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

Zhao, Yuwen; Zhang, Zeshuai; Ning, Ying; Miao, Peiqi; Li, Zheng; Wang, Haixia

doi:10.1016/j.saa.2023.122510

Cited by 14 publications

(7 citation statements)

References 33 publications

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“…Machine learning, recognised as a powerful data analysis method, excels in exploring local features and extracting global characteristics from signal data 30,82 . Leveraging its immense potential in SERS spectral data processing and analysis, it has found its applications in rapidly identifying and predicting bacterial genera and species 19,83 . We constructed six supervised machine learning models to identify the algorithm with optimal predictive performance (AdaBoost, DT, QDA, RF, SVM and XGB).…”

Section: Discussionmentioning

confidence: 99%

“… 30 , 82 Leveraging its immense potential in SERS spectral data processing and analysis, it has found its applications in rapidly identifying and predicting bacterial genera and species. 19 , 83 We constructed six supervised machine learning models to identify the algorithm with optimal predictive performance (AdaBoost, DT, QDA, RF, SVM and XGB). We applied them to SERS spectral data from benchtops and handheld Raman spectrometers.…”

Section: Discussionmentioning

confidence: 99%

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Rapid discrimination of four Salmonella enterica serovars: A performance comparison between benchtop and handheld Raman spectrometers

Yuan,

Gu,

Liu

et al. 2024

J Cellular Molecular Medi

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Foodborne illnesses, particularly those caused by Salmonella enterica with its extensive array of over 2600 serovars, present a significant public health challenge. Therefore, prompt and precise identification of S. enterica serovars is essential for clinical relevance, which facilitates the understanding of S. enterica transmission routes and the determination of outbreak sources. Classical serotyping methods via molecular subtyping and genomic markers currently suffer from various limitations, such as labour intensiveness, time consumption, etc. Therefore, there is a pressing need to develop new diagnostic techniques. Surface‐enhanced Raman spectroscopy (SERS) is a non‐invasive diagnostic technique that can generate Raman spectra, based on which rapid and accurate discrimination of bacterial pathogens could be achieved. To generate SERS spectra, a Raman spectrometer is needed to detect and collect signals, which are divided into two types: the expensive benchtop spectrometer and the inexpensive handheld spectrometer. In this study, we compared the performance of two Raman spectrometers to discriminate four closely associated S. enterica serovars, that is, S. enterica subsp. enterica serovar dublin, enteritidis, typhi and typhimurium. Six machine learning algorithms were applied to analyse these SERS spectra. The support vector machine (SVM) model showed the highest accuracy for both handheld (99.97%) and benchtop (99.38%) Raman spectrometers. This study demonstrated that handheld Raman spectrometers achieved similar prediction accuracy as benchtop spectrometers when combined with machine learning models, providing an effective solution for rapid, accurate and cost‐effective identification of closely associated S. enterica serovars.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Rapid discrimination of four Salmonella enterica serovars: A performance comparison between benchtop and handheld Raman spectrometers

Yuan,

Gu,

Liu

et al. 2024

J Cellular Molecular Medi

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“…Some serotypes of E. coli can produce enterotoxins that cause diarrhea, abdominal pain, inflammation, ulcers, and other manifestations of food poisoning. Staphylococcus can also produce various enterotoxins, which can cause food poisoning or purulent-inflammatory infections in humans [29]. In this regard, S. aureus ST228 and E. coli 603 strains were used as test cultures.…”

Section: Antimicrobial Activity Of Edible Filmsmentioning

confidence: 99%

Obtaining Edible Pullulan-based Films with Antimicrobial Properties

Ignatova,

Urazova,

Brazhnikova

et al. 2024

Eurasian Chem.-Technol. J.

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A nutrient medium was selected for the efficient production of exopolysaccharide (EPS) by A. pullulans C7 strain. The production of pullulan polysaccharide was evaluated on nutrient media with traditional carbon sources and cheap substrates that were plant wastes. For maximum EPS accumulation, we proposed an optimized Czapek-Dox medium with glucose as a carbon source, sodium nitrate as a nitrogen source, and C/N=232:1 ratio (EPS yield 12.79±0.64 g/l). Medium with grape pomace 5% (EPS yield was 15.08±0.34 g/l) and medium with topinambour tuber hydrolysate 5% (EPS yield was 14.44±0.21 g/l) was proposed as a cheap substrate. Edible films with antimicrobial activity were obtained on the basis of the isolated polysaccharide. The antibacterial activity of films against Escherichia coli 603 and Staphylococcus aureus ST228 was shown when essential oils of rosemary (zones of growth inhibition from 8.41±0.71 to 9.98±0.32 mm) and oregano (zones of growth inhibition from 8.09±0.51 to 9.54±0.24 mm) were added to pullulan. The addition of xanthan gum and glycerol to the films increased their strength and elasticity. The infrared spectrum of the pullulan film showed absorption bands characteristic of polysaccharide structures.

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“…Surface-enhanced Raman spectroscopy (SERS) technology offers several advantages, including independence from water interference, rapid detection speed, and the potential for multiple analyses. − Consequently, there has been significant interest in utilizing SERS for microbial detection. − For example, Muthukumar et al developed a SERS substrate by decorating porous silicon with silver, enabling the rapid and reliable detection of Escherichia coli in different milk sources. Their experimental findings demonstrated successful detection of the target bacteria with a linear response in the range of 10 1 –10 5 colony-forming units per milliliter (CFU/mL).…”

Section: Introductionmentioning

confidence: 99%

Novel Digital SERS-Microfluidic Chip for Rapid and Accurate Quantification of Microorganisms

Wen,

Yang,

Zhao

et al. 2024

Anal. Chem.

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In this work, we present a simple and novel digital surface-enhanced Raman spectroscopy (SERS)-microfluidic chip designed for the rapid and accurate quantitative detection of microorganisms. The chip employs a high-density inverted pyramid microcavity (IPM) array to separate and isolate microbial samples. The presence or absence of target microorganisms is determined by scanning the IPM array using SERS and identifying the characteristic Raman bands. This approach allows for the “digitization” of the SERS response of each IPM, enabling quantification through the application of mathematical statistical techniques. Significantly, precise quantitative detection of yeast was achieved within a concentration range of 106–109 cells/mL, with the maximum relative standard deviation from the concentration calibrated by the cultivation method being 5.6%. This innovative approach efficiently addresses the issue of irregularities in SERS quantitative detection, which arises due to fluctuations in SERS intensity and poor reproducibility. We strongly believe that this digital SERS-microfluidic chip holds immense potential for diverse applications in the rapid detection of various microorganisms, including pathogenic bacteria and viruses.

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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

Cited by 14 publications

References 33 publications

Rapid discrimination of four Salmonella enterica serovars: A performance comparison between benchtop and handheld Raman spectrometers

Rapid discrimination of four Salmonella enterica serovars: A performance comparison between benchtop and handheld Raman spectrometers

Obtaining Edible Pullulan-based Films with Antimicrobial Properties

Novel Digital SERS-Microfluidic Chip for Rapid and Accurate Quantification of Microorganisms

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