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Saikia D, Vijay A, Cebajel Bhanwarlal T, Singh SP. Validating the utility of heavy water (Deuterium Oxide) as a potential Raman spectroscopic probe for identification of antibiotic resistance. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 321:124723. [PMID: 38941753 DOI: 10.1016/j.saa.2024.124723] [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: 02/02/2024] [Revised: 05/07/2024] [Accepted: 06/24/2024] [Indexed: 06/30/2024]
Abstract
The impact of microbial infections is increasing over time, and it is one of the major reasons for death in both developed and developing countries. colistin is considered as the antibiotic of last choice for infections brought by major multidrug-resistant (MDR), gram-negative bacteria such as Enterobacter species, Acinetobacter species, and Pseudomonas aeruginosa. Existing approaches to diagnose these resistant species are relatively slow and take up to 2 to 3 days. In this work, we propose a novel interdisciplinary method based on Raman spectroscopy and heavy water to identify colistin-resistant microbes. Our hypothesis is based on the fact that resistant bacteria will be metabolically active in the culture medium containing antibiotics and heavy water, and these bacteria will take up deuterium instead of hydrogen to newly synthesized lipids and proteins. This effect will generate a 'C - D' bond-specific Raman spectral marker. Successful identification of this band in the spectral profile can confirm the presence of colistin-resistant bacteria. We have validated the efficacy of this approach in identifying colistin-resistant bacteria spiked in artificial urine and have compared sensitivity at different bacterial concentrations. Overall findings suggest that heavy water can potentially serve as a suitable Raman probe for identifying metabolically active colistin-resistant bacteria via urine under clinically implementable time and can be used in clinical settings after validation.
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Affiliation(s)
- Dimple Saikia
- Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, Karnataka 580011, India
| | - Arunsree Vijay
- Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, Karnataka 580011, India
| | - Tanan Cebajel Bhanwarlal
- Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, Karnataka 580011, India
| | - S P Singh
- Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, Karnataka 580011, India.
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2
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Vardaki MZ, Gregoriou VG, Chochos CL. Biomedical applications, perspectives and tag design concepts in the cell - silent Raman window. RSC Chem Biol 2024; 5:273-292. [PMID: 38576725 PMCID: PMC10989507 DOI: 10.1039/d3cb00217a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 02/12/2024] [Indexed: 04/06/2024] Open
Abstract
Spectroscopic studies increasingly employ Raman tags exhibiting a signal in the cell - silent region of the Raman spectrum (1800-2800 cm-1), where bands arising from biological molecules are inherently absent. Raman tags bearing functional groups which contain a triple bond, such as alkyne and nitrile or a carbon-deuterium bond, have a distinct vibrational frequency in this region. Due to the lack of spectral background and cell-associated bands in the specific area, the implementation of those tags can help overcome the inherently poor signal-to-noise ratio and presence of overlapping Raman bands in measurements of biological samples. The cell - silent Raman tags allow for bioorthogonal imaging of biomolecules with improved chemical contrast and they have found application in analyte detection and monitoring, biomarker profiling and live cell imaging. This review focuses on the potential of the cell - silent Raman region, reporting on the tags employed for biomedical applications using variants of Raman spectroscopy.
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Affiliation(s)
- Martha Z Vardaki
- Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vassileos Constantinou Avenue Athens 11635 Greece
| | - Vasilis G Gregoriou
- Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vassileos Constantinou Avenue Athens 11635 Greece
- Advent Technologies SA, Stadiou Street, Platani Rio Patras 26504 Greece
| | - Christos L Chochos
- Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vassileos Constantinou Avenue Athens 11635 Greece
- Advent Technologies SA, Stadiou Street, Platani Rio Patras 26504 Greece
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3
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Allakhverdiev ES, Kossalbayev BD, Sadvakasova AK, Bauenova MO, Belkozhayev AM, Rodnenkov OV, Martynyuk TV, Maksimov GV, Allakhverdiev SI. Spectral insights: Navigating the frontiers of biomedical and microbiological exploration with Raman spectroscopy. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY. B, BIOLOGY 2024; 252:112870. [PMID: 38368635 DOI: 10.1016/j.jphotobiol.2024.112870] [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: 11/24/2023] [Revised: 01/04/2024] [Accepted: 02/14/2024] [Indexed: 02/20/2024]
Abstract
Raman spectroscopy (RS), a powerful analytical technique, has gained increasing recognition and utility in the fields of biomedical and biological research. Raman spectroscopic analyses find extensive application in the field of medicine and are employed for intricate research endeavors and diagnostic purposes. Consequently, it enjoys broad utilization within the realm of biological research, facilitating the identification of cellular classifications, metabolite profiling within the cellular milieu, and the assessment of pigment constituents within microalgae. This article also explores the multifaceted role of RS in these domains, highlighting its distinct advantages, acknowledging its limitations, and proposing strategies for enhancement.
