Alteration of seed fatty acid composition by an ethyl methanesulfonate-induced mutation in Arabidopsis thaliana affecting diacylglycerol acyltransferase activity.

In characterizing the enzymes involved in the formation of very long-chain fatty acids (VLCFAs) in the Brassicaceae, we have generated a series of mutants of Arabidopsis thaliana that have reduced VLCFA content. Here we report the characterization of a seed lipid mutant, AS11, which, in comparison to wild type (WT), has reduced levels of 20:1 and 18:1 and accumulates 18:3 as the major fatty acid in triacylglycerols. Proportions of 18:2 remain similar to WT. Genetic analyses indicate that the fatty acid phenotype is caused by a semidominant mutation in a single nuclear gene, designated TAG1, located on chromosome 2. Biochemical analyses have shown that the AS11 phenotype is not due to a deficiency in the capacity to elongate 18:1 or to an increase in the relative delta 15 or delta 12 desaturase activities. Indeed, the ratio of desaturase/elongase activities measured in vitro is virtually identical in developing WT and AS11 seed homogenates. Rather, the fatty acid phenotype of AS11 is the result of reduced diacylglycerol acyltransferase activity throughout development, such that triacylglycerol biosynthesis is reduced. This leads to a reduction in 20:1 biosynthesis during seed development, leaving more 18:1 available for desaturation. Thus, we have demonstrated that changes to triacylglycerol biosynthesis can result in dramatic changes in fatty acid composition and, in particular, in the accumulation of VLCFAs in seed storage lipids.     

Chromosome-level genome assembly and characterization of Sophora Japonica

Sophora japonica is a medium-size deciduous tree belonging to Leguminosae family and famous for its high ecological, economic and medicinal value. Here, we reveal a draft genome of S. japonica, which was ∼511.49 Mb long (contig N50 size of 17.34 Mb) based on Illumina, Nanopore and Hi-C data. We reliably assembled 110 contigs into 14 chromosomes, representing 91.62% of the total genome, with an improved N50 size of 31.32 Mb based on Hi-C data. Further investigation identified 271.76 Mb (53.13%) of repetitive sequences and 31,000 protein-coding genes, of which 30,721 (99.1%) were functionally annotated. Phylogenetic analysis indicates that S. japonica separated from Arabidopsis thaliana and Glycine max ∼107.53 and 61.24 million years ago, respectively. We detected evidence of species-specific and common-legume whole-genome duplication events in S. japonica. We further found that multiple TF families (e.g. BBX and PAL) have expanded in S. japonica, which might have led to its enhanced tolerance to abiotic stress. In addition, S. japonica harbours more genes involved in the lignin and cellulose biosynthesis pathways than the other two species. Finally, population genomic analyses revealed no obvious differentiation among geographical groups and the effective population size continuously declined since 2 Ma. Our genomic data provide a powerful comparative framework to study the adaptation, evolution and active ingredients biosynthesis in S. japonica. More importantly, our high-quality S. japonica genome is important for elucidating the biosynthesis of its main bioactive components, and improving its production and/or processing.     

Modeling relapse in infectious diseases

An integro-differential equation is proposed to model a general relapse phenomenon in infectious diseases including herpes. The basic reproduction number R(0) for the model is identified and the threshold property of R(0) established. For the case of a constant relapse period (giving a delay differential equation), this is achieved by conducting a linear stability analysis of the model, and employing the Lyapunov-Razumikhin technique and monotone dynamical systems theory for global results. Numerical simulations, with parameters relevant for herpes, are presented to complement the theoretical results, and no evidence of sustained oscillatory solutions is found.     

Bioinformatic study of the relationship between protein regulation and sequence properties

Although protein expression and regulation have been intensively studied, a complete picture of its mechanisms is still to be drawn. Analysis of high-throughput quantitative proteomics data provides a way to better understand protein regulation. Here, we introduce a bioinformatic analysis method to correlate protein regulation with individual amino acid patterns. We compare the amino acid composition between groups of regulated and unregulated proteins and investigate the correlation between codon usage patterns and protein regulation levels in two Sulfolobus species in "biofilm vs planktonic" experiments. The identified amino acids can then be associated with the regulation of specific gene functions. Strikingly, our analysis shows that functional categories of regulated proteins with similar composition and codon usage pattern of specific amino acids behave similarly. This finding can contribute to a better understanding of protein and gene expression regulation and could find applications in gene optimisation.     

Differential Phosphorylation of Smad1 Integrates BMP and Neurotrophin Pathways through Erk/Dusp in Axon Development

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Sulfur‐Impregnated,Sandwich‐Type,Hybrid Carbon Nanosheets with Hierarchical Porous Structure for High‐Performance Lithium‐Sulfur Batteries

Sandwich‐type hybrid carbon nanosheets (SCNMM) consisting of graphene and micro/mesoporous carbon layer are fabricated via a double template method using graphene oxide as the shape‐directing agent and SiO₂ nanoparticles as the mesoporous guide. The polypyrrole synthesized in situ on the graphene oxide sheets is used as a carbon precursor. The micro/mesoporous strcutures of the SCNMM are created by a carbonization process followed by HF solution etching and KOH treatment. Sulfur is impregnated into the hybrid carbon nanosheets to generate S@SCNMM composites for the cathode materials in Li‐S secondary batteries. The microstructures and electrochemical performance of the as‐prepared samples are investigated in detail. The hybrid carbon nanosheets, which have a thickness of about 10–25 nm, high surface area of 1588 m² g^?1, and broad pore size distribution of 0.8–6.0 nm, are highly interconnected to form a 3D hierarchical structure. The S@SCNMM sample with the sulfur content of 74 wt% exhibits excellent electrochemical performance, including large reversible capacity, good cycling stability and coulombic efficiency, and good rate capability, which is believed to be due to the structure of hybrid carbon materials with hierarchical porous structure, which have large specific surface area and pore volume.