Transmission efficiency drives host-microbe associations

Transmission efficiency drives host-microbe associations | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Transmission efficiency drives host-microbe associations View ORCID Profile Philip T. Leftwich , Matthew P. Edgington , View ORCID Profile Tracey Chapman doi: https://doi.org/10.1101/2020.07.23.216366 Philip T. Leftwich 1 School of Biological Sciences, University of East Anglia, Norwich Research Park , Norwich, Norfolk, NR4 7TJ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Philip T. Leftwich For correspondence: p.leftwich{at}uea.ac.uk tracey.chapman{at}uea.ac.uk Matthew P. Edgington 2 The Pirbright Institute , Pirbright, Woking, Surrey, GU24 0NF, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tracey Chapman 1 School of Biological Sciences, University of East Anglia, Norwich Research Park , Norwich, Norfolk, NR4 7TJ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Tracey Chapman For correspondence: p.leftwich{at}uea.ac.uk tracey.chapman{at}uea.ac.uk Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Sequencing technologies have fueled a rapid rise in descriptions of microbial communities associated with hosts, but what is often harder to ascertain is their evolutionary significance. Here we review the existing literature on the role of vertical (VT), horizontal (HT), environmental acquisition, and mixed modes (MMT) of transmission for establishing animal host-microbe associations. We then modelled four properties of gut microbiota proposed as key to promoting animal host-microbe relationships: modes of transmission, host reproductive mode, host mate choice, and host fitness. We found: (i) MMT led to the highest frequencies of host-microbe associations, and some environmental acquisition or HT of microbes was required for persistent associations to form unless VT was perfect; (ii) host reproductive mode (sexual vs asexual) and host mate choice (for microbe carriers vs non-carriers) had little impact on the establishment of host-microbe associations; (iii) host mate choice did not itself lead to reproductive isolation, but could reinforce it; (iv) changes in host fitness due to host-microbe associations had a minimal impact upon the formation of co-associations. When we introduced a second population, into which host-microbe carriers could disperse but in which environmental acquisition did not occur, highly efficient VT was required for host-microbe co-associations to persist. Our study reveals that transmission mode is of key importance in establishing host-microbe associations. 1. Introduction Rapid advances in sequencing technologies and bioinformatic analyses are revolutionizing the understanding of microbial communities that live on, in or near plant and animal hosts. Microbial symbionts can play crucial roles in many aspects of an organism’s biology [ 1 ] and associations between hosts and microbes can vary from commensal and parasitic relationships, through to obligate mutualisms in which the fate of microbe and host are intimately entwined [ 2 ]. Microbes can be intracellular, extracellular, co-inherited with their hosts, horizontally transmitted, or acquired from the environment. Crucial to the outcome of host-microbe associations is the mode of microbial inheritance and the mechanisms that allow recurrent co-association of microbes and their hosts [ 3 ]. In this article, we focus on animal (mostly insect)-microbe systems, review modes of transmission of microbes to their hosts and discuss their likely evolutionary significance ( Table 1 ). We also explore the as yet under-researched evolutionary potential for mixed modes of transmission (MMT). To assess the relative importance of the different factors contributing to host-microbe associations, we develop mathematical models at the population-level between a single host and microbe species where we test and evaluate: which modes of transmission favour long-term associations between microbes and animal hosts whether host reproductive mode and host mate choice can aid host-microbe associations if host-microbe associations require a host fitness benefit to establish at high population frequency. do parameters leading to high frequency host-microbe associations alter when considering one homogenous population space when compared to two partially isolated populations View this table: View inline View popup Download powerpoint Table 1. Summary of key terms used within this study and a description of their implementation within the mathematical models. Full details on the mathematical implementation of each mechanism are given in the Supplementary Text. (a) Modes of co-transmission of hosts and their microbes Host-associated microbial communities are ubiquitous, and the bacteria within them can show transient or resident associations. There are three general and non-exclusive mechanisms by which microbes can be introduced to an animal host: i) the passage of a symbiont from the host mother to offspring (vertical transmission or VT); ii) environmental acquisition - usually through ingestion of microbes with diet, though this may also occur via iii) Horizontal transmission (HT) consumption of microbes shed into the environment by conspecifics and/or social/sexual transmission. These mechanisms have been reviewed in detail elsewhere [ 4 , 5 ], we discuss these briefly, below, along with the as yet under-researched evolutionary potential for mixed modes of transmission (MMT). (i) Vertical transmission of symbiotic microbes Vertically transmitted symbionts necessarily exhibit strong host fidelity, arising from their direct transfer from mother to offspring. Many insects carry heritable microbes [ 2 , 6 , 7 ] including the widespread intracellular symbionts Rickettsia, Cardinium , and Wolbachia . These microbes infect the host germline and become incorporated within maturing oocytes [ 6 , 7 ]. The high fidelity of VT has facilitated the transition of many heritable symbionts to obligate associations, leading to the loss of their ability to propagate independently [ 2 ]. Such microbes are reliant solely on maternal VT to spread, with their fitness being dependent on the survival and propagation of their female hosts [ 8 ]. A classic example is found within the aphids and their maternally inherited obligate endosymbiont - Buchnera aphidicola [ 9 ]. Here the bacteria provides the host with essential metabolites and are housed within a specialized structure in the host gut. However, VT does not always indicate mutualism between host and microbe, as evidenced by the many and varied effects of the parasitic intracellular symbiont Wolbachia . Wolbachia strains manifest a wide variety of reproductive manipulations of hosts, such as feminisation, parthenogenesis and most commonly, cytoplasmic incompatibility (CI) [ 7 ]. CI results in sperm-egg incompatibility between infected males and uninfected females, and drives Wolbachia through host populations, as uninfected females have a reproductive disadvantage relative to those that are infected [ 7 ]. Maternal inheritance is not restricted to intracellular symbionts, and there are increasing reports of symbiotic gut bacteria being transmitted from mother to offspring [ 10 , 11 ]. If widespread, this could open up new opportunities for evolutionary co-associations to form. As gut microbes are extracellular, they are unlikely to be transmitted through oocytes (though one such example has been