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Journal articles on the topic 'Prokaryotic Transcription'

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Published: 6 September 2023

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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.

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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.
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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.

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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.

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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.

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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.
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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.

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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.
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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.

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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.

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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.

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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.

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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.
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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.

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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.
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11

Hwang, Seungha, Jimin Lee, and Jin Young Kang. "Erratum: Prokaryotic transcription regulation by the nascent RNA elements." BIODESIGN 9, no. 1 (March 30, 2021): 23. http://dx.doi.org/10.34184/kssb.2021.9.1.23.

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12

Dove, Simon L., J. Keith Joung, and Ann Hochschild. "Activation of prokaryotic transcription through arbitrary protein–protein contacts." Nature 386, no. 6625 (April 1997): 627–30. http://dx.doi.org/10.1038/386627a0.

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13

Cenatiempo, Y. "Prokaryotic gene expression in vitro: transcription-translation coupled systems." Biochimie 68, no. 4 (April 1986): 505–15. http://dx.doi.org/10.1016/s0300-9084(86)80195-x.

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14

Hochschild, Ann, and Simon L. Dove. "Protein–Protein Contacts that Activate and Repress Prokaryotic Transcription." Cell 92, no. 5 (March 1998): 597–600. http://dx.doi.org/10.1016/s0092-8674(00)81126-5.

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15

Minaev, Mihail Yu, and Anzhelika A. Makhova. "THE STUDY OF PROKARYOTIC GENE EXPRESSION." Theory and practice of meat processing 3, no. 2 (July 11, 2018): 40–52. http://dx.doi.org/10.21323/2414-438x-2018-3-2-40-52.

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One of the methods to evaluate the level of gene expression is a real-time quantitative polymerase chain reaction (qPCR). Interest in the study of molecular mechanisms of gene expression and its evaluation in prokaryotes is due to the lack of research on this issue and a number of methodological problems. The paper presents a study of gene expression mechanism in prokaryotes evidence from Aeromonas salmonicida AS1 gyrase B and collagenase genes. As a result of the research, Random primer and oligo (dT) primer (two 3’-terminal nucleotides of the primer complementary to stop codon nucleotides of the transcribed DNA sequence) with anchor and adapter of our own design were tested, which are used in the reaction of reverse transcription. The use of oligo (dT) primer became possible only after polyadenylation of extracted RNA using special poly-A polymerase kit. It is determined that the developed protocol of reverse transcription (RT) using oligo (dT) primer and adapter with certain sequence on its 5’-terminus designed for further annealing of the reverse primer during real-time PCR along with preliminary polyadenylation of RNA excludes specific amplification of the background genomic DNA. This technique may be applied in evaluating the expression level of low-expression genes when high background genomic DNA content is found in the RNA sample, e.g. at the end of logarithmic growth of prokaryotic cells.ContributionAll authors bear responsibility for the work and presented data. All authors made an equal contribution to the work. Minaev M. Yu. developed scientific and methodological approaches to work, determined the scope of research, analyzed the data obtained, performed the narrative and corrected it in final. Makhova A.A. selected research objects, carried out RNA extraction, reverse transcription and PCR analysis, performed the narrative part. The authors were equally involved in writing the manuscript and bear the equal responsibility for plagiarism.Conflict of interestThe authors declare no conflict of interest.
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16

Tromer, Eelco C., Jolien J. E. van Hooff, Geert J. P. L. Kops, and Berend Snel. "Mosaic origin of the eukaryotic kinetochore." Proceedings of the National Academy of Sciences 116, no. 26 (May 24, 2019): 12873–82. http://dx.doi.org/10.1073/pnas.1821945116.

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The emergence of eukaryotes from ancient prokaryotic lineages embodied a remarkable increase in cellular complexity. While prokaryotes operate simple systems to connect DNA to the segregation machinery during cell division, eukaryotes use a highly complex protein assembly known as the kinetochore. Although conceptually similar, prokaryotic segregation systems and the eukaryotic kinetochore are not homologous. Here we investigate the origins of the kinetochore before the last eukaryotic common ancestor (LECA) using phylogenetic trees, sensitive profile-versus-profile homology detection, and structural comparisons of its protein components. We show that LECA’s kinetochore proteins share deep evolutionary histories with proteins involved in a few prokaryotic systems and a multitude of eukaryotic processes, including ubiquitination, transcription, and flagellar and vesicular transport systems. We find that gene duplications played a major role in shaping the kinetochore; more than half of LECA’s kinetochore proteins have other kinetochore proteins as closest homologs. Some of these have no detectable homology to any other eukaryotic protein, suggesting that they arose as kinetochore-specific folds before LECA. We propose that the primordial kinetochore evolved from proteins involved in various (pre)eukaryotic systems as well as evolutionarily novel folds, after which a subset duplicated to give rise to the complex kinetochore of LECA.
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17

Mackiewicz, Pawel, Agnieszka Gierlik, Maria Kowalczuk, Miroslaw R. Dudek, and Stanislaw Cebrat. "How Does Replication-Associated Mutational Pressure Influence Amino Acid Composition of Proteins?" Genome Research 9, no. 5 (May 1, 1999): 409–16. http://dx.doi.org/10.1101/gr.9.5.409.

