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Kang H, Wang Z, Sun J, Song S, Cheng L, Sun Y, Pan X, Wu C, Gong P, Li H. Rapid identification of bloodstream infection pathogens and drug resistance using Raman spectroscopy enhanced by convolutional neural networks. Front Microbiol 2024; 15:1428304. [PMID: 39077742 PMCID: PMC11284601 DOI: 10.3389/fmicb.2024.1428304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Accepted: 07/03/2024] [Indexed: 07/31/2024] Open
Abstract
Bloodstream infections (BSIs) are a critical medical concern, characterized by elevated morbidity, mortality, extended hospital stays, substantial healthcare costs, and diagnostic challenges. The clinical outcomes for patients with BSI can be markedly improved through the prompt identification of the causative pathogens and their susceptibility to antibiotics and antimicrobial agents. Traditional BSI diagnosis via blood culture is often hindered by its lengthy incubation period and its limitations in detecting pathogenic bacteria and their resistance profiles. Surface-enhanced Raman scattering (SERS) has recently gained prominence as a rapid and effective technique for identifying pathogenic bacteria and assessing drug resistance. This method offers molecular fingerprinting with benefits such as rapidity, sensitivity, and non-destructiveness. The objective of this study was to integrate deep learning (DL) with SERS for the rapid identification of common pathogens and their resistance to drugs in BSIs. To assess the feasibility of combining DL with SERS for direct detection, erythrocyte lysis and differential centrifugation were employed to isolate bacteria from blood samples with positive blood cultures. A total of 12,046 and 11,968 SERS spectra were collected from the two methods using Raman spectroscopy and subsequently analyzed using DL algorithms. The findings reveal that convolutional neural networks (CNNs) exhibit considerable potential in identifying prevalent pathogens and their drug-resistant strains. The differential centrifugation technique outperformed erythrocyte lysis in bacterial isolation from blood, achieving a detection accuracy of 98.68% for pathogenic bacteria and an impressive 99.85% accuracy in identifying carbapenem-resistant Klebsiella pneumoniae. In summary, this research successfully developed an innovative approach by combining DL with SERS for the swift identification of pathogenic bacteria and their drug resistance in BSIs. This novel method holds the promise of significantly improving patient prognoses and optimizing healthcare efficiency. Its potential impact could be profound, potentially transforming the diagnostic and therapeutic landscape of BSIs.
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Affiliation(s)
- Haiquan Kang
- Department of Clinical Laboratory, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
- Medical Technology School, Xuzhou Medical University, Xuzhou, China
| | - Ziling Wang
- Medical Technology School, Xuzhou Medical University, Xuzhou, China
| | - Jingfang Sun
- Department of Clinical Laboratory, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Shuang Song
- Department of Clinical Laboratory, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Lei Cheng
- School of Medical Imaging, Xuzhou Medical University, Xuzhou, China
| | - Yi Sun
- School of Medical Imaging, Xuzhou Medical University, Xuzhou, China
| | - Xingqi Pan
- School of Medical Imaging, Xuzhou Medical University, Xuzhou, China
| | - Changyu Wu
- School of Medical Imaging, Xuzhou Medical University, Xuzhou, China
| | - Ping Gong
- School of Medical Imaging, Xuzhou Medical University, Xuzhou, China
| | - Hongchun Li
- Medical Technology School, Xuzhou Medical University, Xuzhou, China
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Frempong SB, Salbreiter M, Mostafapour S, Pistiki A, Bocklitz TW, Rösch P, Popp J. Illuminating the Tiny World: A Navigation Guide for Proper Raman Studies on Microorganisms. Molecules 2024; 29:1077. [PMID: 38474589 DOI: 10.3390/molecules29051077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/13/2024] [Accepted: 02/18/2024] [Indexed: 03/14/2024] Open
Abstract
Raman spectroscopy is an emerging method for the identification of bacteria. Nevertheless, a lot of different parameters need to be considered to establish a reliable database capable of identifying real-world samples such as medical or environmental probes. In this review, the establishment of such reliable databases with the proper design in microbiological Raman studies is demonstrated, shining a light into all the parts that require attention. Aspects such as the strain selection, sample preparation and isolation requirements, the phenotypic influence, measurement strategies, as well as the statistical approaches for discrimination of bacteria, are presented. Furthermore, the influence of these aspects on spectra quality, result accuracy, and read-out are discussed. The aim of this review is to serve as a guide for the design of microbiological Raman studies that can support the establishment of this method in different fields.
