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Bacterial metabolite-directed synthesis of biogenic TiO2–Zn nanocomposites: characterization and multifunctional biomedical evaluation

Ibrahim M. Ibrahima, Hanadi A. Alahmadib, Anes A. Al-Sharqi*c, Nidal Mohammed Zabermawid, Mohammed Alsienia, Dareen Alyousfief, Faten A. S. Alsulaimanyg, Dalal Alfawaza, Issam Alshamih, Zinab Alatawii, Ahmed Eid Alharbij and Ahmed Ghareeb*k
aDepartment of Clinical Pharmacology, Faculty of Medicine, King Abdulaziz University, Jeddah 21589, Saudi Arabia. E-mail: imibrahim1@kau.edu.sa; malsieni@kau.edu.sa; dalfawaz@kau.edu.sa
bCollege of Health Science and Nursing, Alrayan National Colleges, Madinah, 42541, Saudi Arabia. E-mail: ha.alahmadi@amc.edu.sa
cPhotonics Unit, Institute of Laser for Postgraduate Studies, University of Baghdad, Al-Jadiriah, P.O. Box 47314, Baghdad, Iraq. E-mail: anes@ilps.uobaghdad.edu.iq
dSustainable Agriculture Production Research Group, Department of Biological Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia. E-mail: nzabermawi@kau.edu.sa
eDepartment of Clinical Biochemistry, Faculty of Medicine, King Abdulaziz University, 21589, Jeddah, Saudi Arabia. E-mail: dalyousfi@kau.edu.sa
fInstitute of Genomic Medicine Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
gDepartment of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia. E-mail: Faalsulaimany@kau.edu.sa
hDepartment of Basic Medical Sciences, College of Medicine, Taibah University, Madinah 42353, Saudi Arabia. E-mail: ishami@taibahu.edu.sa
iDepartment of Family and Community Medicine, Faculty of Medicine, University of Tabuk, Tabuk 47512, Saudi Arabia. E-mail: zalatawi@ut.edu.sa
jDepartment of Medical Laboratory, College of Applied Medical Sciences in Yanbu, Taibah University, Yanbu Governorate, Saudi Arabia. E-mail: aeharbi@taibahu.edu.sa
kBotany and Microbiology Department, Faculty of Science, Suez Canal University, Ismailia 41522, Egypt. E-mail: aghareeb@science.suez.edu.eg

Received 1st February 2026 , Accepted 3rd April 2026

First published on 27th April 2026


Abstract

This study synthesized TiO2–Zn nanocomposites using metabolites from Red Sea-isolated Bacillus tequilensis MYG163 and evaluated their multifunctional therapeutic potential. Chronic diseases such as diabetes, infections, and inflammation share overlapping pathological mechanisms that single-target therapies cannot adequately manage. XRD analysis confirmed the presence of anatase TiO2 and wurtzite ZnO phases with crystallite sizes of 23.1 and 23.7 nm, respectively, in the TiO2–Zn nanocomposite. TEM analysis revealed spherical particles with sizes ranging from 8 to 15 nm, while DLS analysis indicated a hydrodynamic diameter of 87.3 nm and a polydispersity index of 0.232. EDX analysis indicated the presence of Ti (32.1 wt%), Zn (29.2 wt%), and O (33.8 wt%) and a zeta potential of −34.5 mV, confirming colloidal stability. Hemolysis remained below 0.7% across all concentrations tested (50–1000 µg mL−1), confirming blood compatibility, essential for biomedical applications. DPPH and ABTS radical scavenging assays yielded IC50 values of 11.97 and 7.65 µg mL−1, respectively. Anti-inflammatory testing demonstrated preferential COX-2 inhibition (IC50 = 14.13 µg mL−1) over COX-1 (IC50 = 25.91 µg mL−1), representing a therapeutically favorable selectivity profile that minimizes gastrointestinal side effects associated with nonselective inhibition as well as prevents BSA denaturation (IC50 = 2.78 µg mL−1). Antimicrobial assays showed inhibition zones of 35 ± 0.4 mm (B. subtilis), 33 ± 0.5 mm (C. albicans), 26 ± 0.3 mm (S. typhi), 25 ± 1.0 mm (K. pneumoniae), 25 ± 0.6 mm (F. oxysporum), and 22 ± 0.4 mm (MRSA), with activities matching or exceeding those of reference antibiotics and antifungals against several tested organisms. Antidiabetic screening revealed the inhibition of α-amylase and α-glucosidase with IC50 values of 12.98 and 9.34 µg mL−1, respectively. Marine bacterial metabolites functioned as reducing and stabilizing agents, yielding nanocomposites with multitarget therapeutic properties spanning oxidative, inflammatory, microbial, and metabolic pathways.


Introduction

Standard therapies are often insufficient for treating diabetes, inflammation, infections, and oxidative stress, as these conditions arise from interlinked biological pathways that single-target drugs cannot fix.1 Diabetes worsens when high glucose causes oxidative damage in the retina and kidneys, but conventional treatments only lower blood sugar without stopping the underlying tissue destruction.2 Patients often discontinue their medications because of weight gain, stomach issues, and high costs.3 Natural compounds that work on multiple pathways handle both cellular stress and inflammation better than conventional drugs.4 Traditional medicines provide rapid relief and have established safety profiles, but they do not address the underlying causes of chronic diseases.5

Metal oxide nanoparticles show promise for medical applications due to their unique biological activities.6 TiO2 is a widely studied semiconductor metal oxide characterized by chemical stability, low toxicity, and broad-spectrum biological activity,7 making it attractive for drug delivery, antimicrobial, and tissue engineering applications.8 Similarly, ZnO is also recognized for its potent antimicrobial properties, which are attributed to zinc-ion release and reactive oxygen species generation, alongside established antidiabetic and anti-inflammatory activities.9 TiO2 degrades organic contaminants via photocatalysis under UV irradiation, achieving degradation efficiencies of up to 98%. It kills multiple pathogen types while remaining compatible with living tissues, making it useful for drug transport and tissue repair.10 ZnO fights microorganisms by releasing metal ions and generating reactive oxygen species that damage bacterial and viral structures.11 Combining TiO2 with ZnO yields better results than those obtained using either oxide separately. The heterojunction between these materials improves electron transfer and reduces charge recombination, boosting both photocatalytic efficiency and contaminant removal rates.12 Combining TiO2 with ZnO produces a heterojunction binary system with enhanced biological performance compared to that of either oxide alone, which is attributed to improved charge carrier separation at the interface between the two materials.13 This combination substantially increases antimicrobial strength, and studies have reported that the inhibitory concentration drops by a factor of 8 compared to single-component systems.14 The heterostructure keeps reactive species active for a longer duration, which helps eliminate pathogens and neutralize free radicals more effectively.

Conventional chemical and physical routes for producing metallic nanoparticles rely on toxic reagents that harm people and the environment, consume large amounts of energy, and generate considerable waste. High production costs also prevent their use at the industrial scale.15 Biological methods using bacteria, plants, and fungi address these problems by providing cleaner and cheaper alternatives. Microbes release metabolites that reduce metal ions to their zero-valent states while coating the particle surfaces to stop aggregation and improve stability.16 Bacillus species are particularly well-suited for nanoparticle fabrication, producing extracellular enzymes and proteins that direct particle nucleation and growth, yielding materials with controlled dimensions suitable for medical applications.17 Research shows that Bacillus strains create particles with precise sizes and shapes that fit the requirements for medical, agricultural, and environmental applications.18 This biological route bypasses the hazards and ecological damage of standard methods while delivering stable nanomaterials at lower costs.18

Research on TiO2–Zn nanocomposites produced via bacterial synthesis reveals significant gaps, particularly for strains isolated from Red Sea ecosystems. Studies typically examine single properties rather than testing antioxidant, anti-inflammatory, antimicrobial, antidiabetic, and wound-healing activities within one experimental framework.19–21 Red Sea microbial communities represent an underexplored reservoir of metabolically active strains capable of directing the formation of nanoparticles with distinct physicochemical properties.22 Comprehensive biological evaluations that measure safety and therapeutic effectiveness across multiple disease targets are largely absent. This fragmented approach prevents understanding whether bacterially synthesized TiO2–Zn NCs can address diverse medical needs simultaneously.23

This study synthesized TiO2–Zn NCs using metabolites from Red Sea-isolated Bacillus tequilensis MYG163 and examined their biomedical properties. Characterizations including FT-IR spectroscopy, XRD, TEM, EDX, DLS, and zeta potential analyses were used to establish the particle structure, composition, and surface characteristics. Biological testing measured hemolytic response, radical neutralization via DPPH and ABTS assays, modulation of inflammation via COX-1 and COX-2 inhibition, prevention of BSA denaturation, pathogen suppression against bacteria and fungi, and glucose regulation by targeting α-amylase and α-glucosidase enzymes.

This work investigated whether bacterium-mediated synthesis could yield nanocomposites with therapeutic values across the biomedical applications investigated.

Materials and methods

Bacterial extract preparation and biogenic TiO2–Zn NC synthesis

The bacterial strain Bacillus tequilensis MYG163 was isolated from the coastal environments of the Red Sea and confirmed taxonomically through 16S rRNA sequencing (GenBank: OR906149). Our previous studies have focused on the extraction of its exopolysaccharide fraction (EPS-R1), characterization of its molecular composition, and evaluation of its biomedical capabilities.24 Bacterial strains were grown in marine broth at 37 °C for 72 hours with shaking at 150 rpm to produce the metabolite. The culture was then centrifuged at 8000 rpm for 15 minutes to pellet the cells. The supernatant underwent triple extraction with ethyl acetate (1[thin space (1/6-em)]:[thin space (1/6-em)]1 v/v), with each organic layer collected separately. Combined extracts were concentrated by rotary evaporation under vacuum at 40 °C, reconstituted in ethyl acetate, and stored at 4 °C before use for TiO2–Zn nanoparticle synthesis.24

0.395 g of titanium oxide (anatase, −325 mesh, ≥99%, purchased from Sigma Aldrich, CAS no. 1317-70-0, catalogue no. 248576) was dispersed in 25 mL of dH2O and then combined with 25 mL of the bacterial extract. Concurrently, zinc sulphate (20 mM) was dispersed in 25 mL of distilled water and mixed with 25 mL of the bacterial extract. Zn2+ ions released from zinc sulphate and Ti4+ ions released from titanium oxide underwent bioreduction mediated by the enzymes, proteins, and polysaccharides present in the bacterial extract, affording the biogenic TiO2–Zn NC, consistent with previously reported Bacillus-mediated metal oxide synthesis. Each mixture was stirred at 600 rpm for 48 hours. The two solutions were then combined and agitated at 700 rpm for an additional 24 hours. Following centrifugation at 8000 rpm for 10 minutes, the pellet was collected and stored in a sealed microtube for downstream characterization and biomedical assessments.20

Physicochemical characterization of the biogenic TiO2–Zn NC

The TiO2–Zn NC samples were first heated at 45 °C for 24 hours to remove residual moisture. Following this desiccation step, the dried material was intimately mixed with a KBr powder to create a uniform composite. The resulting mixture was then pressed into a thin disc and examined by Fourier transform infrared (FT-IR) spectroscopy using a Nicolet 6700 instrument (Thermo Fisher Scientific). The spectral region between 400 and 4000 cm−1 was investigated to identify and map the vibrational modes associated with the various surface functional groups and chemical bonds present in the nanocomposite.25 The crystal structure evaluation of the TiO2–Zn NC was performed via X-ray diffraction (XRD) employing a PANalytical-X'Pert-Pro-MRD diffractometer equipped with CuKα radiation (λ = 1.54 Å).26 Diffraction data were collected within the angular range from 10° to 80° (2θ) with the instrument operating at 40 kV and 30 mA, providing insights into the lattice ordering and phase composition of the nanocomposite.27 The surface morphology of the TiO2–Zn NC was examined by scanning electron microscopy using a JEOL JSM-6360LA instrument (Japan) at an accelerating voltage of 15 kV. Samples were mounted on aluminum stubs and sputter-coated with gold prior to imaging.28 Structural details were further elucidated by transmission electron microscopy (TEM) using a JEOL JEM-2100 Plus apparatus (Tokyo, Japan) operating at 200 kV, which enabled the direct visualization of the surface topography, particle geometry, and size heterogeneity within the sample. To prepare the sample for TEM analysis, dry powder was dispersed in deionized H2O via sonication and then transferred to carbon-coated copper grids using the drop-deposition method. After allowing the samples to dry under ambient conditions, high-resolution imaging was performed to characterize the microstructural features.29

The quantitative determination of the constituent elements within the TiO2–Zn NC was accomplished using energy-dispersive X-ray spectroscopy (EDX) coupled to a JEOL JSM6360LA scanning electron microscope (Japan).30 The hydrodynamic diameter and polydispersity of TiO2–Zn dispersed in the liquid phase were ascertained via dynamic light scattering (DLS) using a Malvern Nano-ZS instrument (Malvern Ltd, UK).31 To remove extraneous scattering contributions and noise, stock suspensions of the nanocomposite were prepared by dispersing the material in ultrapure Milli-Q water. Zeta potential measurements, indicative of the electrostatic surface characteristics, were subsequently performed employing the same Malvern Nano-ZS apparatus fitted with a Zeta-sizer module while maintaining identical sample preparation and measurement conditions throughout the investigation.32

Biomedical evaluation of the TiO2–Zn NC

Hemocompatibility assessment. Erythrocytes were obtained from one of the authors. All experiments were performed in accordance with the Guidelines of the Research Ethics Committee, and experiments were approved by the ethics committee of the Suez Canal University (REC125/2022). Informed consent was obtained from the human participants of this study. Erythrocytes were harvested and subjected to three sequential washes with isotonic saline (150 mM NaCl, Sigma-Aldrich, CAS 7647-14-5) by centrifugation at 2500 rpm in 10-minute intervals. The purified cellular suspension was then reconstituted in phosphate-buffered saline (PBS, Sigma-Aldrich, pH 7.4) to achieve a final cell concentration of 2%. A concentration gradient of TiO2–Zn samples ranging from 50 to 1000 µg mL−1 was prepared for testing. Deionized water (Milli-Q, Merck) served as the positive control, inducing complete cell lysis (designated as 100% hemolysis), whereas the absence of the nanocomposite material (0 µg mL−1) served as the negative control, representing baseline hemolytic activity. Phosphate-buffered saline was retained as the spectrophotometric reference for background subtraction. Each TiO2–Zn NC formulation was combined with the RBC suspension at a total reaction volume of 1 mL. The resulting mixtures were incubated at 37 °C for 60 minutes, followed by centrifugation at 2500 rpm for 15 minutes. The resulting supernatants were subsequently analysed spectrophotometrically at 546 nm to quantify the released haemoglobin content.33
Hemolysis percentage (%) = [(AbsTiO2–Zn − Absblank)/Abspositive control] × 100

Antioxidant assessment

DPPH assay. A 0.1 mM 2,2-diphenyl-1-picrylhydrazyl (DPPH, MilliporeSigma, USA) solution in ethanol (Univar Solutions, USA) was prepared. 1 mL of this solution was mixed with 3 mL of the TiO2–Zn NC suspension (1.9–1000 µg mL−1, diluted from ethanol stocks). After shaking, the mixture was allowed to rest for 30 minutes at room temperature, with ascorbic acid (Vivion Inc, USA) serving as the control. The absorbance was measured at 517 nm using a Milton Roy UV-vis spectrophotometer.34
DPPH scavenging % = [(ascorbic acidAbsorbance − TiO2–ZnAbsorbance)/ascorbic acidAbsorbance] × 100
ABTS˙+ scavenging assay. The ABTS radical cation was generated by mixing 7 mM 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS, Cayman Chemical, USA) with 2.45 mM potassium persulfate (K2S2O8, Junteng Chemical, China) and keeping the mixture in the dark. The TiO2–Zn NC sample (0.07 mL) was added to 3 mL of the diluted ABTS˙+ solution.35 The reaction was allowed to proceed for 6 minutes, and then, the absorbance was measured at 734 nm using UV-vis spectrophotometry. Ascorbic acid served as the ref. 36.
ABTS˙+ inhibition % = [(ascorbic acidAbsorbance − TiO2–Znabsorbance)/ascorbic acidAbsorbance] × 100

Anti-inflammatory assessment of the TiO2–Zn NC

COX enzyme inhibition assay. The TiO2–Zn NC's activity against COX-1 and COX-2 was tested using commercial screening kits (COX-1 catalogue k548 and COX-2 catalogue k547; BioVision, USA). The nanomaterial was dissolved in DMSO (analytical grade, Gaylord Chemical, USA) and tested at concentrations ranging from 1000 to 0.5 µg mL−1 in 1-mL reaction mixtures. Celecoxib (Merck, Germany) functioned as the positive control for both assays.37
COX inhibition % = [(Celecoxib − TiO2–Zn NC)/celecoxib] × 100
BSA protein denaturation anti-inflammatory assay. 50 µL of the TiO2–Zn NC preparation was mixed with 450 µL of a 1% aqueous solution of bovine serum albumin (BSA, Sigma-Aldrich/Merck, Germany). Eight dilutions were tested: 1.56, 3.12, 6.25, 12.5, 25, 50, 100, and 200 µg mL−1. The pH was brought to 6.3 by adding 1 N HCl dropwise. After 20 minutes at room temperature, the tubes were placed in a 55 °C water bath for 30 minutes. Once removed, they were allowed to reach ambient temperature before the absorbance was measured at 670 nm using a Biosystem 310 plus spectrophotometer. Diclofenac sodium (LGM Pharma, USA) acted as the reference control.38
% BSA inhibition = (Absdiclofenac sodium − AbsTiO2–Zn NC/Absdiclofenac sodium) × 100

Antimicrobial testing of biogenic TiO2–Zn NC

Agar well diffusion testing was used to assess the antimicrobial performance of the TiO2–Zn NC against ATCC reference strains. Gram-positive bacteria included Bacillus subtilis ATCC 6633 and methicillin-resistant Staphylococcus aureus ATCC 33591 (MRSA). Gram-negative organisms comprised Klebsiella pneumoniae ATCC 13883, Salmonella typhi ATCC 6539, and Proteus vulgaris NCTC 4175/ATCC 13315, all cultured on Mueller–Hinton agar (HiMedia, India, M173). Fungal screening on Sabouraud dextrose agar (HiMedia, India, M063) included Candida albicans ATCC 10221 and Fusarium oxysporum ATCC 46995. Gentamicin and fluconazole (API manufacturers, China) served as the bacterial and fungal benchmarks, respectively.

Inoculum suspensions derived from broth microdilution were introduced to plates within 15 minutes. Three-directional streaking resulted in the uniform distribution of microbes across the dried agar. Sterile 6-mm cork borers were used to create wells using the aseptic technique. The TiO2–Zn NC at 10 µg mL−1 in DMSO (100 µL per well) was filled into each opening.39

Incubation differed by the microbe type: bacteria grew at 37 °C for 24 h, Candida species at 35 °C for 48 h, and Fusarium species at 28 °C for 48–72 h. Suppression zones were quantified to the nearest millimetre (mm) where growth ceased markedly.28

In vitro bioassay for antidiabetic potential

α-Amylase inhibition assay. The inhibitory effect of the TiO2–Zn NC on α-amylase (Type VI-B, Sigma-Aldrich, USA, A3176) was quantified using the 3,5-dinitrosalicylic acid (DNS, MilliporeSigma, USA) reduction assay. The TiO2–Zn NC underwent evaluation at concentrations ranging from 1.95 to 1000 µg mL−1, with acarbose (Bayer AG, Germany) serving as the positive control at matching dose levels. The optical density was measured at 540 nm using a UV-visible Biosystem 310 spectrophotometer.40
α-Amylase inhibition (%) = [(Absacarbose − AbsTiO2–Zn)/Absacarbose] × 100
α-Glucosidase inhibition assay. The TiO2–Zn NC (1.95–1000 µg mL−1) was screened for the suppression of the α-glucosidase (Sigma-Aldrich, USA, G5003) catalytic function. Its inhibitory potency was directly compared with that of acarbose (Bayer AG, Germany), used as the comparative standard. Optical readings were obtained at 405 nm using a Biosystem 310 Plus spectrophotometer, and inhibition percentages were calculated using the standard formula. IC50 estimates were derived via linear regression analysis by plotting the inhibition percentage against the TiO2–Zn NC concentration (1.95–1000 µg mL−1).41
α-Glucosidase inhibition % = [(Absacarbose − AbsTiO2–Zn)/Absacarbose] × 100

Statistical analysis

Statistical tests were performed using SPSS version 29. The Shapiro–Wilk test was used to assess whether the data followed a normal distribution. One-way ANOVA examined differences among experimental groups, with Tukey's HSD posthoc test identifying specific between-group differences.

Results and discussion

Physicochemical characteristics of the biogenic TiO2–Zn NC

The UV-vis spectra of the bacterial extract and biogenic TiO2–Zn NC are presented in Fig. 1. The bacterial extract (black line) showed strong absorption at 214 nm due to protein–peptide bond transitions, with a shoulder at 270–280 nm reflecting aromatic amino acids and a band at 326 nm corresponding to phenolic compounds. The biomolecules responsible for metal-ion reduction and nanoparticle surface capping during synthesis exhibited FT-IR peak shifts at 1645 → 1631 cm−1 (amide I), 1543 → 1524 cm−1 (amide II), and 1078 → 1066 cm−1 (polysaccharide C–O).
image file: d6ra00881j-f1.tif
Fig. 1 Absorption spectra of the bacterial abstract and the biogenic TiO2–Zn NC.

The TiO2–Zn NC's spectrum (red line) showed a dominant absorption at ∼210 nm, corresponding to TiO2 electronic transitions, confirming nanoparticle formation, followed by a sharp decline to a minimum near 280 nm and then a gradual rise through the visible region (400–800 nm). This visible-range tail, absent in pure TiO2, indicates bandgap narrowing due to zinc incorporation into the crystal lattice, consistent with the anatase–wurtzite heterojunction confirmed by XRD. The disappearance of the extract's biological absorption bands at 270–280 nm and 326 nm in the NC's spectrum confirms that bacterial metabolites act as reducing agents during synthesis rather than persisting as surface residues.

The FT-IR spectra revealed substantial structural modification during nanocomposite synthesis. The broad hydroxyl and amine bands near 3400 cm−1 shifted to lower frequencies, accompanied by a reduction in intensity, indicating hydrogen bond formation between biomolecules and the growing metal oxide surface. The aliphatic C–H stretching peaks at 2926 and 2855 cm−1 underwent minor red-shifts, suggesting an interaction between bacterial metabolites and nanoparticle surfaces without the complete degradation of organic capping agents. Amide I and II bands experienced significant shifts from 1645 to 1631 cm−1 and 1543 to 1524 cm−1, respectively, confirming protein coordination with metal centers through carbonyl and amine groups (Fig. 2 and Table 1). The carboxylate symmetric stretch moved from 1396 to 1384 cm−1, demonstrating the bidentate binding of carboxylic acids to metal ions.


image file: d6ra00881j-f2.tif
Fig. 2 FT-IR spectra of the bacterial extract (A) and TiO2–Zn NCs (B) with comparative peak assignments.
Table 1 FT-IR peak assignments and shifts comparing the bacterial extract and TiO2–Zn NCs
Bacterial extract (cm−1) TiO2–Zn NCs (cm−1) Functional group Vibrational mode Peak shift (cm−1) Interpretation
3420 3398 O–H, N–H Stretching −22 Hydrogen bonding between biomolecules and the nanoparticle surface
2926 2918 C–H (aliphatic) Asymmetric stretching −8 Reduced organic content or structural rearrangement
2855 2848 C–H (aliphatic) Symmetric stretching −7 Interaction of alkyl chains with the metal-oxide surface
1645 1631 C[double bond, length as m-dash]O (amide I) Stretching −14 Protein adsorption onto the nanoparticle surface
1543 1524 N–H, C–N (amide II) Bending, stretching −19 Coordination of peptide groups with metal ions
1456 1448 C–H Bending −8 Conformational changes in organic ligands
1396 1384 COO (carboxylate) Symmetric stretching −12 Carboxyl group binding to Zn2+ and Ti4+ ions
1243 1231 C–O, P[double bond, length as m-dash]O Stretching −12 Phosphate or polysaccharide interaction with nanoparticles
1078 1066 C–O (polysaccharides) Stretching −12 Capping by exopolysaccharide components
876 862 C–H aromatic Out-of-plane bending −14 Aromatic compounds involved in the reduction process
658 Ti–O Stretching New peak Formation of titanium oxide bonds
542 Zn–O Stretching New peak Formation of zinc oxide bonds
468 Ti–O–Zn Bridging vibration New peak Heterojunction formation between TiO2 and ZnO


The polysaccharide signatures around 1078 cm−1 shifted downward, verifying exopolysaccharide involvement in nanoparticle stabilization. Most critically, new absorption bands emerged at 658, 542, and 468 cm−1 corresponding to Ti–O, Zn–O, and Ti–O–Zn bridging vibrations, respectively, providing the direct evidence of successful nanocomposite formation and the presence of a heterojunction architecture between the two metal oxides.

The biosynthesized TiO2–Zn NC derived from Bacillus tequilensis MYG163 metabolites exhibited a binary crystalline structure comprising anatase TiO2 (tetragonal, space group I41/amd) and wurtzite ZnO (hexagonal, space group P63mc), confirmed by matching JCPDS references 21-1272 and 36-1451, respectively. Seventeen distinct diffraction peaks in the 2θ range of 20°–75° corresponded to eight TiO2 reflections, with the dominant (101) anatase peak at 25.28° (d = 3.52 Å and intensity = 1200 a.u.), alongside nine ZnO reflections, including the characteristic (101) wurtzite peak at 36.25° (d = 2.48 Å and intensity = 580 a.u.; Fig. 3). Scherrer analysis from the full-width half-maximum (0.353°) yielded crystallite sizes of 23.1 nm for anatase TiO2 and 23.7 nm for wurtzite ZnO, indicating nearly uniform nanoscale dimensions.


image file: d6ra00881j-f3.tif
Fig. 3 XRD pattern of the TiO2–ZnO NC biosynthesized from Bacillus tequilensis metabolites, showing the anatase (JCPDS 21-1272) and wurtzite (JCPDS 36-1451) phases.

Phase quantification based on integrated peak intensities revealed approximately equal proportions of TiO2 (51.6%) and ZnO (48.4%), establishing a balanced binary oxide system. Sharp, well-resolved diffraction peaks with minimal baseline fluctuations, coupled with an exceptional signal-to-noise ratio (148.5) and peak-to-background ratio (11.95), confirm high crystallinity and phase purity, with no detectable secondary phases or impurities. The absence of preferred-orientation effects and the systematic indexing of all major reflections validate the successful green synthesis of a homogeneous nanocomposite structure suitable for photocatalytic applications.

The SEM micrograph (Fig. 4A) recorded at 330[thin space (1/6-em)]00× magnification showed a single quasi-spherical particle with a diffuse organic corona surrounding the electron-dense core, a peripheral halo attributable to the bacterial metabolite layer deposited during biogenic synthesis and consistent with the amide I/II band shifts and carboxylate stretch displacement observed in FT-IR spectroscopy.


image file: d6ra00881j-f4.tif
Fig. 4 Electron microscopy characterization of the biogenic TiO2–Zn nanocomposite: (A) SEM micrograph (330[thin space (1/6-em)]00×; scale bar = 0.5 µm); (B) TEM image (scale bar = 100 nm); (C) HRTEM lattice fringe image (scale bar = 2 nm); and (D) SAED pattern showing polycrystalline diffraction rings indexed to anatase TiO2 and wurtzite ZnO phases.

TEM imaging (Fig. 4B) at the 100-nm scale showed primary crystallite domains assembled into a compact particle, with clearly distinguishable grain boundaries between TiO2 and ZnO domains. The granular multidomain texture and the density of these interfaces were consistent with the heterojunction architecture confirmed by HRTEM and the balanced phase proportions of 51.6% TiO2 and 48.4% ZnO determined by XRD. HRTEM (Fig. 4C) resolved two coexisting sets of lattice fringes within the same imaged domain, d = 0.348 nm, assigned to the (101) plane of anatase TiO2 (JCPDS 21-1272), and d = 0.244 nm, assigned to the (101) plane of wurtzite ZnO (JCPDS 36-1451, reference d = 0.248 nm). Their simultaneous resolution in one region is direct crystallographic proof of a two-phase nanocomposite rather than a physical mixture. The SAED pattern (Fig. 4D) reinforced this conclusion through continuous polycrystalline rings indexed to the (101), (200), and (204) planes of anatase TiO2 alongside the (002), (102), and (112) planes of wurtzite ZnO, with random crystallographic orientations confirming the intimate intermixing of both phases. This structural picture is fully consistent with the XRD-determined phase proportions of 51.6% TiO2 and 48.4% ZnO, the Scherrer crystallite sizes of 23.1 and 23.7 nm, respectively, the Ti–O–Zn bridging vibration at 468 cm−1 in FT-IR spectra, and the EDX quantification of Ti at 32.1 wt% and Zn at 29.2 wt%, collectively establishing the biogenic material as a structurally integrated TiO2/ZnO heterojunction nanocomposite.

EDX analysis verified the elemental composition of the biogenic TiO2–Zn NC. The spectrum revealed Ti at 32.1 wt% (18.4 at%), Zn at 29.2 wt% (12.3 at%), and O at 33.8 wt% (58.1 at%), confirming the successful synthesis of the binary metal oxide system (Fig. 5). Carbon, detected at 4.9 wt% (11.2 at%), originated from bacterial metabolites adsorbed on nanoparticle surfaces during biogenic synthesis, consistent with FT-IR spectra observations of organic capping agents.


image file: d6ra00881j-f5.tif
Fig. 5 EDX spectrum of the biogenic TiO2–Zn nanocomposite and its elemental composition analysis.

The atomic percentage of oxygen (58.1%) exceeded the combined metal content, indicating that both titanium and zinc were fully oxidized during nanoparticle formation. The Ti[thin space (1/6-em)]:[thin space (1/6-em)]Zn atomic ratio of approximately 1.5[thin space (1/6-em)]:[thin space (1/6-em)]1 suggests the preferential incorporation of titanium into the nanocomposite, which may influence heterojunction properties and charge-carrier dynamics at the metal–oxide interface.

The biosynthesized TiO2–ZnO NC exhibited an intensity-weighted Z-average diameter of 87.3 nm with a polydispersity index of 0.232, placing it within the monodisperse classification (PDI < 0.3). The particle size distribution displayed a symmetric Gaussian profile across intensity (87.3 nm), volume (85.1 nm), and number (82.8 nm) weighting methods, with minimal deviation between modes (5.4% range, Fig. 6). The narrow distribution width (σ = 18.45 nm) and consistent PDI values (0.232–0.258) across all measurement approaches indicate controlled nucleation during biogenic synthesis, with the bacterial metabolites functioning as effective stabilizing agents that prevent aggregation.


image file: d6ra00881j-f6.tif
Fig. 6 Particle size distribution of the TiO2–ZnO NC, showing monodispersed formation with a Z-average of 87.3 nm and a PDI of 0.232.

The overlapping distribution curves centered around 80–90 nm, lacking secondary peaks or extended tailing, confirm homogeneous particle formation without polydispersed subpopulations. This size regime (80–90 nm) positions the nanocomposite favorably for photocatalytic applications, where surface area scales with reactivity, while the tight distribution ensures reproducible antimicrobial performance by eliminating size-dependent activity variations.

The zeta potential of −34.5 mV with a narrow deviation of 1.85 mV demonstrates the strong colloidal stability of the TiO2–ZnO NC at pH 7.2, exceeding the ±30 mV threshold required for long-term dispersion stability. The sharp symmetric Gaussian distribution centered at −34.5 mV indicates a uniform surface charge across the particle population, reflecting consistent hydroxyl group deprotonation at near-neutral pH (Fig. 7).


image file: d6ra00881j-f7.tif
Fig. 7 Zeta potential distribution of the TiO2–ZnO NC, showing a mean value of −34.5 mV with a narrow deviation (σζ = 1.85 mV) at pH 7.2, indicating strong colloidal stability.

This negative surface potential generates sufficient electrostatic repulsion to prevent aggregation in aqueous media, maintaining the monodisperse character observed in DLS measurements.

TiO2–Zn NCs derived from microbial sources exhibited varied morphologies, with shapes and sizes determined by synthesis techniques, reaction conditions, and biological templates employed.42 These distinct structural characteristics directly affect their functional performance, particularly in photocatalysis and pathogen inhibition, broadening their potential uses across different fields.43 In accordance with our findings, lemon extract yielded spherical TiO2–Zn NCs measuring approximately 25 nm in diameter ,44 whereas lignin-based methods generated rod-like ZnO structures with sizes between 30 and 70 nm.45 Hibiscus rosa-sinensis, the Chinese hibiscus, facilitated the formation of ellipsoidal ZnO and spherical TiO2, while ZnO/Zn2TiO4 composites exhibited fluffy aggregate-like morphologies forms having dimensions ranging from 18 to 350 nm.46 Similarly, the Trichoderma citrinoviride extract generated TiO2 particles in various forms, such as triangles, pentagons, spheres, and rods, measuring between 10 and 400 nm, with a zeta potential of 29.5 mV.47 Hexagonal ZnO NPs produced alongside TiO2 measured about 57.87 nm on average and showed strong stability with promising antimicrobial activity.48

Hemolytic activity of the TiO2–Zn NC

The hemolytic activity assessment of the TiO2–Zn NC demonstrates excellent biocompatibility across all tested concentrations. The results show remarkably low hemolysis percentages ranging from 0.3% to 0.7%, with the highest value of 0.7% observed at a 600 µg mL−1 concentration. Even at the maximum tested concentration of 1000 µg mL−1, hemolysis remains minimal at 0.3%, well below the 5% threshold typically considered safe for biomedical applications. The absorbance values stay consistently low (0.005 to 0.031) across all concentrations, indicating negligible red blood cell membrane disruption compared to the complete hemolysis control (1.509 ± 0.009, Table 2). These findings position the TiO2–Zn NC as a promising candidate for biomedical applications where blood contact is anticipated, such as drug delivery systems or diagnostic agents, because they preserve erythrocyte integrity even at relatively high exposure levels.
Table 2 Concentration-dependent hemolysis assessment of the TiO2–Zn NC, showing absorbance values and hemolysis percentages
Sample/control Concentration (µg mL−1) Absorbance mean ± SD Hemolysis (%)
Complete hemolysis (+ve control)   1.509 ± 0.009 100
Isotonic solution (−ve control)     0
TiO2–Zn NC 1000 0.031 ± 0.004 0.3
  800 0.031 ± 0.006 0.6
  600 0.021 ± 0.002 0.7
  400 0.018 ± 0.002 0.6
  200 0.010 ± 0.001 0.4
  100 0.007 ± 0.002 0.4
  50 0.005 ± 0.002 0.3


Comparative antioxidant performance of the TiO2–Zn nanocomposite

The TiO2–Zn NC exhibited concentration-dependent scavenging activity against DPPH radicals, with an IC50 value of 11.97 ± 0.04 µg mL−1 compared to 3.08 ± 0.02 µg mL−1 for ascorbic acid. At lower concentrations (1.9–31.2 µg mL−1), the scavenging percentages ranged from 29.5% to 60.7%, showing moderate activity. The difference between the nanocomposite and ascorbic acid narrowed at higher concentrations, reaching 90.8% and 94.6% at 500 µg mL−1 and 94.8% and 97.8% at 1000 µg mL−1, respectively (Table 3). The nanocomposite's scavenging percentage increased by 65.3 percentage points across the concentration range, demonstrating its capacity to neutralize DPPH radicals, though with lower efficiency than the reference compound.
Table 3 DPPH and ABTS radical scavenging activity of the TiO2–Zn NC and ascorbic acid at varying concentrations
Conc. (µg mL−1) Antioxidant scavenging activity
TiO2–Zn NC DPPH scavenging % IC50 = 11.97 ± 0.04 µg mL−1 Ascorbic acid DPPH scavenging % IC50 = 3.08 ± 0.02 µg mL−1 TiO2–Zn NC ABTS˙+ scavenging% IC50 = 7.65 ± 0.09 µg mL−1 ABTS˙+ ascorbic acid scavenging % IC50 = 4.29 ± 0.09 µg mL−1
1.9 29.5 42.7 35.9 44.5
3.9 37.5 49.5 42.3 50.4
7.8 46 57.9 50.6 54.5
15.6 52.1 66.2 55.8 58.2
31.2 60.7 74.1 64.5 66.3
62.5 68.8 82.6 72.4 74.2
125 76.2 90 79.1 80.6
250 84.9 92.6 85.5 87.5
500 90.8 94.6 90.6 94.4
1000 94.8 97.8 93.7 96.1


For ABTS˙+ radical scavenging activity, the nanocomposite showed better performance in the ABTS assay, exhibiting an IC50 of 7.65 ± 0.09 µg mL−1 compared to 4.29 ± 0.09 µg mL−1 for ascorbic acid. The scavenging percentage ranged from 35.9% at the lowest concentration to 93.7% at 1000 µg mL−1, a 57.8 percentage-point increase. The nanocomposite's values maintained proximity to ascorbic acid values throughout the concentration series, with differences of 8.6% at 1.9 µg mL−1 and just 2.4% at the maximum concentration. Between 62.5 and 250 µg mL−1, the nanocomposite achieved 72.4–85.5% scavenging, indicating substantial radical neutralization within the practical concentration range (Table 3). Based on the IC50 values obtained, particularly 7.65 µg mL−1 for ABTS, the TiO2–Zn NC showed considerable potential as an antioxidant agent and was worthy of further investigation for applications requiring free radical scavenging properties.

TiO2–Zn NCs neutralize DPPH and ABTS radicals by donating electrons through single-electron transfer pathways, where ABTS reacts via sequential proton loss electron transfer (SPLET) mechanisms in water, while DPPH follows similar routes in alcoholic media.49 At the interface between TiO2 and ZnO crystals, heterojunction structures permit excited electrons to move from ZnO's conduction band into TiO2's conduction band, and holes simultaneously migrate in reverse, from TiO2's valence band to ZnO's valence band,50 which suppresses electron–hole recombination and extends the lifespan of reactive oxygen species involved in scavenging free radicals.51

Green synthesis using biological sources (bacteria, plants, and algae) offers distinct advantages by depositing bioactive metabolites, including proteins, polysaccharides, and secondary metabolites, onto nanoparticle surfaces during formation.7 Such metabolites serve dual functions as stabilizing agents and direct radical scavengers that amplify the antioxidant capacity beyond what chemical synthesis achieves.52 For instance, Mucor racemosus-mediated ZnO NPs demonstrated an IC50 value of 69.2 µg mL−1, with inhibition reaching 68.36% at a 200 µg mL−1 concentration,53 while lemon extract-mediated Zn–TiO2 nanocomposites achieved 94% DPPH scavenging at a 50 µL concentration compared to 91% for standard antioxidants,44 and plant-synthesized TiO2 NPs exhibited IC50 values ranging from 48.66 to 109.94 µg mL−1 across DPPH, ABTS, and H2O2 assays.54

The biosynthetic route, therefore, not only provides ecofriendly production but also functionalizes nanocomposite surfaces with organic ligands that directly participate in electron donation to radicals, creating a synergistic effect between inorganic electron transfer mechanisms and organic radical scavenging.55

Anti-inflammatory profile of the TiO2–Zn NC

The biogenic TiO2–Zn NC exhibited significant anti-inflammatory activity, with dose-dependent inhibition of both COX-1 and COX-2. Against COX-2, the NC achieved an IC50 of 14.13 ± 0.5 µg mL−1, demonstrating stronger selectivity than its COX-1 inhibition (IC50 = 25.91 ± 0.3 µg mL−1), yielding a selectivity ratio of approximately 1.8-fold in favor of COX-2. Notable inhibition milestones included 49.3% COX-2 inhibition at just 7.8 µg mL−1 and 77.3% inhibition at 250 µg mL−1, while at the maximum concentration of 1000 µg mL−1, the NC exhibited 88.5% COX-1 inhibition and 90.6% COX-2 inhibition (Table 4). The NC demonstrated a promising COX-2 preferential profile, which is therapeutically desirable because COX-2 mediates inflammatory responses, while COX-1 serves protective gastrointestinal functions.
Table 4 In vitro COX-1 and COX-2 inhibitory activity of the biogenic TiO2–Zn NC
Conc. (µg mL−1) COX inhibition assessment
TiO2–Zn NC COX-1 inhibition % IC50 = 25.91 ± 0.3 µg mL−1 Celecoxib COX-1 inhibition % IC50 = 3.42 ± 0.9 µg mL−1 TiO2–Zn NC COX-2 inhibition % IC50 = 14.13 ± 0.5 µg mL−1 Celecoxib COX-2 inhibition % IC50 = 4.11 ± 0.5 µg mL−1
0.5 9 29.3 15.3 27.8
1 16.4 38.7 26.5 31.5
2 21.1 45.4 31.3 47.3
3.9 29.4 50.9 37.5 51.4
7.8 37.3 58 49.3 57.5
15.6 46.5 64.8 51.4 62.9
31.25 52.1 72.5 57.5 69.8
62.5 58.4 78 62.1 76.7
125 65.3 86 69.2 84.3
250 73.7 90.3 77.3 89.1
500 82.8 94.1 83.2 92.8
1000 88.5 98 90.6 97.3


The inhibition patterns showed concentration-dependent increase across the entire range tested (0.5–1000 µg mL−1), with substantial activity emerging above 15.6 µg mL−1, where both enzymes showed greater than 50% inhibition, positioning these biogenic nanocomposites as viable candidates for anti-inflammatory applications with reduced gastrointestinal side effects compared to nonselective NSAIDs.

Regarding the BSA assessment, the NC demonstrated considerable anti-inflammatory activity by inhibiting protein denaturation, with an IC50 of 2.78 ± 0.05 µg mL−1. The NC displayed concentration-dependent protection against BSA denaturation across the tested range of 1.56–200 µg mL−1, with 50.8% inhibition at 3.125 µg mL−1, which increased to 89.3% at 100 µg mL−1 and 93.4% at the maximum concentration of 200 µg mL−1 (Table 5). The low IC50 value indicates a strong membrane-stabilizing capacity, as protein denaturation is a key mechanism underlying inflammation, where heat-induced unfolding mimics pathological conditions. At 25 µg mL−1, the NC achieved 78.3% inhibition, showing substantial activity well below cytotoxic thresholds. Compared to diclofenac sodium (IC50 = 1.63 ± 0.02 µg mL−1), the NC exhibited approximately 1.7-fold higher IC50 values, yet both materials exhibited comparable maximum inhibition percentages above 90% at higher concentrations.

Table 5 Protein denaturation inhibition of the TiO2–Zn NC and diclofenac sodium using the BSA assay
Conc. (µg mL−1) BSA inhibition analysis
TiO2–Zn NC inhibition % IC50 = 2.78 ± 0.05 µg mL−1 Diclofenac sodium inhibition % IC50 = 1.63 ± 0.02 µg mL−1
1.56 40.7 45.5
3.12 50.8 55.8
6.25 58.7 65.0
12.5 68.8 75.2
25 78.3 82.8
50 83.9 90.2
100 89.3 92.5
200 93.4 96.2


Research has demonstrated that TiO2-NPs trigger COX-2 expression in human periodontal ligament cells by generating reactive oxygen species (ROS), a process mediated through NF-κB signalling activation.56 Interestingly, the incorporation of ZnO NPs into TiO2 results in diminished cytotoxic and genotoxic effects, attributed to TiO2's capacity to adsorb Zn2+ ions, thereby altering inflammatory pathways through antagonistic mechanisms.57 Studies on ZnO NPs integrated within TiO2 nanotubes have revealed substantial anti-inflammatory effects by suppressing both macrophage proliferation and adhesion, indirectly suggesting decreased COX-2 activity, because this enzyme plays a central role in inflammatory cascades.58 The selective nature of TiO2–Zn NCs becomes apparent in their preferential inhibition of COX-2, which experiences upregulation during inflammatory states, and their minimal effect on COX-1, thereby circumventing adverse effects commonly linked to nonselective NSAIDs.59 Beyond enzyme inhibition, these nanocomposites markedly decrease proinflammatory cytokine levels, including IL-6 and inducible nitric oxide synthase (iNOS), within macrophages, signifying potent anti-inflammatory action.60 The synergistic architecture of TiO2–Zn NCs thus provides multiple therapeutic avenues through targeted COX-2 suppression, cytokine regulation, and macrophage function modulation, while TiO2's adsorption of Zn2+ ions concurrently mitigates cytotoxic consequences and influences COX-2-related biological pathways.61

Antimicrobial evaluation of the biogenic TiO2–Zn NC

The biogenic TiO2–Zn NC exhibited an inhibition zone of 35 ± 0.4 mm against B. subtilis, compared to 31 ± 0.8 mm exhibited by gentamicin. At the same time, the nanocomposite and gentamicin exhibited inhibition zones against methicillin-resistant S. aureus (MRSA) of 22 ± 0.4 mm and 20 ± 1.0 mm, respectively, indicating superior activity against Gram-positive bacteria. Among this group, B. subtilis showed the largest inhibition zone, while MRSA showed the smallest. For Gram-negative bacteria, the nanocomposite and gentamicin exhibited inhibition zones of 25 ± 1.0 mm vs. 26 ± 0.7 mm for K. pneumoniae, 26 ± 0.3 mm vs. 28 ± 1.3 mm for S. typhi, and 19 ± 1.0 mm vs. 23 ± 0.3 mm for P. vulgaris, respectively (Fig. 8), revealing reduced effectiveness against Gram-negative bacteria. P. vulgaris showed the weakest inhibition at 19 ± 1.0 mm, while S. typhi exhibited the strongest at 26 ± 0.3 mm within this category (Fig. 8).
image file: d6ra00881j-f8.tif
Fig. 8 Antimicrobial activity of the TiO2–ZnO NC (A) and gentamicin (C) against bacterial and fungal pathogens compared to the blank control (B), measured by the inhibition zone diameter (mm). Fluconazole was used as the reference antifungal drug against fungal pathogens.

Among fungal pathogens, C. albicans showed an inhibition zone of 33 ± 0.5 mm for the nanocomposite vs. 31 ± 1.0 mm for fluconazole, while F. oxysporum showed 25 ± 0.6 mm compared to fluconazole's 33 ± 0.6 mm (Fig. 8), where the nanocomposite matched or exceeded fluconazole against the yeast but underperformed against the filamentous fungus. The nanocomposite demonstrated the strongest antimicrobial potential against B. subtilis (35 ± 0.4 mm) and C. albicans (33 ± 0.5 mm), while P. vulgaris proved most resistant (19 ± 1.0 mm, Fig. 8), suggesting selective efficacy influenced by the cell wall architecture and metabolic pathways unique to each microbial species.

Antidiabetic potential of the TiO2–Zn NC through α-amylase and α-glucosidase inhibition

The biogenic NC demonstrated inhibitory activity against α-amylase, with an IC50 of 12.98 ± 0.88 µg mL−1, compared with 7.31 ± 0.11 µg mL−1 for acarbose. At the initial concentration of 1.95 µg mL−1, the NC achieved 26.7% inhibition, which increased progressively to 95.8% at 1000 µg mL−1, a total increment of 69.1 percentage points. The inhibition percentages remained within 6–8% of acarbose values across most concentrations, with the difference narrowing to just 1.4% at the highest dose (95.8% vs. 97.2%, Table 6). Between 31.25 and 250 µg mL−1, the nanocomposite exhibited 62.8–81.4% inhibition, covering the therapeutically relevant concentration range.
Table 6 α-Amylase and α-glucosidase inhibitory activity of the TiO2–Zn NC compared to the acarbose standard at varying concentrations
In vitro antidiabetic assessment
Conc. (µg mL−1) α-Amylase inhibition α-Glucosidase inhibition
TiO2–Zn NC inhibition % IC50 = 12.98 ± 0.88 µg mL−1 Acarbose inhibition % IC50 = 7.31 ± 0.11 µg mL−1 TiO2–Zn NC inhibition % IC50 = 9.34 ± 0.32 µg mL−1 Acarbose inhibition % IC50 = 5.02 ± 0.19 µg mL−1
1.95 26.7 32.9 32 38.7
3.9 35.7 42.1 39.5 47.1
7.81 44.8 51 48 55.2
15.62 55.1 59.6 56.3 61.2
31.25 62.8 66.5 65.1 67.5
62.5 70.1 75.1 71.4 75.5
125 76 82.3 77.6 82.8
250 81.4 89.6 83.7 89.1
500 89.6 92 89.6 93.6
1000 95.8 97.2 93 96.7


The relatively close IC50 values and consistent inhibition pattern across the dose range indicate that the nanocomposite effectively blocks α-amylase activity, though requiring modestly higher concentrations than the standard drug.

Regarding α-glucosidase inhibition, the nanocomposite showed stronger activity against α-glucosidase, with an IC50 of 9.34 ± 0.32 µg mL−1, compared to 5.02 ± 0.19 µg mL−1 for acarbose. Inhibition values ranged from 32% at 1.95 µg mL−1 to 93% at 1000 µg mL−1, representing a 61 percentage-point increase. The NC maintained inhibition percentages of 5–7% below acarbose levels throughout the low-to-mid concentration range, with this gap reducing to 3.7% at the maximum concentration. At clinically relevant concentrations (62.5–250 µg mL−1), inhibition ranged from 71.4% to 83.7%, demonstrating substantial enzyme blockade (Table 6). The IC50 value below 10 µg mL−1, combined with inhibition exceeding 89% at higher concentrations, positions the TiO2–Zn NC as a candidate material for glucose management applications targeting postprandial hyperglycemia.

According to our findings, Cydonia oblonga-mediated ZnO NPs (20–50 nm, spherical) inhibited α-amylase by 81.7% and α-glucosidase by 86.9% at 100 µg mL−1.62 Furthermore, ZnO NPs from Myristica fragrans (spherical/elliptical, 41–23 nm) exhibited α-amylase and α-glucosidase IC50 values of 73.23 ± 0.42 and 65.21 ± 0.49 µg mL−1, respectively.63 Cube-shaped ZnO NPs from Lessertia montana inhibited α-amylase and α-glucosidase at IC50 concentrations of 0.120 and 0.037 g L−1, respectively.64 Streptomyces vinaceusdrappus-mediated TiO2 NPs (spherical, 10–50 nm, anatase) demonstrated IC50 values of 69.3 µg mL−1 against α-amylase and 40.81 µg mL−1 against α-glucosidase.27 TiO2 NPs enhanced α-amylase production in Aspergillus niger, raising the specific activity from 12[thin space (1/6-em)]037 to 15[thin space (1/6-em)]523 U mg−1.65 Another study reported that the immobilization of α-amylase onto TiO2 NPs preserved 95% of the enzymatic activity and improved heat resistance, with nearly complete activity recovery following thermal deactivation.66 Another research showed that TiO2 NPs reduced salivary α-amylase function by 34% under in vitro conditions, though this inhibitory effect weakened in intestinal environments.67

TiO2–Zn NCs demonstrate antidiabetic efficacy through several integrated biological pathways. These nanostructures function by competitively blocking α-amylase through active site occupation, thereby restricting starch accessibility, whereas α-glucosidase experiences noncompetitive suppression via allosteric site binding, which modifies the enzyme structure, ultimately delaying carbohydrate breakdown and regulating postmeal blood glucose elevation.68 The gradual liberation of Zn2+ ions proves instrumental in facilitating insulin biosynthesis, storage, and release from pancreatic β-cells, alongside amplifying insulin responsiveness by stimulating glucose transporter protein expression (GLUT-2 and GLUT-4) and activating glucokinase, a pivotal enzyme governing glucose metabolism.69,70

Beyond enzyme modulation, ZnO nanoparticles trigger GLUT-4 membrane translocation, accelerate β-cell regeneration, and diminish oxidative burden, consequently preserving pancreatic islet architectural integrity.71 The therapeutic profile expands through the inhibition of AGE formation, addressing critical diabetic sequelae such as neurodegeneration, obesity, renal impairment, and retinopathy.72 This integrated strategy, encompassing enzyme suppression, insulin pathway enhancement, β-cell preservation, and oxidative stress mitigation, establishes TiO2–Zn NCs as viable therapeutic alternatives with reduced gastrointestinal complications relative to standard medications, including acarbose, miglitol, and voglibose.73,74

This study presents initial evidence that biogenic TiO2–Zn NCs synthesized via Bacillus tequilensis MYG163 metabolites possess multiple therapeutic properties. Future work should prioritize animal models of wound healing and hyperglycemia, followed by mechanistic studies employing gene expression profiling. Investigating photocatalytic performance under visible light could expand environmental applications, while scale-up feasibility and long-term colloidal stability testing would address industrial viability. Examining the nanocomposite's behavior in complex biological matrices and against drug-resistant clinical isolates would better define its therapeutic boundaries and inform rational formulation strategies.

Conclusion

The TiO2–Zn NC biosynthesized through Bacillus tequilensis MYG163 metabolites exhibited multifunctional biomedical properties across five therapeutic domains. The spherical nanoparticles (primary size = 8–15 nm, hydrodynamic diameter = 87.3 nm) demonstrated structural integrity through anatase–wurtzite phase coexistence and maintained colloidal stability at a −34.5 mV zeta potential. Hemolytic activity stayed well below safety thresholds, confirming blood compatibility. The nanocomposite scavenged DPPH and ABTS radicals with concentration-dependent efficiency. Anti-inflammatory tests revealed preferential COX-2 suppression over COX-1 and significant inhibition of protein denaturation. Antimicrobial assays showed strong activity against Gram-positive bacteria and fungi, surpassing standard agents, though G −ve strains exhibited moderate resistance. Antidiabetic screening demonstrated dual enzyme blockade, with stronger α-glucosidase inhibition than α-amylase suppression.

The convergence of these activities within a single bacterial-mediated synthesis platform indicates that Red Sea-derived Bacillus strains can generate metal oxide heterojunctions capable of addressing interconnected pathological processes. Bacterial metabolites functioned simultaneously as reducing agents, crystal growth directors, and surface stabilizers, yielding nanostructures with therapeutic attributes that chemical synthesis routes rarely achieve. These results establish a foundation for developing multitarget therapeutic agents that operate through complementary biochemical pathways rather than single-mechanism interventions.

Author contributions

Methodology: I. M. I., M. A., D. A., N. M. Z., F. A. S. A., I. A. Investigation: H. A. A., Z. A., A. E. A. Formal analysis and visualization: A. G., A. E. A., Z. A., I. A., D. A., F. A. S. A. Data curation and validation: D. A., M. A., I. M. I., A. A. A. Writing – original draft: A. G., H. A. A., D. A. Writing – review & editing: A. G., I. A., Z. A.

Conflicts of interest

The authors state that they have no conflicts of interest to declare.

Data availability

Data are available by contacting the corresponding author.

Acknowledgements

The project was funded by the Deanship of Scientific Research (DSR) At King Abdulaziz University, Jeddah, Saudi Arabia under grant no. (IPP: 942-140-2025). The authors, therefore, acknowledge with thanks DSR for technical and financial support.

References

  1. S. Shukar, F. Zahoor, K. Hayat, A. Saeed, A. H. Gillani, S. Omer, S. Hu, Z.-U.-D. Babar, Y. Fang and C. Yang, Front. Pharmacol, 2021, 12, 693426 CrossRef CAS PubMed.
  2. C. D. Haydinger, G. F. Oliver, L. M. Ashander and J. R. Smith, Antioxidants, 2023, 12, 1649 CrossRef CAS PubMed.
  3. A. Hussain, S. Ashique, O. Afzal, M. A. Altamimi, A. Malik, S. Kumar, A. Garg, N. Sharma, A. Farid, T. Khan and A. S. A. Altamimi, Exp. Eye Res., 2023, 236, 109650 CrossRef CAS PubMed.
  4. R. Yadav, N. Sana, U. Afaq, C. Bibi and J. Khatoon, in A Mechanistic Exploration of Natural Compounds for Neuronal Health, ed. S. Jahan, A. J. Siddiqui and A. Khan, Springer Nature, Singapore, 2025, pp. 207–225 Search PubMed.
  5. S. Salm, J. Rutz, M. van den Akker, R. A. Blaheta and B. E. Bachmeier, Front. Pharmacol., 2023, 14, 1234701 CrossRef PubMed.
  6. P. Shanumuganandam and S. Thangavelu, BioMetals, 2026, 39(1), 25–57 CrossRef CAS PubMed.
  7. A. Ghareeb, A. Fouda, R. Kishk and W. Kazzaz, Microb. Cell Factories, 2024, 23, 341 CrossRef CAS PubMed.
  8. R. Sharma and J. Prakash, in Titanium Dioxide-Based Multifunctional Hybrid Nanomaterials: Application on Health, Energy and Environment, ed. J. Prakash, J. Cho, O. Ruzimuradov and D. Fang, Springer Nature Switzerland, Cham, 2025, pp. 1–25 Search PubMed.
  9. A. M. Mohammed, M. Mohammed, J. K. Oleiwi, F. H. Ihmedee, T. Adam, B. O. Betar and S. C. B. Gopinath, Nano TransMed, 2025, 4, 100097 CrossRef.
  10. N. H. S. Suhaimi, R. Azhar, N. S. Adzis, M. A. Mohd Ishak, M. Z. Ramli, M. Y. Hamzah, K. Ismail and W. I. Nawawi, Desalin. Water Treat., 2025, 321, 100976 CrossRef CAS.
  11. S. Dey, D. lochan Mohanty, N. Divya, V. Bakshi, A. Mohanty, D. Rath, S. Das, A. Mondal, S. Roy and R. Sabui, Intell. Pharm., 2025, 3, 53–70 Search PubMed.
  12. I. Abdelfattah and A. M. El-Shamy, Sci. Rep., 2024, 14, 27175 CrossRef CAS PubMed.
  13. J. Pei, X. Wan, M. Guo, J. Mi, W. Wu, Y. Hong, P. Hu, P. Chen, L. Chen, S. Xiang, Q. Zhang, H. Zeng, L. Liu, X. Fan and B. Yu, Chem. Eng. J., 2025, 523, 168624 CrossRef CAS.
  14. J. Pei, X. Wan, M. Guo, J. Mi, W. Wu, Y. Hong, P. Hu, P. Chen, L. Chen, S. Xiang, Q. Zhang, H. Zeng, L. Liu, X. Fan and B. Yu, Chem. Eng. J., 2025, 523, 168624 CrossRef CAS.
  15. M. Shahalaei, A. K. Azad, W. M. A. W. Sulaiman, A. Derakhshani, E. B. Mofakham, M. Mallandrich, V. Kumarasamy and V. Subramaniyan, Front. Chem., 2024, 12, 1398979 Search PubMed.
  16. G. Maglione, P. Zinno, A. Tropea, C. U. Mussagy, L. Dufossé, D. Giuffrida and A. Mondello, AIMS Microbiol., 2024, 10, 723–755 CAS.
  17. X. Blanco Crivelli, C. Cundon, M. Bonino, M. S. Sanin and A. Bentancor, Bacteria, 2024, 3, 256–270 CrossRef.
  18. J. Qian, Y. Wang, Z. Hu, T. Shi, Y. Wang, C. Ye and H. Huang, Biotechnol. Adv., 2023, 69, 108278 CrossRef CAS PubMed.
  19. M. Duraisamy, S. Sreekantan, G. A. Govindasamy, S. S. Murthe, J. N. Appaturi and S. S. Md Noor, J. Sol-Gel Sci. Technol., 2025, 115, 1156–1168 CrossRef CAS.
  20. M. S. Missier, M. Ramakrishnan, S. D. Sudalaimani Paulpandian, S. Rajeshkumar and M. Tania, Bioinformation, 2023, 19, 638–643 CrossRef PubMed.
  21. E. R. Sheltagh, O. Almukhtar, M. F. Rafeeq, K. H. Rasool, S. A. Mahdi, K. H. Jawad, B. A. Hasoon, A. Abdullah Issa, M. S. Jabir and S. F. Jawad, Inorg. Chem. Commun., 2024, 169, 112994 CrossRef CAS.
  22. J. Chen, Y. Jia, Y. Sun, K. Liu, C. Zhou, C. Liu, D. Li, G. Liu, C. Zhang, T. Yang, L. Huang, Y. Zhuang, D. Wang, D. Xu, Q. Zhong, Y. Guo, A. Li, I. Seim, L. Jiang, L. Wang, S. M. Y. Lee, Y. Liu, D. Wang, G. Zhang, S. Liu, X. Wei, Z. Yue, S. Zheng, X. Shen, S. Wang, C. Qi, J. Chen, C. Ye, F. Zhao, J. Wang, J. Fan, B. Li, J. Sun, X. Jia, Z. Xia, H. Zhang, J. Liu, Y. Zheng, X. Liu, J. Wang, H. Yang, K. Kristiansen, X. Xu, T. Mock, S. Li, W. Zhang and G. Fan, Nature, 2024, 633, 371–379 CrossRef CAS PubMed.
  23. A. J. A. A.-H. Alkawaz, M. S. Naser and A. J. Obaid, Micro, 2025, 5, 45 CrossRef.
  24. R. A. Metwally, J. El Nady, S. Ebrahim, A. El Sikaily, N. A. El-Sersy, S. A. Sabry and H. A. Ghozlan, Microb. Cell Factories, 2023, 22, 78 CrossRef CAS PubMed.
  25. R. H. Naser, M. I. Attia, Z. Alatawi, H. A. Alahmadi, N. A. Tharwat, F. M. K. Albaqami, I. Alshami, T. A. Yousef, I. M. Ibrahim, A. Al-Dakhil, A. Fouda and A. Ghareeb, Rev. Adv. Mater. Sci., 2025, 5, 45 Search PubMed.
  26. A. A. Al-Sharqi, M. E. Eissa, D. Alyousfi, A. E. Alharbi, I. M. Ibrahim, S. M. Abdelkhalig, F. M. K. Albaqami, A. M. Eldesoky, A. A. Sherbini, T. A. Yousef, M. N. Goda and A. Ghareeb, RSC Adv., 2026, 16, 7132–7148 RSC.
  27. A. Ghareeb, A. Fouda, R. M. Kishk and W. M. El Kazzaz, Sci. Rep., 2025, 15, 20244 CrossRef CAS PubMed.
  28. M. M. Ghaith, R. A. Almaimani, A. Ghareeb, M. M. Habibullah, S. M. Abdelkhalig, H. AlOmari, F. M. K. Albaqami, F. O. Albaldi, S. A. Alnumaani, S. Z. Alshawwa, A. A. Alrashidi and H. F. A. El-Kareem, RSC Adv., 2025, 15, 39391–39407 RSC.
  29. A. Ghareeb, A. Fouda, R. Kishk and W. Kazzaz, BMC Complementary Med. Ther., 2025, 25, 73 CrossRef PubMed.
  30. A. Gunasekaran, A. K. Rajamani, C. Masilamani, I. Chinnappan, U. Ramamoorthy and K. Kaviyarasu, Catalysts, 2023, 13, 215 CrossRef CAS.
  31. S. Rao, M. P. Shilpa, S. J. Shetty, S. S. Bhat, N. B. Gummagol, S. Surabhi and S. C. Gurumurthy, J. Mater. Sci.:Mater. Electron., 2025, 36, 1144 CrossRef CAS.
  32. S. Karmakar, Adv. Genet., 2019, 117–159 Search PubMed.
  33. V. Bulmus, M. Woodward, L. Lin, N. Murthy, P. Stayton and A. Hoffman, J. Controlled Release, 2003, 93, 105–120 CrossRef CAS PubMed.
  34. M. Khowdiary, Z. Alatawi, A. Alhowiti, M. Amin, H. Daghistani, F. Albaqami, M. A. Abdel-Rahman, A. Ghareeb, N. A. Shaer and A. Fouda, Life, 2024, 14, 1629 CrossRef CAS PubMed.
  35. S. S. Aljameel, M. E. Eissa, Z. Alatawi, H. A. Alahmadi, M. E. Azab, T. A. Yousef, S. K. Ramadan, H. A. Aljohi, E. S. Al-Farraj, E. A. Bahattab, A. Ghareeb and E. A. E. El-Helw, Libyan J. Med., 2026, 21, 2642992 CrossRef PubMed.
  36. N. K. Alharbi, Z. F. Azeez, H. M. Alhussain, A. M. A. Shahlol, M. O. I. Albureikan, M. G. Elsehrawy, G. S. Aloraini, M. El-Nablaway, E. M. Khatrawi and A. Ghareeb, Front. Microbiol., 2024, 15, 1385493 CrossRef CAS PubMed.
  37. R. H. Naser, Z. F. Azeez, Z. Alatawi, A. Albalawi, T. Shamrani, A. M. A. Shahlol, M. El-Nablaway, H. A. Alahmadi, G. S. Aloraini, N. A. Tharwat, A. Fouda and A. Ghareeb, RSC Adv., 2025, 15, 17203–17221 RSC.
  38. A. Ameena M, M. Arumugham I, K. Ramalingam and S. Rajeshkumar, Cureus, 2023, 15, e46003 Search PubMed.
  39. E. M. Khatrawi, Z. F. Azeez, R. H. Naser, O. Alharbi, Z. Alatawi, A. A. Najjar, E. Mattar, F. M. K. Albaqami, S. A. Mandour, I. Alshami, I. M. Ibrahim, M. A. Bazuhair and A. Ghareeb, J. Taibah Univ. Sci., 2025, 19, 2602222 CrossRef.
  40. G. S. Aloraini, M. O. I. Albureikan, A. M. A. Shahlol, T. Shamrani, H. Daghistani, M. El-Nablaway, N. A. Tharwat, A. M. Elazzazy, A. F. Basyony and A. Ghareeb, Rev. Adv. Mater. Sci., 2024, 63(1), 20240016 Search PubMed.
  41. A. Ghareeb, A. Fouda, R. M. Kishk and W. M. El Kazzaz, Int. J. Biol. Macromol., 2024, 133861 CrossRef CAS PubMed.
  42. F. Pinzari, Reactions, 2024, 5, 680–739 Search PubMed.
  43. I. Abdelfattah and A. M. El-Shamy, Sci. Rep., 2024, 14, 27175 Search PubMed.
  44. M. S. Missier, M. Ramakrishnan, S. D. Sudalaimani Paulpandian, S. Rajeshkumar and M. Tania, Bioinformation, 2023, 19, 638–643 CrossRef PubMed.
  45. K. M. Samb-Joshi, Y. A. Sethi, A. A. Ambalkar, H. B. Sonawane, S. P. Rasale, R. P. Panmand, R. Patil, B. B. Kale and M. G. Chaskar, J. Compos. Sci., 2019, 3, 90 CrossRef CAS.
  46. M. F. H. Abd El-Kader, M. T. Elabbasy, A. A. Adeboye, M. G. M. Zeariya and A. A. Menazea, J. Mater. Res. Technol., 2021, 15, 2213–2220 CrossRef CAS.
  47. S. Arya, H. Sonawane, S. Math, P. Tambade, M. Chaskar and D. Shinde, Int. Nano Lett., 2021, 11, 35–42 Search PubMed.
  48. M. Masoudi, M. Mashreghi, A. Zenhari and A. Mashreghi, Int. J. Pharm., 2024, 652, 123821 CrossRef CAS PubMed.
  49. M. Platzer, S. Kiese, T. Herfellner, U. Schweiggert-Weisz, O. Miesbauer and P. Eisner, Molecules, 2021, 26, 1244 Search PubMed.
  50. C. Cheng, A. Amini, C. Zhu, Z. Xu, H. Song and N. Wang, Sci. Rep., 2014, 4, 4181 CrossRef PubMed.
  51. F. Pinzari, Reactions, 2024, 5, 680–739 CrossRef CAS.
  52. R. Saxena, S. Kotnala, S. C. Bhatt, M. Uniyal, B. S. Rawat, P. Negi and M. K. Riyal, Sustain. Chem. Clim. Action, 2025, 6, 100071 CrossRef.
  53. F. M. Elkady, B. M. Badr, E. Saied, A. H. Hashem, M. S. Abdulrahman, M. M. Alkherkhisy, T. A. Selim, F. M. Alshabrmi, E. A. Alatawi, F. F. Aba Alkhayl, A. Salama, M. S. Mansy and M. Aufy, Sci. Rep., 2025, 15, 18772 CrossRef CAS PubMed.
  54. A. Bhatti, A. Sanchez-Martinez, G. Sanchez-Ante, D. A. Jacobo-Velázquez, J. A. Qui-Zapata, S. S. Mahmoud, G. M. Channa, L. M. Lozano, J. L. Mejía-Méndez, E. R. López-Mena and D. E. Navarro-López, Antioxidants, 2025, 14, 707 CrossRef CAS PubMed.
  55. G. S. El-Sayyad, D. Elfadil, M. A. Mosleh, Y. A. Hasanien, A. Mostafa, R. S. Abdelkader, N. Refaey, E. M. Elkafoury, G. Eshaq, E. A. Abdelrahman, M. N. Malash, S. H. Rizk, M. Gobara, H. G. Nada, A. H. Hashem, M. S. Attia, A. M. Noreddin, M. I. A. Abdel Maksoud, M. M. Ghobashy, D. E. Basher, R. Magdy, W. F. Elkhatib and A. I. El-Batal, BioNanoScience, 2024, 14, 3617–3659 CrossRef.
  56. D.-H. Kim, J. Kundu, I. G. Chae, J. K. Lee, J. S. Heo and K.-S. Chun, J. Toxicol. Sci., 2019, 44, 335–345 CrossRef CAS PubMed.
  57. A. Gunasekaran, A. K. Rajamani, C. Masilamani, I. Chinnappan, U. Ramamoorthy and K. Kaviyarasu, Catalysts, 2023, 13, 215 CrossRef CAS.
  58. F. Pinzari, Reactions, 2024, 5, 680–739 CrossRef CAS.
  59. T. R. Lakshman, J. Deb and T. K. Paine, Dalton Trans., 2016, 45, 14053–14057 RSC.
  60. D. Lomada, S. Gulla and M. C. Reddy, Chem. Biodiversity, 2023, 20, e202301188 CrossRef CAS PubMed.
  61. A. Yavaş, Ö. Kesmez, F. Demir and M. Aksel, Biol. Trace Elem. Res., 2026, 204, 25–37 CrossRef PubMed.
  62. M. Sajid Khan, S. Sultana and M. Akram, Pak. J. Pharm. Sci., 2025, 38, 1647–1655 Search PubMed.
  63. S. Faisal, H. Jan, S. A. Shah, S. Shah, A. Khan, M. T. Akbar, M. Rizwan, F. Jan, Wajidullah, N. Akhtar, A. Khattak and S. Syed, ACS Omega, 2021, 6, 9709–9722 CrossRef CAS PubMed.
  64. F. O. Balogun and A. O. T. Ashafa, Acta Biol., 2020, 64, 239–249 Search PubMed.
  65. A. A. Ciloci, V. P. Bulimaga, S. F. Clapco, S. V. Labliuc and E. G. Dvornina, Surf. Eng. Appl. Electrochem., 2025, 61, 164–170 Search PubMed.
  66. R. Ahmad, A. Mishra and M. Sardar, Adv. Sci., Eng. Med., 2014, 6, 1264–1268 CrossRef CAS.
  67. W. Dudefoi, H. Rabesona, C. Rivard, M. Mercier-Bonin, B. Humbert, H. Terrisse and M.-H. Ropers, Food Funct., 2021, 12, 5975–5988 RSC.
  68. S. Shafique, Z. Khalid, S. Arif, Z. Noreen, L. Tabassam and M. Waseem, Inorg. Chem. Commun., 2024, 163, 112383 CrossRef CAS.
  69. A. Nakamura, T. Kido, Y. Seki and M. Suka, J. Trace Elem. Med. Biol., 2024, 83, 127375 CrossRef CAS PubMed.
  70. A. Q. Nkemzi, K. Okaiyeto, O. Oyenihi, C. S. Opuwari, O. E. Ekpo and O. O. Oguntibeju, 3 Biotech, 2024, 14, 291 CrossRef PubMed.
  71. N. Elassy, S. El-Dafrawy, A. O. Abd El-Azim, O. A. Y. El-Khawaga and A. Negm, IET Nanobiotechnol., 2020, 14, 680–687 CrossRef PubMed.
  72. A. Ragu Prasath and K. Selvam, Biomed. Mater. & Devices, 2025, 3(3), 422 Search PubMed.
  73. A. Ebrahimikia, A. Bahari and M. Roeinfard, J. Inorg. Organomet. Polym. Mater., 2025, 35, 6546–6560 CrossRef CAS.
  74. S. Joseph, D. Nallaswamy, S. Rajeshkumar, P. Dathan and L. Jose, J. Clin. Diagn. Res., 2024, 18(12) DOI:10.7860/JCDR/2024/69854.19399.

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