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We have performed detrended DNA walks on whole prokaryotic genomes, on noncoding sequences and, separately, on each position in codons of coding sequences. Our method enables us to distinguish between the mutational pressure associated with replication and the mutational pressure associated with transcription and other mechanisms that introduce asymmetry into prokaryotic chromosomes. In many prokaryotic genomes, each component of mutational pressure affects coding sequences not only in silent positions but also in positions in which changes cause amino acid substitutions in coded proteins. Asymmetry in the silent positions of codons differentiates the rate of translation of mRNA produced from leading and lagging strands. Asymmetry in the amino acid composition of proteins resulting from replication-associated mutational pressure also corresponds to leading and lagging roles of DNA strands, whereas asymmetry connected with transcription and coding function corresponds to the distance of genes from the origin or terminus of chromosome replication.
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18

Becskei, Attila. "Tuning up Transcription Factors for Therapy." Molecules 25, no. 8 (April 20, 2020): 1902. http://dx.doi.org/10.3390/molecules25081902.

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The recent developments in the delivery and design of transcription factors put their therapeutic applications within reach, exemplified by cell replacement, cancer differentiation and T-cell based cancer therapies. The success of such applications depends on the efficacy and precision in the action of transcription factors. The biophysical and genetic characterization of the paradigmatic prokaryotic repressors, LacI and TetR and the designer transcription factors, transcription activator-like effector (TALE) and CRISPR-dCas9 revealed common principles behind their efficacy, which can aid the optimization of transcriptional activators and repressors. Further studies will be required to analyze the linkage between dissociation constants and enzymatic activity, the role of phase separation and squelching in activation and repression and the long-range interaction of transcription factors with epigenetic regulators in the context of the chromosomes. Understanding these mechanisms will help to tailor natural and synthetic transcription factors to the needs of specific applications.
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19

Dudek, Christian-Alexander, and Dieter Jahn. "PRODORIC: state-of-the-art database of prokaryotic gene regulation." Nucleic Acids Research 50, no. D1 (November 26, 2021): D295—D302. http://dx.doi.org/10.1093/nar/gkab1110.

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Abstract PRODORIC is worldwide one of the largest collections of prokaryotic transcription factor binding sites from multiple bacterial sources with corresponding interpretation and visualization tools. With the introduction of PRODORIC2 in 2017, the transition to a modern web interface and maintainable backend was started. With this latest PRODORIC release the database backend is now fully API-based and provides programmatical access to the complete PRODORIC data. The visualization tools Genome Browser and ProdoNet from the original PRODORIC have been reintroduced and were integrated into the PRODORIC website. Missing input and output options from the original Virtual Footprint were added again for position weight matrix pattern-based searches. The whole PRODORIC dataset was reannotated. Every transcription factor binding site was re-evaluated to increase the overall database quality. During this process, additional parameters, like bound effectors, regulation type and different types of experimental evidence have been added for every transcription factor. Additionally, 109 new transcription factors and 6 new organisms have been added. PRODORIC is publicly available at https://www.prodoric.de.
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20

Bernardo, Nerea, Isidro Crespo, Anna Cuppari, Wilfried J. J. Meijer, and D. Roeland Boer. "A tetramerization domain in prokaryotic and eukaryotic transcription regulators homologous to p53." Acta Crystallographica Section D Structural Biology 79, no. 3 (March 1, 2023): 259–67. http://dx.doi.org/10.1107/s2059798323001298.

