Improving Sensitivity and Reproducibility of SERS Sensing in Microenvironments Using Individual, Optically Trapped Surface-Enhanced Raman Spectroscopy(SERS) Probes

2016 ◽  
Vol 71 (2) ◽  
pp. 279-287 ◽  
Author(s):  
Pietro Strobbia ◽  
Adam Mayer ◽  
Brian M Cullum
Keyword(s):  
Raman Spectroscopy ◽  
Optical Tweezers ◽  
Surface Enhanced Raman Spectroscopy ◽  
High Signal ◽  
Specific Information ◽  
Laser Fluences ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Trapped Surface ◽  
Tip Enhanced Raman Spectroscopy

Surface-enhanced Raman spectroscopy (SERS) sensors offer many advantages for chemical analyses, including the ability to provide chemical specific information and multiplexed detection capability at specific locations. However, to have operative SERS sensors for probing microenvironments, probes with high signal enhancement and reproducibility are necessary. To this end, dynamic enhancement of SERS (i.e., in-situ amplification of signal-to-noise and signal-to-background ratios) from individual probes has been explored. In this paper, we characterize the use of optical tweezers to amplify SERS signals as well as suppress background signals via trapping of individual SERS active probes. This amplification is achieved through a steady presence of a single “hot” particle in the focus of the excitation laser. In addition to increases in signal and concomitant decreases in non-SERS backgrounds, optical trapping results in an eightfold increase in the stability of the signal as well. This enhancement strategy was demonstrated using both single and multilayered SERS sub-micron probes, producing combined signal enhancements of 24-fold (beyond the native 106 SERS enhancement) for a three-layered geometry. The ability to dynamically control the enhancement offers the possibility to develop SERS-based sensors and probes with tailored sensitivities. In addition, since this trapping enhancement can be used to observe individual probes with low laser fluences, it could offer particular interest in probing the composition of microenvironments not amenable to tip-enhanced Raman spectroscopy or other scanning probe methods (e.g., intracellular analyses, etc.).

scholarly journals Drug-resistant Staphylococcus aureus bacteria detection by combining surface-enhanced Raman spectroscopy (SERS) and deep learning techniques

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fatma Uysal Ciloglu ◽  
Abdullah Caliskan ◽  
Ayse Mine Saridag ◽  
Ibrahim Halil Kilic ◽  
Mahmut Tokmakci ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Raman Spectroscopy ◽  
Deep Learning ◽  
Surface Enhanced Raman Spectroscopy ◽  
Resistant Bacteria ◽  
High Signal ◽  
Antibiotic Resistant Bacteria ◽  
Antibiotic Resistant ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

AbstractOver the past year, the world's attention has focused on combating COVID-19 disease, but the other threat waiting at the door—antimicrobial resistance should not be forgotten. Although making the diagnosis rapidly and accurately is crucial in preventing antibiotic resistance development, bacterial identification techniques include some challenging processes. To address this challenge, we proposed a deep neural network (DNN) that can discriminate antibiotic-resistant bacteria using surface-enhanced Raman spectroscopy (SERS). Stacked autoencoder (SAE)-based DNN was used for the rapid identification of methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-sensitive S. aureus (MSSA) bacteria using a label-free SERS technique. The performance of the DNN was compared with traditional classifiers. Since the SERS technique provides high signal-to-noise ratio (SNR) data, some subtle differences were found between MRSA and MSSA in relative band intensities. SAE-based DNN can learn features from raw data and classify them with an accuracy of 97.66%. Moreover, the model discriminates bacteria with an area under curve (AUC) of 0.99. Compared to traditional classifiers, SAE-based DNN was found superior in accuracy and AUC values. The obtained results are also supported by statistical analysis. These results demonstrate that deep learning has great potential to characterize and detect antibiotic-resistant bacteria by using SERS spectral data.

scholarly journals Spectroscopic characterization of sixteenth century panel painting references using Raman, surface-enhanced Raman spectroscopy and helium-Raman system for in situ analysis of Ibero-American Colonial paintings

2016 ◽  
Vol 374 (2082) ◽  
pp. 20160051 ◽  
Author(s):  
María Angélica García-Bucio ◽  
Edgar Casanova-González ◽  
José Luis Ruvalcaba-Sil ◽  
Elsa Arroyo-Lemus ◽  
Alejandro Mitrani-Viggiano
Keyword(s):  
Raman Spectroscopy ◽  
Sixteenth Century ◽  
Latin American ◽  
Surface Enhanced Raman Spectroscopy ◽  
Specific Information ◽  
Panel Painting ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Panel Paintings

Colonial panel paintings constitute an essential part of Latin-American cultural heritage. Their study is vital for understanding the manufacturing process, including its evolution in history, as well as its authorship, dating and other information significant to art history and conservation purposes. Raman spectroscopy supplies a non-destructive characterization tool, which can be implemented for in situ analysis, via portable equipment. Specific methodologies must be developed, comprising the elaboration of reference panel paintings using techniques and materials similar to those of the analysed period, as well as the determination of the best analysis conditions for different pigments and ground preparations. In order to do so, Raman spectroscopy at 532, 785 and 1064 nm, surface-enhanced Raman spectroscopy (SERS) and a helium-Raman system were applied to a panel painting reference, in combination with X-ray fluorescence analysis. We were able to establish the analysis conditions for a number of sixteenth century pigments and dyes, and other relevant components of panel paintings from this period, 1064 nm Raman and SERS being the most successful. The acquired spectra contain valuable specific information for their identification and they conform a very useful database that can be applied to the analysis of Ibero-American Colonial paintings. This article is part of the themed issue ‘Raman spectroscopy in art and archaeology’.