reported in the wax moth Galleria mellonella [ 12 ]). Despite this, several direct and indirect routes for VT have been identified, including (i) contact smearing of microbes onto the egg surface during or after oviposition [ 13 ], (ii) oviposition site inoculation and reingestion by offspring [ 14 ], (iii) coprophagy [ 15 ] and (iv) social acquisition from parent to offspring [ 16 ]. (ii) Environmental acquisition or horizontal transmission of symbiotic microbes For many insects, the majority of their symbionts are residents of the gut microbiome, composed mostly of bacteria acquired via contact, in or on, ingested food. However, the microbiome also has the potential to be structured in various ways, e.g. by host diet selection [ 17 , 18 ], screening [ 5 , 19 – 21 ], gut physiology [ 22 ] or by spatial compartmentalization of microbial species within the gut [ 10 ]. Sequencing of 16s rRNA genes has shown that insect hosts typically house relatively simple gut communities (often dominated by a few key taxa [ 18 ]) with the majority of the gut microbiome comprised of non-specialist microbes [ 23 , 24 ]. These tend to be newly acquired from the external environment each generation [ 19 , 25 – 27 ]. Differences between the species composition of gut microbiomes and the communities of the host’s external environments, suggests that at least some form of microbiome structuring occurs [ 17 , 28 ]. The ability to describe gut microbiomes and hosts across space and time (phylosymbiosis) has led to much interest in the roles and functional significance for hosts of their microbiomes [ 29 , 30 ]. There are two key questions to consider when evaluating the evolutionary significance of host-gut microbiome relationships [ 31 ]. The first is the extent to which host-microbiome associations are assembled randomly or deterministically [ 5 ]. The second is whether there is the potential for recurrent environmental acquisition of specific symbionts at sufficient fidelity for them to have the potential to shape the evolution of their hosts [ 3 ]. In general, we expect this process to be less efficient than VT, lowering the likelihood that host-microbe associations will evolve [ 5 , 10 , 32 , 33 ]. However, specific conditions may nevertheless allow environmental acquisition or HT to favour selection for host-microbe co-associations. HT may occur when juvenile hosts acquire microbes through a source pool of parental or conspecific microbes. If there are fitness benefits gained by hosts, then microbe carriers will increase each generation as the ratio of carriers to non-carriers, and therefore the number of contributors of microbes, has increased. Alternatively, mechanisms which manipulate hosts or promote transmission fidelity might also promote associations. For example, one route by which the transmission fidelity of HT bacteria might increase is via mate choice for individual hosts with similar microbiome. In Drosophila melanogaster , assortative mating by diet, and thus microbiome similarity, is reported [ 34 ]. Different gut microbiota are associated with differences in cuticular hydrocarbon profiles [ 35 ] that may influence the expression of mating pheromones [ 36 ]. The finding of positive assortative mating by microbiomes, however, shows a lack of replicability [ 37 – 40 ]. Nevertheless, control of host behaviour by symbionts, particularly when this influences transmission dynamics, has the potential to influence the strength of co-associations [ 41 – 45 ]. It has been proposed that influences on host mate choice effects by transient gut microbiota, such as a preference for carriers of a particular microbe to only mate with other carriers of the same microbe, can act as a precursor to reproductive isolation and thus speciation [ 46 ]. In theory, within these newly isolated populations, key bacteria could be routinely ‘added back to the pool’ for acquisition by juvenile hosts (VT or HT), while the introduction of new microbes is restricted by host-mating exclusion. However, to our knowledge, no experimental or theoretical models have yet addressed how bacteria-induced host mate choice can act as a driver of RI within a homogenous population or reinforce isolation between populations. This is an omission that we tackle here by developing new theory, as described below. Alternatively, host-microbe relationships with asocially environmentally-acquired bacteria might occur if hosts can screen in or out specific bacterial species or functional traits [ 5 , 19 – 21 ]. Then environmentally-acquired bacteria could play a role in shaping host evolution, even in the absence of VT or HT. Consistent with this, an increasing number of studies show that, when controlling for diet and environment, it is often possible to align the microbiome with that of its host’s evolutionary history [ 29 , 30 ]. This suggests that the non-stochastic assembly of microbiomes occurs through environmental acquisition. The strength of selection for such host-microbe co-associations is likely to be strongly affected by whether microbial selection is primarily host-led [ 47 , 48 ] or due to microbial niche selection [ 49 ]. Host-led selection, in particular, is thought to promote parallelism / phylosymbiosis at a functional, but not necessarily taxonomic, level [ 50 , 51 ]. For example, host physiology may be adapted to the metabolic functions of resident microbiomes, thus directing the functional properties of microbes that can colonise them. The mechanisms involved may include the actions of host antimicrobial peptides [ 52 ], immune genes [ 53 ] and host-specific biofilms that affect gut colonization efficiency [ 54 ]. Host-led control of colonisation could also be influenced instead by the morphological and physicochemical conditions in the host gut [ 10 ]. Phylosymbiosis would then result because the guts of closely related host species provide similar environmental niches and thus favor the formation of microbiomes that echo evolutionary phylogeny, independent of any host fitness benefits or close evolutionary co-associations. Studies reporting the existence of phylosymbiosis in host-gut microbiome associations are increasing. However, in general, microbial detection methods, in isolation, cannot separate residents from dead or transient microbes [ 55 ], potentially leading to overestimates of phylosymbiosis. Bacteria may also sometimes be repeatedly acquired from the environment into non-primary hosts, which would represent a microbial evolutionary dead-end. There are well-verified examples in which a resident microbiome seems mostly lacking [ 56 ]. For example, in an investigation of inter- and intra-specific variability in microbial biomass in caterpillars, Hammer et al. [ 42 ] observed an extremely low density of recurrent bacteria in guts in comparison to those found on the hosts’ food. Given current detection methods used and the near ubiquity of laboratory contaminants, transients, parasitic and pathogenic microbes, it seems likely that there are more cases of hosts lacking resident or beneficial microbiomes than has so far been realized. (iii) Mixed modes of transmission of symbiotic microbes In highly specialised intracellular host-microbe associations, such as the Buchnera – pea aphid system, host and microbe phylogenies match with high fidelity [ 57 ] and the genomes of the obligate symbionts display evolutionary signatures of VT, namely a reduction in genome size and a loss of