Pub Date : 2025-03-25DOI: 10.1021/acssensors.5c00525
Fangfang Yang, Jieyu Zhang, Li Wang, Shufeng Liu
Considering the intrinsic importance of alkaline phosphatase (ALP) as a biomarker in disease monitoring and as a mostly widely used biolabel for signal transmission in bioanalysis, the development of a new ALP assay method is highly pursued. Herein, a well-known ALP-catalyzed silver deposition reaction onto gold nanoparticles (Au NPs) was developed into a single-particle-collision-based electrochemical biosensor. ALP-catalyzed dephosphorylation of ascorbic acid 2-phosphate (AA-P) resulted in ascorbic acid (AA), which in turn reduced the silver ion to form a silver nanoshell on the surface of Au NPs (Au@Ag NPs). The generated Au@Ag NPs could stochastically collide with the microelectrode to produce transient current spikes. The collision frequency and charge could concurrently indicate the amount of produced Au@Ag NPs and then the ALP activity. Thus, a new single-particle collision-based electrochemical biosensing platform for ALP was constructed. It operates homogeneously and does not require electrode modification, nanoparticle biofunctionalization, and washing and separation steps. It showed good detection sensitivity toward ALP activity with a quantification limit of 2 mU/mL in 10 μL. The background-free feature endows it with absolute selectivity. It could also be used for inhibitor screening and applied for the ALP assay in the serum. In addition, the proposed collision-based electrochemical strategy was developed for a new enzyme-linked immunosorbent assay. With the human immunoglobulin G (IgG) as a model target, it could effortlessly evaluate 5 ng/mL analytes. It thus opens a new avenue toward the development of single-particle collision-based electrochemical biosensors for a wide range of applications in disease diagnosis and bioanalysis.
{"title":"Single-Particle Collision Electrochemical Biosensor Developed by a Typical Alkaline Phosphatase-Catalyzed Silver Deposition Reaction","authors":"Fangfang Yang, Jieyu Zhang, Li Wang, Shufeng Liu","doi":"10.1021/acssensors.5c00525","DOIUrl":"https://doi.org/10.1021/acssensors.5c00525","url":null,"abstract":"Considering the intrinsic importance of alkaline phosphatase (ALP) as a biomarker in disease monitoring and as a mostly widely used biolabel for signal transmission in bioanalysis, the development of a new ALP assay method is highly pursued. Herein, a well-known ALP-catalyzed silver deposition reaction onto gold nanoparticles (Au NPs) was developed into a single-particle-collision-based electrochemical biosensor. ALP-catalyzed dephosphorylation of ascorbic acid 2-phosphate (AA-P) resulted in ascorbic acid (AA), which in turn reduced the silver ion to form a silver nanoshell on the surface of Au NPs (Au@Ag NPs). The generated Au@Ag NPs could stochastically collide with the microelectrode to produce transient current spikes. The collision frequency and charge could concurrently indicate the amount of produced Au@Ag NPs and then the ALP activity. Thus, a new single-particle collision-based electrochemical biosensing platform for ALP was constructed. It operates homogeneously and does not require electrode modification, nanoparticle biofunctionalization, and washing and separation steps. It showed good detection sensitivity toward ALP activity with a quantification limit of 2 mU/mL in 10 μL. The background-free feature endows it with absolute selectivity. It could also be used for inhibitor screening and applied for the ALP assay in the serum. In addition, the proposed collision-based electrochemical strategy was developed for a new enzyme-linked immunosorbent assay. With the human immunoglobulin G (IgG) as a model target, it could effortlessly evaluate 5 ng/mL analytes. It thus opens a new avenue toward the development of single-particle collision-based electrochemical biosensors for a wide range of applications in disease diagnosis and bioanalysis.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"22 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143695236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-25DOI: 10.1021/acssensors.4c03116
Ke-Peng Lai, Bo-Yu Liu, Wei-Lung Tseng, Hwang-Shang Kou, Chun-Chi Wang
The optimal sequence for synthesizing copper nanoclusters is a promising research area. Initially, random dsDNA sequences yielded low fluorescence intensity, which constrained visual detection under UV light. Poly-AT dsDNA sequences later produced visible fluorescence, but it caused significant interference in negative samples when combined with gene amplification techniques. This interference occurs because the single-stranded poly-AT primer can self-anneal into a double-stranded AT sequence, efficiently synthesizing copper nanoclusters. To mitigate this, we designed a poly-AAT sequence at the primer’s 5′ end, creating a single base pair mismatch every three nucleotides during self-annealing. This adjustment reduced synthesis efficiency of copper nanoclusters in negative samples, improving the visual distinction between negative and positive results. We applied this method to identify the HLA-B*5801 gene, thereby demonstrating its efficacy even within a GC-rich region of human genomic DNA. Our method showed 100% agreement with a commercial qPCR kit, with results distinguishable under UV light. We conclude that the poly-AAT sequence is more suitable for integrating copper nanoclusters synthesis with nucleic acid amplification detection techniques, with potential applications in microelectronics, biosensing, and catalysis.
