An enzymatic reaction-based phenylboronic acid-modified microporous array chip for chiral differentiation and high-throughput detection of D-amino acids

doi:10.21203/rs.3.rs-4892983/v1

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Research Article

An enzymatic reaction-based phenylboronic acid-modified microporous array chip for chiral differentiation and high-throughput detection of D-amino acids

https://doi.org/10.21203/rs.3.rs-4892983/v1

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published 08 Oct, 2024

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D-amino acids (D-AAs), which are potential biomarkers, are found at considerably higher levels in the saliva of individuals with early gastric cancer (GC), making the development of a rapid and sensitive assay imperative. In this paper, a Raman-active boronate modified surface-enhanced Raman scattering (SERS) microporous array chip based on enzymatic reaction was constructed for reliable, sensitive and quantitative monitoring of D-Proline (D-Pro) and D-Alanine (D-Ala) in saliva. Initially, 3-mercaptophenylboronic acid (3-MPBA) was bonded to Au-coated Si nanocrown arrays (Au/SiNCA) via Au-S bonding. Following this, H₂O₂ obtained from D-Amino acid oxidase (DAAO)-specific catalyzed D-AAs further reduced 3-MPBA to 3-hydroxythiophenol (3-HTP) with a new Raman peak at 882 cm^-1. Meanwhile, the original characteristic peak at 998 cm^-1 remained unchanged. Therefore, the I₈₈₂/I₉₉₈ ratio increased as the D-AAs content in the sample to be tested rose, allowing D-AAs to be quantitatively detected. Proudly, the Au/SiNCA with large-area periodic crown structure prepared in this paper could provide numerous, uniform “hot spots”, and the microporous array chip with 16 detection units was employed as the platform for SERS analysis, realizing high-throughput, high sensitivity, high specificity and high reliability quantitative detection of D-AAs (D-Pro and D-Ala). The limits of detection (LOD) were down to 10.1 μM and 13.7 μM throughout the linear range of 20-500 μM. The good results of the saliva detection suggested that this SERS sensor could rapidly differentiate between early-stage GC patients and healthy individuals.

Surface-enhanced Raman scattering

D-amino acids

Au/SiNCA

Microporous chip

Gastric cancer

Gastric cancer (GC) is the second most lethal cancer in the world with commonly diagnosed techniques such as gastroscopy, tissue biopsy, and microbial culture, which are standard methods that fail to avoid time-consuming and poor patient experience [1–5]. Thus, salivary biomarker testing has attracted increasing attention in recent years as an emerging cancer diagnostic method that is noninvasive, risk-free, and patient-acceptable [6–8]. Zhang et al. developed a ratiometric fluorescence enrichment detection platform for highly sensitive visual fluorescence detection of carcinoembryonic antigen (CEA) in saliva [9]. Zhang et al. discovered that a model established by six miRNAs in salivary exosomes was effective in differentiating patients with esophageal squamous cell carcinoma (ESCC) [10]. Amino acids in saliva in the form of both D-/L- enantiomers have gained great attention for their potential application in cancer, especially GC [11–12]. Recent researches have displayed that salivary concentrations of D-proline (D-Pro) and D-alanine (D-Ala) are significantly elevated in patients with early-stage GC (126.3-285.3 µM and 46.1-114.5 µM, respectively), which are ten times higher than that of normal subjects [13]. Meanwhile, the increase of salivary D-amino acids (D-AAs) was tightly correlated with the malignant progression of GC [14], suggesting that D-AAs is expected to be a promising biomarker for the early diagnosis, efficacy evaluation, and prognosis determination of GC.

