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Analysis of phenformin hydrochloride and atypical antipsychotics in plasma using surface-enhanced Raman scattering
Vibrational Spectroscopy 101 (2019) 46–51
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Vibrational Spectroscopy journal homepage: www.elsevier.com/locate/vibspec
Analysis of phenformin hydrochloride and atypical antipsychotics in plasma using surface-enhanced Raman scattering
T
Jianxiang Longa, Jin Chengb, Xiaoyan Huanga, Yan Zhangc, Wenfang Liua, Chuanpin Chena,
⁎
a
Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, PR China School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, PR China c Hunan Xiangtan Institute for Food and Drug Control, Xiangtan, Hunan 411100, PR China b
ARTICLE INFO
ABSTRACT
Keywords: SERS Phenformin hydrochloride Atypical antipsychotics Plasma Colloidal silver
The increasing number of deaths caused by drug poisoning indicates that a rapid and accurate method to identify the type of drugs is critically needed to provide a real-time and effective treatment for poisoned patients. In this report, a surface-enhanced Raman scattering (SERS) analysis method for the detection of phenformin hydrochloride and atypical antipsychotics in plasma was successfully developed. Colloidal silver, prepared by a redox reaction of hydroxylamine and silver nitrate, was used as a SERS substrate. The pH condition and the sample incubation time for each drug were also explored to improve SERS enhancement factor. Based on these, phenformin hydrochloride and atypical antipsychotics (quetiapine fumarate, risperidone, olanzapine and clozapine) in plasma at concentration of 10−6 M were detected successfully. Thus, we provided a potentially method for rapid diagnosis of acute drugs poisoning.
1. Introduction Death caused by drug poisoning is a growing problem in the United States. In 2015, more than 16,300 people died from drug poisoning – about 2.6 times of 6100 in 1999 [1]. Phenformin hydrochloride, a biguanide antidiabetic agent, has a relatively large side effect of lactic acidosis and the mortality rate resulted from phenformin-induced lactic acidosis is up to 50% [2]. Atypical antipsychotics are the first-line medicines for treatment of psychosis because of their efficacy in easing both positive and negative symptoms of schizophrenia and their low risk of extra pyramidal symptoms. However, the atypical antipsychotics show their own form of adverse effects and improper use or excessive dose of these antipsychotics would easily result in poisoning or even death [3–6]. Though we all know that it is urgent for the poisoning patients to be treated, the real-time and accurate identification for the type of drugs is difficult. Firstly, the concentration of drugs to be analyzed in biological sample is as low as micromolar to nanomolar level. Secondly, the composition of biological sample is complex. In addition to the target analyte, they also contain a large number of endogenous substances. Moreover, metabolites or degradation products often interfere with the detection of target analyte [7–10]. Thus far, the commonly used methods for the detection of the above drugs in biological fluids, such as high-performance liquid chromatography, gas chromatography, gas chromatography–mass spectrometry ⁎
and liquid chromatography–mass spectrometry (LC–MS) have high sensitivity and accuracy. Especially for LC–MS which is most widely used because of its high separation capacity of LC and its high specificity and sensitivity of MS. However, almost all equipments for these methods are bulky and expensive, and the analysis usually demands sophisticated and time-consuming sample preparation, as well as personnel skills in chromatographic techniques [11–15]. Same with LC–MS, Raman spectroscopy is possible to obtain abundant ‘fingerprint’ information which can provide high information content of target molecule. In addition, Raman spectroscopy has its unique advantages [9,16,17]. It takes only a few milliseconds to dozens of seconds to detect drugs in vivo with simple disposal, which can reduce the sample pretreatment time and save the analysis cost. It is also able to analyze target molecule in organic or aqueous solvents. However, the widely use of Raman scattering technique in chemical and biomolecular detection has been restricted because of its low sensitivity. Differing from conventional Raman spectroscopy, surface-enhanced Raman scattering (SERS) can obtain enhancements of 106, and with resonance, the enhancement factor can even be increased to 1015 [18]. Most importantly, with portable/hand-held Raman spectrometer, a rapid in-situ analysis of target samples could be achieved to accurately diagnose the types of poisoning drugs in a few minutes, thus providing an efficient treatment for patients. There is an increased interest in pharmaceutical analysis by SERS in
Corresponding author. E-mail address: [email protected] (C. Chen).
https://doi.org/10.1016/j.vibspec.2019.01.003 Received 2 September 2018; Received in revised form 2 January 2019; Accepted 28 January 2019 Available online 29 January 2019 0924-2031/ © 2019 Elsevier B.V. All rights reserved.
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recent years. Researchers have acquired SERS spectrum of some drugs of abuse or illicit such as diazepam, methadone, amphetamine and cocaine in saliva [19,20]. Choi et al. has realized in-line detection of urea in artificial urine by incorporating a SERS sensor consisted of an array of gold nanoparticles (GNPs) into flexible tubing [21]. After separating and purifying samples using HPLC, Georg Brehm et al. have achieved a qualitative detection of dihydrocodeine in urine and blood with enhanced microwave-treated gold-polystyrene beads substrate [22]. This kind of ordered nanoparticle array can give rise to SERS enhancement factor more than 1010 with a good reproducibility, but it is difficult to obtain sufficient substrate for practical analysis because of a complicated preparation process and high requirement of equipments. Instead, colloidal silver is the most widely used substrate due to its simple preparation and its high enhancement for SERS [23–25]. In spite of this, the unoptimized colloidal silver has some limitations in selectivity and sensitivity (only 10−4–10−5 M) [26–28]. Moreover, some of the residual reactants in the colloidal silver may cause interference in target analytes detection. All these factors make it difficult to be directly used for the analysis of biological samples with complex components and low drug content. Therefore, an optimized process for colloidal silver is essential to obtain high sensitivity and selectivity. In this study, an effective SERS method was developed to measure phenformin hydrochloride and atypical antipsychotics in plasma. To effectively improve SERS enhancement factor, the influence of pH condition on the adsorption between silver nanoparticle and analyte was explored. Meanwhile, the effect of incubation time on the aggregation of colloidal silver was studied. Based on the optimized test conditions, phenformin hydrochloride and atypical antipsychotics in plasma with a simple pretreatment were detected by SERS.
