Mapping the fine structure of a eukaryotic promoter input-output function

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

Binding to binding site clusters has yet to be characterized in depth, and the functional relevance of low-affinity clusters remains uncertain. We characterized transcription factor binding to low-affinity clusters in vitro and found that transcription factors can bind concurrently to overlapping sites, challenging the notion of binding exclusivity. Furthermore, small clusters with binding sites an order of magnitude lower in affinity give rise to high mean occupancies at physiologically-relevant transcription factor concentrations. To assess whether the observed in vitro occupancies translate to transcriptional activation in vivo, we tested low-affinity binding site clusters in a synthetic and native gene regulatory network in S. cerevisiae. In both systems, clusters of low-affinity binding sites generated transcriptional output comparable to single or even multiple consensus sites. This systematic characterization demonstrates that clusters of low-affinity binding sites achieve substantial occupancies, and that this occupancy can drive expression in eukaryotic promoters.

Saccharomyces cerevisiae Promoter Engineering before and during the Synthetic Biology Era

Simple Summary

Promoters are DNA sequences where the process of transcription starts. They can work constitutively or be controlled by environmental signals of different types. The quantity of proteins and RNA present in yeast genetic circuits highly depends on promoter strength. Hence, they have been deeply studied and modified over, at least, the last forty years, especially since the year 2000 when Synthetic Biology was born. Here, we present how promoter engineering changed over these four decades and discuss its possible future directions due to novel computational methods and technology.

Abstract

Synthetic gene circuits are made of DNA sequences, referred to as transcription units, that communicate by exchanging proteins or RNA molecules. Proteins are, mostly, transcription factors that bind promoter sequences to modulate the expression of other molecules. Promoters are, therefore, key components in genetic circuits. In this review, we focus our attention on the construction of artificial promoters for the yeast S. cerevisiae, a popular chassis for gene circuits. We describe the initial techniques and achievements in promoter engineering that predated the start of the Synthetic Biology epoch of about 20 years. We present the main applications of synthetic promoters built via different methods and discuss the latest innovations in the wet-lab engineering of novel promoter sequences.

Effective dynamics of nucleosome configurations at the yeast PHO5 promoter

Chromatin dynamics are mediated by remodeling enzymes and play crucial roles in gene regulation, as established in a paradigmatic model, the Saccharomyces cerevisiae PHO5 promoter. However, effective nucleosome dynamics, that is, trajectories of promoter nucleosome configurations, remain elusive. Here, we infer such dynamics from the integration of published single-molecule data capturing multi-nucleosome configurations for repressed to fully active PHO5 promoter states with other existing histone turnover and new chromatin accessibility data. We devised and systematically investigated a new class of 'regulated on-off-slide' models simulating global and local nucleosome (dis)assembly and sliding. Only seven of 68,145 models agreed well with all data. All seven models involve sliding and the known central role of the N-2 nucleosome, but regulate promoter state transitions by modulating just one assembly rather than disassembly process. This is consistent with but challenges common interpretations of previous observations at the PHO5 promoter and suggests chromatin opening by binding competition.

High-Throughput Affinity Measurements of Transcription Factor and DNA Mutations Reveal Affinity and Specificity Determinants

Transcription factors (TFs) bind regulatory DNA to control gene expression, and mutations to either TFs or DNA can alter binding affinities to rewire regulatory networks and drive phenotypic variation. While studies have profiled energetic effects of DNA mutations extensively, we lack similar information for TF variants. Here, we present STAMMP (simultaneous transcription factor affinity measurements via microfluidic protein arrays), a high-throughput microfluidic platform enabling quantitative characterization of hundreds of TF variants simultaneously. Measured affinities for ∼210 mutants of a model yeast TF (Pho4) interacting with 9 oligonucleotides (>1,800 K_ds) reveal that many combinations of mutations to poorly conserved TF residues and nucleotides flanking the core binding site alter but preserve physiological binding, providing a mechanism by which combinations of mutations in cis and trans could modulate TF binding to tune occupancies during evolution. Moreover, biochemical double-mutant cycles across the TF-DNA interface reveal molecular mechanisms driving recognition, linking sequence to function. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.

How affinity of the ELT-2 GATA factor binding to cis-acting regulatory sites controls Caenorhabditis elegans intestinal gene transcription

We define a quantitative relationship between the affinity with which the intestine-specific GATA factor ELT-2 binds to cis-acting regulatory motifs and the resulting transcription of asp-1, a target gene representative of genes involved in Caenorhabditis elegans intestine differentiation. By establishing an experimental system that allows unknown parameters (e.g. the influence of chromatin) to effectively cancel out, we show that levels of asp-1 transcripts increase monotonically with increasing binding affinity of ELT-2 to variant promoter TGATAA sites. The shape of the response curve reveals that the product of the unbound ELT-2 concentration in vivo [i.e. (ELT-2free) or ELT-2 'activity'] and the largest ELT-XXTGATAAXX association constant (Kmax) lies between five and ten. We suggest that this (unitless) product [Kmax×(ELT-2free) or the equivalent product for any other transcription factor] provides an important quantitative descriptor of transcription-factor/regulatory-motif interaction in development, evolution and genetic disease. A more complicated model than simple binding affinity is necessary to explain the fact that ELT-2 appears to discriminate in vivo against equal-affinity binding sites that contain AGATAA instead of TGATAA.

