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High-Throughput, High-Precision Colony Phenotyping with Pyphe.

Stephan Kamrad1,2,3, Jürg Bähler1, Markus Ralser4,5

  • 1Department of Genetics, Evolution and Environment, Institute of Healthy Ageing, University College London, London, UK.

Methods in Molecular Biology (Clifton, N.J.)
|May 6, 2022
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Summary

This study presents a high-throughput method for microbial fitness screening using colony analysis. The protocol enables rapid data generation for functional genomics and genetics research.

Keywords:
Cell viabilityColonyFitnessFunctional genomicsGrowth curveLarge-scale phenotypingMicrobiologyPhenomicsPython softwareScreen

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Area of Science:

  • Microbiology
  • Functional Genomics
  • Bioinformatics

Background:

  • Colony fitness screens are essential for understanding microbial strain behavior.
  • High-throughput methods are needed to analyze large numbers of strains across diverse conditions.

Purpose of the Study:

  • To describe a protocol for parallel microbial fitness screening.
  • To introduce the pyphe bioinformatics toolbox for data analysis.

Main Methods:

  • Utilizing endpoint colony areas, growth curves, or viability staining (phloxine B) as fitness proxies.
  • Employing the pyphe toolbox for scanning, image analysis, normalization, and interpretation.
  • Implementing strategies for experimental design, normalization, and quality control.

Main Results:

  • The protocol allows for the assaying of thousands of microbial strains in parallel.
  • Data analysis is facilitated by the comprehensive pyphe bioinformatics toolbox.
  • Low technical noise levels (around 5%) are achieved.

Conclusions:

  • This protocol provides an efficient method for microbial fitness screening.
  • Experiments can be completed in two weeks or less, generating extensive datasets.
  • The approach is valuable for functional genomics and genetics studies.