Hosts are likely to respond to parasitic infections by a combination of resistance (expulsion of pathogens) and tolerance (active mitigation of pathology). Of these strategies, the basis of tolerance in animal hosts is relatively poorly understood, with especially little known about how tolerance is manifested in natural populations. We monitored a natural population of field voles using longitudinal and cross-sectional sampling modes and taking measurements on body condition, infection, immune gene expression, and survival. Using analyses stratified by life history stage, we demonstrate a pattern of tolerance to macroparasites in mature compared to immature males. In comparison to immature males, mature males resisted infection less and instead increased investment in body condition in response to accumulating burdens, but at the expense of reduced reproductive effort. We identified expression of the transcription factor Gata3 (a mediator of Th2 immunity) as an immunological biomarker of this tolerance response. Time series data for individual animals suggested that macroparasite infections gave rise to increased expression of Gata3, which gave rise to improved body condition and enhanced survival as hosts aged. These findings provide a clear and unexpected insight into tolerance responses (and their life history sequelae) in a natural vertebrate population. The demonstration that such responses (potentially promoting parasite transmission) can move from resistance to tolerance through the course of an individual' s lifetime emphasises the need to incorporate them into our understanding of the dynamics and risk of infection in the natural environment. Moreover, the identification of Gata3 as a marker of tolerance to macroparasites raises important new questions regarding the role of Th2 immunity and the mechanistic nature of the tolerance response itself. A more manipulative, experimental approach is likely to be valuable in elaborating this further.
There is increasing recognition that the ability to tolerate a parasite' s presence, where the host accepts infection but actively limits the damage caused, may be a crucial host defence strategy [1], [2]. This is distinct from resistance, where the focus is on limiting the infection burden itself [3], [4], though in reality hosts often combine tolerance and resistance. Adopting a tolerance strategy may have major implications for the epidemiology and co-evolutionary dynamics of infectious disease through its effects both on individual hosts and on parasite transmission [5], [6]—for example, leading tolerant individuals to become infectious “super spreaders” [7] or promoting the evolution of higher transmissibility in tolerant populations [8]. However, parasite tolerance has often been neglected in animal and human studies [4], [9], and virtually nothing is known of its manifestation in natural systems. Here we focus on the expression of tolerance in a natural population and attempt to identify immunological processes underlying this and their consequences for important fitness components. In doing so, though, we must first address how tolerance can be defined and interpreted in studies of field systems. The term “tolerance” is used differently by immunologists and disease ecologists. In moving towards some unification of meaning, we must distinguish between pattern and process. The pattern associated with tolerance, typically the main focus of ecologists, is a relative insensitivity of host health (fitness) to increases in parasite burden [4]. This can result from various host responses (processes) that protect the host from the parasite without reducing parasite fitness. Examples include the up-regulation of wound healing or the down-regulation of immunopathology [9]. The latter would often involve the process conventionally termed tolerance by immunologists: the limitation of T- or B-cell responsiveness to cognate antigens. The pattern of tolerance may also result from host responses that ameliorate pathogen virulence (not tolerance in an immunological vocabulary), for example, by up-regulating lipoproteins that protect against endotoxins or serpins that target bacterial proteases [8]. In using the term tolerance, therefore, it is important to distinguish whether it is the pattern or the process that is being referred to, or both. In natural populations, and also in ecological experiments [4], the pattern will often be known, but the process will not. But equally, in laboratory immunology studies, details of the process may be available, but its consequences in a natural setting (the pattern) may not. The study of tolerance in field systems, then, is an indispensible complement to studies in the laboratory, and there have been calls for the greater integration of data from natural populations on host fitness, immunological variation, and infection pressure [10], [11]. However, field studies prove challenging in separating pertinent patterns from background noise with other causes and in distinguishing causal relationships from simple associations. Hence, it is necessary to predefine putative markers (“signatures”) of tolerance (patterns) and to assess these within a study framework aimed at disentangling alternative causalities. To achieve this, we draw on the perspective provided by an emphasis on “phase space” [12], where the important distinction