Photoluminescence dynamics of copper nanoclusters synthesized by cellulase: role of the random-coil structure

Abstract

This study demonstrates the one-pot cellulase-directed synthesis of magic numbered copper nanoclusters (Cu NCs) with blue-, cyan-, and green-luminescence from Cu₁₂, Cu₂₀, and Cu₃₄, respectively. The developed Cu NCs have an excellent luminescence quantum yield, photostability and better colloidal stability. The temperature-dependent response of the blue luminescent nanocluster gets flipped over by changing the aqueous medium to a methanolic one. Moreover, the preferential stabilization of large-sized Cu₃₄ (green-luminescent) NCs–cellulase over a relatively small one, Cu₂₀ NCs–cellulase is found to be dependent on both temperature as well as solvent. The luminescence of Cu₂₀ NCs–cellulase can be greatly augmented by the addition of Zn(II) and Cd(II) ions, whereas the Fe(III) ions quench the luminescence. The random coil structure of the enzyme dictates the size and luminescent properties of the Cu NCs. This unique and beneficial aspect of the Cu NCs warrants them to find possible applications as a sensitive marker for cell imaging, and nanophotonic materials.

---

Introduction

Noble metal nanoclusters (NCs) composed of several to tens of atoms (core size ≤ 2 nm) have generated burgeoning interest owing to their unique size-dependent luminescent and bioconjugation properties.^1–20 They find profound applications in catalysis,^2,3 optoelectronics,⁴ bioimaging⁵ and sensing applications.⁶ The low toxicity of these highly luminescent NCs makes them a better candidate to replace toxic quantum dots in biomedical applications.^7,8 Metal NCs have molecule-like electronic transitions within their conduction bands due to quantum confinement.⁹ The spherical Jellium model, a conventional theoretical model, which is generally employed to predict the size of nanoclusters, states that the energy gap between the adjacent levels, i.e. the emission maximum of a NC is the indicator of its size, , where E_em is the emission maximum of nanocluster of radius (R) with N number of metal atoms, E_Fermi is the Fermi energy of the bulk metal and r_s is the Wigner–Seitz radius of the metals.^10,11 The stability of the nanoclusters is dependent on its composition, i.e. number of atoms. Both gas and condensed-phase studies reveal the existence of magic-numbered clusters (N = 2, 8, 18, 20, 34, 40, and etc.) which possess better stability over others due to geometric and electronic shell closings.^12,13 The shell closing rules for copper being a group IB element is expected to follow the same as Au, Ag. However, the preferential stabilization of a relatively large-sized magic-numbered cluster from the nearby one has not been explored in detail. In this report, we have observed such stabilization of copper nanoclusters by employing steady state and time-resolved fluorescence spectroscopy and circular dichroism studies.

The nanoclusters tend to agglomerate without proper protection and form nanoparticles, which are nonfluorescent. Inspired by biochemical synthetic routes for Au¹⁴ and Ag NCs,¹⁵ limited efforts have been made to stabilize Cu NCs using serum albumins,^16–18 lysozyme,¹⁹ polymer,²⁰ glutathione.^21,22 Thus, the investigation of Cu NCs which are susceptible to oxidation needs to be carried out in great detail for primarily two reasons: the development of better synthetic methods and tuning of its luminescent properties for versatile use. Moreover, Cu is an important trace element in metal homeostasis²³ and serves as a cofactor in metallochaperones, metalloregulatory and redox-active proteins.²⁴ In this report, we unravel the synthetic methods using cellulase as sole reducing and stabilizing agent for Cu NCs in aqueous solution. Cellulase is a highly efficient enzyme synthesized by microbes for the extracellular degradation of substrates and biomineralization. The presence of metal ion impurities in cellulosic materials plays a key role in retarding the turn over number of enzyme. The catalytic role of enzyme toward degradation of cellulosic materials for bio-fuel production is of great interest due to global energy scarcity. However, a very limited report exists on cellulase mediated synthesis of nanostructures.²⁵ In this context, it is very essential to understand the mechanism by which cellulase interacts with metal ions. Cellulase from Trichoderma reesei ATCC 26921 is composed of 344 amino acid residues of which 8 are cysteine and one is methionine.^26,27 We report the synthesis of “magic numbered” Cu NCs by cellulase using two different synthetic routes: simple incubation and sonication followed by incubation of cellulase–metal ion solution, both the methods yield the formation of luminescent Cu NC. We have also observed that the enzyme structure regulates the size and luminescent properties of Cu NCs. The effect of temperature and solvent on luminescent properties of cellulase synthesized NCs have also been investigated.

