A dynamic network model of mTOR signaling reveals TSC-independent mTORC2 regulation

The paradox of fatty-acid β-oxidation in muscle insulin resistance: Metabolic control and muscle heterogeneity

The skeletal muscle is a metabolically heterogeneous tissue that plays a key role in maintaining whole-body glucose homeostasis. It is well known that muscle insulin resistance (IR) precedes the development of type 2 diabetes. There is a consensus that the accumulation of specific lipid species in the tissue can drive IR. However, the role of the mitochondrial fatty-acid β-oxidation in IR and, consequently, in the control of glucose uptake remains paradoxical: interventions that either inhibit or activate fatty-acid β-oxidation have been shown to prevent IR. We here discuss the current theories and evidence for the interplay between β-oxidation and glucose uptake in IR. To address the underlying intricacies, we (1) dive into the control of glucose uptake fluxes into muscle tissues using the framework of Metabolic Control Analysis, and (2) disentangle concepts of flux and catalytic capacities taking into account skeletal muscle heterogeneity. Finally, we speculate about hitherto unexplored mechanisms that could bring contrasting evidence together. Elucidating how β-oxidation is connected to muscle IR and the underlying role of muscle heterogeneity enhances disease understanding and paves the way for new treatments for type 2 diabetes.

The mTORC2 signaling network: targets and cross-talks

The mechanistic target of rapamycin, mTOR, controls cell metabolism in response to growth signals and stress stimuli. The cellular functions of mTOR are mediated by two distinct protein complexes, mTOR complex 1 (mTORC1) and mTORC2. Rapamycin and its analogs are currently used in the clinic to treat a variety of diseases and have been instrumental in delineating the functions of its direct target, mTORC1. Despite the lack of a specific mTORC2 inhibitor, genetic studies that disrupt mTORC2 expression unravel the functions of this more elusive mTOR complex. Like mTORC1 which responds to growth signals, mTORC2 is also activated by anabolic signals but is additionally triggered by stress. mTORC2 mediates signals from growth factor receptors and G-protein coupled receptors. How stress conditions such as nutrient limitation modulate mTORC2 activation to allow metabolic reprogramming and ensure cell survival remains poorly understood. A variety of downstream effectors of mTORC2 have been identified but the most well-characterized mTORC2 substrates include Akt, PKC, and SGK, which are members of the AGC protein kinase family. Here, we review how mTORC2 is regulated by cellular stimuli including how compartmentalization and modulation of complex components affect mTORC2 signaling. We elaborate on how phosphorylation of its substrates, particularly the AGC kinases, mediates its diverse functions in growth, proliferation, survival, and differentiation. We discuss other signaling and metabolic components that cross-talk with mTORC2 and the cellular output of these signals. Lastly, we consider how to more effectively target the mTORC2 pathway to treat diseases that have deregulated mTOR signaling.

Insulin Signaling Pathway Model in Adipocyte Cells

BACKGROUND

Worldwide, type 2 diabetes mellitus (T2DM) is one of the most pervasive and fastgrowing disorders, bringing long-term adverse effects. T2DM arises from pancreatic β-cells deficiency to produce enough insulin or when the body cannot effectively use the insulin produced by such cells. Accordingly, early diagnosis will decrease the long-term effects and high-healthcare costs of diabetes.

OBJECTIVE

The objective is developing an integrated mathematical model of the insulin signaling network based on Brännmark's model, which can simulate the signaling events more comprehensively with the added key components.

METHODS

In this study, a thorough mathematical model of the insulin signaling network was developed by expanding the previously validated model and incorporating the glycogen synthesis module. Parameters (69 parameters) of the integrated model were evaluated by a genetic algorithm by fitting the model predictions to eighty percent of experimental data from the literature. Twenty percent of the experimental data were used to evaluate the final optimized model.

RESULTS

The time-response curves indicate that the GS phosphorylation reaches its maximum in response to 10^-7 M insulin after 4 min, while the maximum phosphorylated GSK3 is attained within ~50 min. The doseresponse curves for the GSP and GSK3 of the insulin signaling intermediaries in response to the increased concentration of insulin, after 10 min, in the input from 0-100 nM exhibits a decreasing trend, whereas an increasing trend was observed for the GS and GSK3P. The GSK and GS phosphorylation sensitivity was enhanced by increasing the initial insulin concentration level from 0.001 to 100 nM. However, the sensitivity of GSK3 to insulin concentration changes (from 0.001 to 100 nM) was 3-fold higher than GS sensitivity.

CONCLUSION

Considerably, the trends of all signaling components simulated by the expanded model shows high compatibility with experimental data (R2 ≥ 0.9), which approves the accuracy of the proposed model. The proposed mathematical model can be used in many biological systems and combined with the whole-body model of the blood glucose regulation system for a better understanding of the causes and potential treatment of type 2 diabetes. Although, this model is not a complete description of insulin signaling, yet it can make profound contributions to improvements regarding other important components and signaling branches such as epidermal growth factor (EGF) signaling, as well as signaling in other cell types in the model structure of future works.

A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling

Mechanistic models of how single cells respond to different perturbations can help integrate disparate big data sets or predict response to varied drug combinations. However, the construction and simulation of such models have proved challenging. Here, we developed a python-based model creation and simulation pipeline that converts a few structured text files into an SBML standard and is high-performance- and cloud-computing ready. We applied this pipeline to our large-scale, mechanistic pan-cancer signaling model (named SPARCED) and demonstrate it by adding an IFNγ pathway submodel. We then investigated whether a putative crosstalk mechanism could be consistent with experimental observations from the LINCS MCF10A Data Cube that IFNγ acts as an anti-proliferative factor. The analyses suggested this observation can be explained by IFNγ-induced SOCS1 sequestering activated EGF receptors. This work forms a foundational recipe for increased mechanistic model-based data integration on a single-cell level, an important building block for clinically-predictive mechanistic models.

The mixed blessing of AMPK signaling in Cancer treatments

Background

Nutrient acquisition and metabolism pathways are altered in cancer cells to meet bioenergetic and biosynthetic demands. A major regulator of cellular metabolism and energy homeostasis, in normal and cancer cells, is AMP-activated protein kinase (AMPK). AMPK influences cell growth via its modulation of the mechanistic target of Rapamycin (mTOR) pathway, specifically, by inhibiting mTOR complex mTORC1, which facilitates cell proliferation, and by activating mTORC2 and cell survival. Given its conflicting roles, the effects of AMPK activation in cancer can be counter intuitive. Prior to the establishment of cancer, AMPK acts as a tumor suppressor. However, following the onset of cancer, AMPK has been shown to either suppress or promote cancer, depending on cell type or state.

Methods

To unravel the controversial roles of AMPK in cancer, we developed a computational model to simulate the effects of pharmacological maneuvers that target key metabolic signalling nodes, with a specific focus on AMPK, mTORC, and their modulators. Specifically, we constructed an ordinary differential equation-based mechanistic model of AMPK-mTORC signaling, and parametrized the model based on existing experimental data.

Results

Model simulations were conducted to yield the following predictions: (i) increasing AMPK activity has opposite effects on mTORC depending on the nutrient availability; (ii) indirect inhibition of AMPK activity through inhibition of sirtuin 1 (SIRT1) only has an effect on mTORC activity under conditions of low nutrient availability; (iii) the balance between cell proliferation and survival exhibits an intricate dependence on DEP domain-containing mTOR-interacting protein (DEPTOR) abundance and AMPK activity; (iv) simultaneous direct inhibition of mTORC2 and activation of AMPK is a potential strategy for suppressing both cell survival and proliferation.