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Transcriptional regulation usually requires the action of several proteins that either repress or activate a promotor of an open reading frame. These proteins can counteract each other, thus allowing tight regulation of the transcription of the corresponding genes, where tight repression is often linked to DNA looping or cross-linking. Here, the tetramerization domain of the bacterial gene repressor Rco from Bacillus subtilis plasmid pLS20 (RcopLS20) has been identified and its structure is shown to share high similarity to the tetramerization domain of the well known p53 family of human tumor suppressors, despite lacking clear sequence homology. In RcopLS20, this tetramerization domain is responsible for inducing DNA looping, a process that involves multiple tetramers. In accordance, it is shown that RcopLS20 can form octamers. This domain was named TetDloop and its occurrence was identified in other Bacillus species. The TetDloop fold was also found in the structure of a transcriptional repressor from Salmonella phage SPC32H. It is proposed that the TetDloop fold has evolved through divergent evolution and that the TetDloop originates from a common ancestor predating the occurrence of multicellular life.
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21

Ortet, Philippe, Gilles De Luca, David E. Whitworth, and Mohamed Barakat. "P2TF: a comprehensive resource for analysis of prokaryotic transcription factors." BMC Genomics 13, no. 1 (2012): 628. http://dx.doi.org/10.1186/1471-2164-13-628.

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22

Zuo, Yong-chun, and Qian-zhong Li. "The hidden physical codes for modulating the prokaryotic transcription initiation." Physica A: Statistical Mechanics and its Applications 389, no. 19 (October 2010): 4217–23. http://dx.doi.org/10.1016/j.physa.2010.05.034.

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23

Roy, Sourav Singha, Monobesh Patra, Tarakdas Basu, Rakhi Dasgupta, and Angshuman Bagchi. "Evolutionary analysis of prokaryotic heat-shock transcription regulatory protein σ32." Gene 495, no. 1 (March 2012): 49–55. http://dx.doi.org/10.1016/j.gene.2011.12.043.

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24

Chen, Liang-Jwu, and Emil M. Orozco. "Recognition of prokaryotic transcription terminators by spinach chloroplast RNA polymerase." Nucleic Acids Research 16, no. 17 (1988): 8411–31. http://dx.doi.org/10.1093/nar/16.17.8411.

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25

Wei, Wenping, Yanzhe Shang, Ping Zhang, Yong Liu, Di You, Bincheng Yin, and Bangce Ye. "Engineering Prokaryotic Transcriptional Activator XylR as a Xylose-Inducible Biosensor for Transcription Activation in Yeast." ACS Synthetic Biology 9, no. 5 (April 8, 2020): 1022–29. http://dx.doi.org/10.1021/acssynbio.0c00122.

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26

Macadlo, Lauren A., Iskander M. Ibrahim, and Sujith Puthiyaveetil. "Sigma factor 1 in chloroplast gene transcription and photosynthetic light acclimation." Journal of Experimental Botany 71, no. 3 (October 23, 2019): 1029–38. http://dx.doi.org/10.1093/jxb/erz464.

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Abstract Sigma factors are dissociable subunits of bacterial RNA polymerase that ensure efficient transcription initiation from gene promoters. Owing to their prokaryotic origin, chloroplasts possess a typical bacterial RNA polymerase together with its sigma factor subunit. The higher plant Arabidopsis thaliana contain as many as six sigma factors for the hundred or so of its chloroplast genes. The role of this relatively large number of transcription initiation factors for the miniature chloroplast genome, however, is not fully understood. Using two Arabidopsis T-DNA insertion mutants, we show that sigma factor 1 (SIG1) initiates transcription of a specific subset of chloroplast genes. We further show that the photosynthetic control of PSI reaction center gene transcription requires complementary regulation of the nuclear SIG1 gene at the transcriptional level. This SIG1 gene regulation is dependent on both a plastid redox signal and a light signal transduced by the phytochrome photoreceptor.
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27

Binas, Oliver, Tatjana Schamber, and Harald Schwalbe. "The conformational landscape of transcription intermediates involved in the regulation of the ZMP-sensing riboswitch from Thermosinus carboxydivorans." Nucleic Acids Research 48, no. 12 (June 1, 2020): 6970–79. http://dx.doi.org/10.1093/nar/gkaa427.

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Abstract Recently, prokaryotic riboswitches have been identified that regulate transcription in response to change of the concentration of secondary messengers. The ZMP (5-Aminoimidazole-4-carboxamide ribonucleotide (AICAR))-sensing riboswitch from Thermosinus carboxydivorans is a transcriptional ON-switch that is involved in purine and carbon-1 metabolic cycles. Its aptamer domain includes the pfl motif, which features a pseudoknot, impeding rho-independent terminator formation upon stabilization by ZMP interaction. We herein investigate the conformational landscape of transcriptional intermediates including the expression platform of this riboswitch and characterize the formation and unfolding of the important pseudoknot structure in the context of increasing length of RNA transcripts. NMR spectroscopic data show that even surprisingly short pre-terminator stems are able to disrupt ligand binding and thus metabolite sensing. We further show that the pseudoknot structure, a prerequisite for ligand binding, is preformed in transcription intermediates up to a certain length. Our results describe the conformational changes of 13 transcription intermediates of increasing length to delineate the change in structure as mRNA is elongated during transcription. We thus determine the length of the key transcription intermediate to which addition of a single nucleotide leads to a drastic drop in ZMP affinity.
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28

Tooba Khalid, Aqsa Khalid, and Sikander Ali. "A critical review on the progression of gene expression in prokaryotic and eukaryotic animals." International Journal of Science and Technology Research Archive 3, no. 2 (November 30, 2022): 060–72. http://dx.doi.org/10.53771/ijstra.2022.3.2.0108.

