Bioactive metabolites and antidiabetic activity of Cannabis sativa-derived endophytic fungi

doi:10.21203/rs.3.rs-7549570/v1

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Bioactive metabolites and antidiabetic activity of Cannabis sativa-derived endophytic fungi

https://doi.org/10.21203/rs.3.rs-7549570/v1

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published 18 Nov, 2025

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Cannabis sativa L. (Cannabaceae) has long been valued in traditional medicine, including Ayurveda, for managing disorders such as diabetes, cancer, and kidney diseases. Although the plant itself is known to influence glucose metabolism, the therapeutic potential of its associated endophytic fungi remains underexplored. In this study, 56 fungal isolates were obtained from different tissues of C. sativa and evaluated for antidiabetic activity. Two isolates, identified by ITS1/4 rDNA sequencing as Aspergillus micronesiensis and Nodulisporium verrucosum, exhibited strong inhibitory effects on α-amylase, α-glucosidase, DPP-IV, and lipase (IC₅₀ < 100 µg/mL). Their ethyl acetate extracts demonstrated low cytotoxicity, enhanced cell viability, and significantly promoted insulin secretion in MIN6 pancreatic β-cells. GC–MS analysis revealed bioactive metabolites, including 2,4-di-tert-butylphenol, 7,9-di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione, 2-methylcinnamic acid, and tetraneurin-A, which are reported to possess antidiabetic potential. FTIR further confirmed the presence of functional groups corresponding to these compounds. Together, these findings highlight C. sativa-derived endophytic fungi as promising sources of novel antidiabetic agents, bridging traditional knowledge with modern drug discovery.

Cannabis sativa

endophytic fungi

antidiabetic activity

insulin secretion

bioactive metabolites

Type 2 diabetes mellitus (T2DM) is a chronic and progressive metabolic disorder characterized by persistent hyperglycemia and associated complications. With an estimated 589 million people currently affected worldwide and projections exceeding 850 million by 2050, T2DM represents one of the most pressing global health challenges, placing an immense economic burden on healthcare systems (IDF, 2025; Sun et al., 2022). Despite the availability of pharmacological agents, lifestyle interventions, and monitoring strategies, long-term glycemic control remains difficult to achieve, largely due to the multifactorial pathogenesis of the disease, which involves insulin resistance, impaired insulin secretion, oxidative stress, and chronic inflammation (Ashcroft and Rorsman, 2012; Khin et al., 2023). These limitations highlight the urgent need for novel therapeutic agents capable of targeting multiple aspects of T2DM progression, including pancreatic β-cell protection and insulin secretion.

Natural products have historically served as a rich source of antidiabetic agents. Plant- and microbe-derived bioactive compounds, often referred to as “privileged structures” in drug discovery, are evolutionarily optimized to interact with biological targets such as carbohydrate-metabolizing enzymes and β-cells (Mukherjee et al., 2020; Atanasov et al., 2021). Endophytic fungi—symbiotic microorganisms residing within plant tissues without causing harm—have emerged as promising reservoirs of structurally diverse secondary metabolites, including alkaloids, terpenoids, and phenolics, many of which exhibit antioxidant, anti-inflammatory, and antidiabetic activities (Gouda et al., 2016; Singh et al., 2021). Importantly, medicinal plants traditionally used for diabetes management provide a unique ecological niche for isolating endophytes with potential therapeutic relevance (Toppo et al., 2024).

Cannabis sativa L. (Cannabaceae), widely distributed across temperate and subtropical regions, has been used for centuries in traditional medicine for the management of diabetes, cancer, pain, and insomnia (Chaachouay et al., 2022; Odeyemi et al., 2018). However, while the phytochemistry of C. sativa has been extensively studied, its associated endophytic fungi remain largely unexplored as potential sources of antidiabetic agents.

In this study, endophytic fungi were isolated from different tissues of C. sativa and evaluated for their antidiabetic potential. Ethyl acetate extracts were screened for inhibitory activity against α-amylase, α-glucosidase, dipeptidyl peptidase-IV (DPP-IV), and lipase, as well as for their effects on insulin secretion and β-cell viability in MIN6 cells. Potent isolates were identified through ITS rDNA sequencing, while GC–MS and FTIR analyses were performed to characterize the bioactive metabolites. This work provides the first comprehensive evaluation of C. sativa-associated endophytic fungi as a novel source of bioactive compounds with potential applications in diabetes management.

2.1 Collection and identification of the Plant

Cannabis sativa L. was collected from the botanical garden of the Institute (26° 51'27" N 80° 57'12" E) in November 2022. Dr. Prabhukumar K.M. taxonomically identified the plant and deposited it in the institutional herbarium with the voucher specimen collection number and accession number, which are 355801 and 119252, respectively. The healthy and mature organs, such as stems, roots, leaves, petioles, and inflorescences, were collected and kept in labeled sterile packets before being transported directly to the laboratory for subsequent processing.