To date, many traditional methods have been employed for the analysis of amino acids in saliva, including colorimetric methods [14], electrochemical biosensors [15], fluorescence biosensors [16], and others. Yet, these methods have their limitations, and it is demanding to develop a rapid and ultrasensitive D-AAs assay for the detection of early GC. Surface-enhanced Raman scattering (SERS) is regarded as a powerful spectroscopic analysis technique [17–20], which can rapidly and accurately detect target components in various complex samples due to high sensitivity, non-invasive detection capability and unique fingerprinting effect, making it widely applicable in the fields of chemical analysis, biosensing, and so on [21–22]. “Hot spots”, namely localized areas of space with extremely strong electromagnetic fields, play an important role in SERS enhancement [23]. The SERS signals of the small number of analyte molecules that fall into the “Hot spots” account for a high proportion of the overall measured SERS signal [24–25]. Nevertheless, fabricating metal substrates with uniform and dense “Hot spots” for sensitive and reproducible SERS detection remains a challenge. The large-scale ordered nanostructures have been found to generate uniform “Hot spots” for SERS signal enhancement while achieving excellent signal reproducibility and accurate SERS quantitative detection [26–27]. Au-coated Si nanocrown arrays (Au/SiNCA) are high-performance SERS substrates prepared by colloidal template-assisted etching of Au on Si nanocrown arrays, which are considered suitable for SERS applications owing to their exceptional uniformity and sensitivity.

Nevertheless, considering that D-AAs and L-AAs are enantiomers of each other with the same chemical formula and cannot avoid generating similar Raman signals, the direct discriminative detection of amino acid enantiomers with SERS remains difficult [28]. To be able to increase the enantioselectivity of SERS technology, novel chiral selection procedures must be implemented in order to overcome the aforementioned issues. Experimental evidence has confirmed that D-amino acid oxidase (DAAO) has the ability to specifically oxidize D-Ala and D-Pro, resulting in the production of H₂O₂ [29–30]. Utilizing the catalytic activity and stereoselectivity of DAAO, the chiral recognition of amino acids in real clinical samples can be easily achieved by indirectly measuring the H₂O₂ produced by D-AAs after the enzymatic reaction.

In this study, we designed and fabricated a 4 × 4 microporous array chip embedded with phenylboronic acid-modified Au/SiNCA to achieve high-throughput, ultrasensitive and specific measurement of D-AAs in subjects’ saliva (Fig. 1c). Firstly, Au/SiNCA arrays with periodic structures were prepared by monolayer colloidal template-assisted reactive ion etching (RIE) and Au deposition techniques (Fig. 1b). 3-mercaptophenylboronic acid (3-MPBA) as a traditional H₂O₂-responsive probe molecule was modified on the Au/SiNCA surface, denoted as 3-MPBA@Au/SiNCA. Lastly, the ITO glass embedded with 3-MPBA@Au/SiNCA was aligned with the designed PDMS cover to fabricate a high-throughput microporous array chip containing 16 SERS detection units. On this basis, an enzymatic reaction was designed to measure D-AAs as indicated in Fig. 1a. The natural enzyme DAAO first catalyzed the formation of H₂O₂ from D-AAs in saliva, followed by the reaction probe 3-MPBA underwent oxidation to become 3-HTP, leading to an elevated characteristic peak in the Raman spectrum at 882 cm^− 1. Additionally, the strength of this SERS peak gradually increased as the concentration of H₂O₂ increased. Finally, a ratiometric SERS sensor was established to detect D-Ala and D-Pro content based on the intensity ratio between two characteristic peaks at 882 cm^− 1 (response peak) and 998 cm^− 1 (internal standard peak). The above-mentioned microporous array chip was effectively used for the high-throughput detection of D-AAs in saliva samples, and the ultimate clinical outcomes were in line with our anticipations. We believe that this enzymatic reaction-based ratiometric SERS assay enables simpler and faster detection of GC.

2.1. Materials and reagents

Chloroauric acid tetrahydrate (HAuCl₄·4H₂O), sodium borohydride (NaBH₄), 3-Mercaptophenylboronic acid (3-MPBA), 3-Hydroxythiophenol (3-HTP), and triphenylphosphine (TPP) were obtained from Shanghai Aladdin Biochemical Technology Co; Polystyrene sphere (PS) suspension (5 wt%), anhydrous ethanol, hydrogen peroxide (H₂O₂), and PBS phosphate buffer were obtained from Sinopharm Chemical Reagent Co; Sulfur hexafluoride (SF₆) etching gas was purchased from Nanjing Special Gas Factory Co; D-Alanine (D-Ala), L-Alanine (L-Ala), D-Proline (D-Pro), L-Proline (L-Pro), and D-Amino acid oxidase (D-AAO) were obtained from Shanghai Adamas Reagent Co; All reagents were provided at analytical grade and were used without further purification; Deionized water was obtained through a Milli-Q purifier (resistivity of 18 MΩ.cm).

