Cu(II) Biosorption and Synthesis of CuO Nanoparticles by Staphylococcus epidermidis CECT 4183: Evaluation of the Biocidal Effect

Featured Application

Staphylococcus epidermidis CECT 4183 presents a good capacity for its application in the bioremediation of Cu(II) in contaminated water, and at the same time, its cellular extract has a good capacity to synthesize CuO-NPs with potential applications in nanomedicine.

Abstract

Copper contamination of natural waters is a global problem that affects ecosystems and public health, yet this metal is an essential micronutrient and has important applications. The efficacy of Staphylococcus epidermidis CECT 4183 as a Cu(II) biosorbent in synthetic solutions and its potential ability to synthesize CuO nanoparticles (CuO-NPs) from its cellular extract was investigated. In addition, the biocidal potential of the nanoparticles was evaluated against five microorganisms. Using response surface methodology, the optimal operating conditions were determined to be biomass dose, 0.2 g/L, and pH 5.5. Equilibrium tests were performed, and biosorption isotherms were obtained for four models with a maximum biosorption capacity of 48.14 mg/g for the Langmuir model. Different spectroscopic and microscopic techniques were used to determine the mechanisms involved in the biosorption process, which was dominated by surface physicochemical interactions with strong involvement of methyl, methylene, carbonyl, amino, and phosphate groups. The techniques also allowed for characterizing the obtained nanoparticles, which had a quasi-spherical morphology and an average size of 14 nm. Finally, biocidal tests showed that the CuO-NPs had a good inhibitory capacity for the microorganisms tested, with minimum inhibitory concentrations (MIC) between 62.5 and 500 µg/mL for bacteria and between 1000 and 2000 µg/mL for yeasts. S. epidermidis CECT 4183 showed good potential for Cu(II) bioremediation and for the synthesis of CuO-NPs with biocidal capacity. S. epidermidis CECT 4183 showed good potential for use in Cu(II) biosorption, and its cell extract presented a high capacity for the green synthesis of CuO-NPs, which at the same time turned out to be good biocidal agents.

1. Introduction

Copper contamination of natural waters is a serious environmental problem because this metal is associated with both industrial and agricultural discharges and is highly toxic. It can also migrate through rainwater bound to surfactants, which increases its distribution [1]. Copper can enter natural waters and soils from various emission sources such as mining [2] and is listed by the U.S. Environmental Protection Agency (EPA) as a priority toxic pollutant due to its adverse effects on the environment and human health. Industrial activities and road traffic are also sources of emissions of this metal, which is often present in the dust produced by these sources and then enters aquatic environments through runoff [3]. Although it is an essential micronutrient, when it is deposited in the soil it can have devastating effects on the soil microbiota, which is why several authors are working to identify methods that incorporate markers capable of identifying the tolerance of microorganisms to basal concentrations of this metal [4]. Recent studies have shown that in addition to inducing cellular damage through induction mechanisms, copper can stimulate the conjugation and transfer of plasmids in the environment, accelerating the spread and amplification of antibiotic-resistance genes (ARGs). In parallel, the formation of complexes between heavy metals and antibiotics can modify the bioavailability of the metal and affect the toxicity of the mixture, which in many cases has a greater ease in crossing the cell membrane [5]. The case of the antibiotic sulfamethoxazole (SMX) is widely studied. Peng and coworkers studied the interaction between this antibiotic and Cu(II) and its role as a carrier of runoff pollutants in roadway sediments (RDS). The authors demonstrated that when SMX and Cu(II) coexist in the runoff, and an appropriate pH is provided, they form a ternary complex RDS-Cu(II)-SMX to increase the occurrence of both [6].

For all these reasons, the search for technological solutions aimed at mitigating the dispersion of copper in natural environments is highly topical, with biological techniques such as biosorption of heavy metals being one of the most promising, effective, and ecological strategies since in most cases this metal is found in low concentrations in the effluents that carry it, preventing its elimination by conventional physicochemical techniques and causing it to end up biomagnifying in ecosystems.