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This article is totally based on the literature review about gene expression. Gene is the part of the DNA that is responsible for the formation of the genotype and then a phenotype. Gene can only be expressed in case of formation of protein. The process of the gene expression is accomplished in the two steps; Transcription and translation. Transcription is the process of the formation of the mRNA. Transcription proceeds in the three steps. In initiation step the RNA polymerase moves on the unwind DNA strand until the promoter sequence is reached, next is the elongation step in the newly synthesized RNA strand elongates, the process terminates as the RNA polymerase realize the termination sequence. After the mRNA is formed it is released into the cytoplasm without any alterations in case of prokaryotes, but in case of eukaryotes post transcriptional modifications takes place which include capping, tailing and splicing. Translation is the process of the formation of protein from mRNA. Translation proceeds in the four steps in which the t RNA is charged, the initiation complex is formed with Met-tRNA at the P site start codon is recognized after binding of the ribosomal subunits to mRNA, in elongation step the peptide bond is formed and the polypeptide chain grows, stop codons enters at the A site and thus the process is terminated.
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29

van Hijum, Sacha A. F. T., Marnix H. Medema, and Oscar P. Kuipers. "Mechanisms and Evolution of Control Logic in Prokaryotic Transcriptional Regulation." Microbiology and Molecular Biology Reviews 73, no. 3 (September 2009): 481–509. http://dx.doi.org/10.1128/mmbr.00037-08.

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SUMMARY A major part of organismal complexity and versatility of prokaryotes resides in their ability to fine-tune gene expression to adequately respond to internal and external stimuli. Evolution has been very innovative in creating intricate mechanisms by which different regulatory signals operate and interact at promoters to drive gene expression. The regulation of target gene expression by transcription factors (TFs) is governed by control logic brought about by the interaction of regulators with TF binding sites (TFBSs) in cis-regulatory regions. A factor that in large part determines the strength of the response of a target to a given TF is motif stringency, the extent to which the TFBS fits the optimal TFBS sequence for a given TF. Advances in high-throughput technologies and computational genomics allow reconstruction of transcriptional regulatory networks in silico. To optimize the prediction of transcriptional regulatory networks, i.e., to separate direct regulation from indirect regulation, a thorough understanding of the control logic underlying the regulation of gene expression is required. This review summarizes the state of the art of the elements that determine the functionality of TFBSs by focusing on the molecular biological mechanisms and evolutionary origins of cis-regulatory regions.
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30

Budarina, Zhanna I., Dmitri V. Nikitin, Nikolay Zenkin, Marina Zakharova, Ekaterina Semenova, Michael G. Shlyapnikov, Ekaterina A. Rodikova, et al. "A new Bacillus cereus DNA-binding protein, HlyIIR, negatively regulates expression of B. cereus haemolysin II." Microbiology 150, no. 11 (November 1, 2004): 3691–701. http://dx.doi.org/10.1099/mic.0.27142-0.

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Haemolysin II, HlyII, is one of several cytotoxic proteins produced by Bacillus cereus, an opportunistic human pathogen that causes food poisoning. The hlyII gene confers haemolytic activity to Escherichia coli cells. Here a new B. cereus gene, hlyIIR, which is located immediately downstream of hlyII and regulates hlyII expression, is reported. The deduced amino acid sequence of HlyIIR is similar to prokaryotic DNA-binding transcriptional regulators of the TetR/AcrA family. Measurements of haemolytic activity levels and of hlyII promoter activity levels using gene fusions and primer-extension assays demonstrated that, in E. coli, hlyII transcription decreased in the presence of hlyIIR. Recombinant HlyIIR binds to a 22 bp inverted DNA repeat centred 48 bp upstream of the hlyII promoter transcription initiation point. In vitro transcription studies showed that HlyIIR inhibits transcription from the hlyII promoter by binding to the 22 bp repeat and RNA polymerase, and by decreasing the formation of the catalytically competent open promoter complex.
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31

Espinal-Enríquez, Jesús, Daniel González-Terán, and Enrique Hernández-Lemus. "The Transcriptional Network Structure of a Myeloid Cell: A Computational Approach." International Journal of Genomics 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/4858173.

