Physical Constraints and Functional Characteristics of Transcription Factor-DNA Interaction

We study theoretical ``design principles'' for transcription factor-DNA interaction in bacteria, focusing particularly on the statistical interaction of the transcription factors (TF's) with the genomic background (i.e., the genome without the target sites). We introduce and motivate the concept of `programmability', i.e. the ability to set the threshold concentration for TF binding over a wide range merely by mutating the binding sequence of a target site. This functional demand, together with physical constraints arising from the thermodynamics and kinetics of TF-DNA interaction, leads us to a narrow range of ``optimal'' interaction parameters. We find that this parameter set agrees well with experimental data for the interaction parameters of a few exemplary prokaryotic TF's. This indicates that TF-DNA interaction is indeed programmable. We suggest further experiments to test whether this is a general feature for a large class of TF's.Comment: 9 pages, 4 figures; revised version as published in PNA

Opening-closing dynamics of the mitochondrial transcription pre-initiation complex

Promoter recognition and local melting of DNA are key steps of transcription initiation catalyzed by RNA polymerase and initiation factors. From single molecule fluorescence resonance energy transfer studies of the yeast (Saccharomyces cerevisiae) mitochondrial RNA polymerase Rpo41 and its transcription factor Mtf1, we show that the pre-initiation complex is highly dynamic and undergoes repetitive opening-closing transitions that are modulated by Mtf1 and ATP. We found that Rpo41 alone has the intrinsic ability to bend the promoter but only very briefly. Mtf1 enhances bending/opening transition and suppresses closing transition, indicating its dual roles of nucleating promoter opening and stabilizing the open state. The cognate initiating ATP prolongs the lifetime of the open state, plausibly explaining the 'ATP sensing mechanism' suggested for the system. We discovered short-lived opening trials upon initial binding of Rpo41-Mtf1 before the establishment of the opening/closing equilibrium, which may aid in promoter selection before the formation of stable pre-initiation complex. The dynamics of open complex formation provides unique insights into the interplay between RNA polymerase and transcription factors in regulating initiation.open4

Module-Based Analysis of Robustness Tradeoffs in the Heat Shock Response System

Biological systems have evolved complex regulatory mechanisms, even in situations where much simpler designs seem to be sufficient for generating nominal functionality. Using module-based analysis coupled with rigorous mathematical comparisons, we propose that in analogy to control engineering architectures, the complexity of cellular systems and the presence of hierarchical modular structures can be attributed to the necessity of achieving robustness. We employ the Escherichia coli heat shock response system, a strongly conserved cellular mechanism, as an example to explore the design principles of such modular architectures. In the heat shock response system, the sigma-factor σ(32) is a central regulator that integrates multiple feedforward and feedback modules. Each of these modules provides a different type of robustness with its inherent tradeoffs in terms of transient response and efficiency. We demonstrate how the overall architecture of the system balances such tradeoffs. An extensive mathematical exploration nevertheless points to the existence of an array of alternative strategies for the existing heat shock response that could exhibit similar behavior. We therefore deduce that the evolutionary constraints facing the system might have steered its architecture toward one of many robustly functional solutions

Genetic noise control via protein oligomerization

Gene expression in a cell entails random reaction events occurring over disparate time scales. Thus, molecular noise that often results in phenotypic and population-dynamic consequences sets a fundamental limit to biochemical signaling. While there have been numerous studies correlating the architecture of cellular reaction networks with noise tolerance, only a limited effort has been made to understand the dynamic role of protein-protein interactions. Here we have developed a fully stochastic model for the positive feedback control of a single gene, as well as a pair of genes (toggle switch), integrating quantitative results from previous in vivo and in vitro studies. We find that the overall noise-level is reduced and the frequency content of the noise is dramatically shifted to the physiologically irrelevant high-frequency regime in the presence of protein dimerization. This is independent of the choice of monomer or dimer as transcription factor and persists throughout the multiple model topologies considered. For the toggle switch, we additionally find that the presence of a protein dimer, either homodimer or heterodimer, may significantly reduce its random switching rate. Hence, the dimer promotes the robust function of bistable switches by preventing the uninduced (induced) state from randomly being induced (uninduced). The specific binding between regulatory proteins provides a buffer that may prevent the propagation of fluctuations in genetic activity. The capacity of the buffer is a non-monotonic function of association-dissociation rates. Since the protein oligomerization per se does not require extra protein components to be expressed, it provides a basis for the rapid control of intrinsic or extrinsic noise