2.4. Preparation of samples for exploring the effect of pH condition and incubation time on SERS enhancement To explore the pH condition of phenformin hydrochloride, a series of concentrations of NaOH and H2SO4 (1 × 10−1, 1 × 10−2, 1 × 10−3, 1 × 10−4, 1 × 10−5 and 1 × 10−6 M) were prepared as PH adjusting agent. The colloidal silver, PH adjusting agent and phenformin hydrochloride solution (5 × 10−5 M) were mixed at a volume ratio of 8:1:1 and incubated for 4 h for full adsorption of target analyte onto the nanoparticles. After then, 10 μL of the sample was directly laid on the glass slide for detection. In the same way, the optimal pH values of clozapine, olanzapine, risperidone and quetiapine were obtained. For the exploration of sample incubation time, two different concentrations of phenformin hydrochloride samples, flocculated with a concentration of 1 × 10−4 M and unflocculated with a concentration of 5 × 10−7 M were prepared. After adding a fixed volume of NaOH solution to adjust the pH value of colloidal silver to 12, colloidal silver and phenformin hydrochloride solution were mixed at a volume ratio of 9:1. Taking 1 mL of the sample into the sample cell and incubating it for 0, 10, 20, 30, 40, 50 min and 1, 1.5, 2, 3, 4, 5, 6, 7, 8 h before detection. 2.5. Preparation of samples for SERS detection Standard stock solutions of phenformin hydrochloride and atypical antipsychotics (clozapine, risperidone, olanzapine and quetiapine) were separately prepared in methanol. A series of different concentrations of working solutions were prepared by appropriate dilution in methanol. The working solutions (100 μL) of each concentration were mixed with methanol (100 μL) in a glass tube and evaporated to remove methanol by using an evaporator at 45 °C under a stream of nitrogen, then added 1 mL blank plasma and vortex mixed for 30 s. A series concentrations of 1 × 10−3, 1 × 10−4, 1 × 10−5 and 1 × 10−6 mol/L standard plasma samples were obtained. The proteins in the standard plasma samples were settled with 6% perchloric acid solution. For example, vortex mixing the standard plasma samples (1 mL) with 6% perchloric acid solution (0.6 mL) for 3 min and then putting it at room temperature for 10 min. Finally, centrifuging the samples at 12,000 r/min for 10 min and the spiked plasma samples (the supernatant) were obtained. For all samples, including spiked plasma samples, 1 × 10−2 standard samples and blank plasma, the volume ratio of colloidal silver and analyte solution was 9:1. A fixed amount of NaOH or H2SO4 solution was added to adjust the pH value. Similarly, the samples were incubated for 4 h and then 3 mL of the samples were taken into the sample cells for detection.
2. Experimental 2.1. Chemicals and materials All of the reagents used were analytical-grade chemicals. Phenformin hydrochloride, quetiapine fumarate, risperidone, olanzapine and clozapine reference substances were all purchased from the National Institute for the Control of Pharmaceutical and Biological Products (Beijing, China). 70% perchloric acid was purchased as protein precipitant with a concentration of 6% (w/w). Blank plasma was obtained from healthy New Zealand rabbit. All of the chemical drug solutions were prepared by deionized water.
3. Results & discussion
2.2. Apparatus
To investigate the influence of pH value on SERS signal intensity, SERS spectra of phenformin hydrochloride (5 × 10−5 M) under different pH condition were obtained. In this study, the pH value was controlled by adding a fixed volume of NaOH or H2SO4 with different concentration (from 1 × 10−1 M to 1 × 10−6 M). As is shown in Fig. 1, employing characteristic peak at 1002 cm−1 as inspection standard, phenformin hydrochloride could not be detected under acidic condition (spectra g–l) even at a concentration as high as 5 × 10−5 M. But under alkaline condition (spectra a–f), the signal intensity of SERS was enhanced with the increase of NaOH concentration, and reached the maximum value at pH = 12. In fact, the pH condition of the system could affect the dissociation state of the target analyte and then changed its adsorption site and its stereotactic orientation in silver nanoparticles, thus affecting the SERS enhancement effect of colloidal silver [30,31]. The pKa value of phenformin hydrochloride is about 12.15. Under acidic conditions, phenformin hydrochloride was protonated to become positively charged and could also adsorb on AgNPs by electrostatic interaction, thus resulting the nanoparticles to aggregate. At the same time, however, the polarity of phenformin hydrochloride was enhanced. According to the Raman mechanism, non-polar
A portable Raman spectrometer (532 nm, i-Raman plus, BWTEK, USA) with a data collecting and analyzing system (LabSpec5) was used for the detection. The SERS spectra were recorded from 300 to 2000 cm−1 with a spectral resolution of 5 cm−1, and the signal acquisition time was 20 s. A high-speed refrigerated centrifuge (TGL-16, Yingtai Instrumental Co. Ltd) was employed to centrifuge samples. 2.3. Preparation of silver colloidal Colloidal silver was prepared by the redox reaction of hydroxylamine and silver nitrate [29]. First, 1 × 10−3 M silver nitrate solution, 0.1 M NaOH solution and 6 × 10−2 M hydroxylamine solution were prepared, respectively. The hydroxylamine (5 mL, 6 × 10−2 M) whose pH was adjusted to 5 by adding NaOH solution (4.5 mL, 0.1 M) was used as reducing agent. Quickly, the prepared reducing agent was added into silver nitrate solution (90 mL, 1.11 × 10−3 M) with a rapid stir. Keep stirring for 40 min until the solution turned dark yellowgreen. 47
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Fig. 3. The absolute intensity of characteristic peak (1002 cm−1) – incubation time curve of phenformin hydrochloride. The concentrations of aggregated sample and un-aggregated sample were 1 × 10−4 M and 5 × 10−7 M, respectively.
