Transcriptional integration of plant responses to iron availability

Helix Loop Helix ◽

Regulatory Cascade ◽

Electron Transport Chains

Abstract Iron is one of the most important micronutrients for plant growth and development. It functions as the enzyme cofactor or component of electron transport chains in various vital metabolic processes, including photosynthesis, respiration, and amino acid biosynthesis. To maintain iron homeostasis, and therefore prevent any deficiency or excess that could be detrimental, plants have evolved complex transcriptional regulatory networks to tightly control iron uptake, translocation, assimilation, and storage. These regulatory networks are composed of various transcription factors; among them, members of the basic helix-loop-helix (bHLH) family play an essential role. Here, we first review recent advances in understanding the roles of bHLH transcription factors involved in the regulatory cascade controlling iron homeostasis in the model plant Arabidopsis, and extend this understanding to rice and other plant species. The importance of other classes of transcription factors will also be discussed. Second, we elaborate on the post-translational mechanisms involved in the regulation of these regulatory networks. Finally, we provide some perspectives on future research that should be conducted in order to precisely understand how plants control the homeostasis of this micronutrient.

Current and emerging approaches to define intestinal epithelium-specific transcriptional networks

AJP Gastrointestinal and Liver Physiology ◽

10.1152/ajpgi.00362.2011 ◽

2012 ◽

Vol 302 (3) ◽

pp. G277-G286 ◽

Cited By ~ 13

Author(s):

Anders Krüger Olsen ◽

Mette Boyd ◽

Erik Thomas Danielsen ◽

Jesper Thorvald Troelsen

Keyword(s):

Transcription Factors ◽

Regulatory Networks ◽

Transcriptional Regulatory Network ◽

Tissue Type ◽

Intestinal Cell ◽

Future Research ◽

Transcriptional Networks ◽

Differentiation Process ◽

Upon developmental or environmental cues, the composition of transcription factors in a transcriptional regulatory network is deeply implicated in controlling the signature of the gene expression and thereby specifies the cell or tissue type. Novel methods including ChIP-chip and ChIP-Seq have been applied to analyze known transcription factors and their interacting regulatory DNA elements in the intestine. The intestine is an example of a dynamic tissue where stem cells in the crypt proliferate and undergo a differentiation process toward the villus. During this differentiation process, specific regulatory networks of transcription factors are activated to target specific genes, which determine the intestinal cell fate. The expanding genomewide mapping of transcription factor binding sites and construction of transcriptional regulatory networks provide new insight into how intestinal differentiation occurs. This review summarizes the current overview of the transcriptional regulatory networks driving epithelial differentiation in adult intestine. The novel technologies that have been implied to study these networks are presented and their prospects for implications in future research are also addressed.

Transcriptional Control of Parturition: Insights from Gene Regulation Studies in the Myometrium

MHR Basic science of reproductive medicine ◽

10.1093/molehr/gaab024 ◽

2021 ◽

Author(s):

Nawrah Khader ◽

Virlana M Shchuka ◽

Oksana Shynlova ◽

Jennifer A Mitchell

Keyword(s):

Transcription Factors ◽

Regulatory Networks ◽

Transcriptional Control ◽

Progesterone Receptors ◽

Activator Protein 1 ◽

Regulatory Pathways ◽

Mechanistic Basis ◽

Labour Onset

Abstract The onset of labour is a culmination of a series of highly coordinated and preparatory physiological events that take place throughout the gestational period. In order to produce the associated contractions needed for fetal delivery, smooth muscle cells in the muscular layer of the uterus (i.e. myometrium) undergo a transition from quiescent to contractile phenotypes. Here, we present the current understanding of the roles transcription factors play in critical labour-associated gene expression changes as part of the molecular mechanistic basis for this transition. Consideration is given to both transcription factors that have been well-studied in a myometrial context, i.e. activator protein 1 (AP-1), progesterone receptors (PRs), estrogen receptors (ERs), and nuclear factor kappa B (NF-κB), as well as additional transcription factors whose gestational event-driving contributions have been demonstrated more recently. These transcription factors may form pregnancy- and labour- associated transcriptional regulatory networks in the myometrium to modulate the timing of labour onset. A more thorough understanding of the transcription factor-mediated, labour-promoting regulatory pathways holds promise for the development of new therapeutic treatments that can be used for the prevention of preterm labour in at-risk women.

