Relevant bibliographies by topics / MicroRNA turnover

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'MicroRNA turnover'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "MicroRNA turnover"

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Sanei, Maryam, and Xuemei Chen. "Mechanisms of microRNA turnover." Current Opinion in Plant Biology 27 (October 2015): 199–206. http://dx.doi.org/10.1016/j.pbi.2015.07.008.

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Michaud, Pascale, Vivek Nilesh Shah, Pauline Adjibade, Francois Houle, Miguel Quévillon Huberdeau, Rachel Rioux, Camille Lavoie-Ouellet, Weifeng Gu, Rachid Mazroui, and Martin J. Simard. "The RabGAP TBC-11 controls Argonaute localization for proper microRNA function in C. elegans." PLOS Genetics 17, no. 4 (April 7, 2021): e1009511. http://dx.doi.org/10.1371/journal.pgen.1009511.

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Once loaded onto Argonaute proteins, microRNAs form a silencing complex called miRISC that targets mostly the 3’UTR of mRNAs to silence their translation. How microRNAs are transported to and from their target mRNA remains poorly characterized. While some reports linked intracellular trafficking to microRNA activity, it is still unclear how these pathways coordinate for proper microRNA-mediated gene silencing and turnover. Through a forward genetic screen usingCaenorhabditis elegans, we identified the RabGAPtbc-11as an important factor for the microRNA pathway. We show that TBC-11 acts mainly through the small GTPase RAB-6 and that its regulation is required for microRNA function. The absence of functional TBC-11 increases the pool of microRNA-unloaded Argonaute ALG-1 that is likely associated to endomembranes. Furthermore, in this condition, this pool of Argonaute accumulates in a perinuclear region and forms a high molecular weight complex. Altogether, our data suggest that the alteration of TBC-11 generates a fraction of ALG-1 that cannot bind to target mRNAs, leading to defective gene repression. Our results establish the importance of intracellular trafficking for microRNA function and demonstrate the involvement of a small GTPase and its GAP in proper Argonaute localizationin vivo.
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Rogers, K., and X. Chen. "microRNA Biogenesis and Turnover in Plants." Cold Spring Harbor Symposia on Quantitative Biology 77 (January 1, 2012): 183–94. http://dx.doi.org/10.1101/sqb.2013.77.014530.

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Rüegger, Stefan, and Helge Großhans. "MicroRNA turnover: when, how, and why." Trends in Biochemical Sciences 37, no. 10 (October 2012): 436–46. http://dx.doi.org/10.1016/j.tibs.2012.07.002.

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Zhang, Zhuo, Yong-Wen Qin, Gary Brewer, and Qing Jing. "MicroRNA degradation and turnover: regulating the regulators." Wiley Interdisciplinary Reviews: RNA 3, no. 4 (March 28, 2012): 593–600. http://dx.doi.org/10.1002/wrna.1114.

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Medina, Lisvaneth, Jesús Alejandro Guerrero-Muñoz, Ana Isabel Liempi, Christian Castillo, Yessica Ortega, Alfredo Sepúlveda, Fernando Salomó, Juan Diego Maya, and Ulrike Kemmerling. "Ex Vivo Infection of Human Placental Explants by Trypanosoma cruzi Reveals a microRNA Profile Similar to That Seen in Trophoblast Differentiation." Pathogens 11, no. 3 (March 16, 2022): 361. http://dx.doi.org/10.3390/pathogens11030361.

