Nonlinearity in interspecific interactions in response to climate change: Cod and haddock as an example

Climate change has profound ecological effects, yet our understanding of how trophic interactions among species are affected by climate change is still patchy. The sympatric Atlantic haddock and cod are co‐occurring across the North Atlantic. They compete for food at younger stages and thereafter the former is preyed by the latter. Climate change might affect the interaction and coexistence of these two species. Particularly, the increase in sea temperature (ST) has been shown to affect distribution, population growth and trophic interactions in marine systems. We used 33‐year long time series of haddock and cod abundances estimates from two data sources (acoustic and trawl survey) to analyse the dynamic effect of climate on the coexistence of these two sympatric species in the Arcto‐Boreal Barents Sea. Using a Bayesian state‐space threshold model, we demonstrated that long‐term climate variation, as expressed by changes of ST, affected species demography through different influences on density‐independent processes. The interaction between cod and haddock has shifted in the last two decades due to an increase in ST, altering the equilibrium abundances and the dynamics of the system. During warm years (ST over ca. 4°C), the increase in the cod abundance negatively affected haddock abundance while it did not during cold years. This change in interactions therefore changed the equilibrium population size with a higher population size during warm years. Our analyses show that long‐term climate change in the Arcto‐Boreal system can generate differences in the equilibrium conditions of species assemblages.     

Chemical reactivity of the carbon-centered free radicals and ferrous iron in coals: Role of bioavailable Fe2+ in coal workers' pneumoconiosis

Striking differences in the prevalence of coal workers' pneumoconiosis (CWP) exist between different coal mine regions. The major factors responsible for the observed regional differences in CWP have not yet been identified. In the present study, chemical reactivity of the carbon-centered free radicals in coals and lung tissues, as well as ferrous iron in the coals, were studied by ESR techniques. The ESR spectra clearly demonstrated the presence of at least two types of carbon-centered free radical species, which might respectively attribute to the macromolecular phase and the molecular phase of coal. Grinding produced free radicals in coals. Exposure of freshly ground coal to air for 28 h induced a slight increase of free radicals for most of the coals, and a slight decrease after 4 months' exposure. The lung tissue samples of coal workers deceased of CWP showed similar ESR spectra as coal samples, and these radicals were highly stable in the lung. After incubation of coals with glutathione, hydrogen peroxide, sodium formate or oxygen, the coal sample from the Gardanne mine which has never induced CWP, and thus is the least hazardous coal, showed the most significant change in the carbon-centered free radical concentration. No significant changes were observed among other coals reported to induce CWP. On the other hand, we found that the coals released different amounts of Fe²⁺ in an acidic medium. Interestingly, the prevalence of CWP correlates positively with the released Fe²⁺ content in these coals and with the amount of oxygen radicals produced by the interaction of Fe²⁺ with O₂ in the acidified coal filtrates. Our studies indicate that the carbon-centered free radicals may not be biologically relevant to coal dust-induced pneumoconiosis, whereas the acid soluble Fe²⁺, which may be dissolved in the phagolysosomes of macrophages, can then lead to Fe²⁺-induced oxidative stress and eventual CWP development.     

Discriminating the effects of phylogenetic hypothesis,tree resolution and clade age estimates on phylogenetic signal measurements

Understanding how species traits evolved over time is the central question to comprehend assembly rules that govern the phylogenetic structure of communities. The measurement of phylogenetic signal (PS) in ecologically relevant traits is a first step to understand phylogenetically structured community patterns. The different methods available to estimate PS make it difficult to choose which is most appropriate. Furthermore, alternative phylogenetic tree hypotheses, node resolution and clade age estimates might influence PS measurements. In this study, we evaluated to what extent these parameters affect different methods of PS analysis, and discuss advantages and disadvantages when selecting which method to use. We measured fruit/seed traits and flowering/fruiting phenology of endozoochoric species occurring in Southern Brazilian Araucaria forests and evaluated their PS using Mantel regressions, phylogenetic eigenvector regressions (PVR) and K statistic. Mantel regressions always gave less significant results compared to PVR and K statistic in all combinations of phylogenetic trees constructed. Moreover, a better phylogenetic resolution affected PS, independently of the method used to estimate it. Morphological seed traits tended to show higher PS than diaspores traits, while PS in flowering/fruiting phenology depended mostly on the method used to estimate it. This study demonstrates that different PS estimates are obtained depending on the chosen method and the phylogenetic tree resolution. This finding has implications for inferences on phylogenetic niche conservatism or ecological processes determining phylogenetic community structure.     