Recent insights into the genotype-phenotype relationship from massively parallel genetic assays

With the molecular revolution in Biology, a mechanistic understanding of the genotype-phenotype relationship became possible. Recently, advances in DNA synthesis and sequencing have enabled the development of deep mutational scanning assays, capable of scoring comprehensive libraries of genotypes for fitness and a variety of phenotypes in massively parallel fashion. The resulting empirical genotype-fitness maps pave the way to predictive models, potentially accelerating our ability to anticipate the behaviour of pathogen and cancerous cell populations from sequencing data. Besides from cellular fitness, phenotypes of direct application in industry (e.g. enzyme activity) and medicine (e.g. antibody binding) can be quantified and even selected directly by these assays. This review discusses the technological basis of and recent developments in massively parallel genetics, along with the trends it is uncovering in the genotype-phenotype relationship (distribution of mutation effects, epistasis), their possible mechanistic bases and future directions for advancing towards the goal of predictive genetics.

Cell-free gene-regulatory network engineering with synthetic transcription factors

Gene-regulatory networks are ubiquitous in nature and critical for bottom-up engineering of synthetic networks. Transcriptional repression is a fundamental function that can be tuned at the level of DNA, protein, and cooperative protein-protein interactions, necessitating high-throughput experimental approaches for in-depth characterization. Here, we used a cell-free system in combination with a high-throughput microfluidic device to comprehensively study the different tuning mechanisms of a synthetic zinc-finger repressor library, whose affinity and cooperativity can be rationally engineered. The device is integrated into a comprehensive workflow that includes determination of transcription-factor binding-energy landscapes and mechanistic modeling, enabling us to generate a library of well-characterized synthetic transcription factors and corresponding promoters, which we then used to build gene-regulatory networks de novo. The well-characterized synthetic parts and insights gained should be useful for rationally engineering gene-regulatory networks and for studying the biophysics of transcriptional regulation.

Flexibility and structure of flanking DNA impact transcription factor affinity for its core motif

Spatial and temporal expression of genes is essential for maintaining phenotype integrity. Transcription factors (TFs) modulate expression patterns by binding to specific DNA sequences in the genome. Along with the core binding motif, the flanking sequence context can play a role in DNA-TF recognition. Here, we employ high-throughput in vitro and in silico analyses to understand the influence of sequences flanking the cognate sites in binding of three most prevalent eukaryotic TF families (zinc finger, homeodomain and bZIP). In vitro binding preferences of each TF toward the entire DNA sequence space were correlated with a wide range of DNA structural parameters, including DNA flexibility. Results demonstrate that conformational plasticity of flanking regions modulates binding affinity of certain TF families. DNA duplex stability and minor groove width also play an important role in DNA-TF recognition but differ in how exactly they influence the binding in each specific case. Our analyses further reveal that the structural features of preferred flanking sequences are not universal, as similar DNA-binding folds can employ distinct DNA recognition modes.

Microfluidic device for real-time formulation of reagents and their subsequent encapsulation into double emulsions

Emulsion drops are often employed as picoliter-sized containers to perform screening assays. These assays usually entail the formation of drops encompassing discrete objects such as cells or microparticles and reagents to study interactions between the different encapsulants. Drops are also used to screen influences of reagent concentrations on the final product. However, these latter assays are less frequently performed because it is difficult to change the reagent concentration over a wide range and with high precision within a single experiment. In this paper, we present a microfluidic double emulsion drop maker containing pneumatic valves that enable real-time formulation of different reagents using pulse width modulation and consequent encapsulation of the mixed solutions. This device can produce drops from reagent volumes as low as 10 µL with minimal sample loss, thereby enabling experiments that would be prohibitively expensive using drop generators that do not contain valves. We employ this device to monitor the kinetics of the cell-free synthesis of green fluorescent proteins inside double emulsions. To demonstrate the potential of this device for real-time formulation, we perform DNA titration experiments to test the influence of DNA concentration on the amount of green fluorescence protein produced in double emulsions by a coupled cell-free transcription / translation system.

Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding

Transcription factors (TFs) are primary regulators of gene expression in cells, where they bind specific genomic target sites to control transcription. Quantitative measurements of TF-DNA binding energies can improve the accuracy of predictions of TF occupancy and downstream gene expression in vivo and shed light on how transcriptional networks are rewired throughout evolution. Here, we present a sequencing-based TF binding assay and analysis pipeline (BET-seq, for Binding Energy Topography by sequencing) capable of providing quantitative estimates of binding energies for more than one million DNA sequences in parallel at high energetic resolution. Using this platform, we measured the binding energies associated with all possible combinations of 10 nucleotides flanking the known consensus DNA target interacting with two model yeast TFs, Pho4 and Cbf1. A large fraction of these flanking mutations change overall binding energies by an amount equal to or greater than consensus site mutations, suggesting that current definitions of TF binding sites may be too restrictive. By systematically comparing estimates of binding energies output by deep neural networks (NNs) and biophysical models trained on these data, we establish that dinucleotide (DN) specificities are sufficient to explain essentially all variance in observed binding behavior, with Cbf1 binding exhibiting significantly more nonadditivity than Pho4. NN-derived binding energies agree with orthogonal biochemical measurements and reveal that dynamically occupied sites in vivo are both energetically and mutationally distant from the highest affinity sites.

