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A tool-kit for high-throughput, quantitative analyses of genetic interactions in E. coli
Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in S. cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological infer...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2700713/ https://www.ncbi.nlm.nih.gov/pubmed/19160513 |
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author | Typas, Athanasios Nichols, Robert J. Siegele, Deborah A. Shales, Michael Collins, Sean Lim, Bentley Braberg, Hannes Yamamoto, Natsuko Takeuchi, Rikiya Wanner, Barry L. Mori, Hirotada Weissman, Jonathan S. Krogan, Nevan J. Gross, Carol A. |
author_facet | Typas, Athanasios Nichols, Robert J. Siegele, Deborah A. Shales, Michael Collins, Sean Lim, Bentley Braberg, Hannes Yamamoto, Natsuko Takeuchi, Rikiya Wanner, Barry L. Mori, Hirotada Weissman, Jonathan S. Krogan, Nevan J. Gross, Carol A. |
author_sort | Typas, Athanasios |
collection | PubMed |
description | Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in S. cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here, we describe a method based on F-driven conjugation, which allows for high-throughput generation of double mutants in E. coli. This method, termed Genetic Interaction ANalysis Technology for E. coli (GIANT-coli), permits us to systematically generate and array double mutant cells on solid media, in high-density arrays. We show that colony size provides a robust and quantitative output of cellular fitness and that GIANT-coli can recapitulate known synthetic interactions and identify new negative (synthetic sickness/lethality) and positive (suppressive/epistatic) relationships. Finally, we describe a complementary strategy for suppressor mutant identification on a genome-wide level. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli. |
format | Text |
id | pubmed-2700713 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
record_format | MEDLINE/PubMed |
spelling | pubmed-27007132009-06-23 A tool-kit for high-throughput, quantitative analyses of genetic interactions in E. coli Typas, Athanasios Nichols, Robert J. Siegele, Deborah A. Shales, Michael Collins, Sean Lim, Bentley Braberg, Hannes Yamamoto, Natsuko Takeuchi, Rikiya Wanner, Barry L. Mori, Hirotada Weissman, Jonathan S. Krogan, Nevan J. Gross, Carol A. Nat Methods Article Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in S. cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here, we describe a method based on F-driven conjugation, which allows for high-throughput generation of double mutants in E. coli. This method, termed Genetic Interaction ANalysis Technology for E. coli (GIANT-coli), permits us to systematically generate and array double mutant cells on solid media, in high-density arrays. We show that colony size provides a robust and quantitative output of cellular fitness and that GIANT-coli can recapitulate known synthetic interactions and identify new negative (synthetic sickness/lethality) and positive (suppressive/epistatic) relationships. Finally, we describe a complementary strategy for suppressor mutant identification on a genome-wide level. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli. 2008-09 /pmc/articles/PMC2700713/ /pubmed/19160513 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 Typas, Athanasios Nichols, Robert J. Siegele, Deborah A. Shales, Michael Collins, Sean Lim, Bentley Braberg, Hannes Yamamoto, Natsuko Takeuchi, Rikiya Wanner, Barry L. Mori, Hirotada Weissman, Jonathan S. Krogan, Nevan J. Gross, Carol A. A tool-kit for high-throughput, quantitative analyses of genetic interactions in E. coli |
title | A tool-kit for high-throughput, quantitative analyses of genetic interactions in E. coli |
title_full | A tool-kit for high-throughput, quantitative analyses of genetic interactions in E. coli |
title_fullStr | A tool-kit for high-throughput, quantitative analyses of genetic interactions in E. coli |
title_full_unstemmed | A tool-kit for high-throughput, quantitative analyses of genetic interactions in E. coli |
title_short | A tool-kit for high-throughput, quantitative analyses of genetic interactions in E. coli |
title_sort | tool-kit for high-throughput, quantitative analyses of genetic interactions in e. coli |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2700713/ https://www.ncbi.nlm.nih.gov/pubmed/19160513 |
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