Conclusions

Taken together, model simulations clarify the competing effects and the roles of key metabolic signalling pathways in tumorigenesis, which may yield insights on innovative therapeutic strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09211-1.

Betulinic Acid Suppresses de novo Lipogenesis by Inhibiting Insulin and IGF1 Signaling as Upstream Effectors of the Nutrient-Sensing mTOR Pathway

Despite its beneficial properties, effects of betulinic acid on the nutrient-sensing mTOR pathway via insulin or IGF1 signaling remain unclear. Here, we investigated whether betulinic acid reduces intracellular lipid accumulation via the nutrient-sensing pathway in HepG2 cells. Results showed that betulinic acid reduced intracellular lipid accumulation in a dose-dependent manner and inhibited the expression of de novo lipogenesis-related genes and proteins. RNA sequencing analysis revealed the transcriptional modulation of plasma membrane proteins by betulinic acid, and an in silico binding assay indicated an interaction between betulinic acid and IR or IGF1R. Furthermore, betulinic acid downregulated the post-translational modification of the canonical IRS1/PI3K/AKT-pT308 and IGF1/mTORC2/AKT-pS473 pathways, thereby reducing the activity of the mTOR/S6K/S6 pathway. These findings imply that betulinic acid suppresses hepatic lipid synthesis by inhibiting insulin and IGF1 signaling as upstream effectors of the nutrient-sensing mTOR pathway and could be a potent nutraceutical agent for the treatment of metabolic syndromes.

Assessment of tantalum nanoparticle-induced MC3T3-E1 proliferation and underlying mechanisms

OBJECTIVE

In our previous study, tantalum nanoparticle (Ta-NPs) was demonstrated to promote osteoblast proliferation via autophagy induction, but the specific mechanism remains unclear. In the present study, we will explore the potential mechanism.

METHODS

Ta-NPs was characterized by transmission electron microscopy, scanning electron microscopy, dynamic light scattering, and BET specific surface area test. MC3T3-E1 were treated with 0 or 20 μg/mL Ta-NPs with or without pretreatment with 10 μM LY294002, Triciribine, Rapamycin (PI3K/Akt/mTOR pathway inhibitors) for 1 h respectively. Western blotting was used to detect the expressions of pathway proteins and LC3B. CCK-8 assay was used to assess cell viability. Flow cytometry was used to detect apoptosis and cell cycle.

RESULTS

After pretreatment with LY294002, Triciribine and Rapamycin, the p-Akt/Akt ratio of pathway protein in Triciribine and Rapamycin groups decreased (P < 0.05), while the autophagy protein LC3-II/LC3-I in the Rapamycin group was upregulated obviously (P < 0.001). In all pretreated groups, apoptosis was increased (LY294002 group was the most obvious), G1 phase cell cycle was arrested (Triciribine and Rapamycin groups were more obvious), and MC3T3-E1 cells were proliferated much more (P < 0.01, P < 0.001, P < 0.05).

CONCLUSION

Pretreatment with Triciribine or Rapamycin has a greater effect on pathway protein Akt, cell cycle arrest, autophagy protein, and cell proliferation but with inconsistent magnitude, which may be inferred that the Akt/mTOR pathway, as well as its feedback loop, were more likely involved in these processes.

Fluctuations in AKT and PTEN Activity Are Linked by the E3 Ubiquitin Ligase cCBL

3-Poly-phosphoinositides (PIP₃) regulate cell survival, division, and migration. Both PI3-kinase (phosphoinositide-3-kinase) and PTEN (phosphatase and tensin-homolog in chromosome 10) control PIP₃ levels, but the mechanisms connecting PI3-kinase and PTEN are unknown. Using non-transformed cells, the activation kinetics of PTEN and of the PIP₃-effector AKT were examined after the addition of growth factors. Both epidermal growth factor and serum induced the early activation of AKT and the simultaneous inactivation of PTEN (at ~5 min). This PIP₃/AKT peak was followed by a general reduction in AKT activity coincident with the recovery of PTEN phosphatase activity (at ~10–15 min). Subsequent AKT peaks and troughs followed. The fluctuation in AKT activity was linked to that of PTEN; PTEN reconstitution in PTEN-null cells restored AKT fluctuations, while PTEN depletion in control cells abrogated them. The analysis of PTEN activity fluctuations after the addition of growth factors showed its inactivation at ~5 min to be simultaneous with its transient ubiquitination, which was regulated by the ubiquitin E3 ligase cCBL (casitas B-lineage lymphoma proto-oncogene). Protein-protein interaction analysis revealed cCBL to be brought into the proximity of PTEN in a PI3-kinase-dependent manner. These results reveal a mechanism for PI3-kinase/PTEN crosstalk and suggest that cCBL could be new target in strategies designed to modulate PTEN activity in cancer.

Dynamic modelling of the PI3K/MTOR signalling network uncovers biphasic dependence of mTORC1 activity on the mTORC2 subunit SIN1

The PI3K/MTOR signalling network regulates a broad array of critical cellular processes, including cell growth, metabolism and autophagy. The mechanistic target of rapamycin (MTOR) kinase functions as a core catalytic subunit in two physically and functionally distinct complexes mTORC1 and mTORC2, which also share other common components including MLST8 (also known as GβL) and DEPTOR. Despite intensive research, how mTORC1 and 2 assembly and activity are coordinated, and how they are functionally linked remain to be fully characterized. This is due in part to the complex network wiring, featuring multiple feedback loops and intricate post-translational modifications. Here, we integrate predictive network modelling, in vitro experiments and -omics data analysis to elucidate the emergent dynamic behaviour of the PI3K/MTOR network. We construct new mechanistic models that encapsulate critical mechanistic details, including mTORC1/2 coordination by MLST8 (de)ubiquitination and the Akt-to-mTORC2 positive feedback loop. Model simulations validated by experimental studies revealed a previously unknown biphasic, threshold-gated dependence of mTORC1 activity on the key mTORC2 subunit SIN1, which is robust against cell-to-cell variation in protein expression. In addition, our integrative analysis demonstrates that ubiquitination of MLST8, which is reversed by OTUD7B, is regulated by IRS1/2. Our results further support the essential role of MLST8 in enabling both mTORC1 and 2’s activity and suggest MLST8 as a viable therapeutic target in breast cancer. Overall, our study reports a new mechanistic model of PI3K/MTOR signalling incorporating MLST8-mediated mTORC1/2 formation and unveils a novel regulatory linkage between mTORC1 and mTORC2.

Signalling networks are the key information-processing machineries that underpin the ability of living cells to respond proportionately to extra- (and intra-) cellular cues. The PI3K/MTOR signalling network is one of the most important signalling networks in human cells that regulates cellular response to critical hormones such as insulin; yet our understanding of the network behaviour remains far from complete. Here, we employed a highly integrative approach that combines predictive mathematical modelling, biological experimentation, and data analysis to gain novel systems-level insights into PI3K/MTOR signalling. We constructed new mathematical models of this complex network incorporating important regulatory mechanisms. In contrary to commonly-held views that mTORC2 lies upstream and is a positive regulator of mTORC1, we found that their relationship is highly non-linear and dose dependent. This finding has major implications for anti-mTORC2 therapy as depending on the cellular contexts, inhibiting mTORC2 may either reduce or enhance mTORC1 activation, the latter could inadvertently dampen the effect of mTORC2 blockade. Furthermore, our results demonstrate that MLST8 is required for the assembly and activity of both MTOR complexes and suggest MLST8 is a viable therapeutic target in breast cancer.

