Introduction

Microbial secondary metabolites emerge as a promising sustainable source for new opportunities of application, emphasizing their potential for several agricultural purposes1. Actinobacteria, in particular, effectively enhance the overall durability of plants in agricultural and ecological settings by synthesizing secondary metabolites and enzymes that serve as natural defenses against damaging pests and diseases2. Natural insecticides were derived from soil actinobacteria by fermentation procedures, including avermectins, spinosyns, and milbemycins3,4,5. Streptomyces is the largest producer genus of known secondary metabolites of actinomycetes that produce 70–80% of bioactive natural products6. Streptomyces mutabilis IMA8 produces a chitinase enzyme that has a larvicidal effect against the larval and pupal stages of Anopheles stephensi and Aedes aegypti (Diptera)7.

The herbivorous cotton leafworm, Spodoptera littoralis (Boisduval), attacks more than a hundred plant species annually by feeding gregariously on its shoot system, causing massive economic losses8. It is considered a global economic threat9. The management of S. littoralis to ensure stable and high crop output is a great challenge that necessitates permanent and continuous research to find renewable and innovative control agents10. Efforts to limit insect spread and reduce damage should consider environmental considerations11,12.

Untargeted metabolomics is an analytical approach utilized to identify and analyze chemical constituents of metabolites without prior knowledge of their specific identity13. Recently, it has been increasingly used to identify microbial metabolites, which are promising sources of bioactive compounds with potential applications in medicine, agriculture, and industry14,15,16,17. Its application in fungal research has helped in five aspects: identification, response to stress, metabolite discovery, metabolism engineering, and fungal interactions with plants18. Untargeted metabolomics and bioinformatics were applied to set up biomarkers of aflatoxigenic Aspergillus species19. In drug discovery field, the approach of combining metabolomics with molecular docking is successfully applied to investigate the mechanisms of action of natural compounds derived from microorganisms 20. Molecular docking has determined the inhibition types and binding modes of α-glucosidase from two mangrove-derived actinomycetes, Streptomyces sp. WHUA03267 and St. sp. WHUA0307221. Additionally, molecular docking was used to assess insecticidal activity against Plutella xylostella and illustrate the identified compound action with the GABA (γ-aminobutyric acid) receptor21.

Measuring the enzymatic activities in insects can provide valuable information on the effectiveness of insecticide treatments and the potential for the development of resistance22,23. Nonspecific esterases (NSEs) are an enzymatic class that play an important role in xenobiotic metabolism, including insecticides24. In insects, NSEs are classified into two groups: alpha and beta, responsible for insecticide detoxification and insecticide resistance development. The detoxification enzyme activity (α and β esterase) was measured for Aedes aegypti and Spodoptera litura exposed to different concentrations of biosynthesized TiO2 nanoparticles25. Polyphenol oxidase (PPO) and catalase (CAT) are two enzymes that play important roles in defense mechanisms. PPO is involved in toxic quinone production from phenolic compounds, while CAT is involved in hydrogen peroxide breakdown26. Abdel-Aziz’s research team have proved the role of PPO and CAT in the defense response on Citrus aurantium against Parlatoria ziziphi27.

This research intended to shed light on the activity of the endophytic actinobacterium Streptomyces ES2 EMCC2291 as a pesticide agent and to demonstrate its chemical profile. Moreover, this study contributes to the systematic evaluation and application of crude ES2 extract as an ovicidal and larvicidal agent against the cotton leafworm S. littoralis. Our study illustrates endophytes as a prospective future source that can be relied upon in the field of pest control.

