Social animal models for quantifying plasticity, assortment, and selection on interacting phenotypes.
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ABSTRACT:
SUBMITTER: Martin JS
PROVIDER: S-EPMC9292565 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Organisms express phenotypic plasticity during social interactions. Interacting phenotype theory has explored the consequences of social plasticity for evolution, but it is unclear how this theory applies to complex social structures. We adapt interacting phenotype models to general social structures to explore how the number of social connections between individuals and preference for phenotypically similar social partners affect phenotypic variation and evolution. We derive an analytical model that ignores phenotypic feedback and use simulations to test the predictions of this model. We find that adapting previous models to more general social structures does not alter their general conclusions but generates insights into the effect of social plasticity and social structure on the maintenance of phenotypic variation and evolution. Contribution of indirect genetic effects to phenotypic variance is highest when interactions occur at intermediate densities and decrease at higher densities, when individuals approach interacting with all group members, homogenizing the social environment across individuals. However, evolutionary response to selection tends to increase at greater network densities as the effects of an individual's genes are amplified through increasing effects on other group members. Preferential associations among similar individuals (homophily) increase both phenotypic variance within groups and evolutionary response to selection. Our results represent a first step in relating social network structure to the expression of social plasticity and evolutionary responses to selection.
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Project description:Tinnitus is a phantom auditory sensation experienced by up to 14% of the United States population with a smaller percentage experiencing decreased quality of life. A compelling hypothesis is that tinnitus results from a maladaptive plastic net down-regulation of inhibitory amino acid neurotransmission in the central auditory pathway. This loss of inhibition may be a compensatory response to loss of afferent input such as that caused by acoustic insult and/or age-related hearing loss, the most common causes of tinnitus in people. Compensatory plastic changes may result in pathologic neural activity that underpins tinnitus. The neural correlates include increased spontaneous spiking, increased bursting and decreased variance of inter-spike intervals. This review will examine evidence for chronic plastic neuropathic changes in the central auditory system of animals with psychophysically-defined tinnitus. Neurochemical studies will focus on plastic tinnitus-related changes of inhibitory glycinergic neurotransmission in the adult dorsal cochlear nucleus (DCN). Electrophysiological studies will focus on functional changes in the DCN and inferior colliculus (IC). Tinnitus was associated with increased spontaneous activity and altered response properties of fusiform cells, the major output neurons of DCN. Coincident with these physiologic alterations were changes in glycine receptor (GlyR) subunit composition, its anchoring/trafficking protein, gephyrin and the number and affinity of membrane GlyRs revealed by receptor binding. In the IC, the primary afferent target of DCN fusiform cells, multi-dimensional alterations in unit-spontaneous activity (rate, burst rate, bursting pattern) were found in animals with behavioral evidence of chronic tinnitus more than 9 months following the acoustic/cochlear insult. In contrast, immediately following an intense sound exposure, acute alterations in IC spontaneous activity resembled chronic tinnitus-related changes but were not identical. This suggests that long-term neuroplastic changes responsible for chronic tinnitus are likely to be responsible for its persistence. A clear understanding of tinnitus-related plasticity in the central auditory system and its associated neurochemistry may help define unique targets for therapeutic drug development.
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Project description:Patterns of dispersal behavior are often driven by the composition and configuration of suitable habitat in a matrix of unsuitable habitat. Interactions between animal behavior and landscapes can therefore influence population dynamics, population and species distributions, population genetic structure, and the evolution of behavior. Spatially explicit individual-based models (IBMs) are ideal tools for exploring the effects of landscape structure on dispersal. We developed an empirically parameterized IBM in the modeling framework SEARCH to simulate dispersal of translocated American martens in Wisconsin. We tested the hypothesis that a time-limited disperser should be willing to settle in lower quality habitat over time. To evaluate model performance, we used a pattern-oriented modeling approach. Our best model matched all empirical dispersal patterns (e.g., dispersal distance) except time to settlement. This model incorporated a required search phase as well as the mechanism for declining habitat selectivity over time, which represents the first demonstration of this hypothesis for a vertebrate species. We suggest that temporal plasticity in habitat selectivity allows individuals to maximize fitness by making a tradeoff between habitat quality and risk of mortality. Our IBM is pragmatic in that it addresses a management need for a species of conservation concern. However, our model is also paradigmatic in that we explicitly tested a theory of dispersal behavior. Linking these 2 approaches to ecological modeling can further the utility of individual-based modeling and provide direction for future theoretical and empirical work on animal behavior.