VHL suppresses RAPTOR and inhibits mTORC1 signaling in clear cell renal cell carcinoma

Inactivation of the tumor suppressor von Hippel-Lindau (VHL) gene is a key event in hereditary and sporadic clear cell renal cell carcinomas (ccRCC). The mechanistic target of rapamycin (mTOR) signaling pathway is a fundamental regulator of cell growth and proliferation, and hyperactivation of mTOR signaling is a common finding in VHL-dependent ccRCC. Deregulation of mTOR signaling correlates with tumor progression and poor outcome in patients with ccRCC. Here, we report that the regulatory-associated protein of mTOR (RAPTOR) is strikingly repressed by VHL. VHL interacts with RAPTOR and increases RAPTOR degradation by ubiquitination, thereby inhibiting mTORC1 signaling. Consistent with hyperactivation of mTORC1 signaling in VHL-deficient ccRCC, we observed that loss of vhl-1 function in C. elegans increased mTORC1 activity, supporting an evolutionary conserved mechanism. Our work reveals important new mechanistic insight into deregulation of mTORC1 signaling in ccRCC and links VHL directly to the control of RAPTOR/mTORC1. This may represent a novel mechanism whereby loss of VHL affects organ integrity and tumor behavior.

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.

Emerging Roles of BRD7 in Pathophysiology

Bromodomain is a conserved structural module found in many chromatin-associated proteins. Bromodomain-containing protein 7 (BRD7) is a member of the bromodomain-containing protein family, and was discovered two decades ago as a protein that is downregulated in nasopharyngeal carcinoma. Since then, BRD7 has been implicated in a variety of cellular processes, including chromatin remodeling, transcriptional regulation, and cell cycle progression. Decreased BRD7 activity underlies the pathophysiological properties of various diseases in different organs. BRD7 plays an important role in the pathogenesis of many cancers and, more recently, its roles in the regulation of metabolism and obesity have also been highlighted. Here, we review the involvement of BRD7 in a variety of pathophysiological conditions, with a focus on glucose homeostasis, obesity, and cancer.

Breaking the Interface: Efficient Extraction of Magnetic Beads from Nanoliter Droplets for Automated Sequential Immunoassays

Droplet-based microfluidic systems offer a high potential for miniaturization and automation. Therefore, they are becoming an increasingly important tool in analytical chemistry, biosciences, and medicine. Heterogeneous assays commonly utilize magnetic beads as a solid phase. However, the sensitivity of state of the art microfluidic systems is limited by the high bead concentrations required for efficient extraction across the water-oil interface. Furthermore, current systems suffer from a lack of technical solutions for sequential measurements of multiple samples, limiting their throughput and capacity for automation. Taking advantage of the different wetting properties of hydrophilic and hydrophobic areas in the channels, we improve the extraction efficiency of magnetic beads from aqueous nanoliter-sized droplets by 2 orders of magnitude to the low μg/mL range. Furthermore, the introduction of a switchable magnetic trap enables repetitive capture and release of magnetic particles for sequential analysis of multiple samples, enhancing the throughput. In comparison to conventional ELISA-based sandwich immunoassays on microtiter plates, our microfluidic setup offers a 25-50-fold reduction of sample and reagent consumption with up to 50 technical replicates per sample. The enhanced sensitivity and throughput of this system open avenues for the development of automated detection of biomolecules at the nanoliter scale.

Glucocorticoids Promote the Onset of Acute Experimental Colitis and Cancer by Upregulating mTOR Signaling in Intestinal Epithelial Cells

The therapeutic effects of glucocorticoids on colitis and colitis-associated cancer are unclear. In this study, we investigated the therapeutic roles of glucocorticoids in acute experimental ulcerative colitis and colitis-associated cancer in mice and their immunoregulatory mechanisms. Murine acute ulcerative colitis was induced by dextran sulfate sodium (DSS) and treated with dexamethasone (Dex) at different doses. Dex significantly exacerbated the onset and severity of DSS-induced colitis and potentiated mucosal inflammatory macrophage and neutrophil infiltration, as well as cytokine production. Furthermore, under inflammatory conditions, the expression of the glucocorticoid receptor (GR) did not change significantly, while mammalian target of rapamycin (mTOR) signaling was higher in colonic epithelial cells than in colonic immune cells. The deletion of mTOR in intestinal epithelial cells, but not that in myeloid immune cells, in mice significantly ameliorated the severe course of colitis caused by Dex, including weight loss, clinical score, colon length, pathological damage, inflammatory cell infiltration and pro-inflammatory cytokine production. These data suggest that mTOR signaling in intestinal epithelial cells, mainly mTORC1, plays a critical role in the Dex-induced exacerbation of acute colitis and colitis-associated cancer. Thus, these pieces of evidence indicate that glucocorticoid-induced mTOR signaling in epithelial cells is required in the early stages of acute ulcerative colitis by modulating the dynamics of innate immune cell recruitment and activation.

mTORC2 Signaling Is Necessary for Timely Liver Regeneration after Partial Hepatectomy

Liver regeneration is a fundamental biological process required for sustaining body homeostasis and restoring liver function after injury. Emerging evidence demonstrates that cytokines, growth factors, and multiple signaling pathways contribute to liver regeneration. Mammalian target of rapamycin complex 2 (mTORC2) regulates cell metabolism, proliferation and survival. The major substrates for mTORC2 are the AGC family members of kinases, including AKT, SGK, and PKC-α. We investigated the functional roles of mTORC2 during liver regeneration. Partial hepatectomy (PHx) was performed in liver-specific Rictor (the pivotal unit of mTORC2 complex) knockout (Rictor^LKO) and wild-type (Rictor^fl/fl) mice. Rictor-deficient mice were found to be more intolerant to PHx and displayed higher mortality after PHx. Mechanistically, loss of Rictor resulted in decreased Akt phosphorylation, leading to a delay in hepatocyte proliferation and lipid droplets formation along liver regeneration. Overall, these results indicate an essential role of the mTORC2 signaling pathway during liver regeneration.

TopoFilter: a MATLAB package for mechanistic model identification in systems biology

Background

To develop mechanistic dynamic models in systems biology, one often needs to identify all (or minimal) representations of the biological processes that are consistent with experimental data, out of a potentially large set of hypothetical mechanisms. However, a simple enumeration of all alternatives becomes quickly intractable when the number of model parameters grows. Selecting appropriate dynamic models out of a large ensemble of models, taking the uncertainty in our biological knowledge and in the experimental data into account, is therefore a key current problem in systems biology.

Results

The TopoFilter package addresses this problem in a heuristic and automated fashion by implementing the previously described topological filtering method for Bayesian model selection. It includes a core heuristic for searching the space of submodels of a parametrized model, coupled with a sampling-based exploration of the parameter space. Recent developments of the method allow to balance exhaustiveness and speed of the model space search, to efficiently re-sample parameters, to parallelize the search, and to use custom scoring functions. We use a theoretical example to motivate these features and then demonstrate TopoFilter’s applicability for a yeast signaling network with more than 250’000 possible model structures.

Conclusions

TopoFilter is a flexible software framework that makes Bayesian model selection and reduction efficient and scalable to network models of a complexity that represents contemporary problems in, for example, cell signaling. TopoFilter is open-source, available under the GPL-3.0 license at https://gitlab.com/csb.ethz/TopoFilter. It includes installation instructions, a quickstart guide, a description of all package options, and multiple examples.

PyCoTools: a Python toolbox for COPASI

Motivation

COPASI is an open source software package for constructing, simulating and analyzing dynamic models of biochemical networks. COPASI is primarily intended to be used with a graphical user interface but often it is desirable to be able to access COPASI features programmatically, with a high level interface.

