Unraveling the regulation of mTORC2 using logical modeling

Modeling and analysis of the macronutrient signaling network in budding yeast

Adaptive modulation of the global cellular growth state of unicellular organisms is crucial for their survival in fluctuating nutrient environments. Because these organisms must be able to respond reliably to ever varying and unpredictable nutritional conditions, their nutrient signaling networks must have a certain inbuilt robustness. In eukaryotes, such as the budding yeast Saccharomyces cerevisiae, distinct nutrient signals are relayed by specific plasma membrane receptors to signal transduction pathways that are interconnected in complex information-processing networks, which have been well characterized. However, the complexity of the signaling network confounds the interpretation of the overall regulatory "logic" of the control system. Here, we propose a literature-curated molecular mechanism of the integrated nutrient signaling network in budding yeast, focusing on early temporal responses to carbon and nitrogen signaling. We build a computational model of this network to reconcile literature-curated quantitative experimental data with our proposed molecular mechanism. We evaluate the robustness of our estimates of the model's kinetic parameter values. We test the model by comparing predictions made in mutant strains with qualitative experimental observations made in the same strains. Finally, we use the model to predict nutrient-responsive transcription factor activities in a number of mutant strains undergoing complex nutrient shifts.

Interaction between PI3K/AKT and Hippo pathways during in vitro follicular activation and response to fragmentation and chemotherapy exposure using a mouse immature ovary model

Understanding and control of the massive and accelerated follicular growth that occurs during in vitro culture of ovarian tissue is a crucial step toward the development of efficient culture systems that offer an attractive alternative to ovarian tissue transplantation for fertility restoration in cancer survivors. One outstanding question focuses on processes that occur prior to cryopreservation, such as tissue sectioning or chemotherapeutic treatment, might exacerbate this follicular activation. Although the PI3K/AKT/mTOR pathway is well known as a major trigger of physiological and chemotherapy-induced follicular activation, studies have shown that disruption of Hippo pathway due to ovarian fragmentation acts as an additional stimulator. This study aimed to characterize the possible interactions between these pathways using post-natal day 3 mouse ovaries cultured for 4 or 48 h. Morphology, gene transcription, and protein levels were assessed to investigate the impact of sectioning or chemotherapy exposure (4-hydroperoxycyclophosphamide [4HC], 3 and 20 μM). The effect of an mTORC1 inhibitor, Everolimus, alone or as a 4HC co-treatment to prevent follicle activation was evaluated. The results showed that organ removal from its physiological environment was as effective as sectioning for disruption of Hippo pathway and induction of follicle activation. Both PI3K/AKT/mTOR and Hippo pathways were involved in chemotherapy-induced follicular activation and responded to fragmentation. Surprisingly, Everolimus was able to prevent the activation of both pathways during chemotherapy exposure, suggesting cross-talk between them. This study underscores the major involvement of PI3K/AKT/mTOR and Hippo pathways in in vitro follicle activation and provides evidence that both can be regulated using mTORC1 inhibitor.

Interactions among mTORC, AMPK and SIRT: a computational model for cell energy balance and metabolism

Background

Cells adapt their metabolism and activities in response to signals from their surroundings, and this ability is essential for their survival in the face of perturbations. In tissues a deficit of these mechanisms is commonly associated with cellular aging and diseases, such as cardiovascular disease, cancer, immune system decline, and neurological pathologies. Several proteins have been identified as being able to respond directly to energy, nutrient, and growth factor levels and stress stimuli in order to mediate adaptations in the cell. In particular, mTOR, AMPK, and sirtuins are known to play an essential role in the management of metabolic stress and energy balance in mammals.

Methods

To understand the complex interactions of these signalling pathways and environmental signals, and how those interactions may impact lifespan and health-span, we have developed a computational model of metabolic signalling pathways. Specifically, the model includes (i) the insulin/IGF-1 pathway, which couples energy and nutrient abundance to the execution of cell growth and division, (ii) mTORC1 and the amino acid sensors such as sestrin, (iii) the Preiss-Handler and salvage pathways, which regulate the metabolism of NAD+ and the NAD+ -consuming factor SIRT1, (iv) the energy sensor AMPK, and (v) transcription factors FOXO and PGC-1α.

Results

The model simulates the interactions among key regulators such as AKT, mTORC1, AMPK, NAD+ , and SIRT, and predicts their dynamics. Key findings include the clinically important role of PRAS40 and diet in mTORC1 inhibition, and a potential link between SIRT1-activating compounds and premature autophagy. Moreover, the model captures the exquisite interactions of leucine, sestrin2, and arginine, and the resulting signal to the mTORC1 pathway. These results can be leveraged in the development of novel treatment of cancers and other diseases.