Relationship between histone modifications and transcription factor binding is protein family specific

The very small fraction of putative binding sites (BSs) that are occupied by transcription factors (TFs) in vivo can be highly variable across different cell types. This observation has been partly attributed to changes in chromatin accessibility and histone modification (HM) patterns surrounding BSs. Previous studies focusing on BSs within DNA regulatory regions found correlations between HM patterns and TF binding specificities. However, a mechanistic understanding of TF-DNA binding specificity determinants is still not available. The ability to predict in vivo TF binding on a genome-wide scale requires the identification of features that determine TF binding based on evolutionary relationships of DNA binding proteins. To reveal protein family-dependent mechanisms of TF binding, we conducted comprehensive comparisons of HM patterns surrounding BSs and non-BSs with exactly matched core motifs for TFs in three cell lines: 33 TFs in GM12878, 37 TFs in K562, and 18 TFs in H1-hESC. These TFs displayed protein family-specific preferences for HM patterns surrounding BSs, with high agreement among cell lines. Moreover, compared to models based on DNA sequence and shape at flanking regions of BSs, HM-augmented quantitative machine-learning methods resulted in increased performance in a TF family-specific manner. Analysis of the relative importance of features in these models indicated that TFs, displaying larger HM pattern differences between BSs and non-BSs, bound DNA in an HM-specific manner on a protein family-specific basis. We propose that TF family-specific HM preferences reveal distinct mechanisms that assist in guiding TFs to their cognate BSs by altering chromatin structure and accessibility.

Toward Predictable 5'UTRs in Saccharomyces cerevisiae: Development of a yUTR Calculator

Fine-tuning biosynthetic pathways is crucial for the development of economic feasible microbial cell factories. Therefore, the use of computational models able to predictably design regulatory sequences for pathway engineering proves to be a valuable tool, especially for modifying genes at the translational level. In this study we developed a computational approach for the de novo design of 5'-untranslated regions (5'UTRs) in Saccharomyces cerevisiae with a predictive outcome on translation initiation rate. On the basis of existing data, a partial least-squares (PLS) regression model was trained and showed good performance on predicting protein abundances of an independent test set. This model was further used for the construction of a "yUTR calculator" that can design 5'UTR sequences with a diverse range of desired translation efficiencies. The predictive power of our yUTR calculator was confirmed in vivo by different representative case studies. As such, these results show the great potential of data driven approaches for reliable pathway engineering in S. cerevisiae.

Microfluidic Module for Real-Time Generation of Complex Multimolecule Temporal Concentration Profiles

We designed a microfluidic module that generates complex and dynamic concentration profiles of multiple molecules over a large concentration range using pulse-width modulation (PWM). Our PWM module can combine up to six different inputs and select among three downstream mixing channels, as required by the application. The module can produce concentrations with a dynamic range of three decades. We created complex, temporal concentration profiles of two molecules, with each concentration independently controllable, and show that the PWM module can execute rapid concentration changes as well as long-time scale pharmacokinetic profiles. Concentration profiles were generated for molecules with molecular weights ranging from 560 Da to 150 kDa. Our PWM module produces robust and precise concentration profiles under a variety of operating conditions, making it ideal for integration with existing microfluidic devices for advanced cell and pharmacokinetic studies.

A Microfluidic Biodisplay

Synthetically engineered cells are powerful and potentially useful biosensors, but it remains problematic to deploy such systems due to practical difficulties and biosafety concerns. To overcome these hurdles, we developed a microfluidic device that serves as an interface between an engineered cellular system, environment, and user. We created a biodisplay consisting of 768 individually programmable biopixels and demonstrated that it can perform multiplexed, continuous sampling. The biodisplay detected 10 μg/L sodium-arsenite in tap water using a research grade fluorescent microscope, and reported arsenic contamination down to 20 μg/L with an easy to interpret "skull and crossbones" symbol detectable with a low-cost USB microscope or by eye. The biodisplay was designed to prevent release of chemical or biological material to avoid environmental contamination. The microfluidic biodisplay thus provides a practical solution for the deployment and application of engineered cellular systems.

Digital logic circuits in yeast with CRISPR-dCas9 NOR gates

Natural genetic circuits enable cells to make sophisticated digital decisions. Building equally complex synthetic circuits in eukaryotes remains difficult, however, because commonly used components leak transcriptionally, do not arbitrarily interconnect or do not have digital responses. Here, we designed dCas9-Mxi1-based NOR gates in Saccharomyces cerevisiae that allow arbitrary connectivity and large genetic circuits. Because we used the chromatin remodeller Mxi1, our gates showed minimal leak and digital responses. We built a combinatorial library of NOR gates that directly convert guide RNA (gRNA) inputs into gRNA outputs, enabling the gates to be 'wired' together. We constructed logic circuits with up to seven gRNAs, including repression cascades with up to seven layers. Modelling predicted the NOR gates have effectively zero transcriptional leak explaining the limited signal degradation in the circuits. Our approach enabled the largest, eukaryotic gene circuits to date and will form the basis for large, synthetic, cellular decision-making systems.

