Nutrients are assimilated efficiently by Lymantria dispar caterpillars from the mature leaves of trees in the Salicaceae

The efficient aquisition of nutrients from leaves by insect herbivores increases their nutrient assimilation rates and overall fitness. Caterpillars of the gypsy moth (Lymantria dispar L.) have high protein assimilation efficiencies (PAE) from the immature leaves of trees such as red oak (Quercus rubra) and sugar maple (Acer saccharum) (71–81%) but significantly lower PAE from their mature leaves (45–52%). By contrast to this pattern, both PAE and carbohydrate assimilation efficiencies (CAE) remain high for L. dispar larvae on the mature leaves of poplar (Populus alba × Populus tremula) grown in greenhouse conditions. The present study tests two alternative hypotheses: (i) outdoor environmental stresses cause decreased nutrient assimilation efficiencies from mature poplar leaves and (ii) nutrients in the mature leaves of trees in the poplar family (Salicaceae) remain readily available for L. dispar larvae. When poplar trees are grown in ambient outdoor conditions, PAE and CAE remain high (approximately 75% and 78%, respectively) in L. dispar larvae, in contrast to the first hypothesis. When larvae feed on the mature leaves of species in the Salicaceae [aspen (Populus tremuloides), cottonwood (Populus deltoides), willow (Salix nigra) and poplar], PAE and CAE also remain high (68–76% and 72–92%, respectively), consistent with the second hypothesis. Larval growth rates are strongly associated with protein assimilation rates, and more strongly associated with protein assimilation rates than with carbohydrate assimilation rates. It is concluded that tree species in the Salicaceae are relatively high‐quality host plants for L. dispar larvae, in part, because nutrients in their mature leaves remain readily available.     

Altitudinal distribution limits of aquatic macroinvertebrates: an experimental test in a tropical alpine stream

1. Temperature and oxygen are recognised as the main drivers of altitudinal limits of species distributions. However, the two factors are linked, and both decrease with altitude, why their effects are difficult to disentangle. 2. This was experimentally addressed using aquatic macroinvertebrates; larvae of Andesiops (Ephemeroptera), Claudioperla, (Plecoptera), Scirtes (Coleoptera) and Anomalocosmoecus (Trichoptera), and the amphipod Hyalella in an Ecuadorian glacier‐fed stream (4100–4500 m a.s.l.). The following were performed: (i) quantitative benthic sampling at three sites to determine altitudinal patterns in population densities, (ii) transplants of the five taxa upstream of their natural altitudinal limit to test the short‐term (14 days) effect on survival, and (iii) in situ experiments of locomotory activity as a proxy for animal response to relatively small differences in temperature (5 °C vs. 10 °C) and oxygen saturation (55% vs. 62%). 3. The transplant experiment reduced survival to a varying degree among taxa, but Claudioperla survived well at a site where it did not naturally occur. In the in situ experiment, Scirtes and Hyalella decreased their activity at lower oxygen saturation, whereas Andesiops and Anomalocosmoecus did so at a low temperature. The decrease in activity from a high to a low temperature and oxygen for the five taxa was significantly correlated with their mortality in the transplant experiment. 4. Together the present experiments indicate that even relatively small differences in temperature and oxygen may produce effects explaining ecological patterns, and depending on the taxon, either water temperature or oxygen saturation, without clear interacting effects, are important drivers of altitudinal limits.     

Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

Genome‐wide analysis of Italian sheep diversity reveals a strong geographic pattern and cryptic relationships between breeds

Italy counts several sheep breeds, arisen over centuries as a consequence of ancient and recent genetic and demographic events. To finely reconstruct genetic structure and relationships between Italian sheep, 496 subjects from 19 breeds were typed at 50K single nucleotide polymorphism loci. A subset of foreign breeds from the Sheep HapMap dataset was also included in the analyses. Genetic distances (as visualized either in a network or in a multidimensional scaling analysis of identical by state distances) closely reflected geographic proximity between breeds, with a clear north–south gradient, likely because of high levels of past gene flow and admixture all along the peninsula. Sardinian breeds diverged more from other breeds, a probable consequence of the combined effect of ancient sporadic introgression of feral mouflon and long‐lasting genetic isolation from continental sheep populations. The study allowed the detection of previously undocumented episodes of recent introgression (Delle Langhe into the endangered Altamurana breed) as well as signatures of known, or claimed, historical introgression (Merino into Sopravissana and Gentile di Puglia; Bergamasca into Fabrianese, Appenninica and, to a lesser extent, Leccese). Arguments that would question, from a genomic point of view, the current breed classification of Bergamasca and Biellese into two separate breeds are presented. Finally, a role for traditional transhumance practices in shaping the genetic makeup of Alpine sheep breeds is proposed. The study represents the first exhaustive analysis of Italian sheep diversity in an European context, and it bridges the gap in the previous HapMap panel between Western Mediterranean and Swiss breeds.     

Screening of significant biomarkers related with prognosis of liver cancer by lncRNA-associated ceRNAs analysis

This study aimed to identify significant biomarkers related to the prognosis of liver cancer using long noncoding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) analysis. Differentially expressed mRNA and lncRNAs between liver cancer and paracancerous tissues were screened, and the functions of these mRNAs were predicted by gene ontology and pathway enrichment analyses. A ceRNA network consisting of differentially expressed mRNAs and lncRNAs was constructed. LncRNA FENDRR and lncRNA HAND2-AS1 were hub nodes in the ceRNA network. A risk score assessment model consisting of eight genes (PDE2A, ESR1, FBLN5, ALDH8A1, AKR1D1, EHHADH, ADRA1A, and GNE) associated with prognosis were developed. Multivariate Cox regression suggested that both pathologic_T and risk group could be regarded as independent prognostic factors. Furthermore, a nomogram model consisting of pathologic_T and risk group showed a good prediction ability for predicting the survival rate of liver cancer patients. The nomogram model consisting of pathologic_T and a risk score assessment model could be regarded as an independent factor for predicting prognosis of liver cancer.