In this work, the bacterium Staphylococcus epidermidis CECT 4183 was used to evaluate its capacity for Cu(II) biosorption in synthetic solutions. At the same time, it is known that copper is a metal that can form CuO nanoparticles (CuO-NPs) through the action of some mechanisms involved in biosorption. These mechanisms are based on the presence of proteins, enzymes, and polysaccharides, which are also present in cell and plant extracts [7,8]. The green synthesis of CuO nanoparticles from microorganisms presents great advantages, such as their antibacterial and antifungal properties, their capacity to act as biosensors for different molecules, their marked anticancer character against several types of aggressive cancers, their use as carrier molecules, and their role in the activity of important essential molecules. On the contrary, chemically synthesized CuO-NPs present important drawbacks, such as the use of chemical reagents that produce residual contamination and, at the same time, are harmful in the clinical or agro-food application of the obtained nanoparticles, which limits their scaling towards targeted therapies in humans [7]. Some authors have analyzed in detail the toxicity and activity of these nanoparticles obtained by both synthesis routes and have determined that the antibacterial, anti-inflammatory, and antidiabetic activity of the CuO-NPs obtained by green synthesis was more pronounced than those obtained by chemical synthesis. At the same time, the activity of the former against human cancer cells (MCF-7) was more potent, while they showed lower toxicity against zebrafish embryos [9]. All this has promoted the study of CuO-NPs synthesized by biological procedures and their possible application in the field of biomedicine, where they have already demonstrated high thermal stability and long shelf life that give them the potential to eliminate microorganisms, catalyze reactions, stop the growth of cancer cells, and coat surfaces. In addition, the choice of green synthesis using microorganisms presents the additional advantages of being clean, ecological, cheap, and environmentally friendly compared to traditional chemical and physical methods [10]. For this reason, the capacity of the S. epidermidis CECT 4183 cell extract to synthesize CuO-NPs was analyzed to subsequently evaluate its biocidal capacity against different microbial strains.

2. Materials and Methods

2.1. Preparation and Characterization of Biomass and Nanoparticles

2.1.1. Preparation of Biomass

The microorganism, obtained from the Spanish Type Culture Collection (CECT) and stored in glycerol stock at −80 °C, was cultured in liquid medium no. 1 (beef extract 5 g, peptone 10 g, NaCl 5 g flushed to 1 L). From a 24 h inoculum, 10 flasks of 250 mL each were inoculated with 200 mL of the same medium and kept for 24 h at 27 °C and 150 rpm with shaking. The medium was then washed with an electrolytic solution of 0.1 M NaNO₃ until a concentrated cell suspension was obtained, the concentration of which was determined by calculating the dry weight per mL. Then, 1 mL of cell suspension and 1 mL of 0.1 M NaCl electrolyte (to correct the weight of the salts) were pipetted and weighed in sextuplicate, then kept at 104 °C for 24 h; finally, they were transferred to the desiccator and weighed again to determine the mass of microorganisms present per milliliter of cell suspension. This cell suspension was obtained for each biosorption test. After the biosorption tests, the biomass was recovered and washed with the same electrolyte and subjected to different sample preparation protocols depending on the analytical technique to which it was to be subjected. In all cases, the biomass was compared before and after the biosorption step.

2.1.2. FT-IR Analysis

A VERTEX 70 (Bruker Corporation, Billerica, MA, USA) instrument was used for Fourier transform infrared spectroscopy (FT-IR). The biomass obtained before and after the biosorption tests was washed and kept at 60 °C for 48 h, then ground in a porcelain mortar until a fine powder was obtained that allowed the analysis of the absorbance of the samples by attenuated total diffraction (ATR) in the range between 4000 and 400 cm⁻¹. The FT-IR technique provides important information on the presence of functional groups in the biomass and determines which of them were involved in the biosorption process.

2.1.3. XRD Analysis

X-ray diffraction (XRD) is a technique that allows obtaining information about the crystalline nature of the precipitates formed during the biosorption stage. For this reason, the samples analyzed by FT-IR were also analyzed by XRD to identify the presence of crystalline precipitates, indicating the presence of metallic nanoparticles in the biomass. A Malvern Panalytical Empyrean instrument (Malvern, UK) was used under the conditions described in Muñoz et al. [11]. In parallel, the technique was also used to identify the presence of CuO-NPs after the synthesis stage with cellular extract of the microorganism studied. In both cases, the theoretical size of the crystal was calculated from the most intense peak and using the Debye–Scherrer equation (Equation (1)).

$$d={\displaystyle \frac{k\lambda }{\beta cos\theta }}$$

(1)

where d is the mean diameter (nm) of the crystals, k is Scherrer’s constant, which has a value of 0.9, λ is the wavelength (nm) of the incident X-rays, β is the width of the mean XRD peak height expressed in radians, and θ is the Bragg diffraction angle.

