1
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Behera P, De M. Surface-Engineered Nanomaterials for Optical Array Based Sensing. Chempluschem 2024; 89:e202300610. [PMID: 38109071 DOI: 10.1002/cplu.202300610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 12/01/2023] [Indexed: 12/19/2023]
Abstract
Array based sensing governed by optical methods provides fast and economic way for detection of wide variety of analytes where the ideality of detection processes depends on the sensor element's versatile mode of interaction with multiple analytes in an unbiased manner. This can be achieved by either the receptor unit having multiple recognition moiety, or their surface property should possess tuning ability upon fabrication called surface engineering. Nanomaterials have a high surface to volume ratio, making them viable candidates for molecule recognition through surface adsorption phenomena, which makes it ideal to meet the above requirements. Most crucially, by engineering a nanomaterial's surface, one may produce cross-reactive responses for a variety of analytes while focusing solely on a single nanomaterial. Depending on the nature of receptor elements, in the last decade the array-based sensing has been considering as multimodal detection platform which operates through various pathway including single channel, multichannel, binding and indicator displacement assay, sequential ON-OFF sensing, enzyme amplified and nanozyme based sensing etc. In this review we will deliver the working principle for Array-based sensing by using various nanomaterials like nanoparticles, nanosheets, nanodots and self-assembled nanomaterials and their surface functionality for suitable molecular recognition.
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Affiliation(s)
- Pradipta Behera
- Department of Organic Chemistry, Indian Institute of Science, Bangalore, 560012, India
| | - Mrinmoy De
- Department of Organic Chemistry, Indian Institute of Science, Bangalore, 560012, India
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2
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Wang L, Wen Y, Li L, Yang X, Li W, Cao M, Tao Q, Sun X, Liu G. Development of Optical Differential Sensing Based on Nanomaterials for Biological Analysis. BIOSENSORS 2024; 14:170. [PMID: 38667163 PMCID: PMC11048167 DOI: 10.3390/bios14040170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 03/25/2024] [Accepted: 03/29/2024] [Indexed: 04/28/2024]
Abstract
The discrimination and recognition of biological targets, such as proteins, cells, and bacteria, are of utmost importance in various fields of biological research and production. These include areas like biological medicine, clinical diagnosis, and microbiology analysis. In order to efficiently and cost-effectively identify a specific target from a wide range of possibilities, researchers have developed a technique called differential sensing. Unlike traditional "lock-and-key" sensors that rely on specific interactions between receptors and analytes, differential sensing makes use of cross-reactive receptors. These sensors offer less specificity but can cross-react with a wide range of analytes to produce a large amount of data. Many pattern recognition strategies have been developed and have shown promising results in identifying complex analytes. To create advanced sensor arrays for higher analysis efficiency and larger recognizing range, various nanomaterials have been utilized as sensing probes. These nanomaterials possess distinct molecular affinities, optical/electrical properties, and biological compatibility, and are conveniently functionalized. In this review, our focus is on recently reported optical sensor arrays that utilize nanomaterials to discriminate bioanalytes, including proteins, cells, and bacteria.
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Affiliation(s)
| | - Yanli Wen
- Key Laboratory of Bioanalysis and Metrology for State Market Regulation, Shanghai Institute of Measurement and Testing Technology, 1500 Zhang Heng Road, Shanghai 201203, China; (L.W.); (L.L.); (X.Y.); (W.L.); (M.C.); (Q.T.); (X.S.)
| | | | | | | | | | | | | | - Gang Liu
- Key Laboratory of Bioanalysis and Metrology for State Market Regulation, Shanghai Institute of Measurement and Testing Technology, 1500 Zhang Heng Road, Shanghai 201203, China; (L.W.); (L.L.); (X.Y.); (W.L.); (M.C.); (Q.T.); (X.S.)
