Elsevier

Microchemical Journal

Volume 158, November 2020, 105202
Microchemical Journal

Quantitative detection of nanomolar drug using surface-enhanced Raman scattering combined with internal standard method and two-step centrifugation method

https://doi.org/10.1016/j.microc.2020.105202Get rights and content

Highlights

  • A surface-enhanced Raman scattering quantitative detection method was developed.

  • Centrifugal treatment significantly increased the hot spot density.

  • The quantitative linear range was decreased to nanomolar level (R2 > 0.992).

  • The method exhibited high repeatability on a portable Raman spectrometer (RSD < 2%).

Abstract

Quantitative detection for nanomolar analytes is a challenge for surface-enhanced Raman scattering (SERS). In this report, a SERS method which combined with an internal standard method and a two-step centrifugation method was established for trace analysis of two drugs using a portable Raman spectrometer. Metformin hydrochloride was used as an internal standard for phenformin hydrochloride to increase the linearity of SERS detection, while, streptomycin sulfate was used for tigecycline. The two-step centrifugation method for sample preparation increased the density of hot spots and the concentration of analyte by accumulating silver nanoparticles. Therefore, the detection sensitivity was significantly improved. Furthermore, the repeatability of SERS signals was increased by adding 200 µL of the sample solution into a slit-type quartz cuvette to make the excitation light transmit through a heavy thickness sample solution. The RSDs of SERS signal intensity ratio of phenformin hydrochloride and tigecycline to internal standard were 1% and 1.6%, respectively. Finally, phenformin hydrochloride and tigecycline exhibited a good linearity in the range of 1–500 nM (R2 = 0.9976) and 10–750 nM (R2 = 0.9926), respectively. In a word, this method greatly improved the lower limit of quantitation of SERS, and laid foundation for rapid and convenient quantitative detection of low concentration drug in biological samples.

Introduction

In the past decades, illegal addition of drugs and abuse of antibiotics have been widespread and seriously endangering people’s health [1]. Phenformin hydrochloride (PHE) is a biguanide antidiabetic drug used to treat non-insulin-dependent diabetes [2]. In some developed countries such as the United States and the United Kingdom, PHE has been banned, and most hospitals in China have stopped using this medicine. However, in order to obtain quick profit, some unscrupulous manufacturers often add certain PHE to health care products, so that they will have obvious health effects in a short time [3]. If people take health care products containing PHE for a long time, it will be easy to cause side effects such as lactic acidosis, gastrointestinal adverse reactions, liver and kidney damage [4]. Similarly, antibiotics are widely used because they are very effective in treating bacterial or pathogenic microbial infections. Tigecycline (TGC), for example, the first approved new intravenous glycyl tetracycline antibiotic, has broad-spectrum antimicrobial activity for the treatment of complex intraluminal infections and complex skin soft tissue infections caused by staphylococcus aureus and Escherichia coli. However, overused antibiotic residues pose serious risks to human health, including carcinogenic, teratogenic, and mutagenic effects. Therefore, it is urgent to develop a rapid method for detecting PHE and TGC.

At present, the commonly used quantitative detection techniques for PHE include thin layer chromatography combined with dynamic surface enhanced Raman spectroscopy (TLC-DSERS) [5], molecular imprinting combined with flow injection chemiluminescence (MI-FIC) [6], fluorescence spectrometry [7] and high performance liquid chromatography (HPLC) [8]. The main methods for the determination of TGC include HPLC [9] and Liquid chromatography-tandem mass spectrometry (LC-MS/MS) [10]. Although the above methods have high sensitivity and resolution, their widespread use was often limited by complex separation process, expensive instruments, and time-consuming detection process. Therefore, a simple, rapid, and sensitive analysis method is essential to be developed for on-site monitoring of these drugs.