Fig. 1. SERS spectra of phenformin hydrochloride (5 × 10−5 M) under different pH conditions. Spectra (a–f) represent mixing NaOH solution at concentration of 1 × 10−1, 1 × 10−2, 1 × 10−3, 1 × 10−4, 1 × 10−5, 1 × 10−6 M; Spectra (g–l) represent mixing H2SO4 solution at concentration of 1 × 10−6, 1 × 10−5, 1 × 10−4, 1 × 10−3, 1 × 10−2, 1 × 10−1 M, respectively.
molecules adsorbed on the surface of silver nanoparticles was still so low that little change of the negative charge on the silver surface was caused. Thus flocculation couldn’t occur. This was demonstrated by Fig. 3. The maximum signal intensity of low concentration samples was only 1230 even after incubation for 8 h, which was far less than the high concentration ones whose SERS intensity was up to 30,631 after incubation for only 2 h. The SERS intensity of the high concentration sample decreased dramatically during the first 10 min, and then kept in a relatively low level within 10–60 min (Fig. 3). It was because the adsorption of the analyte and NPs has not reached equilibrium during this time period. At the beginning of adding high concentration samples, the aggregation and precipitation of colloidal silver were so fast that the nanoparticles at the focusing point of the microscope system kept moving and then the ‘hot spots’ estranged from the focusing point which brought about the decrease of SERS signal [35]. Aggregated nanoparticles continued precipitating to the bottom of the sample cell with the increasing incubation time until reach a stable status. A relatively stable aggregation, rich ‘hot spots’ and high concentration of nanoparticles make it perfect for SERS [36]. So from 60 min on, the signal was significantly increased and keeping at a high-level steady status after incubating for 90 min. In this case, in order to compare different concentration sample’s SERS signal in a consistent experimental condition, the 4-h incubation time was chosen for the subsequent experiments. In order to determine the detection sensitivity of the analysis after optimization, phenformin hydrochlorides standard solutions at concentrations of 5 × 10−7 M and 1 × 10−7 M were detected respectively. As is shown in Fig. 4, the characteristic peak at 1002 cm−1 of 5 × 10−7 M phenformin hydrochlorides was found, while measurements at 1 × 10−7 M produced sporadic results. This was demonstrated
molecules have a stronger Raman effect than polar molecules [32]. Therefore, the signal intensity of SERS under acidic conditions was too low to be detected. While under alkaline conditions, phenformin hydrochloride was deprotonated to be neutral molecules. With the increasing of pH value, more neutral molecules were generated and then adsorbed onto metal surface [33]. With that, nanoparticles aggregated rapidly. The inter-particle space then significantly decreased and more ‘hot sites’, a critical factor for enhancement, were generated in this way [34]. It follows that by adjusting pH value, the sensitivity and selectivity of SERS could be enhanced since the most suitable pH value of different chemicals are closely related to their chemical structures. After mixing the colloidal silver and the target analyte, the adsorption and flocculation process of them would increase with the incubation time. The phenformin hydrochloride for both high concentration (1 × 10−4 M) and low concentration (5 × 10−7 M) has been carried out to explore the impact of incubation time on SERS signal intensity. As is shown in Fig. 2, with the addition of high concentration samples (1 × 10−4 M), silver nanoparticles started to flocculate together, and further grew into large clusters with the increase of incubation time until completely flocculating into blocks. However, after the mixture of low concentration samples (5 × 10−7 M), nanoparticles kept as colloidal state within 24 h and no any clusters could be seen under microscope. It was because that the flocculation process of the colloidal silver could not be activated until the concentration of the target analyte was reached to a certain degree [27]. Although incubation for 24 h, for low concentration samples, the amount of analyte
Fig. 2. The images of self-aggregated samples (1 × 10−4) with different incubation time under microscope. 48
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Fig. 4. SERS spectra of phenformin hydrochloride at concentrations of 5 × 10−7 and 1 × 10−7 M.
