Single-molecule detection of transcription factor binding to DNA in real time: specificity, equilibrium, and kinetic parameters

Assembly mechanism of the inflammasome sensor AIM2 revealed by single molecule analysis

Pathogenic dsDNA prompts AIM2 assembly leading to the formation of the inflammasome, a multimeric complex that triggers the inflammatory response. The recognition of foreign dsDNA involves AIM2 self-assembly concomitant with dsDNA binding. However, we lack mechanistic and kinetic information on the formation and propagation of the assembly, which can shed light on innate immunity's time response and specificity. Combining optical traps and confocal fluorescence microscopy, we determine here the association and dissociation rates of the AIM2-DNA complex at the single molecule level. We identify distinct mechanisms for oligomer growth via the binding of incoming AIM2 molecules to adjacent dsDNA or direct interaction with bound AIM2 assemblies, resembling primary and secondary nucleation. Through these mechanisms, the size of AIM2 oligomers can increase fourfold in seconds. Finally, our data indicate that single AIM2 molecules do not diffuse/scan along the DNA, suggesting that oligomerization depends on stochastic encounters with DNA and/or DNA-bound AIM2.

Thermodynamic Additivity for Impacts of Base-Pair Substitutions on Association of the Egr-1 Zinc-Finger Protein with DNA

The transcription factor Egr-1 specifically binds as a monomer to its 9 bp target DNA sequence, GCGTGGGCG, via three zinc fingers and plays important roles in the brain and cardiovascular systems. Using fluorescence-based competitive binding assays, we systematically analyzed the impacts of all possible single-nucleotide substitutions in the target DNA sequence and determined the change in binding free energy for each. Then, we measured the changes in binding free energy for sequences with multiple substitutions and compared them with the sum of the changes in binding free energy for each constituent single substitution. For the DNA variants with two or three nucleotide substitutions in the target sequence, we found excellent agreement between the measured and predicted changes in binding free energy. Interestingly, however, we found that this thermodynamic additivity broke down with a larger number of substitutions. For DNA sequences with four or more substitutions, the measured changes in binding free energy were significantly larger than predicted. On the basis of these results, we analyzed the occurrences of high-affinity sequences in the genome and found that the genome contains millions of such sequences that might functionally sequester Egr-1.

A mammalian circadian clock model incorporating daytime expression elements

Models of the mammalian clock have traditionally been based around two feedback loops-the self-repression of Per/Cry by interfering with activation by BMAL/CLOCK, and the repression of Bmal/Clock by the REV-ERB proteins. Recent experimental evidence suggests that the D-box, a transcription factor binding site associated with daytime expression, plays a larger role in clock function than has previously been understood. We present a simplified clock model that highlights the role of the D-box and illustrate an approach for finding maximum-entropy ensembles of model parameters, given experimentally imposed constraints. Parameter variability can be mitigated using prior probability distributions derived from genome-wide studies of cellular kinetics. Our model reproduces predictions concerning the dual regulation of Cry1 by the D-box and Rev-ErbA/ROR response element (RRE) promoter elements and allows for ensemble-based predictions of phase response curves (PRCs). Nonphotic signals such as Neuropeptide Y (NPY) may act by promoting Cry1 expression, whereas photic signals likely act by stimulating expression from the E/E' box. Ensemble generation with parameter probability restraints reveals more about a model's behavior than a single optimal parameter set.

Massively parallel measurements of molecular interaction kinetics on a microfluidic platform

Quantitative biology requires quantitative data. No high-throughput technologies exist capable of obtaining several hundred independent kinetic binding measurements in a single experiment. We present an integrated microfluidic device (k-MITOMI) for the simultaneous kinetic characterization of 768 biomolecular interactions. We applied k-MITOMI to the kinetic analysis of transcription factor (TF)-DNA interactions, measuring the detailed kinetic landscapes of the mouse TF Zif268, and the yeast TFs Tye7p, Yox1p, and Tbf1p. We demonstrated the integrated nature of k-MITOMI by expressing, purifying, and characterizing 27 additional yeast transcription factors in parallel on a single device. Overall, we obtained 2,388 association and dissociation curves of 223 unique molecular interactions with equilibrium dissociation constants ranging from 2 × 10(-6) M to 2 × 10(-9) M, and dissociation rate constants of approximately 6 s(-1) to 8.5 × 10(-3) s(-1). Association rate constants were uniform across 3 TF families, ranging from 3.7 × 10(6) M(-1) s(-1) to 9.6 × 10(7) M(-1) s(-1), and are well below the diffusion limit. We expect that k-MITOMI will contribute to our quantitative understanding of biological systems and accelerate the development and characterization of engineered systems.