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Project description:Analyzing social behaviors is critical for many fields, including neuroscience, psychology, and ecology. While computational tools have been developed to analyze videos containing animals engaging in limited social interactions under specific experimental conditions, automated identification of the social roles of freely moving individuals in a multi-animal group remains unresolved. Here we describe a deep-learning-based system - named LabGym2 - for identifying and quantifying social roles in multi-animal groups. This system uses a subject-aware approach: it evaluates the behavioral state of every individual in a group of two or more animals while factoring in its social and environmental surroundings. We demonstrate the performance of subject-aware deep-learning in different species and assays, from partner preference in freely-moving insects to primate social interactions in the field. Our subject-aware deep learning approach provides a controllable, interpretable, and efficient framework to enable new experimental paradigms and systematic evaluation of interactive behavior in individuals identified within a group.
| S-EPMC11257443 | biostudies-literature
Project description:Over the last decade the important concept has emerged that microglia, similar to other tissue macrophages, assume different phenotypes and serve several effector functions, generating the theory that activated microglia can be organized by their pro-inflammatory or anti-inflammatory and repairing functions. Importantly, microglia exist in a heterogenous population and their phenotypes are not permanently polarized into two categories; they exist along a continuum where they acquire different profiles based on their local environment. In Parkinson's disease (PD), neuroinflammation and microglia activation are considered neuropathological hallmarks, however their precise role in relation to disease progression is not clear, yet represent a critical challenge in the search of disease-modifying strategies. This review will critically address current knowledge on the activation states of microglia as well as microglial phenotypes found in PD and in animal models of PD, focusing on the expression of surface molecules as well as pro-inflammatory and anti-inflammatory cytokine production during the disease process. While human studies have reported an elevation of both pro- or anti-inflammatory markers in the serum and CSF of PD patients, animal models have provided insights on dynamic changes of microglia phenotypes in relation to disease progression especially prior to the development of motor deficits. We also review recent evidence of malfunction at multiple steps of NF?B signaling that may have a causal interrelationship with pathological microglia activation in animal models of PD. Finally, we discuss the immune-modifying strategies that have been explored regarding mechanisms of chronic microglial activation.
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Project description:Null models are an important component of the social network analysis toolbox. However, their use in hypothesis testing is still not widespread. Furthermore, several different approaches for constructing null models exist, each with their relative strengths and weaknesses, and often testing different hypotheses.In this study, I highlight why null models are important for robust hypothesis testing in studies of animal social networks. Using simulated data containing a known observation bias, I test how different statistical tests and null models perform if such a bias was unknown.I show that permutations of the raw observational (or 'pre-network') data consistently account for underlying structure in the generated social network, and thus can reduce both type I and type II error rates. However, permutations of pre-network data remain relatively uncommon in animal social network analysis because they are challenging to implement for certain data types, particularly those from focal follows and GPS tracking.I explain simple routines that can easily be implemented across different types of data, and supply R code that applies each type of null model to the same simulated dataset. The R code can easily be modified to test hypotheses with empirical data. Widespread use of pre-network data permutation methods will benefit researchers by facilitating robust hypothesis testing.
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Project description:Epilepsy is a common chronic neurological disease affecting almost 3 million people in the United States and 50 million people worldwide. Despite availability of more than two dozen FDA-approved anti-epileptic drugs (AEDs), one-third of patients fail to receive adequate seizure control. Specifically, pediatric genetic epilepsies are often the most severe, debilitating and pharmaco-resistant forms of epilepsy. Epileptic syndromes share a common symptom of unprovoked seizures. While some epilepsies/forms of epilepsy are the result of acquired insults such as head trauma, febrile seizure, or viral infection, others have a genetic basis. The discovery of epilepsy associated genes suggests varied underlying pathologies and opens the door for development of new "personalized" treatment options for each genetic epilepsy. Among these, Dravet syndrome (DS) has received substantial attention for both the pre-clinical and early clinical development of novel therapeutics. Despite these advances, there is no FDA-approved treatment for DS. Over 80% of patients diagnosed with DS carry a de novo mutation within the voltage-gated sodium channel gene SCN1A and these patients suffer with drug resistant and life-threatening seizures. Here we will review the preclinical animal models for DS featuring inactivation of SCN1A (including zebrafish and mice) with an emphasis on seizure phenotypes and behavioral comorbidities. Because many drugs fail somewhere between initial preclinical discovery and clinical trials, it is equally important that we understand how these models respond to known AEDs. As such, we will also review the available literature and recent drug screening efforts using these models with a focus on assay protocols and predictive pharmacological profiles. Validation of these preclinical models is a critical step in our efforts to efficiently discover new therapies for these patients. The behavioral and electrophysiological drug screening assays in zebrafish will be discussed in detail including specific examples from our laboratory using a zebrafish scn1 mutant and a summary of the nearly 3000 drugs screened to date. As the discovery and development phase rapidly moves from the lab-to-the-clinic for DS, it is hoped that this preclinical strategy offers a platform for how to approach any genetic epilepsy.