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Understanding the general principles underlying genetic regulation in eukaryotes is an incomplete and challenging endeavor. The lack of experimental information regarding the regulation of the whole set of transcription factors and their targets in different cell types is one of the main reasons to this incompleteness. So far, there is a small set of curated known interactions between transcription factors and their downstream genes. Here, we built a transcription factor network for human monocytic THP-1 myeloid cells based on the experimentally curated FANTOM4 database where nodes are genes and the experimental interactions correspond to links. We present the topological parameters which define the network as well as some global structural features and introduce a relative inuence parameter to quantify the relevance of a transcription factor in the context of induction of a phenotype. Genes like ZHX2, ADNP, or SMAD6 seem to be highly regulated to avoid an avalanche transcription event. We compare these results with those of RegulonDB, a highly curated transcriptional network for the prokaryotic organism E. coli, finding similarities between general hallmarks on both transcriptional programs. We believe that an approach, such as the one shown here, could help to understand the one regulation of transcription in eukaryotic cells.
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32

Puthiyaveetil, Sujith, Iskander M. Ibrahim, and John F. Allen. "Evolutionary rewiring: a modified prokaryotic gene-regulatory pathway in chloroplasts." Philosophical Transactions of the Royal Society B: Biological Sciences 368, no. 1622 (July 19, 2013): 20120260. http://dx.doi.org/10.1098/rstb.2012.0260.

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Photosynthetic electron transport regulates chloroplast gene transcription through the action of a bacterial-type sensor kinase known as chloroplast sensor kinase (CSK). CSK represses photosystem I (PS I) gene transcription in PS I light and thus initiates photosystem stoichiometry adjustment. In cyanobacteria and in non-green algae, CSK homologues co-exist with their response regulator partners in canonical bacterial two-component systems. In green algae and plants, however, no response regulator partner of CSK is found. Yeast two-hybrid analysis has revealed interaction of CSK with sigma factor 1 (SIG1) of chloroplast RNA polymerase. Here we present further evidence for the interaction between CSK and SIG1. We also show that CSK interacts with quinone. Arabidopsis SIG1 becomes phosphorylated in PS I light, which then specifically represses transcription of PS I genes. In view of the identical signalling properties of CSK and SIG1 and of their interactions, we suggest that CSK is a SIG1 kinase. We propose that the selective repression of PS I genes arises from the operation of a gene-regulatory phosphoswitch in SIG1. The CSK-SIG1 system represents a novel, rewired chloroplast-signalling pathway created by evolutionary tinkering. This regulatory system supports a proposal for the selection pressure behind the evolutionary stasis of chloroplast genes.
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Murata, Masaharu, Tomo Yamasaki, Mizuo Maeda, and Yoshiki Katayama. "An Artificial Regulation System for DNA-transcription: Learning from Prokaryotic Organisms." Chemistry Letters 33, no. 1 (January 2004): 4–5. http://dx.doi.org/10.1246/cl.2004.4.

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34

Kim, D. M., and C. Y. Choi. "A Semicontinuous Prokaryotic Coupled Transcription/Translation System Using a Dialysis Membrane." Biotechnology Progress 12, no. 5 (October 3, 1996): 645–49. http://dx.doi.org/10.1021/bp960052l.

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35

Huffman, Joy L., and Richard G. Brennan. "Prokaryotic transcription regulators: more than just the helix-turn-helix motif." Current Opinion in Structural Biology 12, no. 1 (February 2002): 98–106. http://dx.doi.org/10.1016/s0959-440x(02)00295-6.

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36

Bai, J., J. Wang, F. Xue, J. Li, L. Bu, J. Hu, G. Xu, et al. "proTF: a comprehensive data and phylogenomics resource for prokaryotic transcription factors." Bioinformatics 26, no. 19 (July 27, 2010): 2493–95. http://dx.doi.org/10.1093/bioinformatics/btq432.

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37

Allfano, Pietro, Flavia Rivellini, Danila Limauro, Carmelo B. Bruni, and M. Stella Carlomagno. "A consensus motif common to all rho-dependent prokaryotic transcription terminators." Cell 64, no. 3 (February 1991): 553–63. http://dx.doi.org/10.1016/0092-8674(91)90239-u.

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38

Park, Kyung-Soon, Young-Soon Jang, Horim Lee, and Jin-Soo Kim. "Phenotypic Alteration and Target Gene Identification Using Combinatorial Libraries of Zinc Finger Proteins in Prokaryotic Cells." Journal of Bacteriology 187, no. 15 (August 1, 2005): 5496–99. http://dx.doi.org/10.1128/jb.187.15.5496-5499.2005.

