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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Chem.</journal-id>
<journal-title>Frontiers in Chemistry</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Chem.</abbrev-journal-title>
<issn pub-type="epub">2296-2646</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">861353</article-id>
<article-id pub-id-type="doi">10.3389/fchem.2022.861353</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Chemistry</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>A Copper-Based Biosensor for Dual-Mode Glucose Detection</article-title>
<alt-title alt-title-type="left-running-head">Li et al.</alt-title>
<alt-title alt-title-type="right-running-head">Dual-Mode Glucose Biosensor</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Kai</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Xu</surname>
<given-names>Xiaoyu</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1721047/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liu</surname>
<given-names>Wanshan</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yang</surname>
<given-names>Shouzhi</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Huang</surname>
<given-names>Lin</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Tang</surname>
<given-names>Shuai</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Ziyue</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Wang</surname>
<given-names>Yuning</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Chen</surname>
<given-names>Fangmin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Qian</surname>
<given-names>Kun</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/816716/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Urology</institution>, <institution>Tianjin Third Central Hospital Affiliated to Nankai University</institution>, <addr-line>Tianjin</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>State Key Laboratory for Oncogenes and Related Genes</institution>, <institution>School of Biomedical Engineering</institution>, <institution>Institute of Medical Robotics and Med-X Research Institute</institution>, <institution>Shanghai Jiao Tong University</institution>, <addr-line>Shanghai</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Division of Cardiology</institution>, <institution>Renji Hospital</institution>, <institution>School of Medicine</institution>, <institution>Shanghai Jiao Tong University</institution>, <addr-line>Shanghai</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Clinical Laboratory Medicine</institution>, <institution>Shanghai Chest Hospital</institution>, <institution>Shanghai Jiao Tong University</institution>, <addr-line>Shanghai</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/449059/overview">Xiaomin Li</ext-link>, Fudan University, China</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/310333/overview">Aihua Liu</ext-link>, Qingdao University, China</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/823222/overview">Liang Qiao</ext-link>, Fudan University, China</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Yuning Wang, <email>YuningWang@sjtu.edu.cn</email>; Fangmin Chen, <email>5020201287@nankai.edu.cn</email>; Kun Qian, <email>k.qian@sjtu.edu.cn</email>
</corresp>
<fn fn-type="other">
<p>This article was submitted to Analytical Chemistry, a section of the journal Frontiers in Chemistry</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>04</day>
<month>04</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>10</volume>
<elocation-id>861353</elocation-id>
<history>
<date date-type="received">
<day>25</day>
<month>01</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>15</day>
<month>03</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Li, Xu, Liu, Yang, Huang, Tang, Zhang, Wang, Chen and Qian.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Li, Xu, Liu, Yang, Huang, Tang, Zhang, Wang, Chen and Qian</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Glucose is a source of energy for daily activities of the human body and is regarded as a clinical biomarker, due to the abnormal glucose level in the blood leading to many endocrine metabolic diseases. Thus, it is indispensable to develop simple, accurate, and sensitive methods for glucose detection. However, the current methods mainly depend on natural enzymes, which are unstable, hard to prepare, and expensive, limiting the extensive applications in clinics. Herein, we propose a dual-mode Cu<sub>2</sub>O nanoparticles (NPs) based biosensor for glucose analysis based on colorimetric assay and laser desorption/ionization mass spectrometry (LDI MS). Cu<sub>2</sub>O NPs exhibited excellent peroxidase-like activity and served as a matrix for LDI MS analysis, achieving visual and accurate quantitative analysis of glucose in serum. Our proposed method possesses promising application values in clinical disease diagnostics and monitoring.</p>