is drawn between tolerance curves and phase or disease curves. In tolerance curves, the relationship between host health and parasite load is plotted, with each data point being an observation contributed by a different individual at a standardised stage in an infection (e. g. , maximal parasite load). A more tolerant population or subgroup would then be one in which the slope of this relationship was less negative, and a slope of zero (or even more, a positive slope) would be strongly suggestive of tolerance. In phase curves, by contrast, the relationship between an individual host' s health and parasite load is plotted, with each data point being an observation at a different stage in the infection. A more tolerant individual would then be one in which the decline in health with increasing load was less steep, and no decline at all (or even more, a positive slope) would be strongly suggestive of tolerance. This phase space perspective also highlights the absence of any agreed measure to quantify health but favours the use of “gross” (whole organism) measures such as those we have adopted here [12]. We hypothesised, first, that different groups of individuals (e. g. , life-history stages) will differ in their tolerance—their relationship between health and parasite load—and second, that those individuals that maintain good health in relation to parasite burden (i. e. , are more tolerant) will express more of the physiological pattern associated with tolerance. We monitored immunological gene expression, infection, body condition, and survival in replicated natural populations of field voles, Microtus agrestis, using interwoven cross-sectional and longitudinal sampling protocols. This hybrid study design took advantage of the greater range and precision of measurement possible in destructive (cross-sectional) sampling, and of the stronger causal inferences possible in capture–recapture (longitudinal) sequences, where driver variables may be observed to precede the responses they trigger [13]. Our objective was to identify patterns of tolerance, to link these to biomarkers among gene expression variables, and then to examine the life history consequences of the tolerance strategy through the surrogate of biomarker expression. Our overall aim was to place tolerance within a life history context and at the same time suggest possible immunological mechanisms (processes) based on the biomarker (s) identified. Specifically, adopting the phase space perspective (above), plotting our cross-sectional data comes closest to generating a tolerance curve. However, infection stage cannot be standardized in observations on natural populations. Hence, a less negative, zero, or even positive relationship between health and parasite load will be consistent with tolerance (and suggestive of it), but alternative explanations cannot be excluded. By contrast, our longitudinal data generate sequences of time points on a phase curve for a “typical” individual. A pattern in which health fails to decline (or even increases) following an increase in parasite load will therefore be directly indicative of tolerance. The case for demonstrable tolerance will, of course, be strongest if the results from the cross-sectional and longitudinal studies are consistent with one another. In contrast to tolerance, resistance resulting from acquired responses (usually the key component of resistance in co-adapted host–parasite associations; e. g. , [14]) is likely to be characterised by a decelerating or even negative accumulation of parasites over time and by a negative association between resistance markers and infection levels.
Our sampling, carried out in natural M. agrestis populations in Kielder Forest, Northumberland, United Kingdom, involved a cross-sectional component (n = 576 destructively sampled voles) and a longitudinal component (n = 920 marked individuals monitored through time, with n = 1,665 sampling points) and was replicated at two different sites in each of 2 y. Biometric and infection data were recorded at all sampling points. In the cross-sectional component, ligands for Toll-like receptors (TLRs) 2 and 7 were used to stimulate splenocyte cultures, from which we measured the expression of immune genes involved in regulatory (IL-10, TGF-β1) and effector (IRF5, IL-1β) pathways recruited during antimicrobial pattern recognition responses. In addition, the expression of genes reflecting different T-helper phenotypes was measured in nonspecifically (mitogen, PHA-L) activated splenocytes. The activity of regulatory T cells was represented by the anti-inflammatory cytokines IL-10 and TGF-β1 and the transcription factor FoxP3. The activity of T-helper cell type 1 (Th1) responses was represented by the pro-inflammatory cytokine IFN-γ and transcription factor Tbet and that of Th2 responses by the transcription factor Gata3. In the longitudinal component, constitutive expression of IFN-γ, IL-10, and Gata3 were measured in peripheral blood. Our overall analytical strategy (initially using standard statistical modelling techniques for single response variables) was to begin with our more detailed cross-sectional data and search first for the patterns of resistance or tolerance described above. We then sought to identify immunological gene expression markers of these patterns and, in turn, to link these to infection and life