Transient noise amplification and gene expression synchronization in a bistable mammalian cell-fate switch

Progenitor cells within a clonal population show variable proclivity toward lineage commitment and differentiation. This cell-to-cell variability has been attributed to transcriptome-wide gene expression noise generated by fluctuations in the amount of cellular machinery and stochasticity in the biochemical reactions involved in protein synthesis. It therefore remains unclear how a signaling network, in the presence of such noise, can execute unequivocal cell-fate decisions from external cues. Here, we use mathematical modeling and model-guided experiments to reveal functional interplay between instructive signaling and noise in erythropoiesis. We present evidence that positive transcriptional feedback loops in a lineage-specific receptor signaling pathway can generate ligand-induced memory to engender robust, switch-like responses. These same feedback loops can also transiently amplify gene expression noise in the signaling network, suggesting that external cues can actually bias seemingly stochastic decisions during cell-fate specification. Gene expression levels among key effectors in the signaling pathway are uncorrelated in the initial population of progenitor cells but become synchronized after addition of ligand, which activates the transcriptional feedback loops. Finally, we show that this transient noise amplification and gene expression synchronization induced by ligand can directly influence cell survival and differentiation kinetics within the population.

The CodY pleiotropic repressor controls virulence in gram-positive pathogens

CodY is involved in the adaptive response to starvation in at least 30 different low G+C gram-positive bacteria. After dimerization and activation by cofactor binding, CodY binds to a consensus palindromic DNA sequence, leading to the repression of approximately 5% of the genome. CodY represses the transcription of target genes when bound to DNA by competition with the RNA polymerase for promoter binding, or by interference with transcriptional elongation as a roadblock. CodY displays enhanced affinity for its DNA target when bound to GTP and/or branched chain amino acids (BCAA). When nutrients become limiting in the postexponential growth phase, a decrease of intracellular levels of GTP and BCAA causes a deactivation of CodY and decreases its affinity for DNA, leading to the induction of its regulon. CodY-regulated genes trigger adaptation of the bacteria to starvation by highly diverse mechanisms, such as secretion of proteases coupled to expression of amino acid transporters, and promotion of survival strategies like sporulation or biofilm formation. Additionally, in pathogenic bacteria, several virulence factors are regulated by CodY. As a function of their access to nutrients, pathogenic gram-positive bacteria express virulence factors in a codY-dependant manner. This is true for the anthrax toxins of Bacillus anthracis and the haemolysins of Staphylococcus aureus. The purpose of this review is to illustrate CodY-regulated mechanisms on virulence in major gram-positive pathogens.

A systematically coarse-grained model for DNA and its predictions for persistence length, stacking, twist, and chirality

We introduce a coarse-grained model of DNA with bases modeled as rigid-body ellipsoids to capture their anisotropic stereochemistry. Interaction potentials are all physicochemical and generated from all-atom simulation/parameterization with minimal phenomenology. Persistence length, degree of stacking, and twist are studied by molecular dynamics simulation as functions of temperature, salt concentration, sequence, interaction potential strength, and local position along the chain for both single- and double-stranded DNA where appropriate. The model of DNA shows several phase transitions and crossover regimes in addition to dehybridization, including unstacking, untwisting, and collapse, which affect mechanical properties such as rigidity and persistence length. The model also exhibits chirality with a stable right-handed and metastable left-handed helix.

Quantitative transcription factor binding kinetics at the single-molecule level

We investigated the binding interaction between the bacteriophage lambda-repressor CI and its target DNA using total internal reflection fluorescence microscopy. Large stepwise changes in the intensity of the red fluorescent protein fused to CI were observed as it associated with and dissociated from individually labeled single-molecule DNA targets. The stochastic association and dissociation were characterized by Poisson statistics. Dark and bright intervals were measured for thousands of individual events. The exponential distribution of the intervals allowed direct determination of the association and dissociation rate constants (k(a) and k(d), respectively). We resolved in detail how k(a) and k(d) varied as a function of three control parameters: the DNA length L, the CI dimer concentration, and the binding affinity. Our results show that although interactions with nonoperator DNA sequences are observable, CI binding to the operator site is not dependent on the length of flanking nonoperator DNA.

