Eukaryotic Release Factor 3 Is Required for Multiple Turnovers of Peptide Release Catalysis by Eukaryotic Release Factor 1

Eukaryotic peptide release factor 3 (eRF3) is a conserved, essential gene in eukaryotes implicated in translation termination. We have systematically measured the contribution of eRF3 to the rates of peptide release with both saturating and limiting levels of eukaryotic release factor 1 (eRF1). Although eRF3 modestly stimulates the absolute rate of peptide release (∼5-fold), it strongly increases the rate of peptide release when eRF1 is limiting (>20-fold). This effect was generalizable across all stop codons and in a variety of contexts. Further investigation revealed that eRF1 remains associated with ribosomal complexes after peptide release and subunit dissociation and that eRF3 promotes the dissociation of eRF1 from these post-termination complexes. These data are consistent with models where eRF3 principally affects binding interactions between eRF1 and the ribosome, either prior to or subsequent to peptide release. A role for eRF3 as an escort for eRF1 into its fully accommodated state is easily reconciled with its close sequence similarity to the translational GTPase EFTu.     

Turning Cancer Stem Cells Inside Out: An Exploration of Glioma Stem Cell Signaling Pathways

Tumors are complex collections of heterogeneous cells with recruited vasculature, inflammatory cells, and stromal elements. Neoplastic cells frequently display a hierarchy in differentiation status. Recent studies suggest that brain tumors have a limited population of neoplastic cells called cancer stem cells with the capacity for sustained self-renewal and tumor propagation. Brain tumor stem cells contribute to therapeutic resistance and tumor angiogenesis. In this minireview, we summarize recent data regarding critical signaling pathways involved in brain tumor stem cell biology and discuss how targeting these molecules may contribute to the development of novel anti-glioma therapies.Cancers can be considered organ systems with aberrant activation of developmental and wound response pathways. Recent evidence suggests that within some tumors there is a cell subpopulation with the special capacity for sustained self-renewal and tumor propagation in vivo. Cells fulfilling these criteria were originally reported in acute myeloid leukemia (1), but similar populations were soon successively identified within various solid tumors (2). The proper terminology regarding these cells remains unsettled, with most groups using terms such as CSCs,² tumor-initiating/propagating cells, and stem-like cancer cells. Although CSCs are a source of controversy, the concept recognizes the well described heterogeneity of tumor cells. Many critics contest the hypothesis on the grounds of a potential stem cell origin, challenge of current markers, or CSC frequency, none of which are implicit requirements of the CSC hypothesis (3).Malignant gliomas are essentially universally lethal despite conventional therapy, with surgical resection and chemoradiation limited to palliation. Glioma CSCs were among the first solid tumor CSCs described (4) and remain one of the most widely used CSC models. Glioma CSCs share significant similarities with normal NSCs, including the expression of stem cell markers (CD133, Nestin, Musashi, and Sox2) and the capacity to differentiate into multiple lineages (5), but the overlap is incomplete. Notably, glioma CSCs are also highly resistant to chemoradiotherapies (5, 6), underscoring the importance of developing more efficient therapies against CSCs and prompting researchers to elucidate the molecular mechanisms regulating CSCs. Here, we summarize recent findings regarding the signaling pathways that are critical to glioma CSC biology.     

A multivariate twin study of hippocampal volume, self-esteem and well-being in middle-aged men

Self-esteem and well-being are important for successful aging, and some evidence suggests that self-esteem and well-being are associated with hippocampal volume, cognition and stress responsivity. Whereas most of this evidence is based on studies on older adults, we investigated self-esteem, well-being and hippocampal volume in 474 male middle-aged twins. Self-esteem was significantly positively correlated with hippocampal volume (0.09, P = 0.03 for left hippocampus, 0.10, P = 0.04 for right). Correlations for well-being were not significant (Ps > 0.05). There were strong phenotypic correlations between self-esteem and well-being (0.72, P < 0.001) and between left and right hippocampal volume (0.72, P < 0.001). In multivariate genetic analyses, a two-factor additive genetic and unique environmental (AE) model with well-being and self-esteem on one factor and left and right hippocampal volumes on the other factor fits the data better than Cholesky, independent pathway or common pathway models. The correlation between the two genetic factors was 0.12 (P = 0.03); the correlation between the environmental factors was 0.09 (P > 0.05). Our results indicate that largely different genetic and environmental factors underlie self-esteem and well-being on one hand and hippocampal volume on the other.     

FTICR-MS analysis of 14-3-3 isoform substrate selection

The 14-3-3s are a ubiquitous class of eukaryotic proteins that participate in a second regulatory step in many phosphorylation-based signal transduction systems. The Arabidopsis family of 14-3-3 proteins represents a rather large 14-3-3 gene family. The biological motive for such diversity within a single protein family is not yet completely understood. The work presented here utilizes 14-3-3 micro-affinity chromatography in conjunction with Fourier transform ion cyclotron resonance mass spectrometry to survey the substrate sequence selectivity of two Arabidopsis 14-3-3 isoforms that represent the two major subclasses of this protein family. A method was developed to compare the relative binding of eight synthetic phosphopeptide sequences. The degree to which each phosphopeptide bound to either isoform was assigned a relative value, defined here as the binding ratio. The method provided a simple means for visualizing differences in substrate sequence selection among different 14-3-3 isoforms. A reproducible preference for specific phosphopeptide sequences was measured for both isoforms. This binding preference was consistent among the two classes of isoforms, suggesting that any pressure for isoform selectivity must reside outside the central core that interacts with the phosphopeptide sequence of the client.     

Disrupted neural synchronization in toddlers with autism

Autism is often described as a disorder of neural synchronization. However, it is unknown how early in development synchronization abnormalities emerge and whether they are related to the development of early autistic behavioral symptoms. Here, we show that disrupted synchronization is evident in the spontaneous cortical activity of naturally sleeping toddlers with autism, but not in toddlers with language delay or typical development. Toddlers with autism exhibited significantly weaker interhemispheric synchronization (i.e., weak "functional connectivity" across the two hemispheres) in putative language areas. The strength of synchronization was positively correlated with verbal ability and negatively correlated with autism severity, and it enabled identification of the majority of autistic toddlers (72%) with high accuracy (84%). Disrupted cortical synchronization, therefore, appears to be a notable characteristic of autism neurophysiology that is evident at very early stages of autism development.     

Bayesian adaptive sequence alignment algorithms

The selection of a scoring matrix and gap penalty parameters continues to be an important problem in sequence alignment. We describe here an algorithm, the 'Bayes block aligner, which bypasses this requirement. Instead of requiring a fixed set of parameter settings, this algorithm returns the Bayesian posterior probability for the number of gaps and for the scoring matrices in any series of interest. Furthermore, instead of returning the single best alignment for the chosen parameter settings, this algorithm returns the posterior distribution of all alignments considering the full range of gapping and scoring matrices selected, weighing each in proportion to its probability based on the data. We compared the Bayes aligner with the popular Smith-Waterman algorithm with parameter settings from the literature which had been optimized for the identification of structural neighbors, and found that the Bayes aligner correctly identified more structural neighbors. In a detailed examination of the alignment of a pair of kinase and a pair of GTPase sequences, we illustrate the algorithm's potential to identify subsequences that are conserved to different degrees. In addition, this example shows that the Bayes aligner returns an alignment-free assessment of the distance between a pair of sequences.