scholarly journals Optical tweezers-controlled hotspot for sensitive and reproducible surface-enhanced Raman spectroscopy characterization of native protein structures

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Xin Dai ◽  
Wenhao Fu ◽  
Huanyu Chi ◽  
Vince St. Dollente Mesias ◽  
Hongni Zhu ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Optical Tweezers ◽  
Single Molecule ◽  
Protein Structures ◽  
Surface Enhanced Raman Spectroscopy ◽  
Alpha Synuclein ◽  
Ensemble Averaging ◽  
Physiological Concentration ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

AbstractSurface-enhanced Raman spectroscopy (SERS) has emerged as a powerful tool to detect biomolecules in aqueous environments. However, it is challenging to identify protein structures at low concentrations, especially for the proteins existing in an equilibrium mixture of various conformations. Here, we develop an in situ optical tweezers-coupled Raman spectroscopy to visualize and control the hotspot between two Ag nanoparticle-coated silica beads, generating tunable and reproducible SERS enhancements with single-molecule level sensitivity. This dynamic SERS detection window is placed in a microfluidic flow chamber to detect the passing-by proteins, which precisely characterizes the structures of three globular proteins without perturbation to their native states. Moreover, it directly identifies the structural features of the transient species of alpha-synuclein among its predominant monomers at physiological concentration of 1 μM by reducing the ensemble averaging. Hence, this SERS platform holds the promise to resolve the structural details of dynamic, heterogeneous, and complex biological systems.

scholarly journals Comparison of 4-Mercaptobenzoic Acid Surface-Enhanced Raman Spectroscopy-Based Methods for pH Determination in Cells

2020 ◽  
Vol 74 (11) ◽  
pp. 1423-1432
Author(s):  
Brian T. Scarpitti ◽  
Amy M. Morrison ◽  
Marina Buyanova ◽  
Zachary D. Schultz
Keyword(s):  
Raman Spectroscopy ◽  
Frequency Shift ◽  
Intracellular Ph ◽  
Surface Enhanced Raman Spectroscopy ◽  
Therapeutic Drug ◽  
High Signal ◽  
Signal To Noise ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
In Cells

Measurements of cellular pH are used to infer information such as stage of cell cycle, presence of cancer and other diseases, as well as delivery or effect of a therapeutic drug. Surface-enhanced Raman spectroscopy (SERS) of nanoparticle-based pH probes have been used to interrogate intracellular pH, with the significant advantage of avoiding photobleaching compared to fluorescent indicators. 4-Mercaptobenzoic acid (MBA) is a commonly used pH-sensitive reporter molecule. Intracellular pH sensing by SERS requires analysis of the observed MBA spectrum and spectral interference can affect the pH determination. Background from common cell containers, imaging too few particles, signal-to-noise ratios, and degradation of reporter molecules are among the factors that may alter appropriate SERS-based pH determination in cells. Here, we have compared common methods of spectral analysis to see how different factors alter the calculated pH in Raman maps of MBA functionalized Au nanostars in SW620 cancer cells. The methods included in our comparison use the relative intensity of the ν(COO–) stretch, chemometric analysis of the ν8a mode, and analyzing the frequency shift of the ν8a mode. These methods show different sensitivity to some of these sources of error in live cell experiments. pH determination based on Raman frequency shift appears to give a more reliable pH determination, though in high signal-to-noise environments, intensity ratios may provide better sensitivity to small changes in pH for cellular imaging.

scholarly journals Highly stable SERS pH nanoprobes produced by co-solvent controlled AuNP aggregation

The Analyst ◽  
2016 ◽  
Vol 141 (17) ◽  
pp. 5159-5169 ◽  
Author(s):  
Haoran Wei ◽  
Marjorie R. Willner ◽  
Linsey C. Marr ◽  
Peter J. Vikesland
Keyword(s):  
Raman Spectroscopy ◽  
Gold Nanoparticle ◽  
Signal Intensity ◽  
Surface Enhanced Raman Spectroscopy ◽  
High Signal Intensity ◽  
High Signal ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Aunp Surface

Production of gold nanoparticle (AuNP) surface-enhanced Raman spectroscopy (SERS) nanoprobes requires replicable aggregation to produce multimers with high signal intensity.

Bacterial detection and differentiation via direct volatile organic compound sensing with surface enhanced Raman spectroscopy

2017 ◽  
Author(s):  
Caitlin S. DeJong ◽  
David I. Wang ◽  
Aleksandr Polyakov ◽  
Anita Rogacs ◽  
Steven J. Simske ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Bacterial Infections ◽  
Direct Detection ◽  
Point Of Care ◽  
Surface Enhanced Raman Spectroscopy ◽  
E Coli ◽  
Recent Emergence ◽  
Surface Enhanced ◽  
Volatile Organic ◽  
Surface Enhanced Raman

Through the direct detection of bacterial volatile organic compounds (VOCs), via surface enhanced Raman spectroscopy (SERS), we report here a reconfigurable assay for the identification and monitoring of bacteria. We demonstrate differentiation between highly clinically relevant organisms: <i>Escherichia coli</i>, <i>Enterobacter cloacae</i>, and <i>Serratia marcescens</i>. This is the first differentiation of bacteria via SERS of bacterial VOC signatures. The assay also detected as few as 10 CFU/ml of <i>E. coli</i> in under 12 hrs, and detected <i>E. coli</i> from whole human blood and human urine in 16 hrs at clinically relevant concentrations of 10<sup>3</sup> CFU/ml and 10<sup>4</sup> CFU/ml, respectively. In addition, the recent emergence of portable Raman spectrometers uniquely allows SERS to bring VOC detection to point-of-care settings for diagnosing bacterial infections.

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