{"title":"Novel Primer Design for Significantly Reducing Fluorescent Interferences in the Synthesis of DNA-Templated Copper Nanoclusters for the Detection of the HLA-B*5801 Gene","authors":"Ke-Peng Lai, Bo-Yu Liu, Wei-Lung Tseng, Hwang-Shang Kou, Chun-Chi Wang","doi":"10.1021/acssensors.4c03116","DOIUrl":"https://doi.org/10.1021/acssensors.4c03116","url":null,"abstract":"The optimal sequence for synthesizing copper nanoclusters is a promising research area. Initially, random dsDNA sequences yielded low fluorescence intensity, which constrained visual detection under UV light. Poly-AT dsDNA sequences later produced visible fluorescence, but it caused significant interference in negative samples when combined with gene amplification techniques. This interference occurs because the single-stranded poly-AT primer can self-anneal into a double-stranded AT sequence, efficiently synthesizing copper nanoclusters. To mitigate this, we designed a poly-AAT sequence at the primer’s 5′ end, creating a single base pair mismatch every three nucleotides during self-annealing. This adjustment reduced synthesis efficiency of copper nanoclusters in negative samples, improving the visual distinction between negative and positive results. We applied this method to identify the <i>HLA-B*</i>5801 gene, thereby demonstrating its efficacy even within a GC-rich region of human genomic DNA. Our method showed 100% agreement with a commercial qPCR kit, with results distinguishable under UV light. We conclude that the poly-AAT sequence is more suitable for integrating copper nanoclusters synthesis with nucleic acid amplification detection techniques, with potential applications in microelectronics, biosensing, and catalysis.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"61 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143703488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-24DOI: 10.1021/acssensors.4c03304
Der Vang, Jonathan Pahren, Emily Duderstadt, Frances Joan Alvarez, Manisha Sheokand, Justin A. Caserta, Tom Cambron, Pietro Strobbia
Antibiotic and antibacterial-resistant bacteria continue to pose a global-health threat. Understanding the mechanism of action (MoA) of antibacterial agents is crucial for developing precise and novel treatment methods. Traditionally, the MoA of a novel treatment is studied with genome sequencing and mass spectrometry, which are both labor-intensive and costly. In contrast, surface-enhanced Raman spectroscopy (SERS) provides a rapid, sensitive, and noninvasive alternative for analyzing bacterial molecular responses to antibacterial agents. In this study, we employed SERS to analyze the effects of various antibacterial agents on Escherichia coli. We treated E. coli cultures with agents that have different known MoAs, including oxidative stress, metabolic disruption, and membrane lysis. Through partial least-squares (PLS) analysis, we correlated changes in the SERS spectra with bacterial viability, achieving high predictive accuracy (R2 > 0.98). From the PLS models, we were able to extract variable importance projection scores, which were used to identify the MoA in subsets of the data. Our results revealed distinct spectral signatures associated with each MoA, demonstrating the potential of SERS to differentiate between different antibacterial treatments. This study highlights the feasibility of using SERS combined with multivariate analysis to rapidly characterize the molecular effects of antibacterial agents even with smaller data sets. By providing a real-time method for monitoring bacterial responses, this SERS approach could accelerate the discovery of novel antibacterial therapies while reducing dependency on more time-consuming and expensive analytical techniques.
