Planomonospora: A Metabolomics Perspective on an Underexplored Actinobacteria Genus

Accessing the specialized metabolome of actinobacteria from the bulk soil of Paullinia cupana Mart. on the Brazilian Amazon: a promising source of bioactive compounds against soybean phytopathogens

The Amazon rainforest, an incredibly biodiverse ecosystem, has been increasingly vulnerable to deforestation. Despite its undeniable importance and potential, the Amazonian microbiome has historically received limited study, particularly in relation to its unique arsenal of specialized metabolites. Therefore, in this study our aim was to assess the metabolic diversity and the antifungal activity of actinobacterial strains isolated from the bulk soil of Paullinia cupana, a native crop, in the Brazilian Amazon Rainforest. Extracts from 24 strains were subjected to UPLC-MS/MS analysis using an integrative approach that relied on the Chemical Structural and Compositional Similarity (CSCS) metric, GNPS molecular networking, and in silico dereplication tools. This procedure allowed the comprehensive understanding of the chemical space encompassed by these actinobacteria, which consists of features belonging to known bioactive metabolite classes and several unannotated molecular families. Among the evaluated strains, five isolates exhibited bioactivity against a panel of soybean fungal phytopathogens (Rhizoctonia solani, Macrophomina phaseolina, and Sclerotinia sclerotiorum). A focused inspection led to the annotation of pepstatins, oligomycins, hydroxamate siderophores and dorrigocins as metabolites produced by these bioactive strains, with potentially unknown compounds also comprising their metabolomes. This study introduces a pragmatic protocol grounded in established and readily available tools for the annotation of metabolites and the prioritization of strains to optimize further isolation of specialized metabolites. Conclusively, we demonstrate the relevance of the Amazonian actinobacteria as sources for bioactive metabolites useful for agriculture. We also emphasize the importance of preserving this biome and conducting more in-depth studies on its microbiota.

A Novel Two-Component Bacteriocin, Acidicin P, and Its Key Residues for Inhibiting Listeria monocytogenes by Targeting the Cell Membrane

Listeria monocytogenes is an important pathogen which easily contaminates food and causes fatal systemic infections in human. Bacteriocins have received much attention regarding their natural methods of controlling health-related pathogens. Here, we investigated and characterized a novel two-component bacteriocin named acidicin P from Pediococcus acidilactici LAC5-17. Acidicin P showed obvious antimicrobial activity to L. monocytogenes. Through a sequence similarity network analysis for two-component bacteriocin precursors mined in the RefSeq database, acidicin P was observed to belong to an unusual group of two-component bacteriocins. Acidicin P contains two peptides designated Adpα and Adpβ which are assessed to interact with each other and form a helical dimer structure which can be inserted into the lipid bilayer of target cell membrane. We demonstrate that A5, N7, and G9 in the A5xxxG9 motif of Adpα and S16, R19, and G20 in the S16xxxG20 motif of Adpβ played crucial roles in stabilizing the helix-helix interaction of Adpα and Adpβ and were essential for the antilisterial activity of acidicin P by site-directed mutagenesis. A positive residue, R14, in Adpα and a negative residue, D12, in Adpβ are also important for acidicin P to fight against L. monocytogenes. These key residues are supposed to form hydrogen bonding, which is crucial for the interaction of Adpα and Adpβ. Furthermore, acidicin P induces severe permeabilization and depolarization of the cytoplasmic membrane and causes dramatic changes in L. monocytogenes cell morphology and ultrastructure. Acidicin P has the potential to be applied to inhibit L. monocytogenes efficiently both in the food industry and medical treatments. IMPORTANCE L. monocytogenes can cause widespread food contamination and severe human listeriosis, which amount to a large proportion of the public health and economic burdens. Today, L. monocytogenes is usually treated with chemical compounds in the food industry or antibiotics for human listeriosis. Natural and safe antilisterial agents are urgently required. Bacteriocins are natural antimicrobial peptides that have comparable narrow antimicrobial spectra and are attractive potentials for precision therapy for pathogen infection. In this work, we discover a novel two-component bacteriocin designated acidicin P, which shows obvious antilisterial activity. We also identify the key residues in both peptides of acidicin P and demonstrate that acidicin P is inserted into the target cell membrane and disrupts the cell envelop to inhibit the growth of L. monocytogenes. We believe that acidicin P is a promising lead for further development as an antilisterial drug.