2.2. Sample collection and processing

The specified time for saliva collection was between 8am-10am, and patients were not allowed to eat or drink or perform any other hygienic procedures in the mouth (water rinsing only) for at least 2 h prior to saliva collection and were not taking medication for 8 h. The obtained saliva samples were centrifuged using 2000 rpm for 10 min and the supernatant was taken and stored in -70℃. Five healthy individuals from our subject group and five gastric cancer patients from the affiliated Hospital, with a total of 10 samples No. 1–10 (No. 1–5 were healthy individuals).

2.3. Fabrication of 3-MPBA@Au/SiNCA

Au-coated Si nanocrown arrays (Au/SiNCA) were prepared by polystyrene (PS) microsphere template-assisted reactive ion etching (RIE) process in combination with magnetron sputtering, as illustrated in Fig. 1b. Initially, single-layer densely-arranged microsphere arrays were obtained by a gas-liquid interface self-assembly method employing PS microspheres as precursors and hydrophilic-treated silicon wafers as substrates [31]. After heating and drying (70℃, 30 min), the single-layer PS colloidal sphere template could be firmly fixed on the wafer surface. Subsequently, O₂ and SF₆ were employed as etching gases (flow rate 10 sccm, 20 sccm) for RIE for 2 min followed by Ar gas (20 sccm) for physical etching of the ionized surface for 1 min. Then, rinsing with ethanol and heat treatment to remove the residual PS microspheres (600 ℃, 2 h), i.e., pure Si nanocrown arrays (SiNCA) were obtained. Finally, a dense layer of Au nanoparticles (AuNPs) was deposited on the surface of the SiNCA by magnetron sputtering (deposition rate 0.5 nm/s) to obtain Au/SiNCA.

Next, for the preparation of 3-MPBA functionalized Au/SiNCA, the configured 3-MPBA solution (20 µL, 2.5 mM) was dropped on Au/SiNCA firstly. After incubation for 2 h, the Raman probe 3-MPBA could be immobilized with AuNPs by Au-S bonding [32]. At last, it was rinsed clean with ethanol and deionized water successively and blown dry with N₂ to obtain 3-MPBA@Au/SiNCA.

2.4. Preparation of the microporous array chip

To maximize the throughput, reproducibility and sensitivity of the SERS assay, a microporous array chip with a “sandwich” structure was fabricated. As depicted in Fig. 1c, the microporous array chip consisted of three parts: a ITO glass substrate embedded with Au/SiNCA, a PDMS microporous array sandwich, and a PDMS cover sheet. The chip measured 25 mm × 25 mm and contained 16 arrays of microwells with a diameter of 3 mm, a spacing of 3 mm, and a height of 2 mm. Briefly, the 3-MPBA@Au/SiNCA was first embedded into the glass substrate by laser etching, whose aperture size and distribution were required to match the microporous array on the PDMS chip. The glass substrate containing 3-MPBA@Au/SiNCA material only in the SERS test area and the PDMS sandwich containing 16 arrayed microporous were then accurately aligned and bonded by the oxygen plasma technique. At last, the PDMS cover slip was covered to successfully construct the SERS microporous array chip.

2.5. Quantitative SERS detection of D-Pro and D-Ala

DAAO solution (0.25 µL, 10 U/mL) and 10 µL of different concentrations of D-Pro solution were mixed and fixed to 15 µL by adding phosphate buffer (10 mmol/L, pH = 7.4), then incubated for 45 min under the condition of 37 ℃ constant temperature water bath. Subsequently, the above solution was added dropwise into the microporous array chip integrated with 3-MPBA@Au/SiNCA and rinsed with deionized water after 0.5 h reaction at 37 ℃ with drying under N₂ gas for Raman spectroscopy. A Renishaw Invia miniature Raman spectrometer was employed, with Raman detection conditions set to 785 nm laser wavelength, 5.0 mW laser power, ×50 objective, 2 µm spot size and 5 s exposure time. Spectral measurements were conducted at five different points to ensure representativeness and confidence.

