Parasite spill-back from domestic hosts may induce an Allee effect in wildlife hosts

The exchange of native pathogens between wild and domesticated animals can lead to novel disease dynamics. A simple model reveals that the spill-back of native parasites\ud from domestic to wild hosts may cause a demographic Allee effect. Because parasite spill-over and spill-back decouples the abundance of parasite infectious stages from the abundance of the wild host population, parasitism and mortality of the wild host population increases non-linearly as host abundance decreases. Analogous to the effects of satiation of generalist predators, parasite spill-back can produce an unstable equilibrium in the abundance of the host population above which the host population persists and below which it is at risk of extirpation. These effects are likely to be most pronounced in systems where the parasite has a high efficiency of transmission from domestic to wild host populations due to prolonged sympatry, disease vectors, or proximity of domesticated populations to wildlife migratory corridors

Optimal Investment to Enable Evolutionary Rescue

'Evolutionary rescue' is the potential for evolution to enable population persistence in a changing environment. Even with eventual rescue, evolutionary time lags can cause the population size to temporarily fall below a threshold susceptible to extinction. To reduce extinction risk given human-driven global change, conservation management can enhance populations through actions such as captive breeding. To quantify the optimal timing of, and indicators for engaging in, investment in temporary enhancement to enable evolutionary rescue, we construct a model of coupled demographic-genetic dynamics given a moving optimum. We assume 'decelerating change', as might be relevant to climate change, where the rate of environmental change initially exceeds a rate where evolutionary rescue is possible, but eventually slows. We analyze the optimal control path of an intervention to avoid the population size falling below a threshold susceptible to extinction, minimizing costs. We find that the optimal path of intervention initially increases as the population declines, then declines and ceases when the population growth rate becomes positive, which lags the stabilization in environmental change. In other words, the optimal strategy involves increasing investment even in the face of a declining population, and positive population growth could serve as a signal to end the intervention. In addition, a greater carrying capacity relative to the initial population size decreases the optimal intervention. Therefore, a one-time action to increase carrying capacity, such as habitat restoration, can reduce the amount and duration of longer-term investment in population enhancement, even if the population is initially lower than and declining away from the new carrying capacity

The mechanisms of phenology: the patterns and processes of phenological shifts

Species across a wide range of taxa and habitats are shifting phenological events in response to climate change. While advances are common, shifts vary in magnitude and direction within and among species, and the basis for this variation is relatively unknown. We examine previously suggested patterns of variation in phenological shifts in order to understand the cue-response mechanisms that underlie phenological change. Here, we review what is known about the mechanistic basis for nine factors proposed to predict phenological change (latitude, elevation, habitat type, trophic level, migratory strategy, ecological specialization, species\u27 seasonality, thermoregulatory mode, and generation time). We find that many studies either do not identify a specific underlying mechanism or do not evaluate alternative mechanistic hypotheses, limiting the ability of scientists to predict future responses to global change with accuracy. We present a conceptual framework that emphasizes a critical distinction between environmental (cue-driven) and organismal (response-driven) mechanisms causing variation in phenological shifts and discuss how this distinction can reduce confusion in the field and improve predictions of future phenological change

Network metrics can guide nearly-optimal management of invasive species at large scales

Invasive species harm biodiversity and ecosystem services, with global economic costs of invasions exceeding $40 billion annually. Widespread invasions are a particular challenge because they involve large spatial scales with many interacting components. In these contexts, typical optimization-based approaches to management may fail due to computational or data constraints. Here we evaluate an alternative solution that leverages network science, representing the invasion as occurring across a network of connected sites and using network metrics to prioritize sites for intervention. Such heuristic network-guided methods require less data and are less computationally intensive than optimization methods, yet network-guided approaches have not been bench-marked against optimal solutions for real-world invasive species management problems. We provide the first comparison of the performance of network-guided management relative to optimal solutions for invasive species, examining the placement of watercraft inspection stations for preventing spread of invasive zebra mussels through recreational boat movement within 58 Minnesota counties in the United States. To additionally test the promise of network-based approaches in limited data contexts, we evaluate their performance when using only partial data on network structure and invaded status. Metric-based approaches can achieve a median of 100% of optimal performance with full data. Even with partial data, 80% of optimal performance is achievable. Finally, we show that performance of metric-guided management improves for counties with denser and larger networks, suggesting this approach is viable for large-scale invasions. Together, our results suggest network metrics are a promising approach to guiding management actions for large-scale invasions.Comment: 29 pages, 8 figures, 3 table

Selection of reference genes for studies of human retinal endothelial cell gene expression by reverse transcriptionquantitative real-time polymerase chain reaction

