Continuous sensing of nutrients and growth factors by the mTORC1-TFEB axis
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eLife assessment
In this study, Sparta et al., generated and employed a battery of fluorescent reporters that allowed them to perform time-resolved monitoring of mechanistic target of rapamycin complex 1 (mTORC1) responses to stimuli including glucose, amino acids, and insulin at the single cell resolution. The results of this elegant approach support a model of graded mTORC1 activation in response to the aforementioned stimuli when applied individually or in combination. This model is consistent with continuous adjustment of mTORC1 signaling to changes in cellular environment and opposed to the "on/off" model of mTORC1 function. Considering the pivotal role of mTORC1 in integrating signals such as nutrients, hormones, growth factors, oxygen, and energy status with a plethora of outputs that affect cell fate and organismal physiology, it was thought that this study will be of interests across a variety of biomedical disciplines. Overall, the elegance and robustness of the approach was highly appreciated, though the paper would be strengthened by addressing some technical issues and concerns regarding the positioning of the proposed model of mTORC1 regulation in the field.
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Abstract
mTORC1 senses nutrients and growth factors and phosphorylates downstream targets, including the transcription factor TFEB, to coordinate metabolic supply and demand. These functions position mTORC1 as a central controller of cellular homeostasis, but the behavior of this system in individual cells has not been well characterized. Here, we provide measurements necessary to refine quantitative models for mTORC1 as a metabolic controller. We developed a series of fluorescent protein-TFEB fusions and a multiplexed immunofluorescence approach to investigate how combinations of stimuli jointly regulate mTORC1 signaling at the single-cell level. Live imaging of individual MCF10A cells confirmed that mTORC1-TFEB signaling responds continuously to individual, sequential, or simultaneous treatment with amino acids and the growth factor insulin. Under physiologically relevant concentrations of amino acids, we observe correlated fluctuations in TFEB, AMPK, and AKT signaling that indicate continuous activity adjustments to nutrient availability. Using partial least squares regression modeling, we show that these continuous gradations are connected to protein synthesis rate via a distributed network of mTORC1 effectors, providing quantitative support for the qualitative model of mTORC1 as a homeostatic controller and clarifying its functional behavior within individual cells.
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eLife assessment
In this study, Sparta et al., generated and employed a battery of fluorescent reporters that allowed them to perform time-resolved monitoring of mechanistic target of rapamycin complex 1 (mTORC1) responses to stimuli including glucose, amino acids, and insulin at the single cell resolution. The results of this elegant approach support a model of graded mTORC1 activation in response to the aforementioned stimuli when applied individually or in combination. This model is consistent with continuous adjustment of mTORC1 signaling to changes in cellular environment and opposed to the "on/off" model of mTORC1 function. Considering the pivotal role of mTORC1 in integrating signals such as nutrients, hormones, growth factors, oxygen, and energy status with a plethora of outputs that affect cell fate and organismal physiology, …
eLife assessment
In this study, Sparta et al., generated and employed a battery of fluorescent reporters that allowed them to perform time-resolved monitoring of mechanistic target of rapamycin complex 1 (mTORC1) responses to stimuli including glucose, amino acids, and insulin at the single cell resolution. The results of this elegant approach support a model of graded mTORC1 activation in response to the aforementioned stimuli when applied individually or in combination. This model is consistent with continuous adjustment of mTORC1 signaling to changes in cellular environment and opposed to the "on/off" model of mTORC1 function. Considering the pivotal role of mTORC1 in integrating signals such as nutrients, hormones, growth factors, oxygen, and energy status with a plethora of outputs that affect cell fate and organismal physiology, it was thought that this study will be of interests across a variety of biomedical disciplines. Overall, the elegance and robustness of the approach was highly appreciated, though the paper would be strengthened by addressing some technical issues and concerns regarding the positioning of the proposed model of mTORC1 regulation in the field.
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Reviewer #1 (Public Review):
Notwithstanding that the molecular underpinnings of the mechanistic target of rapamycin complex 1 (mTORC1) signaling are relatively well understood, quantitative data pertinent to mTORC1-dependent integration of a variety of stimuli is lacking. To address this question, Sparta et al., developed a series of fluorescent reporters that in combination with live cell microscopy allowed them to determine responses of mTORC1 to several stimuli including glucose, amino acids, and insulin at the single cell resolution. Considering the central role of mTORC1 in homeostasis and its dysregulation across a variety of pathological states, it was thought that this study should be of broad interest to a wide spectrum of biomedical disciplines ranging from biochemistry, molecular and cellular biology to neurobiology and …
Reviewer #1 (Public Review):
Notwithstanding that the molecular underpinnings of the mechanistic target of rapamycin complex 1 (mTORC1) signaling are relatively well understood, quantitative data pertinent to mTORC1-dependent integration of a variety of stimuli is lacking. To address this question, Sparta et al., developed a series of fluorescent reporters that in combination with live cell microscopy allowed them to determine responses of mTORC1 to several stimuli including glucose, amino acids, and insulin at the single cell resolution. Considering the central role of mTORC1 in homeostasis and its dysregulation across a variety of pathological states, it was thought that this study should be of broad interest to a wide spectrum of biomedical disciplines ranging from biochemistry, molecular and cellular biology to neurobiology and cancer research.