history variables. Next, we used our independent longitudinal data to corroborate the robustness of the immunological markers, place them within a stronger cause–effect context in relation to the infection and life history variables, and measure their effect on survival. Finally, we returned to the cross-sectional data and used structural equations modelling (SEM) to support the interdependencies between variables indicated by the longitudinal data. In analyses of the cross-sectional data, we primarily represented macroparasite infection using a reduced variable derived as scores from the first principal component of a principal components analysis (PCA) of the most common species that would be expected to be in contact with the host immune system (fleas, ticks, and adult tapeworms) (Table S1). In the search for immunological markers, this variable (PCM main) was tested first against similarly reduced immune gene expression variables (Table S2) and then against individual variables using multiplicity adjustments. Equivalent results were obtained if PCM main was replaced in analyses by a similar reduced variable for all macroparasite species recorded (PCM) or by measures of some influential species (e. g. , ticks). However, the composite measure (PCM main) has the advantage that relationships with host responses will not be diluted when, for example, a low burden for one parasite is accompanied by high burdens for others, such that the response to the low burden is “greater than expected, ” driven by the other parasites. In our initial search for patterns of tolerance or acquired resistance, we used general and generalized linear mixed models (LMMs and GLMMs; details in Methods S1). In the overall population (in models with slopes averaged across life history stages), macroparasites (PCM main) tended to accumulate linearly with individual size and age, with no indication that acquired resistance decelerated the acquisition of infection in older animals (Figure S5). This was not uniform across life history stages, though, with a particularly robust contrast occurring between mature males (those with large descended testes and expanded seminal vesicles) and immature males (Figure 1A). Mature males accumulated macroparasites linearly as age indicators increased (SVL [mm], slope parameter 0. 034±0. 009, p = 4. 5×10−4; eye lens weight [g], 283±79, p = 3. 9×10−4), but immature males supported less infection as age indicators increased (SVL, −0. 035±0. 013, p =. 011; lens weight, −317±97, p =. 002). This pattern is consistent with resistance building up prior to maturity but being absent postmaturity (Figure 1A). By contrast, there was a strong overall pattern consistent with a tolerance response. To examine this, we used as a proxy for individual health, not simple measures of weight but “body condition”: body (or organ) weight normalised for individual size – snout-vent length (SVL) and its quadratic term (see Methods S1). Considering all voles together, those in the best condition tended to be infected with the most macroparasites (body condition, p<5×10−7; Tables S3, S4, S5). Furthermore, stage-specific differences in tolerance were suggested by heterogenous slopes of body condition on macroparasite loads (PCM main) amongst different life history stages. A particularly robust contrast occurred again between mature males, which showed a strong positive relationship between parasite burden and body condition, and immature males, which showed no such relationship (Figure 1B, LMM, Stage×PCM main interaction, p =. 003) (Table S7). Amongst the microparasitic infections that we surveyed, animals displaying overt signs of tuberculosis (TB) (Mycobacterium microti) were also in better condition relative to others (body condition, p =. 018; Tables S3, S4). To identify immunological markers for a tolerance strategy and determine their consequences for host fitness, we then focused primarily on the dichotomy between mature and immature males, as the former showed the strongest increased body condition response to macroparasite infection but no epidemiological evidence of resistance. Patterns in females, which may be obscured by immunosuppression during pregnancy, were less clear cut, as discussed briefly below. We began by asking (using LMM analyses) whether the trend for apparent tolerance rather than resistance in mature versus immature males was linked to variation in immune gene expression. We found that a single parameter, mitogen-stimulated Gata3 expression in cultured splenocytes (Gata3mit-stim), was consistently and strongly associated with macroparasite burden, host condition, and life history in mature males and also showed a different pattern in immature males. First, Gata3mit-stim correlated with macroparasite burden positively in mature males (Figure 1C, p =. 007; Table S11) and negatively in immature males (Figure 1C). Second, Gata3mit-stim was positively correlated with liver and body condition in mature males (Figure 1D, p =. 027 and 7. 1×10−5, respectively; Tables S8 and S9) but not immature males (Figure 1D), even after controlling for the association between macroparasite burden and body condition noted above. Third, Gata3mit-stim had a significant negative association with size-adjusted testis weight (an estimator of male reproductive effort) in mature males (Figure 1E, p =. 