Conclusions

This study presents a state-of-the-art computational model for investigating the interactions among signaling pathways and environmental stimuli in growth, ageing, metabolism, and diseases. The model can be used as an essential component to simulate gene manipulation, therapies (e.g., rapamycin and wortmannin), calorie restrictions, and chronic stress, and assess their functional implications on longevity and ageing‐related diseases.

Experimental Approaches in Delineating mTOR Signaling

The mTOR signaling controls essential biological functions including proliferation, growth, metabolism, autophagy, ageing, and others. Hyperactivation of mTOR signaling leads to a plethora of human disorders; thus, mTOR is an attractive drug target. The discovery of mTOR signaling started from isolation of rapamycin in 1975 and cloning of TOR genes in 1993. In the past 27 years, numerous research groups have contributed significantly to advancing our understanding of mTOR signaling and mTOR biology. Notably, a variety of experimental approaches have been employed in these studies to identify key mTOR pathway members that shape up the mTOR signaling we know today. Technique development drives mTOR research, while canonical biochemical and yeast genetics lay the foundation for mTOR studies. Here in this review, we summarize major experimental approaches used in the past in delineating mTOR signaling, including biochemical immunoprecipitation approaches, genetic approaches, immunofluorescence microscopic approaches, hypothesis-driven studies, protein sequence or motif search driven approaches, and bioinformatic approaches. We hope that revisiting these distinct types of experimental approaches will provide a blueprint for major techniques driving mTOR research. More importantly, we hope that thinking and reasonings behind these experimental designs will inspire future mTOR research as well as studies of other protein kinases beyond mTOR.

Modulating autophagy as a therapeutic strategy for the treatment of paediatric high-grade glioma

Paediatric high-grade gliomas (pHGG) represent a therapeutically challenging group of tumors. Despite decades of research, there has been minimal improvement in treatment and the clinical prognosis remains poor. Autophagy, a highly conserved process for recycling metabolic substrates is upregulated in pHGG, promoting tumor progression and evading cell death. There is significant crosstalk between autophagy and a plethora of critical cellular pathways, many of which are dysregulated in pHGG. The following article will discuss our current understanding of autophagy signaling in pHGG and the potential modulation of this network as a therapeutic target.

PI3K-AKT-mTOR and NFκB Pathways in Ovarian Cancer: Implications for Targeted Therapeutics

Ovarian cancer is the most lethal gynecologic malignancy in the United States, with an estimated 22,530 new cases and 13,980 deaths in 2019. Recent studies have indicated that the phosphoinositol 3 kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR), as well as the nuclear factor-κ light chain enhancer of activated B cells (NFκB) pathways are highly mutated and/or hyper-activated in a majority of ovarian cancer patients, and are associated with advanced grade and stage disease and poor prognosis. In this review, we will investigate PI3K/AKT/mTOR and their interconnection with NFκB pathway in ovarian cancer cells.

Akt Signaling in Macrophage Polarization, Survival, and Atherosclerosis

The PI3K/Akt pathway plays a crucial role in the survival, proliferation, and migration of macrophages, which may impact the development of atherosclerosis. Changes in Akt isoforms or modulation of the Akt activity levels in macrophages significantly affect their polarization phenotype and consequently atherosclerosis in mice. Moreover, the activity levels of Akt signaling determine the viability of monocytes/macrophages and their resistance to pro-apoptotic stimuli in atherosclerotic lesions. Therefore, elimination of pro-apoptotic factors as well as factors that antagonize or suppress Akt signaling in macrophages increases cell viability, protecting them from apoptosis, and this markedly accelerates atherosclerosis in mice. In contrast, inhibition of Akt signaling by the ablation of Rictor in myeloid cells, which disrupts mTORC2 assembly, significantly decreases the viability and proliferation of blood monocytes and macrophages with the suppression of atherosclerosis. In addition, monocytes and macrophages exhibit a threshold effect for Akt protein levels in their ability to survive. Ablation of two Akt isoforms, preserving only a single Akt isoform in myeloid cells, markedly compromises monocyte and macrophage viability, inducing monocytopenia and diminishing early atherosclerosis. These recent advances in our understanding of Akt signaling in macrophages in atherosclerosis may have significant relevance in the burgeoning field of cardio-oncology, where PI3K/Akt inhibitors being tested in cancer patients can have significant cardiovascular and metabolic ramifications.