Results

Metabolite profiling of ES2 crude extract using LC-QTOF-MS/MS

Untargeted metabolomics is a method that aims to comprehensively analyze all metabolites present in a sample, without prior knowledge of their chemical identity. The untargeted metabolomics analysis, using the LC-QTOF-MS/MS technique, identified 83 metabolic compounds (Supplementary Table S1 online) from the complete metabolite profiling of ES2 crude extract (Fig. 1). The identified compounds belonged to 15 chemical classes: phenol (17), acid (13), aromatic amine (12), amide (7), ester (7), alcohol (5), aliphatic amine (5), α, β unsaturated carbonyl compound (5), amino acid (3), ketone (3), aliphatic hydrocarbon (2), aliphatic ether (1), sulfur-containing compound (1), anhydride (1), and phosphorous compound (1). Seven compounds were identified as key constituents of the ES2 metabolic extract. These were 4-nitrophenol, Cyromazine, Di (2-ethylhexyl) phthalate (DEHP), Jasmonic acid, Diazinon, Dioctyl Phthalate, and Brevicompanine B (Table 1). The acquired data from LC-QTOF-MS/MS libraries were compared to the five most common chemical databases: ChemSpider ID, Chemical structure database identifier (http://www.chemspider.com/); InChI key, International chemical identifier (https://pubchem.ncbi.nlm.nih.gov/source/ChEBI); KEGG ID, Kyoto encyclopedia of genes and genomes (https://www.genome.jp/kegg/); METLIN ID, METLIN metabolite and chemical entity database (https://metlin.scripps.edu/); and CAS registry number, chemical abstracts service database (https://www.cas.org/). The data were identified with a ratio of more than 99.9% compared to the built-in database (Data Acquisition Analyst TF 1.7.1 software, Sciex) and online databases (MassBank of North America “MoNA”, Yeast Metabolome database “YMDB”, EcoCyc E. coli database, Human Metabolome database “HMDB”, and DrugBank database).

Figure 1
figure 1

Positive mode total identified chromatogram for Streptomyces ES2 EMCC2291 ethyl acetate metabolic extract using LC-QTOF-MS/MS. The total identified chromatogram (TIC) represents the main raw dataset compared to the built-in database (Data Acquisition Analyst TF 1.7.1 software, Sciex) and online databases. The chromatogram is shown as the peak relative retention time. LC-QTOF-MS/MS, liquid chromatography, combined with quadrupole-time-of-flight high-definition mass spectrometry instrument.

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Table 1 Key constituents of Streptomyces ES2 EMCC2291 ethyl acetate metabolic extract.
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Biochemical assessments for nonspecific esterases of treated S. littoralis fourth instar larvae

Alpha esterase enzymatic activity at normal (distilled water), negative control (ethyl acetate), Biosad® 22.8%, and ES2 Metabolite showed an average (± SE) of 13.266 ± 0.425, 13.966 ± 0.463, 10.033 ± 0.088, and 10.433 ± 0.233 µg α-naphthol/min/mg protein. Alpha esterase activity in Biosad® 22.8% (10.033 ± 0.088) was significantly decreased compared with the normal control (13.266 ± 0.425) and negative control (13.966 ± 0.463), as revealed by DMRTs at the 0.05 level. In addition, alpha esterase activity in the ES2 metabolite (10.433 ± 0.233) was significantly decreased versus the normal control (13.266 ± 0.425) and negative control (13.966 ± 0.463), as revealed by DMRTs at the 0.05 level (Table 2). Beta esterase activities in Biosad® 22.8% showed an average of 9.233 ± 0.12 µg β-naphthol/min/mg protein, which is significantly lower than that of the normal control (11.1 ± 0.208) and negative control (12.233 ± 0.202), as revealed by DMRTs. Furthermore, beta esterase activities in the ES2 metabolite group (11.133 ± 0.176) showed no significant difference versus the normal control; however, a significant difference against the negative control was observed, as revealed by ANOVA and DMRTs.

Table 2 Alpha and beta esterase activities of Spodoptera littoralis fourth instar larvae treated with Streptomyces ES2 metabolites.
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Biochemical assessments for polyphenol oxidase and catalase activities of treated S. littoralis egg masses

Biochemical assessments of laboratory S. littoralis egg masses treated with crude ES2 metabolites; in particular, polyphenol oxidase and catalase enzyme activities present ovicidal biological effects. Polyphenol oxidase enzyme activities in Biosad® 22.8% showed an average of 1748 ± 13.316 m ∆ O.D./min/mg protein, which is significantly higher than the normal control (414.333 ± 12.732) by 321.9% and the negative control (428.666 ± 16.414 m ∆ O.D./min/mg) by 307.8%, as revealed by DMRTs. Furthermore, treatment with the ES2 metabolite group significantly increased PPO activity by Biosad® 22.8% (509.0 ± 8.50), as revealed by ANOVA and DMRTs. On the other hand, Biosad® 22.8% significantly lowered CAT activities by 10.2% and ES by 5.3% from the normal control as revealed by DMRTs at 0.05 (Table 3).