Design, construction and characterization of a set of insulated bacterial promoters

We have generated a series of variable-strength, constitutive, bacterial promoters that act predictably in different sequence contexts, span two orders of magnitude in strength and contain convenient sites for cloning and the introduction of downstream open-reading frames. Importantly, their design insulates these promoters from the stimulatory or repressive effects of many 5′- or 3′-sequence elements. We show that different promoters from our library produce constant relative levels of two different proteins in multiple genetic contexts. This set of promoters should be a useful resource for the synthetic-biology community

Anatomy of Escherichia coli σ(70) promoters

Information theory was used to build a promoter model that accounts for the −10, the −35 and the uncertainty of the gap between them on a common scale. Helical face assignment indicated that base −7, rather than −11, of the −10 may be flipping to initiate transcription. We found that the sequence conservation of σ(70) binding sites is 6.5 ± 0.1 bits. Some promoters lack a −35 region, but have a 6.7 ± 0.2 bit extended −10, almost the same information as the bipartite promoter. These results and similarities between the contacts in the extended −10 binding and the −35 suggest that the flexible bipartite σ factor evolved from a simpler polymerase. Binding predicted by the bipartite model is enriched around 35 bases upstream of the translational start. This distance is the smallest 5′ mRNA leader necessary for ribosome binding, suggesting that selective pressure minimizes transcript length. The promoter model was combined with models of the transcription factors Fur and Lrp to locate new promoters, to quantify promoter strengths, and to predict activation and repression. Finally, the DNA-bending proteins Fis, H-NS and IHF frequently have sites within one DNA persistence length from the −35, so bending allows distal activators to reach the polymerase

DNA melting by RNA polymerase at the T7A1 promoter precedes the rate-limiting step at 37°C and results in the accumulation of an off-pathway intermediate

The formation of a transcriptionally active complex by RNA polymerase involves a series of short-lived structural intermediates where protein conformational changes are coupled to DNA wrapping and melting. We have used time-resolved KMnO4 and hydroxyl-radical X-ray footprinting to directly probe conformational signatures of these complexes at the T7A1 promoter. Here we demonstrate that DNA melting from m12 to m4 precedes the rate-limiting step in the pathway and takes place prior to the formation of full downstream contacts. In addition, on the wild-type promoter, we can detect the accumulation of a stable off-pathway intermediate that results from the absence of sequence-specific contacts with the melted non-consensus –10 region. Finally, the comparison of the results obtained at 37°C with those at 20°C reveals significant differences in the structure of the intermediates resulting in a different pathway for the formation of a transcriptionally active complex

Dissecting the expression patterns of transcription factors across conditions using an integrated network-based approach

In prokaryotes, regulation of gene expression is predominantly controlled at the level of transcription. Transcription in turn is mediated by a set of DNA-binding factors called transcription factors (TFs). In this study, we map the complete repertoire of ∼300 TFs of the bacterial model, Escherichia coli, onto gene expression data for a number of nonredundant experimental conditions and show that TFs are generally expressed at a lower level than other gene classes. We also demonstrate that different conditions harbor varying number of active TFs, with an average of about 15% of the total repertoire, with certain stress and drug-induced conditions exhibiting as high as one-third of the collection of TFs. Our results also show that activators are more frequently expressed than repressors, indicating that activation of promoters might be a more common phenomenon than repression in bacteria. Finally, to understand the association of TFs with different conditions and to elucidate their dynamic interplay with other TFs, we develop a network-based framework to identify TFs which act as markers, defined as those which are responsible for condition-specific transcriptional rewiring. This approach allowed us to pinpoint several marker TFs as being central in various specialized conditions such as drug induction or growth condition variations, which we discuss in light of previously reported experimental findings. Further analysis showed that a majority of identified markers effectively control the expression of their regulons and, in general, transcriptional programs of most conditions can be effectively rewired by a very small number of TFs. It was also found that closeness is a key centrality measure which can aid in the successful identification of marker TFs in regulatory networks. Our results suggest the utility of the network-based approaches developed in this study to be applicable for understanding other interactomic data sets