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Abstract

Background

The growing threat of drug-resistant bacterial infections demands the discovery of bioactive compounds from natural sources. This study explored the chemical diversity generated through the cocultivation of two fungal strains, Aspergillus pseudocaelatus and Trichoderma gamsii, isolated from the rhizospheres of medicinal plants.

Methods

Co-culture fermentation on rice medium was employed to induce unique hybrid metabolites alongside other bioactive metabolites. LC-QTOF/MS metabolomic profiling combined with molecular network-based dereplication identified terpene–amino acid conjugates, while genome mining revealed biosynthetic potential.

Results

Time-course experiments demonstrated that prolonged incubation enhanced metabolite yields, with coculture significantly increasing secondary metabolite production versus monocultures. Chromatographic isolation and spectroscopic characterization yielded two terpene–amino acid hybrids (1 and 2), one organic acid (3), and one polyketide (4), with structures elucidated through 1D/2D NMR and HRMS analysis. Compound 1 exhibited antibacterial inhibition of 48.9%, 48.1%, and 27.9% against Staphylococcus aureus, Bacillus subtilis, and E. coli, respectively. Compound 2 showed 44.2% and 33.7% inhibition against S. aureus and B. subtilis, while compound 4 demonstrated 43.1%, 29.8%, and 22.8% inhibition against the same pathogens at 100 μg/mL.

Conclusion

These findings underscore the value of microbial interactions in activating cryptic biosynthetic pathways and expanding the chemical space accessible from microbial sources. This work contributes to the growing field of microbial natural product discovery by demonstrating that fungal‒fungal interactions can be strategically leveraged to access active molecules with promising bioactivities, supporting ongoing efforts to address the global challenge of antibiotic resistance.

Keywords

microbial crosstalk mixed culture LC‒MS hybrid metabolites terpenes

Introduction

Bacterial infections caused by multidrug-resistant (MDR) pathogens are a growing global health threat, driving the search for novel antimicrobials from natural sources.¹ Bacterial infections contribute to an altered immune state characterized by chronic low-grade inflammation, immune dysregulation, and disrupt the balance of the gut microbiome (dysbiosis), potentially contributing to inflammation and metabolic dysfunction.^2,3 This compromised immune environment increases susceptibility to infections, including those caused by MDR pathogens.

Fungal secondary metabolites have long been a rich source of antibiotics, and cocultivation strategies have emerged as powerful tools to activate otherwise silent biosynthetic pathways.⁴ Microbial natural compounds play essential roles in cell signaling, crosstalk, defense, and microbial evolution. They facilitate interactions among microorganisms within communities and with their abiotic environment elements.^5,6 Owing to their remarkable structural and functional diversity, these compounds serve as ideal sources for developing therapeutic drugs, antimicrobial agents, and other bioactive agents.⁷ While the structures and biosynthetic pathways of these compounds are often well characterized, microbes typically exist in complex microbiomes, where chemical signaling can be influenced by community-specific dynamics and modifications. These powerful chemical and biological factors help elucidate this poorly understood aspect of microbial chemical development.⁶

Hybrid metabolites are compounds that originate from diverse biosynthetic pathways and are subsequently joined through a conjugation process, increasing their chemical diversity and biological activity. Among these compounds, terpene-amino acids and meroterpenoids have attracted attention in recent years, driven by the discovery of notable examples such as the anthelmintic CJ-12662, the insecticidal paeciloxazine, and aculene A. In the biosynthesis of these hybrid metabolites, single-module nonribosomal peptide synthetases (NRPSs) play a key role in the esterification step, facilitating the fusion of modified terpene backbones and amino acid-derived moieties.⁸ The clear chemical benefit of combining terpene and amino acid biosynthesis is the enrichment of compounds with nitrogen atoms, which are rare among hydrocarbon-derived terpenoids.⁹

The aim of this study stems from the need to discover natural resources capable of producing compounds effective against drug-resistant bacteria. Here, we developed a coculturing process for two fungal strains to screen their potential for the production of diverse compounds. This was achieved through metabolomic screening of fungal extracts via an in-house established library of microbial hybrid metabolites. Two terpene-conjugated amino acids were isolated and evaluated for their antibacterial activity.

Experimental

General Experimental Procedures

LC/MS grade reagents and solvents were used. Acetonitrile, methanol, and formic acid were purchased from Wako Pure Chemicals Ltd (Osaka, Japan). Ultrapure water was produced via a Milli-Q integral system equipped with a 0.22-μm point-of-use membrane filter cartridge (EMD Millipore, Billerica, MA, USA). HPLC analysis was carried out via the Agilent 1260-LC system equipped by DAD detector (Agilent Technologies). HR-ESI-MS data for compounds were recorded on a quadrupole time-of-flight mass spectrometer (Agilent QTOF-LC-MS, Agilent Technologies, USA). A JNM-ECS400 spectrometer (JEOL, Tokyo, Japan) or Bruker Avance 600 MHz (Bruker, Germany) was used to record 1D (¹H and ¹³C NMR) and 2D NMR (HSQC, HMBC, COSY) experiments using CD₃OD or DMSO-d₆ as solvents. Chemical shifts (δ) were expressed as parts per million (ppm).

