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A tool named Iris for versatile high-throughput phenotyping in microorganisms
Advances in our ability to systematically introduce and track controlled genetic variance in microbes have fueled high-throughput reverse genetics approaches in the past decade. When coupled to quantitative readouts, such approaches are extremely powerful at elucidating gene function and providing i...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5464397/ https://www.ncbi.nlm.nih.gov/pubmed/28211844 http://dx.doi.org/10.1038/nmicrobiol.2017.14 |
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author | Kritikos, George Banzhaf, Manuel Herrera-Dominguez, Lucia Koumoutsi, Alexandra Wartel, Morgane Zietek, Matylda Typas, Athanasios |
author_facet | Kritikos, George Banzhaf, Manuel Herrera-Dominguez, Lucia Koumoutsi, Alexandra Wartel, Morgane Zietek, Matylda Typas, Athanasios |
author_sort | Kritikos, George |
collection | PubMed |
description | Advances in our ability to systematically introduce and track controlled genetic variance in microbes have fueled high-throughput reverse genetics approaches in the past decade. When coupled to quantitative readouts, such approaches are extremely powerful at elucidating gene function and providing insights into the underlying pathways and the overall cellular network organization. Yet, until now all efforts for quantifying microbial macroscopic phenotypes have been restricted to monitoring growth in a small number of model microbes. We developed an image analysis software named Iris, which allows for systematic exploration of a number of orthogonal-to-growth processes, including biofilm formation, colony morphogenesis, envelope biogenesis, sporulation and reporter activity. In addition, Iris provides more sensitive growth measurements than current available software, and is compatible with a variety of different microbes, as well as with endpoint or kinetic data. We used Iris to reanalyze existing chemical genomics data in Escherichia coli and to perform proof-of-principle screens on colony biofilm formation and morphogenesis of different bacterial species and the pathogenic fungus, Candida albicans. Thereby we recapitulated existing knowledge but also identified a plethora of additional genes and pathways involved in both processes. |
format | Online Article Text |
id | pubmed-5464397 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
record_format | MEDLINE/PubMed |
spelling | pubmed-54643972017-08-17 A tool named Iris for versatile high-throughput phenotyping in microorganisms Kritikos, George Banzhaf, Manuel Herrera-Dominguez, Lucia Koumoutsi, Alexandra Wartel, Morgane Zietek, Matylda Typas, Athanasios Nat Microbiol Article Advances in our ability to systematically introduce and track controlled genetic variance in microbes have fueled high-throughput reverse genetics approaches in the past decade. When coupled to quantitative readouts, such approaches are extremely powerful at elucidating gene function and providing insights into the underlying pathways and the overall cellular network organization. Yet, until now all efforts for quantifying microbial macroscopic phenotypes have been restricted to monitoring growth in a small number of model microbes. We developed an image analysis software named Iris, which allows for systematic exploration of a number of orthogonal-to-growth processes, including biofilm formation, colony morphogenesis, envelope biogenesis, sporulation and reporter activity. In addition, Iris provides more sensitive growth measurements than current available software, and is compatible with a variety of different microbes, as well as with endpoint or kinetic data. We used Iris to reanalyze existing chemical genomics data in Escherichia coli and to perform proof-of-principle screens on colony biofilm formation and morphogenesis of different bacterial species and the pathogenic fungus, Candida albicans. Thereby we recapitulated existing knowledge but also identified a plethora of additional genes and pathways involved in both processes. 2017-02-17 /pmc/articles/PMC5464397/ /pubmed/28211844 http://dx.doi.org/10.1038/nmicrobiol.2017.14 Text en http://www.nature.com/authors/editorial_policies/license.html#terms Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Kritikos, George Banzhaf, Manuel Herrera-Dominguez, Lucia Koumoutsi, Alexandra Wartel, Morgane Zietek, Matylda Typas, Athanasios A tool named Iris for versatile high-throughput phenotyping in microorganisms |
title | A tool named Iris for versatile high-throughput phenotyping in microorganisms |
title_full | A tool named Iris for versatile high-throughput phenotyping in microorganisms |
title_fullStr | A tool named Iris for versatile high-throughput phenotyping in microorganisms |
title_full_unstemmed | A tool named Iris for versatile high-throughput phenotyping in microorganisms |
title_short | A tool named Iris for versatile high-throughput phenotyping in microorganisms |
title_sort | tool named iris for versatile high-throughput phenotyping in microorganisms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5464397/ https://www.ncbi.nlm.nih.gov/pubmed/28211844 http://dx.doi.org/10.1038/nmicrobiol.2017.14 |
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