Literature DB >> 33180303

Tn-Core: Functionally Interpreting Transposon-Sequencing Data with Metabolic Network Analysis.

George C diCenzo1, Marco Galardini2,3, Marco Fondi4.   

Abstract

Transposon-sequencing (Tn-seq) is a powerful tool facilitating the genome-scale identification of genes required for bacterial growth or survival in an environment of interest. However, Tn-seq suffers from two primary drawbacks: (1) genetic interactions masking phenotypes thereby resulting in important cellular functions remaining undiscovered and (2) a difficulty in easily going from a list of essential genes to a functional understanding of cell physiology. Tn-Core is a computational toolbox to help overcome these limitations through combining the output of Tn-seq studies with in silico genome-scale metabolic networks. In this chapter, we outline how to use Tn-Core to contextualize Tn-seq data (and optionally RNA-seq data) with metabolic models to: (1) generate a complete view of essential metabolism, (2) prepare context-specific metabolic models for further computational analyses, and (3) refine genome-scale metabolic models. All functions of Tn-Core are provided for download from a freely available repository ( github.com/diCenzo-GC/Tn-Core ), and a web-app requiring limited computational experience is also available ( combo.dbe.unifi.it /tncore).

Keywords:  Bacterial metabolism; Essential genes; Functional genomics; GENRE; Genome-scale metabolic network analysis; Insertion-sequencing; RNA-sequencing; Transposon-sequencing

Year:  2021        PMID: 33180303     DOI: 10.1007/978-1-0716-0822-7_15

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  1 in total

Review 1.  Genomic landscapes of bacterial transposons and their applications in strain improvement.

Authors:  Shengrui Wu; Pingfang Tian; Tianwei Tan
Journal:  Appl Microbiol Biotechnol       Date:  2022-09-12       Impact factor: 5.560

  1 in total

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