Phenotype-based Screening
Phenotype-based Screening - Related Videos
09:40
RNAi Screening to Identify Postembryonic Phenotypes in C. elegans
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Cited by 9 •
2012
We describe a sensitized method to identify postembryonic regulators of protein expression and localization in C. elegans using an RNAi-based genomic screen and an integrated transgene that expresses a functional, fluorescently tagged protein.
08:12
High-throughput Screening for Protein-based Inheritance in S. cerevisiae
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Cited by 2 •
2017
This protocol describes a high-throughput methodology to functionally screen for protein-based inheritance in S. cerevisiae.
07:03
Large Scale Zebrafish-Based In vivo Small Molecule Screen
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Cited by 18 •
2010
Zebrafish has emerged as a powerful in vivo platform for phenotype-based drug screens and chemical genetic analysis. Here, we demonstrate a simple, practical method for large-scale screening of small molecules using zebrafish embryos.
15:28
A Microscopic Phenotypic Assay for the Quantification of Intracellular Mycobacteria Adapted for High-throughput/High-content Screening
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Cited by 30 •
2014
Here, we describe a phenotypic assay applicable to the High-throughput/High-content screens of small-interfering synthetic RNA (siRNA), chemical compound, and Mycobacterium tuberculosis mutant libraries. This method relies on the detection of fluorescently labeled Mycobacterium tuberculosis within fluorescently labeled host cell using automated confocal microscopy.
11:44
Generation and Multi-phenotypic High-content Screening of Coxiella burnetii Transposon Mutants
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Cited by 28 •
2015
Coxiella burnetii is an obligate intracellular Gram-negative bacterium responsible for the zoonotic disease Q fever. Here we describe methods for the generation of Coxiella fluorescent transposon mutants as well as the automated identification and analysis of the resulting internalization, replication and cytotoxic phenotypes.
FAQs
The strategy can detect a useful biological effect before researchers know which molecule or pathway produces it. By starting with a measurable change in morphology, behavior, viability, or another functional trait, the screen can expose unexpected mechanisms and disease-relevant pathways. This makes it particularly valuable for exploratory studies where existing molecular knowledge does not yet identify a suitable target.
Chemical and genetic libraries provide different kinds of perturbations, while the selected readout determines which biological consequences become visible. Morphology can capture structural changes, behavior can report organismal function, and viability can indicate whether a perturbation supports survival. Matching the perturbation set with a relevant functional measurement helps researchers identify hits that are meaningful for the biological question.
Rather than selecting compounds or genes because they are expected to affect a specified molecular target, researchers select perturbations according to the traits they change. This target-independent starting point can uncover relationships that were not anticipated in advance, although the resulting hits require follow-up assays to connect the observed phenotype with an underlying mechanism.
A typical workflow begins by exposing cells or model organisms to a library of chemical or genetic perturbations. Researchers then quantify selected traits, such as morphology, behavior, viability, or another functional readout, and identify perturbations associated with relevant changes. Promising hits are subsequently examined in follow-up assays to confirm that the observed effects are reproducible and biologically meaningful.
Initial screening identifies perturbations associated with an observable change, but that result alone does not establish how the effect occurs. Follow-up assays provide a way to confirm promising hits and examine their relationship to the original phenotype. This additional step helps distinguish findings worth pursuing from observations that do not support further investigation.
The approach supports drug discovery by identifying compounds that produce desired biological effects without requiring a fully specified target at the outset. In functional genomics, researchers can use genetic perturbations to investigate how genes influence observable traits. Its use with complex biological models also helps connect cellular or organismal phenotypes with disease-relevant pathways.