{"title":"Surface-Enhanced Raman Spectroscopy and Multivariate Analysis for Elucidating Mechanisms of Action in Antibacterial Agents","authors":"Der Vang, Jonathan Pahren, Emily Duderstadt, Frances Joan Alvarez, Manisha Sheokand, Justin A. Caserta, Tom Cambron, Pietro Strobbia","doi":"10.1021/acssensors.4c03304","DOIUrl":"https://doi.org/10.1021/acssensors.4c03304","url":null,"abstract":"Antibiotic and antibacterial-resistant bacteria continue to pose a global-health threat. Understanding the mechanism of action (MoA) of antibacterial agents is crucial for developing precise and novel treatment methods. Traditionally, the MoA of a novel treatment is studied with genome sequencing and mass spectrometry, which are both labor-intensive and costly. In contrast, surface-enhanced Raman spectroscopy (SERS) provides a rapid, sensitive, and noninvasive alternative for analyzing bacterial molecular responses to antibacterial agents. In this study, we employed SERS to analyze the effects of various antibacterial agents on <i>Escherichia coli</i>. We treated <i>E. coli</i> cultures with agents that have different known MoAs, including oxidative stress, metabolic disruption, and membrane lysis. Through partial least-squares (PLS) analysis, we correlated changes in the SERS spectra with bacterial viability, achieving high predictive accuracy (<i>R</i><sup>2</sup> > 0.98). From the PLS models, we were able to extract variable importance projection scores, which were used to identify the MoA in subsets of the data. Our results revealed distinct spectral signatures associated with each MoA, demonstrating the potential of SERS to differentiate between different antibacterial treatments. This study highlights the feasibility of using SERS combined with multivariate analysis to rapidly characterize the molecular effects of antibacterial agents even with smaller data sets. By providing a real-time method for monitoring bacterial responses, this SERS approach could accelerate the discovery of novel antibacterial therapies while reducing dependency on more time-consuming and expensive analytical techniques.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"13 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143695234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-24DOI: 10.1021/acssensors.4c02955
Xukun Wang, Xiaoyi Xu, Tingting Zhou, Tong Zhang
Carbon dioxide (CO2) detection is indispensable for monitoring climate change, ensuring air quality, managing industrial processes, and safeguarding human health. Nevertheless, the chemical inertness and stability of CO2 pose significant challenges in advancing detection technologies in practical applications. In order to overcome these challenges, nanoscale MOF-74 metal–organic frameworks (MOFs) functionalized with alkali metals (Li, Na, and K) have been synthesized for the effective detection of the CO2 gas. The sensing results indicate that the Li–Mg-MOF-74-based quartz crystal microbalance (QCM) CO2 sensors demonstrate excellent properties, such as very high sensitivity, rapid response/recovery time (84 s/69 s), broad detection range (300–10000 ppm), and remarkable selectivity at room temperature. The enhanced performance benefits from the increased electrostatic force and Lewis’s acidity resulting from alkali metal ions (Li+) and open metal sites (Mg2+). In addition, the equilibrium constant of CO2 on the sensor surface was calculated by the Langmuir adsorption isotherm model, revealing spontaneous and robust adsorption behavior. These results indicate that alkali-metal-modified Mg-MOF-74 materials have great potential for practical CO2 detection and provide a feasible solution for the design of high-performance, room-temperature CO2 sensing platforms.
