Systematic analysis of low-affinity transcription factor binding site clusters in vitro and in vivo establishes their functional relevance

Rise and SINE: roles of transcription factors and retrotransposons in zygotic genome activation

In sexually reproducing organisms, life begins with the fusion of transcriptionally silent gametes, the oocyte and sperm. Although initiation of transcription in the embryo, known as zygotic genome activation (ZGA), is universally required for development, the transcription factors regulating this process are poorly conserved. In this Perspective, we discuss recent insights into the mechanisms of ZGA in totipotent mammalian embryos, namely ZGA regulation by several transcription factors, including by orphan nuclear receptors (OrphNRs) such as the pioneer transcription factor NR5A2, and by factors of the DUX, TPRX and OBOX families. We performed a meta-analysis and compiled a list of pan-ZGA genes, and found that most of these genes are indeed targets of the above transcription factors. Remarkably, more than a third of these ZGA genes appear to be regulated both by OrphNRs such as NR5A2 and by OBOX proteins, whose motifs co-occur in SINE B1 retrotransposable elements, which are enriched near ZGA genes. We propose that ZGA in mice is activated by recruitment of multiple transcription factors to SINE B1 elements that function as enhancers, and discuss a potential relevance of this mechanism to Alu retrotransposable elements in human ZGA.

Regulatory Components for Bacterial Cell-Free Systems Engineering

Cell-free systems are advancing synthetic biology through fast prototyping and modularity. Complex regulatory networks can now be implemented in cell-free systems enabling various applications, such as diagnostic tool development, gene circuit prototyping, and metabolic engineering. As functional complexity increases, the need for regulatory components also grows. This review provides a comprehensive overview of native as well as engineered regulatory components and their use in bacterial cell-free systems.

CelEst: a unified gene regulatory network for estimating transcription factor activities in C. elegans

Transcription factors (TFs) play a pivotal role in orchestrating critical intricate patterns of gene regulation. Although gene expression is complex, differential expression of hundreds of genes is often due to regulation by just a handful of TFs. Despite extensive efforts to elucidate TF-target regulatory relationships in Caenorhabditis elegans, existing experimental datasets cover distinct subsets of TFs and leave data integration challenging. Here, I introduce CelEst, a unified gene regulatory network designed to estimate the activity of 487 distinct C. elegans TFs-∼58% of the total-from gene expression data. To integrate data from ChIP-seq, DNA-binding motifs, and eY1H screens, optimal processing of each data type was benchmarked against a set of TF perturbation RNA-seq experiments. Moreover, I showcase how leveraging TF motif conservation in target promoters across genomes of related species can distinguish highly informative interactions, a strategy which can be applied to many model organisms. Integrated analyses of data from commonly studied conditions including heat shock, bacterial infection, and sex differences validates CelEst's performance and highlights overlooked TFs that likely play major roles in coordinating the transcriptional response to these conditions. CelEst can infer TF activity on a standard laptop computer within minutes. Furthermore, an R Shiny app with a step-by-step guide is provided for the community to perform rapid analysis with minimal coding required. I anticipate that widespread adoption of CelEsT will significantly enhance the interpretive power of transcriptomic experiments, both present and retrospective, thereby advancing our understanding of gene regulation in C. elegans and beyond.

A Cryptic Prophage Transcription Factor Drives Phenotypic Changes via Host Gene Regulation

Cryptic prophages (CPs) are elements of bacterial genomes acquired from bacteriophage that infect the host cell and ultimately become stably integrated within the host genome. While some proteins encoded by CPs can modulate host phenotypes, the potential for Transcription Factors (TFs) encoded by CPs to impact host physiology by regulating host genes has not been thoroughly investigated. In this work, we report hundreds of host genes regulated by DicC, a DNA-binding TF encoded in the Qin prophage of Esherichia coli. We identified host-encoded regulatory targets of DicC that could be linked to known phenotypes of its induction. We also demonstrate that a DicC-induced growth defect is largely independent of other Qin prophage genes. Our data suggest a greater role for cryptic prophage TFs in controlling bacterial host gene expression than previously appreciated.