Metabolome-guided genome mining of RiPP natural products

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a chemically diverse class of metabolites. Many RiPPs show potent biological activities that make them attractive starting points for drug development. A promising approach for the discovery of new classes of RiPPs is genome mining. However, the accuracy of genome mining is hampered by the lack of signature genes shared across different RiPP classes. One way to reduce false-positive predictions is by complementing genomic information with metabolomics data. In recent years, several new approaches addressing such integrative genomics and metabolomics analyses have been developed. In this review, we provide a detailed discussion of RiPP-compatible software tools that integrate paired genomics and metabolomics data. We highlight current challenges in data integration and identify opportunities for further developments targeting new classes of bioactive RiPPs.

Species-specific secondary metabolism by actinomycetes of the genus Phytohabitans and discovery of new pyranonaphthoquinones and isatin derivatives

To further exploit secondary metabolic potential of a minor actinomycete genus Phytohabitans within the family Micromonosporaceae, metabolite profiling by HPLC-UV analysis, combined with 16S rDNA sequence-based phylotyping were attempted on seven Phytohabitans strains available at the public culture collection. The strains were grouped into three clades and each exhibited unique and distinct metabolite profiles, which were highly conserved among strains within the same clade. These results were consistent with previous observations on two other actinomycetes genera, reconfirming species-specificity of secondary metabolite production, which were conventionally thought to be strain-specific. A strain RD003215, belonging to the P. suffuscus clade, produced multiple metabolites, some of which were presumed to be naphthoquinones. Liquid fermentation followed by chromatographic separation of the broth extract led to the discovery of three new pyranonaphthoquinones, designated habipyranoquinones A-C (1-3), and one new isatin derivative, (R)-N-methyl-3-hydroxy-5,6-dimethoxyoxindole (4), along with three known synthetic compounds, 6,8-dihydroxydehydro-α-lapachone (5), N-methyl-5,6-dimethoxyisatin (6), and 5,6-dimethoxyisatin (7). Structures of 1-4 were unequivocally elucidated by NMR, MS, and CD spectral analysis, with assistance of density functional theory-based NMR chemical shift prediction and ECD spectral calculation. Compound 2 displayed antibacterial activity against Kocuria rhizophila and Staphylococcus aureus with MIC 50 µg/mL and cytotoxicity against P388 murine leukemia cells with an IC₅₀ value of 34 µM. Compounds 1 and 4 also showed cytotoxicity against P388 cells with IC₅₀ values of 29 and 14 µM, respectively.

Microbial Metabolites Annotation by Mass Spectrometry-Based Metabolomics

Since the discovery of penicillin, microbial metabolites have been extensively investigated for drug discovery purposes. In the last decades, microbial derived compounds have gained increasing attention in different fields from pharmacognosy to industry and agriculture. Microbial metabolites in microbiomes present specific functions and can be associated with the maintenance of the natural ecosystems. These metabolites may exhibit a broad range of biological activities of great interest to human purposes. Samples from either microbial isolated cultures or microbiomes consist of complex mixtures of metabolites and their analysis are not a simple process. Mass spectrometry-based metabolomics encompass a set of analytical methods that have brought several improvements to the microbial natural products field. This analytical tool allows the comprehensively detection of metabolites, and therefore, the access of the chemical profile from those biological samples. These analyses generate thousands of mass spectra which is challenging to analyse. In this context, bioinformatic metabolomics tools have been successfully employed to accelerate and facilitate the investigation of specialized microbial metabolites. Herein, we describe metabolomics tools used to provide chemical information for the metabolites, and furthermore, we discuss how they can improve investigation of microbial cultures and interactions.

LC-MS Based Phytochemical Profiling towards the Identification of Antioxidant Markers in Some Endemic Aloe Species from Mascarene Islands

Aloe plant species have been used for centuries in traditional medicine and are reported to be an important source of natural products. However, despite the large number of species within the Aloe genus, only a few have been investigated chemotaxonomically. A Molecular Network approach was used to highlight the different chemical classes characterizing the leaves of five Aloe species: Aloe macra, Aloe vera, Aloe tormentorii, Aloe ferox, and Aloe purpurea. Aloe macra, A. tormentorii, and A. purpurea are endemic from the Mascarene Islands comprising Reunion, Mauritius, and Rodrigues. UHPLC-MS/MS analysis followed by a dereplication process allowed the characterization of 93 metabolites. The newly developed MolNotator algorithm was usedfor molecular networking and allowed a better exploration of the Aloe metabolome chemodiversity. The five species appeared rich in polyphenols (anthracene derivatives, flavonoids, phenolic acids). Therefore, the total phenolic content and antioxidant activity of the five species were evaluated, and a DPPH-On-Line-HPLC assay was used to determine the metabolites responsible for the radical scavenging activity. The use of computational tools allowed a better description of the comparative phytochemical profiling of five Aloe species, which showed differences in their metabolite composition, both qualitative and quantitative. Moreover, the molecular network approach combined with the On-Line-HPLC assay allowed the identification of 9 metabolites responsible for the antioxidant activity. Two of them, aloeresin A and coumaroylaloesin, could be the principal metabolites responsible for the activity. From 374 metabolites calculated by MolNator, 93 could be characterized. Therefore, the Aloe species can be a rich source of new chemical structures that need to be discovered.

