Identification of microbes in wounds using near-infrared spectroscopy

• Published in: Burns Vol. 48; no. 4; pp. 791 - 798
• Main 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
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01.06.2022
• Subjects: Animals; Burns - microbiology; Escherichia coli; Humans; Methicillin-Resistant Staphylococcus aureus; Microbiology; Near-infrared spectroscopy; Noncontact; Spectroscopy, Near-Infrared; Staphylococcal Infections - diagnosis; Staphylococcal Infections - microbiology; Staphylococcus aureus; Supporting vector machine; Swine; Wound infection; Wound Infection - diagnosis; Wound Infection - microbiology; Wound infection; Supporting vector machine; Microbiology; Noncontact; Near-infrared spectroscopy
• ISSN: 0305-4179; 1879-1409
• DOI: 10.1016/j.burns.2021.09.002

•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. 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. 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. 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 109 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 101 cfu ml−1 in LB medium. Identification time was less than 5 s. 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.