The Metabolic Interplay between Plants and Phytopathogens
Abstract
:1. Introduction
2. Methods
2.1. Plant-Pathogen pairs, Sequence Information
Pathogen | Plant | Pathogen type | Unicellular/multicellular | Tissue colonisation | Obligate pathogen |
---|---|---|---|---|---|
Pseudomonas syringae pv. tomato (323) | Arabidopsis thaliana (3702) [1] | Bacterium/hemi-biotrophic [6] | unicellular | apoplast | no |
Xanthomonas oryzae pv. Oryzae(64187) | Oryza sativa (4530) [25] | Bacterium/biotrophic [29] | unicellular | apoplast | no |
Ustilago maydis (5270) | Zea mays (4577) [27] | Fungus/biotrophic [27] | multicellular | apoplast and cells | yes |
Melampsora larici-populina (203908) | Populus trichocarpa (3694) [30] | Fungus/biotrophic [30] | multicellular | apoplast and cells | yes |
Sclerotinia sclerotiorum (5180) | Glycine max (3847) [31] | Fungus/necrotrophic [32] | multicellular | apoplast | no |
Organism pair | Abbreviation | Number of proteins |
---|---|---|
Arabidopsis thaliana [33] | At | 221,677 |
Pseudomonas syringae pv. Tomato [34] | Ps | 41,274 |
Oryza sativa [35] | Os | 257,407 |
Xanthomonas oryzae pv. Oryzae [25,36] | Xo | 29,011 |
Zea mays [37] | Zm | 101,421 |
Ustilago maydis [38] | Um | 14,433 |
Populus trichocarpa [39] | Pt | 87,553 |
Melampsora larici-populina [40] | Ml | 16,384 |
Glycine max [41] | Gm | 35,645 |
Sclerotinia sclerotiorum | Ss | 30,901 |
2.2. Species-Independent Reaction Models
2.3. Network Curation and Gap-Filling
2.4. Interaction Analysis of Metabolic Networks
2.5. Network Comparison and Multidimensional Scaling (MDS)
2.6. Network Visualization
3. Results
3.1. The Genome-Scale Metabolic Networks
Organism | Kingdom | No. reactions (annotated) | No. reactions (curated) | No. metabolites (curated) | No. of added extension reactions |
At | Planta | 3,608 | 3,316 (91.9%) | 3,560 | 2 |
Ps | Bactera | 3,223 | 2,964 (92.0%) | 3,175 | NA |
Os | Planta | 3,680 | 3,357 (91.2%) | 3,617 | 1 |
Xo | Bacteria | 3,026 | 2,799 (92.5%) | 3,064 | NA |
Zm | Planta | 3,606 | 3,315 (91.9%) | 3,596 | 4 |
Um | Fungi | 3,398 | 3,107 (91.4%) | 3,398 | NA |
Pt | Planta | 3,758 | 3,442 (91.6%) | 3,653 | 1 |
Ml | Fungi | 3,368 | 3,084 (91.6%) | 3,356 | NA |
Gm | Planta | 3,380 | 3,130 (92.6%) | 3,446 | 4 |
Ss | Fungi | 3,505 | 3,200 (91.3%) | 3,493 | NA |
MC | 9,531 | 8,780 (92.1%) | 7,755 | NA |
3.2. Visualization of Pathogen-Plant Metabolic Networks
3.3. Network Analysis of Plant-Pathogen Network Pairs
gain | asymmetric gain plant | asymmetric gain pathogen | Jaccard distance | |
At - Ps | 1 | 34 | 146 | 0.216 |
Gm– Ss | 191 | 238 | 220 | 0.145 |
Os– Xo | 21 | 68 | 214 | 0.223 |
Pt– Ml | 2 | 14 | 301 | 0.140 |
Zm –Um | 8 | 19 | 308 | 0.122 |
4. Discussion and Conclusions
Supplementary Material
- (1)
- Navigable metabolic network maps for the plant-pathogen pairs At-Ps, Gm-Ss, Os-Xo, Pt-Ml, and Zm-Um.
- (2)
- The reactions list for all the species used in this research and MetaCyc.
- (3)
- Various plant-pathogen impairment profile plots.
Acknowledgments
Conflict of Interest
References
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Duan, G.; Christian, N.; Schwachtje, J.; Walther, D.; Ebenhöh, O. The Metabolic Interplay between Plants and Phytopathogens. Metabolites 2013, 3, 1-23. https://doi.org/10.3390/metabo3010001
Duan G, Christian N, Schwachtje J, Walther D, Ebenhöh O. The Metabolic Interplay between Plants and Phytopathogens. Metabolites. 2013; 3(1):1-23. https://doi.org/10.3390/metabo3010001
Chicago/Turabian StyleDuan, Guangyou, Nils Christian, Jens Schwachtje, Dirk Walther, and Oliver Ebenhöh. 2013. "The Metabolic Interplay between Plants and Phytopathogens" Metabolites 3, no. 1: 1-23. https://doi.org/10.3390/metabo3010001
APA StyleDuan, G., Christian, N., Schwachtje, J., Walther, D., & Ebenhöh, O. (2013). The Metabolic Interplay between Plants and Phytopathogens. Metabolites, 3(1), 1-23. https://doi.org/10.3390/metabo3010001