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Scientific Reports volume  12, Article number: 18883 (2022 ) Cite this article

Pine wilt disease (PWD) is a destructive vector-borne forest disease caused by the nematode Bursaphelenchus xylophilus. To date, several options are available for the management of pine wilt disease; however constant development and search for natural products with potential nematicidal activity are imperative to diversify management options and to cope with the possible future emergence of resistance in parasitic nematodes. Here, a combined metabolomics and genomics approach was employed to investigate the chemical repertoire and biosynthetic potential of the bacterial endophyte Peribacillus frigoritolerans BE93, previously characterized to exhibit nematicidal activity against B. xylophilus. Feature-based molecular networking revealed the presence of diverse secondary metabolites. A cyclic imine heptapeptide, koranimine, was found to be among the most abundant secondary metabolites produced. Genome mining displayed the presence of several putative biosynthetic gene clusters (BGCs), including a dedicated non-ribosomal peptide synthase (NRPS) BGC for koranimine. Given the non-ribosomal peptide nature of koranimine, in silico molecular docking analysis was conducted to investigate its potential nematicidal activity against the target receptor ivermectin-sensitive invertebrate α glutamate-gated chloride channel (GluCl). Results revealed the binding of koranimine at the allosteric site of the channel—the ivermectin binding site. Moreover, the ligand-receptor interactions observed were mostly shared between koranimine and ivermectin when bound to the α GluCl receptor thus, suggesting a possibly shared mechanism of potential nematicidal activity. This study highlights the efficiency of combined metabolomics and genomics approach in the identification of candidate compounds.

Pine wood nematode (PWN) Bursaphelenchus xylophilus is an invasive endoparasitic nematode which has been long considered a serious threat to trees of the genus Pinus, causing a destructive vector-borne pine wilt disease (PWD)1. The occurrence of the disease was first reported in Japan in the 1900s, but it was not until 1972 that the causative nematode was identified2. The infection cycle of PWD is facilitated by sawyer beetles Monochamus spp. vectors. These vectors emerge from the dead pine trees and migrate to healthy trees to feed on succulent branches bringing along the parasitic nematode. The feeding wounds left by the vectors provide an entry points for the nematode to commence the infection process3. The nematodes then migrate to the resin canals where they feed and reproduce. As a result, the functionality of the vascular system is compromised which will eventually lead to the wilting of the tree4. The nematode B. xylophilus is native to North America and believed to have been introduced to Japan at the start of the twentieth century through anthropogenic activities5. Since then, the nematode has been devastating pine forests in Japan, spreading to other Asian countries including Korea, China, Taiwan, and even countries in Europe like Portugal and Spain6,7,8 and thus, has become an economically important pest across the globe9.

To date, several options are available for the management of PWD. These measures may either be directed against the vector or directly against the nematode, or a combination of both. These can be achieved through aerial spraying of insecticides, fumigation, and trunk-injection of nematicidal compounds (avermectin, abamectin, emamectin benzoate, mesulfenfos, morantel tartrate, and levamisole chloride)10. Silvicultural control is also employed which involves clear-cutting and manual removal of infected pine trees11. However this physical preventive method requires elimination of pine trees within a radius of 10–50 m surrounding the infected tree which could cause possible loss of uninfected pine trees. Although the use of chemical-based management approaches such as insecticides and nematicidal compounds have been successful in controlling the prevalence of PWD, cautions must be taken into consideration. The use of insecticides has been associated with environmental pollution and may exert adverse impacts on non-target organisms and even on human health12. Frequent use of nematicidal compounds on the other hand, may increase the risk of developing resistance against the compound, a phenomenon observed in other parasitic nematodes13. Hence, constant development and search for natural products with potential nematicidal activity are imperative to diversify management options and to cope with the possible emergence of resistance in parasitic nematodes including B. xylophilus.

Since the discovery of penicillin in the 1940s, microorganisms and their specialized secondary metabolites have been drawing much attention from the scientific community14. Secondary metabolites of microbial origin are of great interest for their structural diversity and varied bioactivities. The ubiquitous nature of microorganisms coupled with their vast arsenal of secondary metabolites has made them powerful sources of compounds with biotechnological potentials15. To this end, a number of secondary metabolites from bacteria have been shown to possess nematicidal/anthelmintic activity against parasitic nematodes16,17,18,19,20. Among the known potent anthelminthic compounds, the macrocyclic lactone avermectins and its analogs (e.g., ivermectin and abamectin) originally produced by Streptomyces avermitilis, are widely used in agriculture, veterinary and medical fields due to their broad anthelmintic spectrum21. Avermectins target the invertebrate glutamate-gated chloride channel (GluCl), a member of the Cys-loop receptor family of ligand-gated ion channels which includes nicotinic acetylcholine and type 3 5-hydroxytryptamine receptors (nAChRs and 5-HT3Rs) and inhibitory γ-aminobutyric acid (GABA) type A and glycine receptors (GABAARs and GlyRs)22. The anthelmintic compound acts as a strong agonist, activating the GluCls present in nerve or muscle cells at nanomolar concentrations causing hyperpolarization that will result to subsequent paralysis23,24,25. Although the microbial secondary metabolites are highly promising agents, it has been believed that only a portion of the organisms’ total metabolites (metabolome) have been tapped so far due to the laborious traditional screening and compound identification approaches26.

