Rapid enrichment and SERS differentiation of various bacteria in skin interstitial fluid by 4-MPBA-AuNPs-functionalized hydrogel microneedles

Ying Yang; Xingyu Wang; Yexin Hu; Zhongyao Liu; Xiao Ma; Feng Feng; Feng Zheng; Xinlin Guo; Wenyuan Liu; Wenting Liao; Lingfei Han

doi:10.1016/j.jpha.2024.101152

Volume 15 Issue 3

Apr. 2025

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Article Navigation > Journal of Pharmaceutical Analysis > 2025 > 15(3): 101152

Ying Yang, Xingyu Wang, Yexin Hu, Zhongyao Liu, Xiao Ma, Feng Feng, Feng Zheng, Xinlin Guo, Wenyuan Liu, Wenting Liao, Lingfei Han. Rapid enrichment and SERS differentiation of various bacteria in skin interstitial fluid by 4-MPBA-AuNPs-functionalized hydrogel microneedles[J]. Journal of Pharmaceutical Analysis, 2025, 15(3): 101152. doi: 10.1016/j.jpha.2024.101152

Citation:

Ying Yang, Xingyu Wang, Yexin Hu, Zhongyao Liu, Xiao Ma, Feng Feng, Feng Zheng, Xinlin Guo, Wenyuan Liu, Wenting Liao, Lingfei Han. Rapid enrichment and SERS differentiation of various bacteria in skin interstitial fluid by 4-MPBA-AuNPs-functionalized hydrogel microneedles[J]. Journal of Pharmaceutical Analysis, 2025, 15(3): 101152. doi: 10.1016/j.jpha.2024.101152

Citation:

Ying Yang, Xingyu Wang, Yexin Hu, Zhongyao Liu, Xiao Ma, Feng Feng, Feng Zheng, Xinlin Guo, Wenyuan Liu, Wenting Liao, Lingfei Han. Rapid enrichment and SERS differentiation of various bacteria in skin interstitial fluid by 4-MPBA-AuNPs-functionalized hydrogel microneedles[J]. Journal of Pharmaceutical Analysis, 2025, 15(3): 101152. doi: 10.1016/j.jpha.2024.101152

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Rapid enrichment and SERS differentiation of various bacteria in skin interstitial fluid by 4-MPBA-AuNPs-functionalized hydrogel microneedles

doi: 10.1016/j.jpha.2024.101152

a. Department of Pharmaceutical Analysis, China Pharmaceutical University, Nanjing, 211198, China;
b. Gansu Institute for Drug Control, Lanzhou, Gansu, 730000, China;
c. School of Pharmacy, Nanjing Medical University, Nanjing, 211166, China;
d. School of Chemistry, University of Manchester, Manchester, M13 9PL, UK;
e. Zhejiang Center for Safety Study of Drug Substances (Industrial Technology Innovation Platform), Hangzhou, 310018, China

Funds:

This work was financially supported by the National Natural Science Foundation of China (Grant Nos.: 82204340, 82173954, and 82073815), the Natural Science Foundation of Jiangsu Province, China (Grant No.: BK20221048), the Jiangsu Funding Program for Excellent Postdoctoral Talent, China (Grant No.: 2022ZB295), and Key Laboratory Project of Quality Control of Chinese Herbal Medicines and Decoction Pieces, Gansu Institute for Drug Control, China (Grant No.: 2024GSMPA-KL02).

Received Date: Jul. 15, 2024
Accepted Date: Nov. 18, 2024
Rev Recd Date: Nov. 01, 2024
Publish Date: Nov. 20, 2024

Abstract

Abstract

Bacterial infection is a major threat to global public health, and can cause serious diseases such as bacterial skin infection and foodborne diseases. It is essential to develop a new method to rapidly diagnose clinical multiple bacterial infections and monitor food microbial contamination in production sites in real-time. In this work, we developed a 4-mercaptophenylboronic acid gold nanoparticles (4-MPBA-AuNPs)-functionalized hydrogel microneedle (MPBA-H-MN) for bacteria detection in skin interstitial fluid. MPBA-H-MN could conveniently capture and enrich a variety of bacteria within 5 min. Surface enhanced Raman spectroscopy (SERS) detection was then performed and combined with machine learning technology to distinguish and identify a variety of bacteria. Overall, the capture efficiency of this method exceeded 50%. In the concentration range of 1 × 10⁷ to 1 × 10¹⁰ colony-forming units/mL (CFU/mL), the corresponding SERS intensity showed a certain linear relationship with the bacterial concentration. Using random forest (RF)-based machine learning, bacteria were effectively distinguished with an accuracy of 97.87%. In addition, the harmless disposal of used MNs by photothermal ablation was convenient, environmentally friendly, and inexpensive. This technique provided a potential method for rapid and real-time diagnosis of multiple clinical bacterial infections and for monitoring microbial contamination of food in production sites.
- Hydrogel microneedle,
- SERS,
- Broad-spectrum bacteria detection,
- Skin interstitial fluid,
- Machine learning

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References(41)

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