</abstract>
<kwd-group>
<kwd>Cu<sub>2</sub>O nanoparticle</kwd>
<kwd>colorimetric</kwd>
<kwd>mass spectrometry</kwd>
<kwd>glucose</kwd>
<kwd>biosensor</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>Glucose plays important role in the human body, providing energy for metabolism and normal operation of various organs (<xref ref-type="bibr" rid="B11">Grochowska et al., 2017</xref>). As is reported, disorders of glucose metabolism cause diabetes (<xref ref-type="bibr" rid="B51">Zheng et al., 2018</xref>), hyperglycemia (<xref ref-type="bibr" rid="B3">Beaudry et al., 2013</xref>), or other diseases (<xref ref-type="bibr" rid="B39">Sardarinia et al., 2016</xref>). Glucose is regarded as a biomarker in the clinic, the concentration of which reflects the abnormal behavior of the body. For example, the glucose level in cancer cells is higher than that in healthy cells (<xref ref-type="bibr" rid="B45">Wu et al., 2019</xref>). Thus, it is indispensable to develop simple, accurate, and sensitive methods for glucose detection.</p>
<p>At present, the usually used methods for glucose detection mainly depend on enzymatic reactions (<xref ref-type="bibr" rid="B1">Aksorn and Teepoo, 2020</xref>; <xref ref-type="bibr" rid="B24">Kim et al., 2020</xref>). In brief, glucose could be transferred to hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) and gluconic acid with the help of glucose oxidase (GOD). The generated H<sub>2</sub>O<sub>2</sub> catalyzes the substrates to colored products in the presence of peroxidase, which could be analyzed by electrochemical sensors or optical sensors (<xref ref-type="bibr" rid="B36">Qu et al., 2021</xref>). Specifically, colorimetric biosensors with the advantages of simplicity, visualization, and low cost, have been widely used in glucose detection (<xref ref-type="bibr" rid="B32">Liu et al., 2019</xref>). However, the natural enzymes are unstable, hard to prepare and expensive limiting the extensively clinical applications (<xref ref-type="bibr" rid="B2">Ambati and Jachak, 2021</xref>). Since the nanoenzymes come out (<xref ref-type="bibr" rid="B34">Mei et al., 2020</xref>; <xref ref-type="bibr" rid="B19">Huo et al., 2022</xref>), various nanomaterials possessing peroxidase-like activity have been successfully utilized to detect glucose (<xref ref-type="bibr" rid="B22">Jia et al., 2016</xref>). Remarkably, it is important to fabricate the easily prepared nanomaterials-based peroxidase-like colorimetric biosensors for glucose analysis.</p>
<p>Currently, matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) has been widely applied in biomolecules analysis (<xref ref-type="bibr" rid="B27">Li et al., 2020</xref>; <xref ref-type="bibr" rid="B44">Wang et al., 2021</xref>). Compared to colorimetric assay, MALDI MS presents high sensitivity, accuracy, throughput and provides molecular information (<xref ref-type="bibr" rid="B21">Israr et al., 2020</xref>). Nevertheless, it is a challenge to quantitatively analyze small molecules due to the background signal and coffee effect of traditional organic matrices (<xref ref-type="bibr" rid="B46">Wu et al., 2018</xref>). In recent years, plenty of research has been paid more attention to nanomaterials-assisted LDI MS for metabolic analysis (<xref ref-type="bibr" rid="B4">Cao et al., 2020</xref>; <xref ref-type="bibr" rid="B31">Liu et al., 2020</xref>; <xref ref-type="bibr" rid="B7">Ding et al., 2022</xref>). In the process of LDI MS, the matrix can uniformly distribute among the targets (<xref ref-type="bibr" rid="B6">Dai et al., 2020</xref>) and enhance the ionization efficiency, largely improving the MS quantitative performance (<xref ref-type="bibr" rid="B25">Kim et al., 2021</xref>).</p>
<p>Herein, we propose a copper-based biosensor for dual-mode glucose analysis based on colorimetric assay and LDI MS (<xref ref-type="fig" rid="F5">Schem 1</xref>). Cu<sub>2</sub>O nanoparticles (NPs) were facilely prepared and testified the peroxidase-like activity, achieving visual detection of glucose combined with GOD. Meanwhile, Cu<sub>2</sub>O NPs were utilized as a matrix for LDI MS analysis of small molecules (e.g. glucose) with good salt tolerance. By adding internal standard, glucose level could be quantitative analysis by Cu<sub>2</sub>O NPs assisted LDI MS. Notably, the dual-mode Cu<sub>2</sub>O NPs based biosensor was applied to detect glucose from serum and a consistent result was obtained, demonstrating that the method could be reliable in glucose analysis for clinical diseases diagnostics and monitoring.</p>