Secondary metabolites are typically purified, identified and characterized after an extensive screening of crude extracts with biological activities—a so called bioactivity-based screening approach. Though proven to be efficient, still the approach is plagued by high rediscovery rates of known compounds and limited to the detection of the highly abundant metabolites27. Recently, with the availability of genome sequences, the application of genome mining approach which tries to identify biosynthetic gene clusters (BGCs) and predict corresponding compound has been widely pursued as a complementary approach to the classical bioactivity-guided screening28. Rapid annotation or identification of compounds present in the metabolome prior to purification is also a crucial step, and also been considered a stumbling block in the natural product research arena29. In this context, the application of liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) in untargeted metabolomics studies has allowed the global analysis of secondary metabolites due to the high sensitivity and flexibility of the technique. Besides, the technique also provides important structural information of the detected compounds, aiding in the identification process30. In addition, the introduction of molecular networking, an approach that enables the analysis and organization of tandem mass (MS/MS) spectrometry data based on structural similarity has also provided great assistance and improved efficiency in natural product discovery31. The Global Natural Products Social Molecular Networking (GNPS), a web-based platform, has enabled the molecular networking algorithm accessible to the scientific community32. This online pipeline has been successfully used to identify known compounds, analogs or derivatives, and even the discovery of novel compounds from different complex biological samples33,34,35,36,37,38.

Studying the interactions of natural products with their probable biological targets can render insights into their potential drug applications. Over the past years, computational molecular docking methods have been frequently employed in structure-based drug designing, owing to its ability to detect appropriate binding sites in the targets and the interactions of the small molecule (ligand) with high accuracy. Molecular docking programs work by calculating probable ligand conformations or poses in the target active site and ranking them based on their individual binding energies39,40,41. A number of studies have demonstrated the efficiency of molecular docking approaches in predicting potential drug candidates as validated by their corresponding in vitro studies42,43,44,45. Hence, this in silico screening can significantly accelerate the identification of potential natural product drug candidates while minimizing experimental labor.

Previous study from our group has identified bacterial endophytes from pine trees showing potent nematicidal activity against B. xylophilus46. One of the bacterial endophytes was identified as Peribacillus frigoritolerans BE9347, formerly identified as Bacillus sp. BE93. Though shown to possess nematicidal activity, the chemical potential of BE93 has not been characterized. In this study, we used a combined metabolomics and genomics approach to investigate the biosynthetic potential and chemical repertoire of BE93. Untargeted LC–MS/MS was used to characterize the metabolome of BE93 grown in different culture media. The MS/MS data were then analyzed using the feature-based molecular networking (FBMN) workflow within the GNPS web platform analysis environment48. The genome sequence of BE93 was analyzed using antiSMASH 5.049 and PRISM50 to identify specialized BGCs. Additionally, in silico analysis of the identified compound of interest was carried out using AutoDock Vina51 within the UCSF Chimera52 working space to investigate its potential nematicidal activity.

To characterize the secondary metabolites produced by BE93, four different media [tryptic soy broth (TSB), R2A, nutrient broth (NB), and Luria-Bertani (LB)] were used for the cultivation of the bacterium. The culture extracts were then subjected to LC-MS/MS analysis and the data were processed for the establishment of molecular network using the GNPS online platform. After background and media subtraction, molecular networks were established with a total of 110 compounds or nodes (Fig. 1a). Majority of these compounds were detected and shared in all four culture media conditions, although distinct compounds were also found to be media specific, and with TSB having the most number of detected compounds (Fig. 1b). In addition, the abundance of the detected compounds varied from one culture medium to another. Some of the detected compounds were successfully annotated while the other compounds remained unknown. Of the four culture media used, TSB was the most favorable medium for the cultivation of the bacterium (Fig. 1c).

