DDAP: docking domain affinity and biosynthetic pathway prediction tool for type I polyketide synthases

Discovering type I cis-AT polyketides through computational mass spectrometry and genome mining with Seq2PKS

Type 1 polyketides are a major class of natural products used as antiviral, antibiotic, antifungal, antiparasitic, immunosuppressive, and antitumor drugs. Analysis of public microbial genomes leads to the discovery of over sixty thousand type 1 polyketide gene clusters. However, the molecular products of only about a hundred of these clusters are characterized, leaving most metabolites unknown. Characterizing polyketides relies on bioactivity-guided purification, which is expensive and time-consuming. To address this, we present Seq2PKS, a machine learning algorithm that predicts chemical structures derived from Type 1 polyketide synthases. Seq2PKS predicts numerous putative structures for each gene cluster to enhance accuracy. The correct structure is identified using a variable mass spectral database search. Benchmarks show that Seq2PKS outperforms existing methods. Applying Seq2PKS to Actinobacteria datasets, we discover biosynthetic gene clusters for monazomycin, oasomycin A, and 2-aminobenzamide-actiphenol.

Flux balance analysis-based metabolic modeling of microbial secondary metabolism: Current status and outlook

In microorganisms, different from primary metabolism for cellular growth, secondary metabolism is for ecological interactions and stress responses and an important source of natural products widely used in various areas such as pharmaceutics and food additives. With advancements of sequencing technologies and bioinformatics tools, a large number of biosynthetic gene clusters of secondary metabolites have been discovered from microbial genomes. However, due to challenges from the difficulty of genome-scale pathway reconstruction and the limitation of conventional flux balance analysis (FBA) on secondary metabolism, the quantitative modeling of secondary metabolism is poorly established, in contrast to that of primary metabolism. This review first discusses current efforts on the reconstruction of secondary metabolic pathways in genome-scale metabolic models (GSMMs), as well as related FBA-based modeling techniques. Additionally, potential extensions of FBA are suggested to improve the prediction accuracy of secondary metabolite production. As this review posits, biosynthetic pathway reconstruction for various secondary metabolites will become automated and a modeling framework capturing secondary metabolism onset will enhance the predictive power. Expectedly, an improved FBA-based modeling workflow will facilitate quantitative study of secondary metabolism and in silico design of engineering strategies for natural product production.

Metabolic pathway assembly using docking domains from type I cis-AT polyketide synthases

Engineered metabolic pathways in microbial cell factories often have no natural organization and have challenging flux imbalances, leading to low biocatalytic efficiency. Modular polyketide synthases (PKSs) are multienzyme complexes that synthesize polyketide products via an assembly line thiotemplate mechanism. Here, we develop a strategy named mimic PKS enzyme assembly line (mPKSeal) that assembles key cascade enzymes to enhance biocatalytic efficiency and increase target production by recruiting cascade enzymes tagged with docking domains from type I cis-AT PKS. We apply this strategy to the astaxanthin biosynthetic pathway in engineered Escherichia coli for multienzyme assembly to increase astaxanthin production by 2.4-fold. The docking pairs, from the same PKSs or those from different cis-AT PKSs evidently belonging to distinct classes, are effective enzyme assembly tools for increasing astaxanthin production. This study addresses the challenge of cascade catalytic efficiency and highlights the potential for engineering enzyme assembly.

Assembly artificial pathway in design connecting media can increase biosynthetic efficiency, but the choice of connecting media is limited. Here, the authors develop a new protein assembly strategy using a pool of docking peptides from polyketide synthase and show its application in astaxanthin biosynthesis in E. coli.

Biosynthesis of Chlorinated Lactylates in Sphaerospermopsis sp. LEGE 00249

Lactylates are an important group of molecules in the food and cosmetic industries. A series of natural halogenated 1-lactylates, chlorosphaerolactylates (1-4), were recently reported from Sphaerospermopsis sp. LEGE 00249. Here, we identify the cly biosynthetic gene cluster, containing all the necessary functionalities for the biosynthesis of the natural lactylates, based on in silico analyses. Using a combination of stable isotope incorporation experiments and bioinformatic analysis, we propose that dodecanoic acid and pyruvate are the key building blocks in the biosynthesis of 1-4. We additionally report minor analogues of these molecules with varying alkyl chains. This work paves the way to accessing industrially relevant lactylates through pathway engineering.

The year 2020 in natural product bioinformatics: an overview of the latest tools and databases

Covering: 2020 Bioinformatic approaches to document and analyse chemical structures, biosynthetic gene clusters and analytical data play an important role in the study of natural products. Every year, such a large number of new algorithms, tools and databases are released, that it is difficult to keep track of all the latest developments. The aim of this short article is to provide a concise overview of and reference to the major tools, methods and databases that have been released in the past year.

Synthetic biology enabling access to designer polyketides

The full potential of polyketide discovery has yet to be reached owing to a lack of suitable technologies and knowledge required to advance engineering of polyketide biosynthesis. Recent investigations on the discovery, enhancement, and non-natural use of these biosynthetic gene clusters via computational biology, metabolic engineering, structural biology, and enzymology-guided approaches have facilitated improved access to designer polyketides. Here, we discuss recent successes in gene cluster discovery, host strain engineering, precursor-directed biosynthesis, combinatorial biosynthesis, polyketide tailoring, and high-throughput synthetic biology, as well as challenges and outlooks for rapidly generating useful target polyketides.