Health trajectories reveal the dynamic contributions of host genetic resistance and tolerance to infection outcome

Animal board invited review: Quantification of resilience in farm animals

Resilience, when defined as the capacity of an animal to respond to short-term environmental challenges and to return to the prechallenge status, is a dynamic and complex trait. Resilient animals can reinforce the capacity of the herd to cope with often fluctuating and unpredictable environmental conditions. The ability of modern technologies to simultaneously record multiple performance measures of individual animals over time is a huge step forward to evaluate the resilience of farm animals. However, resilience is not directly measurable and requires mathematical models with biologically meaningful parameters to obtain quantitative resilience indicators. Furthermore, interpretive models may also be needed to determine the periods of perturbation as perceived by the animal. These applications do not require explicit knowledge of the origin of the perturbations and are developed based on real-time information obtained in the data during and outside the perturbation period. The main objective of this paper was to review and illustrate with examples, different modelling approaches applied to this new generation of data (i.e., with high-frequency recording) to detect and quantify animal responses to perturbations. Case studies were developed to illustrate alternative approaches to real-time and post-treatment of data. In addition, perspectives on the use of hybrid models for better understanding and predicting animal resilience are presented. Quantification of resilience at the individual level makes possible the inclusion of this trait into future breeding programmes. This would allow improvement of the capacity of animals to adapt to a changing environment, and therefore potentially reduce the impact of disease and other environmental stressors on animal welfare. Moreover, such quantification allows the farmer to tailor the management strategy to help individual animals to cope with the perturbation, hence reducing the use of pharmaceuticals, and decreasing the level of pain of the animal.

Linking genotypic and phenotypic changes in the E. coli Long-Term Evolution Experiment using metabolomics

Changes in an organism's environment, genome, or gene expression patterns can lead to changes in its metabolism. The metabolic phenotype can be under selection and contributes to adaptation. However, the networked and convoluted nature of an organism's metabolism makes relating mutations, metabolic changes, and effects on fitness challenging. To overcome this challenge, we use the Long-Term Evolution Experiment (LTEE) with E. coli as a model to understand how mutations can eventually affect metabolism and perhaps fitness. We used mass-spectrometry to broadly survey the metabolomes of the ancestral strains and all 12 evolved lines. We combined this metabolic data with mutation and expression data to suggest how mutations that alter specific reaction pathways, such as the biosynthesis of nicotinamide adenine dinucleotide, might increase fitness in the system. Our work provides a better understanding of how mutations might affect fitness through the metabolic changes in the LTEE and thus provides a major step in developing a complete genotype-phenotype map for this experimental system.

Elucidating Mechanisms of Tolerance to Salmonella Typhimurium across Long-Term Infections Using the Collaborative Cross

Understanding the molecular mechanisms underlying resistance and tolerance to pathogen infection may present the opportunity to develop novel interventions. Resistance is the absence of clinical disease with a low pathogen burden, while tolerance is minimal clinical disease with a high pathogen burden. Salmonella is a worldwide health concern. We studied 18 strains of collaborative cross mice that survive acute Salmonella Typhimurium (STm) infections. We infected these strains orally and monitored them for 3 weeks. Five strains cleared STm (resistant), six strains maintained a bacterial load and survived (tolerant), while seven strains survived >7 days but succumbed to infection within the study period and were called “delayed susceptible.” Tolerant strains were colonized in the Peyer’s patches, mesenteric lymph node, spleen, and liver, while resistant strains had significantly reduced bacterial colonization. Tolerant strains had lower preinfection core body temperatures and had disrupted circadian patterns of body temperature postinfection sooner than other strains. Tolerant strains had higher circulating total white blood cells than resistant strains, driven by increased numbers of neutrophils. Tolerant strains had more severe tissue damage and higher circulating levels of monocyte chemoattractant protein 1 (MCP-1) and interferon gamma (IFN-γ), but lower levels of epithelial neutrophil-activating protein 78 (ENA-78) than resistant strains. Quantitative trait locus (QTL) analysis revealed one significant association and six suggestive associations. Gene expression analysis identified 22 genes that are differentially regulated in tolerant versus resistant animals that overlapped these QTLs. Fibrinogen genes (Fga, Fgb, and Fgg) were found across the QTL, RNA, and top canonical pathways, making them the best candidate genes for differentiating tolerance and resistance.

