# TnSeek: analysing Tn-seq data for multiple conditions and multiple species

Loïc Couderc, Erwan Gueguen, Maxime Brunin, Areski Flissi, Guillemette

Marot, Guy Condemine, Hélène Touzet

► To cite this version:

Loïc Couderc, Erwan Gueguen, Maxime Brunin, Areski Flissi, Guillemette Marot, et al. TnSeek: analysing Tn-seq data for multiple conditions and multiple species. Journées Ouvertes en Biologie, Informatique et Mathématiques (JOBIM 2022), Jul 2022, Rennes, France. hal-03827389

HAL Id: hal-03827389

https://hal.science/hal-03827389

Submitted on 24 Oct 2022

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Distributed under a Creative Commons Attribution 4.0 International License
# TnSeek : analysing Tn-seq data for multiple conditions and multiple species

Loïc Couderc¹, Erwan Gueguen², Maxime Brunin¹, Areski Flissi³, Guillemette Marot⁴, Guy Condemine² and Hélène Touzet³

1 Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, US 41 - UAR 2014 - PLBS - Plateforme bilille, F-59000 Lille, France
2 Univ. Lyon, Univ. Lyon 1, UMR CNRS 5240, Villeurbanne, France
3 Univ. Lille, CNRS, Centrale Lille, UMR 9189 CRISTAL, F-59000 Lille, France
4 Univ. Lille, CHU Lille, ULR 2694 - METRICS - Inria MODAL, F-59000 Lille, France

## Tn-seq → Transposon sequencing

Tn-seq is a genome-wide screening method that rapidly identifies, on a large panel of strains, genes related to a specific phenotype or growth condition in bacteria. It consists in random transposon mutagenesis in parallel coupled with high throughput sequencing.

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### Main steps

* creation of a pool of mutants by random insertion of a transposon

* growth (and selection)

* high-throughput sequencing of surviving cells

### Essential genes

genes essential for growth under a given condition.

### Conditionally essential genes

genes that are required for growth under one condition but not another

Example of applications: identification of virulence factors of pathogenic bacteria, identification of genes involved in antibioresistance, ...

## TnSeek → our pipeline, any number of conditions + any number of strains

<figure><img src="image_3.png" /></figure>

## TnSeek in practice → easy-to-install + easy-to-use

1. Download source at https://gitlab.cristal.univ-lille.fr/bonsai/tnseek

2. Build the Docker image and run it

3. Connect to the Shiny server at http://localhost:3838

implemented in Python and R
installation with docker
reports in R markdown

web application for exploration and visualization: R Shiny & SQLite

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<table><thead><tr><th>genus</th><th>strain</th><th>condition</th><th>genes</th><th>p-value histogram</th><th>volcano</th><th>all conditions</th></tr></thead><tbody><tr><td>Dickeya</td><td>Dickeya_dadantil_3937</td><td>water</td><td>tsv</td><td>graph</td><td>plot</td><td>tsv (Dickeya_dadantil_3937)</td></tr><tr><td>Dickeya</td><td>Dickeya_dadantil_3937</td><td>planta</td><td>tsv</td><td>graph</td><td>plot</td><td>tsv (Dickeya_dadantil_3937)</td></tr><tr><td>Dickeya</td><td>Dickeya_zeae_A586</td><td>water</td><td>tsv</td><td>graph</td><td>plot</td><td>tsv (Dickeya_zeae_A586)</td></tr><tr><td>Dickeya</td><td>Dickeya_zeae_A586</td><td>planta</td><td>tsv</td><td>graph</td><td>plot</td><td>tsv (Dickeya_zeae_A586)</td></tr><tr><td>Pectobacterium</td><td>Pectobacterium_aquaticum_A212</td><td>water</td><td>tsv</td><td>graph</td><td>plot</td><td>tsv (Pectobacterium_aquaticum_A212)</td></tr><tr><td>Pectobacterium</td><td>Pectobacterium_aquaticum_A212</td><td>planta</td><td>tsv</td><td>graph</td><td>plot</td><td>tsv (Pectobacterium_aquaticum_A212)</td></tr><tr><td>Pectobacterium</td><td>Pectobacterium_varetila_Δ73</td><td>water</td><td>tsv</td><td>graph</td><td>plot</td><td>tsv</td></tr></tbody></table>

Overall summary