Microbial Materials and Fermentation

The fungal strains Aspergillus pseudocaelatus (MG772677) and Trichoderma gamsii (KX685665) were recovered from the rhizosphere areas of the medicinal plants Aloe vera and Ocimum basilicum, respectively, their antimicrobial activity and genomic richness made these strains particularly promising candidates for cocultivation-based natural product discovery, according to.^10,11 The culture and morphological of fungal characterizations were done according to their macro and microscopic characteristics and compared with species characteristics of the standard taxonomic guidelines to identify the fungal genera and species as well as genetic analysis based on 18S rDNA.^10,11 Rhizopus sp. was recovered from the rhizosphere of Japanese cypress (Chamaecyparis obtusa). The strains were maintained on the surface of potato dextrose medium (PDA) slants at 4 °C. The bacterial strain Bacillus subtilis ATCC 6633 was obtained from the American Type Culture Collection and maintained on the surface of nutrient agar medium (NA) slants at 4 °C.

Genome Mining of Microbial Genera

Available genomes of the fungal strains Aspergillus pseudocaelatus (A), Trichoderma gamsii (T), and Rhizopus sp. (R). In addition, the bacterial strain Bacillus subtili (B) was obtained from the database of the National Center for Biotechnology Information (NCBI) (https://www.ncbi.nlm.nih.gov/). Genome mining was conducted via antiSMASH software version 8.0. (https://antismash.secondaryspecializedmetabolites.org/) to identify the gene putatively encoding the biosynthesis of specialized metabolites.¹²

Cocultivation and Extraction Process

Seed culture of each strain was prepared on PDA medium incubated for 7 days at 28 °C in static conditions. For co-culture fermentation, two 6 mm diameter discs of each strain was applied to an autoclaved flask containing 2.5 g of rice in 50 mL of water with ratio 1:1 of inoculum. For mono- and mixed cultures, three biological replicates of each condition were incubated until the desired period. The yield was then harvested after 0, 7, 14, 21 and 28 days of incubation at 28 °C by adding 100 mL of ethyl acetate, sonicated for 30 min, extracted three times, and then concentrated under vacuum.¹⁰

Extraction and Isolation of Compounds

The large-scale fermentation of (A) and (T) for 28 days yielded 8 g of the EtOAc extract, which was subjected to chromatographic fractionation via Biotage equipped with flash column chromatography (Biotage Selekt, Sfär HC Duo column, 30 μm, 50 g) and eluted with n-hexane containing increasing proportions of EtOAc and MeOH to obtain 14 fractions (Fr1-14). Further purification steps were applied, as shown in Figure 1, to obtain four pure compounds (1- 4).

Figure 1.

Isolation of compounds 1-4 from the ethyl acetate extract of AT.

LC-QTOF/MS Profiling

The microbial extracts were analyzed via an Agilent 1290 UHPLC system coupled with an Agilent G6545 hybrid Q-TOF/MS system. Chromatographic separation was performed via an Agilent 2.1 × 100 mm C18 Poroshell column at 40 °C with a flow rate of 0.2 mL/min. The gradient of the mobile phase was A: 0.1% formic acid in H₂O and B: 0.1% formic acid in ACN starting from 5%-9% B from 1-4 min. The gradient increased to 50% B in 2 min. from 50%-70% in 9 min. This was followed by increasing from 70%-95% in 1 min and holding for 4 min. Finally, the gradient was returned to 5% B in 4 min. For each sample, 2 μL of a 1 mg/mL mixture was injected. The dual ESI source was adjusted under the following conditions: nebulizer gas pressure: 50 psi; drying gas flow rate: 12 L/min; drying gas temperature: 300 °C; and sheath gas flow rate: 11 L/min with a sheath gas temperature of 350 °C. For the parameters of the scan sources, Vcap was set at 3500 V in positive mode, the skimmer voltage was adjusted to 65 V, the octopole voltage was 750 V, and the fragmentor voltage was 130 V. The data were collected in both centroid and profile modes in the extended dynamic range (2 GHz). Calibration and tuning of the instrument were performed following procedures recommended by the manufacturer. Accurate mass spectra were obtained in the m/z range of 100-1700, and all ion MS/MS acquisition was applied with 5 scans/sec. The desired mass accuracy of the recorded ions was confirmed via continuous internal calibration during analysis with reference solution signals at m/z 121.0509 (protonated purine) and 922.0098 (protonated hexakis [1H, 1H, 3H-tetrafluoropropoxy]) in positive mode.¹³ For structure elucidation, MS/MS spectra were predicted via CFM-ID 4.0 and compared with the experimental MS/MS spectra.