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3
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Xu Y, Qian C, Yu Y, Yang S, Shi F, Xu L, Gao X, Liu Y, Huang H, Stewart C, Li F, Han J. Machine Learning-Assisted Nanoenzyme/Bioenzyme Dual-Coupled Array for Rapid Detection of Amyloids. Anal Chem 2023; 95:4605-4611. [PMID: 36859794 DOI: 10.1021/acs.analchem.2c04244] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2023]
Abstract
Array-based sensing methods offer significant advantages in the simultaneous detection of multiple amyloid biomarkers and thus have great potential for diagnosing early-stage Alzheimer's disease. Yet, detecting low concentrations of amyloids remains exceptionally challenging. Here, we have developed a fluorescent sensor array based on the dual coupling of a nanoenzyme (AuNPs) and bioenzyme (horseradish peroxidase) to detect amyloids. Various ss-DNAs were bound to the nanoenzyme for regulating enzymatic activity and recognizing amyloids. A simplified sensor array was generated from a screening model via machine learning algorithms and achieved signal amplification through a two-step enzymatic reaction. As a result, our sensing system could discriminate the aggregation species and aggregation kinetics at 200 nM with 100% accuracy. Moreover, AD model mice and healthy mice were distinguished with 100% accuracy through the sensor array, providing a powerful sensing platform for diagnosing AD.
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Affiliation(s)
- Yu Xu
- State Key Laboratory of Natural Medicines, National R&D Center for Chinese Herbal Medicine Processing, Department of Food Quality and Safety, College of Engineering, China Pharmaceutical University, Nanjing 210009, China
| | - Cheng Qian
- Department of Pathology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing 211166, China
| | - Yang Yu
- State Key Laboratory of Natural Medicines, National R&D Center for Chinese Herbal Medicine Processing, Department of Food Quality and Safety, College of Engineering, China Pharmaceutical University, Nanjing 210009, China
| | - Shijie Yang
- State Key Laboratory of Natural Medicines, National R&D Center for Chinese Herbal Medicine Processing, Department of Food Quality and Safety, College of Engineering, China Pharmaceutical University, Nanjing 210009, China
| | - Fangfang Shi
- State Key Laboratory of Natural Medicines, National R&D Center for Chinese Herbal Medicine Processing, Department of Food Quality and Safety, College of Engineering, China Pharmaceutical University, Nanjing 210009, China
| | - Lian Xu
- State Key Laboratory of Natural Medicines, National R&D Center for Chinese Herbal Medicine Processing, Department of Food Quality and Safety, College of Engineering, China Pharmaceutical University, Nanjing 210009, China
| | - Xu Gao
- State Key Laboratory of Natural Medicines, National R&D Center for Chinese Herbal Medicine Processing, Department of Food Quality and Safety, College of Engineering, China Pharmaceutical University, Nanjing 210009, China
| | - Yuhang Liu
- State Key Laboratory of Natural Medicines, National R&D Center for Chinese Herbal Medicine Processing, Department of Food Quality and Safety, College of Engineering, China Pharmaceutical University, Nanjing 210009, China
| | - Hui Huang
- Ming Wai Lau Centre for Reparative Medicine, Karolinska Institutet, Stockholm 17177, Sweden
| | - Callum Stewart
- Ming Wai Lau Centre for Reparative Medicine, Karolinska Institutet, Stockholm 17177, Sweden
| | - Fei Li
- State Key Laboratory of Natural Medicines, National R&D Center for Chinese Herbal Medicine Processing, Department of Food Quality and Safety, College of Engineering, China Pharmaceutical University, Nanjing 210009, China
| | - Jinsong Han
- State Key Laboratory of Natural Medicines, National R&D Center for Chinese Herbal Medicine Processing, Department of Food Quality and Safety, College of Engineering, China Pharmaceutical University, Nanjing 210009, China
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4
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Shi L, Tang Q, Yang B, Liu W, Li B, Yang C, Jin Y. Portable and Label-Free Sensor Array for Discriminating Multiple Analytes via a Handheld Gas Pressure Meter. Anal Chem 2022; 94:14453-14459. [PMID: 36194124 DOI: 10.1021/acs.analchem.2c03497] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Cross-reactive sensor arrays are useful for discriminating multiple analytes in a complex sample. Herein, a portable and label-free gas pressure sensor array was proposed for multiplex analysis via a handheld gas pressure meter. It is based on the interaction diversity of analytes with catalase-like nanomaterials, including Pt nanoparticles (PtNP), Co3O4 nanosheets (Co3O4NS), and Pt-Co alloy nanosheets (PtCoNS), respectively. Thus, the diverse influence of analytes on the catalase-like activity could be output as the difference in the gas pressure. By using principal component analysis, eight proteins were well distinguished by the gas pressure sensor array at the 10 nM level within 12 min. Moreover, different concentrations of proteins and mixtures of proteins could likewise be discriminated. More importantly, the effective discrimination of proteins in human serum and discrimination of five kinds of cells further confirmed the potential of the gas pressure sensor array. Therefore, it provides a portable, cheap, sensitive, and label-free gas pressure sensor array, which is totally different from the reported sensor arrays and holds great potential for portable and cheap discrimination of multiple analytes.