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Affiliation(s)
- Sandra Baaba Frempong
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Markus Salbreiter
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Sara Mostafapour
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Aikaterini Pistiki
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance-Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Thomas W Bocklitz
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance-Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Jürgen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance-Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
- Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, 07743 Jena, Germany
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Wichmann C, Dengler J, Hoffmann M, Rösch P, Popp J. Simulating a reference medium for determining bacterial growth in hospital wastewater for Raman spectroscopic investigation. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 305:123425. [PMID: 37751647 DOI: 10.1016/j.saa.2023.123425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 08/23/2023] [Accepted: 09/16/2023] [Indexed: 09/28/2023]
Abstract
Wastewater is a very complex and diverse medium, which despite low nutrient density still harbors bacteria. Especially the wastewater from hospitals contains a high germ load. However, wastewater is also very variable and differs not only from day to day, but also from house to house. Since wastewater is always changing and medium has an impact on Raman spectra of bacteria, it is necessary to find a surrogate material in which bacteria can be cultured to mimic a real hospital wastewater sample. In this study, we investigate two different artificial wastewaters for their abilities as a good alternative to real wastewater from the Jena University Hospital and to serve as a reference material for bacterial cultivation with subsequent Raman measurement. Each of the artificial wastewater on its own was not suitable to be used as a reference medium. Only the combination of the two simulated wastewaters achieved satisfactory results in the Raman spectroscopic identification of bacteria from real wastewater. These results could be used later in new experiments as a reference dataset to identify bacteria from real hospital wastewater samples.
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Affiliation(s)
- Christina Wichmann
- Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Helmholtzweg 4, 07743 Jena, Germany; InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Jennifer Dengler
- Integrative Health and Security Management Center, Staff Section Environmental Protection and Sustainability, Jena University Hospital, Kastanienstraße 1, 07747 Jena, Germany
| | - Marc Hoffmann
- Integrative Health and Security Management Center, Staff Section Environmental Protection and Sustainability, Jena University Hospital, Kastanienstraße 1, 07747 Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Helmholtzweg 4, 07743 Jena, Germany; InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany.
| | - Jürgen Popp
- Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Helmholtzweg 4, 07743 Jena, Germany; InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany; Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert‑Einstein‑Straße 9, 07745 Jena, Germany
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Zhu M, Xu T, Cheng Y, Ma B, Xu J, Diao Z, Wu F, Dai J, Han X, Zhu P, Pang C, Li J, Wang H, Xu R, Li X. Integrated Microfluidic Chip for Rapid Antimicrobial Susceptibility Testing Directly from Positive Blood Cultures. Anal Chem 2023; 95:14375-14383. [PMID: 37710979 DOI: 10.1021/acs.analchem.3c02737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/16/2023]
Abstract
Rapid and accurate antimicrobial prescriptions are critical for bloodstream infection (BSI) patients, as they can guide drug use and decrease mortality significantly. The traditional antimicrobial susceptibility testing (AST) for BSI is time-consuming and tedious, taking 2-3 days. Avoiding lengthy monoclonal cultures and shortening the drug sensitivity incubation time are keys to accelerating the AST. Here, we introduced a bacteria separation integrated AST (BSI-AST) chip, which could extract bacteria directly from positive blood cultures (PBCs) within 10 min and quickly give susceptibility information within 3 h. The integrated chip includes a bacteria separation chamber, multiple AST chambers, and connection channels. The separator gel was first preloaded into the bacteria separation chamber, enabling the swift separation of bacteria cells from PBCs through on-chip centrifugation. Then, the bacteria suspension was distributed in the AST chambers with preloaded antibiotics through a quick vacuum-assisted aliquoting strategy. Through centrifuge-assisted on-chip enrichment, detectable growth of the phenotype under different antibiotics could be easily observed in the taper tips of AST chambers within a few hours. As a proof of concept, direct AST from artificial PBCs with Escherichia coli against 18 antibiotics was performed on the BSI-AST chip, and the whole process from bacteria extraction to AST result output was less than 3.5 h. Moreover, the integrated chip was successfully applied to the diagnosis of clinical PBCs, showing 93.3% categorical agreement with clinical standard methods. The reliable and fast pathogen characterization of the integrated chip suggested its great potential application in clinical diagnosis.
