Browsing by Author "Tiwari, Abhinav"

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Coupling between feedback loops in autoregulatory networks affects bistability range, open-loop gain and switching times
    (IOP Publishing, 2012) Tiwari, Abhinav; Igoshin, Oleg A.; Bioengineering
    Biochemical regulatory networks governing diverse cellular processes such as stress-response, differentiation and cell cycle often contain coupled feedback loops. We aim at understanding how features of feedback architecture, such as the number of loops, the sign of the loops and the type of their coupling, affect network dynamical performance. Specifically, we investigate how bistability range, maximum open-loop gain and switching times of a network with transcriptional positive feedback are affected by additive or multiplicative coupling with another positive- or negative-feedback loop. We show that a network's bistability range is positively correlated with its maximum open-loop gain and that both quantities depend on the sign of the feedback loops and the type of feedback coupling. Moreover, we find that the addition of positive feedback could decrease the bistability range if we control the basal level in the signal-response curves of the two systems. Furthermore, the addition of negative feedback has the capacity to increase the bistability range if its dissociation constant is much lower than that of the positive feedback. We also find that the addition of a positive feedback to a bistable network increases the robustness of its bistability range, whereas the addition of a negative feedback decreases it. Finally, we show that the switching time for a transition from a high to a low steady state increases with the effective fold change in gene regulation. In summary, we show that the effect of coupled feedback loops on the bistability range and switching times depends on the underlying mechanistic details.
  • Thumbnail Image
    Item
    Tunable Protease-Activatable Virus Nanonodes
    (American Chemical Society, 2014) Judd, Justin; Ho, Michelle L.; Tiwari, Abhinav; Gomez, Eric J.; Dempsey, Christopher; Vliet, Kim Van; Igoshin, Oleg A.; Silberg, Jonathan J.; Agbandje-McKenna, Mavis; Suh, Junghae; Bioengineering; Biosciences
    We explored the unique signal integration properties of the self-assembling 60-mer protein capsid of adeno-associated virus (AAV), a clinically proven human gene therapy vector, by engineering proteolytic regulation of virusﾖreceptor interactions such that processing of the capsid by proteases is required for infection. We find the transfer function of our engineered protease-activatable viruses (PAVs), relating the degree of proteolysis (input) to PAV activity (output), is highly nonlinear, likely due to increased polyvalency. By exploiting this dynamic polyvalency, in combination with the self-assembly properties of the virus capsid, we show that mosaic PAVs can be constructed that operate under a digital AND gate regime, where two different protease inputs are required for virus activation. These results show viruses can be engineered as signal-integrating nanoscale nodes whose functional properties are regulated by multiple proteolytic signals with easily tunable and predictable response surfaces, a promising development toward advanced control of gene delivery.
  • Thumbnail Image
    Item
    Uncovering Mechanisms of Bistability and Ultrasensitivity in Bacterial Stress Response
    (2013-11-26) Tiwari, Abhinav; Igoshin, Oleg A.; Nakhleh, Luay K.; Qutub, Amina A.; Balazsi, Gabor
    Bacteria have evolved optimized biochemical and genetic networks to sense diverse stimuli and implement appropriate dynamic responses. Despite the remarkable progress in experimental approaches and the increasingly common use of mathematical modeling, very few examples exist of general design principles that relate a network’s structure to its response. To improve this understanding we develop biochemically accurate models of networks that contain well-conserved regulatory modules, which allows us to make both specific and biologically-relevant predictions. First, we analyze the mycobacterial stress-response network which consists of the MprA/MprB two-component system and the alternative sigma factor Sig E. This network contains multiple positive feedback loops which may give rise to bistability, thereby making it a good candidate for controlling the mycobacterial persistence switch. We find that neither the positive autoregulation in the two-component system nor the Sig E-mediated feedback is sufficient to induce bistability. Nonetheless, including the post-translational regulation of SigE by RseA increases system’s effective cooperativity resulting in bistability. We predict that overexpression or deletion of RseA, the key element controlling the ultrasensitive response, can eliminate bistability. Second, we investigate how dynamical properties of a network with positive autoregulation are affected by additive or multiplicative coupling with another positive or negative feedback. We find that a network’s bistability range is positively correlated with its maximum open-loop gain and that both the quantities depend on the sign of feedback loops and the type of feedback coupling. Moreover, we show that addition of a positive feedback can decrease, whereas addition of a negative feedback can increase the bistability range. Third, we examine the mechanism of pulsing in Bacillus subtilis stress-response sigma factor Sig B. We determine that the concentration of anti-sigma factor RsbW must lie in an optimal range for pulsing. We also observe that pulsing occurs only above a phosphatase threshold, beyond which the amount of RsbW is insufficient to fully sequester its binding partners Sig B and anti-anti-sigma factor RsbV. Furthermore, we compare our simulation results with experimental data to show that the network encodes phosphatase burst size into Sig B pulses. We predict that genetic perturbations which disrupt the fine-tuning of RsbW concentration will curb pulsing.
  • Thumbnail Image
    Item
    Unraveling the regulatory connections between two controllers of breast cancer cell fate
    (Oxford University Press, 2014) Lee, Jinho; Tiwari, Abhinav; Shum, Victor; Mills, Gordon B.; Mancini, Michael A.; Igoshin, Oleg A.; Balázsi, Gábor; Bioengineering
    Estrogen receptor alpha (ERα) expression is critical for breast cancer classification, high ERα expression being associated with better prognosis. ERα levels strongly correlate with that of GATA binding protein 3 (GATA3), a major regulator of ERα expression. However, the mechanistic details of ERα–GATA3 regulation remain incompletely understood. Here we combine mathematical modeling with perturbation experiments to unravel the nature of regulatory connections in the ERα–GATA3 network. Through cell population-average, single-cell and single-nucleus measurements, we show that the cross-regulation between ERα and GATA3 amounts to overall negative feedback. Further, mathematical modeling reveals that GATA3 positively regulates its own expression and that ERα autoregulation is most likely absent. Lastly, we show that the two cross-regulatory connections in the ERα–GATA3 negative feedback network decrease the noise in ERα or GATA3 expression. This may ensure robust cell fate maintenance in the face of intracellular and environmental fluctuations, contributing to tissue homeostasis in normal conditions, but also to the maintenance of pathogenic states during cancer progression.