Exploring the Untapped Biosynthetic Potential of Apicomplexan Parasites

Exploring the Chain Release Mechanism from an Atypical Apicomplexan Polyketide Synthase

Polyketide synthases (PKSs) are megaenzymes that form chemically diverse polyketides and are found within the genomes of nearly all classes of life. We recently discovered the type I PKS from the apicomplexan parasite Toxoplasma gondii, TgPKS2, which contains a unique putative chain release mechanism that includes ketosynthase (KS) and thioester reductase (TR) domains. Our bioinformatic analysis of the thioester reductase of TgPKS2, TgTR, suggests differences compared to other systems and hints at a possibly conserved release mechanism within the apicomplexan subclass Coccidia. To evaluate this release module, we first isolated TgTR and observed that it is capable of 4 electron (4e-) reduction of octanoyl-CoA to the primary alcohol, octanol, utilizing NADH. TgTR was also capable of generating octanol in the presence of octanal and NADH, but no reactions were observed when NADPH was supplied as a cofactor. To biochemically characterize the protein, we measured the catalytic efficiency of TgTR using a fluorescence assay and determined the TgTR binding affinity for cofactor and substrates using isothermal titration calorimetry (ITC). We additionally show that TgTR is capable of reducing an acyl carrier protein (ACP)-tethered substrate by liquid chromatography mass spectrometry and determine that TgTR binds to holo-TgACP4, its predicted cognate ACP, with a KD of 5.75 ± 0.77 μM. Finally, our transcriptional analysis shows that TgPKS2 is upregulated ∼4-fold in the parasite's cyst-forming bradyzoite stage compared to tachyzoites. Our study identifies features that distinguish TgPKS2 from well-characterized systems in bacteria and fungi and suggests it aids the T. gondii cyst stage.

Examination of Secondary Metabolite Biosynthesis in Apicomplexa

Natural product discovery has traditionally relied on the isolation of small molecules from producing species, but genome-sequencing technology and advances in molecular biology techniques have expanded efforts to a wider array of organisms. Protists represent an underexplored kingdom for specialized metabolite searches despite bioinformatic analysis that suggests they harbor distinct biologically active small molecules. Specifically, pathogenic apicomplexan parasites, responsible for billions of global infections, have been found to possess multiple biosynthetic gene clusters, which hints at their capacity to produce polyketide metabolites. Biochemical studies have revealed unique features of apicomplexan polyketide synthases, but to date, the identity and function of the polyketides synthesized by these megaenzymes remains unknown. Herein, we discuss the potential for specialized metabolite production in protists and the possible evolution of polyketide biosynthetic gene clusters in apicomplexan parasites. We then focus on a polyketide synthase from the apicomplexan Toxoplasma gondii to discuss the unique domain architecture and properties of these proteins when compared to previously characterized systems, and further speculate on the possible functions for polyketides in these pathogenic parasites.

A single amino acid residue controls acyltransferase activity in a polyketide synthase from Toxoplasma gondii

Type I polyketide synthases (PKSs) are multidomain, multimodule enzymes capable of producing complex polyketide metabolites. These modules contain an acyltransferase (AT) domain, which selects acyl-CoA substrates to be incorporated into the metabolite scaffold. Herein, we reveal the sequences of three AT domains from a polyketide synthase (TgPKS2) from the apicomplexan parasite Toxoplasma gondii. Phylogenic analysis indicates these ATs (AT1, AT2, and AT3) are distinct from domains in well-characterized microbial biosynthetic gene clusters. Biochemical investigations revealed that AT1 and AT2 hydrolyze malonyl-CoA but the terminal AT3 domain is non-functional. We further identify an "on-off switch" residue that controls activity such that a single amino acid change in AT3 confers hydrolysis activity while the analogous mutation in AT2 eliminates activity. This biochemical analysis of AT domains from an apicomplexan PKS lays the foundation for further molecular and structural studies on PKSs from T. gondii and other protists.

