A sequence-specific detection method of DNA is presented combining a solid chip surface for immobilisation of capture DNAs with a microfluidic platform and a readout of the chip based on SERS. The solid chip surface is used for immobilisation of different capture DNAs, where target strands can be hybridised and unbound surfactants can be washed away. For the detection via SERS, short-labelled oligonucleotides are hybridised to the target strands. This technique is combined with a microfluidic platform that enables a fast and automated preparation process. By applying a chip format, the problems of sequence-specific DNA detection in solution phase by means of SERS can be overcome. With this setup, we are able to distinguish between different complementary and non-complementary target sequences in one sample solution.

SummarySilver nanoparticles were synthesized by an enzyme-induced growth process on solid substrates. In order to customize the enzymatically grown nanoparticles (EGNP) for analytical applications in biomolecular research, a detailed study was carried out concerning the time evolution of the formation of the silver nanoparticles, their morphology, and their chemical composition. Therefore, silver-nanoparticle films of different densities were investigated by using scanning as well as transmission electron microscopy to examine their structure. Cross sections of silver nanoparticles, prepared for analysis by transmission electron microscopy were additionally studied by energy-dispersive X-ray spectroscopy in order to probe their chemical composition. The surface coverage of substrates with silver nanoparticles and the maximum particle height were determined by Rutherford backscattering spectroscopy. Variations in the silver-nanoparticle films depending on the conditions during synthesis were observed. After an initial growth state the silver nanoparticles exhibit the so-called desert-rose or nanoflower-like structure. This complex nanoparticle structure is in clear contrast to the auto-catalytically grown spherical particles, which maintain their overall geometrical appearance while increasing their diameter. It is shown, that the desert-rose-like silver nanoparticles consist of single-crystalline plates of pure silver. The surface-enhanced Raman spectroscopic (SERS) activity of the EGNP structures is promising due to the exceptionally rough surface structure of the silver nanoparticles. SERS measurements of the vitamin riboflavin incubated on the silver nanoparticles are shown as an exemplary application for quantitative analysis.

Here we present a novel approach using surface-enhanced Raman scattering (SERS) spectroscopy for the sequence-specific detection of DNA utilizing magnetic nanoparticles (MNPs) for the enrichment of the target molecules. To achieve fast and efficient binding of longer DNA strands, e.g. PCR products, the hybridization procedure is performed in solution. To further purify and enrich the DNA strands of interest, MNPs are used for their separation. Following the binding of the target DNA, a dye-modified, short synthetic ssDNA is hybridized, which serves as label for the SERS detection. The SERS spectra are used to identify the bound molecules. The applicability of this approach was first tested with short synthetic oligonucleotides to evaluate its specificity. Afterward, the system was applied to detect PCR products amplified from DNA of specific agents of epizootic diseases. Sequences of the bacterium Mycoplasma mycoides subspecies mycoides small colony type (MmmSC), causing contagious bovine pleuropneumonia (CBPP) were used as PCR targets. To demonstrate the multiplexing capability of SERS, the simultaneous detection of three different PCR products labeled with three dyes was performed.

Surface-enhanced Raman spectroscopy (SERS) is an emerging technology in the field of analytics. Due to the high sensitivity in connection with specific Raman molecular fingerprint information SERS can be used in a variety of analytical, bioanalytical, and biosensing applications. However, for the SERS effect substrates with metal nanostructures are needed. The broad application of this technology is greatly hampered by the lack of reliable and reproducible substrates. Usually the activity of a given substrate has to be determined by time-consuming experiments such as calibration or ultramicroscopic studies. To use SERS as a standard analytical tool, cheap and reproducible substrates are required, preferably with a characterization technique that does not interfere with the subsequent measurements. Herein we introduce an innovative approach to produce low-cost and large-scale reproducible substrates for SERS applications, which allows easy and economical production of micropatterned SERS active surfaces on a large scale. This approach is based on an enzyme-induced growth of silver nanostructures. The special structural feature of the enzymatically deposited silver nanoparticles prevents the breakdown of SERS activity even at high particle densities (particle density >60%) that lead to a conductive layer. In contrast to other approaches, this substrate exhibits a relationship between electrical conductivity and the resulting SERS activity of a given spot. This enables the prediction of the SERS activity of the nanostructure ensemble and therewith the controllable and reproducible production of SERS substrates of enzymatic silver nanoparticles on a large scale, utilizing a simple measurement of the electrical conductivity. Furthermore, through a correlation between the conductivity and the SERS activity of the substrates it is possible to quantify SERS measurements with these substrates.

No abstract

In this paper, a method for the detection of norbixin and tartrazine in sugar by means of resonance Raman spectroscopy is presented. The extraction was done in four steps using methanol and the measurements were performed in aqueous solution. The excitation wavelength was 514 nm for norbixin and 488 nm for tartrazine samples. The characteristic resonance Raman signals of the dyes were fitted by different functions. Depending on the R² values of the different fits, each spectrum was classified as positive or negative response. A detection limit of 250 ng g⁻¹ for norbixin and 989 ng g⁻¹ for tartrazine in solid sugar samples could be reached by logistic regression.

No abstract

No abstract