The cost of host genetic resistance on body condition: evidence from divergently selected sheep

Trade‐offs between host resistance to parasites and host growth or reproduction can occur due to allocation of limited available resources between competing demands. To predict potential trade‐offs arising from genetic selection for host resistance, a better understanding of the associated nutritional costs is required. Here, we studied resistance costs by using sheep from lines divergently selected on their resistance to a common blood‐feeding gastro‐intestinal parasite (Haemonchus contortus). First, we assessed the effects of selection for high or low host resistance on condition traits (body weight, back fat, and muscle thickness) and infection traits (parasite fecal egg excretion and loss in blood haematocrit) at various life stages, in particular during the periparturient period when resource allocation to immunity may limit host resistance. Second, we analysed the condition–infection relationship to detect a possible trade‐off, in particular during the periparturient period. We experimentally infected young females in four stages over their first 2 years of life, including twice around parturition (at 1 year and at 2 years of age). Linear mixed‐model analyses revealed a large and consistent between‐line difference in infection traits during growth and outside of the periparturient period, whereas this difference was strongly attenuated during the periparturient period. Despite their different responses to infection, lines had similar body condition traits. Using covariance decomposition, we then found that the phenotypic relationship between infection and condition was dominated by direct infection costs arising from parasite development within the host. Accounting for these within‐individual effects, a cost of resistance on body weight was detected among ewes during their first reproduction. Although this cost and the reproductive constraint on resistance are unlikely to represent a major concern for animal breeding in nutrient‐rich environments, this study provides important new insights regarding the nutritional costs of parasite resistance at different lifestages and how these may affect response to selection.

Breeding for disease resilience: opportunities to manage polymicrobial challenge and improve commercial performance in the pig industry

Disease resilience, defined as an animal's ability to maintain productive performance in the face of infection, provides opportunities to manage the polymicrobial challenge common in pig production. Disease resilience can deliver a number of benefits, including more sustainable production as well as improved animal health and the potential for reduced antimicrobial use. However, little progress has been made to date in the application of disease resilience in breeding programs due to a number of factors, including (1) confusion around definitions of disease resilience and its component traits disease resistance and tolerance, and (2) the difficulty in characterizing such a complex trait consisting of multiple biological functions and dynamic elements of rates of response and recovery from infection. Accordingly, this review refines the definitions of disease resistance, tolerance, and resilience based on previous studies to help improve the understanding and application of these breeding goals and traits under different scenarios. We also describe and summarize results from a "natural disease challenge model" designed to provide inputs for selection of disease resilience. The next steps for managing polymicrobial challenges faced by the pig industry will include the development of large-scale multi-omics data, new phenotyping technologies, and mathematical and statistical methods adapted to these data. Genome editing to produce pigs resistant to major diseases may complement selection for disease resilience along with continued efforts in the more traditional areas of biosecurity, vaccination and treatment. Altogether genomic approaches provide exciting opportunities for the pig industry to overcome the challenges provided by hard-to-manage diseases as well as new environmental challenges associated with climate change.

DEAD/H-box helicases:Anti-viral and pro-viral roles during infections

DEAD/H-box RNA helicases make the prominent family of helicases super family-2 which take part in almost all RNA-related processes, from initiation of transcription to RNA decay pathways. In addition to these RNA-related activities, in recent years a certain number of these helicases are reported to play important roles in anti-viral immunity through various ways. Along with RLHs, endosomal TLRs, and cytosolic DNA receptors, many RNA helicases including DDX3, DHX9, DDX6, DDX41, DHX33, DDX60, DHX36 and DDX1-DDX21-DHX36 complex act as viral nucleic acid sensors or co-sensors. These helicases mostly follow RLHs-MAVS and STING mediated signaling cascades to trigger induction of type-I interferons and pro-inflammatory cytokines. Many of them also function as downstream adaptor molecules (DDX3), segments of stress and processing bodies (DDX3 and DDX6) or negative regulators (DDX19, DDX24, DDX25, DDX39A and DDX46). On the contrary, many studies indicated that several DEAD/H-box helicases such as DDX1, DDX3, DDX6, DDX24, and DHX9 could be exploited by viruses to evade innate immune responses, suggesting that these helicases seem to have a dual function as anti-viral innate immune mediators and viral replication cofactors. In this review, we summarized the current knowledge on several representative DEAD/H-box helicases, with an emphasis on their functions in innate immunity responses, involved in their anti-viral and pro-viral roles.

Potential of genomic technologies to improve disease resistance in molluscan aquaculture

Molluscan aquaculture is a major contributor to global seafood production, but is hampered by infectious disease outbreaks that can cause serious economic losses. Selective breeding has been widely used to improve disease resistance in major agricultural and aquaculture species, and has clear potential in molluscs, albeit its commercial application remains at a formative stage. Advances in genomic technologies, especially the development of cost-efficient genomic selection, have the potential to accelerate genetic improvement. However, tailored approaches are required owing to the distinctive reproductive and life cycle characteristics of molluscan species. Transgenesis and genome editing, in particular CRISPR/Cas systems, have been successfully trialled in molluscs and may further understanding and improvement of genetic resistance to disease through targeted changes to the host genome. Whole-organism genome editing is achievable on a much greater scale compared to other farmed species, making genome-wide CRISPR screening approaches plausible. This review discusses the current state and future potential of selective breeding, genomic tools and genome editing approaches to understand and improve host resistance to infectious disease in molluscs. This article is part of the Theo Murphy meeting issue 'Molluscan genomics: broad insights and future directions for a neglected phylum'.