Metabolomics analysis of Peribacillus frigoritolerans BE93 grown in different culture media. (a) Feature-based molecular networking (FBMN) of the detected secondary metabolites from BE93 culture extracts. Each node represents one fragmentation spectrum from a detected compound, node size represents the summed ion intensity from all samples, edge thickness indicates the relative similarity of the tandem mass (MS/MS) data between nodes, and the pie charts indicate the relative abundance of each compound from the different samples. Nodes having a putative library match are outlined in black. Colors represent the culture medium. (b) Venn diagram showing the counts and distributions of nodes among the different culture media. (c) Growth curve of BE93 in different culture media.

In our previous study, the culture extract of BE93 grown in TSB showed nematicidal activity against B. xylophilus46. Considering the previous result, we then next closely characterized the secondary metabolites detected in the culture extract of BE93 cultivated in TSB medium. Out of the total 110 compounds or spectral features, 109 were detected in the TSB culture extract, each with varying abundance (Fig. 2a). Spectral feature 22 with molecular ion of 804.328 m/z was found to be the most abundant spectral feature. Other abundant spectral features were also observed with molecular ions ranging from 211.10 to 261.05 m/z, representing compounds of the same class (Supplementary Table S1, Fig. S1). The molecular ion 804.328 m/z [M+H] was annotated by the GNPS spectral library as a close match to koranimine, a cyclic imine compound isolated from Bacillus sp. NK200353 (Supplementary Fig. S2). A molecular network of koranimine was also observed, with a single node having a molecular ion of 822.302 m/z [M+H] connected to koranimine (Fig. 2b). The 822.302 m/z [M+H] molecular ion represented the open form of koranimine, the direct result of reductive release from the biosynthetic assembly. Moreover, koranimine and its open form were observed to be produced in all culture media used in varying degree of abundance. We further verified the identity of the detected koranimine in our sample by manually assessing the fragment spectrum (MS/MS) of the compound. Two fragmentation pathways were elucidated (Fig. 2c). Ring opening in pathway 1 occurred through cleavage between the sixth and seventh amino acids (Phe-Val). Successive cleavage between residues resulted in the generation of different observed fragment ions. The cleavage between the seventh and first amino acids (Val-Thr) resulted in the opening of the ring as indicated in pathway 2. We also evaluated the production of koranimine in the TSB medium (Fig. 2d). BE93 showed a time-dependent production of koranimine, commencing at the late exponential phase and gradually increased towards the stationary phase. From these results, we have speculated that koranimine, a dominant secondary metabolite, might be responsible for the reported nematicidal activity of BE93.

Characterization of koranimine from Peribacillus frigoritolerans BE93. (a) Relative abundance of the detected spectral features in tryptic soy broth (TSB) medium. Asterisk (*) represents koranimine. (b) Koranimine molecular network showing the structure of koranimine and its open aldehyde form. Pie chart represents relative abundance in each culture medium. (c) Elucidated tandem mass (MS/MS) fragmentation pathways of koranimine. (d) Time-dependent production of koranimine in TSB medium.

Whole genome sequencing was performed to examine the biosynthetic potential of BE93 and to further verify the production of koranimine, through the identification of BGCs encoded in the genome. The bacterium has a genome size of 5, 693, 946 base pair (bp) with 40.54 mol % G + C content, and 5, 653 identified coding sequences (Fig. 3a). Putative functions of the coding sequences were predicted using the eggNOG platform (Fig. 3b). Out of the 5, 653 coding sequences 5, 321 were successfully assigned to a specific clusters of orthologous group (COG) category, accounting for 94% of the total coding sequences. The remaining 332 coding sequences were unclassified.

Analysis of the whole genome sequence and biosynthetic gene clusters (BGCs) of Peribacillus frigoritolerans BE93. (a) Circular whole genome map with marked characteristics. (b) Clusters of orthologous group (COG) classification of coding sequences (CDS) based on eggNOG annotation. (c) Putative BGCs predicted using the antiSMASH 5.0 algorithms.

The antiSMASH 5.0 algorithms were used to analyze the genome sequence for the presence of BGCs. The analysis revealed 9 putative BGCs comprising 2 non-ribosomal peptide synthases (NRPS), 2 terpenes, 1 siderophore, post-translationally modified peptides (RiPPs), sactipeptide, type III polyketide synthase (T3PKS), and betalactone (Fig. 3c). One of the predicted BGCs showed high similarity (> 80%) to the known koranimine BGC in the MIBiG database, substantiating the detected koranimine production in the bacterium. Three of the other predicted BGCs displayed moderate levels of similarity (28–53%) to known BGCs, while the remaining 5 BGCs exhibited low to no similarity. The consolidated length of the predicted BGCs was 272,302 bp, accounting for around 4.8% of the BE93 genome.

