Stereoscopic diagnosing of a filament-cavity flux rope system by tracing the path of a two-sided-loop jet

The fine magnetic structure is vitally important to understanding the formation, stabilization and eruption of solar filaments, but so far, it is still an open question yet to be resolved. Using stereoscopic observations taken by the Solar Dynamics Observatory and Solar TErrestrial RElations Obsevatory, we studied the generation mechanism of a two-sided-loop jet (TJ) and the ejection process of the jet plasma into the overlying filament-cavity system. We find that the generation of the two-sided-loop jet was due to the magnetic reconnection between an emerging flux loop and the overlying filament. The jet's two arms ejected along the filament axis during the initial stage. Then, the north arm bifurcated into two parts at about 50 Mm from the reconnection site. After the bifurcation, the two bifurcated parts were along the filament axis and the cavity which hosted the filament, respectively. By tracing the ejecting plasma flows of the TJ inside the filament, we not only measured that the magnetic twist stored in the filament was at least 5$\pi$ but also found that the fine magnetic structure of the filament-cavity flux rope system is in well agreement with the theoretical results of Magnetic flux rope models.Comment: 6 pages, 7 figures. Accepted by the MNRAS Letter

Genome-wide functional annotation and structural verification of metabolic ORFeome of Chlamydomonas reinhardtii

<p>Abstract</p> <p>Background</p> <p>Recent advances in the field of metabolic engineering have been expedited by the availability of genome sequences and metabolic modelling approaches. The complete sequencing of the <it>C. reinhardtii</it> genome has made this unicellular alga a good candidate for metabolic engineering studies; however, the annotation of the relevant genes has not been validated and the much-needed metabolic ORFeome is currently unavailable. We describe our efforts on the functional annotation of the ORF models released by the Joint Genome Institute (JGI), prediction of their subcellular localizations, and experimental verification of their structural annotation at the genome scale.</p> <p>Results</p> <p>We assigned enzymatic functions to the translated JGI ORF models of <it>C. reinhardtii</it> by reciprocal BLAST searches of the putative proteome against the UniProt and AraCyc enzyme databases. The best match for each translated ORF was identified and the EC numbers were transferred onto the ORF models. Enzymatic functional assignment was extended to the paralogs of the ORFs by clustering ORFs using BLASTCLUST.</p> <p>In total, we assigned 911 enzymatic functions, including 886 EC numbers, to 1,427 transcripts. We further annotated the enzymatic ORFs by prediction of their subcellular localization. The majority of the ORFs are predicted to be compartmentalized in the cytosol and chloroplast. We verified the structure of the metabolism-related ORF models by reverse transcription-PCR of the functionally annotated ORFs. Following amplification and cloning, we carried out 454FLX and Sanger sequencing of the ORFs. Based on alignment of the 454FLX reads to the ORF predicted sequences, we obtained more than 90% coverage for more than 80% of the ORFs. In total, 1,087 ORF models were verified by 454 and Sanger sequencing methods. We obtained expression evidence for 98% of the metabolic ORFs in the algal cells grown under constant light in the presence of acetate.</p> <p>Conclusions</p> <p>We functionally annotated approximately 1,400 JGI predicted metabolic ORFs that can facilitate the reconstruction and refinement of a genome-scale metabolic network. The unveiling of the metabolic potential of this organism, along with structural verification of the relevant ORFs, facilitates the selection of metabolic engineering targets with applications in bioenergy and biopharmaceuticals. The ORF clones are a resource for downstream studies.</p

SH3 interactome conserves general function over specific form

Src homology 3 (SH3) domains bind peptides to mediate protein–protein interactions that assemble and regulate dynamic biological processes. We surveyed the repertoire of SH3 binding specificity using peptide phage display in a metazoan, the worm Caenorhabditis elegans, and discovered that it structurally mirrors that of the budding yeast Saccharomyces cerevisiae. We then mapped the worm SH3 interactome using stringent yeast two-hybrid and compared it with the equivalent map for yeast. We found that the worm SH3 interactome resembles the analogous yeast network because it is significantly enriched for proteins with roles in endocytosis. Nevertheless, orthologous SH3 domain-mediated interactions are highly rewired. Our results suggest a model of network evolution where general function of the SH3 domain network is conserved over its specific form

Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism

Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases

A reference map of the human binary protein interactome.

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships(1,2). Here we present a human 'all-by-all' reference interactome map of human binary protein interactions, or 'HuRI'. With approximately 53,000 protein-protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome(3), transcriptome(4) and proteome(5) data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein-protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes

An economic analysis of oases environmental deterioration in Xinjiang autonomous region of China

新彊は豊富な農業と鉱山資源を持ち、中国においても綿花、食料、それに石油資源のー大供給基地となっている。しかし広大の新彊自治区は気候が乾燥のため、人間活動の殆どが天然、或いは人工アオシスに集中しているが、そのアオシスの生態環境は人口増加と過度の農業開発などにより、全体的に悪化しつづけている。本論文は、新彊自治区における自然条件とアオシスの生態悪化の現状を概観し、環境悪化をもたらした自然的・経済的・制度的な要因を分析したい