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Online monitoring of horseradish peroxidase structural changes by Near Infrared (NIR) Spectroscopy
Process Biochemistry xxx (xxxx) xxx–xxx
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Process Biochemistry journal homepage: www.elsevier.com/locate/procbio
Online monitoring of horseradish peroxidase structural changes by Near Infrared (NIR) Spectroscopy Lucas Costa Lopesa,b, Igor Ventura Brandãoa,b, Osmar Calderón Sánchezc, Elton Franceschia,b, Gustavo Borgesa,b, Cláudio Darivaa,b, Alini Tinoco Fricksa,b,* a
Universidade Tiradentes, Av. Murilo Dantas, 300, Farolândia, 49032-490 Aracaju, SE, Brazil Instituto de Tecnologia e Pesquisa. Laboratório de Engenharia de Bioprocessos, Av. Murilo Dantas, 300, Farolândia, 49032-490 Aracaju, SE, Brazil c Laboratorio de Síntesis Orgánica, Facultad de Química, Universidad de La Habana, 10400, La Habana, Cuba b
A R T I C LE I N FO
A B S T R A C T
Keywords: Horseradish peroxidase Near-infrared spectroscopy Circular dichroism Fluorescence PLS
The development of online monitoring techniques is of great relevance for understanding the structural changes of proteins under different conditions in order to maximize their catalytic activity. This study aimed to evaluate the potential of the NIR (near-infrared spectroscopy) technique for the monitoring of alterations of secondary and tertiary structures of Horseradish peroxidase (HRP), an oxidoreductase that has several applications in the industrial environment, food industry and bioremediation. The NIR associated to the multivariate calibration, through the PLS (partial least square) method allowed the construction of a robust model for the prediction of the analysis. The values of the correlation coefficient (R²), root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP) and root mean square error of cross validation (RMSECV) for secondary structure analysis using circular dichroism (CD) data as reference (actual values) were 0.9681, 0.647 (mdeg), 0.945 (mdeg), and 1.12 (mdeg), respectively. For tertiary structure analysis, fluorescence spectroscopy (FL) data were used as reference. R2, RMSEC, RMSEP and RMSECV were, respectively 0.9999, 1.95 (a.u.), 2.09 (a.u.); and 2.19 (a.u.). NIR combined multivariate calibration showed promising results for sctructural changes monitoring of HRP.
1. Introduction Peroxidases (POD) are heme proteins involved in the oxidation of a wide range of organic and inorganic substrates by either H2O2 or organic peroxides as terminal oxidants. In recent years, in order to maintain the original characteristics of foods and also reduce the production costs in food industry, alternative methods to the conventional thermal heating, such as microwave irradiation have been investigated with respect to peroxidase inactivation. However, all monitoring analyses are commonly performed after sample processing (offline analysis). Thus, there is a gap in the literature regarding a technique that allows real-time analysis of processing (online analysis) [1]. Near infrared (NIR) is a fast, non-destructive, low-cost analytical technique and has been successfully applied for quantitative and qualitative analysis of several compounds in environmental, agricultural processes such as quality control for animal feed and herbal products [2,3]. For the analysis and correlation of the data collected by NIR, chemometric techniques such as PLS (partial least square) are generally used [4,5].
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Recent studies have shown the versatility and potentiality of near infrared spectroscopy for analysis of chemical compounds and analyzed the protein content of several samples. Lopes et al. [6] analyzed NIR detection capacity for biocatalytic oxidation of guaiacol catalyzed by horseradish peroxidase (HRP). The study showed excellent correlation coefficient values between NIR and UV–vis spectroscopy. The study concluded that the NIR can be a great alternative to UV–vis spectroscopy, which allows in situ analysis of biocatalytic reactions. Escuredo et al. [7] used NIR as an alternative technique to determine specific amino acids in quinoa (Chenopodium quinoa). The study showed that the predictive capacity of NIR was excellent for the amino acids arginine, cysteine, isoleucine, lysine, phenylalanine, proline, serine, threonine, tyrosine, tryptophan and valine. Astruc et al. [8] analyzed molecular alterations in gelatin aging using NIR and fluorescence spectroscopy. The study mentioned that both techniques allows a characterization of the sample in the native state, thus avoiding possible changes in the structure and composition of the sample through the preparation thereof. However, there is a gap between the analysis of enzyme structures
Corresponding author at: Universidade Tiradentes, Av. Murilo Dantas, 300, Farolândia, 49032-490 Aracaju, SE, Brazil. E-mail address: [email protected] (A.T. Fricks).
https://doi.org/10.1016/j.procbio.2019.11.004 Received 11 June 2019; Received in revised form 7 October 2019; Accepted 4 November 2019 1359-5113/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: Lucas Costa Lopes, et al., Process Biochemistry, https://doi.org/10.1016/j.procbio.2019.11.004
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Fluorescence analysis was performed on a Jasco spectrofluorimeter (FP6300 - Jasco Corporation, Tokyo, Japan) using a quartz cuvette with 1.00 cm optical path at room temperature (25 °C). All samples were made in triplicate. The emission spectra (λem at 290−400 nm) were obtained with the maximum excitation wavelength of λex =280 nm.
and their correlation with enzyme stability. The calibration and correlation of data collected from the circular dichroism (CD) and fluorescence associated with the conveniently selected spectra allows, through chemometric techniques, the determination of prediction models for changes in HRP structures using NIR. Thus, the objective of this work is to investigate and correlate data of CD and fluorescence spectroscopy to NIR spectra under the same experimental conditions, in order to correlate these data and develop NIR as a promising alternative tool for in situ analysis of structural modifications in the enzyme.