Genetic, social and maternal contributions to Mycobacterium bovis infection status in European badgers (Meles meles)

Within host populations, individuals can vary in their susceptibility to infections and in the severity and progression of disease once infected. Though mediated through differences in behaviour, resistance or tolerance, variation in disease outcomes ultimately stems from genetic and environmental (including social) factors. Despite obvious implications for the evolutionary, ecological and epidemiological dynamics of disease traits, the relative importance of these factors has rarely been quantified in naturally infected wild animal hosts. Here, we use a long-term capture-mark-recapture study of group-living European badgers (Meles meles) to characterize genetic and environmental sources of variation in host infection status by Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB). We find that genetic factors contribute to M. bovis infection status, whether measured over a lifetime or across repeated captures. In the latter case, the heritability (h² ) of infection status is close to zero in cubs and yearlings but increases in adulthood. Overall, environmental influences arising from a combination of social group membership (defined in time and space) and maternal effects appear to be more important than genetic factors. Thus, while genes do contribute to among-individual variation, they play a comparatively minor role, meaning that rapid evolution of host defences under parasite-mediated selection is unlikely (especially if selection is on young animals where h² is lowest). Conversely, our results lend further support to the view that social and early-life environments are important drivers of the dynamics of bTB infection in badger populations specifically, and of disease traits in wild hosts more generally.

A novel modelling approach to quantify the response of dairy goats to a high-concentrate diet

High-producing ruminants need high-concentrate diets to satisfy their nutrient requirements and meet performance objectives. However, such diets induce sub-acute ruminal acidosis (SARA), which will adversely affect dry matter intake and lead to lower production performance. This work develops a novel modelling approach to quantify the capacity of dairy goats to adapt to a high-concentrate diet challenge at the individual level. The animal model used was dairy goats (from Saanen or Alpine breed), and rumen pH was used as the indicator of the response. A three-step modelling procedure was developed to quantify daily scores and produce a single global index for animals' adaptive response to the new diet. The first step summarizes the post-prandial kinetics of rumen acid status using three synthetic variables. In the second step, the effect of time on the response of goats is described, in the short and long terms. In the last step, a metric based on phase trajectories ranks goats for their resilience capacity. This modelling procedure showed a high variability among the goats in response to the new diet, highlighting in particular their daily and general strategies to buffer the effect of the diet change. Two main categories of adaptive strategies were observed: (i) acid status increased, but the goats tried to minimize its variations, and (ii) acid status oscillated between increases and decreases. Such phenotyping, alongside other behavioral, digestive, and metabolic measures, can help to determine biomarkers of goats' capacity to adapt to diets of higher nutritive value and to increase production performance without compromising their health status. Quantifying the capacity of goats to buffer the effect of highly fermentable diets helps to better adapt feed to animals in precision livestock farming. This procedure is generic and can be adapted to any indicator of animal health and performance. In particular, several indicators can be combined to assess multi-performance, which is of major interest in the context of selection for robust animals.

Why breed disease-resilient livestock, and how?

BACKGROUND

Fighting and controlling epidemic and endemic diseases represents a considerable cost to livestock production. Much research is dedicated to breeding disease resilient livestock, but this is not yet a common objective in practical breeding programs. In this paper, we investigate how future breeding programs may benefit from recent research on disease resilience.

MAIN BODY

We define disease resilience in terms of its component traits resistance (R: the ability of a host animal to limit within-host pathogen load (PL)) and tolerance (T: the ability of an infected host to limit the damage caused by a given PL), and model the host's production performance as a reaction norm on PL, depending on R and T. Based on this, we derive equations for the economic values of resilience and its component traits. A case study on porcine respiratory and reproductive syndrome (PRRS) in pigs illustrates that the economic value of increasing production in infectious conditions through selection for R and T can be more than three times higher than by selection for production in disease-free conditions. Although this reaction norm model of resilience is helpful for quantifying its relationship to its component traits, its parameters are difficult and expensive to quantify. We consider the consequences of ignoring R and T in breeding programs that measure resilience as production in infectious conditions with unknown PL-particularly, the risk that the genetic correlation between R and T is unfavourable (antagonistic) and that a trade-off between them neutralizes the resilience improvement. We describe four approaches to avoid such antagonisms: (1) by producing sufficient PL records to estimate this correlation and check for antagonisms-if found, continue routine PL recording, and if not found, shift to cheaper proxies for PL; (2) by selection on quantitative trait loci (QTL) known to influence both R and T in favourable ways; (3) by rapidly modifying towards near-complete resistance or tolerance, (4) by re-defining resilience as the animal's capacity to resist (or recover from) the perturbation caused by an infection, measured as temporal deviations of production traits in within-host longitudinal data series.

CONCLUSIONS

All four alternatives offer promising options for genetic improvement of disease resilience, and most rely on technological and methodological developments and innovation in automated data generation.

