Cargando…
AlbaTraDIS: Comparative analysis of large datasets from parallel transposon mutagenesis experiments
Bacteria need to survive in a wide range of environments. Currently, there is an incomplete understanding of the genetic basis for mechanisms underpinning survival in stressful conditions, such as the presence of anti-microbials. Transposon directed insertion-site sequencing (TraDIS) is a powerful t...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390408/ https://www.ncbi.nlm.nih.gov/pubmed/32678849 http://dx.doi.org/10.1371/journal.pcbi.1007980 |
_version_ | 1783564452770086912 |
---|---|
author | Page, Andrew J. Bastkowski, Sarah Yasir, Muhammad Turner, A. Keith Le Viet, Thanh Savva, George M. Webber, Mark A. Charles, Ian G. |
author_facet | Page, Andrew J. Bastkowski, Sarah Yasir, Muhammad Turner, A. Keith Le Viet, Thanh Savva, George M. Webber, Mark A. Charles, Ian G. |
author_sort | Page, Andrew J. |
collection | PubMed |
description | Bacteria need to survive in a wide range of environments. Currently, there is an incomplete understanding of the genetic basis for mechanisms underpinning survival in stressful conditions, such as the presence of anti-microbials. Transposon directed insertion-site sequencing (TraDIS) is a powerful tool to identify genes and networks which are involved in survival and fitness under a given condition by simultaneously assaying the fitness of millions of mutants, thereby relating genotype to phenotype and contributing to an understanding of bacterial cell biology. A recent refinement of this approach allows the roles of essential genes in conditional stress survival to be inferred by altering their expression. These advancements combined with the rapidly falling costs of sequencing now allows comparisons between multiple experiments to identify commonalities in stress responses to different conditions. This capacity however poses a new challenge for analysis of multiple data sets in conjunction. To address this analysis need, we have developed ‘AlbaTraDIS’; a software application for rapid large-scale comparative analysis of TraDIS experiments that predicts the impact of transposon insertions on nearby genes. AlbaTraDIS can identify genes which are up or down regulated, or inactivated, between multiple conditions, producing a filtered list of genes for further experimental validation as well as several accompanying data visualisations. We demonstrate the utility of our new approach by applying it to identify genes used by Escherichia coli to survive in a wide range of different concentrations of the biocide Triclosan. AlbaTraDIS identified all well characterised Triclosan resistance genes, including the primary target, fabI. A number of new loci were also implicated in Triclosan resistance and the predicted phenotypes for a selection of these were validated experimentally with results being consistent with predictions. AlbaTraDIS provides a simple and rapid method to analyse multiple transposon mutagenesis data sets allowing this technology to be used at large scale. To our knowledge this is the only tool currently available that can perform these tasks. AlbaTraDIS is written in Python 3 and is available under the open source licence GNU GPL 3 from https://github.com/quadram-institute-bioscience/albatradis. |
format | Online Article Text |
id | pubmed-7390408 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-73904082020-08-05 AlbaTraDIS: Comparative analysis of large datasets from parallel transposon mutagenesis experiments Page, Andrew J. Bastkowski, Sarah Yasir, Muhammad Turner, A. Keith Le Viet, Thanh Savva, George M. Webber, Mark A. Charles, Ian G. PLoS Comput Biol Research Article Bacteria need to survive in a wide range of environments. Currently, there is an incomplete understanding of the genetic basis for mechanisms underpinning survival in stressful conditions, such as the presence of anti-microbials. Transposon directed insertion-site sequencing (TraDIS) is a powerful tool to identify genes and networks which are involved in survival and fitness under a given condition by simultaneously assaying the fitness of millions of mutants, thereby relating genotype to phenotype and contributing to an understanding of bacterial cell biology. A recent refinement of this approach allows the roles of essential genes in conditional stress survival to be inferred by altering their expression. These advancements combined with the rapidly falling costs of sequencing now allows comparisons between multiple experiments to identify commonalities in stress responses to different conditions. This capacity however poses a new challenge for analysis of multiple data sets in conjunction. To address this analysis need, we have developed ‘AlbaTraDIS’; a software application for rapid large-scale comparative analysis of TraDIS experiments that predicts the impact of transposon insertions on nearby genes. AlbaTraDIS can identify genes which are up or down regulated, or inactivated, between multiple conditions, producing a filtered list of genes for further experimental validation as well as several accompanying data visualisations. We demonstrate the utility of our new approach by applying it to identify genes used by Escherichia coli to survive in a wide range of different concentrations of the biocide Triclosan. AlbaTraDIS identified all well characterised Triclosan resistance genes, including the primary target, fabI. A number of new loci were also implicated in Triclosan resistance and the predicted phenotypes for a selection of these were validated experimentally with results being consistent with predictions. AlbaTraDIS provides a simple and rapid method to analyse multiple transposon mutagenesis data sets allowing this technology to be used at large scale. To our knowledge this is the only tool currently available that can perform these tasks. AlbaTraDIS is written in Python 3 and is available under the open source licence GNU GPL 3 from https://github.com/quadram-institute-bioscience/albatradis. Public Library of Science 2020-07-17 /pmc/articles/PMC7390408/ /pubmed/32678849 http://dx.doi.org/10.1371/journal.pcbi.1007980 Text en © 2020 Page et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Page, Andrew J. Bastkowski, Sarah Yasir, Muhammad Turner, A. Keith Le Viet, Thanh Savva, George M. Webber, Mark A. Charles, Ian G. AlbaTraDIS: Comparative analysis of large datasets from parallel transposon mutagenesis experiments |
title | AlbaTraDIS: Comparative analysis of large datasets from parallel transposon mutagenesis experiments |
title_full | AlbaTraDIS: Comparative analysis of large datasets from parallel transposon mutagenesis experiments |
title_fullStr | AlbaTraDIS: Comparative analysis of large datasets from parallel transposon mutagenesis experiments |
title_full_unstemmed | AlbaTraDIS: Comparative analysis of large datasets from parallel transposon mutagenesis experiments |
title_short | AlbaTraDIS: Comparative analysis of large datasets from parallel transposon mutagenesis experiments |
title_sort | albatradis: comparative analysis of large datasets from parallel transposon mutagenesis experiments |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390408/ https://www.ncbi.nlm.nih.gov/pubmed/32678849 http://dx.doi.org/10.1371/journal.pcbi.1007980 |
work_keys_str_mv | AT pageandrewj albatradiscomparativeanalysisoflargedatasetsfromparalleltransposonmutagenesisexperiments AT bastkowskisarah albatradiscomparativeanalysisoflargedatasetsfromparalleltransposonmutagenesisexperiments AT yasirmuhammad albatradiscomparativeanalysisoflargedatasetsfromparalleltransposonmutagenesisexperiments AT turnerakeith albatradiscomparativeanalysisoflargedatasetsfromparalleltransposonmutagenesisexperiments AT levietthanh albatradiscomparativeanalysisoflargedatasetsfromparalleltransposonmutagenesisexperiments AT savvageorgem albatradiscomparativeanalysisoflargedatasetsfromparalleltransposonmutagenesisexperiments AT webbermarka albatradiscomparativeanalysisoflargedatasetsfromparalleltransposonmutagenesisexperiments AT charlesiang albatradiscomparativeanalysisoflargedatasetsfromparalleltransposonmutagenesisexperiments |