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Project description:Developmental plasticity generates phenotypic variation, but how it contributes to evolutionary change is unclear. Phenotypes of individuals in caste-based (eusocial) societies are particularly sensitive to developmental processes, and the evolutionary origins of eusociality may be rooted in developmental plasticity of ancestral forms. We used an integrative genomics approach to evaluate the relationships among developmental plasticity, molecular evolution, and social behavior in a bee species (Megalopta genalis) that expresses flexible sociality, and thus provides a window into the factors that may have been important at the evolutionary origins of eusociality. We find that differences in social behavior are derived from genes that also regulate sex differentiation and metamorphosis. Positive selection on social traits is influenced by the function of these genes in development. We further identify evidence that social polyphenisms may become encoded in the genome via genetic changes in regulatory regions, specifically in transcription factor binding sites. Taken together, our results provide evidence that developmental plasticity provides the substrate for evolutionary novelty and shapes the selective landscape for molecular evolution in a major evolutionary innovation: Eusociality.
| S-EPMC7306772 | biostudies-literature
Project description:Animals often use social information about conspecifics in making decisions about cooperation and conflict. While the importance of kin selection in the evolution of intraspecific cooperation and conflict is widely acknowledged, few studies have examined how relatedness influences the evolution of social information use. Here we specifically examine how relatedness affects the evolution of a stylised form of social information use known as eavesdropping. Eavesdropping involves individuals escalating conflicts with rivals observed to have lost their last encounter and avoiding fights with those seen to have won. We use a game theoretical model to examine how relatedness affects the evolution of eavesdropping, both when strategies are discrete and when they are continuous or mixed. We show that relatedness influences the evolution of eavesdropping, such that information use peaks at intermediate relatedness. Our study highlights the importance of considering kin selection when exploring the evolution of complex forms of information use.
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Project description:BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental condition, which is characterized by clinical heterogeneity and high heritability. Core symptoms of ASD include deficits in social communication and interaction, as well as restricted, repetitive patterns of behavior, interests, or activities. Many genes have been identified that are associated with an increased risk for ASD. Proteins encoded by these ASD risk genes are often involved in processes related to fetal brain development, chromatin modification and regulation of gene expression in general, as well as the structural and functional integrity of synapses. Genes of the SH3 and multiple ankyrin repeat domains (SHANK) family encode crucial scaffolding proteins (SHANK1-3) of excitatory synapses and other macromolecular complexes. SHANK gene mutations are highly associated with ASD and more specifically the Phelan-McDermid syndrome (PMDS), which is caused by heterozygous 22q13.3-deletion resulting in SHANK3-haploinsufficiency, or by SHANK3 missense variants. SHANK3 deficiency and potential treatment options have been extensively studied in animal models, especially in mice, but also in rats and non-human primates. However, few of the proposed therapeutic strategies have translated into clinical practice yet.Main textThis review summarizes the literature concerning SHANK3-deficient animal models. In particular, the structural, behavioral, and neurological abnormalities are described and compared, providing a broad and comprehensive overview. Additionally, the underlying pathophysiologies and possible treatments that have been investigated in these models are discussed and evaluated with respect to their effect on ASD- or PMDS-associated phenotypes.ConclusionsAnimal models of SHANK3 deficiency generated by various genetic strategies, which determine the composition of the residual SHANK3-isoforms and affected cell types, show phenotypes resembling ASD and PMDS. The phenotypic heterogeneity across multiple models and studies resembles the variation of clinical severity in human ASD and PMDS patients. Multiple therapeutic strategies have been proposed and tested in animal models, which might lead to translational implications for human patients with ASD and/or PMDS. Future studies should explore the effects of new therapeutic approaches that target genetic haploinsufficiency, like CRISPR-mediated activation of promotors.
| S-EPMC8594088 | biostudies-literature