Identity
- Canonical name: Azospirillum brasilense. 1
- Known alias:
azobra. 1 - Stable external identifier: Not reported in
annotation_gap_discovery. 1
Role in annotation-gap discovery
Azospirillum brasilense was one of 14 organisms evaluated in a study integrating metabolic-model gapfilling, Fitness Browser phenotypes, pangenome annotations, GapMind pathway evidence, and BLAST homology to assign candidate genes to gapfilled reactions. 1
The study evaluated 21 gapfilled reaction-organism pairs for Azospirillum brasilense and resolved 13 of them, giving a resolution rate of 61.9%. 1
The organism’s result contributed to the cross-organism analysis of metabolic-model-gapfilling, which found that 96 of 201 gapfilled enzymatic reaction-organism pairs received candidate genes with confidence scoring. 1
Evidence context
The evidence pipeline combined draft-model flux-balance analysis (FBA), a constraint-based method for predicting metabolic flux and growth, with Fitness Browser carbon-source phenotypes, pangenome conservation, pathway-completeness evidence, automated annotations, and sequence homology. 1
The study used random-barcode transposon sequencing (RB-TnSeq), a method that measures genome-wide mutant fitness using barcoded transposon libraries, to obtain carbon-source fitness evidence for the selected organisms. 1
These findings support pangenome-integration by using cross-organism gene-cluster conservation as one evidence stream, and they contribute to condition-specific-fitness by linking carbon-source fitness patterns to metabolic annotation gaps. 1
Role in metabolic capability-versus-dependency analysis
Azospirillum brasilense was one of the 7 Tier 1 organisms with matching GapMind genome data in a comparison of pathway completeness with Fitness Browser fitness evidence; only 7 of the 48 Fitness Browser organisms had matching GapMind data. 2 This supports the existing pathway-completeness context while reinforcing that the comparison is based on a small, model-organism subset rather than broad species coverage. 2
The analysis distinguished genomic pathway capability from experimentally observed dependency and found that complete pathways could lack fitness defects under standard conditions, while becoming important under other tested conditions. 2 This refines the organism’s GapMind evidence: its predicted pathway completeness should not be treated as proof of constitutive pathway dependence or viability essentiality. 2
Role in metal-tolerance validation and field ecology
Azospirillum brasilense was one of 12 organisms representing 6 unique species in a direct Fitness Browser–BacDive validation of phenotype records against genome-based metal-tolerance scores. 3
This refines the organism’s evidence context: the validation connected its classical phenotype data to the metal-fitness-atlas, but the set was underpowered for broad phenotype associations because all Gram-typed organisms were Gram-negative and the single anaerobe was not interpretable. 3 The study therefore does not establish an organism-specific metal-tolerance mechanism for A. brasilense; it supports using matched phenotype and genome data while motivating better-controlled, per-metal validation. 3
In the Oak Ridge field-ecology analysis, Azospirillum was detected among the 14 Fitness Browser genera found in groundwater communities and showed a marginal positive association with uranium abundance (Spearman rho=+0.20, p=0.042, q=0.077) after Benjamini–Hochberg false-discovery-rate correction. 4 This refines the organism’s metal-tolerance evidence: the direction is consistent with greater abundance under uranium exposure, but the association did not pass the report’s q<0.05 threshold and is therefore suggestive rather than established. 4 Because 16S amplicon sequencing, a marker-gene method for profiling microbial composition, resolved the field data only to genus level, this result cannot be matched confidently to A. brasilense at species or strain level. 4
Role in essential-metabolome analysis
Azospirillum brasilense was one of 7 organisms successfully mapped for a pilot GapMind pathway-completeness analysis, reduced from an underlying collection of 45 essential-gene organisms. 5 This supports the existing metabolic-gapfilling evidence by adding an independent pathway-completeness context, but does not establish that any complete pathway is essential for viability. 5
GapMind, a computational pathway-completeness method, predicted 18/18 amino-acid biosynthesis pathways for A. brasilense (100%); this was one of 6 organisms with complete coverage in the pilot. 5 The result refines the organism’s annotation context because it is computational evidence of pathway completeness rather than experimental confirmation of pathway function or essentiality. 5
The pilot’s interpretation is limited by its 7-organism sample and by possible missed non-canonical or divergent pathways, so the result should not be generalized to bacteria as a whole. 5
Source
- Annotation-Gap Discovery via Phenotype-Fitness-Pangenome-Gapfilling Integration — reports the 61.9% resolution rate for Azospirillum brasilense and the broader annotation-gap discovery pipeline. 1
- Metabolic Capability vs Dependency — places A. brasilense among the 7 Tier 1 organisms in the pathway capability-versus-dependency analysis. 2
- BacDive Phenotype Signatures of Metal Tolerance — reports its inclusion in the direct Fitness Browser–BacDive metal-tolerance validation. 3
- Essential Metabolome: GapMind Pathway Analysis Across Essential-Gene Organisms — reports its 18/18 amino-acid pathway completeness in the GapMind pilot. 5
- Lab Fitness Predicts Field Ecology at Oak Ridge — reports the genus-level Oak Ridge uranium association and its limitations. 4