Single Amino Acid Substitutions Alter the Efficiency of Docking in Modular Polyketide Biosynthesis

Polyketide synthases mutation in tuberculosis transmission revealed by whole genomic sequence, China, 2011-2019

Introduction: Tuberculosis (TB) is an infectious disease caused by a bacterium called Mycobacterium tuberculosis (Mtb). Previous studies have primarily focused on the transmissibility of multidrug-resistant (MDR) or extensively drug-resistant (XDR) Mtb. However, variations in virulence across Mtb lineages may also account for differences in transmissibility. In Mtb, polyketide synthase (PKS) genes encode large multifunctional proteins which have been shown to be major mycobacterial virulence factors. Therefore, this study aimed to identify the role of PKS mutations in TB transmission and assess its risk and characteristics. Methods: Whole genome sequences (WGSs) data from 3,204 Mtb isolates was collected from 2011 to 2019 in China. Whole genome single nucleotide polymorphism (SNP) profiles were used for phylogenetic tree analysis. Putative transmission clusters (≤10 SNPs) were identified. To identify the role of PKS mutations in TB transmission, we compared SNPs in the PKS gene region between "clustered isolates" and "non-clustered isolates" in different lineages. Results: Cluster-associated mutations in ppsA, pks12, and pks13 were identified among different lineage isolates. They were statistically significant among clustered strains, indicating that they may enhance the transmissibility of Mtb. Conclusion: Overall, this study provides new insights into the function of PKS and its localization in M. tuberculosis. The study found that ppsA, pks12, and pks13 may contribute to disease progression and higher transmission of certain strains. We also discussed the prospective use of mutant ppsA, pks12, and pks13 genes as drug targets.

Coevolution-based prediction of protein-protein interactions in polyketide biosynthetic assembly lines

MOTIVATION

Polyketide synthases (PKSs) are enzymes that generate diverse molecules of great pharmaceutical importance, including a range of clinically used antimicrobials and antitumor agents. Many polyketides are synthesized by cis-AT modular PKSs, which are organized in assembly lines, in which multiple enzymes line up in a specific order. This order is defined by specific protein-protein interactions (PPIs). The unique modular structure and catalyzing mechanism of these assembly lines makes their products predictable and also spurred combinatorial biosynthesis studies to produce novel polyketides using synthetic biology. However, predicting the interactions of PKSs, and thereby inferring the order of their assembly line, is still challenging, especially for cases in which this order is not reflected by the ordering of the PKS-encoding genes in the genome.

RESULTS

Here, we introduce PKSpop, which uses a coevolution-based PPI algorithm to infer protein order in PKS assembly lines. Our method accurately predicts protein orders (93% accuracy). Additionally, we identify new residue pairs that are key in determining interaction specificity, and show that coevolution of N- and C-terminal docking domains of PKSs is significantly more predictive for PPIs than coevolution between ketosynthase and acyl carrier protein domains.

AVAILABILITY AND IMPLEMENTATION

The code is available on http://www.bif.wur.nl/ (under 'Software').

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Protein-protein interactions in "cis-AT" polyketide synthases

Covering: up to the end of 2018 Polyketides are a valuable source of bioactive and clinically important molecules. The biosynthesis of these chemically complex molecules has led to the discovery of equally complex polyketide synthase (PKS) pathways. Crystallography has yielded snapshots of individual catalytic domains, di-domains, and multi-domains from a variety of PKS megasynthases, and cryo-EM studies have provided initial views of a PKS module in a series of defined biochemical states. Here, we review the structural and biochemical results that shed light on the protein-protein interactions critical to catalysis by PKS systems with an embedded acyltransferase. Interactions include those that occur both within and between PKS modules, as well as with accessory enzymes.

Cyanobacterial polyketide synthase docking domains: a tool for engineering natural product biosynthesis

Modular type I polyketide synthases (PKSs) are versatile biosynthetic systems that initiate, successively elongate, and modify acyl chains. Intermediate transfer between modules is mediated via docking domains, which are attractive targets for PKS pathway engineering to produce natural product analogs. We identified a class 2 docking domain in cyanobacterial PKSs and determined crystal structures for two docking domain pairs, revealing a distinct class 2 docking strategy for promoting intermediate transfer. The selectivity of class 2 docking interactions, demonstrated in binding and biochemical assays, could be altered by mutagenesis. We determined the ideal fusion location for exchanging class 1 and class 2 docking domains and demonstrated effective polyketide chain transfer in heterologous modules. Thus, class 2 docking domains are tools for rational bioengineering of a broad range of PKSs containing either class 1 or 2 docking domains.

