How transcription factors can adjust the gene expression floodgates

Transcription factor competition facilitates self-sustained oscillations in single gene genetic circuits

Genetic feedback loops can be used by cells to regulate internal processes or to keep track of time. It is often thought that, for a genetic circuit to display self-sustained oscillations, a degree of cooperativity is needed in the binding and unbinding of actor species. This cooperativity is usually modeled using a Hill function, regardless of the actual promoter architecture. Furthermore, genetic circuits do not operate in isolation and often transcription factors are shared between different promoters. In this work we show how mathematical modelling of genetic feedback loops can be facilitated with a mechanistic fold-change function that takes into account the titration effect caused by competing binding sites for transcription factors. The model shows how the titration effect facilitates self-sustained oscillations in a minimal genetic feedback loop: a gene that produces its own repressor directly without cooperative transcription factor binding. The use of delay-differential equations leads to a stability contour that predicts whether a genetic feedback loop will show self-sustained oscillations, even when taking the bursty nature of transcription into account.

Reconciling kinetic and thermodynamic models of bacterial transcription

The study of transcription remains one of the centerpieces of modern biology with implications in settings from development to metabolism to evolution to disease. Precision measurements using a host of different techniques including fluorescence and sequencing readouts have raised the bar for what it means to quantitatively understand transcriptional regulation. In particular our understanding of the simplest genetic circuit is sufficiently refined both experimentally and theoretically that it has become possible to carefully discriminate between different conceptual pictures of how this regulatory system works. This regulatory motif, originally posited by Jacob and Monod in the 1960s, consists of a single transcriptional repressor binding to a promoter site and inhibiting transcription. In this paper, we show how seven distinct models of this so-called simple-repression motif, based both on thermodynamic and kinetic thinking, can be used to derive the predicted levels of gene expression and shed light on the often surprising past success of the thermodynamic models. These different models are then invoked to confront a variety of different data on mean, variance and full gene expression distributions, illustrating the extent to which such models can and cannot be distinguished, and suggesting a two-state model with a distribution of burst sizes as the most potent of the seven for describing the simple-repression motif.

Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression

It is tempting to believe that we now own the genome. The ability to read and rewrite it at will has ushered in a stunning period in the history of science. Nonetheless, there is an Achilles' heel exposed by all of the genomic data that has accrued: We still do not know how to interpret them. Many genes are subject to sophisticated programs of transcriptional regulation, mediated by DNA sequences that harbor binding sites for transcription factors, which can up- or down-regulate gene expression depending upon environmental conditions. This gives rise to an input-output function describing how the level of expression depends upon the parameters of the regulated gene-for instance, on the number and type of binding sites in its regulatory sequence. In recent years, the ability to make precision measurements of expression, coupled with the ability to make increasingly sophisticated theoretical predictions, has enabled an explicit dialogue between theory and experiment that holds the promise of covering this genomic Achilles' heel. The goal is to reach a predictive understanding of transcriptional regulation that makes it possible to calculate gene expression levels from DNA regulatory sequence. This review focuses on the canonical simple repression motif to ask how well the models that have been used to characterize it actually work. We consider a hierarchy of increasingly sophisticated experiments in which the minimal parameter set learned at one level is applied to make quantitative predictions at the next. We show that these careful quantitative dissections provide a template for a predictive understanding of the many more complex regulatory arrangements found across all domains of life.

mRNA function after intracellular delivery and release

Nanocarrier-mediated mRNA delivery and release into the cells with subsequent translation to protein is of interest in the context of the development of a new generation of drugs. In particular, this protein can play a role of a transcription factor and be used as a tool to regulate temporarily the genetic networks. The corresponding transient kinetics of gene expression are expected to depend on the mechanism and duration of mRNA release. Assuming the release to be rapid on the time scale of other steps, the author shows theoretically the mRNA-related transient features of gene expression occurring in stable, bistable, and oscillatory regimes in a single cell. Qualitatively, the results obtained are found to be fairly similar to those reported earlier for the situation when the release is slow. Thus, the features of the transient kinetics under consideration appear to be less sensitive to the duration of mRNA release compared to what one might expect.

