Targeted Dereplication of Microbial Natural Products by High-Resolution MS and Predicted LC Retention Time

Natural Products Dereplication: Databases and Analytical Methods

The development of efficient methods for dereplication has been critical in the re-emergence of the research in natural products as a source of drug leads. Current dereplication workflows rapidly identify already known bioactive secondary metabolites in the early stages of any drug discovery screening campaign based on natural extracts or enriched fractions. Two main factors have driven the evolution of natural products dereplication over the last decades. First, the availability of both commercial and public large databases of natural products containing the key annotations against which the biological and chemical data derived from the studied sample are searched for. Second, the considerable improvement achieved in analytical technologies (including instrumentation and software tools) employed to obtain robust and precise chemical information (particularly spectroscopic signatures) on the compounds present in the bioactive natural product samples. This chapter describes the main methods of dereplication, which rely on the combined use of large natural product databases and spectral libraries, alongside the information obtained from chromatographic, UV-Vis, MS, and NMR spectroscopic analyses of the samples of interest.

Rapid Discovery of Substances with Anticancer Potential from Marine Fungi Based on a One Strain-Many Compounds Strategy and UPLC-QTOF-MS

The secondary metabolites of marine fungi with rich chemical diversity and biological activity are an important and exciting target for natural product research. This study aimed to investigate the fungal community in Quanzhou Bay, Fujian, and identified 28 strains of marine fungi. A total of 28 strains of marine fungi were screened for small-scale fermentation by the OSMAC (One Strain-Many Compounds) strategy, and 77 EtOAc crude extracts were obtained and assayed for cancer cell inhibition rate. A total of six strains of marine fungi (P-WZ-2, P-WZ-3-2, P-WZ-4, P-WZ-5, P56, and P341) with significant changes in cancer cell inhibition induced by the OSMAC strategy were analysed by UPLC-QTOF-MS. The ACD/MS Structure ID Suite software was used to predict the possible structures with inhibitory effects on cancer cells. A total of 23 compounds were identified, of which 10 compounds have been reported to have potential anticancer activity or cytotoxicity. In this study, the OSMAC strategy was combined with an untargeted metabolomics approach based on UPLC-QTOF-MS to efficiently analyse the effect of changes in culture conditions on anticancer potentials and to rapidly find active substances that inhibit cancer cell growth.

Advancements in capturing and mining mass spectrometry data are transforming natural products research

Covering: 2016 up to 2021Mass spectrometry (MS) is an essential technology in natural products research with MS fragmentation (MS/MS) approaches becoming a key tool. Recent advancements in MS yield dense metabolomics datasets which have been, conventionally, used by individual labs for individual projects; however, a shift is brewing. The movement towards open MS data (and other structural characterization data) and accessible data mining tools is emerging in natural products research. Over the past 5 years, this movement has rapidly expanded and evolved with no slowdown in sight; the capabilities of today vastly exceed those of 5 years ago. Herein, we address the analysis of individual datasets, a situation we are calling the '2021 status quo', and the emergent framework to systematically capture sample information (metadata) and perform repository-scale analyses. We evaluate public data deposition, discuss the challenges of working in the repository scale, highlight the challenges of metadata capture and provide illustrative examples of the power of utilizing repository data and the tools that enable it. We conclude that the advancements in MS data collection must be met with advancements in how we utilize data; therefore, we argue that open data and data mining is the next evolution in obtaining the maximum potential in natural products research.

