Добірка наукової літератури з теми "Prokaryotic Transcription"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Prokaryotic Transcription".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Статті в журналах з теми "Prokaryotic Transcription"
1
Dixit, Vidula, Elisabetta Bini, Melissa Drozda, and Paul Blum. "Mercury Inactivates Transcription and the Generalized Transcription Factor TFB in the Archaeon Sulfolobus solfataricus." Antimicrobial Agents and Chemotherapy 48, no. 6 (June 2004): 1993–99. http://dx.doi.org/10.1128/aac.48.6.1993-1999.2004.
Повний текст джерелаАнотація:
ABSTRACT Mercury has a long history as an antimicrobial agent effective against eukaryotic and prokaryotic organisms. Despite its prolonged use, the basis for mercury toxicity in prokaryotes is not well understood. Archaea, like bacteria, are prokaryotes but they use a simplified version of the eukaryotic transcription apparatus. This study examined the mechanism of mercury toxicity to the archaeal prokaryote Sulfolobus solfataricus. In vivo challenge with mercuric chloride instantaneously blocked cell division, eliciting a cytostatic response at submicromolar concentrations and a cytocidal response at micromolar concentrations. The cytostatic response was accompanied by a 70% reduction in bulk RNA synthesis and elevated rates of degradation of several transcripts, including tfb-1, tfb-2, and lacS. Whole-cell extracts prepared from mercuric chloride-treated cells or from cell extracts treated in vitro failed to support in vitro transcription of 16S rRNAp and lacSp promoters. Extract-mixing experiments with treated and untreated extracts excluded the occurrence of negative-acting factors in the mercury-treated cell extracts. Addition of transcription factor B (TFB), a general transcription factor homolog of eukaryotic TFIIB, to mercury-treated cell extracts restored >50% of in vitro transcription activity. Consistent with this finding, mercuric ion treatment of TFB in vitro inactivated its ability to restore the in vitro transcription activity of TFB-immunodepleted cell extracts. These findings indicate that the toxicity of mercuric ion in S. solfataricus is in part the consequence of transcription inhibition due to TFB-1 inactivation.
2
Goodrich, James A., and William R. McClure. "Competing promoters in prokaryotic transcription." Trends in Biochemical Sciences 16 (January 1991): 394–97. http://dx.doi.org/10.1016/0968-0004(91)90162-o.
Повний текст джерела
3
Pruss, Gail J., and Karl Drlica. "DNA supercoiling and prokaryotic transcription." Cell 56, no. 4 (February 1989): 521–23. http://dx.doi.org/10.1016/0092-8674(89)90574-6.
Повний текст джерела
4
Chávez, Joselyn, Damien P. Devos, and Enrique Merino. "Complementary Tendencies in the Use of Regulatory Elements (Transcription Factors, Sigma Factors, and Riboswitches) in Bacteria and Archaea." Journal of Bacteriology 203, no. 2 (October 19, 2020): e00413-20. http://dx.doi.org/10.1128/jb.00413-20.
Повний текст джерелаАнотація:
ABSTRACTIn prokaryotes, the key players in transcription initiation are sigma factors and transcription factors that bind to DNA to modulate the process, while premature transcription termination at the 5′ end of the genes is regulated by attenuation and, in particular, by attenuation associated with riboswitches. In this study, we describe the distribution of these regulators across phylogenetic groups of bacteria and archaea and find that their abundance not only depends on the genome size, as previously described, but also varies according to the phylogeny of the organism. Furthermore, we observed a tendency for organisms to compensate for the low frequencies of a particular type of regulatory element (i.e., transcription factors) with a high frequency of other types of regulatory elements (i.e., sigma factors). This study provides a comprehensive description of the more abundant COG, KEGG, and Rfam families of transcriptional regulators present in prokaryotic genomes.IMPORTANCE In this study, we analyzed the relationship between the relative frequencies of the primary regulatory elements in bacteria and archaea, namely, transcription factors, sigma factors, and riboswitches. In bacteria, we reveal a compensatory behavior for transcription factors and sigma factors, meaning that in phylogenetic groups in which the relative number of transcription factors was low, we found a tendency for the number of sigma factors to be high and vice versa. For most of the phylogenetic groups analyzed here, except for Firmicutes and Tenericutes, a clear relationship with other mechanisms was not detected for transcriptional riboswitches, suggesting that their low frequency in most genomes does not constitute a significant impact on the global variety of transcriptional regulatory elements in prokaryotic organisms.
5
Decker, Katherine T., Ye Gao, Kevin Rychel, Tahani Al Bulushi, Siddharth M. Chauhan, Donghyuk Kim, Byung-Kwan Cho, and Bernhard O. Palsson. "proChIPdb: a chromatin immunoprecipitation database for prokaryotic organisms." Nucleic Acids Research 50, no. D1 (November 17, 2021): D1077—D1084. http://dx.doi.org/10.1093/nar/gkab1043.
