Nicoleta Elena Dina , Alia Colniță , Nicolae Leopold , Christoph Haisch
{"title":"利用表面增强拉曼光谱快速检测和鉴定细菌","authors":"Nicoleta Elena Dina , Alia Colniță , Nicolae Leopold , Christoph Haisch","doi":"10.1016/j.protcy.2017.04.086","DOIUrl":null,"url":null,"abstract":"<div><p>Recently, the possibility of developing surface-enhanced Raman scattering (SERS)-based biosensors for rapid detection of bacteria is widely explored. With this purpose, we used SERS spectroscopy along with chemometric techniques to detect and identify by their spectral profiles relevant pathogens grown in different cultivation conditions by using <em>in situ</em> synthesized silver colloid (Bacteria@AgNPs) and incubation in silver colloid <span>[1]</span>, <span>[2]</span>. Enhanced darkfield hyperspectral microscopy analysis was employed for characterizing the interaction between the bacteria and silver nanoparticles (Bacteria@AgNPs system). Moreover, a label-free SERS-based protocol was optimized and the influence of taxonomic affiliation and time-dependent effects of incubation in silver colloid were monitored.</p><p>By using SERS-based protocol with the optimized experimental parameters, the label-free detection and identification of the most common pathogens (<em>E. coli</em>, <em>Aeromonas</em>, <em>M. morganii</em>, <em>E. lactis, L. casei</em> and <em>L. monocytogenes</em>) was assessed. The reduced sample volume required, the rapid spectral acquisition (within 5 minutes), and the use of chemometric techniques for an unbiased analysis of the SERS single-cell spectra, provided the optimum platform for developing SERS-based biosensors for food safety, water research, or health care real-life applications.</p></div>","PeriodicalId":101042,"journal":{"name":"Procedia Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.protcy.2017.04.086","citationCount":"12","resultStr":"{\"title\":\"Rapid Single-cell Detection and Identification of Bacteria by Using Surface-enhanced Raman Spectroscopy\",\"authors\":\"Nicoleta Elena Dina , Alia Colniță , Nicolae Leopold , Christoph Haisch\",\"doi\":\"10.1016/j.protcy.2017.04.086\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Recently, the possibility of developing surface-enhanced Raman scattering (SERS)-based biosensors for rapid detection of bacteria is widely explored. With this purpose, we used SERS spectroscopy along with chemometric techniques to detect and identify by their spectral profiles relevant pathogens grown in different cultivation conditions by using <em>in situ</em> synthesized silver colloid (Bacteria@AgNPs) and incubation in silver colloid <span>[1]</span>, <span>[2]</span>. Enhanced darkfield hyperspectral microscopy analysis was employed for characterizing the interaction between the bacteria and silver nanoparticles (Bacteria@AgNPs system). Moreover, a label-free SERS-based protocol was optimized and the influence of taxonomic affiliation and time-dependent effects of incubation in silver colloid were monitored.</p><p>By using SERS-based protocol with the optimized experimental parameters, the label-free detection and identification of the most common pathogens (<em>E. coli</em>, <em>Aeromonas</em>, <em>M. morganii</em>, <em>E. lactis, L. casei</em> and <em>L. monocytogenes</em>) was assessed. The reduced sample volume required, the rapid spectral acquisition (within 5 minutes), and the use of chemometric techniques for an unbiased analysis of the SERS single-cell spectra, provided the optimum platform for developing SERS-based biosensors for food safety, water research, or health care real-life applications.</p></div>\",\"PeriodicalId\":101042,\"journal\":{\"name\":\"Procedia Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.protcy.2017.04.086\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Procedia Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212017317300877\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Procedia Technology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212017317300877","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Rapid Single-cell Detection and Identification of Bacteria by Using Surface-enhanced Raman Spectroscopy
Recently, the possibility of developing surface-enhanced Raman scattering (SERS)-based biosensors for rapid detection of bacteria is widely explored. With this purpose, we used SERS spectroscopy along with chemometric techniques to detect and identify by their spectral profiles relevant pathogens grown in different cultivation conditions by using in situ synthesized silver colloid (Bacteria@AgNPs) and incubation in silver colloid [1], [2]. Enhanced darkfield hyperspectral microscopy analysis was employed for characterizing the interaction between the bacteria and silver nanoparticles (Bacteria@AgNPs system). Moreover, a label-free SERS-based protocol was optimized and the influence of taxonomic affiliation and time-dependent effects of incubation in silver colloid were monitored.
By using SERS-based protocol with the optimized experimental parameters, the label-free detection and identification of the most common pathogens (E. coli, Aeromonas, M. morganii, E. lactis, L. casei and L. monocytogenes) was assessed. The reduced sample volume required, the rapid spectral acquisition (within 5 minutes), and the use of chemometric techniques for an unbiased analysis of the SERS single-cell spectra, provided the optimum platform for developing SERS-based biosensors for food safety, water research, or health care real-life applications.