Kinetics of lipid-nanoparticle-mediated intracellular mRNA delivery and function

mRNA delivery into cells forms the basis for one of the new and promising ways to treat various diseases. Among suitable carriers, lipid nanoparticles (LNPs) with a size of about 100 nm are now often employed. Despite high current interest in this area, the understanding of the basic details of LNP-mediated mRNA delivery and function is limited. To clarify the kinetics of mRNA release from LNPs, the author uses three generic models implying (i) exponential, (ii) diffusion-controlled, and (iii) detachment-controlled kinetic regimes, respectively. Despite the distinct differences in these kinetics, the associated transient kinetics of mRNA translation to the corresponding protein and its degradation are shown to be not too sensitive to the details of the mRNA delivery by LNPs (or other nanocarriers). In addition, the author illustrates how this protein may temporarily influence the expression of one gene or a few equivalent genes. The analysis includes positive or negative regulation of the gene transcription via the attachment of the protein without or with positive or negative feedback in the gene expression. Stable, bistable, and oscillatory schemes have been scrutinized in this context.

Self-consistent theory of transcriptional control in complex regulatory architectures

Individual regulatory proteins are typically charged with the simultaneous regulation of a battery of different genes. As a result, when one of these proteins is limiting, competitive effects have a significant impact on the transcriptional response of the regulated genes. Here we present a general framework for the analysis of any generic regulatory architecture that accounts for the competitive effects of the regulatory environment by isolating these effects into an effective concentration parameter. These predictions are formulated using the grand-canonical ensemble of statistical mechanics and the fold-change in gene expression is predicted as a function of the number of transcription factors, the strength of interactions between the transcription factors and their DNA binding sites, and the effective concentration of the transcription factor. The effective concentration is set by the transcription factor interactions with competing binding sites within the cell and is determined self-consistently. Using this approach, we analyze regulatory architectures in the grand-canonical ensemble ranging from simple repression and simple activation to scenarios that include repression mediated by DNA looping of distal regulatory sites. It is demonstrated that all the canonical expressions previously derived in the case of an isolated, non-competing gene, can be generalised by a simple substitution to their grand canonical counterpart, which allows for simple intuitive incorporation of the influence of multiple competing transcription factor binding sites. As an example of the strength of this approach, we build on these results to present an analytical description of transcriptional regulation of the lac operon.

Cooperative stabilization of Mycobacterium tuberculosis rrnAP3 promoter open complexes by RbpA and CarD

The essential mycobacterial transcriptional regulators RbpA and CarD act to modulate transcription by associating to the initiation complex and increasing the flux of transcript production. Each of these factors interacts directly with the promoter DNA template and with RNA polymerase (RNAP) holoenzyme. We recently reported on the energetics of CarD-mediated open complex stabilization on the Mycobacterium tuberculosis rrnAP3 ribosomal promoter using a stopped-flow fluorescence assay. Here, we apply this approach to RbpA and show that RbpA stabilizes RNAP-promoter open complexes (RPo) via a distinct mechanism from that of CarD. Furthermore, concentration-dependent stopped-flow experiments with both factors reveal positive linkage (cooperativity) between RbpA and CarD with regard to their ability to stabilize RPo The observation of positive linkage between RbpA and CarD demonstrates that the two factors can act on the same transcription initiation complex simultaneously. Lastly, with both factors present, the kinetics of open complex formation is significantly faster than in the presence of either factor alone and approaches that of E. coli RNAP on the same promoter. This work provides a quantitative framework for the molecular mechanisms of these two essential transcription factors and the critical roles they play in the biology and pathology of mycobacteria.

Napoleon Is in Equilibrium

It has been said that the cell is the test tube of the twenty-first century. If so, the theoretical tools needed to quantitatively and predictively describe what goes on in such test tubes lag sorely behind the stunning experimental advances in biology seen in the decades since the molecular biology revolution began. Perhaps surprisingly, one of the theoretical tools that has been used with great success on problems ranging from how cells communicate with their environment and each other to the nature of the organization of proteins and lipids within the cell membrane is statistical mechanics. A knee-jerk reaction to the use of statistical mechanics in the description of cellular processes is that living organisms are so far from equilibrium that one has no business even thinking about it. But such reactions are probably too hasty given that there are many regimes in which, because of a separation of timescales, for example, such an approach can be a useful first step. In this article, we explore the power of statistical mechanical thinking in the biological setting, with special emphasis on cell signaling and regulation. We show how such models are used to make predictions and describe some recent experiments designed to test them. We also consider the limits of such models based on the relative timescales of the processes of interest.