Повний текст джерелаАнотація:
Abstract The transcriptional regulatory network in prokaryotes controls global gene expression mostly through transcription factors (TFs), which are DNA-binding proteins. Chromatin immunoprecipitation (ChIP) with DNA sequencing methods can identify TF binding sites across the genome, providing a bottom-up, mechanistic understanding of how gene expression is regulated. ChIP provides indispensable evidence toward the goal of acquiring a comprehensive understanding of cellular adaptation and regulation, including condition-specificity. ChIP-derived data's importance and labor-intensiveness motivate its broad dissemination and reuse, which is currently an unmet need in the prokaryotic domain. To fill this gap, we present proChIPdb (prochipdb.org), an information-rich, interactive web database. This website collects public ChIP-seq/-exo data across several prokaryotes and presents them in dashboards that include curated binding sites, nucleotide-resolution genome viewers, and summary plots such as motif enrichment sequence logos. Users can search for TFs of interest or their target genes, download all data, dashboards, and visuals, and follow external links to understand regulons through biological databases and the literature. This initial release of proChIPdb covers diverse organisms, including most major TFs of Escherichia coli, and can be expanded to support regulon discovery across the prokaryotic domain.
6
Zheng, Ming, and Gisela Storz. "Redox sensing by prokaryotic transcription factors." Biochemical Pharmacology 59, no. 1 (January 2000): 1–6. http://dx.doi.org/10.1016/s0006-2952(99)00289-0.
Повний текст джерела
7
Hwang, Seungha, Jimin Lee, and Jin Young Kang. "Prokaryotic transcription regulation by the nascent RNA elements." Korean Society for Structural Biology 8, no. 2 (June 30, 2020): 33–40. http://dx.doi.org/10.34184/kssb.2020.8.2.33.
Повний текст джерела
8
Jacques, J. P., and D. Kolakofsky. "Pseudo-templated transcription in prokaryotic and eukaryotic organisms." Genes & Development 5, no. 5 (May 1, 1991): 707–13. http://dx.doi.org/10.1101/gad.5.5.707.
Повний текст джерела
9
Chetal, Kashish, and Sarath Chandra Janga. "OperomeDB: A Database of Condition-Specific Transcription Units in Prokaryotic Genomes." BioMed Research International 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/318217.
Повний текст джерелаАнотація:
Background. In prokaryotic organisms, a substantial fraction of adjacent genes are organized into operons—codirectionally organized genes in prokaryotic genomes with the presence of a common promoter and terminator. Although several available operon databases provide information with varying levels of reliability, very few resources provide experimentally supported results. Therefore, we believe that the biological community could benefit from having a new operon prediction database with operons predicted using next-generation RNA-seq datasets.Description. We present operomeDB, a database which provides an ensemble of all the predicted operons for bacterial genomes using available RNA-sequencing datasets across a wide range of experimental conditions. Although several studies have recently confirmed that prokaryotic operon structure is dynamic with significant alterations across environmental and experimental conditions, there are no comprehensive databases for studying such variations across prokaryotic transcriptomes. Currently our database contains nine bacterial organisms and 168 transcriptomes for which we predicted operons. User interface is simple and easy to use, in terms of visualization, downloading, and querying of data. In addition, because of its ability to load custom datasets, users can also compare their datasets with publicly available transcriptomic data of an organism.Conclusion. OperomeDB as a database should not only aid experimental groups working on transcriptome analysis of specific organisms but also enable studies related to computational and comparative operomics.
10
Jones, Daniel L., Robert C. Brewster, and Rob Phillips. "Promoter architecture dictates cell-to-cell variability in gene expression." Science 346, no. 6216 (December 18, 2014): 1533–36. http://dx.doi.org/10.1126/science.1255301.
Повний текст джерелаАнотація:
Variability in gene expression among genetically identical cells has emerged as a central preoccupation in the study of gene regulation; however, a divide exists between the predictions of molecular models of prokaryotic transcriptional regulation and genome-wide experimental studies suggesting that this variability is indifferent to the underlying regulatory architecture. We constructed a set of promoters in Escherichia coli in which promoter strength, transcription factor binding strength, and transcription factor copy numbers are systematically varied, and used messenger RNA (mRNA) fluorescence in situ hybridization to observe how these changes affected variability in gene expression. Our parameter-free models predicted the observed variability; hence, the molecular details of transcription dictate variability in mRNA expression, and transcriptional noise is specifically tunable and thus represents an evolutionarily accessible phenotypic parameter.
Дисертації з теми "Prokaryotic Transcription"
1
Martins, Leonardo Pedro Donas-Boto de Vilhena. "Stochastic model of transcription initiation of closely spaced promoters in escherichia coli." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/7009.
