Temporal coding of insulin action through multiplexing of the AKT pathway

Model selection reveals selective regulation of blood amino acid and lipid metabolism by insulin in humans

Insulin plays a crucial role in regulating the metabolism of blood glucose, amino acids (aa), and lipids in humans. However, the mechanisms by which insulin selectively regulates these metabolites are not fully understood. To address this question, we used mathematical modeling to identify the selective regulatory mechanisms of insulin on blood aa and lipids. Our study revealed that insulin negatively regulates the influx and positively regulates the efflux of lipids, consistent with previous findings. By contrast, we did not observe the previously reported insulin's negative regulation of branched-chain aa (BCAA) influx; instead, we found that insulin positively regulates BCAA efflux. We observed that the earlier peak time of lipids compared to BCAA is dependent on insulin's negative regulation of their influx. Overall, our findings shed new light on how insulin selectively regulates the levels of different metabolites in human blood, providing insights into the metabolic disorder pathogenesis and potential therapies.

Periodic insulin stimulation of Akt: Dynamic steady states and robustness

The periodic secretion of insulin is a salient feature of the blood glucose control system in vivo. Insulin levels in the blood exhibit oscillations on multiple time scales - rapid, ultradian, and circadian - and the improved metabolic regulation resulting from pulsatile insulin release has been well established. Although numerous mathematical models investigating the causal mechanisms of insulin oscillations have appeared in the literature, to date there has been comparatively little attention given to the influence of periodic insulin stimulation on downstream components of the insulin signalling pathway. In this paper, we explore the effect of high frequency periodic insulin stimulation on Akt (also known as PKB), a crucial crosstalk node in the insulin signalling pathway that coordinates metabolic and mitogenic processes in the cell. We analyse a mathematical model of Akt translocation to the plasma membrane under both single step insulin perturbations and periodic insulin stimulation with an emphasis on - but not limited to - the physiological range of parameter values. It was shown that the system rapidly attains a robust dynamic steady state entrained to the periodic insulin stimulation. Moreover, the translocation of Akt to the plasma membrane in the model permits a sufficient level of phosphorylation to trigger downstream metabolic regulators. However, the modelling also indicated that further investigation of this activation process is required to determine whether the response of Akt is a key determinant of the enhanced metabolic control observed under periodic insulin stimulation.

Phenotypic consequences of logarithmic signaling in MAPK stress response

How cells respond to dynamic environmental changes is crucial for understanding fundamental biological processes and cell physiology. In this study, we developed an experimental and quantitative analytical framework to explore how dynamic stress gradients that change over time regulate cellular volume, signaling activation, and growth phenotypes. Our findings reveal that gradual stress conditions substantially enhance cell growth compared to conventional acute stress. This growth advantage correlates with a minimal reduction in cell volume dependent on the dynamic of stress. We explain the growth phenotype with our finding of a logarithmic signal transduction mechanism in the yeast Mitogen-Activated Protein Kinase (MAPK) osmotic stress response pathway. These insights into the interplay between gradual environments, cell volume change, dynamic cell signaling, and growth, advance our understanding of fundamental cellular processes in gradual stress environments.

PI3K signaling through a biochemical systems lens

Following 3 decades of extensive research into PI3K signaling, it is now evidently clear that the underlying network does not equate to a simple ON/OFF switch. This is best illustrated by the multifaceted nature of the many diseases associated with aberrant PI3K signaling, including common cancers, metabolic disease, and rare developmental disorders. However, we are still far from a complete understanding of the fundamental control principles that govern the numerous phenotypic outputs that are elicited by activation of this well-characterized biochemical signaling network, downstream of an equally diverse set of extrinsic inputs. At its core, this is a question on the role of PI3K signaling in cellular information processing and decision making. Here, we review the determinants of accurate encoding and decoding of growth factor signals and discuss outstanding questions in the PI3K signal relay network. We emphasize the importance of quantitative biochemistry, in close integration with advances in single-cell time-resolved signaling measurements and mathematical modeling.

An optogenetic-phosphoproteomic study reveals dynamic Akt1 signaling profiles in endothelial cells

The serine/threonine kinase AKT is a central node in cell signaling. While aberrant AKT activation underlies the development of a variety of human diseases, how different patterns of AKT-dependent phosphorylation dictate downstream signaling and phenotypic outcomes remains largely enigmatic. Herein, we perform a systems-level analysis that integrates methodological advances in optogenetics, mass spectrometry-based phosphoproteomics, and bioinformatics to elucidate how different intensity, duration, and pattern of Akt1 stimulation lead to distinct temporal phosphorylation profiles in vascular endothelial cells. Through the analysis of ~35,000 phosphorylation sites across multiple conditions precisely controlled by light stimulation, we identify a series of signaling circuits activated downstream of Akt1 and interrogate how Akt1 signaling integrates with growth factor signaling in endothelial cells. Furthermore, our results categorize kinase substrates that are preferably activated by oscillating, transient, and sustained Akt1 signals. We validate a list of phosphorylation sites that covaried with Akt1 phosphorylation across experimental conditions as potential Akt1 substrates. Our resulting dataset provides a rich resource for future studies on AKT signaling and dynamics.

Onco-Pathogen Mediated Cancer Progression and Associated Signaling Pathways in Cancer Development

Infection with viruses, bacteria, and parasites are thought to be the underlying cause of about 8-17% of the world's cancer burden, i.e., approximately one in every five malignancies globally is caused by an infectious pathogen. Oncogenesis is thought to be aided by eleven major pathogens. It is crucial to identify microorganisms that potentially act as human carcinogens and to understand how exposure to such pathogens occur as well as the following carcinogenic pathways they induce. Gaining knowledge in this field will give important suggestions for effective pathogen-driven cancer care, control, and, ultimately, prevention. This review will mainly focus on the major onco-pathogens and the types of cancer caused by them. It will also discuss the major pathways which, when altered, lead to the progression of these cancers.

Optogenetic decoding of Akt2-regulated metabolic signaling pathways in skeletal muscle cells using transomics analysis

Insulin regulates various cellular metabolic processes by activating specific isoforms of the Akt family of kinases. Here, we elucidated metabolic pathways that are regulated in an Akt2-dependent manner. We constructed a transomics network by quantifying phosphorylated Akt substrates, metabolites, and transcripts in C2C12 skeletal muscle cells with acute, optogenetically induced activation of Akt2. We found that Akt2-specific activation predominantly affected Akt substrate phosphorylation and metabolite regulation rather than transcript regulation. The transomics network revealed that Akt2 regulated the lower glycolysis pathway and nucleotide metabolism and cooperated with Akt2-independent signaling to promote the rate-limiting steps in these processes, such as the first step of glycolysis, glucose uptake, and the activation of the pyrimidine metabolic enzyme CAD. Together, our findings reveal the mechanism of Akt2-dependent metabolic pathway regulation, paving the way for Akt2-targeting therapeutics in diabetes and metabolic disorders.