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ABSTRACT We have developed a method with prokaryotic organisms that uses randomized libraries of zinc finger-containing artificial transcription factors to induce phenotypic variations and to identify genes involved in the generation of a specific phenotype of interest. Combining chromatin immunoprecipitation experiments and in silico prediction of target DNA binding sequences for the artificial transcription factors, we identified ubiX, whose down-regulation correlates with the thermotolerance phenotype in Escherichia coli. Our results show that randomized libraries of artificial transcription factors are powerful tools for functional genomic studies.
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39

Landick, R. "The regulatory roles and mechanism of transcriptional pausing." Biochemical Society Transactions 34, no. 6 (October 25, 2006): 1062–66. http://dx.doi.org/10.1042/bst0341062.

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The multisubunit RNAPs (RNA polymerases) found in all cellular life forms are remarkably conserved in fundamental structure, in mechanism and in their susceptibility to sequence-dependent pausing during transcription of DNA in the absence of elongation regulators. Recent studies of both prokaryotic and eukaryotic transcription have yielded an increasing appreciation of the extent to which gene regulation is accomplished during the elongation phase of transcription. Transcriptional pausing is a fundamental enzymatic mechanism that underlies many of these regulatory schemes. In some cases, pausing functions by halting RNAP for times or at positions required for regulatory interactions. In other cases, pauses function by making RNAP susceptible to premature termination of transcription unless the enzyme is modified by elongation regulators that programme efficient gene expression. Pausing appears to occur by a two-tiered mechanism in which an initial rearrangement of the enzyme's active site interrupts active elongation and puts RNAP in an elemental pause state from which additional rearrangements or regulator interactions can create long-lived pauses. Recent findings from biochemical and single-molecule transcription experiments, coupled with the invaluable availability of RNAP crystal structures, have produced attractive hypotheses to explain the fundamental mechanism of pausing.
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40

Karlin, Samuel, and Jan Mrázek. "Predicted Highly Expressed Genes of Diverse Prokaryotic Genomes." Journal of Bacteriology 182, no. 18 (September 15, 2000): 5238–50. http://dx.doi.org/10.1128/jb.182.18.5238-5250.2000.

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ABSTRACT Our approach in predicting gene expression levels relates to codon usage differences among gene classes. In prokaryotic genomes, genes that deviate strongly in codon usage from the average gene but are sufficiently similar in codon usage to ribosomal protein genes, to translation and transcription processing factors, and to chaperone-degradation proteins are predicted highly expressed (PHX). By these criteria, PHX genes in most prokaryotic genomes include those encoding ribosomal proteins, translation and transcription processing factors, and chaperone proteins and genes of principal energy metabolism. In particular, for the fast-growing speciesEscherichia coli, Vibrio cholerae,Bacillus subtilis, and Haemophilus influenzae, major glycolysis and tricarboxylic acid cycle genes are PHX. InSynechocystis, prime genes of photosynthesis are PHX, and in methanogens, PHX genes include those essential for methanogenesis. Overall, the three protein families—ribosomal proteins, protein synthesis factors, and chaperone complexes—are needed at many stages of the life cycle, and apparently bacteria have evolved codon usage to maintain appropriate growth, stability, and plasticity. New interpretations of the capacity of Deinococcus radioduransfor resistance to high doses of ionizing radiation is based on an excess of PHX chaperone-degradation genes and detoxification genes. Expression levels of selected classes of genes, including those for flagella, electron transport, detoxification, histidine kinases, and others, are analyzed. Flagellar PHX genes are conspicuous among spirochete genomes. PHX genes are positively correlated with strong Shine-Dalgarno signal sequences. Specific regulatory proteins, e.g., two-component sensor proteins, are rarely PHX. Genes involved in pathways for the synthesis of vitamins record low predicted expression levels. Several distinctive PHX genes of the available complete prokaryotic genomes are highlighted. Relationships of PHX genes with stoichiometry, multifunctionality, and operon structures are discussed. Our methodology may be used complementary to experimental expression analysis.
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Trinh, Vincent, Marie-France Langelier, Jacques Archambault, and Benoit Coulombe. "Structural Perspective on Mutations Affecting the Function of Multisubunit RNA Polymerases." Microbiology and Molecular Biology Reviews 70, no. 1 (March 2006): 12–36. http://dx.doi.org/10.1128/mmbr.70.1.12-36.2006.

