Literature DB >> 31863076

A workflow for generating multi-strain genome-scale metabolic models of prokaryotes.

Charles J Norsigian1, Xin Fang1, Yara Seif1, Jonathan M Monk1, Bernhard O Palsson2,3,4.   

Abstract

Genome-scale models (GEMs) of bacterial strains' metabolism have been formulated and used over the past 20 years. Recently, with the number of genome sequences exponentially increasing, multi-strain GEMs have proved valuable to define the properties of a species. Here, through four major stages, we extend the original Protocol used to generate a GEM for a single strain to enable multi-strain GEMs: (i) obtain or generate a high-quality model of a reference strain; (ii) compare the genome sequence between a reference strain and target strains to generate a homology matrix; (iii) generate draft strain-specific models from the homology matrix; and (iv) manually curate draft models. These multi-strain GEMs can be used to study pan-metabolic capabilities and strain-specific differences across a species, thus providing insights into its range of lifestyles. Unlike the original Protocol, this procedure is scalable and can be partly automated with the Supplementary Jupyter notebook Tutorial. This Protocol Extension joins the ranks of other comparable methods for generating models such as CarveMe and KBase. This extension of the original Protocol takes on the order of weeks to multiple months to complete depending on the availability of a suitable reference model.

Entities:  

Mesh:

Year:  2019        PMID: 31863076      PMCID: PMC7017905          DOI: 10.1038/s41596-019-0254-3

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  10 in total

Review 1.  Path to improving the life cycle and quality of genome-scale models of metabolism.

Authors:  Yara Seif; Bernhard Ørn Palsson
Journal:  Cell Syst       Date:  2021-09-22       Impact factor: 11.091

Review 2.  Mathematical models to study the biology of pathogens and the infectious diseases they cause.

Authors:  Joao B Xavier; Jonathan M Monk; Saugat Poudel; Charles J Norsigian; Anand V Sastry; Chen Liao; Jose Bento; Marc A Suchard; Mario L Arrieta-Ortiz; Eliza J R Peterson; Nitin S Baliga; Thomas Stoeger; Felicia Ruffin; Reese A K Richardson; Catherine A Gao; Thomas D Horvath; Anthony M Haag; Qinglong Wu; Tor Savidge; Michael R Yeaman
Journal:  iScience       Date:  2022-03-15

3.  PhenoMapping: a protocol to map cellular phenotypes to metabolic bottlenecks, identify conditional essentiality, and curate metabolic models.

Authors:  Anush Chiappino-Pepe; Vassily Hatzimanikatis
Journal:  STAR Protoc       Date:  2021-01-22

4.  High-Quality Genome-Scale Models From Error-Prone, Long-Read Assemblies.

Authors:  Jared T Broddrick; Richard Szubin; Charles J Norsigian; Jonathan M Monk; Bernhard O Palsson; Mary N Parenteau
Journal:  Front Microbiol       Date:  2020-11-12       Impact factor: 5.640

5.  Adaptation to Varying Salinity in Halomonas elongata: Much More Than Ectoine Accumulation.

Authors:  Karina Hobmeier; Martina Cantone; Quynh Anh Nguyen; Katharina Pflüger-Grau; Andreas Kremling; Hans Jörg Kunte; Friedhelm Pfeiffer; Alberto Marin-Sanguino
Journal:  Front Microbiol       Date:  2022-03-30       Impact factor: 5.640

6.  Systems biology approach to functionally assess the Clostridioides difficile pangenome reveals genetic diversity with discriminatory power.

Authors:  Charles J Norsigian; Heather A Danhof; Colleen K Brand; Firas S Midani; Jared T Broddrick; Tor C Savidge; Robert A Britton; Bernhard O Palsson; Jennifer K Spinler; Jonathan M Monk
Journal:  Proc Natl Acad Sci U S A       Date:  2022-04-27       Impact factor: 12.779

7.  Genome-scale metabolic network reconstructions of diverse Escherichia strains reveal strain-specific adaptations.

Authors:  Jonathan M Monk
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2022-08-22       Impact factor: 6.671

8.  Host-mycobiome metabolic interactions in health and disease.

Authors:  Neelu Begum; Azadeh Harzandi; Sunjae Lee; Mathias Uhlen; David L Moyes; Saeed Shoaie
Journal:  Gut Microbes       Date:  2022 Jan-Dec

Review 9.  Antibiotic resistance: Time of synthesis in a post-genomic age.

Authors:  Teresa Gil-Gil; Luz Edith Ochoa-Sánchez; Fernando Baquero; José Luis Martínez
Journal:  Comput Struct Biotechnol J       Date:  2021-05-21       Impact factor: 7.271

10.  A curated collection of Klebsiella metabolic models reveals variable substrate usage and gene essentiality.

Authors:  Jane Hawkey; Ben Vezina; Jonathan M Monk; Louise M Judd; Taylor Harshegyi; Sebastián López-Fernández; Carla Rodrigues; Sylvain Brisse; Kathryn E Holt; Kelly L Wyres
Journal:  Genome Res       Date:  2022-03-11       Impact factor: 9.438

  10 in total

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