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Affiliation(s)
- Elvin S Allakhverdiev
- National Medical Research Center of Cardiology named after academician E.I. Chazov, Academician Chazov 15А St., Moscow 121552, Russia; Department of Biophysics, Faculty of Biology, Lomonosov Moscow State University, Moscow, Leninskie Gory 1/12, Moscow 119991, Russia.
| | - Bekzhan D Kossalbayev
- Ecology Research Institute, Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkistan, Kazakhstan; Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, No. 32, West 7th Road, Tianjin Airport Economic Area, 300308 Tianjin, China; Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, Almaty 050038, Kazakhstan; Department of Chemical and Biochemical Engineering, Institute of Geology and Oil-Gas Business Institute Named after K. Turyssov, Satbayev University, Almaty 050043, Kazakhstan
| | - Asemgul K Sadvakasova
- Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, Almaty 050038, Kazakhstan
| | - Meruyert O Bauenova
- Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, Almaty 050038, Kazakhstan
| | - Ayaz M Belkozhayev
- Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, Almaty 050038, Kazakhstan; Department of Chemical and Biochemical Engineering, Institute of Geology and Oil-Gas Business Institute Named after K. Turyssov, Satbayev University, Almaty 050043, Kazakhstan; M.A. Aitkhozhin Institute of Molecular Biology and Biochemistry, Almaty 050012, Kazakhstan
| | - Oleg V Rodnenkov
- National Medical Research Center of Cardiology named after academician E.I. Chazov, Academician Chazov 15А St., Moscow 121552, Russia
| | - Tamila V Martynyuk
- National Medical Research Center of Cardiology named after academician E.I. Chazov, Academician Chazov 15А St., Moscow 121552, Russia
| | - Georgy V Maksimov
- Department of Biophysics, Faculty of Biology, Lomonosov Moscow State University, Moscow, Leninskie Gory 1/12, Moscow 119991, Russia
| | - Suleyman I Allakhverdiev
- K.A. Timiryazev Institute of Plant Physiology, Russian Academy of Sciences, Botanicheskaya Street 35, Moscow 127276, Russia; Institute of Basic Biological Problems, FRC PSCBR Russian Academy of Sciences, Pushchino 142290, Russia; Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey.
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4
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Lu Y, Lei B, Zhao Q, Yang X, Wei Y, Xiao T, Zhu S, Ouyang Y, Zhang H, Cai W. Solid-State Au Nanocone Arrays Substrate for Reliable SERS Profiling of Serum for Disease Diagnosis. ACS OMEGA 2023; 8:29836-29846. [PMID: 37599935 PMCID: PMC10433333 DOI: 10.1021/acsomega.3c04910] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 07/25/2023] [Indexed: 08/22/2023]
Abstract
Surface-enhanced Raman scattering (SERS) is a widely used rapid and noninvasive method for detecting biological substances in serum samples and is commonly employed in disease screening and diagnosis. Solid-state nanoarray SERS substrates used in serum detection may cause spectral instability due to imperfections in the detection method. For the purpose of identifying optimal detection conditions, various dilution levels of the serum were tested in this study. The study found that a complete and stable serum SERS spectrum can be obtained when the serum is diluted by a factor of 50. The study reports the successful preparation of an Au nanocone array (Au NCA) plasmonic substrate with a uniform, controllable microstructure and high activity, achieved through a combination of PS colloidal sphere template-assisted reactive ion etching (RIE) process and magnetron sputtering deposition technology. Based on this substrate, a standard detection scheme was developed to obtain highly stable and repeatable serum SERS spectra. The study verified the reliability of the optimized serum detection scheme by comparing the SERS spectra of serum samples from healthy individuals and gastric cancer patients, and confirmed the potential benefits of the scheme for disease screening and diagnosis.
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Affiliation(s)
- Yanyan Lu
- Key
Lab of Materials Physics, Anhui Key Lab of Nanomaterials and Nanotechnology,
Institute of Solid State Physics, HFIPS,
Chinese Academy of Sciences, Hefei 230031, P. R. China
- University
of Science and Technology of China, Hefei 230026, P. R. China
| | - Biao Lei
- Key
Lab of Materials Physics, Anhui Key Lab of Nanomaterials and Nanotechnology,
Institute of Solid State Physics, HFIPS,
Chinese Academy of Sciences, Hefei 230031, P. R. China
- University
of Science and Technology of China, Hefei 230026, P. R. China
| | - Qian Zhao
- Key
Lab of Materials Physics, Anhui Key Lab of Nanomaterials and Nanotechnology,
Institute of Solid State Physics, HFIPS,
Chinese Academy of Sciences, Hefei 230031, P. R. China
| | - Xiaowei Yang
- Key
Lab of Materials Physics, Anhui Key Lab of Nanomaterials and Nanotechnology,
Institute of Solid State Physics, HFIPS,
Chinese Academy of Sciences, Hefei 230031, P. R. China
- University
of Science and Technology of China, Hefei 230026, P. R. China
| | - Yi Wei
- Key
Lab of Materials Physics, Anhui Key Lab of Nanomaterials and Nanotechnology,
Institute of Solid State Physics, HFIPS,
Chinese Academy of Sciences, Hefei 230031, P. R. China
| | - Tingting Xiao
- Key
Lab of Materials Physics, Anhui Key Lab of Nanomaterials and Nanotechnology,
Institute of Solid State Physics, HFIPS,
Chinese Academy of Sciences, Hefei 230031, P. R. China
| | - Shuyi Zhu
- Key
Lab of Materials Physics, Anhui Key Lab of Nanomaterials and Nanotechnology,
Institute of Solid State Physics, HFIPS,