Table 3 Polyphenol oxidase and catalase enzyme activities of Spodoptera littoralis egg masses treated with Streptomyces ES2 metabolites.
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Molecular docking simulation

Molecular docking was conducted for the seven major compounds in ES2 metabolites to illustrate the virtual binding mechanism inside polyphenol oxidase and catalase proteins. The results explained the mode of action inside the treated S. littoralis egg cells. As summarized in Table 4, all the compounds exhibited good binding affinity toward the tested proteins with good binding energy (negative values -26.18 to -2.1 kcal/mol), except DEHP and brevicompanine B compounds for CAT protein with positive values. The compounds exhibited good interaction profiles with the key amino acids of both proteins. The three-dimensional visualization in Fig. 2 shows that cyromazine (with the lowest binding energy) was deposited inside the binding sites of polyphenol oxidase and catalase proteins and formed good interactive profiles with the key amino acids.

Table 4 Molecular docking for the seven key Streptomyces ES2 constituents inside polyphenol oxidase and catalase proteins of Spodoptera littoralis eggs.
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Figure 2
figure 2

Binding disposition and ligand-receptor interactions of cyromazine toward polyphenol oxidase and catalase active sites. Cyromazine is shown in green; a, polyphenol oxidase (PPO) and b, catalase (CAT) active sites are shown in black. Hereto-atoms of oxygen, nitrogen, and hydrogen with standard colors. Molecular docking studies were carried out using AutoDock Vina version 4 (https://vina.scripps.edu/) as the computational software.

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Discussion

This study was conducted to assess the significance of endophytic actinobacterial secondary metabolites in controlling the devastating pest S. littoralis, demonstrating their ovicidal and larvicidal activities and providing valuable insights into their mode of action and potential applications.

The results revealed that the ES2 crude metabolite contains seven unique constituents (brevianamid F, 1-naphthylamine, S-adenosylmethioninaminium, palitanin, phthalic anhydride, galaxolidone, and brevicompanine B) that have not previously been recorded from actinomycetes based on our search using the Derwent innovation database40. The crude constituents of ES2 combine a variety of biological activities, including biocontrol, protein inhibitor, neurotoxin, antioxidant, immunostimulant, and anticancer activities. The compound 1-naphthylamine has antitumor41, antimicrobial42, and biocontrol activities against a lepidopteran pest, Tryporyza intacta43. S-adenosylmethioninaminium has anticancer activity44, whereas Brevianamid F and Palitantin have antimicrobial activity45,46. These findings highlight the richness of the studied Streptomyces ES2 EMCC2291 strain with a highly bioactive metabolome outcome.

The ES2 metabolite showed an ovicidal action stronger than its larvicidal impact against S. littoralis. This may be due to the mode of action of ES2 chemical constituents or because the larval stage is stronger than the egg stage9. The LC50 values were compatible with the toxicity results, where the LC50 of the ES2 metabolite was 165 and 695 mg/mL for ovicidal and larvicidal effects, respectively, in parallel with Biosad® 22.8% LC50. The biochemical assessments of ES2 showed a significant decrease in α- and β-esterase activities in the treated S. littoralis larvae. These results are confirmed by the molecular docking outcomes. These findings varied as a result of the evaluation of compounds on target proteins, confirming El-Kareem’s study47. In contrast, the molecular docking results showed good binding energy (negative values, Kcal/mol) for the antioxidant PPO and CAT target proteins and supported its response to ES2 activity in S. littoralis eggs. PPO showed a significantly different increase from controls and a decrease from Biosad® 22.8%, while CAT enzymatic activity showed a slightly significant response. Our results indicated that the potency of ES2 against S. littoralis eggs agrees with Wang’s research outcome26.

