The SAUR gene family in coffee: genome-wide identification and gene expression analysis during somatic embryogenesis

Molecular Biology Reports - Small auxin-up RNA (SAUR) genes form a wide family supposedly involved in different physiological and developmental processes in plants such as leaf senescence, auxin...     

Novel pH-Stable Glycoside Hydrolase Family 3 β-Xylosidase from Talaromyces amestolkiae: an Enzyme Displaying Regioselective Transxylosylation

This paper reports on a novel β-xylosidase from the hemicellulolytic fungus Talaromyces amestolkiae. The expression of this enzyme, called BxTW1, could be induced by beechwood xylan and was purified as a glycoprotein from culture supernatants. We characterized the gene encoding this enzyme as an intronless gene belonging to the glycoside hydrolase gene family 3 (GH3). BxTW1 exhibited transxylosylation activity in a regioselective way. This feature would allow the synthesis of oligosaccharides or other compounds not available from natural sources, such as alkyl glycosides displaying antimicrobial or surfactant properties. Regioselective transxylosylation, an uncommon combination, makes the synthesis reproducible, which is desirable for its potential industrial application. BxTW1 showed high pH stability and Cu²⁺ tolerance. The enzyme displayed a pI of 7.6, a molecular mass around 200 kDa in its active dimeric form, and K_m and V_max values of 0.17 mM and 52.0 U/mg, respectively, using commercial p-nitrophenyl-β-d-xylopyranoside as the substrate. The catalytic efficiencies for the hydrolysis of xylooligosaccharides were remarkably high, making it suitable for different applications in food and bioenergy industries.     

Predicting chromatin organization using histone marks

Genome-wide mapping of three dimensional chromatin organization is an important yet technically challenging task. To aid experimental effort and to understand the determinants of long-range chromatin interactions, we have developed a computational model integrating Hi-C and histone mark ChIP-seq data to predict two important features of chromatin organization: chromatin interaction hubs and topologically associated domain (TAD) boundaries. Our model accurately and robustly predicts these features across datasets and cell types. Cell-type specific histone mark information is required for prediction of chromatin interaction hubs but not for TAD boundaries. Our predictions provide a useful guide for the exploration of chromatin organization.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0740-z) contains supplementary material, which is available to authorized users.     

N-Glycans mutations rule oligomeric assembly and functional expression of P2X3 receptor for extracellular ATP

N-Glycosylation affects the function of ion channels at the level of multisubunit assembly, protein trafficking, ligand binding and channel opening. Like the majority of membrane proteins, ionotropic P2X receptors for extracellular ATP are glycosylated in their extracellular moiety. Here, we used site-directed mutagenesis to the four predicted N-glycosylation sites of P2X(3) receptor (Asn(139), Asn(170), Asn(194) and Asn(290)) and performed comparative analysis of the role of N-glycans on protein stability, plasma membrane delivery, trimer formation and inward currents. We have found that in transiently transfected HEK293 cells, Asn(170) is apparently the most important site for receptor stability, since its mutation causes a primary loss in protein content and indirect failure in membrane expression, oligomeric association and inward current responses. Even stronger effects are obtained when mutating Thr(172) in the same glycosylation consensus. Asn(194) and Asn(290) are the most dispensable, since even their simultaneous mutation does not affect any tested receptor feature. All double mutants containing Asn(170) mutation or the Asn(139)/Asn(290) double mutant are instead almost unable to assemble into a functional trimeric structure. The main emerging finding is that the inability to assemble into trimers might account for the impaired function in P2X(3) mutants where residue Asn(170) is replaced. These results improve our knowledge about the role of N-glycosylation in proper folding and oligomeric association of P2X(3) receptor.     

Biliverdin reductase-A protein levels and activity in the brains of subjects with Alzheimer disease and mild cognitive impairment

Biliverdin reductase-A is a pleiotropic enzyme involved not only in the reduction of biliverdin-IX-alpha into bilirubin-IX-alpha, but also in the regulation of glucose metabolism and cell growth secondary to its serine/threonine/tyrosine kinase activity. Together with heme oxygenase, whose metabolic role is to degrade heme into biliverdin-IX-alpha, it forms a powerful system involved in the cell stress response during neurodegenerative disorders. In this paper, an up-regulation of the biliverdin reductase-A protein levels was found in the hippocampus of the subjects with Alzheimer disease and arguably its earliest form, mild cognitive impairment. Moreover a significant reduction in the phosphorylation of serine, threonine and tyrosine residues of biliverdin reductase-A was found, and this was paralleled by a marked reduction in its reductase activity. Interestingly, the levels of both total and phosphorylated biliverdin reductase-A were unchanged as well as its enzymatic activity in the cerebella. These results demonstrated a dichotomy between biliverdin reductase-A protein levels and activity in the hippocampus of subjects affected by Alzheimer disease and mild cognitive impairment, and this effect likely is attributable to a reduction in the phosphorylation of serine, threonine and tyrosine residues of biliverdin reductase-A. Consequently, not just the increased levels of biliverdin reductase-A, but also its changed activity and phosphorylation state, should be taken into account when considering potential biomarkers for Alzheimer disease and mild cognitive impairment.     

