Stimulator of interferon genes (STING): A “new chapter” in virus-associated cancer research. Lessons from wild-derived mouse models of innate immunity

Thanks to the numerous studies that have been carried out recently in the field of cytosolic DNA sensing, STING (Stimulator of Interferon Genes) is now recognized as a key mediator of innate immune signaling. A substantial body of evidence derived from in vivo mouse models demonstrates that STING-regulated pathways underlie the pathogenesis of many diseases including infectious diseases and cancers. It has also become evident from these studies that STING is a promising therapeutic target for the treatment of cancer. However, mouse strains commonly used for modelling innate immune response against infections or tumors do not allow investigators to accurately reproduce certain specific characteristics of immune response observed in human cells. In this review, we will discuss recent data demonstrating that the use of wild-derived genetically distinct inbred mice as a model for investigation into the innate immunity signaling networks may provide valuable insight into the STING-regulated pathways specific for human cells. The maximum complexity of STING-mediated mechanisms can probably be seen in case of DNA virus-induced carcinogenesis in which STING may perform unexpected biological activities. Therefore, in another part of this review we will summarize emerging data on the role of STING in human DNA virus-related oncopathologies, with particular attention to HPV-associated cervical cancer, aiming to demonstrate that STING indeed “starts a new chapter” in research on this issue and that wild-derived mouse models of STING-mediated response to infections will probably be helpful in finding out molecular basis for clinical observations.     

Density-dependent population regulation detected in short time series of saproxylic beetles

Understanding the regulation of natural populations has been a long-standing problem in ecology. Here we analyze the population dynamics of 17 species of saproxylic beetles in Shizuoka Prefecture, Japan collected over 11–12 years using autoregressive integrated moving average (ARIMA) models. We first examined the dynamics for indications of the order of the ARIMA models and evaluated the time series to determine that it was not simply a random, white noise sequence. All species dynamics were not mere random noise, and ARIMA models up to lag 3 were considered. The best model was selected from the possible ones using several criteria: model convergence, weak residual autocorrelation, the small sample AIC must be among the smallest that were not significantly different, and the lag indicated by the cutoff values in the detrended partial autocorrelation function. We found significant and nearly significant direct density-dependence for 14 of the 17 species, varying from −0.709 and stronger. The characteristic return rates were strong and only one species had a weak return rate (>0.9), implying that these species were strongly regulated by density-dependent factors. We found that populations with higher order ARIMA models (lag 2 and 3) had weaker return rates than populations with ARIMA models with only one lag, suggesting that species with more complex dynamics were more weakly regulated. These results contrast with previous suggestions that 20+ years are needed to detect density dependence from population time series and that most populations are weakly regulated.     

Using dynamic sustainability indicators to assess environmental policy measures in Biosphere Reserves

The assessment of different policy options represents a major tool for decision-makers in Biosphere Reserves, to develop more-resilient strategies for sustainable development and to visualise unintended consequences of these policies.In this work we analyse eight measures proposed by different agents in order to meet the main objectives of environmental sustainability, included in the Action Plan of the Fuerteventura Biosphere Reserve (Spain). We quantified the effects of these measures in terms of the sustainability thresholds of 10 environmental indicators, also proposed by the Action Plan, which was integrated in the Fuerteventura Biosphere Reserve dynamic model. Their behaviours under these measures allow determination of whether the objectives will be met in the period 2012–2025. Although some indicators would improve under these measures, fitting certain objectives, some negative effects on other indicators confirm the existence of trade-offs among these objectives. For instance, grazing limitation would improve the proportion of high-quality vegetation but would negatively affect the Egyptian vulture population, which would even fall below its sustainability threshold. The definition of thresholds for each indicator allows decision-makers to establish a way to prioritise among the eight measures analysed. The results show that these measures are insufficient to meet the sustainability thresholds of four indicators (the landscape indicator, the proportion of renewable energy, the per capita primary energy consumption and carbon dioxide emissions). Focusing on the remaining six indicators and following the rule “Threshold out, measure out”, seven out of the eight measures would exceed some thresholds and should be avoided. Only one option, aimed at growing fodder to feed cattle on restored traditional agricultural lands, would not exceed any of these thresholds. However, this measure also presents certain negative effects regarding indicators related to flagship species (the houbara habitat and the Egyptian vulture population), which would require compensation measures.     