accurately detect phenformin hydrochloride in plasma even at a low concentration of 10-6 M. To further employ the method for the detection of atypical antipsychotics in plasma under their most suitable conditions, the Raman responses of the four atypical antipsychotics, clozapine, risperidone, olanzapine and quetiapine in plasma were investigated. The spectra of clozapine under different pH conditions could be obtained according to the phenformin hydrochloride’ s research. As is shown in Fig. 6, its optimal pH was 6, also the standard spectra of risperidone, olanzapine and quetiapine under different pH condition were available (the results were unshown) and their optimal pH were 4, 8 and 11, respectively. Consistent with the adsorption theory of phenformin hydrochloride, all the optimal pH value of these drugs were near their pKa. The pKa/ pHoptimal of hydrochloride, clozapine, risperidone, olanzapine and quetiapine was 12.15/12, 7.5/6, 3.11/4, 7.24/8 and 10.7/11, respectively. Therefore, we could roughly infer the optimal pH of the target molecules according to their pKa when detected by SERS. Here, we detected several different concentration samples including 1 × 10−2 M standard sample (Fig. 7, spectra a), which was used as standard control group, spiked plasma samples at concentrations of 1 × 10−3, 1 × 10−4, 1 × 10−5, 1 × 10−6 M (Fig. 7, spectra b–e) and blank plasma (Fig. 7, spectra f). Same with phenformin hydrochloride, atypical antipsychotics in plasma were capable to be well detected even at a low concentration of 1 × 10-6 M. According to the standard control group (Fig. 7(A–D), spectra a), characteristic peaks of four drugs are as follows: 334, 380, 525, 587, 949, 1041, 1085, 1178, 1227 and 1589 cm−1 of clozapine; 344, 421, 674, 806, 858, 915, 1044, 1174, 1307 and 1539 cm−1 of olanzapine; 428, 611, 761, 954, 1018, 1175, 1274 and 1350 cm-1 of risperidone; 320, 544, 616, 686, 1031, 1158 and 1558 cm−1 of quetiapine. After a treatment with protein precipitation, there were few peaks of 851, 1174 and 1585 cm−1 in blank plasma samples. These peaks may interfere with the characteristic peaks of clozapine at 1178 and 1585 cm-1, olanzapine at 1174 and 1539 cm-1, risperidone at 1175 cm−1 and quetiapine at 1158 and 1558 cm-1 for low concentration samples. For example, the absorption peak of olanzapine at 1539 cm−1 shifted to 1585 cm−1 when its concentration was 1 × 10−6 M. However, except for these absorption peaks, the remaining other characteristic peaks, such as 334, 380, 525, 587, 1085 and 1227 of clozapine; 344, 421, 674, 858, 1307 of olanzapine; 428, 761, 954, 1018, 1350 of risperidone; 320, 544, 616, 686, 1031 of quetiapine in Fig. 7(A–D), spectra b–e (concentration from 1 × 10−3 to 1 × 10−6 M), could be found and didn’t interfered by the blank plasma. The SERS spectra of clozapine (Fig. 7(A)) and olanzapine (Fig. 7(B)) were completely different though their structures are similar. It is because that the olanzapine structure contains a thiophene ring in which the S atom can bond with Ag to form an S-Ag bond, which makes a significant change in its adsorption and spatial orientation. The above
by our team in former research [36], when the concentration of the samples was 5 × 10−7 M or lower, the amount of analyte molecules was so limited that silver nanoparticles could not adsorb enough analyte molecules. Thus the flocculation couldn’t occur and the SERS signal dropped sharply so that it could hardly be detected. According to the instructions, the maximum dose of phenformin hydrochloride should not exceed 75 mg/d. The lowest toxic levels of clozapine, olanzapine, risperidone and quetiapine were 2.4 × 10−6, 0.6 × 10−6, 0.2 × 10−6 and 4.7 × 10−6 M, respectively [37]. However, the actual concentrations of the above drugs in suicide patients would be much higher (ten times or more) [38]. Therefore, in the following experiments, we chose 1 × 10−6 M as the lowest detection concentration of spiked plasma samples. To investigate the optimum detection parameters for the analysis of target molecules in plasma samples, the phenformin hydrochlorides at 1 × 10−2 M standard sample (Fig. 5, spectrum a), and at 1 × 10−3, 1 × 10−4, 1 × 10−5 and 1 × 10−6 M spiked plasma samples were detected (Fig. 5, spectra b–e). According to the standard control group (Fig. 5, spectrum a), we can see that all the characteristic peaks at 620, 1002, 1029 and 1203 cm−1 of phenformin hydrochlorides spiked plasma samples could be found. After a simple protein precipitation pretreatment, there were few peaks in the blank plasma sample (Fig. 5, spectrum f) and these peaks were too low to interfere with the detection of phenformin hydrochloride. Especially at the characteristic peak of 1002 cm−1, the sample groups have distinct absorption peak, while the blank plasma group has no interference peak. Therefore, we could
Fig. 5. SERS spectra of phenformin hydrochloride. Spectra (a–f) represent 1 × 10−2 M standard sample, 1 × 10−3, 1 × 10−4, 1 × 10−5, 1 × 10−6 M spiked plasma samples and blank plasma, respectively. 49
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Fig. 7. SERS spectra of atypical antipsychotics. (A)–(D) represents clozapine, olanzapine, risperidone and quetiapine, respectively. Spectra (a–f) represent 1 × 10−2 M standard sample, 1 × 10−3, 1 × 10−4, 1 × 10−5, 1 × 10−6 M spiked plasma samples and blank plasma, respectively.
results indicated that the optimum SERS method was capable to achieve the analysis of atypical antipsychotics in plasma.