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Congenital Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, is responsible for 22.5% of new cases each year. However, placental transmission occurs in only 5% of infected mothers and it has been proposed that the epithelial turnover of the trophoblast can be considered a local placental defense against the parasite. Thus, Trypanosoma cruzi induces cellular proliferation, differentiation, and apoptotic cell death in the trophoblast, which are regulated, among other mechanisms, by small non-coding RNAs such as microRNAs. On the other hand, ex vivo infection of human placental explants induces a specific microRNA profile that includes microRNAs related to trophoblast differentiation such as miR-512-3p miR-515-5p, codified at the chromosome 19 microRNA cluster. Here we determined the expression validated target genes of miR-512-3p and miR-515-5p, specifically human glial cells missing 1 transcription factor and cellular FLICE-like inhibitory protein, as well as the expression of the main trophoblast differentiation marker human chorionic gonadotrophin during ex vivo infection of human placental explants, and examined how the inhibition or overexpression of both microRNAs affects parasite infection. We conclude that Trypanosoma cruzi-induced trophoblast epithelial turnover, particularly trophoblast differentiation, is at least partially mediated by placenta-specific miR-512-3p and miR-515-5p and that both miRNAs mediate placental susceptibility to ex vivo infection of human placental explants. Knowledge about the role of parasite-modulated microRNAs in the placenta might enable their use as biomarkers, as prognostic and therapeutic tools for congenital Chagas disease in the future.
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Larsson, Erik, Chris Sander, and Debora Marks. "mRNA turnover rate limits siRNA and microRNA efficacy." Molecular Systems Biology 6, no. 1 (January 2010): 454. http://dx.doi.org/10.1038/msb.2010.113.

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Larsson, Erik, Chris Sander, and Debora Marks. "mRNA turnover rate limits siRNA and microRNA efficacy." Molecular Systems Biology 6, no. 1 (January 2010): 433. http://dx.doi.org/10.1038/msb.2010.89.

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Chatterjee, Saibal, and Helge Großhans. "Active turnover modulates mature microRNA activity in Caenorhabditis elegans." Nature 461, no. 7263 (September 2009): 546–49. http://dx.doi.org/10.1038/nature08349.

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Hutvagner, G. "A microRNA in a Multiple-Turnover RNAi Enzyme Complex." Science 297, no. 5589 (August 1, 2002): 2056–60. http://dx.doi.org/10.1126/science.1073827.

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Dissertations / Theses on the topic "MicroRNA turnover"

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Ghini, F. "THE PLASTICITY OF MIRNA POOL: A NOVEL APPROACH TO REVEAL MECHANISMS BEHIND MIRNA TURNOVER." Doctoral thesis, Università degli Studi di Milano, 2017. http://hdl.handle.net/2434/466760.

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MicroRNAs (miRNAs) are a small (18-25nt long), evolutionary conserved, class of non-coding RNAs that appears as a major regulatory component of gene expression, implicated in virtually all known physiological and pathological processes. They act at post-transcriptional level by silencing the expression of a multitude of target mRNAs through various mechanisms, including target degradation and protein synthesis inhibition. As a result, the regulation of the miRNA pool is one of the critical events in the definition of cell identity and behavior both in physiology and disease. Although large efforts have been put in understanding how miRNA transcription and biogenesis are regulated, to date very little is known on what happens to miRNAs once they exerted their repressive function, if they are recycled on other target molecules or degraded, and how fast they are turned over. Typically, miRNAs are thought to be stable molecules with long half-lives. Nevertheless, in last years it emerged that some miRNAs could be also turned over rapidly upon different cellular conditions. To clarify how miRNAs decay in mammalian cells, we developed a new tailored approach based on in vivo RNA labeling (4sU pulse-chase) and high-throughput sequencing, which allows to investigate the modes and the mechanisms of miRNAs decay without perturbing global miRNA levels or miRNA processing. By this approach, we precisely measured miRNA decay rates in exponentially growing 3T9 mouse fibroblasts. Overall, miRNA turnover appeared heterogeneous; hence, miRNAs are not just stable molecules as previously thought. We could distinguish two pools of miRNA by decay: a group of miRNAs that are, indeed, very stable molecules (T1/2 >24h, ‘slow’); and another group composed of miRNAs quickly turned over in the cell (T1/2 <14h, ‘fast’). We further exploited RNA labeling by 4sU to quantitatively measure the biosynthetic rate (transcription) of miRNAs alongside. By integrating decay rates with biosynthesis, we developed a mathematical model to infer how different decays impact on miRNA regulation during cell transitions: fast miRNAs quickly reach a plateau of accumulation and are downregulated in few hours as compared to slow miRNAs. These findings were recapitulated in a specific biological process, namely the regulation of miRNAs by serum stimulation of quiescent fibroblast, which is characterized by a consistent 15 change in gene and miRNA expression in absence of cell division (hence, miRNA cannot be diluted). Indeed, serum ‘up’ and ‘down’ regulated miRNAs were characterized by marked difference in turnover rate, compatible with the kinetic of their changes and often coupled with transcriptional regulation, pointing out how multiple mechanisms concomitantly control miRNAs and their activity in mammalian cells. Mechanistically, our analyses suggested that the ratio between high affinity targets and miRNA abundance [which we termed target per miRNA (TPM) value] is a key determinant in the definition of the type of miRNA decay, supporting the ‘target-induced miRNA decay’ (TIMD) as a common mechanism that promotes miRNA degradation. This contention is also supported by a clear parallelism between decay-associated miRNA isoforms (trimmed and tailed sequence variants) and miRNA degradation dynamics, implying that i) the distribution of miRNA isoforms is reflecting the type of decay of miRNAs, and ii) specific enzymatic activities (i.e. nucleases, transferases) are in place and mediate miRNA degradation. So far, no endogenous target has been directly linked to TIMD mechanism. Our analyses provided a list of potential targets involved in TIMD, which could be critical in clarifying the role played by such mechanism in physiology. Preliminary experiments were performed on one of such target, which is much expressed upon serum stimulation of quiescent fibroblasts and highly complementary to a miRNA suddenly downregulated. Exploiting CRISPR/cas9 based genome engineering, we specifically affected miRNA:target interaction, keeping transcript level and protein functionality unaltered, ensuing in a consequent effect on miRNA regulation (loss of downregulation upon serum stimulation), fully supporting TIMD as an endogenous mechanism in control of miRNA functions.
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Cuellar, Trinna Lee. "The role of Dicer in post-mitotic dopaminoceptive neurons and turnover of Dicer generated microRNAs." Diss., Search in ProQuest Dissertations & Theses. UC Only, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3359544.