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SUMMARY High-resolution crystallographic structures of multisubunit RNA polymerases (RNAPs) have increased our understanding of transcriptional mechanisms. Based on a thorough review of the literature, we have compiled the mutations affecting the function of multisubunit RNA polymerases, many of which having been generated and studied prior to the publication of the first high-resolution structure, and highlighted the positions of the altered amino acids in the structures of both the prokaryotic and eukaryotic enzymes. The observations support many previous hypotheses on the transcriptional process, including the implication of the bridge helix and the trigger loop in the processivity of RNAP, the importance of contacts between the RNAP jaw-lobe module and the downstream DNA in the establishment of a transcription bubble and selection of the transcription start site, the destabilizing effects of ppGpp on the open promoter complex, and the link between RNAP processivity and termination. This study also revealed novel, remarkable features of the RNA polymerase catalytic mechanisms that will require additional investigation, including the putative roles of fork loop 2 in the establishment of a transcription bubble, the trigger loop in start site selection, and the uncharacterized funnel domain in RNAP processivity.
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42

Chowdhury, Nilkanta, and Angshuman Bagchi. "Comparative analysis of prokaryotic and eukaryotic transcription factors using machine-learning techniques." Bioinformation 14, no. 06 (June 30, 2018): 315–26. http://dx.doi.org/10.6026/97320630014315.

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43

Wang, Jian-Ying. "Mathematical relationships among DNA supercoiling, cation concentration, and temperature for prokaryotic transcription." Mathematical Biosciences 151, no. 2 (August 1998): 155–63. http://dx.doi.org/10.1016/s0025-5564(98)10012-3.

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44

Perez-Rueda, Ernesto, Rafael Hernandez-Guerrero, Mario Alberto Martinez-Nuñez, Dagoberto Armenta-Medina, Israel Sanchez, and J. Antonio Ibarra. "Abundance, diversity and domain architecture variability in prokaryotic DNA-binding transcription factors." PLOS ONE 13, no. 4 (April 3, 2018): e0195332. http://dx.doi.org/10.1371/journal.pone.0195332.

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45

Le Berre, Diana, Sylvie Reverchon, Georgi Muskhelishvili, and William Nasser. "Relationship between the Chromosome Structural Dynamics and Gene Expression—A Chicken and Egg Dilemma?" Microorganisms 10, no. 5 (April 20, 2022): 846. http://dx.doi.org/10.3390/microorganisms10050846.

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Prokaryotic transcription was extensively studied over the last half-century. A great deal of data has been accumulated regarding the control of gene expression by transcription factors regulating their target genes by binding at specific DNA sites. However, there is a significant gap between the mechanistic description of transcriptional control obtained from in vitro biochemical studies and the complexity of transcriptional regulation in the context of the living cell. Indeed, recent studies provide ample evidence for additional levels of complexity pertaining to the regulation of transcription in vivo, such as, for example, the role of the subcellular localization and spatial organization of different molecular components involved in the transcriptional control and, especially, the role of chromosome configurational dynamics. The question as to how the chromosome is dynamically reorganized under the changing environmental conditions and how this reorganization is related to gene expression is still far from being clear. In this article, we focus on the relationships between the chromosome structural dynamics and modulation of gene expression during bacterial adaptation. We argue that spatial organization of the bacterial chromosome is of central importance in the adaptation of gene expression to changing environmental conditions and vice versa, that gene expression affects chromosome dynamics.
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46

Mirkin, Ekaterina V., and Sergei M. Mirkin. "Replication Fork Stalling at Natural Impediments." Microbiology and Molecular Biology Reviews 71, no. 1 (March 2007): 13–35. http://dx.doi.org/10.1128/mmbr.00030-06.

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SUMMARY Accurate and complete replication of the genome in every cell division is a prerequisite of genomic stability. Thus, both prokaryotic and eukaryotic replication forks are extremely precise and robust molecular machines that have evolved to be up to the task. However, it has recently become clear that the replication fork is more of a hurdler than a runner: it must overcome various obstacles present on its way. Such obstacles can be called natural impediments to DNA replication, as opposed to external and genetic factors. Natural impediments to DNA replication are particular DNA binding proteins, unusual secondary structures in DNA, and transcription complexes that occasionally (in eukaryotes) or constantly (in prokaryotes) operate on replicating templates. This review describes the mechanisms and consequences of replication stalling at various natural impediments, with an emphasis on the role of replication stalling in genomic instability.
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47

Du, Pei, Chunbo Lou, Xuejin Zhao, Qihui Wang, Xiangyu Ji, and Weijia Wei. "CRISPR-Based Genetic Switches and Other Complex Circuits: Research and Application." Life 11, no. 11 (November 17, 2021): 1255. http://dx.doi.org/10.3390/life11111255.

