Structure of Haze Forming Proteins in White Wines: Vitis vinifera Thaumatin-Like Proteins

Grape thaumatin-like proteins (TLPs) play roles in plant-pathogen interactions and can cause protein haze in white wine unless removed prior to bottling. Different isoforms of TLPs have different hazing potential and aggregation behavior. Here we present the elucidation of the molecular structures of three grape TLPs that display different hazing potential. The three TLPs have very similar structures despite belonging to two different classes (F2/4JRU is a thaumatin-like protein while I/4L5H and H2/4MBT are VVTL1), and having different unfolding temperatures (56 vs. 62°C), with protein F2/4JRU being heat unstable and forming haze, while I/4L5H does not. These differences in properties are attributable to the conformation of a single loop and the amino acid composition of its flanking regions.     

Effect of temperature on the stability and activity of crystalline ox liver nuclear and mitochondrial glutamate dehydrogenases

A study on the response of the stability and activity of crystalline ox liver nuclear and mitochondrial glutamate dehydrogenases to temperature variations has been carried out. The thermodynamic properties of the heat inactivation process and of the reaction with the substrates glutamate and α-ketoglutarate have been investigated. The heat inactivation of nuclear glutamate dehydrogenase proceeds at a faster rate than that of the mitochondrial enzyme in the temperature range 40–51 °C; the enthalpy of activation of the inactivation process is higher and the entropy is almost double, compared to the values of mitochondrial glutamate dehydrogenase. The effect of temperature on the maximal velocity shows that, with both glutamate and α-ketoglutarate, the enthalpy of activation with nuclear glutamate dehydrogenase is double and the decrease in entropy almost half of the values of the mitochondrial enzyme. The variation of the apparent K_m with temperature shows a decrease of the affinity of both enzymes for glutamate, with no major difference in the thermodynamic properties of the reaction. With α-ketoglutarate, on the other hand, the affinity of nuclear glutamate dehydrogenase decreased, whereas that of the mitochondrial enzyme increased with temperature. The process is therefore exothermic with the former enzyme, endothermic with the latter; furthermore, it occurs with a decrease in enthropy with nuclear glutamate dehydrogenase, but with a large increase with the mitochondrial enzyme. The studies on the effect of temperature on the activity were carried out in the range 20–44 °C.     

Origin,diversity, and biogeography of Antarctic scale worms (Polychaeta: Polynoidae): a wide‐scale barcoding approach

The Antarctic marine environment hosts diversified and highly endemic benthos owing to its unique geologic and climatic history. Current warming trends have increased the urgency of understanding Antarctic species history to predict how environmental changes will impact ecosystem functioning. Antarctic benthic lineages have traditionally been examined under three hypotheses: (1) high endemism and local radiation, (2) emergence of deep‐sea taxa through thermohaline circulation, and (3) species migrations across the Polar Front. In this study, we investigated which hypotheses best describe benthic invertebrate origins by examining Antarctic scale worms (Polynoidae). We amassed 691 polynoid sequences from the Southern Ocean and neighboring areas: the Kerguelen and Tierra del Fuego (South America) archipelagos, the Indian Ocean, and waters around New Zealand. We performed phylogenetic reconstructions to identify lineages across geographic regions, aided by mitochondrial markers cytochrome c oxidase subunit I (Cox1) and 16S ribosomal RNA (16S). Additionally, we produced haplotype networks at the species scale to examine genetic diversity, biogeographic separations, and past demography. The Cox1 dataset provided the most illuminating insights into the evolution of polynoids, with a total of 36 lineages identified. Eunoe sp. was present at Tierra del Fuego and Kerguelen, in favor of the latter acting as a migration crossroads. Harmothoe fuligineum, widespread around the Antarctic continent, was also present but isolated at Kerguelen, possibly resulting from historical freeze–thaw cycles. The genus Polyeunoa appears to have diversified prior to colonizing the continent, leading to the co‐occurrence of at least three cryptic species around the Southern and Indian Oceans. Analyses identified that nearly all populations are presently expanding following a bottleneck event, possibly caused by habitat reduction from the last glacial episodes. Findings support multiple origins for contemporary Antarctic polynoids, and some species investigated here provide information on ancestral scenarios of (re)colonization. First, it is apparent that species collected from the Antarctic continent are endemic, as the absence of closely related species in the Kerguelen and Tierra del Fuego datasets for most lineages argues in favor of Hypothesis 1 of local origin. Next, Eunoe sp. and H. fuligineum, however, support the possibility of Kerguelen and other sub‐Antarctic islands acting as a crossroads for larvae of some species, in support of Hypothesis 3. Finally, the genus Polyeunoa, conversely, is found at depths greater than 150 m and may have a deep origin, in line with Hypothesis 2. These “non endemic” groups, nevertheless, have a distribution that is either north or south of the Antarctic Polar Front, indicating that there is still a barrier to dispersal, even in the deep sea.     