Transmissible Cancers in an Evolutionary Perspective

Inter-individual transmission of cancer cells represents an intriguing and unexplored host-pathogen system, with significant ecological and evolutionary ramifications. The pathogen consists of clonal malignant cell lines that spread horizontally as allografts and/or xenografts. Although only nine transmissible cancer lineages in eight host species from both terrestrial and marine environments have been investigated, they exhibit evolutionary dynamics that may provide novel insights into tumor-host interactions particularly in the formation of metastases. Here we present an overview of known transmissible cancers, discuss the necessary and sufficient conditions for cancer transmission, and provide a comprehensive review on the evolutionary dynamics between transmissible cancers and their hosts.

The evolution of resistance and tolerance as cancer defences

Although there is a plethora of cancer associated-factors that can ultimately culminate in death (cachexia, organ impairment, metastases, opportunistic infections, etc.), the focal element of every terminal malignancy is the failure of our natural defences to control unlimited cell proliferation. The reasons why our defences apparently lack efficiency is a complex question, potentially indicating that, under Darwinian terms, solutions other than preventing cancer progression are also important contributors. In analogy with host-parasite systems, we propose to call this latter option ‘tolerance’ to cancer. Here, we argue that the ubiquity of oncogenic processes among metazoans is at least partially attributable to both the limitations of resistance mechanisms and to the evolution of tolerance to cancer. Deciphering the ecological contexts of alternative responses to the cancer burden is not a semantic question, but rather a focal point in understanding the evolutionary ecology of host-tumour relationships, the evolution of our defences, as well as why and when certain cancers are likely to be detrimental for survival.

How Individual Variation in Host Tolerance Affects Competence to Transmit Parasites

Tolerance, or the maintenance of host health or fitness at a given parasite burden, has often been studied in evolutionary and medical contexts, particularly with respect to effects on the evolution of parasite virulence and individual patient outcomes. These bodies of work have provided insight about tolerance for evolutionary phenomena (e.g., virulence) and individual health (e.g., recovering from an infection). However, due to the specific motivations of that work, few studies have considered the ecological ramifications of variation in tolerance, namely, how variation in forms of tolerance could mediate parasite movement through populations and even community-level disease dynamics. Tolerance is most commonly regarded as the relationship between host fitness and parasite burden. However, few if any studies have actually quantified host fitness, instead utilizing proxies of fitness as the response variables to be regressed against parasite burden. Here, we address how attention to the effects of parasite burden on traits that are relevant to host competence (i.e., the ability to amplify parasites to levels transmissible to other hosts/vectors) will enhance our understanding of disease dynamics in nature. We also provide several forms of guidance for how to overcome the challenges of quantifying tolerance in wild organisms.

Novel Resilience Phenotypes Using Feed Intake Data From a Natural Disease Challenge Model in Wean-to-Finish Pigs

The objective of this study was to extract novel phenotypes related to disease resilience using daily feed intake data from growing pigs under a multifactorial natural disease challenge that was designed to mimic a commercial environment with high disease pressure to maximize expression of resilience. Data used were the first 1,341 crossbred wean-to-finish pigs from a research facility in Québec, Canada. The natural challenge was established under careful veterinary oversight by seeding the facility with diseased pigs from local health-challenged farms, targeting various viral and bacterial diseases, and maintaining disease pressure by entering batches of 60–75 pigs in a continuous flow system. Feed intake (FI) is sensitive to disease, as pigs tend to eat less when they become ill. Four phenotypes were extracted from the individual daily FI data during finishing as novel measures of resilience. The first two were daily variability in FI or FI duration, quantified by the root mean square error (RMSE) from the within individual regressions of FI or duration at the feeder (DUR) on age (RMSE_FI and RMSE_DUR). The other two were the proportion of off-feed days, classified based on negative residuals from a 5% quantile regression (QR) of daily feed intake or duration data on age across all pigs (QR_FI and QR_DUR). Mortality and treatment rate had a heritability of 0.13 (±0.05) and 0.29 (±0.07), respectively. Heritability estimates for RMSE_FI, RMSE_DUR, QR_FI, and QR_DUR were 0.21 (±0.07) 0.26 (±0.07), 0.15 (±0.06), and 0.23 (±0.07), respectively. Genetic correlations of RMSE and QR measures with mortality and treatment rate ranged from 0.37 to 0.85, with QR measures having stronger correlations with both. Estimates of genetic correlations of RMSE measures with production traits were typically low, but often favorable (e.g., −0.31 between RMSE_FI and finishing ADG). Although disease resilience was our target, fluctuations in FI and duration can be caused by many factors other than disease and should be viewed as overall indicators of general resilience to a variety of stressors. In conclusion, daily variation in FI or duration at the feeder can be used as heritable measures of resilience.

Harnessing longitudinal information to identify genetic variation in tolerance of pigs to Porcine Reproductive and Respiratory Syndrome virus infection

BACKGROUND

High resistance (the ability of the host to reduce pathogen load) and tolerance (the ability to maintain high performance at a given pathogen load) are two desirable host traits for producing animals that are resilient to infections. For Porcine Reproductive and Respiratory Syndrome (PRRS), one of the most devastating swine diseases worldwide, studies have identified substantial genetic variation in resistance of pigs, but evidence for genetic variation in tolerance has so far been inconclusive. Resistance and tolerance are usually considered as static traits. In this study, we used longitudinal viremia measurements of PRRS virus infected pigs to define discrete stages of infection based on viremia profile characteristics. These were used to investigate host genetic effects on viral load (VL) and growth at different stages of infection, to quantify genetic variation in tolerance at these stages and throughout the entire 42-day observation period, and to assess whether the single nucleotide polymorphism (SNP) WUR10000125 (WUR) with known large effects on resistance confers significant differences in tolerance.

