Biology subjects

Viswanathan, G. A.

Publications and source records attributed to Viswanathan, G. A..

4 recordsLinked to original sources

bioRxiv2022

Boolean dynamic modeling of TNFR1 signaling predicts a nested feedback loop regulating the apoptotic response at single-cell level

Cell-to-cell variability during Tumor Necrosis Factor Receptor 1 (TNFR1) signaling triggered by the pleiotropic cytokine TNF can lead to pro-survival and apoptotic phenotypic responses at single-cell level. Harnessing the ability to modulate the signal flow responsible for the balance between these two phenotypes and make cells favour apoptosis have been considered in cancer therapies. We show that a 6-node nested feedback loop facilitates the crucial crosstalk regulation modulating the signal flow between these two responses. We identify this by systematically analysing the partial state transition graph (pSTG) underlying a Boolean dynamic model of the TNFR1 signaling network that accounts for signal flow path variability. We demonstrate a novel approach "Boolean Modeling based Prediction of Steady-state probability of Phenotype Reachability (BM-ProSPR)" that enables constructing a reliable pSTG in a computationally efficient manner and predicting accurately the networks ability to settle into different phenotypes. We deduce that knocking-off Comp1 - IKK* complex tweaks the signal flow paths leading to a 62% increase in the steady state probability of TNFR1 signaling culminating in apoptosis and thereby favours phenotype switching from pro-survival to apoptosis. Priming cancerous cells with inhibitors targeting the interaction involving Comp1 and IKK* prior to TNF exposure could be a potential therapeutic strategy.

systems biology↗

bioRxiv2021

Unraveling the intracellular cross-talk governing the balance between TNFα mediated survival and apoptosis signaling

Tumor necrosis factor alpha (TNF), a pleiotropic cytokine, helps maintain a balance between proliferation and apoptosis in normal cells. This balance is often sacrificed in a diseased cell, such as that of a cancer, by preferring survival phenotype over apoptosis. Restoring this balance requires a detailed understanding of the causal intracellular mechanisms that govern TNF stimulated apoptotic response. In this study, we use a systems biology approach to unravel the interplay between the intracellular signaling markers that orchestrate apoptosis levels. Our approach deciphered the synergism between the early intracellular markers phosphorylated JNK (pJNK) and phosphorylated AKT (pAKT) that modulate the activation of Caspase3, an important apoptotic regulator. We demonstrate that this synergism depends critically on the survival pathway signaling mediated by NF{kappa}B which plays a dominant role in controlling the extent of the overall apoptotic response. By systematic inhibition of the signaling markers, we establish that the dynamic cross-talk between the pJNK and pAKT transients directs the apoptosis phenotype via accumulated Caspase3 response. Interestingly, superposition of the semi-quantitative correlation between apoptosis and Caspase3 transient levels on the proposed TNF network model permits quantification of the dynamic apoptotic response under different stimulation conditions. Thus, the predictive model can be leveraged towards arriving at useful insights that can identify potential targeted therapeutic strategies for altering apoptotic response.

systems biology↗

bioRxiv2020

Retroactivity induced operating regime transition in a phosphorylation- dephosphorylation cycle

Operating regimes characterizing the input-output behaviour of an activated phosphorylation-dephosphorylation reaction cycle (PdPC) such as a single MAPK cascade are dictated by the saturated/unsaturated state of the two underlying enzymatic reactions. Four combinations of the states of these two enzymatic reactions led to identification of distinct operating regimes, viz., Hyperbolic (H), Signal transducing (ST), Threshold-hyperbolic (TH) and Ultrasensitive (U). A single PdPC without an explicit feedback have been classically viewed as a module offering signal flow from upstream to downstream, that is, one-way communication. Recently it has been shown that load due to sequestration of the phosphorylated or unphosphorylated form of the substrate by corresponding downstream targets permits retroactive signalling that offers two-way communication. We systematically characterize the operating regimes of a single PdPC subject to retroactivity in either of the substrate forms. We identify five possible regime transitions that could be achieved by increasing the retroactivity strength on either of the two substrate forms. Remarkably, a retroactivity strength of 0.30 in the unphosphorylated form of the substrate is sufficient to induce a transition from ST to H regime indicating that the input-output behaviour of a PdPC is highly sensitive to the presence of a downstream load. Using sensitivity and rate-balance analysis, we show that modulation of the saturation levels of the two enzymatic reactions by increasing retroactivity is the fundamental mechanism governing operating regime transition. HighlightsO_LICharacterization of operating regimes in the presence of retroactivity. C_LIO_LIRetroactivity can induce a transition between different operating regimes. C_LIO_LISaturation levels of the two enzymatic reactions govern the regime transition. C_LIO_LISensitivity of the protein levels to retroactivity is dictated by saturation levels. C_LI