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Affiliation(s)
- Meijia Zhu
- School of Environmental Science and Engineering, Institute of Eco-Environmental Forensics, Shandong University (Qingdao), Qingdao, Shandong 266237, China
| | - Teng Xu
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong 266101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yongqiang Cheng
- School of Environmental Science and Engineering, Institute of Eco-Environmental Forensics, Shandong University (Qingdao), Qingdao, Shandong 266237, China
| | - Bo Ma
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong 266101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jian Xu
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong 266101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhidian Diao
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong 266101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fei Wu
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong 266101, China
| | - Jing Dai
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong 266101, China
| | - Xiao Han
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong 266101, China
- School of Chemistry and Chemical Engineering, University of Jinan, Jinan, Shandong 250024, China
| | - Pengfei Zhu
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong 266101, China
- Qingdao Single Cell Biotechnology Company Limited, Qingdao, Shandong 266000, China
| | - Chao Pang
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong 266101, China
| | - Jing Li
- Department of Clinical Laboratory, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266003, China
| | - Hongwei Wang
- Department of Clinical Laboratory, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266003, China
| | - Ranran Xu
- School of Environmental Science and Engineering, Institute of Eco-Environmental Forensics, Shandong University (Qingdao), Qingdao, Shandong 266237, China
| | - Xiaotong Li
- School of Environmental Science and Engineering, Institute of Eco-Environmental Forensics, Shandong University (Qingdao), Qingdao, Shandong 266237, China
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Shen H, Rösch P, Thieme L, Pletz MW, Popp J. Comparison of bacteria in different metabolic states by micro-Raman spectroscopy. J Mol Struct 2022. [DOI: 10.1016/j.molstruc.2022.134831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Comparison of Different Label-Free Raman Spectroscopy Approaches for the Discrimination of Clinical MRSA and MSSA Isolates. Microbiol Spectr 2022; 10:e0076322. [PMID: 36005817 PMCID: PMC9603629 DOI: 10.1128/spectrum.00763-22] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) is classified as one of the priority pathogens that threaten human health. Resistance detection with conventional microbiological methods takes several days, forcing physicians to administer empirical antimicrobial treatment that is not always appropriate. A need exists for a rapid, accurate, and cost-effective method that allows targeted antimicrobial therapy in limited time. In this pilot study, we investigate the efficacy of three different label-free Raman spectroscopic approaches to differentiate methicillin-resistant and -susceptible clinical isolates of S. aureus (MSSA). Single-cell analysis using 532 nm excitation was shown to be the most suitable approach since it captures information on the overall biochemical composition of the bacteria, predicting 87.5% of the strains correctly. UV resonance Raman microspectroscopy provided a balanced accuracy of 62.5% and was not sensitive enough in discriminating MRSA from MSSA. Excitation of 785 nm directly on the petri dish provided a balanced accuracy of 87.5%. However, the difference between the strains was derived from the dominant staphyloxanthin bands in the MRSA, a cell component not associated with the presence of methicillin resistance. This is the first step toward the development of label-free Raman spectroscopy for the discrimination of MRSA and MSSA using single-cell analysis with 532 nm excitation. IMPORTANCE Label-free Raman spectra capture the high chemical complexity of bacterial cells. Many different Raman approaches have been developed using different excitation wavelength and cell analysis methods. This study highlights the major importance of selecting the most suitable Raman approach, capable of providing spectral features that can be associated with the cell mechanism under investigation. It is shown that the approach of choice for differentiating MRSA from MSSA should be single-cell analysis with 532 nm excitation since it captures the difference in the overall biochemical composition. These results should be taken into consideration in future studies aiming for the development of label-free Raman spectroscopy as a clinical analytical tool for antimicrobial resistance determination.
