GRINS: Genetic elements that recode assembly-line polyketide synthases and accelerate their diversification

Mixing and Matching of Hybrid Megasynthases is a Hub for the Evolution of Metabolic Diversity in Cyanobacteria

Modular megasynthases, such as polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs), are molecular assembly lines that biosynthesize many pharmaceutically and ecologically important natural products. Understanding how these compounds evolve could inspire the artificial evolution of compound diversity by metabolic engineering. Over the past two decades, a number of seminal studies have significantly contributed to our understanding of natural product evolution. However, the evolution of NRPS and PKS assembly lines remains poorly understood, especially for NRPS/PKS hybrids. Here, we provide substantial evidence for a remarkable cluster-mixing event involving three cyanobacterial biosynthetic gene clusters (BGCs), resulting in the emergence of novel peptide-polyketide hybrids that were named minutumamides. By combining retro-evolutionary analysis with structure-guided genome mining, we could discover a potential evolutionary ancestor that links nostopeptolide and minutumamide biosynthesis. In addition, we were able to trace nostopeptolide-related module and domain blocks in various other biosynthetic pathways, indicating a surprisingly vivid mixing and matching of biosynthesis genes in the evolution of NRPS and cis-acyltransferase PKS/NRPS pathways, which was previously regarded as a unique feature of trans-acyltransferase (trans-AT) PKS. These remarkable insights into the evolutionary plasticity of NRPS-PKS assembly lines provide valuable guidance for pathway engineers looking for productive combinations that yield "nonnatural" hybrid natural products.

Context matters: assessing the impacts of genomic background and ecology on microbial biosynthetic gene cluster evolution

Encoded within many microbial genomes, biosynthetic gene clusters (BGCs) underlie the synthesis of various secondary metabolites that often mediate ecologically important functions. Several studies and bioinformatics methods developed over the past decade have advanced our understanding of both microbial pangenomes and BGC evolution. In this minireview, we first highlight challenges in broad evolutionary analysis of BGCs, including delineation of BGC boundaries and clustering of BGCs across genomes. We further summarize key findings from microbial comparative genomics studies on BGC conservation across taxa and habitats and discuss the potential fitness effects of BGCs in different settings. Afterward, recent research showing the importance of genomic context on the production of secondary metabolites and the evolution of BGCs is highlighted. These studies draw parallels to recent, broader, investigations on gene-to-gene associations within microbial pangenomes. Finally, we describe mechanisms by which microbial pangenomes and BGCs evolve, ranging from the acquisition or origination of entire BGCs to micro-evolutionary trends of individual biosynthetic genes. An outlook on how expansions in the biosynthetic capabilities of some taxa might support theories that open pangenomes are the result of adaptive evolution is also discussed. We conclude with remarks about how future work leveraging longitudinal metagenomics across diverse ecosystems is likely to significantly improve our understanding on the evolution of microbial genomes and BGCs.

zol and fai: large-scale targeted detection and evolutionary investigation of gene clusters

Many universally and conditionally important genes are genomically aggregated within clusters. Here, we introduce fai and zol, which together enable large-scale comparative analysis of different types of gene clusters and mobile-genetic elements, such as biosynthetic gene clusters (BGCs) or viruses. Fundamentally, they overcome a current bottleneck to reliably perform comprehensive orthology inference at large scale across broad taxonomic contexts and thousands of genomes. First, fai allows the identification of orthologous instances of a query gene cluster of interest amongst a database of target genomes. Subsequently, zol enables reliable, context-specific inference of ortholog groups for individual protein-encoding genes across gene cluster instances. In addition, zol performs functional annotation and computes a variety of evolutionary statistics for each inferred ortholog group. Importantly, in comparison to tools for visual exploration of homologous relationships between gene clusters, zol can scale to handle thousands of gene cluster instances and produce detailed reports that are easy to digest. To showcase fai and zol, we apply them for: (i) longitudinal tracking of a virus in metagenomes, (ii) performing population genetic investigations of BGCs for a fungal species, and (iii) uncovering evolutionary trends for a virulence-associated gene cluster across thousands of genomes from a diverse bacterial genus.