Koranimine and its biosynthesis genes were first characterized in the soil dwelling bacterium Bacillus sp. NK200353. The BGC for koranimine in BE93 shared 87% similarity with the koranimine BGC of Bacillus sp. NK2003. The koranimine BGC of Bacillus sp. NK2003 is composed of 6 open reading frames (ORFs) representing the core biosynthesis genes encoding phosphopantetheinyl transferase (kfp), koranimine (korA, korB, korC, korD), type II thioesterase (korTE), and one hypothetical gene. Close analysis of the BE93 koranimine BGC revealed striking different gene architecture (Fig. 4a). Unlike the previously characterized BGC, 11 ORFs were present in the koranimine BGC of BE93 stretching 25,089 bp. Three ORFs were found to comprise korA, and 2 ORFs for korB and korC. Amino acid identity of the individual ORFs displayed high level of similarity to the core biosynthesis genes of koranimine BGC (Table 1).

Characterization of koranimine biosynthetic gene cluster. (a) Comparison of koranimine biosynthetic gene cluster (BGC) gene organization detected in Peribacillus frigoritolerans BE93 with that of Bacillus sp. NK2003. (b) Non-ribosomal peptide synthase (NRPS) domains and modules found in the BE93 koranimine BGC and the proposed pathway for the biosynthesis of koranimine.

The difference in the gene architecture of the koranimine BGC between BE93 and Bacillus sp. NK2003 was also evident in the biosynthesis NRPS domains and modules. Previous report revealed 5 adenylation domains of the koranimine BGC, lacking a dedicated adenylation domain for 1 leucine residue. Here, the koranimine BGC of BE93 displayed 6 adenylation domains, including a dedicated adenlylation domain for installing the second leucine residue. As expected, the groupings of the NRPS modules were also different as the core genes were divided into several ORFs. Figure 4b shows the NRPS domain architecture of koranimine BGC and the proposed biosynthesis pathway of koranimine in BE93.

To assess the potential of koranimine as a nematicidal compound, in silico analysis through molecular docking was performed. We chose the ivermectin-sensitive invertebrate glutamate-gated chloride channel (GluCl) (Fig. 5a) as the target protein or receptor, considering the comparable molecular weight (804 g/mol) and the macrocyclic nature of koranimine to the known macrocyclic nematicidal compound ivermectin (875 g/mol). We first conducted a re-docking experiment of Caenorhabditis elegans α GluCl receptor54 with its cognate agonist ivermectin to demonstrate the accuracy of our adopted molecular docking system. The re-docking experiment resulted in a good docking score with a binding energy of − 10.3 kcal/mol. Close analysis of the best docking pose of ivermectin revealed highly congruent ligand-receptor conformation with the previous report54. The docking results displayed the binding of ivermectin at the subunit interfaces of the transmembrane domains, the allosteric site proximal to the extracellular side (Fig. 5b,c). Specifically, ivermectin showed binding between the M3 α-helix of the principal (+) subunit and the M1 α-helix of the adjacent complementary (‒) subunit, and with the benzofuran structure contacting the M2 pore-lining α-helix of the (+) subunit. Analysis of the ligand-receptor interactions revealed three hydrogen bonds formed between the ligand and the M2(+) Ser260, M3(+) Thr285, and M1(‒) Leu218 residues of the receptor. Moreover, extensive van der Waals and hydrophobic interactions were also observed such as alkyl, and pi-alkyl interactions.

Molecular docking simulation of koranimine and ivermectin with Caenorhabditis elegans α GluCl receptor. (a) Three-dimensional (3D) protein model of C. elegans ivermectin-sensitive invertebrate α glutamate-gated chloride channel (GluCl) obtained from research collaboratory for structural bioinformatics protein data bank (RCSB PDB). (b) Best docking pose of ivermectin bound to the allosteric site of α GluCl receptor. (c). Ligand-receptor interactions between ivermectin- α GluCl receptor shown in 2D. (d) Best docking pose of koranimine bound to the allosteric site of α GluCl receptor. (e) Ligand-receptor interactions between koranimine- α GluCl shown in 2D.

Using the C. elegans α GluCl receptor, we also performed docking experiment with koranimine. Having shown the ligand-receptor interactions of ivermectin—α GluCl receptor, a good comparative evaluation can be employed. The docking results showed the binding of koranimine at the subunit interfaces of the transmembrane domains of the α GluCl receptor similar to the one observed in ivermectin, with a binding energy of − 8.66 kcal/mol (Fig. 5d,e). Koranimine positioned between the M3(+) α-helix subunit and the M1(‒) α-helix subunit of α GluCl receptor. A close look on the formed ligand-receptor interactions displayed a hydrogen bond with the M3(+) Thr285 residue of the receptor. Extensive van der Waals and hydrophobic interactions, mostly found in ivermectin—α GluCl receptor interaction were also observed, especially with the amino acid residues deemed important for ivermectin binding [M1(‒) Leu218 and M3(+) Gly281].

