化学
调制(音乐)
鉴定(生物学)
纳米技术
细菌
比色法
色谱法
生物物理学
分析物
生物系统
作者
Ning Shen,Ruian Tang,Changfa Shao,Yuxi Zhang,Feier Wang,Jianyu Yang,Yiming Zhu
标识
DOI:10.1016/j.mseb.2026.119871
摘要
Rapid and accurate bacterial identification is essential for public health. Catalytic nanomaterials are widely used in energy conversion because their electronic structures and interfacial charge-transfer processes can be rationally regulated. These properties also enable the conversion of biological interactions into measurable catalytic signals. However, amplifying subtle differences in bacterial surfaces into distinguishable fingerprints remains challenging. Herein, we construct a graphdiyne (GDY)-supported metalloporphyrin nanozyme colorimetric sensor array (GM-CSA) by immobilizing Fe-, Co-, and Mn-centered metalloporphyrins on GDY nanosheets. GDY enhances catalyst dispersion and stability while regulating electron transfer, active-site accessibility, and bacteria-nanozyme interactions. The target bacteria-dependent catalytic inhibition produces distinct colorimetric fingerprint patterns. Machine-learning-assisted pattern recognition decodes these multidimensional fingerprints, enabling accurate discrimination of six bacterial species associated with urinary tract infections. This work extends the interfacial regulation principles of catalytic nanomaterials from energy-related processes to biological signal conversion, providing a GDY-based strategy for colorimetric fingerprinting and intelligent bacterial identification.
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