Identification and quantitation of pathogenic bacteria via in-situ formation of silver nanoparticles on cell walls, and their detection via SERS

Alula, Melisew Tadele; Krishnan, Sriram; Hendricks, Nicolette R.; Karamchand, Leshern; Blackburn, Jonathan M.

doi:10.1007/s00604-016-2013-2

Cited by 35 publications

(27 citation statements)

References 34 publications

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“…Moreover, the SERS spectra of intact bacteria reflect the cell wall structure, reporting on the physiological state of the bacteria cell (Alula et al 2017). Alula et al (2017) demonstrated the SERS applicability to the detection of hydrophobic bacteria such as M. smegmatis, M. bovis BCG and M. tuberculosis. Their method was based on the formation of silver nanoparticles directly on the bacterial surface via the silver mirror reaction.…”

Section: Raman Spectroscopymentioning

confidence: 93%

“…The SERS advantage is a non-destructive and molecular specific analysis, without the need of using labels or specific receptors (Dina et al 2017). Moreover, the SERS spectra of intact bacteria reflect the cell wall structure, reporting on the physiological state of the bacteria cell (Alula et al 2017). Alula et al (2017) demonstrated the SERS applicability to the detection of hydrophobic bacteria such as M. smegmatis, M. bovis BCG and M. tuberculosis.…”

Section: Raman Spectroscopymentioning

confidence: 97%

“…Surface--enhanced Raman spectroscopy (SERS) represents a faster and ultrasensitive alternative to normal Raman spectroscopy capable of single-cell or even single--molecule detection (Dina et al 2017). SERS deals with the increase of the weak Raman scattering intensity, thereby enabling the chemical characterisation and detection of various analytes at low concentrations directly from an aqueous sample (Alula et al 2017). In the SERS technique, the target analyte approaches or adsorbs certain rough metal (gold, silver, etc.)…”

Section: Raman Spectroscopymentioning

confidence: 99%

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Instrumental analytical tools for mycobacteria characterisation

Ozana¹,

Hruška²

2021

Czech J. Food Sci.

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Mycobacteria in drinking water and in the water of swimming pools, whirlpools, hydrotherapy facilities and aquaria contribute significantly to human exposure to triggers of immune regulated chronic inflammatory and autoimmune diseases. Technological elements of water distribution systems, especially their inner surface, taps, shower heads and blind spots where sediments settle, affect the number of mycobacteria in the water. The review presents the possibilities of using analytical instruments for rapid determination of mycobacteria and for their typing as an alternative to classical culture and a method of monitoring specific nucleic acid sequences by polymerase chain reaction (PCR). Information about the use of flow cytometry (FCM), matrix-assisted laser desorption ionisation time-of-flight (MALDI-TOF) spectrometry, Raman and infrared (IR) spectroscopy and biosensors are presented.

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Section: Raman Spectroscopymentioning

confidence: 93%

Section: Raman Spectroscopymentioning

confidence: 97%

Section: Raman Spectroscopymentioning

confidence: 99%

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Instrumental analytical tools for mycobacteria characterisation

Ozana¹,

Hruška²

2021

Czech J. Food Sci.

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“…In Situ Synthesis of Monometallic Substrates: Our team proposed in situ synthesis of Ag NPs on the bacterial cell wall for label-free SERS detection. [14][15][16] Similarly, the silver mirror reaction was used for the in situ synthesis of Ag NPs on the surface of bacteria by Alula et al [17] Gao et al reported the aptamer in situ synthesis of Ag NPs to form well-defined Staphylococcus aureus aptamer@Ag NPs. [18] With this strategy, the enhancement and reproducibility of the Raman signals of bacteria are much greater than those of the simply mixed colloid-bacterial method.…”

Section: Enhanced Detection Sensitivitymentioning

confidence: 99%

“…[ 14–16 ] Similarly, the silver mirror reaction was used for the in situ synthesis of Ag NPs on the surface of bacteria by Alula et al. [ 17 ] Gao et al. reported the aptamer in situ synthesis of Ag NPs to form well‐defined Staphylococcus aureus aptamer@Ag NPs.…”

Section: Label‐free Bacterial Detection Using Sersmentioning

confidence: 99%

Bacteria Detection: From Powerful SERS to Its Advanced Compatible Techniques

et al. 2020

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The rapid, highly sensitive, and accurate detection of bacteria is the focus of various fields, especially food safety and public health. Surface-enhanced Raman spectroscopy (SERS), with the advantages of being fast, sensitive, and nondestructive, can be used to directly obtain molecular fingerprint information, as well as for the on-line qualitative analysis of multicomponent samples. It has therefore become an effective technique for bacterial detection. Within this progress report, advances in the detection of bacteria using SERS and other compatible techniques are discussed in order to summarize its development in recent years. First, the enhancement principle and mechanism of SERS technology are briefly overviewed. The second part is devoted to a label-free strategy for the detection of bacterial cells and bacterial metabolites. In this section, important considerations that must be made to improve bacterial SERS signals are discussed. Then, the label-based SERS strategy involves the design strategy of SERS tags, the immunomagnetic separation of SERS tags, and the capture of bacteria from solution and dye-labeled SERS primers. In the third part, several novel SERS compatible technologies and applications in clinical and food safety are introduced. In the final part, the results achieved are summarized and future perspectives are proposed.

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Classification of pathogenic bacteria by Raman spectroscopy combined with variational auto‐encoder and deep learning

Liu

Sun

et al. 2023

Journal of Biophotonics

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Rapid and early identification of pathogens is critical to guide antibiotic therapy. Raman spectroscopy as a noninvasive diagnostic technique provides rapid and accurate detection of pathogens. Raman spectrum of single cells serves as the “fingerprint” of the cell, revealing its metabolic characteristics. Rapid identification of pathogens can be achieved by combining Raman spectroscopy and deep learning. Traditional classification techniques frequently require lots of data for training, which is time costing to collect Raman spectra. For trace samples and strains that are difficult to culture, it is difficult to provide an accurate classification model. In order to reduce the number of samples collected and improve the accuracy of the classification model, a new pathogen detection method integrating Raman spectroscopy, variational auto‐encoder (VAE), and long short‐term memory network (LSTM) is proposed in this paper. We collect the Raman signals of pathogens and input them to VAE for training. VAE will generate a large number of Raman spectral data that cannot be distinguished from the real spectrum, and the signal‐to‐noise ratio is higher than that of the real spectrum. These spectra are input into the LSTM together with the real spectrum for training, and a good classification model is obtained. The results of the experiments reveal that this method not only improves the average accuracy of pathogen classification to 96.9% but also reduces the number of Raman spectra collected from 1000 to 200. With this technology, the number of Raman spectra collected can be greatly reduced, so that strains that are difficult to culture or trace can be rapidly identified.

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Identification and quantitation of pathogenic bacteria via in-situ formation of silver nanoparticles on cell walls, and their detection via SERS

Cited by 35 publications

References 34 publications

Instrumental analytical tools for mycobacteria characterisation

Instrumental analytical tools for mycobacteria characterisation

Bacteria Detection: From Powerful SERS to Its Advanced Compatible Techniques

Classification of pathogenic bacteria by Raman spectroscopy combined with variational auto‐encoder and deep learning

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