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Pistiki A, Salbreiter M, Sultan S, Rösch P, Popp J. Application of Raman spectroscopy in the hospital environment. TRANSLATIONAL BIOPHOTONICS 2022. [DOI: 10.1002/tbio.202200011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Aikaterini Pistiki
- Leibniz‐Institute of Photonic Technology Member of the Leibniz Research Alliance–Leibniz Health Technologies Jena Germany
- InfectoGnostics Research Campus Jena Center of Applied Research Jena Germany
| | - Markus Salbreiter
- InfectoGnostics Research Campus Jena Center of Applied Research Jena Germany
- Institute of Physical Chemistry and Abbe Center of Photonics Friedrich Schiller University Jena Germany
| | - Salwa Sultan
- InfectoGnostics Research Campus Jena Center of Applied Research Jena Germany
- Institute of Physical Chemistry and Abbe Center of Photonics Friedrich Schiller University Jena Germany
| | - Petra Rösch
- InfectoGnostics Research Campus Jena Center of Applied Research Jena Germany
- Institute of Physical Chemistry and Abbe Center of Photonics Friedrich Schiller University Jena Germany
| | - Jürgen Popp
- Leibniz‐Institute of Photonic Technology Member of the Leibniz Research Alliance–Leibniz Health Technologies Jena Germany
- InfectoGnostics Research Campus Jena Center of Applied Research Jena Germany
- Institute of Physical Chemistry and Abbe Center of Photonics Friedrich Schiller University Jena Germany
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Vaitiekūnaitė D, Bružaitė I, Snitka V. Endophytes from blueberry (Vaccinium sp.) fruit: Characterization of yeast and bacteria via label-free surface-enhanced Raman spectroscopy (SERS). SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 275:121158. [PMID: 35334429 DOI: 10.1016/j.saa.2022.121158] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 03/06/2022] [Accepted: 03/11/2022] [Indexed: 06/14/2023]
Abstract
Blueberries (Vaccinium sp.) are consumed all around the globe, however, their endophytic community has not been thoroughly researched, specifically their fruit endophytes. We aimed to isolate and analyze easily cultivable blueberry fruit endophytes to help in future research, concerning probiotic microorganisms. Twelve strains were isolated in this pilot study, genetically homologous with Staphylococcus hominis, Staphylococcus cohnii, Salmonella enterica, Leuconostoc mesenteroides, and [Candida] santamariae. To determine the molecular composition of these isolates we used label-free surface-enhanced Raman spectroscopy (SERS). To our knowledge, this is the first time that SERS spectra for L. mesenteroides and C. santamariae are presented, as well as the first report of Candida yeast, isolated specifically from blueberry fruits. Our findings suggest that the differences in tested yeast and bacteria SERS spectra and subsequent differentiation are facilitated by minor shifts in spectral peak positions as well as their intensities. Moreover, we used principal component and discriminant function analyses to differentiate chemotypes within our isolate group, proving the sensitivity of the technique and its usefulness to recognize different strains in plant-associated microbe samples, which will aid to streamline future studies in biofertilizers and biocontrol agents.
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Affiliation(s)
- Dorotėja Vaitiekūnaitė
- Lithuanian Research Centre for Agriculture and Forestry, Laboratory of Forest Plant Biotechnology, Institute of Forestry, Liepu st. 1, LT-53101 Girionys, Lithuania.
| | - Ingrida Bružaitė
- Department of Chemistry and Bioengineering, Faculty of Fundamental Sciences, Vilnius Gediminas Technical University, Sauletekio av. 11, LT-10223 Vilnius, Lithuania.
| | - Valentinas Snitka
- Research Center for Microsystems and Nanotechnology, Kaunas University of Technology, Studentu str. 65, LT-51369 Kaunas, Lithuania.
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Nakar A, Pistiki A, Ryabchykov O, Bocklitz T, Rösch P, Popp J. Label-free differentiation of clinical E. coli and Klebsiella isolates with Raman spectroscopy. JOURNAL OF BIOPHOTONICS 2022; 15:e202200005. [PMID: 35388631 DOI: 10.1002/jbio.202200005] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/18/2022] [Accepted: 04/04/2022] [Indexed: 05/14/2023]
Abstract
Raman spectroscopy is a promising spectroscopic technique for microbiological diagnostics. In routine diagnostic, the differentiation of pathogens of the Enterobacteriaceae family remain challenging. In this study, Raman spectroscopy was applied for the differentiation of 24 clinical E. coli, Klebsiella pneumoniae and Klebsiella oxytoca isolates. Spectra were collected with two spectroscopic approaches: UV-Resonance Raman spectroscopy (UVRR) and single-cell Raman microspectroscopy with 532 nm excitation. A description of the different biochemical profiles provided by the different excitation wavelengths was performed followed by machine-learning models for the classification at the genus and species levels. UVRR was shown to outperform 532 nm excitation, enabling correct classification at the genus level of 23/24 isolates. Furthermore, for the first time, Klebsiella species were correctly classified at the species level with 92% accuracy, classifying all three K. oxytoca isolates correctly. These findings should guide future applicative studies, increasing the scope of Raman spectroscopy's suitability for clinical applications.
