Contributions
Metabolic Capability vs Metabolic Dependency compared GapMind genomic pathway completeness with Fitness Browser gene-fitness data, using SEED subsystem annotations as a pathway-membership proxy, across 1,695 pathway-organism pairs from 48 organisms 1. It found that 267 (15.8%) were latent capabilities (complete but fitness-neutral under tested conditions), 547 (32.3%) were intermediate and 881 (51.9%) were active dependencies, with pathway category predicting dependency class (χ²=163.6, df=4, p=2.5×10⁻³⁴) 1. In that project, 217 of 892 (24.3%) carbon source utilization pathways were latent against 48 of 735 (6.5%) amino acid biosynthesis pathways, which the report expresses as carbon pathways being 3.7× more likely to be latent; the report’s prediction that carbon-pathway genes are preferentially lost in nutrient-rich environments was not tested 1. A sensitivity analysis across 16 threshold combinations gave latent fractions from 4.7% to 21.1% (SD = 5.9 percentage points) 1. The project reported several caveats: SEED-proxy mapping can introduce false-positive genes that dilute fitness signal, and laboratory-biased fitness conditions may inflate the latent fraction 1.
The same project found that pathway-level conservation did not distinguish latent from active pathways (mean 0.869 vs 0.829; Mann–Whitney U p = 0.94, rank-biserial r = 0.052), so H2a was not supported 1. At the clade level, the latent capability rate correlated positively with pangenome openness (Spearman ρ = 0.69, p = 0.0004, n = 22 clades), supporting H2b, and the report reads the combined results as mixed support for the Black Queen framework 1. The project also clustered within-species pathway profiles and found that all 10 target species had silhouette scores above 0.2, ranging from 0.349 for PALSA-747 sp. to 0.894 for Salmonella enterica 1. Clusters were associated with isolation environment in Salmonella enterica (χ²=1570.2, df=25, p<0.0001) and Phenylobacterium sp. (χ²=12.2, df=1, p=0.0005) but not in the marine organisms tested 1. The report states that these associations are observational and may be confounded by phylogenetic structure, because no phylogenetic correction was performed 1.
Community Metabolic Ecology via NMDC × Pangenome Integration combined NMDC community taxonomy and liquid chromatography–mass spectrometry (LC-MS) metabolomics with GapMind pathway completeness for GTDB pangenome species from the KBase Data Lakehouse 2. It computed community-weighted completeness for 220 samples × 80 pathways, and all samples passed the 30% bridge-coverage quality-control threshold, with mean coverage of 94.6% 2. Across 13 testable amino-acid pathways, the project found that 11 of 13 (85%) correlated negatively with ambient metabolite intensity, the direction the Black Queen Hypothesis (BQH) predicts (sign test p = 0.011) 2. Leucine (r = −0.390, q = 0.022, n = 62) and arginine (r = −0.297, q = 0.049, n = 80) were significant after Benjamini-Hochberg false-discovery-rate correction (FDR, the expected share of false positives among significant calls) 2. Methionine showed the largest effect (r = −0.496, n = 18, q = 0.117) but was underpowered, and tyrosine was an anti-BQH outlier (r = +0.419, ns), for which the report offers phenylalanine hydroxylation as an untested explanation 2. Glutamine (n = 4) and proline (n = 9) were skipped for insufficient metabolomics coverage 2.
That project’s robustness checks found that leucine stayed significant in a soil-only analysis (r = −0.390, q = 0.022, n = 62) 2. Arginine stayed directionally consistent there but lost FDR significance (r = −0.264, q = 0.117, n = 78) 2. It noted that 125/131 H1 samples (95%) came from a single NMDC study 2. It also reported that correcting an isoleucine/leucine compound-mapping collision strengthened the leucine correlation from r = −0.326 to r = −0.390 2. The report frames the energetic-cost explanation for leucine and arginine as a mechanistic interpretation rather than direct evidence of gene loss 2.