2.5. Chemometric analysis The method of multivariate calibration used to quantify the variations in the enzymatic structures was the partial least squares (PLS) method. All calibrations were done using TQ Analyst software (thermo scientific). For the construction of each multivariate calibration model, the data were distinguished into calibration values (70 %) and validation values (30 %). Root mean squared error (RMSEC), root mean squared error prediction (RMSEP) and root mean cross-validation squared error (RMSECV) values were used to evaluate each regression model as well as to determine the best number of factors for each analysis. The use of RMSEP is indicated, as it generates more realistic results compared to the other quadratic error values. In addition, the accuracy of the model was assessed using the coefficient of determination (R²) [9–11].
2. Material and methods The enzyme solution was prepared and divided into separate containers for separate analysis under specific temperature conditions using the near infrared spectroscopy technique. Subsequently, the collected data were treated using the partial least squares (PLS) chemometric tool, with the aim of generating a good chemometric model for the classification and prediction of the structural alterations of the enzyme in the reaction medium. 2.1. Preparation of the HRP solution
3. Results and discussion
Horseradish isoenzyme C-peroxidase (HRP, EC 1.11.1.7) was purchased from Sigma Aldrich (RZ = 3.0). The HRP solution was prepared in accordance with the literature by dissolving 7.42 mg of the enzyme in 35 mL of Phosphate buffer Na2 HPO4·2H2O - 100 mM pH 6.0 (0.212 mg/mL) [1]. The HRP concentration for all experimental conditions was 5.3 μM, considering a molecular mass of 40 KDa.
3.1. NIR and CD/fluorescence espectra measurements For studies of alterations in the secondary and tertiary structures of HRP in conventional heating under different temperatures (30 °C, 40 °C, 45 °C, 50 °C and 60 °C), NIR spectra of specific bands (amide bands) were correlated with previous data of circular dichroism and fluorescence [1]. The far-UV CD spectrum of HRP has characteristic bands of α-helix structure at 208 and 222 nm. The intensities of the two negative peaks in the CD spectra of HRP decreased with increasing temperature under CH, indicating partial loss of the α-helix content of HRP [1]. Changes in the tertiary structure of HRP are analyzed according to the exposure of the amino acid tryptophan (trp) as it is positioned close to the active site of the enzyme [1,12]. Intrinsic fluorescence spectroscopy is used in the literature to evaluate changes in the tertiary structure of proteins due to apparatus being able to detect fluorophores (Trp, Tyr and Phe), which are amino acid residues with phenolic compounds in their structure. These amino acids are part of the structure of a series of proteins, and may be linked to specific regions of the protein, such as the active site of an enzyme. HRP has 1 residue of tryptophan (Trp 117) near the Heme region (active site), thus fluorescence spectroscopy can be used to analyze changes in the tertiary structure of this enzyme [1]. The fluorescence spectra acquired for untreated HRP are characterized by a single peak at approximately 327 nm, suggesting that Trp is protected from the action of the solvent [1]. As shown in Fig. 1B the fluorescence intensity increased with increasing temperature of exposure (30−45 °C). At 50 and 60 °C, the fluorescense intensity decreased, this can be correlated to protein aggregation process. Fig. 1 shows that the NIR was able to capture variations of absorbance values in specific bands of the spectra in the enzymatic solution treated in conventional heating at all mentioned temperatures. It is suggested that these specific band changes can be related to changes in the secondary and tertiary structure of HRP. The bands in the 6565 to 6248 cm-1 and 10,525 to 9091 cm-1 regions correspond to the first and the second overtone of the amide band A, respectively. This band is characterized by stretching of the NH bond and its frequency depends on the strength of the hydrogen bond [13]. The region between 6320 and 6039 cm-1 is related to the amide band II and the first overtone of the amide band B. The amide band II, in fundament state, represents mainly NH (60 %) folding and the amide band B is related to Fermi resonance between the overtone of amide II or amide combination I / amide II and the vibrational intensity of NH
2.2. HRP Conventional heating (CH) treatment procedure Each vessel containing HRP solutions (7 mL) was placed in a thermostatic bath (Marconi - MA 159) at specific temperatures (30 °C, 40 °C, 45 °C, 50 °C and 60 °C), respectively, for 12 h. The temperatures were selected according to a previous study that relates enzymatic activity, data of circular dichroism and fluorescence to the secondary and tertiary structure of HRP [1]. Throughout the procedure of heating the samples at specific temperatures, the NIR probe remained immersed in the solution to monitor the entire process. 2.3. NIR measurements HRP samples (native and treated as item 2.2) were submitted, and an average of 16 sequential scans generated a spectra NIR, totaling 10 spectra of each experiment performed at the respective temperatures. The NIR (FTNIR·MPA - Bruker ®) spectrometer was operated in absorbance mode. A 5 mm optical path transfer probe (Falcata -FTNIR-MPABruker®) was coupled to the equipment using a fiber optic cable. A total of 192 spectra with a resolution of 8 cm-1 were collected, with a delay of 900 s for each measurement, totaling 12 h of procedure for each sample. A spectral capture software (OPUS / OVP - Opus Validation Program) was used. The spectrometer was operated with a scanning spectral region between 800–2500 nm (12,500– 4000 cm-1). However, due to the presence of spectral noise, specific regions of the spectrum were selected for analysis. 2.4. HRP circular dichroism (CD) and fluorescence (FL) analysis Circular dichroism (CD) data (raw ellipticity data (Ө) in milli degrees (mdeg)) and fluorescence (u.a) were obtained under the same conditions (published data) [1] and were used as reference for calibration and validation of NIR. CD spectra were collected using the Chirascan spectro-polarimeter (Applied Photophysics, Surrey, UK), with a 1.00 mm quartz cuvette optical path at room temperature (25 °C). The spectra were scanned in triplicate in a specific UV-distant spectral band (260−190 nm) at 50 nm/min and 0.2 nm bandwidth. 2
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Fig. 1. Characterization of amide bands (A: amide band A - second overtone / B: amide band A – first overtone / C: amide band II and first overtone of amide B / D: Amide III band) at specific wavelengths of the spectra obtained by Near infrared (NIR) treated in conventional heating at 30 °C, 40 °C, 45 °C, 50 °C, 60 °C and native.
