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Updated: May 23, 2025
Spatial and Temporal Analysis of Active ERK in the C. elegans Germline
Published on: November 29, 2016
Deciphering the history of ERK activity from fixed-cell immunofluorescence measurements
Abhineet Ram1, Michael Pargett1, Yongin Choi1
1Department of Molecular and Cellular Biology, University of California, Davis, CA, USA.
Abstract:
The RAS/ERK pathway plays a central role in diagnosis and therapy for many cancers. ERK activity is highly dynamic within individual cells and drives cell proliferation, metabolism, and other processes through effector proteins including c-Myc, c-Fos, Fra-1, and Egr-1. These proteins are sensitive to the dynamics of ERK activity, but it is not clear to what extent the pattern of ERK activity in an individual cell determines effector protein expression, or how much information about ERK dynamics is embedded in the pattern of effector expression. Here, we evaluate these relationships using live-cell biosensor measurements of ERK activity, multiplexed with immunofluorescence staining for downstream target proteins of the pathway. Combining these datasets with linear regression, machine learning, and differential equation models, we develop an interpretive framework for immunofluorescence data, wherein Fra-1 and pRb levels imply long-term activation of ERK signaling, while Egr-1 and c-Myc indicate more recent activation. Analysis of multiple cancer cell lines reveals a distorted relationship between ERK activity and cell state in malignant cells. We show that this framework can infer various classes of ERK dynamics from effector protein stains within a heterogeneous population, providing a basis for annotating ERK dynamics within fixed cells.
Insights
This study reveals how patterns of ERK pathway activity relate to effector protein expression in cancer cells. This framework helps infer ERK signaling dynamics from fixed cell data, aiding cancer diagnosis and therapy.
Area of Science:
- Molecular Biology
- Cell Biology
- Cancer Research
Background:
- The RAS/ERK pathway is crucial for cancer diagnosis and therapy.
- ERK activity dynamics influence cell processes via effector proteins like c-Myc and Fra-1.
- The link between ERK activity patterns and effector expression is not fully understood.
Purpose of the Study:
- To determine how ERK activity dynamics dictate effector protein expression.
- To quantify the information about ERK dynamics encoded in effector protein patterns.
- To develop a framework for interpreting immunofluorescence data of ERK pathway effectors.
Main Methods:
- Live-cell biosensor measurements of ERK activity.
- Multiplexed immunofluorescence staining for downstream effector proteins (c-Myc, c-Fos, Fra-1, Egr-1).
- Integration of data using linear regression, machine learning, and differential equation models.
Main Results:
- Developed an interpretive framework linking effector protein levels to ERK activity duration (Fra-1/pRb for long-term, Egr-1/c-Myc for recent).
- Observed distorted ERK activity-cell state relationships in malignant cells.
- Demonstrated the ability to infer diverse ERK dynamics from effector protein stains in heterogeneous cell populations.
Conclusions:
- Established a method to infer ERK signaling dynamics from fixed cell immunofluorescence data.
- Provided a basis for annotating ERK dynamics in cancer cells, potentially improving diagnosis and therapy.
- Highlighted alterations in ERK signaling regulation within cancer cells.