Computational Methods for Identification of Novel Secondary Metabolite Biosynthetic Pathways by Genome Analysis

Secondary metabolites belonging to polyketide and nonribosomal peptide families constitute a major class of natural products with diverse biological functions and a variety of pharmaceutically important properties. Experimental studies have shown that the biosynthetic machinery for polyketide and nonribosomal peptides involves multi-functional megasynthases like Polyketide Synthases (PKSs) and nonribosomal peptide synthetases (NRPSs) which utilize a thiotemplate mechanism similar to that for fatty acid biosynthesis. Availability of complete genome sequences for an increasing number of microbial organisms has provided opportunities for using in silico genome mining to decipher the secondary metabolite natural product repertoire encoded by these organisms. Therefore, in recent years there have been major advances in development of computational methods which can analyze genome sequences to identify genes involved in secondary metabolite biosynthesis and help in deciphering the putative chemical structures of their biosynthetic products based on analysis of the sequence and structural features of the proteins encoded by these genes. These computational methods for deciphering the secondary metabolite biosynthetic code essentially involve identification of various catalytic domains present in this PKS/NRPS family of enzymes; a prediction of various reactions in these enzymatic domains and their substrate specificities and also precise identification of the order in which these domains would catalyze various biosynthetic steps. Structural bioinformatics analysis of known secondary metabolite biosynthetic clusters has helped in formulation of predictive rules for deciphering domain organization, substrate specificity, and order of substrate channeling. In this chapter, the progress in development of various computational methods is discussed by different research groups, and specifically, the utility in identification of novel metabolites by genome mining and rational design of natural product analogs by biosynthetic engineering studies.

SBSPKS: structure based sequence analysis of polyketide synthases

Polyketide synthases (PKSs) catalyze biosynthesis of a diverse family of pharmaceutically important secondary metabolites. Bioinformatics analysis of sequence and structural features of PKS proteins plays a crucial role in discovery of new natural products by genome mining, as well as in design of novel secondary metabolites by biosynthetic engineering. The availability of the crystal structures of various PKS catalytic and docking domains, and mammalian fatty acid synthase module prompted us to develop SBSPKS software which consists of three major components. Model_3D_PKS can be used for modeling, visualization and analysis of 3D structure of individual PKS catalytic domains, dimeric structures for complete PKS modules and prediction of substrate specificity. Dock_Dom_Anal identifies the key interacting residue pairs in inter-subunit interfaces based on alignment of inter-polypeptide linker sequences to the docking domain structure. In case of modular PKS with multiple open reading frames (ORFs), it can predict the cognate order of substrate channeling based on combinatorial evaluation of all possible interface contacts. NRPS–PKS provides user friendly tools for identifying various catalytic domains in the sequence of a Type I PKS protein and comparing them with experimentally characterized PKS/NRPS clusters cataloged in the backend databases of SBSPKS. SBSPKS is available at http://www.nii.ac.in/sbspks.html.

Functional dissection of a multimodular polypeptide of the pikromycin polyketide synthase into monomodules by using a matched pair of heterologous docking domains

The pikromyin polyketide synthase (PKS) in Streptomyces venezulae is comprised of a loading module and six extension modules, which generate the corresponding 14-membered macrolactone product. PikAI is a multimodular component of this PKS and houses both the loading domain and the first two extension modules, joined by short intraprotein linkers. We have shown that PikAI can be separated into two proteins at either of these linkers, only when matched pairs of docking domains (DDs) from a heterologous modular phoslactomycin PKS are used in place of the intraprotein linker. In both cases the yields of pikromycin produced by the S. venezuelae mutant were 50% of that of a S. venezuelae strain expressing the native trimodular PikAI. This observation provides the first demonstration that such separations do not dramatically impact the efficiency of the entire in vivo biosynthetic process. Expression of module 2 as a monomodular protein fused to a heterologous N-terminal docking domain was also observed to give almost a tenfold improvement in the in vivo generation of pikromycin from a synthetic diketide intermediate. These results demonstrate the utility of DDs to manipulate biosynthetic processes catalyzed by modular PKSs and the quest to generate novel polyketide products.

