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Applications of Raman Spectroscopy in Biosensors

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: closed (31 May 2017) | Viewed by 82996

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Special Issue Editors

Prof. Zachary J. Smith

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Guest Editor

Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230000, China
Interests: raman spectroscopy for biomedical applications; spectroscopic instrumentation; biomedical data analysis; low cost and portable diagnostics; microscopy and super resolution

Prof. Dr. Sebastian Wachsmann-Hogiu

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Guest Editor

Department of Bioengineering, McGill University, Montreal, QC H3A 0G4, Canada
Interests: plasmonics-based sensors and assays; structure-derived functionality of materials; M(O)EMS; biomimetics; point of care technologies

Special Issue Information

Dear Colleagues,

Raman spectroscopy is a non-invasive tool to quantitatively and qualitatively assess the chemical content of a wide range of biological samples. It has found great use in classifying disease states of cells and tissues, in imaging of living cells and organisms, and in quantitatively assessing chemical content of biofluids, tissues, and even subcellular organelles. This is all possible without the use of labels or other chemicals that could potentially perturb the fragile dynamics of biological systems. This sensitivity and versatility has allowed Raman to find wide use in biosensing applications. In addition to traditional spontaneous Raman spectroscopy, plasmonic techniques, such as SERS and TERS, have allowed the development more rapid and specific Raman-based biosensors, while multiphoton methods, such as CARS and SRS, allow the recording of high-speed movies of biological dynamics, even deep within tissue. Adding to this rich landscape are a myriad of data analysis techniques to extract the most out of the highly mixed Raman spectra. These include both standard methods such as least squares and principal components, along with emerging methods, such as multivariate curve resolution and vertex component analysis.

We invite manuscripts for this forthcoming Special Issue that describe all aspects of Raman-based biosensing and bioimaging. We are seeking both reviews and original research articles. Reviews should provide an up-to-date and critical overview of the current state of the art in a particular application, such as cancer diagnostics or intracellular sensing, or particular techniques, such as hyperspectral imaging or endoscopy. Original research papers that describe the utilization of Raman spectroscopy applied to biological and medical applications will be the main focus, yet new concepts and fundamental studies that have strong potential for biosensing are also of interest. If you any questions or would like to discuss your submission beforehand, we encourage you to reach out and contact us. We look forward to and welcome your participation in this Special Issue.

Prof. Sebastian Wachsmann-Hogiu
Prof. Zachary J. Smith
Guest Editors

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Keywords

Raman

SERS

CARS

hyperspectral imaging

spectral analysis

multivariate analysis, biosensing

label-free

cellular imaging

cellular dynamics

plasmonics

cancer

disease detection

point-of-care

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Published Papers (11 papers)

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3179 KiB

Open AccessArticle

Evaluation of Shifted Excitation Raman Difference Spectroscopy and Comparison to Computational Background Correction Methods Applied to Biochemical Raman Spectra

by Eliana Cordero, Florian Korinth, Clara Stiebing, Christoph Krafft, Iwan W. Schie and Jürgen Popp

Sensors 2017, 17(8), 1724; https://doi.org/10.3390/s17081724 - 27 Jul 2017

Cited by 40 | Viewed by 8519

Abstract

Raman spectroscopy provides label-free biochemical information from tissue samples without complicated sample preparation. The clinical capability of Raman spectroscopy has been demonstrated in a wide range of in vitro and in vivo applications. However, a challenge for in vivo applications is the simultaneous excitation of auto-fluorescence in the majority of tissues of interest, such as liver, bladder, brain, and others. Raman bands are then superimposed on a fluorescence background, which can be several orders of magnitude larger than the Raman signal. To eliminate the disturbing fluorescence background, several approaches are available. Among instrumentational methods shifted excitation Raman difference spectroscopy (SERDS) has been widely applied and studied. Similarly, computational techniques, for instance extended multiplicative scatter correction (EMSC), have also been employed to remove undesired background contributions. Here, we present a theoretical and experimental evaluation and comparison of fluorescence background removal approaches for Raman spectra based on SERDS and EMSC. Full article