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Affiliation(s)
- Lu Shi
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, Key Laboratory of Applied Surface and Colloid Chemistry, Ministry of Education, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710119, China
| | - Qiaorong Tang
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, Key Laboratory of Applied Surface and Colloid Chemistry, Ministry of Education, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710119, China
| | - Bing Yang
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, Key Laboratory of Applied Surface and Colloid Chemistry, Ministry of Education, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710119, China
| | - Wei Liu
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, Key Laboratory of Applied Surface and Colloid Chemistry, Ministry of Education, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710119, China
| | - Baoxin Li
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, Key Laboratory of Applied Surface and Colloid Chemistry, Ministry of Education, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710119, China
| | - Chaoyong Yang
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Collaborative Innovation Center of Chemistry for Energy Materials, Key Laboratory for Chemical Biology of Fujian Province, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Yan Jin
- Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, Key Laboratory of Applied Surface and Colloid Chemistry, Ministry of Education, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710119, China
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5
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Davydova A, Vorobyeva M. Aptamer-Based Biosensors for the Colorimetric Detection of Blood Biomarkers: Paving the Way to Clinical Laboratory Testing. Biomedicines 2022; 10:biomedicines10071606. [PMID: 35884911 PMCID: PMC9313021 DOI: 10.3390/biomedicines10071606] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/01/2022] [Accepted: 07/04/2022] [Indexed: 11/16/2022] Open
Abstract
Clinical diagnostics for human diseases rely largely on enzyme immunoassays for the detection of blood biomarkers. Nevertheless, antibody-based test systems have a number of shortcomings that have stimulated a search for alternative diagnostic assays. Oligonucleotide aptamers are now considered as promising molecular recognizing elements for biosensors (aptasensors) due to their high affinity and specificity of target binding. At the moment, a huge variety of aptasensors have been engineered for the detection of various analytes, especially disease biomarkers. However, despite their great potential and excellent characteristics in model systems, only a few of these aptamer-based assays have been translated into practice as diagnostic kits. Here, we will review the current progress in the engineering of aptamer-based colorimetric assays as the most suitable format for clinical lab diagnostics. In particular, we will focus on aptasensors for the detection of blood biomarkers of cardiovascular, malignant, and neurodegenerative diseases along with common inflammation biomarkers. We will also analyze the main obstacles that have to be overcome before aptamer test systems can become tantamount to ELISA for clinical diagnosis purposes.
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6
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Li Z, Jiang Y, Tang S, Zou H, Wang W, Qi G, Zhang H, Jin K, Wang Y, Chen H, Zhang L, Qu X. 2D nanomaterial sensing array using machine learning for differential profiling of pathogenic microbial taxonomic identification. Mikrochim Acta 2022; 189:273. [PMID: 35792975 PMCID: PMC9259531 DOI: 10.1007/s00604-022-05368-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 06/04/2022] [Indexed: 11/28/2022]
Abstract
An integrated custom cross-response sensing array has been developed combining the algorithm module’s visible machine learning approach for rapid and accurate pathogenic microbial taxonomic identification. The diversified cross-response sensing array consists of two-dimensional nanomaterial (2D-n) with fluorescently labeled single-stranded DNA (ssDNA) as sensing elements to extract a set of differential response profiles for each pathogenic microorganism. By altering the 2D-n and different ssDNA with different sequences, we can form multiple sensing elements. While interacting with microorganisms, the competition between ssDNA and 2D-n leads to the release of ssDNA from 2D-n. The signals are generated from binding force driven by the exfoliation of either ssDNA or 2D-n from the microorganisms. Thus, the signal is distinguished from different ssDNA and 2D-n combinations, differentiating the extracted information and visualizing the recognition process. Fluorescent signals collected from each sensing element at the wavelength around 520 nm are applied to generate a fingerprint. As a proof of concept, we demonstrate that a six-sensing array enables rapid and accurate pathogenic microbial taxonomic identification, including the drug-resistant microorganisms, under a data size of n = 288. We precisely identify microbial with an overall accuracy of 97.9%, which overcomes the big data dependence for identifying recurrent patterns in conventional methods. For each microorganism, the detection concentration is 105 ~ 108 CFU/mL for Escherichia coli, 102 ~ 107 CFU/mL for E. coli-β, 103 ~ 108 CFU/mL for Staphylococcus aureus, 103 ~ 107 CFU/mL for MRSA, 102 ~ 108 CFU/mL for Pseudomonas aeruginosa, 103 ~ 108 CFU/mL for Enterococcus faecalis, 102 ~ 108 CFU/mL for Klebsiella pneumoniae, and 103 ~ 108 CFU/mL for Candida albicans. Combining the visible machine learning approach, this sensing array provides strategies for precision pathogenic microbial taxonomic identification.