metabolic capabilities [ 9 ]. However, it is thought that even for obligate symbiotic bacteria, propagation exclusively through VT is comparatively rare [ 11 ], and in many cases there is instead evidence for current or previous mixed modes of microbial transmission. For example, the intracellular symbiont Wolbachia exhibits strong VT, yet has a considerably larger genome than would be predicted on the basis of evolved co-dependence with its hosts [ 58 , 59 ], and discordant phylogenies between Wolbachia species and their hosts suggests an extensive evolutionary history of HT [ 60 , 61 ]. In contrast, gut microbiomes, previously perceived as transient, may exhibit greater stability than expected. For example, the D. melanogaster fruit fly microbiome has long thought to be formed from communities of microbes living on recently ingested food [ 62 , 63 ]. However, it also appears that some bacterial strains may form stable associations in a host-specific manner [ 64 , 65 ]. For example, Acetobacter thailandicu s appears to form a permanent association with the D. melanogaster gut once it becomes established through environmental acquisition. However, it can also propagate to offspring (VT) and conspecifics (HT) through continuous bacterial shedding [ 65 ]. At least some symbiotic microbes, therefore, may be subject to mixed modes of transmission (MMT), involving combinations of VT, HT and environmental acquisition [ 4 , 11 , 14 , 65 – 67 ]. Bacteria that are capable of independent replication and proliferation in the environment but are also capable of colonization of the insect gut and VT, gain multiple opportunities for spread within hosts. A combination of transmission modes may thus greatly increase the range of ecological conditions that support symbionts [ 11 , 68 ]. For the host, there is also growing evidence that having some degree of flexibility around a core microbiome may aid in rapid diet-switching and localized adaptation [ 69 ]. Specific mechanisms of transmission are not necessarily required for MMT. For example, bacterial films surround insect eggs from contact smearing during oviposition and bacteria here may independently replicate to establish free-living independently replicating populations and or be ingested by neonate larvae (and thus represent VT) and their conspecifics (HT) [ 14 ]. The lack of specialism and relaxed ecological constraints required may make this a frequent mechanism for symbiotic transmission [ 2 , 14 , 70 ]. MMT may also include transmission in a social context (e.g. parental care or social interactions such as mating [98]) where the conditions of bacterial transfer through mechanisms such as egg-smearing may be predominantly vertical, horizontal, or both depending on the social environment [ 4 ]. While MMT has the potential to reduce the strength and consistency of VT and selection for tight co-associations between microbes and hosts, it may have other benefits that increase the host fitness across a wide range of ecological conditions if hosts are able to supplement the microbiome with microbes from novel environments [ 66 , 69 ]. For these reasons, MMT is starting to garner increasing attention [ 4 , 11 , 70 ], though empirical and theoretical evidence for it is so far limited. We address this here by developing theory that evaluates combinations of different symbiont transmission mechanisms. 2. Using models to test the effect of alternative transmission modes, host reproduction and microbe fitness benefits on the frequency of microbe-carrying hosts To our knowledge, while there are verbal models of induced host mate-choice manipulation on host-associated microbes, there are as yet no theoretical models Here we address this omission by developing a series of hierarchical, deterministic, discrete generation mathematical models of the population-level frequency of host-microbe associations. In turn, we varied the mode of microbe acquisition (VT, HT or environmental acquisition), host reproductive mode (sex / asex), host mate choice (assortative mating or carrier preference), and magnitude of microbe effects on host-fitness – all over a range of realistic parameter space ( figure1 ). Download figure Open in new tab Fig 1. Testing the effects of symbiont transmission mode, host reproductive mode, host mate choice, microbe effects on host fitness and host dispersal across populations on the stability of host - symbiont relationships. (i) Effect of symbiont transmission mode (top left) . We assumed three non-exclusive mechanisms by which individuals could become microbe carriers, with a probability from 0 to 1 for each transmission route. The first was VT (we do not differentiate from pseudo-VT) by maternal transmission, whereby offspring of a female carrier would inherit that microbe with probability (α). The second was environmental acquisition, wherein hosts within an area would recurrently uptake the microbe from an open pool of independently replicating microbes with probability (β) (note that we do not differentiate here between host-selection or bacterial niche exploitation). The third was horizontal transmission, whereby an individual can become a microbe carrier via contact between carriers and non-carriers in the same area, with probability (τ) where conversion of non-carrier individuals into carriers occurs at a probability that varies depending upon the overall frequency of carrier individuals within the population. (ii) Effect of host reproductive mode and mate choice (bottom left). We considered the effect of different forms of host reproduction and assortative mating. We first considered scenarios in which reproduction was entirely asexual, and then exclusively sexual. In the case of sexual reproduction, we assessed the impact of assortative mating (bottom left), where individuals have n chances (1-9) to find a preferred mate. In the main text we present models of male mating preferences. Models of female choice are included in SI. Female mate choice produces little or no effect on carrier frequencies, as females are the sex producing VT and choice of partner (carrier or non-carrier) does not alter transmission. We considered mate preferences in two scenarios, first where individuals prefer to mate with those of the same carrier type (carrier:carrier/ non-carrier:non-carrier) and second where individuals of any carrier type prefer to mate with carriers. (iii) Effect of microbe acquisition on host fitness (bottom right) . Carriers were either more or less fit relative to non-carriers (relative fitness, ε) as measured by lifetime reproductive success. (iv) Effect of host population structure (top right) . The final step was to consider whether host-microbe associations could increase in frequency in a single homogenous population versus in a scenario in which we included a second population in which the symbiotic microbes could not be acquired from the environment (i.e. only via VT from migrant hosts). Here we used discrete generational mathematical models and set a dispersal rate of 2% between populations. Key assumptions in all of these simple models were that relative fitness mediated by bacteria was fixed and not environmentally-dependent, and we did not include population density parameters that might have affected indirect transmission dynamics. This figure was created by using BioRender.com. In doing so, we addressed four main questions: which modes of transmission, either singly (VT, HT, or environmental