Farnesylation-defective Rheb Increases Axonal Length Independently of mTORC1 Activity in Embryonic Primary Neurons

Rheb (Ras homolog enriched in the brain) is a small GTPase protein that plays an important role in cell signaling for development of the neocortex through modulation of mTORC1 (mammalian-target-of-rapamycin-complex-1) activity. mTORC1 is known to control various biological processes including axonal growth in forming complexes at the lysosomal membrane compartment. As such, anchoring of Rheb on the lysosomal membrane via the farnesylation of Rheb at its cysteine residue (C180) is required for its promotion of mTOR activity. To test the significance of Rheb farnesylation, we overexpressed a farnesylation mutant form of Rheb, Rheb C180S, in primary rat hippocampal neurons and also in mouse embryonic neurons using in utero electroporation. Interestingly, we found that Rheb C180S maintained promotional effect of axonal elongation similar to the wild-type Rheb in both test systems. On the other hand, Rheb C180S failed to exhibit the multiple axon-promoting effect which is found in wild-type Rheb. The levels of phospho-4EBP1, a downstream target of mTORC1, were surprisingly increased in Rheb C180S transfected neurons, despite the levels of phosphorylated mTOR being significantly decreased compared to control vector transfectants. A specific mTORC1 inhibitor, rapamycin, also could not completely abolish axon elongation characteristics of Rheb C180S in transfected cells. Our data suggests that Rheb in a non-membrane compartment can promote the axonal elongation via phosphorylation of 4EBP1 and through an mTORC1-independent pathway.

Evaluating Uncertainty in Signaling Networks Using Logical Modeling

Systems biology studies the structure and dynamics of biological systems using mathematical approaches. Bottom-up approaches create models from prior knowledge but usually cannot cope with uncertainty, whereas top-down approaches infer models directly from data using statistical methods but mostly neglect valuable known information from former studies. Here, we want to present a workflow that includes prior knowledge while allowing for uncertainty in the modeling process. We build not one but all possible models that arise from the uncertainty using logical modeling and subsequently filter for those models in agreement with data in a top-down manner. This approach enables us to investigate new and more complex biological research questions, however, the encoding in such a framework is often not obvious and thus not easily accessible for researcher from life sciences. To mitigate this problem, we formulate a pipeline with specific templates to address some research questions common in signaling network analysis. To illustrate the potential of this approach, we applied the pipeline to growth factor signaling processes in two renal cancer cell lines. These two cell lines originate from similar tissue, but surprisingly showed a very different behavior toward the cancer drug Sorafenib. Thus our aim was to explore differences between these cell lines regarding three sources of uncertainty in one analysis: possible targets of Sorafenib, crosstalk between involved pathways, and the effect of a mutation in mammalian target of Rapamycin (mTOR) in one of the cell lines. We were able to show that the model pools from the cell lines are disjoint, thus the discrepancies in behavior originate from differences in the cellular wiring. Also the mutation in mTOR is not affecting its activity in the pathway. The results on Sorafenib, while not fully clarifying the mechanisms involved, illustrate the potential of this analysis for generating new hypotheses.

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.

Formal Modeling of mTOR Associated Biological Regulatory Network Reveals Novel Therapeutic Strategy for the Treatment of Cancer

Cellular homeostasis is a continuous phenomenon that if compromised can lead to several disorders including cancer. There is a need to understand the dynamics of cellular proliferation to get deeper insights into the prevalence of cancer. Mechanistic Target of Rapamycin (mTOR) is implicated as the central regulator of the metabolic pathway involved in growth whereas its two distinct complexes mTORC1 and mTORC2 perform particular functions in cellular propagation. To date, mTORC1 is a well defined therapeutic target to inhibit uncontrolled cell division, while the role of mTORC2 is not well characterized. Therefore, the current study is designed to understand the signaling dynamics of mTOR and its partner proteins such as PI3K, PTEN, mTORC2, PKB (Akt), mTORC1, and FOXO. For this purpose, a qualitative model of mTOR-associated Biological Regulatory Network (BRN) is constructed to predict its regulatory behaviors which may not be predictable otherwise. The depleted expression of PTEN and FOXO along with the overexpression of PI3K, mTORC2, mTORC1 and Akt is predicted as a stable steady state which is in accordance with their observed expression levels in the progression of various cancers. The qualitative model also predicts the homeostasis of all the entities in the form of qualitative cycles. The significant qualitative (discrete) cycle is identified by analyzing betweenness centralities of the qualitative (discrete) states. This cycle is further refined as a linear hybrid automaton model with the production (activation) and degradation (inhibition) time delays in order to analyze the real-time constraints for its existence. The analysis of the hybrid model provides a formal proof that during homeostasis the inhibition time delay of Akt is less than the inhibition time delay of mTORC2. In conclusion, our observations characterize that in homeostasis Akt is degraded with a faster rate than mTORC2 which suggests that the inhibition of Akt along with the activation of mTORC2 may be a better therapeutic strategy for the treatment of cancer.