ClusterCAD 2.0: an updated computational platform for chimeric type I polyketide synthase and nonribosomal peptide synthetase design

Novel Gene Clusters for Secondary Metabolite Synthesis in Mesophotic Sponge-Associated Bacteria

Mesophotic coral ecosystems (MCEs) host a diverse array of sponge species, which represent a promising source of bioactive compounds. Increasing evidence suggests that sponge-associated bacteria may be the primary producers of these compounds. However, cultivating these bacteria under laboratory conditions remains a significant challenge. To investigate the rich resource of bioactive compounds synthesised by mesophotic sponge-associated bacteria, we retrieved 429 metagenome-assembled genomes (MAGs) from 15 mesophotic sponges, revealing a strong correlation between bacterial diversity and sponge species. Furthermore, we identified 1637 secondary metabolite biosynthetic gene clusters (BGCs) within these MAGs. Among the identified BGCs, terpenes were the most abundant (495), followed by 369 polyketide synthases (PKSs), 293 ribosomally synthesised and post-translationally modified peptides (RiPPs) and 135 nonribosomal peptide synthetases (NRPSs). The BGCs were classified into 1086 gene cluster families (GCFs) based on sequence similarity. Notably, only five GCFs included experimentally validated reference BGCs from the Minimum Information about a Biosynthetic Gene cluster database (MIBiG). Additionally, an unusual abundance of BGCs was detected in Entotheonella sp. (s191209.Bin93) from the Tectomicrobia phylum. In contrast, members of Proteobacteria and Acidobacteriota harboured fewer BGCs (6-7 on average), yet their high abundance in MCE sponges suggests a potentially rich reservoir of BGCs. Analysis of the BGC distribution patterns revealed that a subset of BGCs, including terpene GCFs (FAM_00447 and FAM_01046), PKS GCF (FAM_00235), and RiPPs GCF (FAM_01143), were widespread across mesophotic sponges. Furthermore, 32 GCFs were consistently present in the same MAGs across different sponges, highlighting their potential key biological roles and capacity to yield novel bioactive compounds. This study not only underscores the untapped potential of mesophotic sponge-associated bacteria as a source of bioactive compounds but also provides valuable insights into the intricate interactions between sponges and their symbiotic microbial communities.

Repurposing a Fully Reducing Polyketide Synthase toward 2-Methyl Guerbet-like Lipids

In nature, thousands of diverse and bioactive polyketides are assembled by a family of multifunctional, "assembly line" enzyme complexes called polyketide synthases (PKS). Since the late 20th century, there have been several attempts to decode, rearrange, and "reprogram" the PKS assembly line to generate valuable materials such as biofuels and platform chemicals. Here, the first module from Mycobacterium tuberculosis (Mt) PKS12, an unorthodox, "modularly iterative" PKS, was modified and repurposed toward the formation of 2-methyl Guerbet lipids, which have wide applications in industry. We established a robust method for the recombinant expression and purification of this modified module (named [M1*]), and we demonstrated its ability to catalyze the formation of several 2-methyl Guerbet-like lipids (C13-C21). Furthermore, we studied and applied the promiscuous thioesterase activity of a neighboring β-ketoacyl synthase (KS) to release [M1*]-bound condensation products in a one-pot biosynthetic cascade. Finally, starting from lauric acid, we could generate our primary target compound (2-methyltetradecanoic acid) by coupling the Escherichia coli fatty acyl-CoA synthetase FadD to [M1*]. This work supports the biosynthetic utility of engineered PKS modules such as [M1*] and their ability to derive valuable Guerbet-like lipids from inexpensive fatty acids.

Seamless site-directed mutagenesis in complex cloned DNA sequences using the RedEx method

Seamless site-directed mutagenesis is an important technique for studying protein functions, tuning enzyme catalytic activities and modifying genetic elements in multiple rounds because it can insert, delete or substitute nucleotides, DNA segments or even entire genes at the target site without introducing any unwanted change. To facilitate seamless site-directed mutagenesis in large plasmids and bacterial artificial chromosomes (BACs) with repetitive sequences, we recently developed the RedEx strategy. Compared with previous methods, our approach achieves the recovery of correct recombinants with high accuracy by circumventing unwanted recombination between repetitive sequences. RedEx readily yields more than 80% accuracy in seamless DNA insertion and deletion in large multimodular polyketide synthase gene clusters, which are among the most difficult targets due to the large number of repetitive DNA sequences in modules encoding almost identical enzymes. Here we present the RedEx method by describing in detail the seamless site-directed mutagenesis in a BAC vector. Overall, the process includes three parts: (1) insertion of the RedEx cassette containing the desired mutation together with selection-counterselection markers flanked by unique restriction sites and 20-bp overlapping sequences into the target site by recombineering, (2) removal of the selection-counterselection markers in the BAC by restriction digestion and (3) circularization of the linear BAC by exonuclease-mediated in vitro DNA annealing. This protocol can be performed within 3 weeks and will enable researchers with DNA cloning experience to master seamless site-directed mutagenesis to accelerate their research.

Advances, opportunities, and challenges in methods for interrogating the structure activity relationships of natural products

Time span in literature: 1985-early 2024Natural products play a key role in drug discovery, both as a direct source of drugs and as a starting point for the development of synthetic compounds. Most natural products are not suitable to be used as drugs without further modification due to insufficient activity or poor pharmacokinetic properties. Choosing what modifications to make requires an understanding of the compound's structure-activity relationships. Use of structure-activity relationships is commonplace and essential in medicinal chemistry campaigns applied to human-designed synthetic compounds. Structure-activity relationships have also been used to improve the properties of natural products, but several challenges still limit these efforts. Here, we review methods for studying the structure-activity relationships of natural products and their limitations. Specifically, we will discuss how synthesis, including total synthesis, late-stage derivatization, chemoenzymatic synthetic pathways, and engineering and genome mining of biosynthetic pathways can be used to produce natural product analogs and discuss the challenges of each of these approaches. Finally, we will discuss computational methods including machine learning methods for analyzing the relationship between biosynthetic genes and product activity, computer aided drug design techniques, and interpretable artificial intelligence approaches towards elucidating structure-activity relationships from models trained to predict bioactivity from chemical structure. Our focus will be on these latter topics as their applications for natural products have not been extensively reviewed. We suggest that these methods are all complementary to each other, and that only collaborative efforts using a combination of these techniques will result in a full understanding of the structure-activity relationships of natural products.