On the mechanistic nature of epistasis in a canonical cis-regulatory element

Understanding the relation between genotype and phenotype remains a major challenge. The difficulty of predicting individual mutation effects, and particularly the interactions between them, has prevented the development of a comprehensive theory that links genotypic changes to their phenotypic effects. We show that a general thermodynamic framework for gene regulation, based on a biophysical understanding of protein-DNA binding, accurately predicts the sign of epistasis in a canonical cis-regulatory element consisting of overlapping RNA polymerase and repressor binding sites. Sign and magnitude of individual mutation effects are sufficient to predict the sign of epistasis and its environmental dependence. Thus, the thermodynamic model offers the correct null prediction for epistasis between mutations across DNA-binding sites. Our results indicate that a predictive theory for the effects of cis-regulatory mutations is possible from first principles, as long as the essential molecular mechanisms and the constraints these impose on a biological system are accounted for.

DOI:http://dx.doi.org/10.7554/eLife.25192.001

Mutations are changes to DNA that provide the raw material upon which evolution can act. Therefore, to understand evolution, we need to know the effects of mutations, and how those mutations interact with each other (a phenomenon referred to as epistasis). So far, few mathematical models allow scientists to predict the effects of mutations, and even fewer are able to predict epistasis.

Biological systems are complex and consist of many proteins and other molecules. Genes are the sections of DNA that provide the instructions needed to produce these molecules, and some genes encode proteins that can bind to DNA to control whether other genes are switched on or off. Lagator, Paixão et al. have now used mathematical models and experiments to understand how the environment inside the cells of a bacterium known as E. coli, specifically the amount of particular proteins, affects epistasis.

These mathematical models are able to predict interactions between mutations in the most abundant class of DNA-binding sites in proteins. This approach found that the nature of the interaction between mutations can be explained through biophysical laws, combined with the basic knowledge of the logic of how genes regulate each other’s activities. Furthermore, the models allow Lagator, Paixão et al. to predict interactions between mutations in several different environments, such as the presence of a new food source or a toxin, defined by the amounts of relevant DNA-binding proteins in cells.

By providing new ways of understanding how genes are regulated in bacteria, and how gene regulation is affected by mutations, these findings contribute to our understanding of how organisms evolve. In addition, this work may help us to build artificial networks of genes that interact with each other to produce a desired response, such as more efficient production of fuel from ethanol or the break down of hazardous chemicals.

DOI:http://dx.doi.org/10.7554/eLife.25192.002

Large-scale mapping of gene regulatory logic reveals context-dependent repression by transcriptional activators

Transcription factors (TFs) are key mediators that propagate extracellular and intracellular signals through to changes in gene expression profiles. However, the rules by which promoters decode the amount of active TF into target gene expression are not well understood. To determine the mapping between promoter DNA sequence, TF concentration, and gene expression output, we have conducted in budding yeast a large-scale measurement of the activity of thousands of designed promoters at six different levels of TF. We observe that maximum promoter activity is determined by TF concentration and not by the number of binding sites. Surprisingly, the addition of an activator site often reduces expression. A thermodynamic model that incorporates competition between neighboring binding sites for a local pool of TF molecules explains this behavior and accurately predicts both absolute expression and the amount by which addition of a site increases or reduces expression. Taken together, our findings support a model in which neighboring binding sites interact competitively when TF is limiting but otherwise act additively.

Emergence of the Noncoding Cancer Genome: A Target of Genetic and Epigenetic Alterations

The emergence of whole-genome annotation approaches is paving the way for the comprehensive annotation of the human genome across diverse cell and tissue types exposed to various environmental conditions. This has already unmasked the positions of thousands of functional cis-regulatory elements integral to transcriptional regulation, such as enhancers, promoters, and anchors of chromatin interactions that populate the noncoding genome. Recent studies have shown that cis-regulatory elements are commonly the targets of genetic and epigenetic alterations associated with aberrant gene expression in cancer. Here, we review these findings to showcase the contribution of the noncoding genome and its alteration in the development and progression of cancer. We also highlight the opportunities to translate the biological characterization of genetic and epigenetic alterations in the noncoding cancer genome into novel approaches to treat or monitor disease.

SIGNIFICANCE

The majority of genetic and epigenetic alterations accumulate in the noncoding genome throughout oncogenesis. Discriminating driver from passenger events is a challenge that holds great promise to improve our understanding of the etiology of different cancer types. Advancing our understanding of the noncoding cancer genome may thus identify new therapeutic opportunities and accelerate our capacity to find improved biomarkers to monitor various stages of cancer development. Cancer Discov; 6(11); 1215-29. ©2016 AACR.