Reinitiation enhances reliable transcriptional responses in eukaryotes

Gene transcription is a noisy process carried out by the transcription machinery recruited to the promoter. Noise reduction is a fundamental requirement for reliable transcriptional responses which in turn are crucial for signal transduction. Compared with the relatively simple transcription initiation in prokaryotes, eukaryotic transcription is more complex partially owing to its additional reinitiation mechanism. By theoretical analysis, we showed that reinitiation reduces noise in eukaryotic transcription independent of the transcription level. Besides, a higher reinitiation rate enables a stable scaffold complex an advantage in noise reduction. Finally, we showed that the coupling between scaffold formation and transcription can further reduce transcription noise independent of the transcription level. Furthermore, compared with the reinitiation mechanism, the noise reduction effect of the coupling can be of more significance in the case that the transcription level is low and the intrinsic noise dominates. Our results uncover a mechanistic route which eukaryotes may use to facilitate a more reliable response in the noisy transcription process.

A framework for modelling gene regulation which accommodates non-equilibrium mechanisms

BACKGROUND

Gene regulation has, for the most part, been quantitatively analysed by assuming that regulatory mechanisms operate at thermodynamic equilibrium. This formalism was originally developed to analyse the binding and unbinding of transcription factors from naked DNA in eubacteria. Although widely used, it has made it difficult to understand the role of energy-dissipating, epigenetic mechanisms, such as DNA methylation, nucleosome remodelling and post-translational modification of histones and co-regulators, which act together with transcription factors to regulate gene expression in eukaryotes.

RESULTS

Here, we introduce a graph-based framework that can accommodate non-equilibrium mechanisms. A gene-regulatory system is described as a graph, which specifies the DNA microstates (vertices), the transitions between microstates (edges) and the transition rates (edge labels). The graph yields a stochastic master equation for how microstate probabilities change over time. We show that this framework has broad scope by providing new insights into three very different ad hoc models, of steroid-hormone responsive genes, of inherently bounded chromatin domains and of the yeast PHO5 gene. We find, moreover, surprising complexity in the regulation of PHO5, which has not yet been experimentally explored, and we show that this complexity is an inherent feature of being away from equilibrium. At equilibrium, microstate probabilities do not depend on how a microstate is reached but, away from equilibrium, each path to a microstate can contribute to its steady-state probability. Systems that are far from equilibrium thereby become dependent on history and the resulting complexity is a fundamental challenge. To begin addressing this, we introduce a graph-based concept of independence, which can be applied to sub-systems that are far from equilibrium, and prove that history-dependent complexity can be circumvented when sub-systems operate independently.

CONCLUSIONS

As epigenomic data become increasingly available, we anticipate that gene function will come to be represented by graphs, as gene structure has been represented by sequences, and that the methods introduced here will provide a broader foundation for understanding how genes work.

Drawing a Waddington landscape to capture dynamic epigenetics

Epigenetics is most often reduced to chromatin marking in the current literature, whereas this notion was initially defined in a more general context. This restricted view ignores that epigenetic memories are in fact more robustly ensured in living systems by steady-state mechanisms with permanent molecule renewal. This misconception is likely to result from misleading intuitions and insufficient dialogues between traditional and quantitative biologists. To demystify dynamic epigenetics, its most famous image, a Waddington landscape and its attractors, are explicitly drawn. The simple example provided, is sufficient to highlight the main requirements and characteristics of dynamic gene networks, underlying cellular differentiation, de-differentiation and trans-differentiation.