2.2 Isolation of endophytic fungi

The collected parts of C. sativa were rinsed with tap water and subsequently segmented into diminutive segments measuring 4–5 mm in length. After 10 min of sterilizing with 75% ethanol for 60 seconds, leaves, petioles, and inflorescences were rinsed thrice in sterile distilled water. The stems and roots underwent a series of surface sterilization procedures, which included immersion in 65% ethanol for 5 minutes, followed by rinsing with sterile distilled water. Subsequently, they were subjected to a bleaching process using 2% sodium hypochlorite for 120 seconds, treated again with 70% ethanol for 120 seconds, and finally washed with sterile distilled water. Disinfected samples were subsequently plated onto PDA, with five pieces allocated per sample per plate (HiMedia, Bangalore, India), comprising 200 mg/L of chloramphenicol to prevent bacterial contamination, and incubated for 12 h of dark and light cycles at 25 ± 2°C. Five plates were used for each sample. Hyphal filaments emerging after 4–5 days of incubation in a BOD incubator from small plant pieces were transferred onto a fresh PDA plate. The EIF was determined by computing the ratio of fungal isolates retrieved from each organ to the total samples plated for each corresponding plant tissue (Toghueo et al., 2019).

2.3 Cultivation and endophytic fungi metabolites extraction

The pure cultures of isolated fungal strains were cultivated on PDA for one week. Then, 1×1 cm pieces obtained with a sterile cork borer from fungal isolates were utilized to inoculate 100 mL of three separate PDB media contained within 500 mL Erlenmeyer flasks. The fungal isolates were cultivated for a duration of 20 days under static conditions at 25 ± 1°C before extraction. The developed mycelium mat of each culture was separated, extracted by adding 100 mL of ethyl acetate, followed by shaking and allowing it to rest overnight at room temperature to ensure effective metabolite extraction. The organic layer from the supernatant mixture was separated through decantation. This procedure was conducted three times, yielding a cumulative volume of 300 mL for each sample. The organic solvent was then evaporated at a temperature of 40°C using an evaporation system (Labconco, USA). The remaining residue was re-dissolved in ethanol, transferred into a culture glass tube, and allowed to evaporate completely. The extract yield was measured and subsequently re-dissolved in DMSO (Sigma-Aldrich, Bangalore) to conduct the antidiabetic screening.

2.4 Identification and molecular characterization of potent antidiabetic endophytic fungi

The compound microscopy and SEM techniques were used to identify the isolates, revealing promising antidiabetic potential. These isolates were additionally delineated through the analysis of the nucleotide sequence encompassing the ITS1-5.8S rRNA-ITS4 region. Genomic DNA was isolated from the mycelium cultivated in PDB through the phenol/chloroform protocol (Prateeksha et al., 2020). A nanodrop spectrophotometer (Thermo Scientific, India) was used to evaluate both the content and purity of the isolated DNA, as indicated by the A260/A280 ratio. The ITS1-5.8S rRNA-ITS4 region was amplified by PCR using universal primers ITS1 [5'-TCC GTA GGT GAA CCT GCG G-3'] and ITS4 [5'-TCC TCC GCT TAT TGA TAT GC-3'] (Prateeksha et al., 2021). The PCR amplification was carried out at 95°C for 120 seconds, followed by 35 cycles consisting of 94°C for 60 seconds, 54°C for 60 seconds, and 72°C for 60 seconds. The procedure concluded with a final step at 72°C for 10 min. The amplified segments were purified using the polyethylene glycol sodium chloride precipitation method and sequenced in an ABI 3730XL automated DNA sequencer (Applied Biosystems, Inc., Foster City, CA). The sequencing was performed on both strands of the PCR amplicons. Sequences resembling those from fungal isolates were found using the BLAST program. Isolates were identified using criteria based on how closely their sequences matched and those of trustworthy reference isolates found in open-access nucleotide databases. To perform phylogenetic analysis, the consensus sequences underwent a BLASTn search within the NCBI GenBank database to identify similar sequences. The sequences obtained were subsequently aligned with the consensus sequence by employing the multiple alignment software Clustal X 2.1. A phylogenetic tree was constructed employing the Neighbor-Joining method, which involved calculating distances using the Kimura 2-parameter model in MEGA X software. The reliability of the classifications was assessed utilizing data that was resampled 500 times.

