12 research outputs found

    Cognitive Effects of Combined Amisulpride and Quetiapine Treatment in Patients With Refractory Schizophrenia: A Naturalistic, Prospective Study.

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    Background: There are different treatment options, but little support of evidence in the treatment of patients with resistant schizophrenia. In this study we used antipsychotic polypharmacy (AP) comprising 1200 mg of amisulpride and 600 mg of quetiapine, using neurocognitive evaluations to measure clinical change. Study Question: The AP of amisulpride and quetiapine implicará una mejoría clínica en pacientes with resistant schizophrenia que reflejará especialmente en una mejoría cognitiva. Study Design: Naturalistic and prospective study. 26 patients with no biological response to medication, high social maladjustment, a long history of the disease, to whom Kane's and Brenner's criteria for treatment-resistant schizophrenia were applied and assessed by a battery of neurocognitive evaluations desde a pre-treatment baseline y a los six months treatment. Measures and Outcomes: La mejoría cognitiva implicara una mejora significativa in the cognitive test: Stroop test, WAIS Coding Subtest, Continuous Trail Making Test (CTMT) desde la línea base y los 6 meses de tratamiento. También implicará mejoría en las escalas de Calgary Depression Scale (CDS), Simpson-Angus Scale (SAS) and a Visual Analogue Scale (EVA) con las que fueron evaluados en línea base, a los 3 meses y a los 6 meses. Results: Subjects, after six months treatment with amisulpride and quetiapine, did statistically significant difference in the assessed areas: WAIS Coding Subtest (P <0.001), CTMT A & B (CTMTA P< 0,034; CTMTB P< 0,000) and in Stroop tests: Word (P< 0,001), word-color (P< 0,007) and interference (P< 0,039). Furthermore they showed a statistically significant difference in CDS (P< 0,002), SAS (P< 0,019), and EVA (P < 0.001). Conclusion: The results of this report show a cognitive and clinical improvement in refractory patients after the administration of amisulpride and quetiapine.pre-print523 K

    Alternative processing of its precursor is related to miR319 decreasing in melon plants exposed to cold

