Hernan G. Garcia

Quantitative Imaging of Transcription in Living Drosophila Embryos Links Polymerase Activity to Patterning

Spatiotemporal patterns of gene expression are fundamental to every developmental program. The resulting macroscopic domains have been mainly characterized by their levels of gene products. However, the establishment of such patterns results from differences in the dynamics of microscopic events in individual cells such as transcription. It is unclear how these microscopic decisions lead to macroscopic patterns, as measurements in fixed tissue cannot access the underlying transcriptional dynamics. In vivo transcriptional dynamics have long been approached in single-celled organisms, but never in a multicellular developmental context. Here, we directly address how boundaries of gene expression emerge in the Drosophila embryo by measuring the absolute number of actively transcribing polymerases in real time in individual nuclei. Specifically, we show that the formation of a boundary cannot be quantitatively explained by the rate of mRNA production in each cell, but instead requires amplification of the dynamic range of the expression boundary. This amplification is accomplished by nuclei randomly adopting active or inactive states of transcription, leading to a collective effect where the fraction of active nuclei is modulated in space. Thus, developmental patterns are not just the consequence of reproducible transcriptional dynamics in individual nuclei, but are the result of averaging expression over space and time.

Dynamic regulation of eve stripe 2 expression reveals transcriptional bursts in living Drosophila embryos.

Significance There is considerable information about the spatial regulation of gene expression during pattern formation in animal development. Significantly less is known about temporal control, in part due to our inability to analyze gene activity in real time. Using a recently developed approach for the visualization of gene expression in living Drosophila embryos, we examined the well-known even-skipped stripe 2 expression pattern. Surprisingly, we observe that this classic pattern is quite transient and generated by discontinuous surges of transcriptional activity in individual cells. These results challenge a purely static framework for dissecting developmental programs and emphasize the importance of the dynamic features of pattern formation. We present the use of recently developed live imaging methods to examine the dynamic regulation of even-skipped (eve) stripe 2 expression in the precellular Drosophila embryo. Nascent transcripts were visualized via MS2 RNA stem loops. The eve stripe 2 transgene exhibits a highly dynamic pattern of de novo transcription, beginning with a broad domain of expression during nuclear cycle 12 (nc12), and progressive refinement during nc13 and nc14. The mature stripe 2 pattern is surprisingly transient, constituting just ∼15 min of the ∼90-min period of expression. Nonetheless, this dynamic transcription profile faithfully predicts the limits of the mature stripe visualized by conventional in situ detection methods. Analysis of individual transcription foci reveals intermittent bursts of de novo transcription, with duration cycles of 4–10 min. We discuss a multistate model of transcription regulation and speculate on its role in the dynamic repression of the eve stripe 2 expression pattern during development.

Concentration and Length Dependence of DNA Looping in Transcriptional Regulation

In many cases, transcriptional regulation involves the binding of transcription factors at sites on the DNA that are not immediately adjacent to the promoter of interest. This action at a distance is often mediated by the formation of DNA loops: Binding at two or more sites on the DNA results in the formation of a loop, which can bring the transcription factor into the immediate neighborhood of the relevant promoter. These processes are important in settings ranging from the historic bacterial examples (bacterial metabolism and the lytic-lysogeny decision in bacteriophage), to the modern concept of gene regulation to regulatory processes central to pattern formation during development of multicellular organisms. Though there have been a variety of insights into the combinatorial aspects of transcriptional control, the mechanism of DNA looping as an agent of combinatorial control in both prokaryotes and eukaryotes remains unclear. We use single-molecule techniques to dissect DNA looping in the lac operon. In particular, we measure the propensity for DNA looping by the Lac repressor as a function of the concentration of repressor protein and as a function of the distance between repressor binding sites. As with earlier single-molecule studies, we find (at least) two distinct looped states and demonstrate that the presence of these two states depends both upon the concentration of repressor protein and the distance between the two repressor binding sites. We find that loops form even at interoperator spacings considerably shorter than the DNA persistence length, without the intervention of any other proteins to prebend the DNA. The concentration measurements also permit us to use a simple statistical mechanical model of DNA loop formation to determine the free energy of DNA looping, or equivalently, the for looping.

Effect of promoter architecture on the cell-to-cell variability in gene expression.

According to recent experimental evidence, promoter architecture, defined by the number, strength and regulatory role of the operators that control transcription, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect variability in gene expression in a systematic rather than case-by-case fashion. In this article we make such a systematic investigation, based on a microscopic model of gene regulation that incorporates stochastic effects. In particular, we show how operator strength and operator multiplicity affect this variability. We examine different modes of transcription factor binding to complex promoters (cooperative, independent, simultaneous) and how each of these affects the level of variability in transcriptional output from cell-to-cell. We propose that direct comparison between in vivo single-cell experiments and theoretical predictions for the moments of the probability distribution of mRNA number per cell can be used to test kinetic models of gene regulation. The emphasis of the discussion is on prokaryotic gene regulation, but our analysis can be extended to eukaryotic cells as well.