Experimental

Materials

Cellulase from Trichoderma reesei ATCC 26921 is purchased from Sigma Aldrich and used as received. Copper sulphate and sodium hydroxide are obtained from RANKEM. Methanol (Fischer Scientific, HPLC grade) and metal salts such as zinc nitrate (SDFCL), mercuric chloride (Fisher Scientific), ferric chloride (Fisher Scientific) and cadmium chloride (Fisher Scientific) are obtained from the respective companies. All chemicals used in the experiments of analytical grade and used without any purification. Water from ELGA LAB Water-purifier (18.2 mΩ) is used throughout the experiments.

Cellulase-directed synthesis of copper nanoclusters

In a typical synthesis, 1 mL of 1.5 mg mL⁻¹ cellulase dissolved in water is added to 1 mL, 1.5 mg mL⁻¹ CuSO₄ solution and mixed well. Few drops (30 μL) of NaOH (1 M) is added to the enzyme–metal ion solution to make the solution alkaline (pH ∼ 11). The solution is stirred for 2 hours, thereafter incubated at 4 °C for 3 days. The addition of NaOH to enzyme–metal ion solution changes the color of the solution from colorless to greenish and thereafter to reddish brown suggesting the formation of Cu NC. In an another method, the enzyme–metal ion solution is sonicated for 30 min, then stirred for 2 hours followed by incubation at 4 °C for 3 days. The color of solution changes to intense violet indicating the synthesis of Cu NC. It can be added here that the timescale to synthesize nanoclusters solely depends on the nature of the protein. However, the synthesized nanoclusters have been characterized by steady state and time-resolved fluorometric methods. The cellulase synthesized Cu NCs is added to methanol, lower polarity than that of water. The absorption and fluorescence spectra of the solvent mixture (solvent : water = 2 : 1) are recorded. The temperature of the aqueous and methanolic (2 : 1) media is also regulated to study its effect on the luminescent properties of different sized Cu NCs.

Instrumentation

The steady state absorption spectra are collected using a LAB India UV-Vis 3200 spectrophotometer. The absorption spectra are recorded from 200 to 1100 nm. Steady state photoluminescence (PL) spectra are recorded on a Varian Cary Eclipse fluorescence spectrophotometer with Peltier temperature controller. Synchronous luminescence studies are performed by scanning the excitation and the emission monochromators of the fluorimeter simultaneously, with a constant offset of 20 nm between the two. The relative quantum yield (ϕ_s) of the samples is defined as the area under the curve of excitation corrected fluorescence spectrum. The absolute luminescence quantum yield (ϕ_f) of the sample is determined by the equation, ϕ_f = (ϕ_s/ϕ_r) × φ_f, where ϕ_r and φ_f, are the relative and absolute quantum yield of the reference (coumarin 102).²⁸ Time-resolved photoluminescence measurements are performed using a picosecond pulsed-diode laser-based TCSPC fluorescence spectrometer from LifeSpec II (Edinburg Instruments).²⁹ The laser diodes: 375 nm with pulse width 170 ps and 440 nm of pulse width 180 ps are used as excitation sources. Emissions from the blue luminescent NC at 410 nm (λ_exc = 375 nm) and from red luminescent NCs at 485 nm and 600 nm (λ_exc = 440 nm) are collected at right angles to the direction of the excitation beam, at magic angle polarization and the resolution is 12 ps per channel. The data are fitted to multiexponential functions after deconvolution of the instrument response function by an iterative reconvolution technique, using the F900 data analysis software, where reduced χ² and weighted residuals serve as parameters for goodness of fit. Circular dichroism data are recorded using Jasco J-815 CD spectrophotometer equipped with Peltier temperature controller, in the range of 190–400 nm at the rate of 100 nm s⁻¹ with band width of 1 nm. CD spectra are measured using quartz cuvettes. The spectropolarimeter was purged with N₂ prior to the experiment. Each CD plot is an average of three accumulated plots and also baseline corrected. The molar ellipticity is calculated from the observed ellipticity θ as 100θ/cl where c is the concentration of the protein solution in molarity and l is the path length of the cell in centimeters. The nanoclusters formed are imaged by a transmission electron microscope (TEM) (JEOL 2100F) mounted with field emission gun FEG TEM at 200 kV accelerating voltage. The samples for TEM are prepared on amorphous carbon films supported on a copper grid.³⁰