Повний текст джерелаАнотація:
Dissertação para obtenção do Grau de Mestre
em Engenharia BiomédicaThe regulatory mechanisms of transcription allow organisms to quickly adapt to changes in their environment and often act during transcription initiation. Here, a stochastic model of transcription initiation at the nucleotide level is proposed to study the dynamics of RNA production in closely spaced promoters and their regulatory mechanisms. We study how different arrangements (convergent e divergent), distance between transcription start sites (TSS), and various kinetic parameters affect the dynamics of RNA production. Further, we analyze how the kinetics of various steps in transcription initiation can be regulated by varying locations of repressor binding sites. From the results, we observe that the rate limiting steps have strong influence in the kinetics of RNA production. We find that interferences between RNA polymerases in divergent overlapped and convergent geometries causes the distribution of time intervals between the production of consecutive RNA molecules from each TSS to increase in mean and standard deviation, which leads to stronger fluctuations in the temporal levels of RNA molecules. We observe that small changes in the distance between TSSs can lead to abrupt transitions in the dynamics of RNA production, particularly when this change changes the geometry from overlapped to non-overlapped promoters. From the study of the correlation in the choices of directionality and on the time series of RNA productions we show that by tuning the distances and directions of the two TSS one can obtain both negative and positive correlations. We further show that distinct repression mechanisms of transcription initiation in steps such as the open and closed complex formation and promoter escape have different effects on the dynamics of RNA production. The study of these models will help the study of how genetic circuits have evolved and assist in designing artificial genetic circuits with desired dynamics.
2
Bandekar, Aditya C. "Cell Cycle Associated Gene Expression Predicts Function in Mycobacteria." eScholarship@UMMS, 2020. https://escholarship.umassmed.edu/gsbs_diss/1068.
Повний текст джерелаАнотація:
While the major events in prokaryotic cell cycle progression are likely to be coordinated with transcriptional and metabolic changes, these processes remain poorly characterized. Unlike many rapidly-growing bacteria, DNA replication and cell division are temporally-resolved in mycobacteria, making these slow-growing organisms a potentially useful system to investigate the prokaryotic cell cycle. To determine if cell-cycle dependent gene regulation occurs in mycobacteria, we characterized the temporal changes in the transcriptome of synchronously replicating populations of Mycobacterium tuberculosis (Mtb). By enriching for genes that display a sinusoidal expression pattern, we discover 485 genes that oscillate with a period consistent with the cell cycle. During cytokinesis, the timing of gene induction could be used to predict the timing of gene function, as mRNA abundance was found to correlate with the order in which proteins were recruited to the developing septum. Similarly, the expression pattern of primary metabolic genes could be used to predict the relative importance of these pathways for different cell cycle processes. Pyrimidine synthetic genes peaked during DNA replication and their depletion caused a filamentation phenotype that phenocopied defects in this process. In contrast, the IMP dehydrogenase guaB2 dedicated to guanosine synthesis displayed the opposite expression pattern and its depletion perturbed septation. Together, these data imply obligate coordination between primary metabolism and cell division, and identify periodically regulated genes that can be related to specific cell biological functions.
3
Dian, Cyril. "Adaptive Responses by Transcriptional Regulators to small molecules in Prokaryotes : Structural studies of two bacterial one-component signal transduction systems DntR and HpNikR." Doctoral thesis, Stockholm : Department of Biochemistry and Biophysics, Stockholm University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-7052.
Повний текст джерела
4
Elison, Kalman Grim. "Purification, functional characterization and crystallization of the PerR peroxide sensor from Saccharopolyspora erythraea." Thesis, Uppsala universitet, Strukturbiologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-387943.
Повний текст джерелаАнотація:
This report summarizes the work on the cloning, expression, and purification of PerR, a metal sensing regulator from Saccharopolyspora erythraea and the subsequent characterization using small angle X-ray scattering and other biochemical methods. The report aims to provide an insight into prokaryotic metal homeostasis, provide a better understanding of how PerR works and provide valuable information for the continued work on the crystallization of PerR.
5
Ott, Alban. "Approches bioinformatiques pour identifier et caractériser les ARN régulateurs chez les procaryotes." Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112029.