Dissecting the Repertoire of DNA-Binding Transcription Factors of the Archaeon Pyrococcus furiosus DSM 3638

Life ◽

10.3390/life8040040 ◽

2018 ◽

Vol 8 (4) ◽

pp. 40 ◽

Cited By ~ 2

Author(s):

Antonia Denis ◽

Mario Alberto Martínez-Núñez ◽

Silvia Tenorio-Salgado ◽

Ernesto Perez-Rueda

Keyword(s):

Transcription Factors ◽

Dna Binding ◽

Regulatory Networks ◽

Pyrococcus Furiosus ◽

Structural Domain ◽

Dna Binding Domains ◽

Binding Domains ◽

Cellular Domain

In recent years, there has been a large increase in the amount of experimental evidence for diverse archaeal organisms, and these findings allow for a comprehensive analysis of archaeal genetic organization. However, studies about regulatory mechanisms in this cellular domain are still limited. In this context, we identified a repertoire of 86 DNA-binding transcription factors (TFs) in the archaeon Pyrococcus furiosus DSM 3638, that are clustered into 32 evolutionary families. In structural terms, 45% of these proteins are composed of one structural domain, 41% have two domains, and 14% have three structural domains. The most abundant DNA-binding domain corresponds to the winged helix-turn-helix domain; with few alternative DNA-binding domains. We also identified seven regulons, which represent 13.5% (279 genes) of the total genes in this archaeon. These analyses increase our knowledge about gene regulation in P. furiosus DSM 3638 and provide additional clues for comprehensive modeling of transcriptional regulatory networks in the Archaea cellular domain.

Construction of transcriptional regulatory networks based on found transcription factors and their binding sites in annotated bacterial genomes

10.18699/sbb-plantgen-2021-09 ◽

2021 ◽

Keyword(s):

Transcription Factors ◽

Binding Sites ◽

Regulatory Networks ◽

Bacterial Genomes ◽

Structure, evolution and dynamics of transcriptional regulatory networks

Biochemical Society Transactions ◽

10.1042/bst0381155 ◽

2010 ◽

Vol 38 (5) ◽

pp. 1155-1178 ◽

Cited By ~ 14

Author(s):

M. Madan Babu

Keyword(s):

Regulatory Networks ◽

Target Genes ◽

Network Evolution ◽

Structure Evolution ◽

Future Research ◽

Regulation System ◽

Transcriptional Networks ◽

Entire Genome ◽

The availability of entire genome sequences and the wealth of literature on gene regulation have enabled researchers to model an organism's transcriptional regulation system in the form of a network. In such a network, TFs (transcription factors) and TGs (target genes) are represented as nodes and regulatory interactions between TFs and TGs are represented as directed links. In the present review, I address the following topics pertaining to transcriptional regulatory networks. (i) Structure and organization: first, I introduce the concept of networks and discuss our understanding of the structure and organization of transcriptional networks. (ii) Evolution: I then describe the different mechanisms and forces that influence network evolution and shape network structure. (iii) Dynamics: I discuss studies that have integrated information on dynamics such as mRNA abundance or half-life, with data on transcriptional network in order to elucidate general principles of regulatory network dynamics. In particular, I discuss how cell-to-cell variability in the expression level of TFs could permit differential utilization of the same underlying network by distinct members of a genetically identical cell population. Finally, I conclude by discussing open questions for future research and highlighting the implications for evolution, development, disease and applications such as genetic engineering.