Relationship between bacterial phylotype and specialized metabolite production in the culturable microbiome of two freshwater sponges

Microbial drug discovery programs rely heavily on accessing bacterial diversity from the environment to acquire new specialized metabolite (SM) lead compounds for the therapeutic pipeline. Therefore, knowledge of how commonly culturable bacterial taxa are distributed in nature, in addition to the degree of variation of SM production within those taxa, is critical to informing these front-end discovery efforts and making the overall sample collection and bacterial library creation process more efficient. In the current study, we employed MALDI-TOF mass spectrometry and the bioinformatics pipeline IDBac to analyze diversity within phylotype groupings and SM profiles of hundreds of bacterial isolates from two Eunapius fragilis freshwater sponges, collected 1.5 km apart. We demonstrated that within two sponge samples of the same species, the culturable bacterial populations contained significant overlap in approximate genus-level phylotypes but mostly nonoverlapping populations of isolates when grouped lower than the level of genus. Further, correlations between bacterial phylotype and SM production varied at the species level and below, suggesting SM distribution within bacterial taxa must be analyzed on a case-by-case basis. Our results suggest that two E. fragilis freshwater sponges collected in similar environments can exhibit large culturable diversity on a species-level scale, thus researchers should scrutinize the isolates with analyses that take both phylogeny and SM production into account to optimize the chemical space entering into a downstream bacterial library.

Allopeptimicins: unique antibacterial metabolites generated by hybrid PKS-NRPS, with original self-defense mechanism in Actinoallomurus

In the search for structurally novel metabolites with antibacterial activity, innovative approaches must be implemented to increase the probability of discovering novel chemistry from microbial sources. Here we report on the application of metabolomic tools to the genus Actinoallomurus, a poorly explored member of the Actinobacteria. From examining extracts derived from 88 isolates belonging to this genus, we identified a family of cyclodepsipeptides acylated with a C₂₀ polyketide chain, which we named allopeptimicins. These molecules possess unusual structural features, including several double bonds in the amino-polyketide chain and four non-proteinogenic amino acids in the octapeptide. Remarkably, allopeptimicins are produced as a complex of active and inactive congeners, the latter carrying a sulfate group on the polyketide amine. This modification is also a mechanism of self-protection in the producer strain. The structural uniqueness of allopeptimicins is reflected in a biosynthetic gene cluster showing a mosaic structure, with dedicated gene cassettes devoted to formation of specialized precursors and modular assembly lines related to those from different pathways.

Untargeted metabolomic analysis of Actinoallomurus spp. unveiled an unprecedented acylated cyclodepsipeptide with unusual features and potent antibacterial activity.

Integrated molecular networking strategy enhance the accuracy and visualization of components identification: A case study of Ginkgo biloba leaf extract

Molecular networking (MN) is an efficient tool for natural product research. However, single MN might lead to false annotation due to the limited information, and the importance of combining MN with chromatogram is always ignored. In this study, we proposed a comprehensive MN strategy combining feature-based molecular networking (FBMN) and dual ionization mode MS/MS to improve the annotation accuracy and to achieve structural feature visualization in a chemotaxonomic chromatogram. Three steps were taken: (1) employing FBMN and dual ionization mode MS/MS to distinguish isomers and improve components' identification accuracy. (2) Using a 3-level initiative supported by in-house database to evaluate the annotation confidence. As a result, 95 compounds were successfully identified from Ginkgo biloba leaf extract (GBE) and Ginkgo biloba leaf (GBL), and 70 compounds mainly consisting of flavonoid glycosides, ginkgolides, and lignan glycosides were assigned as high-confidence molecules. (3) Building color-dependent chemotaxonomic chromatograms, to achieve component visualization by connecting FBMN with chromatogram in which the peaks of the same color indicated the compounds with similar structural features. Our research provided a new and efficient strategy for component identification and visualization of herbal medicine.