Life is a self-organizing machine driven by the informational cycle of Brillouin

Acquiring information is indisputably energy-consuming and conversely, the availability of information permits greater efficiency. Strangely, the scientific community long remained reluctant to establish a physical equivalence between the abstract notion of information and sensible thermodynamics. However, certain physicists such as Szilard and Brillouin proposed: (i) to give to information the status of a genuine thermodynamic entity (k B T ln2 joules/bit) and (ii) to link the capacity of storing information inferred from correlated systems, to that of indefinitely increasing organization. This positive feedback coupled to the self-templating molecular potential could provide a universal basis for the spontaneous rise of highly organized structures, typified by the emergence of life from a prebiotic chemical soup. Once established, this mechanism ensures the longevity and robustness of life envisioned as a general system, by allowing it to accumulate and optimize microstate-reducing recipes, thereby giving rise to strong nonlinearity, decisional capacity and multistability. Mechanisms possibly involved in priming this cycle are proposed.

Kinetic approaches to lactose operon induction and bimodality

The quasi-equilibrium approximation is acceptable when molecular interactions are fast enough compared to circuit dynamics, but is no longer allowed when cellular activities are governed by rare events. A typical example is the lactose operon (lac), one of the most famous paradigms of transcription regulation, for which several theories still coexist to describe its behaviors. The lac system is generally analyzed by using equilibrium constants, contradicting single-event hypotheses long suggested by Novick and Weiner (1957). Enzyme induction as an all-or-none phenomenon. Proc. Natl. Acad. Sci. USA 43, 553-566) and recently refined in the study of (Choi et al., 2008. A stochastic single-molecule event triggers phenotype switching of a bacterial cell. Science 322, 442-446). In the present report, a lac repressor (LacI)-mediated DNA immunoprecipitation experiment reveals that the natural LacI-lac DNA complex built in vivo is extremely tight and long-lived compared to the time scale of lac expression dynamics, which could functionally disconnect the abortive expression bursts and forbid using the standard modes of lac bistability. As alternatives, purely kinetic mechanisms are examined for their capacity to restrict induction through: (i) widely scattered derepression related to the arrival time variance of a predominantly backward asymmetric random walk and (ii) an induction threshold arising in a single window of derepression without recourse to nonlinear multimeric binding and Hill functions. Considering the complete disengagement of the lac repressor from the lac promoter as the probabilistic consequence of a transient stepwise mechanism, is sufficient to explain the sigmoidal lac responses as functions of time and of inducer concentration. This sigmoidal shape can be misleadingly interpreted as a phenomenon of equilibrium cooperativity classically used to explain bistability, but which has been reported to be weak in this system.

SOX2 co-occupies distal enhancer elements with distinct POU factors in ESCs and NPCs to specify cell state

SOX2 is a master regulator of both pluripotent embryonic stem cells (ESCs) and multipotent neural progenitor cells (NPCs); however, we currently lack a detailed understanding of how SOX2 controls these distinct stem cell populations. Here we show by genome-wide analysis that, while SOX2 bound to a distinct set of gene promoters in ESCs and NPCs, the majority of regions coincided with unique distal enhancer elements, important cis-acting regulators of tissue-specific gene expression programs. Notably, SOX2 bound the same consensus DNA motif in both cell types, suggesting that additional factors contribute to target specificity. We found that, similar to its association with OCT4 (Pou5f1) in ESCs, the related POU family member BRN2 (Pou3f2) co-occupied a large set of putative distal enhancers with SOX2 in NPCs. Forced expression of BRN2 in ESCs led to functional recruitment of SOX2 to a subset of NPC-specific targets and to precocious differentiation toward a neural-like state. Further analysis of the bound sequences revealed differences in the distances of SOX and POU peaks in the two cell types and identified motifs for additional transcription factors. Together, these data suggest that SOX2 controls a larger network of genes than previously anticipated through binding of distal enhancers and that transitions in POU partner factors may control tissue-specific transcriptional programs. Our findings have important implications for understanding lineage specification and somatic cell reprogramming, where SOX2, OCT4, and BRN2 have been shown to be key factors.