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Affiliation(s)
- Amir Nakar
- Leibniz Institute of Photonic Technology Jena-Member of the Research Alliance "Leibniz Health Technologies", Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
- Research Campus Infectognostics, Jena, Germany
| | - Aikaterini Pistiki
- Leibniz Institute of Photonic Technology Jena-Member of the Research Alliance "Leibniz Health Technologies", Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
- Research Campus Infectognostics, Jena, Germany
| | - Oleg Ryabchykov
- Leibniz Institute of Photonic Technology Jena-Member of the Research Alliance "Leibniz Health Technologies", Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
| | - Thomas Bocklitz
- Leibniz Institute of Photonic Technology Jena-Member of the Research Alliance "Leibniz Health Technologies", Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
- Research Campus Infectognostics, Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
- Research Campus Infectognostics, Jena, Germany
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology Jena-Member of the Research Alliance "Leibniz Health Technologies", Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
- Research Campus Infectognostics, Jena, Germany
- Jena Biophotonics and Imaging Laboratory, Jena, Germany
- Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany
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Nakar A, Pistiki A, Ryabchykov O, Bocklitz T, Rösch P, Popp J. Detection of multi-resistant clinical strains of E. coli with Raman spectroscopy. Anal Bioanal Chem 2022; 414:1481-1492. [PMID: 34982178 PMCID: PMC8761712 DOI: 10.1007/s00216-021-03800-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/05/2021] [Accepted: 11/22/2021] [Indexed: 01/08/2023]
Abstract
In recent years, we have seen a steady rise in the prevalence of antibiotic-resistant bacteria. This creates many challenges in treating patients who carry these infections, as well as stopping and preventing outbreaks. Identifying these resistant bacteria is critical for treatment decisions and epidemiological studies. However, current methods for identification of resistance either require long cultivation steps or expensive reagents. Raman spectroscopy has been shown in the past to enable the rapid identification of bacterial strains from single cells and cultures. In this study, Raman spectroscopy was applied for the differentiation of resistant and sensitive strains of Escherichia coli. Our focus was on clinical multi-resistant (extended-spectrum β-lactam and carbapenem-resistant) bacteria from hospital patients. The spectra were collected using both UV resonance Raman spectroscopy in bulk and single-cell Raman microspectroscopy, without exposure to antibiotics. We found resistant strains have a higher nucleic acid/protein ratio, and used the spectra to train a machine learning model that differentiates resistant and sensitive strains. In addition, we applied a majority of voting system to both improve the accuracy of our models and make them more applicable for a clinical setting. This method could allow rapid and accurate identification of antibiotic resistant bacteria, and thus improve public health.
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Affiliation(s)
- Amir Nakar
- Leibniz Institute of Photonic Technology Jena (a Member of Leibniz Health Technologies), Albert-Einstein-Straße 9, 07745, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany
- Research Campus Infectognostics Jena E.V, Philosophenweg 7, 07743, Jena, Germany
| | - Aikaterini Pistiki
- Leibniz Institute of Photonic Technology Jena (a Member of Leibniz Health Technologies), Albert-Einstein-Straße 9, 07745, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany
- Research Campus Infectognostics Jena E.V, Philosophenweg 7, 07743, Jena, Germany
| | - Oleg Ryabchykov
- Leibniz Institute of Photonic Technology Jena (a Member of Leibniz Health Technologies), Albert-Einstein-Straße 9, 07745, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany
| | - Thomas Bocklitz
- Leibniz Institute of Photonic Technology Jena (a Member of Leibniz Health Technologies), Albert-Einstein-Straße 9, 07745, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany
- Research Campus Infectognostics Jena E.V, Philosophenweg 7, 07743, Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany.
- Research Campus Infectognostics Jena E.V, Philosophenweg 7, 07743, Jena, Germany.
