The antioxidative function of eicosapentaenoic acid in a marine bacterium, Shewanella marinintestina IK-1

When the eicosapentaenoic acid (EPA)-deficient mutant strain IK-1Delta8 of the marine EPA-producing Shewanella marinintestina IK-1 was treated with various concentrations of hydrogen peroxide (H(2)O(2)), its colony-forming ability decreased more than that of the wild type. Protein carbonylation, induced by treating cells with 0.01 mM H(2)O(2) under bacteriostatic conditions, was enhanced only in cells lacking EPA. The amount of cells recovered from the cultures was decreased more significantly by the presence of H(2)O(2) for cells lacking EPA than for those producing EPA. Treatment of the cells with 0.1 mM H(2)O(2) resulted in much lower intracellular concentrations of H(2)O(2) being consistently detected in cells with EPA than in those without EPA. These results suggest that cellular EPA can directly protect cells against oxidative damage by shielding the entry of exogenously added H(2)O(2) in S. marinintestina IK-1.     

The sex-determining locus in the tiger pufferfish, Takifugu rubripes

The tiger pufferfish (fugu), Takifugu rubripes, is a model fish that has had its genome entirely sequenced. By performing genomewide linkage analyses, we show that the sex of fugu is determined by a single chromosomal region on linkage group 19 in an XX-XY system.     

Probabilistic protein function prediction from heterogeneous genome-wide data

Dramatic improvements in high throughput sequencing technologies have led to a staggering growth in the number of predicted genes. However, a large fraction of these newly discovered genes do not have a functional assignment. Fortunately, a variety of novel high-throughput genome-wide functional screening technologies provide important clues that shed light on gene function. The integration of heterogeneous data to predict protein function has been shown to improve the accuracy of automated gene annotation systems. In this paper, we propose and evaluate a probabilistic approach for protein function prediction that integrates protein-protein interaction (PPI) data, gene expression data, protein motif information, mutant phenotype data, and protein localization data. First, functional linkage graphs are constructed from PPI data and gene expression data, in which an edge between nodes (proteins) represents evidence for functional similarity. The assumption here is that graph neighbors are more likely to share protein function, compared to proteins that are not neighbors. The functional linkage graph model is then used in concert with protein domain, mutant phenotype and protein localization data to produce a functional prediction. Our method is applied to the functional prediction of Saccharomyces cerevisiae genes, using Gene Ontology (GO) terms as the basis of our annotation. In a cross validation study we show that the integrated model increases recall by 18%, compared to using PPI data alone at the 50% precision. We also show that the integrated predictor is significantly better than each individual predictor. However, the observed improvement vs. PPI depends on both the new source of data and the functional category to be predicted. Surprisingly, in some contexts integration hurts overall prediction accuracy. Lastly, we provide a comprehensive assignment of putative GO terms to 463 proteins that currently have no assigned function.     

Sensitive determination of aspirin and its metabolites in plasma by LC-UV using on-line solid-phase extraction with methylcellulose-immobilized anion-exchange restricted access media

We describe a sensitive determination of aspirin (ASA) and its three metabolites (salicylic acid [SA], 2,3-dihydroxybenzoic acid [2,3-DHBA], and 2,5-dihydroxybenzoic acid [gentisic acid (GA)]) in rat plasma. Analysis was carried out by on-line solid-phase extraction (SPE) using a methylcellulose-immobilized-strong anion-exchanger (MC-SAX), followed by liquid chromatography (LC) coupled with UV detection. The lower limits of quantitation for ASA and SA were 60 ng/mL in 100 microL of plasma, respectively. This method was validated with respect to intra- and inter-day precision, accuracy, and linearity up to concentrations of 20,000 ng/mL for ASA, SA, 2,3-DHBA and gentisic acid, respectively. The method was successfully applied to an analysis of the pharmacokinetics of ASA and SA in rats.     

Roles of the Akt/mTOR/p70S6K and ERK1/2 signaling pathways in curcumin-induced autophagy

Curcumin has a potent anticancer effect and is a promising new therapeutic strategy. We previously demonstrated that curcumin induced non-apoptotic autophagic cell death in malignant glioma cells in vitro and in vivo. This compound inhibited the Akt/mammalian target of rapamycin/p70 ribosomal protein S6 kinase pathway and activated the extracellular signal-regulated kinases 1/2 thereby inducing autophagy. Interestingly, activation of the first pathway inhibited curcumin-induced autophagy and cytotoxicity, whereas inhibition of the latter pathway inhibited curcumin-induced autophagy and induced apoptosis, thus augmenting the cytotoxicity of curcumin. These results imply that these two autophagic pathways have opposite effects on curcumin's cytotoxicity. However, inhibition of nuclear factor kappaB, which is the main target of curcumin for its anticancer effect, was not observed in malignant glioma cells. These results suggest that autophagy but not nuclear factor kappaB plays a central role in curcumin anticancer therapy and warrant further investigation toward application in patients with malignant gliomas. Here, we discuss the therapeutic role of two autophagic pathways influenced by curcumin.     

