Transcription-Austin最新文献

{"title":"TFBSFootprinter: a multiomics tool for prediction of transcription factor binding sites in vertebrate species.","authors":"Harlan R Barker, Seppo Parkkila, MarttiE E Tolvanen","doi":"10.1080/21541264.2025.2521764","DOIUrl":"10.1080/21541264.2025.2521764","url":null,"abstract":"<p><strong>Background: </strong>Transcription factor (TF) proteins play a critical role in the regulation of eukaryotic gene expression via sequence-specific binding to genomic locations known as transcription factor binding sites (TFBSs). Accurate prediction of TFBSs is essential for understanding gene regulation, disease mechanisms, and drug discovery. These studies are therefore relevant not only in humans but also in model organisms and domesticated and wild animals. However, current tools for the automatic analysis of TFBSs in gene promoter regions are limited in their usability across multiple species. To our knowledge, no tools currently exist that allow for automatic analysis of TFBSs in gene promoter regions for many species.</p><p><strong>Methodology and findings: </strong>The TFBSFootprinter tool combines multiomic transcription-relevant data for more accurate prediction of functional TFBSs in 317 vertebrate species. In humans, this includes vertebrate sequence conservation (GERP), proximity to transcription start sites (FANTOM5), correlation of expression between target genes and TFs predicted to bind promoters (FANTOM5), overlap with ChIP-Seq TF metaclusters (GTRD), overlap with ATAC-Seq peaks (ENCODE), eQTLs (GTEx), and the observed/expected CpG ratio (Ensembl). In non-human vertebrates, this includes GERP, proximity to transcription start sites, and CpG ratio.TFBSFootprinter analyses are based on the Ensembl transcript ID for simplicity of use and require minimal setup steps. Benchmarking of the TFBSFootprinter on a manually curated and experimentally verified dataset of TFBSs produced superior results when using all multiomic data (average area under the receiver operating characteristic curve, 0.881), compared with DeepBind (0.798), DeepSEA (0.682), FIMO (0.817) and traditional PWM (0.854). The results were further improved by selecting the best overall combination of multiomic data (0.910). Additionally, we determined combinations of multiomic data that provide the best model of binding for each TF. TFBSFootprinter is available as Conda and Python packages.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":"16 2-3","pages":"204-223"},"PeriodicalIF":3.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12258250/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144620874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding complexity: tackling the challenge of how many transcription factors regulate a plant gene.","authors":"John Gray, Erich Grotewold","doi":"10.1080/21541264.2025.2521767","DOIUrl":"10.1080/21541264.2025.2521767","url":null,"abstract":"<p><p>The regulation of transcription is a major control point in the flow of information from the genome to the phenome. Central to this regulation are transcription factors (TFs), which bind specific DNA motifs in gene regulatory regions. In both metazoans and plants, 5-7% of all genes encode TFs. Although individual TFs can recognize and regulate thousands of target genes, an important question remains: how many TFs are required to precisely control the expression of a single gene? In this review, we compare the regulation of gene expression in plants and metazoans, outline key methodologies for identifying genes recognized or regulated by TFs, and explore what is currently known about the number of TFs needed to define the expression of any given plant gene. As the volume of high-throughput sequencing data continues to grow exponentially, it becomes increasingly clear that transcriptional regulatory networks exhibit remarkable complexity, characterized by many targets influenced by each TF; and that many TFs, often several dozens, contribute to the regulation of individual genes.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"261-283"},"PeriodicalIF":3.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12258188/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144498360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rho-dependent termination: a bacterial evolutionary capacitor for stress resistance.","authors":"Sarah B Worthan, Megan I Grant, Megan G Behringer","doi":"10.1080/21541264.2025.2474367","DOIUrl":"10.1080/21541264.2025.2474367","url":null,"abstract":"<p><p>Since the Modern Synthesis, interest has grown in resolving the \"black box\" between genotype and phenotype. Contained within this black box are highly plastic RNA and proteins with global effects on chromosome integrity and gene expression that serve as evolutionary capacitors - elements that enable the accumulation and buffering of genetic variation in normal conditions and reveal hidden genetic variation when induced by environmental stress. Discussion of evolutionary capacitors has primarily focused on eukaryotic translation factors and chaperones, such as Hsp90 and PSI+ prion. However, due to the coupling of transcription and translation in prokaryotes, transcription factors can be equally impactful in the modulation of gene expression and phenotypes. In this review, we discuss the prokaryotic transcription terminator Rho and how mutagenesis and plasticity of Rho influence epistasis, evolvability, and adaptation to stress in bacteria. We discuss the effects of variation in Rho generated by nature, laboratory mutagenesis, and experimental evolution; and how this variation is constrained or encouraged by Rho's extensive network of protein interactors. Exploring Rho's role as an evolutionary capacitor, along with identifying additional elements that can serve this function, can significantly advance our understanding of how organisms adapt to thrive in diverse environments.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"176-189"},"PeriodicalIF":3.