Multiplex identification of bacteria in bacterial mixtures with surface‐enhanced Raman scattering

Çam, Dilek; Keseroğlu, Kemal; Kahraman, Mehmet; Şahın, Fikrettin; Çulha, Mustafa

doi:10.1002/jrs.2475

Cited by 50 publications

(23 citation statements)

References 31 publications

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“…The suspended bacteria were washed three times by centrifugation for 5 min at 7500 rpm. Then, 10 7 bacteria were seeded onto half of 9 different nutrient agar plates, and each plate was incubated for different hours (1,2,4,6,8,10,12,18, and 24 h). At each specific time, bacteria were collected with either loop or spatula.…”

Section: Preparation Of Bacteria Samples For Sers Measurementsmentioning

confidence: 99%

“…As explained in the experimental section, nine different time points (1,2,4,6,8,10,12,18, and 24 h) during growth of seven different bacteria species were selected for spectral acquisition. For the sake of the manuscript length, we here show spectra of the bacteria at 4 different time points (1, 6, 12, and 24 h) in Fig.…”

Section: Sers Investigation Of Spectral Changes Of Bacteria During Thmentioning

confidence: 99%

“…The fluorescence quenching is another advantage of the technique to mention. Due to its remarkable and versatile features, this technique has been used heavily for detection and identification of bacteria [15][16][17][18][19][20][21], cells [22], tissues [23], and biomolecules [24] within the last decade. Therefore, SERS has a potential to be used for diagnostic purposes in clinical settings and several studies have been published on the way to realize this goal [25].…”

Section: Introductionmentioning

confidence: 99%

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Discrimination of urinary tract infection pathogens by means of their growth profiles using surface enhanced Raman scattering

et al. 2015

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Urinary tract infection (UTI) is a widespread infection and affects millions of people around the globe. The gold standard for identification of microorganisms causing infection is urine culture. However, current methods require at least 24 h for the results. In clinical settings, identification and discrimination of bacteria with less time-consuming and cheaper methods are highly desired. In recent years, the power of surface-enhanced Raman scattering (SERS) for fast identification of bacteria and biomolecules has been demonstrated. In this study, we show discrimination of urinary tract infection causative pathogens within 1 h of incubation using principal component analysis (PCA) of SERS spectra of seven different UTI causative bacterial species. In addition, we showed differentiation of them at their different growth phases. We also analyzed origins of bacterial SERS spectra and demonstrated the highly dynamic structure of the bacteria cell wall during their growth. Graphical Abstract Collection of bacteria from urine sample, and their discrimination using their SERS spectra and multivariate analysis.

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Section: Preparation Of Bacteria Samples For Sers Measurementsmentioning

confidence: 99%

Section: Sers Investigation Of Spectral Changes Of Bacteria During Thmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Discrimination of urinary tract infection pathogens by means of their growth profiles using surface enhanced Raman scattering

et al. 2015

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“…The average size of the silver colloid nanoparticles was about 35-40 nm. Other studies [33,34] demonstrated a similar diameter of silver nanoparticles produced by the same method.…”

Section: Discussionmentioning

confidence: 55%

Differentiation of bacterial strains by means of surface enhanced FT-Raman spectroscopy

Kairyte¹,

Lukšienė²,

Pučetaitė³

et al. 2012

Lith. J. Phys.

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The silver nanoparticle colloid was used to obtain surface enhanced Raman spectra of Listeria monocytogenes, Salmonela enterica, and Esherichia coli bacteria. The SERS spectra were captured using for excitation the near-infrared (1064 nm) laser radiation with reduced intensity, which ensured the prevention of the fluorescence background as well as photo-and thermal decomposition of the samples. It was found that the optimal size of silver nanoparticles for the enhancement of the Raman signal in the near-infrared spectral region is ca. 50 nm. The spectral data obtained in this study indicate that relative intensities of SERS spectral bands of bacteria can be used for spectral differentiation of bacteria. In case of Listeria, Salmonela, and Esherichia cells, the intensity ratio of spectral bands of adenine and cysteine can be used as a spectral marker for differentiation of the bacteria.

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“…The identification and discrimination of bacterial mixtures were investigated. [21] In order to demonstrate the effectiveness of the approach, we have constructed a 3D plot of Euclidean distances calculated using the 10 SERS spectra of each yeast, bacteria species and their mixtures. The 3D plot is seen in Fig.…”

Section: Resultsmentioning

confidence: 99%

Rapid identification of bacteria and yeast using surface‐enhanced Raman scattering

Çulha

Kahraman

Çam

et al. 2010

Surface & Interface Analysis

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Surface-enhanced Raman scattering (SERS) is a powerful technique used for obtaining chemical information about the moleculesand molecular structures in the vicinity of surfaces of noble metal nanostructures. The chemical information acquired through SERS can be used for not only characterization but also detection and identification. In a clinical setting, rapid and accurate identification of micro-organisms is critical. The biochemical information collected through the SERS spectra can be used for quick identification of micro-organisms. The concentrated silver colloidal nanoparticles (AgNPs) are simply mixed with micro-organisms after culturing, and their SERS spectra acquired. Since the nanoparticles are in contact with the cell wall of the micro-organism, the biochemical information obtained is mostly assumed as originating from the cell wall which the AgNPs are in contact with, and is considered as the 'fingerprint' of the micro-organism, which can be used for the identification. Since a SERS spectrum can be acquired only in seconds, the obtained spectrum can be used for fast micro-organism identification. The reproducibility of the spectra obtained from micro-organisms is first tested, and then the obtained spectra are used for the goal. The identification of micro-organisms in mixtures is also attempted in model mixtures. It is demonstrated that the SERS can be used for fast and accurate identification of micro-organisms such as bacteria and yeast, even in their mixtures. Four bacteria, i.e. Shigella sonnei, Erwinia amylovara, Proteus vulgaris and DH5α (E. coli strain), and three yeast cells, i.e. Hyphopichia burtonii, Candida parapsilosis and Filobasidiella neoformans are used as model micro-organisms in the study.

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Multiplex identification of bacteria in bacterial mixtures with surface‐enhanced Raman scattering

Cited by 50 publications

References 31 publications

Discrimination of urinary tract infection pathogens by means of their growth profiles using surface enhanced Raman scattering

Discrimination of urinary tract infection pathogens by means of their growth profiles using surface enhanced Raman scattering

Differentiation of bacterial strains by means of surface enhanced FT-Raman spectroscopy

Rapid identification of bacteria and yeast using surface‐enhanced Raman scattering

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