Phylogenetic methods in natural product 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.

Predicting metallophore structure and function through genome mining

Metallophores are small molecule chelators that many microbes use to obtain trace metals from their environment. Through genome mining, where genomes are scanned for metallophore biosynthesis genes, one can not only identify which organisms are likely to produce a metallophore, but also predict the metallophore structure, thus preventing undesired reisolation of known compounds and accelerating characterization. Furthermore, the presence of accessory genes for the transport, utilization, and regulation can suggest the biological function and fate of a metallophore. Modern, user-friendly tools have made powerful genomic analyses accessible to scientists with no bioinformatics experience, but these tools are often not utilized to their full potential. This chapter provides an introduction to metallophore genomics and demonstrates how to use the free, publicly available antiSMASH platform to infer metallophore function and structure.

Untargeted Metabolomics Sheds Light on the Diversity of Major Classes of Secondary Metabolites in the Malpighiaceae Botanical Family

Natural products produced by plants are one of the most investigated natural sources, which substantially contributed to the development of the natural products field. Even though these compounds are widely explored, the literature still lacks comprehensive investigations aiming to explore the evolution of secondary metabolites produced by plants, especially if classical methodologies are employed. The development of sensitive hyphenated techniques and computational tools for data processing has enabled the study of large datasets, being valuable assets for chemosystematic studies. Here, we describe a strategy for chemotaxonomic investigations using the Malpighiaceae botanical family as a model. Our workflow was based on MS/MS untargeted metabolomics, spectral searches, and recently described in silico classification tools, which were mapped into the latest molecular phylogeny accepted for this family. The metabolomic analysis revealed that different ionization modes and extraction protocols significantly impacted the chemical profiles, influencing the chemotaxonomic results. Spectral searches within public databases revealed several clades or genera-specific molecular families, being potential chemical markers for these taxa, while the in silico classification tools were able to expand the Malpighiaceae chemical space. The classes putatively annotated were used for ancestral character reconstructions, which recovered several classes of metabolites as homoplasies (i.e., non-exclusive) or synapomorphies (i.e., exclusive) for all sampled clades and genera. Our workflow combines several approaches to perform a comprehensive evolutionary chemical study. We expect it to be used on further chemotaxonomic investigations to expand chemical knowledge and reveal biological insights for compounds classes in different biological groups.

Streptomyces: host for refactoring of diverse bioactive secondary metabolites

Microbial secondary metabolites are intensively explored due to their demands in pharmaceutical, agricultural and food industries. Streptomyces are one of the largest sources of secondary metabolites having diverse applications. In particular, the abundance of secondary metabolites encoding biosynthetic gene clusters and presence of wobble position in Streptomyces strains make it potential candidate as a native or heterologous host for secondary metabolite production including several cryptic gene clusters expression. Here, we have discussed the developments in Streptomyces strains genome mining, its exploration as a suitable host and application of synthetic biology for refactoring genetic systems for developing chassis for enhanced as well as novel secondary metabolites with reduced genome and cleaned background.

Analysis of Unusual Sulfated Constituents and Anti-infective Properties of Two Indonesian Mangroves, Lumnitzera littorea and Lumnitzera racemosa (Combretaceae)

Lumnitzera littorea and Lumnitzera racemosa are mangrove species distributed widely along the Indonesian coasts. Besides their ecological importance, both are of interest owing to their wealth of natural products, some of which constitute potential sources for medicinal applications. We aimed to discover and characterize new anti-infective compounds, based on population-level sampling of both species from across the Indonesian Archipelago. Root metabolites were investigated by TLC, hyphenated LC-MS/MS and isolation, the internal transcribed spacer (ITS) region of rDNA was used for genetic characterization. Phytochemical characterization of both species revealed an unusual diversity in sulfated constituents with 3,3’,4’-tri-O-methyl-ellagic acid 4-sulfate representing the major compound in most samples. None of these compounds was previously reported for mangroves. Chemophenetic comparison of L. racemosa populations from different localities provided evolutionary information, as supported by molecular phylogenetic evidence. Samples of both species from particular locations exhibited anti-bacterial potential (Southern Nias Island and East Java against Gram-negative bacteria, Halmahera and Ternate Island against Gram-positive bacteria). In conclusion, Lumnitzera roots from natural mangrove stands represent a promising source for sulfated ellagic acid derivatives and further sulfur containing plant metabolites with potential human health benefits.