2.5 Assessment of the antidiabetic property of endophytic fungi

2.5.1 Preliminary antidiabetic screening by biochemical enzymatic assays

For the initial antidiabetic assessment, all extracts were evaluated at 100 µg/mL through biochemical enzymatic assays, including α-amylase, α-glucosidase (Liu et al., 2017), DPP-IV (Ahmad et al., 2019), and lipase (Kim et al., 2007). To measure the anti-α-amylase property, a mixture solution comprising α-amylase (0.1 mL, 3.50 U/mL) and test sample (0.1 mL) or 0.1 mL of PBS as a control. This mixture was preincubated at 37°C for 10 minutes, after which a soluble starch solution (0.2 mL, 0.45%, w/v) was added. The resultant mixture underwent a reaction at 37°C for 15 min, which was subsequently stopped by the incorporation of the DNS color reagent (0.4 mL). The mixture was subjected to incubation in boiling water at 100°C for 5 min. After cooling at ambient temperature, the absorbance was recorded at 540 nm using a Synergy XTH multimode reader (Biotek, Germany). Acarbose served as a positive control. To evaluate the anti-α-glucosidase activity, a mixture containing α-glucosidase (0.05 mL at a concentration of 0.5 U/mL) and the test sample (0.1 mL dissolved in 0.1 M PBS, pH 6.8) or PBS (0.1 mL) as a control was incubated at 37°C for 10 min. The mixture was initiated by adding 3 mM pNPG solution (0.1 mL) and subsequently incubated at 37°C for 15 min. Following this period, the reaction was concluded by the incorporation of 0.1 M sodium carbonate (0.75 mL) and the absorbance at 405 nm.

For DPP-IV inhibitory activity, 3 mM GPPN (0.05 mL) and the test sample in PBS (0.025 mL) were preincubated at 37°C for 10 min. The reactions were started with the addition of DPP-IV solution (0.05 mL; 16 U/L, prepared in 100 mM Tris–HCl, pH 8.0) and placed at 37°C for 90 min. The reaction was subsequently halted by the addition of 100 µL of sodium acetate buffer (pH 4.0, 1 M). The liberated p-nitrophenol was analyzed at 405 nm using a Synergy XTH multimode reader (Biotek, Germany). Vildagliptin was used as a positive control. To evaluate the anti-lipase activity, a mixture of pancreatic lipase solution (0.03 mL, 10 U/L, dissolved in 100 mM Tris–HCl, pH 7.0), test sample (0.1 mL), and 10 mM of 4-nitrophenyl butyrate (0.02 mL) was placed at 37°C for 15 min. The absorbance measurement was taken at a wavelength of 405 nm, with orlistat serving as the positive control.

2.5.2 β-cell proliferation antidiabetic assay

MIN6 cells, originating from pancreatic β-cells, were obtained from the National Centre for Cell Science, India. The cells were cultivated in DMEM (Gibco, USA) comprising 10% FBS (Gibco, USA) to prepare a complete medium, maintained in a humidified atmosphere containing 95% air and 5% CO₂ at a temperature of 37°C. First, an Almar blue-reduction assay was performed to determine the safe concentration of extracts of endophytic fungi on the viability of MIN 6 pancreatic β-cells at 48 h, as previously described method (Aldoss et al., 2023).

To examine the proliferative effect of endophytic fungal extracts (AMEE&NVEE), the cell morphology assay was performed (Conner et al., 2024). Briefly, MIN6 cells (2×10⁵ cells/well) were grown on glass coverslips in the presence or absence of the test sample for 24 h. The cells were rinsed with PBS and were subsequently fixed in 2% paraformaldehyde for a duration of 15 min at room temperature. The cells were analyzed under a phase-contrast microscope (Leica DCF 700 T, Germany) at 20x magnification. After fixation, another set of cells was stained with 4mM Syto9 (Invitrogen, USA) and observed under a fluorescence microscope (Leica DCF 700 T, Germany). The colony-forming assay was performed following previously described methods (Chiba et al., 1998). MIN6 cells (1×10³ cells/well) were seeded in the presence and absence of the test sample for 7 to 10 days, with the medium being replaced on the fifth day. The washed cells were fixed with 2% paraformaldehyde and stained with 1% CV solution (HiMedia, India) at room temperature for 30 min. The cells were air-dried and photographed using a Nikon D5600 DSLR camera. CV staining assay was also used to examine the cell proliferation effects of extracts [33]. MIN6 cells (1×10⁴ cells) were seeded in 24-well plates and allowed to incubate for a duration of different time intervals 24,48&72 h. Following incubation, the cells were washed with PBS and subsequently stained with a 0.5% (v/v) solution of CV dye in PBS for 10 min. Cells were rinsed with PBS three times and then fixed in 70% ethanol. The absorbance of the ethanolic solution was recorded at 570 nm using a Synergy XTH multiplate reader (Biotek, Germany). Cell proliferation was quantified to compare the treatment versus the control cells. DMSO was used as a vehicle control.