Rate thresholds in cell signaling have functional and phenotypic consequences in non-linear time-dependent environments

All cells employ signal transduction pathways to respond to physiologically relevant extracellular cytokines, stressors, nutrient levels, hormones, morphogens, and other stimuli that vary in concentration and rate in healthy and diseased states. A central unsolved fundamental question in cell signaling is whether and how cells sense and integrate information conveyed by changes in the rate of extracellular stimuli concentrations, in addition to the absolute difference in concentration. We propose that different environmental changes over time influence cell behavior in addition to different signaling molecules or different genetic backgrounds. However, most current biomedical research focuses on acute environmental changes and does not consider how cells respond to environments that change slowly over time. As an example of such environmental change, we review cell sensitivity to environmental rate changes, including the novel mechanism of rate threshold. A rate threshold is defined as a threshold in the rate of change in the environment in which a rate value below the threshold does not activate signaling and a rate value above the threshold leads to signal activation. We reviewed p38/Hog1 osmotic stress signaling in yeast, chemotaxis and stress response in bacteria, cyclic adenosine monophosphate signaling in Amoebae, growth factors signaling in mammalian cells, morphogen dynamics during development, temporal dynamics of glucose and insulin signaling, and spatio-temproral stressors in the kidney. These reviewed examples from the literature indicate that rate thresholds are widespread and an underappreciated fundamental property of cell signaling. Finally, by studying cells in non-linear environments, we outline future directions to understand cell physiology better in normal and pathophysiological conditions.

Mechanistic insights into cancer drug resistance through optogenetic PI3K signaling hyperactivation

Hyperactivation of phosphatidylinositol 3-kinase (PI3K) signaling is a prominent feature in cancer cells. However, the mechanism underlying malignant behaviors in the state remains unknown. Here, we describe a mechanism of cancer drug resistance through the protein synthesis pathway, downstream of PI3K signaling. An optogenetic tool (named PPAP2) controlling PI3K signaling was developed. Melanoma cells stably expressing PPAP2 (A375-PPAP2) acquired resistance to a cancer drug in the hyperactivation state. Proteome analyses revealed that expression of the antiapoptotic factor tumor necrosis factor alpha-induced protein 8 (TNFAIP8) was upregulated. TNFAIP8 upregulation was mediated by protein translation from preexisting mRNA. These results suggest that cancer cells escape death via upregulation of TNFAIP8 expression from preexisting mRNA even though alkylating cancer drugs damage DNA.

Synthetic gene networks recapitulate dynamic signal decoding and differential gene expression

Cells live in constantly changing environments and employ dynamic signaling pathways to transduce information about the signals they encounter. However, the mechanisms by which dynamic signals are decoded into appropriate gene expression patterns remain poorly understood. Here, we devise networked optogenetic pathways that achieve dynamic signal processing functions that recapitulate cellular information processing. Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling edge pulse detector and show that this circuit can be employed to demultiplex dynamically encoded signals. We combine this demultiplexer with dCas9-based gene networks to construct pulsatile signal filters and decoders. Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state. Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway. Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.

Principles of synthetic biology

In synthetic biology, biological cells and processes are dismantled and reassembled to make novel systems that do useful things. Designs are encoded by deoxyribonucleic acid (DNA); DNA makes biological (bio-)parts; bioparts are combined to make devices; devices are built into biological systems. Computers are used at all stages of the Design-Build-Test-Learn cycle, from mathematical modelling through to the use of robots for the automation of assembly and experimentation. Synthetic biology applies engineering principles of standardisation, modularity, and abstraction, enabling fast prototyping and the ready exchange of designs between synthetic biologists working around the world. Like toy building blocks, compatible modular designs enable bioparts to be combined and optimised easily; biopart specifications are shared in open registries. Synthetic biology is made possible due to major advances in DNA sequencing and synthesis technologies, and through knowledge gleaned in the field of systems biology. Systems biology aims to understand biology across scales, from the molecular and cellular, up to tissues and organisms, and describes cells as complex information-processing systems. By contrast, synthetic biology seeks to design and build its own systems. Applications of synthetic biology are wide-ranging but include impacting healthcare to improve diagnosis and make better treatments for disease; it seeks to improve the environment by finding novel ways to clean up pollution, make industrial processes for chemical synthesis sustainable, and remove the need for damaging farming practices by making better fertilisers. Synthetic biology has the potential to change the way we live and help us to protect the future of our planet.

Continuous variable responses and signal gating form kinetic bases for pulsatile insulin signaling and emergence of resistance

Evolutionarily conserved insulin signaling is central to nutrient sensing, storage, and utilization across tissues. Dysfunctional insulin signaling is associated with metabolic disorders, cancer, and aging. Hence, the pathway components have emerged as key targets for pharmacological interventions in addition to insulin administration itself. Despite this, activation–inactivation dynamics of individual components, which exert regulatory control in a physiological context, is poorly understood. Now, with our systems-based approach, we reveal kinetic parameters, which define the flow of information through both metabolic and growth-factor arms and thus determine signaling architecture. We also provide a kinetic basis for 1) the advantage of pulsatile-fasted insulin signaling that enables fed-insulin response and 2) the detrimental impact of repeat fed-insulin inputs that causes resistance.

Understanding kinetic control of biological processes is as important as identifying components that constitute pathways. Insulin signaling is central for almost all metazoans, and its perturbations are associated with various developmental disorders, metabolic diseases, and aging. While temporal phosphorylation changes and kinetic constants have provided some insights, constant or variable parameters that establish and maintain signal topology are poorly understood. Here, we report kinetic parameters that encode insulin concentration and nutrient-dependent flow of information using iterative experimental and mathematical simulation-based approaches. Our results illustrate how dynamics of distinct phosphorylation events collectively contribute to selective kinetic gating of signals and maximum connectivity of the signaling cascade under normo-insulinemic but not hyper-insulinemic states. In addition to identifying parameters that provide predictive value for maintaining the balance between metabolic and growth-factor arms, we posit a kinetic basis for the emergence of insulin resistance. Given that pulsatile insulin secretion during a fasted state precedes a fed response, our findings reveal rewiring of insulin signaling akin to memory and anticipation, which was hitherto unknown. Striking disparate temporal behavior of key phosphorylation events that destroy the topology under hyper-insulinemic states underscores the importance of unraveling regulatory components that act as bandwidth filters. In conclusion, besides providing fundamental insights, our study will help in identifying therapeutic strategies that conserve coupling between metabolic and growth-factor arms, which is lost in diseases and conditions of hyper-insulinemia.