Results & discussion

Cellulase-directed synthesis of copper nanoclusters

Cellulase as the sole reducing and nucleating agent unprecedentedly synthesizes copper nanoclusters in aqueous solution. Simple incubation (method-I) of cellulase–copper ion solution at 4 °C temperature over 72 hours results reddish brown color of solution, suggesting slow kinetics of Cu NC synthesis by cellulase alone (Scheme 1). Whereas, sonication (40 kHz, 15 min) followed by overnight incubation at 4 °C (method-II) of enzyme–metal ion solution changes the color of the solutions from colorless to greenish and finally to color resembling to Prussian blue (Fig. S1, ESI†). The pH of the medium is maintained is at ∼pH 11. In order to understand the cellulase mediated biomineralization process, the use of extraneous reducing agent has been avoided in particular. However, the synthesized nanoclusters are quite stable in aqueous solution for more than a month (Fig. S2 and S3†). The absorption spectra of pure cellulase and copper nanoclusters obtained from two different methods are plotted in Fig. 1A. The absorption spectra of cellulase alone have a peak centered at 278 nm which is characteristics of tryptophan, tyrosine and phenyl alanine residues. The absorption spectra of Cu NCs–cellulase, as expected, are markedly different and broader than that of enzyme alone, confirming the formation of nanoclusters. Cellulase from Trichoderma reesei ATCC 26921 is composed of 344 amino acid residues of which 8 are cysteine and one is methionine.^26,27 Upon addition of copper sulphate solution to cellulase solution, the metal ions possibly be coordinated to amino acid residues of enzyme containing such as –NH, –SH, and –OH groups (Scheme 1) and they are subsequently reduced. Inhibition of nanocluster formation in acidic pH indicates the pivotal of role of concentration of hydroxide ion in enzyme-catalyzed nanocluster synthesis. We have reported that cellulase which contains 14 Tyr residues, even at low concentration can effectively synthesizes silver nanoparticles indicating its strong reducing ability.²⁴ The standard reduction potential of Cu²⁺/Cu is 0.34 V (vs. NHE), whereas, the redox potentials for tyrȮ/tyrOH couple which is regulated by polypeptide chain lies in the range of 0.78–0.93 V (vs. NHE).^31,32 The plausible mechanism for nanocluster formation is that the deprotonated tyrosine residues in cellulase at pH 11 undergo oxidation and yielding atomic copper metal. The regeneration of tyrosine residues might occur through 1e⁻ reduction in the medium. The polypeptide chain acts as a scaffold for copper nanoclusters. At the molecular level the nanoparticle synthesis by cellulase is similar to the biomineralization process executed by living organisms in nature.³³

Scheme 1 Schematic representation of reaction methods employed for the synthesis of Cu NCs in cellulase solution.

Fig. 1 [A] In aqueous solution, absorption spectra of – (i) cellulase (black line), (ii) Cu NC obtained in method-I (blue line), (iii) Cu NC obtained in method-II (red line). [B] Normalized excitation (dashed line) and emission spectra (solid line) of Cu NCs (method-I) in aqueous solution. [C] Normalized excitation (dotted line) and emission spectra (solid line) of Cu NCs (method-II) in aqueous solution.

