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Liu C, Du J, Wang Y, Qian X, Ji B, Wang M, Xia Z. Protein Recognition Based on Temperature-Stimulated Multiparameter Response Virtual Array Sensing Strategy. Anal Chem 2023; 95:16996-17002. [PMID: 37943990 DOI: 10.1021/acs.analchem.3c03336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
In the field of array sensing, researchers are committed to miniaturizing array sensing systems while ensuring the acquisition of multiple sensing information. Here, a new strategy called "stimulus responsive array sensing" was presented to obtain virtual multiple sensing without constructing multiple physical sensing units. Based on bioluminescence resonance energy transfer, where luciferase acts as the donor and temperature stimulus response polymers act as the receptors, by using only one sensing unit to output multiple stimulus responsive sensing signals in temperature dimension, an equivalent array sensing could be achieved. This strategy can distinguish and quantify a variety of proteins. More importantly, glucose responsive monomers were doped in polymers; thus, more virtual sensing units can be further increased to obtain more sensing signals, greatly increasing the accuracy of protein recognition, and it can also be used to differentiate several compositions of protein under different glucose concentrations in urine caused by different renal diseases. The results show the potential of the "stimulus responsive array sensing" for analyzing molecular compositions in complex biological systems and show a new tack in array sensing.
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Affiliation(s)
- Chunlan Liu
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, Innovative Drug Research Center, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Jiayin Du
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, Innovative Drug Research Center, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Yue Wang
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, Innovative Drug Research Center, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Xin Qian
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, Innovative Drug Research Center, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Baian Ji
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, Innovative Drug Research Center, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Min Wang
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, Innovative Drug Research Center, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Zhining Xia
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, Innovative Drug Research Center, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
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Austin MJ, Schunk HC, Ling N, Rosales AM. Peptomer substrates for quantitative pattern-recognition sensing of proteases. Chem Commun (Camb) 2023; 59:1685-1688. [PMID: 36692178 DOI: 10.1039/d2cc06587h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The utility of active proteases as biomarkers is often limited by overlapping substrate specificity. Here, this feature is leveraged to develop a quantitative pattern-recognition sensing system driven by the degradation patterns of peptide-peptoid hybrid substrates to classify proteases and estimate their concentration by multivariate data analysis.
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Affiliation(s)
- Mariah J Austin
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA.
| | - Hattie C Schunk
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA. .,Biomedical Engineering Department, University of Texas at Austin, Austin, TX, 78712, USA
| | - Natalie Ling
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA.
| | - Adrianne M Rosales
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA.
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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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Tomita S, Ishihara S, Kurita R. A polymer-based chemical tongue for the non-invasive monitoring of osteogenic stem-cell differentiation by pattern recognition of serum-supplemented spent media. J Mater Chem B 2022; 10:7581-7590. [DOI: 10.1039/d2tb00606e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The development of non-invasive techniques to characterize cultured cells is invaluable not only to ensure the reproducibility of cell research, but also for quality assurance of industrial cell products for...
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