Повний текст джерелаАнотація:
L’objectif de cette thèse était de progresser dans la compréhension de la régulation génique ARN‑dépendante chez les procaryotes. Le développement de nouvelles approches bioinformatiques a permis de découvrir de nouveaux ARN régulateurs non-codant (ARNrnc), de les caractériser notamment évolutivement et d’identifier leurs cibles putatives. Les ARNrnc ont en commun de pouvoir modifier l’abondance de certaines protéines en interagissant avec l’ARN messager (ARNm) qui les code. Cet effet peut être obtenu selon divers modes d’action qui mènent à la distinction de trois classes d’ARNrnc, les petits ARN régulateurs (pARN), les ARN cis-régulateurs (ARNcis) et les ARN antisens (ARNa). Avec la généralisation des approches d‘identification expérimentale des ARN (transcriptomique), il devient plus facile d’obtenir la liste des pARN que d'identifier les ARNm qu’ils ciblent. Dans le cas des ARNcis, c’est l’inverse, les méthodes expérimentales ne permettent pas de les identifier, mais une fois connus leurs cibles sont évidentes.Pour répondre à ces problématiques, nous avons principalement développé deux nouvelles méthodes : la première permet de prédire des couples pARN/ARNm en se basant leurs profils d’expressions, les résultats nous ont permis de proposer un réseau de régulation pour lequel les pARN auraient un rôle central dans la sporulation bactérienne. La seconde permet d’identifier de nouveaux ARNcis dans les génomes sur la base d’un profilage phylogénétique. Nos résultats nous conduisent à penser que le nombre de pARN et d’ARNcis dans les génomes est actuellement sous estimé. Nous proposons aussi la présence de plusieurs ARNcis chez une Archée, dont un candidat capable de détecter des variations de températures.Les avancées réalisées lors de cette thèse ont permis de mieux appréhender l’importance des ARNrnc dans la régulation génique. Les ARNrnc sont présents dans plus d’organismes et en plus grand nombre que ce que nous le pensions jusqu’à présent. Ces résultats constituent des éléments supplémentaires en faveur d’un rôle plus central des pARN que ce qui était admis jusqu’alorsThe aim of this thesis was to improve our understanding of the RNA-dependent gene regulation in prokaryotes. Newly developed bioinformatics approaches revealed new non-coding regulatory RNAs and allowed us to identify putative targets.Regulatory RNAs can change the abundance of certain proteins by interacting with cognate messenger RNAs (mRNA). This effect is achieved through various modes of action that lead to the distinction of three RNA classes: small RNA (sRNA), cis-regulatory RNA (cisRNA) and antisense RNA (asRNA). With the generalization of experimental RNA identification (transcriptomics), it becomes easier to obtain the list of expressed RNA but most of their target mRNA remain unknown. Conversely, cisRNA cannot be easily identified through experimental procedures but their targets are obvious.To address these issues, we developed two new methods: the first predicts pairs of sRNA and mRNA targets based on the analysis of expression profiles and led us to propose a new regulatory network with sRNAs playing a central role in bacterial sporulation. The second identifies new RNAs in genomes based on the analysis of phylogenetic profiles. Our results suggest that the abundance of sRNAs and cisRNA were previously underestimated. We also suggest the presence of several cisRNAs in an Archaea, including a strong candidate of thermosensitive regulator.Progress made in this thesis contributed to a better understanding of RNA importance in bacterial cell regulation. Regulatory RNAs are abundant and present in more organisms than expected previously. These results are new evidences that the physiological roles of sRNAs are more central than was previously thought
6
Aditya, Kumar *. "Structural Feature of Prokaryotic Promoters and their Role in Gene Expression." Thesis, 2015. http://etd.iisc.ernet.in/2005/3528.
Повний текст джерелаАнотація:
Transcription initiation is an important step in the process of gene regulation in prokaryotes. Promoters are stretches of DNA sequence that are present in the upstream region of transcription start sites (TSSs), where RNA polymerase and other transcription factors bind to initiate transcription. Recent advancement in sequencing technologies has resulted in huge amount of raw data in the form of whole genome sequences. This sequence data has to be annotated, in order to identify coding, non-coding and regulatory regions. Computational tools are useful for a quick and fairly reliable annotation of many genome sequences. Promoter prediction is an important step in genome annotation process which is needed, not only for the validation of predicted genes, but also for the identification of novel genes, especially those coding for non-coding RNA, which are missed by gene prediction programs. DNA sequence dependent structural properties such as DNA duplex stability, bendability and intrinsic curvature have been found to be associated with promoter regions in all domains of life. The work presented in this thesis focuses on the analysis of these structural features in the promoter regions of published prokaryotic transcriptome data. Furthermore, promoters were predicted using these structural features and their role in gene expression were studied. The organization of thesis is as follows. An overview of transcription machinery of prokaryotes, promoter architecture, available promoter prediction programs and sequence dependent structural features is presented in chapter 1.
Chapter 2 describes the datasets and methods used in entire study.