Photophysical properties of Cu NCs–cellulase

Cu NCs obtained in method-I exhibit maximum excitation and emission peaks at 320 nm and 401 nm respectively (Fig. 1B). Excitation dependent emission spectra confirm the presence of one type of nanocluster and its spectral characteristics in aqueous solution (Fig. S4, ESI†). Surprisingly, the excitation spectra of Cu NCs prepared using sonication method are of vibronic in nature. Two excitation peaks are separated by about 28 nm, with peak maximum at 468 nm. The emission spectra exhibit also two peaks, maxima centered at 484 nm and second one at 511 nm (Fig. 1C). Its excitation dependent emission spectra also prove the vibronic coupling (Fig. S5, ESI†). However, in order to resolve the ground state heterogeneity, the synchronous luminescence technique is employed.^34,35 In this technique, excitation and emission wavelengths are varied simultaneously with a constant offset, chosen by trial and error, such that the experiment is performed along the diagonal of the excitation–emission matrix, which passes through the maximum number of peaks and troughs. The resulting spectra have a greater number of narrower peaks compared with that obtained in conventional excitation spectroscopy, allowing discrimination between luminescent molecules that have broad and overlapping spectra. This method has previously been utilized to analyze complex mixtures in as widely separated fields as hydrocarbon analysis in mineral oils,³⁶ and the study of mitochondria.³⁷ In the present experiment, the synchronous luminescence spectra of Cu NCs (method-II) exhibit two peaks in aqueous solution, intense one at 468 nm and relatively weak at 530 nm (Fig. 2A). Excitation spectra (recorded at λ_ems = 600 nm) is relatively broad with a peak at 510 nm and excitation dependent emission spectra exhibits peak maxima at 570 nm (Fig. 2B). The simple incubation method yields blue-luminescent copper nanoclusters whereas sonication method results the formation of cyan-luminescent Cu NCs (major) and green-luminescent Cu NCs (minor). The quantum yields of the synthesized Cu NCs in aqueous solution are estimated to be 0.23 for blue-luminescent Cu NCs, 0.24 and 0.07 for cyan-luminescent Cu NCs and green-luminescent Cu NCs respectively, using coumarin 102 as the reference.³⁸

Fig. 2 [A] Synchronous luminescence spectra of – (i) Cu NCs (method-II) in aqueous solution, (ii) Cu NCs (method-II) in methanolic solution, Δλ = 20 nm. [B] Normalized excitation at λ_ems = 600 nm (dashed line) and excitation-dependent emission spectra of the Cu₃₄ NC–cellulase in aqueous solution at λ_exc: (i) 500 nm, (ii) 510 nm, (iii) 520 nm, and (iv) 530 nm.

The atomic composition of synthesized NCs can effectively be deduced from the Jellium model, =(λ_ems/λ_Fermi)³, even the predicted composition is directly matched with mass spectrometry results using MALDI-TOF (biosystems) spectrometer.^17,39,40 For blue-luminescent Cu NCs, (E_em = 401 nm and E_Fermi of Cu, which is 177.12 nm (7 eV)) the number of atoms, N, present in Cu NCs is evaluated to be ∼12 (11.6 ± 0.1), the most stable (magic numbered) atomic composition of the blue-luminescent Cu₁₂ NCs–cellulase. Whereas for cyan-luminescent Cu NCs (E_em = 484 nm), and green-luminescent Cu NCs (E_em = 570 nm) the number of atoms, N, present in Cu NCs is evaluated to be ∼20 (20.4 ± 0.2) and ∼34 (33.7 ± 0.5) respectively. The experimental error in determination of emission maxima (swallow in nature) is also mentioned in the prediction of atomic composition of nanoclusters. Interestingly, both Cu₂₀ NC and Cu₃₄ NC are also the magic numbered copper nanoclusters. To the best of our knowledge this is the first report where an enzyme synthesizes two nearby magic numbered clusters. The transmission electron microscopy (TEM) is also employed to confirm the formation of copper nanoclusters. Typical TEM images of the synthesized red luminescent Cu NCs reveals the formation of the NCs has indeed taken place with a size regime of ∼4 nm. The reason for relatively large sized in TEM might be due to the evaporation of water which lead to aggregation of Cu NCs–cellulase (Fig. S6, ESI†).

Unprecedentedly, the synchronous luminescence spectra of Cu NCs (method-II) in methanolic medium, exhibit the complete reversal of PL intensities, the peak at 530 nm becomes the strong one whereas intensity of 468 nm peak drops dramatically. Such reversal might happen on two accounts: first, the better stabilization of relatively large-sized nanoclusters over smaller one due to solvent-induced structural rearrangement of protein; another, energy transfer from cyan-fluorescent Cu NCs to a green-luminescent one. In order to substantiate the above proposed hypotheses, we have carried out picosecond time-resolved measurements for synthesized Cu NCs. Fig. 3 shows the luminescence decay traces of Cu NCs in aqueous and methanolic media. The decay traces are well fitted with triexponential (Table 1). Since the decays are multiexponential, therefore, then it is pertinent to use an average decay time, which is proportional to the steady state intensity.²⁸ An analysis of the decay traces of Cu₂₀ NCs–cellulase reveals the presence of three components in aqueous solution: a shorter one with a lifetime of 0.38 ns (τ₁) and two longer components (τ₂ ∼ 2.82 ns and τ₃ ∼ 4.67 ns) (Table 1). The lifetimes and its corresponding weightage of Cu₂₀ NCs–cellulase remain unchanged in methanolic media. Interestingly, the decay traces recorded at λ_ems = 600 nm (Cu₃₄ NC–cellulase) in aqueous and methanolic media differ significantly. The amplitude of short component decreases while the same for longer component increases. However, the absence of rise-time bolsters the first hypothesis, the better scaffolding ability of cellulase in methanolic media for green-fluorescent nanoclusters. The time-resolved trace of Cu₁₂ NCs–cellulase in aqueous medium, as expected, exhibits an average luminescent lifetime of ∼3.16 ns [0.1 ns (5%), 2.22 ns (68%); 6.10 ns (27%)] (Fig. S7, ESI†). The origin of multiexponential decay of Cu NC can be rationalized by the electronic transition between the filled d orbital and sp conduction bands.¹⁶ The shorter component may be attributed to Cu NCs–solvent interaction, whereas relatively longer components to the Cu–Cu interaction and the transition between Cu–amino acid residues in enzyme.

