Michael R. MacArthur

Dr. Michael R. MacArthur

Department of Health Sciences and Technology, ETH Zürich, Schorenstrasse 16, 8603 Schwerzenbach, Switzerland

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2018 in Cell
Verified
Journal Article
Closed access
ALAlban Longchamp
Alban Longchamp
TMTeodelinda Mirabella
Teodelinda Mirabella
AAAlessandro Arduini
Alessandro Arduini
MMMichael R. MacArthur
Michael R. MacArthur
Abhirup DasAbhirup Das
Abhirup Das
JMJames R. Mitchell
James R. Mitchell

1 March 2021 in eLife
Verified
Journal Article
Open access
MTMargaret E Torrence
Margaret E Torrence
MMMichael R. MacArthur
Michael R. MacArthur
AHAaron M Hosios
Aaron M Hosios
AVAlexander J Valvezan
Alexander J Valvezan
JAJohn M Asara
John M Asara
BMBrendan D Manning
Brendan D Manning
The mechanistic target of rapamycin complex 1 (mTORC1) stimulates a coordinated anabolic program in response to growth-promoting signals. Paradoxically, recent studies indicate that mTORC1 can activate the transcription factor ATF4 through mechanisms distinct from its canonical induction by the integrated stress response (ISR). However, its broader roles as a downstream target of mTORC1 are unknown. Therefore, we directly compared ATF4-dependent transcriptional changes induced upon insulin-stimulated mTORC1 signaling to those activated by the ISR. In multiple mouse embryo fibroblast and human cancer cell lines, the mTORC1-ATF4 pathway stimulated expression of only a subset of the ATF4 target genes induced by the ISR, including genes involved in amino acid uptake, synthesis, and tRNA charging. We demonstrate that ATF4 is a metabolic effector of mTORC1 involved in both its established role in promoting protein synthesis and in a previously unappreciated function for mTORC1 in stimulating cellular cystine uptake and glutathione synthesis.

5 August 2019 in Nature Immunology
Verified
Journal Article
Closed access
PDF file
PLP. Kent Langston
P. Kent Langston
ANAya Nambu
Aya Nambu
JJJonathan Jung
Jonathan Jung
MSMunehiko Shibata
Munehiko Shibata
HAH. Ibrahim Aksoylar
H. Ibrahim Aksoylar
THTiffany Horng
Tiffany Horng

15 September 2020 in Nature Communications
Verified
Journal Article
Open access
PDF file
MSMichael B. Schultz
Michael B. Schultz
AKAlice E. Kane
Alice E. Kane
SMSarah J. Mitchell
Sarah J. Mitchell
MMMichael R. MacArthur
Michael R. MacArthur
EWElisa Warner
Elisa Warner
DSDavid A. Sinclair
David A. Sinclair
The identification of genes and interventions that slow or reverse aging is hampered by the lack of non-invasive metrics that can predict the life expectancy of pre-clinical models. Frailty Indices (FIs) in mice are composite measures of health that are cost-effective and non-invasive, but whether they can accurately predict health and lifespan is not known. Here, mouse FIs are scored longitudinally until death and machine learning is employed to develop two clocks. A random forest regression is trained on FI components for chronological age to generate the FRIGHT (FrailtyInferredGeriatricHealthTimeline) clock, a strong predictor of chronological age. A second model is trained on remaining lifespan to generate the AFRAID (Analysis ofFrailty andDeath) clock, which accurately predicts life expectancy and the efficacy of a lifespan-extending intervention up to a year in advance. Adoption of these clocks should accelerate the identification of longevity genes and aging interventions.

15 July 2021 in Cell Metabolism
Verified
Journal Article
Closed access
MMMichael R. MacArthur
Michael R. MacArthur
SMSarah J. Mitchell
Sarah J. Mitchell
JTJ. Humberto Treviño-Villarreal
J. Humberto Treviño-Villarreal
YGYohann Grondin
Yohann Grondin
JRJustin S. Reynolds
Justin S. Reynolds
JMJames R. Mitchell
James R. Mitchell

2 November 2018 in JCI Insight
Verified
Journal Article
Open access
PDF file
JTJ. Humberto Treviño-Villarreal
J. Humberto Treviño-Villarreal
JRJustin S. Reynolds
Justin S. Reynolds
ABAlexander Bartelt
Alexander Bartelt
PLP. Kent Langston
P. Kent Langston
MMMichael R. MacArthur
Michael R. MacArthur
JMJames R. Mitchell
James R. Mitchell
Hypertriglyceridemia is an independent risk factor for cardiovascular disease. Dietary interventions based on protein restriction (PR) reduce circulating triglycerides (TGs), but underlying mechanisms and clinical relevance remain unclear. Here, we show that 1 week of a protein-free diet without enforced calorie restriction significantly lowered circulating TGs in both lean and diet-induced obese mice. Mechanistically, the TG-lowering effect of PR was due, in part, to changes in very low–density lipoprotein (VLDL) metabolism both in liver and peripheral tissues. In the periphery, PR stimulated VLDL-TG consumption by increasing VLDL-bound APOA5 expression and promoting VLDL-TG hydrolysis and clearance from circulation. The PR-mediated increase in Apoa5 expression was controlled by the transcription factor CREBH, which coordinately regulated hepatic expression of fatty acid oxidation–related genes, including Fgf21 and Ppara . The CREBH-APOA5 axis activation upon PR was intact in mice lacking the GCN2-dependent amino acid–sensing arm of the integrated stress response. However, constitutive hepatic activation of the amino acid–responsive kinase mTORC1 compromised CREBH activation, leading to blunted APOA5 expression and PR-recalcitrant hypertriglyceridemia. PR also contributed to hypotriglyceridemia by reducing the rate of VLDL-TG secretion, independently of activation of the CREBH-APOA5 axis. Finally, a randomized controlled clinical trial revealed that 4–6 weeks of reduced protein intake (7%–9% of calories) decreased VLDL particle number, increased VLDL-bound APOA5 expression, and lowered plasma TGs, consistent with mechanistic conservation of PR-mediated hypotriglyceridemia in humans with translational potential as a nutraceutical intervention for dyslipidemia.