acquisition) or in combination (MMT), are most likely to lead to high frequencies of association between microbes and hosts? can modes of host reproduction (sexual or asexual) and host mate choice (positive or negative assortment for microbe carriers) increase the frequency of host-microbe associations? do associations between host and microbes require the microbial partner to increase host fitness in order to increase population frequencies of carriers? do parameters leading to high frequency host-microbe associations alter when considering one homogenous population space when compared to two partially isolated populations? These models allowed us, in a stepwise fashion, to predict whether stable host-microbe relationships would establish, first in a single homogenous population, and then within a second, partially isolated population. We chose this population structure scenario to explore because it allowed us to model explicitly the suggestion from the literature, that mate choice linked to microbiome carrier status can represent a strong precursor of reproductive isolation [ 38 – 40 ]. We restricted our approach to deterministic modelling due to the number of distinct modes of microbe transmission we wished to consider. This allowed us to disentangle the impacts of each parameter more easily. We also reasoned that, in considering a sufficiently large population, stochastic effects would only play a significant role when microbe frequencies are very low. The models and results were developed and run in MATLAB (R2016a; The MathWorks Inc., Natick, MA). A summary of model parameters is in Table 1 , while full details of modelling methods, effects and parameters tested are described in the Supplementary Information. The full set of results for all parameters tested are shown in figures S1-5, and we summarise the key results in the main text, below. (i) Single population model: effects of transmission mode, host reproductive mode, host mate choice and microbe effects on host fitness on host-microbe carrier frequency Under scenarios of reduced or neutral fitness, when maternal VT was anything less than 100%, some degree of environmental acquisition, or horizontal transmission was required to promote a high frequency of microbe carrying hosts ( figure 2a ; figures S1-S5 show the influence of horizontal transmission effects of τ = 0, 0.25 and 0.5 for all scenarios modelled). This effect was less pronounced when host microbe carriers had higher fitness than non-carriers, and in this scenario imperfect (but nevertheless high) maternal VT could still lead to a high (>90%) frequency of carriers within the population ( figure 2b ). Download figure Open in new tab Figure 2. High frequency transmission of microbes (through a variety of mechanisms - MMT) is a primary determinant of host-microbe carrier frequencies within a single population of sexually reproducing individuals. Each line represents different steady-state microbe carrier frequencies (0.1-0.9, increasing in 0.2 intervals). Multiples of each line represent additional degrees of male mate choice, e.g. the number of opportunities a male has to find a preferred mating partner from n= 1, (no choice) to 9 (choosiest). Black arrows in panels (b) and (d) are used to highlight the main differences in conditions leading to a high carrier frequency (>0.9). Each panel represents a possible combination of host mate preference and relative fitness levels of host microbe carriers (ε = 0.75 in panels (a) and (c), vs ε = 1.33 in (b) and (d)) as specified. In all cases, anything less than perfect 100% maternal VT required some environmental acquisition of the microbe for carriers to reach a high frequency within the population. A comparison of panels (a) and (b) shows that the relative fitness of host microbe carriers compared to non-carriers had only a modest effect on the conditions required for carriers to reach high frequency. Positive assortative host mating by males for the same host type (carrier-carrier vs non-carrier-non-carrier) slightly changed the transmission conditions and either relaxed or increased transmission requirements based on overall carrier proportions. However, overall, the actual strength of host assortative mating had only a minimal effect. A comparison of panels (c) and (d) shows that preference by males for female microbe carriers had a modest effect on relaxing the stringency of transmission for carriers at all population frequencies. Effects of the microbes on host fitness again had minimal effect on the conditions required for carriers to reach high frequency. For full model outputs, see figures S4A and S5A. In each case, here and for figure 3 , equilibrium carrier frequencies of zero are not possible for most parameter combinations due to the model structure considered (instead frequencies asymptote toward zero). Carrier frequencies equal to one are attained but only in cases with perfect vertical transmission and/or environmental acquisition meaning they overlie figure axes and are not visible. Download figure Open in new tab Figure 3. Host-associated microbes cannot establish in a new population in which they are incapable of independent proliferation outside hosts, unless VT is high, and they increase host fitness significantly. In population 1 microbes can proliferate independently of hosts and there is environmental acquisition by the host. In population 2 microbes cannot be acquired by hosts from the environment, only via maternal VT from migrants from population 1. Each line represents different steady-state microbe carrier proportions (0.1-0.9, increasing in 0.2 intervals). Multiples of each line represent additional degrees of host mate choice, e.g. the number of opportunities a male has to find a preferred mating partner from n= 1, (no choice) to 9 (choosiest). Black arrows in panels (b) and (d) are used to highlight the main differences in parameter combinations capable of producing a high carrier frequency (>0.9). Each panel shows a possible combination of host mate choice and host-microbe carrier fitness relative to non-carrier fitness, with details as specified in the figure labels. Here the microbe cannot spread with its host carriers into a second population at anything less than equal fitness to non-microbe carrying hosts. Positive assortative mating by hosts for the same carrier type (carrier-carrier vs non-carrier - non carrier) in panels (a) and (b) strongly reinforces population separation. In (c) and (d) preference by males is for female microbe carriers and this has the opposite effect, relaxing the degree of VT required for carriers to persist in population 2. For full model outputs, see figures S4B and S5B. The overall effect of host reproductive mode (sexual vs asexual) on host-microbe carrier frequency was minimal (compare figure 2 with figure S1A). Within models including sexually reproducing hosts, the type and strength of mate choice did have modest effects on transmission dynamics. When males had a positive assortative preference for mating with the same type of host (carrier:carrier/ non-carrier:non-carrier) it generally decreased the transmission efficiency needed for high microbe carrier frequencies to be reached. However, at the highest levels of assortative mating, these parameter ranges were reduced as it became harder for the microbe to pass from carriers to non-carriers ( figure 2a-b ; S5A). Preference for carriers, in which all males preferred