Negative reciprocity, not ordered assembly, underlies the interaction of Sox2 and Oct4 on DNA

Governing principles of transcriptional logic out of equilibrium

To survive, adapt, and develop, cells respond to external and internal stimuli by tightly regulating transcription. Transcriptional regulation involves the combinatorial binding of a repertoire of transcription factors to DNA, which often results in switch-like binary outputs akin to Boolean logic gates. Recent experimental studies have demonstrated that in eukaryotes, transcription factor binding to DNA often involves energy expenditure, thereby driving the system out of equilibrium. The governing principles of transcriptional logic operations out of equilibrium remain unexplored. Here, we employ a simple two-input, single-locus model of transcription that can accommodate both equilibrium and nonequilibrium mechanisms. Using this model, we find that nonequilibrium regimes can give rise to all the logic operations accessible in equilibrium. Strikingly, energy expenditure alters the regulatory function of the two transcription factors in a mutually exclusive manner. This allows for the emergence of new logic operations that are inaccessible in equilibrium. Overall, our results show that energy expenditure can expand the range of cellular decision-making without the need for more complex promoter architectures.

The linear framework II: using graph theory to analyse the transient regime of Markov processes

The linear framework uses finite, directed graphs with labelled edges to model biomolecular systems. Graph vertices represent chemical species or molecular states, edges represent reactions or transitions and edge labels represent rates that also describe how the system is interacting with its environment. The present paper is a sequel to a recent review of the framework that focussed on how graph-theoretic methods give insight into steady states as rational algebraic functions of the edge labels. Here, we focus on the transient regime for systems that correspond to continuous-time Markov processes. In this case, the graph specifies the infinitesimal generator of the process. We show how the moments of the first-passage time distribution, and related quantities, such as splitting probabilities and conditional first-passage times, can also be expressed as rational algebraic functions of the labels. This capability is timely, as new experimental methods are finally giving access to the transient dynamic regime and revealing the computations and information processing that occur before a steady state is reached. We illustrate the concepts, methods and formulas through examples and show how the results may be used to illuminate previous findings in the literature.

Theoretical investigation of functional responses of bio-molecular assembly networks

Cooperative protein-protein and protein-DNA interactions form programmable complex assemblies, often performing non-linear gene regulatory operations involved in signal transductions and cell fate determination. The apparent structure of those complex assemblies is very similar, but their functional response strongly depends on the topology of the protein-DNA interaction networks. Here, we demonstrate how the coordinated self-assembly creates gene regulatory network motifs that corroborate the existence of a precise functional response at the molecular level using thermodynamic and dynamic analyses. Our theoretical and Monte Carlo simulations show that a complex network of interactions can form a decision-making loop, such as feedback and feed-forward circuits, only by a few molecular mechanisms. We characterize each possible network of interactions by systematic variations of free energy parameters associated with the binding among biomolecules and DNA looping. We also find that the higher-order networks exhibit alternative steady states from the stochastic dynamics of each network. We capture this signature by calculating stochastic potentials and attributing their multi-stability features. We validate our findings against the Gal promoter system in yeast cells. Overall, we show that the network topology is vital in phenotype diversity in regulatory circuits.

Transcriptional kinetic synergy: A complex landscape revealed by integrating modeling and synthetic biology

Transcription factors (TFs) control gene expression, often acting synergistically. Classical thermodynamic models offer a biophysical explanation for synergy based on binding cooperativity and regulated recruitment of RNA polymerase. Because transcription requires polymerase to transition through multiple states, recent work suggests that "kinetic synergy" can arise through TFs acting on distinct steps of the transcription cycle. These types of synergy are not mutually exclusive and are difficult to disentangle conceptually and experimentally. Here, we model and build a synthetic circuit in which TFs bind to a single shared site on DNA, such that TFs cannot synergize by simultaneous binding. We model mRNA production as a function of both TF binding and regulation of the transcription cycle, revealing a complex landscape dependent on TF concentration, DNA binding affinity, and regulatory activity. We use synthetic TFs to confirm that the transcription cycle must be integrated with recruitment for a quantitative understanding of gene regulation.

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.

