Literature DB >> 22252737

Genome-scale metabolic representation of Amycolatopsis balhimycina.

Wanwipa Vongsangnak1, Luís Filipe Figueiredo, Jochen Förster, Tilmann Weber, Jette Thykaer, Evi Stegmann, Wolfgang Wohlleben, Jens Nielsen.   

Abstract

Infection caused by methicillin-resistant Staphylococcus aureus (MRSA) is an increasing societal problem. Typically, glycopeptide antibiotics are used in the treatment of these infections. The most comprehensively studied glycopeptide antibiotic biosynthetic pathway is that of balhimycin biosynthesis in Amycolatopsis balhimycina. The balhimycin yield obtained by A. balhimycina is, however, low and there is therefore a need to improve balhimycin production. In this study, we performed genome sequencing, assembly and annotation analysis of A. balhimycina and further used these annotated data to reconstruct a genome-scale metabolic model for the organism. Here we generated an almost complete A. balhimycina genome sequence comprising 10,562,587 base pairs assembled into 2,153 contigs. The high GC-genome (∼ 69%) includes 8,585 open reading frames (ORFs). We used our integrative toolbox called SEQTOR for functional annotation and then integrated annotated data with biochemical and physiological information available for this organism to reconstruct a genome-scale metabolic model of A. balhimycina. The resulting metabolic model contains 583 ORFs as protein encoding genes (7% of the predicted 8,585 ORFs), 407 EC numbers, 647 metabolites and 1,363 metabolic reactions. During the analysis of the metabolic model, linear, quadratic and evolutionary programming algorithms using flux balance analysis (FBA), minimization of metabolic adjustment (MOMA), and OptGene, respectively were applied as well as phenotypic behavior and improved balhimycin production were simulated. The A. balhimycina model shows a good agreement between in silico data and experimental data and also identifies key reactions associated with increased balhimycin production. The reconstruction of the genome-scale metabolic model of A. balhimycina serves as a basis for physiological characterization. The model allows a rational design of engineering strategies for increasing balhimycin production in A. balhimycina and glycopeptide production in general.
Copyright © 2012 Wiley Periodicals, Inc.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 22252737     DOI: 10.1002/bit.24436

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  4 in total

1.  New Molecular Tools for Regulation and Improvement of A40926 Glycopeptide Antibiotic Production in Nonomuraea gerenzanensis ATCC 39727.

Authors:  Oleksandr Yushchuk; Andres Andreo-Vidal; Giorgia Letizia Marcone; Mervyn Bibb; Flavia Marinelli; Elisa Binda
Journal:  Front Microbiol       Date:  2020-01-21       Impact factor: 5.640

2.  A metabolite-centric view on flux distributions in genome-scale metabolic models.

Authors:  S Alexander Riemer; René Rex; Dietmar Schomburg
Journal:  BMC Syst Biol       Date:  2013-04-12

3.  MEMOSys 2.0: an update of the bioinformatics database for genome-scale models and genomic data.

Authors:  Stephan Pabinger; Rene Snajder; Timo Hardiman; Michaela Willi; Andreas Dander; Zlatko Trajanoski
Journal:  Database (Oxford)       Date:  2014-02-14       Impact factor: 3.451

4.  The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases.

Authors:  Ron Caspi; Tomer Altman; Richard Billington; Kate Dreher; Hartmut Foerster; Carol A Fulcher; Timothy A Holland; Ingrid M Keseler; Anamika Kothari; Aya Kubo; Markus Krummenacker; Mario Latendresse; Lukas A Mueller; Quang Ong; Suzanne Paley; Pallavi Subhraveti; Daniel S Weaver; Deepika Weerasinghe; Peifen Zhang; Peter D Karp
Journal:  Nucleic Acids Res       Date:  2013-11-12       Impact factor: 16.971

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.