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology Jena (a Member of Leibniz Health Technologies), Albert-Einstein-Straße 9, 07745, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743, Jena, Germany
- Research Campus Infectognostics Jena E.V, Philosophenweg 7, 07743, Jena, Germany
- Jena Biophotonics and Imaging Laboratory, Albert-Einstein-Straße 9, 07745, Jena, Germany
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Nakar A, Wagenhaus A, Rösch P, Popp J. Raman spectroscopy for the differentiation of Enterobacteriaceae: a comparison of two methods. Analyst 2022; 147:3938-3946. [DOI: 10.1039/d2an00822j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A comprehensive dataset of bacteria of the family Enterobacteriaceae was collected and measured with Raman spectroscopy. Fiber-probe based Raman spectroscopy enabled classification with 100% accuracy and remained robust with a validation dataset.
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Affiliation(s)
- Amir Nakar
- Leibniz Institute of Photonic Technology Jena – Member of the research alliance “Leibniz Health Technologies”, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Germany
- Research Campus Infectognostics, Jena, Germany
| | - Annette Wagenhaus
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Germany
- Research Campus Infectognostics, Jena, Germany
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology Jena – Member of the research alliance “Leibniz Health Technologies”, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Germany
- Research Campus Infectognostics, Jena, Germany
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12
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Cialla-May D, Krafft C, Rösch P, Deckert-Gaudig T, Frosch T, Jahn IJ, Pahlow S, Stiebing C, Meyer-Zedler T, Bocklitz T, Schie I, Deckert V, Popp J. Raman Spectroscopy and Imaging in Bioanalytics. Anal Chem 2021; 94:86-119. [PMID: 34920669 DOI: 10.1021/acs.analchem.1c03235] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Dana Cialla-May
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany.,InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Christoph Krafft
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Tanja Deckert-Gaudig
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Torsten Frosch
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Izabella J Jahn
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Susanne Pahlow
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany.,InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Clara Stiebing
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Tobias Meyer-Zedler
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Thomas Bocklitz
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Iwan Schie
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Ernst-Abbe-Hochschule Jena, University of Applied Sciences, Department of Biomedical Engineering and Biotechnology, Carl-Zeiss-Promenade 2, 07745 Jena, Germany
| | - Volker Deckert
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Jürgen Popp
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany.,InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
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13
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Isolation of bacteria from artificial bronchoalveolar lavage fluid using density gradient centrifugation and their accessibility by Raman spectroscopy. Anal Bioanal Chem 2021; 413:5193-5200. [PMID: 34215913 PMCID: PMC8405473 DOI: 10.1007/s00216-021-03488-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 06/10/2021] [Accepted: 06/16/2021] [Indexed: 11/20/2022]
Abstract
Raman spectroscopy is an analytical method to identify medical samples of bacteria. Because Raman spectroscopy detects the biochemical properties of a cell, there are many factors that can influence and modify the Raman spectra of bacteria. One possible influence is a proper method for isolation of the bacteria. Medical samples in particular never occur in purified form, so a Raman-compatible isolation method is needed which does not affect the bacteria and thus the resulting spectra. In this study, we present a Raman-compatible method for isolation of bacteria from bronchoalveolar lavage (BAL) fluid using density gradient centrifugation. In addition to measuring the bacteria from a patient sample, the yield and the spectral influence of the isolation on the bacteria were investigated. Bacteria isolated from BAL fluid show additional peaks in comparison to pure culture bacteria, which can be attributed to components in the BAL sample. The isolation gradient itself has no effect on the spectra, and with a yield of 63% and 78%, the method is suitable for isolation of low concentrations of bacteria from a complex matrix. Graphical abstract ![]()
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14
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Wichmann C, Bocklitz T, Rösch P, Popp J. Bacterial phenotype dependency from CO 2 measured by Raman spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 248:119170. [PMID: 33296748 DOI: 10.1016/j.saa.2020.119170] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 10/26/2020] [Accepted: 10/30/2020] [Indexed: 06/12/2023]
Abstract
In recent years, Raman spectroscopy has become an established method to study medical, biological or environmental samples. Since Raman spectroscopy is a phenotypic method, many parameters can influence the spectra. One of these parameters is the concentration of CO2, as this never remains stable in nature, but always adjusts itself in a dynamic equilibrium. So, it is obvious that the concentration of CO2 cannot be controlled but it might have a big impact on the bacteria and bacterial composition in medical samples. When using a phenotypic method like Raman spectroscopy it is also important to know the influence of CO2 to the dataset. To investigate the influence of CO2 towards Raman spectra we cultivated E. coli at different concentration of CO2 since this bacterium is able to switch metabolism from aerobic to microaerophilic conditions. After applying statistic methods small changes in the spectra became visible and it was even possible to observe the change of metabolism in this species according to the concentration of CO2.
