Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Pareto-optimal synthesis of multiple glycans in Golgi compartments.

Biophysical journal·2026
Same author

Multinucleation as a recurring evolutionary strategy for scaling and plasticity.

Current biology : CB·2026
Same author

A Tubules-First Model for the Origin of Eukaryotic Membrane Traffic.

Annual review of biophysics·2026
Same author

Molecular pathways for learning in the single-cell Stentor coeruleus.

Current biology : CB·2026
Same author

Septin-mediated coupling of protein import and division during chloroplast evolution.

bioRxiv : the preprint server for biology·2026
Same author

OpenPore: A low-cost, portable, battery-powered exponential decay pulse generator for electroporation.

HardwareX·2026

Related Experiment Video

Updated: May 2, 2026

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques
09:48

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

9.2K

Exploiting cell-to-cell variability to detect cellular perturbations.

Gautam Dey1, Gagan D Gupta2, Balaji Ramalingam3

  • 1Stanford University, Palo Alto, California, United States of America.

Plos One
|March 6, 2014
PubMed
Summary
This summary is machine-generated.

Analyzing cell populations reveals that changes in phenotypic distribution shape can identify genes affecting cellular processes. This method uncovers biological information from cell-to-cell variability, even effects missed by population-averaged analysis.

More Related Videos

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions
07:59

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Published on: March 22, 2018

6.6K
Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells
10:21

Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells

Published on: September 16, 2020

5.3K

Related Experiment Videos

Last Updated: May 2, 2026

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques
09:48

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

9.2K
An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions
07:59

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Published on: March 22, 2018

6.6K
Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells
10:21

Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells

Published on: September 16, 2020

5.3K

Area of Science:

  • Cell Biology
  • Genomics
  • High-content screening

Background:

  • Single-cell measurements yield phenotypic distributions with mean, variance, and shape.
  • Cellular process perturbations can alter these distribution shapes.

Purpose of the Study:

  • To demonstrate that phenotypic distribution shape changes can signal cellular process perturbations.
  • To develop a method for screening underlying molecular machinery using cell-to-cell variability.

Main Methods:

  • Analysis of Drosophila S2R+ cell line images after RNA interference (RNAi) perturbation.
  • Tracking 27 single-cell features related to endocytosis, cell, and nuclear morphology.
  • Utilizing a Kolmogorov-Smirnov-like statistic to detect reproducible shape deviations in feature distributions.

Main Results:

  • Replicate measurements showed reproducible distribution shapes despite variable means and variances.
  • RNAi-mediated down-regulation of 1072 out of 7131 genes induced reliable shape deviations in at least one feature.
  • Identified genes influencing cell morphology, nuclear morphology, and endocytosis pathways.
  • Detected biological effects invisible to population-averaged analysis by preserving single-cell data.

Conclusions:

  • Cell-to-cell variability contains accessible and useful biological information.
  • Phenotypic distribution shape analysis is a viable method for screening molecular machinery.
  • This approach can be integrated into existing cell-based assays for enhanced discovery.