RAIChU: automating the visualisation of natural product biosynthesis

Natural products are molecules that fulfil a range of important ecological functions. Many natural products have been exploited for pharmaceutical and agricultural applications. In contrast to many other specialised metabolites, the products of modular nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) systems can often (partially) be predicted from the DNA sequence of the biosynthetic gene clusters. This is because the biosynthetic pathways of NRPS and PKS systems adhere to consistent rulesets. These universal biosynthetic rules can be leveraged to generate biosynthetic models of biosynthetic pathways. While these principles have been largely deciphered, software that leverages these rules to automatically generate visualisations of biosynthetic models has not yet been developed. To enable high-quality automated visualisations of natural product biosynthetic pathways, we developed RAIChU (Reaction Analysis through Illustrating Chemical Units), which produces depictions of biosynthetic transformations of PKS, NRPS, and hybrid PKS/NRPS systems from predicted or experimentally verified module architectures and domain substrate specificities. RAIChU also boasts a library of functions to perform and visualise reactions and pathways whose specifics (e.g., regioselectivity, stereoselectivity) are still difficult to predict, including terpenes, ribosomally synthesised and posttranslationally modified peptides and alkaloids. Additionally, RAIChU includes 34 prevalent tailoring reactions to enable the visualisation of biosynthetic pathways of fully maturated natural products. RAIChU can be integrated into Python pipelines, allowing users to upload and edit results from antiSMASH, a widely used BGC detection and annotation tool, or to build biosynthetic PKS/NRPS systems from scratch. RAIChU's cluster drawing correctness (100%) and drawing readability (97.66%) were validated on 5000 randomly generated PKS/NRPS systems, and on the MIBiG database. The automated visualisation of these pathways accelerates the generation of biosynthetic models, facilitates the analysis of large (meta-) genomic datasets and reduces human error. RAIChU is available at https://github.com/BTheDragonMaster/RAIChU and https://pypi.org/project/raichu .Scientific contributionRAIChU is the first software package capable of automating high-quality visualisations of natural product biosynthetic pathways. By leveraging universal biosynthetic rules, RAIChU enables the depiction of complex biosynthetic transformations for PKS, NRPS, ribosomally synthesised and posttranslationally modified peptide (RiPP), terpene and alkaloid systems, enhancing predictive and analytical capabilities. This innovation not only streamlines the creation of biosynthetic models, making the analysis of large genomic datasets more efficient and accurate, but also bridges a crucial gap in predicting and visualising the complexities of natural product biosynthesis.

Triumphs and Challenges of Natural Product Discovery in the Postgenomic Era

Natural products have played significant roles as medicine and food throughout human history. Here, we first provide a brief historical overview of natural products, their classification and biosynthetic origins, and the microbiological and genetic methods used for their discovery. We also describe and discuss the technologies that revolutionized the field, which transitioned from classic genetics to genome-centric discovery approximately two decades ago. We then highlight the most recent advancements and approaches in the current postgenomic era, in which genome mining is a standard operation and high-throughput analytical methods allow parallel discovery of genes and molecules at an unprecedented pace. Finally, we discuss the new challenges faced by the field of natural products and the future of systematic heterologous expression and strain-independent discovery, which promises to deliver more molecules in vials than ever before.

Design and engineering of artificial biosynthetic pathways-where do we stand and where do we go?

The production of commodity and specialty chemicals relies heavily on fossil fuels. The negative impact of this dependency on our environment and climate has spurred a rising demand for more sustainable methods to obtain such chemicals from renewable resources. Herein, biotransformations of these renewable resources facilitated by enzymes or (micro)organisms have gained significant attention, since they can occur under mild conditions and reduce waste. These biotransformations typically leverage natural metabolic processes, which limits the scope and production capacity of such processes. In this mini-review, we provide an overview of advancements made in the past 5 years to expand the repertoire of biotransformations in engineered microorganisms. This ranges from redesign of existing pathways driven by retrobiosynthesis and computational design to directed evolution of enzymes and de novo pathway design to unlock novel routes for the synthesis of desired chemicals. We highlight notable examples of pathway designs for the production of commodity and specialty chemicals, showcasing the potential of these approaches. Lastly, we provide an outlook on future pathway design approaches.

Enzyme Databases in the Era of Omics and Artificial Intelligence

Enzyme research is important for the development of various scientific fields such as medicine and biotechnology. Enzyme databases facilitate this research by providing a wide range of information relevant to research planning and data analysis. Over the years, various databases that cover different aspects of enzyme biology (e.g., kinetic parameters, enzyme occurrence, and reaction mechanisms) have been developed. Most of the databases are curated manually, which improves reliability of the information; however, such curation cannot keep pace with the exponential growth in published data. Lack of data standardization is another obstacle for data extraction and analysis. Improving machine readability of databases is especially important in the light of recent advances in deep learning algorithms that require big training datasets. This review provides information regarding the current state of enzyme databases, especially in relation to the ever-increasing amount of generated research data and recent advancements in artificial intelligence algorithms. Furthermore, it describes several enzyme databases, providing the reader with necessary information for their use.