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Gelatinase-responsive photonic crystal membrane for pathogenic bacteria detection and application in vitro health diagnosis. | LitMetric

Gelatinase-responsive photonic crystal membrane for pathogenic bacteria detection and application in vitro health diagnosis.

Biosens Bioelectron

Key Laboratory of Textile Fiber and Products (Wuhan Textile University) Ministry of Education, Hubei International Scientific and Technological Cooperation Base of Intelligent Textile Materials & Application, Wuhan Textile University, Wuhan, 430200, China. Electronic address:

Published: April 2022


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Article Abstract

Selective identification and rapid detection for multiple pathogenic bacteria are important to prevent bacterial infection. Herein, gelatinase-responsive photonic crystal membrane (PCM) is reported as rapid, selective and direct detection platform for multiple pathogenic bacteria. PCMs exhibit angle-independent structural color, and reflection spectra has negligible change after irradiation and storage under different temperature. The ultra-thin response layer makes shorter detection time (30 min) than the reported gelatin-based photonic crystal detection platform (10-12 h). There is obvious positive correlation between reflection spectra change and gelatinase concentration, even if the gelatinase was as low as 4.8 pM. PCM has high stability against multiple interferers, which are beneficial to improve the detection accuracy and reliability. PCM also show "selective" ability to identify typical pathogens from atypical pathogens through specific response to gelatinase, and good selectivity gives PCM direct detection ability without pretreatment. PCM could detect the pathogens bacteria concentration range spanning 7 orders of magnitude from 10 to 10 CFU/mL, and the relative error between gold standard method and the new platform is less than 10%. Furthermore, PCM's in vitro health diagnosis ability was proved by detecting pathogenic bacteria in artificial wound fluid and urine. All the results show that PCM is well promising platform for selective identifying and rapid detecting pathogenic bacteria in vitro diagnosis.

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http://dx.doi.org/10.1016/j.bios.2022.114013DOI Listing

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