com/. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) ecology investigations can differentiate among potential host- or vector- 3.2. Interactions within ticks associated mechanisms underlying these patterns. Adapting to novel vector species exposes Borrelia populations to Borrelia species interact with other microbes within tick vectors, previously unencountered ecological interactions with both the novel including other Borrelia species or strains, other pathogens, and non- vector and with the vertebrate community within the host range of the pathogenic components of the tick microbiome (Ross et al., 2018; Diuk- novel vector. For example, populations of Bbss that adapted to a new Wasser et al., 2016; Moutailler et al., 2016). As Borrelia density is po vector species, I. pacificus, diverged phenotypically from the ancestral sitively correlated with the probability of tick-to-host transmission populations carried by I. scapularis such that Bbss acquisition efficiency (Rego et al., 2014; Durand et al., 2017b), the competition between is higher in sympatric pairings of ticks and Bbss populations than al Borrelia strains within individual ticks that reduces the density of each lopatric pairings (Couper et al., 2020). I. pacificus-associated Bbss po strain (Durand et al., 2017b; Genne et al., 2018; Genné et al., 2019; pulations also expanded geographically into the range of its new vector. Walter et al., 2016a) decreases the evolutionary fitness of Borrelia While the evolutionary divergence is currently insufficient to observe strains. Evolutionary theory predicts that inter-strain competition that geographically-based clusters when neutrally evolving loci are used to negatively impacts evolutionary fitness should select for traits that in build phylogenies (Tyler et al., 2018), the geographic differences in crease growth rates within ticks or for molecules that suppress com selection pressures at one or several genes have resulted in observable peting strains (Alizon et al., 2013; Cattadori et al., 2008; Susi et al., phenotypic differences. Adaptation to a novel vector,I. ricinus, also split 2015; Telfer et al., 2010). Although Borrelia is often found in multi- two populations of B. bavariensis; one population was likely able to strain infections in ticks that reduce evolutionary fitness by reducing invade Europe by adapting to I. ricinus (Becker et al., 2016; Gatzmann transmission probabilities (Durand et al., 2017b), there is no evidence et al., 2015) (Fig. 2). Through an evolutionary ecology lens, future that traits enhancing competitive ability have evolved. This may in research could consider the genetic mechanisms underlying this di dicate that there are other important ecological interactions that are vergence and how the evolved changes influenced ecological interac imposing selective pressures on Borrelia populations. Future evolu tions. tionary ecology research can experimentally or statistically investigate Although Borrelia species can disperse within vectors and vertebrate the selective pressures created by competitive interactions between hosts, the direction and rate of Borrelia migration (gene flow) and that coinfecting Borrelia strains, as well as other ecological interactions, to of their primary vector are often only weakly correlated at fine geo determine their relative evolutionary impact. graphic and temporal scales (Walter et al., 2017). This discord may be Borrelia can also interact with other human pathogens vectored by explained by Borrelia dispersing predominantly within infected verte ticks such as Babesia microti, the protozoan pathogen that causes human brates. For example, migrating birds infected with Borrelia may seed babesiosis (Diuk-Wasser et al., 2016). The number of ticks coinfected local tick populations in non-endemic areas (Ogden et al., 2010). Bor with B. microti and Bbss is higher than expected by random chance relia that do disperse within ticks may still have different rates and alone (Diuk-Wasser et al., 2016; Hersh et al., 2014) suggesting that Bbss direction of gene flow from the tick vector if the bacteria and vectors may be facilitating infection with Babesia. This facilitation may be re colonize areas at different rates. That is, while the colonization effi sponsible for the increased prevalence and range expansion of Babesia ciency of Borrelia is expected to be positively correlated with the local in the northeastern United States (Diuk-Wasser et al., 2016; Dunn et al., density of vectors needed to transmit the bacterium, the colonization 2014). While facilitation of Babesia may occur as a byproduct of natural efficiency of ticks may be inversely proportional to local vector den selection Bbss otherwise experiences, future evolutionary ecology re sities due to competition with resident ticks. While the mechanisms search can determine the traits of Bbss that are key to this ecological underlying competitive interactions between ticks within or between interaction and their impacts on the evolutionary trajectories of both species – as well as the impact this competition may have on coloni species. zation efficiency – require further research, recent evidence suggests Experimentally detecting and quantifying biological interactions that ticks do compete for rodent hosts (Karbowiak et al., 2019). By between pathogens is a long-standing challenge (Hamelin et al., 2019; considering how ecological interactions impact migration rates (micro- Johnson and Buller, 2011; Hellard et al., 2015). Longitudinal sampling, evolution), an evolutionary ecology framework could identify the cause the current gold standard for inferring ecological interactions (Gerber, of the observed differences in gene flow between Borrelia and tick. 2014; Fenton et al., 2014), requires resource-intensive efforts over