Conjugation Mediates Large-Scale Chromosomal Transfer in Streptomyces Driving Diversification of Antibiotic Biosynthetic Gene Clusters

Streptomyces are ubiquitous soil-dwelling bacteria with large, linear genomes that are of special importance as a source of metabolites used in human and veterinary medicine, agronomy, and industry. Conjugative elements (actinomycetes integrative and conjugative elements, AICEs) are the main drivers of Streptomyces Horizontal Gene Transfer. AICE transfer has long been known to be accompanied by mobilization of chromosomal DNA. However, the magnitude of DNA transfer, or the localization of acquired DNA across their linear chromosome, has remained undetermined. We here show that conjugative crossings in sympatric strains of Streptomyces result in the large-scale, genome-wide distributed replacement of up to one-third of the recipient chromosome, a phenomenon for which we propose the name "Streptomyces Chromosomal Transfer" (SCT). Such chromosome blending results in the acquisition, loss, and hybridization of Specialized Metabolite Biosynthetic Gene Clusters, leading to a novel metabolic arsenal in exconjugant offspring. Harnessing conjugation-mediated specialized metabolite biosynthesis gene cluster diversification holds great promise in the discovery of new bioactive compounds including antibiotics.

Structure and Mechanisms of Assembly-Line Polyketide Synthases

Three decades of studies on the multifunctional 6-deoxyerythronolide B synthase have laid a foundation for understanding the chemistry and evolution of polyketide antibiotic biosynthesis by a large family of versatile enzymatic assembly lines. Recent progress in applying chemical and structural biology tools to this prototypical assembly-line polyketide synthase (PKS) and related systems has highlighted several features of their catalytic cycles and associated protein dynamics. There is compelling evidence that multiple mechanisms have evolved in this enzyme family to channel growing polyketide chains along uniquely defined sequences of 10-100 active sites, each of which is used only once in the overall catalytic cycle of an assembly-line PKS. Looking forward, one anticipates major advances in our understanding of the mechanisms by which the free energy of a repetitive Claisen-like reaction is harnessed to guide the growing polyketide chain along the assembly line in a manner that is kinetically robust yet evolutionarily adaptable.

Evolution-inspired engineering of nonribosomal peptide synthetases

Many clinically used drugs are derived from or inspired by bacterial natural products that often are produced through nonribosomal peptide synthetases (NRPSs), megasynthetases that activate and join individual amino acids in an assembly line fashion. In this work, we describe a detailed phylogenetic analysis of several bacterial NRPSs that led to the identification of yet undescribed recombination sites within the thiolation (T) domain that can be used for NRPS engineering. We then developed an evolution-inspired "eXchange Unit between T domains" (XUT) approach, which allows the assembly of NRPS fragments over a broad range of GC contents, protein similarities, and extender unit specificities, as demonstrated for the specific production of a proteasome inhibitor designed and assembled from five different NRPS fragments.

Module-Based Polyketide Synthase Engineering for de Novo Polyketide Biosynthesis

Polyketide retrobiosynthesis, where the biosynthetic pathway of a given polyketide can be reversibly engineered due to the colinearity of the polyketide synthase (PKS) structure and function, has the potential to produce millions of organic molecules. Mixing and matching modules from natural PKSs is one of the routes to produce many of these molecules. Evolutionary analysis of PKSs suggests that traditionally used module boundaries may not lead to the most productive hybrid PKSs and that new boundaries around and within the ketosynthase domain may be more active when constructing hybrid PKSs. As this is still a nascent area of research, the generality of these design principles based on existing engineering efforts remains inconclusive. Recent advances in structural modeling and synthetic biology present an opportunity to accelerate PKS engineering by re-evaluating insights gained from previous engineering efforts with cutting edge tools.

Effects of Epigenetic Modification and High Hydrostatic Pressure on Polyketide Synthase Genes and Secondary Metabolites of Alternaria alternata Derived from the Mariana Trench Sediments

The hadal biosphere is the most mysterious ecosystem on the planet, located in a unique and extreme environment on Earth. To adapt to extreme environmental conditions, hadal microorganisms evolve special strategies and metabolisms to survive and reproduce. However, the secondary metabolites of the hadal microorganisms are poorly understood. In this study, we focused on the isolation and characterization of hadal fungi, screening the potential strains with bioactive natural products. The isolates obtained were detected further for the polyketide synthase (PKS) genes. Two isolates of Alternaria alternata were picked up as the representatives, which had the potential to synthesize active natural products. The epigenetic modifiers were used for the two A. alternata isolates to stimulate functional gene expression in hadal fungi under laboratory conditions. The results showed that the chemical epigenetic modifier, 5-Azacytidine (5-Aza), affected the phenotype, PKS gene expression, production of secondary metabolites, and antimicrobial activity of the hadal fungus A. alternata. The influence of epigenetic modification on natural products was strongest when the concentration of 5-Aza was 50 μM. Furthermore, the modification of epigenetic agents on hadal fungi under high hydrostatic pressure (HHP) of 40 MPa displayed significant effects on PKS gene expression, and also activated the production of new compounds. Our study demonstrates the high biosynthetic potential of cultivable hadal fungi, but also provides evidence for the utility of chemical epigenetic modifiers on active natural products from hadal fungi, providing new ideas for the development and exploitation of microbial resources in extreme environments.