Concentrated growth factor regulates the macrophage-mediated immune response

Concentrated growth factor (CGF) is a promising regenerative material that serves as a scaffold and adjunct growth factor for tissue engineering. The host immune response, particularly macrophage activity, plays a critical role in injury repair and tissue regeneration. However, the biological effect of CGF on the immune response is not clear. To enrich the theoretical groundwork for clinical application, the present study examined the immunoregulatory role of CGF in macrophage functional activities in vitro. The CGF scaffold appeared as a dense fibrin network with multiple embedded leukocytes and platelets, and it was biocompatible with macrophages. Concentrated bioactive factors in the CGF extract enhanced THP-1 monocyte recruitment and promoted the maturation of suspended monocytes into adherent macrophages. CGF extract also promoted THP-1 macrophage polarization toward the M2 phenotype with upregulated CD163 expression, as detected by cell morphology and surface marker expression. A cytokine antibody array showed that CGF extract exerted a regulatory effect on macrophage functional activities by reducing secretion of the inflammatory factor interleukin-1β while inducing expression of the chemokine regulated on activation, normal T cell expressed and secreted. Mechanistically, the AKT signaling pathway was activated, and an AKT inhibitor partially suppressed the immunomodulatory effect of CGF. Our findings reveal that CGF induces a favorable immune response mediated by macrophages, which represents a promising strategy for functional tissue regeneration.

Insulin Exacerbates Inflammation in Fibroblast-Like Synoviocytes

Osteoarthritis (OA) is considered the most frequent degenerative disease and is characterized by cartilage degradation and synovial inflammation. Fibroblast-like synoviocytes (FLSs) are vital to synovial inflammation in OA. Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance and hyperinsulinemia (HINS) and has been demonstrated to be an independent risk factor for OA. Autophagy is involved in the processes of various inflammatory diseases, and autophagy inhibition can stimulate OA development. Thus, we aimed to investigate the role of insulin in the inflammatory phenotype and autophagy of FLSs in OA. The data showed that cell viability and proinflammatory cytokine production in FLSs were both increased after insulin stimulation. We also found that high insulin could promote macrophage infiltration and chemokine production but inhibited autophagy in FLSs. To further explore the potential mechanisms, the effects of insulin on PI3K/Akt/mTOR and NF-ĸB signaling activation were evaluated. The results indicated that insulin activated PI3K/Akt/mTOR/NF-ĸB signaling, and the above-mentioned inflammatory responses, including autophagy inhibition, were notably attenuated by specific signaling inhibitors in the presence of high insulin. Moreover, the data showed that a positive feedback loop existed between proinflammatory cytokines (e.g., IL-1β, IL-6, and TNF-α) and PI3K/mTOR/Akt/NF-ĸB signaling in FLSs, and insulin enhanced this feedback loop to accelerate OA progression. Our study suggests that insulin may be a novel therapeutic strategy for OA prevention and treatment in the future.

Rapid Enzyme-Mediated Biotinylation for Cell Surface Proteome Profiling

Cell surface is the primary site for sensing extracellular stimuli. The knowledge of the transient changes on the surfaceome upon a perturbation is very important as the initial changed proteins could be driving molecules for some phenotype. In this study, we report a fast cell surface labeling strategy based on peroxidase-mediated oxidative tyrosine coupling strategy, enabling efficient and selective cell surface labeling within seconds. With a labeling time of 1 min, 2684 proteins, including 1370 (51%) cell surface-annotated proteins (cell surface/plasma membrane/extracellular), 732 transmembrane proteins, and 81 cluster of differentiation antigens, were identified from HeLa cells. By comparison with the negative control experiment using quantitative proteomics, 500 (68%) out of the 731 significantly enriched proteins (p-value < 0.05, ≥2-fold) in positive experimental samples were cell surface-annotated proteins. Finally, this technology was applied to track the dynamic changes of the surfaceome upon insulin stimulation at two time points (5 min and 2 h) in HepG2 cells. Thirty-two proteins, including INSR, CTNNB1, TFRC, IGF2R, and SORT1, were found to be significantly regulated (p-value < 0.01, ≥1.5-fold) after insulin exposure by different mechanisms. We envision that this technique could be a powerful tool to analyze the transient changes of the surfaceome with a good time resolution and to delineate the temporal and spatial regulation of cellular signaling.

A predictive model of gene expression reveals the role of network motifs in the mating response of yeast

Cells use signaling pathways to receive and process information about their environment. These nonlinear systems rely on feedback and feedforward regulation to respond appropriately to changing environmental conditions. Mathematical models describing signaling pathways often lack predictive power because they are not trained on data that encompass the diverse time scales on which these regulatory mechanisms operate. We addressed this limitation by measuring transcriptional changes induced by the mating response in Saccharomyces cerevisiae exposed to different dynamic patterns of pheromone. We found that pheromone-induced transcription persisted after pheromone removal and showed long-term adaptation upon sustained pheromone exposure. We developed a model of the regulatory network that captured both characteristics of the mating response. We fit this model to experimental data with an evolutionary algorithm and used the parameterized model to predict scenarios for which it was not trained, including different temporal stimulus profiles and genetic perturbations to pathway components. Our model allowed us to establish the role of four architectural elements of the network in regulating gene expression. These network motifs are incoherent feedforward, positive feedback, negative feedback, and repressor binding. Experimental and computational perturbations to these network motifs established a specific role for each in coordinating the mating response to persistent and dynamic stimulation.

Finding new edges: systems approaches to MTOR signaling

Cells have evolved highly intertwined kinase networks to finely tune cellular homeostasis to the environment. The network converging on the mechanistic target of rapamycin (MTOR) kinase constitutes a central hub that integrates metabolic signals and adapts cellular metabolism and functions to nutritional changes and stress. Feedforward and feedback loops, crosstalks and a plethora of modulators finely balance MTOR-driven anabolic and catabolic processes. This complexity renders it difficult — if not impossible — to intuitively decipher signaling dynamics and network topology. Over the last two decades, systems approaches have emerged as powerful tools to simulate signaling network dynamics and responses. In this review, we discuss the contribution of systems studies to the discovery of novel edges and modulators in the MTOR network in healthy cells and in disease.

