Phosphorylation of an actin.tropomyosin.troponin complex from human skeletal muscle.

A human skeletal actin.tropomyosin.troponin complex was phosphorylated in the presence of [gamma-32 P]ATP, Mg2+, adenosine 3':5'-monophosphate (cyclic AMP) and cyclic AMP-dependent protein kinase (protein kinase). Phosphorylation was not observed when the actin complex was incubated in the absence of protein kinase or 1 microM cyclic AMP. In the presence of 10(-7) M Ca2+ and protein kinase 0.1 mole of [32P]phosphate per 196 000 g of protein was incorporated. This was two-fold higher than the [32P]phosphate content of a rabbit skeletal actin complex but two-fold lower than that of a bovine cardiac actin complex. At high Ca2+, 5.10(-5) M, little change in the phosphorylation of a human skeletal actin complex occurred. Phosphoserine and phosphothreonine were identified in the [32P]phosphorylated actin complex. Polyacrylamide gel electrophoresis in sodium dodecyl sulfate showed that 60% of the label was associated with the tropomyosin binding component of troponin. The inhibitory component of troponin contained 16% of the bound [32P]phosphate. Increasing the Ca2+ concentration did not significantly decrease the [32P]phosphate content of the phosphorylated proteins in the actin complex. No change in the distribution of phosphoserine or phosphothreonine was observed. Half maximal calcium activation of the ATPase activity of reconstitute human skeletal actomyosin made with the [32P] phosphorylated human skeletal actin complex was the same as a reconstituted actomyosin made with an actin complex incubated in the absence of protein kinase at low or high Ca2+.     

Conformational change of syntaxin linker region induced by Munc13s initiates SNARE complex formation in synaptic exocytosis

The soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) protein syntaxin-1 adopts a closed conformation when bound to Munc18-1, preventing binding to synaptobrevin-2 and SNAP-25 to form the ternary SNARE complex. Although it is known that the MUN domain of Munc13-1 catalyzes the transition from the Munc18-1/syntaxin-1 complex to the SNARE complex, the molecular mechanism is unclear. Here, we identified two conserved residues (R151, I155) in the syntaxin-1 linker region as key sites for the MUN domain interaction. This interaction is essential for SNARE complex formation in vitro and synaptic vesicle priming in neuronal cultures. Moreover, this interaction is important for a tripartite Munc18-1/syntaxin-1/MUN complex, in which syntaxin-1 still adopts a closed conformation tightly bound to Munc18-1, whereas the syntaxin-1 linker region changes its conformation, similar to that of the LE mutant of syntaxin-1 when bound to Munc18-1. We suggest that the conformational change of the syntaxin-1 linker region induced by Munc13-1 initiates ternary SNARE complex formation in the neuronal system.     

Auto-adaptive Alpha Allocation: A Strategy to Mitigate Risk on Study Assumptions

In some clinical development programs, there are potential biomarkers with promising but uncertain predictive effect, while the probability of success in the overall population cannot be readily dismissed. It is risky to focus only on the overall population, or just the biomarker subpopulation. In 2009, Chen and Beckman proposed a Bayesian decision framework to optimize the type I error rate (alpha) allocation in a Phase III clinical study with possible predictive subset effect. The utilization of internal data in this framework is of particular interest because it provides an opportunity to mitigate the potential risk of misspecified study assumptions using an auto-adaptive strategy. In this paper, we examine this auto-adaptive strategy in detail through extensive numerical case studies and provide guidance on the appropriate use of partial current trial (internal) data in this data-driven optimization framework. We show that internal data can be used to inform the alpha allocation to hypothesis testing in the overall population and the subgroup. The resulting adaptive testing strategy is robust with respect to the uncertainty in the predictive subgroup effect and biomarker prevalence.     

Development of genome-wide insertion and deletion markers for maize,based on next-generation sequencing data

Background

Insertions and deletions (indels) are the most abundant form of structural variation in all genomes. Indels have been increasingly recognized as an important source of molecular markers due to high-density occurrence, cost-effectiveness, and ease of genotyping. Coupled with developments in bioinformatics, next-generation sequencing (NGS) platforms enable the discovery of millions of indel polymorphisms by comparing the whole genome sequences of individuals within a species.

Results

A total of 1,973,746 unique indels were identified in 345 maize genomes, with an overall density of 958.79 indels/Mbp, and an average allele number of 2.76, ranging from 2 to 107. There were 264,214 indels with polymorphism information content (PIC) values greater than or equal to 0.5, accounting for 13.39 % of overall indels. Of these highly polymorphic indels, we designed primer pairs for 83,481 and 29,403 indels with major allele differences (i.e. the size difference between the most and second most frequent alleles) greater than or equal to 3 and 8 bp, respectively, based on the differing resolution capabilities of gel electrophoresis. The accuracy of our indel markers was experimentally validated, and among 100 indel markers, average accuracy was approximately 90 %. In addition, we also validated the polymorphism of the indel markers. Of 100 highly polymorphic indel markers, all had polymorphisms with average PIC values of 0.54.

Conclusions

The maize genome is rich in indel polymorphisms. Intriguingly, the level of polymorphism in genic regions of the maize genome was higher than that in intergenic regions. The polymorphic indel markers developed from this study may enhance the efficiency of genetic research and marker-assisted breeding in maize.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1797-5) contains supplementary material, which is available to authorized users.     

Composition and dynamics of microbial community in a zeolite biofilter-membrane bioreactor treating coking wastewater

In this study, a lab-scale anaerobic/anoxic/zeolite biofilter-membrane bioreactor (A₁/A₂/ZB-MBR) was designed to treat coking wastewater. The 454 pyrosequencing was used to obtain the composition and dynamics of microbial community about the treatment system. The results showed that the system yielded stable effluent chemical oxidation demand (158.5?±?21.8 mg/L) and ammonia (8.56?±?7.30 mg/L), but fluctuant total nitrogen (31.4–165.1 mg/L) concentrations. In addition, 66,256 16S rRNA gene sequences were obtained from A₂ and ZB-MBR, and the microbial diversity and richness for five samples were determined. Although community compositions in the five samples were quite different, bacteria assigned to phylum Proteobacteria and class Flavobacteria commonly existed and dominated the microbial populations. The pyrosequencing analysis revealed that the microbial community shifted in the ZB-MBR with the presence of zeolite. Some taxa began to appear in ZB-MBR and contributed to the system performance. Additionally, Nitrosomonas and Nitrobacter gradually became the dominant ammonia-oxidizing bacteria and nitrite-oxidizing bacteria during the operation, respectively, which are favorable for the stabilized ammonia removal. Our results proved that the ZB-MBR is an alternative technique for treating coking wastewater.