2.6. Instrumentation

S-4800 II Field Emission Scanning Electron Microscope (Hitachi, Japan); InVia Reflex Microscopic Raman Spectrometer (Renishaw, U.K.); DXR3xi Raman Imaging Microscope (Thermo Fisher, U.S.A.); TS-P05 Plasma Surface Treatment Machine (Tonson Tech, China).

3.1 Characterization of Au/SiNCA and microporous chip

The morphology of the stage products and final products during the fabrication of Au/SiNCA was characterized using Scanning Electron Microscopy (SEM). As indicated in Fig. 2a, a layer of uniform and tightly packed PS colloidal spheres with a diameter of 200 nm was firstly obtained by the gas-liquid interfacial self-assembly strategy and monolithic transfer during the preparation process. Then, Au/SiNCA arrays with unique morphology were obtained by adjusting the RIE process conditions and sputtering Au nanoparticles with a magnetron sputtering apparatus. It was evident in Fig. 2b and c that the SERS substrate consisted of crown-like structural units in an ordered periodic arrangement with a period of 200 nm, corresponding to the diameter of the PS colloidal spheres. Theoretically, the unique crown-like structure of Au/SiNCA with superior specific surface area could provide abundant binding sites for the immobilization of biomolecules, which would be beneficial for subsequent functionalization. Figure 2d well demonstrated the top and side views of a microporous array with a three-layer structure.

The suitability of the array as a SERS substrate was evaluated using TPP-labeled Au/SiNCA at a concentration of 1 × 10^− 8 M. Ten points on the array were randomly selected to acquire Raman spectra and histograms of the intensity of the characteristic peaks at 998 cm^-1 (phenyl N1 mode) were obtained (Fig. 2e and f). The shapes of the obtained Raman spectra exhibited a consistent trend, but the intensities were slightly different with an RSD value of only 6.22%, demonstrating the advantage of the high homogeneity of the array. The enhancement factor (EF) of Au/SiNCA was calculated according to the following equation: EF = (I_SERS/C_SERS)/(I_R/C_R), where I_SERS and I_R denoted the peak intensity (998 cm^-1) of TPP on Au/SiNCA and silicon wafers, and C_SERS and C_R were 1 × 10^− 8 M and 1 × 10^− 1 M, respectively (Fig. 2g). The final calculated EF for Au/SiNCA was 1.68 × 10⁹, higher than that of the annular gap array fabricated by Luo et al. (EF of 10⁸) [33]. The sensitivity of Au/SiNCA was crucial for the subsequent quantitative detection of H₂O₂. As could be seen from Fig. 2h, the spectra of different concentrations of TPP (10^− 8-10^− 13 M) displayed significant variability and there was a large linear correlation between the logarithm of the TPP concentration and the intensity of the characteristic peak at 998 cm^-1 (Fig. 2i). The linear equation was y = 6182.6x + 82187.9 with R² = 0.986. Therefore, the limit of detection (LOD) could be calculated as 73.4 fM, revealing the excellent SERS signal amplification performance of the Au/SiNCA.