(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)

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2735 KiB

Open AccessArticle

Detection of Pseudomonas aeruginosa Metabolite Pyocyanin in Water and Saliva by Employing the SERS Technique

by Olga Žukovskaja, Izabella Jolan Jahn, Karina Weber, Dana Cialla-May and Jürgen Popp

Sensors 2017, 17(8), 1704; https://doi.org/10.3390/s17081704 - 25 Jul 2017

Cited by 63 | Viewed by 8733

Abstract

Pyocyanin (PYO) is a metabolite specific for Pseudomonas aeruginosa. In the case of immunocompromised patients, it is currently considered a biomarker for life-threating Pseudomonas infections. In the frame of this study it is shown, that PYO can be detected in aqueous solution by employing surface-enhanced Raman spectroscopy (SERS) combined with a microfluidic platform. The achieved limit of detection is 0.5 μM. This is ~2 orders of magnitude below the concentration of PYO found in clinical samples. Furthermore, as proof of principle, the SERS detection of PYO in the saliva of three volunteers was also investigated. This body fluid can be collected in a non-invasive manner and is highly chemically complex, making the detection of the target molecule challenging. Nevertheless, PYO was successfully detected in two saliva samples down to 10 μM and in one sample at a concentration of 25 μM. This indicates that the molecules present in saliva do not inhibit the efficient adsorption of PYO on the surface of the employed SERS active substrates. Full article

(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)

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2100 KiB

Open AccessArticle

Substrate Oxide Layer Thickness Optimization for a Dual-Width Plasmonic Grating for Surface-Enhanced Raman Spectroscopy (SERS) Biosensor Applications

by Stephen J. Bauman, Zachary T. Brawley, Ahmad A. Darweesh and Joseph B. Herzog

Sensors 2017, 17(7), 1530; https://doi.org/10.3390/s17071530 - 30 Jun 2017

Cited by 15 | Viewed by 6988

Abstract

This work investigates a new design for a plasmonic SERS biosensor via computational electromagnetic models. It utilizes a dual-width plasmonic grating design, which has two different metallic widths per grating period. These types of plasmonic gratings have shown larger optical enhancement than standard single-width gratings. The new structures have additional increased enhancement when the spacing between the metal decreases to sub-10 nm dimensions. This work integrates an oxide layer to improve the enhancement even further by carefully studying the effects of the substrate oxide thickness on the enhancement and reports ideal substrate parameters. The combined effects of varying the substrate and the grating geometry are studied to fully optimize the device’s enhancement for SERS biosensing and other plasmonic applications. The work reports the ideal widths and substrate thickness for both a standard and a dual-width plasmonic grating SERS biosensor. The ideal geometry, comprising a dual-width grating structure atop an optimal SiO₂ layer thickness, improves the enhancement by 800%, as compared to non-optimized structures with a single-width grating and a non-optimal oxide thickness. Full article

(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)

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2304 KiB

Open AccessArticle

Analysis of Serotonin Molecules on Silver Nanocolloids—A Raman Computational and Experimental Study

by Felicia S. Manciu, John D. Ciubuc, Emma M. Sundin, Chao Qiu and Kevin E. Bennet