<fig id="F5" position="float">
<label>SCHEME 1</label>
<caption>
<p>Schematic workflow of the copper-based biosensor for dual-mode glucose detection.</p>
</caption>
<graphic xlink:href="fchem-10-861353-g005.tif"/>
</fig>
<sec id="s1-1">
<title>Experimental Section</title>
<sec id="s1-1-1">
<title>Chemicals and Materials</title>
<p>CuSO<sub>4</sub> 5H<sub>2</sub>O (98%), sodium hydroxide (NaOH, 96%), D-(&#x2b;)-glucose (Glu, 99.5%), ethylene glycol (99%), D-(&#x2b;)-cellobiose (Cel, 98%), L-arginine (Arg, 98%), <sc>d</sc>-phenylalanine (98%), anhydrous ethanol (EtOH, 99.7%), sodium acetate (98.5%), choline (Cho, 90%), ascorbic acid (Vc, 99%), <sc>d</sc>-galactose (Gla, 95%), and dopamine (DA, 98%) were acquired from Inno-chem Co., Ltd. (Beijing, China). Polyvinylpyrrolidone (PVP, MW &#x3d; 40,000), L-aspartic acid (Asp, 98%), D-(-)-fructose (Fru, 98%), L-alanine (Ala, 99%), 3,3&#x2032;,5,5&#x2032;-tetramethylbenzidine (TMB, 99%), and acetic acid (99%) were ordered from Sigma, United States. Dimethylsulfoxide (DMSO, 99.8%) was bought from Aladdin Reagent Co., Ltd. (Shanghai, China). Phosphate-buffered saline (PBS, 10&#xd7;, pH 7.4, cell-culture grade) and Sodium acetate (98.5%) were ordered from Tokyo Chemical Industry Co., Ltd. (Tokyo, Japan). Glucose oxidase (GOD) was acquired from Shanghai Macklin Biochemical Co., Ltd. (Shanghai, China). All chemicals were used without any further purification unless otherwise stated. Deionized (DI) water (18.2&#xa0;M&#x3a9;&#xa0;cm) was prepared by a Milli-Q water purification system (Millipore, Billerica, MA).</p>
</sec>
<sec id="s1-1-2">
<title>Instruments and Characterization</title>
<p>Transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), high-angle annular dark-filed (HAADF), and elemental mapping images were collected using a JEOL JEM-2100F instrument by depositing materials on a copper grid with a mesh size of 200. Scanning electron microscopy (SEM) images were recorded on Hitachi S-4800 by dropping the ethanolic material suspensions on aluminum foil. The crystal structure of the wide-angle powder pattern was analyzed through X-ray diffraction (BrukerD8, Germany) with Cu K&#x3b1; radiation (<italic>&#x3bb;</italic> &#x3d; 0.154&#xa0;nm). The materials absorption spectra were obtained on an Ultraviolet-visible (UV-Vis) (AuCy UV1900, China) spectrophotometer and MD SpectraMax i3x using water suspension at room temperature (RT, 25&#xb0;C). The LDI MS analysis was performed on Matrix-Assisted Laser Desorption/ionization Time of Flight Mass Spectrometry (MALDI-TOF MS, Bruker Autoflex Speed, Germany) with the Nd: YAG laser (2&#xa0;kHz, 355&#xa0;nm) and smart beam system. The acquisitions were conducted in positive reflector ion mode with the repetition rate of 1&#xa0;kHz and an acceleration voltage of delayed extraction set as 20&#xa0;kV. Optimized delay time for this experiment to 250&#xa0;ns and laser shots of 2000 per detection was applied throughout LDI MS analysis. For the calibration of each spot, dropped mixed small molecules for the accurate measurement of mass spectrometry (&#x3c;20&#xa0;ppm). Each sample detection performed five independent experiments and all spectra results were used for analysis directly without any smoothing procedures.</p>
</sec>
<sec id="s1-1-3">
<title>Preparation of Biofluid</title>
<p>Blood samples were donated by healthy controls and patients in Tianjin Third Central Hospital. The serum samples were prepared from blood according to the previous report (<xref ref-type="bibr" rid="B16">Huang L. et al., 2019</xref>). 3&#xa0;ml of blood was drawn to BD Vacutainer SST tubes (Becton, Dickinson and Co., United States) and centrifuged at 3,000&#xa0;rpm for 15&#xa0;min to collect aliquots of the supernatant as serum. All samples were harvested in tubes and stored at &#x2212;80&#xb0;C for use. All the investigation protocols in this study were approved by the institutional ethics committees of Tianjin Third Central Hospital and School of Biomedical Engineering, Shanghai Jiao Tong University (SJTU). Informed consent from healthy controls and patients had been obtained since the project started.</p>
</sec>
<sec id="s1-1-4">
<title>Synthesis of Cu<sub>2</sub>O Nanoparticles</title>