Exploring patterns of fine root morphological,chemical, and anatomical traits of 12 tree species from visible–near-infrared spectral reflectance

Plant and Soil - Root morphological response to localised phosphorus (P) application plays a crucial role in P acquisition. However, detailed knowledge of when and where roots respond to P patch...     

Similarity-Based Analysis of Allele Frequency Distribution among Multiple Populations Identifies Adaptive Genomic Structural Variants

Structural variants have a considerable impact on human genomic diversity. However, their evolutionary history remains mostly unexplored. Here, we developed a new method to identify potentially adaptive structural variants based on a similarity-based analysis that incorporates genotype frequency data from 26 populations simultaneously. Using this method, we analyzed 57,629 structural variants and identified 576 structural variants that show unusual population differentiation. Of these putatively adaptive structural variants, we further showed that 24 variants are multiallelic and overlap with coding sequences, and 20 variants are significantly associated with GWAS traits. Closer inspection of the haplotypic variation associated with these putatively adaptive and functional structural variants reveals deviations from neutral expectations due to: 1) population differentiation of rapidly evolving multiallelic variants, 2) incomplete sweeps, and 3) recent population-specific negative selection. Overall, our study provides new methodological insights, documents hundreds of putatively adaptive variants, and introduces evolutionary models that may better explain the complex evolution of structural variants.     

Fifteen compelling open questions in plant cell biology

As scientists, we are at least as excited about the open questions—the things we do not know—as the discoveries. Here, we asked 15 experts to describe the most compelling open questions in plant cell biology. These are their questions: How are organelle identity, domains, and boundaries maintained under the continuous flux of vesicle trafficking and membrane remodeling? Is the plant cortical microtubule cytoskeleton a mechanosensory apparatus? How are the cellular pathways of cell wall synthesis, assembly, modification, and integrity sensing linked in plants? Why do plasmodesmata open and close? Is there retrograde signaling from vacuoles to the nucleus? How do root cells accommodate fungal endosymbionts? What is the role of cell edges in plant morphogenesis? How is the cell division site determined? What are the emergent effects of polyploidy on the biology of the cell, and how are any such “rules” conditioned by cell type? Can mechanical forces trigger new cell fates in plants? How does a single differentiated somatic cell reprogram and gain pluripotency? How does polarity develop de-novo in isolated plant cells? What is the spectrum of cellular functions for membraneless organelles and intrinsically disordered proteins? How do plants deal with internal noise? How does order emerge in cells and propagate to organs and organisms from complex dynamical processes? We hope you find the discussions of these questions thought provoking and inspiring.

We asked 15 experts to address what they consider to be the most compelling open questions in plant cell biology and these are their questions.     

Endogenously released DOPA is a causal factor for glutamate release and resultant delayed neuronal cell death by transient ischemia in rat striata

Glutamate is implicated in neuronal cell death. Exogenously applied DOPA by itself releases neuronal glutamate and causes neuronal cell death in in vitro striatal systems. Herein, we attempt to clarify whether endogenous DOPA is released by 10 min transient ischemia due to four-vessel occlusion during rat striatal microdialysis and, further, whether DOPA, when released, functions to cause glutamate release and resultant delayed neuronal cell death. Ischemia increased extracellular DOPA, dopamine, and glutamate, and elicited neuronal cell death 96 h after ischemic insult. Inhibition of striatal L-aromatic amino acid decarboxylase 10 min before ischemia increased markedly basal DOPA, tripled glutamate release with a tendency of decrease in dopamine release by ischemia, and exaggerated neuronal cell death. Intrastriatal perfusion of 10-30 nM DOPA cyclohexyl ester, a competitive DOPA antagonist, 10 min before ischemia, concentration-dependently decreased glutamate release without modification of dopamine release by ischemia. At 100 nM, the antagonist elicited a slight ceiling effect on decreases in glutamate release by ischemia and protected neurons from cell death. Glutamate was released concentration-dependently by intrastriatal perfusion of 0.3-1 mM DOPA and stereoselectively by 0.6 mM DOPA. The antagonist elicited no hypothermia during and after ischemia. Endogenously released DOPA is an upstream causal factor for glutamate release and resultant delayed neuronal cell death by brain ischemia in rat striata. DOPA antagonist has a neuroprotective action.