Data Analysis of the Mass Profile

MassHunter Proﬁnder software B.10.00 with recursive molecular feature extraction (rMFE) was used for nontarget screening. In rMFE, all ions with similar elution proﬁles and m/z values were extracted as molecular features (MFs). For peak picking, the MS1 and MS2 tolerances were set to 0.03 and 0.1 Da, respectively, in centroid mode for each dataset. The data between 0.5 and 24 min were collected within the mass range of 100-1700 m/z. The extracted data were exported in Files in compound exchange (.cef format) for further analysis via the Agilent Mass Proﬁler Professional (MPP) software package (version 15.1) (Agilent Technologies, Santa Clara, CA, USA) for further processing of the differential analysis, and the CSV file format was exported to MetaboAnalyst 5.0 for visualization and statistical analysis.¹⁰

Molecular Network-Based Analysis

Tandem mass spectrometry molecular networks were created via the GNPS platform (http://gnps.ucsd.edu). The data (.d) were converted to the .mzML format with MS-Convert. The converted files were used to generate an MS/MS molecular network via the GNPS data analysis workflow version release 30. The precursor and fragment ion mass tolerances were set to 0.02 Da, and the product ion tolerance was 0.02 Da. Networks were generated using six minimum matched ion fragments, a minimum cluster size of 2 and a cosine score of 0.7. The remaining parameters were kept at default values. The library spectra were filtered in the same manner as the input data. All matches kept between network spectra and library spectra were required to have a score above 0.7 and at least 6 matched peaks.¹⁴

Antimicrobial Evaluation

The isolated compounds were prepared at a concentration of 100 µg/mL via nutrient broth dilution methods¹⁵ for their antimicrobial efficacy against Gram-positive bacteria (Bacillus subtilis ATCC 6633 and Staphylococcus aureus ATCC25923) and Gram-negative bacteria (Escherichia coli JCM 1649). Bacterial strains were obtained from ATCC or Japan collection of microorganisms (JCM) and maintained on the surface of nutrient agar medium (NA) slants at 4 °C. The bacterial inoculum was standardized to 1 × 10⁵ CFU·mL⁻¹. Each well of a 96-well plate was filled with 5 µL and then 100 µL of nutrient broth media inoculated with 1 × 10⁵ CFU·mL⁻¹ bacterial strains in triplicate and added to each well. The plates were incubated at 37 °C for 18 h under static conditions. Sorbic acid was used as a positive control at a concentration of 100 μg/mL.¹⁶ DMSO was used as a negative control. After the incubation period, the optical density was measured via a plate reader (BioTek Synergy HTX Multimode Reader) at OD₆₀₀. The percent inhibition was calculated as follows:

\begin{aligned} I n h i b i t i o n % = O D_{600} [(B a c t e r i a l o n l y - S a m p l e) / B a c t e r i a l o n l y] \times 100 \end{aligned}

Results

Microbial Coculture Combinations

Different combinations of coculturing experiments were designed to investigate the power of coculturing strategy for quantitative and qualitative enhancement of metabolite yield as shown in Figure 2 and Figures S1-7. The dual interaction after 4 weeks of incubation increased the yield of the extract and the pairwise fungal-fungal interactions, especially those of Trichoderma (T) and Aspergillus (A), followed by interactions with Rhizopus (R) and then interactions with Bacillus bacteria. The yields produced via pairwise interactions were greater than those produced via monoculture.

Figure 2.

The metabolite yields of pairwise interactions between Trichoderma (T) and Aspergillus (A), Rhizopus (R) and Bacillus (B) bacteria after 28 days of interaction.

Metabolite Yield of Time-Dependent Fungal Cocultures

The total yield of metabolites increased gradually with increasing fermentation time; the fungal dual interaction improved the productivity of secondary metabolites, as shown in Figure 3. The metabolites yield of AT interaction elevated from 11.2 mg to 81.7 mg for 7 and 28 days of incubation, respectively. The same pattern for monoculture of Trichoderma (T) and Aspergillus (A) was observed. The yield of coculture of AT was higher than the yield of Trichoderma (T) and Aspergillus (A) in monoculture conditions.

Figure 3.

Metabolite yield of the interaction between Trichoderma (T) and Aspergillus (A) during different incubation periods (0-28 days).

Isolation and Identification

The cocultivation of (A) and (T) for 28 days on rice media extracted three times with ethyl acetate which produced 8 g. as shown in Figure 4 after vacuum drying as shown in Figure 4. The chemical investigation guided by molecular network analysis of the (AT) extract led to the isolation of two hybrid metabolites, namely, terpene-amino acid residue compounds (1, 2) and one organic acid and one polyketide (3-4). These isolated compounds were identified by detailed spectroscopic analysis and by comparison with data previously reported in the literature.