Quantitative dissection of the simple repression input–output function

We present a quantitative case study of transcriptional regulation in which we carry out a systematic dialogue between theory and measurement for an important and ubiquitous regulatory motif in bacteria, namely, that of simple repression. This architecture is realized by a single repressor binding site overlapping the promoter. From the theory point of view, this motif is described by a single gene regulation function based upon only a few parameters that are convenient theoretically and accessible experimentally. The usual approach is turned on its side by using the mathematical description of these regulatory motifs as a predictive tool to determine the number of repressors in a collection of strains with a large variation in repressor copy number. The predictions and corresponding measurements are carried out over a large dynamic range in both expression fold change (spanning nearly four orders of magnitude) and repressor copy number (spanning about two orders of magnitude). The predictions are tested by measuring the resulting level of gene expression and are then validated by using quantitative immunoblots. The key outcomes of this study include a systematic quantitative analysis of the limits and validity of the input–output relation for simple repression, a precise determination of the in vivo binding energies for DNA–repressor interactions for several distinct repressor binding sites, and a repressor census for Lac repressor in Escherichia coli.

Enhancer additivity and non-additivity are determined by enhancer strength in the Drosophila embryo.

Metazoan genes are embedded in a rich milieu of regulatory information that often includes multiple enhancers possessing overlapping activities. In this study, we employ quantitative live imaging methods to assess the function of pairs of primary and shadow enhancers in the regulation of key patterning genes-knirps, hunchback, and snail-in developing Drosophila embryos. The knirps enhancers exhibit additive, sometimes even super-additive activities, consistent with classical gene fusion studies. In contrast, the hunchback enhancers function sub-additively in anterior regions containing saturating levels of the Bicoid activator, but function additively in regions where there are diminishing levels of the Bicoid gradient. Strikingly sub-additive behavior is also observed for snail, whereby removal of the proximal enhancer causes a significant increase in gene expression. Quantitative modeling of enhancer–promoter interactions suggests that weakly active enhancers function additively while strong enhancers behave sub-additively due to competition with the target promoter. DOI: http://dx.doi.org/10.7554/eLife.07956.001

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.

Transcription by the Numbers Redux: Experiments and Calculations that Surprise

The study of transcription has witnessed an explosion of quantitative effort both experimentally and theoretically. In this article we highlight some of the exciting recent experimental efforts in the study of transcription with an eye to the demands that such experiments put on theoretical models of transcription. From a modeling perspective, we focus on two broad classes of models: the so-called thermodynamic models that use statistical mechanics to reckon the level of gene expression as probabilities of promoter occupancy, and rate-equation treatments that focus on the temporal evolution of the activity of a given promoter and that make it possible to compute the distributions of messenger RNA and proteins. We consider several appealing case studies to illustrate how quantitative models have been used to dissect transcriptional regulation.

The embryo as a laboratory: quantifying transcription in Drosophila

Transcriptional regulation of gene expression is fundamental to most cellular processes, including determination of cellular fates. Quantitative studies of transcription in cultured cells have led to significant advances in identifying mechanisms underlying transcriptional control. Recent progress allowed implementation of these same quantitative methods in multicellular organisms to ask how transcriptional regulation unfolds both in vivo and at the single molecule level in the context of embryonic development. Here we review some of these advances in early Drosophila development, which bring the embryo on par with its single celled counterparts. In particular, we discuss progress in methods to measure mRNA and protein distributions in fixed and living embryos, and we highlight some initial applications that lead to fundamental new insights about molecular transcription processes. We end with an outlook on how to further exploit the unique advantages that come with investigating transcriptional control in the multicellular context of development.

DNA sequence-dependent mechanics and protein-assisted bending in repressor-mediated loop formation

As the chief informational molecule of life, DNA is subject to extensive physical manipulations. The energy required to deform double-helical DNA depends on sequence, and this mechanical code of DNA influences gene regulation, such as through nucleosome positioning. Here we examine the sequence-dependent flexibility of DNA in bacterial transcription factor-mediated looping, a context for which the role of sequence remains poorly understood. Using a suite of synthetic constructs repressed by the Lac repressor and two well-known sequences that show large flexibility differences in vitro, we make precise statistical mechanical predictions as to how DNA sequence influences loop formation and test these predictions using in vivo transcription and in vitro single-molecule assays. Surprisingly, sequence-dependent flexibility does not affect in vivo gene regulation. By theoretically and experimentally quantifying the relative contributions of sequence and the DNA-bending protein HU to DNA mechanical properties, we reveal that bending by HU dominates DNA mechanics and masks intrinsic sequence-dependent flexibility. Such a quantitative understanding of how mechanical regulatory information is encoded in the genome will be a key step towards a predictive understanding of gene regulation at single-base pair resolution.