SELMAP - SELEX affinity landscape MAPping of transcription factor binding sites using integrated microfluidics

Transcription factors (TFs) alter gene expression in response to changes in the environment through sequence-specific interactions with the DNA. These interactions are best portrayed as a landscape of TF binding affinities. Current methods to study sequence-specific binding preferences suffer from limited dynamic range, sequence bias, lack of specificity and limited throughput. We have developed a microfluidic-based device for SELEX Affinity Landscape MAPping (SELMAP) of TF binding, which allows high-throughput measurement of 16 proteins in parallel. We used it to measure the relative affinities of Pho4, AtERF2 and Btd full-length proteins to millions of different DNA binding sites, and detected both high and low-affinity interactions in equilibrium conditions, generating a comprehensive landscape of the relative TF affinities to all possible DNA 6-mers, and even DNA10-mers with increased sequencing depth. Low quantities of both the TFs and DNA oligomers were sufficient for obtaining high-quality results, significantly reducing experimental costs. SELMAP allows in-depth screening of hundreds of TFs, and provides a means for better understanding of the regulatory processes that govern gene expression.

How motif environment influences transcription factor search dynamics: Finding a needle in a haystack

Transcription factors (TFs) have to find their binding sites, which are distributed throughout the genome. Facilitated diffusion is currently the most widely accepted model for this search process. Based on this model the TF alternates between one-dimensional sliding along the DNA, and three-dimensional bulk diffusion. In this view, the non-specific associations between the proteins and the DNA play a major role in the search dynamics. However, little is known about how the DNA properties around the motif contribute to the search. Accumulating evidence showing that TF binding sites are embedded within a unique environment, specific to each TF, leads to the hypothesis that the search process is facilitated by favorable DNA features that help to improve the search efficiency. Here, we review the field and present the hypothesis that TF-DNA recognition is dictated not only by the motif, but is also influenced by the environment in which the motif resides.

In Silico Constraint-Based Strain Optimization Methods: the Quest for Optimal Cell Factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

cis Determinants of Promoter Threshold and Activation Timescale

Although the relationship between DNA cis-regulatory sequences and gene expression has been extensively studied at steady state, how cis-regulatory sequences affect the dynamics of gene induction is not known. The dynamics of gene induction can be described by the promoter activation timescale (AcTime) and amplitude threshold (AmpThr). Combining high-throughput microfluidics with quantitative time-lapse microscopy, we control the activation dynamics of the budding yeast transcription factor, Msn2, and reveal how cis-regulatory motifs in 20 promoter variants of the Msn2-target-gene SIP18 affect AcTime and AmpThr. By modulating Msn2 binding sites, we can decouple AmpThr from AcTime and switch the SIP18 promoter class from high AmpThr and slow AcTime to low AmpThr and either fast or slow AcTime. We present a model that quantitatively explains gene-induction dynamics on the basis of the Msn2-binding-site number, TATA box location, and promoter nucleosome organization. Overall, we elucidate the cis-regulatory logic underlying promoter decoding of TF dynamics.

Integrative Comparison of the Role of the PHOSPHATE RESPONSE1 Subfamily in Phosphate Signaling and Homeostasis in Rice

Phosphorus (P), an essential macronutrient for all living cells, is indispensable for agricultural production. Although Arabidopsis (Arabidopsis thaliana) PHOSPHATE RESPONSE1 (PHR1) and its orthologs in other species have been shown to function in transcriptional regulation of phosphate (Pi) signaling and Pi homeostasis, an integrative comparison of PHR1-related proteins in rice (Oryza sativa) has not previously been reported. Here, we identified functional redundancy among three PHR1 orthologs in rice (OsPHR1, OsPHR2, and OsPHR3) using phylogenetic and mutation analysis. OsPHR3 in conjunction with OsPHR1 and OsPHR2 function in transcriptional activation of most Pi starvation-induced genes. Loss-of-function mutations in any one of these transcription factors (TFs) impaired root hair growth (primarily root hair elongation). However, these three TFs showed differences in DNA binding affinities and messenger RNA expression patterns in different tissues and growth stages, and transcriptomic analysis revealed differential effects on Pi starvation-induced gene expression of single mutants of the three TFs, indicating some degree of functional diversification. Overexpression of genes encoding any of these TFs resulted in partial constitutive activation of Pi starvation response and led to Pi accumulation in the shoot. Furthermore, unlike OsPHR2-overexpressing lines, which exhibited growth retardation under normal or Pi-deficient conditions, OsPHR3-overexpressing plants exhibited significant tolerance to low-Pi stress but normal growth rates under normal Pi conditions, suggesting that OsPHR3 would be useful for molecular breeding to improve Pi uptake/use efficiency under Pi-deficient conditions. We propose that OsPHR1, OsPHR2, and OsPHR3 form a network and play diverse roles in regulating Pi signaling and homeostasis in rice.

Optimizing information flow in small genetic networks. IV. Spatial coupling

We typically think of cells as responding to external signals independently by regulating their gene expression levels, yet they often locally exchange information and coordinate. Can such spatial coupling be of benefit for conveying signals subject to gene regulatory noise? Here we extend our information-theoretic framework for gene regulation to spatially extended systems. As an example, we consider a lattice of nuclei responding to a concentration field of a transcriptional regulator (the input) by expressing a single diffusible target gene. When input concentrations are low, diffusive coupling markedly improves information transmission; optimal gene activation functions also systematically change. A qualitatively different regulatory strategy emerges where individual cells respond to the input in a nearly steplike fashion that is subsequently averaged out by strong diffusion. While motivated by early patterning events in the Drosophila embryo, our framework is generically applicable to spatially coupled stochastic gene expression models.