Figure 4.

Microbial culture and extracts of Aspergillus (A), Trichoderma (T), and pairwise (AT) fungi at 0 and 28 days of interaction.

Determination of Isolated Compounds

Talaroconvolutin A (1) was isolated as a yellow oil. The molecular formula was confirmed by HRMS to be C₃₂H₄₁NO₃ based on the molecular ion peak at m/z 488.3177 [M + H]⁺ (calcd. 488.3156). The structure was identified by detailed spectroscopic analysis as shown in Figures S8-14 and by comparison with data previously reported in the literature^17,18 as shown in Table S1. The planar structure of 1 was confirmed from detailed analyses NMR spectra. The ¹³C NMR signals at δ_C 197.1 were assigned to the ketone carbonyl carbon (C-13), and those at δ 170.5 (C-2) were assigned to the carbonyl of the amide moiety, which is characteristic of amino acid conjugation. The δ_C 159.3 (C-10) and 145.6 (C-4) signals suggest a substituted aromatic ring system, and the δ_C 136.5 (C-25), 136.1 (C-17), 132.6 (C-24), 132.0 (C-8, 12), 131.3 (C-5), 130.2 (C-3), 130.0 (C-16), 125.7 (C-7), and 122.5 (C-6) signals revealed multiple sp² carbons, indicating extensive conjugation and aromatic substitution. Three α-carbon signals were detected at δ_C 51.1, 49.3, and 48.4 and assigned for C-15, 14, and 18, respectively. The signals at δ_C 40.1 (C-22) and 11.12 (C-28) were assigned to the terpene backbone and side chains. ¹H NMR (400 MHz, CD₃OD) revealed signals at δ_H 8.23 (s, 1H, NH), 7.73 (d, J = 2.0 Hz, 1H), 7.52-7.44 (d, J = 8.7 Hz, 2H), 6.90-6.79 (d, J = 8.7 Hz, 2H), 6.48 (s, 1H), 5.37 (s, 1H), 4.70 (d, J = 9.6 Hz, 1H), 3.93 (dd, J = 12.4, 7.7 Hz, 1H), 3.20 (d, J = 7.7 Hz, 1H), 2.11 (m, 1H), 1.82-1.77 (m, 1H), 1.68 (m, 1H), 1.49 (s, 3H), 1.42 (s, 3H), 1.05-0.97 (m, 3H), 0.93 (m, 3H), 0.92 (s, 3H), 0.85 (d, J = 6.1 Hz, 3H), 0.75 (t, J = 7.4 Hz, 3H), 0.68 (d, J = 6.6 Hz, 3H), which correlated with the ¹³C NMR data.

Berkedrimane A (2) was produced from the coculturing of Aspergillus pseudocaelatus MG772677 and Trichoderma gamsii KX685665 on rice media. Compound (2) was isolated as a colorless oily. The molecular formula was determined to be C₂₂H₃₃NO₅ on the basis of HRMS of molecular ion peak at 392.2439 [M + H]⁺, (calcd. 392.2431) indicated seven degrees of unsaturation. The structure of compound (2) was determined on the basis of spectroscopic data, as 22 carbon signals were detected. The ¹³C NMR spectrum revealed three ester and amide carbonyl carbons (δ_C 172.3, 170.6, 168.9), a trisubstituted double bond (δ_C 135.7, 126.9), two oxygenated carbons (δ_C 74.5, 67.0), a nitrogen-bearing carbon (δ_C 59.4), four quaternary carbons (δ_C 37.5, 32.2), three methine carbons (δ_C 44.3, 42.7, 32.0), three methylene carbons (δ_C 34.6, 24.7, 22.3), and six methyl carbons (δ_C 32.0, 20.7, 20.3, 18.2, 17.3, 12.2). ¹H NMR (600 MHz, CD₃OD) δ 0.91 (s, 3H, H-15) 1.02 (s, 3H, H-13) 0.96 (s, 3H, H-14) 1.01, 0.93 (d, J = 6.8 and 6.9 Hz, 6H, H-4′,5′), 1.31, (dt, J = 12.0, 3.3 Hz, H-3) 1.72(dd, J = 11.0, 6.5 Hz, H-4), 3.26 (m, 1H, H-9) 4.28 (t, J = 9.2, 1H, H-11) 4.81 (m, 1H, H-1) 4.52 (m, 1H, H-2′), 2.01(s, Ac), 2.23 (m, 1H, H-3′), 5.17 (d, J = 8.6 Hz, 1H, NH) 6.85 (q, J = 3.5 Hz, 1H, H-7). The presence of an N-acetyl valine residue was established by ¹H–¹H COSY, which identified the NH–CH–CH–CH3 spin system, and by HMBC correlations from both the NH and the methyl singlet (H3-2’) to the carbonyl carbon (C1’, δ_C 172.3), as well as from the NH and the methyl singlet (H3-2'’) to the carbonyl carbon (C1'’, δ_C 170.6). The structure of compound (2) was determined on the basis of spectroscopic data as presented in Figures S15-21, with comparison with the NMR data of reported berkedrimane A¹⁹ as shown in Table S2.