<p>The Cu<sub>2</sub>O NPs were prepared according to the improved glucose reduction method (<xref ref-type="bibr" rid="B41">Sheng et al., 2020</xref>). Briefly, 0.2496&#xa0;g of CuSO<sub>4</sub>.5H<sub>2</sub>O and 0.04&#xa0;g of PVP were dispersed in 50&#xa0;ml of ethylene glycol for 30&#xa0;min under ultrasonic vibration. Then, 25&#xa0;ml of NaOH (0.1&#xa0;M) were added and stirred at RT for 10&#xa0;min. After that, 25&#xa0;ml of glucose (1.3&#xa0;M) were added with slowly stirring for 15&#xa0;min and the obtained mixture was heated at 80&#xb0;C for 1&#xa0;h in a water bath. After the resulting solution cooled to RT naturally, the orange sediment was collected and washed several times thoroughly with DI water and EtOH by centrifugation. Finally, the Cu<sub>2</sub>O NPs were obtained by drying for 5&#xa0;h in a vacuum oven at 55&#xb0;C.</p>
</sec>
<sec id="s1-1-5">
<title>Peroxidase Activity of the Cu<sub>2</sub>O NPs</title>
<p>The Cu<sub>2</sub>O NPs have the property of peroxidase, which was verified by the oxidation of TMB in the presence of H<sub>2</sub>O<sub>2</sub>. In a typical procedure, 100&#xa0;&#xb5;l of TMB (20.8&#xa0;mM, dissolved in DMSO), 100&#xa0;&#xb5;l of H<sub>2</sub>O<sub>2</sub> (5&#xa0;mM) and 5&#xa0;&#xb5;l of Cu<sub>2</sub>O NPs (7&#xa0;mM) were added in 400&#xa0;&#xb5;l of HAc-NaAc buffer (pH 3.0). After incubation at 37&#xb0;C for 5&#xa0;min, the color of the solution turned blue and its absorption at 652&#xa0;nm was measured by UV-vis spectrophotometer.</p>
</sec>
<sec id="s1-1-6">
<title>Catalytic Reactions of Glucose</title>
<p>A series of concentrations of glucose (20&#xa0;&#xb5;l) and GOD (200&#xa0;&#x3bc;l, 32.5&#xa0;mM) were mixed in PBS and incubated at 37&#xb0;C for 60&#xa0;min, respectively. Then, 5&#xa0;&#xb5;l of Cu<sub>2</sub>O NPs (7&#xa0;mM), 100&#xa0;&#xb5;l of TMB (20.8&#xa0;mM), and 400&#xa0;&#xb5;l of acetate buffer (pH 3.0) were added to the above solution and incubated for 10&#xa0;min for absorption measurement. For serum glucose detection, instead of glucose solution, a 20&#xa0;&#xb5;l serum sample was performed with the same experimental steps as mentioned above and the absorption values reflected the glucose concentration in serum samples due to the linear curve.</p>
</sec>
<sec id="s1-1-7">
<title>LDI Analysis of Glucose</title>
<p>One milliliter of glucose with concentrations ranging from 0.56 to 5.6&#xa0;mM was mixed with an equal volume of cellobiose solution (2.9&#xa0;mM), respectively. Then 500&#xa0;nL of mixture solution and 500&#xa0;nL of Cu<sub>2</sub>O NPs were dropped on the plate and analyzed by LDI-MS after drying. Cu<sub>2</sub>O NPs were dispersed in DI water at the concentration of 2.9&#xa0;mM for use as a matrix. For LDI-MS analysis of glucose in serum, typically, the liquid of serum sample was mixed with equal volume cellobiose solution (2.9&#xa0;mM) and spotted on the plate (1.5&#xa0;&#xb5;l) until dried in air at 25&#xb0;C, followed by adding 1.5&#xa0;&#xb5;l of matrix and also dried in the same condition for LDI MS analysis.</p>
</sec>
</sec>
<sec sec-type="results|discussion" id="s1-2">
<title>Results and Discussion</title>
<sec id="s1-2-1">
<title>The Characterization of Cu<sub>2</sub>O NPs</title>
<p>The morphology of the prepared Cu<sub>2</sub>O NPs was characterized by SEM and TEM. As shown in <xref ref-type="fig" rid="F1">Figures 1A,B</xref>, the Cu<sub>2</sub>O NPs exhibited a uniform spherical morphology with an average diameter of about 200&#xa0;nm. Meanwhile, TEM images in <xref ref-type="sec" rid="s8">Supplementary Figure S1</xref> (ESI&#x2020;) showed that the distribution of particles varied from 150 to 240&#xa0;nm and was mainly concentrated on 200&#xa0;nm. The selected area electron diffraction (SAED) pattern shown in <xref ref-type="sec" rid="s8">Supplementary Figure S2</xref> (ESI&#x2020;) further confirmed the successful synthesis of pure Cu<sub>2</sub>O NPs (<xref ref-type="bibr" rid="B20">Hur et al., 2019</xref>). In <xref ref-type="fig" rid="F1">Figure 1B</xref>, the surface of the Cu<sub>2</sub>O NPs was rough and its SAED (inset of <xref ref-type="fig" rid="F1">Figure 1B</xref>) indicated that the Cu<sub>2</sub>O NPs have a polycrystalline structure (<xref ref-type="bibr" rid="B5">Chinnaiah et al., 2022</xref>). The elemental mapping of Cu<sub>2</sub>O NPs (<xref ref-type="fig" rid="F1">Figure 1C</xref>) and the corresponding high-resolution transmission electron microscopy (HRTEM) image shown in <xref ref-type="sec" rid="s8">Supplementary Figure S3</xref> (ESI&#x2020;) confirmed its high-quality polycrystalline nature (<xref ref-type="bibr" rid="B15">Huang and Luo, 2021</xref>). The phase structure and the purity of Cu<sub>2</sub>O NPs were analyzed using X-ray diffraction (XRD). As shown in <xref ref-type="fig" rid="F1">Figure 