2.1.4. FE-SEM-EDX and TEM Analysis

To identify the presence of metal precipitates on the cell surface, which would reveal the involvement of surface adsorption mechanisms by the bacteria, a scanning electron microscopy analysis with dark field emission and an X-ray scattering detector (FE-SEM-EDX) was performed. A MERLIN instrument from Carl Zeiss (Goettingen, Germany) was used, and the biomass was repeatedly washed with PBS buffer pH 7.4 and prepared as described in Muñoz et al. [12].

Finally, to study the morphology and approximate size of the nanoparticles obtained in the synthesis stage, a JEOL JEM-1010 (Jeol Company, Peabody, MA, USA) transmission electron microscope (TEM) was used. The nanoparticles were suspended in ultrapure water to obtain a homogeneous colloidal suspension, of which 3 µL was pipetted onto the grids, which were then visualized to obtain the images. The same grids were also visualized by FE-SEM-EDX to obtain elemental maps that would allow the identification of the participation of the different elements in the synthesis of the nanoparticles.

2.2. Biosorption Assays

All biosorption assays were performed at 27 °C and 200 rpm in duplicate in an SI-600R Orbital (Lab Companion, Chalgrove, Oxfordshire, UK); 100 mL flasks were used with a working volume of 50 mL of Cu(II) solution at a concentration of 50 mg/L. Samples obtained in the assays were filtered with 0.22 µm PES filters and analyzed by atomic absorption spectroscopy (AAS) in a Perkin Elmer AAnalyst 800 instrument (Midland, ON, Canada) using Equation (2).

$$q={\displaystyle \frac{\left(C_i-C_f\right)V}{m}}$$

(2)

where C_i and C_f are the initial and final concentrations of Ag(I) in mg/L, respectively; V is the volume of metal solution (0.05 L), and m is the dry mass of biomass (g).

Response surface methodology (RSM) and a rotatable central composite design were used to determine the optimal operating conditions (pH and biomass concentration). The equilibrium tests to obtain the biosorption isotherms were carried out under the optimal conditions obtained in the experimental design and in the concentration range between 10 and 50 mg/L, with a contact time of 4 days to ensure that the process, generally rapid, was completed.

In order to fit the experimental data, the models shown in

Table 1. Isotherm models and biosorption equilibrium parameters for the different isotherm models tested for the biosorption of Cu(II) by S. epidermidis CECT 4183.

Model	Equation	Parameter
Langmuir [13]	$q_e={\displaystyle \frac{q_{m\hspace{0.33em}}b\hspace{0.33em}{C}_e}{1+b\hspace{0.33em}{C}_e}}$	qm	48.14
		b	0.349
		R2	0.987
		Σ(q − qcal)2	0.876
Freundlich [14]	$q_e=K_F\hspace{0.33em}{C}_e^{\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$n$}\right.}$	KF	22.884
		n	5.27
		R2	0.928
		Σ(q − qcal)2	4.984
Sips [15]	$q_e={\displaystyle \frac{K_s{C}_e^{\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$n$}\right.}}{1+a_s\hspace{0.33em}{C}_e^{\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$n$}\right.}}}$	Ks	16.530
		as	0.344
		n	0.987
		R2	0.987
		Σ(q − qcal)2	1.313
Redlich–Peterson [16]	$q_e={\displaystyle \frac{K_{RP}\hspace{0.33em}{C}_e}{1+a_{RP}\hspace{0.33em}{C}_e^{\beta }}}$	KRP	17.149
		aRP	0.363
		β	0.995
		R2	0.987
		Σ(q − qcal)2	1.310

q_e: biosorption capacity (mg/g) at equilibrium; q_m: maximum biosorption capacity (mg/g); b: Langmuir biosorption equilibrium constant (L/mg); C_e: equilibrium concentrations of metal (mg/L); K_F: characteristic constant related to the biosorption capacity; n: characteristic constant related to the biosorption intensity; K_s and a_s: Sips isotherm parameters; K_RP, a_RP, and β: Redlich–Peterson parameters, and β varies between 0 and 1; R²: coefficient of determination; Σ(q − q_cal)²: sum of the errors squared.