Sensors 2017, 17(7), 1471; https://doi.org/10.3390/s17071471 - 22 Jun 2017

Cited by 10 | Viewed by 5551

Abstract

Combined theoretical and experimental analysis of serotonin by quantum chemical density functional calculations and surface-enhanced Raman spectroscopy, respectively, is presented in this work to better understand phenomena related to this neurotransmitter’s detection and monitoring at very low concentrations specific to physiological levels. In addition to the successful ultrasensitive analyte detection on silver nanoparticles for concentrations as low as 10⁻¹¹ molar, the relatively good agreement between the simulated and experimentally determined results indicates the presence of all serotonin molecular forms, such as neutral, ionic, and those oxidized through redox reactions. Obvious structural molecular deformations such as bending of lateral amino chains are observed for both ionic and oxidized forms. Not only does this combined approach reveal more probable adsorption of serotonin into the silver surface through hydroxyl/oxygen sites than through NH/nitrogen sites, but also that it does so predominantly in its neutral (reduced) form, somewhat less so in its ionic forms, and much less in its oxidized forms. If the development of opto-voltammetric biosensors and their effective implementation is envisioned for the future, this study provides some needed scientific background for comprehending changes in the vibrational signatures of this important neurotransmitter. Full article

(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)

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762 KiB

Open AccessArticle

Diagnosis of Breast Cancer Tissues Using 785 nm Miniature Raman Spectrometer and Pattern Regression

by Qingbo Li, Can Hao and Zhi Xu

Sensors 2017, 17(3), 627; https://doi.org/10.3390/s17030627 - 19 Mar 2017

Cited by 22 | Viewed by 5082

Abstract

For achieving the development of a portable, low-cost and in vivo cancer diagnosis instrument, a laser 785 nm miniature Raman spectrometer was used to acquire the Raman spectra for breast cancer detection in this paper. However, because of the low spectral signal-to-noise ratio, it is difficult to achieve high discrimination accuracy by using the miniature Raman spectrometer. Therefore, a pattern recognition method of the adaptive net analyte signal (NAS) weight k-local hyperplane (ANWKH) is proposed to increase the classification accuracy. ANWKH is an extension and improvement of K-local hyperplane distance nearest-neighbor (HKNN), and combines the advantages of the adaptive weight k-local hyperplane (AWKH) and the net analyte signal (NAS). In this algorithm, NAS was first used to eliminate the influence caused by other non-target factors. Then, the distance between the test set samples and hyperplane was calculated with consideration of the feature weights. The HKNN only works well for small values of the nearest-neighbor. However, the accuracy decreases with increasing values of the nearest-neighbor. The method presented in this paper can resolve the basic shortcoming by using the feature weights. The original spectra are projected into the vertical subspace without the objective factors. NAS was employed to obtain the spectra without irrelevant information. NAS can improve the classification accuracy, sensitivity, and specificity of breast cancer early diagnosis. Experimental results of Raman spectra detection in vitro of breast tissues showed that the proposed algorithm can obtain high classification accuracy, sensitivity, and specificity. This paper demonstrates that the ANWKH algorithm is feasible for early clinical diagnosis of breast cancer in the future. Full article

(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)

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4327 KiB

Open AccessArticle

A Spatially Offset Raman Spectroscopy Method for Non-Destructive Detection of Gelatin-Encapsulated Powders

by Kuanglin Chao, Sagar Dhakal, Jianwei Qin, Yankun Peng, Walter F. Schmidt, Moon S. Kim and Diane E. Chan

Sensors 2017, 17(3), 618; https://doi.org/10.3390/s17030618 - 18 Mar 2017

Cited by 22 | Viewed by 8743

Abstract

Non-destructive subsurface detection of encapsulated, coated, or seal-packaged foods and pharmaceuticals can help prevent distribution and consumption of counterfeit or hazardous products. This study used a Spatially Offset Raman Spectroscopy (SORS) method to detect and identify urea, ibuprofen, and acetaminophen powders contained within one or more (up to eight) layers of gelatin capsules to demonstrate subsurface chemical detection and identification. A 785-nm point-scan Raman spectroscopy system was used to acquire spatially offset Raman spectra for an offset range of 0 to 10 mm from the surfaces of 24 encapsulated samples, using a step size of 0.1 mm to obtain 101 spectral measurements per sample. As the offset distance was increased, the spectral contribution from the subsurface powder gradually outweighed that of the surface capsule layers, allowing for detection of the encapsulated powders. Containing mixed contributions from the powder and capsule, the SORS spectra for each sample were resolved into pure component spectra using self-modeling mixture analysis (SMA) and the corresponding components were identified using spectral information divergence values. As demonstrated here for detecting chemicals contained inside thick capsule layers, this SORS measurement technique coupled with SMA has the potential to be a reliable non-destructive method for subsurface inspection and authentication of foods, health supplements, and pharmaceutical products that are prepared or packaged with semi-transparent materials. Full article