3.2 SERS performance evaluation of 3-MPBA@Au/SiNCA

The detection strategy in this work was designed based on the reaction of H₂O₂ oxidizing 3-MPBA to 3-HTP. To verify the feasibility of this reaction, SERS spectroscopy was performed on the modified 3-MPBA@Au/SiNCA, 3-MPBA + H₂O₂@Au/SiNCA, and 3-HTP@Au/SiNCA chips, respectively. As demonstrated in Fig. 3, the signaling molecule 3-MPBA has been successfully modified on the surface of Au/SiNCA arrays via Au-S bonding, and its SERS spectrum were found to have distinct characteristic peaks at 785, 995, 1076, and 1554 cm^-1, which were in good agreement with the previous work [34]. After H₂O₂ treatment, the SERS spectra of 3-MPBA@Au/SiNCA closely matched the SERS spectra of 3-HTP (Fig. 3a), indicating that the conversion of borate to phenol was as expected. The new peak at 882 cm^-1 was associated with the stretching vibration of the benzene ring of 3-HTP [35]. The SERS mapping of the 3-MPBA@Au/SiNCA exhibited an overall homogeneous green color (Fig. 3b), indicating that 3-MPBA has been uniformly modified on the surface of the SERS substrate. To verify the reliability of this SERS substrate for H₂O₂ detection, we synthesized five batches of 3-MPBA@Au/SiNCA at different times and treated them with 1 mM H₂O₂, respectively. As displayed in Fig. 3c, the ratio intensity I₈₈₂/I₉₉₈ remained essentially constant with an RSD of only 2.12% in the SERS measurements of five different batches of Au/SiNCA. In additional, we left the same batch of prepared SERS substrates for different number of days before H₂O₂ treatment, and the SERS assay revealed only a weak change in I₈₈₂/I₉₉₈ over time (Fig. 3d). Hence, the SERS sensing platform designed in this study was successfully prepared with favorable uniformity, reproducibility and stability.

3.3 Quantitative SERS detection of H₂O₂

Under optimized experimental conditions (Fig. S1), H₂O₂ (500 µM) solution prepared in phosphate buffer was added dropwise into the 3-MPBA@Au/SiNCA integrated microporous array chip for SERS detection after reaction. In Fig. 4a, the value of I₈₈₂/I₉₉₈ varied with time (min), and the signal stabilized after 30 min. Therefore, the optimal time for the reaction was chosen as 30 min. Figure 4b showed the SERS spectra obtained after the reaction of the microporous array chip and different concentrations of H₂O₂, and it was clearly observed that the peak at 882 cm^-1 became higher with the increase of H₂O₂ concentration. Figure 4c plotted the curve of I₈₈₂/I₉₉₈ versus H₂O₂ concentration, and it was found that excellent linearity was obtained between the values of I₈₈₂/I₉₉₈ and the H₂O₂ concentration in the range of 10–500 µM. The linear equation was y = 0.768 x + 0.133, R² = 0.986, and the limit of detection (LOD) was calculated to be 7.7 µM based on the triple signal-to-noise ratio.

3.4 Quantitative SERS detection of D-Pro and D-Ala

This study aimed to explore the feasibility of quantifying D-Pro using the quantitative H₂O₂ assay mentioned above. Similar to H₂O₂ sensing, the I₈₈₂ exhibited a significant dependence on the H₂O₂ produced by the oxidation of D-Pro by DAAO. As indicated in Fig. 5a, the 882 cm^-1 peak gradually increased with the increase of D-Pro concentration and the 998 cm^-1 peak height was basically unchanged. The association curve between I₈₈₂/I₉₉₈ and the concentration of D-Pro was shown in Fig. 5b, and it was a surprise to find that there was a good linearity between them in the concentration range of 20–500 µM. The corresponding linear regression equation for D-Pro was y = 0.656 x + 0.121, with a correlation coefficient of R² = 0.993, and the LOD was 10.1 µM. Figure 5c was the SERS spectra obtained from the detection of different concentrations of D-Ala using the microporous array chip. As observed in Fig. 5d, there was also a good linearity between the concentration of D-Ala and I₈₈₂/I₉₉₈ in the concentration range of 20–500 µM. The corresponding regression equation was y = 0.618 x + 0.117, with R² = 0.997, and LOD was down to 13.7 µM.