Our outcomes are in agreement with a study that investigated the nematocidal activity of Streptomyces enissocaesilis OM182843 against root-knot nematodes (Meloidogyne incognita)48. Our results thus indicated the potential of ES2 to control different S. littoralis stages. On the other hand, Zayed et al. assessed the commercial microbial formulation “effective microorganisms” against S. littoralis fourth instar larvae, and they reported its antifeedant activity49. ES2, being a crude microbial metabolite with both active and inactive constituents, resulted in LC50 levels of 165 mg/mL for ovicidal effects and 695 mg/mL for larvicidal effects. These higher LC50 values are attributed to the diverse composition of ES2. Previously reported LC50 values reflect the overall impact of the heterogeneous metabolite. Examples include, LC50 467.44 mg/mL of fungal metabolites from Trichoderma longibrachiatum towards the third instar larvae of Aedes aegypti, and LC90 719.07 mg/mL of T. virde towards Ae. Albopictus50. Our future investigations will explore deeper into understanding the specific contributions of active and inactive constituents within ES2, providing valuable insights for refining its application and optimizing its efficacy in pest control strategies."

In conclusion, our current study provides insights into endophytic actinobacterial secondary metabolites as ovicidal and larvicidal activities against a destructive polyphagous pest, S. littoralis. Untargeted metabolomics increases the coverage of the metabolome and introduces a widespread recognition of a multiplatform approach to metabolomics. The untargeted metabolomics and molecular docking studies revealed the mode of action inside the treated S. littoralis eggs and larvae. The data are beneficial to researchers interested in natural product discovery, particularly microbiologists who focus on secondary metabolite biosynthesis from microbial origin and its applications, and the direction of research for the development of industrial microbiology. Furthermore, these data could be shared with entomologists interested in pest control and the implementation of biocontrol protocols to overcome insecticide resistance phenomena. The full chemical profiling of ES2 active constituents and their expected targets is in progress using biological, bioinformatics, and molecular docking studies.

Materials and methods

All chemicals and solvents were purchased from Sigma Aldrich. A commercial pesticide, Biosad® 22.8% SC (Mobedco Co., Jordan), was used in all bioassay investigations as a positive control using its recommended rate (0.1 mL/L). Biosad® 22.8% suspension concentrate, w/v active ingredient Spinosad (A + D), is obtained organically from Saccharopolyspora spinosa fermentation, a naturally occurring soil actinobacterium. All experiments were performed with relevant institutional, national and international guidelines and legislation.

Ethical approval

This work does not contain any studies with human participants but includes studies for insects and all protocols and procedures employed in insect studies were ethically reviewed and approved by the Agriculture Research Center, Plant Protection Research Institute and Suez Canal University's ethical committees. All experiments on tested insects will be conducted according to the guidelines of the Food and Agriculture Organization of the United Nations (FAO).

Endophytic actinobacterium source

The studied actinobacterium strain was previously recovered from the internal tissues of a wild medicinal plant species, Artemisia judaica L. (F. Asteraceae), from the World Heritage Site of Saint Catherine (WHS No. 954), South Sinai, Egypt (33°57΄29.8˝E 28°33΄51.9˝N 1545.34 m)28, and we have previously proven its larvicidal potency29. The strain was provided by the Actinobacteria Laboratory, Suez Canal University, Egypt. The strain was provided as spore suspensions in 20% v/v glycerol (ADWIC, Egypt) at -15 °C and was refreshed on starch casein agar (Sigma‒Aldrich, Germany).

Actinobacterium fermentation and crude secondary metabolite extraction

The studied strain was grown from 2 µL (4–8 × 107 cfu/mL) of spore suspension in 250 mL shake flasks containing 50 mL starch casein broth media and incubated at 28 ± 2 °C for 21 days with continuous shaking at 100 rpm. After complete growth, the broth cultures were centrifuged at 15,000 rpm and filtered to obtain the active crude metabolites. The filtrates were extracted by the liquid–liquid extraction method three times, with absolute ethyl acetate HPLC grade (Sigma‒Aldrich, Germany) equal volumes for 30 min each time. After extraction, the solvent layers were merged and evaporated to dryness using a rotary evaporator (HS-2005S-N, HAHN SHIN Scientific Co., Korea) at 40 °C. The extract was weighed to obtain one gram of the crude metabolite and preserved at 4 °C for the untargeted metabolomics analysis. For the biological assays, the metabolic extract was redissolved in ethyl acetate (Sigma‒Aldrich, Germany) to prepare 200 mg/mL stock concentrations as outlined30.