{"title":"Room-Temperature CO2 Monitoring Platform Enabled by Alkali Metal Functionalization of a Mg-MOF-74-Based QCM Sensor","authors":"Xukun Wang, Xiaoyi Xu, Tingting Zhou, Tong Zhang","doi":"10.1021/acssensors.4c02955","DOIUrl":"https://doi.org/10.1021/acssensors.4c02955","url":null,"abstract":"Carbon dioxide (CO<sub>2</sub>) detection is indispensable for monitoring climate change, ensuring air quality, managing industrial processes, and safeguarding human health. Nevertheless, the chemical inertness and stability of CO<sub>2</sub> pose significant challenges in advancing detection technologies in practical applications. In order to overcome these challenges, nanoscale MOF-74 metal–organic frameworks (MOFs) functionalized with alkali metals (Li, Na, and K) have been synthesized for the effective detection of the CO<sub>2</sub> gas. The sensing results indicate that the Li–Mg-MOF-74-based quartz crystal microbalance (QCM) CO<sub>2</sub> sensors demonstrate excellent properties, such as very high sensitivity, rapid response/recovery time (84 s/69 s), broad detection range (300–10000 ppm), and remarkable selectivity at room temperature. The enhanced performance benefits from the increased electrostatic force and Lewis’s acidity resulting from alkali metal ions (Li<sup>+</sup>) and open metal sites (Mg<sup>2+</sup>). In addition, the equilibrium constant of CO<sub>2</sub> on the sensor surface was calculated by the Langmuir adsorption isotherm model, revealing spontaneous and robust adsorption behavior. These results indicate that alkali-metal-modified Mg-MOF-74 materials have great potential for practical CO<sub>2</sub> detection and provide a feasible solution for the design of high-performance, room-temperature CO<sub>2</sub> sensing platforms.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"183 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-24DOI: 10.1021/acssensors.4c02197
Lin Zhang, Bo He, Yi Li, Jiangni Yun, Linwei Yao, Hongyuan Zhao, Junfeng Yan, Wu Zhao, Zhiyong Zhang
Using density functional theory and the nonequilibrium Green function method, the interaction between two-dimensional nitrogen-doped graphyne (N-GY) and volatile organic compounds (ethanol, ethylene glycol, acetone, and toluene) was investigated, and the potential application of N-GY for sensing volatile biomarkers exhaled by human breath was explored. The N-GY is a direct band gap semiconductor with a band gap width of 0.408 eV. The bottom of the conduction band and the top of the valence band are both located at the Γ point. All target volatile organic compounds (VOCs) are in physical adsorption states. In order to verify the sensing mechanism of VOCs, Bader charge transfer, adsorption distance, work function, electron localization function, charge density difference, energy band structure, and density of states were analyzed. At the same time, the I–V relationship of VOCs molecules before and after adsorption was calculated by using the NEGF method. The results show that at 0.5 V bias voltage under the armchair direction, N-GY can well distinguish four gas molecules and has the highest sensitivity for acetone with a sensitivity of 81%. Therefore, the N-GY monolayer is a potential candidate material for analyzing VOCs exhaled by the human body as well as for early screening of diabetes.
{"title":"Nitrogen-Doped Graphyne as a Promising Material for Sensing Volatile Organic Compounds in Human Breath","authors":"Lin Zhang, Bo He, Yi Li, Jiangni Yun, Linwei Yao, Hongyuan Zhao, Junfeng Yan, Wu Zhao, Zhiyong Zhang","doi":"10.1021/acssensors.4c02197","DOIUrl":"https://doi.org/10.1021/acssensors.4c02197","url":null,"abstract":"Using density functional theory and the nonequilibrium Green function method, the interaction between two-dimensional nitrogen-doped graphyne (N-GY) and volatile organic compounds (ethanol, ethylene glycol, acetone, and toluene) was investigated, and the potential application of N-GY for sensing volatile biomarkers exhaled by human breath was explored. The N-GY is a direct band gap semiconductor with a band gap width of 0.408 eV. The bottom of the conduction band and the top of the valence band are both located at the Γ point. All target volatile organic compounds (VOCs) are in physical adsorption states. In order to verify the sensing mechanism of VOCs, Bader charge transfer, adsorption distance, work function, electron localization function, charge density difference, energy band structure, and density of states were analyzed. At the same time, the <i>I</i>–<i>V</i> relationship of VOCs molecules before and after adsorption was calculated by using the NEGF method. The results show that at 0.5 V bias voltage under the armchair direction, N-GY can well distinguish four gas molecules and has the highest sensitivity for acetone with a sensitivity of 81%. Therefore, the N-GY monolayer is a potential candidate material for analyzing VOCs exhaled by the human body as well as for early screening of diabetes.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"25 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-24DOI: 10.1021/acssensors.4c02789
Jiaqing Zhu, Lechen Chen, Wangze Ni, Weiwei Cheng, Zhi Yang, Shusheng Xu, Tao Wang, Bowei Zhang, Fuzhen Xuan
Gas sensor arrays designed for pattern recognition face persistent challenges in achieving high sensitivity and selectivity for multiple volatile organic compounds (VOCs), particularly under varying environmental conditions. To address these limitations, we developed multimodal intelligent MEMS gas sensors by precisely tailoring the nanocomposite ratio of NiO and ZnO components. These sensors demonstrate enhanced responses to ethylene glycol (EG) and limonene (LM) at different operating temperatures, demonstrating material-specific selectivity. Additionally, a multitask deep learning model is employed for real-time, quantitative detection of VOCs, accurately predicting their concentration and type. These results showcase the effectiveness of combining material optimization with advanced algorithms for real-world VOCs detection, advancing the field of odor analysis tools.
