A high-throughput platform for single-molecule tracking identifies drug interaction and cellular mechanisms

The regulation of cell physiology depends largely upon interactions of functionally distinct proteins and cellular components. These interactions may be transient or long-lived, but often affect protein motion. Measurement of protein dynamics within a cellular environment, particularly while perturbing protein function with small molecules, may enable dissection of key interactions and facilitate drug discovery; however, current approaches are limited by throughput with respect to data acquisition and analysis. As a result, studies using super-resolution imaging are typically drawing conclusions from tens of cells and a few experimental conditions tested. We addressed these limitations by developing a high-throughput single-molecule tracking (htSMT) platform for pharmacologic dissection of protein dynamics in living cells at an unprecedented scale (capable of imaging >10 6 cells/day and screening >10 4 compounds). We applied htSMT to measure the cellular dynamics of fluorescently tagged estrogen receptor (ER) and screened a diverse library to identify small molecules that perturbed ER function in real time. With this one experimental modality, we determined the potency, pathway selectivity, target engagement, and mechanism of action for identified hits. Kinetic htSMT experiments were capable of distinguishing between on-target and on-pathway modulators of ER signaling. Integrated pathway analysis recapitulated the network of known ER interaction partners and suggested potentially novel, kinase-mediated regulatory mechanisms. The sensitivity of htSMT revealed a new correlation between ER dynamics and the ability of ER antagonists to suppress cancer cell growth. Therefore, measuring protein motion at scale is a powerful method to investigate dynamic interactions among proteins and may facilitate the identification and characterization of novel therapeutics.

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Publication Details

Journal
eLife
Published
2024-12-13
DOI
https://doi.org/10.7554/elife.93183.3
Citations
9
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
5.96
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article

A high-throughput platform for single-molecule tracking identifies drug interaction and cellular mechanisms

Jifu Li, Jaclyn J. Ho, Alec Heckert, Sarah E. Pierce et al.
9 citations
eLife
Cell Image Analysis Techniques
5.96
article

A high-throughput platform for single-molecule tracking identifies drug interaction and cellular mechanisms

Jifu Li, Jaclyn J. Ho, Alec Heckert, Sarah E. Pierce, Mason Bretan, Akshay Sule, Sebastia Agramunt Puig, Hilary P. Beck, Yangzhong Tang, Connor Stashko, Kevin Lin, Aaron Klammer, Kelsey Ford, Reed Kelso, Ruchira Krishnamurthy, Ruensern Tan, Adi Hanuka, Daniel J. Anderson, Brian Margolin, Ruth Godbey, Xavier Darzacq, Lakshmi B. Akella, Hanzhe Chen, David T. McSwiggen, Eric Gonzalez, Patrick McNamara, Helen Liu, Stephanie Johnson, Russell Berman, Laurence Meyer
article en
9 citations

Abstract

The regulation of cell physiology depends largely upon interactions of functionally distinct proteins and cellular components. These interactions may be transient or long-lived, but often affect protein motion. Measurement of protein dynamics within a cellular environment, particularly while perturbing protein function with small molecules, may enable dissection of key interactions and facilitate drug discovery; however, current approaches are limited by throughput with respect to data acquisition and analysis. As a result, studies using super-resolution imaging are typically drawing conclusions from tens of cells and a few experimental conditions tested. We addressed these limitations by developing a high-throughput single-molecule tracking (htSMT) platform for pharmacologic dissection of protein dynamics in living cells at an unprecedented scale (capable of imaging >10 6 cells/day and screening >10 4 compounds). We applied htSMT to measure the cellular dynamics of fluorescently tagged estrogen receptor (ER) and screened a diverse library to identify small molecules that perturbed ER function in real time. With this one experimental modality, we determined the potency, pathway selectivity, target engagement, and mechanism of action for identified hits. Kinetic htSMT experiments were capable of distinguishing between on-target and on-pathway modulators of ER signaling. Integrated pathway analysis recapitulated the network of known ER interaction partners and suggested potentially novel, kinase-mediated regulatory mechanisms. The sensitivity of htSMT revealed a new correlation between ER dynamics and the ability of ER antagonists to suppress cancer cell growth. Therefore, measuring protein motion at scale is a powerful method to investigate dynamic interactions among proteins and may facilitate the identification and characterization of novel therapeutics.

eLifeVol. 12
University of California, Berkeley (US)
Good health and well-being
Openalex Percentile: Top 4%
Cell Image Analysis Techniques
5.96
DOIOpen Access PDFOpenAlex
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