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Schwanhäußer, Björn. "Global analysis of cellular protein dynamics by pulse-labeling and quanti tati ve mass spectrometry." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2011. http://dx.doi.org/10.18452/16305.

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Der erste Teil der Arbeit beschreibt die Etablierung einer modifizierten Form des klassichen SILAC-Verfahrens, das in der quantitativen Massenspektrometrie zur Bestimmung von relativen Änderungen in Proteinmengen benutzt wird. Im sog. „pulsed SILAC (pSILAC)“ Verfahren werden Zellen im Zuge einer differentiellen Behandlung in Kulturmedien transferiert, die unterschiedlich Isotop-markierte Aminosäuren enthalten. Da hier die Quantifizierung auf dem Verhältnis der neusynthetisierten Proteinmengen beruht, können gezielt Unterschiede in der Proteinproduktion bestimmt werden. Mit Hilfe von pSILAC konnte im zweiten Teil der Arbeit erstmals quantitativ erfasst werden, welchen Einfluss microRNAs auf die Proteinsynthese ausüben. So konnte gezeigt werden, dass sowohl die Überexpression als auch die Repression einzelner microRNAs die Produktion hunderter Proteine beeinflussen kann. Außerdem konnten Genprodukte identifiziert werden, die ausschließlich translational reguliert werden. Die Messung von Proteinneusynthese ermöglichte auch die Bestimmung von Proteinumsatzraten, dargestellt im dritten Teil der Arbeit. Zusammen mit mRNA-Umsatzraten sowie Protein- und mRNA-Mengen bilden sie die Grundlage für eine dynamische Beschreibung zelluärer Genexpression. Durch den gleichzeitigen Einsatz des Nukleosidanalogons 4-Thiouridin (4sU) und von schweren Aminosäuren (SILAC) konnte eine metabolische Markierung neusynthetiserter mRNAs und Proteine in murinen Fibroblasten erreicht und damit eine Berechnung von Protein- und mRNA-Halbwertszeiten und absoluten Mengen für ca. 5,000 Gene ermöglicht werden. Während mRNA- und Proteinenmengen deutlich korrelierten, war zwischen mRNA- und Proteinhalbwertszeiten nur eine äußerste schwache Korrelation zu erkennen. Dennoch stehen mRNA- und Proteinumsatzraten nicht einem willkürlichen Zusammhang zu einander, da bestimmte Kombinationen von mRNA- und Proteinhalbwertszeiten eine Optimierung von Genen hinsichtlich ihrer biologischen Funktionen erkennen ließen.
The first part of the thesis describes the establishment of a modified version of the classic SILAC approach routinely used in quantitative mass spectrometry (MS) to assay relative changes in protein levels. In the newly-devised approach termed pulsed SILAC (pSILAC) differentially treated cells are transferred to culture medium supplemented with different versions of stable-isotope labeled heavy amino acids. As MS-based relative quantification is exclusively based on the newly-synthesized heavy protein amounts the method enables the detection of differences in protein production resulting from the treatment. The second part of the thesis shows the use of pSILAC to globally quantify the impact of microRNAs onto the proteome. Ectopic over-expression or knock-down of a single microRNA both affected protein production of hundreds of proteins. pSILAC identified several target genes as exclusively translationally regulated as changes in corresponding transcript levels were virtually absent. Measuring newly-synthesized protein amounts with heavy amino acids in a pulsed-labeling fashion has also been used to determine turnover rates of individual proteins, described in the third part of the present work. Along with transcript turnover as well as mRNA and protein levels they are essential for a dynamic description of gene expression. Simultaneous application of the nucleoside analogue 4-thiouridine (4sU) and heavy amino acids (SILAC) to metabolically label newly-produced mRNAs and proteins in mouse fibroblasts resulted in the calculation of mRNA and protein lifetimes and absolute levels for approximately 5,000 genes. While mRNA and protein levels were overall well correlated, a correlation between mRNA and protein half-lives was virtually absent. Yet this seemingly chaotic distribution of mRNA and protein half-lives was highly instructive since specific gene subsets have obviously evolved distinct combinations of half-lives that relate to their biological functions.
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Book chapters on the topic "MicroRNA turnover"