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    [EN] miRNAs are fundamental endogenous regulators of gene expression in higher organisms. miRNAs modulate multiple biological processes in plants. Consequently, miRNA accumulation is strictly controlled through miRNA precursor accumulation and processing. Members of the miRNA319 family are ancient ribo-regulators that are essential for plant development and stress responses and exhibit an unusual biogenesis that is characterized by multiple processing of their precursors. The significance of the high conservation of these non-canonical biogenesis pathways remains unknown. Here, we analyze data obtained by massive sRNA sequencing and 5 ' - RACE to explore the accumulation and infer the processing of members of the miR319 family in melon plants exposed to adverse environmental conditions. Sequence data showed that miR319c was down regulated in response to low temperature. However, the level of its precursor was increased by cold, indicating that miR319c accumulation is not related to the stem loop levels. Furthermore, we found that a decrease in miR319c was inversely correlated with the stable accumulation of an alternative miRNA (#miR319c) derived from multiple processing of the miR319c precursor. Interestingly, the alternative accumulation of miR319c and #miR319c was associated with an additional and non-canonical partial cleavage of the miR319c precursor during its loop-to-base-processing. Analysis of the transcriptional activity showed that miR319c negatively regulated the accumulation of HY5 via TCP2 in melon plants exposed to cold, supporting its involvement in the low temperature signaling pathway associated with anthocyanin biosynthesis. Our results provide new insights regarding the versatility of plant miRNA processing and the mechanisms regulating them as well as the hypothetical mechanism for the response to cold-induced stress in melon, which is based on the alternative regulation of miRNA biogenesis.Bustamante-González, AJ.; Marques Romero, MC.; Sanz-Carbonell, A.; Mulet, JM.; Gomez, GG. (2018). Alternative processing of its precursor is related to miR319 decreasing in melon plants exposed to cold. Scientific Reports. 8:1-13. https://doi.org/10.1038/s41598-018-34012-7S1138Borges, F. & Martienssen, R. A. The expanding world of small RNAs in plants. Nat Rev Mol Cell Biol 16, 727–741 (2015).Shriram, V., Kumar, V., Devarumath, R. M., Khare, T. S. & Wani, S. H. MicroRNAs As Potential Targets for Abiotic Stress Tolerance in Plants. Front Plant Sci 7, 817 (2016).Xie, M., Zhang, S. & Yu, B. microRNA biogenesis, degradation and activity in plants. Cell Mol Life Sci 72, 87–99 (2015).Bologna, N. G., Schapire, A. L. & Palatnik, J. F. Processing of plant microRNA precursors. Brief Funct Genomics 12, 37–45 (2012).Achkar, N. P., Cambiagno, D. A. & Manavella, P. A. miRNA Biogenesis: A Dynamic Pathway. Trends Plant Sci 21, 1034–1044 (2016).Dong, Z., Han, M. H. & Fedoroff, N. The RNA-binding proteins HYL1 and SE promote accurate in vitro processing of pri-miRNA by DCL1. Proc Natl Acad Sci USA 105, 9970–9975 (2008).Bologna, N. G. et al. Multiple RNA recognition patterns during microRNA biogenesis in plants. Genome Research 23, 1675–1689 (2013).Baranauskė, S. et al. Functional mapping of the plant small RNA methyltransferase: HEN1 physically interacts with HYL1 and DICER-LIKE 1 proteins. Nucleic Acids Res 43, 2802–2812 (2015).Zhang, S., Liu, Y. & Yu, B. New insights into pri-miRNA processing and accumulation in plants. WIREs. RNA 6, 533–545 (2015).Ren, G. et al. Regulation of miRNA abundance by RNA binding protein TOUGH in Arabidopsis. Proc Natl Acad Sci USA 109, 12817–12821 (2012).Cuperus, J. T., Fahlgren, N. & Carrington, J. C. Evolution and functional diversification of MIRNA genes. Plant Cell 23, 431–442 (2011).Zhang, W. et al. Multiple distinct small RNAs originate from the same microRNA precursors. Genome Biol 11(8), r81 (2010).Addo-Quaye, C. et al. Sliced microRNA targets and precise loop-first processing of MIR319 hairpins revealed by analysis of the Physcomitrella patens degradome. RNA 15, 2112–2121 (2009).Axtell, M. J., Snyder, J. A. & Bartel, D. P. Common functions for diverse small RNAs of land plants. Plant Cell 19, 1750–1769 (2007).Bologna, N. G., Mateos, J. L., Bresso, E. G. & Palatnik, J. F. A loop-to-base processing mechanism underlies the biogenesis of plant microRNAs miR319 and miR159. EMBO J 28, 3646–3656 (2009).Li, Y., Li, C., Ding, G. & Jin, Y. Evolution of MIR159/319 microRNA genes and their post-transcriptional regulatory link to siRNA pathways. BMC Evol Biol 11, 122 (2011).Sobkowiak, L., Karlowski, W., Jarmolowski, A. & Szweykowska-Kulinska, Z. Non-Canonical Processing of Arabidopsis pri-miR319a/b/c Generates Additional microRNAs to Target One RAP2.12 mRNA Isoform. Front Plant Sci 3, 46 (2012).Achard, P., Herr, A., Baulcombe, D. C. & Harberd, N. P. Modulation of floral development by a gibberellin-regulated microRNA. Development 131, 3357–3365 (2004).Allen, R. S. et al. Genetic analysis reveals functional redundancy and the major target genes of the Arabidopsis miR159 family. Proc Natl Acad Sci USA 104, 16371–16376 (2007).Jones-Rhoades, M. W. & Bartel, D. P. Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Mol Cell 14, 787–799 (2004).Palatnik, J. F. et al. Control of leaf morphogenesis by microRNAs. Nature 425, 257–263 (2003).Wang, S. T. et al. MicroRNA319 positively regulates cold tolerance by targeting OsPCF6 and OsTCP21 in rice (Oryza sativa). PLoS One 9(3), e91357 (2014).Thiebaut, F. et al. Regulation of miR319 during cold stress in sugarcane. Plant Cell Environ 35, 502–512 (2012).Sunkar, R. & Zhu, J. K. Novel and stress-regulated microRNAs and other small RNAs from Arabidopsis. Plant Cell 16, 2001–2019 (2004).Chen, H. et al. A comparison of the low temperature transcriptomes of two tomato genotypes that differ in freezing tolerance: Solanum lycopersicum and Solanum habrochaites. BMC Plant Biol 15, 132 (2015).Garcia-Mas, J. et al. The genome of melon (Cucumis melo L.). Proc Natl Acad Sci USA 109, 11872–11877 (2012).Nuñez-Palenius, H. G. et al. Melon fruits: genetic diversity, physiology, and biotechnology features. Crit Rev Biotechnol 28, 13–55 (2008).Gonzalez-Ibeas, D. et al. Analysis of the melon (Cucumis melo) small RNAome by high-throughput pyrosequencing. BMC Genomics 12, 393 (2011).Herranz, M. C., Navarro, J. A., Sommen, E. & Pallas, V. Comparative analysis among the small RNA populations of source, sink and conductive tissues in two different plant-virus pathosystems. BMC Genomics 16, 117 (2015).Sattar, S. et al. Expression of small RNA in Aphis gossypii and its potential role in the resistance interaction with melon. PLoS One 7(11), e48579 (2012).Dai, X. & Zhao, P. X. psRNATarget: a plant small RNA target analysis server. Nucleic Acids Res. 39, W155–9 (2011).Palatnik, J. F. et al. Sequence and expression differences underlie functional specialization of Arabidopsis microRNAs miR159 and miR319. Dev Cell 13, 115–125 (2007).He, Z., Zhao, X., Kong, F., Zuo, Z. & Liu, X. TCP2 positively regulates HY5/HYH and photomorphogenesis in Arabidopsis. J Exp Bot 67, 775–785 (2016).Lau, O. S. & Deng, X. W. Plant hormone signaling lightens up: integrators of light and hormones. Curr Opin Plant Biol 13, 571–577 (2010).Oyama, T., Shimura, Y. & Okada, K. The Arabidopsis HY5 gene encodes a bZIP protein that regulates stimulus-induced development of root and hypocotyl. Genes Dev 11, 2983–2995 (1997).Ahmed, N. U., Park, J. I., Jung, H. J., Hur, Y. & Nou, I. S. Anthocyanin biosynthesis for cold and freezing stress tolerance and desirable color in Brassica rapa. Funct Integr Genomics 15, 383–394 (2015).Catalá, R., Medina, J. & Salinas, J. Integration of low temperature and light signaling during cold acclimation response in Arabidopsis. Proc Natl Acad Sci USA 108, 16475–16480 (2011).Schulz, E., Tohge, T., Zuther, E., Fernie, A. R. & Hincha, D. K. Natural variation in flavonol and anthocyanin metabolism during cold acclimation in Arabidopsis thaliana accessions. Plant Cell Environ 38, 1658–1672 (2015).Perea-Resa, C., Rodríguez-Milla, M. A., Iniesto, E., Rubio, V. & Salinas, J. Prefoldins Negatively Regulate Cold Acclimation in Arabidopsis thaliana by Promoting Nuclear Proteasome-Mediated HY5 Degradation. Mol Plant 10, 791–804 (2017).Solfanelli, C., Poggi, A., Loreti, E., Alpi, A. & Perata, P. Sucrose-Specific Induction of the Anthocyanin Biosynthetic Pathway in Arabidopsis. Plant Physiol 140, 637–646 (2006).Reis, R. S., Eamens, A. L. & Waterhouse, P. M. Missing Pieces in the Puzzle of Plant MicroRNAs. Trends Plant Sci 20, 721–728 (2015).Kumar, R. Role of microRNAs in biotic and abiotic stress responses in crop plants. Appl Biochem Biotech 174, 93–115 (2014).Ma, C., Burd, S. & Lers, A. miR408 is involved in abiotic stress responses in Arabidopsis. Plant J 84, 169–187 (2015).Song, L., Axtell, M. J. & Fedoroff, N. V. RNA secondary structural determinants of miRNA precursor processing in Arabidopsis. Curr Biol 20, 37–41 (2010).Bracken, C. P. et al. Global analysis of the mammalian RNA degradome reveals widespread miRNA-dependent and miRNA-independent endonucleolytic cleavage. Nucleic Acids Res 39, 5658–5668 (2011).Gurtan, A. M., Lu, V., Bhutkar, A. & Sharp, P. A. In vivo structure-function analysis of human Dicer reveals directional processing of precursor miRNAs. RNA 18, 1116–1122 (2012).Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet Journal 17, 10–12 (2011).Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq-2. Genome Biol 15, 550 (2014).Robinson, M. D. & Oshlack, A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol 11, 3–r25 (2010).Griffiths-Jones, S. miRBase: microRNA sequences and annotation. Current protocols in bioinformatics 12, 9 (2010).Li, H. et al. 1000 Genome Project Data Processing Subgroup The sequence alignment/map format & SAMtools. Bioinformatics 25, 2078–2079 (2009).Quinlan, A. & Hall, I. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 25, 402–408 (2001).Llave, C., Xie, Z., Kasschau, K. D. & Carrington, J. C. Cleavage of Scarecrow-like mRNA targets directed by a class of Arabidopsis miRNA. Science 297, 2053–2056 (2002).Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10, 3–r25 (2009)