have been used. The Langmuir model is well known [13]. It assumes monolayer adsorption on a homogeneous adsorbent. The Freundlich model is an empirical equation that assumes that the adsorbent increases its adsorption area as the adsorbate concentration increases and can then be applied to multilayers and heterogeneous surfaces [14]. The Sips model incorporates the basic principles of Langmuir and Freundlich and can be used over a wide range of concentrations [15]. Finally, the Redlich–Peterson model is an empirical model that can also be used over a wide range of concentrations [16]. When β equals one, we have the Langmuir isotherm, and when β equals zero, we have Henry’s law. IBM SPSS Statistics v.27 was also used to fit the experimental data.

2.3. Obtaining Cell Extract and Synthesis of Nanoparticles

The cell extract was prepared based on the preparation of the fresh biomass as described in Section 2.1. In 250 mL flasks, 5 g of fresh biomass was placed in contact with 100 mL of ultrapure water and kept under agitation (150 rpm) at 27 °C for 5 days. The volume was then filtered through 45 µm PVDF filters and stored at 5 °C until use. The CuO-NPs nanoparticle synthesis assays were performed by optimizing a protocol based on previous studies by other authors [17,18] and included the following steps: (1) 40 mL of cell extract was kept under constant stirring until it reached 75 °C, and then 40 mL of a Cu(NO₃)₂·3H₂O solution prepared from 2 g of reagent in 100 mL of sterile distilled water was added dropwise, and the mixture was kept under the same conditions for 1 h; (2) the suspension obtained was kept at 5 °C for 4 days; (3) after tempering the suspension, its pH was raised to a value of 11 by adding 0.1 M NaOH until a visible precipitate was obtained, which was washed with ultrapure water at 5500 rpm/4 min for several cycles until a transparent supernatant was obtained; (4) the precipitate was placed in an oven at 60 °C for 48 h to eliminate any residual moisture; (5) the powder obtained was calcined at 500 °C for 2 h to eliminate organic residues; (6) finally, the powder obtained was subjected to intense grinding in an agate mortar before its characterization by XRD and subsequent use.

2.4. Determination of Biocidal Effect

To determine the biocidal activity of the obtained CuO-NPs, 5 microbial strains were used: 2 Gram-negative bacteria (Escherichia coli, CECT 101 and Pseudomonas fluorescens, CECT 378), 2 Gram-positive bacteria (Bacillus cereus, CECT 131 and Staphylococcus epidermidis, CECT 4183) and a yeast, Rhodotorula mucilaginosa 1S1, isolated from wastewater in a previous work [19]. To determine the minimum inhibitory concentration (MIC) of the nanoparticles against the microorganisms studied, two types of tests were performed. The first was carried out in Petri dishes with Mueller–Hitton agar (MHA) nutrient medium that was contaminated with increasing concentrations of nanoparticles ranging from 3.9 to 2000 µg/mL, using the serial dilution method and starting from a colloidal suspension of CuO-NPs in ultrapure water (UPW) of known concentration (4000 µg/mL). The microorganisms grown for 24 h in liquid medium were inoculated in triplicate and stored at 27 °C along with a non-toxic positive control to record the growth of the microorganism and a negative control to verify that the medium was free of external contamination. The second type of biocidal test was based on that described in the Clinical and Laboratory Standards Institute (CLSI) standard method M07-A9 with some modifications and was performed in 96-well microplates. In this case, polyvinyl alcohol (PVA) was previously added to the ultrapure water at 10% of the weight of the nanoparticles and heated to 60 °C to facilitate their complete dissolution [20]. The aim was to achieve better dispersion of CuO-NPs in the final colloidal suspension to improve its biocidal activity. Serial dilutions were performed to obtain a range of concentrations between 7.8 and 4000 µg/mL. Mueller–Hitton (MH) medium was used, and a positive control (100 µL MH/100 µL NaCl 0.1 M/100 µL UPW-PVA 10%) containing PVA was included to rule out its possible biocidal effect, and a negative control (100 µL MH/100 µL NaCl 0.1 M/100 µL UPW-PVA 10%) to rule out contamination of the original medium. Colloidal suspensions were prepared from a 24 h culture at 27 °C in sterile 0.1 M NaCl electrolyte adjusted to 0.5 on the McFarland scale, and 100 µL were inoculated into each well tested along with 100 µL of MH medium and 100 µL of CuO-NPs colloidal suspension. Assays were performed in triplicate, and plates were incubated at 27 °C for 24 h to obtain growth kinetics in a BioTek Synergy HT microplate reader (Santa Clara, CA 95051, USA), where readings were taken every 30 min at 630 nm.