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4. Conclusion A SERS method was successfully developed to detect phenformin hydrochloride and atypical antipsychotics in plasma with a low concentration of 10−6 M after exploring the effects of pH condition and sample incubation time on SERS signal. It was found that both of them played a critical role in the adsorption of analyte on nanoparticle and the aggregation of colloidal silver, thus promoting the generation of ‘hot spots’ and producing high enhancement factor. Therefore, this research implied a possible way to improve analytical performance of SERS-based technique and hopefully provide a real-time and effective analysis method for the diagnosis of acute drug poisoning. Obviously, the SERS-based technique with further improvement is possibly a promising analytical tool for ultrasensitive detection of one or more target analytes simultaneously. And coupled with portable Raman scattering equipment, an economical and efficient technique for on-site detection could be achieved and easily introduced into daily detection. Competing financial interest The authors declare no competing financial interest. Acknowledgements This work was supported by the National Natural Science Foundation of China (81202378 and 81311140268) and the Fundamental Research Funds for the Central Universities of Central South University, China (1053320170603). 50
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Vibrational Spectroscopy journal homepage: www.elsevier.com/locate/vibspec
Analysis of phenformin hydrochloride and atypical antipsychotics in plasma using surface-enhanced Raman scattering
T
Jianxiang Longa, Jin Chengb, Xiaoyan Huanga, Yan Zhangc, Wenfang Liua, Chuanpin Chena,
⁎
a
Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, PR China School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, PR China c Hunan Xiangtan Institute for Food and Drug Control, Xiangtan, Hunan 411100, PR China b
ARTICLE INFO
ABSTRACT
Keywords: SERS Phenformin hydrochloride Atypical antipsychotics Plasma Colloidal silver
The increasing number of deaths caused by drug poisoning indicates that a rapid and accurate method to identify the type of drugs is critically needed to provide a real-time and effective treatment for poisoned patients. In this report, a surface-enhanced Raman scattering (SERS) analysis method for the detection of phenformin hydrochloride and atypical antipsychotics in plasma was successfully developed. Colloidal silver, prepared by a redox reaction of hydroxylamine and silver nitrate, was used as a SERS substrate. The pH condition and the sample incubation time for each drug were also explored to improve SERS enhancement factor. Based on these, phenformin hydrochloride and atypical antipsychotics (quetiapine fumarate, risperidone, olanzapine and clozapine) in plasma at concentration of 10−6 M were detected successfully. Thus, we provided a potentially method for rapid diagnosis of acute drugs poisoning.
1. Introduction Death caused by drug poisoning is a growing problem in the United States. In 2015, more than 16,300 people died from drug poisoning – about 2.6 times of 6100 in 1999 [1]. Phenformin hydrochloride, a biguanide antidiabetic agent, has a relatively large side effect of lactic acidosis and the mortality rate resulted from phenformin-induced lactic acidosis is up to 50% [2]. Atypical antipsychotics are the first-line medicines for treatment of psychosis because of their efficacy in easing both positive and negative symptoms of schizophrenia and their low risk of extra pyramidal symptoms. However, the atypical antipsychotics show their own form of adverse effects and improper use or excessive dose of these antipsychotics would easily result in poisoning or even death [3–6]. Though we all know that it is urgent for the poisoning patients to be treated, the real-time and accurate identification for the type of drugs is difficult. Firstly, the concentration of drugs to be analyzed in biological sample is as low as micromolar to nanomolar level. Secondly, the composition of biological sample is complex. In addition to the target analyte, they also contain a large number of endogenous substances. Moreover, metabolites or degradation products often interfere with the detection of target analyte [7–10]. Thus far, the commonly used methods for the detection of the above drugs in biological fluids, such as high-performance liquid chromatography, gas chromatography, gas chromatography–mass spectrometry ⁎
and liquid chromatography–mass spectrometry (LC–MS) have high sensitivity and accuracy. Especially for LC–MS which is most widely used because of its high separation capacity of LC and its high specificity and sensitivity of MS. However, almost all equipments for these methods are bulky and expensive, and the analysis usually demands sophisticated and time-consuming sample preparation, as well as personnel skills in chromatographic techniques [11–15]. Same with LC–MS, Raman spectroscopy is possible to obtain abundant ‘fingerprint’ information which can provide high information content of target molecule. In addition, Raman spectroscopy has its unique advantages [9,16,17]. It takes only a few milliseconds to dozens of seconds to detect drugs in vivo with simple disposal, which can reduce the sample pretreatment time and save the analysis cost. It is also able to analyze target molecule in organic or aqueous solvents. However, the widely use of Raman scattering technique in chemical and biomolecular detection has been restricted because of its low sensitivity. Differing from conventional Raman spectroscopy, surface-enhanced Raman scattering (SERS) can obtain enhancements of 106, and with resonance, the enhancement factor can even be increased to 1015 [18]. Most importantly, with portable/hand-held Raman spectrometer, a rapid in-situ analysis of target samples could be achieved to accurately diagnose the types of poisoning drugs in a few minutes, thus providing an efficient treatment for patients. There is an increased interest in pharmaceutical analysis by SERS in
Corresponding author. E-mail address: [email protected] (C. Chen).
https://doi.org/10.1016/j.vibspec.2019.01.003 Received 2 September 2018; Received in revised form 2 January 2019; Accepted 28 January 2019 Available online 29 January 2019 0924-2031/ © 2019 Elsevier B.V. All rights reserved.
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recent years. Researchers have acquired SERS spectrum of some drugs of abuse or illicit such as diazepam, methadone, amphetamine and cocaine in saliva [19,20]. Choi et al. has realized in-line detection of urea in artificial urine by incorporating a SERS sensor consisted of an array of gold nanoparticles (GNPs) into flexible tubing [21]. After separating and purifying samples using HPLC, Georg Brehm et al. have achieved a qualitative detection of dihydrocodeine in urine and blood with enhanced microwave-treated gold-polystyrene beads substrate [22]. This kind of ordered nanoparticle array can give rise to SERS enhancement factor more than 1010 with a good reproducibility, but it is difficult to obtain sufficient substrate for practical analysis because of a complicated preparation process and high requirement of equipments. Instead, colloidal silver is the most widely used substrate due to its simple preparation and its high enhancement for SERS [23–25]. In spite of this, the unoptimized colloidal silver has some limitations in selectivity and sensitivity (only 10−4–10−5 M) [26–28]. Moreover, some of the residual reactants in the colloidal silver may cause interference in target analytes detection. All these factors make it difficult to be directly used for the analysis of biological samples with complex components and low drug content. Therefore, an optimized process for colloidal silver is essential to obtain high sensitivity and selectivity. In this study, an effective SERS method was developed to measure phenformin hydrochloride and atypical antipsychotics in plasma. To effectively improve SERS enhancement factor, the influence of pH condition on the adsorption between silver nanoparticle and analyte was explored. Meanwhile, the effect of incubation time on the aggregation of colloidal silver was studied. Based on the optimized test conditions, phenformin hydrochloride and atypical antipsychotics in plasma with a simple pretreatment were detected by SERS.