Compound 3 was separated as a white solid. Its molecular formula was assigned to be C₁₇H₂₈O₆ based on the observed signal at m/z 329.1926 [M + H)⁺, (calcd. 329.1958) together with 1D NMR data indicating four degrees of unsaturation as shown in Figures S22-24. The ¹³CNMR data showed a characteristic pattern of dicarboxylic acid with γ-lactone ring with peaks at (δ_C 178.1, 176.8, and 171.5), one quaternary carbon (δ_C 87.0) and one methine carbon (δ_C 52.1). Additionally, a cluster of methylene carbons at carbons (δ_C 31.7-22.3), and one terminal methyl carbon (δ_C 13.0). The ¹H NMR (400 MHz, CD₃OD) spectrum of compound (3) exhibited signals characteristic of one methine proton at δ_H 2.97 (dd, J = 8.7, 2.7 Hz, H-5), three methylene groups at δ_H 2.53-2.46 (m, H₂-2 and H₂-3), one triplet methyl moiety at δ_H 0.87 (t, J = 6.9 Hz, H3-15)1.91-1.19 (multiplet, H₂-6-H₂-14). These spectroscopic features were consistent with those reported for spiculisporic acid in the literature^20,21 as shown in Table S3.

Phomaligol A (4) was isolated as a colorless oil with a molecular formula of C₁₄H₂₀O₆ based on the detected m/z 285.1348 [M + H]⁺, (calcd for 285.1332). HR-MS data together NMR data^22–24 indicating five degrees of unsaturation as shown in Figures S25-30. The ¹³C NMR spectrum indicated the presence of six quaternary carbons including; three carbonyl carbons, two of them were ketones and observed at δ_C 204.1 (C-1) and 192.6 ppm(C-5) and ester group (δ_C 175.5 ppm (C-7), and two quaternary carbons bound to oxygen at 74.2 and 82.6 ppm(C-2 and C-6) respectively. Additionally, one methylene carbon at 40.0 ppm (C-8), two methine carbons at 98.8 and 174.9 (C-4 and C-3) and four methyl groups at 10.3, 16.0, 25.3 and 22.2 ppm (C-10,11,13,14) respectively. The ¹HNMR (600 MHz, CD₃OD) spectra revealed 5.64 (1H, s, H-4), 3.73 (3H, s, H-12), 2.47 (1H, m, H-8), 1.71 (1H, m, H-9), 1.63 (3H, s, H-14), 1.66 (3H, s, H-13), 1.16 (3H, d, J = 7.0 Hz, H-11), 0.97 (3H, t, J = 7.5 Hz, H-10). The spin system of a second butyl group of 9 protons and five signals for eleven protons representing two methyl groups at δ_H 0.97-1.16 ppm, OMe group at δ_H 3.73 as well two methyl appeared at 1.66, 1.63, a methylene at δ_H 2.47 and a methine proton at 5.5 ppm. Theses spectroscopic characteristics in addition to the comparison with reported literature^22–24 revealed its structure as Phomaligol A 4, as shown in Figure 5 and 6 and Table S4.

Figure 5.

Chemical structures of the isolated compounds (1-4).

Figure 6.

Total ion chromatograms of A, T, and AT interactions.

Molecular Network Analysis

The molecular network of AT interactions constructed via GNPS included 1229 nodes connected with 1318 edges forming 35 clusters, as shown in supplementary data Figure S31. The second large cluster consisted of 21 nodes, including the node with a molecular weight of 231.138, which represents a building block unit of C₁₅H₁₉O₂ for the hybrid molecule of drimane sesquiterpenoids conjugated with amino acid residues as shown in Figure 7. The propagation identification of this cluster resulted in the identification of five hybrid molecules, berkedrimanes A and B, and purpurides B and F in addition to minioluteumides A. The MS/MS fragmentation patterns of these molecules are presented in Figures 8 –14 and Table 1.

Figure 7.

Metabolic network cluster of hybrid metabolites produced by AT interactions.

Figure 8.

MS/MS fragmentation spectrum of talaroconvolutin A.

Figure 9.

MS/MS fragmentation spectrum of berkedrimanes A.

Figure 10.

MS/MS fragmentation spectrum of purpuride B.

Figure 11.

MS/MS fragmentation spectrum of talaminoid B.

Figure 12.

MS/MS fragmentation spectrum of minioluteumides A.