Protein degradation sets the fraction of active ribosomes at vanishing growth

Growing cells adopt common basic strategies to achieve optimal resource allocation under limited resource availability. Our current understanding of such “growth laws” neglects degradation, assuming that it occurs slowly compared to the cell cycle duration. Here we argue that this assumption cannot hold at slow growth, leading to important consequences. We propose a simple framework showing that at slow growth protein degradation is balanced by a fraction of “maintenance” ribosomes. Consequently, active ribosomes do not drop to zero at vanishing growth, but as growth rate diminishes, an increasing fraction of active ribosomes performs maintenance. Through a detailed analysis of compiled data, we show that the predictions of this model agree with data from E. coli and S. cerevisiae. Intriguingly, we also find that protein degradation increases at slow growth, which we interpret as a consequence of active waste management and/or recycling. Our results highlight protein turnover as an underrated factor for our understanding of growth laws across kingdoms.     

The helical content of the YscP molecular ruler determines the length of the Yersinia injectisome

The length of the Yersinia injectisome needle is determined by the protein YscP, which could act as a molecular ruler. The analysis of the correlation between the size of YscP and the needle length in seven wild-type strains of Yersinia enterocolitica reinforced this hypothesis but hinted that the secondary structure of YscP might influence needle length. Hence, 11 variants of YscP₅₁₅ were generated by multiple Pro or Gly substitutions. The needle length changed in inverse function of the helical content, indicating that not only the number of residues but also their structure controls length. Taking the secondary motifs into account, Pro/Gly-variants were subjected to in silico modelling to simulate the extension of YscP upon needle growth. The calculated lengths when the helical content is preserved correlated strikingly with the measured needle length, with a constant difference of ∼29 nm, which corresponds approximately to the size of the basal body. These data support the ruler model and show that the functional ruler has a helical structure.     

Using LiDAR Data to Measure the 3D Green Biomass of Beijing Urban Forest in China

The purpose of the paper is to find a new approach to measure 3D green biomass of urban forest and to testify its precision. In this study, the 3D green biomass could be acquired on basis of a remote sensing inversion model in which each standing wood was first scanned by Terrestrial Laser Scanner to catch its point cloud data, then the point cloud picture was opened in a digital mapping data acquisition system to get the elevation in an independent coordinate, and at last the individual volume captured was associated with the remote sensing image in SPOT5(System Probatoired''Observation dela Tarre)by means of such tools as SPSS (Statistical Product and Service Solutions), GIS (Geographic Information System), RS (Remote Sensing) and spatial analysis software (FARO SCENE and Geomagic studio11). The results showed that the 3D green biomass of Beijing urban forest was 399.1295 million m³, of which coniferous was 28.7871 million m³ and broad-leaf was 370.3424 million m³. The accuracy of 3D green biomass was over 85%, comparison with the values from 235 field sample data in a typical sampling way. This suggested that the precision done by the 3D forest green biomass based on the image in SPOT5 could meet requirements. This represents an improvement over the conventional method because it not only provides a basis to evalue indices of Beijing urban greenings, but also introduces a new technique to assess 3D green biomass in other cities.     

Sequential Application of Ligand and Structure Based Modeling Approaches to Index Chemicals for Their hH4R Antagonism

The human histamine H₄ receptor (hH₄R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH₄R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH₄R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH₄R bioactivity. An application of the prediction model on external test set composed of more than 160 hH₄R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼4000 chemicals highly indexed as H₄R antagonists'' candidates. Next, a series of 3D models of hH₄R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH₄R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner.