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The tumour suppressor p53 has a central role in the response to cellular stress. Activated p53 transcriptionally regulates hundreds of genes that are involved in multiple biological processes, including in DNA damage repair, cell cycle arrest, apoptosis and senescence. In the context of DNA damage, p53 is thought to be a decision-making transcription factor that selectively activates genes as part of specific gene expression programmes to determine cellular outcomes. In this Review, we discuss the multiple molecular mechanisms of p53 regulation and how they modulate the induction of apoptosis or cell cycle arrest following DNA damage. Specifically, we discuss how the interaction of p53 with DNA and chromatin affects gene expression, and how p53 post-translational modifications, its temporal expression dynamics and its interactions with chromatin regulators and transcription factors influence cell fate. These multiple layers of regulation enable p53 to execute cellular responses that are appropriate for specific cellular states and environmental conditions.Following DNA damage, the transcription factor p53 determines whether cells undergo apoptosis or cell cycle arrest and DNA repair. To enable different cellular outcomes, p53 is regulated through its temporal expression dynamics and post-translational modification, and by interactions with chromatin, chromatin regulators and transcription factors.

Oncoproteins of the MYC family are major drivers of human tumorigenesis. Since a large body of evidence indicates that MYC proteins are transcription factors, studying their function has focused on the biology of their target genes. Detailed studies of MYC-dependent changes in RNA levels have provided contrasting models of the oncogenic activity of MYC proteins through either enhancing or repressing the expression of specific target genes, or as global amplifiers of transcription. In this Review, we first summarize the biochemistry of MYC proteins and what is known (or is unclear) about the MYC target genes. We then discuss recent progress in defining the interactomes of MYC and MYCN and how this information affects central concepts of MYC biology, focusing on mechanisms by which MYC proteins modulate transcription. MYC proteins promote transcription termination upon stalling of RNA polymerase II, and we propose that this mechanism enhances the stress resilience of basal transcription. Furthermore, MYC proteins coordinate transcription elongation with DNA replication and cell cycle progression. Finally, we argue that the mechanism by which MYC proteins regulate the transcription machinery is likely to promote tumorigenesis independently of global or relative changes in the expression of their target genes.The MYC oncoproteins are transcription factors, but the molecular mechanism of their oncogenic activity is unclear. MYC proteins promote transcription termination in stress conditions, which is proposed to increase cellular resilience to stress and to promote tumorigenesis independently of changes in the expression of their target genes.

Cell behaviour is strongly influenced by physical, mechanical contacts between cells and their extracellular matrix. We review how the transcriptional regulators YAP and TAZ integrate mechanical cues with the response to soluble signals and metabolic pathways to control multiple aspects of cell behaviour, including proliferation, cell plasticity and stemness essential for tissue regeneration. Corruption of cell-environment interplay leads to aberrant YAP and TAZ activation that is instrumental for multiple diseases, including cancer. Stefano Piccolo and co-authors review recent insights into how YAP and TAZ transcription factors respond to the tissue environment, and how they mediate altered cell behaviour. Feedback mechanisms and crosstalk with other pathways are discussed, as are outstanding questions in the field.

Key Points Glucocorticoid receptor (GR), the founding member of the nuclear receptor superfamily, is a ubiquitously expressed, ligand-regulated vertebrate transcriptional regulatory factor (TRF) that regulates precisely determined gene networks. Although precise, GR-regulated gene networks are highly plastic, changing dramatically with changes in cell or physiological context. GR is regulated by multiple signals (ligands, DNA-binding sequences, post-translational modifications and non-GR TRFs). We propose that each of these signals acts as an allosteric effector that conveys gene, cell or physiological context information to GR by specifically altering its conformation. Integrated signal-driven conformational modifications of GR produce context-specific patterns of GR protein surfaces that are recognized by unique combinations of co-regulator proteins. GR, and perhaps many or all other TRFs, seems to lack intrinsic transcription regulatory activity and instead may be a molecular scaffold whose signal-driven structures nucleate the assembly of enzymatic machineries that confer distinct regulatory outcomes. Regulatory precision, signal-driven allostery and context-specified network plasticity are properties that are likely shared by most, if not all, metazoan TRFs. In response to steroid ligands, glucocorticoid receptor (GR) activates or represses gene expression in a highly context-specific manner. New evidence suggests that the conformation of GR is allosterically modulated by contextual signals, including DNA sequences, ligands, post-translational modifications and other transcription regulators, and that this supports the assembly of distinct transcription complexes. The glucocorticoid receptor (GR) is a constitutively expressed transcriptional regulatory factor (TRF) that controls many distinct gene networks, each uniquely determined by particular cellular and physiological contexts. The precision of GR-mediated responses seems to depend on combinatorial, context-specific assembly of GR-nucleated transcription regulatory complexes at genomic response elements. In turn, evidence suggests that context-driven plasticity is conferred by the integration of multiple signals, each serving as an allosteric effector of GR conformation, a key determinant of regulatory complex composition and activity. This structural and mechanistic perspective on GR regulatory specificity is likely to extend to other eukaryotic TRFs.

Cell-based biosensors have great potential to detect various toxic and pathogenic contaminants in aqueous environments. However, frequently they cannot meet practical requirements due to insufficient sensing performance. To address this issue, we investigated a modular, cascaded signal amplifying methodology. We first tuned intracellular sensory receptor densities to increase sensitivity, and then engineered multi-layered transcriptional amplifiers to sequentially boost output expression level. We demonstrated these strategies by engineering ultrasensitive bacterial sensors for arsenic and mercury, and improved detection limit and output up to 5,000-fold and 750-fold, respectively. Coupled by leakage regulation approaches, we developed an encapsulated microbial sensor cell array for low-cost, portable and precise field monitoring, where the analyte can be readily quantified via displaying an easy-to-interpret volume bar-like pattern. The ultrasensitive signal amplifying methodology along with the background regulation and the sensing platform will be widely applicable to many other cell-based sensors, paving the way for their real-world applications. An engineered biosensor, which optimizes metal-sensing and couples it to transcriptional amplification cascades that produce a fluorescent protein, was applied to build a sensitive and easy-to-use sensor for the toxic metals As 3+ and Hg 2+ .

Membraneless organelles or condensates form through liquid–liquid phase separation1–4, which is thought to underlie gene transcription through condensation of the large-scale nucleolus5–7 or in smaller assemblies known as transcriptional condensates8–11. Transcriptional condensates have been hypothesized to phase separate at particular genomic loci and locally promote the biomolecular interactions underlying gene expression. However, there have been few quantitative biophysical tests of this model in living cells, and phase separation has not yet been directly linked with dynamic transcriptional outputs12,13. Here, we apply an optogenetic approach to show that FET-family transcriptional regulators exhibit a strong tendency to phase separate within living cells, a process that can drive localized RNA transcription. We find that TAF15 has a unique charge distribution among the FET family members that enhances its interactions with the C-terminal domain of RNA polymerase II. Nascent C-terminal domain clusters at primed genomic loci lower the energetic barrier for nucleation of TAF15 condensates, which in turn further recruit RNA polymerase II to drive transcriptional output. These results suggest that positive feedback between interacting transcriptional components drives localized phase separation to amplify gene expression.Wei et al. show that clusters of unphosphorylated RNA polymerase II seed the nucleation of phase-separated condensates of TAF15, which further recruit RNA polymerase II to amplify transcriptional activation.

