208 research outputs found

    Complex sequencing rules of birdsong can be explained by simple hidden Markov processes

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    Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical propertiesof the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable sequences, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. This property is shared with other complex sequential behaviors. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model (GMM)), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex sequences with higher-order dependencies

    Anti-prion activity of an RNA aptamer and its structural basis.

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    Prion proteins (PrPs) cause prion diseases, such as bovine spongiform encephalopathy. The conversion of a normal cellular form (PrP(C)) of PrP into an abnormal form (PrP(Sc)) is thought to be associated with the pathogenesis. An RNA aptamer that tightly binds to and stabilizes PrP(C) is expected to block this conversion and to thereby prevent prion diseases. Here, we show that an RNA aptamer comprising only 12 residues, r(GGAGGAGGAGGA) (R12), reduces the PrP(Sc) level in mouse neuronal cells persistently infected with the transmissible spongiform encephalopathy agent. Nuclear magnetic resonance analysis revealed that R12, folded into a unique quadruplex structure, forms a dimer and that each monomer simultaneously binds to two portions of the N-terminal half of PrP(C), resulting in tight binding. Electrostatic and stacking interactions contribute to the affinity of each portion. Our results demonstrate the therapeutic potential of an RNA aptamer as to prion diseases

    Topoisomer Differentiation of Molecular Knots by FTICR MS: Lessons from Class II Lasso Peptides

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    Lasso peptides constitute a class of bioactive peptides sharing a knotted structure where the C-terminal tail of the peptide is threaded through and trapped within an N-terminalmacrolactamring. The structural characterization of lasso structures and differentiation from their unthreaded topoisomers is not trivial and generally requires the use of complementary biochemical and spectroscopic methods. Here we investigated two antimicrobial peptides belonging to the class II lasso peptide family and their corresponding unthreaded topoisomers: microcin J25 (MccJ25), which is known to yield two-peptide product ions specific of the lasso structure under collisioninduced dissociation (CID), and capistruin, for which CID does not permit to unambiguously assign the lasso structure. The two pairs of topoisomers were analyzed by electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FTICR MS) upon CID, infrared multiple photon dissociation (IRMPD), and electron capture dissociation (ECD). CID and ECDspectra clearly permitted to differentiate MccJ25 from its non-lasso topoisomer MccJ25-Icm, while for capistruin, only ECD was informative and showed different extent of hydrogen migration (formation of c\bullet/z from c/z\bullet) for the threaded and unthreaded topoisomers. The ECD spectra of the triply-charged MccJ25 and MccJ25-lcm showed a series of radical b-type product ions {\eth}b0In{\TH}. We proposed that these ions are specific of cyclic-branched peptides and result from a dual c/z\bullet and y/b dissociation, in the ring and in the tail, respectively. This work shows the potentiality of ECD for structural characterization of peptide topoisomers, as well as the effect of conformation on hydrogen migration subsequent to electron capture

    Functional and structural characterization of the mammalian TREX-2 complex that links transcription with nuclear messenger RNA export

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    Export of messenger RNA (mRNA) from the nucleus to the cytoplasm is a critical step in the gene expression pathway of eukaryotic cells. Here, we report the functional and structural characterization of the mammalian TREX-2 complex and show how it links transcription/processing with nuclear mRNA export. Mammalian TREX-2 is based on a germinal-centre associated nuclear protein (GANP) scaffold to which ENY2, PCID2 and centrins bind and depletion of any of these components inhibits mRNA export. The crystal structure of the GANP:ENY2 complex shows that two ENY2 chains interact directly with GANP, but they have different orientations from those observed on yeast Sac3. GANP is required to recruit ENY2 to nuclear pore complexes (NPCs), but ENY2 is not necessary to recruit GANP, which requires both its CID and MCM3AP domains, together with nucleoporin Nup153. GANP and ENY2 associate with RNA polymerase II and inhibition of mRNA processing redistributes GANP from NPCs into nuclear foci indicating that mammalian TREX-2 is associated with transcription. Thus, we implicate TREX-2 as an integral component of the mammalian mRNA export machinery where it links transcription and nuclear export by facilitating the transfer of mature mRNPs from the nuclear interior to NPCs

    Identification of claudin-4 as a marker highly overexpressed in both primary and metastatic prostate cancer