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12258240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143568424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GATA3 and E2F6 negatively regulate WDR77 expression to inhibit prostate cancer cell growth.","authors":"Robin Brice, Zhengxin Wang","doi":"10.1080/21541264.2025.2476848","DOIUrl":"10.1080/21541264.2025.2476848","url":null,"abstract":"<p><p>The WD repeat domain 77 (WDR77) protein plays a critical role in prostate development and dysregulation of WDR77 expression is associated with prostate tumorigenesis. This study investigated the regulatory effects of GATA3 and E2F6 on WDR77 gene expression. A negative correlation between GATA3/E2F6 and WDR77 expression at both mRNA and protein levels was observed during prostate development and prostate tumorigenesis. Prostate cancer cells lost expression of GATA3 and E2F6 and re-expression of GATA3 and E2F6 resulted in a dose-dependent reduction in WDR77 expression and cell growth. Exogenous expression of WDR77 relieved the growth inhibition by GATA3. GATA3 and E2F6 directly interact with the promoter of the WDR77 gene in vitro and in vivo and repress WDR77 promoter activity. These results provide valuable insights into the molecular mechanisms governing WDR77 expression during prostate development and prostate tumorigenesis.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"190-203"},"PeriodicalIF":3.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12258259/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing transcription factors for therapeutic purposes.","authors":"Joaquin M Espinosa","doi":"10.1080/21541264.2025.2460249","DOIUrl":"10.1080/21541264.2025.2460249","url":null,"abstract":"","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"1-2"},"PeriodicalIF":3.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970771/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143415825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hypoxia-inducible transcription factors: architects of tumorigenesis and targets for anticancer drug discovery.","authors":"Alexander McDermott, Ali Tavassoli","doi":"10.1080/21541264.2024.2417475","DOIUrl":"10.1080/21541264.2024.2417475","url":null,"abstract":"<p><p>Hypoxia-inducible factors (HIFs) play a pivotal role as master regulators of tumor survival and growth, controlling a wide array of cellular processes in response to hypoxic stress. Clinical data correlates upregulated HIF-1 and HIF-2 levels with an aggressive tumor phenotype and poor patient outcome. Despite extensive validation as a target in cancer, pharmaceutical targeting of HIFs, particularly the interaction between α and βsubunits that forms the active transcription factor, has proved challenging. Nonetheless, many indirect inhibitors of HIFs have been identified, targeting diverse parts of this pathway. Significant strides have also been made in the development of direct inhibitors of HIF-2, exemplified by the FDA approval of Belzutifan for the treatment of metastatic clear cell renal carcinoma. While efforts to target HIF-1 using various therapeutic modalities have shown promise, no clinical candidates have yet emerged. This review aims to provide insights into the intricate and extensive role played by HIFs in cancer, and the ongoing efforts to develop therapeutic agents against this target.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"86-117"},"PeriodicalIF":3.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970764/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142523307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeting bacterial transcription factors for infection control: opportunities and challenges.","authors":"Ahmed Al-Tohamy, Anne Grove","doi":"10.1080/21541264.2023.2293523","DOIUrl":"10.1080/21541264.2023.2293523","url":null,"abstract":"<p><p>The rising threat of antibiotic resistance in pathogenic bacteria emphasizes the need for new therapeutic strategies. This review focuses on bacterial transcription factors (TFs), which play crucial roles in bacterial pathogenesis. We discuss the regulatory roles of these factors through examples, and we outline potential therapeutic strategies targeting bacterial TFs. Specifically, we discuss the use of small molecules to interfere with TF function and the development of transcription factor decoys, oligonucleotides that compete with promoters for TF binding. We also cover peptides that target the interaction between the bacterial TF and other factors, such as RNA polymerase, and the targeting of sigma factors. These strategies, while promising, come with challenges, from identifying targets to designing interventions, managing side effects, and accounting for changing bacterial resistance patterns. We also delve into how Artificial Intelligence contributes to these efforts and how it may be exploited in the future, and we touch on the roles of multidisciplinary collaboration and policy to advance this research domain.<b>Abbreviations:</b> AI, artificial intelligence; CNN, convolutional neural networks; DTI: drug-target interaction; HTH, helix-turn-helix; IHF, integration host factor; LTTRs, LysR-type transcriptional regulators; MarR, multiple antibiotic resistance regulator; MRSA, methicillin resistant <i>Staphylococcus aureus</i>; MSA: multiple sequence alignment; NAP, nucleoid-associated protein; PROTACs, proteolysis targeting chimeras; RNAP, RNA polymerase; TF, transcription factor; TFD, transcription factor decoying; TFTRs, TetR-family transcriptional regulators; wHTH, winged helix-turn-helix.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"141-168"},"PeriodicalIF":3.