    Activation of the interferon induction cascade by influenza A viruses requires viral RNA synthesis and nuclear export

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    This work is supported by grants from the Wellcome Trust (grants 087751/A/08/Z) and MRC (G1001726/1).We have examined the requirements for virus transcription and replication and thus the roles of input and progeny genomes in the generation of interferon (IFN)-inducing pathogen-associated molecular patterns (PAMPs) by influenza A viruses using inhibitors of these processes. Using IFN regulatory factor 3 (IRF3) phosphorylation as a marker of activation of the IFN induction cascade that occurs upstream of the IFN-β promoter, we demonstrate strong activation of the IFN induction cascade in A549 cells infected with a variety of influenza A viruses in the presence of cycloheximide or nucleoprotein (NP) small interfering RNA (siRNA), which inhibits viral protein synthesis and thus complementary ribonucleoprotein (cRNP) and progeny viral RNP (vRNP) synthesis. In contrast, activation of the IFN induction cascade by influenza viruses was very effectively abrogated by treatment with actinomycin D and other transcription inhibitors, which correlated with the inhibition of the synthesis of all viral RNA species. Furthermore, 5,6-dichloro-1-β-d-ribofuranosyl-benzimidazole, an inhibitor that prevents viral RNA export from the nucleus, was also a potent inhibitor of IRF3 activation; thus, both viral RNA synthesis and nuclear export are required for IFN induction by influenza A viruses. While the exact nature of the viral PAMPs remains to be determined, our data suggest that in this experimental system the major influenza A virus PAMPs are distinct from those of incoming genomes or progeny vRNPs.Publisher PDFPeer reviewe

    Generation and Comprehensive Analysis of an Influenza Virus Polymerase Cellular Interaction Network▿†§

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    The influenza virus transcribes and replicates its genome inside the nucleus of infected cells. Both activities are performed by the viral RNA-dependent RNA polymerase that is composed of the three subunits PA, PB1, and PB2, and recent studies have shown that it requires host cell factors to transcribe and replicate the viral genome. To identify these cellular partners, we generated a comprehensive physical interaction map between each polymerase subunit and the host cellular proteome. A total of 109 human interactors were identified by yeast two-hybrid screens, whereas 90 were retrieved by literature mining. We built the FluPol interactome network composed of the influenza virus polymerase (PA, PB1, and PB2) and the nucleoprotein NP and 234 human proteins that are connected through 279 viral-cellular protein interactions. Analysis of this interactome map revealed enriched cellular functions associated with the influenza virus polymerase, including host factors involved in RNA polymerase II-dependent transcription and mRNA processing. We confirmed that eight influenza virus polymerase-interacting proteins are required for virus replication and transcriptional activity of the viral polymerase. These are involved in cellular transcription (C14orf166, COPS5, MNAT1, NMI, and POLR2A), translation (EIF3S6IP), nuclear transport (NUP54), and DNA repair (FANCG). Conversely, we identified PRKRA, which acts as an inhibitor of the viral polymerase transcriptional activity and thus is required for the cellular antiviral response

    Microbial metabolites as biological control agents in food safety

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    Ensuring food safety and at the same time meeting such demands for retention of nutrition and quality attributes have resulted in increased interest in alternative preservation techniques for inactivating microorganisms and enzymes in foods. This increasing demand has opened new dimensions for the use of natural preservatives derived from plants, animals, or microflora. Extensive research has investigated the potential application of natural antimicrobial agents in food preservation. Especially the significance and use of microbes as producers of antimicrobial metabolites has increased significantly during the last decades. Reported studies have demonstrated that microbial metabolites from microorganisms exhibited a great numbers of diverse and versatile biological effects about antimicrobial activities. These microorganisms produce many compounds that are active against other microorganisms, which can be harnessed to inhibit the growth of potential spoilage or pathogenic microorganisms. These include fermentation end products (metabolites) such as organic acids, hydrogen peroxide, and diacetyl, biofilm, exopolysaccharides in addition to bacteriocins and other antagonistic compounds such as reuterin. Up to now, antimicrobial metabolites from lactic acid bacteria (such as nisin) have been mostly used in food preservation. In addition to lactic acid bacteria, some yeast, mold, and another bacteria species as well as some pathogenic bacteria can produce antimicrobial metabolites. Antimicrobial metabolites present in foods can extend the shelf life of unprocessed or processed foods by reducing the microbial growth rate or viability. This offers a new knowledge-based approach to the exploitation of bacteria for food production, from metabolic engineering of microorganisms to produce antimicrobials or nutritionals, to the molecular mining of activities as yet unknown but which could benefit food production. In addition, the availability of the genomes of many food pathogenic and spoilage bacteria may open up new possibilities for the design of novel antimicrobials which target essential functions of these problematic bacteria. In this chapter, antimicrobial metabolites from microorganism in food safety as a biocontrol agent reviewed. © 2014, Springer Science+Business Media New York
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