Stresses like low nutrients, systemic inflammation, cancer or infections provoke a catabolic state characterized by enhanced muscle proteolysis and amino acid release to sustain liver gluconeogenesis and tissue protein synthesis. These conditions activate the family of Forkhead Box (Fox) O transcription factors. Here we report that muscle-specific deletion of FoxO members protects from muscle loss as a result of the role of FoxOs in the induction of autophagy–lysosome and ubiquitin–proteasome systems. Notably, in the setting of low nutrient signalling, we demonstrate that FoxOs are required for Akt activity but not for mTOR signalling. FoxOs control several stress–response pathways such as the unfolded protein response, ROS detoxification, DNA repair and translation. Finally, we identify FoxO-dependent ubiquitin ligases including MUSA1 and a previously uncharacterised ligase termed SMART (Specific of Muscle Atrophy and Regulated by Transcription). Our findings underscore the central function of FoxOs in coordinating a variety of stress-response genes during catabolic conditions. FoxO transcription factors promote muscle atrophy in response to stresses such as low nutrient availability. By generating muscle-specific FoxO triple-knockout mice, Milan et al. identify mechanisms by which the FoxO transcriptional network coordinates autophagic and proteasomal protein degradation.

The multiple antibiotic resistance ( mar ) operon of Escherichia coli is a paradigm for chromosomally encoded antibiotic resistance in enteric bacteria. The locus is recognised for its ability to modulate efflux pump and porin expression via two encoded transcription factors, MarR and MarA. Here we map binding of these regulators across the E . coli genome and identify an extensive mar regulon. Most notably, MarA activates expression of genes required for DNA repair and lipid trafficking. Consequently, the mar locus reduces quinolone-induced DNA damage and the ability of tetracyclines to traverse the outer membrane. These previously unrecognised mar pathways reside within a core regulon, shared by most enteric bacteria. Hence, we provide a framework for understanding multidrug resistance, mediated by analogous systems, across the Enterobacteriaceae. Transcription factors MarR and MarA confer multidrug resistance in enteric bacteria by modulating efflux pump and porin expression. Here, Sharma et al. show that MarA also upregulates genes required for lipid trafficking and DNA repair, thus reducing antibiotic entry and quinolone-induced DNA damage. Transcription factors MarR and MarA confer multidrug resistance in enteric bacteria by modulating efflux pump and porin expression. Here, Sharma et al. show that MarA also upregulates genes required for lipid trafficking and DNA repair, thus reducing antibiotic entry and quinolone-induced DNA damage.

In synthetic biology designs, circuit components can generally move within the cell, meaning that functional cross-talk can cause faulty wiring. Genome mining, synthetic promoter construction and cross-reactivity screening now identify 20 orthogonal TetR repressor-promoter pairs for use in complex applications. Genetic circuits perform computational operations based on interactions between freely diffusing molecules within a cell. When transcription factors are combined to build a circuit, unintended interactions can disrupt its function. Here, we apply 'part mining' to build a library of 73 TetR-family repressors gleaned from prokaryotic genomes. The operators of a subset were determined using an in vitro method, and this information was used to build synthetic promoters. The promoters and repressors were screened for cross-reactions. Of these, 16 were identified that both strongly repress their cognate promoter (5- to 207-fold) and exhibit minimal interactions with other promoters. Each repressor-promoter pair was converted to a NOT gate and characterized. Used as a set of 16 NOT/NOR gates, there are >10 54 circuits that could be built by changing the pattern of input and output promoters. This represents a large set of compatible gates that can be used to construct user-defined circuits.

A fundamental unit of gene-regulatory control is the contact between a regulatory protein and its target DNA or RNA molecule. Biophysical models that directly predict these interactions are incomplete and confined to specific types of structures, but computational analysis of large-scale experimental datasets allows regulatory motifs to be identified by their over- representation in target sequences. In this issue, Alipanahi et al. describe the use of a deep learning strategy to calculate proteinnucleic acid interactions from diverse experimental data sets. They show that their algorithm, called DeepBind, is broadly applicable and results in increased predictive power compared to traditional single-domain methods, and they use its predictions to discover regulatory motifs, to predict RNA editing and alternative splicing, and to interpret genetic variants.