Results

PyCoTools is a Python package aimed at providing a high level interface to COPASI tasks with an emphasis on model calibration. PyCoTools enables the construction of COPASI models and the execution of a subset of COPASI tasks including time courses, parameter scans and parameter estimations. Additional ‘composite’ tasks which use COPASI tasks as building blocks are available for increasing parameter estimation throughput, performing identifiability analysis and performing model selection. PyCoTools supports exploratory data analysis on parameter estimation data to assist with troubleshooting model calibrations. We demonstrate PyCoTools by posing a model selection problem designed to show case PyCoTools within a realistic scenario. The aim of the model selection problem is to test the feasibility of three alternative hypotheses in explaining experimental data derived from neonatal dermal fibroblasts in response to TGF-β over time. PyCoTools is used to critically analyze the parameter estimations and propose strategies for model improvement.

Availability and implementation

PyCoTools can be downloaded from the Python Package Index (PyPI) using the command ’pip install pycotools’ or directly from GitHub (https://github.com/CiaranWelsh/pycotools). Documentation at http://pycotools.readthedocs.io.

Supplementary information

Supplementary data are available at Bioinformatics online.

Negative Regulation of mTOR Signaling Restricts Cell Proliferation in the Floor Plate

The neural tube is composed of a number of neural progenitors and postmitotic neurons distributed in a quantitatively and spatially precise manner. The floor plate, located in the ventral-most region of the neural tube, has a lot of unique characteristics, including a low cell proliferation rate. The mechanisms by which this region-specific proliferation rate is regulated remain elusive. Here we show that the activity of the mTOR signaling pathway, which regulates the proliferation of the neural progenitor cells, is significantly lower in the floor plate than in other domains of the embryonic neural tube. We identified the forkhead-type transcription factor FoxA2 as a negative regulator of mTOR signaling in the floor plate, and showed that FoxA2 transcriptionally induces the expression of the E3 ubiquitin ligase RNF152, which together with its substrate RagA, regulates cell proliferation via the mTOR pathway. Silencing of RNF152 led to the aberrant upregulation of the mTOR signal and aberrant cell division in the floor plate. Taken together, the present findings suggest that floor plate cell number is controlled by the negative regulation of mTOR signaling through the activity of FoxA2 and its downstream effector RNF152.

A Systems Biology Roadmap to Decode mTOR Control System in Cancer

Mechanistic target of rapamycin (mTOR) is a critical protein in the regulation of cell fate decision making, especially in cancer cells. mTOR acts as a signal integrator and is one of the main elements of interactions among the pivotal cellular processes such as cell death, autophagy, metabolic reprogramming, cell growth, and cell cycle. The temporal control of these processes is essential for the cellular homeostasis and dysregulation of mTOR signaling pathway results in different phenotypes, including aging, oncogenesis, cell survival, cell growth, senescence, quiescence, and cell death. In this paper, we have proposed a systems biology roadmap to study mTOR control system, which introduces the theoretical and experimental modalities to decode temporal and dynamical characteristics of mTOR signaling in cancer.

Dynamic modeling of signal transduction by mTOR complexes in cancer

Signal integration has a crucial role in the cell fate decision and dysregulation of the cellular signaling pathways is a primary characteristic of cancer. As a signal integrator, mTOR shows a complex dynamical behavior which determines the cell fate at different cellular processes levels, including cell cycle progression, cell survival, cell death, metabolic reprogramming, and aging. The dynamics of the complex responses to rapamycin in cancer cells have been attributed to its differential time-dependent inhibitory effects on mTORC1 and mTORC2, the two main complexes of mTOR. Two explanations were previously provided for this phenomenon: 1-Rapamycin does not inhibit mTORC2 directly, whereas it prevents mTORC2 formation by sequestering free mTOR protein (Le Chatelier's principle). 2-Components like Phosphatidic Acid (PA) further stabilize mTORC2 compared with mTORC1. To understand the mechanism by which rapamycin differentially inhibits the mTOR complexes in the cancer cells, we present a mathematical model of rapamycin mode of action based on the first explanation, i.e., Le Chatelier's principle. Translating the interactions among components of mTORC1 and mTORC2 into a mathematical model revealed the dynamics of rapamycin action in different doses and time-intervals of rapamycin treatment. This model shows that rapamycin has stronger effects on mTORC1 compared with mTORC2, simply due to its direct interaction with free mTOR and mTORC1, but not mTORC2, without the need to consider other components that might further stabilize mTORC2. Based on our results, even when mTORC2 is less stable compared with mTORC1, it can be less inhibited by rapamycin.

Boolean model of growth signaling, cell cycle and apoptosis predicts the molecular mechanism of aberrant cell cycle progression driven by hyperactive PI3K

The PI3K/AKT signaling pathway plays a role in most cellular functions linked to cancer progression, including cell growth, proliferation, cell survival, tissue invasion and angiogenesis. It is generally recognized that hyperactive PI3K/AKT1 are oncogenic due to their boost to cell survival, cell cycle entry and growth-promoting metabolism. That said, the dynamics of PI3K and AKT1 during cell cycle progression are highly nonlinear. In addition to negative feedback that curtails their activity, protein expression of PI3K subunits has been shown to oscillate in dividing cells. The low-PI3K/low-AKT1 phase of these oscillations is required for cytokinesis, indicating that oncogenic PI3K may directly contribute to genome duplication. To explore this, we construct a Boolean model of growth factor signaling that can reproduce PI3K oscillations and link them to cell cycle progression and apoptosis. The resulting modular model reproduces hyperactive PI3K-driven cytokinesis failure and genome duplication and predicts the molecular drivers responsible for these failures by linking hyperactive PI3K to mis-regulation of Polo-like kinase 1 (Plk1) expression late in G2. To do this, our model captures the role of Plk1 in cell cycle progression and accurately reproduces multiple effects of its loss: G2 arrest, mitotic catastrophe, chromosome mis-segregation / aneuploidy due to premature anaphase, and cytokinesis failure leading to genome duplication, depending on the timing of Plk1 inhibition along the cell cycle. Finally, we offer testable predictions on the molecular drivers of PI3K oscillations, the timing of these oscillations with respect to division, and the role of altered Plk1 and FoxO activity in genome-level defects caused by hyperactive PI3K. Our model is an important starting point for the predictive modeling of cell fate decisions that include AKT1-driven senescence, as well as the non-intuitive effects of drugs that interfere with mitosis.

Therapeutic Use of mTOR Inhibitors in Renal Diseases: Advances, Drawbacks, and Challenges

The mammalian (or mechanistic) target of rapamycin (mTOR) pathway has a key role in the regulation of a variety of biological processes pivotal for cellular life, aging, and death. Impaired activity of mTOR complexes (mTORC1/mTORC2), particularly mTORC1 overactivation, has been implicated in a plethora of age-related disorders, including human renal diseases. Since the discovery of rapamycin (or sirolimus), more than four decades ago, advances in our understanding of how mTOR participates in renal physiological and pathological mechanisms have grown exponentially, due to both preclinical studies in animal models with genetic modification of some mTOR components as well as due to evidence coming from the clinical experience. The main clinical indication of rapamycin is as immunosuppressive therapy for the prevention of allograft rejection, namely, in renal transplantation. However, considering the central participation of mTOR in the pathogenesis of other renal disorders, the use of rapamycin and its analogs meanwhile developed (rapalogues) everolimus and temsirolimus has been viewed as a promising pharmacological strategy. This article critically reviews the use of mTOR inhibitors in renal diseases. Firstly, we briefly overview the mTOR components and signaling as well as the pharmacological armamentarium targeting the mTOR pathway currently available or in the research and development stages. Thereafter, we revisit the mTOR pathway in renal physiology to conclude with the advances, drawbacks, and challenges regarding the use of mTOR inhibitors, in a translational perspective, in four classes of renal diseases: kidney transplantation, polycystic kidney diseases, renal carcinomas, and diabetic nephropathy.