(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)

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3517 KiB

Open AccessArticle

Alternative cDEP Design to Facilitate Cell Isolation for Identification by Raman Spectroscopy

by Cynthia Hanson and Elizabeth Vargis

Sensors 2017, 17(2), 327; https://doi.org/10.3390/s17020327 - 9 Feb 2017

Cited by 10 | Viewed by 6284

Abstract

Dielectrophoresis (DEP) uses non-uniform electric fields to cause motion in particles due to the particles’ intrinsic properties. As such, DEP is a well-suited label-free means for cell sorting. Of the various methods of implementing DEP, contactless dielectrophoresis (cDEP) is advantageous as it avoids common problems associated with DEP, such as electrode fouling and electrolysis. Unfortunately, cDEP devices can be difficult to fabricate, replicate, and reuse. In addition, the operating parameters are limited by the dielectric breakdown of polydimethylsiloxane (PDMS). This study presents an alternative way to fabricate a cDEP device allowing for higher operating voltages, improved replication, and the opportunity for analysis using Raman spectroscopy. In this device, channels were formed in fused silica rather than PDMS. The device successfully trapped 3.3 μm polystyrene spheres for analysis by Raman spectroscopy. The successful implementation indicates the potential to use cDEP to isolate and identify biological samples on a single device. Full article

(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)

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4921 KiB

Open AccessArticle

Chemically Roughened Solid Silver: A Simple, Robust and Broadband SERS Substrate

by Shavini Wijesuriya, Krishna Burugapalli, Ruth Mackay, Godwin Chukwuebuka Ajaezi and Wamadeva Balachandran

Sensors 2016, 16(10), 1742; https://doi.org/10.3390/s16101742 - 19 Oct 2016

Cited by 21 | Viewed by 7948

Abstract

Surface-enhanced Raman spectroscopy (SERS) substrates manufactured using complex nano-patterning techniques have become the norm. However, their cost of manufacture makes them unaffordable to incorporate into most biosensors. The technique shown in this paper is low-cost, reliable and highly sensitive. Chemical etching of solid Ag metal was used to produce simple, yet robust SERS substrates with broadband characteristics. Etching with ammonium hydroxide (NH₄OH) and nitric acid (HNO₃) helped obtain roughened Ag SERS substrates. Scanning electron microscopy (SEM) and interferometry were used to visualize and quantify surface roughness. Flattened Ag wires had inherent, but non-uniform roughness having peaks and valleys in the microscale. NH₄OH treatment removed dirt and smoothened the surface, while HNO₃ treatment produced a flake-like morphology with visibly more surface roughness features on Ag metal. SERS efficacy was tested using 4-methylbenzenethiol (MBT). The best SERS enhancement for 1 mM MBT was observed for Ag metal etched for 30 s in NH₄OH followed by 10 s in HNO₃. Further, MBT could be quantified with detection limits of 1 pM and 100 µM, respectively, using 514 nm and 1064 nm Raman spectrometers. Thus, a rapid and less energy intensive method for producing solid Ag SERS substrate and its efficacy in analyte sensing was demonstrated. Full article

(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)