{"title":"NiO/ZnO Nanocomposites for Multimodal Intelligent MEMS Gas Sensors.","authors":"Jiaqing Zhu, Lechen Chen, Wangze Ni, Weiwei Cheng, Zhi Yang, Shusheng Xu, Tao Wang, Bowei Zhang, Fuzhen Xuan","doi":"10.1021/acssensors.4c02789","DOIUrl":"https://doi.org/10.1021/acssensors.4c02789","url":null,"abstract":"<p><p>Gas sensor arrays designed for pattern recognition face persistent challenges in achieving high sensitivity and selectivity for multiple volatile organic compounds (VOCs), particularly under varying environmental conditions. To address these limitations, we developed multimodal intelligent MEMS gas sensors by precisely tailoring the nanocomposite ratio of NiO and ZnO components. These sensors demonstrate enhanced responses to ethylene glycol (EG) and limonene (LM) at different operating temperatures, demonstrating material-specific selectivity. Additionally, a multitask deep learning model is employed for real-time, quantitative detection of VOCs, accurately predicting their concentration and type. These results showcase the effectiveness of combining material optimization with advanced algorithms for real-world VOCs detection, advancing the field of odor analysis tools.</p>","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":" ","pages":""},"PeriodicalIF":8.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143690390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-24DOI: 10.1021/acssensors.4c03637
Claire M. S. Michielsen, Yu-Ting Lin, Junhong Yan, Arthur M. de Jong, Menno W. J. Prins
Sensing technologies for the continuous monitoring of protein concentrations are important for understanding time-dependent behaviors of biological systems and for controlling bioprocesses. We present a continuous sensing methodology based on tethered particle motion (t-BPM) that utilizes fast-dissociating antibody fragments (Fabs) for continuous protein monitoring. A competition-based t-BPM sensor was developed and characterized utilizing custom-made Fabs. The sensing concept was demonstrated for lactoferrin, an 80 kDa iron-binding glycoprotein that is part of the innate immune response. Thirteen Fabs were compared using free particle motion sensing as well as surface plasmon resonance, of which six Fabs showed rapid association and dissociation. The integration of the Fabs into the t-BPM sensor enabled nanomolar lactoferrin detection in both buffer solutions and milk matrices over tens of hours. This work demonstrates how continuous protein sensing can be realized using fast-dissociating antibodies in a competitive sensor format.