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970743/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138832205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transcription factors in the development and treatment of immune disorders.","authors":"Samantha D Patalano, Paula Fuxman Bass, Juan I Fuxman Bass","doi":"10.1080/21541264.2023.2294623","DOIUrl":"10.1080/21541264.2023.2294623","url":null,"abstract":"<p><p>Immune function is highly controlled at the transcriptional level by the binding of transcription factors (TFs) to promoter and enhancer elements. Several TF families play major roles in immune gene expression, including NF-κB, STAT, IRF, AP-1, NRs, and NFAT, which trigger anti-pathogen responses, promote cell differentiation, and maintain immune system homeostasis. Aberrant expression, activation, or sequence of isoforms and variants of these TFs can result in autoimmune and inflammatory diseases as well as hematological and solid tumor cancers. For this reason, TFs have become attractive drug targets, even though most were previously deemed \"undruggable\" due to their lack of small molecule binding pockets and the presence of intrinsically disordered regions. However, several aspects of TF structure and function can be targeted for therapeutic intervention, such as ligand-binding domains, protein-protein interactions between TFs and with cofactors, TF-DNA binding, TF stability, upstream signaling pathways, and TF expression. In this review, we provide an overview of each of the important TF families, how they function in immunity, and some related diseases they are involved in. Additionally, we discuss the ways of targeting TFs with drugs along with recent research developments in these areas and their clinical applications, followed by the advantages and disadvantages of targeting TFs for the treatment of immune disorders.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"118-140"},"PeriodicalIF":3.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970766/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138802192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aryl hydrocarbon receptor as a drug target in advanced prostate cancer therapy - obstacles and perspectives.","authors":"Jiřina Procházková, Zuzana Kahounová, Jan Vondráček, Karel Souček","doi":"10.1080/21541264.2024.2334106","DOIUrl":"10.1080/21541264.2024.2334106","url":null,"abstract":"<p><p>Aryl hydrocarbon receptor (AhR) is a transcription factor that is primarily known as an intracellular sensor of environmental pollution. After five decades, the list of synthetic and toxic chemicals that activate AhR signaling has been extended to include a number of endogenous compounds produced by various types of cells via their metabolic activity. AhR signaling is active from the very beginning of embryonal development throughout the life cycle and participates in numerous biological processes such as control of cell proliferation and differentiation, metabolism of aromatic compounds of endogenous and exogenous origin, tissue regeneration and stratification, immune system development and polarization, control of stemness potential, and homeostasis maintenance. AhR signaling can be affected by various pharmaceuticals that may help modulate abnormal AhR signaling and drive pathological states. Given their role in immune system development and regulation, AhR antagonistic ligands are attractive candidates for immunotherapy of disease states such as advanced prostate cancer, where an aberrant immune microenvironment contributes to cancer progression and needs to be reeducated. Advanced stages of prostate cancer are therapeutically challenging and characterized by decreased overall survival (OS) due to the metastatic burden. Therefore, this review addresses the role of AhR signaling in the development and progression of prostate cancer and discusses the potential of AhR as a drug target for the treatment of advanced prostate cancer upon entering the phase of drug resistance and failure of first-line androgen deprivation therapy.<b>Abbreviation</b>: ADC: antibody-drug conjugate; ADT: androgen deprivation therapy; AhR: aryl hydrocarbon receptor; AR: androgen receptor; ARE: androgen response element; ARPI: androgen receptor pathway inhibitor; mCRPC: metastatic castration-resistant prostate cancer; DHT: 5a-dihydrotestosterone; FICZ: 6-formylindolo[3,2-b]carbazole; 3-MC: 3-methylcholanthrene; 6-MCDF: 6-methyl-1,3,8-trichlorodibenzofuran; MDSCs: myeloid-derived suppressor cells; PAHs: polycyclic aromatic hydrocarbons; PCa: prostate cancer; TAMs: tumor-associated macrophages; TF: transcription factor; TCDD, 2,3,7,8-tetrachlorodibenzo-<i>p</i>-dioxin; TME: tumor microenvironment; TRAMP: transgenic adenocarcinoma of the mouse prostate; TROP2: tumor associated calcium signal transducer 2.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"47-66"},"PeriodicalIF":3.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970783/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140319480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond small molecules: advancing MYC-targeted cancer therapies through protein engineering.","authors":"Rama Edaibis, Raneem Akel, Jumi A Shin","doi":"10.1080/21541264.2025.2453315","DOIUrl":"10.1080/21541264.2025.2453315","url":null,"abstract":"<p><p>Protein engineering has emerged as a powerful approach toward the development of novel therapeutics targeting the MYC/MAX/E-box network, an active driver of >70% of cancers. The MYC/MAX heterodimer regulates numerous genes in our cells by binding the Enhancer box (E-box) DNA site and activating the transcription of downstream genes. Traditional small molecules that inhibit MYC face significant limitations that include toxic effects, drug delivery challenges, and resistance. Recent advances in protein engineering offer promising alternatives by creating protein-based drugs that directly disrupt the MYC/MAX dimerization interface and/or MYC/MAX's binding to specific DNA targets. Designed DNA binding proteins like Omomyc, DuoMyc, ME47, MEF, and Mad inhibit MYC activity through specific dimerization, sequestration, and DNA-binding mechanisms. Compared to small molecules, these engineered proteins can offer superior specificity and efficacy and provide a potential pathway for overcoming the limitations of traditional cancer therapies. The success of these protein therapeutics highlights the importance of protein engineering in developing cancer treatments.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"67-85"},"PeriodicalIF":3.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143061100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}