AlbaTraDIS

AlbaTraDIS performs large-scale comparative analysis of Transposon Directed Insertion-site Sequencing (TraDIS) experiments to identify genes influencing bacterial survival under environmental stresses such as antimicrobial exposure.


Key Features:

  • Comparative Analysis: Compares multiple TraDIS datasets simultaneously to identify common genetic responses across experimental conditions.
  • Impact Prediction: Predicts the impact of transposon insertions on nearby genes to infer disruptions of gene expression and function.
  • Statistical Analysis: Applies statistical methods from the Bio-TraDIS toolkit to identify significant genetic elements involved in phenotypes.
  • Data Visualization: Produces visualizations to explore patterns and interpret TraDIS results.
  • Experimental Validation Support: Generates filtered lists of candidate genes implicated in specific phenotypes to guide experimental validation.

Scientific Applications:

  • Bacterial stress survival studies: Used to dissect genetic determinants of bacterial survival and adaptation under environmental stresses and antimicrobial exposure.
  • Triclosan resistance in Escherichia coli: Applied to identify genes involved in E. coli resistance to the biocide Triclosan, confirming known loci such as fabI and highlighting novel candidate loci with experimental validation.

Methodology:

Integrates and analyzes large-scale TraDIS datasets, predicts impacts of transposon insertions on nearby genes, and applies statistical methods from the Bio-TraDIS toolkit; implemented in Python 3.

Topics

Details

License:
GPL-3.0
Tool Type:
command-line tool
Programming Languages:
Python
Added:
1/18/2021
Last Updated:
1/21/2021

Operations

Publications

Page AJ, Bastkowski S, Yasir M, Turner AK, Le Viet T, Savva GM, Webber MA, Charles IG. AlbaTraDIS: Comparative analysis of large datasets from parallel transposon mutagenesis experiments. PLOS Computational Biology. 2020;16(7):e1007980. doi:10.1371/journal.pcbi.1007980. PMID:32678849. PMCID:PMC7390408.

PMID: 32678849
PMCID: PMC7390408
Funding: - BBSRC Core Capability Grant: BB/CCG1860/1 - BBSRC Institute Strategic Programme Microbes in the Food Chain: BB/R012504/1 and BBS/E/F/000PR10349