Chinese Academy of Sciences, Hefei 230031, P. R. China
- University
of Science and Technology of China, Hefei 230026, P. R. China
| | - Yu Ouyang
- Department
of Clinical Laboratory, The Affiliated Taizhou
Second People’s Hospital of Yangzhou University, Taizhou 225300, P. R. China
| | - Hongwen Zhang
- Key
Lab of Materials Physics, Anhui Key Lab of Nanomaterials and Nanotechnology,
Institute of Solid State Physics, HFIPS,
Chinese Academy of Sciences, Hefei 230031, P. R. China
- Lu’an
Branch, Anhui Institute of Innovation for
Industrial Technology, Lu’an 237100, P. R. China
| | - Weiping Cai
- Key
Lab of Materials Physics, Anhui Key Lab of Nanomaterials and Nanotechnology,
Institute of Solid State Physics, HFIPS,
Chinese Academy of Sciences, Hefei 230031, P. R. China
- University
of Science and Technology of China, Hefei 230026, P. R. China
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5
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Aubrechtová Dragounová K, Ryabchykov O, Steinbach D, Recla V, Lindig N, González Vázquez MJ, Foller S, Bauer M, Bocklitz TW, Popp J, Rödel J, Neugebauer U. Identification of bacteria in mixed infection from urinary tract of patient's samples using Raman analysis of dried droplets. Analyst 2023; 148:3806-3816. [PMID: 37463011 DOI: 10.1039/d3an00679d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Urinary tract infections (UTI) are among the most frequent nosocomial infections. A fast identification of the pathogen and assignment of Gram type could help to prescribe most suitable treatments. Raman spectroscopy holds high potential for fast and reliable bacterial pathogens identification. While most studies so far have focused on individual pathogens or artificial mixtures, this contribution aims to translate the analysis to primary urine samples from patients with suspected UTIs. For this, we have included 59 primary urine samples out of which 29 were diagnosed as mixed infections. For Raman analysis, we first trained two classification models based on principal component analysis - linear discriminant analysis (PCA-LDA) with more than 3500 Raman spectra of 85 clinical isolates from 23 species in order to (1) identify the Gram type of the bacteria and (2) assign family membership to one of the six most abundant bacterial families in urinary tract infections (Enterobacteriaceae, Morganellaceae, Pseudomonadaceae, Enterococcaceae, Staphylococcaceae and Streptococcaceae). The classification models were applied to artificial mixtures of Gram positive and Gram negative bacteria to correctly predict mixed infections with an accuracy of 75%. Raman scans of dried droplets did not yet yield optimal classification results on family level. When translating the method to primary urine samples, we observed a strong bias towards Gram negative bacteria, on family level towards Morganellaceae, which reduced prediction accuracy. Spectral differences were observed between isolates grown on standard growth medium and bacteria of the same strain when characterized directly from the patient. Thus, improvement of the classification accuracy is expected with a larger data base containing also bacteria measured directly from the urine sample.
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Affiliation(s)
- Kateřina Aubrechtová Dragounová
- Department of Anaesthesiology and Intensive Care Medicine and Center for Sepsis Control and Care (CSCC), Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany.
- Leibniz Institute of Photonic Technology (Leibniz-IPHT), a member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Straße 9, 07745 Jena, Germany
| | - Oleg Ryabchykov
- Leibniz Institute of Photonic Technology (Leibniz-IPHT), a member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Straße 9, 07745 Jena, Germany
- Biophotonics Diagnostics GmbH, Am Wiesenbach 30, 07751 Jena, Germany
| | - Daniel Steinbach
- Department of Urology, Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
| | - Vincent Recla
- Institute of Medical Microbiology, Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
| | - Nora Lindig
- Institute of Medical Microbiology, Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
| | - María José González Vázquez
- Department of Anaesthesiology and Intensive Care Medicine and Center for Sepsis Control and Care (CSCC), Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany.
- Leibniz Institute of Photonic Technology (Leibniz-IPHT), a member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Straße 9, 07745 Jena, Germany
| | - Susan Foller
- Department of Urology, Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
| | - Michael Bauer
- Department of Anaesthesiology and Intensive Care Medicine and Center for Sepsis Control and Care (CSCC), Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany.
| | - Thomas W Bocklitz
- Leibniz Institute of Photonic Technology (Leibniz-IPHT), a member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe School of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Institute of Computer Science, Faculty of Mathematics, Physics & Computer Science, University Bayreuth, Universitätsstraße 30, 95447 Bayreuth, Germany
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology (Leibniz-IPHT), a member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe School of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
| | - Jürgen Rödel
- Institute of Medical Microbiology, Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
| | - Ute Neugebauer
- Department of Anaesthesiology and Intensive Care Medicine and Center for Sepsis Control and Care (CSCC), Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany.