An Integrated Database of Small RNAs and Their Interplay With Transcriptional Gene Regulatory Networks in Corynebacteria

Frontiers in Microbiology ◽

10.3389/fmicb.2021.656435 ◽

2021 ◽

Vol 12 ◽

Author(s):

Mariana Teixeira Dornelles Parise ◽

Doglas Parise ◽

Flavia Figueira Aburjaile ◽

Anne Cybelle Pinto Gomide ◽

Rodrigo Bentes Kato ◽

...

Keyword(s):

Transcription Factors ◽

Gene Regulatory Networks ◽

Small Rnas ◽

Regulatory Networks ◽

Bacterial Gene ◽

Bacterial Gene Expression ◽

Animal Pathogens ◽

Gene Regulatory

Small RNAs (sRNAs) are one of the key players in the post-transcriptional regulation of bacterial gene expression. These molecules, together with transcription factors, form regulatory networks and greatly influence the bacterial regulatory landscape. Little is known concerning sRNAs and their influence on the regulatory machinery in the genus Corynebacterium, despite its medical, veterinary and biotechnological importance. Here, we expand corynebacterial regulatory knowledge by integrating sRNAs and their regulatory interactions into the transcriptional regulatory networks of six corynebacterial species, covering four human and animal pathogens, and integrate this data into the CoryneRegNet database. To this end, we predicted sRNAs to regulate 754 genes, including 206 transcription factors, in corynebacterial gene regulatory networks. Amongst them, the sRNA Cd-NCTC13129-sRNA-2 is predicted to directly regulate ydfH, which indirectly regulates 66 genes, including the global regulator glxR in C. diphtheriae. All of the sRNA-enriched regulatory networks of the genus Corynebacterium have been made publicly available in the newest release of CoryneRegNet(www.exbio.wzw.tum.de/coryneregnet/) to aid in providing valuable insights and to guide future experiments.

Genome-wide screening of upstream transcription factors using an expression library

F1000Research ◽

10.12688/f1000research.27532.1 ◽

2021 ◽

Vol 10 ◽

pp. 51

Author(s):

Naoya Yahagi ◽

Yoshinori Takeuchi

Keyword(s):

Transcription Factors ◽

Regulatory Networks ◽

Dependent Manner ◽

Expression Library ◽

Genome Wide ◽

Powerful Approach ◽

Transcription Factor Expression ◽

Expression Cdna Library

The identification of upstream transcription factors regulating the expression of a gene is generally not an easy process. To facilitate this task, we constructed an expression cDNA library named Transcription Factor Expression Library (TFEL), which is composed of nearly all the transcription factors in the mouse genome. Genome-wide screening using this library (TFEL scan method) enables us to easily identify transcription factors controlling any given promoter or enhancer of interest in a chromosomal context-dependent manner. Thus, TFEL scan method is a powerful approach to explore transcriptional regulatory networks.

mSphere of Influence: Decoding Transcriptional Regulatory Networks To Illuminate the Mechanisms of Microbial Pathogenicity

mSphere ◽

10.1128/msphere.00917-19 ◽

2020 ◽

Vol 5 (1) ◽

Author(s):

Sadri Znaidi

Keyword(s):

Candida Albicans ◽

Functional Genomics ◽

Regulatory Networks ◽

Iron Homeostasis ◽

Content Type ◽

Host Environment ◽

Regulatory Circuit ◽

Cell Host Microbe

ABSTRACT Sadri Znaidi works in the field of molecular mycology with a focus on functional genomics in Candida albicans. In this mSphere of Influence article, he reflects on how the paper “An iron homeostasis regulatory circuit with reciprocal roles in Candida albicans commensalism and pathogenesis” by Chen et al. (C. Chen, K. Pande, S. D. French, B. B. Tuch, and S. M. Noble, Cell Host Microbe 10:118–135, 2011, https://doi.org/10.1016/j.chom.2011.07.005) made an impact on his research on how transcriptional regulatory networks function to control C. albicans’ ability to efficiently interact with the host environment.