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Affiliation(s)
- Christina Wichmann
- Leibniz Institute of Photonic Technology Jena - Member of the Research Alliance "Leibniz Health Technologies", Albert-Einstein-Str. 9, 07745 Jena, Germany; Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany; Research Campus Infectognostics, Philosophenweg 7, 07743 Jena, Germany
| | - Thomas Bocklitz
- Leibniz Institute of Photonic Technology Jena - Member of the Research Alliance "Leibniz Health Technologies", Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Petra Rösch
- Leibniz Institute of Photonic Technology Jena - Member of the Research Alliance "Leibniz Health Technologies", Albert-Einstein-Str. 9, 07745 Jena, Germany; Research Campus Infectognostics, Philosophenweg 7, 07743 Jena, Germany.
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology Jena - Member of the Research Alliance "Leibniz Health Technologies", Albert-Einstein-Str. 9, 07745 Jena, Germany; Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany; Research Campus Infectognostics, Philosophenweg 7, 07743 Jena, Germany
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15
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Han YY, Lin YC, Cheng WC, Lin YT, Teng LJ, Wang JK, Wang YL. Rapid antibiotic susceptibility testing of bacteria from patients' blood via assaying bacterial metabolic response with surface-enhanced Raman spectroscopy. Sci Rep 2020; 10:12538. [PMID: 32719444 PMCID: PMC7385103 DOI: 10.1038/s41598-020-68855-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Accepted: 06/03/2020] [Indexed: 12/20/2022] Open
Abstract
Blood stream infection is one of the major public health issues characterized with high cost and high mortality. Timely effective antibiotics usage to control infection is crucial for patients’ survival. The standard microbiological diagnosis of infection however can last days. The delay in accurate antibiotic therapy would lead to not only poor clinical outcomes, but also to a rise in antibiotic resistance due to widespread use of empirical broad-spectrum antibiotics. An important measure to tackle this problem is fast determination of bacterial antibiotic susceptibility to optimize antibiotic treatment. We show that a protocol based on surface-enhanced Raman spectroscopy can obtain consistent antibiotic susceptibility test results from clinical blood-culture samples within four hours. The characteristic spectral signatures of the obtained spectra of Staphylococcus aureus and Escherichia coli—prototypic Gram-positive and Gram-negative bacteria—became prominent after an effective pretreatment procedure removed strong interferences from blood constituents. Using them as the biomarkers of bacterial metabolic responses to antibiotics, the protocol reported the susceptibility profiles of tested drugs against these two bacteria acquired from patients’ blood with high specificity, sensitivity and speed.
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Affiliation(s)
- Yin-Yi Han
- Department of Anesthesia, National Taiwan University Hospital, Taipei, Taiwan. .,Department of Traumatology, National Taiwan University Hospital, Taipei, Taiwan.
| | - Yi-Chun Lin
- Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan
| | - Wei-Chih Cheng
- Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan
| | - Yu-Tzu Lin
- Department of Clinical Laboratory Sciences and Medical Biotechnology, National Taiwan University, Taipei, Taiwan.,Department of Medical Laboratory Science and Biotechnology, China Medical University, Taichung, Taiwan
| | - Lee-Jene Teng
- Department of Clinical Laboratory Sciences and Medical Biotechnology, National Taiwan University, Taipei, Taiwan
| | - Juen-Kai Wang
- Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan. .,Center for Condensed Matter Sciences, National Taiwan University, Taipei, Taiwan. .,Center of Atomic Initiative for New Materials, National Taiwan University, Taipei, Taiwan.
| | - Yuh-Lin Wang
- Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan. .,Department of Physics, National Taiwan University, Taipei, Taiwan.
