A range of innate and adaptive immunity genes are up-regulated in captivity and this is, in part, associated with a loss of seasonality. Fishes reared in captivity or taken from the wild showed similar, and extensively overlapping, biometric characteristics (Additional file 1: Fig. S1c, d).An initial overall confounder-adjusted MANOVA test for expression in 13 immunity genes revealed a highly.
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On the BASS GUITAR NOTES SECTION you can click on the strings and frets of the Electric Bass to see the corresponding note on the staff, its name and its pitch. Bass Guitar Notes PRO v1.0.10 [Paid] APK Free Download Latest version for Android. Download full APK of Bass Guitar Notes PRO v1.0.10 [Paid].
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Overview: On the BASS GUITAR NOTES SECTION you can click on the strings and frets of the Electric Bass to see the corresponding note on the staff, its name and its pitch.
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BackgroundThe effect of anthropogenic environments on the function of the vertebrate immune system is a problem of general importance. For example, it relates to the increasing rates of immunologically-based disease in modern human populations and to the desirability of identifying optimal immune function in domesticated animals. Despite this importance, our present understanding is compromised by a deficit of experimental studies that make adequately matched comparisons between wild and captive vertebrates. ResultsWe transferred post-larval fishes (three-spined sticklebacks), collected in the wild, to an anthropogenic (captive) environment.
We then monitored, over 11 months, how the systemic expression of immunity genes changed in comparison to cohort-matched wild individuals in the originator population (total n = 299). We found that a range of innate ( lyz, defbl2, il1r-like, tbk1) and adaptive ( cd8a, igmh) immunity genes were up-regulated in captivity, accompanied by an increase in expression of the antioxidant enzyme, gpx4a. For some genes previously known to show seasonality in the wild, this appeared to be reduced in captive fishes. Captive fishes tended to express immunity genes, including igzh, foxp3b, lyz, defbl2, and il1r-like, more variably. Furthermore, although gene co-expression patterns (analyzed through gene-by-gene correlations and mutual information theory based networks) shared common structure in wild and captive fishes, there was also significant divergence.
For one gene in particular, defbl2, high expression was associated with adverse health outcomes in captive fishes. ConclusionTaken together, these results demonstrate widespread regulatory changes in the immune system in captive populations, and that the expression of immunity genes is more constrained in the wild. An increase in constitutive systemic immune activity, such as we observed here, may alter the risk of immunopathology and contribute to variance in health in vertebrate populations exposed to anthropogenic environments. During the transition between natural and anthropogenic environments the vertebrate immune system faces combinations of conditions unlike those it evolved to deal with.
This is known to result in functional changes and what these changes are, and how and why they occur, is a key problem. There is a direct parallel to health in humans inhabiting relatively anthropogenic settings (for example, higher income countries), where an increasing burden of illness results from non-infectious diseases with inflammatory origins –. There is an equal relevance to domesticated animals or wild animals occupying urbanized habitats, where the immune system also functions (or malfunctions) under environmental conditions very different to those in nature.Despite this background, research comparing immune function in the wild to in artificial habitats is in its early stages. The main body of existing work, comparing wild rodents with laboratory counterparts, suggests increased immunological activation in wild animals , –, which may result from a greater exposure to infection in nature. Some responses to stimulation may be more intense and variably expressed in wild rodents , , whilst other responses may be attenuated. Although these results are of great interest, the laboratory rodent models used as the basis for comparison bring with them aspects that may be unrepresentative of the real-world problem.
Thus inbred mouse lines, unlike humans and domesticated animals, are genetically homogenous and even outbred stocks may show restricted genetic variability. Furthermore laboratory rodents are maintained under extremely benign and pathogen-free conditions, whereas humans and domesticated animals still encounter many infections and environmental insults, albeit that these are different to those occurring in nature. Moreover, the singular genealogies of laboratory rodents make them difficult to compare directly with wild counterparts, even leaving the effects of inbreeding aside. Thus most laboratory stocks and lines have been in captivity for very many generations and are thus distant from the originator population, if this is identifiable at all. And they will often have been generated through arbitrary crosses , , resulting in haplotypes unrepresentative of those seen in nature. Hence complex genetic influences confound any comparison made to wild animals, leading to a basic lack of experimental control and uncertainty in interpretation.In order to understand how loss of natural environment modifies the immune system it will be informative to study the immunophenotypic trajectory of wild animals newly acclimatized to anthropogenic conditions, with matched in situ controls in the wild ,.