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Affiliation(s)
- Zhijun Li
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518017, China
| | - Yizhou Jiang
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518017, China
| | - Shihuan Tang
- Department of Clinical Laboratory, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518017, Guangdong, China
| | - Haixia Zou
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518017, China
| | - Wentao Wang
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518017, China
| | - Guangpei Qi
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518017, China
| | - Hongbo Zhang
- Pharmaceutical Sciences Laboratory, Åbo Akademi University, 20520, Turku, Finland.
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, 20520, Turku, Finland.
| | - Kun Jin
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518017, China
| | - Yuhe Wang
- School of Petroleum Engineering, State Key Laboratory of Heavy Oil Processing, China University of Petroleum (East China), Qingdao, 266580, China
| | - Hong Chen
- Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, Xiamen, 361005, China
| | - Liyuan Zhang
- School of Petroleum Engineering, State Key Laboratory of Heavy Oil Processing, China University of Petroleum (East China), Qingdao, 266580, China.
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA.
| | - Xiangmeng Qu
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518017, China.
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7
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Pu F, Ren J, Qu X. Recent progress in sensor arrays using nucleic acid as sensing elements. Coord Chem Rev 2022. [DOI: 10.1016/j.ccr.2021.214379] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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8
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A Multichannel Pattern-Recognition-Based Protein Sensor with a Fluorophore-Conjugated Single-Stranded DNA Set. SENSORS 2020; 20:s20185110. [PMID: 32911729 PMCID: PMC7570997 DOI: 10.3390/s20185110] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 09/04/2020] [Accepted: 09/05/2020] [Indexed: 12/16/2022]
Abstract
Recently, pattern-recognition-based protein sensing has received considerable attention because it offers unique opportunities that complement more conventional antibody-based detection methods. Here, we report a multichannel pattern-recognition-based sensor using a set of fluorophore-conjugated single-stranded DNAs (ssDNAs), which can detect various proteins. Three different fluorophore-conjugated ssDNAs were placed into a single microplate well together with a target protein, and the generated optical response pattern that corresponds to each environment-sensitive fluorophore was read via multiple detection channels. Multivariate analysis of the resulting optical response patterns allowed an accurate detection of eight different proteases, indicating that fluorescence signal acquisition from a single compartment containing a mixture of ssDNAs is an effective strategy for the characterization of the target proteins. Additionally, the sensor could identify proteins, which are potential targets for disease diagnosis, in a protease and inhibitor mixture of different composition ratios. As our sensor benefits from simple construction and measurement procedures, and uses accessible materials, it offers a rapid and simple platform for the detection of proteins.
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9
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Davydova A, Krasitskaya V, Vorobjev P, Timoshenko V, Tupikin A, Kabilov M, Frank L, Venyaminova A, Vorobyeva M. Reporter-recruiting bifunctional aptasensor for bioluminescent analytical assays. RSC Adv 2020; 10:32393-32399. [PMID: 35516485 PMCID: PMC9056652 DOI: 10.1039/d0ra05117a] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 08/21/2020] [Indexed: 12/26/2022] Open
Abstract
A novel structure-switching bioluminescent 2′-F-RNA aptasensor consists of analyte-binding and obelin-recruiting modules, joined into a bi-specific aptamer construct.