Fig. 2. Variations of the Near infrared spectra of the Horseradish peroxidase (HRP) solution at different temperatures (30 °C, 40 °C, 45 °C, 50 °C and 60 °C) in the specific band of tryptophan (trp).
HRP. stretching [14]. In conjunction with amide A, it presents twice the energetic level of the amide band II [15]. Finally, the region between 5600 and 5440 cm-1 corresponds to the amide band III, which according to the literature, can also be used to predict the secondary structure [15]. All these correlations of the NIR wavelength values with the specific amide bands are graphically elucidated in Fig. 1. Two regions of the NIR spectra (5500 to 4000 and 8000 to 6800) presented noises (Fig. 1). The band (6600 to 6600) in the region containing noise is correlated with the amide band I. This phenomenon is due to the fact that the NIR bands are generally large and often overlapping, causing a strong multicollinearity of the data. The NIR spectra bands most predominant in biological samples from overtones and combinations of the fundamental vibrations of the MIR are the CeH, NH, OH and SHeee bonds [16]. Although the amide band I is one of the most studied in the literature; when the study in focus analyses secondary structures in proteins, the reports showed that the amide II amide III, amide A and amide B bands presented satisfactory results [13]. The most common application of infrared spectroscopy in protein studies in the literature is related to changes in secondary structure. These changes are analyzed by investigating the modifications in the amide bands [13,15]. The spectra of HRP solutions treated by conventional heat obtained using the NIR probe showed absorption bands in specific regions of the spectra. The selection of these bands was based on the visual changes of the spectra associated to the regions corresponding to specific vibrations based on the literature; 6565 to 6248 cm -1 , 10,525 to 9091 cm-1, 6320 to 6039 cm-1 and 5600 to 5440 cm-1, corresponding to combinations, first and second near infrared overtones (Fig. 1). Correlating the spectral range of the tryptophan band (trp) in the mid infrared (1334 to 1455 cm-1) with the near infrared electromagnetic spectra, the NIR spectrum band between 5336 to 5820 cm-1 corresponds to changes of this amino acid [17]. Thus, the study of modifications in tertiary structure was done by associating this region of the NIR spectrum with the fluorescence spectroscopy data acquired from previous studies [1]. Fig. 2 presents, in an approximate perspective, the variations of the NIR spectra of the HRP native and treated at different temperatures captured by the NIR probe in the specific band related to the amino acid tryptophan (trp). When comparing Figs. 1 and 2, a similarity in spectral variations can be observed for all temperatures. This fact suggests an efficiency of the NIR in capturing the variations in tertiary structure of
3.2. Parameters of the calibration models: PLS - partial least square In the present work, chemometric models were elaborated with the intention of investigating the alterations of the secondary and tertiary structure of HRP. The models were constructed using chemistric method PLS (partial least square), which is often used in the literature for biochemical analysis [18–21]. The multivariate calibration model was constructed by associating the values of circular dichroism (CD) and fluorescence spectroscopy (FL) of previous studies to specific bands corresponding to the modifications in the amide and residue regions of the amino acid tryptophan, respectively, using chemometric method PLS [1]. To quantify the changes in the secondary structure through the regression model, 70 % and 30 % of the data were correlated to the calibration and prediction values, respectively [20]. Usually, the investigation of better calibration models is based on some parameters such as, correlation coefficient (R²), RMSEC, RMSEP and RMSECV as well as the correlation between them [5]. The latter is used to determine the optimal number of latent variables. A sample is removed from the total samples for validation and the remaining samples are used to construct a calibration model. This procedure is repeated for all the samples under analysis, generating a final value of RMSECV [5,10,18]. In addition, the RMSECV value associated with the RMSEP value is also considered a valid parameter for the robustness of the model created [22,23]. The RMSEP is defined as the standard deviation for residues resulting from the difference between actual values and values predicted by the NIR for samples outside the calibration set. RMSEC is the standard deviation for residues resulting from the difference between actual values and values predicted by the NIR for samples within the calibration set. The proximity of the RMSEP and RMSEC values, as well as their values of correlation coefficient, give acceptable parameters for the validation of the constructed model [18]. A basic relation for a good calibration model can be presented as follows: 0 ≤ R² ≤ 1, and 0 ≤ RMSEC, and since the higher the value of the correlation coefficient, the lower the RMSEC value [5]. In addition, it is recommended to use the RMSEP to evaluate the model, since it generates more realistic results because it is calculated using values outside the elaboration of the model [9]. High R² values of validation associated with low RMSEP values are considered as high levels of precision and efficiency for the prediction of the chemometric model 3
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Table 1 Statistical descriptions of the Circular Dichroism (CD) versus Near infrared (NIR) calibration for HRP secondary structure changes. Sample HRP 0.2 mg/mL
Number of latent variables 6
Calibration RMSEC (mdeg) 0.647
Validation 2
R 0.9681
RMSEP (mdeg) 0.945
Cross-validation 2
R 0.9633
RMSECV (mdeg) 1.12
R2 0.9018
[16,23].
of the secondary structure of the HRP enzyme.