3. Results and Discussion

3.1. FT-IR Analysis

Figure 1 shows the FT-IR spectra obtained for the biomass of Staphylococcus epidermidis CECT 4183 before and after the biosorption step. As can be seen, the biomass initially had a large number of available functional groups, which were affected after contact with Cu(II) ions. The spectrum obtained after Cu(II) biosorption showed a significant loss of intensity, and several functional groups were displaced or disappeared. In this sense, there is a clear involvement of methyl groups (-CH₃), as indicated by the shifts of the peaks located at 3267 cm⁻¹ (which changes to 3074 cm⁻¹) and at 2853 cm⁻¹ (which changes to 2875 cm⁻¹), both involving vibrations due to asymmetric stretching of C-H bonds. This involvement of C-H bonds is confirmed in the region between 1300 and 1400 cm⁻¹, characteristic of bending vibrations for this type of bond, where a band shift from 1398 cm⁻¹ to 1386 cm⁻¹ occurs together with a band disappearance at 1335 cm⁻¹ [21].

Likewise, the involvement of carbonyl and amino groups linked to amide I and amide II is demonstrated by the shifts 1628–1634 cm⁻¹ and 1539–1518 cm⁻¹, respectively, which are related to stretching of -CO and -CN bonds and bending vibrations of N-H bonds. On the other hand, a strong shift in the 1218 cm⁻¹ band (which shifted to 1229 cm⁻¹) was observed and could indicate the participation of carbonyl groups but also the participation of phosphate groups due to asymmetric P=O bond strains. This participation of phosphate groups could be confirmed by the disappearance of three bands in the region between 800 and 1000 cm⁻¹ and by the shift of the band located at 525 cm⁻¹ after the biosorption stage. [22,23]. Other authors have reached similar conclusions, Gu et al. [24] identified the participation of carboxyl, hydroxyl, and phosphate groups in the biosorption of Cu(II) by the green alga Neochloris oleoabundans. Similarly, Fatollahi et al. identified the participation of hydroxyl, carboxyl, amino, carbonyl, and phosphate groups in the biosorption of Cu(II) by bacterial biofilms [25].

3.2. XRD Analysis

The XRD spectra obtained after the biosorption stage did not show any peaks characteristic of the presence of CuO-NPs. This could be due to the fact that the crystalline precipitates were present in very low concentrations compared to the total biomass and went unnoticed. Nevertheless, as described in Section 2.3, nanoparticle synthesis tests were carried out from the cell extract of Staphylococcus epidermidis CECT 4183. Figure 2 shows the XRD spectra corresponding to the powder obtained after the synthesis stage and clearly shows the presence of the characteristic peaks of this type of nanoparticle [26]. It shows the peaks identified by the 2θ angle and their corresponding Miller indices, which identify the crystallographic planes. Figure 2 shows the spectrum before (blue) and after (red) the calcination step, demonstrating that, despite the presence of some impurities of organic origin, the last step could be omitted if necessary. However, calcination allowed us to obtain nanoparticles of high purity and crystallinity, as indicated by the narrow and intense peaks obtained in the spectrum. Finally, a theoretical average crystal size of 16 nm was calculated from the Debye–Scherrer equation.

