Identity
- Canonical name: cobalt. 1
- Known alias: Co. 1
- Stable external identifier: No stable external identifier was reported in Counter Ion Effects on Metal Fitness Measurements. 1
Evidence from Counter-Ion Effects
Cobalt was one of 14 metals evaluated across 19 organisms and 86 organism × metal pairs in a study of whether counter ions confound genome-wide metal-fitness measurements. 1
Cobalt-associated metal-important genes had a 41.3% overlap with NaCl-important genes. 1 Cobalt delivered up to 500 mM chloride in the tested metal-salt experiments. 1 The mean NaCl overlap for metals delivered with chloride was 41.6%, compared with 37.8% for metals delivered without chloride; cobalt’s 41.3% overlap therefore did not establish a chloride-dose relationship. 1
In the DvH whole-genome correlation analysis, cobalt fitness profiles had a Pearson correlation of r=0.498 with NaCl fitness profiles. 1 The DvH correlation hierarchy did not follow chloride concentration, because zinc sulfate supplied 0 mM chloride yet ranked above cobalt with r=0.715 versus cobalt’s r=0.498. 1
The report interprets cobalt’s relatively high NaCl correlation as consistent with broad toxicity involving essential-cofactor displacement or disruption of multiple cellular systems, but this is an extrapolation from fitness-profile correlations rather than a direct biochemical test. 1 After shared-stress genes were removed, cobalt’s corrected core-genome enrichment remained +0.076, unchanged from the original value. 1 This unchanged enrichment supports the conclusion that cobalt’s Metal Fitness Atlas core-enrichment signal was not produced by genes shared with NaCl stress responses. 1
Evidence from Cross-Resistance
Across 452 metal experiments, cobalt participated in a gene-level cross-resistance analysis spanning 37 organisms and 14 metals; among 28 organisms with data for at least 3 metals, the Co–Ni fitness correlation was r = 0.56 across n = 28 organisms, Co–Zn was r = 0.52 across n = 18, Co–Fe was r = 0.45 across n = 7, and Co–Cu was r = 0.43 across n = 24. 2
These consistently positive associations support the existing interpretation of broad cobalt toxicity, while refining it: cross-resistance showed a universal positive directional layer, whereas the magnitude of the association varied by metal pair. 2 No tested metal pair showed systematically negative cross-resistance, and all 15 pairs tested in at least 5 organisms had greater than 90% sign consistency; the report therefore suggests that cobalt-associated fitness responses are part of a conserved cross-metal stress architecture rather than evidence of cobalt-specific antagonism. 2
Cobalt was among the more strongly connected metals in the cross-resistance network, while Al–Co was among the weaker listed pairings at r = 0.30; this refines the interpretation that chemistry influences response magnitude without overturning the general positive direction. 2 The cross-resistance analysis identified 318 ortholog groups that were metal-shared in at least 2 organisms, with broadly conserved functions including cell envelope, energy metabolism, DNA repair, and ion homeostasis; these findings support a shared cellular basis for cobalt responses but do not identify a cobalt-exclusive mechanism. 2
Evidence from the Pan-Bacterial Metal Fitness Atlas
The Metal Fitness Atlas included cobalt in 559 metal-related experiments across 31 organisms and 16 metals; cobalt had cross-species coverage in 27 organisms, among the broadest coverage in the atlas. 3 Among cobalt-associated metal-important genes, 1,859 were identified, with a core fraction of 0.859, a core-fraction delta of +0.072, OR=1.67, and p=8.1e-16. 3 This supports the counter-ion result that cobalt’s core-enrichment signal persists after removing shared-stress genes, while refining the interpretation: cobalt responses include broadly conserved cellular functions, not only accessory cobalt-resistance genes. 3
The metal-specificity analysis refines this broad atlas classification: 1,167 of 2,324 cobalt-associated records (50.2%) were metal-specific, defined as significant under metal stress but sick in fewer than 5% of 5,945 non-metal experiments. 4 Thus, cobalt combines a substantial condition-specific component with the broadly conserved component captured by the atlas’s wider metal-important definition. 4
The atlas’s two-tier model distinguishes core general-stress functions from accessory specialized mechanisms such as efflux, sequestration, and enzymatic detoxification. 3 This supports the existing evidence for broad cobalt toxicity but refines it by treating accessory cobalt-specific resistance as a second tier that is less visible under a genome-wide metal-important definition. 3 The atlas also cautions that its broad definition, fit < -1 OR n_sick ≥ 1, captures many general-stress genes; it recommends testing genes important for metals but not other stresses to isolate cobalt-specific resistance. 3 The 50.2% cobalt-specific fraction directly implements that proposed separation, although it was calculated from 24 organisms included after locusId filtering rather than all 31 metal-tested organisms. 4
Evidence from Field-vs-Lab Fitness
The field-vs-lab analysis included cobalt among the heavy-metal conditions, alongside nickel, zinc, copper, manganese, selenium, molybdate, tungstate, and aluminum. 5 This refines the counter-ion analysis by placing cobalt-associated fitness measurements within a broader environmental heavy-metal category rather than treating them as a direct cobalt-specific conservation result.
