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Dinçtürk E. Determination of Raman spectrum under different culture conditions: preliminary research on bacterial fish pathogens. Anim Biotechnol 2024; 35:2299733. [PMID: 38166494 DOI: 10.1080/10495398.2023.2299733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2024]
Abstract
The intensive labour and time required for conventional methods to identify bacterial fish pathogens have revealed the need to develop alternative methods. Raman spectroscopy has been used in the rapid optical identification of bacterial pathogens in recent years as an alternative method in microbiology. Strains of bacterial fish pathogens (Vibrio anguillarum, Lactococcus garvieae and Yersinia ruckeri) that often cause infectious diseases in fish were here identified and analyzed in terms of their biochemical structures in different media and at different incubation times, and the data were specified by using Raman spectroscopy. The results demonstrated that Raman spectroscopy presents species-specific Raman spectra of each disease-causing bacteria and that it would be more appropriate to choose general microbiological media over selective media for routine studies. Additionally, it was found that species-specific band regions did not differ in 24- and 48-hour cultures, but there could be a difference in peak intensity which may lead to difficult characterization of spectrum. The current study, conducted for the first time with bacterial fish pathogens under different incubation conditions, is believed to provide a basis for the routine use of Raman spectroscopy for quick pathogen identification and the precise determination of the methodology for further research.
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Affiliation(s)
- Ezgi Dinçtürk
- Fish Disease and Biotechnology Laboratory, Department of Aquaculture, Izmir Katip Celebi University, Izmir, Türkiye
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2
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Fernández-Manteca MG, Ocampo-Sosa AA, Vecilla DF, Ruiz MS, Roiz MP, Madrazo F, Rodríguez-Grande J, Calvo-Montes J, Rodríguez-Cobo L, López-Higuera JM, Fariñas MC, Cobo A. Identification of hypermucoviscous Klebsiella pneumoniae K1, K2, K54 and K57 capsular serotypes by Raman spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 319:124533. [PMID: 38820814 DOI: 10.1016/j.saa.2024.124533] [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: 02/01/2024] [Revised: 05/17/2024] [Accepted: 05/24/2024] [Indexed: 06/02/2024]
Abstract
Antimicrobial resistance poses a significant challenge in modern medicine, affecting public health. Klebsiella pneumoniae infections compound this issue due to their broad range of infections and the emergence of multiple antibiotic resistance mechanisms. Efficient detection of its capsular serotypes is crucial for immediate patient treatment, epidemiological tracking and outbreak containment. Current methods have limitations that can delay interventions and increase the risk of morbidity and mortality. Raman spectroscopy is a promising alternative to identify capsular serotypes in hypermucoviscous K. pneumoniae isolates. It provides rapid and in situ measurements with minimal sample preparation. Moreover, its combination with machine learning tools demonstrates high accuracy and reproducibility. This study analyzed the viability of combining Raman spectroscopy with one-dimensional convolutional neural networks (1-D CNN) to classify four capsular serotypes of hypermucoviscous K. pneumoniae: K1, K2, K54 and K57. Our approach involved identifying the most relevant Raman features for classification to prevent overfitting in the training models. Simplifying the dataset to essential information maintains accuracy and reduces computational costs and training time. Capsular serotypes were classified with 96 % accuracy using less than 30 Raman features out of 2400 contained in each spectrum. To validate our methodology, we expanded the dataset to include both hypermucoviscous and non-mucoid isolates and distinguished between them. This resulted in an accuracy rate of 94 %. The results obtained have significant potential for practical healthcare applications, especially for enabling the prompt prescription of the appropriate antibiotic treatment against infections.