RESULTS

Genetic correlations between resistance and growth changed considerably over time. Individuals that expressed high genetic resistance early in infection tended to grow slower during that time-period, but were more likely to experience lower VL and recovery in growth by the later stage. The WUR genotype was most strongly associated with VL at early- to mid-stages of infection, and with growth at mid- to late-stages of infection. Both, single-stage and repeated measurements random regression models identified significant genetic variation in tolerance. The WUR SNP was significantly associated only with the overall tolerance slope fitted through all stages of infection, with the genetically more resistant AB pigs for the WUR SNP being also more tolerant to PRRS.

CONCLUSIONS

The results suggest that genetic selection for improved tolerance of pigs to PRRS is possible in principle, but may be feasible only with genomic selection, requiring intense recording schemes that involve repeated measurements to reliably estimate genetic effects. In the absence of such records, consideration of the WUR genotype in current selection schemes appears to be a promising strategy to improve simultaneously resistance and tolerance of growing pigs to PRRS.

Inbreeding shapes tuberculosis progression in female adult badgers (Meles meles)

In Focus: Beton, C. H., Delahay, R. J., Smith, F. A. P., Robertson, A., McDonald, R. A., Young, A. J., Burke T. A., & Hodgson, D. (2018). Inbreeding intensifies sex- and age-dependent disease in a wild mammal. Journal of Animal Ecology, 87, 1497-1499. https://doi.org/10.1111/1365-2656.12878 Increasing crossbreeding of relatives promotes inbreeding which, in turn, can cause a reduction in fitness and the emergence of a phenomenon known as inbreeding depression. Benton et al., used the badger (Meles meles)-Mycobacterium bovis model system to study the relationship between inbreeding, disease, ageing and sex. A link between multilocus homozygosity (general effect) and TB progression (measured as antibody response to infection) and between homozygosity at specific loci (local effect) and TB progression were established in this study, highlighting the importance of host genetic background in determining host disease outcomes, and thus on shaping disease dynamics in wild populations. Moreover, the authors demonstrated for the first time in a natural population that this positive association might be modulated by sex and age. In infected individuals, inbreeding only affects disease progression in adult females.

Predicting position along a looping immune response trajectory

When we get sick, we want to be resilient and recover our original health. To measure resilience, we need to quantify a host's position along its disease trajectory. Here we present Looper, a computational method to analyze longitudinally gathered datasets and identify gene pairs that form looping trajectories when plotted in the space described by these phases. These loops enable us to track where patients lie on a typical trajectory back to health. We analyzed two publicly available, longitudinal human microarray datasets that describe self-resolving immune responses. Looper identified looping gene pairs expressed by human donor monocytes stimulated by immune elicitors, and in YF17D-vaccinated individuals. Using loops derived from training data, we found that we could predict the time of perturbation in withheld test samples with accuracies of 94% in the human monocyte data, and 65-83% within the same cohort and in two independent cohorts of YF17D vaccinated individuals. We suggest that Looper will be useful in building maps of resilient immune processes across organisms.

Does selection for growth rate in broilers affect their resistance and tolerance to Eimeria maxima?

Chickens exhibit varied responses to infection with Eimeria parasites. We hypothesise that broilers selected for increased growth rate will show lower resistance and tolerance to a coccidian challenge. 288 chickens of fast (F) or slow (S) growing lines were inoculated with 0 (control), 2500 (low-dose), or 7000 (high-dose) sporulated E. maxima oocysts at 13 days of age in two consecutive rounds. Gain and Intake were measured daily and their values relative to BW at the point of infection were calculated over the pre-patent (days 1-4 post-infection), acute (d5-8 pi), and recovery (d9-12 pi) phases of infection to assess the impact of infection. Levels of plasma carotenoids, vitamins E and A, long bone mineralisation, caecal microbiota diversity indices, and histological measurements were assessed at the acute (d6 pi) and recovery stage (d13 pi). In addition, we measured the levels of nitric oxide metabolites and the number of parasite genome copies in the jejunumat d6pi. In absolute terms F birds grew 1.42 times faster than S birds when not infected. Infection significantly reduced relative daily gain and intake (P < 0.001), with the effects being most pronounced during the acute phase (P < 0.001). Levels of all metabolites were significantly decreased, apart from NO which increased (P < 0.001) in response to infection on d6pi, and were accompanied by changes in histomorphometric features and the presence of E. maxima genome copies in infected birds, which persisted to d13pi. Furthermore, infection reduced tibia and femur mineralisation, which also persisted to d13pi. Reductions in measured variables were mostly independent of dose size, as was the level of parasite replication. The impact of infection was similar for S and F-line birds for all measured parameters, and there were no significant interactions between line x dose size on any of these parameters. In conclusion, our results suggest that line differences in productive performance do not influence host responses to coccidiosis when offered nutrient adequate diets.