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Affiliation(s)
- Anna Davydova
- Institute of Chemical Biology and Fundamental Medicine SB RAS
- Novosibirsk 630090
- Russia
| | - Vasilisa Krasitskaya
- Institute of Biophysics SB RAS
- Federal Research Center “Krasnoyarsk Science Center SB RAS”
- Krasnoyarsk 660036
- Russia
| | - Pavel Vorobjev
- Institute of Chemical Biology and Fundamental Medicine SB RAS
- Novosibirsk 630090
- Russia
- Novosibirsk State University
- 630090 Novosibirsk
| | - Valentina Timoshenko
- Institute of Chemical Biology and Fundamental Medicine SB RAS
- Novosibirsk 630090
- Russia
| | - Alexey Tupikin
- Institute of Chemical Biology and Fundamental Medicine SB RAS
- Novosibirsk 630090
- Russia
| | - Marsel Kabilov
- Institute of Chemical Biology and Fundamental Medicine SB RAS
- Novosibirsk 630090
- Russia
| | - Ludmila Frank
- Institute of Biophysics SB RAS
- Federal Research Center “Krasnoyarsk Science Center SB RAS”
- Krasnoyarsk 660036
- Russia
- Siberian Federal University
| | - Alya Venyaminova
- Institute of Chemical Biology and Fundamental Medicine SB RAS
- Novosibirsk 630090
- Russia
| | - Mariya Vorobyeva
- Institute of Chemical Biology and Fundamental Medicine SB RAS
- Novosibirsk 630090
- Russia
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Das Saha N, Sasmal R, Meethal SK, Vats S, Gopinathan PV, Jash O, Manjithaya R, Gagey-Eilstein N, Agasti SS. Multichannel DNA Sensor Array Fingerprints Cell States and Identifies Pharmacological Effectors of Catabolic Processes. ACS Sens 2019; 4:3124-3132. [PMID: 31763818 DOI: 10.1021/acssensors.9b01009] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Cells at disease onset are often associated with subtle changes in the expression level of a single or few molecular components, making traditionally used biomarker-driven clinical diagnosis a challenging task. We demonstrate here the design of a DNA nanosensor array with multichannel output that identifies the normal or pathological state of a cell based on the alteration of its global proteomic signature. Fluorophore-encoded single-stranded DNA (ssDNA) strands were coupled via supramolecular interaction with a surface-functionalized gold nanoparticle quencher to generate this integrated sensor array. In this design, ssDNA sequences exhibit dual roles, where they provide differential affinities with the receptor gold nanoparticle as well as act as transducer elements. The unique interaction mode of the analyte molecules disrupts the noncovalent supramolecular complexation, generating simultaneous multichannel fluorescence output to enable signature-based analyte identification via a linear discriminant analysis-based machine learning algorithm. Different cell types, particularly normal and cancerous cells, were effectively distinguished using their fluorescent fingerprints. Additionally, this DNA sensor array displayed excellent sensitivity to identify cellular alterations associated with chemical modulation of catabolic processes. Importantly, pharmacological effectors, which could modulate autophagic flux, have been effectively distinguished by generating responses from their global protein signatures. Taken together, these studies demonstrate that our multichannel DNA nanosensor is well suited for rapid identification of subtle changes in a complex mixture and thus can be readily expanded for point-of-care clinical diagnosis, high-throughput drug screening, or predicting the therapeutic outcome from a limited sample volume.
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Affiliation(s)
| | | | | | | | | | | | | | - Nathalie Gagey-Eilstein
- UMR-S 1139, INSERM, 3PHM, Université Paris Descartes, Faculté des Sciences Pharmaceutiques et Biologiques, Sorbonne Paris Cité, 4 avenue de l’Observatoire, 75006 Paris, France
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Tomita S, Sugai H, Mimura M, Ishihara S, Shiraki K, Kurita R. Optical Fingerprints of Proteases and Their Inhibited Complexes Provided by Differential Cross-Reactivity of Fluorophore-Labeled Single-Stranded DNA. ACS APPLIED MATERIALS & INTERFACES 2019; 11:47428-47436. [PMID: 31747245 DOI: 10.1021/acsami.9b17829] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The detection of proteases and their complexes with inhibitor proteins is of great importance for diagnosis and medical-treatment applications. In this study, we report a fingerprint-based sensor using an array of single-stranded DNAs (ssDNAs) labeled with environment-responsive 3'-carboxytetramethylrhodamine (TAMRA) for the identification of proteases. Four TAMRA-modified ssDNAs with different sequences solubilized in two different buffer solutions were incorporated in an array that was capable of generating fluorescent fingerprints unique to the proteases through diverse cross-reactive interactions, allowing the discrimination of (i) 8 proteases and (ii) 12 different mixtures of trypsin and its inhibitor protein (α1-antitrypsin) by multivariate analysis. Constructing an array with TAMRA-modified DNA aptamers that bind to different sites of human thrombin provides fluorescence fingerprints that reflect a reduction of the exposed surface area of thrombin upon complexation with antithrombin III, even in the presence of human serum. We finally demonstrate the potential of hybridization with complementary DNAs as an effective means to easily double the fingerprint information for proteases. Our approach based on the cross-reactive capability of ssDNAs enables high-throughput fingerprint-based sensing that can be flexibly designed and easily constructed, not only for the identification of a variety of proteins including proteases but also for the evaluation of their complexation ability.