Antimicrobial activity of ginger on cariogenic bacteria: molecular networking and molecular docking analyses

Streptococcus mutans and Streptococcus sobrinus have been implicated as the primary causative agents of dental caries in humans. This study aimed to screen the antibacterial activity of the n-hexane, ethyl acetate, methanol, and aqueous extracts of Ginger against mentioned bacteria and investigate chemical constituents of the extracts, and their activity against some drug targets in S. mutans. Antimicrobial tests including biofilm inhibition, time-kill kinetics, and adherence inhibition alongside cytotoxicity of extracts, were assessed. A molecular networking technique was used to find chemical constituents of the extracts. Molecular docking analysis on the Schrodinger package was applied to identify the binding interactions of the compounds to targeted enzymes. Methanol and ethyl acetate extracts showed the highest antibacterial activity against S. mutans and S. sobrinus. Different compounds including polyphenols, alkaloids, anthraquinones, flavonoids, terpenoids, glycosides, steroids, and reducing sugars dereplicated from Ginger extracts. The binding affinity of ligands with free hydroxyl groups was better than other ligands against all tested enzymes. This study introduces a wide range of Z. officinal extracts compounds to be used in different drug discovery studies. Some Ginger compounds with high affinity to investigated enzymes can be considered as candidate compounds for anti-caries drug development studies.Communicated by Ramaswamy H. Sarma.

Natural potential neuroinflammatory inhibitors from Stephania epigaea H.S. Lo

Stephania epigaea H. S. Lo is a folk medicine widely distributed in the south of China, especially in Yunnan and Guangxi province. An in vitro anti-neuroinflammatory study showed that total alkaloids of it can potently inhibit LPS-induced NO releasing of BV2 cells with an IC₅₀ value of 10.05 ± 2.03 μg/mL (minocycline as the positive drug, IC₅₀ 15.49 ± 2.14 μM). The phytochemical investigation of the total alkaloids afforded three new phenanthrene (1-3), two lactams (4a, 4b), and nine aporphine derivatives (5-13). The final structure of 1 was identified by computer-assisted structure elucidation (ACD/Structure Elucidator software and the ¹³C NMR calculation with GIAO method) due to many possibilities of the substituent pattern. All isolates were evaluated for their anti-neuroinflammatory effects, and as a result, 5, 8, 10, and 11 exhibited stronger inhibitory activities than the minocycline. The results suggested S. epigaea could provide potential therapeutic agents for neurodegenerative diseases.

Molecular networking based dereplication of AChE inhibitory compounds from the medicinal plant Vincetoxicum funebre (Boiss. & Kotschy)

Alzheimer's disease (AD) is a devastating neurodegenerative disease affecting 47 million people worldwide. While acetylcholinesterase (AChE) inhibitors such as donepezil and galantamine are leading drugs in the symptomatic treatment of AD, new AChE inhibitors continue to be explored for improved potency and selectivity. Herein, a molecular networking approach using high resolution (HR-MS) and tandem mass spectrometry (MS²) has been used for rapid chemical profiling of an extract of the medicinal plant Vincetoxicum funebre Boiss. & Kotschy (Apocynaceae family) that was active against AChE. A total of 44 compounds were identified by combining the MN with traditional natural product methods, including the isolation and identification of five known compounds (13, 41-44) and a novel C₁₃-norisoprenoid (40). In addition, the potential inhibitory activity of all 44 compounds was evaluated against the AChE enzyme via molecular docking to provide further support to the proposed structures. The glycosylated flavonoid querciturone (31) exhibited the highest affinity with a docking score value of -13.43 kJ/mol. Another five compounds showed stronger docking scores against AChE than the clinically used donepezil including the most active isolated compound daucosterol (44), with a binding affinity of -10.11 kJ/mol towards AChE. These findings broaden our understanding of Vincetoxicum metabolites and highlight the potential of glycosylated flavonoids as AChE inhibitors.Communicated by Ramaswamy H. Sarma.