2.4. Preparation of samples for exploring the effect of pH condition and incubation time on SERS enhancement To explore the pH condition of phenformin hydrochloride, a series of concentrations of NaOH and H2SO4 (1 × 10−1, 1 × 10−2, 1 × 10−3, 1 × 10−4, 1 × 10−5 and 1 × 10−6 M) were prepared as PH adjusting agent. The colloidal silver, PH adjusting agent and phenformin hydrochloride solution (5 × 10−5 M) were mixed at a volume ratio of 8:1:1 and incubated for 4 h for full adsorption of target analyte onto the nanoparticles. After then, 10 μL of the sample was directly laid on the glass slide for detection. In the same way, the optimal pH values of clozapine, olanzapine, risperidone and quetiapine were obtained. For the exploration of sample incubation time, two different concentrations of phenformin hydrochloride samples, flocculated with a concentration of 1 × 10−4 M and unflocculated with a concentration of 5 × 10−7 M were prepared. After adding a fixed volume of NaOH solution to adjust the pH value of colloidal silver to 12, colloidal silver and phenformin hydrochloride solution were mixed at a volume ratio of 9:1. Taking 1 mL of the sample into the sample cell and incubating it for 0, 10, 20, 30, 40, 50 min and 1, 1.5, 2, 3, 4, 5, 6, 7, 8 h before detection. 2.5. Preparation of samples for SERS detection Standard stock solutions of phenformin hydrochloride and atypical antipsychotics (clozapine, risperidone, olanzapine and quetiapine) were separately prepared in methanol. A series of different concentrations of working solutions were prepared by appropriate dilution in methanol. The working solutions (100 μL) of each concentration were mixed with methanol (100 μL) in a glass tube and evaporated to remove methanol by using an evaporator at 45 °C under a stream of nitrogen, then added 1 mL blank plasma and vortex mixed for 30 s. A series concentrations of 1 × 10−3, 1 × 10−4, 1 × 10−5 and 1 × 10−6 mol/L standard plasma samples were obtained. The proteins in the standard plasma samples were settled with 6% perchloric acid solution. For example, vortex mixing the standard plasma samples (1 mL) with 6% perchloric acid solution (0.6 mL) for 3 min and then putting it at room temperature for 10 min. Finally, centrifuging the samples at 12,000 r/min for 10 min and the spiked plasma samples (the supernatant) were obtained. For all samples, including spiked plasma samples, 1 × 10−2 standard samples and blank plasma, the volume ratio of colloidal silver and analyte solution was 9:1. A fixed amount of NaOH or H2SO4 solution was added to adjust the pH value. Similarly, the samples were incubated for 4 h and then 3 mL of the samples were taken into the sample cells for detection.
2. Experimental 2.1. Chemicals and materials All of the reagents used were analytical-grade chemicals. Phenformin hydrochloride, quetiapine fumarate, risperidone, olanzapine and clozapine reference substances were all purchased from the National Institute for the Control of Pharmaceutical and Biological Products (Beijing, China). 70% perchloric acid was purchased as protein precipitant with a concentration of 6% (w/w). Blank plasma was obtained from healthy New Zealand rabbit. All of the chemical drug solutions were prepared by deionized water.
3. Results & discussion
2.2. Apparatus
To investigate the influence of pH value on SERS signal intensity, SERS spectra of phenformin hydrochloride (5 × 10−5 M) under different pH condition were obtained. In this study, the pH value was controlled by adding a fixed volume of NaOH or H2SO4 with different concentration (from 1 × 10−1 M to 1 × 10−6 M). As is shown in Fig. 1, employing characteristic peak at 1002 cm−1 as inspection standard, phenformin hydrochloride could not be detected under acidic condition (spectra g–l) even at a concentration as high as 5 × 10−5 M. But under alkaline condition (spectra a–f), the signal intensity of SERS was enhanced with the increase of NaOH concentration, and reached the maximum value at pH = 12. In fact, the pH condition of the system could affect the dissociation state of the target analyte and then changed its adsorption site and its stereotactic orientation in silver nanoparticles, thus affecting the SERS enhancement effect of colloidal silver [30,31]. The pKa value of phenformin hydrochloride is about 12.15. Under acidic conditions, phenformin hydrochloride was protonated to become positively charged and could also adsorb on AgNPs by electrostatic interaction, thus resulting the nanoparticles to aggregate. At the same time, however, the polarity of phenformin hydrochloride was enhanced. According to the Raman mechanism, non-polar
A portable Raman spectrometer (532 nm, i-Raman plus, BWTEK, USA) with a data collecting and analyzing system (LabSpec5) was used for the detection. The SERS spectra were recorded from 300 to 2000 cm−1 with a spectral resolution of 5 cm−1, and the signal acquisition time was 20 s. A high-speed refrigerated centrifuge (TGL-16, Yingtai Instrumental Co. Ltd) was employed to centrifuge samples. 2.3. Preparation of silver colloidal Colloidal silver was prepared by the redox reaction of hydroxylamine and silver nitrate [29]. First, 1 × 10−3 M silver nitrate solution, 0.1 M NaOH solution and 6 × 10−2 M hydroxylamine solution were prepared, respectively. The hydroxylamine (5 mL, 6 × 10−2 M) whose pH was adjusted to 5 by adding NaOH solution (4.5 mL, 0.1 M) was used as reducing agent. Quickly, the prepared reducing agent was added into silver nitrate solution (90 mL, 1.11 × 10−3 M) with a rapid stir. Keep stirring for 40 min until the solution turned dark yellowgreen. 47
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Fig. 3. The absolute intensity of characteristic peak (1002 cm−1) – incubation time curve of phenformin hydrochloride. The concentrations of aggregated sample and un-aggregated sample were 1 × 10−4 M and 5 × 10−7 M, respectively.
