Identification of a Nuclear Exosome Decay Pathway for Processed Transcripts.

The RNA exosome is fundamental for the degradation of RNA in eukaryotic nuclei. Substrate targeting is facilitated by its co-factor Mtr4p/hMTR4, which links to RNA-binding protein adaptors. One example is the trimeric human nuclear exosome targeting (NEXT) complex, which is composed of hMTR4, the Zn-finger protein ZCCHC8, and the RNA-binding factor RBM7. NEXT primarily targets early and unprocessed transcripts, which demands a rationale for how the nuclear exosome recognizes processed RNAs. Here, we describe the poly(A) tail exosome targeting (PAXT) connection, which comprises the ZFC3H1 Zn-knuckle protein as a central link between hMTR4 and the nuclear poly(A)-binding protein PABPN1. Individual depletion of ZFC3H1 and PABPN1 results in the accumulation of common transcripts that are generally both longer and more extensively polyadenylated than NEXT substrates. Importantly, ZFC3H1/PABPN1 and ZCCHC8/RBM7 contact hMTR4 in a mutually exclusive manner, revealing that the exosome targets nuclear transcripts of different maturation status by substituting its hMTR4-associating adaptors.

A systems approach delivers a functional microRNA catalog and expanded targets for seizure suppression in temporal lobe epilepsy.

Temporal lobe epilepsy is the most common drug-resistant form of epilepsy in adults. The reorganization of neural networks and the gene expression landscape underlying pathophysiologic network behavior in brain structures such as the hippocampus has been suggested to be controlled, in part, by microRNAs. To systematically assess their significance, we sequenced Argonaute-loaded microRNAs to define functionally engaged microRNAs in the hippocampus of three different animal models in two species and at six time points between the initial precipitating insult through to the establishment of chronic epilepsy. We then selected commonly up-regulated microRNAs for a functional in vivo therapeutic screen using oligonucleotide inhibitors. Argonaute sequencing generated 1.44 billion small RNA reads of which up to 82% were microRNAs, with over 400 unique microRNAs detected per model. Approximately half of the detected microRNAs were dysregulated in each epilepsy model. We prioritized commonly up-regulated microRNAs that were fully conserved in humans and designed custom antisense oligonucleotides for these candidate targets. Antiseizure phenotypes were observed upon knockdown of miR-10a-5p, miR-21a-5p, and miR-142a-5p and electrophysiological analyses indicated broad safety of this approach. Combined inhibition of these three microRNAs reduced spontaneous seizures in epileptic mice. Proteomic data, RNA sequencing, and pathway analysis on predicted and validated targets of these microRNAs implicated derepressed TGF-ß signaling as a shared seizure-modifying mechanism. Correspondingly, inhibition of TGF-ß signaling occluded the antiseizure effects of the antagomirs. Together, these results identify shared, dysregulated, and functionally active microRNAs during the pathogenesis of epilepsy which represent therapeutic antiseizure targets.

Quantitative proteomics by amino acid labeling in C. elegans.

We demonstrate labeling of Caenorhabditis elegans with heavy isotope-labeled lysine by feeding them with heavy isotope-labeled Escherichia coli. Using heavy isotope-labeled worms and quantitative proteomics methods, we identified several proteins that are regulated in response to loss or RNAi-mediated knockdown of the nuclear hormone receptor 49 in C. elegans. The combined use of quantitative proteomics and selective gene knockdown is a powerful tool for C. elegans biology.

BioServices: a common Python package to access biological Web Services programmatically.

MOTIVATION: Web interfaces provide access to numerous biological databases. Many can be accessed to in a programmatic way thanks to Web Services. Building applications that combine several of them would benefit from a single framework. RESULTS: BioServices is a comprehensive Python framework that provides programmatic access to major bioinformatics Web Services (e.g. KEGG, UniProt, BioModels, ChEMBLdb). Wrapping additional Web Services based either on Representational State Transfer or Simple Object Access Protocol/Web Services Description Language technologies is eased by the usage of object-oriented programming. AVAILABILITY AND IMPLEMENTATION: BioServices releases and documentation are available at http://pypi.python.org/pypi/bioservices under a GPL-v3 license.

Quantitative proteomics identifies unanticipated regulators of nitrogen- and glucose starvation.

The molecular mechanisms underlying how cells sense, respond, and adapt to alterations in nutrient availability have been studied extensively during the past years. While most of these studies have focused on the linear connections between signaling components, it is increasingly being recognized that signaling pathways are interlinked in molecular circuits and networks such that any metabolic perturbation will induce signaling-wide ripple effects. In the present study, we have used quantitative mass spectrometry (MS) to examine how the yeast Saccharomyces cerevisiae responds to nitrogen- or glucose starvation. We identify nearly 1400 phosphorylation sites of which more than 500 are regulated in a temporal manner in response to glucose- or nitrogen starvation. By bioinformatics and network analyses, we have identified the cyclin-dependent kinase (CDK) inhibitor Sic1, the Hsp90 co-chaperone Cdc37, and the Hsp90 isoform Hsp82 to putatively mediate some of the starvation responses. Consistently, quantitative expression analyses showed that Sic1, Cdc37, and Hsp82 are required for normal expression of nutrient-responsive genes. Collectively, we therefore propose that Sic1, Cdc37, and Hsp82 may orchestrate parts of the cellular starvation response by regulating transcription factor- and kinase activities.