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Bhagtaney, Lekha, and Priya Sundarrajan. "MicroRNA-induced Silencing Complex Assembly and MicroRNA Turnover." In Plant MicroRNAs and Stress Response, 1–14. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003322214-1.

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Campos-Melo, Danae, Zachary C. E. Hawley, Crystal McLellan, and Michael J. Strong. "MicroRNA turnover and nuclear function." In MicroRNA, 109–40. Elsevier, 2022. http://dx.doi.org/10.1016/b978-0-323-89774-7.00026-1.

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Conference papers on the topic "MicroRNA turnover"

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Lo, U.-Ging, Rey-Chen Pong, Jer-Tsong Hsieh, and Leah Gandee. "Abstract 1466: Interferon-induced microRNA turnover leading to epithelial-to-mesenchymal transition (EMT) in cancer." In Proceedings: AACR 107th Annual Meeting 2016; April 16-20, 2016; New Orleans, LA. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1538-7445.am2016-1466.

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Lo, U.-Ging, Rey-Chen Pong, Diane Yang, Jiancheng Zhou, Leah Gandee, Shu-Fen Tseng, and Jer-Tsong Hsieh. "Abstract 2873: Identification of a new mechanism of microRNA turnover from miR-106a-363 cluster leading to epithelial-to-mesenchymal transition in prostate cancer." In Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1538-7445.am2015-2873.

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Pickering, M. E., M. Croset, M. Millet, E. Sornay-Rendu, J. C. Rousseau, O. Borel, P. Szulc, and R. Chapurlat. "AB0008 Cross-talk between bone turnover and cardiovascular disease. association of micrornas expression, fracture and abdominal aortic calcifications." In Annual European Congress of Rheumatology, EULAR 2018, Amsterdam, 13–16 June 2018. BMJ Publishing Group Ltd and European League Against Rheumatism, 2018. http://dx.doi.org/10.1136/annrheumdis-2018-eular.5792.

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Visileanu, Emilia, Marian Catalin Grosu, Paul Tiberiu Miclea, Korinna Altmann, and Dirk Brossell. "Methods for the collection and characterization of airborne particles in the textile industry." In 5th International Conference on Human Systems Engineering and Design: Future Trends and Applications (IHSED 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004132.