Tolerance to bovine clinical mastitis: Total, direct, and indirect milk losses

The objectives of this paper were to estimate direct and indirect milk losses associated with mastitis. Indirect losses, linked to indirect tolerance, are mediated by the increase in milk somatic cell count (SCC) in response to bacterial infection. Direct losses, linked to weak direct tolerance, are not mediated by the increase in SCC. So far, studies have evaluated milk loss associated with clinical mastitis without considering both components, which may lead to biased estimates of their sum; that is, the total loss in milk. A total of 43,903 test-day records on milk and SCC from 3,716 cows and 5,858 lactations were analyzed with mediation mixed models and health trajectories to estimate the amount of direct, indirect, and total milk losses after adjustment for known and potentially unmeasured (sensitivity analyses) confounding factors. Estimates were formalized under the counterfactual causal theory of causation. In this study, milk losses were mostly mediated by an increase in SCC. They were highest in the first month of lactation, when SCC were highest. Milk losses were estimated at 0.5, 0.8, and 1.1 kg/d in first, second, and third and greater parity, respectively. Two phases described how changes in milk were associated with changes in SCC: on average, one occurred before and one after the day preceding the clinical diagnosis. In both phases, changes in milk were estimated at 1 mg/d per 10³ cells/mL. After adjusting for known confounders, cow effect accounted for 20.7 and 64.2% of the variation in milk in the first and second phases, respectively. This suggests that deviations from the resilient path were highest during the second phase of inflammation and that selection for cows more tolerant to mastitis is feasible. As discussed herein, epigenetic regulation of macrophage polarization may contribute to the variation in milk observed in the second phase.

Contrasting consequences of different defence strategies in a natural multihost-parasite system

Hosts counteract infections using two distinct defence strategies, resistance (reduction in pathogen fitness) and tolerance (limitation of infection damage). These strategies have been minimally investigated in multi-host systems, where they may vary across host species, entailing consequences both for hosts (virulence) and parasites (transmission). Comprehending the interplay among resistance, tolerance, virulence and parasite success is highly relevant for our understanding of the ecology and evolution of infectious and parasitic diseases. Our work investigated the interaction between an insect parasite and its most common bird host species, focusing on two relevant questions: (i) are defence strategies different between main and alternative hosts and, (ii) what are the consequences (virulence and parasite success) of different defence strategies? We conducted a matched field experiment and longitudinal studies at the host and the parasite levels under natural conditions, using a system comprising Philornis torquans flies and three bird hosts - the main host and two of the most frequently used alternative hosts. We found that main and alternative hosts have contrasting defence strategies, which gave rise in turn to contrasting virulence and parasite success. In the main bird host, minor loss of fitness, no detectable immune response, and high parasite success suggest a strategy of high tolerance and negligible resistance. Alternative hosts, on the contrary, resisted by mounting inflammatory responses, although with very different efficiency, which resulted in highly dissimilar parasite success and virulence. These results show clearly distinct defence strategies between main and alternative hosts in a natural multi-host system. They also highlight the importance of defence strategies in determining virulence and infection dynamics, and hint that defence efficiency is a crucial intervening element in these processes.

The Role of the Environment in the Evolution of Tolerance and Resistance to a Pathogen

Defense against parasites can be divided into resistance, which limits parasite burden, and tolerance, which reduces pathogenesis at a given parasite burden. Distinguishing between the two and understanding which defense is favored by evolution in different ecological settings are important, as they lead to fundamentally different evolutionary trajectories of host-parasite interactions. We let the mosquito Aedes aegypti evolve under different food levels and with either no parasite, a constant parasite, or a coevolving parasite (the microsporidian Vavraia culicis). We then tested tolerance and resistance of the evolved lines on a population level at the two food levels. Exposure to parasites during evolution increased resistance and tolerance, but there were no differences between the lines evolved with coevolving or constant parasites. Mosquitoes that had evolved with food restriction had higher resistance than those evolved with high food but similar tolerance. The mosquitoes that had restricted food when being tested had lower tolerance than those with normal food, but there was no difference in resistance. Our results emphasize the complexity and dependence on environmental conditions of the evolution and expression of resistance and tolerance and help to evaluate some of the predictions about the evolution of host defense against parasites.

The Evolutionary Consequences of Stepwise Infection Processes

Molecular and cellular studies reveal that the resistance of hosts to parasites and pathogens is a cascade-like process with multiple steps required to be passed for successful infection. By contrast, much of evolutionary reasoning is based on strongly simplified, one- or two-step infection processes with simple genetics or on resistance being a quantitative trait. Here we attempt a conceptual unification of these two perspectives with the aim of cross-fostering research and filling some of the gaps in our concepts of the ecology and evolution of disease. This conceptual unification has a profound impact on the way we understand the genetics and evolution of host resistance, ecological immunity, evolution of virulence, defence portfolios, and host-pathogen coevolution.