Temporal hierarchy of gene expression mediated by transcription factor binding affinity and activation dynamics

Understanding cellular responses to environmental stimuli requires not only the knowledge of specific regulatory components but also the quantitative characterization of the magnitude and timing of regulatory events. The two-component system is one of the major prokaryotic signaling schemes and is the focus of extensive interest in quantitative modeling and investigation of signaling dynamics. Here we report how the binding affinity of the PhoB two-component response regulator (RR) to target promoters impacts the level and timing of expression of PhoB-regulated genes. Information content has often been used to assess the degree of conservation for transcription factor (TF)-binding sites. We show that increasing the information content of PhoB-binding sites in designed phoA promoters increased the binding affinity and that the binding affinity and concentration of phosphorylated PhoB (PhoB~P) together dictate the level and timing of expression of phoA promoter variants. For various PhoB-regulated promoters with distinct promoter architectures, expression levels appear not to be correlated with TF-binding affinities, in contrast to the intuitive and oversimplified assumption that promoters with higher affinity for a TF tend to have higher expression levels. However, the expression timing of the core set of PhoB-regulated genes correlates well with the binding affinity of PhoB~P to individual promoters and the temporal hierarchy of gene expression appears to be related to the function of gene products during the phosphate starvation response. Modulation of the information content and binding affinity of TF-binding sites may be a common strategy for temporal programming of the expression profile of RR-regulated genes.

IMPORTANCE

A single TF often orchestrates the expression of multiple genes in response to environmental stimuli. It is not clear how different TF-binding sites within the regulon dictate the expression profile. Our studies of Escherichia coli PhoB, a response regulator that controls expression of a core set of phosphate assimilation genes in response to phosphate starvation, showed that expression levels of PhoB-regulated genes are under sophisticated control and do not follow a simple correlation with the binding affinity of PhoB~P to individual promoters. However, the expression timing correlates with the PhoB-binding affinity and gene functions. Genes involved in direct Pi uptake contain high-affinity sites and are transcribed earlier than genes involved in phosphorus scavenging. This illustrates an elaborate mechanism of temporally programmed gene expression, even for nondevelopmental pathways.

Core promoter sequence in yeast is a major determinant of expression level

The core promoter is the regulatory sequence to which RNA polymerase is recruited and where it acts to initiate transcription. Here, we present the first comprehensive study of yeast core promoters, providing massively parallel measurements of core promoter activity and of TSS locations and relative usage for thousands of native and designed sequences. We found core promoter activity to be highly correlated to the activity of the entire promoter and that sequence variation in different core promoter regions substantially tunes its activity in a predictable way. We also show that location, orientation, and flanking bases critically affect TATA element function, that transcription initiation in highly active core promoters is focused within a narrow region, that poly(dA:dT) orientation has a functional consequence at the 3' end of promoters, and that orthologous core promoters across yeast species have conserved activities. Our results demonstrate the importance of core promoters in the quantitative study of gene regulation.

Unraveling determinants of transcription factor binding outside the core binding site

Binding of transcription factors (TFs) to regulatory sequences is a pivotal step in the control of gene expression. Despite many advances in the characterization of sequence motifs recognized by TFs, our ability to quantitatively predict TF binding to different regulatory sequences is still limited. Here, we present a novel experimental assay termed BunDLE-seq that provides quantitative measurements of TF binding to thousands of fully designed sequences of 200 bp in length within a single experiment. Applying this binding assay to two yeast TFs, we demonstrate that sequences outside the core TF binding site profoundly affect TF binding. We show that TF-specific models based on the sequence or DNA shape of the regions flanking the core binding site are highly predictive of the measured differential TF binding. We further characterize the dependence of TF binding, accounting for measurements of single and co-occurring binding events, on the number and location of binding sites and on the TF concentration. Finally, by coupling our in vitro TF binding measurements, and another application of our method probing nucleosome formation, to in vivo expression measurements carried out with the same template sequences serving as promoters, we offer insights into mechanisms that may determine the different expression outcomes observed. Our assay thus paves the way to a more comprehensive understanding of TF binding to regulatory sequences and allows the characterization of TF binding determinants within and outside of core binding sites.

Genetic manipulation of a high-affinity PHR1 target cis-element to improve phosphorous uptake in Oryza sativa L

Phosphorus (P) is an essential macronutrient for crop development and production. Phosphate starvation response 1 (PHR1) acts as the central regulator for Pi-signaling and Pi-homeostasis in plants by binding to the cis-element PHR1 binding sequence (P1BS; GNATATNC). However, how phosphate starvation-induced gene expression is regulated remains obscure. In this work, we investigated the DNA binding affinity of the PHR1 ortholog OsPHR2 to its downstream target genes in Oryza sativa (rice). We confirmed that a combination of P1BS and P1BS-like motifs are essential for stable binding by OsPHR2. Furthermore, we report that variations in P1BS motif bases affected the binding affinity of OsPHR2 and that the highest affinity motif was GaATATtC (designated the A-T-type P1BS). We also found that a combination of two A-T-type P1BS elements in tandem, namely HA-P1BS, was very efficient for binding of OsPHR2. Using the cis-regulator HA-P1BS, we modified the promoters of Transporter Traffic Facilitator 1 (PHF1), a key factor controlling endoplasmic reticulum-exit of phosphate transporters to the plasma membrane, for efficient uptake of phosphorous in an energetically neutral way. Transgenic plants with the modified promoters showed significantly enhanced tolerance to low phosphate stress in both solution and soil conditions, which provides a new strategy for crop improvement to enhance tolerance of nutrient deficiency.