Fig. 3 Photoluminescence decays of Cu NCs (method-II) in – [A] aqueous solution and [B] methanolic solution. (i) λ_ems = 485 nm and (ii) λ_ems = 600 nm. The IRF (λ_exc = 440 nm) is shown in the dashed line.

Table 1 PL decay parameters of Cu NCs–cellulase obtained in method-II^a

	λems = 485 nm								λems = 600 nm
	a1	a2	a3	τ1	τ2	τ3	〈τ〉	χ^2	a1	a2	a3	τ1	τ2	τ3	〈τ〉	χ^2
a Luminescence lifetimes, τi are in ns and 〈τ〉 = ∑aiτi^2/∑aiτi.
In aqueous	0.03	0.80	0.17	0.38	2.82	4.67	3.29	1.10	0.15	0.51	0.34	0.33	2.62	4.12	3.33	0.97
In methanol	0.02	0.79	0.19	0.33	3.08	4.60	3.47	1.13	0.05	0.89	0.06	0.30	3.75	6.82	4.07	1.25
20 μM Zn(II)	0.03	0.72	0.25	0.33	2.82	4.71	3.50	1.17	0.23	0.77		0.37	3.34		3.24	0.96
20 μM Cd(II)	0.03	0.80	0.17	0.32	2.81	4.72	3.30	1.09	0.170	0.82		0.37	3.22		3.15	1.01
20 μM Hg(II)	0.03	0.68	0.29	0.29	2.67	4.21	3.28	1.08	0.18	0.82		0.35	3.22		3.15	0.99
20 μM Fe(III)	0.04	0.84	0.12	0.34	2.86	5.01	3.28	1.11	0.19	0.81		0.35	3.41		3.33	1.14

---

Temperature dependent luminescence properties of Cu NCs

In order to explore the temperature dependence on the luminescent properties of synthesized Cu NCs, we have recorded luminescence spectra of nanoclusters in both aqueous and methanolic media as a function of temperature. With increase in temperature, the PL intensity of the NCs–cellulase in aqueous media is quenched, whereas enhanced luminescence is noticed in methanolic media (Fig. 4A). Expectedly, in aqueous media, Cu₂₀ NCs–cellulase follows the similar luminescence quenching trend like Cu₁₂ NCs–cellulase (Fig. S8A, ESI†). The quenching mechanism can be understood by the thermal unfolding of stabilizing scaffolds of cellulase. Surprisingly, in methanolic media, PL intensity at 465 nm (Cu₂₀ NCs–cellulase) is getting quenched whereas the PL intensity at 540 nm is getting enhanced with increasing temperature (Fig. 4B). To get an insight on the heterogeneity present in methanolic media, synchronous luminescence study has also been carried out, which reveals that with increasing temperature, the peak at 530 nm (Cu₃₄ NCs–cellulase) is initially blue-shifted and then undergoes spectral broadening (Fig. 4B, inset). Interestingly, it also reveals that in aqueous media the PL intensity of (Cu₂₀ NCs–cellulase) is decreasing whereas the PL intensity of Cu₃₄ NCs–cellulase is increasing with rise in temperature (Fig. S9B, ESI†). The observation of luminescence enhancement may be rationalized by the solvent/temperature-triggered preferential scaffolding ability of cellulase for large-sized nanoclusters through redistribution of secondary structure (greater content of random coil) of enzyme by strengthening the hydrogen-bonding interactions in the backbone.⁴¹ However, the above results demonstrate that photoluminescence of as-synthesized Cu NCs–cellulase are not only temperature dependent, solvent responsive as well. This unique ability of Cu NCs–cellulase can be highly advantageous for imaging of heterogeneous systems (varied polarity), and for probing the temperature as well. Therefore, as-synthesized luminescent nanoclusters may find applications in the biomedical field and nanophotonics.

