scholarly journals Identification of a GrgA-Euo-HrcA Transcriptional Regulatory Network in Chlamydia

mSystems ◽  
2021 ◽  
Author(s):  
Wurihan Wurihan ◽  
Yi Zou ◽  
Alec M. Weber ◽  
Korri Weldon ◽  
Yehong Huang ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Regulatory Network ◽  
Transcriptional Regulatory Network ◽  
Bacterial Pathogen ◽  
Developed Countries ◽  
Developmental Cycle ◽  
Content Type ◽  
Sexually Transmitted ◽  
Transcriptional Regulatory ◽  
Preventable Blindness

Chlamydia trachomatis is the most prevalent sexually transmitted bacterial pathogen worldwide and is a leading cause of preventable blindness in underdeveloped areas as well as some developed countries. Chlamydia carries genes that encode a limited number of known transcription factors. While Euo is thought to be critical for early chlamydial development, the functions of GrgA and HrcA in the developmental cycle are unclear.

scholarly journals Screening Driving Transcription Factors in the Processing of Gastric Cancer

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Guangzhong Xu ◽  
Kai Li ◽  
Nengwei Zhang ◽  
Bin Zhu ◽  
Guosheng Feng
Keyword(s):  
Gastric Cancer ◽  
Transcription Factors ◽  
Regulatory Network ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Regulatory Mechanisms ◽  
Integrated Analysis ◽  
Transcriptional Regulatory

Background. Construction of the transcriptional regulatory network can provide additional clues on the regulatory mechanisms and therapeutic applications in gastric cancer.Methods. Gene expression profiles of gastric cancer were downloaded from GEO database for integrated analysis. All of DEGs were analyzed by GO enrichment and KEGG pathway enrichment. Transcription factors were further identified and then a global transcriptional regulatory network was constructed.Results. By integrated analysis of the six eligible datasets (340 cases and 43 controls), a bunch of 2327 DEGs were identified, including 2100 upregulated and 227 downregulated DEGs. Functional enrichment analysis of DEGs showed that digestion was a significantly enriched GO term for biological process. Moreover, there were two important enriched KEGG pathways: cell cycle and homologous recombination. Furthermore, a total of 70 differentially expressed TFs were identified and the transcriptional regulatory network was constructed, which consisted of 566 TF-target interactions. The top ten TFs regulating most downstream target genes were BRCA1, ARID3A, EHF, SOX10, ZNF263, FOXL1, FEV, GATA3, FOXC1, and FOXD1. Most of them were involved in the carcinogenesis of gastric cancer.Conclusion. The transcriptional regulatory network can help researchers to further clarify the underlying regulatory mechanisms of gastric cancer tumorigenesis.

scholarly journals Role for GrgA in Regulation of σ28-Dependent Transcription in the Obligate Intracellular Bacterial PathogenChlamydia trachomatis

2018 ◽  
Vol 200 (20) ◽  
Author(s):  
Malhar Desai ◽  
Wurihan Wurihan ◽  
Rong Di ◽  
Joseph D. Fondell ◽  
Bryce E. Nickels ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Chlamydia Trachomatis ◽  
Sigma Factor ◽  
Bacterial Pathogen ◽  
Direct Interaction ◽  
Developmental Cycle ◽  
Content Type ◽  
Sexually Transmitted ◽  
Obligate Intracellular ◽  
Specific Transcription Factor

ABSTRACTThe obligate intracellular bacterial pathogenChlamydia trachomatishas a unique developmental cycle consisting of two contrasting cellular forms. Whereas the primaryChlamydiasigma factor, σ66, is involved in the expression of the majority of chlamydial genes throughout the developmental cycle, expression of several late genes requires the alternative sigma factor, σ28. In prior work, we identified GrgA as aChlamydia-specific transcription factor that activates σ66-dependent transcription by binding DNA and interacting with a nonconserved region (NCR) of σ66. Here, we extend these findings by showing GrgA can also activate σ28-dependent transcription through direct interaction with σ28. We measure the binding affinity of GrgA for both σ66and σ28, and we identify regions of GrgA important for σ28-dependent transcription. Similar to results obtained with σ66, we find that GrgA's interaction with σ28involves an NCR located upstream of conserved region 2 of σ28. Our findings suggest that GrgA is an important regulator of both σ66- and σ28-dependent transcription inC. trachomatisand further highlight NCRs of bacterial RNA polymerase as targets for regulatory factors unique to particular organisms.IMPORTANCEChlamydia trachomatisis the number one sexually transmitted bacterial pathogen worldwide. A substantial proportion ofC. trachomatis-infected women develop infertility, pelvic inflammatory syndrome, and other serious complications.C. trachomatisis also a leading infectious cause of blindness in underdeveloped countries. The pathogen has a unique developmental cycle that is transcriptionally regulated. The discovery of an expanded role for theChlamydia-specific transcription factor GrgA helps us understand the progression of the chlamydial developmental cycle.

scholarly journals Coregulation of transcription factors and microRNAs in human transcriptional regulatory network