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16
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Wang P, Chen W, Wang J, Tang J, Shi Y, Wan F. Multigas Analysis by Cavity-Enhanced Raman Spectroscopy for Power Transformer Diagnosis. Anal Chem 2020; 92:5969-5977. [PMID: 32216282 DOI: 10.1021/acs.analchem.0c00179] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
We demonstrate the utility of cavity-enhanced Raman spectroscopy (CERS) as a unique multigas analysis tool for power transformer diagnosis. For this purpose, improvements have been added to our recently introduced CERS apparatus. Based on optical feedback frequency-locking, laser radiation is coupled into a high-finesse optical cavity, thus resulting in huge intracavity laser power. With 20 s exposure time, ppm-level gas sensing at 1 bar total pressure is achieved, including carbon dioxide (CO2), carbon monoxide (CO), hydrogen (H2), methane (CH4), ethane (C2H6), ethylene (C2H4), acetylene (C2H2), nitrogen (N2), and oxygen (O2). By using the internal standard gas (sulfur hexafluoride, SF6), the quantification of multigas with high accuracy is also realized, which is confirmed by the measurement of calibration gases. For fault diagnosis, transformer oil is sampled from a 110 kV power transformer in service. Dissolved gases are extracted and analyzed by the CERS apparatus. Then the transformer is diagnosed according to the measurement results. CERS has the ability to analyze multigas with high selectivity, sensitivity, and accuracy, it has great potential in gas sensing fields.
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Affiliation(s)
- Pinyi Wang
- State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, No. 174, Shazheng Street, Chongqing, 400044, China
| | - Weigen Chen
- State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, No. 174, Shazheng Street, Chongqing, 400044, China
| | - Jianxin Wang
- State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, No. 174, Shazheng Street, Chongqing, 400044, China
| | - Jun Tang
- State Grid Sichuan Electric Power Company, No. 18, Jiaozi North Second Road, Chengdu, 610041, China
| | - Yongli Shi
- China Southern Power Grid Company Limited, No. 137, Guanshan West Road, Guiyang, 550081, China
| | - Fu Wan
- State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, No. 174, Shazheng Street, Chongqing, 400044, China
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17
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Rapid detection of the aspergillosis biomarker triacetylfusarinine C using interference-enhanced Raman spectroscopy. Anal Bioanal Chem 2020; 412:6351-6360. [PMID: 32170382 PMCID: PMC7442771 DOI: 10.1007/s00216-020-02571-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 02/20/2020] [Accepted: 03/02/2020] [Indexed: 11/02/2022]
Abstract
Triacetylfusarinine C (TAFC) is a siderophore produced by certain fungal species and might serve as a highly useful biomarker for the fast diagnosis of invasive aspergillosis. Due to its renal elimination, the biomarker is found in urine samples of patients suffering from Aspergillus infections. Accordingly, non-invasive diagnosis from this easily obtainable body fluid is possible. Within our contribution, we demonstrate how Raman microspectroscopy enables a sensitive and specific detection of TAFC. We characterized the TAFC iron complex and its iron-free form using conventional and interference-enhanced Raman spectroscopy (IERS) and compared the spectra with the related compound ferrioxamine B, which is produced by bacterial species. Even though IERS only offers a moderate enhancement of the Raman signal, the employment of respective substrates allowed lowering the detection limit to reach the clinically relevant range. The achieved limit of detection using IERS was 0.5 ng of TAFC, which is already well within the clinically relevant range. By using an extraction protocol, we were able to detect 1.4 μg/mL TAFC via IERS from urine within less than 3 h including sample preparation and data analysis. We could further show that TAFC and ferrioxamine B can be clearly distinguished by means of their Raman spectra even in very low concentrations.
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18
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Wichmann C, Chhallani M, Bocklitz T, Rösch P, Popp J. Simulation of Transportation and Storage and Their Influence on Raman Spectra of Bacteria. Anal Chem 2019; 91:13688-13694. [DOI: 10.1021/acs.analchem.9b02932] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Christina Wichmann
- Leibniz Institute of Photonic Technology Jena − Member of the Research Alliance “Leibniz Health Technologies”, Albert-Einstein-Str. 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Research Campus Infectognostics, Philosophenweg 7, 07743 Jena, Germany
| | - Mehul Chhallani
- Leibniz Institute of Photonic Technology Jena − Member of the Research Alliance “Leibniz Health Technologies”, Albert-Einstein-Str. 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Research Campus Infectognostics, Philosophenweg 7, 07743 Jena, Germany
| | - Thomas Bocklitz
- Leibniz Institute of Photonic Technology Jena − Member of the Research Alliance “Leibniz Health Technologies”, Albert-Einstein-Str. 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Research Campus Infectognostics, Philosophenweg 7, 07743 Jena, Germany
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology Jena − Member of the Research Alliance “Leibniz Health Technologies”, Albert-Einstein-Str. 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Research Campus Infectognostics, Philosophenweg 7, 07743 Jena, Germany
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