Flexible Mixture Model Approaches That Accommodate Footprint Size Variability for Robust Detection of Balancing Selection

Long-term balancing selection typically leaves narrow footprints of increased genetic diversity, and therefore most detection approaches only achieve optimal performances when sufficiently small genomic regions (i.e., windows) are examined. Such methods are sensitive to window sizes and suffer substantial losses in power when windows are large. Here, we employ mixture models to construct a set of five composite likelihood ratio test statistics, which we collectively term B statistics. These statistics are agnostic to window sizes and can operate on diverse forms of input data. Through simulations, we show that they exhibit comparable power to the best-performing current methods, and retain substantially high power regardless of window sizes. They also display considerable robustness to high mutation rates and uneven recombination landscapes, as well as an array of other common confounding scenarios. Moreover, we applied a specific version of the B statistics, termed B₂, to a human population-genomic data set and recovered many top candidates from prior studies, including the then-uncharacterized STPG2 and CCDC169–SOHLH2, both of which are related to gamete functions. We further applied B₂ on a bonobo population-genomic data set. In addition to the MHC-DQ genes, we uncovered several novel candidate genes, such as KLRD1, involved in viral defense, and SCN9A, associated with pain perception. Finally, we show that our methods can be extended to account for multiallelic balancing selection and integrated the set of statistics into open-source software named BalLeRMix for future applications by the scientific community.     

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.     

Classical Molecular Dynamics Simulation of Kappa Squared Factor in Resonance Energy Transfer for Linear Dipole Models

Molecular dynamics simulations of linear models interacting through a dipolar Kihara intermolecular potential are presented. Molecular orientation correlations are used to calculate the orientational factor kappa squared in the resonance energy transfer (RET) as a function of the intermolecular separation. The distance, R 0 (2/3), at which the simulated systems show an isotropic behavior is calculated and an analysis of the dependence of R 0 (2/3) on microscopic properties (molecular aspect ratio and dipole moment) as well on thermodynamics (temperature and density) is presented. An explanation of the use of metallic cations as probes in RET is given and some relations of our models with biological molecules are pointed out.     

Monte Carlo simulation of the adsorption of C2–C7 linear alkanes in aluminophosphate AlPO4-11

The adsorption behaviors of linear alkanes ranging in length from C₂ to C₇ in AlPO₄-11 have been simulated by using configurational-bias Monte Carlo technique at 313 K. The calculated heats of adsorption at zero coverage for linear alkanes, estimated by Henry coefficients, are consistent well with previously reported experimental and simulation results. The simulated isotherms for n-hexane in AlPO₄-11 at 298 K agree with the experimental data. The isotherms of C₂–C₇ linear alkane were predicted, in which butane presents a substep. The adsorbed alkane molecules are only localized in 10-membered ring channels, and adsorbed phase structures for each alkane were investigated. Total potentials for individual alkane molecule decrease with increasing number of carbon atoms. A linear change in total potential is observed for each linear alkane with increasing loading per unit cell, except that an increasing trend is found in the total potential curve of butane as the loading per unit cell is higher than two molecules.     

Structural Mechanism for the Specific Assembly and Activation of the Extracellular Signal Regulated Kinase 5 (ERK5) Module

Mitogen-activated protein kinase (MAPK) activation depends on a linear binding motif found in all MAPK kinases (MKK). In addition, the PB1 (Phox and Bem1) domain of MKK5 is required for extracellular signal regulated kinase 5 (ERK5) activation. We present the crystal structure of ERK5 in complex with an MKK5 construct comprised of the PB1 domain and the linear binding motif. We show that ERK5 has distinct protein-protein interaction surfaces compared with ERK2, which is the closest ERK5 paralog. The two MAPKs have characteristically different physiological functions and their distinct protein-protein interaction surface topography enables them to bind different sets of activators and substrates. Structural and biochemical characterization revealed that the MKK5 PB1 domain cooperates with the MAPK binding linear motif to achieve substrate specific binding, and it also enables co-recruitment of the upstream activating enzyme and the downstream substrate into one signaling competent complex. Studies on present day MAPKs and MKKs hint on the way protein kinase networks may evolve. In particular, they suggest how paralogous enzymes with similar catalytic properties could acquire novel signaling roles by merely changing the way they make physical links to other proteins.