1D</xref>, the diffraction peaks at a 2theta of 36.58, 42.40, 61.72, and 73.84 could be perfectly indexed to the lattices of Cu<sub>2</sub>O as (111), (200), (220), and 311) (JCPDS card No. 5-0667), respectively (<xref ref-type="bibr" rid="B52">Zhu et al., 2021</xref>). X-ray photoelectron spectroscopy (XPS) analysis was employed to further characterize the surface composition of the obtained Cu<sub>2</sub>O NPs. The XPS survey is shown in <xref ref-type="fig" rid="F1">Figure 1E</xref> and <xref ref-type="fig" rid="F1">Figure 1F</xref> for the high-resolution XPS spectrum of Cu 2p and the binding energy at 932.01 and 951.93&#xa0;eV corresponds to Cu 2p<sub>3/2</sub> and Cu 2p<sub>1/2</sub>, respectively, which are in good agreement with previous reports on Cu<sub>2</sub>O NPs (<xref ref-type="bibr" rid="B35">Pan et al., 2018</xref>; <xref ref-type="bibr" rid="B48">Zhang et al., 2020</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>
<bold>(A)</bold> SEM images of Cu<sub>2</sub>O NPs. The scale bar is 400&#xa0;nm. <bold>(B)</bold> Transmission electron microscopy (TEM) image of Cu<sub>2</sub>O NPs (n &#x2265; 3 randomly selected) and selected area electron diffraction (SAED) pattern (inset) showing polycrystalline structure. The scale bar is 200&#xa0;nm. <bold>(C)</bold> Elemental mapping of Cu<sub>2</sub>O NPs showing (ii) Cu in green, (iii) O in red, and (iv) overlapped Cu &#x2b; O, with HAADF in (i), Scale bar is 100&#xa0;nm. <bold>(D)</bold> XRD pattern of the Cu<sub>2</sub>O NPs. XPS spectra of the Cu<sub>2</sub>O NPs: <bold>(E)</bold> XPS Survey, and <bold>(F)</bold> Cu 2p.</p>
</caption>
<graphic xlink:href="fchem-10-861353-g001.tif"/>
</fig>
</sec>
<sec id="s1-2-2">
<title>The Peroxidase-Like Activity of Cu<sub>2</sub>O NPs</title>
<p>To demonstrate the prepared Cu<sub>2</sub>O NPs possess the peroxidase-like catalytic activity as peroxidase mimics, the oxidation discoloration of TMB in the presence of H<sub>2</sub>O<sub>2</sub> (TMB-H<sub>2</sub>O<sub>2</sub> system) was selected (<xref ref-type="bibr" rid="B29">Liang et al., 2022</xref>). In the presence of the Cu<sub>2</sub>O NPs and H<sub>2</sub>O<sub>2</sub>, the peroxidase substrate TMB could be catalyzed to the oxidation state of TMB (ox TMB) by OH radicals produced from H<sub>2</sub>O<sub>2</sub> and the solution will turn to blue (<xref ref-type="bibr" rid="B49">Zhang Z. et al., 2021</xref>). An electron paramagnetic resonance (EPR) analysis result shown in <xref ref-type="sec" rid="s8">Supplementary Figure S4</xref> (ESI&#x2020;) further illustrated the existence of hydroxyl radicals in the system. As the results displayed in <xref ref-type="fig" rid="F2">Figure 2A</xref>, an obvious absorption peak at 652&#xa0;nm was observed when Cu<sub>2</sub>O NPs catalyzed TMB to ox TMB, while only a weak signal appeared in the absence of Cu<sub>2</sub>O NPs, indicating the good catalytic property of the Cu<sub>2</sub>O NPs.</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>
<bold>(A)</bold> UV-Vis absorption spectra of different systems. Inset images: color changes of the corresponding system. <bold>(B)</bold> UV-Vis absorption spectra of various concentrations of glucose were analyzed based on the GOD-Cu<sub>2</sub>O NPs-TMB system (0&#x2013;10&#xa0;mM, the interval of 1.25&#xa0;mM from bottom to top). <bold>(C)</bold> The relationship plot and the linear curve (inset) between the concentration of glucose and the absorbance intensity at 652&#xa0;nm. The error bars denote the SD of three measurements. <bold>(D)</bold> Selectivity analysis of the assay by monitoring the absorbance change of glucose and its analogs. The error bars denote the SD of five measurements.</p>
</caption>
<graphic xlink:href="fchem-10-861353-g002.tif"/>
</fig>
</sec>
<sec id="s1-2-3">
<title>Catalytic Reactions of Glucose by Cu<sub>2</sub>O NPs</title>
<p>Glucose is a source of energy for daily activities of the human body, while abnormal concentrations of glucose in the blood could lead to many endocrine metabolic diseases, such as diabetes (<xref ref-type="bibr" rid="B40">Senior, 2021</xref>). Given the high catalytic activity of the Cu<sub>2</sub>O NPs as peroxidase mimics for the TMB-H<sub>2</sub>O<sub>2</sub> system, we constructed a glucose colorimetric biosensor based on the GOD-Cu<sub>2</sub>O NPs-TMB system. For glucose detection, the specific procedures are as follows. Firstly, GOD was used to oxidize glucose to gluconic acid and H<sub>2</sub>O<sub>2</sub> in PBS (pH 7.4). Then, the <italic>in situ</italic> generated H<sub>2</sub>O<sub>2</sub> was subsequently utilized to oxidize substrate TMB to chromogenic ox TMB with the Cu<sub>2</sub>O NPs in acetate buffer (pH 3.0). And the discoloration degree was recorded by microplate reader at the absorbance of 652&#xa0;nm, which could reflect the concentrations of glucose. Using this method, a series of concentrations of glucose were detected and the results were displayed in <xref ref-type="fig" rid="F2">Figure 2B</xref>. It can be observed that the color change was much more drastic as the concentration of glucose increased. Furthermore, a good linear relationship (<italic>R</italic>
