# Trepenoid Biosynthesis Dominates among Secondary Metabolite Clusters in _Mucoromycotina_ Genomes
## 4 Conclusions  
Our analysis underscores the blurry boundaries between primary and secondary metabolism, especially in the light of automated annotation based on the incomplete annotation of available resources. Figure 5: Schematic architecture of malpicyclin (GCA_000507065_21_glim) and malpibaldin (GCA_000507065_29_glim) clusters in the _M. alpina_ B6842 assembly GCA_000507065. The mulpibaldin NRPS region is surrounded by repeat-rich and disordered protein coding genes. On one hand, the domain/rule-based approach clearly requires supervision in order to filter out the most promising SM biosynthetic genes. As evidenced by the entanglement of NRPS-like candidate clusters with lysine biosynthesis genes, this is often insufficient to understand the relationships between distantly related SM biosynthetic gene candidates. On the other hand, by bringing in additional, largely unsupervised lines of evidence (such as adenylation domain substrate prediction, homology to sequences of known function and intercluster similarity), the annotation can be improved considerably. In our case, the combined approach was able to support previous findings that some aspects of secondary metabolism in _Mucoronycota_ are clearly limited in taxonomic distribution (including the identified canonical NRPS clusters in _Mortierellomycotina_ for the recently discovered malpibaldin and malpicyclin synthetases [12]). As evidenced by recent papers, a likely evolutionary source for divergent SMCs is the horizontal transfers from bacterial donors (the PKS-NRPS hybrid clusters found in _Diversisporales_), possibly facilitated by prior symbiosis. However, the overview of our results also suggests that the native secondary metabolism-related toolkit of basal fungal lineages is far from scarce. Terpenoid biosynthesis, with a focus on the formation of carotenoid SM-related clusters, can be viewed as an early evolutionary trait, one shared by both _Dikarya_ and _Mucoronycotina_. Retention of non-NRPS siderophore synthesis is likewise common, even in _Glomeromycotina_. There is a high diversity of adenylate forming reductases, suggesting that while clusters might not form, the early-diverging fungi do make use of an extensive array of activated substrates, which can be modified by other enzymes encoded in separate genomic loci. It remains an open question how the SMCs are regulated and when they are expressed. In the future, the desired follow-up to our work will proceed through expression studies, followed by precise delineation of cluster boundaries that can be achieved once coexpression is established. Ultimately, for the most promising candidates, this may culminate in direct characterisation of (novel) natural products. **Supplementary Materials:** The following are available online at [[https://www.mdpi.com/article/10.3390/jof7040285/s1](https://www.mdpi.com/article/10.3390/jof7040285/s1)]([https://www.mdpi.com/article/10.3390/jof7040285/s1](https://www.mdpi.com/article/10.3390/jof7040285/s1)). Supplementary Table S1: Number of identified SMCs in each of the assemblies. Supplementary Table S2: Assembly identifiers and references. Supplementary Table S3: Coordinates of all identified candidate SMCs (secondary metabolite clusters). Their positions and predicted frequent candidate gene families (as identified by the MCL approach). SMC description: abbreviated family labels are explained in Table S5, including AdenylPred results where available. Supplementary Table S4: Prediction differences between GLIMMER/GFF-based and the final conjoined approach. Supplementary Table S5: MCL clusters of individual SMC genes. Description of select, manually annotated candidate families (one line per candidate = MCL cluster). Supplementary Table S6: MCL clusters membership lists for all annotated candidate families (one line per candidate). Supplementary Table S7: MCL cluster annotation of members of candidate families in terms of similarity to InterPro domains/motifs and DIAMOND matches vs. UniProt/SwissProt and MIBIG proteins (one line per hit).