Figure 13.

MS/MS fragmentation spectrum of berkedrimanes B.

Figure 14.

MS/MS fragmentation spectrum of purpuride F.

Table 1.

Tentative Identification of Other Hybrid Molecules in AT Interaction.

Compounds	Adducts	Calculated Mass	RT	Formula	Observed Mass	Δ mass (ppm)
Berkedrimanes B	[M + H]⁺ [M + Na]⁺	407.2311	11.05	C₂₂H₃₃NO₆	408.2395; 430.2203	0.74
Talaminoid B	[M + H]⁺ [M + Na]⁺	479.2857	11.73	C₂₆H₄₁NO₇	480.2960; 502.2727	−5.53
Purpuride F	[M + H]^+, [M + Na]⁺	421.2465	11.92	C₂₃H₃₅NO₆	422.2549; 444.2359	0.18
Minioluteumides A	[M + H]⁺, [M + Na]⁺	425.1978	12.23	C₂₂H₃₂ClNO₅	426.2043; 448.1873	2.11
Purpurides B	[M + H]⁺, [M + Na]⁺	389.2202	12.29	C₂₂H₃₁NO₅	390.2282; 412.2095	−0.18

The relative quantification of detected hybrid metabolites was calculated based on the relative peak area of 1 mg of EtOAc extract. The berkedrimanes B represented the highest abundance in the profile of AT interaction followed by berkedrimanes B, then purpuride F then talaroconvolutin A, as shown in Figure 15.

Figure 15.

Relative abundance of compounds in clusters associated with AT interactions. Relative peak area/1 mg extract weight-averaged abundance calculated from three biological replicates (n=3 ± standard error).

Biological Activity

The antimicrobial potential of the isolated compounds 1, 2, 4 was assessed. While compound 3 (spiculisporic acid) a well-characterized biosurfactant with extensively documented antimicrobial properties against pathogenic bacteria, was not tested as its bioactivity profile has been comprehensively reported in previous studies. The antibacterial activities of compound 1 were 48.9, 48.1 and 27.9% against Staphylococcus aureus, Bacillus subtilis and E. coli, respectively. Compound 2 exhibited moderate antibacterial efficacy, with inhibition percentages of 44.2, 33.7 and 23.3 against Staphylococcus aureus, Bacillus subtilis and E. coli, respectively. While compound 4 showed antibacterial activity with inhibition percentage 43.1, 29.8 and 22.8 against Staphylococcus aureus, Bacillus subtilis and E. coli, respectively as indicated in Figure 16.

Figure 16.

Antibacterial efficacy of isolated compounds (1, 2 and 4) at a concentration of 100 μg/mL. Sorbic acid at a concentration of 100 μg/mL was used as a positive control (PC), which was calculated from three biological replicates (n=3 ± standard deviation).

Discussion

Metabolite Yield Enhancement During Microbial Co-Culturing

Microbial co-culturing is a powerful strategy to enhance metabolite yield and diversity. Nonaka et al²⁵ reported that cocultivation of Penicillium pinophilum FKI-5653 with Trichoderma harzianum FKI-5655 led to a remarkable increase in the production of Secopenicillide C. The yield increased from 23.2 mg·L^-1 in monoculture to 87.4 mg·L^-1 under coculture conditions, representing a 3.7-fold improvement. This increase is due to the significant impact of fungal–fungal interactions on the activation and upregulation of secondary metabolite biosynthesis-related gene clusters. Wu et al²⁶ demonstrated that, compared with monoculture conditions with a 1:1 inoculation ratio, coculturing Bacillus amyloliquefaciens and Trichoderma asperellum significantly increased the production of antibacterial compounds, further increasing specific amino acid yields. Zohair et al¹⁰ found that cross interaction between bacteria and fungi, coculturing between Trichoderma and Bacillus produced 18 unique chemical features relative to monoculture and coculture of Aspergillus and /or Bacillus. Coculturing is a powerful strategy for activating silent biosynthetic gene clusters (BGCs) that remain unexpressed under standard laboratory conditions. In natural environments, microbes constantly interact, and these interspecies interactions can serve as cues to trigger the expression of cryptic or silent gene clusters, leading to the production of novel secondary metabolites²⁷ or improve the yield of sepcific products. Metabolomic profiling revealed several additional hybrid metabolites, including Berkedrimanes B, Talaminoid B, Purpuride F, and Minioluteumides A. While these compounds represent promising targets for future investigation, their isolation was hindered by challenges including structural similarity leading to chromatographic separation difficulty, and the prioritization of resources toward obtaining comprehensive structural and biological data for representative compound classes. Nevertheless, the detection of this diverse array of hybrid metabolites underscores the chemical richness activated through fungal cocultivation and validates the approach as a strategy for accessing rare natural product scaffolds.