to mate with female carriers, had a modest effect on increasing the range of environmental acquisition and maternal transmission parameters that could result in high microbe carrier frequencies (>90%). Female mate choice had minimal effect on carrier frequencies (compare figures S3A and S3B with figures S2A and S2B). This is because females mediate VT, hence choice of partner (carrier or non-carrier) does not alter transmission (compare figure S2A to S4A; figure S3A to S5A). The overall effects of mate preferences were minimal in comparison to the requirements for high maternal VT. Surprisingly, in these models, the effect of the microbe on host fitness had little impact upon the conditions required for carriers to reach high frequency ( figure 2a vs 2b and figure 2c vs 2d ; for the full range of fitness from 0-2 across all scenarios modelled, see figures S1-S5). Note that in all cases we find a large variation in the time taken to reach a microbe carrier frequency >0.9 (from an initial carrier frequency of 0.01), ranging from one to ~250 generations depending on the precise parameter combination. (ii) Two population model: effects of transmission mode, host reproductive mode, host mate choice and microbe effects on host fitness on host-microbe carrier frequency When we included a neighboring population that did not naturally host the microbe (with 2% bidirectional rate of dispersal), we found that the microbe could not spread into this second population under any set of transmission parameters, if that microbe reduced the fitness of carriers. For the microbe to spread, the fitness of carriers had to be at least equal to non-carriers. A high fitness advantage to microbe carriers somewhat compensated for imperfect maternal VT, a high level of maternal VT was still required for microbes to spread in the second population (figure S1A vs S1B; figures S2B, S3B, S4B, S5B). The effect of host reproductive mode (sexual vs asexual) on host-microbe carrier frequency was again minimal (figure S1B). In the sexual scenarios, mate preference for the same carrier host type reinforced the separation of the two populations ( figure 3a ). Even when microbe carriers were fitter than non-carriers, this type of assortative mating prevented the spread of the microbe into the second population ( figure 3b ). In contrast, when all male hosts had a preference for mating with female microbe carriers, increasing mate choice promoted an increase in host-microbe carriers. The parameters of maternal VT required for the microbe to establish at high frequency in the second population were relaxed ( figure 3c-d ). Increasingly levels of HT allowed microbes to spread more easily into the second population (figures S4B, S5B) under both mechanisms of mate choice. This interesting result shows that host-mate choice based on the presence of gut microbes can potentially reinforce or weaken reproductive isolation, depending on the type of host mating preference expressed. This effect may be reinforced or weakened depending on whether novel environmental microbe acquisition or HT predominates in specific animal systems. 3. Discussion and conclusions Overall the modelling results revealed that the spread of microbes at a high frequency within a host population was more easily attained when there were high fidelity transmission routes, and mixed modes of transmission that incorporated both maternal VT, HT, and environmental acquisition. This supports the idea that that the importance of such mixed transmission modes may have been overlooked [ 68 ]. Surprisingly, rather than host-microbe associations being strongly contingent upon benefits to host fitness and mutualism, the models suggest that transmission efficiency is the primary determinant of host microbe carrier frequency. Furthermore, efficient microbial transmission, using one or several mechanisms, led to high host microbe carrier frequencies even in the presence of a slight detriment to host fitness caused by microbe carrying. A growing body of studies focus on the existence of distinct modes of bacterial transmission and the effect of microbes on host physiology and fitness. However, what is less clear is the relative importance of these factors. In particular widely held assumptions that the presence of a recurrent association in host-microbe interactions, or physiological effect on hosts, necessarily indicates the presence of a mutualism, need to be challenged. We explored here key factors in the establishment of host-microbial relationships by analysing population dynamics models of co-association. The results suggested that neither phenotypic nor behavioural changes in the host (e.g. due to host mate choice for carriers) had a significant bearing on the transmission efficiencies required to promote a high frequency of host microbe carriers. The overall effect of host reproductive mode (sexual/asexual) was minimal in our models. Within the sexual scenarios, mate choice for host microbe carrier status, within a single population, had little effect on host carrier frequency, and is thus unlikely by itself to lead to reproductive isolation. Surprisingly, our results also suggested that the relative fitness of host carriers vs non-carriers was less important for increasing host microbe carriers than the existence of efficient microbial transmission [ 1 ]. This is not to say that effects of microbes on the fitness of their hosts were absent. However, over a large parameter space of relative fitness from 0.75 to 2.0, the frequency of host-microbe carriers hardly changed. Though this finding underlies our general conclusion that microbe effects on hosts had a modest effect, we note that such fitness effects gained in importance when we included dispersal and hence there may be scenarios that we did not explore here, where microbe-host effects have higher relative importance. If there is a strong fitness benefit to an association, it is possible that there could be selection on higher fidelity of transmission, and future research should also seek to verify these models, introduced fluorescently labelled bacteria with whole community analyses could be an easy mechanism to track transmission and fitness benefits across generations, to check that the reported outcomes are not unduly impacted by inaccurate model assumptions. At present, we lack suitable proofing data due to the absence of previous empirical or theoretical tests. However, our aim is that this initial theory will prove useful as a guide to frame future experiments, as outlined above, and others we have not yet considered, and thus provide future verifications. When we extended our models to consider a second population, both the effects of microbes on their hosts and maternal VT became more important. When microbes were incapable of independent replication (and hence environmental acquisition) in the second population, introduction of microbes was possible only via migration of host carriers from the first population. Microbial spread was then only possible if the microbes significantly increased the fitness of host carriers relative to non-carriers and achieved high fidelity of transmission. Effects of host mating behaviour were also more pronounced in scenarios with a second population: microbes that induced a preference for same host-type matings reinforced pre-existing reproductive isolation caused by the low dispersal rate (2%), while an overall mating preference for carriers