Assessing in silico the recruitment and functional spectrum of bacterial enzymes from secondary metabolism. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Veprinskiy, Valery; Heizinger, Leonhard; Plach, Maximilian; Merkl, Rainer
• Is Part Of: BMC evolutionary biology. Volume 17:Issue 1(2017)
• Page Start: 1
• Page End: 15
• Publication Date: 2017-12
• Subjects: Primary metabolism -- Secondary metabolism -- Enzyme evolution -- Enzyme design; Evolution (Biology) -- Periodicals; 576.805
• DOI: 10.1186/s12862-017-0886-2
• Languages: English
• ISSNs: 1471-2148

Abstract

Abstract Background Microbes, plants, and fungi synthesize an enormous number of metabolites exhibiting rich chemical diversity. For a high-level classification, metabolism is subdivided into primary (PM) and secondary (SM) metabolism. SM products are often not essential for survival of the organism and it is generally assumed that SM enzymes stem from PM homologs. Results We wanted to assess evolutionary relationships and function ofbona fide bacterial PM and SM enzymes. Thus, we analyzed the content of 1010 biosynthetic gene clusters (BGCs) from the MIBiG dataset; the encoded bacterial enzymes served as representatives of SM. The content of 15 bacterial genomes known not to harbor BGCs served as a representation of PM. Enzymes were categorized on their EC number and for these enzyme functions, frequencies were determined. The comparison of PM/SM frequencies indicates a certain preference for hydrolases (EC class 3) and ligases (EC class 6) in PM and of oxidoreductases (EC class 1) and lyases (EC class 4) in SM. Based on BLAST searches, we determined pairs of PM/SM homologs and their functional diversity. Oxidoreductases, transferases (EC class 2), lyases and isomerases (EC class 5) form a tightly interlinked network indicating that many protein folds can accommodate different functions in PM and SM. In contrast, the functional diversity of hydrolases and especially ligases is significantly limited in PM and SM. For the most direct comparison of PM/SM homologs, we restricted for each BGC the search to the content of the genome it comes from. For each homologous hit, the contribution of the genomic neighborhood to metabolic pathways was summarized in BGC-specific html-pages that are interlinked with KEGG; this dataset can be downloaded fromhttps://www.bioinf.ur.de . Conclusions Only few reaction chemistries are overrepresented in bacterial SM and at least 55% of the enzymatic functions present in BGCs possess PM homologs. Many SM enzymes arose in PM and Nature utilized the evolvability of enzymes similarly to establish novel functions both in PM and SM. Future work aimed at the elucidation of evolutionary routes that have interconverted a PM enzyme into an SM homolog can profit from our BGC-specific annotations.