Next Article in Journal
New R-Based Methodology to Optimize the Identification of Root Endophytes against Heterobasidion parviporum
Previous Article in Journal
Lysis Profiles of Salmonella Phages on Salmonella Isolates from Various Sources and Efficiency of a Phage Cocktail against S. Enteritidis and S. Typhimurium
Previous Article in Special Issue
Green Technology: Bacteria-Based Approach Could Lead to Unsuspected Microbe–Plant–Animal Interactions
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Microorganisms 2019, 7(4), 101; https://doi.org/10.3390/microorganisms7040101

Metabolic Modeling of Pectobacterium parmentieri SCC3193 Provides Insights into Metabolic Pathways of Plant Pathogenic Bacteria

1
Department of Biotechnology, Intercollegiate Faculty of Biotechnology, University of Gdansk and Medical University of Gdansk, 58 Abrahama Street, 80-307 Gdansk, Poland
2
Department of Biology, University of Florence, via Madonna del Piano 6, Sesto Fiorentino, 50019 Florence, Italy
3
Department of Agri-food Production and Environmental Sciences, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Received: 17 February 2019 / Revised: 26 March 2019 / Accepted: 2 April 2019 / Published: 5 April 2019
(This article belongs to the Special Issue Macro and Microorganism Interactions)
  |  
PDF [1426 KB, uploaded 19 April 2019]
  |  

Abstract

Understanding plant–microbe interactions is crucial for improving plants’ productivity and protection. Constraint-based metabolic modeling is one of the possible ways to investigate the bacterial adaptation to different ecological niches and may give insights into the metabolic versatility of plant pathogenic bacteria. We reconstructed a raw metabolic model of the emerging plant pathogenic bacterium Pectobacterium parmentieri SCC3193 with the use of KBase. The model was curated by using inParanoind and phenotypic data generated with the use of the OmniLog system. Metabolic modeling was performed through COBRApy Toolbox v. 0.10.1. The curated metabolic model of P. parmentieri SCC3193 is highly reliable, as in silico obtained results overlapped up to 91% with experimental data on carbon utilization phenotypes. By mean of flux balance analysis (FBA), we predicted the metabolic adaptation of P. parmentieri SCC3193 to two different ecological niches, relevant for the persistence and plant colonization by this bacterium: soil and the rhizosphere. We performed in silico gene deletions to predict the set of essential core genes for this bacterium to grow in such environments. We anticipate that our metabolic model will be a valuable element for defining a set of metabolic targets to control infection and spreading of this plant pathogen. View Full-Text
Keywords: Flux Balance Analysis; plant pathogenic bacteria; bacterial adaptation; metabolic reactions Flux Balance Analysis; plant pathogenic bacteria; bacterial adaptation; metabolic reactions
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Zoledowska, S.; Presta, L.; Fondi, M.; Decorosi, F.; Giovannetti, L.; Mengoni, A.; Lojkowska, E. Metabolic Modeling of Pectobacterium parmentieri SCC3193 Provides Insights into Metabolic Pathways of Plant Pathogenic Bacteria. Microorganisms 2019, 7, 101.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Microorganisms EISSN 2076-2607 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top