Towards prediction of metabolic products of polyketide synthases: an in silico analysis

Sequence data arising from an increasing number of partial and complete genome projects is revealing the presence of the polyketide synthase (PKS) family of genes not only in microbes and fungi but also in plants and other eukaryotes. PKSs are huge multifunctional megasynthases that use a variety of biosynthetic paradigms to generate enormously diverse arrays of polyketide products that posses several pharmaceutically important properties. The remarkable conservation of these gene clusters across organisms offers abundant scope for obtaining novel insights into PKS biosynthetic code by computational analysis. We have carried out a comprehensive in silico analysis of modular and iterative gene clusters to test whether chemical structures of the secondary metabolites can be predicted from PKS protein sequences. Here, we report the success of our method and demonstrate the feasibility of deciphering the putative metabolic products of uncharacterized PKS clusters found in newly sequenced genomes. Profile Hidden Markov Model analysis has revealed distinct sequence features that can distinguish modular PKS proteins from their iterative counterparts. For iterative PKS proteins, structural models of iterative ketosynthase (KS) domains have revealed novel correlations between the size of the polyketide products and volume of the active site pocket. Furthermore, we have identified key residues in the substrate binding pocket that control the number of chain extensions in iterative PKSs. For modular PKS proteins, we describe for the first time an automated method based on crucial intermolecular contacts that can distinguish the correct biosynthetic order of substrate channeling from a large number of non-cognate combinatorial possibilities. Taken together, our in silico analysis provides valuable clues for formulating rules for predicting polyketide products of iterative as well as modular PKS clusters. These results have promising potential for discovery of novel natural products by genome mining and rational design of novel natural products.

Bioinformatic perspectives on NRPS/PKS megasynthases: advances and challenges

The increased understanding of both fundamental principles and mechanistic variations of NRPS/PKS megasynthases along with the unprecedented availability of microbial sequences has inspired a number of in silico studies of both enzyme families. The insights that can be extracted from these analyses go far beyond a rough classification of data and have turned bioinformatics into a frontier field of natural products research. As databases are flooded with NRPS/PKS gene sequence of microbial genomes and metagenomes, increasingly reliable structural prediction methods can help to uncover hidden treasures. Already, phylogenetic analyses have revealed that NRPS/PKS pathways should not simply be regarded as enzyme complexes, specifically evolved to product a selected natural product. Rather, they represent a collection of genetic opinions, allowing biosynthetic pathways to be shuffled in a process of perpetual chemical innovations and pathways diversification in nature can give impulses for specificities, protein interactions and genetic engineering of libraries of novel peptides and polyketides. The successful translation of the knowledge obtained from bioinformatic dissection of NRPS/PKS megasynthases into new techniques for drug discovery and design remain challenges for the future.

Opportunities for enzyme engineering in natural product biosynthesis

Organisms from all kingdoms of life produce a plethora of natural products that display a range of biological activities. One key limitation of developing these natural products into pharmaceuticals is the inability to perform effective, fast, and inexpensive structure-activity relationship studies (SAR). Recently, enzyme engineering strategies have allowed the exploration of metabolic engineering of biosynthetic pathways to create new 'natural' products that can be used for SAR. The enzymes that enable the biosynthesis of natural products represent a largely untapped resource of potential biocatalysts. A challenge for the field is how to harness the wealth of reaction types used for natural product metabolism to obtain useful biocatalysts for industrial biotransformations.

Structural basis for binding specificity between subclasses of modular polyketide synthase docking domains

Bacterial type I polyketide synthases (PKSs) assemble structurally diverse natural products of significant clinical value from simple metabolic building blocks. The synthesis of these compounds occurs in a processive fashion along a large multiprotein complex. Transfer of the acyl intermediate across interpolypeptide junctions is mediated, at least in large part, by N- and C-terminal docking domains. We report here a comprehensive analysis of the binding affinity and selectivity for the complete set of discrete docking domain pairs in the pikromycin and erythromycin PKS systems. Despite disconnection from their parent module, each cognate pair of docking domains retained exquisite binding selectivity. Further insights were obtained by X-ray crystallographic analysis of the PikAIII/PikAIV docking domain interface. This new information revealed a series of key interacting residues that enabled development of a structural model for the recently proposed H2-T2 class of polypeptides involved in PKS intermodular molecular recognition.

Novel intermolecular iterative mechanism for biosynthesis of mycoketide catalyzed by a bimodular polyketide synthase

