Browsing by Subject "transcriptional regulation"

Now showing 1 - 6 of 6
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    Conservation of transcriptional sensing systems in prokaryotes: A perspective from Escherichia coli
    (2007-07) Salgado, Heladia; Martínez-Antonio, Agustino; Janga, Sarath Chandra
    The activity of transcription factors is usually governed by allosteric physicochemical signals or metabolites, which are in turn produced in the cell or obtained from the environment by the activity of the products of effector genes. Previously, we identified a collection of more than 110 transcription factors and their corresponding effector genes in Escherichia coli K-12. Here, we introduce the notion of “triferog”, which relates to the identification of orthologous transcription factors and effector genes across genomes and show that transcriptional sensing systems known in E. coli are poorly conserved beyond Salmonella. We also find that enzymes that act as effector genes for the production of endogenous effector metabolites are more conserved than their corresponding effector genes encoding for transport and two-component systems for sensing exogenous signals. Finally, we observe that on an evolutionary scale enzymes are more conserved than their respective TFs, suggesting a homogenous cellular metabolism across genomes and the conservation of transcriptional control of critical cellular processes like DNA replication by a common endogenous signal. We hypothesize that extensive variation in the domain architecture of TFs and changes in endogenous conditions at large phylogenetic distances could be the major contributing factors for the observed differential conservation of TFs and their corresponding effector genes encoding for enzymes, causing variations in transcriptional responses across organisms.
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    Crystal structure of the DNA binding domain of the transcription factor T-bet suggests simultaneous recognition of distant genome sites
    (Proceedings of the National Academy of Sciences, 2016-10-25) Liu, Ce Feng; Brandt, Gabriel S.; Hoang, Quyen Q.; Naumova, Natalia; Lazarevic, Vanja; Hwang, Eun Sook; Dekker, Job; Glimcher, Laurie H.; Ringe, Dagmar; Petsko, Gregory A.; Department of Biochemistry & Molecular Biology, IU School of Medicine
    The transcription factor T-bet (Tbox protein expressed in T cells) is one of the master regulators of both the innate and adaptive immune responses. It plays a central role in T-cell lineage commitment, where it controls the TH1 response, and in gene regulation in plasma B-cells and dendritic cells. T-bet is a member of the Tbox family of transcription factors; however, T-bet coordinately regulates the expression of many more genes than other Tbox proteins. A central unresolved question is how T-bet is able to simultaneously recognize distant Tbox binding sites, which may be located thousands of base pairs away. We have determined the crystal structure of the Tbox DNA binding domain (DBD) of T-bet in complex with a palindromic DNA. The structure shows a quaternary structure in which the T-bet dimer has its DNA binding regions splayed far apart, making it impossible for a single dimer to bind both sites of the DNA palindrome. In contrast to most other Tbox proteins, a single T-bet DBD dimer binds simultaneously to identical half-sites on two independent DNA. A fluorescence-based assay confirms that T-bet dimers are able to bring two independent DNA molecules into close juxtaposition. Furthermore, chromosome conformation capture assays confirm that T-bet functions in the direct formation of chromatin loops in vitro and in vivo. The data are consistent with a looping/synapsing model for transcriptional regulation by T-bet in which a single dimer of the transcription factor can recognize and coalesce distinct genetic elements, either a promoter plus a distant regulatory element, or promoters on two different genes.
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    Functional organisation of Escherichia coli transcriptional regulatory network
    (2008-08) Martinez-Antonio, Agustino; Janga, Sarath Chandra; Thieffry, Denis
    Taking advantage of available functional data associated with 115 transcription and 7 sigma factors, we have performed a structural analysis of the regulatory network of Escherichia coli. While the mode of regulatory interaction between transcription factors (TFs) is predominantly positive, TFs are frequently negatively autoregulated. Furthermore, feedback loops, regulatory motifs and regulatory pathways are unevenly distributed in this network. Short pathways, multiple feed-forward loops and negative autoregulatory interactions are particularly predominant in the subnetwork controlling metabolic functions such as the use of alternative carbon sources. In contrast, long hierarchical cascades and positive autoregulatory loops are overrepresented in the subnetworks controlling developmental processes for biofilm and chemotaxis. We propose that these long transcriptional cascades coupled with regulatory switches (positive loops) for external sensing enable the coexistence of multiple bacterial phenotypes. In contrast, short regulatory pathways and negative autoregulatory loops enable an efficient homeostatic control of crucial metabolites despite external variations. TFs at the core of the network coordinate the most basic endogenous processes by passing information onto multi-element circuits. Transcriptional expression data support broader and higher transcription of global TFs compared to specific ones. Global regulators are also more broadly conserved than specific regulators in bacteria, pointing to varying functional constraints.