Effect of impeller type and stirring frequency on the behavior of an AnSBBR in the treatment of low-strength wastewater

The influence of impeller type and stirring frequency on the performance of a mechanically stirred anaerobic sequencing batch reactor containing immobilized biomass on an inert support (AnSBBR - Anaerobic Sequencing Batch Biofilm Reactor) was evaluated. The biomass was immobilized on polyurethane foam cubes placed in a stainless-steel basket inside a glass cylinder. Each 8-h batch run consisted of three stages: feed (10 min), reaction (460 min) and discharge (10 min) at 30 °C. Experiments were performed with four impeller types, i.e., helical, flat-blade, inclined-blade and curved-blade turbines, at stirring frequencies ranging from 100 to 1100 rpm. Synthetic wastewater was used in all experiments with an organic-matter concentration of 530 ± 37 mg/L measured as chemical oxygen demand (COD). The reactor achieved an organic-matter removal efficiency of around 87% under all investigated conditions. Analysis of the four impeller types and the investigated stirring frequencies showed that mass transfer in the liquid phase was affected not only by the applied stirring frequency but also by the agitation mode imposed by each impeller type. The best reactor performance at all stirring frequencies was obtained when agitation was provided by the flat-blade turbine impeller.     

Inter-limb coordination, strength, jump, and sprint performances following a youth men's basketball game

This study aimed to verify whether basketball players are able to maintain strength (handgrip), jump (countermovement jump [CMJ]), sprint (10 m and 10 m bouncing the ball [10 mBB]), and interlimb coordination (i.e., synchronized hand and foot flexions and extensions at 80, 120, and 180 bpm) performances at the end of their game. Ten young (age 15.7 ± 0.2 years) male basketball players volunteered for this study. During the friendly game, heart rate (HR), rate of perceived exertion (RPE), and rate of muscle pain (RMP) were assessed to evaluate the exercise intensity. Overall, players spent 80% of the time playing at intensities higher than 85% HRmax. Main effects (p < 0.05) for game periods emerged for HR and the number of players involved in a single action, with lower occurrence of maximal efforts and higher involvement of teammates after the first 2 periods. At the end of the game, players reported high (p < 0.05) RPE (15.7 ± 2.4) and RMP (5.2 ± 2.3) values; decreased (p < 0.05) sprint capabilities (10 m: pre = 1.79 ± 0.09 seconds, post = 1.84 ± 0.08 seconds; 10 mBB: pre = 1.81 ± 0.11 seconds, post = 1.96 ± 0.08 seconds); increased (p < 0.05) interlimb coordination at 180 bpm (pre = 33.3 ± 20.2 seconds, post = 43.9 ± 19.8 seconds); and maintained jump (pre = 35.2 ± 5.2 cm, post = 35.7 ± 5.2 cm), handgrip (pre = 437 ± 73 N, post = 427 ± 55 N), and coordinative performances at lower frequencies of executions (80 bpm: pre = 59.7 ± 1.3 seconds, post = 60.0 ± 0.0 seconds; 120 bpm: pre = 54.7 ± 12.3 seconds, post = 57.3 ± 6.7 seconds). These findings indicate that the heavy load of the game exerts beneficial effects on the efficiency of executive and attentive control functions involved in complex motor behaviors. Coaches should structure training sessions that couple intense physical exercises with complex coordination tasks to improve the attentional capabilities of the players.     

Identification of metabolic network models from incomplete high-throughput datasets

MOTIVATION: High-throughput measurement techniques for metabolism and gene expression provide a wealth of information for the identification of metabolic network models. Yet, missing observations scattered over the dataset restrict the number of effectively available datapoints and make classical regression techniques inaccurate or inapplicable. Thorough exploitation of the data by identification techniques that explicitly cope with missing observations is therefore of major importance. RESULTS: We develop a maximum-likelihood approach for the estimation of unknown parameters of metabolic network models that relies on the integration of statistical priors to compensate for the missing data. In the context of the linlog metabolic modeling framework, we implement the identification method by an Expectation-Maximization (EM) algorithm and by a simpler direct numerical optimization method. We evaluate performance of our methods by comparison to existing approaches, and show that our EM method provides the best results over a variety of simulated scenarios. We then apply the EM algorithm to a real problem, the identification of a model for the Escherichia coli central carbon metabolism, based on challenging experimental data from the literature. This leads to promising results and allows us to highlight critical identification issues.