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Nutrient environments shape amino acid auxotrophy and cross-feeding

Amichai Baichman‐KassiD, Lianet Noda‐GarcíaiD, Jonathan FriedmaniD

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In-depth summary

Claude Opus 5.5 · xhigh effort · 8 Nov 2026 · from the full text of version 3 (6 Aug 2026) · CC BY 4.0

Across 40 carbon-nitrogen environments, six matched E. coli and B. subtilis amino acid auxotrophs show context-dependent auxotrophy, while auxotroph type predicts cross-feeding yield better than environment.

Earlier screens measured auxotroph cross-feeding in one species and one environment, or across species where many prototrophs failed to grow, leaving the relative roles of auxotrophy type, species identity and nutrient context unresolved. Matched auxotroph sets in E. coli and B. subtilis, profiled with prototroph and monoculture controls across 40 environments, allow these factors to be partitioned.

Key results

  1. ShownAuxotrophy depends on nutrient context: every knockout genotype in both species grew without its required amino acid in some carbon-nitrogen environments, and reanalyzed public knockout-library screens show the same conditional pattern.

    Growth defined as ≥10% of prototroph. ΔpheA grew in approximately 60% of environments in both species; ΔserA grew in over 20% (B. subtilis) and 10% (E. coli). Pooling own and reanalyzed screens, 125 of 152 KO-dataset combinations (82.2%) exceeded 10% of prototroph somewhere; only three of 48 B. subtilis and three of 44 E. coli published KOs never grew. · Amino acid auxotrophy is dependent on the…; Discussion; Determining auxotrophy from different datasets

  2. ShownB. subtilis auxotroph pairs cross-fed to higher yields than E. coli pairs, even though E. coli auxotrophs grew better when supplemented with their amino acid, so monoculture growth capacity did not predict cross-feeding.

    Coculture yield: B. subtilis over E. coli fold-change of geometric mean = 2.4 (two-sided Wilcoxon signed-rank p=4.4×10^−30). Supplemented monocultures: E. coli over B. subtilis fold-change = 1.73 (p=3.4×10^−8). · Amino acid crossfeeding is shaped by…

  3. SuggestedCross-feeding strength tracked auxotrophy type more consistently across species than it tracked environment: Met and Phe auxotrophs formed strong pairs and Cys, Ser and Leu weak ones in both organisms, while Arg-containing pairs diverged most between species.

    Pair means across environments, B. subtilis vs E. coli: Spearman ρ = 0.49, p = 0.06; environment means across pairs: ρ = 0.28, p = 0.08. Top environments differed (B. subtilis: proline + glucose highest mean; E. coli: alanine + fumarate). Arg auxotrophs used different deletions (ΔargH vs ΔargA). · Amino acid crossfeeding is shaped by…; Auxotrophy is a better cross-feeding predictor…

  4. ShownSpecies-specific prototroph yield in each environment explained little of pair-level coculture yield, and cross-feeding pairs almost never outgrew the prototroph, giving no general division-of-labor yield advantage.

    Linear regression on log values of coculture vs prototroph yield: B. subtilis R² = 0.14; E. coli R² = 0.03 (p = 1.65×10⁻⁴). Only 33 of 523 B. subtilis and 1 of 450 E. coli cocultures exceeded the prototroph (3.5% of pair-environment observations); environment effects persisted after prototroph normalization. · Auxotrophy is a better cross-feeding predictor…

  5. ShownA random forest trained on species, carbon and nitrogen source, prototroph growth, auxotrophy type and amino acid requirement ranked auxotroph type as the most important feature block, on par with species and above environment.

    Train/test split grouped by species × nutrient environment; hyperparameters via group-aware 10-fold cross-validation. Held-out RMSE = 0.03, R² = 0.38, Spearman ρ = 0.80. Auxotroph type ranked first in mean block permutation importance, similar to species, above environment, prototroph growth and amino acid requirement (Mann-Whitney U, Benjamini-Hochberg FDR). · Auxotrophy is a better cross-feeding predictor…; Machine learning model and evaluation; Feature importance analysis; Figure legends

Methods, data and reproducibility

Endpoint OD600 yields after 96 hours of static growth were measured for prototrophs, auxotroph monocultures with and without the required amino acid, and all 15 intraspecies auxotroph cocultures per species in 40 media; cross-species correlations, log-linear regression and a group-split random forest with block permutation importance partitioned drivers.