3.5 Characterization of clinical samples

Information was provided on samples from gastroscopy, pathologic biopsy, and CT from a healthy individual and a patient with GC. Gastroscopy serves as a common examination and treatment tool in gastroenterology to visualize and biopsy lesions in the stomach. Gastroscopy revealed smooth and well-dilated gastric mucosa in a healthy individual, with no obvious ulcers or neoplastic organisms (Fig. 6a), and pathologic biopsy results contained no abnormalities (Fig. 6b). Gastroscopic examination of GC patients revealed that extensive ulceration was seen in their cardia and gastric body, which was characterized by depressed yellow-brown moss accompanied by granulomatous necrosis, with a slightly hard texture, and bleeding easily when touched (Fig. 6d). Pathologic biopsy was taken, which visualized heterogeneous hyperplastic glandular epithelium in the form of irregular glandular tubular with infiltrative growth (Fig. 6e), and the diagnosis of ulcerative tubular adenocarcinoma of the cardia was made. No abnormalities were detected on CT examination in a healthy person (Fig. 6c), whereas CT in a GC patient indicated localized thickening of the gastric wall with hepatogastric hiatus nodules (Fig. 6f).

3.6 Detection of clinical saliva samples

Testing clinical saliva samples proved more intricate compared to those conducted in a controlled laboratory environment. L-proline (L-Pro), L-alanine (L-Ala), Cysteine (Cys), glutathione (GSH), glycine, valine, serine, threonine, and some inorganic salts in saliva samples may confound D-Pro and D-Ala results, resulting in a false-positive diagnosis of GC. Fortunately, as indicated in Fig. 7a, these introduced interferences could not react with the natural enzyme DAAO to trigger the H₂O₂ responsive probe thereby failing to produce a change in the spectrum at 882 cm^-1. Thus, this SERS microporous array chip exhibited excellent specificity for D-Pro and D-Ala, with no response to potential interferences. In order to investigate the possibility of selectively detecting a particular amino acid in the presence of two D-amino acids, we conducted experiments using mixes of D-Pro and D-Ala in varying ratios (with a total concentration of 1 mM for both D-Pro and D-Ala). Testing revealed that I₈₈₂/I₉₉₈ varied insignificantly with the molar ratio of the two amino acids (Fig. 7b), suggesting that specific detection of one amino acid could not be realized. Given that both D-Pro and D-Ala were present in the actual saliva sample and their linear regression equation shown a high degree of similarity, this SERS approach has the capability to measure the total concentration of D-Pro and D-Ala.

To test the effectiveness of this SERS microporous array chip, 100-fold dilutions of actual saliva samples from healthy individuals were treated with different concentrations of D-Pro. Excellent recoveries ranging from 98.44–105.08% were obtained as shown in Table 1. To investigate the possibilities of clinical use of the chip, we conducted experiments on clinical samples No. 1–10 (No. 6–10 were GC patients). It is obvious from Fig. 7c inset that GC patients have significantly higher characteristic peak intensity at 882 cm^-1 than healthy individuals. Based on the linear fitting equation for D-Ala, the total concentration of D-Pro and D-Ala in saliva samples No. 6–10 were calculated to be 304.88, 278.96, 335.37, 388.72 and 361.28 µM, respectively, which were consistent with the range of total concentrations of the two amino acids in the saliva of GC patients (174.2-399.8 µM).

Table 1

Assay results for D-Pro detection in diluted saliva sample
Saliva sample	D-Pro (µM)			Recovery (%)
Saliva sample	Added (µM)	Found (µM)	RSD (%)	Recovery (%)
Sample 1	50.00	51.57	4.71	103.14
	100.00	99.49	2.48	99.49
	300.00	308.85	6.52	102.95
Sample 2	50.00	49.22	4.29	98.44
	100.00	98.71	4.12	98.71
	300.00	315.24	3.45	105.08
Sample 3	50.00	50.99	1.99	101.98
	100.00	104.76	3.78	104.76
	300.00	305.91	5.74	101.97