Fig. 1. SERS spectra of phenformin hydrochloride (5 × 10−5 M) under different pH conditions. Spectra (a–f) represent mixing NaOH solution at concentration of 1 × 10−1, 1 × 10−2, 1 × 10−3, 1 × 10−4, 1 × 10−5, 1 × 10−6 M; Spectra (g–l) represent mixing H2SO4 solution at concentration of 1 × 10−6, 1 × 10−5, 1 × 10−4, 1 × 10−3, 1 × 10−2, 1 × 10−1 M, respectively.
molecules adsorbed on the surface of silver nanoparticles was still so low that little change of the negative charge on the silver surface was caused. Thus flocculation couldn’t occur. This was demonstrated by Fig. 3. The maximum signal intensity of low concentration samples was only 1230 even after incubation for 8 h, which was far less than the high concentration ones whose SERS intensity was up to 30,631 after incubation for only 2 h. The SERS intensity of the high concentration sample decreased dramatically during the first 10 min, and then kept in a relatively low level within 10–60 min (Fig. 3). It was because the adsorption of the analyte and NPs has not reached equilibrium during this time period. At the beginning of adding high concentration samples, the aggregation and precipitation of colloidal silver were so fast that the nanoparticles at the focusing point of the microscope system kept moving and then the ‘hot spots’ estranged from the focusing point which brought about the decrease of SERS signal [35]. Aggregated nanoparticles continued precipitating to the bottom of the sample cell with the increasing incubation time until reach a stable status. A relatively stable aggregation, rich ‘hot spots’ and high concentration of nanoparticles make it perfect for SERS [36]. So from 60 min on, the signal was significantly increased and keeping at a high-level steady status after incubating for 90 min. In this case, in order to compare different concentration sample’s SERS signal in a consistent experimental condition, the 4-h incubation time was chosen for the subsequent experiments. In order to determine the detection sensitivity of the analysis after optimization, phenformin hydrochlorides standard solutions at concentrations of 5 × 10−7 M and 1 × 10−7 M were detected respectively. As is shown in Fig. 4, the characteristic peak at 1002 cm−1 of 5 × 10−7 M phenformin hydrochlorides was found, while measurements at 1 × 10−7 M produced sporadic results. This was demonstrated
molecules have a stronger Raman effect than polar molecules [32]. Therefore, the signal intensity of SERS under acidic conditions was too low to be detected. While under alkaline conditions, phenformin hydrochloride was deprotonated to be neutral molecules. With the increasing of pH value, more neutral molecules were generated and then adsorbed onto metal surface [33]. With that, nanoparticles aggregated rapidly. The inter-particle space then significantly decreased and more ‘hot sites’, a critical factor for enhancement, were generated in this way [34]. It follows that by adjusting pH value, the sensitivity and selectivity of SERS could be enhanced since the most suitable pH value of different chemicals are closely related to their chemical structures. After mixing the colloidal silver and the target analyte, the adsorption and flocculation process of them would increase with the incubation time. The phenformin hydrochloride for both high concentration (1 × 10−4 M) and low concentration (5 × 10−7 M) has been carried out to explore the impact of incubation time on SERS signal intensity. As is shown in Fig. 2, with the addition of high concentration samples (1 × 10−4 M), silver nanoparticles started to flocculate together, and further grew into large clusters with the increase of incubation time until completely flocculating into blocks. However, after the mixture of low concentration samples (5 × 10−7 M), nanoparticles kept as colloidal state within 24 h and no any clusters could be seen under microscope. It was because that the flocculation process of the colloidal silver could not be activated until the concentration of the target analyte was reached to a certain degree [27]. Although incubation for 24 h, for low concentration samples, the amount of analyte
Fig. 2. The images of self-aggregated samples (1 × 10−4) with different incubation time under microscope. 48
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Fig. 4. SERS spectra of phenformin hydrochloride at concentrations of 5 × 10−7 and 1 × 10−7 M.