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    Mis-Expression of a Cranial Neural Crest Cell-Specific Gene Program in Cardiac Neural Crest Cells Modulates HAND Factor Expression, Causing Cardiac Outflow Tract Phenotypes
    (MDPI, 2020-04-20) Vincentz, Joshua W.; Clouthier, David E.; Firulli, Anthony B.; Pediatrics, School of Medicine
    Congenital heart defects (CHDs) occur with such a frequency that they constitute a significant cause of morbidity and mortality in both children and adults. A significant portion of CHDs can be attributed to aberrant development of the cardiac outflow tract (OFT), and of one of its cellular progenitors known as the cardiac neural crest cells (NCCs). The gene regulatory networks that identify cardiac NCCs as a distinct NCC population are not completely understood. Heart and neural crest derivatives (HAND) bHLH transcription factors play essential roles in NCC morphogenesis. The Hand1PA/OFT enhancer is dependent upon bone morphogenic protein (BMP) signaling in both cranial and cardiac NCCs. The Hand1PA/OFT enhancer is directly repressed by the endothelin-induced transcription factors DLX5 and DLX6 in cranial but not cardiac NCCs. This transcriptional distinction offers the unique opportunity to interrogate NCC specification, and to understand why, despite similarities, cranial NCC fate determination is so diverse. We generated a conditionally active transgene that can ectopically express DLX5 within the developing mouse embryo in a Cre-recombinase-dependent manner. Ectopic DLX5 expression represses cranial NCC Hand1PA/OFT-lacZ reporter expression more effectively than cardiac NCC reporter expression. Ectopic DLX5 expression induces broad domains of NCC cell death within the cranial pharyngeal arches, but minimal cell death in cardiac NCC populations. This study shows that transcription control of NCC gene regulatory programs is influenced by their initial specification at the dorsal neural tube.
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    OperomeDB: A Database of Condition-Specific Transcription Units in Prokaryotic Genomes
    (Hindawi, 2015-03) Chetal, Kashish; Janga, Sarath Chandra; School of Informatics and Computing, Department of BioHealth Informatics
    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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    regSNPs-ASB: A Computational Framework for Identifying Allele-Specific Transcription Factor Binding From ATAC-seq Data
    (Frontiers, 2020-07-29) Xu, Siwen; Feng, Weixing; Lu, Zixiao; Yu, Christina Y.; Shao, Wei; Nakshatri, Harikrishna; Reiter, Jill L.; Gao, Hongyu; Chu, Xiaona; Wang, Yue; Liu, Yunlong; Medical and Molecular Genetics, School of Medicine
    Expression quantitative trait loci (eQTL) analysis is useful for identifying genetic variants correlated with gene expression, however, it cannot distinguish between causal and nearby non-functional variants. Because the majority of disease-associated SNPs are located in regulatory regions, they can impact allele-specific binding (ASB) of transcription factors and result in differential expression of the target gene alleles. In this study, our aim was to identify functional single-nucleotide polymorphisms (SNPs) that alter transcriptional regulation and thus, potentially impact cellular function. Here, we present regSNPs-ASB, a generalized linear model-based approach to identify regulatory SNPs that are located in transcription factor binding sites. The input for this model includes ATAC-seq (assay for transposase-accessible chromatin with high-throughput sequencing) raw read counts from heterozygous loci, where differential transposase-cleavage patterns between two alleles indicate preferential transcription factor binding to one of the alleles. Using regSNPs-ASB, we identified 53 regulatory SNPs in human MCF-7 breast cancer cells and 125 regulatory SNPs in human mesenchymal stem cells (MSC). By integrating the regSNPs-ASB output with RNA-seq experimental data and publicly available chromatin interaction data from MCF-7 cells, we found that these 53 regulatory SNPs were associated with 74 potential target genes and that 32 (43%) of these genes showed significant allele-specific expression. By comparing all of the MCF-7 and MSC regulatory SNPs to the eQTLs in the Genome-Tissue Expression (GTEx) Project database, we found that 30% (16/53) of the regulatory SNPs in MCF-7 and 43% (52/122) of the regulatory SNPs in MSC were also in eQTL regions. The enrichment of regulatory SNPs in eQTLs indicated that many of them are likely responsible for allelic differences in gene expression (chi-square test, p-value < 0.01). In summary, we conclude that regSNPs-ASB is a useful tool for identifying causal variants from ATAC-seq data. This new computational tool will enable efficient prioritization of genetic variants identified as eQTL for further studies to validate their causal regulatory function. Ultimately, identifying causal genetic variants will further our understanding of the underlying molecular mechanisms of disease and the eventual development of potential therapeutic targets.