Identification of microbes in wounds using near-infrared spectroscopy. Issue 4 (June 2022)

• Record Type: Journal Article
• Authors: Yin, Meifang; Li, Jiangfeng; Huang, Lixian; Li, Yongming; Yuan, Mingzhou; Luo, Yongquan; Armato, Ubaldo; Zhang, Lijun; Wei, Yating; Li, Yuanyuan; Deng, Jiawen; Wang, Pin; Wu, Jun
• Is Part Of: Burns. Volume 48:Issue 4(2022)
• Page Start: 791
• Page End: 798
• Publication Date: 2022-06
• Subjects: Wound infection -- Microbiology -- Noncontact -- Near-infrared spectroscopy -- Supporting vector machine; Burns and scalds -- Periodicals; 617.11
• DOI: 10.1016/j.burns.2021.09.002
• Languages: English
• ISSNs: 0305-4179

Abstract

Highlights: Demonstrates a novel approach using near-infrared spectroscopy technology together with supporting vector machine. It provides a promising approach to identify diverse microbial species. It provides a potential bedside device for the fast in-situ recognition of wound-infecting microbes. It can further achieve the detection of infections in wounds, biopsy samples, surgically exposed organs, et cetera. Abstract: Background: Rapid diagnosis of microbes in the burn wound is a big challenge in the medical field. Traditional biochemical detection techniques take hours or days to identify the species of contaminating and drug-resistant microbes. Near-infrared spectroscopy (NIRS) is evaluated to address the need for a fast and sensitive method for the detection of bacterial contamination in liquids. Methods: Herin, we developed a novel technique which by using NIRS together with supporting vector machine (SVM), to identify the microbial species and drug-resistant microbes in LB medium, and to diagnose the wound colonization and wound infection models of pigs. Results: The device could recognize 100% of seven kinds of microbes and 99.47% of the multi-drug resistant Staphylococcus aureus ( S. aureus ), with a concentration of 10 9 cfu ml −1 in LB medium. The accuracy of the microbial identification in colonized and infected wounds in-situ was 100%. The detection limit of NIRS with SVM for the detection of S. aureus and Escherichia coli ( E. coli ) was 10 1 cfu ml −1 in LB medium. Identification time was less than 5 s. Conclusion: Our findings validate for the first time a novel technique aimed at the rapid, noncontacted, highly sensitive, and specific recognition of several microbial species including drug-resistant ones. This technique could represent a promising approach to identify diverse microbial species and a potential bedside device to rapidly diagnose infected wounds.