Taken into account the results from the comparative ligand-receptor interactions of ivermectin and koranimine with C. elegans α GluCl receptor, we then sought to investigate the compounds’ interactions with the α GluCl receptor of the target nematode B. xylophilus. The α GluCl receptor of B. xylophilus has not been resolved yet through crystallographic methods. However, the gene encoding for the receptor is present in the genome of B. xylophilus. In this regard, we used homology modelling to obtain the 3-dimensional (3D) structure of the α GluCl receptor from B. xylophilus. The identified α GluCl receptor of B. xylophilus (CAD5232901) displayed 72.40% protein sequence similarity with the C. elegans α GluCl receptor (3RHW_A). The C. elegans α GluCl receptor was then used as a template for the homology modelling. The built 3D model of the α GluCl receptor is shown in Fig. 6a,b. The Ramachandran plot of the modelled structure showed decent quality assessment, exhibiting more number of residues in the most favorable regions (96.04%), and low number of residues were found in the disallowed regions (Fig. 6c). The ERRAT plot also showed good resolution of the modelled 3D structure (Supplementary Fig. S3). The modelled structure was then used for the molecular docking experiment.

Homology modelling of Bursaphelenchus xylophilus α glutamate-gated chloride channel (GluCl) receptor. (a) Three-dimensional (3D) model of B. xylophilus α GluCl receptor obtained through homology modelling. (b) Superimposed 3D structures of α GluCl receptor from B. xylophilus (green) and C. elegans (brown). (c) Ramachandran plot showing the quality assessment of B. xylophilus α GluCl receptor 3D model.

Results from the molecular docking of ivermectin and α GluCl receptor of B. xylophilus revealed similar binding pose with that of ivermectin—C. elegans α GluCl receptor interaction (Fig. 7a), with ivermectin positioned between the M3(+) α-helix and the M1(‒) α-helix subunits of receptor having a binding energy of − 8.7 kcal/mol. Two hydrogen bonds were observed, formed between the ligand and the M2(+) Ser317 [counterpart of M2(+) Ser260 of C. elegans α GluCl receptor] and the M1(‒) Leu275 [M1(‒) Leu218 equivalent] residues of the receptor. Hydrophobic interaction (van der Waals) was only observed between the ligand and the M3(+) Thr330 [M3(+) Thr285 equivalent] residue of the receptor, unlike with the hydrogen bond observed in the ivermectin—C. elegans α GluCl receptor interaction. Extensive interactions such as van der Waals, and hydrophobic alkyl, and pi-alkyl interactions were also observed. On the other hand, the best docking result of koranimine with the B. xylophilus α GluCl receptor still positioned the ligand in the allosteric site, between the two subunits M3(+) and M1(‒) of the receptor with a binding energy of − 7.0 kcal/mol (Fig. 7b). Koranimine formed van der Waals and hydrophobic interactions with the important key residues of the receptor, M1(‒) Leu275, M3( +) Thr330, M3( +) Gly330, and with some other residues observed in the ivermectin—B. xylophilus α GluCl receptor interaction. Taken together, these results reveal the potential of koranimine as a nematicidal compound that targets the invertebrate α GluCl channel.

Molecular docking simulation of koranimine and ivermectin with Bursaphelenchus xylophilus α glutamate-gated chloride channel (GluCl) receptor. (a) Best docking pose of ivermectin bound to the allosteric site of α GluCl receptor (left) and the ligand-receptor interactions shown in 2D (right). (b) Best docking pose of koranimine bound to the allosteric site of α GluCl receptor (left) and the ligand-receptor interactions shown in 2D (right).

Secondary metabolites, also known as natural products are small molecules produced by a diverse group of living organisms. Bacterial endophytes, in particular are long been known sources of structurally diverse bioactive compounds with potential biotechnological applications. In this study, we explored the secondary metabolites of BE93 to uncover potential compound responsible for the observed nematicidal activity of the bacterium against B. xylophilus. We employed a combination of metabolomics and genomics approach to reveal the chemical and biosynthetic potential of BE93. In addition, in silico analysis through molecular docking was also employed to evaluate the nematicidal potential of the compound of interest.