- Leibniz Institute of Photonic Technology (Leibniz-IPHT), a member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe School of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
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6
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Kastner S, Dietel AK, Seier F, Ghosh S, Weiß D, Makarewicz O, Csáki A, Fritzsche W. LSPR-Based Biosensing Enables the Detection of Antimicrobial Resistance Genes. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2023; 19:e2207953. [PMID: 37093195 DOI: 10.1002/smll.202207953] [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: 12/19/2022] [Revised: 03/30/2023] [Indexed: 05/03/2023]
Abstract
The development of rapid, simple, and accurate bioassays for the detection of nucleic acids has received increasing demand in recent years. Here, localized surface plasmon resonance (LSPR) spectroscopy for the detection of an antimicrobial resistance gene, sulfhydryl variable β-lactamase (blaSHV), which confers resistance against a broad spectrum of β-lactam antibiotics is used. By performing limit of detection experiments, a 23 nucleotide (nt) long deoxyribonucleic acid (DNA) sequence down to 25 nm was detected, whereby the signal intensity is inversely correlated with sequence length (23, 43, 63, and 100 nt). In addition to endpoint measurements of hybridization events, the setup also allowed to monitor the hybridization events in real-time, and consequently enabled to extract kinetic parameters of the studied binding reaction. Performing LSPR measurements using single nucleotide polymorphism (SNP) variants of blaSHV revealed that these sequences can be distinguished from the fully complementary sequence. The possibility to distinguish such sequences is of utmost importance in clinical environments, as it allows to identify mutations essential for enzyme function and thus, is crucial for the correct treatment with antibiotics. Taken together, this system provides a robust, label-free, and cost-efficient analytical tool for the detection of nucleic acids and will enable the surveillance of antimicrobial resistance determinants.
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Affiliation(s)
- Stephan Kastner
- Molecular Plasmonics work group, Department of Nanobiophotonics, Leibniz Institute of Photonic Technology, Albert-Einstein-Strasse 9, 07745, Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Research Alliance Health Technologies and Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Strasse 9, 07745, Jena, Germany
| | - Anne-Kathrin Dietel
- Molecular Plasmonics work group, Department of Nanobiophotonics, Leibniz Institute of Photonic Technology, Albert-Einstein-Strasse 9, 07745, Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Research Alliance Health Technologies and Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Strasse 9, 07745, Jena, Germany
| | - Florian Seier
- Molecular Plasmonics work group, Department of Nanobiophotonics, Leibniz Institute of Photonic Technology, Albert-Einstein-Strasse 9, 07745, Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Research Alliance Health Technologies and Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Strasse 9, 07745, Jena, Germany
| | - Shaunak Ghosh
- Molecular Plasmonics work group, Department of Nanobiophotonics, Leibniz Institute of Photonic Technology, Albert-Einstein-Strasse 9, 07745, Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Research Alliance Health Technologies and Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Strasse 9, 07745, Jena, Germany
| | - Daniel Weiß
- Institute for Infectious Diseases and Infection Control, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany
- Leibniz Institute of Photonic Technology e.V., Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Strasse 9, 07745, Jena, Germany
| | - Oliwia Makarewicz
- Institute for Infectious Diseases and Infection Control, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany
- Leibniz Institute of Photonic Technology e.V., Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Strasse 9, 07745, Jena, Germany
| | - Andrea Csáki
- Molecular Plasmonics work group, Department of Nanobiophotonics, Leibniz Institute of Photonic Technology, Albert-Einstein-Strasse 9, 07745, Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Research Alliance Health Technologies and Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Strasse 9, 07745, Jena, Germany
| | - Wolfgang Fritzsche
- Molecular Plasmonics work group, Department of Nanobiophotonics, Leibniz Institute of Photonic Technology, Albert-Einstein-Strasse 9, 07745, Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Research Alliance Health Technologies and Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Strasse 9, 07745, Jena, Germany
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7
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Rebrosova K, Bernatová S, Šiler M, Mašek J, Samek O, Ježek J, Kizovsky M, Holá V, Zemanek P, Růžička F. Rapid Identification of Pathogens Causing Bloodstream Infections by Raman Spectroscopy and Raman Tweezers. Microbiol Spectr 2023; 11:e0002823. [PMID: 37078868 PMCID: PMC10269886 DOI: 10.1128/spectrum.00028-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 03/24/2023] [Indexed: 04/21/2023] Open
Abstract
The search for the "Holy Grail" in clinical diagnostic microbiology-a reliable, accurate, low-cost, real-time, easy-to-use method-has brought up several methods with the potential to meet these criteria. One is Raman spectroscopy, an optical, nondestructive method based on the inelastic scattering of monochromatic light. The current study focuses on the possible use of Raman spectroscopy for identifying microbes causing severe, often life-threatening bloodstream infections. We included 305 microbial strains of 28 species acting as causative agents of bloodstream infections. Raman spectroscopy identified the strains from grown colonies, with 2.8% and 7% incorrectly identified strains using the support vector machine algorithm based on centered and uncentred principal-component analyses, respectively. We combined Raman spectroscopy with optical tweezers to speed up the process and captured and analyzed microbes directly from spiked human serum. The pilot study suggests that it is possible to capture individual microbial cells from human serum and characterize them by Raman spectroscopy with notable differences among different species. IMPORTANCE Bloodstream infections are among the most common causes of hospitalizations and are often life-threatening. To establish an effective therapy for a patient, the timely identification of the causative agent and characterization of its antimicrobial susceptibility and resistance profiles are essential. Therefore, our multidisciplinary team of microbiologists and physicists presents a method that reliably, rapidly, and inexpensively identifies pathogens causing bloodstream infections-Raman spectroscopy. We believe that it might become a valuable diagnostic tool in the future. Combined with optical trapping, it offers a new approach where the microorganisms are individually trapped in a noncontact way by optical tweezers and investigated by Raman spectroscopy directly in a liquid sample. Together with the automatic processing of measured Raman spectra and comparison with a database of microorganisms, it makes the whole identification process almost real time.