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Airborne particulate matter is one of the main air pollutants. Their impact on mortality, and the occurrence of pulmonary and cardiovascular complications, have been the subject of numerous studies. Airborne particles are complex mixtures of organic and inorganic substances from different sources of particle emissions. Particulate Matter (PM) particles are classified according to their aerodynamic diameter expressed in µm and can vary from coarse (PM 10) to fine (less than PM 2.5). These diameter considerations are fundamental because they condition the penetration of particles into the bronchopulmonary system and the body. In recent years, there has been an interest in so-called “ultra-fine” particles, with a diameter of 0.1 µm (or 100 nm), or PM 0.1. They are nanoparticles and their impact on human health is not yet clear.With more than 1.5 million employees, textiles and clothing is a diverse sector that plays an important role in the European manufacturing industry, producing a turnover of €162 billion.An important component of the solid particles that generate air pollution in the textile industry is microplastics (MP) and nano plastics (NP), which also include microfibers (<5mm) and nanofibers (<100 nm), respectively. The particles released into the air during fiber and yarn processing range from 1 µg/m3 to 50 µg/m3.The paper presents the results of the determination of indoor and outdoor air concentration levels in textile companies, to identify the areas with the highest concentration level, by using an online recording system such as the Laser Aerosol Spectrometer MINI LAS model 11-E. The total concentration level TSP (µg/m3), the fractions PM 10(µg/m3), PM 2.5(µg/m3), PM1(µg/m3), as well as the total number of particles TC (1/l), were shown. It was noted that TSP is approximately at the same level both indoors and outdoors, but the fractions of PM10, PM2.5, and PM1 have much higher values indoors than outdoors with possible consequences on workers' health.The next step was the collection of fibers, namely micro and nano plastic particles from the vicinity of the workplaces of polyester, polyamide, and polypropylene fibers processing units in the textile industry in Romania, to obtain a sufficient quantity for laboratory analysis to determine the size and shape of the particles as well as their chemical composition. Two types of pumps were used, differentiated by their operating parameters: TECORA SKYPOST with airflow of 38 l/min and GILAIRPLUS with airflow 2l/min. Filters made of different materials with different diameters and pore sizes were used, namely: quartz filters (ø 47 mm, and ø 37 mm) on a TECORA SKYPOST type pump, polycarbonate nucleopore coated with a gold membrane (ø 25 mm) and silica filter (ø 9 mm) on GILAIRPLUS type pump.Using descriptive statistics, the calculation of correlation coefficients highlighted a strong correlation between the variables: "Collected mass/ Air concentration" and "Collected mass/ Air volume" for all diameters of the filters.The highest collected particle volume, determined by weighing the filters before and after collection, was obtained with the quartz filters (ø 47 mm) at an airflow of 38 l/min. The particles collected (polyester, polyamide, polypropylene) in the first stage were analyzed by SEM and thermogravimetric and it was found that the quartz filters absorbed the particles inside, with very few remaining on the surface. Thus no known methods can be used to perform analysis for particles collected on quartz filters. The number of particles on the filters was insufficient for analysis either because of the collection parameters used or because of the loss of particles during transport. As a result, in the next step, the use of 9 mm Si filters using the GILAIRPLUS pump at an airflow rate of 2l/min was chosen.To improve the transport conditions and avoid the loss of the particles and keep them on the surface of the filters, two methods were applied:- after weighing the filters were reintroduced into the collection pump holder;- a filtration system for airborne micro-nano plastics was designed and manufactured to selectively collect and transport PM10 and PM1 particles collected on SI filters.In both cases, SEM, Raman mapping, and GS-MS microscopy were used for analysis.Several times more PM10 than PM1 (74.5µg compared to 12.5 µg) was found. In all cases, both particles and fibers showed the same Raman fingerprint.The GS-MS analyses showed some contamination of the workspaces with particles other than the processed fibers. The presence of non-notifiable substances was also observed.The most viable filters are Si filters with a pore size of 10 microns to 1 micron and the use of the selected collection and transport filter system. In the following a filter system will be applied for collection on Au membrane-coated polycarbonate filters.
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