<sup>2</sup> &#x3d; 0.999) between glucose concentration and the absorbance intensity of 652&#xa0;nm was obtained (<xref ref-type="fig" rid="F2">Figure 2C</xref>). The glucose colorimetric biosensor based on the GOD-Cu<sub>2</sub>O NPs-TMB system exhibited a broad linear range (0.28&#x2013;2.8&#xa0;mM) and the limit of detection (LOD) of the assay was 1.37&#xa0;&#xb5;M (S/N &#x3d; 3), which is comparable or even superior to many recently reported nanocomposites in the literature (<xref ref-type="bibr" rid="B50">Zhao et al., 2015</xref>; <xref ref-type="bibr" rid="B42">Tan et al., 2017</xref>; <xref ref-type="bibr" rid="B18">Huang Y. et al., 2019</xref>; <xref ref-type="bibr" rid="B23">Kang et al., 2019</xref>; <xref ref-type="bibr" rid="B43">Vinothkumar et al., 2019</xref>). The detailed information is shown in <xref ref-type="table" rid="T1">Table 1</xref>.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Comparison of linearity and LOD results for different materials-based glucose biosensors.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Material</th>
<th align="center">LOD (&#xb5;M)</th>
<th align="center">Linear Range (mM)</th>
<th align="center">Ref</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Mn<sub>2</sub>O<sub>3</sub> hollow NPs</td>
<td align="char" char=".">2.46</td>
<td align="center">0.01-0.1</td>
<td align="left">
<xref ref-type="bibr" rid="B23">Kang et al. (2019)</xref>
</td>
</tr>
<tr>
<td align="left">CeO<sub>2</sub>-TiO<sub>2</sub>
</td>
<td align="char" char=".">6.1</td>
<td align="center">0.01-0.5</td>
<td align="left">
<xref ref-type="bibr" rid="B50">Zhao et al. (2015)</xref>
</td>
</tr>
<tr>
<td align="left">CePO<sub>4</sub>-CeO<sub>2</sub>
</td>
<td align="char" char=".">4.12</td>
<td align="center">0-0.1</td>
<td align="left">
<xref ref-type="bibr" rid="B43">Vinothkumar et al. (2019)</xref>
</td>
</tr>
<tr>
<td align="left">CoO-OMC</td>
<td align="char" char=".">68</td>
<td align="center">0.1-5.0</td>
<td align="left">
<xref ref-type="bibr" rid="B13">Guo et al. (2019)</xref>
</td>
</tr>
<tr>
<td align="left">MnO<sub>2</sub> nanowires</td>
<td align="char" char=".">2</td>
<td align="center">0.01-1</td>
<td align="left">
<xref ref-type="bibr" rid="B14">Han et al. (2017)</xref>
</td>
</tr>
<tr>
<td align="left">EPC</td>
<td align="char" char=".">30</td>
<td align="center">0.05-10</td>
<td align="left">
<xref ref-type="bibr" rid="B37">Ren et al. (2020)</xref>
</td>
</tr>
<tr>
<td align="left">MoO<sub>3</sub>/C</td>
<td align="char" char=".">10</td>
<td align="center">0.02-0.5, 0.5-6.0</td>
<td align="left">
<xref ref-type="bibr" rid="B38">Ren et al. (2019)</xref>
</td>
</tr>
<tr>
<td align="left">Cu<sub>2</sub>O NPs</td>
<td align="char" char=".">1.37</td>
<td align="center">0.28-2.8</td>
<td align="left">This work</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>In the comparison with some other nanomaterial sensors for glucose detection (<xref ref-type="bibr" rid="B14">Han et al., 2017</xref>; <xref ref-type="bibr" rid="B13">Guo et al., 2019</xref>; <xref ref-type="bibr" rid="B38">Ren et al., 2019</xref>; <xref ref-type="bibr" rid="B37">Ren et al., 2020</xref>; <xref ref-type="bibr" rid="B28">Li et al., 2021</xref>; <xref ref-type="bibr" rid="B33">Liu et al., 2022</xref>), our proposed sensor shows a broad linear response in the range of 0.28&#x2013;2.8&#xa0;mM, which has wide prospects and great application values in the direct detection of glucose from human serum or other biological samples (<xref ref-type="bibr" rid="B10">Gluchowska et al., 2021</xref>). Currently, most glucose detection methods with low LOD can only realize standard samples analysis, while our work greatly achieved glucose detection from 31 serum samples. Besides, compared to most of the complicated nanoenzymes (<xref ref-type="bibr" rid="B9">Dong et al., 2016</xref>; <xref ref-type="bibr" rid="B12">Guo and Li, 2019</xref>; <xref ref-type="bibr" rid="B47">Zhang X. et al., 2021</xref>; <xref ref-type="bibr" rid="B30">Liu et al., 2021</xref>), an obvious advantage of Cu<sub>2</sub>O NPs as peroxidase mimic is their simple preparation and lower cost. Therefore, the prepared Cu<sub>2</sub>O NPs should be easily popularized and used in glucose detection.</p>