Structural features of promoters associated with primary and operon TSSs of H.pylori26695 genes and their orthologs (chapter 3)
Promoter regions in genomic sequences from all domains of life show similar trends in their structural properties such as stability, bendability, curvature. This chapter dis-cuss the DNA duplex stability and bendability of various classes of promoter regions (based on the identification of different classes of transcription start sites, viz. primary, secondary, internal, operon TSSs etc, in transcriptome study) of Helicobacter pylori 26695 strain. It is found that the primary TSS and operon associated TSS promoters show significantly strong structural features in their promoter regions. DNA free energy based promoter prediction tool PromPredict has been used to annotate promoters of different classes and very high recall values (80%) are obtained for primary TSS. Orthologous genes from 10 different strains of H. pylori show conservation of structural properties in promoter regions as well as coding regions. PromPredict annotates promoters of orthologous genes with very high recall and precision values. DNA duplex stability of promoter region is conserved in the orthologous genes in 10 different strains of Helicobacter pylori genome.
Sequence dependent structural features of promoters in prokaryotic transcriptome (chapter 4)
Next-generation sequencing studies have revealed that a wide range of transcripts such as primary, internal, antisense and non-coding RNA, are present in the prokaryotic transcriptome and a large fraction of them are functionally involved in various regulatory activities. Identification of promoters associated with different transcripts is important for characterization of transcriptome. The current chapter discusses DNA sequence dependent structural properties like stability, bendability and curvature in the promoter region of six different prokaryotic transcriptomes (Helicobacter pylori, Anabaena, Synechocystis, Escherichia coli, Salmonella and Klebsiella). Using these structural features, promoters associated with different category of transcripts were predicted, which constitute an integral part of the transcriptome. Promoter annotation using structural features is fairly accurate and reliable as compared to motif-based approach since different category of transcripts show poor sequence conservation in the promoter region. Most importantly, it is universal in nature unlike sequence-based approach that is generally organism specific.
Role of sequence dependent structural properties in gene expression in prokaryotes (chapter 5)
DNA duplex stability, bendability and intrinsic curvature play crucial roles in the process of transcription initiation. Hence, in order to understand the relationship be-tween these structural features and gene expression, the relative differences in stability, bendability and curvature in the promoter regions of high and low expressed genes were studied. It is found that these features are relatively accentuated in the promoter regions associated with high gene expression as compared to low gene expression. Promoter regions associated with high gene expression are annotated more reliably using DNA structural features, compared to those for low gene expression.
Sequence dependent structural properties in the promoter region of essential and non-essential genes of the prokaryotes (chapter 6)
Essential genes are the minimal possible set of genes required for the survival of organism. These sets of genes can be identified by experiments such as single gene deletion and transposon mediated inactivation. Here, the analysis of DNA duplex stability and bendability in the promoter regions of essential and nonessential genes of prokaryotes is reported. It is found that the average free energy and bendability pro-files are distinct in the promoters regions of essential and nonessential genes. Whole genome promoter predictions using in-house program, PromPredict, for essential and nonessential genes has also been carried out.
Chapter 7 present the summary and conclusion of the entire thesis work followed by future perspectives in the field.
Optimization of PromPredict algorithm and updating PromBase with newly sequenced genomes (Appendix A)
PromPredict is an in-house program, which is based on the relative stability of the DNA in flanking regions. It was found to perform well in predicting promoters across all organisms. In previous studies, it was observed that for organisms having low genomic GC content (<35%), promoter prediction resulted in low precision values, which indicates higher false positive rate. Threshold values of PromPredict algorithm were re-vised in order to optimize the algorithm with low false positive rate. PromBase is a comparative genomics database of microbial genomes. It stores different genomic and structural properties of the microbial genomes. It also displays the predictions obtained from PromPredict in a graphical as well as tabular format. Newly sequenced genomes were downloaded from NCBI and processed using in-house programs and added to the mysql database (back end of the PromBase). Stability profiles for predictions were also added for the RNA coding genes, earlier only profiles for protein coding genes were displayed. Comparative genomics of asymmetric gene orientation in prokaryotes (Appendix B)
Transcription proceeds in 5’ to 3’ direction on the template strand, hence it provides directionality. Prokaryotic genomes show asymmetry in gene orientation on leading and lagging strands. The different phyla of prokaryotes were analyzed in terms of asymmetry in gene orientation. It is found that organisms belonging to a particular phyla known as “Firmicutes”, show high asymmetry in gene orientation, which are known to have different DNA polymerase systems for replication.
7
Chetal, Kashish. "OperomeDB: database of condition specific transcription in prokaryotic genomes and genomic insights of convergent transcription in bacterial genomes." Thesis, 2014. http://hdl.handle.net/1805/6228.