2.5.3 GSIS antidiabetic assay

The GSIS assay was conducted using a method previously described with minor modifications (Guzman et al., 2021). MIN6 cells (2×10⁵ cells/well) were seeded and incubated for 48 h. Following the incubation period, the media were discarded, and the cells were washed with PBS. Subsequently, the cells were incubated in KRBH buffer (129 mM NaCl, 4.8 mM KCl, 1.2 mM KH₂PO₄, 1.2 mM MgSO₄, 2 mM CaCl₂, 20 mM HEPES, 24 mM NaHCO₃, 0.2% BSA, 0.2% FBS), with low 5% FBS and glucose for 90 min. Afterward, the medium was replaced with KRBH buffer containing either 3 mM (low) or 25 mM (high) glucose concentrations, along with test samples. The cells were incubated for another 60 min. After this second incubation, the medium was collected for insulin measurement using a Rat Insulin ELISA kit (Elabscience, USA).

2.6 GC-MS analysis of AmEE and NvEE

Both polar and non-polar extracts of endophytic fungi were analyzed using an Agilent 8890 GC system coupled with a 5977C GC/MSD and a 30 m HP-5MS UI Agilent column. Trimethylsilyl (TMS) derivatization was performed to improve analyte volatility. Briefly, 12 mg of the sample was suspended in 210 µL of methoxylamine hydrochloride in pyridine (20 mg/mL), followed by the addition of 150 µL of MSTFA. The mixture was shaken at 37°C for 2 hours. After derivatization, 0.5 µL was injected using an Agilent 7693A autosampler (Mishra et al,.2020).

The GC program included a 5-minute solvent delay at 70°C, followed by a temperature ramp to 270°C at 5°C/min, a 5-minute isothermal hold, and a return to 70°C for an additional 5 minutes. Helium was used as the carrier gas at a flow rate of 1 mL/min with a split ratio of 1:16. Data were analyzed using Agilent OpenLab CDS software. Metabolite identification was carried out using WILLY and NIST spectral libraries, with ribitol used as an internal standard for polar compounds, and palmitic acid, stearic acid, β-sitosterol, and stigmasterol for non-polar compounds.

2.7 FTIR analysis of AmEE and NvEE

To identify the various functional groups found in extracts, an FTIR (Bruker Alpha-E) analysis was performed on the crude extract. The coarse dried material was ground into a powder with potassium bromide (KBr). The next step was to compress the powder into a tiny pellet, which was subsequently examined. Infrared light also revealed that KBr was transparent. After subjecting the sample to a wide range of infrared light, the data were transformed using Fourier analysis, and the absorbance level at a certain frequency was then plotted. The spectra that came out were spot-on for the organic compound in the sample. The absorbance was recorded at 600–4000 nm to identify and quantify organic species. The IR radiation absorbances of molecular vibrations were correlated with the abundance of functional groups (Nischitha et al., 2022).

2.8 Statistical analysis

The findings were reported as the mean ± SD of three independent experiments. Statistical evaluation was performed utilizing one-way and two-way ANOVA in GraphPad Prism software (Version 8, USA).

3.1 Endophytic fungal isolates from different parts of C. sativa

A total of 56 endophytic fungi were isolated from the 280 different tissue parts of C. sativa (Fig. 1A). The EIF varied between 1.07–7.14%, contingent upon the specific organ examined. The leaf exhibited the uppermost infection frequency at 7.14%, followed by the root at 5.71%, whereas the inflorescence displayed a lower frequency of 1.07% (Fig. 1B).

3.2 Screening of 56 endophyte extracts using inhibition of enzymatic activity

Fungal extracts were screened at 100 µg mL^− 1 against α-amylase, α-glucosidase, DPP-IV, and pancreatic lipase (Fig. 2A-D). Among the evaluated extracts, S20 and S50 showed significant inhibitory effects on enzymatic activity. Specifically, S20 demonstrated inhibition of α-amylase, α-glucosidase, DPP-IV, and lipase by 56.28 ± 2.82%, 89.25 ± 4.16%, 59.65 ± 3.68%, and 69.28 ± 4.16%, respectively, whereas S50 displayed inhibition levels of 54.50 ± 3.91%, 87.64 ± 3.84%, 64.53 ± 3.54%, and 61.33 ± 2.96%.