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Affiliation(s)
- Shunsuke Tomita
- Biomedical Research Institute , National Institute of Advanced Industrial Science and Technology , 1-1-1 Higashi , Tsukuba , Ibaraki 305-8566 , Japan
- DBT-AIST International Laboratory for Advanced Biomedicine (DAILAB), DBT-AIST International Center for Translational & Environmental Research (DAICENTER) , National Institute of Advanced Industrial Science and Technology , 1-1-1 Higashi , Tsukuba , Ibaraki 305-8566 , Japan
| | - Hiroka Sugai
- Biomedical Research Institute , National Institute of Advanced Industrial Science and Technology , 1-1-1 Higashi , Tsukuba , Ibaraki 305-8566 , Japan
| | - Masahiro Mimura
- Biomedical Research Institute , National Institute of Advanced Industrial Science and Technology , 1-1-1 Higashi , Tsukuba , Ibaraki 305-8566 , Japan
- Faculty of Pure and Applied Sciences , University of Tsukuba , 1-1-1 Tennodai , Tsukuba , Ibaraki 305-8573 , Japan
| | - Sayaka Ishihara
- Biomedical Research Institute , National Institute of Advanced Industrial Science and Technology , 1-1-1 Higashi , Tsukuba , Ibaraki 305-8566 , Japan
| | - Kentaro Shiraki
- Faculty of Pure and Applied Sciences , University of Tsukuba , 1-1-1 Tennodai , Tsukuba , Ibaraki 305-8573 , Japan
| | - Ryoji Kurita
- Biomedical Research Institute , National Institute of Advanced Industrial Science and Technology , 1-1-1 Higashi , Tsukuba , Ibaraki 305-8566 , Japan
- DBT-AIST International Laboratory for Advanced Biomedicine (DAILAB), DBT-AIST International Center for Translational & Environmental Research (DAICENTER) , National Institute of Advanced Industrial Science and Technology , 1-1-1 Higashi , Tsukuba , Ibaraki 305-8566 , Japan
- Faculty of Pure and Applied Sciences , University of Tsukuba , 1-1-1 Tennodai , Tsukuba , Ibaraki 305-8573 , Japan
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12
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Sun Y, Lu F, Yang H, Ding C, Yuan Z, Lu C. Fluorescent sensor array for separation-free dopamine analogue discrimination via polyethyleneimine-mediated self-polymerization reaction. NANOSCALE 2019; 11:12889-12897. [PMID: 31245804 DOI: 10.1039/c9nr03643a] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The effective discrimination of dopamine (DA) analogues is an enduring challenge because of their very tiny structural differences, and thus a separation technique is generally required during the conventional analysis. In this study, a hyperbranched polyethyleneimine (hPEI)-based fluorescent sensor array has been constructed for the separation-free and effective differentiation of four DA analogues. The discrimination includes two steps: firstly, the formation of fluorescent polymer nanoparticles (FPNs) with diverse emission profiles via hPEI-mediated self-polymerization reaction of DA analogues and secondly, the linear discriminant analysis of fluorescence patterns of the formed FPNs for the differentiation of DA analogues. The hPEI-assisted self-polymerization reaction of DA analogues and substitution group mediated optical properties of the resulted FPNs enable an excellent discrimination of four DA analogues at a concentration of 1.0 μM when linear discriminant analysis and hierarchical cluster analysis are smartly combined. Additionally, binary, tertiary and even quaternary mixtures of analogues can also be well distinguished with the proposed sensor array. The practicability of this established sensor array is validated by a high accuracy (100%) evaluation of 88 blind samples containing a single analogue or a mixture of two, three or four analogues.