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.

Recent Advances in the Systems Biology of Aging

SIGNIFICANCE

Reductionist studies have contributed greatly to our understanding of the basic biology of aging in recent years but we still do not understand fundamental mechanisms for many identified drugs and pathways. Use of systems approaches will help us move forward in our understanding of aging. Recent Advances: Recent work described here has illustrated the power of systems biology to inform our understanding of aging through the study of (i) diet restriction, (ii) neurodegenerative disease, and (iii) biomarkers of aging.

CRITICAL ISSUES

Although we do not understand all of the individual genes and pathways that affect aging, as we continue to uncover more of them, we have now also begun to synthesize existing data using systems-level approaches, often to great effect. The three examples noted here all benefit from computational approaches that were unknown a few years ago, and from biological insights gleaned from multiple model systems, from aging laboratories as well as many other areas of biology.

FUTURE DIRECTIONS

Many new technologies, such as single-cell sequencing, advances in epigenetics beyond the methylome (specifically, assay for transposase-accessible chromatin with high throughput sequencing ), and multiomic network studies, will increase the reach of systems biologists. This suggests that approaches similar to those described here will continue to lead to striking findings, and to interventions that may allow us to delay some of the many age-associated diseases in humans; perhaps sooner that we expect. Antioxid. Redox Signal. 29, 973-984.

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.

Upstream signalling of mTORC1 and its hyperactivation in type 2 diabetes (T2D)

Mammalian target of rapamycin complex 1 (mTORC1) plays a major role in cell growth, proliferation, polarity, differentiation, development, and controls transitioning between anabolic and catabolic states of the cell. It collects almost all extracellular and intracellular signals from growth factors, nutrients, and maintains cellular homeostasis, and is involved in several pathological conditions including, neurodegeneration, Type 2 diabetes (T2D), obesity, and cancer. In this review, we summarize current knowledge of upstream signaling of mTORC1 to explain etiology of T2D and hypertriglyceridemia, in which state, the role of telomere attrition is explained. We discuss if chronic inhibition of mTORC1 can reverse adverse effects resulting from hyperactivation. In conclusion, we suggest the regulatory roles of telomerase (TERT) and hexokinase II (HKII) on mTORC1 as possible remedies to treat hyperactivation. The former inhibits mTORC1 under nutrient-rich while the latter under starved condition. We provide an idea of TOS (TOR signaling) motifs that can be used for regulation of mTORC1.

Topological estimation of signal flow in complex signaling networks

In a cell, any information about extra- or intra-cellular changes is transferred and processed through a signaling network and dysregulation of signal flow often leads to disease such as cancer. So, understanding of signal flow in the signaling network is critical to identify drug targets. Owing to the development of high-throughput measurement technologies, the structure of a signaling network is becoming more available, but detailed kinetic parameter information about molecular interactions is still very limited. A question then arises as to whether we can estimate the signal flow based only on the structure information of a signaling network. To answer this question, we develop a novel algorithm that can estimate the signal flow using only the topological information and apply it to predict the direction of activity change in various signaling networks. Interestingly, we find that the average accuracy of the estimation algorithm is about 60–80% even though we only use the topological information. We also find that this predictive power gets collapsed if we randomly alter the network topology, showing the importance of network topology. Our study provides a basis for utilizing the topological information of signaling networks in precision medicine or drug target discovery.

Protein Translation in the Nucleus Accumbens Is Dysregulated during Cocaine Withdrawal and Required for Expression of Incubation of Cocaine Craving

Exposure to drug-associated cues can induce drug craving and relapse in abstinent addicts. Cue-induced craving that progressively intensifies ("incubates") during withdrawal from cocaine has been observed in both rats and humans. Building on recent evidence that aberrant protein translation underlies incubation-related adaptations in the NAc, we used male rats to test the hypothesis that translation is dysregulated during cocaine withdrawal and/or when rats express incubated cocaine craving. We found that intra-NAc infusion of anisomycin, a general protein translation inhibitor, or rapamycin, an inhibitor of mammalian target of rapamycin, reduced the expression of incubated cocaine craving, consistent with previous results showing that inhibition of translation in slices normalized the adaptations that maintain incubation. We then examined signaling pathways involved in protein translation using NAc synaptoneurosomes prepared after >47 d of withdrawal from cocaine or saline self-administration, or after withdrawal plus a cue-induced seeking test. The most robust changes were observed following seeking tests. Most notably, we found that eukaryotic elongation factor 2 (eEF2) and eukaryotic initiation factor 2α (eIF2α) are dephosphorylated when cocaine rats undergo a cue-induced seeking test; both effects are consistent with increased translation during the test. Blocking eIF2α dephosphorylation and thereby restoring its inhibitory influence on translation, via intra-NAc injection of Sal003 just before the test, substantially reduced cocaine seeking. These results are consistent with dysregulation of protein translation in the NAc during cocaine withdrawal, enabling cocaine cues to elicit an aberrant increase in translation that is required for the expression of incubated cocaine craving.SIGNIFICANCE STATEMENT Cue-induced cocaine craving progressively intensifies (incubates) during withdrawal in both humans and rats. This may contribute to persistent vulnerability to relapse. We previously demonstrated a role for protein translation in synaptic adaptations in the NAc closely linked to incubation. Here, we tested the hypothesis that translation is dysregulated during cocaine withdrawal, and this contributes to incubated craving. Analysis of signaling pathways regulating translation suggested that translation is enhanced when "incubated" rats undergo a cue-induced seeking test. Furthermore, intra-NAc infusions of drugs that inhibit protein translation through different mechanisms reduced expression of incubated cue-induced cocaine seeking. These results demonstrate that the expression of incubation depends on an acute increase in translation that may result from dysregulation of several pathways.

Dynamic modelling of the mTOR signalling network reveals complex emergent behaviours conferred by DEPTOR

The mechanistic Target of Rapamycin (mTOR) signalling network is an evolutionarily conserved network that controls key cellular processes, including cell growth and metabolism. Consisting of the major kinase complexes mTOR Complex 1 and 2 (mTORC1/2), the mTOR network harbours complex interactions and feedback loops. The DEP domain-containing mTOR-interacting protein (DEPTOR) was recently identified as an endogenous inhibitor of both mTORC1 and 2 through direct interactions, and is in turn degraded by mTORC1/2, adding an extra layer of complexity to the mTOR network. Yet, the dynamic properties of the DEPTOR-mTOR network and the roles of DEPTOR in coordinating mTORC1/2 activation dynamics have not been characterised. Using computational modelling, systems analysis and dynamic simulations we show that DEPTOR confers remarkably rich and complex dynamic behaviours to mTOR signalling, including abrupt, bistable switches, oscillations and co-existing bistable/oscillatory responses. Transitions between these distinct modes of behaviour are enabled by modulating DEPTOR expression alone. We characterise the governing conditions for the observed dynamics by elucidating the network in its vast multi-dimensional parameter space, and develop strategies to identify core network design motifs underlying these dynamics. Our findings provide new systems-level insights into the complexity of mTOR signalling contributed by DEPTOR.