{"title":"Continuous Protein Sensing Using Fast-Dissociating Antibody Fragments in Competition-Based Biosensing by Particle Motion","authors":"Claire M. S. Michielsen, Yu-Ting Lin, Junhong Yan, Arthur M. de Jong, Menno W. J. Prins","doi":"10.1021/acssensors.4c03637","DOIUrl":"https://doi.org/10.1021/acssensors.4c03637","url":null,"abstract":"Sensing technologies for the continuous monitoring of protein concentrations are important for understanding time-dependent behaviors of biological systems and for controlling bioprocesses. We present a continuous sensing methodology based on tethered particle motion (t-BPM) that utilizes fast-dissociating antibody fragments (Fabs) for continuous protein monitoring. A competition-based t-BPM sensor was developed and characterized utilizing custom-made Fabs. The sensing concept was demonstrated for lactoferrin, an 80 kDa iron-binding glycoprotein that is part of the innate immune response. Thirteen Fabs were compared using free particle motion sensing as well as surface plasmon resonance, of which six Fabs showed rapid association and dissociation. The integration of the Fabs into the t-BPM sensor enabled nanomolar lactoferrin detection in both buffer solutions and milk matrices over tens of hours. This work demonstrates how continuous protein sensing can be realized using fast-dissociating antibodies in a competitive sensor format.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"18 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-24DOI: 10.1021/acssensors.4c03460
Yiwei Han, Yanbing Wu, Jianyang Lu, Qizhi Liang, Xinyu Qu, Jinlong Li, Peng Miao, Jie Yang, Genxi Li
Bifunctional protein complexes play essential roles in the biomedical field, particularly in biochemical analysis. However, traditional protein engineering methods (e.g., gene fusion and covalent modification) suffer limitations of complex design, low efficiency, and lack of universality. In this work, we propose a straightforward, efficient, and universal strategy for the preparation of a bifunctional protein complex. Green fluorescent protein (GFP) is engineered using the protein purification tag and coordinate-mediated peptide assembly, facilitating both target recognition and signal reporting. It is further applied to develop a sensitive biosensor for the detection of a target protein. Due to the substantial loading of functional components within the complex, the proposed biosensor demonstrates a simple procedure and high sensitivity. Furthermore, the analysis of clinical samples has been achieved to distinguish breast cancer patients from healthy individuals. Given the abundance of histidine-tagged proteins and the customizable nature of peptides, this work is expected to provide a valuable concept for bifunctional protein engineering in biosensing and broader biomedical applications.
{"title":"Construction of Bifunctional Protein/Peptide Complex for Sensitive Detection of Transglutaminase 2","authors":"Yiwei Han, Yanbing Wu, Jianyang Lu, Qizhi Liang, Xinyu Qu, Jinlong Li, Peng Miao, Jie Yang, Genxi Li","doi":"10.1021/acssensors.4c03460","DOIUrl":"https://doi.org/10.1021/acssensors.4c03460","url":null,"abstract":"Bifunctional protein complexes play essential roles in the biomedical field, particularly in biochemical analysis. However, traditional protein engineering methods (e.g., gene fusion and covalent modification) suffer limitations of complex design, low efficiency, and lack of universality. In this work, we propose a straightforward, efficient, and universal strategy for the preparation of a bifunctional protein complex. Green fluorescent protein (GFP) is engineered using the protein purification tag and coordinate-mediated peptide assembly, facilitating both target recognition and signal reporting. It is further applied to develop a sensitive biosensor for the detection of a target protein. Due to the substantial loading of functional components within the complex, the proposed biosensor demonstrates a simple procedure and high sensitivity. Furthermore, the analysis of clinical samples has been achieved to distinguish breast cancer patients from healthy individuals. Given the abundance of histidine-tagged proteins and the customizable nature of peptides, this work is expected to provide a valuable concept for bifunctional protein engineering in biosensing and broader biomedical applications.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"33 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143695233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-24DOI: 10.1021/acssensors.5c00015
Eunji Choi, Tae-In Jeong, Thanh Mien Nguyen, Alexander Gliserin, Jimin Lee, Gyeong-Ha Bak, San Kim, Sehyeon Kim, Jin-Woo Oh, Seungchul Kim
Chemical vapor sensors are essential for various fields, including medical diagnostics and environmental monitoring. Notably, the identification of components in unknown gas mixtures has great potential for noninvasive diagnosis of diseases such as lung cancer. However, current gas identification techniques, despite the development of electronic nose-based sensor platforms, still lack sufficient classification accuracy for mixed gases. In our previous study, we introduced multichannel hierarchical analysis using a time-resolved hyperspectral system to address the spectral ambiguity of conventional RGB sensor-based colorimetric e-noses. Here, we demonstrate the identification of mixed gas components through time-resolved line hyperspectral measurements with an eight-colorimetric sensor array that uses genetically engineered M13 bacteriophages as gas-selective colorimetric sensors. The time-dependent spectral variations induced by mixed gas in the different colorimetric sensors are converted into a hyperspectral three-dimensional (3D) data cube. For efficient machine learning classification, the data cube was converted into a multichannel spectrogram by applying a novel data processing method, including dimensionality reduction and a block average filter to reduce high-dimensional complexity and improve the signal-to-noise ratio. A convolution filter was then used for hierarchical analysis of the multichannel spectrogram, effectively capturing the complex gas-induced spectral patterns and temporal dynamics. Our study demonstrates a classification accuracy of 93.9% for pure and mixed gases of acetone, ethanol, and xylene at a low concentration of 2 ppm.