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Affiliation(s)
- María Gabriela Fernández-Manteca
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Photonics Engineering Group, Universidad de Cantabria, Santander, Spain.
| | - Alain A Ocampo-Sosa
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Servicio de Microbiología, Hospital Universitario Marqués de Valdecilla, Santander, Spain; CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
| | - Domingo Fernandez Vecilla
- Clinical Microbiology and Parasitology Department, Basurto University Hospital, Bilbao, Vizcaya, Spain; Biocruces Bizkaia Health Research Institute, Barakaldo, Vizcaya, Spain
| | - María Siller Ruiz
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Servicio de Microbiología, Hospital Universitario Marqués de Valdecilla, Santander, Spain
| | - María Pía Roiz
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Servicio de Microbiología, Hospital Universitario Marqués de Valdecilla, Santander, Spain
| | - Fidel Madrazo
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain
| | - Jorge Rodríguez-Grande
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Servicio de Microbiología, Hospital Universitario Marqués de Valdecilla, Santander, Spain
| | - Jorge Calvo-Montes
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Servicio de Microbiología, Hospital Universitario Marqués de Valdecilla, Santander, Spain; CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
| | - Luis Rodríguez-Cobo
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Photonics Engineering Group, Universidad de Cantabria, Santander, Spain; CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - José Miguel López-Higuera
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Photonics Engineering Group, Universidad de Cantabria, Santander, Spain; CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - María Carmen Fariñas
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain; Servicio de Enfermedades Infecciosas, Hospital Universitario Marqués de Valdecilla, Santander, Spain; Departamento de Medicina y Psiquiatría, Universidad de Cantabria, Santander, Spain
| | - Adolfo Cobo
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Photonics Engineering Group, Universidad de Cantabria, Santander, Spain; CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain.
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3
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Karlo J, Gupta A, Singh SP. In situ monitoring of the shikimate pathway: a combinatorial approach of Raman reverse stable isotope probing and hyperspectral imaging. Analyst 2024; 149:2833-2841. [PMID: 38587502 DOI: 10.1039/d4an00203b] [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: 04/09/2024]
Abstract
Sensing and visualization of metabolites and metabolic pathways in situ are significant requirements for tracking their spatiotemporal dynamics in a non-destructive manner. The shikimate pathway is an important cellular mechanism that leads to the de novo synthesis of many compounds containing aromatic rings of high importance such as phenylalanine, tyrosine, and tryptophan. In this work, we present a cost-effective and extraction-free method based on the principles of stable isotope-coupled Raman spectroscopy and hyperspectral Raman imaging to monitor and visualize the activity of the shikimate pathway. We also demonstrated the applicability of this approach for nascent aromatic amino acid localization and tracking turnover dynamics in both prokaryotic and eukaryotic model systems. This method can emerge as a promising tool for both qualitative and semi-quantitative in situ metabolomics, contributing to a better understanding of aromatic ring-containing metabolite dynamics across various organisms.
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Affiliation(s)
- Jiro Karlo
- Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, Karnataka, 580011, India.
| | - Aryan Gupta
- Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, Karnataka, 580011, India.
| | - Surya Pratap Singh
- Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, Karnataka, 580011, India.
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Karlo J, Dhillon AK, Siddhanta S, Singh SP. Monitoring of microbial proteome dynamics using Raman stable isotope probing. JOURNAL OF BIOPHOTONICS 2023; 16:e202200341. [PMID: 36527375 DOI: 10.1002/jbio.202200341] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/06/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
Abnormal protein kinetics could be a cause of several diseases associated with essential life processes. An accurate understanding of protein dynamics and turnover is essential for developing diagnostic or therapeutic tools to monitor these changes. Raman spectroscopy in combination with stable isotope probes (SIP) such as carbon-13, and deuterium has been a breakthrough in the qualitative and quantitative study of various metabolites. In this work, we are reporting the utility of Raman-SIP for monitoring dynamic changes in the proteome at the community level. We have used 13 C-labeled glucose as the only carbon source in the medium and verified its incorporation in the microbial biomass in a time-dependent manner. A visible redshift in the Raman spectral vibrations of major biomolecules such as nucleic acids, phenylalanine, tyrosine, amide I, and amide III were observed. Temporal changes in the intensity of these bands demonstrating the feasibility of protein turnover monitoring were also verified. Kanamycin, a protein synthesis inhibitor was used to assess the feasibility of identifying effects on protein turnover in the cells. Successful application of this work can provide an alternate/adjunct tool for monitoring proteome-level changes in an objective and nondestructive manner.
