Salubrinal, an inhibitor of protein synthesis, promotes deep slow wave sleep

Previous work showed that sleep is associated with increased brain protein synthesis and that arrest of protein synthesis facilitates sleep. Arrest of protein synthesis is induced during the endoplasmic reticulum (ER) stress response, through phosphorylation of eukaryotic initiation factor 2alpha (p-eIF2alpha). We tested a hypothesis that elevation of p-eIF2alpha would facilitate sleep. We studied the effects of intracerebroventricular infusion of salubrinal (Salub), which increases p-eIF2alpha by inhibiting its dephosphorylation. Salub increased deep slow wave sleep by 255%, while reducing active waking by 49%. Delta power within non-rapid eye movement (NREM) sleep was increased, while power in the sigma, beta, and gamma bands during NREM was reduced. We found that Salub increased expression of p-eIF2alpha in the basal forebrain (BF) area, a sleep-wake regulatory brain region. Therefore, we quantified the p-eIF2alpha-immunolabeled neurons in the BF area; Salub administration increased the number of p-eIF2alpha-expressing noncholinergic neurons in the caudal BF. In addition, Salub also increased the intensity of p-eIF2alpha expression in both cholinergic and noncholinergic neurons, but this was more widespread among the noncholinergic neurons. Our findings support a hypothesis that sleep is facilitated by signals associated with the ER stress response.     

Mito-GSAAC: mitochondria prediction using genetic ensemble classifier and split amino acid composition

Mitochondria are all-important organelles of eukaryotic cells since they are involved in processes associated with cellular mortality and human diseases. Therefore, trustworthy techniques are highly required for the identification of new mitochondrial proteins. We propose Mito-GSAAC system for prediction of mitochondrial proteins. The aim of this work is to investigate an effective feature extraction strategy and to develop an ensemble approach that can better exploit the advantages of this feature extraction strategy for mitochondria classification. We investigate four kinds of protein representations for prediction of mitochondrial proteins: amino acid composition, dipeptide composition, pseudo amino acid composition, and split amino acid composition (SAAC). Individual classifiers such as support vector machine (SVM), k-nearest neighbor, multilayer perceptron, random forest, AdaBoost, and bagging are first trained. An ensemble classifier is then built using genetic programming (GP) for evolving a complex but effective decision space from the individual decision spaces of the trained classifiers. The highest prediction performance for Jackknife test is 92.62% using GP-based ensemble classifier on SAAC features, which is the highest accuracy, reported so far on the Mitochondria dataset being used. While on the Malaria Parasite Mitochondria dataset, the highest accuracy is obtained by SVM using SAAC and it is further enhanced to 93.21% using GP-based ensemble. It is observed that SAAC has better discrimination power for mitochondria prediction over the rest of the feature extraction strategies. Thus, the improved prediction performance is largely due to the better capability of SAAC for discriminating between mitochondria and non-mitochondria proteins at the N and C terminus and the effective combination capability of GP. Mito-GSAAC can be accessed at . It is expected that the novel approach and the accompanied predictor will have a major impact to Molecular Cell Biology, Proteomics, Bioinformatics, System Biology, and Drug Development.     

Functional analysis of folate polyglutamylation and its essential role in plant metabolism and development

Cellular folates function as co-enzymes in one-carbon metabolism and are predominantly decorated with a polyglutamate tail that enhances co-enzyme affinity, subcellular compartmentation and stability. Polyglutamylation is catalysed by folylpolyglutamate synthetases (FPGSs) that are specified by three genes in Arabidopsis, FPGS1, 2 and 3, which reportedly encode plastidic, mitochondrial and cytosolic isoforms, respectively. A mutational approach was used to probe the functional importance of folate polyglutamylation in one-carbon metabolism and development. Biochemical analysis of single FPGS loss-of-function mutants established that folate polyglutamylation is essential for organellar and whole-plant folate homeostasis. However, polyglutamylated folates were still detectable, albeit at lower levels, in organelles isolated from the corresponding isozyme knockout lines, e.g. in plastids and mitochondria of the fpgs1 (plastidial) and fpgs2 (mitochondrial) mutants. This result is surprising given the purported single-compartment targeting of each FPGS isozyme. These results indicate redundancy in compartmentalised FPGS activity, which in turn explains the lack of anticipated phenotypic defects for the single FPGS mutants. In agreement with this hypothesis, fpgs1 fpgs2 double mutants were embryo-lethal, fpgs2 fpgs3 mutants exhibited seedling lethality, and fpgs1 fpgs3 mutants were dwarfed with reduced fertility. These phenotypic, metabolic and genetic observations are consistent with targeting of one or more FPGS isozymes to multiple organelles. These data confirm the importance of polyglutamylation in folate compartmentation, folate homeostasis and folate-dependent metabolic processes, including photorespiration, methionine and pantothenate biosynthesis.