© 2017 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (Nov 2017) in accordance with the publisher’s archiving policyBackground Human retinal endothelial cells are employed increasingly for investigations of retinal vascular diseases. Analysis of gene expression response to disease-associated stimuli by reverse transcription-quantitative real-time polymerase chain reaction (RT-qPCR) is common. However, most reported work does not follow the minimum information for publication of qPCR experiments (MIQE) recommendation that multiple, stably expressed reference genes be used for normalization. Methods Two human retinal endothelial cell lines were treated with medium alone or containing stimuli that included: glucose at supraphysiological concentration, dimethyloxalyl-glycine, vascular endothelial growth factor, tumor necrosis factor-α, lipopolysaccharide and Toxoplasma gondii tachyzoites. Biological response of cells was confirmed by measuring significant increase in a stimulus-relevant transcript. Total RNA was reverse transcribed and analyzed by commercial PCR arrays designed to detect 28 reference genes. Stability of reference gene expression, for each and both cell lines, and for each and all conditions, was judged on gene-stability measure (M-value) < 0.2 and coefficient of variation (CV-value) < 0.1. Results Reference gene expression varied substantially across stimulations and between cell lines. Of 27 detectable reference genes, 11–21 (41–78%) maintained expression stability across stimuli and cell lines. Ranking indicated substantial diversity in the most stable reference genes under different conditions, and no reference gene was expressed stably under all conditions of stimulation and for both cell lines. Four reference genes were expressed stably under 5 conditions: HSP90AB1, IPO8, PSMC4 and RPLPO. Conclusions We observed variation in stability of reference gene expression with different stimuli and between human retinal endothelial cell lines. Our findings support adherence to MIQE recommendations regarding normalization in RT-qPCR studies of human retinal endothelial cells

A community convention for ecological forecasting: output files and metadata

This document summarizes the open community standards developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast adoption, distribution, validation, and synthesis. For output files EFI has adopted a three-tiered approach reflecting trade-offs in forecast data volume and technical expertise. The preferred output file format is netCDF following the Climate and Forecast Convention for dimensions and variable naming, including an ensemble dimension where appropriate. The second-tier option is a semi-long CSV format, with state variables as columns and each row representing a unique issue date time, prediction date time, location, ensemble member, etc. The third-tier option is similar to option 2, but each row represents a specific summary statistic (mean, upper/lower CI) rather than individual ensemble members. For metadata, EFI expands upon the Ecological Metadata Language (EML), using additional Metadata tags to store information designed to facilitate cross-forecast synthesis (e.g. uncertainty propagation, data assimilation, model complexity) and setting a subset of base EML tags (e.g. temporal resolution, output variables) to be required. To facilitate community adoption we also provides a R package containing a number of vignettes on how to both write and read in the EFI standard, as well as a metadata validator tool.First author draf

Effect of NADPH oxidase 1 and 4 blockade in activated human retinal endothelial cells

© 2018 Royal Australian and New Zealand College of Ophthalmologists. This author accepted manuscript is made available following 12 month embargo from date of publication (January 2018) in accordance with the publisher's archiving policy.Background Over‐production of reactive oxygen species (ROS) and resulting oxidative stress contribute to retinal damage in vascular diseases that include diabetic retinopathy, retinopathy of prematurity and major retinal vessel occlusions. NADPH oxidase (Nox) proteins are professional ROS‐generating enzymes, and therapeutic targeting in these diseases has strong appeal. Pharmacological inhibition of Nox4 reduces the severity of experimental retinal vasculopathy. We investigated the potential application of this drug approach in humans. Methods Differential Nox enzyme expression was studied by real‐time‐quantitative polymerase chain reaction in primary human retinal endothelial cell isolates and a characterized human retinal endothelial cell line. Oxidative stress was triggered chemically in endothelial cells, by treatment with dimethyloxalylglycine (DMOG; 100 μM); Nox4 and vascular endothelial growth factor (VEGFA) transcript were measured; and production of ROS was detected by 2′,7′‐dichlorofluorescein. DMOG‐stimulated endothelial cells were treated with two Nox1/Nox4 inhibitors, GKT136901 and GKT137831; cell growth was monitored by DNA quantification, in addition to VEGFA transcript and ROS production. Results Nox4 (isoform Nox4A) was the predominant Nox enzyme expressed by human retinal endothelial cells. Treatment with DMOG significantly increased endothelial cell expression of Nox4 over 72 h, accompanied by ROS production and increased VEGFA expression. Treatment with GKT136901 or GKT137831 significantly reduced DMOG‐induced ROS production and VEGFA expression by endothelial cells, and the inhibitory effect of DMOG on cell growth. Conclusions Our findings in experiments on activated human retinal endothelial cells provide translational corroboration of studies in experimental models of retinal vasculopathy and support the therapeutic application of Nox4 inhibition by GKT136901 and GKT137831 in patients with retinal vascular diseases

ICAM-1-related long non-coding RNA: promoter analysis and expression in human retinal endothelial cells