Effect of Genetic Material and Species Selection

Zohair et al¹⁰ revealed that genome analysis of Aspergillus sequence contained 95 regions of biosynthesis-related gene clusters (BCGs) expressed for a diverse range of chemical classes, including T1PKs, T3PKs, 28 regions of terpenes, indoles, NRPs, RiPP-like metabolites, and fungal RiPPs. Genome analysis of Trichoderma revealed 41 regions for the BCGs of T1PKs, terpenes, and NRPs, whereas the Bacillus bacterial genome included 14 BCGs for glycocin, epipeptide, T3PKs, and NRPs. The genome of Rhizopus includes 16 genomic regions, including four terpene-precursor regions, seven terpene regions, three NRPS-like regions, betalactone regions, and fungal-RiPP and NI-siderophore regions as shown in supplementary data (Figure S32). The unique BGCs present in the genomes of each microorganism govern their potential to produce secondary metabolites. In coculture, genetic factors not only control a microbe's inherent metabolite profile but also determine responsiveness to cocultivation signals. Some gene clusters remain silent in monocultures but are activated through interspecies interactions either via competitive, cooperative, or signaling pathways.²⁸ Different microbial combinations can elicit the production of distinct classes of metabolites, trigger mutually induced biosynthesis, cross-biotransformation, and, in rare cases, horizontal gene transfer of metabolic capabilities.²⁹ In our study we found that, the combination with different microbial species affected the production of hybrid metabolites. The detected hybrid molecule production was specific to such microbial species. As shown in Figure S33.

Chemical Importance of Hybrid Metabolites

Terpene–amino acid conjugates represent an exceptionally rare class of natural products, with only limited examples reported in the literature. This study reports the first isolation of two hybrid terpene through a cocultivation approach and their first detection from the A. pseudocaelatus–T. gamsii interaction. Notably, these metabolites were absent in monoculture fermentations, indicating that interspecies communication specifically activates their biosynthesis. Drimane sesquiterpenoids conjugated with an N-acetyl-L-valine group are rare compounds in nature that are produced by Penicillium spp,^13,30 and few such hybrid natural compounds have been detected thus far. The first examples of these hybrid compounds were purpuride, reported from Penicillium purpurogenum in 1973,³¹ and the others included berkedrimanes A and B from P. solitum,³¹ purpurides B–D from P. purpurogenum JS03-21³² and P. sp. ZZ1283,³³ and minioluteumides A–D from P. minioluteus PILE 14-5.¹³ Berkedrimanes A and B inhibit the signal transduction enzymes caspase-1 and caspase-3 and reduce the production of interleukin-1β.³¹ Berkedrimane B, purpuride, and purpurides B–D were found to have antifungal activities against Candida albicans. Purpurides B–D also have antibacterial activities.^32,33 The clear chemical importance of integration of terpene and amino acid biosynthesis is enrichment of molecules with nitrogen atoms, which are rare among hydrocarbon-derived terpenoids.³⁴

The Diverse Chemical Structures of Hybrid Metabolites and Their Biological Efficacy

Hybrid metabolites exhibit remarkable chemical diversity, arising from the merging or modification of biosynthetic pathways of distinct organisms or molecular scaffolds. This diversity is reflected in their structural motifs, which may combine features from multiple parent compounds.³⁵ Compound 1 features a terpenoid core conjugated with an aromatic amino acid-derived moiety that facilitates interaction with bacterial cell membranes, potentially disrupting membrane integrity and increasing permeability, which is a common antibacterial mechanism for terpenoid compounds.³⁶ The carbonyl groups can participate in hydrogen bonding or act as electrophilic centers, interacting with nucleophilic sites in bacterial proteins. Additionally, the presence of a free phenolic OH can enhance antibacterial activity through hydrogen bonding with bacterial proteins.³⁷ Compound 2 has a drimane-type sesquiterpene core conjugated to an N-acetyl valine residue via an amide linkage. The fuzed bicyclic ring system (C1–C14) with multiple methyl groups (C13, C14) and a ketone at C8 provides hydrophobic characteristics. This hydrophobicity facilitates the insertion into and disruption of bacterial membranes. Additionally, the side chain (C1'–C5’, C1'’, C2'’) is derived from the amino acid valine, which is acetylated at the N-terminus. The amide linkage (between C2 and C1’) increases molecular rigidity and may enhance binding affinity to bacterial enzymes by mimicking peptide substrates. The presence of three carbonyl groups (at C8, C12, and C1’) introduces electrophilic centers capable of forming hydrogen bonds or interacting with nucleophilic residues in bacterial proteins, potentially inhibiting their function. In the same way, the NH group and carbonyls provide sites for hydrogen bonding, which can facilitate specific interactions with bacterial targets as shown in Figure 17.

Figure 17.

Structure–activity relationships of compounds (1-3).