Cotton leafworm rearing technique

The laboratory strain of S. littoralis used in this trial was established from egg masses collected from an open field in Egyptian habitats and reared for more than 25 generations without being exposed to any insecticide pollution. The strain was maintained under stable circumstances; 26 ± 1 °C and 70 ± 5% R. H. with a light: dark 16:8 h photoperiod. During the larval stage, fresh castor oil plant leaves, Ricinus communis L., were collected daily from the plant protection research institute’s garden in Sharqia Governorate, Egypt, with relevant permission; and introduced daily to feed the larvae. With the end of the larval stage approaching and the beginning of the prepupal period, tissue paper or wet sawdust was placed at the rearing jar base to provide a pupation cradle. Fully developed pupae were gathered and preserved in clean jars until the emergence of the adults. A 10% sugar solution was given to newly emerged moths, sexed, and allowed to lay their eggs on paper stripes. The collected eggs were preserved until hatching in other cleaned jars. From this culture, egg masses and fourth instar larvae were submitted for the bioassay tests31.

In vivo biological assay

To estimate LC50 values of ES2 metabolite on both S. littoralis eggs and larvae, newly molted S. littoralis fourth instar larvae were starved for 4 – 5 h. Fresh castor leaves were collected, cleaned, and cut into equal and identical disks with the help of a cork borer and then impregnated with the corresponding metabolite concentration using a leaf dipping technique assay, as reported31. The toxicity of ES2 metabolites on fourth instar larvae was investigated under laboratory conditions at 25, 50, 100, and 200 mg/mL. Effects of ES2 on the egg stage were investigated under laboratory conditions, at the same above concentrations, using a spraying technique to evaluate their ovicidal activity11. Biosad® 22.8% SC was investigated using concentrations of (0.05, 0.1, and 0.2 mL/L).

Metabolite profiling using LC-QTOF-MS/MS.

LC-QTOF-MS/MS was used to detect the chemical components of crude ES2 metabolites32. The LC-QTOF-MS/MS analysis was performed using a Triple TOF® 5600 + , Sciex (ISO9001), Canada; fused two LC columns, an in-line filter disk precolumn (0.5 µm × 3.0 mm; Phenomenex Co., U.S.A.); and an XBridge C18 column (3.5 µm, 2.1 × 50 mm; Waters Co., U.S.A.) maintained at 40 °C. The sample was injected in the positive TOF–MS mode. Mass spectrometry was performed on a Triple TOF® 5600 + system. MasterView was used for feature (peaks) extraction from the total ion chromatogram (TIC) using PeakView 2.2 Software Sciex based on the following criteria: features should have a signal-to-noise greater than five (untargeted analysis). Untargeted peak finding and clustering were analyzed by MarkerView 1.3 software (Sciex). MarkerView was used for feature annotation and removing isotopic peaks. MasterView was used again to identify peaks based on their fragments using a built-in database (Data Acquisition Analyst TF 1.7.1 software, Sciex) and online databases. The structures of the resulting compounds were drawn using the Reaxys ChemDraw program (version:18.0.0.20) that was accessed through the link (https://08129xwbz-1103-y-https-www-reaxys-com.mplbci.ekb.eg/chemdrawservices/rest).

Biochemical assessments

All biochemical measurements were repeated three times as replicates. A double-beam ultraviolet/visible spectrophotometer (Spectronic 1201, Milton Roy Co., U.S.A.) was used to measure the absorbance of colored substances or metabolic compounds. All enzymatic activities were expressed in enzyme units (EU) per mg protein content.

Sample preparations for biochemical assessments

Healthy individuals of the fourth instar larvae laboratory strain of S. littoralis, which were treated with (LC50, 695 mg/mL) ES2 crude metabolite, in addition to controls (H2O and ethyl acetate solvent) and Biosad® 22.8% SC (LC50, 0.17 mL/L), were picked up after 72 h posttreatment. The collected larvae were transferred to cleaned screw-capped tubes and frozen at −20 °C until examination. Each treated larval group (consisting of five larvae weighing 100—350 mg) was homogenized in distilled water (50 mg/1 mL) using a chilled glass Teflon tissue homogenizer (ST–2 Mechanic-Preczyina, Poland) surrounded with a crushed ice jacket for three minutes. Samples of S. littoralis egg masses, which were treated with (LC50, 165 mg/mL) of ES2 crude metabolite, in addition to controls (H2O and ethyl acetate solvent) and Biosad® 22.8% SC (LC50, 0.033 mL/L), were collected in clean tubes 48 h posttreatment to avoid egg hatching and kept frozen at −20 °C until studied in addition to the controls. The frozen egg mass groups (consisting of nearly 1000 eggs weighing 5–7 mg) were homogenized in phosphate-buffered saline (Sigma‒Aldrich, Germany) to extract the total soluble proteins. The homogenate samples for egg masses and larvae were centrifuged at 8000 rpm for 15 min at 5 °C in a refrigerated microcentrifuge. After the deposits were cleared away, the supernatants—also known as enzyme extracts—were put into cleaned screw-capped tubes and frozen at −20 °C until they were needed for biochemical tests. based on Ismail’s method with modifications33.