systems biology↗

bioRxiv2019

Operating regimes in a single enzymatic cascade at ensemble-level

Operating regime of a single enzymatic cascade such as ubiquitously conserved MAPK building block provides insights into the nature of the sensitivity of the steady-state dose response that maps the upstream kinase and the downstream activated substrate concentrations. Steady-state response can be viewed either at a single-cell level in an ensemble of cells or at population-average level. Four operating regimes, viz., hyperbolic, threshold-hyperbolic, signal transducing and saturated, have been identified using the population-average level dose response curve. However, cell-to-cell variability exists in enzymatic cascades. This variability is captured using reporter based experimentation at ensemble level which permits detection of snapshot(s) of ensemble-level distribution of phosphorylated proteins. As a result, often the corresponding underlying steady-state dose response curve may not be available. We consider the question if the underyling operating regime can be directly inferred from ensemble level snapshot upstream kinase (input) and downstream phosphorylated substrates (response) distributions. In order to address this question, we use mathematical model of a single enzymatic cascade based on quasi-steady state approximation superimposed with an input distribution constrained by single-cell level experimental measurements of the MAPK cascade in Jurkat E6.1 cells stimulated with Phorbol Myristate Acetate (PMA). We prove that, under steady-state conditions, a monotonic relationship between the RIQR (=ratio of the inter-quartile range of the response and input distributions) and Rm (=ratio of medians of the two distributions), both of which are experimental observables, can be used to identify the underlying operating regime. We also show that the identification of the unimodal vs bimodal nature of the response distributions can further lead to identification of the potential parameter range in the planes of Michaelis-Menten constants K1 and K2, the two key parameters that dictate the operating regimes. We implement the proposed method on the stimulus strength dependent steady-state single-cell level pMEK (input) and pERK (response) distributions in Jurkat E6.1 cells treated with PMA. While cells stimulated using low concentrations of PMA are likely to operate in hyperbolic regime, those exposed to higher concentrations may lie in signal-transducing regime. Authors summarySingle enzymatic cascade, a ubiquitously found key building block in biological signaling networks, exhibits different steady-state behaviour at population (ensemble) level compared to population-averaged response. Detection at ensemble level typically achieved by non-plasmid based reporter permits snapshot fluorescence distribution measurement. We ask if there are signatures of fluorescence distribution of input kinase and response activated protein that can help decipher the underlying dose-response belonging to four distinct operating regimes a single enzymatic cascade exhibits. Based on simultaneously measured snapshot input (pMEK) and response (pERK) protein levels in an ensemble of PMA stimulated immortalized cancer (Jurkat E6.1) cells, we superimpose pMEK data-guided upstream kinase distribution capturing cell-to-cell variability on the steady-state Michaelis-Menten (MM) kinetic model. Following extensive MM constants sampling and simulations, we systematically identify that monotonicity between RIQR, the ratio of the inter-quartile range of response and input distributions, and RM, the median ratio of the two distributions, enables regime identification of the measured pERK distribution. We further show qualitative assessment of the modality of the response distribution can constrain the parameter range within an operating regime. Both RIQR and RM being experimental observables makes the proposed method suitable for assessing signal modulation capability of an enzymatic cascade of interest.

systems biology↗