Surface-enhanced Raman scattering method for the identification of methicillin-resistant Staphylococcus aureus using positively charged silver nanoparticles

Chen, Xueping; Tang, Meiqiong; Liu, Yu; Huang, Jiaoqi; Li, Yong; Tian, Huiyan; Zheng, Yuting; Chapelle, Marc Lamy de la; Zhang, Yang; Fu, Weiling

doi:10.1007/s00604-018-3150-6

Cited by 64 publications

(45 citation statements)

References 33 publications

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“…AgNPs + colloids were prepared according to previous methods by van Lierop et al 17 and Chen et al 18 . The AgNPs + diameters could be increased to more than 100 nm 17 , 18 . Solution A was prepared first, as follows: 3.26 mM AgNO 3 , 0.4 M NH 4 OH, and 0.5 mM CTAB (cetyl trimethyl ammonium bromide) were added to 20 mL of ultrapure water.…”

Section: Methodsmentioning

confidence: 99%

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A novel method for identifying and distinguishing Cryptococcus neoformans and Cryptococcus gattii by surface-enhanced Raman scattering using positively charged silver nanoparticles

Hu¹,

Chen

et al. 2020

Sci Rep

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There are approximately 1 million cryptococcal infections per year among HIV+ individuals, resulting in nearly 625,000 deaths. Cryptococcus neoformans and Cryptococcus gattii are the two most common species that cause human cryptococcosis. These two species of Cryptococcus have differences in pathogenicity, diagnosis, and treatment. Cryptococcal infections are usually difficult to identify because of their slow growth in vitro. In addition, the long detection cycle of Cryptococcus in clinical specimens makes the diagnosis of Cryptococcal infections difficult. Here, we used positively charged silver nanoparticles (AgNPs + ) as a substrate to distinguish between C. neoformans and C. gattii in clinical specimens directly via surface-enhanced Raman scattering (SERS) and spectral analysis. The AgNPs + self-assembled on the surface of the fungal cell wall via electrostatic aggregation, leading to enhanced SERS signals that were better than the standard substrate negatively charged silver nanoparticles (AgNPs). The SERS spectra could also be used as a sample database in the multivariate analysis via orthogonal partial least-squares discriminant analysis. This novel SERS detection method can clearly distinguish between the two Cryptococcus species using principal component analysis. The accuracy of the training data and test data was 100% after a tenfold crossover validation.

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Section: Methodsmentioning

confidence: 99%

“…Silver nanoparticles (AgNPs) are widely used as standard SERS substrates 17 , 18 . The most common approach uses 1% sodium citrate mixed with 1.69 mM AgNO 3 with heating at 100 °C 19 .…”

Section: Introductionmentioning

confidence: 99%

A novel method for identifying and distinguishing Cryptococcus neoformans and Cryptococcus gattii by surface-enhanced Raman scattering using positively charged silver nanoparticles

Hu¹,

Chen

et al. 2020

Sci Rep

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“…The longitudinal contribution centered at 653 nm overlaps well with the 633 nm (red laser) excitation wavelength used for SERS measurements. TEM images revealed a strong interaction of Au NRs with the membrane of E. coli ( Figure 4C) most likely due to electrostatic binding interactions [52]. Different interaction durations (15 min to 3 h) were tested, as displayed in the SEM images in Figure S6.…”

Section: Au Nrs As Sers Markersmentioning

confidence: 99%

Rapid and sensitive identification of uropathogenic Escherichia coli using a surface-enhanced-Raman-scattering-based biochip

Andrei

Moraillon

Lau

et al. 2020

Talanta

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Rapid, selective and sensitive sensing of bacteria remains challenging. We report on a highly sensitive and reproducible surface-enhanced Raman spectroscopy (SERS)-based sensing approach for the detection of uropathogenic Escherichia coli (E. coli) bacteria in urine. The assay is based on the specific capture of the bacteria followed by interaction with cetyltrimethylammonium bromide (CTAB)-stabilised gold nanorods (Au NRS) as SERS markers. High sensitivity up to 10 CFU mL-1 is achieved by optimizing the capture interface based on hydrogenated amorphous silicon a-Si:H thin films. The integration of CH 3 O-PEG 750 onto a-Si:H gives the sensing interface an efficient anti-fouling character, while covalent linkage of antibodies directed against the major type-1 fimbrial pilin FimA of the human pathogen E. coli results in the specific trapping of fimbriated E. coli onto the SERS substrate and their spectral fingerprint identification.

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“… 14 , 15 We identified and distinguished three common Candida species through the following steps: We detected the SERS spectrum of three common Candida species with AgNPs + as standard spectrum. 14 , 16 Then magnetic microspheres (Fe 3 O 4 ) were modified by polyethylenimine (PEI) to form Fe 3 O 4 @PEI. Fe 3 O 4 @PEI was mixed with the candidemia samples to form the Fe 3 O 4 @PEI@ Candida mixture.…”

Section: Introductionmentioning

confidence: 99%

Rapid Detection Method for Pathogenic Candida Captured by Magnetic Nanoparticles and Identified Using SERS via AgNPs+

Hu¹,

Kang²,

Gu³

et al. 2021

IJN

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Candidemia infection is common in the clinic and has a high mortality rate. Candida albicans, Candida tropicalis, and Candida krusei are very important and common pathogenic species. Candida is difficult to isolate from clinical samples and culture, and immunological detection cannot distinguish these related strains. Furthermore, Candida has a complex cell wall, which causes difficulties in the extraction of DNA for nucleic acid detection. The purpose of this study was to establish a protocol for the direct identification of Candida from serum. Materials and Methods: We synthesized Fe 3 O 4 @PEI (where PEI stands for polyethylenimine) magnetic nanoparticles to capture Candida and prepared positively charged silver nanoparticles (AgNPs +) as the substrate for surface-enhanced Raman scattering (SERS). Candida was directly identified from serum by SERS detection. Results: Orthogonal partial least squares discriminant analysis (OPLS-DA) was used as the multivariate analysis tool. Principal component analysis confirmed that this method can clearly distinguish common Candida. After 10-fold cross-validation, the accuracy of training data in this model was 100% and the accuracy of test data was 99.8%, indicating that the model has good classification ability. Conclusion: The detection could be completed within 40 minutes using Fe 3 O 4 @PEI and AgNPs + prepared in advance. This is the first time that Fe 3 O 4 @PEI was used in the detection of Candida by SERS. We report the first rapid method to identify fungi directly from serum without breaking the cell wall to extract DNA from the fungi.

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Surface-enhanced Raman scattering method for the identification of methicillin-resistant Staphylococcus aureus using positively charged silver nanoparticles

Cited by 64 publications

References 33 publications

A novel method for identifying and distinguishing Cryptococcus neoformans and Cryptococcus gattii by surface-enhanced Raman scattering using positively charged silver nanoparticles

A novel method for identifying and distinguishing Cryptococcus neoformans and Cryptococcus gattii by surface-enhanced Raman scattering using positively charged silver nanoparticles

Rapid and sensitive identification of uropathogenic Escherichia coli using a surface-enhanced-Raman-scattering-based biochip

Rapid Detection Method for Pathogenic Candida Captured by Magnetic Nanoparticles and Identified Using SERS via AgNPs+

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