The metabolic profile of BE93 grown in different culture media displayed a wide array of secondary metabolites. These secondary metabolites were mostly detected and shared in all culture media used, with varying abundance. Moreover, the GNPS workflow has allowed the reliable annotation of certain compounds from the culture extracts. A compound of interest, koranimine (804.328 m/z [M+H]) was shown to be present in all media used, and found to be the most abundant compound produced in the TSB medium. MS/MS has enabled the use of product ions for the identification of fragmentation pattern useful for the validation of compounds55. The identity of the detected koranimine was further validated through manual inspection of the MS/MS spectrum and the determination of the signature fragment ions. The elucidated fragmentation pathways coincided with the reported fragmentation pathways of koranimine53, thereby confirming the identity of the detected compound. Koranimine was first described from the environmental isolate Bacillus sp. NK2003 as an imine-containing cyclic peptide53. The compound is composed of 7 amino acids Thr-Leu-Leu-Phe-Val-Phe-Val and is produced through non-ribosomal biosynthesis. Previous assessment of the bioactivity of koranimine showed that the compound had no inhibitory effects on the growth of pathogenic bacteria and fungi53, suggesting that the compound does not act as an antimicrobial agent. At the time of writing this manuscript, no biological activities have been attributed yet to koranimine. Of note, peptides produced through non-ribosomal biosynthesis usually possess various potent bioactivities. Members of this chemical group, aside from antibiotics, include anticancer drugs such as bleomycin56, immunosuppressants like cyclosporin57, mycotoxins58, and broad spectrum insecticidals such as beauvericin59. Koranimine as a non-ribosomal peptide may possess bioactivities of relevant interests, such as nematicidal activity of which the producer bacterium BE93 has been shown to exhibit.

The production of secondary metabolites in microorganisms is greatly affected by culture media composition60. Here, the observed variation in the abundance of compounds produced in the different culture conditions can be attributed to the differential growth of the bacterium in each medium. BE93 was found to prefer a plant-based rich medium TSB, compared to other rich media like LB and NB, and low nutrient medium R2A for growth and secondary metabolite production. In TSB medium, koranimine production was observed to peak at the start of the stationary growth phase of the bacterium. This time-dependent increase of koranimine production was similarly detected in Bacillus sp. NK200353. The production of secondary metabolites in microorganisms mostly commences at late exponential and dominates upon entering the stationary phase61.

The genome of BE93 displayed the presence of koranimine BGC, with high similarity to the previously characterized BGC in Bacillus sp. NK200353. Other putative BGCs were also observed suggesting the ability of the bacterium to synthesize diverse specialized metabolites. The koranimine BGC of Bacillus sp. NK2003 is represented by the core biosynthesis genes kfp, korA, korB, korC, korD, korTE and one hypothetical gene. Only 5 adenylation domains were characterized as opposed to the expected 7 for the heptapeptide product. Installing the second and third leucine amino acids have been shown to be facilitated by a single leucine adenlytion domain of KorA. A long-range activation of KorC has also been observed, in which the tandem thiolation domains of KorC were both charged with valine amino acid by the adenylation domain of KorD. KorD hence, is responsible for the incorporation of 2 valine amino acids the fifth and the seventh valine residues, respectively. The NRPS module KorD, aside from installing the 2 valine residues, has been shown to be involved in the NADPH-dependent reductive release of the compound, forming a linear product with terminal aldehyde. Spontaneous macrocyclization facilitated by the terminal aldehyde yields the cyclic imine compound53. Though all the koranimine core biosynthetic genes were found in BE93, the BGC showed a pronounced difference in the gene organization and NRPS domains. Strikingly, the koranimine BGC of BE93 was found to contain 6 adenylation domains, including a third dedicated adenlylation domain in KorA module responsible for installing the second leucine residue. Though different in their NRPS domain organization, both the Bacillus sp. NK2003 and BE93 shared the unusual aspects of the koranimine biosynthesis.

The culture extract of BE93 grown in TSB has been shown to have potent nematicidal activity against different developmental stages of B. xylophilus46. Taken into account this previous finding, coupled with the dominant presence of koranimine in the TSB medium, an in silico analysis through molecular docking was performed to examine the nematicidal potential of the compound. Using the α GluCl channel of both C. elegans and B. xylophilus as the target receptor, koranimine displayed binding specificity at the allosteric site known for ivermectin binding54. Moreover, extensive van der Waals and hydrophobic interactions formed between koranimine and the receptor were observed, specifically with those residues reported to have been involved in ivermectin binding: M1(‒) residues Leu217, Leu218, Ile222, Met226, Pro223, and M2( +) residues Asp227, Gly281, Met284, Thr285, Phe28822. Counterparts of these amino acid residues were mostly observed as well in the B. xylophilus α GluCl-koranimine interaction. Generally, van der Waals and hydrophobic interactions allow the ligand to achieve stable conformation resulting in a stable receptor-ligand complex, hence rendering better activity of the ligand62. Ivermectin acts by activating the α GluCl channels present in nerve or muscle cells causing hyperpolarization that will result to subsequent paralysis23,24,25. This activation is the result of the conformational change of the channel upon binding of ivermectin to the allosteric site54. The binding of koranimine to the allosteric site of α GluCl channel and the extensive ligand-receptor complex interactions shared between koranimine and ivermectin greatly suggest the strong affinity of koranimine to the target Cys-loop receptor α GluCl. These further suggest a potential nematicidal activity, similar to that displayed by ivermectin.

