Back

A metabolic model based on a pangenome core unveils new biochemical features of the phytopathogen Xylella fastidiosa

Corbin Agusti, P.; Alvarez-Herrera, M.; Roman Ecija, M.; Alvarez, P.; Tortajada, M.; Landa, B. B.; Pereto, J.

2026-03-25 systems biology
10.64898/2026.03.23.713690 bioRxiv
Show abstract

Xylella fastidiosa is a xylem-limited phytopathogen bacterium responsible for severe diseases in numerous plant species of major agricultural importance. Despite its economic impact, its metabolism remains poorly characterized due to the bacteriums fastidious growth and the limited availability of defined culture media. In this work, we reconstructed the first pangenome-based genome-scale metabolic model for X. fastidiosa, integrating the conserved metabolic capabilities of 18 strains representing five described subspecies. The resulting core metabolic model, Xfcore, was manually curated and used to investigate the metabolic potential of the species. Model simulations predict minimal nutritional requirements that guide the formulation of defined media capable of supporting biofilm formation in vitro. Analysis of the metabolic network also suggests an undescribed metabolic pathway that enables growth on acetate as a sole carbon source. Furthermore, the model predicts that X. fastidiosa could overproduce polyamines, compounds previously associated with virulence in other phytopathogens. Experimental analyses confirm the production and secretion of polyamines in several X. fastidiosa strains, providing the first in vitro evidence of polyamine production in this pathogen. These findings suggest that polyamine biosynthesis may represent an uncharacterized virulence factor in X. fastidiosa, potentially contributing to bacterial protection against host-induced oxidative stress. Overall, the Xfcore model provides a systems-level framework to explore the metabolism of X. fastidiosa, generate testable hypotheses about its physiology and virulence, and establish a basis for future strain-specific reconstructions and host-pathogen metabolic interaction studies.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
mSystems
361 papers in training set
Top 0.1%
22.5%
2
Nature Communications
4913 papers in training set
Top 18%
10.1%
3
npj Systems Biology and Applications
99 papers in training set
Top 0.2%
6.8%
4
Frontiers in Microbiology
375 papers in training set
Top 2%
4.9%
5
PLOS Computational Biology
1633 papers in training set
Top 7%
4.9%
6
Scientific Reports
3102 papers in training set
Top 37%
3.6%
50% of probability mass above
7
Communications Biology
886 papers in training set
Top 2%
3.6%
8
npj Biofilms and Microbiomes
56 papers in training set
Top 0.6%
2.9%
9
ISME Communications
103 papers in training set
Top 0.8%
2.4%
10
Computational and Structural Biotechnology Journal
216 papers in training set
Top 3%
2.1%
11
mBio
750 papers in training set
Top 7%
1.9%
12
Metabolic Engineering
68 papers in training set
Top 0.4%
1.8%
13
The ISME Journal
194 papers in training set
Top 1%
1.7%
14
Microbiology Spectrum
435 papers in training set
Top 3%
1.5%
15
Environmental Microbiology
119 papers in training set
Top 2%
1.3%
16
Applied and Environmental Microbiology
301 papers in training set
Top 2%
1.2%
17
Advanced Science
249 papers in training set
Top 15%
0.9%
18
Environmental Microbiome
26 papers in training set
Top 0.4%
0.9%
19
Nature Microbiology
133 papers in training set
Top 4%
0.9%
20
ACS Synthetic Biology
256 papers in training set
Top 2%
0.9%
21
iScience
1063 papers in training set
Top 29%
0.8%
22
The Plant Journal
197 papers in training set
Top 3%
0.8%
23
Frontiers in Bioengineering and Biotechnology
88 papers in training set
Top 3%
0.8%
24
eLife
5422 papers in training set
Top 55%
0.8%
25
Plant Physiology
217 papers in training set
Top 3%
0.7%
26
Environmental Microbiology Reports
27 papers in training set
Top 0.8%
0.7%
27
Microbiome
139 papers in training set
Top 3%
0.6%
28
Frontiers in Molecular Biosciences
100 papers in training set
Top 6%
0.6%
29
BMC Genomics
328 papers in training set
Top 7%
0.6%