3.2.1. Circular dichroism versus NIR: partial least squares regression – PLS The PLS calibration model was constructed to investigate and validate the NIR as an alternative technique for analysis of secondary structure in the Horseradish peroxidase enzyme. For this, circular dichroism (CD) values were correlated to the NIR spectra in the same experimental conditions, with the aim of having a better congruence between the studied data and a better comparison of the same ones. The optimal number of latent variables of the model, obtained through RMSECV, was 6 (Table 1). The values of the calibration correlation coefficient R² (cal) and RMSEC of validation R² (val) and RMSEP, as well as the values of the cross-validation correlation coefficient R² (cv) and RMSECV were, respectively 0.9681 / 0.647 (mdeg); 0.9633 / 0.945 (mdeg); and 0.9018 / 1.12 (mdeg) (Table 1). According to the parameters presented in the literature, these results indicate an efficient calibration and prediction model for HRP secondary structure analysis. Lin et al. [24] evaluated the protein content in barley grains using NIR associated with multivariate calibration. The PLS calibration of the study showed values of the correlation coefficient (R²) of 0.9783 and RMSEP of 26.18. The authors concluded that the model showed a good correlation between the real values and predicted values. Ferreira et al. [25] evaluated, among other parameters, the protein content in soybean. The R² was 0.88, the RMSEP and RMSECV were 1.32 and 1.76, respectively. According to the authors, the results presented suggest that NIR is a technique that has predictive abilities. Wang et al. [26] determined the protein content of peanuts using NIR. The authors obtained a correlation coefficient (R²) of 0.99 and RMSEP of 6.53. They affirm that the NIR associated with multivariate calibration has a significant potential to determine the protein content in peanuts. Fig. 3 shows the comparison of the raw ellipticity measurements using the circular dichroism spectroscopic technique (CD) as a parameter for real values and the spectra obtained by the NIR as a parameter for calculated values to calibration. The data presented in the graph shows congruence between the values of the two techniques used. Thus, it is suggested that NIR may be a promising tool for analysis
3.2.2. Fluorescence versus NIR: partial least squares regression – PLS Fluorescence spectroscopy (FL) values were correlated to the NIR spectra in the same experimental conditions, for the construction of a robust model that allows the validation of the NIR as an alternative technique for analysis of the HRP tertiary structure. The RMSECV parameter was used to obtain the optimal number of latent variables for the model used. The optimal number of latent variables in the model was 4 (Table 2). The values of the calibration correlation coefficient R² (cal) and RMSEC; of validation R² (val) and RMSEP; as well as the values of the cross-validation correlation coefficient R² (cv) and RMSECV were, respectively 0.9999 / 1.95 (a.u.); 0.9999 / 2.09 (a.u.); and 0.9999 / 2.19 (a.u.) (Table 2). According to the parameters presented in the literature, these results indicate an efficient calibration and prediction model for HRP secondary structure analysis. Escuredo et al. [7] investigated the amino acid composition in quinoa using fiber-optic NIR probe. The R2 value for the presence of tryptophan (trp) in the sample was 0.92. The RMSEC, RMSEP and RMSECV were, respectively 0.07, 0.06 and 0.16. The authors conclude that NIR has an efficient predictive capacity for the detection of tryptophan. Zhang et al. [27] analyzed the prediction of amino acid composition in brown rice using NIR. Among other amino acids, two fluorophores were investigated, tyrosine (tyr) and phenylalanine (Phe). The values of R², RMSEC, RMSEP and RMSECV for tyrosine were, respectively 0.836, 0.025, 0.033, and 0.028 and for phenylalanine the values were, respectively 0.967, 0.013, 0.016 and 0.014. According to the authors, the results suggest that NIR is an efficient tool for the determination of protein content in brown rice. Fig. 4 shows the comparison of fluorescence intensity measurements using fluorescence spectroscopy (FL) as a parameter for real values and the spectra obtained by NIR as a parameter for calculated values to calibration. The data presented in the graph shows congruence between the values of the two techniques used. The results demonstrated the ability of NIR to obtain linear responses to trp modifications in HRP, hence its efficiency in capturing changes in the tertiary structure of the enzyme. 4. Conclusion Near infrared spectroscopy (NIR) associated with chemometrics is an efficient technique for analysis of secondary and tertiary structure of HRP. The results obtained using the NIR probe showed the ability of the equipment to capture variations in the specific bands for each structure of the enzyme. One of the relevance of the study was to construct a chemometric model that allows the real-time monitoring of the variations of the secondary and tertiary structures of the enzyme of the HRP solution once the probe can be introduced into the reaction medium (on line). Further studies may be performed by analyzing the structural behavior of the enzyme in alternative media, such as pressurized fluids for example using near infrared spectroscopy (NIR). Futhermore, the robustness of NIRs analyses can be evaluated with studies involving other proteins and enzymes. Declaration of Competing Interest
Fig. 3. Comparison of raw ellipticity measurements correlating Circular dichroism (CD) (actual values) and Near infrared (NIR) (calculated values) at specifics temperatures (30 °C, 40 °C, 45 °C, 50 °C and 60 °C).
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to 4
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Table 2 Statistical descriptions of the Fluorescence (FL) versus Near infrared (NIR) calibration for HRP tertiary structure changes. Sample HRP 0.2 mg/mL
Number of latent variables 4
Calibration RMSEC (a.u.) 1.95
Validation 2
R 0.9999
[9]
[10]
[11]
[12]
[13] [14]
Fig. 4. Comparison of fluorescence intensity measurements correlating Fluorescence (FL) (real values) and Near infrared (NIR) (calculated values) at specifics temperatures (30 °C, 40 °C, 45 °C, 50 °C and 60 °C).
[15] [16]
[17]
influence the work reported in this paper.
[18]
Acknowledgements The authors are grateful for the financial support from the Brazilian research funding agencies CAPES,CNPq and FAPITEC/SE.