Fig. 4 [A] Plot of the PL intensity of Cu₁₂ NCs–cellulase in aqueous (filled circle) and in methanolic media (filled square) as a function of temperature. [B] Emission spectra of Cu NCs (method-II) in methanolic medium as a function of temperature (λ_exc = 440 nm). Inset contains the synchronous luminescence spectra of the same mentioned above (Δλ = 20 nm).

Role of the random-coil structure of cellulase

The scaffolding ability of protein is dictated by its secondary structure that plays a central role in biological applications. To get an insight on the post-synthesis structural modification of cellulase, we have performed circular dichroism (CD) studies. The far-UV CD spectra of cellulase alone and Cu NCs are shown in Fig. 5A. The presence of characteristic double minima suggests the existence of α-helical structures in enzyme. However, the CD spectra of nanoclusters stabilized cellulase are remarkably different and indicate total disruption of the helical structure of protein. The random coil structure of cellulase gets significantly populated in order to stabilize the copper nanoclusters. The greater the size of the nanoclusters, higher is the content of random coil. It is quite evident that the random coil structure of cellulase dictates the core-size of the scaffold which promotes preferential stabilization of large-sized nanoclusters over smaller one. Methanol is known to weaken the hydrophobic interactions and thereby resulting in an expansion of the hydrophobic core; at the same time strengthens the interactions between the polar backbone of the protein. Circular dichroism study therefore bolsters again the first hypothesis.

Fig. 5 [A] Far-UV CD spectra of – (i) cellulase, (ii) Cu₁₂ NC–cellulase in aqueous solution, (iii) Cu NCs–cellulase (method-II) in aqueous solution and (iv) Cu NC–cellulase (method-II) in methanolic medium. [B] Extent of luminescence enhancement of Cu₂₀ NC–cellulase in presence of metal ions: I₀ and I are the luminescence intensities in the absence and presence of metal ions, respectively, in aqueous solution containing metal ions – (i) Zn²⁺ ions (filled square), (ii) Cd²⁺ ions (hollow square), (iii) Hg²⁺ ions (filled circle) and (iv) Fe³⁺ ions (hollow circle).

Metal ions are known to stabilize of secondary structure of protein by interacting with carbonyl and amide groups as well as by cross-linking the sidechains.^42–44 “Soft” ions such as Zn(II), Cd(II) and Hg(II), possessing high polarizability and a hard ion, Fe(III) having high positive charge are primarily chosen for this study. “Soft” ions form stable bonds with polarizable ligands such as cysteine thiolates and histidine side whereas hard ions promote electrostatic interactions.^45,46 In this study, aqueous solutions of metal salts, Fe(III), Zn(II), Cd(II), and Hg(II) are gradually added to the solution of the Cu₂₀ NCs–cellulase and stepwise change in luminescence intensity (at 485 nm) of the Cu₂₀ NC–cellulase is shown in Fig. 5B and luminescence spectra are presented in Fig. S10.† The augmentation of luminescence intensity to 100% is observed for all the metal ions upto 40 μM and further addition of Fe(III) ions to signals “turn off” behavior. Interestingly, rapid enhancement of luminescence intensities is observed on the addition of “soft ions”, about 300% enhancement for 60 μM of Zn(II) and Cd(II) ions. The most probable explanation for enhancement of PL of Cu₂₀ NC–cellulase in the presence of ions in aqueous medium is that all of them stabilize the scaffolds of the enzyme through bonding interaction. Time-resolved studies at 20 μM concentration of metal ions indicate that the average lifetime nanoclusters remain unchanged (Table 1). The fluorescence enhancement is therefore the ground state dynamics of enzyme nanocluster complex. However, at higher concentration, the soft ions (d¹⁰ systems) continue to stabilize the structure, whereas Fe(III) ion (d⁵ system) may destabilize the scaffold by induction of strong ionic interaction responsible for quenching of luminescence. Moreover, augmenting luminescence intensity is of vital importance to the development of imaging techniques and illumination sources.