Evaluation of plant sources for antiinfective lead compound discovery by correlating phylogenetic, spatial, and bioactivity data

Antibiotic resistance and viral diseases are rising around the world and are becoming major threats to global health, food security, and development. One measure that has been suggested to mitigate this crisis is the development of new antibiotics. Here, we provide a comprehensive evaluation of the phylogenetic and biogeographic patterns of antiinfective compounds from seed plants in one of the most species-rich regions on Earth and identify clades with naturally occurring substances potentially suitable for the development of new pharmaceutical compounds. Specifically, we combine taxonomic and phylogenetic data for >7,500 seed plant species from the flora of Java with >16,500 secondary metabolites and 6,255 georeferenced occurrence records to 1) identify clades in the phylogeny that are characterized by either an overrepresentation ("hot clades") or an underrepresentation ("cold clades") of antiinfective compounds and 2) assess the spatial patterns of plants with antiinfective compounds relative to total plant diversity across the region. Across the flora of Java, we identify 26 "hot clades" with plant species providing a high probability of finding antibiotic constituents. In addition, 24 "cold clades" constitute lineages with low numbers of reported activities but which have the potential to yield novel compounds. Spatial patterns of plant species and metabolite diversity are strongly correlated across Java, indicating that regions of highest species diversity afford the highest potential to discover novel natural products. Our results indicate that the combination of phylogenetic, spatial, and phytochemical information is a useful tool to guide the selection of taxa for efforts aimed at lead compound discovery.

Evolutionary dynamics of natural product biosynthesis in bacteria

Covering: 2008 up to 2019The forces of biochemical adaptive evolution operate at the level of genes, manifesting in complex phenotypes and the global biodiversity of proteins and metabolites. While evolutionary histories have been deciphered for some other complex traits, the origins of natural product biosynthesis largely remain a mystery. This fundamental knowledge gap is surprising given the many decades of research probing the genetic, chemical, and biophysical mechanisms of bacterial natural product biosynthesis. Recently, evolutionary thinking has begun to permeate this otherwise mechanistically dominated field. Natural products are now sometimes referred to as 'specialized' rather than 'secondary' metabolites, reinforcing the importance of their biological and ecological functions. Here, we review known evolutionary mechanisms underlying the overwhelming chemical diversity of bacterial secondary metabolism, focusing on enzyme promiscuity and the evolution of enzymatic domains that enable metabolic traits. We discuss the mechanisms that drive the assembly of natural product biosynthetic gene clusters and propose formal definitions for 'specialized' and 'secondary' metabolism. We further explore how biosynthetic gene clusters evolve to synthesize related molecular species, and in turn how the biological and ecological roles that emerge from metabolic diversity are acted on by selection. Finally, we reconcile chemical, functional, and genetic data into an evolutionary model, the dynamic chemical matrix evolutionary hypothesis, in which the relationships between chemical distance, biomolecular activity, and relative fitness shape adaptive landscapes.

Applied evolution: phylogeny-based approaches in natural products research

Here we highlight how phylogenetic analyses can be used to facilitate natural product discovery and structure elucidation.

qNMR for profiling the production of fungal secondary metabolites

Analysis of complex mixtures is a common challenge in natural products research. Quantitative nuclear magnetic resonance spectroscopy offers analysis of complex mixtures at early stages and with benefits that are orthogonal to more common methods of quantitation, including ultraviolet absorption spectroscopy and mass spectrometry. Several experiments were conducted to construct a methodology for use in analysis of extracts of fungal cultures. A broadly applicable method was sought for analysis of both pure and complex samples through use of an externally calibrated method. This method has the benefit of not contaminating valuable samples with the calibrant, and it passed scrutiny for line fitting and reproducibility. The method was implemented to measure the yield of griseofulvin and dechlorogriseofulvin from three fungal isolates. An isolate of Xylaria cubensis (coded MSX48662) was found to biosynthesize griseofulvin in the greatest yield, 149 ± 8 mg per fermentation, and was selected for further supply experiments. Copyright © 2016 John Wiley & Sons, Ltd.

Fungal Identification Using Molecular Tools: A Primer for the Natural Products Research Community

Fungi are morphologically, ecologically, metabolically, and phylogenetically diverse. They are known to produce numerous bioactive molecules, which makes them very useful for natural products researchers in their pursuit of discovering new chemical diversity with agricultural, industrial, and pharmaceutical applications. Despite their importance in natural products chemistry, identification of fungi remains a daunting task for chemists, especially those who do not work with a trained mycologist. The purpose of this review is to update natural products researchers about the tools available for molecular identification of fungi. In particular, we discuss (1) problems of using morphology alone in the identification of fungi to the species level; (2) the three nuclear ribosomal genes most commonly used in fungal identification and the potential advantages and limitations of the ITS region, which is the official DNA barcoding marker for species-level identification of fungi; (3) how to use NCBI-BLAST search for DNA barcoding, with a cautionary note regarding its limitations; (4) the numerous curated molecular databases containing fungal sequences; (5) the various protein-coding genes used to augment or supplant ITS in species-level identification of certain fungal groups; and (6) methods used in the construction of phylogenetic trees from DNA sequences to facilitate fungal species identification. We recommend that, whenever possible, both morphology and molecular data be used for fungal identification. Our goal is that this review will provide a set of standardized procedures for the molecular identification of fungi that can be utilized by the natural products research community.