[19] [20]
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5
RMSEP (a.u.) 2.09
Cross-validation 2
R 0.9999
RMSECV (a.u.) 2.19
R2 0.9999
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Process Biochemistry journal homepage: www.elsevier.com/locate/procbio
Online monitoring of horseradish peroxidase structural changes by Near Infrared (NIR) Spectroscopy Lucas Costa Lopesa,b, Igor Ventura Brandãoa,b, Osmar Calderón Sánchezc, Elton Franceschia,b, Gustavo Borgesa,b, Cláudio Darivaa,b, Alini Tinoco Fricksa,b,* a
Universidade Tiradentes, Av. Murilo Dantas, 300, Farolândia, 49032-490 Aracaju, SE, Brazil Instituto de Tecnologia e Pesquisa. Laboratório de Engenharia de Bioprocessos, Av. Murilo Dantas, 300, Farolândia, 49032-490 Aracaju, SE, Brazil c Laboratorio de Síntesis Orgánica, Facultad de Química, Universidad de La Habana, 10400, La Habana, Cuba b
A R T I C LE I N FO
A B S T R A C T
Keywords: Horseradish peroxidase Near-infrared spectroscopy Circular dichroism Fluorescence PLS
The development of online monitoring techniques is of great relevance for understanding the structural changes of proteins under different conditions in order to maximize their catalytic activity. This study aimed to evaluate the potential of the NIR (near-infrared spectroscopy) technique for the monitoring of alterations of secondary and tertiary structures of Horseradish peroxidase (HRP), an oxidoreductase that has several applications in the industrial environment, food industry and bioremediation. The NIR associated to the multivariate calibration, through the PLS (partial least square) method allowed the construction of a robust model for the prediction of the analysis. The values of the correlation coefficient (R²), root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP) and root mean square error of cross validation (RMSECV) for secondary structure analysis using circular dichroism (CD) data as reference (actual values) were 0.9681, 0.647 (mdeg), 0.945 (mdeg), and 1.12 (mdeg), respectively. For tertiary structure analysis, fluorescence spectroscopy (FL) data were used as reference. R2, RMSEC, RMSEP and RMSECV were, respectively 0.9999, 1.95 (a.u.), 2.09 (a.u.); and 2.19 (a.u.). NIR combined multivariate calibration showed promising results for sctructural changes monitoring of HRP.
1. Introduction Peroxidases (POD) are heme proteins involved in the oxidation of a wide range of organic and inorganic substrates by either H2O2 or organic peroxides as terminal oxidants. In recent years, in order to maintain the original characteristics of foods and also reduce the production costs in food industry, alternative methods to the conventional thermal heating, such as microwave irradiation have been investigated with respect to peroxidase inactivation. However, all monitoring analyses are commonly performed after sample processing (offline analysis). Thus, there is a gap in the literature regarding a technique that allows real-time analysis of processing (online analysis) [1]. Near infrared (NIR) is a fast, non-destructive, low-cost analytical technique and has been successfully applied for quantitative and qualitative analysis of several compounds in environmental, agricultural processes such as quality control for animal feed and herbal products [2,3]. For the analysis and correlation of the data collected by NIR, chemometric techniques such as PLS (partial least square) are generally used [4,5].
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Recent studies have shown the versatility and potentiality of near infrared spectroscopy for analysis of chemical compounds and analyzed the protein content of several samples. Lopes et al. [6] analyzed NIR detection capacity for biocatalytic oxidation of guaiacol catalyzed by horseradish peroxidase (HRP). The study showed excellent correlation coefficient values between NIR and UV–vis spectroscopy. The study concluded that the NIR can be a great alternative to UV–vis spectroscopy, which allows in situ analysis of biocatalytic reactions. Escuredo et al. [7] used NIR as an alternative technique to determine specific amino acids in quinoa (Chenopodium quinoa). The study showed that the predictive capacity of NIR was excellent for the amino acids arginine, cysteine, isoleucine, lysine, phenylalanine, proline, serine, threonine, tyrosine, tryptophan and valine. Astruc et al. [8] analyzed molecular alterations in gelatin aging using NIR and fluorescence spectroscopy. The study mentioned that both techniques allows a characterization of the sample in the native state, thus avoiding possible changes in the structure and composition of the sample through the preparation thereof. However, there is a gap between the analysis of enzyme structures
Corresponding author at: Universidade Tiradentes, Av. Murilo Dantas, 300, Farolândia, 49032-490 Aracaju, SE, Brazil. E-mail address: [email protected] (A.T. Fricks).
https://doi.org/10.1016/j.procbio.2019.11.004 Received 11 June 2019; Received in revised form 7 October 2019; Accepted 4 November 2019 1359-5113/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: Lucas Costa Lopes, et al., Process Biochemistry, https://doi.org/10.1016/j.procbio.2019.11.004
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Fluorescence analysis was performed on a Jasco spectrofluorimeter (FP6300 - Jasco Corporation, Tokyo, Japan) using a quartz cuvette with 1.00 cm optical path at room temperature (25 °C). All samples were made in triplicate. The emission spectra (λem at 290−400 nm) were obtained with the maximum excitation wavelength of λex =280 nm.
and their correlation with enzyme stability. The calibration and correlation of data collected from the circular dichroism (CD) and fluorescence associated with the conveniently selected spectra allows, through chemometric techniques, the determination of prediction models for changes in HRP structures using NIR. Thus, the objective of this work is to investigate and correlate data of CD and fluorescence spectroscopy to NIR spectra under the same experimental conditions, in order to correlate these data and develop NIR as a promising alternative tool for in situ analysis of structural modifications in the enzyme.