TORC1 inhibits GSK3-mediated Elo2 phosphorylation to regulate very long chain fatty acid synthesis and autophagy.

Very long chain fatty acids (VLCFAs) are essential fatty acids with multiple functions, including ceramide synthesis. Although the components of the VLCFA biosynthetic machinery have been elucidated, how their activity is regulated to meet the cell's metabolic demand remains unknown. The goal of this study was to identify mechanisms that regulate the rate of VLCFA synthesis, and we discovered that the fatty acid elongase Elo2 is regulated by phosphorylation. Elo2 phosphorylation is induced upon inhibition of TORC1 and requires GSK3. Expression of nonphosphorylatable Elo2 profoundly alters the ceramide spectrum, reflecting aberrant VLCFA synthesis. Furthermore, VLCFA depletion results in constitutive activation of autophagy, which requires sphingoid base phosphorylation. This constitutive activation of autophagy diminishes cell survival, indicating that VLCFAs serve to dampen the amplitude of autophagy. Together, our data reveal a function for TORC1 and GSK3 in the regulation of VLCFA synthesis that has important implications for autophagy and cell homeostasis.

Global mapping of protein phosphorylation events identifies Ste20, Sch9 and the cell-cycle regulatory kinases Cdc28/Pho85 as mediators of fatty acid starvation responses in Saccharomyces cerevisiae.

Synthesis, degradation, and metabolism of fatty acids are strictly coordinated to meet the nutritional and energetic needs of cells and organisms. In the absence of exogenous fatty acids, proliferation and growth of the yeast Saccharomyces cerevisiae depends on endogenous synthesis of fatty acids, which is catalysed by fatty acid synthase. In the present study, we have used quantitative proteomics to examine the cellular response to inhibition of fatty acid synthesis in Saccharomyces cerevisiae. We have identified approximately 2000 phosphorylation sites of which more than 400 have been identified as being regulated in a temporal manner in response to inhibition of fatty acid synthesis by cerulenin. By bioinformatic analysis of these phosphorylation events, we have identified the cell cycle kinases Cdc28 and Pho85, the PAK kinase Ste20 as well as the protein kinase Sch9 as central mediators of the cellular response to inhibition of fatty acid synthesis.

Phosphoproteomic analysis of cells treated with longevity-related autophagy inducers.

Macroautophagy is a self-cannibalistic process that enables cells to adapt to various stresses and maintain energy homeostasis. Additionally, autophagy is an important route for turnover of misfolded proteins and damaged organelles, with important implications in cancer, neurodegenerative diseases and aging. Resveratrol and spermidine are able to induce autophagy by affecting deacetylases and acetylases, respectively, and have been found to extend the life-span of model organisms. With the aim to reveal the signaling networks involved in this drug-induced autophagic response, we quantified resveratrol and spermidine-induced changes in the phosphoproteome using SILAC and mass spectrometry. The data were subsequently analyzed using the NetworKIN algorithm to extract key features of the autophagy-responsive kinase-substrate network. We found that two distinct sequence motifs were highly responsive to resveratrol and spermidine and that key proteins modulating the acetylation, phosphorylation, methylation and ubiquitination status were affected by changes in phosphorylation during the autophagic response. Essential parts of the apoptotic signaling network were subjected to post-translational modifications during the drug-induced autophagy response, suggesting potential crosstalk and balancing between autophagy and apoptosis. Additionally, we predicted cellular signaling networks affected by resveratrol and spermidine using a computational framework. Altogether, these results point to a profound crosstalk between distinct networks of post-translational modifications and provide a resource for future analysis of autophagy and cell death.

Something worth dyeing for: molecular tools for the dissection of lipid metabolism in Caenorhabditis elegans.

The nematode Caenorhabditis elegans (C. elegans) has during the last decade emerged as an invaluable eukaryotic model organism to understand the metabolic and neuro-endocrine regulation of lipid accumulation. The fundamental pathways of food intake, digestion, metabolism, and signalling are evolutionary conserved between mammals and worms making C. elegans a genetically and metabolically extremely tractable model to decipher new regulatory mechanisms of lipid storage and to understand how nutritional and genetic perturbations can lead to obesity and other metabolic diseases. Besides providing an overview of the most important regulatory mechanisms of lipid accumulation in C. elegans, we also critically assess the current methodologies to monitor lipid storage and content as various methods differ in their applicability, consistency, and simplicity.