Bioprocess and Biosystems Engineering

, Volume 41, Issue 5, pp 657–669 | Cite as

An enhanced genome-scale metabolic reconstruction of Streptomyces clavuligerus identifies novel strain improvement strategies

  • León Toro
  • Laura Pinilla
  • Claudio Avignone-Rossa
  • Rigoberto Ríos-Estepa
Research Paper

Abstract

In this work, we expanded and updated a genome-scale metabolic model of Streptomyces clavuligerus. The model includes 1021 genes and 1494 biochemical reactions; genome-reaction information was curated and new features related to clavam metabolism and to the biomass synthesis equation were incorporated. The model was validated using experimental data from the literature and simulations were performed to predict cellular growth and clavulanic acid biosynthesis. Flux balance analysis (FBA) showed that limiting concentrations of phosphate and an excess of ammonia accumulation are unfavorable for growth and clavulanic acid biosynthesis. The evaluation of different objective functions for FBA showed that maximization of ATP yields the best predictions for cellular behavior in continuous cultures, while the maximization of growth rate provides better predictions for batch cultures. Through gene essentiality analysis, 130 essential genes were found using a limited in silico media, while 100 essential genes were identified in amino acid-supplemented media. Finally, a strain design was carried out to identify candidate genes to be overexpressed or knocked out so as to maximize antibiotic biosynthesis. Interestingly, potential metabolic engineering targets, identified in this study, have not been tested experimentally.

Keywords

Genome-scale metabolic reconstruction Flux balance analysis Streptomyces clavuligerus Strain improvement Clavulanic acid 

Notes

Acknowledgements

The authors thank Professor Marnix H. Medema and Mohammad Tauqeer Alam for providing the template for the Streptomyces clavuligerus model, and Professor Andrzej Kierzek for advice on the SurreyFBA platform [15]. This work was supported by Departamento Administrativo de Ciencia, Tecnología e Innovación—COLCIENCIAS-Colombia (Grant no. 111566945929). L. Toro and L. Pinilla thank COLCIENCIAS-Colombia for scholarships. C. Avignone-Rossa was supported by Grant BB/L02683X/1 from the Biotechnology and Biological Sciences Research Council (BBSRC, United Kingdom).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

449_2018_1900_MOESM1_ESM.xlsx (383 kb)
Supplementary Material 1. Model content and Simulation Results. Spreadsheet 1: Reactions included in the S. clavuligerus Sclav_iLT1021 model. Spreadsheet 2: Metabolites included the in S. clavuligerus Sclav_iLT1021 model. Spreadsheet 3: Biomass composition. Spreadsheet 4: MC3 output (gapfilling). Spreadsheet 5: Gene and reaction essentiality for complex media (CPX) and defined media (GAPI). Spreadsheet 6: RoBoKoD analysis, OE: Overexpression ranking, KO: Knockout ranking. Spreadsheet 7: Published experimental data used for testing the different objective functions. (XLSX 382 KB)
449_2018_1900_MOESM2_ESM.xml (2.3 mb)
Supplementary material 2: Metabolic model in SBML format (XML) (XML 2336 KB)
449_2018_1900_MOESM3_ESM.tiff (8.6 mb)
Supplementary figure S1: Validation of the Sclav_iLT1021 model using the experimental data from the literature a. Chemostat data from the literature [19]. Color Code: blue and green: specific glycerol and oxygen uptake rate, respectively; black and yellow: specific CO2 and clavulanic acid secretion rate, respectively. a. Model predictions of the specific growth rate and experimental data from the literature [19]. (TIFF 8790 KB)
449_2018_1900_MOESM4_ESM.tiff (2.1 mb)
Supplementary figure S2: Scatter plot for the correlation of the different objective functions evaluated. a Chemostat, P-limited media [19]; b Chemostat, P-limited media (additional constraints) [28]; c Batch, medium supplemented media with amino acids [31]. (TIFF 2164 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Grupo de Bioprocesos, Instituto de BiologíaUniversidad de AntioquiaMedellínColombia
  2. 2.Department of Microbial Sciences, School of Biosciences and MedicineUniversity of SurreyGuildfordUK
  3. 3.Grupo de Bioprocesos, Departamento de Ingeniería QuímicaUniversidad de AntioquiaMedellínColombia

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