Optimal homeostasis necessitates bistable control

Protocol for live-cell Förster resonance energy transfer imaging to reveal the bistable insulin response of single C2C12-derived myotubes

Based on our hypothesis that myotubes exhibit a bistable response to insulin, here we present a protocol for finely measuring Akt phosphorylation in single myotubes under insulin stimulation. We describe steps to stably express a Förster resonance energy transfer (FRET)-based Akt biosensor in C2C12-derived myotubes and perform single-cell FRET imaging. This protocol highlights its potential for precision medicine in analyzing protein phosphorylation dynamics at the single-cell level. For complete details on the use and execution of this protocol, please refer to Akhtar et al.1.

Wearable Insulin Biosensors for Diabetes Management: Advances and Challenges

We present a critical review of the current progress in wearable insulin biosensors. For over 40 years, glucose biosensors have been used for diabetes management. Measurement of blood glucose is an indirect method for calculating the insulin administration dosage, which is critical for insulin-dependent diabetic patients. Research and development efforts aiming towards continuous-insulin-monitoring biosensors in combination with existing glucose biosensors are expected to offer a more accurate estimation of insulin sensitivity, regulate insulin dosage and facilitate progress towards development of a reliable artificial pancreas, as an ultimate goal in diabetes management and personalised medicine. Conventional laboratory analytical techniques for insulin detection are expensive and time-consuming and lack a real-time monitoring capability. On the other hand, biosensors offer point-of-care testing, continuous monitoring, miniaturisation, high specificity and sensitivity, rapid response time, ease of use and low costs. Current research, future developments and challenges in insulin biosensor technology are reviewed and assessed. Different insulin biosensor categories such as aptamer-based, molecularly imprinted polymer (MIP)-based, label-free and other types are presented among the latest developments in the field. This multidisciplinary field requires engagement between scientists, engineers, clinicians and industry for addressing the challenges for a commercial, reliable, real-time-monitoring wearable insulin biosensor.

Redox regulation of PGRL1 at the onset of low light intensity

PGR5-LIKE PHOTOSYNTHETIC PHENOTYPE1 (PGRL1) regulates photosystem I cyclic electron flow which transiently activates non-photochemical quenching at the onset of light. Here, we show that a disulfide-based mechanism of PGRL1 regulated this process in vivo at the onset of low light levels. We found that PGRL1 regulation depended on active formation of key regulatory disulfides in the dark, and that PGR5 was required for this activity. The disulfide state of PGRL1 was modulated in plants by counteracting reductive and oxidative components and reached a balanced state that depended on the light level. We propose that the redox regulation of PGRL1 fine-tunes a timely activation of photosynthesis at the onset of low light.

Body Mass Dynamics Is Determined by the Metabolic Ohm's Law and Adipocyte-Autonomous Fat Mass Homeostasis

An ODE model integrating metabolic mechanisms with clinical data reveals an Ohm's law governing lifetime body mass dynamics, where fat and lean tissues are analogous to a parallel nonlinear capacitor and resistor, respectively. The law unexpectedly decouples weight stability (a cell-autonomous property of adipocytes) and weight change (a parabolic trajectory governed by Ohm's law). In middle age, insulin resistance causes fat accumulation to avoid excessive body shrinkage in old age. Moderate middle-age spread is thus natural, not an anomaly caused by hypothalamic defects, as proposed by lipostatic theory. These discoveries provide valuable insights into health care practices such as weight control and health assessment, explain certain observed phenomena, make testable predictions, and may help to resolve major conundrums in the field. The ODE model, which is more comprehensive than Ohm's law, is useful to study metabolism at the detailed microscopic levels.

Metabolic transcriptional memory

Background

Organisms can be primed by metabolic exposures to continue expressing response genes even once the metabolite is no longer available, and can affect the speed and magnitude of responsive gene expression during subsequent exposures. This “metabolic transcriptional memory” can have a profound impact on the survivability of organisms in fluctuating environments.

Scope of review

Here I present several examples of metabolic transcriptional memory in the microbial world and discuss what is known so far regarding the underlying mechanisms, which mainly focus on chromatin modifications, protein inheritance, and broad changes in metabolic network. From these lessons learned in microbes, some insights into the yet understudied human metabolic memory can be gained. I thus discuss the implications of metabolic memory in disease progression in humans – i.e., the memory of high blood sugar exposure and the resulting effects on diabetic complications.

Major conclusions

Carbon source shifts from glucose to other less preferred sugars such as lactose, galactose, and maltose for energy metabolism as well as starvation of a signal transduction precursor sugar inositol are well-studied examples of metabolic transcriptional memory in Escherichia coli and Saccharomyces cerevisiae. Although the specific factors guiding metabolic transcriptional memory are not necessarily conserved from microbes to humans, the same basic mechanisms are in play, as is observed in hyperglycemic memory. Exploration of new metabolic transcriptional memory systems as well as further detailed mechanistic analyses of known memory contexts in microbes is therefore central to understanding metabolic memory in humans, and may be of relevance for the successful treatment of the ever-growing epidemic of diabetes.

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Metabolic exposures can prime genes to have memory.

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Memory of carbon source shifts occurs in all kingdoms of life.

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Memory is maintained through multiple mechanisms including chromatin modifications, proteins, and metabolic network.

