Superhelical Duplex Destabilization and the Recombination Position Effect

The susceptibility to recombination of a plasmid inserted into a chromosome varies with its genomic position. This recombination position effect is known to correlate with the average G+C content of the flanking sequences. Here we propose that this effect could be mediated by changes in the susceptibility to superhelical duplex destabilization that would occur. We use standard nonparametric statistical tests, regression analysis and principal component analysis to identify statistically significant differences in the destabilization profiles calculated for the plasmid in different contexts, and correlate the results with their measured recombination rates. We show that the flanking sequences significantly affect the free energy of denaturation at specific sites interior to the plasmid. These changes correlate well with experimentally measured variations of the recombination rates within the plasmid. This correlation of recombination rate with superhelical destabilization properties of the inserted plasmid DNA is stronger than that with average G+C content of the flanking sequences. This model suggests a possible mechanism by which flanking sequence base composition, which is not itself a context-dependent attribute, can affect recombination rates at positions within the plasmid

Investigating the Role of TNF-α and IFN-γ Activation on the Dynamics of iNOS Gene Expression in LPS Stimulated Macrophages.

Macrophage produced inducible nitric oxide synthase (iNOS) is known to play a critical role in the proinflammatory response against intracellular pathogens by promoting the generation of bactericidal reactive nitrogen species. Robust and timely production of nitric oxide (NO) by iNOS and analogous production of reactive oxygen species are critical components of an effective immune response. In addition to pathogen associated lipopolysaccharides (LPS), iNOS gene expression is dependent on numerous proinflammatory cytokines in the cellular microenvironment of the macrophage, two of which include interferon gamma (IFN-γ) and tumor necrosis factor alpha (TNF-α). To understand the synergistic effect of IFN-γ and TNF-α activation, and LPS stimulation on iNOS expression dynamics and NO production, we developed a systems biology based mathematical model. Using our model, we investigated the impact of pre-infection cytokine exposure, or priming, on the system. We explored the essentiality of IFN-γ priming to the robustness of initial proinflammatory response with respect to the ability of macrophages to produce reactive species needed for pathogen clearance. Results from our theoretical studies indicated that IFN-γ and subsequent activation of IRF1 are essential in consequential production of iNOS upon LPS stimulation. We showed that IFN-γ priming at low concentrations greatly increases the effector response of macrophages against intracellular pathogens. Ultimately the model demonstrated that although TNF-α contributed towards a more rapid response time, measured as time to reach maximum iNOS production, IFN-γ stimulation was significantly more significant in terms of the maximum expression of iNOS and the concentration of NO produced

iNOS Gene Expression Mechanism.

<p>The Enzyme term in this figure refers to the DNA-RNA Polymerase complex. Dissociation constants are labeled accordingly and their values can be found in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0153289#pone.0153289.s006" target="_blank">S1 Table</a>.</p

Maximum iNOS Expression.

<p>Maximum iNOS mRNAn values were obtained through model simulation under various conditions. Expression levels are relative to LPS control stimulation. The greatest increase in maximum iNOS production can been seen between TNF-α stimulation and IFN-γ stimulation. However, in the presence of LPS, there is only a slight increase in iNOS gene expression when compared to cytokine activation levels.</p

iNOS Gene Expression as a Function of TNF-α or IFN-γ.

<p>A range of concentrations of TNF-α and IFN-γ were used to stimulate the system and the maximum iNOS gene expression rates were plots as a function of cytokine concentration. The time to reach maximal expression under varying concentrations of cytokines was used to derive the velocity of expression under each respective condition. (A) The Michaelis-Menten type plot shows the rate of iNOS gene expression as a function of TNF-α. Since TNF-α induces peak iNOS expression faster than IFN-γ, the rate of expression is greater for TNF-α than for IFN-γ. (B) The Michaelis-Menten type plot shows the rate of iNOS gene expression as a function of IFN-γ. The Km value is marked at half-maximal velocity. (C) The expanded graph of TNF-α dependent iNOS gene expression rate shows a sigmoidal curve suggesting a cytokine threshold for gene activation. (D) The expanded graph of IFN-γ dependent iNOS gene expression rate also shows a sigmoidal curve in addition to a smaller range upon which Vmax is reached. Vmax values are in arbitrary units, which correlate to the change of relative expression per time.</p

IFN-γ Stimulated iNOS mRNA and Transcription Factor Expression Dynamics.

<p>The system was stimulated with IFN-γ, IFN-γ /TNF-α, IFN-γ and LPS, and IFN-γ /TNF-α and LPS as inputs. (A-D) show the transcription factors of iNOS under the four stimulatory conditions. STAT1 phosphorylated dimers are expressed during IFN-γ stimulation (D) and the dynamics are similar to previous models [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0153289#pone.0153289.ref016" target="_blank">16</a>]. (E) Shows the expression of TNF-α mRNA under IFN-γ stimulation. IFN-γ by itself is able to activate TNF-α gene expression through IRF1. (F) iNOS mRNA gene expression under the four stimulatory conditions. The magnitude of expression is much greater under IFN-γ stimulation as opposed to TNF-α only activation (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0153289#pone.0153289.g004" target="_blank">Fig 4F</a>), which may be attributed to the activation and compounding effect of TNF-α gene expression in the presence of IFN-γ.</p

TNF-α and IFN-γ primed iNOS Gene Expression Dynamics.

<p>The model was simulated with TNF-α, IFN-γ, or both TNF-α /IFN-γ for 24 simulation hours to prime the system. The concentrations of iNOS transcription factors, iNOS mRNA, and iNOS protein were used as inputs to the system for an 8-hour addition simulation under LPS activation. The resulting dynamics display the behavior of iNOS gene expression under primed conditions. The combination of both, TNF-α and IFN-γ causes a significant increase in the dynamics of the primed system however, IFN-γ priming has the ability to generate an increase in the proinflammatory burst when compared to the initial value of iNOS gene expression after IFN-γ priming.</p

LPS Activated Cytokine Synergy on iNOS gene Expression and NO Production.

<p>LPS stimulation activates transcription factors AP1 and NF-κB, which in turn activates the TNF-α gene. Translated TNF-α exports to the extracellular compartment and activates the TNF-α-receptor 1 that proceeds to further stimulate AP1 and NF-κB via an autocrine loop. NF-κB can also activate IRF1, which increases production of TNF-α, however, the production of IRF1 is greatly increased by IFN-γ stimulation and STAT1 phosphorylated dimer activation (bold arrows). Therefore, the synergistic expression of TNF-α and IRF1 by IFN-γ greatly amplifies iNOS gene expression and NO production.</p

Peak and Average iNOS and NO Expression Levels.

<p>Peak and Average iNOS and NO Expression Levels.</p

Time to Peak iNOS mRNA Expression.

<p>The model was simulated under the seven activation conditions and the time to peak iNOS gene expression was obtained for each simulation. The bar graph suggests that LPS is the slowest activator of iNOS whereas TNF-α is the fastest. This feature highlights the need for autocrine regulation of TNF-α during the proinflammatory response to help fight intracellular pathogens. IFN-γ however shows a delayed response when compared to TNF-α. This delayed response may be beneficial to boost the proinflammatory response following TNF-α stimulation.</p