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    In the quest for markers of expression and progression for prostate cancer (PCa), the majority of studies have focussed on molecular data exclusively from primary tumours. Although expression in metastases is inferred, a lack of correlation with secondary tumours potentially limits their applicability diagnostically and therapeutically. Molecular targets were identified by examining expression profiles of prostate cell lines using cDNA microarrays. Those genes identified were verified on PCa cell lines and tumour samples from both primary and secondary tumours using real-time RT–PCR, western blotting and immunohistochemistry. Claudin-4, coding for an integral membrane cell-junction protein, was the most significantly (P<0.00001) upregulated marker in both primary and metastatic tumour specimens compared with benign prostatic hyperplasia at both RNA and protein levels. In primary tumours, claudin-4 was more highly expressed in lower grade (Gleason 6) lesions than in higher grade (Gleason ⩾7) cancers. Expression was prominent throughout metastases from a variety of secondary sites in fresh-frozen and formalin-fixed specimens from both androgen-intact and androgen-suppressed patients. As a result of its prominent expression in both primary and secondary PCas, together with its established role as a receptor for Clostridium perfringens enterotoxin, claudin-4 may be useful as a potential marker and therapeutic target for PCa metastases

    Post-Transcriptional Trafficking and Regulation of Neuronal Gene Expression

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    Intracellular messenger RNA (mRNA) traffic and translation must be highly regulated, both temporally and spatially, within eukaryotic cells to support the complex functional partitioning. This capacity is essential in neurons because it provides a mechanism for rapid input-restricted activity-dependent protein synthesis in individual dendritic spines. While this feature is thought to be important for synaptic plasticity, the structures and mechanisms that support this capability are largely unknown. Certainly specialized RNA binding proteins and binding elements in the 3′ untranslated region (UTR) of translationally regulated mRNA are important, but the subtlety and complexity of this system suggests that an intermediate “specificity” component is also involved. Small non-coding microRNA (miRNA) are essential for CNS development and may fulfill this role by acting as the guide strand for mediating complex patterns of post-transcriptional regulation. In this review we examine post-synaptic gene regulation, mRNA trafficking and the emerging role of post-transcriptional gene silencing in synaptic plasticity

    A reafferent and feed-forward model of song syntax generation in the Bengalese finch

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    Adult Bengalese finches generate a variable song that obeys a distinct and individual syntax. The syntax is gradually lost over a period of days after deafening and is recovered when hearing is restored. We present a spiking neuronal network model of the song syntax generation and its loss, based on the assumption that the syntax is stored in reafferent connections from the auditory to the motor control area. Propagating synfire activity in the HVC codes for individual syllables of the song and priming signals from the auditory network reduce the competition between syllables to allow only those transitions that are permitted by the syntax. Both imprinting of song syntax within HVC and the interaction of the reafferent signal with an efference copy of the motor command are sufficient to explain the gradual loss of syntax in the absence of auditory feedback. The model also reproduces for the first time experimental findings on the influence of altered auditory feedback on the song syntax generation, and predicts song- and species-specific low frequency components in the LFP. This study illustrates how sequential compositionality following a defined syntax can be realized in networks of spiking neurons

    Uncovering spatial topology represented by rat hippocampal population neuronal codes

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    Hippocampal population codes play an important role in representation of spatial environment and spatial navigation. Uncovering the internal representation of hippocampal population codes will help understand neural mechanisms of the hippocampus. For instance, uncovering the patterns represented by rat hippocampus (CA1) pyramidal cells during periods of either navigation or sleep has been an active research topic over the past decades. However, previous approaches to analyze or decode firing patterns of population neurons all assume the knowledge of the place fields, which are estimated from training data a priori. The question still remains unclear how can we extract information from population neuronal responses either without a priori knowledge or in the presence of finite sampling constraint. Finding the answer to this question would leverage our ability to examine the population neuronal codes under different experimental conditions. Using rat hippocampus as a model system, we attempt to uncover the hidden “spatial topology” represented by the hippocampal population codes. We develop a hidden Markov model (HMM) and a variational Bayesian (VB) inference algorithm to achieve this computational goal, and we apply the analysis to extensive simulation and experimental data. Our empirical results show promising direction for discovering structural patterns of ensemble spike activity during periods of active navigation. This study would also provide useful insights for future exploratory data analysis of population neuronal codes during periods of sleep.National Institutes of Health (U.S.) (NIH Grant DP1-OD003646)National Institutes of Health (U.S.) (Grant MH061976
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