Inferring the structures of signaling motifs from paired dynamic traces of single cells

Individual cells show variability in their signaling dynamics that often correlates with phenotypic responses, indicating that cell-to-cell variability is not merely noise but can have functional consequences. Based on this observation, we reasoned that cell-to-cell variability under the same treatment condition could be explained in part by a single signaling motif that maps different upstream signals into a corresponding set of downstream responses. If this assumption holds, then repeated measurements of upstream and downstream signaling dynamics in a population of cells could provide information about the underlying signaling motif for a given pathway, even when no prior knowledge of that motif exists. To test these two hypotheses, we developed a computer algorithm called MISC (Motif Inference from Single Cells) that infers the underlying signaling motif from paired time-series measurements from individual cells. When applied to measurements of transcription factor and reporter gene expression in the yeast stress response, MISC predicted signaling motifs that were consistent with previous mechanistic models of transcription. The ability to detect the underlying mechanism became less certain when a cell's upstream signal was randomly paired with another cell's downstream response, demonstrating how averaging time-series measurements across a population obscures information about the underlying signaling mechanism. In some cases, motif predictions improved as more cells were added to the analysis. These results provide evidence that mechanistic information about cellular signaling networks can be systematically extracted from the dynamical patterns of single cells.

A rate threshold mechanism regulates MAPK stress signaling and survival

Cells are exposed to changes in extracellular stimulus concentration that vary as a function of rate. However, how cells integrate information conveyed from stimulation rate along with concentration remains poorly understood. Here, we examined how varying the rate of stress application alters budding yeast mitogen-activated protein kinase (MAPK) signaling and cell behavior at the single-cell level. We show that signaling depends on a rate threshold that operates in conjunction with stimulus concentration to determine the timing of MAPK signaling during rate-varying stimulus treatments. We also discovered that the stimulation rate threshold and stimulation rate-dependent cell survival are sensitive to changes in the expression levels of the Ptp2 phosphatase, but not of another phosphatase that similarly regulates osmostress signaling during switch-like treatments. Our results demonstrate that stimulation rate is a regulated determinant of cell behavior and provide a paradigm to guide the dissection of major stimulation rate dependent mechanisms in other systems.

Diverse Cell Stimulation Kinetics Identify Predictive Signal Transduction Models

Computationally understanding the molecular mechanisms that give rise to cell signaling responses upon different environmental, chemical, and genetic perturbations is a long-standing challenge that requires models that fit and predict quantitative responses for new biological conditions. Overcoming this challenge depends not only on good models and detailed experimental data but also on the rigorous integration of both. We propose a quantitative framework to perturb and model generic signaling networks using multiple and diverse changing environments (hereafter "kinetic stimulations") resulting in distinct pathway activation dynamics. We demonstrate that utilizing multiple diverse kinetic stimulations better constrains model parameters and enables predictions of signaling dynamics that would be impossible using traditional dose-response or individual kinetic stimulations. To demonstrate our approach, we use experimentally identified models to predict signaling dynamics in normal, mutated, and drug-treated conditions upon multitudes of kinetic stimulations and quantify which proteins and reaction rates are most sensitive to which extracellular stimulations.

Human cathelicidin antimicrobial peptide LL-37 promotes lymphangiogenesis in lymphatic endothelial cells through the ERK and Akt signaling pathways

LL-37, the only member of the cathelicidin family of cationic antimicrobial peptides in humans has been shown to exhibit a wide variety of biological actions in addition to its antimicrobial activity. However, the lymphangiogenic effect of LL-37 has not been elucidated yet. In this study, we examined the effects of LL-37 on lymphangiogenesis and evaluated the underlying molecular mechanisms. LL-37 treatment significantly increased the migration and tube-like formation of human dermal lymphatic microvascular endothelial cells (HDLECs) and promoted the expression of lymphangiogenic factor in HDLECs. Treatment with LL-37 increased phosphorylation of ERK and Akt proteins in HDLECs, and pretreatment with ERK and Akt inhibitors significantly blocked the LL-37-induced HDLEC migration and tube-like formation. Furthermore, to investigate the involvement of formyl peptide receptor-like 1 (FPRL1) signaling in LL-37-induced lymphangiogenesis, HDLECs were treated with an FPRL1 antagonist. Pretreatment with the FPRL1 antagonist inhibited LL-37-induced phosphorylation of ERK and Akt proteins and attenuated LL-37-induced HDLEC migration and tube-like formation. These data indicated that LL-37 induces lymphangiogenesis in lymphatic endothelial cells via FPRL1, and the activation of the ERK and Akt-dependent signaling pathways.

From insulin to Akt: Time delays and dominant processes

Akt/PKB regulates numerous processes in the mammalian cell, including cell survival and proliferation, and glucose uptake in response to insulin. Abnormalities in Akt signalling are linked to the development of Type 2 diabetes, cardio-vascular disease, and cancer. In the absence of insulin, Akt is predominantly found in the inactive state in the cytosol. Following insulin stimulation, Akt translocates to the plasma membrane, docks, and is phosphorylated to take on the active conformation. In turn, the activated Akt travels to and phosphorylates its many downstream substrates. Although crucial to the activation process, the translocation of Akt from the cytosol to the plasma membrane is currently not well understood. Here we detail the parameter optimisation of a mathematical model of Akt translocation to experimental data. We have quantified the time delay between the application of insulin and the downstream Akt translocation response, indicating the constraints on the timing of the intermediate processes. A delay of approximately 0.4 min prior to the Akt response was determined for the application of 1 nM insulin to cells in the basal state, whereas it was found that a further transition from physiological insulin to higher stimuli did not incur a delay. Furthermore, our investigation indicates that the dominant processes regulating the appearance of Akt at the plasma membrane differ with the insulin level. For physiological insulin, the rate limiting step was the release of Akt to the plasma membrane in response to the insulin signal. In contrast, at high insulin levels, regulation of the recycling of Akt from the plasma membrane to the cytosol was also required.

Control of Akt activity and substrate phosphorylation in cells

Protein kinase B/Akt is a serine/threonine kinase that links receptors coupled to the PI3K lipid kinase to cellular anabolic pathways. Its activity in cells is controlled by reversible phosphorylation and an intramolecular lipid-controlled allosteric switch. In this review, I outline the current progress in understanding Akt regulatory mechanisms, define three models of Akt activation in cells, and highlight how intramolecular allosterism cooperates with cell-autonomous mechanisms to control Akt localization and activity and direct it toward specific sets of substrates in cells.

Cracking the context-specific PI3K signaling code

Specificity in signal transduction is determined by the ability of cells to "encode" and subsequently "decode" different environmental signals. Akin to computer software, this "signaling code" governs context-dependent execution of cellular programs through modulation of signaling dynamics and can be corrupted by disease-causing mutations. Class IA phosphoinositide 3-kinase (PI3K) signaling is critical for normal growth and development and is dysregulated in human disorders such as benign overgrowth syndromes, cancer, primary immune deficiency, and metabolic syndrome. Despite decades of PI3K research, understanding of context-dependent regulation of the PI3K pathway and of the underlying signaling code remains rudimentary. Here, we review current knowledge on context-specific PI3K signaling and how technological advances now make it possible to move from a qualitative to quantitative understanding of this pathway. Insight into how cellular PI3K signaling is encoded or decoded may open new avenues for rational pharmacological targeting of PI3K-associated diseases. The principles of PI3K context-dependent signal encoding and decoding described here are likely applicable to most, if not all, major cell signaling pathways.

