Bistability in cell signalling and its significance in identifying potential drug targets

Noise-guided tuning of synthetic protein waves in living cells

Biological systems use protein circuits to organize cellular activities in space and time, but engineering synthetic dynamics is challenging due to stochastic effects of genetic and biochemical variation on circuit behavior. Genetically encoded oscillators (GEOs) built from bacterial MinDE-family ATPase and Activator modules generate fast orthogonal protein waves in eukaryotic cells, providing an experimental model system for genetic and biochemical coordination of synthetic protein dynamics. Here, we use budding yeast to experimentally define and model phase portraits that reveal how the breadth of frequencies and amplitudes available to a GEO are genetically controlled by ATPase and Activator expression levels and noise. GEO amplitude is encoded by ATPase absolute abundance, making it sensitive to extrinsic noise on a population level. In contrast, GEO frequency is remarkably stable because it is controlled by the Activator:ATPase ratio and thus affected primarily by intrinsic noise. These features facilitate noise-guided design of different expression strategies that act as filters on GEO waveform, enabling us to construct clonal populations that oscillate at different frequencies as well as independently tune frequency and amplitude variation within a single population. By characterizing 169 biochemically distinct GEOs, we provide a rich assortment of phase portraits as starting points for application of our waveform engineering approach. Our findings suggest noise-guided design may be a valuable strategy for achieving precision control over dynamic protein circuits.

Bistability regulates TNFR2-mediated survival and death of T-regulatory cells

A subgroup of T cells called T-regulatory cells (Tregs) regulates the body's immune responses to maintain homeostasis and self-tolerance. Tregs are crucial for preventing illnesses like cancer and autoimmunity. However, contrasting patterns of Treg frequency are observed in different autoimmune diseases. The commonality of tumour necrosis factor receptor 2 (TNFR2) defects and decrease in Treg frequency on the onset of autoimmunity demands an in-depth study of the TNFR2 pathway. To unravel this mystery, we need to study the mechanism of cell survival and death in Tregs. Here, we construct an ordinary differential equation (ODE)-based model to capture the mechanism of cell survival and apoptosis in Treg cells via TNFR2 signalling. The sensitivity analysis reveals that the input stimulus, the concentration of tumour necrosis factor (TNF), is the most sensitive parameter for the model system. The model shows that the cell goes into survival or apoptosis via bistable switching. Through hysteretic switching, the system tries to cope with the changing stimuli. In order to understand how stimulus strength and feedback strength influence cell survival and death, we compute bifurcation diagrams and obtain cell fate maps. Our results indicate that the elevated TNF concentration and increased c-Jun N-terminal kinase (JNK) phosphorylation are the major contributors to the death of T-regulatory cells. Biological evidence cements our hypothesis and can be controlled by reducing the TNF concentration. Finally, the system was studied under stochastic perturbation to see the effect of noise on the system's dynamics. We observed that introducing random perturbations disrupts the bistability, reducing the system's bistable region, which can affect the system's normal functioning.

Understanding noise in cell signalling in the prospect of drug-targets

The introduction of noise to signals can alter central regulatory switches of cellular processes leading to diseases. Noise is inherently present in the cellular signalling system and plays a decisive role in the input-output (I/O) relation. The current study aims to understand the noise tolerance of motif structures in the cell signalling processes. The vulnerability of a node to noise could be a significant factor in causing signalling error and need to be controlled. We developed stochastic differential equation (SDE) based mathematical models for different network motifs with two nodes and studied the association between motif structure and signal-noise relation. A two-dimensional parameter space analysis on motif sensitivity with noise and input signal variation was performed to classify and rank the motifs. Identifying sensitive motifs and their high druggability infers their significance in screening potential drug-target candidates. Finally, we proposed a theoretical framework to identify nodes from a network as potential drug targets. We applied this mathematical formalism to three cancer networks to identify drug-targets and validated them with existing databases.

Multistability in Macrophage Activation Pathways and Metabolic Implications

Macrophages are innate immune cells with a dynamic range of reversible activation states including the classical pro-inflammatory (M1) and alternative anti-inflammatory (M2) states. Deciphering how macrophages regulate their transition from one state to the other is key for a deeper understanding of inflammatory diseases and relevant therapies. Common regulatory motifs reported for macrophage transitions, such as positive or double-negative feedback loops, exhibit a switchlike behavior, suggesting the bistability of the system. In this review, we explore the evidence for multistability (including bistability) in macrophage activation pathways at four molecular levels. First, a decision-making module in signal transduction includes mutual inhibitory interactions between M1 (STAT1, NF-KB/p50-p65) and M2 (STAT3, NF-KB/p50-p50) signaling pathways. Second, a switchlike behavior at the gene expression level includes complex network motifs of transcription factors and miRNAs. Third, these changes impact metabolic gene expression, leading to switches in energy production, NADPH and ROS production, TCA cycle functionality, biosynthesis, and nitrogen metabolism. Fourth, metabolic changes are monitored by metabolic sensors coupled to AMPK and mTOR activity to provide stability by maintaining signals promoting M1 or M2 activation. In conclusion, we identify bistability hubs as promising therapeutic targets for reverting or blocking macrophage transitions through modulation of the metabolic environment.