Treatable traits and therapeutic targets: Goals for systems biology in infectious disease

Among the many medical applications of systems biology, we contend that infectious disease is one of the most important and tractable targets. We take the view that the complexity of the immune system is an inevitable consequence of its evolution, and this complexity has frustrated reductionist efforts to develop host-directed therapies for infection. However, since hosts vary widely in susceptibility and tolerance to infection, host-directed therapies are likely to be effective, by altering the biology of a susceptible host to induce a response more similar to a host who survives. Such therapies should exert minimal selection pressure on organisms, thus greatly decreasing the probability of pathogen resistance developing.

A systems medicine approach to infection has the potential to provide new solutions to old problems: to identify host traits that are potentially amenable to therapeutic intervention, and the host immune factors that could be targeted by host-directed therapies. Furthermore, undiscovered sub-groups with different responses to treatment are almost certain to exist among patients presenting with life-threatening infection, since this population is markedly clinically heterogeneous. A major driving force behind high-throughput clinical phenotyping studies is the aspiration that these subgroups, hitherto opaque to observation, may be observed in the data generated by new technologies. Subgroups of patients are unlikely to be static – serial clinical and biological phenotyping may reveal different trajectories through the pathophysiology of disease, in which different therapeutic approaches are required.

We suggest there are two major goals for systems biology in infection medicine: (1) to identify subgroups of patients that share treatable features; and, (2) to integrate high-throughput data from clinical and in vitro sources in order to predict tractable therapeutic targets with the potential to alter disease trajectories for individual patients.

•

High throughput technologies can reveal clinical patterns in infection that were previously opaque.

•

Host-targeted therapies have conceptual advantages but are difficult to develop.

•

Key clinically-relevant objectives are identification of disease endotypes and treatable traits.

•

Mechanistic understanding will reveal opportunities for drug design, repurposing and better targeting.

Use of multi-trait and random regression models to identify genetic variation in tolerance to porcine reproductive and respiratory syndrome virus

BACKGROUND

A host can adopt two response strategies to infection: resistance (reduce pathogen load) and tolerance (minimize impact of infection on performance). Both strategies may be under genetic control and could thus be targeted for genetic improvement. Although there is evidence that supports a genetic basis for resistance to porcine reproductive and respiratory syndrome (PRRS), it is not known whether pigs also differ genetically in tolerance. We determined to what extent pigs that have been shown to vary genetically in resistance to PRRS also exhibit genetic variation in tolerance. Multi-trait linear mixed models and random regression sire models were fitted to PRRS Host Genetics Consortium data from 1320 weaned pigs (offspring of 54 sires) that were experimentally infected with a virulent strain of PRRS virus to obtain genetic parameter estimates for resistance and tolerance. Resistance was defined as the inverse of within-host viral load (VL) from 0 to 21 (VL21) or 0 to 42 (VL42) days post-infection and tolerance as the slope of the reaction-norm of average daily gain (ADG21, ADG42) on VL21 or VL42.

RESULTS

Multi-trait analysis of ADG associated with either low or high VL was not indicative of genetic variation in tolerance. Similarly, random regression models for ADG21 and ADG42 with a tolerance slope fitted for each sire did not result in a better fit to the data than a model without genetic variation in tolerance. However, the distribution of data around average VL suggested possible confounding between level and slope estimates of the regression lines. Augmenting the data with simulated growth rates of non-infected half-sibs (ADG0) helped resolve this statistical confounding and indicated that genetic variation in tolerance to PRRS may exist if genetic correlations between ADG0 and ADG21 or ADG42 are low to moderate.

CONCLUSIONS

Evidence for genetic variation in tolerance of pigs to PRRS was weak when based on data from infected piglets only. However, simulations indicated that genetic variance in tolerance may exist and could be detected if comparable data on uninfected relatives were available. In conclusion, of the two defense strategies, genetics of tolerance is more difficult to elucidate than genetics of resistance.

EMA and EFSA Joint Scientific Opinion on measures to reduce the need to use antimicrobial agents in animal husbandry in the European Union, and the resulting impacts on food safety (RONAFA)