On the other hand, koranimine is a macrocyclic imine-containing compound, a member of known natural products that contain a carbon–nitrogen double bond in the structure like nostocyclopeptide63, scytonemide A64, and lugdunin65. Other members of this group are marine biotoxins produced by dinoflagellates such as spirolides, gymnodimines, pinnatoxins, and among others. These toxins target the nicotinic acetylcholine receptors (nAChRs) which are cholinergic pentameric receptors that formed ligand-gated ion channels in neurons and postsynaptic side of the neuromuscular junction. Interaction of the toxin with the receptor results in a paralysis. In these toxins, it has been deduced that the imine functional group serves as the common pharmacophore as it showed important role in tethering the toxins to their binding site66. It can be noted that nACh and GluCl receptors are members of Cys-loop family of receptors, of which ivermectins have shown to have activities22. Hence, the imine functional group of koranimine which is considered a pharmacophore in marine biotoxins, further substantiates the affinity of the compound towards Cys-loop receptors and its potential nematicidal activity. Single compound isolation, characterization and in vitro studies of the compound to further probe its nematicidal activity are currently underway.

Thus far, there have been no reports of ivermectin resistance in B. xylophilus, however, the possibility of developing resistance remains in place, as observed in other parasitic nematodes13. The mechanism of ivermectin resistance in some parasitic nematodes is far from clear, although most studies have suggested the involvement of ATP-binding cassette (ABC) transporters such as P-glycoproteins67,68. Ivermectin has been shown to be an excellent substrate of some ABC transporters. The affinity of ivermectin to these transporters renders its reduced intracellular concentration, subsequently resulting to reduced ivermectin sensitivity in nematodes68. It is then apparent that the observed ivermectin resistance in some nematodes did not arise from the modification of the ivermectin compound or alteration of the ivermectin targets. Hence, a compound with potentially the same mechanism of action with ivermectin, like koranimine can still be seen as a promising nematicidal agent in managing ivermectin resistant nematodes as long as the compound is not subject to efflux by the ABC transporters.

In general, this study revealed the production of a cyclic imine compound koranimine with potential nematicidal activity from a bacterial endophyte BE93. The compound can be seen as a promising nematicidal agent and could diversify treatment options for the management of PWD caused by B. xylophilus. Nonetheless, in vitro study of the pure compound must be conducted to further confirm the in silico result of this study. On the other hand, this study also highlighted the efficiency of the combined metabolomics and genomics approach in the identification of candidate compounds.

Peribacillus frigoritolerans BE93 was obtained from our in-house collection of bacterial endophytes isolated from 4 pine tree species in Republic of Korea46. The strain was routinely cultured in Bacto tryptic soy broth (TSB) at 30 °C with shaking (150 rpm) for 24 h to generate the seed culture. For secondary metabolite analysis, a 1:100 dilution of the seed culture was inoculated into Difco Nutrient Broth (NB), Difco Luria-Bertani (LB), MBCell R2A Broth, and TSB. The cultures were then incubated at 30 °C, 150 rpm for 3 days. Bacterial growth was also determined every 12 h through standard plate dilution technique.

To extract the secondary metabolites of BE93, the culture broth from each media was mixed with an equal volume of ethyl acetate followed by sonication for 30 min. The organic phase was then separated from the medium and concentrated using a rotary evaporator. The concentrated extract was then dissolved in 1 mL of HPLC-grade methanol and filtered with a syringe filter (0.45 μm).

The ethyl acetate extracts were then subjected to liquid chromatography- mass spectrometry (LC–MS) analysis using LCMS-8040 tandem quadruple mass spectrometer (Shimadzu, Tokyo, Japan). Chromatographic method consisted of solvent A (0.1% formic acid in HPLC-grade water) and B (100% acetonitrile). The flow rate was set to 0.4 mL/min in a C18 column (150 × 4.6 mm, 2.5 μm; Advanced Chromatography Technologies) under the following conditions: 0–1 min, 5% B; 1–30 min, 40% B; 30–52 min 100% B; followed by hold of 100% B for 4 min; and column reconditioning with 5% B for 4 min. The mass spectrometer was operated in positive mode data dependent MS/MS scans, monitoring a mass range from 50 to 2000 atomic mass units (amu), capillary voltage of 3500 V, nebulizer at 60 psi, dry gas flow 15 L/min, and dry temperature at 320 °C.