Across heavy-metal-important genes in Desulfovibrio vulgaris Hildenborough, 71.2% were core, compared with a 76.3% all-gene baseline; the difference was not statistically significant (OR=0.77, FDR q=0.14). 5 This supports the existing interpretation that cobalt-related stress can involve broad toxicity, while refining it by showing that the low conservation pattern was reported for the combined heavy-metals category, not cobalt alone. 5
The report suggests the hypothesis that specific metal-resistance mechanisms, such as efflux pumps and metal-binding proteins, may be accessory, whereas uranium- and mercury-related responses may involve more fundamental stress pathways; this is a category-level hypothesis, not a direct demonstration for cobalt. 5 Cross-resistance scores did not correlate with BacDive isolation from metal environments at the Fitness Browser species scale (Spearman rho approximately -0.02, p > 0.8); because the validation was underpowered and not cobalt-specific, this refines rather than contradicts the broader environmental interpretation. 2
Evidence from Soil Functional Genomics
A soil metagenomic analysis found cobalt among nine metals associated with microbial functional gene content across 51,748 soil samples. Across the nine metals, 2,355 significant COG–metal associations were identified at FDR < 0.05; transporters, including ABC and RND systems, and biosynthesis genes dominated the top hits, while chromium and lead produced the strongest signals. 6 This supports the existing evidence that cobalt responses can involve transport and biosynthetic functions, but refines it by showing that the result is observational, community-level, and not necessarily cobalt-specific. 6
The soil result does not establish a cobalt-exclusive mechanism: chromium, copper, lead, and zinc co-vary in many industrial soils, and partial-correlation analyses are planned to distinguish individual-metal associations from generic multi-metal contamination responses. 6 This refines the positive cross-resistance evidence by identifying co-contamination as a potential confound, rather than contradicting the observed conserved direction of cobalt-associated responses. 6
Related Pages
Cobalt’s results relate to sodium chloride through the comparison of shared NaCl and metal-fitness signals, and to copper and nickel as other tested metals. 1
The findings contribute to condition-specific-fitness by separating shared-stress responses from cobalt-specific fitness responses. 1 They also contribute to metal-cross-resistance and cofitness-network-architecture through conserved positive cross-metal fitness correlations. 2 The atlas additionally connects cobalt to pangenome-integration through its core/accessory conservation analysis. 3 The specificity classification further connects cobalt to metal-cross-resistance by distinguishing its metal-specific records from broadly shared stress responses. 4 The soil analysis connects cobalt to environmental-resistome, ecotype-environment-gene-content, metal-cross-resistance, and environment-embedding-geography through environment-dependent functional associations and unresolved co-contamination and spatial-matching issues. 6
The complete analyses are summarized in Counter Ion Effects on Metal Fitness Measurements, Field vs Lab Gene Importance in *Desulfovibrio vulgaris* Hildenborough, Gene-Resolution Metal Cross-Resistance Across Diverse Bacteria, Pan-Bacterial Metal Fitness Atlas, Metal-Specific vs General Stress Genes, and Soil Metal Concentrations Drive Functional Gene Shifts. 1,5,2,3,4,6