Reformulating nonequilibrium steady states and generalized Hopfield discrimination

Despite substantial progress in nonequilibrium physics, steady-state (s.s.) probabilities remain intractable to analysis. For a Markov process, s.s. probabilities can be expressed in terms of transition rates using the graph-theoretic matrix-tree theorem (MTT). The MTT reveals that, away from equilibrium, s.s. probabilities become globally dependent on all rates, with expressions growing exponentially in the system size. This overwhelming complexity and lack of thermodynamic interpretation have greatly impeded analysis. Here we show that s.s. probabilities are proportional to the average of exp(-S(P)), where S(P) is the entropy generated along minimal paths P in the graph, and the average is taken over a probability distribution on spanning trees. Assuming Arrhenius rates, this "arboreal" distribution becomes Boltzmann-like, with the energy of a tree being its total edge barrier energy. This reformulation offers a thermodynamic interpretation that smoothly generalizes equilibrium statistical mechanics and reorganizes the expression complexity: the number of distinct minimal-path entropies depends not on graph size but on the entropy production index, a measure of nonequilibrium complexity. We demonstrate the power of this reformulation by extending Hopfield's analysis of discrimination by kinetic proofreading to any graph with index 1. We derive a general formula for the error ratio and use it to show how local energy dissipation can yield optimal discrimination through global synergy.

Whole-Transcriptome Sequencing Analyses of Nuclear Antixoxidant-1 in Endothelial Cells: Role in Inflammation and Atherosclerosis

Inflammation, oxidative stress, and copper (Cu) play an important role in cardiovascular disease, including atherosclerosis. We previously reported that cytosolic Cu chaperone antioxidant-1 (Atox1) translocates to the nucleus in response to inflammatory cytokines or exogenous Cu and that Atox1 is localized at the nucleus in the endothelium of inflamed atherosclerotic aorta. However, the roles of nuclear Atox1 and their function are poorly understood. Here we showed that Atox1 deficiency in ApoE-/- mice with a Western diet exhibited a significant reduction of atherosclerotic lesion formation. In vitro, adenovirus-mediated overexpression of nuclear-targeted Atox1 (Ad-Atox1-NLS) in cultured human endothelial cells (ECs) increased monocyte adhesion and reactive oxygen species (ROS) production compared to control cells (Ad-null). To address the underlying mechanisms, we performed genome-wide mapping of Atox1-regulated targets in ECs, using an unbiased systemic approach integrating sequencing data. Combination of ChIP-Seq and RNA-Seq analyses in ECs transfected with Ad-Atox1-NLS or Ad-null identified 1387 differentially expressed genes (DEG). Motif enrichment assay and KEGG pathway enrichment analysis revealed that 248 differentially expressed genes, including inflammatory and angiogenic genes, were regulated by Atox1-NLS, which was then confirmed by real-time qPCR. Among these genes, functional analysis of inflammatory responses identified CD137, CSF1, and IL5RA as new nuclear Atox1-targeted inflammatory genes, while CD137 is also a key regulator of Atox1-NLS-induced ROS production. These findings uncover new nuclear Atox1 downstream targets involved in inflammation and ROS production and provide insights into the nuclear Atox1 as a potential therapeutic target for the treatment of inflammatory diseases such as atherosclerosis.

Pioneer Factor Improves CRISPR-Based C-To-G and C-To-T Base Editing

Base editing events in eukaryote require a compatible chromatin environment, but there is little research on how chromatin factors contribute to the editing efficiency or window. By engineering BEs (base editors) fused with various pioneer factors, the authors found that SOX2 substantially increased the editing efficiency for GBE and CBE. While SoxN-GBE (SOX2-NH3-GBE) improved the editing efficiency at overall cytosines of the protospacer, SoxM-GBE/CBE (SOX2-Middle-GBE/CBE) enabled the higher base editing at PAM-proximal cytosines. By separating functional domains of SOX2, the SadN-GBE (SOX2 activation domain-NH3-GBE) is constructed for higher editing efficiency and SadM-CBE for broader editing window to date. With the DNase I assay, it is also proved the increased editing efficiency is most likely associated with the induction of chromatin accessibility by SAD. Finally, SadM-CBE is employed to introduce a stop codon in the proto-oncogene MYC, at a locus rarely edited by previous editors with high efficiency. In this work, a new class of pioneer-BEs is constructed by fusion of pioneer factor or its functional domains, which exhibits higher editing efficiency or broader editing window in eukaryote.

