Literature DB >> 35524128

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

Stephan Kamrad1,2,3, Jürg Bähler4, Markus Ralser5,6.   

Abstract

Colony fitness screens are powerful approaches for functional genomics and genetics. This protocol describes experimental and computational procedures for assaying the fitness of thousands of microbial strains in numerous conditions in parallel. Data analysis is based on pyphe, an all-in-one bioinformatics toolbox for scanning, image analysis, data normalization, and interpretation. We describe a standard protocol where endpoint colony areas are used as fitness proxy and two variations on this, one using colony growth curves and one using colony viability staining with phloxine B. Different strategies for experimental design, normalization and quality control are discussed. Using these approaches, it is possible to collect hundreds of thousands of data points, with low technical noise levels around 5%, in an experiment typically lasting 2 weeks or less.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Cell viability; Colony; Fitness; Functional genomics; Growth curve; Large-scale phenotyping; Microbiology; Phenomics; Python software; Screen

Mesh:

Year:  2022        PMID: 35524128     DOI: 10.1007/978-1-0716-2257-5_21

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  14 in total

1.  Pyphe, a python toolbox for assessing microbial growth and cell viability in high-throughput colony screens.

Authors:  Stephan Kamrad; María Rodríguez-López; Cristina Cotobal; Clara Correia-Melo; Markus Ralser; Jürg Bähler
Journal:  Elife       Date:  2020-06-16       Impact factor: 8.140

2.  The genomic and phenotypic diversity of Schizosaccharomyces pombe.

Authors:  Daniel C Jeffares; Charalampos Rallis; Adrien Rieux; Doug Speed; Martin Převorovský; Tobias Mourier; Francesc X Marsellach; Zamin Iqbal; Winston Lau; Tammy M K Cheng; Rodrigo Pracana; Michael Mülleder; Jonathan L D Lawson; Anatole Chessel; Sendu Bala; Garrett Hellenthal; Brendan O'Fallon; Thomas Keane; Jared T Simpson; Leanne Bischof; Bartlomiej Tomiczek; Danny A Bitton; Theodora Sideri; Sandra Codlin; Josephine E E U Hellberg; Laurent van Trigt; Linda Jeffery; Juan-Juan Li; Sophie Atkinson; Malte Thodberg; Melanie Febrer; Kirsten McLay; Nizar Drou; William Brown; Jacqueline Hayles; Rafael E Carazo Salas; Markus Ralser; Nikolas Maniatis; David J Balding; Francois Balloux; Richard Durbin; Jürg Bähler
Journal:  Nat Genet       Date:  2015-02-09       Impact factor: 38.330

3.  A global genetic interaction network maps a wiring diagram of cellular function.

Authors:  Michael Costanzo; Benjamin VanderSluis; Elizabeth N Koch; Anastasia Baryshnikova; Carles Pons; Guihong Tan; Wen Wang; Matej Usaj; Julia Hanchard; Susan D Lee; Vicent Pelechano; Erin B Styles; Maximilian Billmann; Jolanda van Leeuwen; Nydia van Dyk; Zhen-Yuan Lin; Elena Kuzmin; Justin Nelson; Jeff S Piotrowski; Tharan Srikumar; Sondra Bahr; Yiqun Chen; Raamesh Deshpande; Christoph F Kurat; Sheena C Li; Zhijian Li; Mojca Mattiazzi Usaj; Hiroki Okada; Natasha Pascoe; Bryan-Joseph San Luis; Sara Sharifpoor; Emira Shuteriqi; Scott W Simpkins; Jamie Snider; Harsha Garadi Suresh; Yizhao Tan; Hongwei Zhu; Noel Malod-Dognin; Vuk Janjic; Natasa Przulj; Olga G Troyanskaya; Igor Stagljar; Tian Xia; Yoshikazu Ohya; Anne-Claude Gingras; Brian Raught; Michael Boutros; Lars M Steinmetz; Claire L Moore; Adam P Rosebrock; Amy A Caudy; Chad L Myers; Brenda Andrews; Charles Boone
Journal:  Science       Date:  2016-09-23       Impact factor: 47.728

4.  Predicting quantitative traits from genome and phenome with near perfect accuracy.

Authors:  Kaspar Märtens; Johan Hallin; Jonas Warringer; Gianni Liti; Leopold Parts
Journal:  Nat Commun       Date:  2016-05-10       Impact factor: 14.919

5.  SGAtools: one-stop analysis and visualization of array-based genetic interaction screens.

Authors:  Omar Wagih; Matej Usaj; Anastasia Baryshnikova; Benjamin VanderSluis; Elena Kuzmin; Michael Costanzo; Chad L Myers; Brenda J Andrews; Charles M Boone; Leopold Parts
Journal:  Nucleic Acids Res       Date:  2013-05-15       Impact factor: 16.971

6.  Colony-live--a high-throughput method for measuring microbial colony growth kinetics--reveals diverse growth effects of gene knockouts in Escherichia coli.

Authors:  Rikiya Takeuchi; Takeyuki Tamura; Toru Nakayashiki; Yuichirou Tanaka; Ai Muto; Barry L Wanner; Hirotada Mori
Journal:  BMC Microbiol       Date:  2014-06-26       Impact factor: 3.605

7.  Finding the sources of missing heritability in a yeast cross.

Authors:  Joshua S Bloom; Ian M Ehrenreich; Wesley T Loo; Thúy-Lan Võ Lite; Leonid Kruglyak
Journal:  Nature       Date:  2013-02-03       Impact factor: 49.962

8.  The contribution of non-essential Schizosaccharomyces pombe genes to fitness in response to altered nutrient supply and target of rapamycin activity.

Authors:  Shervi Lie; Peter Banks; Conor Lawless; David Lydall; Janni Petersen
Journal:  Open Biol       Date:  2018-05       Impact factor: 6.411

9.  Genome evolution across 1,011 Saccharomyces cerevisiae isolates.

Authors:  Jackson Peter; Matteo De Chiara; Anne Friedrich; Jia-Xing Yue; David Pflieger; Anders Bergström; Anastasie Sigwalt; Benjamin Barre; Kelle Freel; Agnès Llored; Corinne Cruaud; Karine Labadie; Jean-Marc Aury; Benjamin Istace; Kevin Lebrigand; Pascal Barbry; Stefan Engelen; Arnaud Lemainque; Patrick Wincker; Gianni Liti; Joseph Schacherer
Journal:  Nature       Date:  2018-04-11       Impact factor: 49.962

10.  Pyruvate kinase variant of fission yeast tunes carbon metabolism, cell regulation, growth and stress resistance.

Authors:  Stephan Kamrad; Jan Grossbach; Maria Rodríguez-López; Michael Mülleder; StJohn Townsend; Valentina Cappelletti; Gorjan Stojanovski; Clara Correia-Melo; Paola Picotti; Andreas Beyer; Markus Ralser; Jürg Bähler
Journal:  Mol Syst Biol       Date:  2020-04       Impact factor: 13.068

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