Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy
As the identification of microorganisms becomes more significant in industry, so does the utilization of microspectroscopy and the development of effective chemometric models for data analysis and classification. Since only microorganisms cultivated under laboratory conditions can be identified, but...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Foods |
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| Online Access: | https://www.mdpi.com/2304-8158/11/10/1506 |
| _version_ | 1797499840869957632 |
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| author | Daniel Klein René Breuch Jessica Reinmüller Carsten Engelhard Peter Kaul |
| author_facet | Daniel Klein René Breuch Jessica Reinmüller Carsten Engelhard Peter Kaul |
| author_sort | Daniel Klein |
| collection | DOAJ |
| description | As the identification of microorganisms becomes more significant in industry, so does the utilization of microspectroscopy and the development of effective chemometric models for data analysis and classification. Since only microorganisms cultivated under laboratory conditions can be identified, but they are exposed to a variety of stress factors, such as temperature differences, there is a demand for a method that can take these stress factors and the associated reactions of the bacteria into account. Therefore, bacterial stress reactions to lifetime conditions (regular treatment, 25 °C, HCl, 2-propanol, NaOH) and sampling conditions (cold sampling, desiccation, heat drying) were induced to explore the effects on Raman spectra in order to improve the chemometric models. As a result, in this study nine food-relevant bacteria were exposed to seven stress conditions in addition to routine cultivation as a control. Spectral alterations in lipids, polysaccharides, nucleic acids, and proteins were observed when compared to normal growth circumstances without stresses. Regardless of the involvement of several stress factors and storage times, a model for differentiating the analyzed microorganisms from genus down to strain level was developed. Classification of the independent training dataset at genus and species level for <i>Escherichia coli</i> and at strain level for the other food relevant microorganisms showed a classification rate of 97.6%. |
| first_indexed | 2024-03-10T03:54:10Z |
| format | Article |
| id | doaj.art-6cc2ccd5e09944e4b1b47a204cfb3c6e |
| institution | Directory Open Access Journal |
| issn | 2304-8158 |
| language | English |
| last_indexed | 2024-03-10T03:54:10Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj.art-6cc2ccd5e09944e4b1b47a204cfb3c6e2023-11-23T11:00:08ZengMDPI AGFoods2304-81582022-05-011110150610.3390/foods11101506Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-MicrospectroscopyDaniel Klein0René Breuch1Jessica Reinmüller2Carsten Engelhard3Peter Kaul4Institute of Safety and Security Research, Bonn-Rhein-Sieg University of Applied Sciences, Von-Liebig-Straße 20, 53359 Rheinbach, GermanyInstitute of Safety and Security Research, Bonn-Rhein-Sieg University of Applied Sciences, Von-Liebig-Straße 20, 53359 Rheinbach, GermanyInstitute of Safety and Security Research, Bonn-Rhein-Sieg University of Applied Sciences, Von-Liebig-Straße 20, 53359 Rheinbach, GermanyDepartment of Chemistry and Biology, University of Siegen, Adolf-Reichwein-Str. 2, 57076 Siegen, GermanyInstitute of Safety and Security Research, Bonn-Rhein-Sieg University of Applied Sciences, Von-Liebig-Straße 20, 53359 Rheinbach, GermanyAs the identification of microorganisms becomes more significant in industry, so does the utilization of microspectroscopy and the development of effective chemometric models for data analysis and classification. Since only microorganisms cultivated under laboratory conditions can be identified, but they are exposed to a variety of stress factors, such as temperature differences, there is a demand for a method that can take these stress factors and the associated reactions of the bacteria into account. Therefore, bacterial stress reactions to lifetime conditions (regular treatment, 25 °C, HCl, 2-propanol, NaOH) and sampling conditions (cold sampling, desiccation, heat drying) were induced to explore the effects on Raman spectra in order to improve the chemometric models. As a result, in this study nine food-relevant bacteria were exposed to seven stress conditions in addition to routine cultivation as a control. Spectral alterations in lipids, polysaccharides, nucleic acids, and proteins were observed when compared to normal growth circumstances without stresses. Regardless of the involvement of several stress factors and storage times, a model for differentiating the analyzed microorganisms from genus down to strain level was developed. Classification of the independent training dataset at genus and species level for <i>Escherichia coli</i> and at strain level for the other food relevant microorganisms showed a classification rate of 97.6%.https://www.mdpi.com/2304-8158/11/10/1506stress responseRaman-microspectroscopydiscriminant analysisclassificationbacteria |
| spellingShingle | Daniel Klein René Breuch Jessica Reinmüller Carsten Engelhard Peter Kaul Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy Foods stress response Raman-microspectroscopy discriminant analysis classification bacteria |
| title | Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy |
| title_full | Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy |
| title_fullStr | Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy |
| title_full_unstemmed | Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy |
| title_short | Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy |
| title_sort | discrimination of stressed and non stressed food related bacteria using raman microspectroscopy |
| topic | stress response Raman-microspectroscopy discriminant analysis classification bacteria |
| url | https://www.mdpi.com/2304-8158/11/10/1506 |
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