The method in the madness: Transcriptional control from stochastic action at the single-molecule scale

Cell states result from the ordered activation of gene expression by transcription factors. Transcription factors face opposing design constraints: they need to be dynamic to trigger rapid cell state transitions, but also stable enough to maintain terminal cell identities indefinitely. Recent progress in live-cell single-molecule microscopy has helped define the biophysical principles underlying this paradox. Beyond transcription factor activity, single-molecule experiments have revealed that at nearly every level of transcription regulation, control emerges from multiple short-lived stochastic interactions, rather than deterministic, stable interactions typical of other biochemical pathways. This architecture generates consistent outcomes that can be rapidly choreographed. Here, we highlight recent results that demonstrate how order in transcription regulation emerges from the apparent molecular-scale chaos and discuss remaining conceptual challenges.

Predictive Biophysical Neural Network Modeling of a Compendium of in vivo Transcription Factor DNA Binding Profiles for Escherichia coli

The DNA binding of most Escherichia coli Transcription Factors (TFs) has not been comprehensively mapped, and few have models that can quantitatively predict binding affinity. We report the global mapping of in vivo DNA binding for 139 E. coli TFs using ChIP-Seq. We used these data to train BoltzNet, a novel neural network that predicts TF binding energy from DNA sequence. BoltzNet mirrors a quantitative biophysical model and provides directly interpretable predictions genome-wide at nucleotide resolution. We used BoltzNet to quantitatively design novel binding sites, which we validated with biophysical experiments on purified protein. We have generated models for 125 TFs that provide insight into global features of TF binding, including clustering of sites, the role of accessory bases, the relevance of weak sites, and the background affinity of the genome. Our paper provides new paradigms for studying TF-DNA binding and for the development of biophysically motivated neural networks.

Transcription factor interactions explain the context-dependent activity of CRX binding sites

The effects of transcription factor binding sites (TFBSs) on the activity of a cis-regulatory element (CRE) depend on the local sequence context. In rod photoreceptors, binding sites for the transcription factor (TF) Cone-rod homeobox (CRX) occur in both enhancers and silencers, but the sequence context that determines whether CRX binding sites contribute to activation or repression of transcription is not understood. To investigate the context-dependent activity of CRX sites, we fit neural network-based models to the activities of synthetic CREs composed of photoreceptor TFBSs. The models revealed that CRX binding sites consistently make positive, independent contributions to CRE activity, while negative homotypic interactions between sites cause CREs composed of multiple CRX sites to function as silencers. The effects of negative homotypic interactions can be overcome by the presence of other TFBSs that either interact cooperatively with CRX sites or make independent positive contributions to activity. The context-dependent activity of CRX sites is thus determined by the balance between positive heterotypic interactions, independent contributions of TFBSs, and negative homotypic interactions. Our findings explain observed patterns of activity among genomic CRX-bound enhancers and silencers, and suggest that enhancers may require diverse TFBSs to overcome negative homotypic interactions between TFBSs.

Transcriptional responses of cancer cells to heat shock-inducing stimuli involve amplification of robust HSF1 binding

Responses of cells to stimuli are increasingly discovered to involve the binding of sequence-specific transcription factors outside of known target genes. We wanted to determine to what extent the genome-wide binding and function of a transcription factor are shaped by the cell type versus the stimulus. To do so, we induced the Heat Shock Response pathway in two different cancer cell lines with two different stimuli and related the binding of its master regulator HSF1 to nascent RNA and chromatin accessibility. Here, we show that HSF1 binding patterns retain their identity between basal conditions and under different magnitudes of activation, so that common HSF1 binding is globally associated with distinct transcription outcomes. HSF1-induced increase in DNA accessibility was modest in scale, but occurred predominantly at remote genomic sites. Apart from regulating transcription at existing elements including promoters and enhancers, HSF1 binding amplified during responses to stimuli may engage inactive chromatin.

Optimisation of TP53 reporters by systematic dissection of synthetic TP53 response elements

TP53 is a transcription factor that controls multiple cellular processes, including cell cycle arrest, DNA repair and apoptosis. The relation between TP53 binding site architecture and transcriptional output is still not fully understood. Here, we systematically examined in three different cell lines the effects of binding site affinity and copy number on TP53-dependent transcriptional output, and also probed the impact of spacer length and sequence between adjacent binding sites, and of core promoter identity. Paradoxically, we found that high-affinity TP53 binding sites are less potent than medium-affinity sites. TP53 achieves supra-additive transcriptional activation through optimally spaced adjacent binding sites, suggesting a cooperative mechanism. Optimally spaced adjacent binding sites have a ∼10-bp periodicity, suggesting a role for spatial orientation along the DNA double helix. We leveraged these insights to construct a log-linear model that explains activity from sequence features, and to identify new highly active and sensitive TP53 reporters.

