Abstract
Ecological diversity in fungi is largely defined by metabolic traits, including the ability to produce secondary or “specialized” metabolites (SMs) that mediate interactions with other organisms. Fungal SM pathways are frequently encoded in biosynthetic gene clusters (BGCs), which facilitate the identification and characterization of metabolic pathways. Variation in BGC composition reflects the diversity of their SM products. Recent studies have documented surprising diversity of BGC repertoires among isolates of the same fungal species, yet little is known about how this population-level variation is inherited across macroevolutionary timescales. Here, we applied a novel linkage-based algorithm to reveal previously unexplored dimensions of diversity in BGC composition, distribution, and repertoire across 101 species of Dothideomycetes, which are considered the most phylogenetically diverse class of fungi and known to produce many SMs. We predicted both complementary and overlapping sets of clustered genes compared with existing methods and identified novel gene pairs that associate with known secondary metabolite genes. We found that variation among sets of BGCs in individual genomes is due to nonoverlapping BGC combinations and that several BGCs have biased ecological distributions, consistent with niche-specific selection. We observed that total BGC diversity scales linearly with increasing repertoire size, suggesting that secondary metabolites have little structural redundancy in individual fungi. We project that there is substantial unsampled BGC diversity across specific families of Dothideomycetes, which will provide a roadmap for future sampling efforts. Our approach and findings lend new insight into how BGC diversity is generated and maintained across an entire fungal taxonomic class.
Highlights
Plants, bacteria and fungi produce the majority of the earth's biochemical diversity
Using a novel cluster detection approach based on shared syntenic relationships among genes (CO-OCCUR, see Methods, Figure 1, Figure SA), we identified 332 gene homolog groups of interest (Table SA, Table SB) whose members were organized into 3399 candidate biosynthetic gene clusters (BGCs) of at least two genes (Table SC) in 101 Dothideomycete genomes (Table SD), representing an average of 33.7 BGCs per genome (SD= 15.4, Figure SB)
We found that no single algorithm was able to annotate all predicted genes of interest in a BGC, even those predicted to be involved in SM biosynthesis (Figure 4a, Table SL)
Summary
Bacteria and fungi produce the majority of the earth's biochemical diversity. These results suggest that it is not optimal for the de novo BGC annotation of individual genomes, and its ability to annotate genes of interest is proportional to their co-occurrence frequency in a given database, meaning that it is not well suited for recovering associated SM genes that are not evolutionarily conserved This may explain in part why 10,295 genes (including 2,478 genes predicted to be involved in secondary metabolism) identified by antiSMASH and SMURF combined were not detected with CO-OCCUR (Figure 4), and why CO-OCCUR detected only a few of the host-selective toxins found in Dothideomycetes. Phylogenetic screens, especially when coupled with more robust phylogenetic analyses, such as gene tree-species tree reconciliation methods and hypothesis testing using phylogenies representing alternative evolutionary scenarios, will be useful for prioritizing the characterization of BGCs most likely to contribute to the success of particular guilds or clades Among those BGCs with hits to the MIBiG database, we identified clusters that displayed both lineage specific and spotty or sporadic distributions. Little overlap was found in biosynthetic gene clusters from different genera, consistent with diverse ecologies and lifestyles among the Dothideomycetes, and suggesting that most of the metabolic capacity of this fungal class remains to be discovered
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