accurately detect phenformin hydrochloride in plasma even at a low concentration of 10-6 M. To further employ the method for the detection of atypical antipsychotics in plasma under their most suitable conditions, the Raman responses of the four atypical antipsychotics, clozapine, risperidone, olanzapine and quetiapine in plasma were investigated. The spectra of clozapine under different pH conditions could be obtained according to the phenformin hydrochloride’ s research. As is shown in Fig. 6, its optimal pH was 6, also the standard spectra of risperidone, olanzapine and quetiapine under different pH condition were available (the results were unshown) and their optimal pH were 4, 8 and 11, respectively. Consistent with the adsorption theory of phenformin hydrochloride, all the optimal pH value of these drugs were near their pKa. The pKa/ pHoptimal of hydrochloride, clozapine, risperidone, olanzapine and quetiapine was 12.15/12, 7.5/6, 3.11/4, 7.24/8 and 10.7/11, respectively. Therefore, we could roughly infer the optimal pH of the target molecules according to their pKa when detected by SERS. Here, we detected several different concentration samples including 1 × 10−2 M standard sample (Fig. 7, spectra a), which was used as standard control group, spiked plasma samples at concentrations of 1 × 10−3, 1 × 10−4, 1 × 10−5, 1 × 10−6 M (Fig. 7, spectra b–e) and blank plasma (Fig. 7, spectra f). Same with phenformin hydrochloride, atypical antipsychotics in plasma were capable to be well detected even at a low concentration of 1 × 10-6 M. According to the standard control group (Fig. 7(A–D), spectra a), characteristic peaks of four drugs are as follows: 334, 380, 525, 587, 949, 1041, 1085, 1178, 1227 and 1589 cm−1 of clozapine; 344, 421, 674, 806, 858, 915, 1044, 1174, 1307 and 1539 cm−1 of olanzapine; 428, 611, 761, 954, 1018, 1175, 1274 and 1350 cm-1 of risperidone; 320, 544, 616, 686, 1031, 1158 and 1558 cm−1 of quetiapine. After a treatment with protein precipitation, there were few peaks of 851, 1174 and 1585 cm−1 in blank plasma samples. These peaks may interfere with the characteristic peaks of clozapine at 1178 and 1585 cm-1, olanzapine at 1174 and 1539 cm-1, risperidone at 1175 cm−1 and quetiapine at 1158 and 1558 cm-1 for low concentration samples. For example, the absorption peak of olanzapine at 1539 cm−1 shifted to 1585 cm−1 when its concentration was 1 × 10−6 M. However, except for these absorption peaks, the remaining other characteristic peaks, such as 334, 380, 525, 587, 1085 and 1227 of clozapine; 344, 421, 674, 858, 1307 of olanzapine; 428, 761, 954, 1018, 1350 of risperidone; 320, 544, 616, 686, 1031 of quetiapine in Fig. 7(A–D), spectra b–e (concentration from 1 × 10−3 to 1 × 10−6 M), could be found and didn’t interfered by the blank plasma. The SERS spectra of clozapine (Fig. 7(A)) and olanzapine (Fig. 7(B)) were completely different though their structures are similar. It is because that the olanzapine structure contains a thiophene ring in which the S atom can bond with Ag to form an S-Ag bond, which makes a significant change in its adsorption and spatial orientation. The above
by our team in former research [36], when the concentration of the samples was 5 × 10−7 M or lower, the amount of analyte molecules was so limited that silver nanoparticles could not adsorb enough analyte molecules. Thus the flocculation couldn’t occur and the SERS signal dropped sharply so that it could hardly be detected. According to the instructions, the maximum dose of phenformin hydrochloride should not exceed 75 mg/d. The lowest toxic levels of clozapine, olanzapine, risperidone and quetiapine were 2.4 × 10−6, 0.6 × 10−6, 0.2 × 10−6 and 4.7 × 10−6 M, respectively [37]. However, the actual concentrations of the above drugs in suicide patients would be much higher (ten times or more) [38]. Therefore, in the following experiments, we chose 1 × 10−6 M as the lowest detection concentration of spiked plasma samples. To investigate the optimum detection parameters for the analysis of target molecules in plasma samples, the phenformin hydrochlorides at 1 × 10−2 M standard sample (Fig. 5, spectrum a), and at 1 × 10−3, 1 × 10−4, 1 × 10−5 and 1 × 10−6 M spiked plasma samples were detected (Fig. 5, spectra b–e). According to the standard control group (Fig. 5, spectrum a), we can see that all the characteristic peaks at 620, 1002, 1029 and 1203 cm−1 of phenformin hydrochlorides spiked plasma samples could be found. After a simple protein precipitation pretreatment, there were few peaks in the blank plasma sample (Fig. 5, spectrum f) and these peaks were too low to interfere with the detection of phenformin hydrochloride. Especially at the characteristic peak of 1002 cm−1, the sample groups have distinct absorption peak, while the blank plasma group has no interference peak. Therefore, we could
Fig. 5. SERS spectra of phenformin hydrochloride. Spectra (a–f) represent 1 × 10−2 M standard sample, 1 × 10−3, 1 × 10−4, 1 × 10−5, 1 × 10−6 M spiked plasma samples and blank plasma, respectively. 49
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Fig. 7. SERS spectra of atypical antipsychotics. (A)–(D) represents clozapine, olanzapine, risperidone and quetiapine, respectively. Spectra (a–f) represent 1 × 10−2 M standard sample, 1 × 10−3, 1 × 10−4, 1 × 10−5, 1 × 10−6 M spiked plasma samples and blank plasma, respectively.
results indicated that the optimum SERS method was capable to achieve the analysis of atypical antipsychotics in plasma.
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4. Conclusion A SERS method was successfully developed to detect phenformin hydrochloride and atypical antipsychotics in plasma with a low concentration of 10−6 M after exploring the effects of pH condition and sample incubation time on SERS signal. It was found that both of them played a critical role in the adsorption of analyte on nanoparticle and the aggregation of colloidal silver, thus promoting the generation of ‘hot spots’ and producing high enhancement factor. Therefore, this research implied a possible way to improve analytical performance of SERS-based technique and hopefully provide a real-time and effective analysis method for the diagnosis of acute drug poisoning. Obviously, the SERS-based technique with further improvement is possibly a promising analytical tool for ultrasensitive detection of one or more target analytes simultaneously. And coupled with portable Raman scattering equipment, an economical and efficient technique for on-site detection could be achieved and easily introduced into daily detection. Competing financial interest The authors declare no competing financial interest. Acknowledgements This work was supported by the National Natural Science Foundation of China (81202378 and 81311140268) and the Fundamental Research Funds for the Central Universities of Central South University, China (1053320170603). 50
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