Dynamics of the Streptomyces chromosome: chance and necessity

Streptomyces are prolific producers of specialized metabolites with applications in medicine and agriculture. Remarkably, these bacteria possess a large linear chromosome that is genetically compartmentalized: core genes are grouped in the central part, while the ends are populated by poorly conserved genes including antibiotic biosynthetic gene clusters. The genome is highly unstable and exhibits distinct evolutionary rates along the chromosome. Recent chromosome conformation capture (3C) and comparative genomics studies have shed new light on the interplay between genome dynamics in space and time. Here, we review insights that illustrate how the balance between chance (random genome variations) and necessity (structural and functional constraints) may have led to the emergence of spatial structuring of the Streptomyces chromosome.

Deep self-supervised learning for biosynthetic gene cluster detection and product classification

Natural products are chemical compounds that form the basis of many therapeutics used in the pharmaceutical industry. In microbes, natural products are synthesized by groups of colocalized genes called biosynthetic gene clusters (BGCs). With advances in high-throughput sequencing, there has been an increase of complete microbial isolate genomes and metagenomes, from which a vast number of BGCs are undiscovered. Here, we introduce a self-supervised learning approach designed to identify and characterize BGCs from such data. To do this, we represent BGCs as chains of functional protein domains and train a masked language model on these domains. We assess the ability of our approach to detect BGCs and characterize BGC properties in bacterial genomes. We also demonstrate that our model can learn meaningful representations of BGCs and their constituent domains, detect BGCs in microbial genomes, and predict BGC product classes. These results highlight self-supervised neural networks as a promising framework for improving BGC prediction and classification.

Enzymology of assembly line synthesis by modular polyketide synthases

Modular polyketide synthases (PKSs) run catalytic reactions over dozens of steps in a highly orchestrated manner. To accomplish this synthetic feat, they form megadalton multienzyme complexes that are among the most intricate proteins on earth. Polyketide products are of elaborate chemistry with molecular weights of usually several hundred daltons and include clinically important drugs such as erythromycin (antibiotic), rapamycin (immunosuppressant) and epothilone (anticancer drug). The term 'modular' refers to a hierarchical structuring of modules and domains within an overall assembly line arrangement, in which PKS organization is colinearly translated into the polyketide structure. New structural information obtained during the past few years provides substantial direct insight into the orchestration of catalytic events within a PKS module and leads to plausible models for synthetic progress along assembly lines. In light of these structural insights, the PKS engineering field is poised to enter a new era of engineering.

Insights into azalomycin F assembly-line contribute to evolution-guided polyketide synthase engineering and identification of intermodular recognition

Modular polyketide synthase (PKS) is an ingenious core machine that catalyzes abundant polyketides in nature. Exploring interactions among modules in PKS is very important for understanding the overall biosynthetic process and for engineering PKS assembly-lines. Here, we show that intermodular recognition between the enoylreductase domain ER_1/2 inside module 1/2 and the ketosynthase domain KS₃ inside module 3 is required for the cross-module enoylreduction in azalomycin F (AZL) biosynthesis. We also show that KS₄ of module 4 acts as a gatekeeper facilitating cross-module enoylreduction. Additionally, evidence is provided that module 3 and module 6 in the AZL PKS are evolutionarily homologous, which makes evolution-oriented PKS engineering possible. These results reveal intermodular recognition, furthering understanding of the mechanism of the PKS assembly-line, thus providing different insights into PKS engineering. This also reveals that gene duplication/conversion and subsequent combinations may be a neofunctionalization process in modular PKS assembly-lines, hence providing a different case for supporting the investigation of modular PKS evolution.

Selection for constrained peptides that bind to a single target protein

Peptide secondary metabolites are common in nature and have diverse pharmacologically-relevant functions, from antibiotics to cross-kingdom signaling. Here, we present a method to design large libraries of modified peptides in Escherichia coli and screen them in vivo to identify those that bind to a single target-of-interest. Constrained peptide scaffolds were produced using modified enzymes gleaned from microbial RiPP (ribosomally synthesized and post-translationally modified peptide) pathways and diversified to build large libraries. The binding of a RiPP to a protein target leads to the intein-catalyzed release of an RNA polymerase σ factor, which drives the expression of selectable markers. As a proof-of-concept, a selection was performed for binding to the SARS-CoV-2 Spike receptor binding domain. A 1625 Da constrained peptide (AMK-1057) was found that binds with similar affinity (990 ± 5 nM) as an ACE2-derived peptide. This demonstrates a generalizable method to identify constrained peptides that adhere to a single protein target, as a step towards "molecular glues" for therapeutics and diagnostics.