Response of soil protozoa to acid mine drainage in a contaminated terrace

Acid mine drainage (AMD) system represents one of the most unfavorable habitats for microorganisms due to its low pH and high concentrations of metals. Compared to bacteria and fungi, our understanding regarding the response of soil protozoa to such extremely acidic environments remains limited. This study characterized the structures of protozoan communities inhabiting a terrace heavily contaminated by AMD. The sharp environmental gradient of this terrace was generated by annual flooding from an AMD lake located below, which provided a natural setting to unravel the environment-protozoa interactions. Previously unrecognized protozoa, such as Apicomplexa and Euglenozoa, dominated the extremely acidic soils, rather than the commonly recognized members (e.g., Ciliophora and Cercozoa). pH was the most important factor regulating the abundance of protozoan taxa. Metagenomic analysis of protozoan metabolic potential showed that many functional genes encoding for the alleviation of acid stress and various metabolic pathways were enriched, which may facilitate the survival and adaptation of protozoa to acidic environments. In addition, numerous co-occurrences between protozoa and bacterial or fungal taxa were observed, suggesting shared environmental preferences or potential bio-interactions among them. Future studies are required to confirm the ecological roles of these previously unrecognized protozoa as being important soil microorganisms.

Linking Genes to Molecules in Eukaryotic Sources: An Endeavor to Expand Our Biosynthetic Repertoire

The discovery of natural products continues to interest chemists and biologists for their utility in medicine as well as facilitating our understanding of signaling, pathogenesis, and evolution. Despite an attenuation in the discovery rate of new molecules, the current genomics and transcriptomics revolution has illuminated the untapped biosynthetic potential of many diverse organisms. Today, natural product discovery can be driven by biosynthetic gene cluster (BGC) analysis, which is capable of predicting enzymes that catalyze novel reactions and organisms that synthesize new chemical structures. This approach has been particularly effective in mining bacterial and fungal genomes where it has facilitated the discovery of new molecules, increased the understanding of metabolite assembly, and in some instances uncovered enzymes with intriguing synthetic utility. While relatively less is known about the biosynthetic potential of non-fungal eukaryotes, there is compelling evidence to suggest many encode biosynthetic enzymes that produce molecules with unique bioactivities. In this review, we highlight how the advances in genomics and transcriptomics have aided natural product discovery in sources from eukaryotic lineages. We summarize work that has successfully connected genes to previously identified molecules and how advancing these techniques can lead to genetics-guided discovery of novel chemical structures and reactions distributed throughout the tree of life. Ultimately, we discuss the advantage of increasing the known biosynthetic space to ease access to complex natural and non-natural small molecules.

Investigating the Role of Class I Adenylate-Forming Enzymes in Natural Product Biosynthesis

Adenylate-forming enzymes represent one of the most important enzyme classes in biology, responsible for the activation of carboxylate substrates for biosynthetic modifications. The byproduct of the adenylate-forming enzyme acetyl-CoA synthetase, acetyl-CoA, is incorporated into virtually every primary and secondary metabolic pathway. Modification of acetyl-CoA by an array of other adenylate-forming enzymes produces complex classes of natural products including nonribosomal peptides, polyketides, phenylpropanoids, lipopeptides, and terpenes. Adenylation domains possess a variety of unique structural and functional features that provide for such diversification in their resulting metabolites. As the number of organisms with sequenced genomes increases, more adenylate-forming enzymes are being identified, each with roles in metabolite production that have yet to be characterized. In this Review, we explore the broad role of class I adenylate-forming enzymes in the context of natural product biosynthesis and how they contribute to primary and secondary metabolism by focusing on important work conducted in the field. We highlight features of subclasses from this family that facilitate the production of structurally diverse metabolites, including those from noncanonical adenylation domains, and additionally discuss when biological roles for these compounds are known.

Molecular modeling of a series of dehydroquinate dehydratase type II inhibitors of Mycobacterium tuberculosis and design of new binders

Tuberculosis, caused by Mycobacterium tuberculosis (M. tuberculosis), is still responsible for a large number of fatal cases, especially in developing countries with alarming rates of incidence and prevalence worldwide. Mycobacterium tuberculosis has a remarkable ability to develop new resistance mechanisms to the conventional antimicrobials treatment. Because of this, there is an urgent need for novel bioactive compounds for its treatment. The dehydroquinate dehydratase II (DHQase II) is considered a key enzyme of shikimate pathway, and it can be used as a promising target for the design of new bioactive compounds with antibacterial action. The aim of this work was the construction of QSAR models to aid the design of new potential DHQase II inhibitors. For that purpose, various molecular modeling approaches, such as activity cliff, QSAR models and computer-aided ligand design were utilized. A predictive in silico 4D-QSAR model was built using a database comprising 86 inhibitors of DHQase II, and the model was used to predict the activity of the designed ligands. The obtained model proved to predict well the DHQase II inhibition for an external validation dataset ([Formula: see text] = 0.72). Also, the Activity Cliff analysis shed light on important structural features applied to the ligand design.