2.5. Chemometric analysis The method of multivariate calibration used to quantify the variations in the enzymatic structures was the partial least squares (PLS) method. All calibrations were done using TQ Analyst software (thermo scientific). For the construction of each multivariate calibration model, the data were distinguished into calibration values (70 %) and validation values (30 %). Root mean squared error (RMSEC), root mean squared error prediction (RMSEP) and root mean cross-validation squared error (RMSECV) values were used to evaluate each regression model as well as to determine the best number of factors for each analysis. The use of RMSEP is indicated, as it generates more realistic results compared to the other quadratic error values. In addition, the accuracy of the model was assessed using the coefficient of determination (R²) [9–11].
2. Material and methods The enzyme solution was prepared and divided into separate containers for separate analysis under specific temperature conditions using the near infrared spectroscopy technique. Subsequently, the collected data were treated using the partial least squares (PLS) chemometric tool, with the aim of generating a good chemometric model for the classification and prediction of the structural alterations of the enzyme in the reaction medium. 2.1. Preparation of the HRP solution
3. Results and discussion
Horseradish isoenzyme C-peroxidase (HRP, EC 1.11.1.7) was purchased from Sigma Aldrich (RZ = 3.0). The HRP solution was prepared in accordance with the literature by dissolving 7.42 mg of the enzyme in 35 mL of Phosphate buffer Na2 HPO4·2H2O - 100 mM pH 6.0 (0.212 mg/mL) [1]. The HRP concentration for all experimental conditions was 5.3 μM, considering a molecular mass of 40 KDa.
3.1. NIR and CD/fluorescence espectra measurements For studies of alterations in the secondary and tertiary structures of HRP in conventional heating under different temperatures (30 °C, 40 °C, 45 °C, 50 °C and 60 °C), NIR spectra of specific bands (amide bands) were correlated with previous data of circular dichroism and fluorescence [1]. The far-UV CD spectrum of HRP has characteristic bands of α-helix structure at 208 and 222 nm. The intensities of the two negative peaks in the CD spectra of HRP decreased with increasing temperature under CH, indicating partial loss of the α-helix content of HRP [1]. Changes in the tertiary structure of HRP are analyzed according to the exposure of the amino acid tryptophan (trp) as it is positioned close to the active site of the enzyme [1,12]. Intrinsic fluorescence spectroscopy is used in the literature to evaluate changes in the tertiary structure of proteins due to apparatus being able to detect fluorophores (Trp, Tyr and Phe), which are amino acid residues with phenolic compounds in their structure. These amino acids are part of the structure of a series of proteins, and may be linked to specific regions of the protein, such as the active site of an enzyme. HRP has 1 residue of tryptophan (Trp 117) near the Heme region (active site), thus fluorescence spectroscopy can be used to analyze changes in the tertiary structure of this enzyme [1]. The fluorescence spectra acquired for untreated HRP are characterized by a single peak at approximately 327 nm, suggesting that Trp is protected from the action of the solvent [1]. As shown in Fig. 1B the fluorescence intensity increased with increasing temperature of exposure (30−45 °C). At 50 and 60 °C, the fluorescense intensity decreased, this can be correlated to protein aggregation process. Fig. 1 shows that the NIR was able to capture variations of absorbance values in specific bands of the spectra in the enzymatic solution treated in conventional heating at all mentioned temperatures. It is suggested that these specific band changes can be related to changes in the secondary and tertiary structure of HRP. The bands in the 6565 to 6248 cm-1 and 10,525 to 9091 cm-1 regions correspond to the first and the second overtone of the amide band A, respectively. This band is characterized by stretching of the NH bond and its frequency depends on the strength of the hydrogen bond [13]. The region between 6320 and 6039 cm-1 is related to the amide band II and the first overtone of the amide band B. The amide band II, in fundament state, represents mainly NH (60 %) folding and the amide band B is related to Fermi resonance between the overtone of amide II or amide combination I / amide II and the vibrational intensity of NH
2.2. HRP Conventional heating (CH) treatment procedure Each vessel containing HRP solutions (7 mL) was placed in a thermostatic bath (Marconi - MA 159) at specific temperatures (30 °C, 40 °C, 45 °C, 50 °C and 60 °C), respectively, for 12 h. The temperatures were selected according to a previous study that relates enzymatic activity, data of circular dichroism and fluorescence to the secondary and tertiary structure of HRP [1]. Throughout the procedure of heating the samples at specific temperatures, the NIR probe remained immersed in the solution to monitor the entire process. 2.3. NIR measurements HRP samples (native and treated as item 2.2) were submitted, and an average of 16 sequential scans generated a spectra NIR, totaling 10 spectra of each experiment performed at the respective temperatures. The NIR (FTNIR·MPA - Bruker ®) spectrometer was operated in absorbance mode. A 5 mm optical path transfer probe (Falcata -FTNIR-MPABruker®) was coupled to the equipment using a fiber optic cable. A total of 192 spectra with a resolution of 8 cm-1 were collected, with a delay of 900 s for each measurement, totaling 12 h of procedure for each sample. A spectral capture software (OPUS / OVP - Opus Validation Program) was used. The spectrometer was operated with a scanning spectral region between 800–2500 nm (12,500– 4000 cm-1). However, due to the presence of spectral noise, specific regions of the spectrum were selected for analysis. 2.4. HRP circular dichroism (CD) and fluorescence (FL) analysis Circular dichroism (CD) data (raw ellipticity data (Ө) in milli degrees (mdeg)) and fluorescence (u.a) were obtained under the same conditions (published data) [1] and were used as reference for calibration and validation of NIR. CD spectra were collected using the Chirascan spectro-polarimeter (Applied Photophysics, Surrey, UK), with a 1.00 mm quartz cuvette optical path at room temperature (25 °C). The spectra were scanned in triplicate in a specific UV-distant spectral band (260−190 nm) at 50 nm/min and 0.2 nm bandwidth. 2
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Fig. 1. Characterization of amide bands (A: amide band A - second overtone / B: amide band A – first overtone / C: amide band II and first overtone of amide B / D: Amide III band) at specific wavelengths of the spectra obtained by Near infrared (NIR) treated in conventional heating at 30 °C, 40 °C, 45 °C, 50 °C, 60 °C and native.
