Genomic insights into Streptomyces albidoflavus SM254: tracing the putative signs of anti-Pseudogymnoascus destructans properties

Abstract

White-nose syndrome, caused by the psychrophilic fungus Pseudogymnoascus destructans, has devastated bat populations across North America. Streptomyces albidoflavus SM254 was previously reported to exhibit antifungal activity against this pathogen, but no comprehensive genomic characterization has been performed to date. Here, we analyzed 34 S. albidoflavus genomes, including the antifungal strain SM254 and 33 publicly available references, to investigate its metabolic potential and functional distinctiveness. Using pangenome reconstruction, phylogenomics, average nucleotide identity, and KEGG pathway profiling, we found that S. albidoflavus SM254 shares high nucleotide identity (> 99%) with five closely related strains but displays a unique combination of complete ethanol fermentation capacity and asparagine biosynthesis deficiency. These traits were exclusive to SM254 and may reflect adaptation to the oxygen-limited, nutrient-variable sediment environment. Functional annotation further revealed high completeness in central energy, redox, and stress-response pathways. Although direct antifungal mechanisms remain to be experimentally validated, S. albidoflavus SM254's unique metabolic profile and ecological specialization suggest potential relevance in biocontrol contexts.

Keywords: Pseudogymnoascus destructans; Streptomyces albidoflavus SM254; Comparative genomics; White-nose syndrome.

Fig. 1

Phylogenomic structure of 34 Streptomyces albidoflavus genomes. Maximum-likelihood tree constructed from 3,867 concatenated core gene alignments under the TVM + F + R5 substitution model. The clade containing the SM254 strain is highlighted in blue, with SM254’s branch tip in bold. Branches with bootstrap support < 70 are shown in gray; those ≥ 70 are black. The country of isolation is indicated by national flags, and the year of isolation is represented as a color gradient. Scale bar denotes substitutions per site

Fig. 2

Pangenome composition of Streptomyces albidoflavus. (A) Species-wide pangenome structure of 34 S. albidoflavus genomes, showing the distribution of gene families into core (3,867), soft-core (761), shell (4,089), and cloud (2,921) categories. (B) Gene family distribution in the SM254 strain genome, consisting of 3,867 core, 744 soft-core, 1,346 shell, and 185 cloud genes

Fig. 3

Pairwise average nucleotide identity (ANI) across Streptomyces albidoflavus genomes. (A) ANI heatmap showing genome-wide similarity across all 34 strains. (B) Subset heatmap highlighting ANI values among the six closest relatives of the SM254 strain. The SM254 genome is bolded for clarity. Color gradients represent ANI percentages

Fig. 4

Functional pathway completeness in Streptomyces albidoflavus SM254. Barplot showing the KEGG-based completeness of 74 annotated metabolic pathways with non-zero completeness values, ranging from partial to fully complete (0 < completeness ≤ 1)

Fig. 5

Strain-level variation in functional pathway completeness among Streptomyces albidoflavus strains. Heatmap displaying the completeness of annotated metabolic and ecological pathway modules across SM254 and its five closest relatives. Pathways are grouped by functional category (e.g., amino acid metabolism, oxidative phosphorylation, metal transporters) for clarity. Despite high ANI (> 99%), several differences in pathway presence and completeness were observed, highlighting fine-scale metabolic divergence

Fig. 6

Functional divergence within the SM254 clade of Streptomyces albidoflavus. (A) Radar plot com-paring completeness values of four KEGG pathways across SM254 and its five closest relatives: ethanol fermentation (Mixed acid: Ethanol, Acetyl-CoA to Acetylaldehyde (reversible), asparagine biosynthesis, polyhydroxybutyrate synthesis, and competence-related core components. Each axis represents pathway completeness from 0 to 1. (B) Correlation network based on pairwise similarity of functional pathway profiles among the same six strains. Edge width and color in-tensity reflect correlation strength, with bolder lines indicating higher similarity. The network highlights fine-scale functional divergence within a group of genomes sharing > 99% ANI