In mammals, a few thousand transcription factors regulate the differential expression of more than 20,000 genes to specify ∼200 functionally distinct cell types during development. How this is accomplished has been a major focus of biology. Transcription factors bind non-coding DNA regulatory elements, including proximal promoters and distal enhancers, to control gene expression. Emerging evidence indicates that transcription factor binding at distal enhancers plays an important role in the establishment of tissue-specific gene expression programs during development. Further, combinatorial binding among groups of transcription factors can further increase the diversity and specificity of regulatory modules. Here, we report the genome-wide binding profile of the HMG-box containing transcription factor SOX2 in mouse embryonic stem cells (ESCs) and neural progenitor cells (NPCs), and we show that SOX2 occupied a distinct set of binding sites with POU homeodomain family members, OCT4 in ESCs and BRN2 in NPCs. Thus, transitions in SOX2-POU partners may control tissue-specific gene networks. Ultimately, a global analysis detailing the combinatorial binding of transcription factors across all tissues is critical to understand cell fate specification in the context of the complex mammalian genome.

Unraveling complex interplay between heat shock factor 1 and 2 splicing isoforms

Chaperone synthesis in response to proteotoxic stress is dependent on a family of transcription factors named heat shock factors (HSFs). The two main factors in this family, HSF1 and HSF2, are co-expressed in numerous tissues where they can interact and form heterotrimers in response to proteasome inhibition. HSF1 and HSF2 exhibit two alternative splicing isoforms, called α and β, which contribute to additional complexity in HSF transcriptional regulation, but remain poorly examined in the literature. In this work, we studied the transcriptional activity of HSF1 and HSF2 splicing isoforms transfected into immortalized Mouse Embryonic Fibroblasts (iMEFs) deleted for both Hsf1 and Hsf2, under normal conditions and after proteasome inhibition. We found that HSF1α is significantly more active than the β isoform after exposure to the proteasome inhibitor MG132. Furthermore, we clearly established that, while HSF2 had no transcriptional activity by itself, short β isoform of HSF2 exerts a negative role on HSF1β-dependent transactivation. To further assess the impact of HSF2β inhibition on HSF1 activity, we developed a mathematical modelling approach which revealed that the balance between each HSF isoform in the cell regulated the strength of the transcriptional response. Moreover, we found that cellular stress such as proteasome inhibition could regulate the splicing of Hsf2 mRNA. All together, our results suggest that relative amounts of each HSF1 and HSF2 isoforms quantitatively determine the cellular level of the proteotoxic stress response.

Epigenetic memories: structural marks or active circuits?

A hallmark of living systems is the management and the storage of information through genetic and epigenetic mechanisms. Although the notion of epigenetics was originally given to any regulation beyond DNA sequence, it has often been restricted to chromatin modifications, supposed to behave as cis-markers, specifying the sets of genes to be expressed or repressed. This definition does not take into account the initial view of epigenetics, based on nonlinear interaction networks whose "attractors" can remain stable without need for any chromatin mark. In addition, most chromatin modifications are the steady state resultants of highly dynamic modification and de-modification activities and, as such, seem poorly appropriate to work as long-term memory keepers. Instead, the basic support of epigenetic memory could remain the attractors, to which chromatin modifications belong as do many other components. The influence of chromatin modifications in memory is highly questionable when envisioned as static structural marks, but can be recovered under the dynamic circuitry perspective, thanks to their self-templating properties. Beside their standard repressive or permissive functions, chromatin modifications can also influence transcription in multiple ways such as: (1) by randomizing or inversely stabilizing gene expression, (2) by mediating cooperativity between pioneer and secondary transcription factors, and (3) in the hysteresis and the ultrasensitivity of gene expression switches, allowing the cells to take unambiguous transcriptional decisions.

A dynamic model of transcriptional imprinting derived from the vitellogenesis memory effect

Transcriptional memory of transient signals can be imprinted on living systems and influence their reactivity to repeated stimulations. Although they are classically ascribed to structural chromatin rearrangements in eukaryotes, such behaviors can also rely on dynamic memory circuits with sustained self-amplification loops. However, these phenomena are either of finite duration, or conversely associated to sustained phenotypic changes. A mechanism is proposed, in which only the responsiveness of the target gene is durably reset at a higher level after primary stimulation, using the celebrated but still puzzling vitellogenesis memory effect. The basic ingredients of this system are: 1), a positive autoregulation of the estrogen receptor α gene; 2), a strongly cooperative action of the estradiol receptor on vitellogenin expression; and 3), a variant isoform of the estradiol receptor with two autonomous transcription-activating modules, one of which is signal-independent and the other, signal-dependent. Realistic quantification supports the possibility of a multistationary situation in which ligand-independent activity is unable by itself to prime the amplification loop, but can click the system over a memory threshold after a primary stimulation. This ratchet transcriptional mechanism can have developmental and ecotoxicological importance and explain lifelong imprinting of past exposures without apparent phenotypic changes before restimulation and without need for persistent chromatin modifications.