BRD7 regulates the insulin-signaling pathway by increasing phosphorylation of GSK3β

Reduced hepatic expression levels of bromodomain-containing protein 7 (BRD7) have been suggested to play a role in the development of glucose intolerance in obesity. However, the molecular mechanism by which BRD7 regulates glucose metabolism has remained unclear. Here, we show that BRD7 increases phosphorylation of glycogen synthase kinase 3β (GSK3β) in response to activation of the insulin receptor-signaling pathway shortly after insulin stimulation and the nutrient-sensing pathway after feeding. BRD7 mediates phosphorylation of GSK3β at the Serine 9 residue and this effect on GSK3β occurs even in the absence of AKT activity. Using both in vitro and in vivo models, we further demonstrate that BRD7 mediates phosphorylation of ribosomal protein S6 kinase (S6K) and leads to increased phosphorylation of the eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) and, therefore, relieves its inhibition of the eukaryotic translation initiation factor 4E (eIF4E). However, the increase in phosphorylation of 4E-BP1 with BRD7 overexpression is blunted in the absence of AKT activity. In addition, using liver-specific BRD7 knockout (LBKO) mice, we show that BRD7 is required for mTORC1 activity on its downstream molecules. These findings show a novel basis for understanding the molecular dynamics of glucose metabolism and suggest the unique function of BRD7 in the regulation of glucose homeostasis.

The Role of Mammalian Target of Rapamycin (mTOR) in Insulin Signaling

The mammalian target of rapamycin (mTOR) is a serine/threonine kinase that controls a wide spectrum of cellular processes, including cell growth, differentiation, and metabolism. mTOR forms two distinct multiprotein complexes known as mTOR complex 1 (mTORC1) and mTOR complex 2 (mTORC2), which are characterized by the presence of raptor and rictor, respectively. mTOR controls insulin signaling by regulating several downstream components such as growth factor receptor-bound protein 10 (Grb10), insulin receptor substrate (IRS-1), F-box/WD repeat-containing protein 8 (Fbw8), and insulin like growth factor 1 receptor/insulin receptor (IGF-IR/IR). In addition, mTORC1 and mTORC2 regulate each other through a feedback loop to control cell growth. This review outlines the current understanding of mTOR regulation in insulin signaling in the context of whole body metabolism.

Cytoprotective activated protein C averts Nlrp3 inflammasome-induced ischemia-reperfusion injury via mTORC1 inhibition

Cytoprotection by activated protein C (aPC) after ischemia-reperfusion injury (IRI) is associated with apoptosis inhibition. However, IRI is hallmarked by inflammation, and hence, cell-death forms disjunct from immunologically silent apoptosis are, in theory, more likely to be relevant. Because pyroptosis (ie, cell death resulting from inflammasome activation) is typically observed in IRI, we speculated that aPC ameliorates IRI by inhibiting inflammasome activation. Here we analyzed the impact of aPC on inflammasome activity in myocardial and renal IRIs. aPC treatment before or after myocardial IRI reduced infarct size and Nlrp3 inflammasome activation in mice. Kinetic in vivo analyses revealed that Nlrp3 inflammasome activation preceded myocardial injury and apoptosis, corroborating a pathogenic role of the Nlrp3 inflammasome. The constitutively active Nlrp3^A350V mutation abolished the protective effect of aPC, demonstrating that Nlrp3 suppression is required for aPC-mediated protection from IRI. In vitro aPC inhibited inflammasome activation in macrophages, cardiomyocytes, and cardiac fibroblasts via proteinase-activated receptor 1 (PAR-1) and mammalian target of rapamycin complex 1 (mTORC1) signaling. Accordingly, inhibiting PAR-1 signaling, but not the anticoagulant properties of aPC, abolished the ability of aPC to restrict Nlrp3 inflammasome activity and tissue damage in myocardial IRI. Targeting biased PAR-1 signaling via parmodulin-2 restricted mTORC1 and Nlrp3 inflammasome activation and limited myocardial IRI as efficiently as aPC. The relevance of aPC-mediated Nlrp3 inflammasome suppression after IRI was corroborated in renal IRI, where the tissue protective effect of aPC was likewise dependent on Nlrp3 inflammasome suppression. These studies reveal that aPC protects from IRI by restricting mTORC1-dependent inflammasome activation and that mimicking biased aPC PAR-1 signaling using parmodulins may be a feasible therapeutic approach to combat IRI.

Systems modelling ageing: from single senescent cells to simple multi-cellular models

Systems modelling has been successfully used to investigate several key molecular mechanisms of ageing. Modelling frameworks to allow integration of models and methods to enhance confidence in models are now well established. In this article, we discuss these issues and work through the process of building an integrated model for cellular senescence as a single cell and in a simple tissue context.

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.

SBpipe: a collection of pipelines for automating repetitive simulation and analysis tasks

BACKGROUND

The rapid growth of the number of mathematical models in Systems Biology fostered the development of many tools to simulate and analyse them. The reliability and precision of these tasks often depend on multiple repetitions and they can be optimised if executed as pipelines. In addition, new formal analyses can be performed on these repeat sequences, revealing important insights about the accuracy of model predictions.

RESULTS

Here we introduce SBpipe, an open source software tool for automating repetitive tasks in model building and simulation. Using basic YAML configuration files, SBpipe builds a sequence of repeated model simulations or parameter estimations, performs analyses from this generated sequence, and finally generates a LaTeX/PDF report. The parameter estimation pipeline offers analyses of parameter profile likelihood and parameter correlation using samples from the computed estimates. Specific pipelines for scanning of one or two model parameters at the same time are also provided. Pipelines can run on multicore computers, Sun Grid Engine (SGE), or Load Sharing Facility (LSF) clusters, speeding up the processes of model building and simulation. SBpipe can execute models implemented in COPASI, Python or coded in any other programming language using Python as a wrapper module. Future support for other software simulators can be dynamically added without affecting the current implementation.

CONCLUSIONS

SBpipe allows users to automatically repeat the tasks of model simulation and parameter estimation, and extract robustness information from these repeat sequences in a solid and consistent manner, facilitating model development and analysis. The source code and documentation of this project are freely available at the web site: https://pdp10.github.io/sbpipe/ .

PLK1 (polo like kinase 1) inhibits MTOR complex 1 and promotes autophagy

Mechanistic target of rapamycin complex 1 (MTORC1) and polo like kinase 1 (PLK1) are major drivers of cancer cell growth and proliferation, and inhibitors of both protein kinases are currently being investigated in clinical studies. To date, MTORC1's and PLK1's functions are mostly studied separately, and reports on their mutual crosstalk are scarce. Here, we identify PLK1 as a physical MTORC1 interactor in human cancer cells. PLK1 inhibition enhances MTORC1 activity under nutrient sufficiency and in starved cells, and PLK1 directly phosphorylates the MTORC1 component RPTOR/RAPTOR in vitro. PLK1 and MTORC1 reside together at lysosomes, the subcellular site where MTORC1 is active. Consistent with an inhibitory role of PLK1 toward MTORC1, PLK1 overexpression inhibits lysosomal association of the PLK1-MTORC1 complex, whereas PLK1 inhibition promotes lysosomal localization of MTOR. PLK1-MTORC1 binding is enhanced by amino acid starvation, a condition known to increase autophagy. MTORC1 inhibition is an important step in autophagy activation. Consistently, PLK1 inhibition mitigates autophagy in cancer cells both under nutrient starvation and sufficiency, and a role of PLK1 in autophagy is also observed in the invertebrate model organism Caenorhabditis elegans. In summary, PLK1 inhibits MTORC1 and thereby positively contributes to autophagy. Since autophagy is increasingly recognized to contribute to tumor cell survival and growth, we propose that cautious monitoring of MTORC1 and autophagy readouts in clinical trials with PLK1 inhibitors is needed to develop strategies for optimized (combinatorial) cancer therapies targeting MTORC1, PLK1, and autophagy.