Total soluble protein assessment

The total protein concentration was determined according to Bradford’s method34. Bovine serum albumin (Stanbio Laboratory, Texas, U.S.A.) was used to convert to mg/mL as the standard. The absorbance of the samples was measured at 595 nm using a microplate reader.

Nonspecific esterase determination

Alpha esterases (α–esterases, EC 3.1.1.1) and beta esterases (β–esterases, EC 3.1.1.2) were determined for the treated S. littoralis fourth instar larvae35 using α–naphthyl acetate or β–naphthyl acetate as substrates. The samples were measured at 600 and 555 nm absorbance for α- and β–naphthol, respectively. The activity was expressed as[µg naphthol/min/mg protein].

Polyphenol oxidase (PPO, EC 1.10.3.1) determination

Polyphenol oxidase (PPO) activity was measured for the treated S. littoralis eggs using a colorimetric assay as declared by Ishaaya36, with minor modifications, based on the oxidation of catechol solution (2%) as a substrate. The absorbance of the samples was measured at 405 nm against a blank. The activity was expressed as [m ∆ O.D./min/mg protein].

Catalase enzyme (CAT, EC 1.11.1.6) determination

Catalase enzyme (CAT) activity was measured for the treated S. littoralis eggs using a spectrophotometric assay, using Biodiagnostic Kit No. SD 2517, which is based on the decomposition of hydrogen peroxide (H2O2) by CAT, resulting in a decrease in absorbance37. The absorbance of the samples was measured at 510 nm against a blank. The activity was expressed as [mU/mg protein].

Molecular docking simulation

Molecular docking simulation is a computational technique aimed at predicting the binding mode and affinity of a small molecule (ligand) to a target protein. It involves the calculation of the energetics and geometry of the interaction between the ligand and the protein. The technique involves the use of computer algorithms to predict and identify the most energetically favorable binding mode of a small molecule to a target protein, which can then be further optimized and tested in vitro and in vivo. Molecular docking illustrates the virtual mechanism of binding of selected compounds polyphenol oxidase (PPO, PDB = 3HHS), and catalase (CAT, PDB = 2A9E) target proteins. The data were freely accessible through the protein data bank. Both proteins and ligands were optimized, and the molecular docking study was carried out using AutoDock Vina as the computational software38. Each complex was analyzed for 3D interaction images taken by Chimera (UCSF)39.

Statistical data analysis

All extractions and determinations were conducted in triplicate, and the results were expressed based on dry weight (DW). Data are expressed as the mean value (n = 3) ± standard error of the mean (SE). The LC50 values were calculated by linear regression analysis. Pearson’s correlation coefficients were computed between secondary metabolites and biocide activity. Normality testing was performed, using Shapiro–Wilk and Kolmogorov–Smirnov at 0.05 level, for detecting parametric and nonparametric variables. The parametric variables included: total protein, α– and β–esterase, and catalase. Phenol oxidases data was nonparametric, and it was represented in a parametric form for better presentation of mean and standard deviation (Supplementary Table S2). Differences between groups were performed using one-way ANOVA and ANOVA followed by Duncan’s Multiple Range Test (DMRTs) to further check the differences between groups. All statistical analyses were performed with the SPSS statistical software program (version 29.0 of Mac OS, SPSS Inc., Chicago, IL, U.S.A.). We performed a probit analysis of the data using MINITAB version 17.1 and the maximum likelihood method to evaluate the distribution fit of the data and the significant effects of ES2 as ovicidal and larvicidal activities. A scheme of the research steps is illustrated (Fig. 3).

Figure 3
figure 3

Schematic flowchart illustrating the research steps of the current study.

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