Phylogeny-guided (meta)genome mining approach for the targeted discovery of new microbial natural products

Genomics-based methods are now commonplace in natural products research. A phylogeny-guided mining approach provides a means to quickly screen a large number of microbial genomes or metagenomes in search of new biosynthetic gene clusters of interest. In this approach, biosynthetic genes serve as molecular markers, and phylogenetic trees built with known and unknown marker gene sequences are used to quickly prioritize biosynthetic gene clusters for their metabolites characterization. An increase in the use of this approach has been observed for the last couple of years along with the emergence of low cost sequencing technologies. The aim of this review is to discuss the basic concept of a phylogeny-guided mining approach, and also to provide examples in which this approach was successfully applied to discover new natural products from microbial genomes and metagenomes. I believe that the phylogeny-guided mining approach will continue to play an important role in genomics-based natural products research.

α-Pyrone derivatives, tetra/hexahydroxanthones, and cyclodepsipeptides from two freshwater fungi

Eighteen (1-18) and seven (1, 4, 6-8, 17 and 18) compounds were isolated from organic extracts of axenic cultures of two freshwater fungi Clohesyomyces sp. and Clohesyomyces aquaticus (Dothideomycetes, Ascomycota), respectively. Compounds 1-12 belong to the α-pyrone class of natural products, compounds 13 and 14 were tetrahydroxanthones, compounds 15 and 16 were hexahydroxanthones, while compounds 17 and 18 were cyclodepsipeptides. The structures were elucidated using a set of spectroscopic and spectrometric techniques. The absolute configurations of compounds 2, 3, 6, and 7 were assigned via a modified Mosher's ester method using ¹H NMR data. The relative configurations of compounds 14-16 were determined through NOE data. Compounds 1, 2, 6, 8, 13, 14, and 15 were found to inhibit the essential enzyme bacterial peptidyl-tRNA hydrolase (Pth1), with (13; secalonic acid A) being the most potent. Compounds 1 and 4-18 were also evaluated for antimicrobial activity against an array of bacteria and fungi but were found to be inactive.

The evolution of genome mining in microbes - a review

Covering: 2006 to 2016The computational mining of genomes has become an important part in the discovery of novel natural products as drug leads. Thousands of bacterial genome sequences are publically available these days containing an even larger number and diversity of secondary metabolite gene clusters that await linkage to their encoded natural products. With the development of high-throughput sequencing methods and the wealth of DNA data available, a variety of genome mining methods and tools have been developed to guide discovery and characterisation of these compounds. This article reviews the development of these computational approaches during the last decade and shows how the revolution of next generation sequencing methods has led to an evolution of various genome mining approaches, techniques and tools. After a short introduction and brief overview of important milestones, this article will focus on the different approaches of mining genomes for secondary metabolites, from detecting biosynthetic genes to resistance based methods and "evo-mining" strategies including a short evaluation of the impact of the development of genome mining methods and tools on the field of natural products and microbial ecology.

Antioxidant potential of lichen species and their secondary metabolites. A systematic review

CONTEXT

Pharmacological interest of lichens lies in their capacity to produce bioactive secondary metabolites, being most of them phenolic compounds with reactive hydroxyl groups that confer antioxidant potential through various mechanisms. Increasing incidence and impact of oxidative stress-related diseases (i.e., neurodegenerative disorders) has encouraged the search of new pharmacological strategies to face them. Lichens appear to be a promising source of phenolic compounds in the discovery of natural products exerting antioxidant activity.

OBJECTIVE

The present review thoroughly discusses the available knowledge on antioxidant properties of lichens, including both in vitro and in vivo studies and the parameters assessed so far on lichen constituents.

METHODS

Literature survey was performed by using as main databases PubMed, Google Scholar, Scopus, Science Direct, and Recent Literature on Lichens. We reviewed 98 highlighted research articles without date restriction.

RESULTS

Current report collects data related to antioxidant activities of more than 75 lichen species (from 18 botanical families) and 65 isolated metabolites. Much information comes from in vitro investigations, such as chemical assays evaluating radical scavenging properties, lipid peroxidation inhibition, and reducing power of lichen species and compounds; similarly, research on cellular substrates and animal models generally measures antioxidant enzymes levels and other antioxidant markers, such as glutathione levels or tissue peroxidation.