<p>In addition, selectivity was regarded as another major issue in analysis. We chose several carbohydrates (Cel, Fru, Gal, Asp, and Ala) to verify the selectivity of the assay for glucose detection (<xref ref-type="bibr" rid="B8">Dong et al., 2021</xref>). As shown in <xref ref-type="fig" rid="F2">Figure 2D</xref>, different from glucose, no significant absorbance was observed from Cel, Fru, Gal, Asp, and Ala, demonstrating that the proposed system has excellent specificity for glucose analysis.</p>
</sec>
<sec id="s1-2-4">
<title>Cu<sub>2</sub>O NPs Based LDI MS Analysis of Small Molecules</title>
<p>LDI MS presents high sensitivity, accuracy, resolution, and throughput in molecular analysis, especially for metabolites at the low molecular weight (<xref ref-type="bibr" rid="B26">Kulkarni et al., 2021</xref>). However, the efficiency of LDI MS relies on the matrix materials with designed molecular interfaces due to the size-exclusive effect and specific affinity (<xref ref-type="bibr" rid="B7">Ding et al., 2022</xref>). In this work, the optimized Cu<sub>2</sub>O NPs could not only be used as peroxidase mimic but also be employed as the matrix for LDI MS analysis. To testify the LDI MS performance based on Cu<sub>2</sub>O NPs, the typical small molecules were analyzed containing alanine, glucose, cellobiose (0.5&#xa0;&#xb5;L, 1&#xa0;mg/ml, respectively). From the mass spectra in <xref ref-type="fig" rid="F3">Figure 3A</xref>, we could clearly observe the peaks at m/z of 112, 203 and 365, corresponding to [Ala &#x2b; Na]<sup>&#x2b;</sup>, [Glu &#x2b; Na]<sup>&#x2b;</sup> and [Cel &#x2b; Na]<sup>&#x2b;</sup>, respectively. Notably, the background signal from Cu<sub>2</sub>O NPs could not affect the detection of the above molecules.</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Cu<sub>2</sub>O NPs assisted LDI MS for analysis of <bold>(A)</bold> Cu<sub>2</sub>O NPs as control and some small metabolites (500&#xa0;nL, 7&#xa0;mM for each). <bold>(B)</bold> mixing liquid of alanine, leucine, aspartic acid, arginine, and glucose in water and salt solution, as well as metabolic fingerprinting of serum (500&#xa0;nL) from healthy control and kidney cancer patient. The red asterisks represent alanine, leucine, aspartic acid, arginine, and glucose at the m/z peaks of 127, 154, 178, 199, and 203, respectively.</p>
</caption>
<graphic xlink:href="fchem-10-861353-g003.tif"/>
</fig>
<p>Meanwhile, we also tested the Cu<sub>2</sub>O NPs based LDI MS for analysis of the mixing liquid in water and salt solution. As shown in <xref ref-type="fig" rid="F3">Figure 3B</xref>, the peaks at m/z of 127, 154, 178, 199 and 203 were assigned to [Cho &#x2b; Na]<sup>&#x2b;</sup>, [Asp &#x2b; Na]<sup>&#x2b;</sup>, [DA &#x2b; Na]<sup>&#x2b;</sup>, [Vc &#x2b; Na]<sup>&#x2b;</sup> and [Glu &#x2b; Na]<sup>&#x2b;</sup>, respectively, even in the interference of salt. Such results demonstrated the capability of multiple metabolites analysis and the good salts tolerance using Cu<sub>2</sub>O NP assisted LDI MS, which is hopefully applied in practical applications without pretreatment (<xref ref-type="bibr" rid="B17">Huang et al., 2017</xref>). To further evaluate the feasibility and practical applicability of glucose detection, serum samples from healthy adults and patients with kidney disease were tested directly by the Cu<sub>2</sub>O NPs assisted LDI MS. It could be apparently seen the peaks of glucose, indicating that our proposed system possesses the potential possibility of analyzing real blood samples.</p>
</sec>
<sec id="s1-2-5">
<title>Cu<sub>2</sub>O NPs Based LDI MS Quantitative Analysis of Glucose</title>
<p>Encouraged by the good performance and salt tolerability of Cu<sub>2</sub>O NPs assisted LDI MS analysis of metabolites, we further detected glucose from serum samples with this method. For accurate quantitative analysis of glucose by LDI MS, cellobiose with a similar ionization efficiency to glucose was selected as internal standard (IS). Firstly, different concentrations of glucose ranging from 0.56 to 5.6&#xa0;mM were mixed with cellobiose (2.9&#xa0;mM) and analyzed by Cu<sub>2</sub>O NP based LDI MS. The results in <xref ref-type="fig" rid="F4">Figure 4A</xref> displayed the peaks of glucose at m/z of 203 and cellobiose at m/z of 365. Moreover, the relative intensity of glucose (<italic>I</italic>
<sub>
<italic>203</italic>
</sub>
<italic>/I</italic>
<sub>
<italic>365</italic>