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6110 KiB

Open AccessArticle

Probing the Kinetic Anabolism of Poly-Beta-Hydroxybutyrate in Cupriavidus necator H16 Using Single-Cell Raman Spectroscopy

by Zhanhua Tao, Lixin Peng, Pengfei Zhang, Yong-Qing Li and Guiwen Wang

Sensors 2016, 16(8), 1257; https://doi.org/10.3390/s16081257 - 8 Aug 2016

Cited by 12 | Viewed by 7275

Abstract

Poly-beta-hydroxybutyrate (PHB) can be formed in large amounts in Cupriavidus necator and is important for the industrial production of biodegradable plastics. In this investigation, laser tweezers Raman spectroscopy (LTRS) was used to characterize dynamic changes in PHB content—as well as in the contents of other common biomolecule—in C. necator during batch growth at both the population and single-cell levels. PHB accumulation began in the early stages of bacterial growth, and the maximum PHB production rate occurred in the early and middle exponential phases. The active biosynthesis of DNA, RNA, and proteins occurred in the lag and early exponential phases, whereas the levels of these molecules decreased continuously during the remaining fermentation process until the minimum values were reached. The PHB content inside single cells was relatively homogenous in the middle stage of fermentation; during the late growth stage, the variation in PHB levels between cells increased. In addition, bacterial cells in various growth phases could be clearly discriminated when principle component analysis was performed on the spectral data. These results suggest that LTRS is a valuable single-cell analysis tool that can provide more comprehensive information about the physiological state of a growing microbial population. Full article

(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)

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Review

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3475 KiB

Open AccessReview

Raman Plus X: Biomedical Applications of Multimodal Raman Spectroscopy

by Nandan K. Das, Yichuan Dai, Peng Liu, Chuanzhen Hu, Lieshu Tong, Xiaoya Chen and Zachary J. Smith

Sensors 2017, 17(7), 1592; https://doi.org/10.3390/s17071592 - 7 Jul 2017

Cited by 32 | Viewed by 7429

Abstract

Raman spectroscopy is a label-free method of obtaining detailed chemical information about samples. Its compatibility with living tissue makes it an attractive choice for biomedical analysis, yet its translation from a research tool to a clinical tool has been slow, hampered by fundamental Raman scattering issues such as long integration times and limited penetration depth. In this review we detail the how combining Raman spectroscopy with other techniques yields multimodal instruments that can help to surmount the translational barriers faced by Raman alone. We review Raman combined with several optical and non-optical methods, including fluorescence, elastic scattering, OCT, phase imaging, and mass spectrometry. In each section we highlight the power of each combination along with a brief history and presentation of representative results. Finally, we conclude with a perspective detailing both benefits and challenges for multimodal Raman measurements, and give thoughts on future directions in the field. Full article

(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)

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949 KiB

Open AccessTechnical Note

Quantitative Raman Spectroscopy Analysis of Polyhydroxyalkanoates Produced by Cupriavidus necator H16

by Ota Samek, Stanislav Obruča, Martin Šiler, Petr Sedláček, Pavla Benešová, Dan Kučera, Ivana Márova, Jan Ježek, Silva Bernatová and Pavel Zemánek

Sensors 2016, 16(11), 1808; https://doi.org/10.3390/s16111808 - 28 Oct 2016

Cited by 24 | Viewed by 8518

Abstract

We report herein on the application of Raman spectroscopy to the rapid quantitative analysis of polyhydroxyalkanoates (PHAs), biodegradable polyesters accumulated by various bacteria. This theme was exemplified for quantitative detection of the most common member of PHAs, poly(3-hydroxybutyrate) (PHB) in Cupriavidus necator H16. We have identified the relevant spectral region (800–1800 cm⁻¹) incorporating the Raman emission lines exploited for the calibration of PHB (PHB line at 1736 cm⁻¹) and for the selection of the two internal standards (DNA at 786 cm⁻¹ and Amide I at 1662 cm⁻¹). In order to obtain quantitative data for calibration of intracellular content of PHB in bacterial cells reference samples containing PHB amounts—determined by gas chromatography—from 12% to 90% (w/w) were used. Consequently, analytical results based on this calibration can be used for fast and reliable determination of intracellular PHB content during biotechnological production of PHB since the whole procedure—from bacteria sampling, centrifugation, and sample preparation to Raman analysis—can take about 12 min. In contrast, gas chromatography analysis takes approximately 8 h. Full article

(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)

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