A novel surface-enhanced Raman scattering (SERS) detection for natural gas exploration using methane-oxidizing bacteria

Simultaneous quantitative analysis of Escherichia coli, Staphylococcus aureus and Salmonella typhimurium using surface-enhanced Raman spectroscopy coupled with partial least squares regression and artificial neural networks

Simultaneous detection of mixed bacteria accurately and sensitively is a major challenge in microbial quality control field. In this study, we proposed a label-free SERS technique coupled with partial least squares regression (PLSR) and artificial neural networks (ANNs) for quantitative analysis of Escherichia coli, Staphylococcus aureus and Salmonella typhimurium simultaneously. SERS-active and reproducible Raman spectra can be acquired directly upon the bacteria and Au@Ag@SiO₂ nanoparticle composites on the surface of gold foil substrates. After applying different preprocessing models, SERS-PLSR and SERS-ANNs quantitative analysis models were developed to map SERS spectra of concentrations of the Escherichia coli, Staphylococcus aureus and Salmonella typhimurium, respectively. Both models achieved high prediction accuracy and low prediction error, while the performance of SERS-ANNs model in both quality of fit (R² > 0.95) and accuracy of predictions (RMSE < 0.06) was superior to SERS-PLSR model. Therefore, it is feasible to develop simultaneous quantitative analysis of mixed pathogenic bacteria by proposed SERS methodology.

A Microfluidic Biosensor Based on Magnetic Nanoparticle Separation, Quantum Dots Labeling and MnO2 Nanoflower Amplification for Rapid and Sensitive Detection of Salmonella Typhimurium

Screening of foodborne pathogens is an effective way to prevent microbial food poisoning. A microfluidic biosensor was developed for rapid and sensitive detection of Salmonella Typhimurium using quantum dots (QDs) as fluorescent probes for sensor readout and manganese dioxide nanoflowers (MnO2 NFs) and as QDs nanocarriers for signal amplification. Prior to testing, amino-modified MnO2 nanoflowers (MnO2-NH2 NFs) were conjugated with carboxyl-modified QDs through EDC/NHSS method to form MnO2-QD NFs, and MnO2-QD NFs were functionalized with polyclonal antibodies (pAbs) to form MnO2-QD-pAb NFs. First, the mixture of target Salmonella Typhimurium cells and magnetic nanoparticles (MNPs) modified with monoclonal antibodies (mAbs) was injected with MnO2-QD-pAb NFs into a microfluidic chip to form MNP-bacteria-QD-MnO2 complexes. Then, glutathione (GSH) was injected to dissolve MnO2 on the complexes into Mn2+, resulting in the release of QDs. Finally, fluorescent intensity of the released QDs was measured using the fluorescent detector to determine the amount of Salmonella. A linear relationship between fluorescent intensity and bacterial concentration from 1.0 × 102 to 1.0 × 107 CFU/mL was found with a low detection limit of 43 CFU/mL and mean recovery of 99.7% for Salmonella in spiked chicken meats, indicating the feasibility of this biosensor for practical applications.

'Mixing-and-measuring' surface-enhanced Raman scattering (SERS) detection of Bacillus cereus for potentially aiding gold mine field exploration

Bacillus cereus, a common soil bacterium, has been shown to act as a biogeochemical indicator for concealed mineralisations, e.g., vein-type Au deposits. Field and cultivation-free detection of Bacillus cereus in the presence of Au³⁺ and other metal ions is significantly important but still almost blank in current biogeochemical prospecting of gold mine system. Herein, a self-established simple approach was slightly improved to make silver nanoparticles (Ag NPs) rapidly concentrated on every bacterial cell, and highly strong and distinct surface-enhanced Raman scattering (SERS) signals of Bacillus cereus free from any native fluorescence have been obtained in a so called 'mixing-and-measuring' manner. Furthermore, SERS was used for the first time to our knowledge to investigate the impacts of different concentrations of metal ions on Bacillus cereus, and successfully utilized for distinguishing Au³⁺ ions from other species. A more convincing multi-Raman criterion based on Raman bands, and further the entire Raman spectrum in combination with statistical analysis (e.g., principal component analysis (PCA)) were found capable of detecting spectral differences of Bacillus cereus in the presence of metal ions (Au³⁺, Ag⁺, Cu²⁺ and Zn²⁺) with different concentrations. An interesting phenomenon has been found that except for Au³⁺ ions, the highest permissive concentration of other metal ions for the detected Bacillus cereus is up to 10 μg/mL possibly due to their resistance to Au. The results also indicate that an effective biogeochemical exploration technique of SERS spectral response may be developed, where Bacillus cereus spore counts are measured in the field and used as a pre-screening method to target areas useful for further sampling and complete geochemical analysis.