3.3. FE-SEM-EDX and TEM Analysis

Figure 3 shows the FE-SEM images obtained before and after the Cu(II) biosorption stage. In images b and d, it is clearly seen that Cu(II) causes significant damage to the cell structure when compared to the images obtained before this stage (images a and c). Likewise, the EDX spectrum (image f) obtained for image d identifies the characteristic peaks of copper, showing that the precipitates covering the cell surface are formed by this metal. Finally, massive clusters are identified in image b, which may correspond to CuO nanoparticles. The EDX spectra, in which an increase of the peak corresponding to oxygen is observed after the biosorption stage, could support this assertion. To prepare Table S1 from the EDX spectra included in Figure 3, ImageJ 1.53e software was used. The table shows the approximate percentage of the elements present before and after the biosorption stage. It is observed that oxygen is involved in the retention of Cu(II) because an increase in percentage and arbitrary units of this element is identified. A similar change was also found in phosphorus, which indicated that this element was also involved in the adsorption of Cu(II). The elemental maps shown in Figure S1 confirm this statement. In conclusion, FE-SEM-EDX images and FT-IR analysis allow us to affirm that for Cu(II) biosorption, Staphylococcus epidermidis CECT 4183 actively involves surface adsorption mechanisms, some of which could be catalyzing the formation of CuO nanoparticles. Other authors have reported similar results; for example, Mir and Rather studied the adsorption of Cu(II) by Chara vulgaris with good results and suggested that the biosorption process was dominated by physicochemical interactions at the surface level such as precipitation, ion exchange, and complexation-coordination [22]. Similarly, Akar and Tunali demonstrated the presence of ion exchange mechanisms using the fungus Botrytis cinerea [27].

On the other hand, Figure 4 shows the FE-SEM and TEM images obtained on the CuO-NPs synthesized from the cell extract, confirming the results of the XRD analysis and indicating that the precipitates obtained are CuO-NPs of high purity. In addition, the images obtained on the original nanoparticles, and therefore without the addition of PVA, show uniform sizes below 50 nm with varied and highly aggregated morphologies.

3.4. Experiment Design: Optimal Operating Conditions

A statistical design of experiments was carried out to study the optimum operating conditions of the factors involved in the biosorption process.

Table 2. Rotatable Central Composite Design (RCCD) for the optimization of biosorption of Cu(II) by S. epidermidis CECT 4183.

pH	B, g/L	q, mg/g
3.0	0.20	7.05
3.0	0.76	10.93
4.3	0.50	16.22
4.3	0.50	14.74
4.3	0.85	15.91
2.5	0.50	2.96
5.5	0.20	42.28 *
4.3	0.50	14.44
4.3	0.50	15.06
4.3	0.08	24.50
6.0	0.50	17.00
4.3	0.50	15.24
5.5	0.76	16.14

B: biosorbent dose; q: biosorption capacity; * The values were not considered in the statistical adjustment.

shows the experimental results obtained for the biosorption capacity (q) under equilibrium conditions, which ranged from 2.96 to 24.50 mg Cu(II)/g dry biomass.

Subsequent statistical adjustment (Design-Expert^® v.12 software, Minneapolis, MN, USA) yielded Equation (3).

$$\begin{array}{c}q=-43.3077+23.1506 pH+5.11094 B-10.5387 pH B -\\ -1.58606 {pH}^2+33.2120 B^2\pm 0.9733\end{array}$$

(3)

where B is the biosorbent dose (g/L).

Based on Equation (3), the optimal operating conditions for Cu(II) biosorption were obtained: pH 5.5 and a biosorbent dose of 0.2 g/L.

Figure 5 shows the response surface (a) and the perturbation diagram (b) of the biosorption process, and in both diagrams, it can be seen that the most determining factor in the biosorption of Cu(II) is the pH.

3.5. Biosorption Isotherms

From the experimental data obtained under the optimum conditions, defined by the experimental design in Table 2 and Figure 5, the parameters shown in Table 1 were obtained by non-linear regression. Three models show a good fit to the experimental data: Langmuir, Sips, and Redlich–Peterson, with a correlation coefficient R² = 0.987. The maximum biosorption capacity, according to the Langmuir model, was 48.14 mg Cu(II)/g dry biomass. The Langmuir model assumes that the surface has a limited number of active sites and that each adsorbate molecule binds to an active site without interacting with the adjacent sites. This model fits a type of monolayer adsorption that can generally be compatible with what is observed in the FT-IR analysis. However, in practice, these assumptions have limitations since not all active sites will have the same affinity for metal ions, and physisorption phenomena may occur on the initial monolayer that improves the retention of Cu(II) ions and give rise to complexation phenomena, as can be seen in the FE-SEM analysis. This fact fits better with what was observed in this work and could explain the good fit of the experimental data to more complex models such as the Redlich–Peterson model (R² = 0.987), which combines Langmuir and Freundlich elements and therefore does not fit an ideal monolayer adsorption model but would contemplate a more heterogeneous type of adsorption, which seems to be more in agreement with what was observed in the biosorption of Cu(II) by S. epidermidis.