014; Table S9). Thus, Gata3 expression was higher in mature males in good condition and infected with many macroparasites (Figure 1F) but with proportionately smaller reproductive investment. Notably, Gata3mit-stim expression was also a strong marker for elevated condition among animals with overt TB (Figure 1G, p<. 001; Table S10). Moreover, because Gata3 would usually be involved where Th2 immunity mediates resistance to macroparasites [15], the differing stage associations of macroparasites with Gata3 expression observed (Figure 1C) are indicative of changes in resistance. Thus, the negative association in immature males contrasted with the positive association in mature males is further evidence (additional to the stage-specific associations of infection with age indicators) (Figure 1A) that immature males may resist macroparasite infections, whereas mature males do not. Gata3 expression, then, may be a useful biomarker for either resistance or tolerance where a predominant pattern of one or the other can be established within groups, as it can in males. Nonpregnant females showed similar tolerance-like accumulations of macroparasites with age indicators and also increases in condition at higher macroparasite burdens. However, post hoc analyses indicated that these trends were not clearly marked by splenic Gata3 expression. This might be because of the re-adjustment of T-helper cell responses often seen during mammalian pregnancy [16] and also because among nonmating nonpregnant females (the majority of the female sample) prereproductives and those returning to a nonmating (imperforate) state following pregnancy could not be distinguished. Females also showed much lower infection levels than males (Figure S5B), and older females in mating condition, which were most heavily parasitized (Figure S5B) and thus most likely to show clear tolerance responses, were poorly represented in our cross-sectional sample (n = 47). Gata3 is a pivotal transcription factor involved in the development of Th2 cells [17]–[19], and its expression in mitogen-stimulated splenocyte cultures is likely to derive from proliferated Th cell populations. Th2 responses are typically triggered by macroparasite infection [20]–[24]. Hence, an initial hypothesis was that macroparasites stimulated higher Gata3 expression in mature males and that either macroparasites or Gata3 expression might then affect host condition and reproductive effort. To further explore possible causal links, we turned to our longitudinal data, focusing on macroparasites. In mature males, exposure to common blood-feeding ectoparasites was strongly associated with increased constitutive Gata3 expression in peripheral blood (Gata3blood) in the following month (LMM, Figure 2A, p =. 010; Table S12). (By contrast, the instantaneous association tended to be negative, perhaps reflecting some level of resistance to ectoparasites due to peripheral blood responses.) In turn, Gata3blood was positively associated with weight gain (adjusted for starting body weight) in the following month (LMM, Figure 2B, p =. 039; Table S13). (By contrast, it was unrelated to weight gain in the preceding month.) Taken together, therefore, the longitudinal data suggest that in mature males at least, macroparasites are the driver of high Gata3 expression, which in turn is part of a response that promotes elevated body condition. That is, as individuals progress along their phase (disease) curve [12], one proxy for health (body condition), far from declining as parasite load increases, appears to increase, indicative of a tolerance response to infection. In applying SEM to our cross-sectional data (Figure 2C; Tables S14 and S15), we specifically sought the SEM that best fitted the data or was indistinguishable from the best in explanatory power, but that was also supported by the details of the longitudinal data analysis above. In fact, the best and one near-best SEM did have this support, though they differed as to whether male reproductive effort had a negative effect on Gata3 expression and body condition or was negatively affected by them (which we take to be more likely biologically). The SEM analysis was thus consistent with a causal path: macroparasites→elevated Gata3→increased somatic condition/reduced reproductive effort. As a final post hoc step in the sequence of analyses in the cross-sectional data, we reiterated the SEM, replacing Gata3mit-stim with each of the other immune gene expression variables in turn. No other variable approached the significant configuration of coefficients seen for Gata3mit-stim, suggesting that this response in particular (and not a wider combination of the expression responses measured) was linked to the tolerance pattern. Constitutive Gata3 expression in peripheral blood (Gata3blood), which decreased with age (using weight as a surrogate), was a significant predictor of survivorship in the longitudinal data (Figure 3; Tables S16 and S17). This effect occurred both for adult males and in the overall dataset including all stages (adult males comprising 27% of records in the longitudinal study). In both the overall and the adult male analyses, younger animals expressing high Gata3blood had lower survival, but older animals expressing high Gata3blood had higher survival (GLMM, Figure 3; Gata3blood×Weight interaction in mature males, p =. 036; in all stages, p =. 011).
