A comparative metabologenomic approach reveals mechanistic insights into Streptomyces antibiotic crypticity

Abstract

Streptomyces genomes harbor numerous, biosynthetic gene clusters (BGCs) encoding for drug-like compounds. While some of these BGCs readily yield expected products, many do not. Biosynthetic crypticity represents a significant hurdle to drug discovery, and the biological mechanisms that underpin it remain poorly understood. Polycyclic tetramate macrolactam (PTM) antibiotic production is widespread within the Streptomyces genus, and examples of active and cryptic PTM BGCs are known. To reveal further insights into the causes of biosynthetic crypticity, we employed a PTM-targeted comparative metabologenomics approach to analyze a panel of S. griseus clade strains that included both poor and robust PTM producers. By comparing the genomes and PTM production profiles of these strains, we systematically mapped the PTM promoter architecture within the group, revealed that these promoters are directly activated via the global regulator AdpA, and discovered that small promoter insertion–deletion lesions (indels) differentiate weaker PTM producers from stronger ones. We also revealed an unexpected link between robust PTM expression and griseorhodin pigment coproduction, with weaker S. griseus–clade PTM producers being unable to produce the latter compound. This study highlights promoter indels and biosynthetic interactions as important, genetically encoded factors that impact BGC outputs, providing mechanistic insights that will undoubtedly extend to other Streptomyces BGCs. We highlight comparative metabologenomics as a powerful approach to expose genomic features that differentiate strong, antibiotic producers from weaker ones. This should prove useful for rational discovery efforts and is orthogonal to current engineering and molecular signaling approaches now standard in the field.

Genome-based classification of Streptomyces pinistramenti sp. nov., a novel actinomycete isolated from a pine forest soil in Poland with a focus on its biotechnological and ecological properties

“…Streptomycetes are a unique source of antibiotics which include many used in agriculture, medicine and veterinary practice (Barka et al 2015;Chater, 2016;Qi et al 2021). Members of the genus are considered to be gifted (Baltz 2017(Baltz , 2019 as they have large genomes (≥ 8.0 Mbp) rich in natural product-biosynthetic gene clusters (NP-BGCs) with the potential to encode for novel and uncharacterized antibiotics of potential therapeutic value, as exempli ed by Streptomyces leeuwenhoekii strains isolated from extreme hyper-arid Atacama desert soils (Busarakam et Sivakala et al, 2021) thereby underpinning the premise that abiotic conditions in extreme biomes select for strains with the capacity to synthesize novel specialised metabolites (Bull and Stach 2007;Bull 2011;Gomez-Escribano et al 2015).…”

Discovery and biosynthetic assessment ofStreptomyces ortussp nov. isolated from a deep-sea sponge

“…dioscori' A217 having activity solely against Gram negative Klebsiella pneumoniae (46) and S. liliiviolacens BH-SS-21 T reporting activity against the Gram negative plant pathogen Ralstonia solanacearum (45). This suggests that the metabolomic profile of A15ISP2-DRY2 T is distinct from its close relatives and highlights the poorly understood relationship between the genome and metabolome of a strain (47,48). It is possible that different environmental niches may select for strains with distinct metabolomes rather than distinct BGCs (48).…”

Comparative transcriptomics reveals highly conserved regional programs between porcine and human colonic enteric nervous system

“…According to our bulk RNA-seq data from both porcine and human ENS, we uncovered 7246 conserved genes between h-aC-MG and p-pC-MG (p-value > 0.001) and 2601 between of h-dC-MG and p-dC-MG (pvalue > 0.001) from a total of 12,291 high-quality orthologous genes using R package SCBN. The functional linkages of gene regulatory networks, where single genes are positioned, have been used as powerful indicator, reflecting mechanistic insights and functional similarities across species [29][30][31][32] . Pathway analysis could identify biological pathways that are enriched in DEG lists and highlight the overlaps among pathways based on the shared genes 29 .…”