Modelling the molecular mechanisms of aging

The aging process is driven at the cellular level by random molecular damage that slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the aging process. The complexity of the aging process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards and discusses many specific examples of models that have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field.

Unraveling the regulation of mTORC2 using logical modeling

Background

The mammalian target of rapamycin (mTOR) is a regulator of cell proliferation, cell growth and apoptosis working through two distinct complexes: mTORC1 and mTORC2. Although much is known about the activation and inactivation of mTORC1, the processes controlling mTORC2 remain poorly characterized. Experimental and modeling studies have attempted to explain the regulation of mTORC2 but have yielded several conflicting hypotheses. More specifically, the Phosphoinositide 3-kinase (PI3K) pathway was shown to be involved in this process, but the identity of the kinase interacting with and regulating mTORC2 remains to be determined (Cybulski and Hall, Trends Biochem Sci 34:620-7, 2009).

Method

We performed a literature search and identified 5 published hypotheses describing mTORC2 regulation. Based on these hypotheses, we built logical models, not only for each single hypothesis but also for all combinations and possible mechanisms among them. Based on data provided by the original studies, a systematic analysis of all models was performed.

Results

We were able to find models that account for experimental observations from every original study, but do not require all 5 hypotheses to be implemented. Surprisingly, all hypotheses were in agreement with all tested data gathered from the different studies and PI3K was identified as an essential regulator of mTORC2.

Conclusion

The results and additional data suggest that more than one regulator is necessary to explain the behavior of mTORC2. Finally, this study proposes a new experiment to validate mTORC1 as second essential regulator.

A comparative review of computational methods for pathway perturbation analysis: dynamical and topological perspectives

Stem cells offer great promise within the field of regenerative medicine but despite encouraging results, the large scale use of stem cells for therapeutic applications still faces challenges when it comes to controlling signaling pathway responses with respect to environmental perturbations.

A systems study reveals concurrent activation of AMPK and mTOR by amino acids

Amino acids (aa) are not only building blocks for proteins, but also signalling molecules, with the mammalian target of rapamycin complex 1 (mTORC1) acting as a key mediator. However, little is known about whether aa, independently of mTORC1, activate other kinases of the mTOR signalling network. To delineate aa-stimulated mTOR network dynamics, we here combine a computational–experimental approach with text mining-enhanced quantitative proteomics. We report that AMP-activated protein kinase (AMPK), phosphatidylinositide 3-kinase (PI3K) and mTOR complex 2 (mTORC2) are acutely activated by aa-readdition in an mTORC1-independent manner. AMPK activation by aa is mediated by Ca²⁺/calmodulin-dependent protein kinase kinase β (CaMKKβ). In response, AMPK impinges on the autophagy regulators Unc-51-like kinase-1 (ULK1) and c-Jun. AMPK is widely recognized as an mTORC1 antagonist that is activated by starvation. We find that aa acutely activate AMPK concurrently with mTOR. We show that AMPK under aa sufficiency acts to sustain autophagy. This may be required to maintain protein homoeostasis and deliver metabolite intermediates for biosynthetic processes.

mTORC1 is known to mediate the signalling activity of amino acids. Here, the authors combine modelling with experiments and find that amino acids acutely stimulate mTORC2, IRS/PI3K and AMPK, independently of mTORC1. AMPK activation through CaMKKβ sustains autophagy under non-starvation conditions.

Targeting mTOR signaling by polyphenols: A new therapeutic target for ageing

Current ageing research is aimed not only at the promotion of longevity, but also at improving ‎health span‎ through the‎ discovery and development‎ of new therapeutic strategies‎‏‎ by investigating ‎molecular and ‎cellular ‎pathways involved in cellular senescence.‎ Understanding the mechanism of action ‎of ‎polyphenolic compounds targeting mTOR (mechanistic target of rapamycin) and related pathways opens up new directions ‎‎to revolutionize ways to slow down the ‎onset and development of age-dependent degeneration. Herein, we will ‎discuss the mechanisms by which polyphenols can delay the‎ molecular ‎pathogenesis of ageing via manipulation or more specifically inhibition of mTOR-signaling pathways. We will also discuss the implications of polyphenols in targeting mTOR and its related ‎pathways‎‎ on ‎health life span extension and longevity.‎.

A rule-based model of insulin signalling pathway

BACKGROUND

The insulin signalling pathway (ISP) is an important biochemical pathway, which regulates some fundamental biological functions such as glucose and lipid metabolism, protein synthesis, cell proliferation, cell differentiation and apoptosis. In the last years, different mathematical models based on ordinary differential equations have been proposed in the literature to describe specific features of the ISP, thus providing a description of the behaviour of the system and its emerging properties. However, protein-protein interactions potentially generate a multiplicity of distinct chemical species, an issue referred to as "combinatorial complexity", which results in defining a high number of state variables equal to the number of possible protein modifications. This often leads to complex, error prone and difficult to handle model definitions.

RESULTS

In this work, we present a comprehensive model of the ISP, which integrates three models previously available in the literature by using the rule-based modelling (RBM) approach. RBM allows for a simple description of a number of signalling pathway characteristics, such as the phosphorylation of signalling proteins at multiple sites with different effects, the simultaneous interaction of many molecules of the signalling pathways with several binding partners, and the information about subcellular localization where reactions take place. Thanks to its modularity, it also allows an easy integration of different pathways. After RBM specification, we simulated the dynamic behaviour of the ISP model and validated it using experimental data. We the examined the predicted profiles of all the active species and clustered them in four clusters according to their dynamic behaviour. Finally, we used parametric sensitivity analysis to show the role of negative feedback loops in controlling the robustness of the system.

CONCLUSIONS

The presented ISP model is a powerful tool for data simulation and can be used in combination with experimental approaches to guide the experimental design. The model is available at http://sysbiobig.dei.unipd.it/ was submitted to Biomodels Database ( https://www.ebi.ac.uk/biomodels-main/ # MODEL 1604100005).

Insulin Signaling in Insulin Resistance States and Cancer: A Modeling Analysis

Insulin resistance is the common denominator of several diseases including type 2 diabetes and cancer, and investigating the mechanisms responsible for insulin signaling impairment is of primary importance. A mathematical model of the insulin signaling network (ISN) is proposed and used to investigate the dose-response curves of components of this network. Experimental data of C2C12 myoblasts with phosphatase and tensin homologue (PTEN) suppressed and data of L6 myotubes with induced insulin resistance have been analyzed by the model. We focused particularly on single and double Akt phosphorylation and pointed out insulin signaling changes related to insulin resistance. Moreover, a new characterization of the upstream signaling of the mammalian target of rapamycin complex 2 (mTORC2) is presented. As it is widely recognized that ISN proteins have a crucial role also in cell proliferation and death, the ISN model was linked to a cell population model and applied to data of a cell line of acute myeloid leukemia treated with a mammalian target of rapamycin inhibitor with antitumor activity. The analysis revealed simple relationships among the concentrations of ISN proteins and the parameters of the cell population model that characterize cell cycle progression and cell death.

The Akt switch model: Is location sufficient?

