Integrating evolution into ecological modelling: accommodating phenotypic changes in agent based models.

PMCID: PMC3733718This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Evolutionary change is a characteristic of living organisms and forms one of the ways in which species adapt to changed conditions. However, most ecological models do not incorporate this ubiquitous phenomenon. We have developed a model that takes a 'phenotypic gambit' approach and focuses on changes in the frequency of phenotypes (which differ in timing of breeding and fecundity) within a population, using, as an example, seasonal breeding. Fitness per phenotype calculated as the individual's contribution to population growth on an annual basis coincide with the population dynamics per phenotype. Simplified model variants were explored to examine whether the complexity included in the model is justified. Outputs from the spatially implicit model underestimated the number of individuals across all phenotypes. When no phenotype transitions are included (i.e. offspring always inherit their parent's phenotype) numbers of all individuals are always underestimated. We conclude that by using a phenotypic gambit approach evolutionary dynamics can be incorporated into individual based models, and that all that is required is an understanding of the probability of offspring inheriting the parental phenotype

Large Differences in Publicly Visible Health Behaviours across Two Neighbourhoods of the Same City

Background: There are socioeconomic disparities in the likelihood of adopting unhealthy behaviours, and success at giving them up. This may be in part because people living in deprived areas are exposed to greater rates of unhealthy behaviour amongst those living around them. Conventional self-report surveys do not capture these differences in exposure, and more ethological methods are required in order to do so. Methodology/Principal Findings: We performed 12 hours of direct behavioural observation in the streets of two neighbourhoods of the same city which were similar in most regards, except that one was much more socioeconomically deprived than the other. There were large differences in the publicly visible health behaviours observed. In the deprived neighbourhood, we observed 266 more adults smoking (rate ratio 3.44), 53 more adults drinking alcohol (rate ratio not calculable), and 38 fewer adults running (rate ratio 0.23), than in the affluent neighbourhood. We used data from the Health Survey for England to calculate the differences we ought to expect to have seen given the individual-level socioeconomic characteristics of the residents. The observed disparities between the two neighbourhoods were considerably greater than this null model predicted. There were also different patterns of smoking in proximity to children in the two neighbourhoods. Conclusions/Significance: The differences in observed smoking, drinking alcohol, and physical activity between these tw

Mucosal Lipocalin 2 Has Pro-Inflammatory and Iron-Sequestering Effects in Response to Bacterial Enterobactin

Nasal colonization by both gram-positive and gram-negative pathogens induces expression of the innate immune protein lipocalin 2 (Lcn2). Lcn2 binds and sequesters the iron-scavenging siderophore enterobactin (Ent), preventing bacterial iron acquisition. In addition, Lcn2 bound to Ent induces release of IL-8 from cultured respiratory cells. As a countermeasure, pathogens of the Enterobacteriaceae family such as Klebsiella pneumoniae produce additional siderophores such as yersiniabactin (Ybt) and contain the iroA locus encoding an Ent glycosylase that prevents Lcn2 binding. Whereas the ability of Lcn2 to sequester iron is well described, the ability of Lcn2 to induce inflammation during infection is unknown. To study each potential effect of Lcn2 on colonization, we exploited K. pneumoniae mutants that are predicted to be susceptible to Lcn2-mediated iron sequestration (iroA ybtS mutant) or inflammation (iroA mutant), or to not interact with Lcn2 (entB mutant). During murine nasal colonization, the iroA ybtS double mutant was inhibited in an Lcn2-dependent manner, indicating that the iroA locus protects against Lcn2-mediated growth inhibition. Since the iroA single mutant was not inhibited, production of Ybt circumvents the iron sequestration effect of Lcn2 binding to Ent. However, colonization with the iroA mutant induced an increased influx of neutrophils compared to the entB mutant. This enhanced neutrophil response to Ent-producing K. pneumoniae was Lcn2-dependent. These findings suggest that Lcn2 has both pro-inflammatory and iron-sequestering effects along the respiratory mucosa in response to bacterial Ent. Therefore, Lcn2 may represent a novel mechanism of sensing microbial metabolism to modulate the host response appropriately