Angiotensin-converting enzyme 2 regulates endoplasmic reticulum stress and mitochondrial function to preserve skeletal muscle lipid metabolism

Objective

Endoplasmic reticulum (ER) stress and mitochondrial function affected intramuscular fat accumulation. However, there is no clear evident on the effect of the regulation of ER stress and mitochondrial function by Angiotensin-converting enzyme 2 (ACE2) on the prevention of intramuscular fat metabolism. We investigated the effects of ACE2 on ER stress and mitochondrial function in skeletal muscle lipid metabolism.

Methods

The triglyceride (TG) content in skeletal muscle of ACE2 knockout mice and Ad-ACE2-treated db/db mice were detected by assay kits. Meanwhile, the expression of lipogenic genes (ACCα, SREBP-1c, LXRα, CPT-1α, PGC-1α and PPARα), ER stress and mitochondrial function related genes (GRP78, eIF2α, ATF4, BCL-2, and SDH6) were analyzed by RT-PCR. Lipid metabolism, ER stress and mitochondrial function related genes were analyzed by RT-PCR in ACE2-overexpression C2C12 cell. Moreover, the IKKβ/NFκB/IRS-1 pathway was determined using lysate sample from skeletal muscle of ACE2 knockout mice.

Results

ACE2 deficiency in vivo is associated with increased lipid accumulation in skeletal muscle. The ACE2 knockout mice displayed an elevated level of ER stress and mitochondrial dysfunctions in skeletal muscle. In contrast, activation of ACE2 can ameliorate ER stress and mitochondrial function, which slightly accompanied by reduced TG content and down-regulated the expression of skeletal muscle lipogenic proteins in the db/db mice. Additionally, ACE2 improved skeletal muscle lipid metabolism and ER stress genes in the C2C12 cells. Mechanistically, endogenous ACE2 improved lipid metabolism through the IKKβ/NFκB/IRS-1 pathway in skeletal muscle.

Conclusions

ACE2 was first reported to play a notable role on intramuscular fat regulation by improving endoplasmic reticulum and mitochondrial function. This study may provide a strategy for treating insulin resistance in skeletal muscle.

Serine 474 phosphorylation is essential for maximal Akt2 kinase activity in adipocytes

The Ser/Thr protein kinase Akt regulates essential biological processes such as cell survival, growth, and metabolism. Upon growth factor stimulation, Akt is phosphorylated at Ser⁴⁷⁴; however, how this phosphorylation contributes to Akt activation remains controversial. Previous studies, which induced loss of Ser⁴⁷⁴ phosphorylation by ablating its upstream kinase mTORC2, have implicated Ser⁴⁷⁴ phosphorylation as a driver of Akt substrate specificity. Here we directly studied the role of Akt2 Ser⁴⁷⁴ phosphorylation in 3T3-L1 adipocytes by preventing Ser⁴⁷⁴ phosphorylation without perturbing mTORC2 activity. This was achieved by utilizing a chemical genetics approach, where ectopically expressed S474A Akt2 was engineered with a W80A mutation to confer resistance to the Akt inhibitor MK2206, and thus allow its activation independent of endogenous Akt. We found that insulin-stimulated phosphorylation of four bona fide Akt substrates (TSC2, PRAS40, FOXO1/3a, and AS160) was reduced by ∼50% in the absence of Ser⁴⁷⁴ phosphorylation. Accordingly, insulin-stimulated mTORC1 activation, protein synthesis, FOXO nuclear exclusion, GLUT4 translocation, and glucose uptake were attenuated upon loss of Ser⁴⁷⁴ phosphorylation. We propose a model where Ser⁴⁷⁴ phosphorylation is required for maximal Akt2 kinase activity in adipocytes.

Generating kinetic environments to study dynamic cellular processes in single cells

Cells of any organism are consistently exposed to changes over time in their environment. The kinetics by which these changes occur are critical for the cellular response and fate decision. It is therefore important to control the temporal changes of extracellular stimuli precisely to understand biological mechanisms in a quantitative manner. Most current cell culture and biochemical studies focus on instant changes in the environment and therefore neglect the importance of kinetic environments. To address these shortcomings, we developed two experimental methodologies to precisely control the environment of single cells. These methodologies are compatible with standard biochemistry, molecular, cell and quantitative biology assays. We demonstrate applicability by obtaining time series and time point measurements in both live and fixed cells. We demonstrate the feasibility of the methodology in yeast and mammalian cell culture in combination with widely used assays such as flow cytometry, time-lapse microscopy and single-molecule RNA Fluorescent in-situ Hybridization (smFISH). Our experimental methodologies are easy to implement in most laboratory settings and allows the study of kinetic environments in a wide range of assays and different cell culture conditions.

From sugar to liver fat and public health: systems biology driven studies in understanding non-alcoholic fatty liver disease pathogenesis

Non-alcoholic fatty liver disease (NAFLD) is now a major public health concern with an estimated prevalence of 25-30% of adults in many countries. Strongly associated with obesity and the metabolic syndrome, the pathogenesis of NAFLD is dependent on complex interactions between genetic and environmental factors that are not completely understood. Weight loss through diet and lifestyle modification underpins clinical management; however, the roles of individual dietary nutrients (e.g. saturated and n-3 fatty acids; fructose, vitamin D, vitamin E) in the pathogenesis or treatment of NAFLD are only partially understood. Systems biology offers valuable interdisciplinary methods that are arguably ideal for application to the studying of chronic diseases such as NAFLD, and the roles of nutrition and diet in their molecular pathogenesis. Although present in silico models are incomplete, computational tools are rapidly evolving and human metabolism can now be simulated at the genome scale. This paper will review NAFLD and its pathogenesis, including the roles of genetics and nutrition in the development and progression of disease. In addition, the paper introduces the concept of systems biology and reviews recent work utilising genome-scale metabolic networks and developing multi-scale models of liver metabolism relevant to NAFLD. A future is envisioned where individual genetic, proteomic and metabolomic information can be integrated computationally with clinical data, yielding mechanistic insight into the pathogenesis of chronic diseases such as NAFLD, and informing personalised nutrition and stratified medicine approaches for improving prognosis.

Getting the Akt Together: Guiding Intracellular Akt Activity by PI3K

Intracellular signaling pathways mediate the rapid response of cells to environmental cues. To control the fidelity of these responses, cells coordinate the activities of signaling enzymes with the strength, timing, and localization of the upstream stimuli. Protein kinase Akt links the PI3K-coupled receptors to cellular anabolic processes by phosphorylating multiple substrates. How the cells ensure that Akt activity remains proportional to upstream signals and control its substrate specificity is unclear. In this review, I examine how cell-autonomous and intrinsic allosteric mechanisms cooperate to ensure localized, context-specific signaling in the PI3K/Akt axis.