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Affiliation(s)
- Katarina Rebrosova
- Department of Microbiology, Faculty of Medicine of Masaryk University, St. Anne’s University Hospital, Brno, Czech Republic
| | - Silvie Bernatová
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Martin Šiler
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Jan Mašek
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Brno, Czech Republic
- Department of Plant Developmental Genetics, Institute of Biophysics, Academy of Sciences of the Czech Republic, Brno, Czech Republic
| | - Ota Samek
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Jan Ježek
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Martin Kizovsky
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Veronika Holá
- Department of Microbiology, Faculty of Medicine of Masaryk University, St. Anne’s University Hospital, Brno, Czech Republic
| | - Pavel Zemanek
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Filip Růžička
- Department of Microbiology, Faculty of Medicine of Masaryk University, St. Anne’s University Hospital, Brno, Czech Republic
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8
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Cao L, Zheng X, Han P, Ren L, Hu F, Li Z. Raman spectroscopy as a promising diagnostic method for rheumatoid arthritis. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:709-718. [PMID: 36598183 DOI: 10.1039/d2ay01904c] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Background: Diagnosis of rheumatoid arthritis (RA) basically relies on clinical symptoms and autoantibodies, especially anti-citrullinated protein antibodies (ACPAs) and rheumatoid factor (RF). However, the lack of autoantibodies is still a dilemma clinically in seronegative RA, especially in the early stage of the disease. This study aimed to provide a unique disease fingerprint with high diagnostic value to discriminate RA based on Raman spectroscopy. Methods: Raman spectroscopy provides a repertoire of biomolecules in serum from RA. Multivariate dimension-reducing methods and machine-learning algorithms were exploited to reveal the intrinsic differences and the potential discrimination power. The underlying differential biomolecules were retrieved by the assignment of Raman peaks. Moreover, the correlations between the spectral differences and RA patient's clinical and immunological manifestations were also analyzed. Results: RA patients exhibited unique Raman spectra characterized by biomolecular alterations during the disease progression. The discrimination power yielded 97.3% sensitivity and 94.8% specificity for RA diagnosis. In the recognition of ACPA-negative RA, the sensitivity and specificity also reached 95.6% and 92.8%, respectively. In particular, the differential Raman spectrum peaks of RA patients mainly represented lipids, amino acids, glycogen, and fatty acids. Further analysis showed that the different serum Raman spectra correlated with the clinical features of RA, including disease duration, RF, anticyclic citrullinated peptide antibodies (anti-CCPs), IgA, IgM, IgG, tender joint count, and swollen joint count (|rs| = 0.15-0.52, p < 0.05). Conclusions: Raman spectroscopy was revealed to be a promising diagnostic method for RA, especially for ACPA-negative patients.
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Affiliation(s)
- Lulu Cao
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
| | - Xi Zheng
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Peng Han
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
| | - Limin Ren
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
| | - Fanlei Hu
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China
- Department of Integration of Chinese and Western Medicine, School of Basic Medical Sciences, Peking University, Beijing, China
| | - Zhanguo Li
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China
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9
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Grigorev GV, Lebedev AV, Wang X, Qian X, Maksimov GV, Lin L. Advances in Microfluidics for Single Red Blood Cell Analysis. BIOSENSORS 2023; 13:117. [PMID: 36671952 PMCID: PMC9856164 DOI: 10.3390/bios13010117] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/04/2022] [Accepted: 12/23/2022] [Indexed: 05/24/2023]
Abstract
The utilizations of microfluidic chips for single RBC (red blood cell) studies have attracted great interests in recent years to filter, trap, analyze, and release single erythrocytes for various applications. Researchers in this field have highlighted the vast potential in developing micro devices for industrial and academia usages, including lab-on-a-chip and organ-on-a-chip systems. This article critically reviews the current state-of-the-art and recent advances of microfluidics for single RBC analyses, including integrated sensors and microfluidic platforms for microscopic/tomographic/spectroscopic single RBC analyses, trapping arrays (including bifurcating channels), dielectrophoretic and agglutination/aggregation studies, as well as clinical implications covering cancer, sepsis, prenatal, and Sickle Cell diseases. Microfluidics based RBC microarrays, sorting/counting and trapping techniques (including acoustic, dielectrophoretic, hydrodynamic, magnetic, and optical techniques) are also reviewed. Lastly, organs on chips, multi-organ chips, and drug discovery involving single RBC are described. The limitations and drawbacks of each technology are addressed and future prospects are discussed.