Metabolomics and genomics in natural products research: complementary tools for targeting new chemical entities

Covering: 2010 to 2021Organisms in nature have evolved into proficient synthetic chemists, utilizing specialized enzymatic machinery to biosynthesize an inspiring diversity of secondary metabolites. Often serving to boost competitive advantage for their producers, these secondary metabolites have widespread human impacts as antibiotics, anti-inflammatories, and antifungal drugs. The natural products discovery field has begun a shift away from traditional activity-guided approaches and is beginning to take advantage of increasingly available metabolomics and genomics datasets to explore undiscovered chemical space. Major strides have been made and now enable -omics-informed prioritization of chemical structures for discovery, including the prospect of confidently linking metabolites to their biosynthetic pathways. Over the last decade, more integrated strategies now provide researchers with pipelines for simultaneous identification of expressed secondary metabolites and their biosynthetic machinery. However, continuous collaboration by the natural products community will be required to optimize strategies for effective evaluation of natural product biosynthetic gene clusters to accelerate discovery efforts. Here, we provide an evaluative guide to scientific literature as it relates to studying natural product biosynthesis using genomics, metabolomics, and their integrated datasets. Particular emphasis is placed on the unique insights that can be gained from large-scale integrated strategies, and we provide source organism-specific considerations to evaluate the gaps in our current knowledge.

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.

Integrating perspectives in actinomycete research: an ActinoBase review of 2020-21

Last year ActinoBase, a Wiki-style initiative supported by the UK Microbiology Society, published a review highlighting the research of particular interest to the actinomycete community. Here, we present the second ActinoBase review showcasing selected reports published in 2020 and early 2021, integrating perspectives in the actinomycete field. Actinomycetes are well-known for their unsurpassed ability to produce specialised metabolites, of which many are used as therapeutic agents with antibacterial, antifungal, or immunosuppressive activities. Much research is carried out to understand the purpose of these metabolites in the environment, either within communities or in host interactions. Moreover, many efforts have been placed in developing computational tools to handle big data, simplify experimental design, and find new biosynthetic gene cluster prioritisation strategies. Alongside, synthetic biology has provided advances in tools to elucidate the biosynthesis of these metabolites. Additionally, there are still mysteries to be uncovered in understanding the fundamentals of filamentous actinomycetes' developmental cycle and regulation of their metabolism. This review focuses on research using integrative methodologies and approaches to understand the bigger picture of actinomycete biology, covering four research areas: i) technology and methodology; ii) specialised metabolites; iii) development and regulation; and iv) ecology and host interactions.

Feature-Based Molecular Networking for the Targeted Identification of Gq-Inhibiting FR900359 Derivatives

Both the soil bacterium Chromobacterium vaccinii and the bacterial endosymbiont Candidatus Burkholderia crenata of the plant Ardisia crenata are producers of FR900359 (FR). This cyclic depsipeptide is a potent and selective G_q protein inhibitor used extensively to investigate the intracellular signaling of G protein coupled receptors (GPCRs). In this study, the metabolomes of both FR producers were investigated and compared using feature-based molecular networking (FBMN). As a result, 30 previously unknown FR derivatives were identified, one-third being unique to C. vaccinii. Guided by MS, a novel FR derivative, FR-6 (compound 1), was isolated, and its structure unambiguously established. In a whole-cell biosensing assay based on detection of dynamic mass redistribution (DMR) as readout for G_q inhibition, FR-6 suppressed G_q signaling with micromolar potency (pIC₅₀ = 5.56). This functional activity was confirmed in radioligand binding assays (pK_i = 7.50). This work demonstrates the power of molecular networking, guiding the way to a novel G_q-inhibiting FR derivative and underlining the potency of FR as a G_q inhibitor.

Effective approaches to discover new microbial metabolites in a large strain library

Natural products have provided many molecules to treat and prevent illnesses in humans, animals and plants. While only a small fraction of the existing microbial diversity has been explored for bioactive metabolites, tens of thousands of molecules have been reported in the literature over the past 80 years. Thus, the main challenge in microbial metabolite screening is to avoid the re-discovery of known metabolites in a cost-effective manner. In this perspective, we report and discuss different approaches used in our laboratory over the past few years, ranging from bioactivity-based screening to looking for metabolic rarity in different datasets to deeply investigating a single Streptomyces strain. Our results show that it is possible to find novel chemistry through a limited screening effort, provided that appropriate selection criteria are in place.