Повний текст джерелаАнотація:
Indiana University-Purdue University Indianapolis (IUPUI)My thesis comprises of two individual projects: 1) we have developed a database for operon prediction using high-throughput sequencing datasets for bacterial genomes. 2) Genomics and mechanistic insights of convergent transcription in bacterial genomes. In the first project we developed a database for the prediction of operons for bacterial genomes using RNA-seq datasets, we predicted operons for bacterial genomes. RNA-seq datasets with different condition for each bacterial genome were taken into account and predicted operons using Rockhopper. We took RNA-seq datasets from NCBI with distinct experimental conditions for each bacterial genome into account and analyzed using tool for operon prediction. Currently our database contains 9 bacterial organisms for which we predicted operons. User interface is simple and easy to use, in terms of visualization, downloading and querying of data. In our database user can browse through reference genome, genes present in that genome and operons predicted from different RNA-seq datasets. Further in the second project, we studied the genomic and mechanistic insights of convergent transcription in bacterial genomes. We know that convergent gene pairs with overlapping head-to-head configuration are widely spread across both eukaryotic and prokaryotic genomes. They are believed to contribute to the regulation of genes at both transcriptional and post-transcriptional levels, although factors contributing to their abundance across genomes and mechanistic basis for their prevalence are poorly understood. In this study, we explore the role of various factors contributing to convergent overlapping transcription in bacterial genomes. Our analysis shows that the proportion of convergent overlapping gene pairs (COGPs) in a genome is affected due to endospore formation, bacterial habitat, oxygen requirement, GC content and the temperature range. In particular, we show that bacterial genomes thriving in specialized habitats, such as thermophiles, exhibit a high proportion of COGPs. Our results also conclude that the density distribution of COGPs across the genomes is high for shorter overlaps with increased conservation of distances for decreasing overlaps. Our study further reveals that COGPs frequently contain stop codon overlaps with the middle base position exhibiting mismatches between complementary strands. Further, for the functional analysis using cluster of orthologous groups (COGs) annotations suggested that cell motility, cell metabolism, storage and cell signaling are enriched among COGPs, suggesting their role in processes beyond regulation. Our analysis provides genomic insights into this unappreciated regulatory phenomenon, allowing a refined understanding of their contribution to bacterial phenotypes.
8
Vogel, Sabine Katja [Verfasser]. "Mechanistic studies on transcription activation via DNA looping in a prokaryotic promoter-enhancer system / presented by Sabine Katja Vogel." 2004. http://d-nb.info/972519467/34.
Повний текст джерела
9
Lyubetskaya, Anna. "Transcription factor binding distribution and properties in prokaryotes." Thesis, 2015. https://hdl.handle.net/2144/15425.
Повний текст джерелаАнотація:
The canonical model of transcriptional regulation in prokaryotes restricted binding site locations to promoter regions and suggested that the binding sequences serve as the main determinants of binding. In this dissertation, I challenge these assumptions.
As a member of the TB Systems Biology Consortium, I analyzed and validated ChIP-Seq and microarray experiments for over 100 transcription factors (TFs). In order to study the transcriptional functions of predicted binding sites, I integrated binding and expression data and assigned potential regulatory roles to 20% of the binding sites. Stronger binding sites were more often associated with regulation than weaker sites, suggesting a correlation between binding strength and regulatory impact. Seventy-six percent of the sites fell into annotated coding regions and a significant proportion was assigned to regulatory functions.
To study the importance of binding sequences, I compared experimental sites with computational motif predictions. Although a conservative binding motif was found for most TFs, only a fraction of the observed motifs appeared bound in the experiment. Some low-affinity binding sites appeared occupied by the corresponding TF while many high-affinity binding sites were not. Interestingly, I found exactly the same nucleotide sequences (up to 15 residues long) bound in one area of the genome but not bound in another area, pointing to DNA accessibility as an important factor for in vivo binding.
To investigate the evolutionary conservation of binding-site occupancy, sequence, and transcriptional impact, I analyzed ChIP-Seq and expression experiments for five conserved TFs for two-to-four Mycobacterial relatives.
The regulon composition showed significantly less conservation than expected from the overall gene conservation level across Mycobacteria. Despite expectations, sequence conservation did not serve as a good indicator of whether or not a computationally predicted motif was bound experimentally; and in some cases, a fully conserved motif was bound in one relative but not in the other. Conservation of genic binding sites was higher than expected from the random model, adding to the evidence that at least some genic sites are functional. Understanding the evolutionary story of binding sites allowed me to explain unusual site configurations, some of which indicated a role for DNA looping.
10
Wu, Fu-Rong, and 吳阜融. "Uncovering the Bursting Phenomenon of Gene Transcription in Prokaryotes." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/90869861888122197099.
