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

Kubota H, Uda S, Matsuzaki F, Yamauchi Y, Kuroda S · 2018 · Cell Systems · Atlas ID KUB2018

What this study shows

The in-vivo follow-up to KUB2012. In rat liver, all temporal patterns of blood insulin were encoded at the insulin receptor, and downstream molecules decoded them selectively through AKT: S6K read the additional (pulse-like) secretion, G6Pase the basal secretion via FoxO1, GSK3-beta all of it. Modelling tied the selectivity to network structure, sensitivity and time constants. Shows that pattern decoding is not only a cell-culture effect.

Abstract

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Cells respond to various extracellular stimuli through a limited number of signaling pathways. One strategy to process such stimuli is to code the information into the temporal patterns of molecules. Although we showed that insulin selectively regulated molecules depending on its temporal patterns using Fao cells, the in vivo mechanism remains unknown. Here, we show how the insulin-AKT pathway processes the information encoded into the temporal patterns of blood insulin.

Read the full abstract on PubMed →

At a glance

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Evidence type A Animal model Marked A because it is an animal intervention or observation study measuring an organismal outcome (model: Rat liver in vivo (hyperinsulinemic-euglycemic clamp with different insulin time patterns) plus mathematical model); the code names the system studied -- animal work can be rigorous and still not be human data.
Study type4 - Animal Study
Model systemRat liver in vivo (hyperinsulinemic-euglycemic clamp with different insulin time patterns) plus mathematical model
JournalCell Systems
Year2018
Peer reviewedYes
Record last updated2026-10-01
SourceDOI 10.1016/j.cels.2018.05.013 · PMID 29960883

Where this study fits

How this study connects to the pathway map, open questions, people and other studies in the Atlas.

People in the Atlas

  • Hiroyuki Kubota first author · 2 studies in the Atlas

    Systems biologist who showed that the insulin pathway carries different messages in the timing of its signal, and that S6K, the mTORC1 target, reads only the fast part

  • Shinya Kuroda last author · 2 studies in the Atlas

    Leads a systems biology lab that studies how cells decode the timing of hormone signals, with insulin and mTORC1-S6K as the main test case

  • Shinsuke Uda 2 studies in the Atlas

    Systems biologist who uses information theory and modelling. He co-authored the studies showing that the insulin–AKT pathway encodes insulin’s timing pattern, and that S6K, downstream of mTORC1, reads only the fast, pulse-like part.

More: 2 other authors

No profile yet: Matsuzaki F, Yamauchi Y

Related studies

More related studies

All 212 studies on mTORC1

Topics

FoxOAkt/PKBmTORC1S6K1

Extracted findings

These fields were extracted from the paper with AI assistance and have not been checked against the source. Read them as a pointer into the paper, not as curated claims; where they disagree with the curated summary above, the curated summary stands.

InterventionInsulin delivered in different temporal patterns under clamp
TargetInsulin receptor; AKT; S6K; FoxO1/G6Pase; GSK3-beta
ModelRat
EffectS6K selectively decodes additional insulin secretion in vivo

Cite this paper

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Kubota, H., Uda, S., Matsuzaki, F., Yamauchi, Y., & Kuroda, S. (2018). In Vivo Decoding Mechanisms of the Temporal Patterns of Blood Insulin by the Insulin-AKT Pathway in the Liver. Cell Systems. https://doi.org/10.1016/j.cels.2018.05.013

@article{KUB2018,
  author       = {Kubota, H. and Uda, S. and Matsuzaki, F. and Yamauchi, Y. and Kuroda, S.},
  title        = {{In Vivo Decoding Mechanisms of the Temporal Patterns of Blood Insulin by the Insulin-AKT Pathway in the Liver}},
  journal      = {Cell Systems},
  year         = {2018},
  doi          = {10.1016/j.cels.2018.05.013},
  note         = {PMID: 29960883},
}

Cite this Atlas record

The record is the Atlas's own work — the evidence label, the extracted findings and the links. It is cited as part of the dataset, not as the paper. 

Barton, O. (2026). Oliver's mTOR Atlas (record KUB2018) [Data set]. https://mtor-atlas.org/study/KUB2018/ · Dataset DOI 10.5281/zenodo.22059963

@misc{atlas_KUB2018,
  author       = {Barton, Oliver},
  title        = {{Oliver's mTOR Atlas}, record KUB2018},
  howpublished = {Data set},
  year         = {2026},
  url          = {https://mtor-atlas.org/study/KUB2018/},
  doi          = {10.5281/zenodo.22059963}
}
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