These analyses suggest that expression of Gata3 (a master transcription factor involved in the differentiation of Th2 cells) can, in some individuals, be a marker for a physiological programme of tolerance to macroparasite infection, with implications for body condition, fecundity, and survival. Tolerance involved apparent overcompensation in body condition following infection, but accompanying that was downwards readjustment of fecundity, and age-dependent changes in survival, with survival improving in older tolerant (Gata3hi) animals. Our longitudinal analyses suggest, moreover, that rather than being a mere correlate, elevated Gata3 expression was triggered by macroparasite infection and preceded the life history readjustments. Some corroborative patterns were also seen for another chronic infectious disease, TB, with animals being in better condition if showing overt signs of infection and especially if also expressing high levels of Gata3. Our ability to infer tolerance in a complex field situation was facilitated by differing responses, in our cross-sectional study, between immature and mature males. These responses indicated a predominant pattern of resistance to macroparasites in the former and tolerance to macroparasites in the latter. Thus, as immature males aged, their infections reduced, consistent with the development of acquired resistance; also, mitogen-stimulated splenocyte Gata3 expression (Gata3mit-stim) was inversely associated with macroparasite infection in these animals. This presents a familiar scenario, consistent with the paradigmatic role of acquired Th2 responses in resistance against macroparasites. Mature males, on the other hand, showed a very different and unexpected pattern. They accumulated macroparasites with age (resulting in very high infection levels) and showed a positive association between Gata3mit-stim and infection. Furthermore, body condition increased in heavily infected animals, whereas Gata3mit-stim was also positively associated with body condition (trends not found in immature males) and negatively associated with male fecundity (adjusted testis weight). Our longitudinal time series data for recaptured adult males indicated that peripheral blood Gata3 expression was triggered by macroparasite exposures and preceded host responses that increased somatic maintenance and ultimately survival (in the oldest Gata3hi animals). This is suggestive of the process, and not just the pattern, of tolerance, as the increase in body condition associated with macroparasite infection and Gata3 expression is indicative of a protective response that does not affect the parasite directly. Gata3 expression in Th2 cells, then, at least in males where there is not the complicating factor of pregnancy, may serve as a biomarker for either resistance or tolerance to macroparasites, depending on whether one of these patterns dominates within a particular group of animals. Further studies are required to determine the relevance of these findings in other vertebrate systems, although the basic data required to establish the context of tolerance or resistance (i. e. , indicators of individual age, condition, and infection levels) are well within the routine scope of ecological researchers focussing on infectious disease. As considered further below, the dual aspect of Gata3 expression (marking either tolerance or resistance in different groups of animals) is biologically plausible given the known role of Th2 responses in some pathways leading to resistance to macroparasites [15] but also in pathways promoting wound-healing and tolerance processes [25]. This suggests the possibility, though, that upstream Th2 signals might drive different response mechanisms during resistance and tolerance. There are alternative possible explanations for some of the cross-sectional associations we observed within mature males. One would be “differential mortality”—that is, high parasite burdens eliciting high Th2 responses, but before our observations are made, animals in poor condition with many macroparasites suffering increased mortality, so that the only animals with high parasite burdens left to observe are those in good condition. A second explanation would be “correlated risk”—that is, increased risk in high condition animals of macroparasite infections, and the Th2 responses they trigger, due, for example, to animals that forage more actively acquiring both more food and more parasites. However, whereas the temporal sequences seen in the longitudinal data directly support the tolerance hypothesis (macroparasites→Gata3→good condition), they support neither differential mortality nor correlated risk, as high Gata3 expression would in neither case precede good condition. Similarly, both differential mortality and correlated risk would predict associations between Gata3 expression and