EFSA and EMA have jointly reviewed measures taken in the EU to reduce the need for and use of antimicrobials in food-producing animals, and the resultant impacts on antimicrobial resistance (AMR). Reduction strategies have been implemented successfully in some Member States. Such strategies include national reduction targets, benchmarking of antimicrobial use, controls on prescribing and restrictions on use of specific critically important antimicrobials, together with improvements to animal husbandry and disease prevention and control measures. Due to the multiplicity of factors contributing to AMR, the impact of any single measure is difficult to quantify, although there is evidence of an association between reduction in antimicrobial use and reduced AMR. To minimise antimicrobial use, a multifaceted integrated approach should be implemented, adapted to local circumstances. Recommended options (non-prioritised) include: development of national strategies; harmonised systems for monitoring antimicrobial use and AMR development; establishing national targets for antimicrobial use reduction; use of on-farm health plans; increasing the responsibility of veterinarians for antimicrobial prescribing; training, education and raising public awareness; increasing the availability of rapid and reliable diagnostics; improving husbandry and management procedures for disease prevention and control; rethinking livestock production systems to reduce inherent disease risk. A limited number of studies provide robust evidence of alternatives to antimicrobials that positively influence health parameters. Possible alternatives include probiotics and prebiotics, competitive exclusion, bacteriophages, immunomodulators, organic acids and teat sealants. Development of a legislative framework that permits the use of specific products as alternatives should be considered. Further research to evaluate the potential of alternative farming systems on reducing AMR is also recommended. Animals suffering from bacterial infections should only be treated with antimicrobials based on veterinary diagnosis and prescription. Options should be reviewed to phase out most preventive use of antimicrobials and to reduce and refine metaphylaxis by applying recognised alternative measures.

Maximising fitness in the face of parasites: a review of host tolerance

Tolerance, the ability of a host to limit the negative fitness effects of a given parasite load, is now recognised as an important host defence strategy in animals. Together with resistance, the ability of a host to limit parasite load, these two host strategies represent two disparate host responses to parasites, each with different predicted evolutionary consequences: resistance is predicted to reduce parasite prevalence, whereas tolerance could be neutral towards, or increase, parasite prevalence in a population. The distinction between these two strategies might have far-reaching epidemiological consequences. Classically, a reaction norm defines host tolerance because it depicts the change in host fitness as a function of parasite load, where a shallow negative slope indicates that host fitness slowly deteriorates as parasite load increases (i.e., high tolerance). Despite the fact that tolerance was only recently acknowledged to be an important component in an animal's immune repertoire, it is frequently referenced, so our aim is to emphasise the current advances on the topic. We begin by summarising the ways in which biologists measure the two components of tolerance, parasite load and fitness, as well as the ways in which the concept has been defined (i.e., point and range tolerance). It is common to test for variation in host tolerance according to intrinsic, innate factors, where variation exists among populations, genders or genotypes. Such variation in tolerance is pervasive across animal taxa, and we briefly review some of the mechanistic bases of variation that have recently begun to be explored. Three further novel advancements in the tolerance field are the appreciation of the role of extrinsic, environmental factors on tolerance, host tolerance in multi-host-parasite systems and individual-based approaches to tolerance measures. We explore these topics using recent examples and suggest some future perspectives. It is becoming increasingly clear that an appreciation of tolerance as a defence strategy can provide significant insights into how hosts coexist with parasites.

The effect of diet and time after bacterial infection on fecundity, resistance, and tolerance in Drosophila melanogaster

Mounting and maintaining an effective immune response in the face of infection can be costly. The outcome of infection depends on two host immune strategies: resistance and tolerance. Resistance limits pathogen load, while tolerance reduces the fitness impact of an infection. While resistance strategies are well studied, tolerance has received less attention, but is now considered to play a vital role in host–pathogen interactions in animals. A major challenge in ecoimmunology is to understand how some hosts maintain their fitness when infected while others succumb to infection, as well as how extrinsic, environmental factors, such as diet, affect defense. We tested whether dietary restriction through yeast (protein) limitation affects resistance, tolerance, and fecundity in Drosophila melanogaster. We predicted that protein restriction would reveal costs of infection. Because infectious diseases are not always lethal, we tested resistance and tolerance using two bacteria with low lethality: Escherichia coli and Lactococcus lactis. We then assayed fecundity and characterized bacterial infection pathology in individual flies at two acute phase time points after infection. As expected, our four fecundity measures all showed a negative effect of a low‐protein diet, but contrary to predictions, diet did not affect resistance to either bacteria species. We found evidence for diet‐induced and time‐dependent variation in host tolerance to E. coli, but not to L. lactis. Furthermore, the two bacteria species exhibited remarkably different infection profiles, and persisted within the flies for at least 7 days postinfection. Our results show that acute phase infections do not necessarily lead to fecundity costs despite high bacterial loads. The influence of intrinsic variables such as genotype are the prevailing factors that have been studied in relation to variation in host tolerance, but here we show that extrinsic factors should also be considered for their role in influencing tolerance strategies.

Beyond killing: Can we find new ways to manage infection?

The antibiotic pipeline is running dry and infectious disease remains a major threat to public health. An efficient strategy to stay ahead of rapidly adapting pathogens should include approaches that replace, complement or enhance the effect of both current and novel antimicrobial compounds. In recent years, a number of innovative approaches to manage disease without the aid of traditional antibiotics and without eliminating the pathogens directly have emerged. These include disabling pathogen virulence-factors, increasing host tissue damage control or altering the microbiota to provide colonization resistance, immune resistance or disease tolerance against pathogens. We discuss the therapeutic potential of these approaches and examine their possible consequences for pathogen evolution. To guarantee a longer half-life of these alternatives to directly killing pathogens, and to gain a full understanding of their population-level consequences, we encourage future work to incorporate evolutionary perspectives into the development of these treatments.