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Metabolic transcriptional memory in unicellular organisms is a part of “bet-hedging” strategies to ensure survival.

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Hyperglycemic memory in humans contributes to diabetes and aging.

Computational Analysis of Insulin-Glucagon Signalling Network: Implications of Bistability to Metabolic Homeostasis and Disease states

Insulin and glucagon control plasma macronutrient homeostasis through their signalling network composed of multiple feedback and crosstalk interactions. To understand how these interactions contribute to metabolic homeostasis and disease states, we analysed the steady state response of metabolic regulation (catabolic or anabolic) with respect to structural and input perturbations in the integrated signalling network, for varying levels of plasma glucose. Structural perturbations revealed: the positive feedback of AKT on IRS is responsible for the bistability in anabolic zone (glucose >5.5 mmol); the positive feedback of calcium on cAMP is responsible for ensuring ultrasensitive response in catabolic zone (glucose <4.5 mmol); the crosstalk between AKT and PDE3 is responsible for efficient catabolic response under low glucose condition; the crosstalk between DAG and PKC regulates the span of anabolic bistable region with respect to plasma glucose levels. The macronutrient perturbations revealed: varying plasma amino acids and fatty acids from normal to high levels gradually shifted the bistable response towards higher glucose range, eventually making the response catabolic or unresponsive to increasing glucose levels. The analysis reveals that certain macronutrient composition may be more conducive to homeostasis than others. The network perturbations that may contribute to disease states such as diabetes, obesity and cancer are discussed.

Chemoinformatics in the New Era: From Molecular Dynamics to Systems Dynamics

Chemoinformatics, due to its power in gathering information at the molecular level, has a wide array of important applications to biology, including fundamental biochemical studies and drug discovery and optimization. As modern "omics" based profiling and network based modeling and simulation techniques grow in sophistication, chemoinformatics now faces a great opportunity to include systems-level control mechanisms as one of its pillar components to extend and refine its various applications. This viewpoint article, through the example of computer aided targeting of the PI3K/Akt/mTOR pathway, outlines major steps of integrating systems dynamics simulations into molecular dynamics simulations to facilitate a higher level of chemoinformatics that would revolutionize drug lead optimization, personalized therapy, and possibly other applications.

Raison d'être of insulin resistance: the adjustable threshold hypothesis

The epidemics of obesity and diabetes demand a deeper understanding of insulin resistance, for which the adjustable threshold hypothesis is formed in this paper. To test the hypothesis, mathematical modelling was used to analyse clinical data and to simulate biological processes at both molecular and organismal levels. I found that insulin resistance roots in the thresholds of the cell's bistable response. By assuming heterogeneity of the thresholds, single cells' all-or-none response can collectively produce a graded response at the whole-body level-conforming to existing data. The thresholds have to be adjustable to adapt to extreme conditions. During pregnancy, for example, the thresholds increase consistently to strengthen the mother's insulin resistance to meet the increasing glucose demand of the expanding fetal brain. I also found that hysteresis, a key element of the adjustable threshold hypothesis, can explain reactive hypoglycaemia, which is characteristic of diabetes complications but remains poorly understood. Contrary to the common belief that insulin promotes glucose disposal, the results imply that insulin is the body's 'ration stamp' to restricting glucose utilization by peripheral tissues and that insulin resistance is primarily a well-evolved mechanism. The hypothesis provides an intuitive and dynamical description of the previously formless insulin resistance, which may make the detection of pre-diabetes possible and may shed light on the optimal timing of therapeutic intervention. It also provides valuable clues to defining subtypes of type 2 diabetes that might respond differently to specific prevention and intervention strategies.

Computer-aided targeting of the PI3K/Akt/mTOR pathway: toxicity reduction and therapeutic opportunities

The PI3K/Akt/mTOR pathway plays an essential role in a wide range of biological functions, including metabolism, macromolecular synthesis, cell growth, proliferation and survival. Its versatility, however, makes it a conspicuous target of many pathogens; and the consequential deregulations of this pathway often lead to complications, such as tumorigenesis, type 2 diabetes and cardiovascular diseases. Molecular targeted therapy, aimed at modulating the deregulated pathway, holds great promise for controlling these diseases, though side effects may be inevitable, given the ubiquity of the pathway in cell functions. Here, we review a variety of factors found to modulate the PI3K/Akt/mTOR pathway, including gene mutations, certain metabolites, inflammatory factors, chemical toxicants, drugs found to rectify the pathway, as well as viruses that hijack the pathway for their own synthetic purposes. Furthermore, this evidence of PI3K/Akt/mTOR pathway alteration and related pathogenesis has inspired the exploration of computer-aided targeting of this pathway to optimize therapeutic strategies. Herein, we discuss several possible options, using computer-aided targeting, to reduce the toxicity of molecularly-targeted therapy, including mathematical modeling, to reveal system-level control mechanisms and to confer a low-dosage combination therapy, the potential of PP2A as a therapeutic target, the formulation of parameters to identify patients who would most benefit from specific targeted therapies and molecular dynamics simulations and docking studies to discover drugs that are isoform specific or mutation selective so as to avoid undesired broad inhibitions. We hope this review will stimulate novel ideas for pharmaceutical discovery and deepen our understanding of curability and toxicity by targeting the PI3K/Akt/mTOR pathway.