Recent applications of synthetic biology tools for yeast metabolic engineering

The last 20 years of metabolic engineering has enabled bio-based production of fuels and chemicals from renewable carbon sources using cost-effective bioprocesses. Much of this work has been accomplished using engineered microorganisms that act as chemical factories. Although the time required to engineer microbial chemical factories has steadily decreased, improvement is still needed. Through the development of synthetic biology tools for key microbial hosts, it should be possible to further decrease the development times and improve the reliability of the resulting microorganism. Together with continuous decreases in price and improvements in DNA synthesis, assembly and sequencing, synthetic biology tools will rationalize time-consuming strain engineering, improve control of metabolic fluxes, and diversify screening assays for cellular metabolism. This review outlines some recently developed synthetic biology tools and their application to improve production of chemicals and fuels in yeast. Finally, we provide a perspective for the challenges that lie ahead.

Bacterial nucleoid-associated protein uncouples transcription levels from transcription timing

The histone-like nucleoid-structuring (H-NS) protein binds to horizontally acquired genes in the bacterium Salmonella enterica serovar Typhimurium, silencing their expression. We now report that overcoming the silencing effects of H-NS imposes a delay in the expression of genes activated by the transcriptional regulator PhoP. We determine that PhoP-activated genes ancestral to Salmonella are expressed before those acquired horizontally. This expression timing reflects the in vivo occupancy of the corresponding promoters by the PhoP protein. These results are surprising because some of these horizontally acquired genes reached higher mRNA levels than ancestral genes expressed earlier and were transcribed from promoters harboring PhoP-binding sites with higher in vitro affinity for the PhoP protein. Our findings challenge the often-made assumption that for genes coregulated by a given transcription factor, early genes are transcribed to higher mRNA levels than those transcribed at later times. Moreover, they provide a singular example of how gene ancestry can impact expression timing.

We report that gene ancestry dictates the expression behavior of genes under the direct control of the Salmonella transcriptional regulator PhoP. That is, ancestral genes are transcribed before horizontally acquired genes. This reflects both the need to overcome silencing by the H-NS protein of the latter genes and the architecture of the corresponding promoters. Unexpectedly, transcription levels do not reflect transcription timing. Our results illustrate how a bacterium can exhibit an elaborate temporal expression behavior among genes coregulated by a transcription factor even though the products encoded by the target genes do not participate in a morphological or developmental pathway.

Two distinct promoter architectures centered on dynamic nucleosomes control ribosomal protein gene transcription

In yeast, ribosome production is controlled transcriptionally by tight coregulation of the 138 ribosomal protein genes (RPGs). RPG promoters display limited sequence homology, and the molecular basis for their coregulation remains largely unknown. Here we identify two prevalent RPG promoter types, both characterized by upstream binding of the general transcription factor (TF) Rap1 followed by the RPG-specific Fhl1/Ifh1 pair, with one type also binding the HMG-B protein Hmo1. We show that the regulatory properties of the two promoter types are remarkably similar, suggesting that they are determined to a large extent by Rap1 and the Fhl1/Ifh1 pair. Rapid depletion experiments allowed us to define a hierarchy of TF binding in which Rap1 acts as a pioneer factor required for binding of all other TFs. We also uncovered unexpected features underlying recruitment of Fhl1, whose forkhead DNA-binding domain is not required for binding at most promoters, and Hmo1, whose binding is supported by repeated motifs. Finally, we describe unusually micrococcal nuclease (MNase)-sensitive nucleosomes at all RPG promoters, located between the canonical +1 and -1 nucleosomes, which coincide with sites of Fhl1/Ifh1 and Hmo1 binding. We speculate that these "fragile" nucleosomes play an important role in regulating RPG transcriptional output.

The yeast PHO5 promoter: from single locus to systems biology of a paradigm for gene regulation through chromatin

Chromatin dynamics crucially contributes to gene regulation. Studies of the yeast PHO5 promoter were key to establish this nowadays accepted view and continuously provide mechanistic insight in chromatin remodeling and promoter regulation, both on single locus as well as on systems level. The PHO5 promoter is a context independent chromatin switch module where in the repressed state positioned nucleosomes occlude transcription factor sites such that nucleosome remodeling is a prerequisite for and not consequence of induced gene transcription. This massive chromatin transition from positioned nucleosomes to an extensive hypersensitive site, together with respective transitions at the co-regulated PHO8 and PHO84 promoters, became a prime model for dissecting how remodelers, histone modifiers and chaperones co-operate in nucleosome remodeling upon gene induction. This revealed a surprisingly complex cofactor network at the PHO5 promoter, including five remodeler ATPases (SWI/SNF, RSC, INO80, Isw1, Chd1), and demonstrated for the first time histone eviction in trans as remodeling mode in vivo. Recently, the PHO5 promoter and the whole PHO regulon were harnessed for quantitative analyses and computational modeling of remodeling, transcription factor binding and promoter input-output relations such that this rewarding single-locus model becomes a paradigm also for theoretical and systems approaches to gene regulatory networks.