Models for Trypanosoma evansi (surra), its control and economic impact on small-hold livestock owners in the Philippines

Simple demographic and infectious disease models of buffaloes and other domestic hosts for animal trypanosomosis (surra) caused by Trypanosoma evansi were developed. The animal models contained deterministic and stochastic elements and were linked to simulate the benefit of control regimes for surra in village domestic animal populations in Mindanao, Philippines. The impact of the disease on host fertility and mortality were key factors in determining the economic losses and net-benefit from the control regimes. If using a high (99%) efficacy drug in surra-moderate to high risk areas, then treating all animals twice each year yielded low prevalence in 2 years; targeted treatment of clinically sick animals, constantly monitored (monthly), required 75% fewer treatments but took longer to reach a low prevalence than treating all animals twice each year. At high drug efficacy both of these treatment strategies increased the benefit over untreated animals by 81%. If drug efficacy declined then the benefit obtained from twice yearly treatment of all animals declined rapidly compared with regular monitoring and targeting treatment to clinically sick animals. The current control regimen applied in the Philippines of annual sero-testing for surra and only treating sero-positive animals provided the lowest net-benefit of all the control options simulated and would not be regarded as effective control. The total net-benefit from effective surra control for a typical village in a moderate/high risk area was 7.9 million pesos per annum (US $158,000). The value added to buffaloes, cattle, horses, goats/sheep and pigs as a result of this control was US $88, $84, $151, $7, $114 per animal/year, respectively.     

Individual-based model of spatio-temporal dynamics of mixed forest stands

This research presents the results of constructing and parameterizing an individual-based model of spatiotemporal dynamics of mixed forest stands. The model facilitates computerized experiments with forest stands having different combinations of species and age structures. These forest stands grow on temperate areas where light is the main system-forming factor that shapes and develops forest ecosystems. The model TEMFORM (TEMperate FORests Model) is developed with few equations and parameters, most of which can be estimated using standard forest inventory data. Parameterization of the model used the growth tables of a set of basic forest-forming species in Far East Russia. Simulation results of the development of the natural single- and mixed-species stands and the effects of different types of disturbances on the stand dynamics and compositions are presented.     

Non‐parametric habitat models with automatic interactions

Questions: Can a statistical model be designed to represent more directly the nature of organismal response to multiple interacting factors? Can multiplicative kernel smoothers be used for this purpose? What advantages does this approach have over more traditional habitat modelling methods? Methods: Non‐parametric multiplicative regression (NPMR) was developed from the premises that: the response variable has a minimum of zero and a physiologically‐determined maximum, species respond simultaneously to multiple ecological factors, the response to any one factor is conditioned by the values of other factors, and that if any of the factors is intolerable then the response is zero. Key features of NPMR are interactive effects of predictors, no need to specify an overall model form in advance, and built‐in controls on overfitting. The effectiveness of the method is demonstrated with simulated and real data sets. Results: Empirical and theoretical relationships of species response to multiple interacting predictors can be represented effectively by multiplicative kernel smoothers. NPMR allows us to abandon simplistic assumptions about overall model form, while embracing the ecological truism that habitat factors interact.     

TREES SIFTER 1.0: an approximate method to estimate the time to the most recent common ancestor of a sample of DNA sequences

trees sifter 1.0 implements an approximate method to estimate the time to the most recent common ancestor (TMRCA) of a set of DNA sequences, using population evolution modelling. In essence, the program simulates genealogies with a user‐defined model of coalescence of lineages, and then compares each simulated genealogy to the genealogy inferred from the real data, through two summary statistics: (i) the number of mutations on the genealogy (M_n), and (ii) the number of different sequence types (alleles) observed (K_n). The simulated genealogies are then submitted to a rejection algorithm that keeps only those that are the most likely to have generated the observed sequence data. At the end of the process, the accepted genealogies can be used to estimate the posterior probability distribution of the TMRCA.     

The influence of stream invertebrate composition at neighbouring sites on local assemblage composition

1. The composition of freshwater invertebrate assemblages at a location is determined by a range of physico‐chemical and biotic factors in the local environment, as well as larger‐scale spatial factors such as sources of recruits. We assessed the relative importance of the species composition of local neighbourhoods and proximal environmental factors on the composition of invertebrate assemblages. 2. Macroinvertebrate assemblages were sampled at 188 running‐water sites in the catchment of the River Rede, north‐east England. A total of 176 species were recorded. 3. Environmental data, in the form of 13 biotic and abiotic measurements that described stream physical structure, aquatic vegetation and water characteristics, were recorded for each site. Detrended correspondence analysis was then used to simplify nine of these stream environmental variables to create an index of stream structure. 4. The species composition of the invertebrate assemblages was related to the environmental variables, using an information theoretic approach. The impact of the species composition of neighbouring sites on each site was determined using Moran's I and autoregressive modelling techniques. 5. Species composition was primarily associated with water pH and stream structure. The importance of the species composition of neighbouring sites in determining local species assemblages differed markedly between taxa. The autoregressive component was low for Coleoptera, intermediate for Trichoptera and Plecoptera, and high for Ephemeroptera. 6. We hypothesise that the observed differences in the autoregressive component amongst these orders reflects variation in their dispersal abilities from neighbouring sites.