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Affiliation(s)
- Georgii V. Grigorev
- Data Science and Information Technology Research Center, Tsinghua Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518055, China
- Mechanical Engineering Department, University of California in Berkeley, Berkeley, CA 94720, USA
- School of Information Technology, Cherepovets State University, 162600 Cherepovets, Russia
| | - Alexander V. Lebedev
- Machine Building Department, Bauman Moscow State University, 105005 Moscow, Russia
| | - Xiaohao Wang
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Xiang Qian
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - George V. Maksimov
- Faculty of Biology, Lomonosov Moscow State University, 119991 Moscow, Russia
- Physical metallurgy Department, Federal State Autonomous Educational Institution of Higher Education National Research Technological University “MISiS”, 119049 Moscow, Russia
| | - Liwei Lin
- Mechanical Engineering Department, University of California in Berkeley, Berkeley, CA 94720, USA
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10
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Lu W, Li H, Qiu H, Wang L, Feng J, Fu YV. Identification of pathogens and detection of antibiotic susceptibility at single-cell resolution by Raman spectroscopy combined with machine learning. Front Microbiol 2023; 13:1076965. [PMID: 36687641 PMCID: PMC9846160 DOI: 10.3389/fmicb.2022.1076965] [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: 10/22/2022] [Accepted: 12/06/2022] [Indexed: 01/05/2023] Open
Abstract
Rapid, accurate, and label-free detection of pathogenic bacteria and antibiotic resistance at single-cell resolution is a technological challenge for clinical diagnosis. Overcoming the cumbersome culture process of pathogenic bacteria and time-consuming antibiotic susceptibility assays will significantly benefit early diagnosis and optimize the use of antibiotics in clinics. Raman spectroscopy can collect molecular fingerprints of pathogenic bacteria in a label-free and culture-independent manner, which is suitable for pathogen diagnosis at single-cell resolution. Here, we report a method based on Raman spectroscopy combined with machine learning to rapidly and accurately identify pathogenic bacteria and detect antibiotic resistance at single-cell resolution. Our results show that the average accuracy of identification of 12 species of common pathogenic bacteria by the machine learning method is 90.73 ± 9.72%. Antibiotic-sensitive and antibiotic-resistant strains of Acinetobacter baumannii isolated from hospital patients were distinguished with 99.92 ± 0.06% accuracy using the machine learning model. Meanwhile, we found that sensitive strains had a higher nucleic acid/protein ratio and antibiotic-resistant strains possessed abundant amide II structures in proteins. This study suggests that Raman spectroscopy is a promising method for rapidly identifying pathogens and detecting their antibiotic susceptibility.
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Affiliation(s)
- Weilai Lu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Haifei Li
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
| | - Haoning Qiu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Lu Wang
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jie Feng
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
| | - Yu Vincent Fu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China,Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China,*Correspondence: Yu Vincent Fu,
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11
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Daniel F, Kesterson D, Lei K, Hord C, Patel A, Kaffenes A, Congivaram H, Prakash S. Application of Microfluidics for Bacterial Identification. Pharmaceuticals (Basel) 2022; 15:ph15121531. [PMID: 36558982 PMCID: PMC9781190 DOI: 10.3390/ph15121531] [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: 10/23/2022] [Revised: 11/29/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022] Open
Abstract
Bacterial infections continue to pose serious public health challenges. Though anti-bacterial therapeutics are effective remedies for treating these infections, the emergence of antibiotic resistance has imposed new challenges to treatment. Often, there is a delay in prescribing antibiotics at initial symptom presentation as it can be challenging to clinically differentiate bacterial infections from other organisms (e.g., viruses) causing infection. Moreover, bacterial infections can arise from food, water, or other sources. These challenges have demonstrated the need for rapid identification of bacteria in liquids, food, clinical spaces, and other environments. Conventional methods of bacterial identification rely on culture-based approaches which require long processing times and higher pathogen concentration thresholds. In the past few years, microfluidic devices paired with various bacterial identification methods have garnered attention for addressing the limitations of conventional methods and demonstrating feasibility for rapid bacterial identification with lower biomass thresholds. However, such culture-free methods often require integration of multiple steps from sample preparation to measurement. Research interest in using microfluidic methods for bacterial identification is growing; therefore, this review article is a summary of current advancements in this field with a focus on comparing the efficacy of polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), and emerging spectroscopic methods.
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Affiliation(s)
- Fraser Daniel
- Department of Mechanical and Aerospace Engineering, College of Engineering, The Ohio State University, Columbus, OH 43210, USA
| | - Delaney Kesterson
- Center for Life Sciences Education, The Ohio State University, Columbus, OH 43210, USA
| | - Kevin Lei
- Department of Chemical and Biomolecular Engineering, College of Engineering, The Ohio State University, Columbus, OH 43210, USA
| | - Catherine Hord
- Center for Life Sciences Education, The Ohio State University, Columbus, OH 43210, USA
| | - Aarti Patel
- Department of Biomedical Engineering, College of Engineering, The Ohio State University, Columbus, OH 43210, USA
| | - Anastasia Kaffenes
- Department of Neuroscience, College of Arts and Sciences and College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Harrshavasan Congivaram
- School of Health and Rehabilitation Sciences, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Shaurya Prakash
- Department of Mechanical and Aerospace Engineering, College of Engineering, The Ohio State University, Columbus, OH 43210, USA
- Correspondence:
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12
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Constantinou M, Hadjigeorgiou K, Abalde-Cela S, Andreou C. Label-Free Sensing with Metal Nanostructure-Based Surface-Enhanced Raman Spectroscopy for Cancer Diagnosis. ACS APPLIED NANO MATERIALS 2022; 5:12276-12299. [PMID: 36210923 PMCID: PMC9534173 DOI: 10.1021/acsanm.2c02392] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 07/27/2022] [Indexed: 05/03/2023]
Abstract
Surface-Enhanced Raman Spectroscopy (SERS) is a powerful analytical technique for the detection of small analytes with great potential for medical diagnostic applications. Its high sensitivity and excellent molecular specificity, which stems from the unique fingerprint of molecular species, have been applied toward the detection of different types of cancer. The noninvasive and rapid detection offered by SERS highlights its applicability for point-of-care (PoC) deployment for cancer diagnosis, screening, and staging, as well as for predicting tumor recurrence and treatment monitoring. This review provides an overview of the progress in label-free (direct) SERS-based chemical detection for cancer diagnosis with the main focus on the advances in the design and preparation of SERS substrates on the basis of metal nanoparticle structures formed via bottom-up strategies. It begins by introducing a synopsis of the working principles of SERS, including key chemometric approaches for spectroscopic data analysis. Then it introduces the advances of label-free sensing with SERS in cancer diagnosis using biofluids (blood, urine, saliva, sweat) and breath as the detection media. In the end, an outlook of the advances and challenges in cancer diagnosis via SERS is provided.