</sub>) was increased as the concentration of glucose increased and a good linear relationship (<italic>R</italic>
<sup>2</sup> &#x3d; 0.997) between the <italic>I</italic>
<sub>
<italic>203</italic>
</sub>
<italic>/I</italic>
<sub>
<italic>365</italic>
</sub> and the concentration of glucose from 0 to 3.36&#xa0;mM was obtained in <xref ref-type="fig" rid="F4">Figure 4B</xref>.</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>
<bold>(A)</bold> LDI MS spectra of a gradient concentration of glucose and cellobiose (IS). <bold>(B)</bold> The relationship plot and the linear curve (inset) of the relative peak intensity of glucose (<italic>I</italic>
<sub>
<italic>203</italic>
</sub>
<italic>/I</italic>
<sub>
<italic>365</italic>
</sub>) and the concentrations of glucose. The error bars denote the SD of three measurements. <bold>(C)</bold> Dual-mode glucose detection results of 31 serum samples. The error bars denote the SD of five measurements.</p>
</caption>
<graphic xlink:href="fchem-10-861353-g004.tif"/>
</fig>
</sec>
<sec id="s1-2-6">
<title>Dual-Mode Quantitative Analysis of Glucose in Serum</title>
<p>Considering that glucose level in serum is associated with various diseases in the clinic, quantitative evaluation of glucose from serum is meaningful. To demonstrate the feasibility of dual-mode quantitative of glucose from serum, 31 serum samples were prepared and analyzed by both colorimetric and LDI MS assay based on Cu<sub>2</sub>O NPs shown in <xref ref-type="fig" rid="F4">Figure 4C</xref>. The glucose concentrations of serum samples were distributed from 4.12 to 7.26&#xa0;mM, basically in line with the range of normal blood glucose values in healthy people (3.61&#x2013;7.77&#xa0;mM). Notably, the difference between the two methods was less than 0.5&#xa0;mM with a correlation coefficient of 0.902 in <xref ref-type="sec" rid="s8">Supplementary Figure S5</xref> (ESI&#x2020;).</p>
</sec>
</sec>
</sec>
<sec sec-type="conclusion" id="s2">
<title>Conclusion</title>
<p>In summary, we developed a dual-mode Cu<sub>2</sub>O NPs based biosensor for glucose analysis by integrating colorimetric assay and LDI MS. The Cu<sub>2</sub>O NPs were simply prepared and low-cost, which presented excellent peroxidase-like activity and assisted LDI MS analysis of metabolites. The Cu<sub>2</sub>O NP based dual-mode biosensor was successfully applied in visual and quantitative analysis of glucose from serum, demonstrating the potential values in clinical diseases diagnostics and monitoring.</p>
</sec>
</body>
<back>
<sec id="s3">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s8">Supplementary Material</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s4">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by The Medical Ethics Committee of Tianjin Third Central Hospital. The patients/participants provided their written informed consent to participate in this study.</p>
</sec>
<sec id="s5">
<title>Author Contributions</title>
<p>KL and XX contributed to the work; YW, FC, and KQ planned and designed the work with KL and XX; KL and XX performed most of the experiment and drafted the paper; WL and SY characterized and analyzed the materials; LH helped to prepared the material; ST collected the blood samples; ZZ helped to analyze the data.</p>
</sec>
<sec sec-type="COI-statement" id="s6">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
<p>The reviewer LQ declared a past co-authorship with the author KQ to the handling editor.</p>
</sec>
<sec sec-type="disclaimer" id="s7">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<ack>
<p>The authors gratefully acknowledge the financial support from Projects 2021YFA0910100, 2021YFF0703500, 2017YFE0124400, and 2017YFC0909000 by National Key R&#x26;D Program of China, Project 81971771 by NSFC, and Project 2021-01-07-00-02-E00083 by Shanghai Institutions of Higher Learning. This work was also sponsored by the Shanghai Rising-Star Programme (19QA1404800), Innovation Group Project of Shanghai Municipal Health Comission (2019CXJQ03), Innovation Research Plan by the Shanghai Municipal Education Commission (ZXWF082101), National Research Center for Translational Medicine Shanghai (TMSK-2021-124, NRCTM(SH)-2021-06), and Medical-Engineering Joint Funds of Shanghai Jiao Tong University (YG2019QNA44, YG2021ZD09, YG2022QN107).</p>
</ack>
<sec id="s8">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fchem.2022.861353/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fchem.2022.861353/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet1.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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