The FBMN workflow of the GNPS web platform was used to generate the molecular networks as it allows for the discrimination of isomers, redundant fragment ions, and quantitative evaluation of the molecular network48. The raw LC-MS/MS data files were converted into mzXML file format using the Proteowizard MSConvert69 and subsequently processed using MZmine 270 to generate the MS/MS mascot generic format (MGF) and quantification comma-separated values (CSVs) files required for the FBMN workflow. All the files for the FBMN workflow are available through the mass spectrometry interactive virtual environment (MassIVE) data repository under the accession code MSV000088477.

For the FBMN workflow, default settings were used unless otherwise stated. The precursor and fragment ion mass tolerances were set at 2.0 and 0.9 dalton (Da), respectively. Advanced network options were set as follows: minimum pairs cosine, 0.6; maximum matched fragment ions, 4; and minimum cluster size, 1. For library search, minimum matching peaks was set at 4, with a score threshold of 0.6. The resulting molecular networks were visualized using Cytoscape v3.9.071. Annotated known secondary metabolites by the GNPS spectral library were further assessed by manual evaluation of the matched mass fragments and cross-checking with available published data.

The genome sequence of BE93 was previously obtained47 and deposited in GenBank (www.ncbi.nlm.nih.gov/genbank/) under the accession number JAACZL010000000. The whole genome sequence was visualized using the CGView tool72 and functional gene annotations or clusters of orthologous groups (COGs) classifications were generated using the eggNOG-mapper v273. To identify secondary metabolite biosynthetic gene clusters (BGCs), the genome sequence was submitted to antiSMASH 5.049 and PRISM50 and analyzed using the default parameters.

Homology modelling was employed to obtain the 3D protein model of ivermectin–sensitive invertebrate α glutamate-gated chloride channel (GluCl) of B. xylophilus. Using the C. elegans protein sequence, a basic local alignment search tool (BLAST) analysis against the genome sequence of B. xylophilus in the database of national center for biotechnology information (NCBI) allowed the retrieval of a homologous protein with an accession code CAD5232901. The α GluCl PDB crystal structure of C. elegans (3RHW_A) from the research collaboratory for structural bioinformatics protein data bank (RCSB PDB; https://www.rcsb.org/) was used as the template for the homology modelling through SWISS-MODEL74. Quality evaluation of the model was employed through PROCHECK75, and ERRAT76 at the SAVES server (https://saves.mbi.ucla.edu/). Energy minimization of the model was carried out through steps of steepest descent and conjugate gradient using GROMOS77 in the Swiss-PDB viewer environment78.

Molecular docking was performed using the AutoDock Vina51 within the UCSF Chimera52 working space. The modelled 3D protein α GluCl of B. xylophilus and the α GluCl of C. elegans (3RHW_A) were used as receptors. Chains A and B of the protein channel were selected for the docking experiment, representing the principal (+) subunit and the adjacent complementary (‒) subunit of the channel. Koranimine and ivermectin structures were retrieved from PubChem (https://pubchem.ncbi.nlm.nih.gov/) and RCSB PDB, respectively. The receptors and ligands were prepared using the Dock prep tool in UCSF Chimera with the default parameters. Although the amino acid residues comprising the allosteric site of the receptor are known, blind docking was still performed to investigate the binding potential of koranimine. The molecular docking was carried out with the default parameters of the AutoDock Vina. The resulting receptor-ligand complex configurations and interactions were visualized and analyzed using the BIOVA discovery studio visualizer (https://discover.3ds.com/discovery-studio-visualizer-download).

All data generated or analyzed during this study are included in this article and in its supporting information.

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This research was supported by Yeungnam University Research Grant 222A380020.

Department of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, 38541, Republic of Korea

Jake Adolf V. Montecillo & Hanhong Bae

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J.A.V.M. and H.B. conceptualized the study. J.A.V.M. conducted the experiments and analyzed the data. H.B. supervised the study and reviewed the manuscript.

The authors declare no competing interests.

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Montecillo, J.A.V., Bae, H. In silico analysis of koranimine, a cyclic imine compound from Peribacillus frigoritolerans reveals potential nematicidal activity. Sci Rep 12, 18883 (2022). https://doi.org/10.1038/s41598-022-20461-8

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