The ribosome assembly gene network is controlled by the feedback regulation of transcription elongation

Ribosome assembly requires the concerted expression of hundreds of genes, which are transcribed by all three nuclear RNA polymerases. Transcription elongation involves dynamic interactions between RNA polymerases and chromatin. We performed a synthetic lethal screening in Saccharomyces cerevisiae with a conditional allele of SPT6, which encodes one of the factors that facilitates this process. Some of these synthetic mutants corresponded to factors that facilitate pre-rRNA processing and ribosome biogenesis. We found that the in vivo depletion of one of these factors, Arb1, activated transcription elongation in the set of genes involved directly in ribosome assembly. Under these depletion conditions, Spt6 was physically targeted to the upregulated genes, where it helped maintain their chromatin integrity and the synthesis of properly stable mRNAs. The mRNA profiles of a large set of ribosome biogenesismutants confirmed the existence of a feedback regulatory network among ribosome assembly genes. The transcriptional response in this network depended on both the specific malfunction and the role of the regulated gene. In accordance with our screening, Spt6 positively contributed to the optimal operation of this global network. On the whole, this work uncovers a feedback control of ribosome biogenesis by fine-tuning transcription elongation in ribosome assembly factor-coding genes.Ministerio de Economía y Competitividad BFU2013-48643-C3-1-P, BFU2016-77728-C3-1-P, BFU2013-48643-C3- 3-P, BFU2013-42958-PJunta de Andalucía P12-BIO1938MO, P08-CVI-03508Comunidad Valenciana 2015/00

The BioVoz Project: Secure Speech Biometrics by Deep Processing Techniques

Currently, voice biometrics systems are attracting a growing interest driven by the need for new authentication modalities. The BioVoz project focuses on the reliability of these systems, threatened by various types of attacks, from a simple playback of prerecorded speech to more sophisticated variants such as impersonation based on voice conversion or synthesis. One problem in detecting spoofed speech is the lack of suitable models based on classical signal processing techniques. Therefore, the current trend is based on the use of deep neural networks, either for direct attack detection, or for obtaining deep feature vectors to represent the audio signals. However, these solutions raise many questions that are still unanswered and are the subject of the research proposed here. These include what spectral or temporal information should be used to feed the network, how to compensate for the effect of acoustic noise, what network architecture is appropriate, or what methodology should be used for training in order to provide the network with discriminative generalization capabilities. The present project focuses on the search for solutions to the aforementioned problems without forgetting a fundamental issue, little studied so far, such as the integration of fraud detection in the whole biometrics system.FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades. Proyecto PY20_00902Project PID2019-104206GB-I00 funded by MCIN/AEI/10.13039/50110001103

Arte & Natureza

A obra contém as actas da IV Conferência de Ciências da Arte, subordinada ao tema "Arte & Natureza", organizada pelo Grupo de Ciências e Teorias da Arte, da Faculdade de Belas Artes da Universidade de Lisboa, onde decorreram em Nov. de 2009info:eu-repo/semantics/publishedVersio