A Comparison of Different Approaches to Unravel the Latent Structure within Metabolic Syndrome

Background: Exploratory factor analysis is a commonly used statistical technique in metabolic syndrome research to uncover latent structure amongst metabolic variables. The application of factor analysis requires methodological decisions that reflect the hypothesis of the metabolic syndrome construct. These decisions often raise the complexity of the interpretation from the output. We propose two alternative techniques developed from cluster analysis which can achieve a clinically relevant structure, whilst maintaining intuitive advantages of clustering methodology. Methods: Two advanced techniques of clustering in the VARCLUS and matroid methods are discussed and implemented on a metabolic syndrome data set to analyze the structure of ten metabolic risk factors. The subjects were selected from the normative aging study based in Boston, Massachusetts. The sample included a total of 847 men aged between 21 and 81 years who provided complete data on selected risk factors during the period 1987 to 1991. Results: Four core components were identified by the clustering methods. These are labelled obesity, lipids, insulin resistance and blood pressure. The exploratory factor analysis with oblique rotation suggested an overlap of the loadings identified on the insulin resistance and obesity factors. The VARCLUS and matroid analyses separated these components and were able to demonstrate associations between individual risk factors. Conclusions: An oblique rotation can be selected to reflect the clinical concept of a single underlying syndrome, howeve

Ubiquitin-Specific Protease 4 Inhibits Mono-Ubiquitination of the Master Growth Factor Signaling Kinase PDK1

BACKGROUND: Phosphorylation by the phospho-inositide-dependent kinase 1 (PDK1) is essential for many growth factor-activated kinases and thus plays a critical role in various processes such as cell proliferation and metabolism. However, the mechanisms that control PDK1 have not been fully explored and this is of great importance as interfering with PDK1 signaling may be useful to treat diseases, including cancer and diabetes. METHODOLOGY/PRINCIPAL FINDINGS: In human cells, few mono-ubiquitinated proteins have been described but in all cases this post-translational modification has a key regulatory function. Unexpectedly, we find that PDK1 is mono-ubiquitinated in a variety of human cell lines, indicating that PDK1 ubiquitination is a common and regulated process. Ubiquitination occurs in the kinase domain of PDK1 yet is independent of its kinase activity. By screening a library of ubiquitin proteases, we further identify the Ubiquitin-Specific Protease 4 (USP4) as an enzyme that removes ubiquitin from PDK1 in vivo and in vitro and co-localizes with PDK1 at the plasma membrane when the two proteins are overexpressed, indicating direct deubiquitination. CONCLUSIONS: The regulated mono-ubiquitination of PDK1 provides an unanticipated layer of complexity in this central signaling network and offers potential novel avenues for drug discovery

PPARδ Activation Acts Cooperatively with 3-Phosphoinositide-Dependent Protein Kinase-1 to Enhance Mammary Tumorigenesis

Peroxisome proliferator-activated receptorδ (PPARδ) is a transcription factor that is associated with metabolic gene regulation and inflammation. It has been implicated in tumor promotion and in the regulation of 3-phosphoinositide-dependent kinase-1 (PDK1). PDK1 is a key regulator of the AGC protein kinase family, which includes the proto-oncogene AKT/PKB implicated in several malignancies, including breast cancer. To assess the role of PDK1 in mammary tumorigenesis and its interaction with PPARδ, transgenic mice were generated in which PDK1 was expressed in mammary epithelium under the control of the MMTV enhancer/promoter region. Transgene expression increased pT308AKT and pS9GSK3β, but did not alter phosphorylation of mTOR, 4EBP1, ribosomal protein S6 and PKCα. The transgenic mammary gland also expressed higher levels of PPARδ and a gene expression profile resembling wild-type mice maintained on a diet containing the PPARδ agonist, GW501516. Both wild-type and transgenic mice treated with GW501516 exhibited accelerated rates of tumor formation that were more pronounced in transgenic animals. GW501516 treatment was accompanied by a distinct metabolic gene expression and metabolomic signature that was not present in untreated animals. GW501516-treated transgenic mice expressed higher levels of fatty acid and phospholipid metabolites than treated wild-type mice, suggesting the involvement of PDK1 in enhancing PPARδ-driven energy metabolism. These results reveal that PPARδ activation elicits a distinct metabolic and metabolomic profile in tumors that is in part related to PDK1 and AKT signaling

Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits

The identification of genes and regulatory elements underlying the associations discovered by GWAS is essential to understanding the aetiology of complex traits (including diseases). Here, we demonstrate an analytical paradigm of prioritizing genes and regulatory elements at GWAS loci for follow-up functional studies. We perform an integrative analysis that uses summary-level SNP data from multi-omics studies to detect DNA methylation (DNAm) sites associated with gene expression and phenotype through shared genetic effects (i.e., pleiotropy). We identify pleiotropic associations between 7858 DNAm sites and 2733 genes. These DNAm sites are enriched in enhancers and promoters, and >40% of them are mapped to distal genes. Further pleiotropic association analyses, which link both the methylome and transcriptome to 12 complex traits, identify 149 DNAm sites and 66 genes, indicating a plausible mechanism whereby the effect of a genetic variant on phenotype is mediated by genetic regulation of transcription through DNAm

Mortality Risk of Hypnotics: Strengths and Limits of Evidence

Sleeping pills, more formally defined as hypnotics, are sedatives used to induce and maintain sleep. In a review of publications for the past 30 years, descriptive epidemiologic studies were identified that examined the mortality risk of hypnotics and related sedative-anxiolytics. Of the 34 studies estimating risk ratios, odds ratios, or hazard ratios, excess mortality associated with hypnotics was significant (p < 0.05) in 24 studies including all 14 of the largest, contrasted with no studies at all suggesting that hypnotics ever prolong life. The studies had many limitations: possibly tending to overestimate risk, such as possible confounding by indication with other risk factors; confusing hypnotics with drugs having other indications; possible genetic confounders; and too much heterogeneity of studies for meta-analyses. There were balancing limitations possibly tending towards underestimates of risk such as limited power, excessive follow-up intervals with possible follow-up mixing of participants taking hypnotics with controls, missing dosage data for most studies, and over-adjustment of confounders. Epidemiologic association in itself is not adequate proof of causality, but there is proof that hypnotics cause death in overdoses; there is thorough understanding of how hypnotics euthanize animals and execute humans; and there is proof that hypnotics cause potentially lethal morbidities such as depression, infection, poor driving, suppressed respiration, and possibly cancer. Combining these proofs with consistent evidence of association, the great weight of evidence is that hypnotics cause huge risks of decreasing a patient's duration of survival

Persistence Increases with Diversity and Connectance in Trophic Metacommunities

We are interested in understanding if metacommunity dynamics contribute to the persistence of complex spatial food webs subject to colonization-extinction dynamics. We study persistence as a measure of stability of communities within discrete patches, and ask how do species diversity, connectance, and topology influence it in spatially structured food webs.We answer this question first by identifying two general mechanisms linking topology of simple food web modules and persistence at the regional scale. We then assess the robustness of these mechanisms to more complex food webs with simulations based on randomly created and empirical webs found in the literature. We find that linkage proximity to primary producers and food web diversity generate a positive relationship between complexity and persistence in spatial food webs. The comparison between empirical and randomly created food webs reveal that the most important element for food web persistence under spatial colonization-extinction dynamics is the degree distribution: the number of prey species per consumer is more important than their identity.With a simple set of rules governing patch colonization and extinction, we have predicted that diversity and connectance promote persistence at the regional scale. The strength of our approach is that it reconciles the effect of complexity on stability at the local and the regional scale. Even if complex food webs are locally prone to extinction, we have shown their complexity could also promote their persistence through regional dynamics. The framework we presented here offers a novel and simple approach to understand the complexity of spatial food webs