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CRISPR-based enzymes have offered a unique capability to the design of genetic switches, with advantages in designability, modularity and orthogonality. CRISPR-based genetic switches operate on multiple levels of life, including transcription and translation. In both prokaryotic and eukaryotic cells, deactivated CRISPR endonuclease and endoribonuclease have served in genetic switches for activating or repressing gene expression, at both transcriptional and translational levels. With these genetic switches, more complex circuits have been assembled to achieve sophisticated functions including inducible switches, non-linear response and logical biocomputation. As more CRISPR enzymes continue to be excavated, CRISPR-based genetic switches will be used in a much wider range of applications.
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48

Kjeldgaard, Jette, Sidsel Henriksen, Marianne Thorup Cohn, Søren Aabo, and Hanne Ingmer. "Method Enabling Gene Expression Studies of Pathogens in a Complex Food Matrix." Applied and Environmental Microbiology 77, no. 23 (October 7, 2011): 8456–58. http://dx.doi.org/10.1128/aem.05471-11.

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ABSTRACTWe describe a simple method for stabilizing and extracting high-quality prokaryotic RNA from meat. Heat and salt stress ofEscherichia coliandSalmonellaspp. in minced meat reproducibly induceddnaKandotsBexpression, respectively, as observed by quantitative reverse transcription-PCR (>5-fold relative changes). Thus, the method is applicable in studies of bacterial gene expression in a meat matrix.
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49

Ogilvy, Sarah, Donald Metcalf, Leonie Gibson, Mary L. Bath, Alan W. Harris, and Jerry M. Adams. "Promoter Elements of vav Drive Transgene Expression In Vivo Throughout the Hematopoietic Compartment." Blood 94, no. 6 (September 15, 1999): 1855–63. http://dx.doi.org/10.1182/blood.v94.6.1855.

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Abstract To develop a method for targeting expression of genes to the full hematopoietic system, we have used transgenic mice to explore the transcriptional regulation of the vav gene, which is expressed throughout this compartment but rarely outside it. Previously, we showed that a cluster of elements surrounding its promoter could drive hematopoietic-specific expression of a bacterial lacZ reporter gene, but the expression was confined to lymphocytes and was sporadically silenced. Those limitations are ascribed here to the prokaryotic reporter gene. With a human CD4 (hCD4) cell surface reporter, the vav promoter elements drove expression efficiently and stably in virtually all nucleated cells of adult hematopoietic tissues but not notably in nonhematopoietic cell types. In multiple lines, hCD4 appeared on most, if not all, B and T lymphocytes, granulocytes, monocytes, megakaryocytes, eosinophils, and nucleated erythroid cells. Moreover, high levels appeared on both lineage-committed progenitors and the more primitive preprogenitors. In the fetus, expression was evident in erythroid cells of the definitive but not the primitive type. These results indicate that a prokaryotic sequence can inactivate a transcription unit and that the vavpromoter region constitutes a potent transgenic vector for the entire definitive hematopoietic compartment.
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50

Ogilvy, Sarah, Donald Metcalf, Leonie Gibson, Mary L. Bath, Alan W. Harris, and Jerry M. Adams. "Promoter Elements of vav Drive Transgene Expression In Vivo Throughout the Hematopoietic Compartment." Blood 94, no. 6 (September 15, 1999): 1855–63. http://dx.doi.org/10.1182/blood.v94.6.1855.418k33_1855_1863.

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To develop a method for targeting expression of genes to the full hematopoietic system, we have used transgenic mice to explore the transcriptional regulation of the vav gene, which is expressed throughout this compartment but rarely outside it. Previously, we showed that a cluster of elements surrounding its promoter could drive hematopoietic-specific expression of a bacterial lacZ reporter gene, but the expression was confined to lymphocytes and was sporadically silenced. Those limitations are ascribed here to the prokaryotic reporter gene. With a human CD4 (hCD4) cell surface reporter, the vav promoter elements drove expression efficiently and stably in virtually all nucleated cells of adult hematopoietic tissues but not notably in nonhematopoietic cell types. In multiple lines, hCD4 appeared on most, if not all, B and T lymphocytes, granulocytes, monocytes, megakaryocytes, eosinophils, and nucleated erythroid cells. Moreover, high levels appeared on both lineage-committed progenitors and the more primitive preprogenitors. In the fetus, expression was evident in erythroid cells of the definitive but not the primitive type. These results indicate that a prokaryotic sequence can inactivate a transcription unit and that the vavpromoter region constitutes a potent transgenic vector for the entire definitive hematopoietic compartment.
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