Conclusion

In conclusion, magic numbered, highly luminescent Cu NCs, each of which possesses unique luminescent properties has been synthesized by cellulase alone. Upon incubation of enzyme–metal ion solution, the resultant nanoclusters turns out be blue-luminescent one with emission peak at 401 nm, whereas sonication results the formation of two nanoclusters: cyan-luminescent which emits strongly 485 nm and green luminescent having emission maxima at 570 nm in aqueous solution. Sonication of enzyme solution perhaps increases the inner-diameter of the scaffold to accommodate large-sized nanoclusters. The Cu NCs show high photoluminescence quantum yield and better colloidal stability. Solvent-induced conformational change of cellulase play a significant role to reverse the temperature-dependent luminescent properties of Cu₁₂ NCs–cellulase. Moreover, the preferential stabilization of large-sized Cu₃₄ NCs–cellulase over a smaller one Cu₂₀ NCs–cellulase is found to be dependent on both temperatures as well as solvent. The content of the random coil structure of enzyme is the governing parameter to stabilize the different-sized copper nanoclusters. The addition of “soft ions” results remarkable enhancement of the luminescent intensity of nanoclusters whereas the presence of hard ion, Fe³⁺ quenches the luminescence. The as-synthesized nanoclusters may find profound applications in bioimaging, nanophotonics and interdisciplinary fields. However, it will be of great interest to study the energy transfer between two nanoclusters, which is currently underway in our group.

Acknowledgements

The authors greatly acknowledge RGIPT-Rae Bareli and the Science and Engineering Research Board, Department of Science and Technology, New Delhi for financial support (DST Project No. SB/FT/CS-135/2013). AS and TR thank RGIPT-Rae Bareli for assistantships. Authors sincerely thank Prof. Pratik Sen, IIT Kanpur for time-resolved studies. Authors also thank SAIF-IIT Bombay for TEM data and Tuhin Khan, Anjali Dhir for their help in experiments.