The linear framework: using graph theory to reveal the algebra and thermodynamics of biomolecular systems

The linear framework uses finite, directed graphs with labelled edges to model biomolecular systems. Graph vertices represent biochemical species or molecular states, edges represent reactions or transitions and labels represent rates. The graph yields a linear dynamics for molecular concentrations or state probabilities, with the graph Laplacian as the operator, and the labels encode the nonlinear interactions between system and environment. The labels can be specified by vertices of other graphs or by conservation laws or, when the environment consists of thermodynamic reservoirs, they may be constants. In the latter case, the graphs correspond to infinitesimal generators of Markov processes. The key advantage of the framework has been that steady states are determined as rational algebraic functions of the labels by the Matrix-Tree theorems of graph theory. When the system is at thermodynamic equilibrium, this prescription recovers equilibrium statistical mechanics but it continues to hold for non-equilibrium steady states. The framework goes beyond other graph-based approaches in treating the graph as a mathematical object, for which general theorems can be formulated that accommodate biomolecular complexity. It has been particularly effective at analysing enzyme-catalysed modification systems and input-output responses.

Oct4 differentially regulates chromatin opening and enhancer transcription in pluripotent stem cells

The transcription factor Oct4 is essential for the maintenance and induction of stem cell pluripotency, but its functional roles are not fully understood. Here, we investigate the functions of Oct4 by depleting and subsequently recovering it in mouse embryonic stem cells (ESCs) and conducting a time-resolved multiomics analysis. Oct4 depletion leads to an immediate loss of its binding to enhancers, accompanied by a decrease in mRNA synthesis from its target genes that are part of the transcriptional network that maintains pluripotency. Gradual decrease of Oct4 binding to enhancers does not immediately change the chromatin accessibility but reduces transcription of enhancers. Conversely, partial recovery of Oct4 expression results in a rapid increase in chromatin accessibility, whereas enhancer transcription does not fully recover. These results indicate different concentration-dependent activities of Oct4. Whereas normal ESC levels of Oct4 are required for transcription of pluripotency enhancers, low levels of Oct4 are sufficient to retain chromatin accessibility, likely together with other factors such as Sox2.

Pluripotency factors determine gene expression repertoire at zygotic genome activation

Awakening of zygotic transcription in animal embryos relies on maternal pioneer transcription factors. The interplay of global and specific functions of these proteins remains poorly understood. Here, we analyze chromatin accessibility and time-resolved transcription in single and double mutant zebrafish embryos lacking pluripotency factors Pou5f3 and Sox19b. We show that two factors modify chromatin in a largely independent manner. We distinguish four types of direct enhancers by differential requirements for Pou5f3 or Sox19b. We demonstrate that changes in chromatin accessibility of enhancers underlie the changes in zygotic expression repertoire in the double mutants. Pou5f3 or Sox19b promote chromatin accessibility of enhancers linked to the genes involved in gastrulation and ventral fate specification. The genes regulating mesendodermal and dorsal fates are primed for activation independently of Pou5f3 and Sox19b. Strikingly, simultaneous loss of Pou5f3 and Sox19b leads to premature expression of genes, involved in regulation of organogenesis and differentiation.

Zygotic genome activation in zebrafish relies on pluripotency transcription factors Pou5f3 and Sox19b. Here the authors investigate how these factors interact in vivo by analyzing the changes in chromatin state and time-resolved transcription in Pou5f3 and Sox19b single and double mutant embryos.

The needle and the haystack: single molecule tracking to probe the transcription factor search in eukaryotes

Transcription factors (TFs) regulate transcription of their target genes by identifying and binding to regulatory regions of the genome among billions of potential non-specific decoy sites, a task that is often presented as a 'needle in the haystack' challenge. The TF search process is now well understood in bacteria, but its characterization in eukaryotes needs to account for the complex organization of the nuclear environment. Here we review how live-cell single molecule tracking is starting to shed light on the TF search mechanism in the eukaryotic cell and we outline the future challenges to tackle in order to understand how nuclear organization modulates the TF search process in physiological and pathological conditions.

Gene Expression at a Single Molecule Level: Implications for MDS and AML

Non-genetic heterogeneity, or gene expression stochasticity, is an important source of variability in biological systems. With the advent and improvement of single molecule resolution technologies, it has been shown that transcription dynamics and resultant transcript number fluctuations generate significant cell-to-cell variability that has important biological effects and may contribute substantially to both tissue homeostasis and disease. In this respect, the pathophysiology of stem cell-derived malignancies such as AML and MDS, which has historically been studied at the ensemble level, may require re-evaluation. To that end, it is our aim in this review to highlight the results of recent single-molecule, biophysical, and systems studies of gene expression dynamics, with the explicit purpose of demonstrating how the insights from these basic science studies may help inform and progress the field of leukemia biology and, ultimately, research into novel therapies.

Altering transcription factor binding reveals comprehensive transcriptional kinetics of a basic gene

Transcription is a vital process activated by transcription factor (TF) binding. The active gene releases a burst of transcripts before turning inactive again. While the basic course of transcription is well understood, it is unclear how binding of a TF affects the frequency, duration and size of a transcriptional burst. We systematically varied the residence time and concentration of a synthetic TF and characterized the transcription of a synthetic reporter gene by combining single molecule imaging, single molecule RNA-FISH, live transcript visualisation and analysis with a novel algorithm, Burst Inference from mRNA Distributions (BIRD). For this well-defined system, we found that TF binding solely affected burst frequency and variations in TF residence time had a stronger influence than variations in concentration. This enabled us to device a model of gene transcription, in which TF binding triggers multiple successive steps before the gene transits to the active state and actual mRNA synthesis is decoupled from TF presence. We quantified all transition times of the TF and the gene, including the TF search time and the delay between TF binding and the onset of transcription. Our quantitative measurements and analysis revealed detailed kinetic insight, which may serve as basis for a bottom-up understanding of gene regulation.

Allosteric conformational ensembles have unlimited capacity for integrating information

Integration of binding information by macromolecular entities is fundamental to cellular functionality. Recent work has shown that such integration cannot be explained by pairwise cooperativities, in which binding is modulated by binding at another site. Higher-order cooperativities (HOCs), in which binding is collectively modulated by multiple other binding events, appear to be necessary but an appropriate mechanism has been lacking. We show here that HOCs arise through allostery, in which effective cooperativity emerges indirectly from an ensemble of dynamically interchanging conformations. Conformational ensembles play important roles in many cellular processes but their integrative capabilities remain poorly understood. We show that sufficiently complex ensembles can implement any form of information integration achievable without energy expenditure, including all patterns of HOCs. Our results provide a rigorous biophysical foundation for analysing the integration of binding information through allostery. We discuss the implications for eukaryotic gene regulation, where complex conformational dynamics accompanies widespread information integration.

Single-molecule tracking of transcription protein dynamics in living cells: seeing is believing, but what are we seeing?

A universe of transcription factors (TFs), cofactors, as well as chromatin remodeling and modifying enzymes combine or compete on chromatin to control transcription. Measuring quantitatively how these proteins dynamically interact is required in order to formulate models with predictive ability to elucidate transcription control mechanisms. Single molecule tracking (SMT) provides a powerful tool towards this goal: it is a fluorescence microscopy approach that measures the location and mobility of individual TF molecules, as well as their rates of association with and dissociation from chromatin in the physiological context of the living cell. Here we review SMT principles, and discuss key TF properties uncovered by live-cell SMT, such as fast turnover (seconds), and formation of clusters that locally increase activity.

Gene Regulation in and out of Equilibrium

Determining whether and how a gene is transcribed are two of the central processes of life. The conceptual basis for understanding such gene regulation arose from pioneering biophysical studies in eubacteria. However, eukaryotic genomes exhibit vastly greater complexity, which raises questions not addressed by this bacterial paradigm. First, how is information integrated from many widely separated binding sites to determine how a gene is transcribed? Second, does the presence of multiple energy-expending mechanisms, which are absent from eubacterial genomes, indicate that eukaryotes are capable of improved forms of genetic information processing? An updated biophysical foundation is needed to answer such questions. We describe the linear framework, a graph-based approach to Markov processes, and show that it can accommodate many previous studies in the field. Under the assumption of thermodynamic equilibrium, we introduce a language of higher-order cooperativities and show how it can rigorously quantify gene regulatory properties suggested by experiment. We point out that fundamental limits to information processing arise at thermodynamic equilibrium and can only be bypassed through energy expenditure. Finally, we outline some of the mathematical challenges that must be overcome to construct an improved biophysical understanding of gene regulation.