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Affiliation(s)
- Marios Constantinou
- Department
of Electrical and Computer Engineering, University of Cyprus, Nicosia, 2112, Cyprus
| | - Katerina Hadjigeorgiou
- Department
of Electrical and Computer Engineering, University of Cyprus, Nicosia, 2112, Cyprus
| | - Sara Abalde-Cela
- International
Iberian Nanotechnology Laboratory, Avenida Mestre José Veiga s/n, Braga 4715-330, Portugal
| | - Chrysafis Andreou
- Department
of Electrical and Computer Engineering, University of Cyprus, Nicosia, 2112, Cyprus
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13
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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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14
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Rebrosova K, Samek O, Kizovsky M, Bernatova S, Hola V, Ruzicka F. Raman Spectroscopy-A Novel Method for Identification and Characterization of Microbes on a Single-Cell Level in Clinical Settings. Front Cell Infect Microbiol 2022; 12:866463. [PMID: 35531343 PMCID: PMC9072635 DOI: 10.3389/fcimb.2022.866463] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 03/07/2022] [Indexed: 12/02/2022] Open
Abstract
Rapid and accurate identification of pathogens causing infections is one of the biggest challenges in medicine. Timely identification of causative agents and their antimicrobial resistance profile can significantly improve the management of infection, lower costs for healthcare, mitigate ever-growing antimicrobial resistance and in many cases, save lives. Raman spectroscopy was shown to be a useful-quick, non-invasive, and non-destructive -tool for identifying microbes from solid and liquid media. Modifications of Raman spectroscopy and/or pretreatment of samples allow single-cell analyses and identification of microbes from various samples. It was shown that those non-culture-based approaches could also detect antimicrobial resistance. Moreover, recent studies suggest that a combination of Raman spectroscopy with optical tweezers has the potential to identify microbes directly from human body fluids. This review aims to summarize recent advances in non-culture-based approaches of identification of microbes and their virulence factors, including antimicrobial resistance, using methods based on Raman spectroscopy in the context of possible use in the future point-of-care diagnostic process.
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Affiliation(s)
- Katarina Rebrosova
- Department of Microbiology, Faculty of Medicine of Masaryk University and St. Anne’s University Hospital, Brno, Czechia
| | - Ota Samek
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czechia
| | - Martin Kizovsky
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czechia
| | - Silvie Bernatova
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czechia
| | - Veronika Hola
- Department of Microbiology, Faculty of Medicine of Masaryk University and St. Anne’s University Hospital, Brno, Czechia
| | - Filip Ruzicka
- Department of Microbiology, Faculty of Medicine of Masaryk University and St. Anne’s University Hospital, Brno, Czechia
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15
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Ling J, Zheng L, Xu M, Chen G, Wang X, Mao D, Shao H. Extreme Point Sort Transformation Combined With a Long Short-Term Memory Network Algorithm for the Raman-Based Identification of Therapeutic Monoclonal Antibodies. Front Chem 2022; 10:887960. [PMID: 35494658 PMCID: PMC9043956 DOI: 10.3389/fchem.2022.887960] [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: 03/02/2022] [Accepted: 03/23/2022] [Indexed: 11/13/2022] Open
Abstract
Therapeutic monoclonal antibodies (mAbs) are a new generation of protein-based medicines that are usually expensive and thus represent a target for counterfeiters. In the present study, a method based on Raman spectroscopy that combined extreme point sort transformation with a long short-term memory (LSTM) network algorithm was presented for the identification of therapeutic mAbs. A total of 15 therapeutic mAbs were used in this study. An in-house Raman spectrum dataset for model training was created with 1,350 spectra. The characteristic region of the Raman spectrum was reduced in dimension and then transformed through an extreme point sort transformation into a sequence array, which was fitted for the LSTM network. The characteristic array was extracted from the sequence array using a well-trained LSTM network and then compared with standard spectra for identification. To demonstrate whether the present algorithm was better, ThermoFisher OMNIC 8.3 software (Thermo Fisher Scientific Inc., U.S.) with two matching modes was selected for comparison. Finally, the present method was successfully applied to identify 30 samples, including 15 therapeutic mAbs and 15 other injections. The characteristic region was selected from 100 to 1800 cm−1 of the full spectrum. The optimized dimensional values were set from 35 to 53, and the threshold value range was from 0.97 to 0.99 for 15 therapeutic mAbs. The results of the robustness test indicated that the present method had good robustness against spectral peak drift, random noise and fluorescence interference from the measurement. The areas under the curve (AUC) values of the present method that were analysed on the full spectrum and analysed on the characteristic region by the OMNIC 8.3 software’s built-in method were 1.000, 0.678, and 0.613, respectively. The similarity scores for 15 therapeutic mAbs using OMNIC 8.3 software in all groups compared with that of the relative present algorithm group had extremely remarkable differences (p < 0.001). The results suggested that the extreme point sort transformation combined with the LSTM network algorithm enabled the characteristic extraction of the therapeutic mAb Raman spectrum. The present method is a proposed solution to rapidly identify therapeutic mAbs.