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Affiliation(s)
- Jiro Karlo
- Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, Karnataka, India
| | | | - Soumik Siddhanta
- Department of Chemistry, Indian Institute of Technology Delhi, New Delhi, India
| | - Surya Pratap Singh
- Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, Karnataka, India
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Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy. Foods 2022; 11:foods11101506. [PMID: 35627076 PMCID: PMC9141442 DOI: 10.3390/foods11101506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/16/2022] [Accepted: 05/19/2022] [Indexed: 01/27/2023] Open
Abstract
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 Escherichia coli and at strain level for the other food relevant microorganisms showed a classification rate of 97.6%.
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Kriem LS, Wright K, Ccahuana-Vasquez RA, Rupp S. Mapping of a Subgingival Dual-Species Biofilm Model Using Confocal Raman Microscopy. Front Microbiol 2021; 12:729720. [PMID: 34675902 PMCID: PMC8525910 DOI: 10.3389/fmicb.2021.729720] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 09/13/2021] [Indexed: 12/14/2022] Open
Abstract
Techniques for continuously monitoring the formation of subgingival biofilm, in relation to the determination of species and their accumulation over time in gingivitis and periodontitis, are limited. In recent years, advancements in the field of optical spectroscopic techniques have provided an alternative for analyzing three-dimensional microbiological structures, replacing the traditional destructive or biofilm staining techniques. In this work, we have demonstrated that the use of confocal Raman spectroscopy coupled with multivariate analysis provides an approach to spatially differentiate bacteria in an in vitro model simulating a subgingival dual-species biofilm. The present study establishes a workflow to evaluate and differentiate bacterial species in a dual-species in vitro biofilm model, using confocal Raman microscopy (CRM). Biofilm models of Actinomyces denticolens and Streptococcus oralis were cultured using the “Zürich in vitro model” and were analyzed using CRM. Cluster analysis was used to spatially differentiate and map the biofilm model over a specified area. To confirm the clustering of species in the cultured biofilm, confocal laser scanning microscopy (CLSM) was coupled with fluorescent in vitro hybridization (FISH). Additionally, dense bacteria interface area (DBIA) samples, as an imitation of the clusters in a biofilm, were used to test the developed multivariate differentiation model. This confirmed model was successfully used to differentiate species in a dual-species biofilm and is comparable to morphology. The results show that the developed workflow was able to identify main clusters of bacteria based on spectral “fingerprint region” information from CRM. Using this workflow, we have demonstrated that CRM can spatially analyze two-species in vitro biofilms, therefore providing an alternative technique to map oral multi-species biofilm models.
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Affiliation(s)
- Lukas Simon Kriem
- Fraunhofer Institute for Interfacial Engineering and Biotechnology, Stuttgart, Germany
| | | | | | - Steffen Rupp
- Fraunhofer Institute for Interfacial Engineering and Biotechnology, Stuttgart, Germany
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Dinçtürk E, Tanrıkul TT. First preliminary study on identification of bacterial fish pathogens with Raman spectroscopy. Anim Biotechnol 2021:1-9. [PMID: 34559037 DOI: 10.1080/10495398.2021.1979567] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Accurate and rapid determination of bacterial disease agents of fish is an important step for sustainable and efficient aquaculture production. In general, biochemical and molecular methods are used for pathogen detection but they are usually time-consuming and required qualified personnel. Recently spectroscopic methods are preferred in clinical and food microbiology and declared as a promising alternative method for pathogens diagnosis with many advantages. In this study, the significant spectra of three important bacterial fish pathogens (Lactococcus garvieae, Vibrio anguillarum and Yersinia ruckeri) were determined by Raman spectroscopy. The first data of the pathogens were obtained and the distinctive differences in polysaccharides, nucleic acids, fatty acids and amino acids were identified. This preliminary study aimed to be pioneer for further studies in aquaculture and veterinary microbiology toward developing an alternative method for routine identification.