Akt/PKB is a biochemical regulator that functions as an important cross-talk node between several signalling pathways in the mammalian cell. In particular, Akt is a key mediator of glucose transport in response to insulin. The phosphorylation (activation) of only a small percentage of the Akt pool of insulin-sensitive cells results in maximal translocation of glucose transporter 4 (GLUT4) to the plasma membrane (PM). This enables the diffusion of glucose into the cell. The dysregulation of Akt signalling is associated with the development of diabetes, cancer and cardiovascular disease. Akt is synthesised in the cytoplasm in the inactive state. Under the influence of insulin, it moves to the PM, where it is phosphorylated to form pAkt. Although phosphorylation occurs only at the PM, pAkt is found in many cellular locations, including the PM, the cytoplasm, and the nucleus. Indeed, the spatial distribution of pAkt within the cell appears to be an important determinant of downstream regulation. Here we present a simple, linear, four-compartment ordinary differential equation (ODE) model of Akt activation that tracks both the biochemical state and the physical location of Akt. This model embodies the main features of the activation of this important cross-talk node and is consistent with the experimental data. In particular, it allows different downstream signalling motifs without invoking separate feedback pathways. Moreover, the model is computationally tractable, readily analysed, and elucidates some of the apparent anomalies in insulin signalling via Akt.

Hydrophobic motif site-phosphorylated protein kinase CβII between mTORC2 and Akt regulates high glucose-induced mesangial cell hypertrophy

PKCβII controls the pathologic features of diabetic nephropathy, including glomerular mesangial cell hypertrophy. PKCβII contains the COOH-terminal hydrophobic motif site Ser-660. Whether this hydrophobic motif phosphorylation contributes to high glucose-induced mesangial cell hypertrophy has not been determined. Here we show that, in mesangial cells, high glucose increased phosphorylation of PKCβII at Ser-660 in a phosphatidylinositol 3-kinase (PI3-kinase)-dependent manner. Using siRNAs to downregulate PKCβII, dominant negative PKCβII, and PKCβII hydrophobic motif phosphorylation-deficient mutant, we found that PKCβII regulates activation of mechanistic target of rapamycin complex 1 (mTORC1) and mesangial cell hypertrophy by high glucose. PKCβII via its phosphorylation at Ser-660 regulated phosphorylation of Akt at both catalytic loop and hydrophobic motif sites, resulting in phosphorylation and inactivation of its substrate PRAS40. Specific inhibition of mTORC2 increased mTORC1 activity and induced mesangial cell hypertrophy. In contrast, inhibition of mTORC2 decreased the phosphorylation of PKCβII and Akt, leading to inhibition of PRAS40 phosphorylation and mTORC1 activity and prevented mesangial cell hypertrophy in response to high glucose; expression of constitutively active Akt or mTORC1 restored mesangial cell hypertrophy. Moreover, constitutively active PKCβII reversed the inhibition of high glucose-stimulated Akt phosphorylation and mesangial cell hypertrophy induced by suppression of mTORC2. Finally, using renal cortexes from type 1 diabetic mice, we found that increased phosphorylation of PKCβII at Ser-660 was associated with enhanced Akt phosphorylation and mTORC1 activation. Collectively, our findings identify a signaling route connecting PI3-kinase to mTORC2 to phosphorylate PKCβII at the hydrophobic motif site necessary for Akt phosphorylation and mTORC1 activation, leading to mesangial cell hypertrophy.

Influence of plasma macronutrient levels on hepatic metabolism: role of regulatory networks in homeostasis and disease states

Multilevel regulations by metabolic, signaling and transcription pathways form a complex network that works to provide robust metabolic regulation in the liver. This analysis indicates that dietary perturbations in these networks can lead to insulin resistance.

Nephrin Contributes to Insulin Secretion and Affects Mammalian Target of Rapamycin Signaling Independently of Insulin Receptor

Nephrin belongs to a family of highly conserved proteins with a well characterized function as modulators of cell adhesion and guidance, and nephrin may have a role in metabolic pathways linked to podocyte and pancreatic β-cell survival. However, this role is incompletely characterized. In this study, we developed floxed nephrin mice for pancreatic β-cell-specific deletion of nephrin, which had no effect on islet size and glycemia. Nephrin deficiency, however, resulted in glucose intolerance in vivo and impaired glucose-stimulated insulin release ex vivo Glucose intolerance was also observed in eight patients with nephrin mutations compared with three patients with other genetic forms of nephrotic syndrome or nine healthy controls.In vitro experiments were conducted to investigate if nephrin affects autocrine signaling through insulin receptor A (IRA) and B (IRB), which are both expressed in human podocytes and pancreatic islets. Coimmunoprecipitation of nephrin and IRB but not IRA was observed and required IR phosphorylation. Nephrin per se was sufficient to induce phosphorylation of p70S6K in an phosphatidylinositol 3-kinase-dependent but IR/Src-independent manner, which was not augmented by exogenous insulin. These results suggest a role for nephrin as an independent modulator of podocyte and pancreatic β-cell nutrient sensing in the fasting state and the potential of nephrin as a drug target in diabetes.

Molecular and Functional Characterization of Three Different Postzygotic Mutations in PIK3CA-Related Overgrowth Spectrum (PROS) Patients: Effects on PI3K/AKT/mTOR Signaling and Sensitivity to PIK3 Inhibitors

Background

PIK3CA-related overgrowth spectrum (PROS) include a group of disorders that affect only the terminal portion of a limb, such as type I macrodactyly, and conditions like fibroadipose overgrowth (FAO), megalencephaly-capillary malformation (MCAP) syndrome, congenital lipomatous asymmetric overgrowth of the trunk, lymphatic, capillary, venous, and combined-type vascular malformations, epidermal nevi, skeletal and spinal anomalies (CLOVES) syndrome and Hemihyperplasia Multiple Lipomatosis (HHML). Heterozygous postzygotic PIK3CA mutations are frequently identified in these syndromes, while timing and tissue specificity of the mutational event are likely responsible for the extreme phenotypic variability observed.

Methods

We carried out a combination of Sanger sequencing and targeted deep sequencing of genes involved in the PI3K/AKT/mTOR pathway in three patients (1 MCAP and 2 FAO) to identify causative mutations, and performed immunoblot analyses to assay the phosphorylation status of AKT and P70S6K in affected dermal fibroblasts. In addition, we evaluated their ability to grow in the absence of serum and their response to the PI3K inhibitors wortmannin and LY294002 in vitro.

Results and Conclusion

Our data indicate that patients’ cells showed constitutive activation of the PI3K/Akt pathway. Of note, PI3K pharmacological blockade resulted in a significant reduction of the proliferation rate in culture, suggesting that inhibition of PI3K might prove beneficial in future therapies for PROS patients.

Functional Proteomics Identifies Acinus L as a Direct Insulin- and Amino Acid-Dependent Mammalian Target of Rapamycin Complex 1 (mTORC1) Substrate

The serine/threonine kinase mammalian target of rapamycin (mTOR) governs growth, metabolism, and aging in response to insulin and amino acids (aa), and is often activated in metabolic disorders and cancer. Much is known about the regulatory signaling network that encompasses mTOR, but surprisingly few direct mTOR substrates have been established to date. To tackle this gap in our knowledge, we took advantage of a combined quantitative phosphoproteomic and interactomic strategy. We analyzed the insulin- and aa-responsive phosphoproteome upon inhibition of the mTOR complex 1 (mTORC1) component raptor, and investigated in parallel the interactome of endogenous mTOR. By overlaying these two datasets, we identified acinus L as a potential novel mTORC1 target. We confirmed acinus L as a direct mTORC1 substrate by co-immunoprecipitation and MS-enhanced kinase assays. Our study delineates a triple proteomics strategy of combined phosphoproteomics, interactomics, and MS-enhanced kinase assays for the de novo-identification of mTOR network components, and provides a rich source of potential novel mTOR interactors and targets for future investigation.