{"title":"Identification of Gas Mixture Components with Multichannel Hierarchical Analysis of Time-Resolved Hyperspectral Data","authors":"Eunji Choi, Tae-In Jeong, Thanh Mien Nguyen, Alexander Gliserin, Jimin Lee, Gyeong-Ha Bak, San Kim, Sehyeon Kim, Jin-Woo Oh, Seungchul Kim","doi":"10.1021/acssensors.5c00015","DOIUrl":"https://doi.org/10.1021/acssensors.5c00015","url":null,"abstract":"Chemical vapor sensors are essential for various fields, including medical diagnostics and environmental monitoring. Notably, the identification of components in unknown gas mixtures has great potential for noninvasive diagnosis of diseases such as lung cancer. However, current gas identification techniques, despite the development of electronic nose-based sensor platforms, still lack sufficient classification accuracy for mixed gases. In our previous study, we introduced multichannel hierarchical analysis using a time-resolved hyperspectral system to address the spectral ambiguity of conventional RGB sensor-based colorimetric e-noses. Here, we demonstrate the identification of mixed gas components through time-resolved line hyperspectral measurements with an eight-colorimetric sensor array that uses genetically engineered M13 bacteriophages as gas-selective colorimetric sensors. The time-dependent spectral variations induced by mixed gas in the different colorimetric sensors are converted into a hyperspectral three-dimensional (3D) data cube. For efficient machine learning classification, the data cube was converted into a multichannel spectrogram by applying a novel data processing method, including dimensionality reduction and a block average filter to reduce high-dimensional complexity and improve the signal-to-noise ratio. A convolution filter was then used for hierarchical analysis of the multichannel spectrogram, effectively capturing the complex gas-induced spectral patterns and temporal dynamics. Our study demonstrates a classification accuracy of 93.9% for pure and mixed gases of acetone, ethanol, and xylene at a low concentration of 2 ppm.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"90 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143695237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-24DOI: 10.1021/acssensors.4c03510
Xinxia Li, Xinyuan Tang, Zihan Wang, Ya Xu, Weiqiang Wei, Yan He, Huifang Li
Single-walled carbon nanotubes (SWCNTs) are a promising candidate material for detecting harmful gases due to their unique advanced character, but their gas-sensing properties still need to be improved. With the aim of exploring more effective modulation ways to improve the gas-sensing behavior of SWCNTs, the surface doping effects of the sodium (Na) atom, a typical n-type dopant, and tetracyanoethylene (TCNE), a typical p-type dopant, on the electronic and sensing properties of (7,3), (6,5), and (7,5) SWCNTs for NO2, SO2, NO, CO2, H2S, and NH3 were examined theoretically with density functional theory (DFT) calculations. It is found that the decoration of SWCNTs with Na/TCNE dopant is energetically favorable, with enhanced/lowered frontier energy levels. Therefore, the energy-level alignment among the frontier orbitals of SWCNTs and gas molecules can be regulated effectively. The interfacial charge transfer that occurs from the occupied valence band maximum (VBM) of SWCNTs to the empty lowest unoccupied molecular orbital (LUMO) of gas molecules is much more significant than that between the occupied VBM of SWCNTs and the highest occupied molecular orbital (HOMO) of gas molecules. As a result, among the gas-adsorbed cases considered here, carrier concentration increments and the frontier energy level of gas-adsorbed SWCNTs (i.e., the internal carrier mobility of SWCNTs and interfacial Schottky barrier of the contact between SWCNTs and neighboring materials within single-walled carbon nanotube field-effect transistors (SWCNT-FETs)) are changed more significantly for NO2- and SO2-adsorbed pristine SWCNTs, for NO2-, SO2-, and NO-adsorbed n-type SWCNTs, and for NO2-adsorbed p-type SWCNTs. Our study highlights the key role that a controlled electronic character of dopants can play in regulating the gas adsorption and selection behaviors for their practical gas sensor applications.
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