© The Author(s) 2018 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Abstract Objective Regulation of intercellular adhesion molecule (ICAM)-1 in retinal endothelial cells is a promising druggable target for retinal vascular diseases. The ICAM-1-related (ICR) long non-coding RNA stabilizes ICAM-1 transcript, increasing protein expression. However, studies of ICR involvement in disease have been limited as the promoter is uncharacterized. To address this issue, we undertook a comprehensive in silico analysis of the human ICR gene promoter region. Results We used genomic evolutionary rate profiling to identify a 115 base pair (bp) sequence within 500 bp upstream of the transcription start site of the annotated human ICR gene that was conserved across 25 eutherian genomes. A second constrained sequence upstream of the orthologous mouse gene (68 bp; conserved across 27 Eutherian genomes including human) was also discovered. Searching these elements identified 33 matrices predictive of binding sites for transcription factors known to be responsive to a broad range of pathological stimuli, including hypoxia, and metabolic and inflammatory proteins. Five phenotype-associated single nucleotide polymorphisms (SNPs) in the immediate vicinity of these elements included four SNPs (i.e. rs2569693, rs281439, rs281440 and rs11575074) predicted to impact binding motifs of transcription factors, and thus the expression of ICR and ICAM-1 genes, with potential to influence disease susceptibility. We verified that human retinal endothelial cells expressed ICR, and observed induction of expression by tumor necrosis factor-α

Immunological Molecular Responses of Human Retinal Pigment Epithelial Cells to Infection With Toxoplasma gondii

Ocular toxoplasmosis is the commonest clinical manifestation of infection with obligate intracellular parasite, Toxoplasma gondii. Active ocular toxoplasmosis is characterized by replication of T. gondii tachyzoites in the retina, with reactive inflammation. The multifunctional retinal pigment epithelium is a key target cell population for T. gondii. Since the global gene expression profile is germane to understanding molecular involvements of retinal pigment epithelial cells in ocular toxoplasmosis, we performed RNA-Sequencing (RNA-Seq) of human cells following infection with T. gondii tachyzoites. Primary cell isolates from eyes of cadaveric donors (n = 3), and the ARPE-19 human retinal pigment epithelial cell line, were infected for 24 h with GT-1 strain T. gondii tachyzoites (multiplicity of infection = 5) or incubated uninfected as control. Total and small RNA were extracted from cells and sequenced on the Illumina NextSeq 500 platform; results were aligned to the human hg19 reference sequence. Multidimensional scaling showed good separation between transcriptomes of infected and uninfected primary cell isolates, which were compared in edgeR software. This differential expression analysis revealed a sizeable response in the total RNA transcriptome—with significantly differentially expressed genes totaling 7,234 (28.9% of assigned transcripts)—but very limited changes in the small RNA transcriptome—totaling 30 (0.35% of assigned transcripts) and including 8 microRNA. Gene ontology and pathway enrichment analyses of differentially expressed total RNA in CAMERA software, identified a strong immunologic transcriptomic signature. We conducted RT-qPCR for 26 immune response-related protein-coding and long non-coding transcripts in epithelial cell isolates from different cadaveric donors (n = 3), extracted by a different isolation protocol but similarly infected with T. gondii, to confirm immunological activity of infected cells. For microRNA, increases in miR-146b and miR-212 were detected by RT-qPCR in 2 and 3 of these independent cell isolates. Biological network analysis in the InnateDB platform, including 735 annotated differentially expressed genes plus 2,046 first-order interactors, identified 10 contextural hubs and 5 subnetworks in the transcriptomic immune response of cells to T. gondii. Our observations provide a solid base for future studies of molecular and cellular interactions between T. gondii and the human retinal pigment epithelium to illuminate mechanisms of ocular toxoplasmosis

The power of forecasts to advance ecological theory

Ecological forecasting provides a powerful set of methods for predicting short- and long-term change in living systems. Forecasts are now widely produced, enabling proactive management for many applied ecological problems. However, despite numerous calls for an increased emphasis on prediction in ecology, the potential for forecasting to accelerate ecological theory development remains underrealized. Here, we provide a conceptual framework describing how ecological forecasts can energize and advance ecological theory. We emphasize the many opportunities for future progress in this area through increased forecast development, comparison and synthesis. Our framework describes how a forecasting approach can shed new light on existing ecological theories while also allowing researchers to address novel questions. Through rigorous and repeated testing of hypotheses, forecasting can help to refine theories and understand their generality across systems. Meanwhile, synthesizing across forecasts allows for the development of novel theory about the relative predictability of ecological variables across forecast horizons and scales. We envision a future where forecasting is integrated as part of the toolset used in fundamental ecology. By outlining the relevance of forecasting methods to ecological theory, we aim to decrease barriers to entry and broaden the community of researchers using forecasting for fundamental ecological insight