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Affiliation(s)
- Ye Sun
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing 100029, China.
| | - Fengniu Lu
- International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba 305-0044, Japan
| | - Hongwei Yang
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing 100029, China.
| | - Caifeng Ding
- Laboratory of Optic-electric Sensing and Analytical Chemistry for Life Science, Ministry of Education; Qingdao University of Science and Technology, Qingdao 266042, China
| | - Zhiqin Yuan
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing 100029, China.
| | - Chao Lu
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing 100029, China.
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13
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Development and characterization of novel 2'-F-RNA aptamers specific to human total and glycated hemoglobins. Anal Biochem 2019; 570:43-50. [PMID: 30742800 DOI: 10.1016/j.ab.2019.02.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 02/05/2019] [Accepted: 02/06/2019] [Indexed: 02/07/2023]
Abstract
Aptamers are short DNA and RNA fragments which bind their molecular targets with affinity and specificity comparable to those of antibodies. Here, we describe the selection of novel 2'-F-RNA aptamers against total human hemoglobin or its glycated form HbA1c. After SELEX and high-throughput sequencing of the enriched libraries, affinities and specificities of candidate aptamers and their truncated variants were examined by the solid-phase bioluminescent assay. As a result, we identified aptamers specific to both hemoglobins or only glycated HbA1c. The developed 2'-F-RNA aptamers have shown their applicability for detection of total and glycated hemoglobin in one sample.
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14
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Differentiation of human blood from animal blood using Raman spectroscopy: A survey of forensically relevant species. Forensic Sci Int 2018; 282:204-210. [DOI: 10.1016/j.forsciint.2017.11.033] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Revised: 11/04/2017] [Accepted: 11/20/2017] [Indexed: 01/20/2023]
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15
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Pattern-based sensing of triple negative breast cancer cells with dual-ligand cofunctionalized gold nanoclusters. Biomaterials 2016; 116:21-33. [PMID: 27914264 DOI: 10.1016/j.biomaterials.2016.11.050] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Revised: 11/08/2016] [Accepted: 11/24/2016] [Indexed: 01/05/2023]
Abstract
Early detection of breast cancer is a critical component in patient prognosis and establishing effective therapy regimens. Here, we developed an easily accessible yet potentially powerful sensor to detect cancer cell targets by utilizing seven dual-ligand cofunctionalized gold nanoclusters (AuNCs) as both effective cell recognition elements and signal transducers. On the basis of this AuNC multichannel sensor, we have successfully distinguished healthy, cancerous and metastatic human breast cells with excellent reproducibility and high sensitivity. Triple negative breast cancer cells (TNBCs), which exhibit low expression of the estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2, were identified. The high accuracy of the blind breast cell sample tests further validates the practical application of the sensor array. In addition, the versatility of the sensor array is further justified by identifying amongst distinct cell types, different cell concentrations and cell mixtures. Notably, the drug-resistant cancer cells can also be efficiently discriminated. Furthermore, the dual-ligand cofunctionalized AuNCs can efficiently differentiate different cells from the peripheral blood of tumor-free and tumor-bearing mice. Taken together, this fluorescent AuNCs based array provides a powerful cell analysis tool with potential applications in biomedical diagnostics.
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16
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Liu W, Lin M, Yang X, Wu B, Chen N, Wang Q, Wang K, Qin S. Investigation of newly identified G-quadruplexes and their application to DNA detection. Analyst 2016; 141:4463-9. [PMID: 27215424 DOI: 10.1039/c6an00987e] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
G-quadruplexes are guanine-rich nucleic acid sequences that can act as universal signal-transducers and generate colorimetric, fluorescence, and chemiluminescence signals when complexed with different ligands. Due to their merits including easy modification and low cost, it is of great importance to explore new G-quadruplexes with improved performance. Herein the properties of newly identified G-quadruplexes 9th-3-35 and 10th-2-40 were investigated in detail with UV-vis spectra, circular dichroism (CD) spectra and fluorescence spectra. The results indicated that 9th-3-35 and 10th-2-40 exhibited excellent peroxidase-like activity, as well as fluorescence enhancement of thioflavin T (ThT). Furthermore, the application of G-quadruplexes to DNA detection was performed on account of the ThT fluorescence enhancement, and the limit of detection was as low as 8 pM. This study implied that 9th-3-35 and 10th-2-40 are competitive candidates as signal-transducers in the design of bioassays.
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Affiliation(s)
- Wenjing Liu
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Key Laboratory for Bio-Nanotechnology and Molecule Engineering of Hunan Province, Hunan University, Changsha, 410082, China.
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