3.3 Identification of most potential endophytic fungi

The morphological identification of the most potential endophytic fungal strains (S20 & S50) was assessed through microscopic examination (Fig. 3A-C and Fig. S2A-C). S20 showed pale yellow colonies on PDA plates, unbranched, smooth-walled, and bearing conidial heads, conidiophores, and globose to sub-globose, small and smooth-walled conidia, often appearing in compact clusters. S50 displayed a white to pale colony, septate mycelium, cylindrical and smooth-walled conidiophores, and ovoid conidia. These fungi were further identified through the examination of the ITS regions of rDNA, coupled with an analysis of sequence similarity employing BLAST nucleotide using FASTA algorithms (Fig. 3D and Fig. S2D). The ITS sequence exhibited a length of approximately 550 base pairs. The S20 isolate showed a remarkable sequence identity value of 99.81% with Aspergillus species that form a monophyletic group, whereas S50 revealed 98.21% similarity with Nodulisporium species, which share a close relationship with Daldinia species. The phylogenetic tree constructed from the ITS sequence database illustrated that the S20 and S50 isolates exhibited a close genetic relationship with Aspergillus micronesiensis (Am) and Nodulisporium verrucosum (Nv), respectively, as assessed using MEGA11 software to estimate the maximum likelihood of the gamma parameter for site rates. The sequences of S20 and S50 isolates have been deposited in GenBank with assigned accession numbers: PP925620 and PP925621, respectively.

3.4 Anti-enzymatic property of potent endophytes

The potent endophytic fungi, namely Am and Nv, were cultivated in 100 mL of PDB and subsequently extracted with ethyl acetate, resulting in extract yields of 9.8 mg and 7.6 mg, respectively. The anti-enzymatic activity of AmEE and NvEE against α-amylase, α-glucosidase, DPP-IV, and lipase in terms of IC₅₀ was calculated (Fig. 4A-D). Although Am and Nv are isolated from the leaf and root tissues of cannabis sativa named as CREE and CLEE were also prepared using the same solvent system and used for the comparative studies. AmEE and NvEE showed superior activity against α-amylase (IC₅₀ values: 87.07 ± 3.17 & 91.07 ± 4.62 µg/mL), α-glucosidase (IC₅₀ values: 52.98 ± 5.48 & 60.38 ± 4.73 µg/mL), DPP-IV (IC₅₀ values: 90.59 ± 3.81 & 80.19 ± 2.86 µg/mL), and lipase (IC₅₀ values: 73.72 ± 3.82 & 80.05 ± 4.57 µg/mL) as compared to CREE and CLEE. These effects of AmEE and NvEE were comparable to their standards.

3.5 Anti-diabetic activity of AmEE and NvEE in MIN6 pancreatic β-cells

First, we assessed the non-toxic dose of AmEE and NvEE on MIN6 cells using the Alamar blue viability assay (Fig. 5A and B). The results indicated that both extracts had no toxic effect up to 100 µg/mL. In addition, live/dead cell viability and morphogenic analyses were also performed to confirm the non-toxic effects of AmEE and NvEE on MIN6 cells (Fig. 6A; Fig. S3). These results also confirmed that both extracts at 100 µg/mL did not induce cell death and morphological variations. Thus, a safe concentration of AmEE and NvEE was selected to perform subsequent cell-based experiments.

Impact of AmEE and NvEE on MIN6 β-cells proliferation was assessed to examine the clonogenic or cell regeneration effects. For qualitative analysis, MIN6 β-cells were exposed to safe concentrations of AmEE and NvEE for 7–10 days, after which the cells were stained using crystal violet. Both extracts exhibited increased colony formation as compared to the untreated control (Fig. 7A). For quantitative analysis, MIN6 β-cells were incubated with both extracts for 24 h, 48 h, and 72 h, and examined cell proliferation using the Crystal violet staining method. AmEE and NvEE showed higher proliferative effects on MIN6 cells than those of untreated cells (Fig. 7B). The microscopic examinations also confirmed the proliferative effects of both extracts (Fig. 7C).

Next, the role of AmEE and NvEE in insulin secretion from MIN6 β-cells was assessed using the GSIS assay (Fig. 7D). AmEE and NvEE promoted insulin secretion under both low (2.8 mM) and high (25 mM) glucose stimulation conditions. At low glucose stimulation in cells, the higher concentrations of both extracts led to greater insulin secretion instead of lower concentrations of extracts. Conversely, under high glucose conditions, both low and high concentrations of the extracts enhanced insulin secretion as compared to the untreated control cells. However, the lower concentrations of both extracts were more effective than the higher concentrations. Overall, AmEE and NvEE exhibit potential antidiabetic activity in terms of cell proliferation and insulin secretion from pancreatic MIN6 β-cells.

3.6 GC-MS and FTIR fingerprinting of AmEE and NvEE

The chromatograms obtained from GC-MS analysis revealed 23 major compounds in the AmEE extract and 23 compounds in the NvEE extract (Fig. 8). Compound identification was performed by matching the mass spectra with entries in the NIST library database. The GC-MS profiling demonstrated a diverse range of secondary metabolites produced by endophytic fungal strains isolated from Cannabis sativa, as detailed in Tables 1 and 2. Importantly, seven compounds in AmEE and five compounds in NvEE are recognized for their established antidiabetic activities, as summarized in Table 3.

