Plasmonic Nanotrough Networks for Scalable Bacterial Raman Biosensing

Abstract

We demonstrate a novel approach for fabricating surface enhanced Raman scattering (SERS) substrates for single bacterial biosensing based on Ag cylindrical nanotrough networks (CNNs). This approach is developed with large scalability by leveraging a cellulose nanofiber template fabrication via facile electrospinning. Specifically, a concave nanotrough structure consisting of interconnected concave Ag nanoshells is demonstrated by depositing a thin layer of Ag atop a sacrificial electrospun nanofiber template and then completely removing the cellulose core in water. Our investigations of the scattering properties and SERS performances of single isolated Ag nanotroughs of different diameters reveal that nanotrough-based substrates provide tunable optical responses and enhanced SERS intensities. Further, Ag CNNs are fabricated in highly interconnected networks that yield reproducible SERS signals for molecular monolayers and whole bacterial cells, enabling rapid spectral discrimination between different bacterial strains. Finally, by performing principal component analysis on a large number of measured SERS spectra (40 spectra per bacterium), we demonstrate successful spectral discrimination between two types of Escherichia coli ( E. coli) bacteria, that is, E. coli K12 with its derivative E. coli DH 5α and E. coli BL21(DE3). The demonstrated cost-effective substrates feature several advantages over conventional SERS substrates including environmentally friendly and scalable fabrication compatible with versatile devices and provide an alternative approach to rapid SERS detection and screening of biochemicals.

Highly Sensitive Surface-Enhanced Raman Spectroscopy Substrates of Ag@PAN Electrospinning Nanofibrous Membranes for Direct Detection of Bacteria

“…and composite nanofibers. 19,20 In our previous work, 21 −23 we reported polymer nanofibers incorporated with Ag NPs or Ag NWs and verified the antibacterial and SERS activities for target molecules of 4mercaptophenol (4-MPh). Subsequently, in order to achieve multifunctional applications of the nanofibrous membrane, we fabricated TiO 2 electrospinning substrates loaded with Ag NPs and provided not only a possibility for SERS detection of bacteria but also excellent antibacterial activities.…”

“…Electrospinning technology, as a convenient and versatile strategy, can be qualified for fabrication of polymers and inorganic (TiO 2 , SiO 2 , etc.) and composite nanofibers. , …”

Bacteria Detection: From Powerful SERS to Its Advanced Compatible Techniques

“…To improve the performance of SERS tags in bacterial detection, various metal substrates have been employed for the signal enhancement, such as Au and Ag NPs, [91] Au@Ag nanorods, [92] Figure 7. a) Schematic illustration of the synthesis of Au-Van SERS tags and the procedure for S. aureus detection via the dual-recognition SERS biosensor. Reproduced with permission.…”

“…To improve the performance of SERS tags in bacterial detection, various metal substrates have been employed for the signal enhancement, such as Au and Ag NPs, [ 91 ] Au@Ag nanorods, [ 92 ] SiO 2 @Au core/shell NPs, [ 93 ] oxide@Au nanoovals, [ 94 ] and Ta@Ag array. [ 95 ] The enhancement factor (EF) is far greater than 10 10 , and can be used for the SERS detection of a single molecule.…”

Surface-enhanced Raman scattering (SERS) spectroscopy platforms for enhanced detection at the nanobio interface: from metabolites to microorganisms

“…In another study, PCA shows distinct, non-overlapping clusters between SERS spectra of different strain types, namely E. coli BL21 from E. coli K12 and E. coli DH 5α, and clear overlap of SERS spectra from the latter two, which are of same origin but derivatives of each other (Figure 1.11C). 93 These studies emphasize the utility of PCA for rapid and sensitive extraction of dominant, relevant inter-class spectral differences, despite interferences from intra-cluster spectral variation due to inevitable sample heterogeneity such as heterogeneous exosome surface compositions even among exosomes derived from the same cell types. In addition to knowledge discovery, another advantage of PCA is that it is an effective dimension reduction technique commonly leveraged as a data preprocessing step to improve prediction accuracies.…”