Повний текст джерелаАнотація:
碩士國立臺灣大學
電子工程學研究所
100
Gene expression consists of two main steps: transcription and translation. It origins from the binding of RNA polymerases to their target sites on DNA sequences. The mechanism how RNA polymerases locate their target sites remains a puzzling mystery. It affects almost all aspects of biology. Over the past few decades, many related studies have been made on the regulation of gene expression. Although several models have been proposed and demonstrated for the mechanism, many details of the elementary steps of gene transcription in vivo are still open for debate. This thesis aims to explain how the motion of RNA polymerases affects gene transcription dynamics and the transcriptional bursting. We introduce a random walk model for the motion of RNA polymerases along DNA during the search of target locations and the transcription process. In order to verify our model, we apply Monte Carlo simulation and simplified statistical computation to compare our prediction to prior experimental data. The findings suggest that under proper assumptions, our model is able to explain the transcriptional bursting phenomenon, and computer simulations are consistent with prior experimental data. Our results also suggest some parameters which await experiments to justify their biological significances.
Книги з теми "Prokaryotic Transcription"
1
Transcription Regulation in Prokaryotes. Oxford University Press, USA, 2000.
Знайти повний текст джерела
2
Kirchman, David L. Genomes and meta-omics for microbes. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789406.003.0005.
Повний текст джерелаАнотація:
The sequencing of entire genomes of microbes grown in pure cultures is now routine. The sequence data from cultivated microbes have provided insights into these microbes and their uncultivated relatives. Sequencing studies have found that bacterial genomes range from 0.18 Mb (intracellular symbiont) to 13 Mb (a soil bacterium), whereas genomes of eukaryotes are much bigger. Genomes from eukaryotes and prokaryotes are organized quite differently. While bacteria and their small genomes often grow faster than eukaryotes, there is no correlation between genome size and growth rates among the bacteria examined so far. Genomic studies have also highlighted the importance of genes exchanged (“horizontal gene transfer”) between organisms, seemingly unrelated, as defined by rRNA gene sequences. Microbial ecologists use metagenomics to sequence all microbes in a community. This approach has revealed unsuspected physiological processes in microbes, such as the occurrence of a light-driven proton pump, rhodopsin, in bacteria (dubbed proteorhodopsin). Genomes from single cells isolated by flow cytometry have also provided insights about the ecophysiology of both bacteria and protists. Oligotrophic bacteria have streamlined genomes, which are usually small but with a high fraction of genomic material devoted to protein-encoding genes, and few transcriptional control mechanisms. The study of all transcripts from a natural community, metatranscriptomics, has been informative about the response of eukaryotes as well as bacteria to changing environmental conditions.
Частини книг з теми "Prokaryotic Transcription"
1
Sybers, David, Daniel Charlier, and Eveline Peeters. "In Vitro Transcription Assay for Archaea Belonging to Sulfolobales." In Prokaryotic Gene Regulation, 81–102. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2413-5_6.
Повний текст джерела
2
Seshasayee, Aswin Sai Narain, Karthikeyan Sivaraman, and Nicholas M. Luscombe. "An Overview of Prokaryotic Transcription Factors." In Subcellular Biochemistry, 7–23. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-9069-0_2.
Повний текст джерела
3
Ledesma, Leonardo, Rafael Hernandez-Guerrero, and Ernesto Perez-Rueda. "Prediction of DNA-Binding Transcription Factors in Bacteria and Archaea Genomes." In Prokaryotic Gene Regulation, 103–12. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2413-5_7.
Повний текст джерела
4
Hilchey, S., J. Xu, and G. B. Koudelka. "Indirect Effects of DNA Sequence on Transcriptional Activation by Prokaryotic DNA Binding Proteins." In Mechanisms of Transcription, 115–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60691-5_9.
Повний текст джерела
5
Bernauw, Amber Joka, Veerke De Kock, and Indra Bervoets. "In Vivo Screening Method for the Identification and Characterization of Prokaryotic, Metabolite-Responsive Transcription Factors." In Prokaryotic Gene Regulation, 113–41. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2413-5_8.
Повний текст джерела
6
Buc, H. "Initiation of Prokaryotic Transcription-Kinetic and Structural Approaches." In Nucleic Acids and Molecular Biology, 186–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-46596-3_11.
Повний текст джерела
7
Kigawa, Takanori. "Cell-Free Protein Preparation Through Prokaryotic Transcription–Translation Methods." In Methods in Molecular Biology, 1–10. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-60327-331-2_1.
Повний текст джерела
8
Oehler, Stefan, and Benno Müller-Hill. "Prokaryotic control of transcription: How and why does it differ from eukaryotic control?" In Inducible Gene Expression, Volume 1, 1–24. Boston, MA: Birkhäuser Boston, 1995. http://dx.doi.org/10.1007/978-1-4684-6840-3_1.
Повний текст джерела
9
Laub, Michael T., and R. Frank Rosenzweig. "Transcriptional Profiling in Bacteria Using Microarrays." In Prokaryotic Genomics, 131–44. Basel: Birkhäuser Basel, 2003. http://dx.doi.org/10.1007/978-3-0348-8963-6_11.