Reconstruction of global regulatory network from signaling to cellular functions using phosphoproteomic data

Cellular signaling regulates various cellular functions via protein phosphorylation. Phosphoproteomic data potentially include information for a global regulatory network from signaling to cellular functions, but a procedure to reconstruct this network using such data has yet to be established. In this paper, we provide a procedure to reconstruct a global regulatory network from signaling to cellular functions from phosphoproteomic data by integrating prior knowledge of cellular functions and inference of the kinase-substrate relationships (KSRs). We used phosphoproteomic data from insulin-stimulated Fao hepatoma cells and identified protein phosphorylation regulated by insulin specifically over-represented in cellular functions in the KEGG database. We inferred kinases for protein phosphorylation by KSRs, and connected the kinases in the insulin signaling layer to the phosphorylated proteins in the cellular functions, revealing that the insulin signal is selectively transmitted via the Pi3k-Akt and Erk signaling pathways to cellular adhesions and RNA maturation, respectively. Thus, we provide a method to reconstruct global regulatory network from signaling to cellular functions based on phosphoproteomic data.

Crosstalk in transition: the translocation of Akt

Akt/PKB is an important crosstalk node at the junction between a number of major signalling pathways in the mammalian cell. As a significant nutrient sensor, Akt plays a central role in many cellular processes, including cell growth, cell survival and glucose metabolism. The dysregulation of Akt signalling is implicated in the development of many diseases, from diabetes to cancer. The translocation of Akt from cytosol to plasma membrane is a crucial step in Akt activation. Akt is initially synthesized on the endoplasmic reticulum, but translocates to the plasma membrane (PM) in response to insulin stimulation, where it may be activated. The Akt is then recycled to the cytoplasm. The activated Akt may propagate signals to downstream substrates both at the PM and in the cytosol, hence understanding the translocation dynamics is an important step in dissecting the signalling system. At the present time, however, knowledge concerning the translocation of either activated and unactivated Akt is scant. Here we present a simple, deterministic, three-compartment ordinary differential equation model of Akt translocation in vitro. This model can reproduce the salient features of Akt translocation in a manner consistent with the experimental data. Furthermore, we demonstrate that this system is equivalent to a damped harmonic oscillator, and analyse the steady state and transient behaviour of the model over the entire parameter space.

Trans-omic Analysis Reveals Selective Responses to Induced and Basal Insulin across Signaling, Transcriptional, and Metabolic Networks

The concentrations of insulin selectively regulate multiple cellular functions. To understand how insulin concentrations are interpreted by cells, we constructed a trans-omic network of insulin action in FAO hepatoma cells using transcriptomic data, western blotting analysis of signaling proteins, and metabolomic data. By integrating sensitivity into the trans-omic network, we identified the selective trans-omic networks stimulated by high and low doses of insulin, denoted as induced and basal insulin signals, respectively. The induced insulin signal was selectively transmitted through the pathway involving Erk to an increase in the expression of immediate-early and upregulated genes, whereas the basal insulin signal was selectively transmitted through a pathway involving Akt and an increase of Foxo phosphorylation and a reduction of downregulated gene expression. We validated the selective trans-omic network in vivo by analysis of the insulin-clamped rat liver. This integrated analysis enabled molecular insight into how liver cells interpret physiological insulin signals to regulate cellular functions.

Investigation of Novel Regulation of N-myristoyltransferase by Mammalian Target of Rapamycin in Breast Cancer Cells

Breast cancer is the most common cancer in women worldwide. Hormone receptor breast cancers are the most common ones and, about 2 out of every 3 cases of breast cancer are estrogen receptor (ER) positive. Selective ER modulators, such as tamoxifen, are the first line of endocrine treatment of breast cancer. Despite the expression of hormone receptors some patients develop tamoxifen resistance and 50% present de novo tamoxifen resistance. Recently, we have demonstrated that activated mammalian target of rapamycin (mTOR) is positively associated with overall survival and recurrence free survival in ER positive breast cancer patients who were later treated with tamoxifen. Since altered expression of protein kinase B (PKB)/Akt in breast cancer cells affect N-myristoyltransferase 1 (NMT1) expression and activity, we investigated whether mTOR, a downstream target of PKB/Akt, regulates NMT1 in ER positive breast cancer cells (MCF7 cells). We inhibited mTOR by treating MCF7 cells with rapamycin and observed that the expression of NMT1 increased with rapamycin treatment over the period of time with a concomitant decrease in mTOR phosphorylation. We further employed mathematical modelling to investigate hitherto not known relationship of mTOR with NMT1. We report here for the first time a collection of models and data validating regulation of NMT1 by mTOR.

Multi-scale, whole-system models of liver metabolic adaptation to fat and sugar in non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is a serious public health issue associated with high fat, high sugar diets. However, the molecular mechanisms mediating NAFLD pathogenesis are only partially understood. Here we adopt an iterative multi-scale, systems biology approach coupled to in vitro experimentation to investigate the roles of sugar and fat metabolism in NAFLD pathogenesis. The use of fructose as a sweetening agent is controversial; to explore this, we developed a predictive model of human monosaccharide transport, signalling and metabolism. The resulting quantitative model comprising a kinetic model describing monosaccharide transport and insulin signalling integrated with a hepatocyte-specific genome-scale metabolic network (GSMN). Differential kinetics for the utilisation of glucose and fructose were predicted, but the resultant triacylglycerol production was predicted to be similar for monosaccharides; these predictions were verified by in vitro data. The role of physiological adaptation to lipid overload was explored through the comprehensive reconstruction of the peroxisome proliferator activated receptor alpha (PPARα) regulome integrated with a hepatocyte-specific GSMN. The resulting qualitative model reproduced metabolic responses to increased fatty acid levels and mimicked lipid loading in vitro. The model predicted that activation of PPARα by lipids produces a biphasic response, which initially exacerbates steatosis. Our data support the evidence that it is the quantity of sugar rather than the type that is critical in driving the steatotic response. Furthermore, we predict PPARα-mediated adaptations to hepatic lipid overload, shedding light on potential challenges for the use of PPARα agonists to treat NAFLD.

