Taivan Batjargal, Francesca Zappa, Ryan J Grant, Robert A Piscopio, Alex Chialastri, Siddharth S Dey, Diego Acosta-Alvear, Maxwell Z Wilson
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引用次数: 0
Abstract
The integrated stress response (ISR) is a conserved signaling network that detects aberrations and computes cellular responses. Dissecting these computations has been difficult because physical and chemical inducers of stress activate multiple parallel pathways. To overcome this challenge, we engineered a photo-switchable control over the ISR sensor kinase PKR (opto-PKR), enabling virtual, on-target activation. Using light to control opto-PKR dynamics, we traced information flow through the transcriptome and for key downstream ISR effectors. Our analyses revealed a biphasic, proportional transcriptional response with two dynamic modes, transient and gradual, that correspond to adaptive and terminal outcomes. We then constructed an ordinary differential equation (ODE) model of the ISR, which demonstrated the dependence of future stress responses on past stress. Finally, we tested our model using high-throughput light-delivery to map the stress memory landscape. Our results demonstrate that cells encode information in stress levels, durations, and the timing between encounters. A record of this paper's transparent peer review process is included in the supplemental information.
Cell SystemsMedicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍:
In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.