In recent years, remarkable versatility of polyketide synthases (PKSs) has been recognized; both in terms of their structural and functional organization as well as their ability to produce compounds other than typical secondary metabolites. Multifunctional Type I PKSs catalyze the biosynthesis of polyketide products by either using the same active sites repetitively (iterative) or by using these catalytic domains only once (modular) during the entire biosynthetic process. The largest open reading frame in Mycobacterium tuberculosis, pks12, was recently proposed to be involved in the biosynthesis of mannosyl-β-1-phosphomycoketide (MPM). The PKS12 protein contains two complete sets of modules and has been suggested to synthesize mycoketide by five alternating condensations of methylmalonyl and malonyl units by using an iterative mode of catalysis. The bimodular iterative catalysis would require transfer of intermediate chains from acyl carrier protein domain of module 2 to ketosynthase domain of module 1. Such bimodular iterations during PKS biosynthesis have not been characterized and appear unlikely based on recent understanding of the three-dimensional organization of these proteins. Moreover, all known examples of iterative PKSs so far characterized involve unimodular iterations. Based on cell-free reconstitution of PKS12 enzymatic machinery, in this study, we provide the first evidence for a novel “modularly iterative” mechanism of biosynthesis. By combination of biochemical, computational, mutagenic, analytical ultracentrifugation and atomic force microscopy studies, we propose that PKS12 protein is organized as a large supramolecular assembly mediated through specific interactions between the C- and N-terminus linkers. PKS12 protein thus forms a modular assembly to perform repetitive condensations analogous to iterative proteins. This novel intermolecular iterative biosynthetic mechanism provides new perspective to our understanding of polyketide biosynthetic machinery and also suggests new ways to engineer polyketide metabolites. The characterization of novel molecular mechanisms involved in biosynthesis of mycobacterial virulent lipids has opened new avenues for drug discovery.

Polyketide synthases (PKSs) form a large family of multifunctional proteins involved in the biosynthesis of diverse classes of natural products. Mycobacterium tuberculosis (Mtb) exploits these polyketide biosynthetic enzymes to synthesize complex lipids, many of which are essential for its virulence. PKSs utilize two common mechanistic themes to produce these metabolites: (1) modular—in which each set of catalytic sites is used only once during the entire biosynthetic process and (2) iterative—in which the same set of active sites is used repeatedly. Our study with PKS12 protein from Mtb (the largest protein in this genome) reveals a third mechanism for polyketide biosynthesis. In this hybrid “modularly iterative” mechanism, PKS12 protein forms a supramolecular assembly to perform repetitive cycles of iterations. The protein assembly is formed by specific intermolecular interactions between N- and C-terminus linkers, analogous to modular PKSs. Our study adds a new dimension to the existing catalytic and mechanistic versatility of PKSs, providing a new perspective on how metabolic diversity could be generated by different combinations of existing functional scaffolds.

A novel iterative biosynthetic mechanism for multifunctional polyketide synthases reveals how the metabolic diversity of this enzyme family can arise by using existing scaffolds in novel combinations.

The origins of specificity in polyketide synthase protein interactions

Polyketides, a diverse group of heteropolymers with antibiotic and antitumor properties, are assembled in bacteria by multiprotein chains of modular polyketide synthase (PKS) proteins. Specific protein–protein interactions determine the order of proteins within a multiprotein chain, and thereby the order in which chemically distinct monomers are added to the growing polyketide product. Here we investigate the evolutionary and molecular origins of protein interaction specificity. We focus on the short, conserved N- and C-terminal docking domains that mediate interactions between modular PKS proteins. Our computational analysis, which combines protein sequence data with experimental protein interaction data, reveals a hierarchical interaction specificity code. PKS docking domains are descended from a single ancestral interacting pair, but have split into three phylogenetic classes that are mutually noninteracting. Specificity within one such compatibility class is determined by a few key residues, which can be used to define compatibility subclasses. We identify these residues using a novel, highly sensitive co-evolution detection algorithm called CRoSS (correlated residues of statistical significance). The residue pairs selected by CRoSS are involved in direct physical interactions in a docked-domain NMR structure. A single PKS system can use docking domain pairs from multiple classes, as well as domain pairs from multiple subclasses of any given class. The termini of individual proteins are frequently shuffled, but docking domain pairs straddling two interacting proteins are linked as an evolutionary module. The hierarchical and modular organization of the specificity code is intimately related to the processes by which bacteria generate new PKS pathways.

Biomolecular interactions can be extraordinarily specific. In many instances, a protein can select its single correct binding partner from among a large array of closely related candidates. For polyketide synthases (PKSs), a family of bacterial enzymes, such specificity is essential. Like workers on an assembly line, PKSs function as multiprotein chains, each enzyme modifying its substrate before passing it along to the next. And like a well-designed jigsaw puzzle, the overall multiprotein chain is correctly ordered precisely because each component protein can only bind to specific nearest neighbors. A PKS multiprotein chain is held together by sticky “head” and “tail” domains found at either end of each protein, the head of one protein binding to the tail of the next. We looked for patterns in the amino-acid sequences of these domains that could explain why certain head–tail pairs bind, while others do not. We discovered that heads and tails each come in three very different varieties. Mismatched head–tail pairs do not bind at all, while the binding of a matching head–tail pair is governed by the amino acids found at a few key positions on the physical interface between these domains.