In Vivo Decoding Mechanisms of the Temporal Patterns of Blood Insulin by the Insulin-AKT Pathway in the Liver

Cells respond to various extracellular stimuli through a limited number of signaling pathways. One strategy to process such stimuli is to code the information into the temporal patterns of molecules. Although we showed that insulin selectively regulated molecules depending on its temporal patterns using Fao cells, the in vivo mechanism remains unknown. Here, we show how the insulin-AKT pathway processes the information encoded into the temporal patterns of blood insulin. We performed hyperinsulinemic-euglycemic clamp experiments and found that, in the liver, all temporal patterns of insulin are encoded into the insulin receptor, and downstream molecules selectively decode them through AKT. S6K selectively decodes the additional secretion information. G6Pase interprets the basal secretion information through FoxO1, while GSK3β decodes all secretion pattern information. Mathematical modeling revealed the mechanism via differences in network structures and from sensitivity and time constants. Given that almost all hormones exhibit distinct temporal patterns, temporal coding may be a general principle of system homeostasis by hormones.

Serine Phosphorylation by mTORC1 Promotes IRS-1 Degradation through SCFβ-TRCP E3 Ubiquitin Ligase

The insulin receptor substrate IRS-1 is a key substrate of insulin and insulin-like growth factor (IGF) receptor tyrosine kinases that mediates their metabolic and growth-promoting actions. Proteasomal degradation of IRS-1 is induced following activation of the downstream kinase mTOR complex 1 (mTORC1) to constitute a negative feedback loop. However, the underlying mechanism remains poorly understood. Here we report that Ser 422 of IRS-1 is phosphorylated by mTORC1 and required for IRS-1 degradation induced by prolonged IGF stimulation. Phosphorylation of Ser 422 then recruits the SCF^β-TRCP E3 ligase complex, which catalyzes IRS-1 ubiquitination. Phosphorylation-dependent IRS-1 degradation contributes to impaired growth and survival responses to IGF in cells lacking TSC2, a negative regulator of mTORC1. Inhibition of IRS-1 degradation promotes sustained Akt activation in IGF-stimulated cells. Our work clarifies the nature of the IRS-1-mTORC1 feedback loop and elucidates its role in temporal regulation of IGF signaling.

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Ser 422 of IRS-1 is identified as a phosphorylation site by mTORC1

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Phosphorylation of Ser 422 induces the binding of SCF β-TRCP E3 ligase to IRS-1

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Ser 422 phosphorylation triggers the SCF β-TRCP-mediated degradation of IRS-1

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The IRS-1-mTORC1 negative feedback loop determines the duration of IGF signaling

PI3K, p38 and JAK/STAT signalling in bronchial tissue from patients with asthma following allergen challenge

Background

Inhaled allergen challenges are often used to evaluate novel asthma treatments in early phase clinical trials. Current novel therapeutic targets in asthma include phosphoinositide 3-kinases (PI3K) delta and gamma, p38 mitogen-activated protein kinase (p38) and Janus kinase/Signal Transducer and Activator of Transcription (JAK/STAT) signalling pathways. The activation of these pathways following allergen exposure in atopic asthma patients it is not known.

Methods

We collected bronchial biopsies from 11 atopic asthma patients at baseline and after allergen challenge to investigate biomarkers of PI3K, p38 MAPK and JAK/STAT activation by immunohistochemistry. Cell counts and levels of eosinophil cationic protein and interleukin-5 were also assessed in sputum and bronchoalvelar lavage.

Results

Biopsies collected post-allergen had an increased percentage of epithelial cells expressing phospho-p38 (17.5 vs 25.6%, p = 0.04), and increased numbers of sub-epithelial cells expressing phospho-STAT5 (122.2 vs 540.6 cells/mm², p = 0.01) and the PI3K marker phospho-ribosomal protein S6 (180.7 vs 777.3 cells/mm^2,p = 0.005). Type 2 inflammation was increased in the airways post allergen, with elevated levels of eosinophils, interleukin-5 and eosinophil cationic protein.

Conclusions

Future clinical trials of novel kinase inhibitors could use the allergen challenge model in proof of concept studies, while employing these biomarkers to investigate pharmacological inhibition in the lungs.

IRS-1 acts as an endocytic regulator of IGF-I receptor to facilitate sustained IGF signaling

Insulin-like growth factor-I receptor (IGF-IR) preferentially regulates the long-term IGF activities including growth and metabolism. Kinetics of ligand-dependent IGF-IR endocytosis determines how IGF induces such downstream signaling outputs. Here, we find that the insulin receptor substrate (IRS)-1 modulates how long ligand-activated IGF-IR remains at the cell surface before undergoing endocytosis in mammalian cells. IRS-1 interacts with the clathrin adaptor complex AP2. IRS-1, but not an AP2-binding-deficient mutant, delays AP2-mediated IGF-IR endocytosis after the ligand stimulation. Mechanistically, IRS-1 inhibits the recruitment of IGF-IR into clathrin-coated structures; for this reason, IGF-IR avoids rapid endocytosis and prolongs its activity on the cell surface. Accelerating IGF-IR endocytosis via IRS-1 depletion induces the shift from sustained to transient Akt activation and augments FoxO-mediated transcription. Our study establishes a new role for IRS-1 as an endocytic regulator of IGF-IR that ensures sustained IGF bioactivity, independent of its classic role as an adaptor in IGF-IR signaling.

Optogenetically controlled protein kinases for regulation of cellular signaling

Protein kinases are involved in the regulation of many cellular processes including cell differentiation, survival, migration, axon guidance and neuronal plasticity. A growing set of optogenetic tools, termed opto-kinases, allows activation and inhibition of different protein kinases with light. The optogenetic regulation enables fast, reversible and non-invasive manipulation of protein kinase activities, complementing traditional methods, such as treatment with growth factors, protein kinase inhibitors or chemical dimerizers. In this review, we summarize the properties of the existing optogenetic tools for controlling tyrosine kinases and serine-threonine kinases. We discuss how the opto-kinases can be applied for studies of spatial and temporal aspects of protein kinase signaling in cells and organisms. We compare approaches for chemical and optogenetic regulation of protein kinase activity and present guidelines for selection of opto-kinases and equipment to control them with light. We also describe strategies to engineer novel opto-kinases on the basis of various photoreceptors.

Increase in hepatic and decrease in peripheral insulin clearance characterize abnormal temporal patterns of serum insulin in diabetic subjects

Insulin plays a central role in glucose homeostasis, and impairment of insulin action causes glucose intolerance and leads to type 2 diabetes mellitus (T2DM). A decrease in the transient peak and sustained increase of circulating insulin following an infusion of glucose accompany T2DM pathogenesis. However, the mechanism underlying this abnormal temporal pattern of circulating insulin concentration remains unknown. Here we show that changes in opposite direction of hepatic and peripheral insulin clearance characterize this abnormal temporal pattern of circulating insulin concentration observed in T2DM. We developed a mathematical model using a hyperglycemic and hyperinsulinemic-euglycemic clamp in 111 subjects, including healthy normoglycemic and diabetic subjects. The hepatic and peripheral insulin clearance significantly increase and decrease, respectively, from healthy to borderline type and T2DM. The increased hepatic insulin clearance reduces the amplitude of circulating insulin concentration, whereas the decreased peripheral insulin clearance changes the temporal patterns of circulating insulin concentration from transient to sustained. These results provide further insight into the pathogenesis of T2DM, and thus may contribute to develop better treatment of this condition.

