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Related Experiment Video

Updated: Jan 3, 2026

Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations

Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations

Published on: December 16, 2017

Isolating live cells after high-throughput, long-term, time-lapse microscopy.

Scott Luro¹, Laurent Potvin-Trottier^2,3, Burak Okumus^2,4

¹Department of Systems Biology, Harvard Medical School, Boston, MA, USA. spl53@cornell.edu.

|November 27, 2019

Summary

This summary is machine-generated.

Introducing SIFT (single-cell isolation following time-lapse imaging), a new method for high-throughput genetic screening. SIFT accurately screens complex dynamic phenotypes by tracking cell lineages over generations, enabling synthetic biology discoveries.

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Area of Science:

Synthetic Biology
Microbiology
Genetic Engineering

Background:

Current high-throughput genetic screening platforms struggle to track dynamic cellular processes.
Existing methods often fail to distinguish mutants of interest from wild-type phenotypic outliers.
There is a need for advanced screening tools to analyze complex cellular behaviors over time.

Purpose of the Study:

To introduce a novel platform, SIFT (single-cell isolation following time-lapse imaging), for high-throughput genetic screening.
To overcome limitations of existing platforms in tracking dynamic processes and isolating specific cell lineages.
To enable accurate screening of complex phenotypes without genetic modifications or barcoding.

Main Methods:

SIFT involves time-lapse imaging and tracking of individual bacterial cells over multiple generations.
Cells of interest are isolated and propagated for downstream analysis under controlled growth conditions.
The platform characterizes tens of thousands of cell lineages daily, ensuring purity and avoiding perturbations.

Main Results:

SIFT successfully identified ultraprecise synthetic gene oscillators with a 30-fold range of average periods.
The platform demonstrated high accuracy in screening diverse dynamic phenotypes.
Novel design principles in synthetic biology were revealed through SIFT analysis.

Conclusions:

SIFT is a powerful tool for high-throughput screening of dynamic cellular phenotypes.
This method overcomes key limitations of current genetic screening technologies.
SIFT facilitates the discovery of new biological principles and the engineering of complex genetic circuits.