Basic statistical recipes for the emergence of biochemical discernment

An essential step towards understanding life would be to identify the very basic mechanisms responsible for the discerning behaviour of living biochemical systems, absent from randomly reacting chemical soups. One intuitively feels that this question goes beyond the particular nature of the biological molecules and should relate to general physical principles. The pre-eminent physicist Ludwig Boltzmann early envisioned life as a struggle for entropy, in concordance with the subsequent principle of self-organization out of equilibrium. Re-examination of elementary steady state biochemical systems from a statistical perspective supports this view and shows that sigmoidal responses arising from microstates elimination, are sufficient to explain innermost characteristics of life, including its capacity to convert random molecular interactions into accurate biological reactions. A primary operating strategy to achieve this goal is the introduction of time-irreversible transitions in molecular state conversion cycles by injection of free energy, which confers decisional capacity to single macromolecules. Selected examples from various fields of molecular biology such as enzymology and gene expression, are provided to show that these non-equilibrium steady state mechanisms remain important in contemporary biochemical systems. But in addition, information archiving allowed the emergence of the time-reversible counterparts of these mechanisms, mediated by evolutionary pre-organized macromolecular complexes capable of generating discernment in a non-dissipative manner.

Thermodynamics of biological processes

There is a long and rich tradition of using ideas from both equilibrium thermodynamics and its microscopic partner theory of equilibrium statistical mechanics. In this chapter, we provide some background on the origins of the seemingly unreasonable effectiveness of ideas from both thermodynamics and statistical mechanics in biology. After making a description of these foundational issues, we turn to a series of case studies primarily focused on binding that are intended to illustrate the broad biological reach of equilibrium thinking in biology. These case studies include ligand-gated ion channels, thermodynamic models of transcription, and recent applications to the problem of bacterial chemotaxis. As part of the description of these case studies, we explore a number of different uses of the famed Monod-Wyman-Changeux (MWC) model as a generic tool for providing a mathematical characterization of two-state systems. These case studies should provide a template for tailoring equilibrium ideas to other problems of biological interest.

Understanding the temporal codes of intra-cellular signals

The health of organisms and cells depends on appropriate responses to diverse internal and external cues, stimuli, or challenges, such as changes in hormone or cytokine levels, or exposure to a pathogen. Cellular responses must be tailored to the identity and intensity of the stimulus and therefore intra-cellular signals must carry information about both. However, signaling mediators often form intricate networks that react to multiple stimuli yet manage to produce stimulus-specific responses. The multi-functionality ('functional pleiotropism') of signaling nodes suggests that biological networks have evolved ways of passing physiologically relevant stimulus information through shared channels. Increasing evidence supports the notion that this is achieved in part through temporal regulation of signaling mediators' activities. The present challenge is to identify the features of temporal activity profile that represent information about a given stimulus and understand how cells read the temporal codes to control their responses.

Condensed DNA: condensing the concepts

DNA is stored in vivo in a highly compact, so-called condensed phase, where gene regulatory processes are governed by the intricate interplay between different states of DNA compaction. These systems often have surprising properties, which one would not predict from classical concepts of dilute solutions. The mechanistic details of DNA packing are essential for its functioning, as revealed by the recent developments coming from biochemistry, electrostatics, statistical mechanics, and molecular and cell biology. Different aspects of condensed DNA behavior are linked to each other, but the links are often hidden in the bulk of experimental and theoretical details. Here we try to condense some of these concepts and provide interconnections between the different fields. After a brief description of main experimental features of DNA condensation inside viruses, bacteria, eukaryotes and the test tube, main theoretical approaches for the description of these systems are presented. We end up with an extended discussion of the role of DNA condensation in the context of gene regulation and mention potential applications of DNA condensation in gene therapy and biotechnology.