reduced reproductive isolation, and slightly reduced the levels of VT required for spread. This suggests that direct effects of microbes on host mate choice cannot themselves result in reproductive isolation in otherwise homogeneous populations but could reinforce or breakdown pre-existing genetic isolation, depending on whether non-carriers prefer to avoid or seek out carriers (i.e. the form of host mating preference), and there is strong fidelity of microbial transmission. This is a recognition of microbial transmission dynamics as a keystone to the model of microbe-induced RI not considered in previous reports [ 46 ], but see [ 31 ], which is vital. We suggest that tests of whether modest levels of VT, within these partially isolated populations, where key bacteria are routinely ‘added back’ to their respective original populations, could be useful to establish long-term associations in which the introduction of competing microbes is restricted by host-mating exclusion. However, from our models, this effect appears to be moderated by the relative strengths of HT and environmental acquisition for microbe associations with juvenile hosts, and this could be tested empirically by combination approaches of microbiome community analyses and/or labelled bacterial strains to test their relative strengths in different model systems. Similar approaches could also be able to test the assumptions in our model that different transmission modes are routinely additive, when multiple species/strains of microbes are considered, do these instead become routes for microbe-microbe exclusion and competition? Our approach here was based upon deterministic modelling, due to the number of distinct modes of microbe transmission we considered. This was an advantage in that it allowed us to easily disentangle the impacts of each parameter and we reasoned that stochastic effects would only play a significant role at low microbe frequencies. Given we were seeking to explore mechanisms leading a microbe to spread to high frequency, we do not anticipate this approach to have had a significant or biasing impact on the results. However, we also recognise that these are preliminary models and that it would be useful in the future to specifically interrogate the effect of stochasticity. Another potentially useful addition to this approach, which lay outside of the initial modelling designs we deployed here, would be to include density dependent effects. This would allow an exploration the relative importance of an expanded range of ecological scenarios and to reveal interacting, non-linear averaging, or synergistic effects as the frequency of microbe carrying hosts increases. Our results also contribute to tests of the hologenome concept [ 3 ], in particular to holobiont assemblage, transmission and mutualism [ 71 ]. An expectation of holobionts is that high partner fidelity leads to mutualisms from the establishment of collective fitness. However, here we found that host fitness may play a relatively minor role in the establishment of host-microbial interactions [ 71 ]. Our results are not incompatible with predictions concerning holobiont assemblage [ 67 ], as we show that there are multiple, potentially synergistic, mechanisms of host-microbe assembly. However, they do suggest that the role of functional effects on host performance may be less important than the ability to evade or downregulate host immune responses [ 30 ]. Data accessibility The annotated MATLAB code for the modelling can be found at DOI 10.5281/zenodo.3746199. Authors’ contributions P.T.L, M.P.E and T.C. conceived the study, M.P.E. conducted the modelling, P.T.L, M.P.E and T.C wrote the manuscript. Competing interests The authors declare no conflicts of interest. Funding This research was supported by funding from the BBSRC (BB/K000489/1, grant to T.C., Matthew Hutchings and P.T.L). M.P.E. is funded through a Wellcome Trust Investigator Award [110117/Z/15/Z]. 4. References 1. ↵ McFall-Ngai , M. et al. 2013 Animals in a bacterial world, a new imperative for the life sciences . Proc. Natl. Acad. Sci. USA 110 , 3229 – 3236 . ( doi: 10.1073/pnas.1218525110 ) OpenUrl Abstract / FREE Full Text 2. ↵ Moran , N. A. , McCutcheon , J. P. & Nakabachi , A. 2008 Genomics and evolution of heritable bacterial symbionts . Annu. Rev. Genet. 42 , 165 – 190 . ( doi: 10.1146/annurev.genet.41.110306.130119 ) OpenUrl CrossRef PubMed Web of Science 3. ↵ Bordenstein , S. R. & Theis , K. R. 2015 Host biology in light of the microbiome: ten principles of holobionts and hologenomes . PLoS Biol. 13 , e1002226 . ( doi: 10.1371/journal.pbio.1002226 ) OpenUrl CrossRef PubMed 4. ↵ Ebert , D. 2013 The Epidemiology and Evolution of Symbionts with Mixed-Mode Transmission . Annu. Rev. Ecol. Evol. Syst. 44 , 623 – 643 . ( doi: 10.1146/annurev-ecolsys-032513-100555 ) OpenUrl CrossRef 5. ↵ Moran , N. A. & Sloan , D. B. 2015 The hologenome concept: helpful or hollow? PLoS Biol. 13 , e1002311 . ( doi: 10.1371/journal.pbio.1002311 ) OpenUrl CrossRef PubMed 6. ↵ Weinert , L. A. , Araujo-Jnr , E. V. , Ahmed , M. Z. & Welch , J. J. 2015 The incidence of bacterial endosymbionts in terrestrial arthropods . Proc. Biol. Sci. 282 , 20150249 . ( doi: 10.1098/rspb.2015.0249 ) OpenUrl CrossRef PubMed 7. ↵ Werren , J. H. , Baldo , L. & Clark , M. E. 2008 Wolbachia: master manipulators of invertebrate biology . Nat Rev Micro 6 , 741 – 751 . OpenUrl 8. ↵ Fine , P. E. 1975 Vectors and vertical transmission: an epidemiologic perspective . Ann. N. Y. Acad. Sci. 266 , 173 – 194 . ( doi: 10.1111/j.1749-6632.1975.tb35099.x ) OpenUrl CrossRef PubMed Web of Science 9. ↵ Moran , N. A. & Wilcox , J. 2002 Genome Evolution in Buchnera aphidicola, the Obligate Symbiont of Aphids . Nova acta Leopoldina 10. ↵ Engel , P. & Moran , N. A. 2013 The gut microbiota of insects - diversity in structure and function . FEMS Microbiol. Rev. 37 , 699 – 735 . ( doi: 10.1111/1574-6976.12025 ) OpenUrl CrossRef PubMed Web of Science 11. ↵ Bright , M. & Bulgheresi , S. 2010 A complex journey: transmission of microbial symbionts . Nat. Rev. Microbiol. 8 , 218 – 230 . ( doi: 10.1038/nrmicro2262 ) OpenUrl CrossRef PubMed Web of Science 12. ↵ Freitak , D. , Schmidtberg , H. , Dickel , F. , Lochnit , G. , Vogel , H. & Vilcinskas , A. 2014 The maternal transfer of bacteria can mediate trans-generational immune priming in insects . Virulence 5 , 547 – 554 . ( doi: 10.4161/viru.28367 ) OpenUrl CrossRef PubMed 13. ↵ Salem , H. , Florez , L. , Gerardo , N. & Kaltenpoth , M. 2015 An out-of-body experience: the extracellular dimension for the transmission of mutualistic bacteria in insects . Proc. Biol. Sci. 282 , 20142957 . ( doi: 10.1098/rspb.2014.2957 ) OpenUrl CrossRef PubMed 14. ↵ Behar , A. , Jurkevitch , E. & Yuval , B. 2008 Bringing back the fruit into fruit fly-bacteria interactions . Mol. Ecol. 17 , 1375 – 1386 . ( doi: 10.1111/j.1365-294X.2008.03674.x ) OpenUrl CrossRef PubMed Web of Science 15. ↵ Dasch & G. A. 1984 Endosymbionts of insects . Bergey’s Manual of Systematic Bacteriology 16. ↵ Kwong , W. K. , Medina , L. A. , Koch , H. , Sing , K.-W. , Soh , E. J. Y. , Ascher , J. S. , Jaffé , R. & Moran , N. A. 2017 Dynamic microbiome evolution in social bees . Sci. Adv. 3 , e1600513 . ( doi: 10.1126/sciadv.1600513 ) OpenUrl FREE Full Text 17. ↵ Chandler , J. A. , Lang , J. M. , Bhatnagar , S. , Eisen , J. A. & Kopp , A. 2011 Bacterial communities of diverse Drosophila species: ecological context of a host-microbe model system . PLoS Genet. 