Table 1
Compound analysis of AmEE.
S.No	¹RT (min)	Molecular formula	Compound	Area %
1.	14.406	C12H36O5Si5	Pentasiloxane, dodecamethyl-	0.27
2.	16.731	C14H22	4-Tert-Butyl-1-n-butylbenzene	0.25
3.	21.378	C12H26O	2-Dodecanol	0.36
4.	25.204	C14H22O	2,4-Di-tert-butylphenol	3.56
5.	29.956	C9H13N3O3	2-Amino-4,5-dimethoxybenzohydrazide	0.37
6.	32.224	C7H10N2O2	2,3,6,7,8,8a hexahydropyrrolo[1,2-a]pyrazine-1,4-dione	0.34
7.	33.486	C19H38	1-Nonadecene	1.97
8.	35.666	C20H30O4	1,2-Benzenedicarboxylic acid, butyl octyl ester	0.69
9.	36.192	-	(No compound listed)	0.27
10.	36.993	C17H24O3	7,9-Di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione	2.99
11.	37.384	C11H18N2O2	3-Isobutylhexahydropyrrolo[1,2-a]pyrazine-1,4-dione	0.55
12.	38.017	C22H34O4	1,2-Benzenedicarboxylic acid, butyl 8-methylnonyl ester	3.28
13.	38.719	C26H52	1-Hexacosene	3.13
14.	38.858	C20H38O2	9,12-Octadecadienal, dimethyl acetal	0.28
15.	40.684	C20H42O	1-Eicosanol	3.11
16.	42.347	C12H22N2O2	2,5-Piperazinedione, 3,6-bis(2-methylpropyl)-	3.77
17.	42.874	C22H46O	1-Docosanol	4.72
18.	42.985	C22H46	Docosane	0.86
19.	43.19	C22H44O2	Eicosyl acetate	2.57
20.	44.814	C27H56	Heptacosane	3.33
21.	48.164	C29H60	Nonacosane	1.79
22.	48.979	C24H38O4	1,2-Benzenedicarboxylic acid, dioctyl ester	1.65
23.	49.651	C35H70	17-Pentatriacontene	1.65
¹Retention time

Table 2
Compound analysis of NvEE.
S. No	¹RT (min)	Molecular formula	Compound	Area %
1.	23.142	C11H10O	Naphthalene, 1-methoxy-	6.11
2.	23.912	C9H6O4	2H-1-benzopyran-2,4(3H)-dione, 6-hydroxy-	0.52
3.	25.163	C10H10O2	2-Methylcinnamic acid	0.85
4.	29.605	C16H13ClN2O5	3-[(3-chlorobenzoyl)amino]-3-(3-nitrophenyl)propanoic acid	0.49
5.	30.434	C8H8N4O3	Benzofurazan, 5-(dimethylamino)-4-nitro-	0.33
6.	30.596	C10H12O3	1-(2,4-Dihydroxyphenyl)-1-butanone	4.63
7.	30.846	C15H24O	1,4-Methanoazulen-9-one, decahydro-1,5,5,8a-tetramethyl-	0.3
8.	31.961	C8H7N3O4	Benzoic acid, 3-(N2-nitromethylidenhydrazono)-	1.64
9.	32.792	C11H10O2	2-Naphthalenol, 3-methoxy-	0.5
10.	33.797	C11H19N5S	1-Methyl-3,6-diazahomoadamantan-9-one thiosemicarbazone	0.69
11.	34.134	C12H22N2O2	Tricyclo[3.3.1.1(3,7)]decane-2,6-diol, 2,6-bis(aminomethyl)	1.3
12.	34.628	C16H19N3O2	2-[5,6-dihydrobenzo[h]quinazolin-4-yl(2-hydroxyethyl)amino]	0.55
13.	34.928	C10H13N3S	2-(2-Aminoanilino)-5-methyl-2-thiazoline	1.21
14.	35.667	C9H13N3OS	2-Amino-6-methyl-4,5,6,7-tetrahydrothieno[2,3-c]pyridine-3-	0.26
15.	36.13	C17H22O6	Solstitialin A	1.08
16.	36.257	C11H12N2OS	5-Ethylamino-4-phenylisothiazol-3-one	1.14
17.	36.986	C17H24O3	7,9-Di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione	0.51
18.	37.142	C11H18N2O2	3-Isobutylhexahydropyrrolo[1,2-a]pyrazine-1,4-dione	0.94
19.	37.994	C17H22O6	Tetraneurin - A	0.48
20.	38.017	C20H30O4	1,2-Benzenedicarboxylic acid, butyl octyl ester	0.57
21.	38.285	C18H35NO	Elaidamide	0.36
22.	40.681	C16H34O	1-Hexadecanol	0.59
23.	42.351	C12H22N2O2	2,5-Piperazinedione, 3,6-bis(2-methylpropyl)-	0.93
¹Retention time