Fig. 2. Variations of the Near infrared spectra of the Horseradish peroxidase (HRP) solution at different temperatures (30 °C, 40 °C, 45 °C, 50 °C and 60 °C) in the specific band of tryptophan (trp).
HRP. stretching [14]. In conjunction with amide A, it presents twice the energetic level of the amide band II [15]. Finally, the region between 5600 and 5440 cm-1 corresponds to the amide band III, which according to the literature, can also be used to predict the secondary structure [15]. All these correlations of the NIR wavelength values with the specific amide bands are graphically elucidated in Fig. 1. Two regions of the NIR spectra (5500 to 4000 and 8000 to 6800) presented noises (Fig. 1). The band (6600 to 6600) in the region containing noise is correlated with the amide band I. This phenomenon is due to the fact that the NIR bands are generally large and often overlapping, causing a strong multicollinearity of the data. The NIR spectra bands most predominant in biological samples from overtones and combinations of the fundamental vibrations of the MIR are the CeH, NH, OH and SHeee bonds [16]. Although the amide band I is one of the most studied in the literature; when the study in focus analyses secondary structures in proteins, the reports showed that the amide II amide III, amide A and amide B bands presented satisfactory results [13]. The most common application of infrared spectroscopy in protein studies in the literature is related to changes in secondary structure. These changes are analyzed by investigating the modifications in the amide bands [13,15]. The spectra of HRP solutions treated by conventional heat obtained using the NIR probe showed absorption bands in specific regions of the spectra. The selection of these bands was based on the visual changes of the spectra associated to the regions corresponding to specific vibrations based on the literature; 6565 to 6248 cm -1 , 10,525 to 9091 cm-1, 6320 to 6039 cm-1 and 5600 to 5440 cm-1, corresponding to combinations, first and second near infrared overtones (Fig. 1). Correlating the spectral range of the tryptophan band (trp) in the mid infrared (1334 to 1455 cm-1) with the near infrared electromagnetic spectra, the NIR spectrum band between 5336 to 5820 cm-1 corresponds to changes of this amino acid [17]. Thus, the study of modifications in tertiary structure was done by associating this region of the NIR spectrum with the fluorescence spectroscopy data acquired from previous studies [1]. Fig. 2 presents, in an approximate perspective, the variations of the NIR spectra of the HRP native and treated at different temperatures captured by the NIR probe in the specific band related to the amino acid tryptophan (trp). When comparing Figs. 1 and 2, a similarity in spectral variations can be observed for all temperatures. This fact suggests an efficiency of the NIR in capturing the variations in tertiary structure of
3.2. Parameters of the calibration models: PLS - partial least square In the present work, chemometric models were elaborated with the intention of investigating the alterations of the secondary and tertiary structure of HRP. The models were constructed using chemistric method PLS (partial least square), which is often used in the literature for biochemical analysis [18–21]. The multivariate calibration model was constructed by associating the values of circular dichroism (CD) and fluorescence spectroscopy (FL) of previous studies to specific bands corresponding to the modifications in the amide and residue regions of the amino acid tryptophan, respectively, using chemometric method PLS [1]. To quantify the changes in the secondary structure through the regression model, 70 % and 30 % of the data were correlated to the calibration and prediction values, respectively [20]. Usually, the investigation of better calibration models is based on some parameters such as, correlation coefficient (R²), RMSEC, RMSEP and RMSECV as well as the correlation between them [5]. The latter is used to determine the optimal number of latent variables. A sample is removed from the total samples for validation and the remaining samples are used to construct a calibration model. This procedure is repeated for all the samples under analysis, generating a final value of RMSECV [5,10,18]. In addition, the RMSECV value associated with the RMSEP value is also considered a valid parameter for the robustness of the model created [22,23]. The RMSEP is defined as the standard deviation for residues resulting from the difference between actual values and values predicted by the NIR for samples outside the calibration set. RMSEC is the standard deviation for residues resulting from the difference between actual values and values predicted by the NIR for samples within the calibration set. The proximity of the RMSEP and RMSEC values, as well as their values of correlation coefficient, give acceptable parameters for the validation of the constructed model [18]. A basic relation for a good calibration model can be presented as follows: 0 ≤ R² ≤ 1, and 0 ≤ RMSEC, and since the higher the value of the correlation coefficient, the lower the RMSEC value [5]. In addition, it is recommended to use the RMSEP to evaluate the model, since it generates more realistic results because it is calculated using values outside the elaboration of the model [9]. High R² values of validation associated with low RMSEP values are considered as high levels of precision and efficiency for the prediction of the chemometric model 3
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Table 1 Statistical descriptions of the Circular Dichroism (CD) versus Near infrared (NIR) calibration for HRP secondary structure changes. Sample HRP 0.2 mg/mL
Number of latent variables 6
Calibration RMSEC (mdeg) 0.647
Validation 2
R 0.9681
RMSEP (mdeg) 0.945
Cross-validation 2
R 0.9633
RMSECV (mdeg) 1.12
R2 0.9018
[16,23].
of the secondary structure of the HRP enzyme.
