Predictive modeling of Pseudomonas syringae virulence on bean using gradient boosted decision trees Article Swipe
Renan N. D. Almeida
,
Michael E. Greenberg
,
Cedoljub Bundalovic-Torma
,
Alexandre Martel
,
Pauline W. Wang
,
Maggie A. Middleton
,
Syama Chatterton
,
Darrell Desveaux
,
David S. Guttman
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1371/journal.ppat.1010716
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1371/journal.ppat.1010716
Pseudomonas syringae is a genetically diverse bacterial species complex responsible for numerous agronomically important crop diseases. Individual P . syringae isolates are assigned pathovar designations based on their host of isolation and the associated disease symptoms, and these pathovar designations are often assumed to reflect host specificity although this assumption has rarely been rigorously tested. Here we developed a rapid seed infection assay to measure the virulence of 121 diverse P . syringae isolates on common bean ( Phaseolus vulgaris ). This collection includes P . syringae phylogroup 2 (PG2) bean isolates (pathovar syringae ) that cause bacterial spot disease and P . syringae phylogroup 3 (PG3) bean isolates (pathovar phaseolicola ) that cause the more serious halo blight disease. We found that bean isolates in general were significantly more virulent on bean than non-bean isolates and observed no significant virulence difference between the PG2 and PG3 bean isolates. However, when we compared virulence within PGs we found that PG3 bean isolates were significantly more virulent than PG3 non-bean isolates, while there was no significant difference in virulence between PG2 bean and non-bean isolates. These results indicate that PG3 strains have a higher level of host specificity than PG2 strains. We then used gradient boosting machine learning to predict each strain’s virulence on bean based on whole genome k-mers, type III secreted effector k-mers, and the presence/absence of type III effectors and phytotoxins. Our model performed best using whole genome data and was able to predict virulence with high accuracy (mean absolute error = 0.05). Finally, we functionally validated the model by predicting virulence for 16 strains and found that 15 (94%) had virulence levels within the bounds of estimated predictions. This study strengthens the hypothesis that P . syringae PG2 strains have evolved a different lifestyle than other P . syringae strains as reflected in their lower level of host specificity. It also acts as a proof-of-principle to demonstrate the power of machine learning for predicting host specific adaptation.
Related Topics
Concepts
Pathovar
Pseudomonas syringae
Virulence
Biology
Phaseolus
Host (biology)
Microbiology
Type three secretion system
Pathogen
Pseudomonas aeruginosa
Pseudomonadaceae
Genetics
Bacteria
Botany
Gene
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.ppat.1010716
- https://journals.plos.org/plospathogens/article/file?id=10.1371/journal.ppat.1010716&type=printable
- OA Status
- gold
- Cited By
- 14
- References
- 58
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4287509875
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4287509875Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1371/journal.ppat.1010716Digital Object Identifier
- Title
-
Predictive modeling of Pseudomonas syringae virulence on bean using gradient boosted decision treesWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2022Year of publication
- Publication date
-
2022-07-25Full publication date if available
- Authors
-
Renan N. D. Almeida, Michael E. Greenberg, Cedoljub Bundalovic-Torma, Alexandre Martel, Pauline W. Wang, Maggie A. Middleton, Syama Chatterton, Darrell Desveaux, David S. GuttmanList of authors in order
- Landing page
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https://doi.org/10.1371/journal.ppat.1010716Publisher landing page
- PDF URL
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https://journals.plos.org/plospathogens/article/file?id=10.1371/journal.ppat.1010716&type=printableDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://journals.plos.org/plospathogens/article/file?id=10.1371/journal.ppat.1010716&type=printableDirect OA link when available
- Concepts
-
Pathovar, Pseudomonas syringae, Virulence, Biology, Phaseolus, Host (biology), Microbiology, Type three secretion system, Pathogen, Pseudomonas aeruginosa, Pseudomonadaceae, Genetics, Bacteria, Botany, GeneTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
14Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 4, 2023: 7, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
58Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.demonstrate | 319 |
| abstract_inverted_index.genetically | 4 |
| abstract_inverted_index.responsible | 9 |
| abstract_inverted_index.significant | 139, 174 |
| abstract_inverted_index.specificity | 46, 196 |
| abstract_inverted_index.strengthens | 283 |
| abstract_inverted_index.designations | 24, 39 |
| abstract_inverted_index.functionally | 257 |
| abstract_inverted_index.phaseolicola | 110 |
| abstract_inverted_index.phytotoxins. | 232 |
| abstract_inverted_index.predictions. | 280 |
| abstract_inverted_index.specificity. | 311 |
| abstract_inverted_index.agronomically | 12 |
| abstract_inverted_index.significantly | 128, 163 |
| abstract_inverted_index.presence/absence | 226 |
| abstract_inverted_index.proof-of-principle | 317 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5035892394, https://openalex.org/A5069091375, https://openalex.org/A5042591265, https://openalex.org/A5082297360, https://openalex.org/A5068099853, https://openalex.org/A5089335497, https://openalex.org/A5033088858, https://openalex.org/A5024994951, https://openalex.org/A5090460944 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 9 |
| corresponding_institution_ids | https://openalex.org/I1331897569, https://openalex.org/I185261750, https://openalex.org/I4390039381 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/15 |
| sustainable_development_goals[0].score | 0.5199999809265137 |
| sustainable_development_goals[0].display_name | Life in Land |
| citation_normalized_percentile.value | 0.90821104 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |