2.1. Chemicals, cultures and mammalian cell lines

Necessary chemicals for present research have been acquired from Merck & Co. Inc. (USA) and Sigma-Aldrich Pvt. Ltd. (USA) which were of analytical chemistry grade. Pathogenic cultures utilised for antibacterial activity, namely Bacillus cereus NCIM 2217 and Escherichia coli MTCC 443, were acquired from NCIM (National Collection of Industrial Microorganisms), Pune, and MTCC (Microbial Type Culture Collection and Gene Bank), Chandigarh. Human breast cancer cell line MCF-7 (ATCC – HTB – 22) and L929 normal mouse fibroblast cell line were used for anticancer experiments. All cell culture experiments were performed using cell culture grade media and reagents under aseptic laboratory conditions. Standard reference bacterial strains obtained from NCIM and MTCC were revived and standardized to 0.5 McFarland turbidity. No specific permits were required for this study as and no activities involved protected species, restricted sites, or regulated procedures.

2.2. Isolation, screening and molecular identification

Marine water samples pertaining to regions of seashore in Goa were collected in an aseptic manner to investigate potential producers of collagenase by using spread plate method. Water samples were collected during the summer season, as seasonal variations are known to significantly influence microbial diversity and extracellular enzyme-producing potential in aquatic environments. 1 ml of water sample has been mixed with sterilized saline (10 mL). Prepared samples were incubated in nutrient broth and inoculated over a solid nutrient agar (NA) plate. Single purified colony grown were subcultured and exposed to primary screening using medium comprising (g/100 mL) NaCl 0.9; skimmed milk powder 1 and agar 2 at pH 7.0. The bacterial colonies displaying highest hydrolytic zones were selected following its verification for subsequent collagenolytic capability thereby growing in specific medium for screening that composed of (g/100 mL) yeast extract 0.1; K₂HPO₄ 0.7; KH₂PO₄ 0.2; MgSO₄ 0.01, citrate 0.05, agar 2% and marine collagen 0.3% was added to autoclaved media. Coomassie brilliant blue (CBB) R-250 mixture was applied to the plates, followed by destaining to visualize clear hydrolysis zone [30]. Among the tested cultures, strain Z1 exhibited the largest zone of clearance and was thus selected for further analysis. It was maintained on collagen agar slants at 4℃, while glycerol stock was preserved at −20℃ for prolonged use. The Z1 strain was subsequently utilized for advanced investigations, including molecular characterization.

The genomicidentity of the potential Z1 strain was conducted through 16S rRNA gene sequencing, in accordance to methodology previously described [31]. DNA extraction kit has been employed to isolate genomic DNA of 20 h old bacterial culture.

Specific primers, forward (27F) and reverse (1492R) have been adopted for amplification process (Veriti® 96-well Thermal Cycler, Applied Biosystems, USA). Amplification through PCR was carried out adopting the method described previously [31]. The reaction mixture is comprised of 25 µL of sterile deionised water, comprising 12.5 µL of Premix Taq, 0.5 µM of primer and about 1 µL of DNA. Amplified product was purified and sequenced (Genetic Analyser, Applied Biosystems, USA). Obtained sequence was matched with comparable homologous sequences available in EzBioCloud database. The dissimilarity matrix was determined by the Ribosomal Database Project (https://rdp.cme.msu.edu). Evolutionary relationship was generated through matching Z1 nucleotide sequence with similar sequences using the neigbour joining technique in MEGA6 software [32].

2.3. Kinetic profiling for collagenase activity in a collagen-fed bacterial culture

The kinetics of collagenase synthesis from isolated bacterium Bacillus siamensis strain Z1 was investigated by employing collagen as important substrate. The composition of collagenase production medium included (g/100 mL) marine collagen 0.3; yeast extract 0.2; citrate 0.4 and salt solution mixture. A study of fermentation dynamics was conducted throughout a duration of six days in an Erlenmeyer flask (250 mL) and a production medium volume of 100 mL. A culture of strain Z1 that was 20 h old was transferred into nutrient broth (NB) and then subjected to incubation at 37℃ for 16–18 h while being shaken continuously at 200 × g (Scigenic biotech, India). The inoculum was introduced to the autoclaved 100 mL production medium (pH 7.0) in an aseptic manner, and the incubation process was continued for 6 days at 37℃ and 200 × g. At every regular 24 hours interval, a hydrolysed sample (~ 5 mL) was collected and subjected for process of centrifugation (10,000 × g for 15 min at 4℃). In addition to serving as protein source and extracellular crude collagenase, the supernatant was utilized for the analysis of total protein and the collagenase assay [30]. Additional parameters like cell growth (OD at 660 nm) and residual substrate concentration (reducing sugars in mg/mL) were estimated utilizing standard glucose by the DNS (3,5-Dinitrosalicyclic acid) procedure as illustrated earlier [33]. Experiments have been performed in triplicate sets and results are expressed (mean ± SD).

2.4. Analytical procedures

2.5. Influence of physicochemical variables on the synthesis of collagenase

The impact of significant physio chemical variables on collagenase production (U/mL) has been assessed. Influence with various physiochemical factors, like inoculum size (1–5%), metal ions (CaCO₃ and FeSO₄) at different concentrations (0.2, 0.5, 0.7 and 1.0 g/L), carbon sources (fructose, starch, maltose and lactose), nitrogen sources (Urea, ammonium sulfate and sodium nitrate), pH (4.0–10.0 using 1.0 N HCl and 1.0 N NaOH) and temperature (30–50℃) was evaluated for collagenase yield. Fermentation flasks underwent incubation for a period of 2 days with shaking at 200 × g. Collagenase activity as well as protein were analysed with method reported previously. Whole experiments were carried out three times [34,35].

2.6. Plackett-Burman design (PBD) to assess influential elements that impact the synthesis of collagenase

The impact of key medium parameters on collagenase production (U/mL) was examined using PBD. The design matrix was prepared with the help of the statistical software Minitab 17. Based on the preliminary findings acquired from earlier experiments, a PBD of 10 factors was designed to be carried out at two defined levels designated as high (+) and low (−1). A total of 12 investigational tests were been carried out in triads. Following components have been used in the experiment namely, Urea(X₁), MgSO₄(X₂), Collagen(X₃), Citrate(X₄), Yeast extract(X₅), CaCl₂(X₆), Maltose(X₇), Peptone(X₈), FeSO₄(X₉) and NH₄SO₄(X₁₀). Conditions for the experimental included 2% inoculum size, 0.5 g/L metal ion mixture, pH 7.0 and 35℃ temperature for 2 days period under shaking (200 × g.). Table 1 reveals the design matrix, which included both the original and coded values of the variables, as well as investigational and envisaged yields (responses). Collagenase production (U/mL) is a measure related to response (yield). The variable Y represents response and is derived from the first order polynomial equation that was discussed priorly [36].

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Table 1. Plackett- Burman experimental matrix for screening key variables affecting collagenase synthesis.

https://doi.org/10.1371/journal.pone.0344482.t001

2.7. Response surface methodology (RSM)-based optimization of collagenase production

Further, demonstration of collagenase optimization was brought about by utilizing the statistical programme Minitab 17 with the central composite design technique of RSM. In a total of 13 experimental runs, the two components notably molasses (A) and peptone (B), were utilized at five distinct levels (–α, –1, 0, + 1 and +α). Designed study was performed under constrain of pH 7.0 and 35ºC for two days. In the experiment, specific levels were been set for various parameters, while all additional elements in the medium were kept consistent. Table 3 illustrates the central composite design (CCD) RSM design table, displaying the factors in both original and coded formats along with the resulting collagenase production levels (U/mL). The relationships between the encoded and actual values of these factors were determined based on the formula previously outlined [37]. Below equation (1) represents second-order polynomial quadratic equation, where Y is calculated mean response, β₀ represents the intercept of the model, β₁ and β₂ denote the linear coefficients, β₁₁ and β₂₂ denote quadratic coefficients and β₁₂ is coefficient of interaction.

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Table 3. CCD-RSM design matrix for significant parameters influencing collagenase synthesis.

https://doi.org/10.1371/journal.pone.0344482.t003

(1)

The response surface plot was used to describe the interaction that occurred between the contributing components. The analysis of variance (ANOVA) study provided a visual representation of the substantial elements of the model as well as the interrelation between factors. Fisher’s ‘F’ function and probability ‘p’ can be utilized to infer importance of obtained model. The co-efficient of determination R² and adjusted R² are two indicators that demonstrate the accuracy of the model. The results acquired were confirmed in triplicate under the conditions that were adjusted to be optimal.

2.8. Synthesis of nanoparticles composed of silver and zinc oxide using collagen hydrolysate

The collagen hydrolysate was obtained by enzymatic hydrolysis of marine collagen using collagenase from Bacillus siamensis strain Z1. The hydrolysis was carried out for 48 h at 37℃ and pH 8.0, followed by enzyme inactivation and centrifugation. The supernatant was collected and used for nanoparticle synthesis. Silver nanoparticles (AgNP) synthesis in addition to collagen hydrolysate was performed using prior described approach [38]. AgNPs were synthesized using 1: 9 (v/v) ratio of collagen hydrolysate to silver nitrate solutions (5mM, 10 mM and 50 mM), followed by continuous magnetic stirring for 30 min to ensure homogenous mixing. A 500 µL of collagen hydrolysate was combined with 4500 µL of silver nitrate and resulting solution was been subjected to incubation under the UV light with set temperature for at 35℃ for 30 min. Further, reactions mixture was heated by subjecting them to microwave radiation for a duration of 30 sec, resulting in a noticeable alteration in color to brown or brown-red. UV-Vis spectroscopic data was collected by optical density of the AgNP mixture that was produced. In order to dry the AgNP suspension, it was subjected through a procedure of the formation of sediments which was obtained by sedimentation at 10,000 × g for 20 min. For the purpose of further characterization, the dried AgNP were utilized.

The zinc oxide nanoparticles (ZnONP) synthesis at concentrations of 10 mM and 50 mM using collagen hydrolysate was performed using methodology described by [39,40]. The reaction mixture comprised of ratio of 700 µL of zinc acetate dihydrate and 300 µL of collagen hydrolysate in 7:3 (v/v) ratio. Obtained mixture has been incubated with temperature of 60℃ for period of 15 min, followed by an extra incubation period of 6 hours carried out at room temperature. The UV-Vis spectrophotometer has been employed to determine optical density of produced ZnONP. Collected suspension was subjected to sedimentation (10,000 × g for 20 min). The collected sediment was dried at 50℃ and dried ZnONP was utilized for subsequent characterization.

2.9. Nanoparticles analytical characterization

2.10. Characteristics of collagen hydrolysate and nanoparticles from biological standpoint

2.11. Statistical analysis

All tests and sample analyses were conducted in triplicate trials. The data are shown as mean ± standard deviation (SD). The IC₅₀ values were estimated by linear interpolation between concentrations corresponding to inhibition values immediately above and below 50%. Error bars shown in images represent the standard deviation, determined using Microsoft Excel tools.

3.1. Isolation and identification of collagenolytic bacterium

This research focused on isolation of potential collagenase producer microbes from marine water of Goa. The isolation of efficient collagenase-producing strains during the summer season supports previous reports that warmer environmental conditions enhance proteolytic enzyme activity and the prevalence of enzyme producing micro-organisms [52]. Bacterial cultures were obtained using spread plate method and pure colonies were isolated on nutrient agar medium. A novel strain Z1 exhibited substantial collagenase activity based on both preliminary and secondary screenings. Z1 demonstrated growth on skimmed milk agar (preliminary screening medium) (S1a in S1 Fig) and collagen agar (secondary screening medium) (S1b S1 Fig). The strain produced the largest zone of hydrolysis with index of 4.5 (S1 Fig) and was confirmed as promising collagenolytic strain. The elected bacterial strain was characterized and confirmed through 16S rRNA gene sequencing and evolutionary tree analysis. The phylogenetic tree was generated employing neighbor-joining technique using MEGA6 software. Fig 1 illustrates evolutionary lineage among the Z1 strain and similarly related homologous gene sequences retrieved from the Gene Bank database (NCBI). Based on phylogenetic analysis, Z1 strain was identified as the species Bacillus siamensis. The identified bacterial strain was classified as Bacillus siamensis strain Z1. The nucleotide sequence of the discovered train Z1 was 1508 bp and was submitted to the NCBI GenBank database, and published under accession number OR054215. Further research was conducted with the Bacillus siamensis strain Z1. Dunlap et al., [53] also reported Bacillus vanillea’ XY18, a vanilla aroma compound producer, was compared to its closest relative, Bacillus siamensis KCTC 13613T. The draft genome showed minor differences, suggesting high similarity. A comprehensive characterization confirmed the close clustering, lead to reclassify it as Bacillus siamensis heterotypic synonym. Heo et al., [54], showed Bacillus siamensis strain B28 genome contained genes responsible for the synthesis of 8 vital amino acids included γ-aminobutyric acid, branched-chain fatty acids, subtilisin and γ-glutamyltransferase. The genes responsible in production of uracil, lipoteichoic acid, gluthione and other enzyme that scavenge reactive oxygen species also existed and the strain displayed susceptibility to eight drugs and also demonstrated antibacterial efficacy over seven foodborne pathogens. Researchers have identified several collagen hydrolysing bacterial strains isolated from various sources and some of them are mentioned here. Serine proteolytic collagenase from Bacillus sp. MO-1 possessed activity towards type I and IV collagen and gelatin [55]. A serine collagenase produced by thermophilic actinomycete strain Thermoactinomyces sp. 21E isolated from Bulgarian soil possessed thermostability [56]. A plant cysteine protease GP2 from ginger rhizomes (Zingiber officinale) exhibited potentiality in collagen hydrolysis and can be an alternative to papain in food industry [57].

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Fig 1. Phylogenetic tree utilizing the neighbour joining technique based on the 16S rRNA gene sequences of isolated bacterial strain Z1.

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A bacterial strain NW4327, that is major pathogen of the Great Barrier Reef sponge Rhopaloeidesodorabile, was found to produce collagenase and sponges that were contaminated with strain NW4327 had significant tissue necrosis, with bacteria detected actively tunnelling through the collagenous spongin fibres [58]. A metalloprotease fungi Rhizoctonia solani collected and isolated from laboratory produced extracellular collagenase [59]. Bacteria producing collagenase identified to be Chryseobacterium contaminans was isolated from soil of slaughter house [60]. Similarly, an extracellular collagenase was produced by Bacillus pumilus Col-J [11].

3.2. Collagenase production kinetics

The kinetics of collagenase production was investigated using the Bacillus siamensis strain Z1, and utilizing marine collagen as the raw energy source and glucose as the main carbon supply over a defined period of 6 days. The analysis encompassed collagenase production, total protein, cell biomass and residual substrate as illustrated in Fig 2A. Glucose intake decreased from 1% to 0.29% to achieve maximal cell biomass (0.97) under duration of six days. The collagenase kinetics profile indicated the collagenase yield began slowly on 1^st day (2.89 U/mL) and progressively rised, reaching a peak of 4.55 U/mL on the 2^nd day and on that day the total protein was found to be at its peak (0.69 mg/mL). Consequently, the 2^nd day was determined to be the optimal duration for collagenase synthesis based on the production kinetics. Additionally, other variables were examined with the harvesting time of the collagenase as on 2^nd day. Microbial collagenase is an extracellular enzyme, and so it is secreted in culture medium. The production of collagenase commonly depends on the availability of collagen concentration. The glucose effect might take place at elevated collagen levels in collagen rich substrates, leading to reduction in enzymatic activity. Literature reports suggest that the degradation of collagen is facilitated by a combination of enzymatic reactions involving collagenase, matrix metalloproteinases and gelatinase. Typically, collagen hydrolysis involves cleavage of peptide bonds. The efficient degradation of collagen by the isolated strain Z1 highlights its potential in managing collagen rich waste from food industries. Additionally, the conversion of insoluble collagen into soluble peptides attributed to isolated strain, highlights its potentiality in food, pharmaceutical and cosmetic industries. Several others described similar profiles of collagenase production. The examined production profile aligns with prior findings. The duration of collagenase synthesis varied from 2 to 5 days or longer, depending on microbial culture. [61], reported highest collagenase production on 3^rd day by Trichosporon sp. strain 7V and a maximum collagenase activity of 0.173 U/mL with 2.21 mg/mL of cell mass was reported from Pseudomonas sp [62]. Collagenase producer from Penicillium genus showed a sharp increase in enzyme activity at 96 h and further reached maximum activity after 126 h and then the activity gradually declined which might be due to microorganism undergoing a period of adaptation when exposed to media that consisted solely of salts and gelatin or the nutrients in medium might have become depleted [63]. A study by Lima et al., [64] showed that Penicillium aurantiogriseum URM4622 grew rapidly, reaching a highest biomass after 48 h. In consent to current study, [65], reported production of collagenase from Penicillium species using collagen type I as substrate. [59] reported maximal collagenase activity by R. solani at 108 hr.

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Fig 2. Collagenase production kinetics and effect of physio-chemical factors on collagenase production (A) production kinetics, (B) inoculum size, (C) effect of metal ions, (D) effect of carbon sources, (E) effect of nitrogen sources, (F) effect of pH and (G) effect of temperature.

The data values are the average of three replicates, while the error bars indicate standard deviation.

https://doi.org/10.1371/journal.pone.0344482.g002

3.3. Effect of physicochemical factors on collagenase production

Various physico chemical factors are accountable for triggering collagenase synthesis. The size of the inoculum is crucial for metabolite synthesis. The impact of varying inoculum sizes between 1% and 5% on collagenase synthesis was assessed. An inoculum size of 5% was shown to be optimal for collagenase synthesis yielding 4.98 U/mL with total protein of 0.55 mg/ml as depicted in Fig 2B. Decline in production and protein was seen at increasing inoculum level up to 6%. The impact of metal ions like ZnSO₄ and FeSO₄ showed improved yield at 0.5 g/L concentration as shown in Fig 2C. FeSO₄ helped to produce the most at 6.12 U/mL with 0.58 mg/mL of protein. There was no discernible rise in production at higher metal ion concentrations of 0.7 and 1.0 g/L. Carbon sources are advised to stimulate microbial proliferation and are correlated with the generation of products. The impact of various carbon sources was evaluated. Maltose was determined to be the most effective inducer of collagenase production of 7.83 U/mL pursued by fructose (6.89 U/mL) with total protein level of 0.65 mg/mL and 0.54 mg/mL, correspondingly as illustrated in Fig 2D. Glucose, being the main carbon source present in the production medium hence not used in OFAT. Another critical factor in the fulfillment of growth necessities and product improvement is the nitrogen source. The impact of various nitrogen sources on production was assessed. As seen in Fig 2E, it became apparent that ammonium sulfate (9.97 U/mL) increased the collagenase synthesis with 0.65 mg/mL of protein. Synthesis of collagenase was aided by both organic (Urea) and inorganic (ammonium sulphate, sodium nitrate) nitrogen sources. The synthesis of collagenase has been found to be impacted by pH in the pH range (4.0–10.0). As seen in Fig 2F. pH 7.0 produced the most, with 10.51 U/mL and 0.68 mg/mL of protein. From pH 6.0 to pH 8.0, collagenase synthesis had surged; at pH 9.0, it gradually decreased showing the formation of collagenase towards slight alkalinity. In acidic regions, synthesis was minimal, likely due to low pH altering amino acid ionization and reducing activity. However, in acidic conditions, the yield was not significantly notable. The growth of microbes and their product yield are often impacted by temperature variations. Fig 2G shows that, out of 30–50℃ temperature range that was considered, a temperature of 35℃ produced the highest amount of collagenase (12.39 U/mL) and protein (0.7 mg/mL). As the temperature exceeded from 45℃, decline in activity was noticed suggesting the collagenase synthesized is thermostable to 40℃. The findings of OFAT optimization point to possibility that Bacillus siamensis strain Z1 can produce thermostable collagenase with alkaline properties.

Many factors impacting the collagenase production were studied. The inoculum size significantly influences enzyme production. Excessive microbial proliferation at high inoculum concentrations during fermentation leads to a decline in enzyme yield due to rapid depletion of essential nutrients. Conversely, a lower inoculum density results in insufficient bacterial cell populations, limiting maximal enzyme synthesis. Our findings indicate that an optimal inoculum size for peak production was 5%. Researchers discovered that the inoculum size that produced the collagenase was 2% [66]. Closely lining with our findings, [62] found that Pseudomonas species had the greatest impact with an inoculum size of 4%.

The typical production medium used was a salt solution combination with metal ions like MgSO₄, but we also tested the influence of various metal ions. Metal ions help microbes maintain their redox potential and are known to have a role in metabolite production. The examined metal ions, namely ZnSO₄ and FeSO₄ did not demonstrate any significant increase in production at elevated concentrations. In agreement with our findings, Omojasola et al., [67] showed significant rise in collagenase yield with calcium ions. The catalytic stabilization of collagenase is known to be enhanced by the triggering impact of Ca²⁺ ions. The saline solution included K₂HPO₄ and KH₂PO₄, indicating the role of phosphate in maintaining the buffering capacity of the medium during fermentation. Another crucial element in the production medium is NaCl. [30] showed NaCl at elevated concentrations produced collagenase.

For the microbial fermentation process to produce primary and secondary metabolites, both carbon and nitrogen sources are essential. Each bacterium has a preference for metabolising a particular carbon source that facilitates its growth. The diverse components of simple and complex carbon sources are absorbed differently by various microorganisms, resulting in varying effects on production. Our work demonstrated that maltose is an effective inducer of collagenase production. Consistent with our findings, [68], also showed that Sucrose and maltose are good sources for enhancing collagenase synthesis. Glucose was proposed to enhance gelatinase production in Brevundimonas vescularis [35]. The addition of casein had a protease stimulatory effect for Bacillus sp. [69]. Glycerol gave optimum collagenase activity by Bacillus cereus, while other sources like maltose, glucose, sucrose and lactose also gave similar production [34].

The current research demonstrated that ammonium sulfate (inorganic) as nitrogen source significantly increased collagenase production. Organic sources such as yeast extract, peptone and inorganic sources, such as ammonium chloride and ammonium sulphate have been reported to yield gelatinase production [35] and protease production [69]. Beef extract and fish hydrolysate have also been shown to promote the protease production by Bacillus cereus [70]. Organic and inorganic sources are widely utilized by microorganisms due to their abundant nitrogenous compounds, minerals, co-factors, and vitamins. However, there exists a varying repressive action of both carbon and nitrogen sources across different microbes.

The medium pH at the cellular position affects transport of vital nutrients across bacterial cell membrane and maintains integrity. Variations in pH modify the ionization states of amino and carboxylic functionalities in proteins, directly impacting their enzymatic performance. Optimal enzyme synthesis transpires at an appropriate pH of the production medium. Consistent with our observations of optimal production within the alkaline pH spectrum, peaking at pH 8.0, collagenase synthesis by A. terreus and A. flavus was similarly identified at pH 7.5 [67]. A study indicated that B. vesicularis produced gelatinase under alkaline conditions at pH 9.0 [35]. A study showed maximum collagenase produced by Pseudomonas sp at pH 6.5. and also showed significant impact of very acidic and alkaline pH on collagenase production. The pH slowly increased from pH 4.0 and attained maximum at pH 6.5 and as it rised above pH 9.0 enzyme activity decreased. This pH variation affected nutrients intake from medium that aid in development and synthesis of metabolite [62]. Collagenase production from B. cereus and K. pneumoniae showed optimal activity at pH 7.0 and 6.5 [34].

Temperature plays a crucial role in regulating microbial growth as well as the timing and efficiency of enzyme production. An incubation temperature of 35℃ was found to be most suitable for collagenase synthesis by Bacillus siamensis strain Z1. Our findings align with earlier reports where A. terrus and A. flavus demonstrated peak collagenase activity at 37℃ [67]. Previous study showed that B. cereus and K. pneumoniae were reported to achieve optimal growth at temperatures of 37℃ [34]. [62], indicated that optimal temperature range for collagenase production by Pseudomonas sp. lied between 35–37℃, beyond which yield reduction is observed. Generally, mesophilic temperatures are advantageous due to lower energy consumption and better adaptability to changing environmental conditions. A previous study has demonstrated effective optimization of collagenase production using the OFAT approach where Enterobacter cloacae isolates F1 and C1 achieved maximum enzyme yield at pH 8.0 and 35℃ using chicken foot waste as substrate. Optimal production was observed with 1% inoculum size and peptone under static conditions resulting in highest collagenase activity of 20.23 U/mL after 48 h [71]. These findings emphasize that collagenase production is highly dependent on cultivation parameters, particularly temperature, which affect microbial proliferation and enzyme synthesis.

3.4. Statistical screening of key variables using PBD

By doing PBD screening, the medium components that contribute to collagenase production from Bacillus siamensis strain Z1 were identified. Table 1 shows the design of matrix (12 runs) accompanying responses (experimental and predicted) for collagenase production (U/mL). In the 11^th run, which included MgSO₄, CaCl₂, Maltose, peptone and NH₄SO₄ at high (+1) levels, the collagenase production response was 17.77 U/mL. A range of collagenase production values were reported, from the lowest at 7.0 U/mL to the highest at 17.63 U/mL. Reason for such distinction include variations in concentrations of components used in each trial run. Table 2 shows the results of the ANOVA which revealed that all of the medium parameters affected collagenase production at varying intensities. But comparatively with all parameters, NH₄SO₄ and Peptone had significant impact (probability ‘p’ < 0.05). As NH₄SO₄ is already supplemented in production media, the following peptone showed the noticeable and beneficial effect, with an effect value of 3.292. There existed a strong correlation between all of the anticipated and actual responses. High accuracy was demonstrated by an R² (coefficient of determination) of 99.90% and an R² (predicted) of 98.94%. The first-order regression analysis for collagenase optimization by PBD yielded the following equation (Equation 1) which is displayed as follows.

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Table 2. Analysis of variance for PBD for collagenase production.

https://doi.org/10.1371/journal.pone.0344482.t002

(1)

Here, Y is the predicted yield (response), while X₁-X₁₀ are coded parameter of variables like urea, MgSO₄, collagen, citrate, yeast extract, CaCl₂, maltose, peptone, FeSO₄ and NH₄SO₄.

In order to improve collagenase production, peptone was chosen for additional optimization utilising CCD-RSM design based on the PBD results. The PBD analysis showed that peptone factor had a substantial and significant impact on collagenase production, surpassing the influence of other factors. According to the FFD study, by Silva et al., [61], independent factors (pH, substrate concentration, aeration) were found to have significant impact on collagenase production. Optimization of collagenase production by PBD was conducted by [4], employing seven variables. Maximum yield was achieved by significant influence by temperature, culture time and concentration of soybean. A factorial design executed utilizing gelatin (0.25%), 200 × g, pH 6.0 and 24℃ resulted in maximum collagenase activity after 126 h of production [63]. A FFD analysis showed at a 95% confidence level, all factors had showed significant main effects with p < 0.05. The predominant effects factors like initial medium pH, temperature and substrate concentration had similar absolute values, but initial 2 had negative values and third one had positive value [72].

3.5. Study on collagenase synthesis using CCD-RSM

The matrix for CCD-RSM designed for collagenase production is detailed in Table 3, comprised of 13 trial runs, highlighting two described factors (peptone and molasses) and their corresponding experimental and predicted yields (collagenase production, U/mL). At the central ‘0’ value of peptone and molasses, the maximum yield of collagenase production was 80.50 U/mL. The ‘F’ value of 18.87 and ‘p’ < 0.05 in the ANOVA indicate that the generated model is satisfactory, as showed in Table 4. Results indicated linear component peptone, quadratic terms and binary interaction were relevant. For collagenase production in the designed exploratory region, the interface among peptone and molasses was analysed to be significant and prominent. The coefficient of determination (R²) was 93.09% while the adjusted R² was 88.16%. Results from experiments and predictions show a good match, validating the accuracy and appropriateness of the executed RSM model. The verification of designed model in present research revealed some lack of fit. A second-order polynomial equation (Eq.2) resulted from the combination of the two elements is displayed below as the modelled equation.

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Table 4. Analysis of variance for quadratic model of CCD-RSM for collagenase production.

https://doi.org/10.1371/journal.pone.0344482.t004

(2)

Here, Y is yield (response) termed to be collagenase production (U/mL) and A and Bare defined factors, namely, peptone and molasses correspondingly.

As shown in Fig 3, the interactions between peptone and molasses are depicted in the response surface plot of collagenase production. In order to position in the experimental conditions for highest yield, the plot is essential. The response surface plot’s curvature indicates to setting the central value to ‘0’ achieves the maximum collagenase production. At the central value, peptone had an intermediate concentration of 2% and molasses of 3%. A concentration of both components below and above the midpoint decreased collagenase synthesis. To maximize CCD-RSM production, optimization settings were validated in triplicates. Collagenase yield was 81.58 U/mL at the optimal circumstances, which closely matched to predicted outcome, proving model’s applicability. The CCD-RSM optimization method increased collagenase production 17.93 times. The model was evaluated under experimentally adjusted settings and confirmed augmentation of collagenase production.

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Fig 3. Response surface plot of collagenase production.

Results show significant interactions among identified parameters at p < 0.05.

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CCD approach was implemented by Silva et al., [61], to optimize production of collagenase from Trichosporon sp. strain 7V using two independent variables. A maximum collagenase activity was seen at pH 5.5 and 4.0 g/L of gelatin concentration. The combination of 16℃ temperature, 3.36 day culture time and 33 g/L soybean concentration was chosen as the central point (zero level) for the optimal design using RSM [4]. A recent RSM optimization study enhanced collagenase activity from Chryseobacterium contaminans by 1.2 folds and characterization showed optimal conditions for enzyme activity were pH 7.5 and 40℃ [73]. A new strain of Penicillium citrinum produced collagenase under 72 h submerged fermentation using licuri oil extraction as substrate and further optimized by RSM following a 2⁴ factorial design showed collagenase to be stable at 37℃ and pH 9.0 [74]. A research study chose new strain of Rhizopus microspores for collagenase production. The combined Full Factorial Design and CCD-RSM optimization led to 63% increase in collagenase production with maximum activity at 40℃ and pH 8.0, maintaining stability across wide range of pH and temperature. It was strongly inhibited by phenylmethylsulphonyl fluoride (PMSF) and was capable of hydrolyzing type I collagen and azocoll [75].

3.6. UV-Visible spectroscopic analysis of nanoparticles

The AgNPs formation (5 mM, 10 mM and 50 mM) was confirmed through visible shift in solution coloration from pale yellow to deep brown, signifying its characteristic surface plasmon resonance (SPR) of silver nanoparticles. UV-Visible spectroscopy was used to analyze the optical nature of the formed AgNPs, with a prominent absorption peak observed at 420 nm. The intensity of the SPR peak progressively increased with higher precursor concentrations, as illustrated in Fig 4A. Similarly, the synthesis of ZnONPs (10 mM and 50 mM) was verified by the appearance of a milky white precipitate following the reaction, indicating nanoparticle formation. The UV-Vis spectrum of ZnONPs exhibited a broad absorption band centered at 370 nm (Fig 4B). The enhancement of SPR peak intensity with increasing concentration further confirmed successful nanoparticle synthesis. The nanoparticles synthesis of AgNP and ZnONP and their optic properties was examined using UV-Visible spectroscopy, revealing a distinct plasmon band.

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Fig 4. UV -Visible spectroscopic characterization of nanoparticles (A) silver nanoparticles (AgNP) at 5mM, 10 mM and 50 mM and (B) zinc oxide nanoparticles (ZnONP) at 10mM and 50mM.

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The synthesis of nanoparticles (AgNP and ZnONP) and their optical properties were examined using UV-Visible spectroscopy, revealing a distinct SPR band. Cardoso et al., stated peak of absorption of 400 nm for silver nanoparticle formed by using type I collagen. Similarly, the NPs obtained by the reduction of the silver nitrate displayed a plasmon band at 420 nm for AgNPcol in the UV Vis spectra [25]. Smaller-sized nanoribbons like nanoparticles synthesized using gelatinase showed a characteristic absorbance peak at 380–400 nm [76]. The Zinc oxide nanoparticles generated by Lactobacillus sp. had absorption peak at 349 nm as described by Yusof et al., [77]. Similarly, a SPR peak was observed at 377 nm for biosynthesized ZnONPs using Lactobacillus gasseri and affirmed that the ZnONPs biosynthesis is possibly attributed to the strain’s inherent negative surface charge that potentially attracts the cations and generates the nanoparticle synthesis [78].

3.7. Structural and Functional assessment of nanoparticles

3.7.1. Functional group identification in nanoparticles by FTIR.

The reactive group characteristics and chemical modifications in AgNPs and ZnONPs synthesized using collagen hydrolysate from Bacillus siamensis strain Z1 was examined through FTIR spectroscopy within wavelength range of 400–4000 cm ⁻ ¹. The FTIR spectrum of AgNPs (Fig 5A) exhibited distinct absorption bands, with a prominent peak at 3749.79 cm ⁻ ¹ denoting to O-H extending vibrations. The existence of aliphatic C-H stretching was identified at 2974.61 cm ⁻ ¹. Additionally, multiple absorption peaks at 1646.49 cm ⁻ ¹, 1541.54 cm ⁻ ¹ and 1395.01 cm ⁻ ¹ were attributed to C = O stretching vibrations. Furthermore, a characteristic C-H aromatic bending was observed at 952.51 cm ⁻ ¹, indicating the possible presence of aromatic functional groups. The prominent peaks at 547.90 cm ⁻ ¹, 473.93 cm ⁻ ¹, and 458.40 cm ⁻ ¹ indicate the metallic characteristics of the substance in concern. The FTIR spectra (Fig 5B) of ZnONP exhibited significant peaks at 3750.04 cm ⁻ ¹ and 3357.38 cm ⁻ ¹, indicative of O-H stretching. The following peak at1640.88 cm ⁻ ¹ revealed C = O stretching. A C-C group was identified at 1542.07 cm ⁻ ¹. The frequency at 1456.89 cm ⁻ ¹ and 1395.59 cm ⁻ ¹ and attributed to the bending modes of –OH in phenols or the symmetric stretching of the –COOH group. A C-O extention was observed at 1016.09 cm ⁻ ¹ and 934.21 cm ⁻ ¹. The bands at 622.29 cm ⁻ ¹ and 567.85 cm ⁻ ¹ correspond to the vibrational modes of the bonds between oxygen and zinc molecules.

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Fig 5. Morphological and compositional analysis of Collagen hydrolysate capped nanoparticles(A) FTIR analysis of AgNP, (B) FTIR analysis of ZnONP, (C) SEM-EDS analysis of AgNP, (D) SEM-EDS analysis of ZnONP, (E) XRD analysis of AgNP, (F) XRD analysis of ZnONP, (G) TGA analysis of AgNP, (H) TGA analysis of ZnONP, (I) AFM analysis of AgNP and (J) AFM analysis of ZnONP.

https://doi.org/10.1371/journal.pone.0344482.g005

FTIR spectroscopy was employed for analyzing chemical composition of the formed AgNP and ZnONP. The findings were consistent with those reported by other researchers in the field. Cardoso et al., [79] reported a FTIR peak for amine I at 1652.84 cm ⁻ ¹ representing presence of C = O of collagen (col) bounded to AgNP (AgNPcol) and also stated that low intensity at that peak might be indicating that this group was possibly aided in the decrease and stabilization of silver nanoparticles. In a research biosynthesized AgNP using metallo serine protease as bioreducing agent in FTIR analysis showed the occurrence of various reactive groups such as carboxylic acids, alkyl ethers and amine salts that has helped in capping and stabilizing nanoparticles [80]. In a study the ZnONPs synthesized using Lactobacillus sp. supernatant (CFS) showed broad absorption peaks at 3282.2 cm ⁻ ¹ attributing to O-H bond, 1638.11 cm ⁻ ¹ for amide I band denoting to C = O stretching and peak at 455.29 cm ⁻ ¹ depicted for zinc oxide core band [77]. Similar absorption bands for ZnONPs synthesized using supernatant of L.gasseri was described by El-Sayed et al., [78] at peaks 3550 cm ⁻ ¹, 1653 cm ⁻ ¹, 1560 cm ⁻ ¹, 1029 cm ⁻ ¹ and 533 cm ⁻ ¹.

3.8. Biological assessment of nanoparticles and collagen hydrolysate

3.8.1. Assessment of antibacterial activity.

The antibacterial potential of collagen hydrolysate, AgNPs, and ZnONPs was assessed, and in Table 5 results are summarized. The synthesized AgNPs at varying concentrations (5 mM, 10 mM, and 50 mM) and ZnONPs (10 mM and 50 mM) were tested for antibacterial activity against Bacillus cereus and Escherichia coli. The green synthesized nanoparticles demonstrated a concentration-dependent increase in inhibitory effect. The maximum antibacterial activity was demonstrated by AgNPs (50 mM) synthesized using collagen hydrolysate derived from collagen hydrolysate by Bacillus siamensis strain Z1, resulting in inhibition zones of 8.4 ± 0.2 mm against B. cereus and 9.8 ± 0.2 mm against E. coli, as shown in Table 5. Reduced antibacterial activity was noted at lower concentrations of AgNPs. Specifically, AgNPs synthesized from collagen hydrolysate at 10 mM and 5 mM exhibited inhibition zones of 5.5 ± 0.5 mm and 4.1 ± 0.6 mm against B. cereus, and 6.4 ± 0.3 mm and 5.0 ± 0.2 mm against E. coli, correspondingly. In contrast, the highest inhibitory activity was observed with 50 mM ZnONPs synthesized from collagen hydrolysate, showing inhibition zones of 7.3 ± 0.6 mm and 8.1 ± 0.4 mm for B. cereus and E. coli, respectively. Furthermore, collagen hydrolysate derived from marine collagen hydrolysis exhibited substantial inhibition zones of 5.1 ± 0.3 mm and 5.4 ± 0.3 mm against B. cereus and E. coli, respectively. Both collagen hydrolysate and the biosynthesized nanoparticles demonstrated a notable antibacterial effect against Gram-positive and Gram-negative pathogenic strains, confirming their promising antimicrobial potential.

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Table 5. Antimicrobial activity assessment of collagenase enzyme and its Nanoparticles.

https://doi.org/10.1371/journal.pone.0344482.t005

The current findings demonstrate that all synthesized nanoparticles at different doses, together with collagen hydrolysate exhibited antibacterial activity, towards certain pathogens. In a study AgNPs stabilized in type I collagen showed anti-bacterial property against E.coli and Bacillus megaterium [99]. Similarly, antibacterial activity on both Staphylococcus aureus and E.coli was exhibited by of collagen based AgNPs [79]. A study reported antibacterial activity of silver nanoparticles stabilized by hydrolyzed collagen and natural polymers on S. aureus, P. aeruginosa and E. coli and, stated the effectiveness of antibacterial mechanism is strongly impacted by particle size. AgNPs provide an extensive contact surface, promoting adhesion to bacterial cell walls and facilitating their entry into the cells. This process disrupts the membrane integrity, ultimately causing cellular damage [25]. The antibacterial efficacy of Calotropis gigantea-derived CuO nanoparticles (CG-CuO-NPs) was evaluated against five bacterial strains (S. aureus, B. subtilis, Enterobacter, E. coli and P. aeruginosa). Antibacterial activity assessed at concentrations of 20–80 µl/mL showed a clear concentration dependent reduction in optical density, and indicated increased bacterial growth inhibition at higher doses [100].

Recent advances in bioenzyme mediated nanomaterials have highlighted potential of enzyme and protein hydrolysates as effective antibacterial agents. Keratinase mediated synthesis of silver nanoparticles (AgNPs) represents a promising bio-based approach, wherein keratinase from Pseudomonas aeruginosa C1M functions simultaneously as a reducing and stabilizing agent for Ag⁺ ions, yielding crystalline AgNPs (~ 119 nm) that exhibited significant antibacterial activity against E.coli and S. aureus in well diffusion assays, demonstrating robust antimicrobial efficacy derived from enzyme-capped NPs without external capping agents [101]. Concordant work using keratin hydrolysate from Bacillus velezensis to biosynthesize both AgNPs and ZnONPs also reported broad antibacterial activity against Bacillus cereus and E.coli, underscoring the capacity of keratin hydrolysate peptides to drive nanoparticle formation with inherent antimicrobial properties [23]. In a Collagen-AgNP nanocomposite research, wherein collagen provides a biocompatible scaffold for noble metal nanoparticles, showed antimicrobial efficacy against B. subtilis and E.coli, indicating that the combination of hydrolyzed protein matrices with metal nanoparticles can yield materials with dual benefits of biodegradability and potent antibacterial activity suited for wound care and biomedical coatings [102].

The antibacterial efficacy of hydrolysate mediated silver and zinc oxide nanoparticles results from combination of physical membrane disruption, oxidative stress induction and metal ion mediated toxicity. Silver nanoparticles release Ag⁺ ions that interact with thiol groups of bacterial enzymes and membrane proteins, leading to impaired respiration and cell death, while ZnONPs generate reactive oxygen species that cause lipid peroxidation, protein oxidation and DNA damage. Sivalingam and Pandian [103] reported that biosynthesized AgNPs exhibit enhanced antibacterial activity due to improved interaction with negatively charged bacterial cell walls, facilitated by surface-bound biomolecules. Chaurasia et al., [104] and Surendran et al., [105] further emphasized that biocomponent capping enhances nanoparticle dispersion and sustained ROS generation, resulting in broader-spectrum antibacterial action. Additionally, Sivalingam et al., [106] demonstrated effective microbial inhibition at lower nanoparticle concentrations with minimal systemic toxicity, highlighting the role of biological surface functionalization in improving antimicrobial efficiency and safety.

3.8.2. Assessment of antioxidant efficacy.

The antioxidant potential of the samples was assessed using ABTS and DPPH assays, which demonstrated their radical scavenging abilities and provided insights into their antioxidant properties. Collagen hydrolysate, AgNPs and ZnONPs exhibited varying antioxidant capacities, as determined by their ability to neutralize the ABTS radical cation. The ABTS assay results revealed a time-dependent enhancement in the antioxidant activity of all tested samples. After 48 h, the ABTS radical scavenging activity ranged between 28% and 55.13% across the samples (Fig 6A). Notably, AgNPs exhibited the highest antioxidant activity, achieving 55.13% inhibition, while the standard antioxidant BHT displayed 73% inhibition. Comparatively, the nanoparticles (AgNPs and ZnONPs) showed significant antioxidant potential over the collagen hydrolysate, which displayed 28% inhibition. The DPPH assay was conducted to assess the capacity of collagen hydrolysate, AgNP and ZnONP to scavenge free radical DPPH at varying concentrations (30–150 µg/mL). The assay revealed a concentration influenced enhancement in antioxidant potential of the analyzed samples. At 30 µg/mL concentration, the radical scavenging activities of AgNPs, ZnONPs and collagen hydrolysate were recorded as 56.89%, 39.35% and 27.28% respectively (Fig 6B), with corresponding IC₅₀ values of 21.60 µg/mL, 29.57 µg/mL and 35.45 µg/mL. A progressive increase in the concentration of collagen hydrolysate, AgNPs and ZnONPs resulted in a significant elevation in % radical scavenging activity. At 150 µg/ml, the scavenging efficiencies of AgNPs, ZnONPs and collagen hydrolysate were observed to be 78.46%, 60.19% and 45.64% respectively, with IC₅₀ values of 108.01 µg/mL, 150 µg/mL demonstrating potent antioxidant efficacy. The findings indicate AgNPs exhibiting superior antioxidant ability. The standard ascorbic acid exhibited 94% radical scavenging activity with IC₅₀ value of 79.78 µg/mL.

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Fig 6. Antioxidant activity of collagen hydrolysate and nanoparticles using(A) ABTS assay and (B) DPPH radical scavenging activity.

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A collagen hydrolysate with short peptide fraction (PF4) exhibited highest DPPH radical scavenging activity at 1 mg/mL concentration [107]. In a study using collagen and aminated xanthan gum bio-capped AgNPs were synthesized which also comprised melatonin that acted as oxidative stress and inflammation modulator. The bio-hybrid nanoparticles exhibited strong antioxidant activity of 50.7 ± 5% by DPPH method and this activity is might be due to presence of AgNP and melatonin and the hydrogels potent radical neutralizing capacity can inhibit oxidative stress generation at the injury site [108]. As similar to current study, Chitosan capped AgNPs showed increased radical scavenging activity towards DPPH with increasing concentrations. The highest activity with lowest EC₅₀ value was noticed in scavenging DPPH (0.4 mg/mL) [109].

Turbinaria ornata marine micro-algae (TUN) as carrier for ZnONP blended nanoparticles were synthesized and characterized as potential antioxidant product which showed very good efficacy against the tested reactive species like DPPH (88.2 ± 1.44%) and ABTS (90.5 ± 1.8%) [110]. Several studies showed biosynthesized zinc oxide nanoparticles exhibiting antioxidant potential through ABTS and DPPH method with similar pattern of dose dependent increase in scavenging radicals [21]. A metallo-serine protease capped AgNPs were biosynthesized and it displayed effective 68.15% DPPH radical scavenging activity at 500 µg/mL concentration. The study has shown that AgNPs have antioxidant capacity, which may help reduce oxidative stress associated with a number of illnesses, including cancer. Their special qualities, such as their high reactivity and surface to volume ratio improve their reactivity with reactive species and their capacity to donate electrons, which makes them appropriate for cancer treatments, since cellular oxidative damage significantly impacts the onset of tumours [80].

The enhanced antioxidant activity of green synthesized nanoparticles is primarily attributed to the synergistic interaction between the nanoparticle surface and hydrolysate-derived bioactive functional groups. Biomolecules such as peptides, phenolics, amino acids and hydroxyl-containing compounds act as capping and stabilizing agents, facilitating efficient hydrogen atom donation and electron transfer to neutralize free radicals. Surendran et al., [105] demonstrated that biofunctionalized nanoparticles exhibit superior radical scavenging activity compared to uncapped counterparts due to increased surface reactivity and redox potential. Chaurasia et al., [104] further reported that biologically synthesized ZnO nanoparticles act as ROS modulators rather than excessive ROS generators, owing to organic surface passivation. Similar observations by Sivalingam et al., [106] and Sivalingam [111,112], indicate that green synthesized AgNPs significantly reduce oxidative stress while maintaining biocompatibility, confirming that hydrolysate-mediated nanosystems provide controlled antioxidant effects through combined nanoscale redox behavior and bioactive surface chemistry.

3.8.3. Analysis of cytotoxic effect.

The cytotoxic potential of the synthesized nanoparticles and collagen hydrolysates were evaluated using the MTT assay, which assessed cell viability and cytotoxic efficiency under specific experimental conditions against MCF-7 breast cancer cell line and normal mammalian cell lines (L929). The anticancer effects of AgNPs, ZnONPs and collagen hydrolysates were examined across varying concentrations (3.125, 6.25, 12.5, 25, 50, and 100 µg/mL), and cell proliferation was analyzed in MCF-7 cells, as illustrated in Fig 7. The IC₅₀ values for AgNPs, ZnONPs, and collagen hydrolysate against MCF-7 cells were determined to be 8.87 µg/mL, 25.21 µg/mL, and 44.81 µg/mL, correspondingly, while the standard drug Doxorubicin exhibited an IC₅₀ of 7.56 µg/mL. AgNPs demonstrated a significantly higher anticancer potential compared to ZnONPs. However, at concentrations of 50 µg/mL and above, both nanoparticles showed notable anticancer efficacy. Additionally, when tested on normal mammalian cell lines (L929), the synthesized nanoparticles did not induce any significant reduction in cell viability.

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Fig 7. Assessment of anticancer potential of nanoparticles and collagen hydrolysates against breast cancer cells.

https://doi.org/10.1371/journal.pone.0344482.g007

[25] reported the biosynthesized AgNPs promoted concentration dependent decrease of macrophage viability indicating low cytotoxicity. In a study bio synthesized ZnO nanoparticles showed strong, selective cytotoxic effects against Caco-2 and A549 cancer cells, with minimal impact on normal WI38 cells. The reaction was dose influential, with higher concentrations causing greater toxicity [84]. A study showed usage of Aspergillus sp. extract to biosynthesize ZnONPs and it exhibited anticancer activity with IC₅₀ values of 59.74 µM, 43.21 µM, 57.03 µM and 35.66 µM against cell lines WI38, HCT116, HePG2 and MCF-7, respectively [113]. Swietenia macrophylla-mediated silver nanoparticles showed notable strong cytotoxicity against MCF-7 breast cancer cell lines with a low IC₅₀ value of 2.1 µg/mL and a high selectivity index of 5, outperforming both plant extract and conventional AgNPs [111].

The anticancer activity of hydrolysate – mediated silver and zinc oxide nanoparticle is mainly governed by selective intracellular ROS generation, mitochondrial dysfunction, and apoptosis induction in cancer cells. Cancer cells exhibit higher baseline oxidative stress and enhanced nanoparticle uptake, making them more susceptible to nanoparticle-induced redox imbalance. Sivalingam [100] reported that biosynthesized AgNPs trigger mitochondrial membrane depolarization, cytochrome-c release, and caspase-mediated apoptosis through excessive ROS accumulation. ZnO nanoparticles further contribute by pH- dependent dissolution and Zn²⁺ ion release in the acidic tumor environment, leading to DNA damage and cell cycle arrest, as discussed by Chaurasia et al., [104]. Surendran et al., [105] and Sivalingam et al., [106] highlighted that hydrolysate functionalized nanoparticles exhibit tumor selectivity and reduced toxicity toward normal cells. In a recent study biosynthesized ZnO nanoparticles were shown to exert dose-dependent cytotoxicity against MCF-7 breast cancer cells with significant cell death attributed to oxidative stress mechanisms at low micromolar concentrations, consistent with increased intracellular ROS apoptosis induction [114].

Both, silver nanoparticle (AgNPs) and zinc oxide nanoparticles (ZnONPs) demonstrate promising biocompatibility and potential for safe biomedical application when engineered and dozed appropriately. Biogenically synthesized AgNPs have shown excellent in-vivo compatibility, with histopathological and serum biochemical analyses indicating no significant liver, kidney, heart, lung, brain or spleen toxicity at therapeutic doses (up to 50 mg/kg body weight), highlighting their suitability for intravenous administration in animal models when surface coated and size-controlled to reduce direct cellular stress [115]. Similarly, ZnO NPs possess intrinsic advantages as biodegradable, essential trace element-based nanoforms; in several preclinical studies, ZnO-based formulations exhibited negligible systemic toxicity in treated animals, stable body weights, and no major organ damage relative to controls, particularly when designed with targeting ligands or coatings to enhance tumor selectivity and minimize off-target exposure. In tissue integration models, ZnONPs have also demonstrated favorable biocompatibility in complex in-vivo systems, promoting endothelial and fibroblast activity relevant for wound healing without adverse reactions [116]. Collectively, these findings support the view that with careful design, dosing and functionalization, AgNPs and ZnONPs can achieve favorable safety profiles in-vivo and serve as viable candidates for further preclinical evaluation in cancer therapy and other biomedical applications.

Highlights

• Collagenase-producing Bacillus siamensis Z1 was isolated and identified from marine water.
• Marine collagen was utilized as a sustainable substrate for eco-friendly waste valorization.
• Collagenase yield was optimized by strategies like OFAT, Plackett-Burman and CCD-RSM enhancing production by 17.93-fold.
• Ag and ZnO nanoparticles were synthesized using collagen hydrolysate and thoroughly characterized.
• Biosynthesized nanoparticles exhibited positive antimicrobial, antioxidant and anticancer activities.