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Affiliation(s)
- Ezgi Dinçtürk
- Department of Aquaculture, Faculty of Fisheries, Izmir Katip Celebi University, Izmir, Turkey
| | - Tevfik Tansel Tanrıkul
- Department of Aquaculture, Faculty of Fisheries, Izmir Katip Celebi University, Izmir, Turkey
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Yu S, Li H, Li X, Fu YV, Liu F. Classification of pathogens by Raman spectroscopy combined with generative adversarial networks. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 726:138477. [PMID: 32315848 DOI: 10.1016/j.scitotenv.2020.138477] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 04/02/2020] [Accepted: 04/03/2020] [Indexed: 06/11/2023]
Abstract
Rapid identification of marine pathogens is very important in marine ecology. Artificial intelligence combined with Raman spectroscopy is a promising choice for identifying marine pathogens due to its rapidity and efficiency. However, considering the cost of sample collection and the challenging nature of the experimental environment, only limited spectra are typically available to build a classification model, which hinders qualitative analysis. In this paper, we propose a novel method to classify marine pathogens by means of Raman spectroscopy combined with generative adversarial networks (GANs). Three marine strains, namely, Staphylococcus hominis, Vibrio alginolyticus, and Bacillus licheniformis, were cultured. Using Raman spectroscopy, we acquired 100 spectra of each strain, and we fitted them into GAN models for training. After 30,000 training iterations, the spectra generated by G were similar to the actual spectra, and D was used to test the accuracy of the spectra. Our results demonstrate that our method not only improves the accuracy of machine learning classification but also solves the problem of requiring a large amount of training data. Moreover, we have attempted to find potential identifying regions in the Raman spectra that can be used for reference in subsequent related work in this field. Therefore, this method has tremendous potential to be developed as a tool for pathogen identification.
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Affiliation(s)
- Shixiang Yu
- Key Laboratory of Coastal Biology and Biological Resources Utilization, CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, P. R. China; University of the Chinese Academy of Sciences, Beijing 100049, PR China
| | - Hanfei Li
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, PR China; University of the Chinese Academy of Sciences, Beijing 100049, PR China
| | - Xin Li
- Key Laboratory of Coastal Biology and Biological Resources Utilization, CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, P. R. China; University of the Chinese Academy of Sciences, Beijing 100049, PR China
| | - Yu Vincent Fu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, PR China.
| | - Fanghua Liu
- Key Laboratory of Coastal Biology and Biological Resources Utilization, CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, P. R. China; National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Guangdong Institute of Eco-environmental Science & Technology, Guangdong Academy of Sciences, Guangzhou 510650, PR China; Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, PR China.
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Mukherjee R, Verma T, Nandi D, Umapathy S. Identification of a resonance Raman marker for cytochrome to monitor stress responses in Escherichia coli. Anal Bioanal Chem 2020; 412:5379-5388. [PMID: 32548767 DOI: 10.1007/s00216-020-02753-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 05/16/2020] [Accepted: 06/02/2020] [Indexed: 11/29/2022]
Abstract
Raman spectroscopy and resonance Raman spectroscopy are widely used to study bacteria and their responses to different environmental conditions. In the present study, the identification of a novel resonance Raman peak for Escherichia coli, recorded with 633 nm laser excitation is discussed. A peak at 740 cm-1 is observed exclusively with 633 nm excitation but not with 514 nm or 785 nm excitation. This peak is absent in the lag phase but appears in the log phase of bacterial growth. The intensity of the peak increases at high temperature (45 °C) compared with growth at low temperature (25 °C) or the physiological temperature (37 °C). Although osmotic stress lowered bacterial growth, the intensity of this peak was unaffected. However, treatment with chemical uncouplers of oxidative phosphorylation resulted in significantly lower intensity of this Raman band, indicating its possible involvement in respiration. Cytochromes, a component of bacterial respiration' can show resonance enhancement at 633 nm due to the presence of a shoulder in that region depending on the type and conformation of cytochrome. Therefore, the peak intensity was monitored in different genetic mutants of E. coli lacking cytochromes. This peak is absent in the Escherichia coli mutant lacking cydB, but not ccmE, demonstrating the contribution of cytochrome bd subunit II in the peak's origin. In future, this newly found cytochrome marker can be used for biochemical assessment of bacteria exposed to various conditions. Overall, this finding opens the scope for use of red laser excitation in resonance Raman in monitoring stress and respiration in bacteria. Graphical abstract.