Noncanonical binding of transcription factors: time to revisit specificity?

Transcription factors (TFs) are one of the most studied classes of DNA-binding proteins that have a direct functional impact on gene transcription and thus, on human physiology and disease. The mechanisms that TFs use for recognizing target DNA binding sites have been studied for nearly five decades, yet they remain poorly understood. It is classically assumed that a TF recognizes a specific sequence pattern, or motif, as its binding sites. However, recent studies are consistently finding examples of noncanonical binding, that is, TFs binding at sites that do not resemble their sequence motifs. Here we review the current literature on four major types of noncanonical TF binding, namely binding based on DNA shape readout, at Guanine-quadruplex structures, at repeat sequences, and bispecific binding. These examples point to a critical need for studies to unify our current observations, many of which are at odds with the "one TF, one motif" view, into a more comprehensive definition of the DNA-binding specificity of TFs.

Ethanol Oxidation via 12-Electron Pathway on Spiky Au@AuPd Nanoparticles Assisted by Near-Infrared Light

In this work, ethanol oxidation reaction (EOR) via 12-electron (C1-12e) pathway on spiky Au@AuPd nanoparticles (NPs) with ultrathin AuPd alloy shells is achieved in alkaline media with the assistance of the near-infrared (NIR) light. It is found that OH radicals can be produced from the OH_ads species adsorbed on the surfaces of Pd atoms led by surface plasmon resonance (SPR) effect of spiky Au@AuPd NPs under the irradiation of NIR light. Moreover, OH radicals play the key role for the achievement of EOR proceeded by the desirable C1-12e pathway because OH radicals can directly break the C-C bonds of ethanol. Accordingly, the electrocatalytic performance of spiky Au@AuPd NPs toward EOR under NIR light is greatly improved. For instance, their mass activity can be up to 33.2 A mg_pd ^-1 in the 0.5 m KOH solution containing 0.5 m ethanol, which is about 158 times higher than that of commercial Pd/C catalysts (0.21 A mg_pd ^-1 ) and is better than those of the state-of-the-art Pd-based catalysts reported in literature thus far, to the best of our knowledge. Moreover, their highest mass activity can be further improved to 118.3 A mg_pd ^-1 in the 1.5 m KOH solution containing 1.25 m ethanol.

Competing constraints shape the nonequilibrium limits of cellular decision-making

Gene regulation is central to cellular function. Yet, despite decades of work, we lack quantitative models that can predict how transcriptional control emerges from molecular interactions at the gene locus. Thermodynamic models of transcription, which assume that gene circuits operate at equilibrium, have previously been employed with considerable success in the context of bacterial systems. However, the presence of ATP-dependent processes within the eukaryotic transcriptional cycle suggests that equilibrium models may be insufficient to capture how eukaryotic gene circuits sense and respond to input transcription factor concentrations. Here, we employ simple kinetic models of transcription to investigate how energy dissipation within the transcriptional cycle impacts the rate at which genes transmit information and drive cellular decisions. We find that biologically plausible levels of energy input can lead to significant gains in how rapidly gene loci transmit information but discover that the regulatory mechanisms underlying these gains change depending on the level of interference from noncognate activator binding. When interference is low, information is maximized by harnessing energy to push the sensitivity of the transcriptional response to input transcription factors beyond its equilibrium limits. Conversely, when interference is high, conditions favor genes that harness energy to increase transcriptional specificity by proofreading activator identity. Our analysis further reveals that equilibrium gene regulatory mechanisms break down as transcriptional interference increases, suggesting that energy dissipation may be indispensable in systems where noncognate factor interference is sufficiently large.

Deciphering the multi-scale, quantitative cis-regulatory code

Uncovering the cis-regulatory code that governs when and how much each gene is transcribed in a given genome and cellular state remains a central goal of biology. Here, we discuss major layers of regulation that influence how transcriptional outputs are encoded by DNA sequence and cellular context. We first discuss how transcription factors bind specific DNA sequences in a dosage-dependent and cooperative manner and then proceed to the cofactors that facilitate transcription factor function and mediate the activity of modular cis-regulatory elements such as enhancers, silencers, and promoters. We then consider the complex and poorly understood interplay of these diverse elements within regulatory landscapes and its relationships with chromatin states and nuclear organization. We propose that a mechanistically informed, quantitative model of transcriptional regulation that integrates these multiple regulatory layers will be the key to ultimately cracking the cis-regulatory code.