7 , e1002272 . ( doi: 10.1371/journal.pgen.1002272 ) OpenUrl CrossRef PubMed 18. ↵ Yun , J.-H. et al. 2014 Insect gut bacterial diversity determined by environmental habitat, diet, developmental stage, and phylogeny of host . Appl. Environ. Microbiol. 80 , 5254 – 5264 . ( doi: 10.1128/AEM.01226-14 ) OpenUrl Abstract / FREE Full Text 19. ↵ Kikuchi , Y. , Hosokawa , T. & Fukatsu , T. 2007 Insect-microbe mutualism without vertical transmission: a stinkbug acquires a beneficial gut symbiont from the environment every generation . Appl. Environ. Microbiol. 73 , 4308 – 4316 . ( doi: 10.1128/AEM.00067-07 ) OpenUrl Abstract / FREE Full Text 20. Brucker , R. M. & Bordenstein , S. R. 2012 The roles of host evolutionary relationships (genus: Nasonia) and development in structuring microbial communities . Evolution 66 , 349 – 362 . ( doi: 10.1111/j.1558-5646.2011.01454.x ) OpenUrl CrossRef PubMed Web of Science 21. ↵ Sanders , J. G. , Powell , S. , Kronauer , D. J. C. , Vasconcelos , H. L. , Frederickson , M. E. & Pierce , N. E. 2014 Stability and phylogenetic correlation in gut microbiota: lessons from ants and apes . Mol. Ecol. 23 , 1268 – 1283 . ( doi: 10.1111/mec.12611 ) OpenUrl CrossRef PubMed Web of Science 22. ↵ Kwong , W. K. & Moran , N. A. 2015 Evolution of host specialization in gut microbes: the bee gut as a model . Gut Microbes 6 , 214 – 220 . ( doi: 10.1080/19490976.2015.1047129 ) OpenUrl CrossRef PubMed 23. ↵ Tang , X. et al. 2012 Complexity and variability of gut commensal microbiota in polyphagous lepidopteran larvae . PLoS One 7 , e36978 . ( doi: 10.1371/journal.pone.0036978 ) OpenUrl CrossRef PubMed 24. ↵ Priya , N. G. , Ojha , A. , Kajla , M. K. , Raj , A. & Rajagopal , R. 2012 Host plant induced variation in gut bacteria of Helicoverpa armigera . PLoS One 7 , e30768 . ( doi: 10.1371/journal.pone.0030768 ) OpenUrl CrossRef PubMed 25. ↵ Hannula , S. E. , Zhu , F. , Heinen , R. & Bezemer , T. M. 2019 Foliar-feeding insects acquire microbiomes from the soil rather than the host plant . Nat. Commun. 10 , 1254 . ( doi: 10.1038/s41467-019-09284-w ) OpenUrl CrossRef 26. Kikuchi , Y. , Hosokawa , T. & Fukatsu , T. 2011 Specific developmental window for establishment of an insect-microbe gut symbiosis . Appl. Environ. Microbiol. 77 , 4075 – 4081 . ( doi: 10.1128/AEM.00358-11 ) OpenUrl Abstract / FREE Full Text 27. ↵ Kikuchi , Y. & Yumoto , I. 2013 Efficient colonization of the bean bug Riptortus pedestris by an environmentally transmitted Burkholderia symbiont . Appl. Environ. Microbiol. 79 , 2088 – 2091 . ( doi: 10.1128/AEM.03299-12 ) OpenUrl Abstract / FREE Full Text 28. ↵ Wong , C. N. A. , Ng , P. & Douglas , A. E. 2011 Low-diversity bacterial community in the gut of the fruitfly Drosophila melanogaster . Environ. Microbiol. 13 , 1889 – 1900 . ( doi: 10.1111/j.1462-2920.2011.02511.x ) OpenUrl CrossRef PubMed Web of Science 29. ↵ Lim , S. J. & Bordenstein , S. R. 2019 An introduction to phylosymbiosis . ( doi: 10.7287/peerj.preprints.27879v1 ) OpenUrl CrossRef 30. ↵ Brooks , A. W. , Kohl , K. D. , Brucker , R. M. , van Opstal , E. J. & Bordenstein , S. R. 2016 Phylosymbiosis: Relationships and Functional Effects of Microbial Communities across Host Evolutionary History . PLoS Biol. 14 , e2000225 . ( doi: 10.1371/journal.pbio.2000225 ) OpenUrl CrossRef PubMed 31. ↵ Leftwich , P. T. , Hutchings , M. I. & Chapman , T. 2018 Diet, Gut Microbes and Host Mate Choice: Understanding the significance of microbiome effects on host mate choice requires a case by case evaluation . Bioessays 40 , e1800053 . ( doi: 10.1002/bies.201800053 ) OpenUrl CrossRef 32. ↵ Douglas , A. E. & Werren , J. H. 2016 Holes in the Hologenome: Why Host-Microbe Symbioses Are Not Holobionts . MBio 7 , e02099 . ( doi: 10.1128/mBio.02099-15 ) OpenUrl CrossRef PubMed 33. ↵ Foster , K. R. , Schluter , J. , Coyte , K. Z. & Rakoff-Nahoum , S. 2017 The evolution of the host microbiome as an ecosystem on a leash . Nature 548 , 43 – 51 . ( doi: 10.1038/nature23292 ) OpenUrl CrossRef PubMed 34. ↵ Sharon , G. , Segal , D. , Ringo , J. M. , Hefetz , A. , Zilber-Rosenberg , I. & Rosenberg , E. 2010 Commensal bacteria play a role in mating preference of Drosophila melanogaster . Proc. Natl. Acad. Sci. USA 107 , 20051 – 20056 . ( doi: 10.1073/pnas.1009906107 ) OpenUrl Abstract / FREE Full Text 35. ↵ Lizé , A. , McKay , R. & Lewis , Z. 2014 Kin recognition in Drosophila: the importance of ecology and gut microbiota . ISME J. 8 , 469 – 477 . ( doi: 10.1038/ismej.2013.157 ) OpenUrl CrossRef PubMed 36. ↵ Dillon , R. J. , Vennard , C. T. & Charnley , A. K. 2002 A note: gut bacteria produce components of a locust cohesion pheromone . J. Appl. Microbiol. 92 , 759 – 763 . ( doi: 10.1046/j.1365-2672.2002.01581.x ) OpenUrl CrossRef PubMed Web of Science 37. ↵ Najarro , M. A. , Sumethasorn , M. , Lamoureux , A. & Turner , T. L. 2015 Choosing mates based on the diet of your ancestors: replication of non-genetic assortative mating in Drosophila melanogaster . PeerJ 3 , e1173 . ( doi: 10.7717/peerj.1173 ) OpenUrl CrossRef PubMed 38. ↵ Leftwich , P. T. , Clarke , N. V. E. , Hutchings , M. I. & Chapman , T. 2017 Gut microbiomes and reproductive isolation inDrosophila . Proc. Natl. Acad. Sci. USA 114 , 12767 – 12772 . ( doi: 10.1073/pnas.1708345114 ) OpenUrl Abstract / FREE Full Text 39. Leftwich , P. T. , Clarke , N. V. E. , Hutchings , M. I. & Chapman , T. 2018 Reply to Rosenberg et al.: Diet, gut bacteria, and assortative mating in Drosophila melanogaster . Proc. Natl. Acad. Sci. USA 115 , E2154 – E2155 . ( doi: 10.1073/pnas.1721804115 ) OpenUrl FREE Full Text 40. ↵ Leftwich , P. T. , Clarke , N. V. E. , Hutchings , M. I. & Chapman , T. 2018 Reply to Obadia et al.: Effect of methyl paraben on host-microbiota interactions in Drosophila melanogaster . Proc. Natl. Acad. Sci. USA 115 , E4549 – E4550 . ( doi: 10.1073/pnas.1805499115 ) OpenUrl FREE Full Text 41. ↵ Brucker , R. M. & Bordenstein , S. R. 2012 Speciation by symbiosis . Trends in ecology & evolution ( Personal edition) 27 , 443 – 451 . OpenUrl 42. ↵ Ezenwa , V. O. , Gerardo , N. M. , Inouye , D. W. , Medina , M. & Xavier , J. B. 2012 Microbiology. Animal behavior and the microbiome . Science 338 , 198 – 199 . ( doi: 10.1126/science.1227412 ) OpenUrl Abstract / FREE Full Text 43. Johnson , K. V.-A. & Foster , K. R. 2018 Why does the microbiome affect behaviour? Nat. Rev. Microbiol. 