Multi-omics Study of Planobispora rosea, Producer of the Thiopeptide Antibiotic GE2270A

Planobispora rosea is the natural producer of the potent thiopeptide antibiotic GE2270A. Here, we present the results of a metabolomics and transcriptomics analysis of P. rosea during production of GE2270A. The data generated provides useful insights into the biology of this genetically intractable bacterium. We characterize the details of the shutdown of protein biosynthesis and the respiratory chain associated with the end of the exponential growth phase. We also provide the first description of the phosphate regulon in P. rosea. Based on the transcriptomics data, we show that both phosphate and iron are limiting P. rosea growth in our experimental conditions. Additionally, we identified and validated a new biosynthetic gene cluster associated with the production of the siderophores benarthin and dibenarthin in P. rosea. Together, the metabolomics and transcriptomics data are used to inform and refine the very first genome-scale metabolic model for P. rosea, which will be a valuable framework for the interpretation of future studies of the biology of this interesting but poorly characterized species.

IMPORTANCEPlanobispora rosea is a genetically intractable bacterium used for the production of GE2270A on an industrial scale. GE2270A is a potent thiopeptide antibiotic currently used as a precursor for the synthesis of two compounds under clinical studies for the treatment of Clostridium difficile infection and acne. Here, we present the very first systematic multi-omics investigation of this important bacterium, which provides a much-needed detailed picture of the dynamics of metabolism of P. rosea while producing GE2270A.

Author Video: An author video summary of this article is available.

Blocks in the pseudouridimycin pathway unlock hidden metabolites in the Streptomyces producer strain

We report a metabolomic analysis of Streptomyces sp. ID38640, a soil isolate that produces the bacterial RNA polymerase inhibitor pseudouridimycin. The analysis was performed on the wild type, on three newly constructed and seven previously reported mutant strains disabled in different genes required for pseudouridimycin biosynthesis. The results indicate that Streptomyces sp. ID38640 is able to produce, in addition to lydicamycins and deferroxiamines, as previously reported, also the lassopeptide ulleungdin, the non-ribosomal peptide antipain and the osmoprotectant ectoine. The corresponding biosynthetic gene clusters were readily identified in the strain genome. We also detected the known compound pyridindolol, for which we propose a previously unreported biosynthetic gene cluster, as well as three families of unknown metabolites. Remarkably, the levels of most metabolites varied strongly in the different mutant strains, an observation that enabled detection of metabolites unnoticed in the wild type. Systematic investigation of the accumulated metabolites in the ten different pum mutants identified shed further light on pseudouridimycin biosynthesis. We also show that several Streptomyces strains, able to produce pseudouridimycin, have distinct genetic relationship and metabolic profile with ID38640.

Coupling Mass Spectral and Genomic Information to Improve Bacterial Natural Product Discovery Workflows

Bacterial natural products possess potent bioactivities and high structural diversity and are typically encoded in biosynthetic gene clusters. Traditional natural product discovery approaches rely on UV- and bioassay-guided fractionation and are limited in terms of dereplication. Recent advances in mass spectrometry, sequencing and bioinformatics have led to large-scale accumulation of genomic and mass spectral data that is increasingly used for signature-based or correlation-based mass spectrometry genome mining approaches that enable rapid linking of metabolomic and genomic information to accelerate and rationalize natural product discovery. In this mini-review, these approaches are presented, and discovery examples provided. Finally, future opportunities and challenges for paired omics-based natural products discovery workflows are discussed.

Comparative Metabologenomics Analysis of Polar Actinomycetes

Biosynthetic and chemical datasets are the two major pillars for microbial drug discovery in the omics era. Despite the advancement of analysis tools and platforms for multi-strain metabolomics and genomics, linking these information sources remains a considerable bottleneck in strain prioritisation and natural product discovery. In this study, molecular networking of the 100 metabolite extracts derived from applying the OSMAC approach to 25 Polar bacterial strains, showed growth media specificity and potential chemical novelty was suggested. Moreover, the metabolite extracts were screened for antibacterial activity and promising selective bioactivity against drug-persistent pathogens such as Klebsiella pneumoniae and Acinetobacter baumannii was observed. Genome sequencing data were combined with metabolomics experiments in the recently developed computational approach, NPLinker, which was used to link BGC and molecular features to prioritise strains for further investigation based on biosynthetic and chemical information. Herein, we putatively identified the known metabolites ectoine and chrloramphenicol which, through NPLinker, were linked to their associated BGCs. The metabologenomics approach followed in this study can potentially be applied to any large microbial datasets for accelerating the discovery of new (bioactive) specialised metabolites.