Eukaryotic cells have several quality control pathways that rely on translation to detect and degrade defective RNAs. Dom34 and Hbs1 are two proteins that are related to translation termination factors and are involved in no-go decay (NGD) and nonfunctional 18S ribosomal RNA (rRNA) decay (18S NRD) pathways that eliminate RNAs that cause strong ribosomal stalls. Here we present the structure of Hbs1 with and without GDP and a low-resolution model of the Dom34–Hbs1 complex. This complex mimics complexes of the elongation factor and transfer RNA or of the translation termination factors eRF1 and eRF3, supporting the idea that it binds to the ribosomal A-site. Scientists show that nucleotide binding by Hbs1 is essential for NGD and 18S NRD. Mutations in Hbs1 that disrupted the interaction between Dom34 and Hbs1 strongly impaired NGD but had almost no effect on 18S NRD. Hence, NGD and 18S NRD could be genetically uncoupled, suggesting that mRNA and rRNA in a stalled translation complex may not always be degraded simultaneously.
Wednesday, November 24, 2010
Tuesday, November 23, 2010
The repair of DNA double-strand breaks (DSBs) by homologous recombination is essential for genomic stability. The first step in this process is resection of 5′ strands to generate 3′ single-stranded DNA intermediates. Efficient resection in budding yeast requires the Mre11–Rad50–Xrs2 (MRX) complex and the Sae2 protein, although the role of MRX has been unclear because Mre11 paradoxically has 3′5′ exonuclease activity in vitro. Here scientists reconstitute resection with purified MRX, Sae2 and Exo1 proteins and show that degradation of the 5′ strand is catalyzed by Exo1 yet completely dependent on MRX and Sae2 when Exo1 levels are limiting. This stimulation is mainly caused by cooperative binding of DNA substrates by Exo1, MRX and Sae2. This work establishes the direct role of MRX and Sae2 in promoting the resection of 5′ strands in DNA DSB repair.
Polymodal, nociceptive sensory neurons are key cellular elements of the way animals sense aversive and painful stimuli. In Caenorhabditis elegans, the polymodal nociceptive ASH sensory neurons detect aversive stimuli and release glutamate to generate avoidance responses. They are thus useful models for the nociceptive neurons of mammals. While several molecules affecting signal generation and transduction in ASH have been identified, less is known about transmission of the signal from ASH to downstream neurons and about the molecules involved in its modulation.
Researchers discovered that the regulator of G protein signalling (RGS) protein, EGL-10, is required for appropriate avoidance responses to noxious stimuli sensed by ASH. As it does for other behaviours in which it is also involved, egl-10 interacts genetically with the Go/ialpha protein GOA-1, the Gqalpha protein EGL-30 and the RGS EAT-16. Genetic, behavioural and Ca2+ imaging analyses of ASH neurons in live animals demonstrate that, within ASH, EGL-10 and GOA-1 act downstream of stimulus-evoked signal transduction and of the main transduction channel OSM-9. EGL-30 instead appears to act upstream by regulating Ca2+ transients in response to aversive stimuli. Analysis of the delay in the avoidance response, of the frequency of spontaneous inversions and of the genetic interaction with the diacylglycerol kinase gene, dgk-1, indicate that EGL-10 and GOA-1 do not affect signal transduction and neuronal depolarization in response to aversive stimuli but act in ASH to modulate downstream transmission of the signal. The ASH polymodal nociceptive sensory neurons can be modulated not only in their capacity to detect stimuli but also in the efficiency with which they respond to them. The Galpha and RGS molecules studied in this work are conserved in evolution and, for each of them, mammalian orthologs can be identified. The discovery of their role in the modulation of signal transduction and signal transmission of nociceptors may help us to understand how pain is generated and how its control can go astray (such as chronic pain) and may suggest new pain control therapies.
Though the linkages between germline mutations of BRCA1 and hereditary breast cancer are well known, recent evidence suggests that altered BRCA1 transcription may also contribute to sporadic forms of breast cancer. Here we show that BRCA1expression is controlled by a dynamic equilibrium between transcriptional coactivators and co-repressors that govern histone acetylation and DNA accessibility at the BRCA1 promoter. Eviction of the transcriptional co-repressor and metabolic sensor, C terminal–binding protein (CtBP), has a central role in this regulation. Loss of CtBP from the BRCA1 promoter through estrogen induction, depletion by RNA interference or increased NAD+/NADH ratio leads to HDAC1 dismissal, elevated histone acetylation and increased BRCA1 transcription. The active control of chromatin marks, DNA accessibility and gene expression at theBRCA1 promoter by this 'metabolic switch' provides an important molecular link between caloric intake and tumor suppressor expression in mammary cells.
Saturday, November 20, 2010
Prediction of drug action in human cells is a major challenge in biomedical research. Additionally, there is strong interest in finding new applications for approved drugs and identifying potential side effects. Scientists present a computational strategy to predict mechanisms, risks and potential new domains of drug treatment on the basis of target profiles acquired through chemical proteomics. Functional protein-protein interaction networks that share one biological function are constructed and their crosstalk with the drug is scored regarding function disruption. They apply this procedure to the target profile of the second-generation BCR-ABL inhibitor bafetinib which is in development for the treatment of imatinib-resistant chronic myeloid leukemia. Beside the well known effect on apoptosis, they propose potential treatment of lung cancer and IGF1R expressing blast crisis.
Protein interaction data are accumulating rapidly and, although imperfect and incomplete, they provide a valuable global description of the complex interplay of proteins in a human cell. In parallel, modern proteomics technologies make it possible to measure in an unbiased manner the protein targets of a drug. Such data reveal multiple targets in a view that contrasts with a previously prevalent paradigm that drugs had single – or a very limited number of – targets. In this context of newly available systems level data and more precise and complete information about drug interactions, it is natural to try to determine the global perturbation exerted by a drug on a human cell to identify potential side effects and additional indications. They present a computational method that aims at making such predictions and apply it to bafetinib, a recently developed leukemia drug. Researchers show that meaningful predictions of additional applications to other cancers or resistant cases and likely side effects are obtained that are not straightforward to determine with existing algorithms. Our method has a strong potential to be applicable to other drugs.