16 , 647 – 655 . ( doi: 10.1038/s41579-018-0014-3 ) OpenUrl CrossRef 44. Selkrig , J. et al. 2018 The Drosophila microbiome has a limited influence on sleep, activity, and courtship behaviors . BioRxiv ( doi: 10.1101/287045 ) OpenUrl Abstract / FREE Full Text 45. ↵ Yuval , B. 2017 Symbiosis: gut bacteria manipulate host behaviour . Curr. Biol. 27 , R746 – R747 . ( doi: 10.1016/j.cub.2017.06.050 ) OpenUrl CrossRef 46. ↵ Ringo , J. , Sharon , G. & Segal , D. 2011 Bacteria-induced sexual isolation in Drosophila . Fly (Austin) 5 , 310 – 315 . ( doi: 10.4161/fly.5.4.15835 ) OpenUrl CrossRef PubMed 47. ↵ McLoughlin , K. , Schluter , J. , Rakoff-Nahoum , S. , Smith , A. L. & Foster , K. R. 2016 Host selection of microbiota via differential adhesion . Cell Host Microbe 19 , 550 – 559 . ( doi: 10.1016/j.chom.2016.02.021 ) OpenUrl CrossRef PubMed 48. ↵ Hooper , L. V. & Gordon , J. I. 2001 Glycans as legislators of host-microbial interactions: spanning the spectrum from symbiosis to pathogenicity . Glycobiology 11 , 1R – 10R . ( doi: 10.1093/glycob/11.2.1R ) OpenUrl CrossRef PubMed Web of Science 49. ↵ Costello , E. K. , Stagaman , K. , Dethlefsen , L. , Bohannan , B. J. M. & Relman , D. A. 2012 The application of ecological theory toward an understanding of the human microbiome . Science 336 , 1255 – 1262 . ( doi: 10.1126/science.1224203 ) OpenUrl Abstract / FREE Full Text 50. ↵ Louca , S. , Parfrey , L. W. & Doebeli , M. 2016 Decoupling function and taxonomy in the global ocean microbiome . Science 353 , 1272 – 1277 . ( doi: 10.1126/science.aaf4507 ) OpenUrl Abstract / FREE Full Text 51. ↵ Rennison , D. J. , Stuart , Y. E. , Bolnick , D. I. & Peichel , C. L. 2019 Ecological factors and morphological traits are associated with repeated genomic differentiation between lake and stream stickleback . Philos. Trans. R. Soc. Lond. B, Biol. Sci. 374 , 20180241 . ( doi: 10.1098/rstb.2018.0241 ) OpenUrl CrossRef 52. ↵ Franzenburg , S. , Walter , J. , Künzel , S. , Wang , J. , Baines , J. F. , Bosch , T. C. G. & Fraune , S. 2013 Distinct antimicrobial peptide expression determines host species-specific bacterial associations . Proc. Natl. Acad. Sci. USA 110 , E3730 – 8 . ( doi: 10.1073/pnas.1304960110 ) OpenUrl Abstract / FREE Full Text 53. ↵ Belkaid , Y. & Harrison , O. J. 2017 Homeostatic immunity and the microbiota . Immunity 46 , 562 – 576 . ( doi: 10.1016/j.immuni.2017.04.008 ) OpenUrl CrossRef PubMed 54. ↵ Frese , S. A. et al. 2013 Molecular characterization of host-specific biofilm formation in a vertebrate gut symbiont . PLoS Genet. 9 , e1004057 . ( doi: 10.1371/journal.pgen.1004057 ) OpenUrl CrossRef PubMed 55. ↵ Hammer , T. J. , Sanders , J. G. & Fierer , N. 2019 Not all animals need a microbiome . FEMS Microbiol. Lett. 366 . ( doi: 10.1093/femsle/fnz117 ) OpenUrl CrossRef 56. ↵ Hammer , T. J. , Janzen , D. H. , Hallwachs , W. , Jaffe , S. P. & Fierer , N. 2017 Caterpillars lack a resident gut microbiome . Proc. Natl. Acad. Sci. USA 114 , 9641 – 9646 . ( doi: 10.1073/pnas.1707186114 ) OpenUrl Abstract / FREE Full Text 57. ↵ Moran , N. A. , Munson , M. A. , Baumann , P. & Ishikawa , H. 1993 A molecular clock in endosymbiotic bacteria is calibrated using the insect hosts . Proc. R. Soc. Lond. B 253 , 167 – 171 . ( doi: 10.1098/rspb.1993.0098 ) OpenUrl CrossRef 58. ↵ Wu , M. et al. 2004 Phylogenomics of the reproductive parasite Wolbachia pipientis wMel: a streamlined genome overrun by mobile genetic elements . PLoS Biol. 2 , E69 . ( doi: 10.1371/journal.pbio.0020069 ) OpenUrl CrossRef PubMed 59. ↵ Sun , L. V. , Foster , J. M. , Tzertzinis , G. , Ono , M. , Bandi , C. , Slatko , B. E. & O’Neill , S. L. 2001 Determination of Wolbachia genome size by pulsed-field gel electrophoresis . J. Bacteriol. 183 , 2219 – 2225 . ( doi: 10.1128/JB.183.7.2219-2225.2001 ) OpenUrl Abstract / FREE Full Text 60. ↵ Werren , J. H. , Zhang , W. & Guo , L. R. 1995 Evolution and phylogeny of Wolbachia: reproductive parasites of arthropods . Proc. Biol. Sci. 261 , 55 – 63 . ( doi: 10.1098/rspb.1995.0117 ) OpenUrl CrossRef 61. ↵ Vavre , F. , Fleury , F. , Lepetit , D. , Fouillet , P. & Boulétreau , M. 1999 Phylogenetic evidence for horizontal transmission of Wolbachia in host-parasitoid associations . Mol. Biol. Evol. 16 , 1711 – 1723 . ( doi: 10.1093/oxfordjournals.molbev.a026084 ) OpenUrl CrossRef PubMed Web of Science 62. ↵ Blum , J. E. , Fischer , C. N. , Miles , J. & Handelsman , J. In press. Frequent replenishment sustains the beneficial microbiome of Drosophila melanogaster . mBio 4 : e00860 – 13 . 63. ↵ Erkosar , B. & Leulier , F. 2014 Transient adult microbiota, gut homeostasis and longevity: novel insights from the Drosophila model . FEBS Lett. 588 , 4250 – 4257 . ( doi: 10.1016/j.febslet.2014.06.041 ) OpenUrl CrossRef PubMed 64. ↵ Obadia , B. , Güvener , Z. T. , Zhang , V. , Ceja-Navarro , J. A. , Brodie , E. L. , Ja , W. W. & Ludington , W. B. 2017 Probabilistic invasion underlies natural gut microbiome stability . Curr. Biol. 27 , 1999 – 2006.e8 . ( doi: 10.1016/j.cub.2017.05.034 ) OpenUrl CrossRef 65. ↵ Pais , I. S. , Valente , R. S. , Sporniak , M. & Teixeira , L. 2018 Drosophila melanogaster establishes a species-specific mutualistic interaction with stable gut-colonizing bacteria . PLoS Biol. 16 , e2005710 . ( doi: 10.1371/journal.pbio.2005710 ) OpenUrl CrossRef 66. ↵ Russell , S. L. 2019 Transmission mode is associated with environment type and taxa across bacteria-eukaryote symbioses: a systematic review and meta-analysis . FEMS Microbiol. Lett. 366 . ( doi: 10.1093/femsle/fnz013 ) OpenUrl CrossRef 67. ↵ Roughgarden , J. 2020 Holobiont Evolution: Mathematical Model with Vertical vs. Horizontal Microbiome Transmission . Philosophy, Theory, and Practice in Biology 12 . ( doi: 10.3998/ptpbio.16039257.0012.002 ) OpenUrl CrossRef 68. ↵ Lipsitch , M. , Nowak , M. A. , Ebert , D. & May , R. M. 1995 The population dynamics of vertically and horizontally transmitted parasites . Proc. Biol. Sci. 260 , 321 – 327 . ( doi: 10.1098/rspb.1995.0099 ) OpenUrl CrossRef 69. ↵ Keebaugh , E. S. , Yamada , R. & Ja , W. W. 2019 The Nutritional Environment Influences the Impact of Microbes on Drosophila melanogaster Life Span . MBio 10 . ( doi: 10.1128/mBio.00885-19 ) OpenUrl Abstract / FREE Full Text 70. ↵ Björk , J. R. , Díez-Vives , C. , Astudillo-García , C. , Archie , E. A. & Montoya , J. M. 2019 Vertical transmission of sponge microbiota is inconsistent and unfaithful . Nat. Ecol. Evol. ( doi: 10.1038/s41559-019-0935-x ) OpenUrl CrossRef 71. ↵ van Vliet , S. & Doebeli , M. 2019 The role of multilevel selection in host microbiome evolution . Proc. Natl. Acad. Sci. USA 116 , 20591 – 20597 . ( doi: 10.1073/pnas.1909790116 ) OpenUrl Abstract / FREE Full Text Back to top Previous Next Posted July 24, 2020. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Transmission efficiency drives host-microbe associations Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Transmission efficiency drives host-microbe associations Philip T. Leftwich , Matthew P. Edgington , Tracey Chapman bioRxiv 2020.07.23.216366; doi: https://doi.org/10.1101/2020.07.23.216366 Share This Article: Copy Citation Tools Transmission efficiency drives host-microbe associations Philip T. Leftwich , Matthew P. Edgington , Tracey Chapman bioRxiv 2020.07.23.216366; doi: https://doi.org/10.1101/2020.07.23.216366 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Evolutionary Biology Subject Areas All Articles Animal Behavior and Cognition (7969) Biochemistry (18633) Bioengineering (14770) Bioinformatics (44156) Biophysics (22458) Cancer Biology (19591) Cell Biology (26746) Clinical Trials (138) Developmental Biology (13902) Ecology (20890) Epidemiology (2067) Evolutionary Biology (25316) Genetics (16100) Genomics (23400) Immunology (18609) Microbiology (42209) Molecular Biology (17947) Neuroscience (92896) Paleontology (693) Pathology (2969) Pharmacology and Toxicology (5063) Physiology (8066) Plant Biology (15908) Scientific Communication and Education (2091) Synthetic Biology (4538) Systems Biology (10188) Zoology (2376) window.__CF$cv$params={r:'a37bfbb95f95d89d',t:'MTc4ODg0OTg1Mg==',u:'01a07fc290d079e29540138422f03456',ut:'fX9J4Bpyi9rX5yZW4LeYEEimPxMnxOqHn4qeEhCPBwY-1788849852-1.2.1.1-tuwqB_PUn6QsVVcLY7GjUqmr9DIFL7Nn2s8ISXQCXWpr25C2IcjzwAnBQSC2SCPwweW.DMk4cMQ4Q.OODUVMPG_CeeN151SvbjwKeznKt18',i:60};(function(){if(!document.body)return;var s=document.createElement('script');s.src='/cdn-cgi/challenge-platform/scripts/precursor/main.js';document.head.appendChild(s);})();