Strengths: This study employs powerful approach based on use of live cell imaging of multiple fluorescent reports that are indicative of alterations in mTORC1 activity. In contrast to traditional approaches based on querying phosphorylation status of mTORC1 substrates by Western blotting this approach allows time-resolved measurement of mTORC1 activity at the single cell resolution. Using this approach, the authors provide solid evidence to corroborate a model of graded activation of mTORC1 by amino acids, insulin, and combination thereof.
Weaknesses: The major weaknesses were thought to be related to the interpretation of the current model of mTORC1 regulation as AND gate and reliance on a single cell line. Some minor technical issues were also observed pertinent to the lack of controls demonstrating the effectiveness of manipulations of nutrients and/or insulin as well as the effects of such manipulation on the expression of reporters used to monitor mTORC1 activity.
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Reviewer #2 (Public Review):
Using fluorescent-TFEB fusion proteins and mutants thereof for live-cell imaging single cells, the authors investigated how mTORC1 responds to amino acids and growth factors. First, they demonstrated that the stably expressed fusion protein behaves as endogenous TFEB with regards to mTORC1 activation. Next, using the phosphodeficient TFEB mutant, they showed that GSK3 phosphorylation amplifies the C/N ratio, supporting the role of GSK3 and mTORC1 in co-regulating TFEB. When amino acids or insulin were added to starved cells, they found a graded response depending on amounts of AA or insulin, respectively, thus suggesting an incremental response. When multiple inputs were assessed, they found that TFEB C/N ratio also increased in increments when nutrients were added first followed by insulin. But when insulin …
Reviewer #2 (Public Review):
Using fluorescent-TFEB fusion proteins and mutants thereof for live-cell imaging single cells, the authors investigated how mTORC1 responds to amino acids and growth factors. First, they demonstrated that the stably expressed fusion protein behaves as endogenous TFEB with regards to mTORC1 activation. Next, using the phosphodeficient TFEB mutant, they showed that GSK3 phosphorylation amplifies the C/N ratio, supporting the role of GSK3 and mTORC1 in co-regulating TFEB. When amino acids or insulin were added to starved cells, they found a graded response depending on amounts of AA or insulin, respectively, thus suggesting an incremental response. When multiple inputs were assessed, they found that TFEB C/N ratio also increased in increments when nutrients were added first followed by insulin. But when insulin was added first before nutrients, a minimal response occurred although this could be subsequently increased upon addition of the nutrients. Lastly, by tracking down TFEB C/N in response to different amounts of nutrients over longer periods (12 hr), they observed that a new steady state is achieved, indicating adaptation of mTORC1 activity and that this correlates with signal inputs from Akt and AMPK. Based on these findings, the authors conclude that the mTORC1-TFEB signaling continuously adjust to nutrient availability rather than just behave in "AND" gate logic fashion.
Overall, the results are robust and supportive of their conclusion. The use of fluorescent fusion proteins/mutants is nicely done. The authors have created useful tools to further analyze mTOR signaling at the single-cell level. However, the findings that mTORC1 signaling behaves like a rheostat is not really new and rather more confirmatory of previous studies. The current studies further support this model with their use of TFEB as mTORC1 target in single cells.
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Reviewer #3 (Public Review):
This is an interesting manuscript from Sparta and colleagues that investigates dynamics of MTOR and TFEB signalling. The main strength is that the study is based on a systems biology approach using live cell imaging of a range of MTOR downstream readouts, capturing data on a single-cell level with capabilities to multiplex tracking over time. To monitor downstream signalling, the authors primarily rely on measuring nuclear translocation of a fluorescent reporter of TFEB, truncated to remove C-terminal DNA-binding domain and the AKT phosphorylation site. The authors further show that a TFEB reporter with 3x S>A mutations at 3 GSK3beta phosphorylation sites (134, 138 and 142) was dramatically less sensitive to stimulation by amino acids, or by insulin. The authors use these single cell tools to determine …
Reviewer #3 (Public Review):
This is an interesting manuscript from Sparta and colleagues that investigates dynamics of MTOR and TFEB signalling. The main strength is that the study is based on a systems biology approach using live cell imaging of a range of MTOR downstream readouts, capturing data on a single-cell level with capabilities to multiplex tracking over time. To monitor downstream signalling, the authors primarily rely on measuring nuclear translocation of a fluorescent reporter of TFEB, truncated to remove C-terminal DNA-binding domain and the AKT phosphorylation site. The authors further show that a TFEB reporter with 3x S>A mutations at 3 GSK3beta phosphorylation sites (134, 138 and 142) was dramatically less sensitive to stimulation by amino acids, or by insulin. The authors use these single cell tools to determine whether MTOR-TFEB signalling better fits a gated / digital pattern of response vs a gradual/ analogue mode. Data based on concentration-dependent titrations provide further support of the ability of MTOR-TFEB to respond to amino acid or insulin stimulations with gradual/incremental sensitivity. To understand how MTOR, AMPK and AKT pathways respond and integrate to multiple signals, the authors were also able to use single cell imaging approaches, comparing: TFEB, AMPK-FRET, and FOXO reporters. As follows, the authors were able to track downstream signalling following various patterns of sequential stimulation by glucose, amino acids and insulin. This work is thus able to provide further insight and illustrate how single cells within a population function during nutrient sensing signalling. The results highlight the power of single cell multi-channel imaging to interrogate signalling in real time.
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