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Affiliation(s)
- Ria Mukherjee
- Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore, Karnataka, 560012, India
| | - Taru Verma
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, Karnataka, 560012, India
| | - Dipankar Nandi
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, Karnataka, 560012, India. .,Department of Biochemistry, Indian Institute of Science, Bangalore, Karnataka, 560012, India.
| | - Siva Umapathy
- Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore, Karnataka, 560012, India. .,Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, Karnataka, 560012, India. .,Department of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore, Karnataka, 560012, India.
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Kriem LS, Wright K, Ccahuana-Vasquez RA, Rupp S. Confocal Raman microscopy to identify bacteria in oral subgingival biofilm models. PLoS One 2020; 15:e0232912. [PMID: 32392236 PMCID: PMC7213720 DOI: 10.1371/journal.pone.0232912] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Accepted: 04/23/2020] [Indexed: 12/16/2022] Open
Abstract
The study of oral disease progression, in relation to the accumulation of subgingival biofilm in gingivitis and periodontitis is limited, due to either the ability to monitor plaque in vitro. When compared, optical spectroscopic techniques offer advantages over traditional destructive or biofilm staining approaches, making it a suitable alternative for the analysis and continued development of three-dimensional structures. In this work, we have developed a confocal Raman spectroscopy analysis approach towards in vitro subgingival plaque models. The main objective of this study was to develop a method for differentiating multiple oral subgingival bacterial species in planktonic and biofilm conditions, using confocal Raman microscopy. Five common subgingival bacteria (Fusobacterium nucleatum, Streptococcus mutans, Veillonella dispar, Actinomyces naeslundii and Prevotella nigrescens) were used and differentiated using a 2-way orthogonal Partial Least Square with Discriminant Analysis (O2PLS-DA) for the collected spectral data. In addition to planktonic growth, mono-species biofilms cultured using the 'Zürich Model' were also analyzed. The developed method was successfully used to predict planktonic and mono-species biofilm species in a cross validation setup. The results show differences in the presence and absence of chemical bands within the Raman spectra. The O2PLS-DA model was able to successfully predict 100% of all tested planktonic samples and 90% of all mono-species biofilm samples. Using this approach we have shown that Confocal Raman microscopy can analyse and predict the identity of planktonic and mono-species biofilm species, thus enabling its potential as a technique to map oral multi-species biofilm models.
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Affiliation(s)
- Lukas Simon Kriem
- Fraunhofer Institute for Interfacial Engineering and Biotechnology, Stuttgart, Germany
| | - Kevin Wright
- Procter & Gamble, Egham, England, United Kingdom
| | | | - Steffen Rupp
- Fraunhofer Institute for Interfacial Engineering and Biotechnology, Stuttgart, Germany
- * E-mail:
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11
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Prasad A, Hasan SMA, Gartia MR. Optical Identification of Middle Ear Infection. Molecules 2020; 25:molecules25092239. [PMID: 32397569 PMCID: PMC7248855 DOI: 10.3390/molecules25092239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 04/28/2020] [Accepted: 04/29/2020] [Indexed: 11/16/2022] Open
Abstract
Ear infection is one of the most commonly occurring inflammation diseases in the world, especially for children. Almost every child encounters at least one episode of ear infection before he/she reaches the age of seven. The typical treatment currently followed by physicians is visual inspection and antibiotic prescription. In most cases, a lack of improper treatment results in severe bacterial infection. Therefore, it is necessary to design and explore advanced practices for effective diagnosis. In this review paper, we present the various types of ear infection and the related pathogens responsible for middle ear infection. We outline the conventional techniques along with clinical trials using those techniques to detect ear infections. Further, we highlight the need for emerging techniques to reduce ear infection complications. Finally, we emphasize the utility of Raman spectroscopy as a prospective non-invasive technique for the identification of middle ear infection.