CONCLUSION

Since consistent evidence demonstrated the contribution of oxidative stress on the development and progression of several human diseases, reviewed data suggest that some lichen compounds are worthy of further investigation and better understanding of their antioxidant and neuroprotective potentials.

Antimicrobial dihydrobenzofurans and xanthenes from a foliar endophyte of Pinus strobus

Foliar fungal endophytes of Pinus strobus (eastern white pine) were collected from different sites across south-eastern New Brunswick, Canada and screened for the production of bioactive metabolites. From one site, two fungal isolates representing a formerly unknown genus and species within the family Massarinaceae (Pleosporales, Dothideomycetes, Ascomycota) were resolved by phylogenetic analysis. These isolates produced crude organic extracts that were active against Microbotryum violaceum and Saccharomyces cerevisiae. From these strains, DAOM 242779 and 242780, four dihydrobenzofurans (1-4) and two xanthenes (5-6) were characterized. Structures were elucidated by HRMS, interpretation of NMR spectra and other spectroscopic techniques. All isolated metabolites displayed antimicrobial activity against the biotrophic fungal pathogen M. violaceum and Bacillus subtilis.

Current strategies for the elucidation of the structures of natural products

The application of the results from various physical methods to the isolation, characterisation and elucidation of the structures and stereochemistry of natural products is reviewed.

Can phylogeny predict chemical diversity and potential medicinal activity of plants? A case study of Amaryllidaceae

BACKGROUND

During evolution, plants and other organisms have developed a diversity of chemical defences, leading to the evolution of various groups of specialized metabolites selected for their endogenous biological function. A correlation between phylogeny and biosynthetic pathways could offer a predictive approach enabling more efficient selection of plants for the development of traditional medicine and lead discovery. However, this relationship has rarely been rigorously tested and the potential predictive power is consequently unknown.

RESULTS

We produced a phylogenetic hypothesis for the medicinally important plant subfamily Amaryllidoideae (Amaryllidaceae) based on parsimony and Bayesian analysis of nuclear, plastid, and mitochondrial DNA sequences of over 100 species. We tested if alkaloid diversity and activity in bioassays related to the central nervous system are significantly correlated with phylogeny and found evidence for a significant phylogenetic signal in these traits, although the effect is not strong.

CONCLUSIONS

Several genera are non-monophyletic emphasizing the importance of using phylogeny for interpretation of character distribution. Alkaloid diversity and in vitro inhibition of acetylcholinesterase (AChE) and binding to the serotonin reuptake transporter (SERT) are significantly correlated with phylogeny. This has implications for the use of phylogenies to interpret chemical evolution and biosynthetic pathways, to select candidate taxa for lead discovery, and to make recommendations for policies regarding traditional use and conservation priorities.

Phylogenetic approaches to natural product structure prediction

Phylogenetics is the study of the evolutionary relatedness among groups of organisms. Molecular phylogenetics uses sequence data to infer these relationships for both organisms and the genes they maintain. With the large amount of publicly available sequence data, phylogenetic inference has become increasingly important in all fields of biology. In the case of natural product research, phylogenetic relationships are proving to be highly informative in terms of delineating the architecture and function of the genes involved in secondary metabolite biosynthesis. Polyketide synthases and nonribosomal peptide synthetases provide model examples in which individual domain phylogenies display different predictive capacities, resolving features ranging from substrate specificity to structural motifs associated with the final metabolic product. This chapter provides examples in which phylogeny has proven effective in terms of predicting functional or structural aspects of secondary metabolism. The basics of how to build a reliable phylogenetic tree are explained along with information about programs and tools that can be used for this purpose. Furthermore, it introduces the Natural Product Domain Seeker, a recently developed Web tool that employs phylogenetic logic to classify ketosynthase and condensation domains based on established enzyme architecture and biochemical function.

Forensically informative nucleotide sequencing (FINS) for the authentication of Chinese medicinal materials

Chinese medicinal materials may be authenticated by molecular identification. As a definitive approach to molecular identification of medicinal materials, forensically informative nucleotide sequencing (FINS) comprises four steps, namely (1) DNA extraction from biological samples, (2) selection and amplification of a specific DNA fragment, (3) determination of the sequence of the amplified DNA fragment and (4) cladistic analysis of the sample DNA sequence against a DNA database. Success of the FINS identification depends on the selection of DNA region and reference species. This article describes the techniques and applications of FINS for authenticating Chinese medicinal materials.