Identity
Canonical name: Pseudomonas putida. 1
Known alias: Putida, the label used for this organism in the report. 1
Stable external identifier: No stable external identifier was reported in the source document. 1
Evidence from co-fitness and co-inheritance analysis
Pseudomonas putida was one of the 9 organisms included in the primary analysis of laboratory-measured gene co-fitness and pangenome gene co-occurrence. 1
The dataset contained 128 genomes, 5,409 pangenome clusters, and 458,688 cofit pairs for Pseudomonas putida. 1
At the pairwise level, Pseudomonas putida had a delta phi of -0.000, with 205,323 cofit pairs, a mean phi of 0.171 for cofit pairs, a mean phi of 0.171 for prevalence-matched random pairs, and a Mann–Whitney p-value of 0.41. 1 This result does not provide evidence that pairwise co-fitness predicted gene co-occurrence in Pseudomonas putida under the reported analysis. 1
Pseudomonas putida contributed 38 independent component analysis (ICA) modules, where ICA identifies coordinated multi-gene variation patterns, and 6 modules (16%) were significant. 1 Within its modules, the mean phi was 0.266 compared with a prevalence-matched null mean of 0.202. 1 This module-level result supports the broader finding that coordinated multi-gene modules may show stronger co-inheritance than individual pairwise co-fitness relationships, although the signal was significant for only 6 of 38 modules. 1
Evidence from pathway completeness, fitness, and carbon ecology
In the gapmind pilot, Pseudomonas putida had complete predictions for 18 of 18 amino-acid biosynthesis pathways (100%), including serine biosynthesis, and 1,041 total GapMind predictions. 2 This computational result refines the co-fitness profile with evidence of broad pathway completeness, but does not establish that those pathways or their genes are essential for viability. 2
The Pseudomonas putida KT2440 strain was one of 7 Tier 1 organisms with matching GapMind and Fitness Browser data in the capability-versus-dependency analysis. 3 This supports the existing GapMind evidence while refining it with a direct comparison between predicted pathway capability and experimentally measured fitness dependence; the report does not assign a separate four-way classification to this organism in the entity-level results. 3
The new carbon-ecology analysis further supports broad metabolic capability at the relevant pseudomonas e group level: the Pseudomonas fluorescens/putida group retained substantially more plant-derived sugar and sugar-alcohol pathway completeness than the Pseudomonas aeruginosa group, while core organic-acid and amino-acid pathways remained near-universal in both groups. 4 This refines the organism-level GapMind evidence by indicating that ecological differentiation is concentrated in accessory carbon capabilities rather than universally conserved core pathways. 4 Carbon profiles also carried a statistically significant but modest environment signal among free-living and plant-associated species, so the result supports ecological relevance of pathway content without establishing that carbon profiles alone identify Pseudomonas putida’s habitat. 4
Evidence from functional dark-matter prioritization
The new dark-gene analysis refines the organism-level picture by prioritizing Pseudomonas putida N2C3 candidate AO356_11255: it had an absolute fitness effect of 3.4 under nitrogen conditions, a D-alanyl-D-alanine carboxypeptidase prediction, an EamA domain, and a lab–field odds ratio of 44. 5 Its enrichment in soil, freshwater, and wastewater matched the reported nitrogen-utilization fitness phenotype, although the environmental association is a prioritization signal rather than direct functional validation. 5
Pseudomonas putida N2C3 also contributed 18 of the top 100 phenotype-bearing dark-gene candidates, and the proposed experimental campaign included N2C3 stress and carbon-source experiments. 5 This supports the existing module-level interpretation that condition-specific, coordinated phenotypes can guide experiments, while extending it from co-inheritance statistics to experimentally actionable dark-gene hypotheses. 5
Related pages
This organism is documented in Co-fitness and Co-inheritance in Bacterial Pangenomes, Essential Metabolome: GapMind Pathway Analysis Across Essential-Gene Organisms, Functional Dark Matter — Experimentally Prioritized Novel Genetic Systems, Metabolic Capability vs Dependency, and Carbon Source Utilization Predicts Ecology and Lifestyle in Pseudomonas, and contributes evidence to cofitness-network-architecture, pangenome-integration, cross-tenant-data-bridging, metabolic-model-gapfilling, gene-essentiality, condition-specific-fitness, ecotype-environment-gene-content, and environment-embedding-geography. 1 2 5 3 4