Dark, rare and inspirational microbial matter in the extremobiosphere: 16 000 m of bioprospecting campaigns

The rationale of our bioprospecting campaigns is that the extremobiosphere, particularly the deep sea and hyper-arid deserts, harbours undiscovered biodiversity that is likely to express novel chemistry and biocatalysts thereby providing opportunities for therapeutic drug and industrial process development. We have focused on actinobacteria because of their frequent role as keystone species in soil ecosystems and their unrivalled track record as a source of bioactive compounds. Population numbers and diversity of actinobacteria in the extremobiosphere are traditionally considered to be low, although they often comprise the dominant bacterial biota. Recent metagenomic evaluation of 'the uncultured microbial majority' has now revealed enormous taxonomic diversity among 'dark' and 'rare' actinobacteria in samples as diverse as sediments from the depths of the Mariana Trench and soils from the heights of the Central Andes. The application of innovative culture and screening options that emphasize rigorous dereplication at each stage of the analysis, and strain prioritization to identify 'gifted' organisms, have been deployed to detect and characterize bioactive hit compounds and sought-after catalysts from this hitherto untapped resource. The rewards include first-in-a-class chemical entities with novel modes of action, as well as a growing microbial seed bank that represents a potentially enormous source of biotechnological and therapeutic innovation.

Exploitation of Potentially New Antibiotics from Mangrove Actinobacteria in Maowei Sea by Combination of Multiple Discovery Strategies

Rediscovery of known antibiotics from actinobacteria, especially Streptomyces, has become a bottleneck issue. Nowadays, more specific identification and dereplication could be acquired by a combination of modern analytic techniques with various databases. In this study, 261 actinobacterial strains were isolated from 8 mangrove soil samples by culture-dependent method. A total of 83 strains were selected to evaluate antibacterial activities and mechanisms by disc diffusion method and a unique double fluorescent protein reporter system (pDualrep2), respectively. Thirty-two strains exhibited antagonistic activity against at least one of the "ESKAPE" pathogens. Four Streptomyces strains (B475, B486, B353, and B98) showed strong inhibitory activity against Gram-positive bacteria and induced DNA damage SOS response. One Micromonospora strain (B704) exhibited inhibitory activity against several pathogens and induced attenuation-based translational inhibitors reporter. Seven members of quinoxaline-type antibiotics including quinomycin A, quinomycin monosulfoxide, and other five putative new analogues were found from the culture broth of strain B475 by a combination of anti-MRSA guide, HPTLC, HPLC-UV, and UPLC-UV-HRESIMS/MS analysis, Chemspider searching, and MS/MS-based molecular networking analysis. In conclusion, this study not only demonstrated that mangrove is a rich source of actinobacteria with the potentially new antibiotics but showed rapid dereplication of known antibiotics in the early stage can improve efficiency for the discovery of new antibiotics.

Accramycin A, a New Aromatic Polyketide, from the Soil Bacterium, Streptomyces sp. MA37

Drug-like molecules are known to contain many different building blocks with great potential as pharmacophores for drug discovery. The continued search for unique scaffolds in our laboratory led to the isolation of a novel Ghanaian soil bacterium, Streptomyces sp. MA37. This strain produces many bioactive molecules, most of which belong to carbazoles, pyrrolizidines, and fluorinated metabolites. Further probing of the metabolites of MA37 has led to the discovery of a new naphthacene-type aromatic natural product, which we have named accramycin A 1. This molecule was isolated using an HPLC-photodiode array (PDA) guided isolation process and MS/MS molecular networking. The structure of 1 was characterized by detailed analysis of LC-MS, UV, 1D, and 2D NMR data. Preliminary studies on the antibacterial properties of 1 using Group B Streptococcus (GBS) produced a minimum inhibitory concentration (MIC) of 27 µg/mL. This represents the first report of such bioactivity amongst the naphthacene-type aromatic polyketides, and also suggests the possibility for the further development of potent molecules against GBS based on the accramycin scaffold. A putative acc biosynthetic pathway for accramycin, featuring a tridecaketide-specific type II polyketide synthase, was proposed.

LC-HRMS-Database Screening Metrics for Rapid Prioritization of Samples to Accelerate the Discovery of Structurally New Natural Products

In order to accelerate the isolation and characterization of structurally new or novel secondary metabolites, it is crucial to develop efficient strategies that prioritize samples with greatest promise early in the workflow so that resources can be utilized in a more efficient and cost-effective manner. We have developed a metrics-based prioritization approach using exact LC-HRMS, which uses data for 24 618 marine natural products held in the PharmaSea database. Each sample was evaluated and allocated a metric score by a software algorithm based on the ratio of new masses over the total (sample novelty), ratio of known masses over the total (chemical novelty), number of peaks above a defined peak area threshold (sample complexity), and peak area (sample diversity). Samples were then ranked and prioritized based on these metric scores. To validate the approach, eight marine sponges and six tunicate samples collected from the Fiji Islands were analyzed, metric scores calculated, and samples targeted for isolation and characterization of new compounds. Structures of new compounds were elucidated by spectroscopic techniques, including 1D and 2D NMR, MS, and MS/MS. Structures were confirmed by computer-assisted structure elucidation methods (CASE) using the ACD/Structure Elucidator Suite.

Electrochemical filtration process for simultaneous removal of refractory organic and particulate contaminants from wastewater effluents

Versatile electrochemical reactions are effective for removing a wide range of water contaminants. This study focuses on the development and testing of bifunctional electrocatalytic filter anodes as reactive and separating media for the simultaneous removal of refractory dissolved organic and particulate contaminants from real wastewater effluents. The results show that the TiO₂ particle interlayers formed between the Ti fiber support and the top composite metal oxide catalyst layers assist in reducing filter pores to an effective size range that enables removal of most particulates within the wastewater. The double-sheet design, which is a sandwich-structured module with an internal void space for permeate, prevents filter fouling, and transmembrane pressure can be maintained at a very low level of <5 kPa during batch and continuous flow reactor operations. Substantive and simultaneous removal of dissolved organics (e.g., chromophores, fluorophores, 1,4-dioxane, chemical oxygen demand, and total organic carbon) and particulate matter (i.e., turbidity) are achieved, although removal rates and efficacies differ depending on the electric current density applied. Decolorization and particulate rejection occur swiftly and immediately, but 1,4-dioxane degradation is relatively slow and quite time-dependent. Possible 1,4-dioxane degradation pathways during electrocatalysis are also proposed. Electrochemical filtration technology shows considerable promise for use in the next generation of advanced wastewater treatment solutions.

13C-NMR dereplication of Garcinia extracts: Predicted chemical shifts as reliable databases

Usually isolated from Garcinia (Clusiaceae) or Hypericum (Hypericaceae) species, some Polycyclic Polyprenylated AcylPhloroglucinols (PPAPs) have been recently reported as potential research tools for immunotherapy. Aiming at exploring the chemodiversity of PPAPs amongst Garcinia genus, a dereplication process suitable for such natural compounds has been developed. Although less sensitive than mass spectrometry, NMR spectroscopy is perfectly reproducible and allows stereoisomers distinction, justifying the development of ¹³C-NMR strategies. Dereplication requires the use of databases (DBs). To define if predicted DBs were accurate enough as dereplication tools, experimental and predicted δ_C of natural products usually isolated from Clusiaceae were compared. The ACD/Labs commercial software allowed to predict 73% of δ_C in a 1.25 ppm range around the experimental values. Consequently, with these parameters, the major PPAPs from a Garcinia bancana extract were successfully identified using a predicted DB.

Current Challenges in Plant Eco-Metabolomics

The relatively new research discipline of Eco-Metabolomics is the application of metabolomics techniques to ecology with the aim to characterise biochemical interactions of organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical approach to measure many thousands of metabolites in different species, including plants and animals. Changes in metabolite concentrations can provide mechanistic evidence for biochemical processes that are relevant at ecological scales. These include physiological, phenotypic and morphological responses of plants and communities to environmental changes and also interactions with other organisms. Traditionally, research in biochemistry and ecology comes from two different directions and is performed at distinct spatiotemporal scales. Biochemical studies most often focus on intrinsic processes in individuals at physiological and cellular scales. Generally, they take a bottom-up approach scaling up cellular processes from spatiotemporally fine to coarser scales. Ecological studies usually focus on extrinsic processes acting upon organisms at population and community scales and typically study top-down and bottom-up processes in combination. Eco-Metabolomics is a transdisciplinary research discipline that links biochemistry and ecology and connects the distinct spatiotemporal scales. In this review, we focus on approaches to study chemical and biochemical interactions of plants at various ecological levels, mainly plant⁻organismal interactions, and discuss related examples from other domains. We present recent developments and highlight advancements in Eco-Metabolomics over the last decade from various angles. We further address the five key challenges: (1) complex experimental designs and large variation of metabolite profiles; (2) feature extraction; (3) metabolite identification; (4) statistical analyses; and (5) bioinformatics software tools and workflows. The presented solutions to these challenges will advance connecting the distinct spatiotemporal scales and bridging biochemistry and ecology.