Reversal symmetries for cyclic paths away from thermodynamic equilibrium

If a system is at thermodynamic equilibrium, an observer cannot tell whether a film of it is being played forward or in reverse: any transition will occur with the same frequency in the forward as in the reverse direction. However, if expenditure of energy changes the rate of even a single transition to yield a nonequilibrium steady state, such time-reversal symmetry undergoes a widespread breakdown, far beyond the point at which the energy is expended. An explosion of interdependency also arises, with steady-state probabilities of system states depending in a complicated manner on the rate of every transition in the system. Nevertheless, in the midst of this global nonequilibrium complexity, we find that cyclic paths have reversibility properties that remain local, and which can exhibit symmetry, no matter how far the system is from thermodynamic equilibrium. Specifically, given any cycle of reversible transitions, the ratio of the frequencies with which the cycle occurs in one direction versus the other is determined, in the long-time limit, only by the thermodynamic force on the cycle itself, without requiring knowledge of transition rates elsewhere in the system. In particular, if there is no net energy expenditure on the cycle, then, over long times, the cycle occurrence frequencies are the same in either direction.

Transcription Factors and DNA Play Hide and Seek

Transcription factors (TFs) bind to specific DNA motifs to regulate the expression of target genes. To reach their binding sites, TFs diffuse in 3D and perform local motions such as 1D sliding, hopping, or intersegmental transfer. TF-DNA interactions depend on multiple parameters, such as the chromatin environment, TF partitioning into distinct subcellular regions, and cooperativity with other DNA-binding proteins. In this review, how current understanding of the search process has initially been shaped by prokaryotic studies is discussed, as well as what is known about the parameters regulating TF search efficiency in the context of the complex eukaryotic chromatin landscape.

Nucleosome-bound SOX2 and SOX11 structures elucidate pioneer factor function

'Pioneer' transcription factors are required for stem-cell pluripotency, cell differentiation and cell reprogramming1,2. Pioneer factors can bind nucleosomal DNA to enable gene expression from regions of the genome with closed chromatin. SOX2 is a prominent pioneer factor that is essential for pluripotency and self-renewal of embryonic stem cells3. Here we report cryo-electron microscopy structures of the DNA-binding domains of SOX2 and its close homologue SOX11 bound to nucleosomes. The structures show that SOX factors can bind and locally distort DNA at superhelical location 2. The factors also facilitate detachment of terminal nucleosomal DNA from the histone octamer, which increases DNA accessibility. SOX-factor binding to the nucleosome can also lead to a repositioning of the N-terminal tail of histone H4 that includes residue lysine 16. We speculate that this repositioning is incompatible with higher-order nucleosome stacking, which involves contacts of the H4 tail with a neighbouring nucleosome. Our results indicate that pioneer transcription factors can use binding energy to initiate chromatin opening, and thereby facilitate nucleosome remodelling and subsequent transcription.

Nonreciprocal and Conditional Cooperativity Directs the Pioneer Activity of Pluripotency Transcription Factors

Cooperative binding of transcription factors (TFs) to chromatin orchestrates gene expression programming and cell fate specification. However, the biophysical principles of TF cooperativity remain incompletely understood. Here we use single-molecule fluorescence microscopy to study the partnership between Sox2 and Oct4, two core members of the pluripotency gene regulatory network. We find that the ability of Sox2 to target DNA inside nucleosomes is strongly affected by the translational and rotational positioning of its binding motif. In contrast, Oct4 can access nucleosomal sites with equal capacities. Furthermore, the Sox2-Oct4 pair displays nonreciprocal cooperativity, with Oct4 modulating interaction of Sox2 with the nucleosome but not vice versa. Such cooperativity is conditional upon the composite motif's residing at specific nucleosomal locations. These results reveal that pioneer factors possess distinct chromatin-binding properties and suggest that the same set of TFs can differentially regulate gene activities on the basis of their motif positions in the nucleosomal context.