References

1. J. Zheng, P. R. Nicovich and R. M. Dickson, Annu. Rev. Phys. Chem., 2007, 58, 409–431.
2. J. Oliver-Meseguer, J. R. Cabrero-Antonino, I. Domínguez, A. Leyva-Pérez and A. Corma, Science, 2012, 338, 1452–1455.
3. H. Zhang, T. Watanabe, M. Okumura, M. Haruta and N. Toshima, Nat. Mater., 2012, 11, 49–52.
4. T.-H. Lee and R. M. Dickson, Opt. Photonics News, 2004, 15, 22–27.
5. S. Chattoraj and K. Bhattacharyya, J. Phys. Chem. C, 2014, 118, 22339–22346.
6. J. Zhang, L. Tu, S. Zhao, G. Liu, Y. Wang, Y. Wang and Z. Yue, Biosens. Bioelectron., 2015, 67, 296–302.
7. S. Choi, R. M. Dickson and J. Yu, Chem. Soc. Rev., 2012, 41, 1867–1891.
8. Z. Luo, K. Zheng and J. Xie, Chem. Commun., 2014, 50, 5143–5155.
9. H. Qian, M. Zhu, Z. Wu and R. Jin, Acc. Chem. Res., 2012, 45, 1470–1479.
10. M. Brack, Rev. Mod. Phys., 1993, 65, 677–732.
11. W. A. de Heer, Rev. Mod. Phys., 1993, 65, 611–676.
12. H. Tsunoyam and T. Tsukuda, J. Am. Chem. Soc., 2009, 131, 18216–18217.
13. S. Kumar, M. D. Bolan and T. P. Bigioni, J. Am. Chem. Soc., 2010, 132, 13141–13143.
14. J. Xie, Y. Zheng and J. Y. Ying, J. Am. Chem. Soc., 2009, 131, 888–889.
15. A. Mathew, P. R. Sajanlal and T. Pradeep, J. Mater. Chem., 2011, 21, 11205–11212.
16. N. Goswami, A. Giri, M. S. Bootharaju, P. L. Xavier, T. Pradeep and S. K. Pal, Anal. Chem., 2011, 83, 9676–9680.
17. C. Wang, C. Wang, L. Xu, H. Cheng, Q. Lin and C. Zhang, Nanoscale, 2014, 6, 1775–1781.
18. S. Ghosh, N. K. Das, U. Anand and S. Mukherjee, J. Phys. Chem. Lett., 2015, 6, 1293–1298.
19. R. Ghosh, A. K. Sahoo, S. S. Ghosh, A. Paul and A. Chattopadhyay, ACS Appl. Mater. Interfaces, 2014, 6, 3822–3828.
20. Y. Ling, J. J. Wu, Z. F. Gao, N. B. Li and H. Q. Luo, J. Phys. Chem. C, 2015, 119, 27173–27177.
21. X. Gao, Y. Lu, M. Liu, S. He and W. Chen, J. Mater. Chem. C, 2015, 3, 4050–4056.
22. C. Wang, L. Ling, Y. Yao and Q. Song, Nano Res., 2015, 8, 1975–1986.
23. C. P. Joshi, D. Panda, D. J. Martell, N. M. Andoy, T.-Y. Chen, A. Gaballa, J. D. Helmann and P. Chen, Proc. Natl. Acad. Sci. U. S. A., 2012, 109, 15121–15126.
24. H. Tapiero, D. M. Townsend and K. D. Tew, Biomed. Pharmacother., 2003, 57, 386–398.
25. T. Rai and D. Panda, Chem. Phys. Lett., 2015, 623, 108–112.
26. J. Karlsson, M. Saloheimo, M. Siika-aho, M. Tenkanen, M. Penttilae and F. Tjerneld, Eur. J. Biochem., 2001, 268, 6498–6507.
27. P. K. Foreman, D. Brown, L. Dankmeyer, R. Dean, S. Diener, N. S. Dunn-Coleman, F. Goedegebuur, T. D. Houfek, G. J. England, A. S. Kelley, H. J. Meerman, T. Mitchell, C. Mitchinson, H. A. Olivares, P. J. M. Teunissen, J. Yao and M. Ward, J. Biol. Chem., 2003, 278, 31988–31997.
28. J. R. Lakowicz, Principles of Fluorescence Spectroscopy, Springer, 3rd edn, 2011.
29. S. Rafiq, R. Yadav and P. Sen, J. Phys. Chem. A, 2011, 115, 8335–8343.
30. S. Banerjee and A. Datta, Langmuir, 2010, 26, 1172–1176.
31. M. R. DeFelippis, C. P. Murthy, F. Broitman, D. Weinraub, M. Faraggi and M. H. Klapper, J. Phys. Chem., 1991, 95, 3416–3419.
32. J. J. Warren, J. R. Winkler and H. B. Gray, FEBS Lett., 2012, 586, 596–602.
33. S. K. Das, J. Liang, M. Schmidt, F. Laffir and E. Marsili, ACS Nano, 2012, 6, 6165–6173.
34. D. Panda, S. Khatua and A. Datta, J. Phys. Chem. B, 2007, 111, 1648–1656.
35. D. Panda and A. Datta, J. Chem. Sci., 2007, 119, 99–104.
36. D. Patra and A. K. Mishra, Analyst, 2000, 125, 1383–1386.
37. M. D. F. Askari and T. Vo-Dinh, Biopolymers, 2004, 73, 510–523.
38. K. Rurack and M. Spieles, Anal. Chem., 2011, 83, 1232–1242.
39. S. Chattoraj, M. Amin, S. Mohapatra, S. Ghosh and K. Bhattacharyya, ChemPhysChem, 2016, 17, 61–68.
40. N. K. Das, S. Ghosh, A. Priya, S. Datta and S. Mukherjee, J. Phys. Chem. C, 2015, 119, 24657–24664.
41. S. Hwang, Q. Shao, H. Williams, C. Hilty and Y. Q. Gao, J. Phys. Chem. B, 2011, 115, 6653–6660.
42. F. Yu, V. M. Cangelosi, M. L. Zastrow, M. Tegoni, J. S. Plegaria, A. G. Tebo, C. S. Mocny, L. Ruckthong, H. Qayyum and V. L. Pecoraro, Chem. Rev., 2014, 114, 3495–3578.
43. M. Luczkowski, R. D. Ricco, M. Stachura, S. Potocki, L. Hemmingsen and D. Valensin, Metallomics, 2015, 7, 478–490.
44. A. J. Doerr and G. L. McLendon, Inorg. Chem., 2004, 43, 7916–7925.
45. M. Bortolato, F. Besson and B. Roux, Proteins, 1999, 37, 310–318.
46. P. Hainaut and J. Milner, Cancer Res., 1993, 53, 1739–1742.

---

Footnote

† Electronic supplementary information (ESI) available. See DOI: 10.1039/c6ra09763d

---