In summary, we successfully constructed a microporous array chip embedded with 3-MPBA-modified Au/SiNCA for the detection of H₂O₂ and D-AAs. This sensor possessed the advantages of high throughput detection, high sensitivity, high specificity and high reliability. Several factors contributed to the excellent performance of this SERS sensor. Firstly, the experimentally prepared Au/SiNCA arrays with large-area ordered crown structures could deliver numerous, uniform SERS “hotspots” with EF as high as 10⁹, thus realizing reproducible and highly sensitive detection of D-AAs with LODs as low as 10.1 µM and 13.7 µM. Secondly, the ratiometric SERS sensing mechanism could effectively improve the accuracy and reliability of the SERS sensor. Thirdly, the constructed SERS sensor carried a 4 × 4 microporous array chip, which realized high-throughput detection while avoiding the contamination of samples by external environment and improving the stability and reproducibility of the salivary SERS detection process. Additionally, the SERS sensor was further applied to the analysis of clinical saliva samples, and found that there were large differences in the total D-Pro and D-Ala content between non-cancer and GC patients, which was expected to realize the non-invasive diagnosis of GC patients. This work would be helpful to facilitate the application of SERS technology in exploring the physiological functions, metabolism and clinical diagnosis of D-AAs.

Author Contributions Feng Lu: Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Writing-original draft preparation, Writing-review & editing. Limao Li: Resources, Validation, Investigation, Writing-original draft preparation. Kang Shen: Conceptualization, Data curation, Methodology. Yayun Qian: Resources, Validation, Methodology. Pengfei Zhang: Data curation, Writing-review & editing. Yan Yang: Software, Writing-review & editing. Qunshan Zhu: Software. Yong Huang: Formal analysis, Funding acquisition. Chunxiang Yan: Supervision, Funding acquisition. Wei Wei: Supervision, Funding acquisition, Project administration. All authors have read and agreed to the published version of the manuscript.

Funding This work was financially supported by the Yangzhou Social Development fund (YZ2022089), the Yangzhou Social Development fund (YZ2023094), and the Key Medical Research Projects of Yangzhou Health Commission (2023-1-04).

Data availability The datasets used and analysed during the current study available from the corresponding author on reasonable request.

Ethics statements Saliva samples from GC patients were obtained at the Affiliated Hospital of Yangzhou University after permission from the School of Clinical Medicine’s Ethics Committee. We certify that the study was performed in accordance with the 1964 declaration of HELSINKI and later amendments.

Consent to participate Informed consent was obtained from all individual participants included in the study.

Conflict of interest There are no conflicts of interest to declare.

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An enzymatic reaction-based phenylboronic acid-modified microporous array chip for chiral differentiation and high-throughput detection of D-amino acids

Status:

Journal Publication

Version 1

Abstract

Figures

1. Introduction

2. Experimental methods

2.1. Materials and reagents

2.2. Sample collection and processing

2.3. Fabrication of 3-MPBA@Au/SiNCA

2.4. Preparation of the microporous array chip

2.5. Quantitative SERS detection of D-Pro and D-Ala

2.6. Instrumentation

3. Results and discussion

3.1 Characterization of Au/SiNCA and microporous chip

3.2 SERS performance evaluation of 3-MPBA@Au/SiNCA

3.3 Quantitative SERS detection of H₂O₂

3.4 Quantitative SERS detection of D-Pro and D-Ala

3.5 Characterization of clinical samples

3.6 Detection of clinical saliva samples

4. Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1

An enzymatic reaction-based phenylboronic acid-modified microporous array chip for chiral differentiation and high-throughput detection of D-amino acids

Status:

Journal Publication

Version 1

Abstract

Figures

1. Introduction

2. Experimental methods

2.1. Materials and reagents

2.2. Sample collection and processing

2.3. Fabrication of 3-MPBA@Au/SiNCA

2.4. Preparation of the microporous array chip

2.5. Quantitative SERS detection of D-Pro and D-Ala

2.6. Instrumentation

3. Results and discussion

3.1 Characterization of Au/SiNCA and microporous chip

3.2 SERS performance evaluation of 3-MPBA@Au/SiNCA

3.3 Quantitative SERS detection of H2O2

3.4 Quantitative SERS detection of D-Pro and D-Ala

3.5 Characterization of clinical samples

3.6 Detection of clinical saliva samples

4. Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1

3.3 Quantitative SERS detection of H₂O₂