The cocultivation strategy represents a promising approach for the discovery of hybrid metabolites and bioactive compounds. However, several limitations require further investigation. Chromatographic challenges arising from structural similarities prevented the complete isolation of all tentatively identified hybrid metabolites. Moreover, the molecular mechanisms underlying metabolite induction—including specific chemical signals, transcriptional networks, and the responsible biosynthetic gene clusters—remain uncharacterized. Finally, the biosynthetic origin of the hybrid compounds, whether from a single organism or through metabolic cooperation, has not been definitively established. Despite these constraints, this work validates cocultivation as a viable strategy for accessing rare bioactive natural products and provides valuable direction for future mechanistic and translational studies.

Conclusion

This study establishes fungal cocultivation as an effective strategy for discovery secondary metabolites through activation of silent biosynthetic gene clusters. The interspecies interaction between Aspergillus pseudocaelatus and Trichoderma gamsii induced structurally unique terpene-amino acid conjugates, demonstrating that microbial competition triggers chemical diversity. The moderate-to-strong antibacterial activities observed against Staphylococcus aureus and Bacillus subtilis highlight the therapeutic potential of these hybrid scaffolds, particularly given their selectivity toward Gram-positive pathogens a feature valuable for targeted antimicrobial development. By systematically leveraging fungal–fungal interactions guided by metabolomic analysis, and genome mining techniques, this strategy offers a promising avenue for discovering antimicrobial scaffolds needed to address the global challenge of drug-resistant infections.

Supplemental Material

sj-docx-1-npx-10.1177_1934578X251405381 - Supplemental material for Fungal–Fungal Cocultivation Unveils Bioactive Metabolites, Including Rare Terpene–Amino Acid Hybrids, with Antibacterial Activity

Supplemental material, sj-docx-1-npx-10.1177_1934578X251405381 for Fungal–Fungal Cocultivation Unveils Bioactive Metabolites, Including Rare Terpene–Amino Acid Hybrids, with Antibacterial Activity by Moustafa M Zohair, Ahmed H El-Desoky, Fahd M Abdelkarem, Yhiya Amen, Ahmed A El-Beih and Kuniyoshi Shimizu in Natural Product Communications

Footnotes

Acknowledgments

The first author (M.Z.) is funded by a full scholarship from the Ministry of Higher Education of the Arab Republic of Egypt, and he would like to express his deepest gratitude for the financial support.

ORCID iDs

Moustafa M Zohair

Fahd M Abdelkarem

Yhiya Amen

Kuniyoshi Shimizu

Ethical Approval

Ethical Approval is not applicable for this article.

Statement of Informed Consent

There are no human subjects in this article and informed consent is not applicable.

Statement of Human and Animal Rights

This article does not contain any studies with human or animal subjects.

Authors’ Contribution

MZ and KS designed the study and wrote the manuscript; MZ conducted the chemical and microbiological parts as well as the metabolomic data interpretation. AHE, FMA, YA and AAE elucidated the compounds structure and revised the manuscript. All authors participated in the critical reading of the final manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Statements and Declarations

Figures 5 and included in this manuscript were created by the authors. No copyrighted material was reproduced from external sources.

Supplemental Material

Supplemental material for this article is available online.

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Supplementary Material

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Fungal–Fungal Cocultivation Unveils Bioactive Metabolites,Including Rare Terpene–Amino Acid Hybrids,with Antibacterial Activity

Abstract

Background

Methods

Results

Conclusion

Keywords

Introduction

Experimental

General Experimental Procedures

Microbial Materials and Fermentation

Genome Mining of Microbial Genera

Cocultivation and Extraction Process

Extraction and Isolation of Compounds

LC-QTOF/MS Profiling

Data Analysis of the Mass Profile

Molecular Network-Based Analysis

Antimicrobial Evaluation

Results

Microbial Coculture Combinations

Metabolite Yield of Time-Dependent Fungal Cocultures

Isolation and Identification

Determination of Isolated Compounds

Molecular Network Analysis

Biological Activity

Discussion

Metabolite Yield Enhancement During Microbial Co-Culturing

Effect of Genetic Material and Species Selection

Chemical Importance of Hybrid Metabolites

The Diverse Chemical Structures of Hybrid Metabolites and Their Biological Efficacy

Conclusion

Supplemental Material

sj-docx-1-npx-10.1177_1934578X251405381 - Supplemental material for Fungal–Fungal Cocultivation Unveils Bioactive Metabolites, Including Rare Terpene–Amino Acid Hybrids, with Antibacterial Activity

Footnotes

Acknowledgments

ORCID iDs

Ethical Approval

Statement of Informed Consent

Statement of Human and Animal Rights

Authors’ Contribution

Funding

Declaration of Conflicting Interests

Statements and Declarations

Supplemental Material

References

Supplementary Material