6 K.R. O'Keeffe, et al. Infection, Genetics and Evolution 85 (2020) 104570 many years. Collecting cross-sectional data is less burdensome and can identified factors associated with host and vector specialization, di be used to identify deviations from the expected probability of coin versification rates and processes, and mechanisms of immune escape fection given the prevalence of each pathogen (Degarege et al., 2012; which reveal ecological interactions with hosts or vectors that impact Traub et al., 2014; Gelaw et al., 2013). A departure from the random the evolution of these microbial species. Ecological investigations have expectation may indicate interactions between pathogens but may also characterized how environmental conditions, host communities, and result from environmental heterogeneity and spatial or ecological host/vector associations directly influence the frequency and type of clustering (Alizon et al., 2019). Further, the assumption that the pre molecular interactions each Borrelia species experiences. Evolutionary valence of noninteracting pathogens should be statistically independent ecology offers a framework by which we can evaluate the ecological has been challenged (Hamelin et al., 2019). It is critical that ecological consequences of evolved traits in Borrelia and predict how present-day interactions are correctly inferred to consider them as selective forces ecological processes may result in further molecular evolutionary within an evolutionary ecology framework. Appropriate analytical change. methods, such as those developed by Alizon et al 2019, can accurately Investigations into some outstanding questions about the biology of infer species interactions from cross-sectional data while accounting for Borrelia within an evolutionary ecology framework may necessitate environmental heterogeneity but, to date, are rarely used (Alizon et al., collecting new empirical data while others can be addressed by lever 2019). aging existing data. For example, more empirical data will be needed to Borrelia species encounter limited diversity and densities of bacteria characterize the frequency, strength, and type of interactions between overall within Ixodid ticks such that selective pressures from interac Borrelia and pathogens coinfecting ticks or hosts and to determine the tions with the tick microbiome as a whole should be minimal. Although selective forces generated by those interactions. These data are neces early studies found diverse microbiomes in multiple Ixodes species and sary to determine how competitive interactions between coinfecting life stages (Abraham et al., 2017; van Treuren et al., 2015; Zolnik et al., pathogens create selective forces that cause micro-evolutionary changes 2016), more recent studies that controlled for bacterial biomass found within Borrelia species. Similarly, how Borrelia has evolved to withstand that the internal microbiome diversity is actually quite low (Ross et al., year-round climatic fluctuations necessitates additional empirical data 2018; Couper et al., 2019). Consistent with limited microbiome di to predict how interactions with the environment under climate change versity and density, Borrelia has lost genes that encode known inter scenarios will impact Borrelia transmission and evolution. In many bacterial interaction pathways that have not been under selective cases, however, existing data from different disciplines can be in pressure by resident microbes (Ross et al., 2018; Zhang et al., 2012). As tegrated to address how ecological interactions – especially those be Borrelia geographic ranges expand, so too does the diversity of inter tween Borrelia and hosts and those between Borrelia and vectors – actions Borrelia experiences, as the composition of tick microbiomes create evolutionary pressures that select for a diverse set of traits. For varies geographically (van Treuren et al., 2015). Further, there is example, integrating ecological and molecular data can identify if and growing evidence that the ranges of other tick-associated microbes like how ecological interactions drive population genetic structure in nat Babesia and Anaplasma are expanding into areas already inhabited by ural Borrelia populations. Borrelia species (Ogden et al., 2008; Walter et al., 2016b). The evolu The massive influx of Borrelia, tick, and vertebrate genomic in tionary loss of genes encoding inter-microbial competition pathways formation (e.g., Walter et al., 2017; Mongodin et al., 2013; Gulia-Nuss may make Borrelia particularly susceptible to inhibition or exclusion by et al., 2016; Kingry et al., 2016) can be used to discern past evolu competing tick-associated microbes. Evolutionary ecology provides the tionary processes across multiple loci to generate tractable evolutionary foundation to determine if the evolutionarily reduced Borrelia genome ecology hypotheses which can subsequently be experimentally vali constrains the ability of Borrelia to outcompete novel microbial com dated. If species under different selective regimes consistently evolve petitors. distinct trait combinations, comparative genomics can be used to draw Borrelia populations are also shaped by the abiotic factors that affect conclusions about the evolutionary impact of ecological interactions. the populations of their non-homeothermic vector (e.g. temperature, Comparative genomic approaches have already been used in an evo climate, landscape connectivity). Survival within unfed or intermolt lutionary ecology framework to determine the genetic underpinnings of ticks poses significant challenges owing to temperature extremes caused host specialization in some infectious microbes (Mourkas et al., 2020). by daily and seasonal fluctuations as well as nutritional stress (Kung Understanding the evolutionary ecology of Borrelia has practical et al., 2013). Environmental stress can create directional selection implications for predicting expansions in host or vector geographic pressures for tolerance to environmental variation (Chevin and ranges and the disease risk associated with these expansions. For ex Hoffmann, 2017). In fact, experimental evidence suggests that fluctu ample, predicting potential host species by their ecological and evolu ating environments select for bacteria that can tolerate a range of tionary similarities to known hosts can identify geographic areas in conditions (Condon et al., 2014; Saarinen et al., 2018). Although no which populations are likely to establish (Becker and Han, 2020). genes have been identified in Borrelia to facilitate tolerance of extreme Evolutionary ecology approaches are invaluable for predicting novel cold during overwintering or extreme heat during summer, the reg hosts of emerging diseases, especially those caused by pathogens that ulation of many genes is temperature-sensitive (Ojaimi et al., 2003; circulate among multiple hosts like many Borrelia species. By over Tokarz et al., 2004; Phelan et al., 2019). For example, a large fraction of coming the assumption that ecology and evolution operate on distinct novel Borrelia sRNAs (43%) are temperature-dependent both in func timescales, evolutionary ecology provides broad insight into factors tion and expression levels (Popitsch et al., 2017). Future evolutionary regulating population and community dynamics, processes critical to ecology research into how Borrelia has evolved to withstand year-round understanding disease dynamics. fluctuations in temperature is critical to determine howBorrelia persists in ticks and to predict how Borrelia distributions may shift with climate change. Declaration of Competing Interest

4. Future directions The authors declare no conflict of interest.

Evolutionary ecology provides a particularly powerful framework to address outstanding questions on Borrelia species. This framework Acknowledgements builds upon a strong research foundation in the biology of Borrelia constructed from the exceptional progress in molecular mechanistic, National Institute of Health: R01AI142572, R01AI097137, ecological, and evolutionary biological studies. Molecular studies have R21AI137433 and Burroughs Wellcome Fund: 1012376.

7 K.R. O'Keeffe, et al. Infection, Genetics and Evolution 85 (2020) 104570

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