3.2.1. Circular dichroism versus NIR: partial least squares regression – PLS The PLS calibration model was constructed to investigate and validate the NIR as an alternative technique for analysis of secondary structure in the Horseradish peroxidase enzyme. For this, circular dichroism (CD) values were correlated to the NIR spectra in the same experimental conditions, with the aim of having a better congruence between the studied data and a better comparison of the same ones. The optimal number of latent variables of the model, obtained through RMSECV, was 6 (Table 1). The values of the calibration correlation coefficient R² (cal) and RMSEC of validation R² (val) and RMSEP, as well as the values of the cross-validation correlation coefficient R² (cv) and RMSECV were, respectively 0.9681 / 0.647 (mdeg); 0.9633 / 0.945 (mdeg); and 0.9018 / 1.12 (mdeg) (Table 1). According to the parameters presented in the literature, these results indicate an efficient calibration and prediction model for HRP secondary structure analysis. Lin et al. [24] evaluated the protein content in barley grains using NIR associated with multivariate calibration. The PLS calibration of the study showed values of the correlation coefficient (R²) of 0.9783 and RMSEP of 26.18. The authors concluded that the model showed a good correlation between the real values and predicted values. Ferreira et al. [25] evaluated, among other parameters, the protein content in soybean. The R² was 0.88, the RMSEP and RMSECV were 1.32 and 1.76, respectively. According to the authors, the results presented suggest that NIR is a technique that has predictive abilities. Wang et al. [26] determined the protein content of peanuts using NIR. The authors obtained a correlation coefficient (R²) of 0.99 and RMSEP of 6.53. They affirm that the NIR associated with multivariate calibration has a significant potential to determine the protein content in peanuts. Fig. 3 shows the comparison of the raw ellipticity measurements using the circular dichroism spectroscopic technique (CD) as a parameter for real values and the spectra obtained by the NIR as a parameter for calculated values to calibration. The data presented in the graph shows congruence between the values of the two techniques used. Thus, it is suggested that NIR may be a promising tool for analysis
3.2.2. Fluorescence versus NIR: partial least squares regression – PLS Fluorescence spectroscopy (FL) values were correlated to the NIR spectra in the same experimental conditions, for the construction of a robust model that allows the validation of the NIR as an alternative technique for analysis of the HRP tertiary structure. The RMSECV parameter was used to obtain the optimal number of latent variables for the model used. The optimal number of latent variables in the model was 4 (Table 2). The values of the calibration correlation coefficient R² (cal) and RMSEC; of validation R² (val) and RMSEP; as well as the values of the cross-validation correlation coefficient R² (cv) and RMSECV were, respectively 0.9999 / 1.95 (a.u.); 0.9999 / 2.09 (a.u.); and 0.9999 / 2.19 (a.u.) (Table 2). According to the parameters presented in the literature, these results indicate an efficient calibration and prediction model for HRP secondary structure analysis. Escuredo et al. [7] investigated the amino acid composition in quinoa using fiber-optic NIR probe. The R2 value for the presence of tryptophan (trp) in the sample was 0.92. The RMSEC, RMSEP and RMSECV were, respectively 0.07, 0.06 and 0.16. The authors conclude that NIR has an efficient predictive capacity for the detection of tryptophan. Zhang et al. [27] analyzed the prediction of amino acid composition in brown rice using NIR. Among other amino acids, two fluorophores were investigated, tyrosine (tyr) and phenylalanine (Phe). The values of R², RMSEC, RMSEP and RMSECV for tyrosine were, respectively 0.836, 0.025, 0.033, and 0.028 and for phenylalanine the values were, respectively 0.967, 0.013, 0.016 and 0.014. According to the authors, the results suggest that NIR is an efficient tool for the determination of protein content in brown rice. Fig. 4 shows the comparison of fluorescence intensity measurements using fluorescence spectroscopy (FL) as a parameter for real values and the spectra obtained by NIR as a parameter for calculated values to calibration. The data presented in the graph shows congruence between the values of the two techniques used. The results demonstrated the ability of NIR to obtain linear responses to trp modifications in HRP, hence its efficiency in capturing changes in the tertiary structure of the enzyme. 4. Conclusion Near infrared spectroscopy (NIR) associated with chemometrics is an efficient technique for analysis of secondary and tertiary structure of HRP. The results obtained using the NIR probe showed the ability of the equipment to capture variations in the specific bands for each structure of the enzyme. One of the relevance of the study was to construct a chemometric model that allows the real-time monitoring of the variations of the secondary and tertiary structures of the enzyme of the HRP solution once the probe can be introduced into the reaction medium (on line). Further studies may be performed by analyzing the structural behavior of the enzyme in alternative media, such as pressurized fluids for example using near infrared spectroscopy (NIR). Futhermore, the robustness of NIRs analyses can be evaluated with studies involving other proteins and enzymes. Declaration of Competing Interest
Fig. 3. Comparison of raw ellipticity measurements correlating Circular dichroism (CD) (actual values) and Near infrared (NIR) (calculated values) at specifics temperatures (30 °C, 40 °C, 45 °C, 50 °C and 60 °C).
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to 4
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Table 2 Statistical descriptions of the Fluorescence (FL) versus Near infrared (NIR) calibration for HRP tertiary structure changes. Sample HRP 0.2 mg/mL
Number of latent variables 4
Calibration RMSEC (a.u.) 1.95
Validation 2
R 0.9999
[9]
[10]
[11]
[12]
[13] [14]
Fig. 4. Comparison of fluorescence intensity measurements correlating Fluorescence (FL) (real values) and Near infrared (NIR) (calculated values) at specifics temperatures (30 °C, 40 °C, 45 °C, 50 °C and 60 °C).
[15] [16]
[17]
influence the work reported in this paper.
[18]
Acknowledgements The authors are grateful for the financial support from the Brazilian research funding agencies CAPES,CNPq and FAPITEC/SE.
[19] [20]
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5
RMSEP (a.u.) 2.09
Cross-validation 2
R 0.9999
RMSECV (a.u.) 2.19
R2 0.9999
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