Table 3
Antidiabetic compounds present in AmEE and NvEE
Compound	¹RT (min)	²Abundance of compounds identified in the extract (%)		Antidiabetic Activity References
Compound	¹RT (min)	AmEE	NvEE	Antidiabetic Activity References
2,4-Di-tert-butylphenol	25.204	3.56	-	(Aravinth et.al.,2023; Momin et.al.,2024)
1-Nonadecene	33.486	1.97	-	(Peng et.al.,2019; Wang et.al.,2018)
7,9-Di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione	36.993	2.99	0.51	(Ahmad et.al.,2023)
Eicosyl acetate	43.190	2.57	-	(Ali et.al.,2021)
Heptacosane	44.814	3.33	-	(Amalraj et.al.,2024)
Nonacosane	48.164	1.79	-	(Khalid et.al.,2024)
17-Pentatriacontene	49.651	1.65	-	(Saha et.al.,2024)
2-Methylcinnamic acid	25.163	-	0.85	(Hafizur et.al.,2015)
3-Isobutylhexahydropyrrolo[1,2-a]pyrazine-1,4-dione	37.142	-	0.94	(Kabir et.al.,2024)
Tetraneurin - A	37.994	-	0.48	(Arafat et.al.,2025)
1-Hexadecanol	40.681	-	0.59	(Ahmad et.al.,2024)
¹Retention time; ²Relative abundance of extract components was automatically generated from electronic integration of individual peak of the chromatogram relative to the total peak area.

FTIR analysis revealed that AmEE contains eleven functional group peaks, while NvEE shows seventeen peaks. The stretching peaks of the hydroxyl group were presented at 3268.44 cm^− 1 and 3270.22 cm^− 1 in AmEE and NvEE, respectively, suggesting the presence of hydroxyl groups in polyphenolic compounds in both extracts. On the other hand, there are many peak stretches attributed to these extracts, like alkanes, aldehydes, carboxylic acids, ketones, alkenes, nitrogen, methyls, amines, aliphatic ethers, sulphoxides, and mono-substituted benzenes functional groups, where the formation of bioactive compounds is shown in Fig. S4.

DM is a chronic, possibly deadly metabolic condition marked by inadequate or improper insulin production, resulting in high blood sugar levels. The increasing prevalence of T2DM in the general population emphasizes the need for improved and safer medical care. Consequently, the exploration of novel antidiabetic compounds is a burning need of our times. Endophytic fungi derived from medicinal plants exhibit distinctive characteristics, as they have demonstrated the potential to synthesize a range of bioactive compounds that engage various mechanisms of action targeting food metabolizing enzymes and insulin production from pancreatic β-cells (Abdel-Azeem et al., 2024). Endophytic fungi used in traditional medicine produce about 35% of the novel metabolites; some of these fungi produce compounds with carbon frameworks that have never been identified before (Toghueo et al., 2019). We therefore hypothesized that C. sativa, extensively utilized in traditional medicine by indigenous populations globally to treat a wide range of diseases, including diabetes, may harbor endophytes that produce compounds that lower blood sugar. The current report appears to be the initial study into the antidiabetic activity of endophytic fungi derived from C. sativa.

We isolated 56 endophytic fungi from various parts of C. sativa and screened them against α-amylase, α-glucosidase, DPP-IV, and pancreatic lipase for their capability to yield antidiabetic compounds. As demonstrated in this study, the antidiabetic screening of these fungal extracts using biochemical enzymatic assays revealed the antidiabetic activity of the most promising extracts with IC₅₀ at < 100 µg/mL against α-amylase, α-glucosidase, DPP-IV, and lipase. The current investigation designates that every part of C. sativa contains one or more endophytes that can provide bioactive metabolites and therefore suggests that a rich repertoire of antidiabetic compounds may be discovered by further investigation of these endophytic fungi.

Out of the 56 fungi tested, 2 (3.7%) demonstrated significant activity (IC₅₀ < 100 µg/mL) against α-amylase, α-glucosidase, DPP-IV, and lipase. These fungi belong to Aspergillus microsiensis (Am) and Nodulisporium verrucosum (Nv) earlier did not reported to demonstrate antidiabetic activity. Ethyl acetate extracts of both AmEE and NvEE isolated from the roots and leaves of C. sativa, respectively, were the most potent against α-amylase (IC₅₀ 87.07 ± 3.17 & 91.07 ± 4.62 µg/mL), α-glucosidase (IC₅₀, 52.98 ± 5.48 & 60.38 ± 4.73 µg/mL), DPP-IV (IC₅₀, 90.59 ± 3.81 & 80.19 ± 2.86 µg/mL), and lipase (IC₅₀ 73.72 ± 3.82 & 80.05 ± 4.57 µg/mL). These effects of AmEE and NvEE were comparable to their standards and were superior to those of the CREE and CLEE. Cell proliferative effects of both AmEE and NvEE on MIN6 β-cells were assessed at 24 h post-treatment with these extracts, showing a significant increase over time, culminating at 72 h of incubation. Moreover, the treatment of MIN6 β-cells to AmEE and NvEE led to the secretion of insulin observed after 48 h incubation.

