For the successful treatment of infections, real-time analysis and enhanced multiplex capacity, sensitivity and cost-effectiveness of the developed detection method are critical. In this work, surface-enhanced Raman scattering (SERS) was employed with the final aim of identification and discrimination of pathogenic bacteria, based on their detected SERS fingerprint at the single-cell level. Several genera of bacteria that are found in most of the isolated infections in bacteraemia were successfully identified in less than 5 minutes without the use of antibodies or other specific receptors. The key element of the SERS direct detection platform is the SERS substrate, which combines easy production at low costs with a high enhancement enabling single-cell detection. The innovative approach of detection required the in situ synthesis of silver nanoparticles (NPs), ensuring an intimate contact with the bacterial membrane. This protocol provided a good reproducibility of the single-cell SERS spectra and was successfully applied both on Gram-negative and Gram-positive microorganisms (E. coli, M. morganii, E. lactis, L. casei). Thus, a label-free SERS-based biosensor for pathogen detection was developed with low costs, minimal sample preparation, high-accuracy and a very short analysis time of less than 5 min, which is crucial for infection diagnosis.

In recent years, bioanalytical surface-enhanced Raman spectroscopy (SERS) has blossomed into a fast-growing research area. We present here a review on SERS-based assays with focus on early bacterial infection detection and chronic disease diagnosis.

Nonculture-based tests are gaining popularity and upsurge in the diagnosis of invasive fungal infections (IFI) fostered by their main asset, the reduced analysis time, which enables a more rapid diagnosis. In this project, three different clinical isolates of relevant filamentous fungal species were discriminated by using a rapid (less than 5 min) and sensitive surface-enhanced Raman scattering (SERS)-based detection method, assisted by chemometrics. The holistic evaluation of the SERS spectra was performed by employing appropriate chemometric tools-classical and fuzzy principal component analysis (FPCA) in combination with linear discriminant analysis (LDA) applied to the first relevant principal components. The efficiency of the proposed robust algorithm is illustrated on the data set including three fungal isolates (Aspergillus fumigatus sensu stricto, cryptic A. fumigatus complex species, and Rhizomucor pusillus) that were isolated from patient materials. The accurate and reliable discrimination between species of common fungal pathogen strains suggest that the developed method has the potential as an alternative, spectroscopic-based routine analysis tool in IFI diagnosis.

Herein, we developed a natural surface-enhanced Raman scattering (SERS) substrate based on size-tunable Au@Ag nanoparticle-coated mussel shell to form large-scale three-dimensional (3D) supercrystals (up to 10 cm2) that exhibit surface-laminated structures and crossed nanoplates and nanochannels. The high content of CaCO3 in the mussel shell results in superior hydrophobicity for analyte enrichment, and the crossed nanoplates and nanochannels provided rich SERS hot spots, which together lead to high sensitivity. Finite-difference time-domain simulations showed that nanoparticles in the channels exhibit apparently a higher electromagnetic field enhancement than nanoparticles on the platelets. Thus, under optimized conditions (using Au@AgNPs with 5 nm shell thickness), highly sensitive SERS detection with a detection limit as low as 10–9 M for rhodamine 6G was obtained. Moreover, the maximum electromagnetic field enhancement of different types of 3D supercrystals shows no apparent difference, and Au@AgNPs were uniformly distributed such that reproducible SERS measurements with a 6.5% variation (613 cm–1 peak) over 20 spectra were achieved. More importantly, the as-prepared SERS substrates can be utilized for the fast discrimination of Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa by discriminant analysis. This novel Au@Ag self-assembled mussel shell template holds considerable promise as low-cost, durable, sensitive, and reproducible substrates for future SERS-based biosensors.

Raman scattering and its particular effect, surface-enhanced Raman scattering (SERS), are whole-organism fingerprinting spectroscopic techniques that gain more and more popularity in bacterial detection. In this work, two relevant Gram-positive bacteria species, Lactobacillus casei (L. casei) and Listeria monocytogenes (L. monocytogenes) were characterized based on their Raman and SERS spectral fingerprints. The SERS spectra were used to identify the biochemical structures of the bacterial cell wall. Two synthesis methods of the SERS-active nanomaterials were used and the recorded spectra were analyzed. L. casei and L. monocytogenes were successfully discriminated by applying Principal Component Analysis (PCA) to their specific spectral data.

No abstract

No abstract

No abstract