Table 3. Maximum Cu(II) biosorption capacity for different types of biomass.

Type of Biomass	Biomass	qm (mg/g) *	Reference
Plant	Ageratum conyzoid	51.57	[21]
Marine macroalgae	Sargassum filipendula	40.8	[28]
Yeast	Saccharomyces cerevisiae	4.73	[29]
Filamentous fungus	Penicillium citrinum	22.7	[30]
Bacteria	Geobacillus toebii Geobacillus thermoleovorans	41.5 48.5	[31]
Bacterial extract	Mucilaginibacter sp. ERMR7:07	8.36	[32]
Bacteria	Ochrobactrum cicero Stenotrophomonas maltophilia Pseudomonas putida	50.56 39.26 38.97	[33]
Bacteria	S. epidermidis CECT 4183	48.14	This work

* q_m: Maximum biosorption capacity expressed in mg of metal per g of biomass.

shows the maximum biosorption capacities obtained by other authors for different types of biomass, including microbial biomass. It can be seen that the values obtained in this work are similar to or slightly better than those obtained for other types of bacteria and higher than those obtained for fungi, yeasts, or marine macroalgae. Furthermore, although in all cases these are theoretical values deduced from the adjustment of experimental data to mathematical models, in the case of S. epidermidis CECT 4183, the data come from a very good fit to the Langmuir model, which indicates that it is a value very close to the reality of the Cu(II) biosorption process by the bacteria.

Likewise, Figure 6 shows the graphical representation of the adsorption isotherms studied. The Redlich–Peterson isotherm is the one that best fits the experimental results, but the Langmuir and Sips isotherms also show good fits. On the contrary, the Freundlich isotherm shows worse results.

3.6. Characterization of Nanoparticles and Biocidal Assays

Figure 7a shows the histogram and frequency polygon for the nanoparticles obtained in the synthesis phase. As can be seen from the size distribution, the CuO-NPs presented sizes between 10 and 32 nm with a predominance of sizes in the range of 13 to 15 nm, which is quite consistent with that predicted by the Debye–Scherrer equation (16 nm).

Size is an important factor when using nanoparticles for biocidal purposes to control pathogenic microorganisms. In the case of CuO-NPs, small sizes below 20 nm improve the access of nanoparticles to the cell cytoplasm where they can promote the formation of reactive oxygen species due to the transition metal character of copper. At the same time, stable and spherical morphologies facilitate the biocidal action of nanoparticles due to their greater specific surface area [10]. The average size of the CuO-NPs obtained in this work is smaller than those obtained by other authors [34] and, in general, smaller than those synthesized by bacteria [10], which, in principle, would support their potential as biocidal agents.

Table 4. Minimum inhibitory concentration (MIC) of different microorganisms against CuO-NPs obtained from Staphylococcus epidermidis CECT 4183 before and after treating it with PVA (10%). The results are expressed in µg/mL.

Bacteria	CuO-NPs	CuO-NPs + PVA (10%) *
B. cereus	1000–2000	62.5–125
S. epidermidis	125–250	62.5–125
E. coli	250–500	62.5–125
P. fluorescens	500–1000	250–500
R. mucilaginosa 1S1	-	500–1000

* PVA: Polyvinyl alcohol.

shows the Minimum Inhibitory Concentration (MIC) results of CuO-NPs for the microorganisms studied before and after the use of PVA. The use of PVA in the biocidal tests showed a significant improvement in the dispersion and stabilization of the nanoparticles, which resulted in a lower MIC that was between 50 and 75% of the initial value for most of the bacteria tested, with a 16-fold better effect in the case of B. cereus. Likewise, the results of the positive controls that included UPW with 10% PVA (liquid base of the CuO-NPs suspension), MH nutrient medium, and the respective bacterial suspensions (at 0.5 on the McFarland scale) confirmed that PVA does not have biocidal properties at that concentration and therefore the effect was exclusively due to the CuO-NPs.