A. microsiensis was first discovered in 2014, a globally red-listed fungal species of the Aspergillus genus that exhibits anti-microbial, anti-cancerous, and anti-HIV activity (Maduranga et al., 2018; Wu et al.,2019; Luyen et al., 2019). N. verrucosum has no pharmacological activity data found in the literature survey. This study presents, for the first time, the potential of N. verrucosum to yield antidiabetic compounds. GC-MS analysis of the AmEE and NvEE extracts revealed a total of approximately forty-six bioactive secondary metabolites. Among these, twelve compounds were identified as having previously reported antidiabetic activity. In AmEE, seven compounds were detected, including 2,4-Di-tert-butylphenol, 1-Nonadecene, 7,9-Di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione, Eicosyl acetate, Heptacosane, Nonacosane, and 17-Pentatriacontene. Similarly, five antidiabetic compounds were found in NvEE, such as 2-Methylcinnamic acid, 3-Isobutylhexahydropyrrolo[1,2-a]pyrazine-1,4-dione, 1-Hexadecanol, and Tetraneurin–A, as previously reported in the literature (Table 3). The validation of mass spectra from bioactive substances was associated with the functional groups found in FTIR spectroscopy. The mass spectroscopy investigation confirmed the presence of functional groups often identified in compounds with anti-diabetic and antioxidant effects. Distinct peaks were detected in the extracts, indicating the presence of distinct functional groups and substances with potential therapeutic properties (Nischitha et al., 2022). The presence of numerous functional groups shows the complicated structure of secondary metabolites. The results indicate that more extensive chemical analyses are required to explore the potential of Am and Nv in producing antidiabetic compounds.

C. sativa has a long history of use in various traditional medicinal systems for the prevention and treatment of a wide range of diseases such as diabetes, cancer, reproductive toxicity, and kidney problems. This is the first study to report that a significant number of endophytic fungi isolated from C. sativa have been evaluated for their antidiabetic properties. Two endophytic fungi revealed effective antidiabetic potential, signifying that each of the 56 isolated fungi can yield antidiabetic compounds. These two potent fungi were identified as Aspergillus microsiensis and Nodulisporium verrucosum. Our findings indicate that endophytes contain compounds with anti-diabetic activity, which encourages future research and development of novel natural medicines that are both cost-effective and safe. This research adds to the expanding knowledge regarding natural products and emphasizes the critical importance of biodiversity in tackling global health issues, notably diabetes.

CRediT authorship contribution statement

Sushil Agrahari: Formal analysis, Writing – original draft, Methodology, Visualization, Validation, Data curation, Investigation, Shailendra P. Singh: Supervision, Writing – review & editing, All authors read and approved the final manuscript. Brahma N. Singh: Supervision, Conceptualization, Formal analysis, Writing – review & editing, Funding acquisition.

Conflicts of interest

The authors declare no potential conflicts of interest among them.

Acknowledgments

This work was supported by the Council of Scientific and Industrial Research, India (grant number OLP-0115). The institutional manuscript number is CSIRNBRI_MS/2025/02/07.

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No competing interests reported.

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Bioactive metabolites and antidiabetic activity of Cannabis sativa-derived endophytic fungi

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Abstract

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1. Introduction

2. Materials and methods

2.1 Collection and identification of the Plant

2.2 Isolation of endophytic fungi

2.3 Cultivation and endophytic fungi metabolites extraction

2.4 Identification and molecular characterization of potent antidiabetic endophytic fungi

2.5 Assessment of the antidiabetic property of endophytic fungi

2.5.1 Preliminary antidiabetic screening by biochemical enzymatic assays

2.5.2 β-cell proliferation antidiabetic assay

2.5.3 GSIS antidiabetic assay

2.6 GC-MS analysis of AmEE and NvEE

2.7 FTIR analysis of AmEE and NvEE

2.8 Statistical analysis

3. Results

3.1 Endophytic fungal isolates from different parts of C. sativa

3.2 Screening of 56 endophyte extracts using inhibition of enzymatic activity

3.3 Identification of most potential endophytic fungi

3.4 Anti-enzymatic property of potent endophytes

3.5 Anti-diabetic activity of AmEE and NvEE in MIN6 pancreatic β-cells

3.6 GC-MS and FTIR fingerprinting of AmEE and NvEE

4. Discussion

5. Conclusion

Declarations

References

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