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12
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Mukherjee R, Verma T, Nandi D, Umapathy S. Understanding the effects of culture conditions in bacterial growth: A biochemical perspective using Raman microscopy. JOURNAL OF BIOPHOTONICS 2020; 13:e201900233. [PMID: 31444944 DOI: 10.1002/jbio.201900233] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 08/16/2019] [Accepted: 08/21/2019] [Indexed: 06/10/2023]
Abstract
Rapid, sensitive and label-free methods to probe bacterial growth irrespective of the culture conditions can shed light on the mechanisms by which bacteria adapt to different environmental stimuli. Raman spectroscopy can rapidly and continuously monitor the growth of bacteria under varied conditions. In this study, the growth of Escherichia coli in Luria broth (nutrient rich conditions) and minimal media with either glucose or glycerol as carbon source (nutrient limiting conditions) is profiled using Raman spectroscopy. Moreover, the study also gives insights into the altered bacterial biochemistry upon exposure to low- (25°C) and high-temperature (45°C) stress. Raman spectral measurement was performed on bulk bacteria cultured under laboratory conditions. A detailed analysis of the spectra as a function of bacterial growth reveals changes in Raman band intensities/area of biomolecules such as DNA, proteins and lipids. We also report five novel ratiometric markers (I830 /I810 , I1126 /I1100 , I1340 /I1440 , I1207 /I1240 and I1580 /I1440 ) that can identify the phase of growth, independent of the culture condition. Unsupervised multivariate methods like Principal Component Analysis also corroborate the aforementioned markers of growth. Altogether, our findings highlight the potential of Raman spectroscopy in yielding universal biochemical signatures that may be indicative of stress and aging in a growth milieu.
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Affiliation(s)
- Ria Mukherjee
- Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore, Karnataka, India
| | - Taru Verma
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, Karnataka, India
| | - Dipankar Nandi
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, Karnataka, India
- Department of Biochemistry, Indian Institute of Science Bangalore, Bangalore, Karnataka, India
| | - Siva Umapathy
- Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore, Karnataka, India
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, Karnataka, India
- Department of Instrumentation and Applied Physics, Indian Institute of Science Bangalore, Bangalore, Karnataka, India
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13
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Verma T, Podder S, Mehta M, Singh S, Singh A, Umapathy S, Nandi D. Raman spectroscopy reveals distinct differences between two closely related bacterial strains, Mycobacterium indicus pranii and Mycobacterium intracellulare. Anal Bioanal Chem 2019; 411:7997-8009. [PMID: 31732785 DOI: 10.1007/s00216-019-02197-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 09/24/2019] [Accepted: 10/07/2019] [Indexed: 02/07/2023]
Abstract
A common technique used to differentiate bacterial species and to determine evolutionary relationships is sequencing their 16S ribosomal RNA genes. However, this method fails when organisms exhibit high similarity in these sequences. Two such strains that have identical 16S rRNA sequences are Mycobacterium indicus pranii (MIP) and Mycobacterium intracellulare. MIP is of significance as it is used as an adjuvant for protection against tuberculosis and leprosy; in addition, it shows potent anti-cancer activity. On the other hand, M. intracellulare is an opportunistic pathogen and causes severe respiratory infections in AIDS patients. It is important to differentiate these two bacterial species as they co-exist in immuno-compromised individuals. To unambiguously distinguish these two closely related bacterial strains, we employed Raman and resonance Raman spectroscopy in conjunction with multivariate statistical tools. Phenotypic profiling for these bacterial species was performed in a kinetic manner. Differences were observed in the mycolic acid profile and carotenoid pigments to show that MIP is biochemically distinct from M. intracellulare. Resonance Raman studies confirmed that carotenoids were produced by both MIP as well as M. intracellulare, though the latter produced higher amounts. Overall, this study demonstrates the potential of Raman spectroscopy in differentiating two closely related mycobacterial strains. Graphical abstract.