Searching for Glycosylated Natural Products in Actinomycetes and Identification of Novel Macrolactams and Angucyclines

Many bioactive natural products are glycosylated compounds in which the sugar components usually participate in interaction and molecular recognition of the cellular target. Therefore, the presence of sugar moieties is important, in some cases essential, for bioactivity. Searching for novel glycosylated bioactive compounds is an important aim in the field of the research for natural products from actinomycetes. A great majority of these sugar moieties belong to the 6-deoxyhexoses and share two common biosynthetic steps catalyzed by a NDP-D-glucose synthase (GS) and a NDP-D-glucose 4,6-dehydratase (DH). Based on this fact, seventy one Streptomyces strains isolated from the integument of ants of the Tribe Attini were screened for the presence of biosynthetic gene clusters (BGCs) for glycosylated compounds. Total DNAs were analyzed by PCR amplification using oligo primers for GSs and DHs and also for a NDP-D-glucose-2,3-dehydratases. Amplicons were used in gene disruption experiments to generate non-producing mutants in the corresponding clusters. Eleven mutants were obtained and comparative dereplication analyses between the wild type strains and the corresponding mutants allowed in some cases the identification of the compound coded by the corresponding cluster (lobophorins, vicenistatin, chromomycins and benzanthrins) and that of two novel macrolactams (sipanmycin A and B). Several strains did not show UPLC differential peaks between the wild type strain and mutant profiles. However, after genome sequencing of these strains, the activation of the expression of two clusters was achieved by using nutritional and genetic approaches leading to the identification of compounds of the cervimycins family and two novel members of the warkmycins family. Our work defines a useful strategy for the identification new glycosylated compounds by a combination of genome mining, gene inactivation experiments and the activation of silent biosynthetic clusters in Streptomyces strains.

Automated Comparative Metabolite Profiling of Large LC-ESIMS Data Sets in an ACD/MS Workbook Suite Add-in, and Data Clustering on a New Open-Source Web Platform FreeClust

The technological development of LC-MS instrumentation has led to significant improvements of performance and sensitivity, enabling high-throughput analysis of complex samples, such as plant extracts. Most software suites allow preprocessing of LC-MS chromatograms to obtain comprehensive information on single constituents. However, more advanced processing needs, such as the systematic and unbiased comparative metabolite profiling of large numbers of complex LC-MS chromatograms remains a challenge. Currently, users have to rely on different tools to perform such data analyses. We developed a two-step protocol comprising a comparative metabolite profiling tool integrated in ACD/MS Workbook Suite, and a web platform developed in R language designed for clustering and visualization of chromatographic data. Initially, all relevant chromatographic and spectroscopic data (retention time, molecular ions with the respective ion abundance, and sample names) are automatically extracted and assembled in an Excel spreadsheet. The file is then loaded into an online web application that includes various statistical algorithms and provides the user with tools to compare and visualize the results in intuitive 2D heatmaps. We applied this workflow to LC-ESIMS profiles obtained from 69 honey samples. Within few hours of calculation with a standard PC, honey samples were preprocessed and organized in clusters based on their metabolite profile similarities, thereby highlighting the common metabolite patterns and distributions among samples. Implementation in the ACD/Laboratories software package enables ulterior integration of other analytical data, and in silico prediction tools for modern drug discovery.