  • E. coli auxotroph set: EcNR1 (MG1655 derivative) knockouts ΔmetA, ΔpheA, ΔargA, ΔcysE, ΔserA, ΔleuB plus prototroph; all pairwise cocultures · Escherichia coli · n = six auxotrophs, 15 cocultures; 450 filtered coculture observations
  • B. subtilis auxotroph set: strain 168 knockouts from a genome-scale deletion library (ΔmetA, ΔpheA, ΔargH, ΔcysE, ΔserA, ΔleuB) plus prototroph · Bacillus subtilis · n = six auxotrophs, 15 cocultures; 523 filtered coculture observations
  • Nutrient panel: MSgg base with 0.5% carbon (fumarate, glucose, glycerol or none) and 0.5% nitrogen (amino acids, amino sugars, ammonium sulfate or urea) · E. coli and B. subtilis · n = 40 environments
  • Amino acid requirement titrations: each auxotroph grown on a gradient of its required amino acid per environment; requirement = inverse of regression slope · E. coli and B. subtilis
  • Published B. subtilis knockout-library growth screen across carbon and nitrogen sources, reanalyzed for amino acid biosynthesis knockouts · Bacillus subtilis · n = 48 KO strains; 13 carbon and nitrogen sources
  • Published E. coli knockout-library growth screen across carbon sources, reanalyzed using ΔkdsC as a prototroph proxy · Escherichia coli · n = 44 KO strains; 30 carbon sources
Methods & tools
Random forest regressor, Block permutation feature importance, Group-aware 10-fold cross-validation, Spearman's rank correlation, Two-sided Wilcoxon signed-rank test, Mann-Whitney U test with Benjamini-Hochberg FDR, Linear regression on log-transformed yields, MSgg minimal medium growth assays in 96-well plates, BioTek Epoch 2 Microplate Spectrophotometer (Agilent), Genome-scale deletion library for Bacillus subtilis, Koo et al. and Tong et al. knockout growth datasets (reanalysis)
Reproducibility gaps
Code is said to be on GitHub, but no repository link is given; no repository or accession is given for the growth measurements; replicate numbers and the random forest software/versions are not specified.
Limitations (6)
  • Growth was scored only as endpoint OD600 yield after 96 h of static culture, without growth curves, a choice the authors attribute to the logistics of a screen at this scale. · stated by the authors
  • Static, unshaken culture may have lowered B. subtilis yield because it favors aerobic growth, and the authors note the B. subtilis versus E. coli contrast could be idiosyncratic rather than a clade-level trait. · stated by the authors
  • Coculture composition (fraction of each auxotroph) and exchanged metabolites were not measured, so mechanisms are inferred; only intraspecies pairs of six auxotrophy types in two species were tested. · stated by the authors
  • Because the base medium contains tryptophan, no-nitrogen conditions sometimes supported minimal growth, and nitrogen-free conditions were excluded from primary analyses; the authors note direct quantitative comparison across available datasets is limited by differing experimental designs. · stated by the authors
  • The pair-level cross-species correlation uses 15 pairs per species, and neither it nor the environment-level correlation reaches 0.05 (p = 0.06 and p = 0.08); held-out R² = 0.38 leaves much variance unexplained, so the type-over-environment ranking is tentative. · noted in this summary
  • Arg auxotrophs carry different deletions (ΔargH in B. subtilis, ΔargA in E. coli), so for that auxotrophy type the deleted gene is confounded with species; biological replicate counts are also not stated. · noted in this summary

Read this if you study microbial cross-feeding, auxotrophy or Black Queen gene loss and want a matched two-species, 40-environment dataset separating auxotroph type, species and nutrient effects.

Citations
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Abstract

Auxotrophy, the absence of biosynthetic capacity for essential metabolites, is widespread in microbes and is thought to shape interactions within communities. Auxotrophies are often treated as fixed properties of organisms; however, evidence indicates that auxotrophic phenotypes can depend on environmental context, thereby affecting community assembly by cross-feeding. Here, we systematically quantify how nutrient environments shape both auxotrophy and cross-feeding. Using matched sets of six amino acid auxotrophs in Escherichia coli and Bacillus subtilis, we measured monoculture and pairwise coculture growth across 40 carbon and nitrogen environments. We find that auxotrophy itself is highly environment dependent, with strains growing in a substantial fraction of amino acid-free conditions despite lacking key biosynthetic enzymes. Cross-feeding likewise varies widely across species, environments, and auxotroph pairs. Despite this variability, cross-feeding outcomes exhibit consistent patterns within and across species. In particular, B. subtilis cross-feeds better overall and cross-feeding growth is better predicted by auxotroph type (i.e., which amino acids the strain cannot produce) than by environmental context. A machine-learning model recapitulates this pattern, identifying auxotroph type as the strongest predictor of cross-feeding growth, similar to species identity, exceeding the contributions of nutrient environment and prototroph growth. Together, these results show that environmental context reshapes both metabolic need and exchange, yet cross-feeding follows emergent patterns linked to the species and auxotrophy type, with implications for predicting community assemblies and the evolution of gene loss.

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