On-chip approach for traceable quantification of biomarkers based on isotope-dilution surface-enhanced Raman scattering (IDSERS)

Yaghobian, Fatemeh; Weimann, Thomas; Güttler, Bernd; Stosch, Rainer

doi:10.1039/c1lc20032a

Cited by 9 publications

(6 citation statements)

References 34 publications

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“…8,14,22,28,30,32,[34][35][36][37]39 Normalization using an internal standard to correct for changes in the sample properties, SERS substrate, or laser beam intensity during the acquisition period is also used for quantification. 26,29,33,41 However, signal averaging might not be appropriate in attempts to use SERS probes to map an analyte that is nonuniformly distributed over a surface, as in the case of a planar assay platform or in the in vitro detection of cell membrane proteins. When mapping a surface, the SERS intensity at each acquisition point depends on the number of NPs at that point and how they are grouped (aggregated) relative to each other.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Typically, the NPs are coated with a Raman reporter molecule and functionalized with an antibody for a particular biomarker of interest to impart selectivity to the assays. ,,− , The NP-reporter-antibody platforms used in these types of applications are known as “SERS probes”. In order to be comparable to more traditional immunoassay techniques, such as the enzyme-linked immunosorbent assay (ELISA), quantification of the detected biomolecules is necessary, and has been attempted in SERS with promising results in many cases. ,,,,,− ,,− However, a well-known difficulty with SERS is the highly variable signal intensity, due to its dependence on the structure of the SERS-active substrate. ,,− In the case of metal nanoparticles, the size, shape, and interparticle distance at the probed area all have a strong influence on the observed SERS intensity. ,− ,, …”

Section: Introductionmentioning

confidence: 99%

“…While modern techniques allow for a great degree of control over the size and shape of NPs, , the random degree of aggregation of SERS probes during an assay can potentially lead to wild variations in SERS signal. If the SERS probes are introduced to a sample that is in solution and assumed to have a relatively uniform target molecule (analyte) concentration, the variations in measured SERS intensity can be addressed by simply performing spectral averaging throughout the sample. ,,,,,,− , Normalization using an internal standard to correct for changes in the sample properties, SERS substrate, or laser beam intensity during the acquisition period is also used for quantification. ,,, …”

Section: Introductionmentioning

confidence: 99%

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Statistical Correlation Between SERS Intensity and Nanoparticle Cluster Size

et al. 2013

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Surface enhanced Raman scattering (SERS) mapping of biomarkers has shown great promise in determining the distribution of proteins of interest in cells and tissues. Metallic nanoparticle (NP) probes are generally used in such mapping. Since SERS intensities from NPs are dependent on size, shape, and interparticle distance/distribution, it is unclear if this method can provide reliable biomarker quantification. To address this problem, we investigated a statistical approach to the quantification of SERS from SERS probe clusters. The investigation began by considering multiple biotinylated surfaces that had been exposed to pegylated NPs (designed for biological SERS mapping) functionalized with streptavidin (defined as SERS probes). The surfaces were imaged with a scanning electron microscope and SERS-mapped with a Raman microscope. Statistical distributions of the SERS probe clusters and mapped SERS intensities on the surfaces were developed. It was found that there was a smooth polynomial relationship between SERS intensity and probe cluster size. Our result is in contrast to the sharp, highly variable intensity increases observed in studies of unmodified NPs. Based on the polynomial relationship found, it is clear that pegylated NP SERS probes might be useful for quantification in the SERS mapping of biological material, as the SERS intensity can be potentially related back to the number of probes at the acquisition point.