Surface-enhanced Raman scattering (SERS) refers to a plasmonic phenomenon. When the analyte molecules are adsorbed on the surface of rough noble metals or nanoparticles, the intensity of Raman scattering signal can be increased exponentially due to local surface plasmon resonance [11], [12]. Its enhancement factor can reach 106–1011 [13], [14]. SERS, as an effective molecular spectroscopy detection method [15] for biological samples [16], [17], [18], illegal drug additives [19], pesticide residues [20], [21], [22], heavy metal elements [23], and other fields [24], [25], [26], [27], has great advantages such as non-destructive, fast, trace detection, and even single molecule detection compared with traditional detection methods [28], [29]. It can provide the characteristic ‘fingerprint’ information of analyte with high accuracy and is suitable for aqueous sample analysis [30], while the application of SERS in quantitative analysis is often limited by the difficulty of producing stable and repeatable SERS signals. One method to overcome the problem of poor reproducibility is to directly detect drugs by preparing uniform and stable SERS substrate. Another approach is to introduce an additional compound as the internal standard (IS) molecule. Ag nanoparticles (AgNPs) of uniform size can be prepared by many techniques based on top-down lithography, such as electron-beam lithography, laser interference lithography, and nanoimprint lithography [31], [32], [33], [34], [35], [36]. Although the reproducible enhancement effect can be obtained, the practical applications of these techniques are restricted, for example, the demand for expensive equipment, the difficulty of fabrication on non-planar surface or the time-consuming and complicated procedures. Therefore, using chemical synthesis method to prepare silver colloidal substrate and combining with internal standard method is another option for SERS quantitative analysis, for example, externally added [37], isotope-edited [38], embedded [39], [40] and intrinsic [41], [42] internal standard method. Although the internal standard method is simple to operate, the analyte and the IS need to reach a certain concentration to have a good SERS effect. Therefore, it cannot be used for quantitative detection of low concentration drugs. Another issue is the possible competition between the analyte and the IS for the metal surface [43], which will be dependent on the concentrations. In our previous study, we developed a two-step centrifugation method for qualitatively detection of PHE with a detection limit of 500 fM, which was 5 orders lower than conventional method [44]. To this end, we propose to deal with low-concentration samples by two-step centrifugation method to reduce the distance between nanoparticles and increase the chance of hot spots, and to conduct quantitative analysis in combination with an internal standard method. In addition, dropping a small amount of sample solution onto the cover glass directly for detection may result in a decrease in repeatability due to unevenness of the sample solution. Therefore, we used a slit quartz cuvette as the detection cell, which effectively solved the above problem because the detection has a uniform and heavy thickness of the light path.

Thus, in order to detect the illegally added PHE and the residual TGC rapidly and sensitively, a two-step centrifugation method combined with internal standard method for SERS quantitative analysis was established. We used silver colloidal SERS substrate which was prepared by reducing silver nitrate (AgNO3) with hydroxylamine hydrochloride (NH2OH·HCl). The sample solution was prepared by two-step centrifugation method to increase detection sensitivity. Here, we optimized the detection conditions for PHE and TGC, and investigated the relationship between the analyte concentration and the peak intensity ratio of the analyte and IS (Ianalyte/IS ratio).

Section snippets

Chemicals and materials

All reagents used were analytical-grade chemicals. PHE, metformin hydrochloride (MH) and TGC were from National Institute for the Control of Pharmaceutical and Biological Products (Beijing, China). Streptomycin sulfate (STR), AgNO3, NH2OH·HCl, HCl, and NaOH were from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China).

Apparatus

When preparing the silver colloidal, a thermostatic magnetic stirrer (HWCL-1, Zhengzhou Changcheng Branch Industry and Trade Co., Ltd., China) was used to mix the solution. A

Effect of pH on the SERS signal

Scheme 1 shows the detection process of the two-step centrifugation method combined with the internal standard method. To obtain the enhanced Raman signal, the target molecules must be adsorbed onto the SERS substrate, and non-polar molecules have a stronger Raman effect than polar molecules [47]. The pH affects enhancement effect by affecting the above process. When the pH is below the isoelectric point of the analyte, the analyte molecules were protonated to become positively charged and

Conclusions

A SERS detection method for quantitative determination of PHE and TGC in nanomolar range was established by using the two-step centrifugation method to prepare sample solution and using the internal standard method as the quantitative basis. PHE and TGC exhibited good linearity in nanomolar range with a high reproducibility. Moreover, by using a slit quartz cuvette as a detection cell, the repeatability of SERS signals was improved. Therefore, this study provides an efficient and stable method

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CRediT authorship contribution statement

Penghui Guo: Conceptualization, Formal analysis, Data curation, Writing - original draft, Writing - review & editing. Wenxin Zeng: Conceptualization, Formal analysis, Data curation, Writing - review & editing. Sanping Tian: Conceptualization, Formal analysis, Data curation. Huaying Chen: Conceptualization, Formal analysis. Wenfang Liu: Conceptualization. Chuanpin Chen: Conceptualization, Formal analysis, Writing - review & editing.

Acknowledgements

We are grateful for the funds supported by the National Natural Science Foundation of China (81202378 and 81311140268), the Fundamental Research Funds for the Central Universities of Central South University (2018zzts876, 1053320183547), the Shenzhen Science and Technology Innovation Committee of China (JCYJ20170413105329648).

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