ANGI-01. IDENTIFICATION OF INVASION-DETERMINISTIC TRANSCRIPTION FACTORS IN GLIOBLASTOMA USING INTEGRATIVE TRANSCRIPTOME ANALYSIS

Neuro-Oncology ◽

10.1093/neuonc/noz175.112 ◽

2019 ◽

Vol 21 (Supplement_6) ◽

pp. vi30-vi30

Author(s):

Junseong Park ◽

Jin-Kyoung Shim ◽

Jae Eun Lee ◽

Seon Jin Yoon ◽

Jihwan Yoo ◽

...

Keyword(s):

Transcription Factors ◽

Transcriptome Analysis ◽

Poor Prognosis ◽

Regulatory Networks ◽

Xenograft Model ◽

Mr Images ◽

Orthotopic Xenograft ◽

Orthotopic Xenograft Model ◽

Abstract Glioblastoma (GBM) is one of the most lethal human tumors with a highly infiltrative phenotype. Although invasiveness is related to poor prognosis, no therapeutic intervention targeting invasion is available for treatment of GBM patient, partially due to the diversity and redundancy of invasion machinery genes. In this regard, additional identification of deterministic and causative targets for invasion is required. Invasiveness of GBM patients and matched tumorspheres (TSs) was quantified using MR images and collagen-based 3D invasion assays, respectively. Transcriptome of GBM samples were obtained using microarrays. The knockdown effects of invasion-deterministic transcription factors (TFs) were evaluated using western blot and mouse orthotopic xenograft model. This study is aimed to identify novel transcriptional regulatory networks, which can collectively modulate invasion-involved genes in GBM. After classification of 23 GBM patient-derived TSs into low and high invasion groups, we applied single sample gene set enrichment analysis using TF target gene sets. According to enrichment scores, TFs responsible for low (PCBP1) and high (STAT3 and SRF) invasiveness were identified. Consistently with computational prediction, knockdown of PCBP1 significantly increased invasion area, whereas knockdown of STAT3 or SRF significantly suppressed invasive properties in all tested TSs. Notably, MR images showed coherent patterns with invasion of originated TS, and high invasiveness was associated with poor prognosis. In addition, mouse orthotopic xenograft model using TSs with down-regulated STAT3 or SRF showed significantly prolonged survival time compared to control. We identified invasion-deterministic TFs in glioblastoma using integrative transcriptome analysis. Owing to relationship among these transcriptional regulatory networks, invasive phenotype, and prognosis, we suggest that these TFs as novel drug targets for GBM.

Unraveling the functions of uncharacterized transcription factors in Escherichia coli using ChIP-exo

10.1101/2021.06.10.447994 ◽

2021 ◽

Author(s):

Ye Gao ◽

Hyun Gyu Lim ◽

Hans Verkler ◽

Richard Szubin ◽

Daniel Quach ◽

...

Keyword(s):

Escherichia Coli ◽

Transcription Factors ◽

Dna Binding ◽

Binding Sites ◽

Regulatory Networks ◽

Cellular Processes ◽

Mutant Phenotypes ◽

K 12

Bacteria regulate gene expression to adapt to changing environments through transcriptional regulatory networks (TRNs). Although extensively studied, no TRN is fully characterized since the identity and activity of all the transcriptional regulators that comprise a TRN are not known. Here, we experimentally evaluate 40 uncharacterized proteins in Escherichia coli K-12 MG1655, which were computationally predicted to be transcription factors (TFs). First, we used a multiplexed ChIP-exo assay to characterize genome-wide binding sites for these candidate TFs; 34 of them were found to be DNA-binding protein. We then compared the relative location between binding sites and RNA polymerase (RNAP). We found 48% (283/588) overlap between the TFs and RNAP. Finally, we used these data to infer potential functions for 10 of the 34 TFs with validated DNA binding sites and consensus binding motifs. These TFs were found to have various roles in regulating primary cellular processes in E. coli. Taken together, this study: (1) significantly expands the number of confirmed TFs, close to the estimated total of about 280 TFs; (2) predicts the putative functions of the newly discovered TFs, and (3) confirms the functions of representative TFs through mutant phenotypes.