In pursuit of design principles of regulatory sequences

Instructions for when, where and to what level each gene should be expressed are encoded within regulatory sequences. The importance of motifs recognized by DNA-binding regulators has long been known, but their extensive characterization afforded by recent technologies only partly accounts for how regulatory instructions are encoded in the genome. Here, we review recent advances in our understanding of regulatory sequences that influence transcription and go beyond the description of motifs. We discuss how understanding different aspects of the sequence-encoded regulation can help to unravel the genotype-phenotype relationship, which would lead to a more accurate and mechanistic interpretation of personal genome sequences.

A DNA-binding-site landscape and regulatory network analysis for NAC transcription factors in Arabidopsis thaliana

Target gene identification for transcription factors is a prerequisite for the systems wide understanding of organismal behaviour. NAM-ATAF1/2-CUC2 (NAC) transcription factors are amongst the largest transcription factor families in plants, yet limited data exist from unbiased approaches to resolve the DNA-binding preferences of individual members. Here, we present a TF-target gene identification workflow based on the integration of novel protein binding microarray data with gene expression and multi-species promoter sequence conservation to identify the DNA-binding specificities and the gene regulatory networks of 12 NAC transcription factors. Our data offer specific single-base resolution fingerprints for most TFs studied and indicate that NAC DNA-binding specificities might be predicted from their DNA-binding domain's sequence. The developed methodology, including the application of complementary functional genomics filters, makes it possible to translate, for each TF, protein binding microarray data into a set of high-quality target genes. With this approach, we confirm NAC target genes reported from independent in vivo analyses. We emphasize that candidate target gene sets together with the workflow associated with functional modules offer a strong resource to unravel the regulatory potential of NAC genes and that this workflow could be used to study other families of transcription factors.

Latent phenotypes pervade gene regulatory circuits

BACKGROUND

Latent phenotypes are non-adaptive byproducts of adaptive phenotypes. They exist in biological systems as different as promiscuous enzymes and genome-scale metabolic reaction networks, and can give rise to evolutionary adaptations and innovations. We know little about their prevalence in the gene expression phenotypes of regulatory circuits, important sources of evolutionary innovations.

RESULTS

Here, we study a space of more than sixteen million three-gene model regulatory circuits, where each circuit is represented by a genotype, and has one or more functions embodied in one or more gene expression phenotypes. We find that the majority of circuits with single functions have latent expression phenotypes. Moreover, the set of circuits with a given spectrum of functions has a repertoire of latent phenotypes that is much larger than that of any one circuit. Most of this latent repertoire can be easily accessed through a series of small genetic changes that preserve a circuit's main functions. Both circuits and gene expression phenotypes that are robust to genetic change are associated with a greater number of latent phenotypes.

CONCLUSIONS

Our observations suggest that latent phenotypes are pervasive in regulatory circuits, and may thus be an important source of evolutionary adaptations and innovations involving gene regulation.

Long-term single cell analysis of S. pombe on a microfluidic microchemostat array

Although Schyzosaccharomyces pombe is one of the principal model organisms for studying the cell cycle, surprisingly few methods have characterized S. pombe growth on the single cell level, and no methods exist capable of analyzing thousands of cells and tens of thousands of cell division events. We developed an automated microfluidic platform permitting S. pombe to be grown on-chip for several days under defined and changeable conditions. We developed an image processing pipeline to extract and quantitate several physiological parameters including cell length, time to division, and elongation rate without requiring synchronization of the culture. Over a period of 50 hours our platform analyzed over 100000 cell division events and reconstructed single cell lineages up to 10 generations in length. We characterized cell lengths and division times in a temperature shift experiment in which cells were initially grown at 30°C and transitioned to 25°C. Although cell length was identical at both temperatures at steady-state, we observed transient changes in cell length if the temperature shift took place during a critical phase of the cell cycle. We further show that cells born with normal length do divide over a wide range of cell lengths and that cell length appears to be controlled in the second generation, were large newly born cells have a tendency to divide more rapidly and thus at a normalized cell size. The platform is thus applicable to measure fine-details in cell cycle dynamics, should be a useful tool to decipher the molecular mechanism underlying size homeostasis, and will be generally applicable to study processes on the single cell level that require large numbers of precision measurements and single cell lineages.

The robustness and evolvability of transcription factor binding sites

Robustness, the maintenance of a character in the presence of genetic change, can help preserve adaptive traits but also may hinder evolvability, the ability to bring forth novel adaptations. We used genotype networks to analyze the binding site repertoires of 193 transcription factors from mice and yeast, providing empirical evidence that robustness and evolvability need not be conflicting properties. Network vertices represent binding sites where two sites are connected if they differ in a single nucleotide. We show that the binding sites of larger genotype networks are not only more robust, but the sequences adjacent to such networks can also bind more transcription factors, thus demonstrating that robustness can facilitate evolvability.