Positive receptor feedback during lineage commitment can generate ultrasensitivity to ligand and confer robustness to a bistable switch

Cytokines and lineage-specific transcription factors are critical molecular effectors for terminal differentiation during hematopoiesis. Intrinsic transcription factor activity is often believed to drive commitment and differentiation, whereas cytokine receptor signals have been implicated in the regulation of cell proliferation, survival, and differentiation. In erythropoiesis, recent experimental findings provide direct evidence that erythropoietin (Epo) can generate commitment cues via the erythropoietin receptor (EpoR); specifically, EpoR signaling leads to activation of the transcription factor GATA-1, which then triggers transcription of erythrocyte-specific genes. In particular, activated GATA-1 induces two positive feedback loops in the system through the enhanced expression of both inactive GATA-1 and EpoR, the latter of which is externally regulatable by Epo. Based upon this network architecture, we present a mathematical model of GATA-1 activation by EpoR, which bidirectionally links a lineage-specific receptor and transcription factor. Our deterministic model offers insight into stimulus-response relationships between Epo and several downstream effectors. In addition to the survival signals that EpoR provides, steady-state analysis of our model suggests that receptor upregulation during lineage commitment can also generate ultrasensitivity to Epo and bistability in GATA-1 activity. These system-level properties can induce a switch-like characteristic during differentiation and provide robustness to the mature state. The topology also suggests a novel mechanism for achieving robust bistability in a purely deterministic manner without molecular cooperativity. The analytical solution of a generalized, minimal model is provided and the significance of each of the two positive feedback loops is elucidated through bifurcation analysis. This network topology, or variations thereof, may link other receptor-transcription factor pairs and may therefore be of general relevance in cellular decision-making.

After a dozen years of progress the origin of angiosperms is still a great mystery

Here we discuss recent advances surrounding the origin of angiosperms. Putatively primitive characters are now much better understood because of a vastly improved understanding of angiosperm phylogenetics, and recent discoveries of fossil flowers have provided an increasingly detailed picture of early diversity in the angiosperms. The 'anthophyte theory', the dominant concept of the 1980s and 1990s, has been eclipsed; Gnetales, previously thought to be closest to the angiosperms, are related instead to other extant gymnosperms, probably most closely to conifers. Finally, new theories of flower origins have been proposed based on gene function, duplication and loss, as well as on morphology. Further studies of genetic mechanisms that control reproductive development in seed plants provide a most promising avenue for further research, including tests of these recent theories. Identification of fossils with morphologies that convincingly place them close to angiosperms could still revolutionize understanding of angiosperm origins.

Split β-Lactamase Sensor for the Sequence-Specific Detection of DNA Methylation

The methylation pattern of genes at CpG dinucleotide sites is an emerging area in epigenetics. Furthermore, the hypermethylation profiles of tumor suppressor genes are linked to specific tumor types. Thus, new molecular approaches for the rapid determination of the methylation status of these genes could provide a powerful method for early cancer diagnosis as well as insight into mechanisms of epigenetic regulation of genetic information. Toward this end, we have recently reported the first design of a split-protein sensor for the site-specific detection of DNA methylation. In this approach a split green fluorescent protein reporter provided a sequence-specific readout of CpG methylation. In the present work, we describe a sensitive second-generation methylation detection system that utilizes the split enzymatic reporter, TEM-1 beta-lactamase, attached to specific DNA binding elements. This system, termed mCpG-SEER-beta-Lac, shows a greater than 40-fold specificity for methylated versus nonmethylated CpG target sites. Importantly, the resulting signal enhancement afforded by the catalytic activity of split-beta-lactamase allowed for the sensitive detection of 2.5 fmol of methylated target dsDNA in 5 min. Thus, this new sensor geometry represents a 250-fold enhancement in assay time and a 2000-fold enhancement in sensitivity over our first-generation system for the detection of specific sites of DNA methylation.