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Section: ■ Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Statistical Correlation Between SERS Intensity and Nanoparticle Cluster Size

et al. 2013

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“…A promising and direct application of nanoplasmonics is the surface-enhanced Raman spectroscopy (SERS) [6][7][8][9], where metallic structures are used as antennas in order to enhance both the cross section and the field intensity [10,11] for Raman scattering. The most effective structures employed in early SERS studies were colloidal gold or silver particles [12][13][14], which provide dramatic enhancement factors in correspondence to randomly distributed hot spots.…”

Section: Introductionmentioning

confidence: 99%

Tailored nanoantennas for directional Raman studies of individual carbon nanotubes

et al. 2015

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We exploit the near field enhancement of nanoantennas to investigate the Raman spectra of otherwise not optically detectable carbon nanotubes (CNTs). We demonstrate that a top-down fabrication approach is particularly promising when applied to CNTs, owing to the sharp dependence of the scattered intensity on the angle between incident light polarization and CNT axis. In contrast to tip enhancement techniques, our method enables us to control the light polarization in the sample plane, locally amplifying and rotating the incident field and hence optimizing the Raman signal. Such promising features are confirmed by numerical simulations presented here. The relative ease of fabrication and alignment makes this technique suitable for the realization of integrated devices that combine scanning probe, optical, and transport characterization.

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“…To achieve highest sensitivity, Raman spectroscopy is combined with nanotechnologies resulting in plasmon resonant signal enhancement, known as surface-enhanced Raman scattering (SERS). Coupling of the analyte to suitable metallic nanostructures or nanoparticles does not only improve the detection limits down to the sub μg/g level, but also opens the opportunity for integrating these methods into lab-on-a-chip devices [ 10 ]. However, specific detection and SI-traceable quantification of large clinical biomarkers occurring at extremely low concentrations is still challenging.…”

Section: Proteins: Traceable Quantification For Detection and Monitormentioning

confidence: 99%

Biomacromolecules as tools and objects in nanometrology—current challenges and perspectives

et al. 2017

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Nucleic acids, proteins, and polysaccharides are the most important classes of biopolymers. The inherent properties of biomacromolecules are contrary to those of well-defined small molecules consequently raising a number of specific challenges which become particularly apparent if biomacromolecules are treated as objects in quantitative analysis. At the same time, their specific functional ability of molecular recognition and self-organization (e.g., enzymes, antibodies, DNA) enables us to make biomacromolecules serving as molecular tools in biochemistry and molecular biology, or as precisely controllable dimensional platforms for nanometrological applications. Given the complexity of biomacromolecules, quantitative analysis is not limited to the measurement of their concentration but also involves the determination of numerous descriptors related to structure, interaction, activity, and function. Among the biomacromolecules, glycans set examples that quantitative characterization is not necessarily directed to the measurement of amount-of-substance concentration but instead involves the determination of relative proportions (molar ratios) of structural features for comparison with theoretical models. This article addresses current activities to combine optical techniques such as Raman spectroscopy with isotope dilution approaches to realize reference measurement procedures for the quantification of protein biomarkers as an alternative to mass spectrometry-based techniques. Furthermore, it is explored how established ID-MS protocols are being modified to make them applicable for quantifying virus proteins to measure the HIV viral load in blood samples. As an example from the class of carbohydrates, the challenges in accurate determination of substitution patterns are outlined and discussed. Finally, it is presented that biomacromolecules can also serve as tools in quantitative measurements of dimensions with an example of DNA origami to generate defined dimensional standards to be used for calibration in super-resolution fluorescence microscopy. Graphical abstractQuantitative analysis of biomacromolecules is accompanied with special challenges different from low molecular weight compounds. In addition, they are not only objects but also tools applicable for quantitative measurements

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On-chip approach for traceable quantification of biomarkers based on isotope-dilution surface-enhanced Raman scattering (IDSERS)

Cited by 9 publications

References 34 publications

Statistical Correlation Between SERS Intensity and Nanoparticle Cluster Size

Statistical Correlation Between SERS Intensity and Nanoparticle Cluster Size

Tailored nanoantennas for directional Raman studies of individual carbon nanotubes

Biomacromolecules as tools and objects in nanometrology—current challenges and perspectives

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