2011 ◽  
Vol 12 (Suppl 1) ◽  
pp. S41 ◽  
Author(s):  
Cho-Yi Chen ◽  
Shui-Tein Chen ◽  
Chiou-Shann Fuh ◽  
Hsueh-Fen Juan ◽  
Hsuan-Cheng Huang
Keyword(s):  
Transcription Factors ◽  
Regulatory Network ◽  
Transcriptional Regulatory Network ◽  
Transcriptional Regulatory

scholarly journals Reconstruction of a Global Transcriptional Regulatory Network for Control of Lipid Metabolism in Yeast by Using Chromatin Immunoprecipitation with Lambda Exonuclease Digestion

mSystems ◽  
2018 ◽  
Vol 3 (4) ◽  
Author(s):  
David Bergenholm ◽  
Guodong Liu ◽  
Petter Holland ◽  
Jens Nielsen
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Lipid Metabolism ◽  
Chromatin Immunoprecipitation ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Transcriptional Regulatory Network ◽  
Lambda Exonuclease ◽  
Transcriptional Regulatory ◽  
Exonuclease Digestion

ABSTRACT To build transcription regulatory networks, transcription factor binding must be analyzed in cells grown under different conditions because their responses and targets differ depending on environmental conditions. We performed whole-genome analysis of the DNA binding of five Saccharomyces cerevisiae transcription factors involved in lipid metabolism, Ino2, Ino4, Hap1, Oaf1, and Pip2, in response to four different environmental conditions in chemostat cultures, which allowed us to keep the specific growth rate constant. Chromatin immunoprecipitation with lambda exonuclease digestion (ChIP-exo) enabled the detection of binding events at a high resolution. We discovered a large number of unidentified targets and thus expanded functions for each transcription factor (e.g., glutamate biosynthesis as a target of Oaf1 and Pip2). Moreover, condition-dependent binding of transcription factors in response to cell metabolic state (e.g., differential binding of Ino2 between fermentative and respiratory metabolic conditions) was clearly suggested. Combining the new binding data with previously published data from transcription factor deletion studies revealed the high complexity of the transcriptional regulatory network for lipid metabolism in yeast, which involves the combinatorial and complementary regulation by multiple transcription factors. We anticipate that our work will provide insights into transcription factor binding dynamics that will prove useful for the understanding of transcription regulatory networks. IMPORTANCE Transcription factors play a crucial role in the regulation of gene expression and adaptation to different environments. To better understand the underlying roles of these adaptations, we performed experiments that give us high-resolution binding of transcription factors to their targets. We investigated five transcription factors involved in lipid metabolism in yeast, and we discovered multiple novel targets and condition-specific responses that allow us to draw a better regulatory map of the lipid metabolism.

scholarly journals Rapid reorganization of the transcriptional regulatory network after genome duplication in yeast

2009 ◽  
Vol 277 (1683) ◽  
pp. 869-876 ◽  
Author(s):  
Gavin C. Conant
Keyword(s):  
Transcription Factors ◽  
Regulatory Network ◽  
Whole Genome Duplication ◽  
Genome Duplication ◽  
Transcriptional Regulatory Network ◽  
Whole Genome ◽  
Functional Roles ◽  
Transcriptional Regulatory ◽  
Dosage Balance ◽  
Tf Gene

I study the reorganization of the yeast transcriptional regulatory network after whole-genome duplication (WGD). Individual transcription factors (TFs) were computationally removed from the regulatory network, and the resulting networks were analysed. TF gene pairs that survive in duplicate from WGD show detectable redundancy as a result of that duplication. However, in most other respects, these duplicated TFs are indistinguishable from other TFs in the genome, suggesting that the duplicate TFs produced by WGD were rapidly diverted to distinct functional roles in the regulatory network. Separately, I find that genes targeted by many TFs appear to be preferentially retained in duplicate after WGD, an effect I attribute to selection to maintain dosage balance in the regulatory network after WGD.

scholarly journals Genome-Wide Mapping of Binding Sites Reveals Multiple Biological Functions of the Transcription Factor Cst6p in Saccharomyces cerevisiae

mBio ◽  
2016 ◽  
Vol 7 (3) ◽  
Author(s):  
Guodong Liu ◽  
David Bergenholm ◽  
Jens Nielsen
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Binding Sites ◽  
Regulatory Network ◽  
Deletion Mutant ◽  
Transcriptional Regulatory Network ◽  
Biological Processes ◽  
Genome Wide ◽  
Transcriptional Regulatory