In parallel,

Table 5. Biocidal effect for different types of CuO-NPs obtained from different types of biomass and by different synthesis methods.

Type of Synthesis	Starting Biomass/ Chemical Method	Size (nm)	Microorganisms Tested	CMI (µg/mL)	Reference
Biological synthesis	Gum karaya	4.8-1.6	E. coli S. aureus	103.5 120.4	[35]
Biological synthesis	Aerva javanica	15–23	E. coli S. aureus	128	[36]
Biological synthesis	Penicillium chrysogenum	15.5–59.7	S. aureus B. subtilis P. aeruginosa E. coli	1000 1500 2000 3000	[37]
Biological synthesis	Averrhoa carambola	80–100	E. coli P. aeruginosa S. typhimurium B. megaterium S. aureus	50	[38]
Biological synthesis	Bacteria ZTB29	15–30	Xanthomonas sp. Alternaria sp.	200	[39]
Chemical synthesis	DARC-AC *	40–50	S. sanguinis P. gingivalis P. melaninogenica S. mutans	125–625	[40]

* DARC-AC: Arc discharge in controlled atmosphere.

summarizes the results obtained by other authors, including the microorganisms tested, the sizes of the nanoparticles, their origin, and their biocidal effect. There are not many works that obtain CuO-NPs from bacteria, nor are there studies that evaluate their biocidal effect based on the MIC expressed in µg/mL, and there is also a wide variety of methods used to determine the biocidal effect. In many cases, the method seeks to obtain an approximation to the real values for practical purposes. In this work, the growth curves of the microorganisms tested were obtained, and it was confirmed that the MIC values were in line with reality. Despite all of the above, the results shown in Table 5 confirm that the CuO-NPs synthesized in this work have a good biocidal potential that, in some cases, is higher than that reported in other works. For example, as shown in the table, Padil and Černík [35] reported similar results for bacteria of the same genus, with MICs of 103.5 and 120.4 μg/mL for E. coli and S. aureus, respectively. Similarly, Amin et al. [36] obtained a MIC of 128 μg/mL for E. coli and S. aureus, while other authors, such as Mohamed et al. [37], reported much higher values of 3 mg/mL for E. coli. In general, the results obtained in this work were better than those reported by most authors.

4. Conclusions

Staphylococcus epidermidis CECT 4183 showed a good potential for the removal of Cu(II) from synthetic solutions with a qm for the Langmuir model of 48.14 mg/g when operated under the optimal conditions provided by the experimental design, a value comparable to that of other microorganisms and in many cases higher. FT-IR and FE-SEM-EDX analyses showed that physicochemical mechanisms were mainly involved in the biosorption process, although the possibility that some of the metal was incorporated into the cytoplasm was not excluded. Staphylococcus epidermidis CECT 4183 showed a good capacity to release the cell extract under stress conditions. The extract was effective in catalyzing the synthesis of CuO-NPs of high purity and crystallinity under the conditions developed and optimized in this work, as shown by XRD analysis. The CuO-NPs presented an average size of 14 nm, smaller than most of those reported by other authors, while their application as biocidal agents gave good results that improved significantly when the colloidal suspensions were mixed with PVA. In the case of B. cereus, the MIC was reduced up to 16-fold. In general, the MICs were between 62.5 and 500 µg/mL for the bacteria and between 1000 and 2000 µg/mL for the yeast tested; these values indicate that the synthesized nanoparticles have a good potential for their use in biomedicine. The good results obtained in this work, based on the principles of green chemistry, add to the current efforts to transfer the potential benefits of CuO-NPs to the field of biomedicine. This type of nanoparticle presents enormous advantages that must be thoroughly explored: biocidal capacity, antiviral capacity, anticancer capacity, etc., all of them in the current context of microbial resistance to antibiotics and an increase in oncological diseases. Future works should address the mechanisms of action of CuO-NPs and their interactions with prokaryotic and eukaryotic cells in order to establish a detailed theoretical–practical framework that allows their general clinical and agri-food use.