survival that did not change with age, with the former specifically predicting an uncomplicated association of high Gata3 with low survival and poor condition. These predictions, too, are contradicted by our results. Furthermore, differential mortality and correlated risk do not provide explanations for differing cross-sectional associations between Gata3mit-stim, body condition, and macroparasite infection in mature and immature males. Hence, we can exclude these alternatives. Beyond our own system, these results may also provide some general insight into the nature of tolerance, as both pattern and process. The regulatory component of the immune system has often been seen as a potential driver of tolerance, through its role in suppressing immunopathological effector responses. Indeed, helminth parasites have been suggested to increase tolerance and reduce resistance by the elevation of regulatory responses [4]. However, while acknowledging the potential limitations of gene expression data [26], the prominent signature in our study of Gata3 in tolerant animals, rather than of archetypal regulatory genes (IL-10, TGF-β1, FoxP3), suggests that tolerance may in fact be significantly associated with a Th2 mechanism. In apparent opposition to this, Th2 responses have often been considered to mediate resistance to macroparasites (as in immature males in this study). In the laboratory they may do so via a diverse cascade of effector mechanisms [15]. However, not all effectors necessarily produce resistance to all species [15], [27], and vigorous effector responses have been observed without efficient resistance [27], [28]. Recently, moreover, Th2 responses have also been linked [25] with tolerance to macroparasites. A Th2 environment is well known to promote damage repair mechanisms, including the differentiation of alternatively activated macrophages [29], [30]. Also, generic Th2-associated effectors (e. g. , eosinophils, mast cells, antibodies) or Th2-driven fibrotic or granulomatous reactions [25], linked to the expression of Gata3, may mediate the pattern of tolerance by physically containing or more generally limiting the direct pathogenic activities of parasites. Furthermore, Th2 responses in chronic Mycobacterium infections have been thought to facilitate clinical disease progression [31]–[33], but the possibility that they function as a tolerance response has not been considered. And finally, although the responses of nonimmunological cell populations were not measured, Gata3 could also be involved in redirecting resources between life history traits during infection, through its role in the differentiation of cells involved in energy stores (e. g. , adipocytes [34], [35]) and reproductive investment (e. g. , mammary epithelia [36]). It seems possible that increased body condition and reduced fecundity, in mature males but not immature males, might be adaptive by increasing residual reproductive value during macroparasite infection. This is consistent with a positive influence of Gata3 expression on survival in the oldest males. The contrasting patterns seen between mature and immature males suggest these may face very different cost/benefit scenarios when deploying immune responses against macroparasites. At present we can only speculate about the nature of these pressures, although a number of interesting possibilities might be considered. For example, altered exposure (perhaps elevated in mature males due to increased ranging and social contacts) might raise the immunopathological or energetic costs of resisting infection above thresholds of sustainability. Mature males also, due to their greater prior opportunity to develop robust adaptive immunity to common pathogens, may face fewer consequences from secondarily adopting a more tolerant phenotype. Thus, tolerance processes might have more serious indirect consequences for younger individuals through the inhibition of inflammatory responses against primary microbial infections. These are the first results to indicate a mechanism of tolerance in a naturally occurring mammalian population and to place this within a holistic framework of host fitness: context-dependent cost–benefit outcomes for individual condition, reproductive investment, and survival. This work therefore illustrates how immunological studies in natural populations may not only benefit from the many advances made in the laboratory but might also feed insights back into mainstream immunology. The results support the view that Th2 responses may play a crucial role in the tolerance of infection, and they more generally add to the growing body of evidence arguing for an increased focus on tolerance in our quest to understand host responses to parasitic infection. Further progress is likely to be facilitated by adopting approaches that incorporate experimental manipulations.
