MOTIVATION: Transposon insertion sequencing (Tn-Seq) is a microbial systems-level tool, that can determine on a genome-wide scale and in high-throughput, whether a gene, or a specific genomic region, is important for fitness under a specific experimental condition. RESULTS: Here, we present MAGenTA, a suite of analysis tools which accurately calculate the growth rate for each disrupted gene in the genome to enable the discovery of: (i) new leads for gene function, (ii) non-coding RNAs; (iii) genes, pathways and ncRNAs that are involved in tolerating drugs or induce disease; (iv) higher order genome organization; and (v) host-factors that affect bacterial host susceptibility. MAGenTA is a complete Tn-Seq analysis pipeline making sensitive genome-wide fitness (i.e. growth rate) analysis available for most transposons and Tn-Seq associated approaches (e.g. TraDis, HiTS, IN-Seq) and includes fitness (growth rate) calculations, sliding window analysis, bottleneck calculations and corrections, statistics to compare experiments and strains and genome-wide fitness visualization. AVAILABILITY AND IMPLEMENTATION: MAGenTA is available at the Galaxy public ToolShed repository and all source code can be found and are freely available at https://vanopijnenlab.github.io/MAGenTA/ . CONTACT: vanopijn@bc.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Transposon insertion sequencing (Tn-Seq) is a microbial systems-level tool, that can determine on a genome-wide scale and in high-throughput, whether a gene, or a specific genomic region, is important for fitness under a specific experimental condition. RESULTS: Here, we present MAGenTA, a suite of analysis tools which accurately calculate the growth rate for each disrupted gene in the genome to enable the discovery of: (i) new leads for gene function, (ii) non-coding RNAs; (iii) genes, pathways and ncRNAs that are involved in tolerating drugs or induce disease; (iv) higher order genome organization; and (v) host-factors that affect bacterial host susceptibility. MAGenTA is a complete Tn-Seq analysis pipeline making sensitive genome-wide fitness (i.e. growth rate) analysis available for most transposons and Tn-Seq associated approaches (e.g. TraDis, HiTS, IN-Seq) and includes fitness (growth rate) calculations, sliding window analysis, bottleneck calculations and corrections, statistics to compare experiments and strains and genome-wide fitness visualization. AVAILABILITY AND IMPLEMENTATION: MAGenTA is available at the Galaxy public ToolShed repository and all source code can be found and are freely available at https://vanopijnenlab.github.io/MAGenTA/ . CONTACT: vanopijn@bc.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Gemma C Langridge; Minh-Duy Phan; Daniel J Turner; Timothy T Perkins; Leopold Parts; Jana Haase; Ian Charles; Duncan J Maskell; Sarah E Peters; Gordon Dougan; John Wain; Julian Parkhill; A Keith Turner Journal: Genome Res Date: 2009-10-13 Impact factor: 9.043
Authors: Jeffrey D Gawronski; Sandy M S Wong; Georgia Giannoukos; Doyle V Ward; Brian J Akerley Journal: Proc Natl Acad Sci U S A Date: 2009-09-04 Impact factor: 11.205
Authors: Robert Carter; Joshua Wolf; Tim van Opijnen; Patricia M Flynn; Elaine I Tuomanen; Jason W Rosch; Martha Muller; Caroline Obert; Corinna Burnham; Beth Mann; Yimei Li; Randall T Hayden; Tamara Pestina; Derek Persons; Andrew Camilli Journal: Cell Host Microbe Date: 2014-05-14 Impact factor: 21.023
Authors: Yanjia J Zhang; Thomas R Ioerger; Curtis Huttenhower; Jarukit E Long; Christopher M Sassetti; James C Sacchettini; Eric J Rubin Journal: PLoS Pathog Date: 2012-09-27 Impact factor: 6.823
Authors: Beth Mann; Tim van Opijnen; Jianmin Wang; Caroline Obert; Yong-Dong Wang; Robert Carter; Daniel J McGoldrick; Granger Ridout; Andrew Camilli; Elaine I Tuomanen; Jason W Rosch Journal: PLoS Pathog Date: 2012-07-12 Impact factor: 6.823
Authors: Yoann Le Breton; Ashton T Belew; Kayla M Valdes; Emrul Islam; Patrick Curry; Hervé Tettelin; Mark E Shirtliff; Najib M El-Sayed; Kevin S McIver Journal: Sci Rep Date: 2015-05-21 Impact factor: 4.379
Authors: Aldert Zomer; Peter Burghout; Hester J Bootsma; Peter W M Hermans; Sacha A F T van Hijum Journal: PLoS One Date: 2012-08-10 Impact factor: 3.240
Authors: Yoann Le Breton; Ashton T Belew; Jeffrey A Freiberg; Ganesh S Sundar; Emrul Islam; Joshua Lieberman; Mark E Shirtliff; Hervé Tettelin; Najib M El-Sayed; Kevin S McIver Journal: PLoS Pathog Date: 2017-08-23 Impact factor: 6.823
Authors: Zhexian Liu; Polina Beskrovnaya; Ryan A Melnyk; Sarzana S Hossain; Sophie Khorasani; Lucy R O'Sullivan; Christina L Wiesmann; Jen Bush; Joël D Richard; Cara H Haney Journal: mBio Date: 2018-11-06 Impact factor: 7.867
Authors: Edward Geisinger; Germán Vargas-Cuebas; Nadav J Mortman; Sapna Syal; Yunfei Dai; Elizabeth L Wainwright; David Lazinski; Stephen Wood; Zeyu Zhu; Jon Anthony; Tim van Opijnen; Ralph R Isberg Journal: mBio Date: 2019-06-11 Impact factor: 7.867
Authors: Amy K Cain; Lars Barquist; Andrew L Goodman; Ian T Paulsen; Julian Parkhill; Tim van Opijnen Journal: Nat Rev Genet Date: 2020-06-12 Impact factor: 53.242