SERSTEM: An app for the statistical analysis of correlative SERS and TEM imaging and evaluation of SERS tags performance

Abstract

Raman spectroscopy is becoming increasingly popular as an in vitro bioimaging technique, when coupled with plasmonic substrates such as gold nanoparticles (AuNPs). Plasmonic AuNPs not only display excellent biocompatibility but can also induce the surface‐enhanced Raman scattering (SERS) effect, which can be exploited for cell labeling, as an interesting alternative to fluorescence‐based techniques. SERS bioimaging requires the use of so‐called SERS tags or SERS‐encoded AuNPs. A remaining difficulty toward the general implementation of this method is the difficulty to correlate the SERS signal (spectral intensity) with the number of SERS tags. Therefore, a general correlation method, suitable for arbitrary AuNP morphologies and Raman‐active molecules (Raman reporters or RaRs), should largely improve the quantitative character of SERS as an imaging technique. We propose a protocol, with an associated app (SERSTEM), which enables the user to determine the average SERS intensity per nanoparticle from transmission electron microscopy (TEM) and SERS data. As a proof of concept, we demonstrated the method for Au nanostars and nanorods, carrying four different RaRs, and implemented the SERSTEM app, which is publicly available from an open‐source platform.

SERS and Fluorescence-Active Multimodal Tessellated Scaffolds for Three-Dimensional Bioimaging

“…We denoted these SERS tags as AuNS-1NAT, AuNS-2NAT, and AuNS-MBT. The choice of 1NAT, 2NAT, and MBT as the Raman reporter molecules allowed multiplexing through their spectral features, which could be distinguished using postprocessing tools such as multiple linear regression analysis (MLRA) 38 or True Component Analysis (Figure 2A). Indeed, exposure of HDF cells to all three SERS tag formulations for 24 h resulted in high levels of uptake (ca.…”

“…This is especially important if we consider the long irradiation times (in the scale of many hours for large samples) required to achieve high resolution 3D SERS maps. For the data analysis, we took advantage of the True Component Analysis tool, a postprocessing function provided in the Witec Raman microscope software, or MLRA 38 analysis when using our Renishaw Raman microscope. Both methods are suitable for dealing with large data sets with multiple components, allowing their separation in a fast and convenient way.…”

Preface to the special issue dedicated to Professor Richard P. Van Duyne (1945–2019)

“…As a proof of concept, they demonstrated the method for Au nanostars and nanorods, carrying four different Raman reporters, and implemented in the SERSTEM App, which is publicly available from an open‐source platform. [ 9 ]…”

“…As a proof of concept, they demonstrated the method for Au nanostars and nanorods, carrying four different Raman reporters, and implemented in the SERSTEM App, which is publicly available from an open-source platform. [9] Zhang, Dong, et al study the formation of ordered supramolecular self-assembly substrates based on cytosine and 4,4-bipyridine adsorption on Ag(111) with subnanometer-resolved TERS using a low-temperature ultrahigh-vacuum scanning tunneling microscope (STM). The combination of sub-nanometer resolution TERS and STM imaging reveals interactions between the twocomponent samples and nearby molecules.…”

Combination of Live Cell Surface-Enhanced Raman Scattering Imaging with Chemometrics to Study Intracellular Nanoparticle Dynamics

“… 8 We have previously demonstrated that similar polymer-coated SERS tags are highly stable in in vitro environments, thanks to the colloidal stability imparted by the polymeric outer coating, which helps prevent AuNP aggregation, even in oxidizing environments. 10 On the basis of a previously reported method for the correlation of SERS tag intensities with the number of labeled AuNPs in a given area (SERSTEM), 23 we demonstrate herein the applicability of this method in biological samples by characterizing cellular uptake of SERS tags. Considering the biologically complex microenvironment within in vitro samples, it is crucial to correctly extract the signal of the SERS tags from the background, i.e., media, cell proteins, cell metabolites, etc.…”