Type 2 diabetes mellitus (T2DM) is one of the fastest growing public health problems, characterized by chronic hyperglycemia with the failure of glucose homeostasis. Evaluating alteration in biological functions regulating circulating glucose concentration is complicated due to the mutual relation between circulating glucose and insulin. A team led by Wataru Ogawa at Kobe University designed clinical experiments for breaking such feedback relations, and a team led by Shinya Kuroda at University of Tokyo developed mathematical models for specifically quantifying the functions from the clinical data. The estimated model parameters revealed the significant increase in hepatic and decrease in peripheral insulin clearance, which occur before and after insulin delivery into systemic circulation, respectively, from healthy to T2DM subjects. Model analysis suggested these insulin clearances centrally regulate the dynamics of circulating insulin concentration in the glucose-insulin regulatory system.

Cancerous perturbations within the ERK, PI3K/Akt, and Wnt/β-catenin signaling network constitutively activate inter-pathway positive feedback loops

Perturbations in molecular signaling pathways are a result of genetic or epigenetic alterations, which may lead to malignant transformation of cells. Despite cellular robustness, specific genetic or epigenetic changes of any gene can trigger a cascade of failures, which result in the malfunctioning of cell signaling pathways and lead to cancer phenotypes. The extent of cellular robustness has a link with the architecture of the network such as feedback and feedforward loops. Perturbation in components within feedback loops causes a transition from a regulated to a persistently activated state and results in uncontrolled cell growth. This work represents the mathematical and quantitative modeling of ERK, PI3K/Akt, and Wnt/β-catenin signaling crosstalk to show the dynamics of signaling responses during genetic and epigenetic changes in cancer. ERK, PI3K/Akt, and Wnt/β-catenin signaling crosstalk networks include both intra and inter-pathway feedback loops which function in a controlled fashion in a healthy cell. Our results show that cancerous perturbations of components such as EGFR, Ras, B-Raf, PTEN, and components of the destruction complex cause extreme fragility in the network and constitutively activate inter-pathway positive feedback loops. We observed that the aberrant signaling response due to the failure of specific network components is transmitted throughout the network via crosstalk, generating an additive effect on cancer growth and proliferation.

Multidimensional biochemical information processing of dynamical patterns

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Biochemical and cellular properties of insulin receptor signalling

The mechanism of insulin action is a central theme in biology and medicine. In addition to the rather rare condition of insulin deficiency caused by autoimmune destruction of pancreatic β-cells, genetic and acquired abnormalities of insulin action underlie the far more common conditions of type 2 diabetes, obesity and insulin resistance. The latter predisposes to diseases ranging from hypertension to Alzheimer disease and cancer. Hence, understanding the biochemical and cellular properties of insulin receptor signalling is arguably a priority in biomedical research. In the past decade, major progress has led to the delineation of mechanisms of glucose transport, lipid synthesis, storage and mobilization. In addition to direct effects of insulin on signalling kinases and metabolic enzymes, the discovery of mechanisms of insulin-regulated gene transcription has led to a reassessment of the general principles of insulin action. These advances will accelerate the discovery of new treatment modalities for diabetes.

PI(3,4,5)P3 Engagement Restricts Akt Activity to Cellular Membranes

Protein kinase B/Akt regulates cellular metabolism, survival, and proliferation in response to hormones and growth factors. Hyperactivation of Akt is frequently observed in cancer, while Akt inactivation is associated with severe diabetes. Here, we investigated the molecular and cellular mechanisms that maintain Akt activity proportional to the activating stimulus. We show that binding of phosphatidylinositol-3,4,5-trisphosphate (PIP₃) or PI(3,4)P₂ to the PH domain allosterically activates Akt by promoting high-affinity substrate binding. Conversely, dissociation from PIP₃ was rate limiting for Akt dephosphorylation, dependent on the presence of the PH domain. In cells, active Akt associated primarily with cellular membranes. In contrast, a transforming mutation that uncouples kinase activation from PIP₃ resulted in the accumulation of hyperphosphorylated, active Akt in the cytosol. Our results suggest that intramolecular allosteric and cellular mechanisms cooperate to restrict Akt activity to cellular membranes, thereby enhancing the fidelity of Akt signaling and the specificity of downstream substrate phosphorylation.

Understanding the mTOR signaling pathway via mathematical modeling

The mechanistic target of rapamycin (mTOR) is a central regulatory pathway that integrates a variety of environmental cues to control cellular growth and homeostasis by intricate molecular feedbacks. In spite of extensive knowledge about its components, the molecular understanding of how these function together in space and time remains poor and there is a need for Systems Biology approaches to perform systematic analyses. In this work, we review the recent progress how the combined efforts of mathematical models and quantitative experiments shed new light on our understanding of the mTOR signaling pathway. In particular, we discuss the modeling concepts applied in mTOR signaling, the role of multiple feedbacks and the crosstalk mechanisms of mTOR with other signaling pathways. We also discuss the contribution of principles from information and network theory that have been successfully applied in dissecting design principles of the mTOR signaling network. We finally propose to classify the mTOR models in terms of the time scale and network complexity, and outline the importance of the classification toward the development of highly comprehensive and predictive models. WIREs Syst Biol Med 2017, 9:e1379. doi: 10.1002/wsbm.1379 For further resources related to this article, please visit the WIREs website.

An improved Akt reporter reveals intra- and inter-cellular heterogeneity and oscillations in signal transduction

Akt is a key node in a range of signal transduction cascades and play a critical role in diseases such as cancer and diabetes. Fluorescently-tagged Akt reporters have been used to discern Akt localisation, yet it has not been clear how well these tools recapitulate the behaviour of endogenous Akt proteins. Here, we observed that fusion of eGFP to Akt2 impaired both its insulin-stimulated plasma membrane recruitment and its phosphorylation. Endogenous-like responses were restored by replacing eGFP with TagRFP-T. The improved response magnitude and sensitivity afforded by TagRFP-T-Akt2 over eGFP-Akt2 enabled monitoring of signalling outcomes in single cells at physiological doses of insulin with subcellular resolution and revealed two previously unreported features of Akt biology. In 3T3-L1 adipocytes, stimulation with insulin resulted in recruitment of Akt2 to the plasma membrane in a polarised fashion. Additionally, we observed oscillations in plasma membrane localised Akt2 in the presence of insulin with a consistent periodicity of 2 min. Our studies highlight the importance of fluorophore choice when generating reporter constructs and shed light on new Akt signalling responses that may encode complex signalling information.This article has an associated First Person interview with the first author of the paper.