All procedures were carried out under UK Home Office licence regulations. We studied field voles (M. agrestis) in Kielder Forest, Northumberland, United Kingdom, using live-trapping to access individual animals from natural populations. Our study was designed to permit the analysis of individual variation in condition and survival, infection status, and the expression of immune genes (additional details in Methods S1). In order to ensure representativeness, we repeated our field design at two spatially separate sites in 2008–2009 and a further two separate sites in 2009–2010 (Figure S1). The study was divided into longitudinal and cross-sectional components. Each site contained a live-trapping grid (∼0. 375 ha) of 150 (10×15) regularly spaced traps (3–5 m intervals) placed in optimal habitat (Figure S1). Animals from this grid were marked with passive radio frequency transponders (AVID) and monitored over time, as sequences of capture and recaptures, forming the longitudinal component of the study. At each capture, biometric, infection, and immune expression measurements were taken (Figure S2). On each site there were also satellite transects (with traps spaced at ≥5 m intervals) from which 10 animals per month per site were sampled destructively, forming the basis for the cross-sectional component of the study. Animals from this part of the study were returned to the laboratory, where it was possible to collect a more comprehensive and detailed set of biometric, infection, and immune expression measurements (Figure S2). The transects aimed to sample a very large area of the habitat, providing data representative of the entire population at each site, while at the same time avoiding significant demographic readjustments. Each site was monitored by monthly trapping sessions between February (in the 2008–2009 season) or April (in the 2009–2010 season) and November, during which the capture–recapture study was carried out on the grid and destructive samples were retained from the transects (Figure S3). At each site, in November at the end of the field season and again in the following March, larger numbers of animals were destructively sampled both from the transects and from the grid habitats, including some animals previously marked with AVID transponders and processed for small tail-tip blood samples as part of the capture–recapture study. These samples also contributed to the overall cross-sectional component of the study (Figure S3). Measurements of gene expression (IFN-γ, Tbet, IL-2, Gata3, IRF5, IL-10, TGF-β1, FoxP3) in the cross-sectional element of the study focussed on cultured splenocytes and are described in detail in Jackson et al (2011) [20]. Through the combination of stimulatory conditions applied and the genes investigated, these measurements were intended to reflect both innate immune responses (including TLR-mediated responses) and adaptive responses (including Th1, Th2, and T-regulatory responses). In the longitudinal study we measured in vivo expression of a subset (IFN-γ, Gata3, IL-10) of the genes investigated in the cross-sectional study, in peripheral blood samples. Using direct counts or semiquantitative abundance indices, we quantified 25 species of macroparasite in our study animals, some of which were aggregated into ecologically and phylogenetically coherent groups to facilitate analysis (additional details in Methods S1). We also recorded overt symptoms of vole TB caused by M. microti and carried out PCR diagnostics for Bartonella spp. and Babesia microti using previously established methods (see Methods S1, Table S18). Data were analyzed using LMMs or GLMMs to relate individual variables to potential explanatory variables while allowing for nonindependence due to sampling and immunological assaying structure. SEM was used to assess patterns of interdependency among multiple variables simultaneously. Some variables used in these analyses were principal component scores (reduced from larger sets of partially redundant measurements using PCA). In the case of macroparasites, we used the first principal component (PCM main) from a PCA of common taxa likely to be in strong contact with the immune system (i. e. , feeding on, or dwelling in or on blood or internal tissues; >20% prevalence overall) as the main analytical variable (see Methods S1 for more details). This component was dominated by high loadings of the same sign for the main macroparasite groups (fleas, ticks, and adult cestodes). Analyses of vole return rates and survivorship were carried out using GLMMs and Cormack-Jolly-Seber (CJS) methods with individual covariates. In order to control the type 1 error rate, the analyses proceeded according to an a priori sequential strategy, starting with a sparing number of initial main hypotheses and moving onto subsequent main hypotheses conditional upon significant results in previous rounds of testing. This strategy also made use of reduced immunological and parasitological data and multiplicity adjustments within each round of main hypothesis tests. More expansive post hoc analysis of individual variables and subsets of the data, for the purposes of corroboration and describing biological patterns in more detail, was conducted subsequent to each round of main hypothesis tests. More details on the methods and strategy for data analysis are given in Methods S1 (see Figure S4 and Table S19). Data available from the Dryad Digital Repository: http: //dx. doi. org/10. 5061/dryad. bk537 [37].
Hosts do not always resist parasites. And once infection establishes, relatively little is known of how naturally occurring hosts tolerate (mitigate for) adverse effects, or what the life history consequences of this tolerance may be. In this article we demonstrate a pattern of tolerance to parasitic worms and arthropods in wild voles and link this to increased expression of an immunological biomarker. The biomarker, Gata3, is triggered by infection, precedes significant changes in body condition, and impacts on fecundity and survival. These results point to the considerable ecological importance of tolerance in wild vertebrates and to how poorly it is understood, while at the same time giving a new perspective on the natural function of immune response pathways involving Gata3.
biology and life sciences
immunology
ecology and environmental sciences
An Immunological Marker of Tolerance to Infection in Wild Rodents