Importantly, this allows effects due to plasticity and to loss of on-going natural selection in the wild to be studied, unconfounded by long term effects of selection and breeding patterns within the anthropogenic environment. Whilst the latter processes are important in animal domestication, they are a separate issue that is not considered here. Furthermore, it should be noted that selection within the anthropogenic environment is unlikely to explain recent upwards trends in human immunopathologies, given their historical context ,. These are more likely driven by relatively recent environmental changes, making the focus of the present study of particular relevance.To provide one case study of the type of acclimatization described above we focussed on the 3-spined stickleback ( Gasterosteus aculeatus), a species that is accessible and much-studied in the wild , that easily acclimates to captivity, and that has an annotated whole genome , facilitating post-genomic studies. In the same way that other teleosts, such as zebrafish and medaka, are increasingly used to study disease processes relevant to mammalian health , the 3-spined stickleback – because it contains all of the central elements of adaptive immunity - has a general comparative relevance for immunity in other vertebrates.We transplanted post-larval fishes from a natural habitat to replicated artificial mesocosm habitats and, following anthelmintic treatment of the transplanted individuals, synchronously monitored both wild and transplanted (captive) cohorts through time. This study design embodies a general scenario typical of anthropogenic environments: where parasite exposure is reduced through anthelmintic treatment and curtailment of transmission , where bacterial exposures are altered due to artificial diets and substrates , and where environmental stressors are different to in the wild due to plentiful food, altered density and social interaction, confined spatial ranges, absence of predation, and altered microclimate and chemical exposures. Our central aim here, though, is not necessarily to dissect the relative contributions of all these influences, but rather to generate a representative scenario and consider the immunological consequences and their health correlates.As immunological readouts from our experiment we consider changes in the expression of a representative panel of conserved vertebrate immunity genes in whole-fish mRNA pools.
In using this whole-organism measurement approach we kept in mind the wide dispersal of the teleost immune system in different tissues and aimed to achieve a holistic metric of immune activity – averaging across the entire immune system and all the tissues of the body. Such a metric is arguably more relevant to the general risk of systemic immunopathology, in comparison to a narrow, arbitrarily chosen focus on a single tissue or cell population within a tissue. Reductionist measurements of the latter type could be unrepresentative at the organism level (as so much is necessarily left unmeasured) and are in danger of reporting cellular trafficking between anatomical compartments, rather than overall levels of systemic activity.This is the first study that we know of to carry out a closely matched immunological comparison of wild and captive vertebrates (i.e., where the individuals are ontogenetically matched and the results not clouded by differing genealogical histories in the study groups). We use our measurements to ask how do individual immune expression profiles vary between the wild and captivity and do certain immune expression profiles in captivity lead to adverse individual health outcomes?
Data analysisOnly wild fishes from the same year class as the mesocosm fishes were included in analyses. Our analyzed dataset consisted of 299 fishes, 84 from the wild and 215 from the mesocosms. Of these, 4.6% overall (1 wild fish and 13 mesocosm fishes) had one or more missing measurements and thus are omitted from some or all analyses.
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An initial test of the hypothesis that habitat affected the expression of immunity genes was carried out using multivariate analysis of variance (MANOVA), with all immune gene expression variables as the responses, and with habitat, sex, Schistocephalus infection (present/absent) and time (month) as factors and body length, body condition and mean temperature in the 14 days before sampling as covariates. Inclusion of body length in the model allows for variation in immune expression due to age (for which body length is a substantial surrogate ) and general size, including the possibility of tissue allometry affecting whole fish measurements. Body condition was derived as the residuals from a quadratic regression of body weight on body length (and there were no linear associations of the weight residuals with sampling time in either habitat, suggesting that the use of the residuals as a condition index was not biased by ontogenetic stage). Following a significant result in the MANOVA, the effects of habitat on the expression of individual immunity genes, and also gpx4a, were considered using general linear models (LMs) of analogous structure to the MANOVA (and allowing variation in the set of explanatory terms used for each gene expression response; see next). Because temperature was partially confounded with habitat (Additional file: Fig. S1a), and did not affect many of the genes examined across the relatively large (2 °C) thermal manipulation in the mesocosms, the MANOVA described above may have been conservative in detecting habitat effects.
Thus for the LMs we only included a temperature covariate for those genes where we found a significant effect of temperature in the mesocosms. The effect of Schistocephalus infection and temperature within the mesocosm environment was tested in LMs containing factors for sex, Schistocephalus infection, time and temperature treatment (ambient/+ 2 °C) and covariates for body length and body condition. The association of individual gene expression variables with body condition (weight residuals, see above) in mesocosm fishes was also tested in LMs, in this case additionally containing factors for sex, Schistocephalus infection, time and temperature treatment. In all cases gene expression data were log 10 transformed before analysis by MANOVA or LM. Principal components analysis (PCA) was used to ordinate gene expression measurements from individual fishes in order to identify habitat-specific patterns of variation.
Differences in the overall variability of untransformed individual gene expression variables between the field and the mesocosms were tested using Levene’s test for equality of variances. MANOVA, LMs, PCA and Levene’s test were implemented in Minitab version 16.2.2.
For co-expression analyses we used gene expression residuals from LMs (with terms for sex, length, body condition and Schistocephalus infection) in order to adjust for confounding variation. We initially constructed Pearson correlation matrices from the residuals and tested for significant structure in individual matrices (null = an identity matrix) using a Steiger test , and for differences between matrices with a Jennrich test (using the R package psych).
We tested for similarity in structure between matrices with a Mantel test (using the R package ape). We also used the residuals to construct co-expression networks with the information-theory (mutual information, MI) based algorithm ARACNe2 (Algorithm for the construction of accurate cellular networks) , , which takes non-linear associations into account. For this analysis we set all genes as hubs and constructed networks using the adaptive partitioning algorithm, estimating the MI threshold by a pre-processing run. P threshold was set at 1 × 10 −7 and the data processing inequality at zero. Networks were bootstrapped (2000 resamples; significance cut-off for reported edges, P = 1.0 × 10 −6). Cytoscape 2.8 was employed to visualize the networks (using arbitrary force-directed layouts) and to calculate network intersections ( Network Analyzer plugin).
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