ABSTRACT In the model eukaryote Saccharomyces cerevisiae , the transcription factor Cst6p has been reported to play important roles in several biological processes. However, the genome-wide targets of Cst6p and its physiological functions remain unknown. Here, we mapped the genome-wide binding sites of Cst6p at high resolution. Cst6p binds to the promoter regions of 59 genes with various biological functions when cells are grown on ethanol but hardly binds to the promoter at any gene when cells are grown on glucose. The retarded growth of the CST6 deletion mutant on ethanol is attributed to the markedly decreased expression of NCE103 , encoding a carbonic anhydrase, which is a direct target of Cst6p. The target genes of Cst6p have a large overlap with those of stress-responsive transcription factors, such as Sko1p and Skn7p. In addition, a CST6 deletion mutant growing on ethanol shows hypersensitivity to oxidative stress and ethanol stress, assigning Cst6p as a new member of the stress-responsive transcriptional regulatory network. These results show that mapping of genome-wide binding sites can provide new insights into the function of transcription factors and highlight the highly connected and condition-dependent nature of the transcriptional regulatory network in S. cerevisiae . IMPORTANCE Transcription factors regulate the activity of various biological processes through binding to specific DNA sequences. Therefore, the determination of binding positions is important for the understanding of the regulatory effects of transcription factors. In the model eukaryote Saccharomyces cerevisiae , the transcription factor Cst6p has been reported to regulate several biological processes, while its genome-wide targets remain unknown. Here, we mapped the genome-wide binding sites of Cst6p at high resolution. We show that the binding of Cst6p to its target promoters is condition dependent and explain the mechanism for the retarded growth of the CST6 deletion mutant on ethanol. Furthermore, we demonstrate that Cst6p is a new member of a stress-responsive transcriptional regulatory network. These results provide deeper understanding of the function of the dynamic transcriptional regulatory network in S. cerevisiae .

scholarly journals Transcriptional Regulatory Network for the Development of Innate Lymphoid Cells

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Chao Zhong ◽  
Jinfang Zhu
Keyword(s):  
Transcription Factors ◽  
Regulatory Network ◽  
Transcriptional Regulatory Network ◽  
Innate Lymphoid Cells ◽  
Lymphoid Cells ◽  
T Helper ◽  
Th Cells ◽  
Transcriptional Regulatory ◽  
Effector Cytokines ◽  
And Function

Recent studies on innate lymphoid cells (ILCs) have expanded our knowledge about the innate arm of the immune system. Helper-like ILCs share both the “innate” feature of conventional natural killer (cNK) cells and the “helper” feature of CD4+T helper (Th) cells. With this combination, helper-like ILCs are capable of initiating early immune responses similar to cNK cells, but via secretion of a set of effector cytokines similar to those produced by Th cells. Although many studies have revealed the functional similarity between helper-like ILCs and Th cells, some aspects of ILCs including the development of this lineage remain elusive. It is intriguing that the majority of transcription factors involved in multiple stages of T cell development, differentiation, and function also play critical roles during ILC development. Regulators such as Id2, GATA-3, Nfil3, TOX, and TCF-1 are expressed and function at various stages of ILC development. In this review, we will summarize the expression and functions of these transcription factors shared by ILCs and Th cells. We will also propose a complex transcriptional regulatory network for the lineage commitment of ILCs.

scholarly journals Revealing 29 sets of independently modulated genes in Staphylococcus aureus, their regulators and role in key physiological responses

2020 ◽  
Author(s):  
Saugat Poudel ◽  
Hannah Tsunemoto ◽  
Yara Seif ◽  
Anand Sastry ◽  
Richard Szubin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Staphylococcus Aureus ◽  
Transcription Factors ◽  
Regulatory Network ◽  
Transcriptional Regulatory Network ◽  
Physiological Responses ◽  
Cellular Systems ◽  
Transcriptional Regulatory ◽  
Successful Infection ◽  
Its Gene

AbstractThe ability of Staphylococcus aureus to infect many different tissue sites is enabled, in part, by its Transcriptional Regulatory Network (TRN) that coordinates its gene expression to respond to different environments. We elucidated the organization and activity of this TRN by applying Independent Component Analysis (ICA) to a compendium of 108 RNAseq expression profiles from two S. aureus clinical strains (TCH1516 and LAC). ICA decomposed the S. aureus transcriptome into 29 independently modulated sets of genes (i-modulons) that revealed (1) high confidence associations between 21 i-modulons and known regulators; (2) an association between an i-modulon and σS, whose regulatory role was previously undefined; (3) the regulatory organization of 65 virulence factors in the form of three i-modulons associated with AgrR, SaeR and Vim-3, (4) the roles of three key transcription factors (codY, Fur and ccpA) in coordinating the metabolic and regulatory networks; and (5) a low dimensional representation, involving the function of few transcription factors, of changes in gene expression between two laboratory media (RPMI, CAMHB) and two physiological media (blood and serum). This representation of the TRN covers 842 genes representing 76% of the variance in gene expression that provides a quantitative reconstruction of transcriptional modules in S. aureus, and a platform enabling its full elucidation.Significance StatementStaphylococcus aureus infections impose an immense burden on the healthcare system. To establish a successful infection in a hostile host environment, S. aureus must coordinate its gene expression to respond to a wide array of challenges. This balancing act is largely orchestrated by the Transcriptional Regulatory Network (TRN). Here, we present a model of 29 independently modulated sets of genes that form the basis for a segment of the TRN in clinical USA300 strains of S. aureus. Using this model, we demonstrate the concerted role of various cellular systems (e.g. metabolism, virulence and stress response) underlying key physiological responses, including response during blood infection.

Sign in / Sign up

Export Citation Format

Share Document