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Affiliation(s)
- Taru Verma
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, 560012, India
| | - Santosh Podder
- Centre for Infectious Disease Research, Indian Institute of Science, Bangalore, 560012, India
- Department of Biochemistry, Indian Institute of Science, Bangalore, 560012, India
| | - Mansi Mehta
- Centre for Infectious Disease Research, Indian Institute of Science, Bangalore, 560012, India
| | - Sarman Singh
- All India Institute of Medical Sciences, Bhopal, 462020, India
| | - Amit Singh
- Centre for Infectious Disease Research, Indian Institute of Science, Bangalore, 560012, India
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bangalore, 560012, India
| | - Siva Umapathy
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, 560012, India.
- Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore, 560012, India.
| | - Dipankar Nandi
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, 560012, India.
- Centre for Infectious Disease Research, Indian Institute of Science, Bangalore, 560012, India.
- Department of Biochemistry, Indian Institute of Science, Bangalore, 560012, India.
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Kuhar N, Sil S, Verma T, Umapathy S. Challenges in application of Raman spectroscopy to biology and materials. RSC Adv 2018; 8:25888-25908. [PMID: 35541973 PMCID: PMC9083091 DOI: 10.1039/c8ra04491k] [Citation(s) in RCA: 124] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Accepted: 07/09/2018] [Indexed: 12/14/2022] Open
Abstract
Raman spectroscopy has become an essential tool for chemists, physicists, biologists and materials scientists. In this article, we present the challenges in unravelling the molecule-specific Raman spectral signatures of different biomolecules like proteins, nucleic acids, lipids and carbohydrates based on the review of our work and the current trends in these areas. We also show how Raman spectroscopy can be used to probe the secondary and tertiary structural changes occurring during thermal denaturation of protein and lysozyme as well as more complex biological systems like bacteria. Complex biological systems like tissues, cells, blood serum etc. are also made up of such biomolecules. Using mice liver and blood serum, it is shown that different tissues yield their unique signature Raman spectra, owing to a difference in the relative composition of the biomolecules. Additionally, recent progress in Raman spectroscopy for diagnosing a multitude of diseases ranging from cancer to infection is also presented. The second part of this article focuses on applications of Raman spectroscopy to materials. As a first example, Raman spectroscopy of a melt cast explosives formulation was carried out to monitor the changes in the peaks which indicates the potential of this technique for remote process monitoring. The second example presents various modern methods of Raman spectroscopy such as spatially offset Raman spectroscopy (SORS), reflection, transmission and universal multiple angle Raman spectroscopy (UMARS) to study layered materials. Studies on chemicals/layered materials hidden in non-metallic containers using the above variants are presented. Using suitable examples, it is shown how a specific excitation or collection geometry can yield different information about the location of materials. Additionally, it is shown that UMARS imaging can also be used as an effective tool to obtain layer specific information of materials located at depths beyond a few centimeters. This paper reviews various facets of Raman spectroscopy. This encompasses biomolecule fingerprinting and conformational analysis, discrimination of healthy vs. diseased states, depth-specific information of materials and 3D Raman imaging.![]()
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Affiliation(s)
- Nikki Kuhar
- Department of Inorganic & Physical Chemistry
- Indian Institute of Science
- Bangalore
- India-560012
| | - Sanchita Sil
- Defence Bioengineering & Electromedical Laboratory
- DRDO
- Bangalore
- India-560093
| | - Taru Verma
- Centre for Biosystems Science and Engineering
- Indian Institute of Science
- Bangalore
- India-560012
| | - Siva Umapathy
- Department of Inorganic & Physical Chemistry
- Indian Institute of Science
- Bangalore
- India-560012
- Department of Instrumentation & Applied Physics
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