Повний текст джерела
10
Georg, Jens, and Wolfgang R. Hess. "Widespread Antisense Transcription in Prokaryotes." In Regulating with RNA in Bacteria and Archaea, 191–210. Washington, DC, USA: ASM Press, 2018. http://dx.doi.org/10.1128/9781683670247.ch12.
Повний текст джерелаТези доповідей конференцій з теми "Prokaryotic Transcription"
1
Ni, Chung-En, Duy-Phuong Doan, Yen-Jung Chiu, and Yen-Hua Huang. "TSSNet – A Deep Neural Network Model for Predicting Prokaryotic Transcription Start Sites." In 2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE). IEEE, 2022. http://dx.doi.org/10.1109/bibe55377.2022.00054.
Повний текст джерела
2
Polstein, Lauren R., and Charles A. Gersbach. "Photoregulated Gene Expression in Human Cells With Light-Inducible Engineered Transcription Factors." In ASME 2012 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/sbc2012-80573.
Повний текст джерелаАнотація:
Systems for controlling gene expression in mammalian cells have a wide range of applications in medicine, biotechnology and basic science. An ideal gene regulatory system would allow for precise and specific control over the magnitude and kinetics of gene expression in space and time, while also exerting minimal influence on other genes and cellular components. Several gene regulatory systems have been developed in which orthogonal transcription machinery from prokaryotes or insects has been imported into mammalian cells and used to control the expression of a specific gene. Despite the transformative impact of these systems in biomedical and biological research, several limitations of these technologies restrict the scope of possible applications. For example, gene expression in these systems is controlled by a freely diffusible small molecule, such as an antibiotic or steroid. Consequently, it is not possible to achieve spatial control over gene expression within cell culture, tissues, or whole organisms. This is in contrast to natural mechanisms of biological regulation in which spatial control is critical, such as developmental patterning and tissue morphogenesis. Second, dynamic gene regulation requires the removal of these small molecules, which may be slow, laborious, and/or impractical for a particular application. To overcome these limitations, we have engineered an optogenetic system in which the magnitude of gene expression in human cells can be finely tuned by photoregulated synthetic transcription factors.
Звіти організацій з теми "Prokaryotic Transcription"
1
Schuster, Gadi, and David Stern. Integrated Studies of Chloroplast Ribonucleases. United States Department of Agriculture, September 2011. http://dx.doi.org/10.32747/2011.7697125.bard.
Повний текст джерелаАнотація:
Gene regulation at the RNA level encompasses multiple mechanisms in prokaryotes and eukaryotes, including splicing, editing, endo- and exonucleolytic cleavage, and various phenomena related to small or interfering RNAs. Ribonucleases are key players in nearly all of these post-transcriptional mechanisms, as the catalytic agents. This proposal continued BARD-funded research into ribonuclease activities in the chloroplast, where RNase mutation or deficiency can cause metabolic defects and is often associated with plant chlorosis, embryo or seedling lethality, and/or failure to tolerate nutrient stress. The first objective of this proposal was to examined a series of point mutations in the PNPase enzyme of Arabidopsis both in vivo and in vitro. This goal is related to structure-function analysis of an enzyme whose importance in many cellular processes in prokaryotes and eukaryotes has only begun to be uncovered. PNPase substrates are mostly generated by endonucleolytic cleavages for which the catalytic enzymes remain poorly described. The second objective of the proposal was to examine two candidate enzymes, RNase E and RNase J. RNase E is well-described in bacteria but its function in plants was still unknown. We hypothesized it catalyzes endonucleolytic cleavages in both RNA maturation and decay. RNase J was recently discovered in bacteria but like RNase E, its function in plants had yet to be explored. The results of this work are described in the scientific manuscripts attached to this report. We have completed the first objective of characterizing in detail TILLING mutants of PNPase Arabidopsis plants and in parallel introducing the same amino acids changes in the protein and characterize the properties of the modified proteins in vitro. This study defined the roles for both RNase PH core domains in polyadenylation, RNA 3’-end maturation and intron degradation. The results are described in the collaborative scientific manuscript (Germain et al 2011). The second part of the project aimed at the characterization of the two endoribonucleases, RNase E and RNase J, also in this case, in vivo and in vitro. Our results described the limited role of RNase E as compared to the pronounced one of RNase J in the elimination of antisense transcripts in the chloroplast (Schein et al 2008; Sharwood et al 2011). In addition, we characterized polyadenylation in the chloroplast of the green alga Chlamydomonas reinhardtii, and in Arabidopsis (Zimmer et al 2009). Our long term collaboration enabling in vivo and in vitro analysis, capturing the expertise of the two collaborating laboratories, has resulted in a biologically significant correlation of biochemical and in planta results for conserved and indispensable ribonucleases. These new insights into chloroplast gene regulation will ultimately support plant improvement for agriculture.