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Affiliation(s)
- Jin Ling
- NMPA Key Laboratory for Quality Control of Therapeutic Monoclonal Antibodies, Shanghai Institute for Food and Drug Control, Shanghai, China
| | - Luxia Zheng
- NMPA Key Laboratory for Quality Control of Therapeutic Monoclonal Antibodies, Shanghai Institute for Food and Drug Control, Shanghai, China
| | - Mingming Xu
- NMPA Key Laboratory for Quality Control of Therapeutic Monoclonal Antibodies, Shanghai Institute for Food and Drug Control, Shanghai, China
| | - Gang Chen
- NMPA Key Laboratory for Quality Control of Therapeutic Monoclonal Antibodies, Shanghai Institute for Food and Drug Control, Shanghai, China
| | - Xiao Wang
- NMPA Key Laboratory for Quality Analysis of Chemical Drug Preparations, Shanghai Institute for Food and Drug Control, Shanghai, China
| | - Danzhuo Mao
- NMPA Key Laboratory for Quality Analysis of Chemical Drug Preparations, Shanghai Institute for Food and Drug Control, Shanghai, China
| | - Hong Shao
- NMPA Key Laboratory for Quality Control of Therapeutic Monoclonal Antibodies, Shanghai Institute for Food and Drug Control, Shanghai, China
- *Correspondence: Hong Shao,
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16
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Rebrošová K, Bernatová S, Šiler M, Uhlirova M, Samek O, Ježek J, Holá V, Růžička F, Zemanek P. Raman spectroscopy-a tool for rapid differentiation among microbes causing urinary tract infections. Anal Chim Acta 2022; 1191:339292. [PMID: 35033248 DOI: 10.1016/j.aca.2021.339292] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 10/20/2021] [Accepted: 11/15/2021] [Indexed: 12/16/2022]
Abstract
Urinary tract infections belong to the most common infections in the world. Besides community-acquired infections, nosocomial infections pose a high risk especially for patients having indwelling catheters, undergoing urological surgeries or staying at hospital for prolonged time. They can be often complicated by antimicrobial resistance and/or biofilm formation. Therefore, a rapid diagnostic tool enabling timely identification of a causative agent and its susceptibility to antimicrobials is a need. Raman spectroscopy appears to be a suitable method that allows rapid differentiation among microbes and provides a space for further analyses, such as determination of capability of biofilm formation or antimicrobial susceptibility/resistance in tested strains. Our work here presents a possibility to differ among most common microbes causing urinary tract infections (belonging to 20 species). We tested 254 strains directly from colonies grown on Mueller-Hinton agar plates. The results show that it is possible to distinguish among the tested species using Raman spectroscopy, which proves its great potential for future use in clinical diagnostics. Moreover, we present here a pilot study of a real-time analysis and identification (in less than 10 min) of single microbial cells directly in urine employing optical tweezers combined with Raman spectroscopy.
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Affiliation(s)
- Katarína Rebrošová
- Department of Microbiology, Faculty of Medicine of Masaryk University and St. Anne's, University Hospital, Pekařská 53, Brno, 65691, Czech Republic.
| | - Silvie Bernatová
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno, 61264, Czech Republic.
| | - Martin Šiler
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno, 61264, Czech Republic.
| | - Magdalena Uhlirova
- Department of Infectious Diseases and Microbiology, Faculty of Veterinary Medicine, University of Veterinary and Pharmaceutical Sciences Brno, Brno, Czech Republic, Palackého tř. 1946/1, 612 42, Brno, Czech Republic.
| | - Ota Samek
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno, 61264, Czech Republic.
| | - Jan Ježek
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno, 61264, Czech Republic.
| | - Veronika Holá
- Department of Microbiology, Faculty of Medicine of Masaryk University and St. Anne's, University Hospital, Pekařská 53, Brno, 65691, Czech Republic
| | - Filip Růžička
- Department of Microbiology, Faculty of Medicine of Masaryk University and St. Anne's, University Hospital, Pekařská 53, Brno, 65691, Czech Republic
| | - Pavel Zemanek
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno, 61264, Czech Republic.
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17
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Drug identification by electroanalysis with multiple classification approaches. CHINESE JOURNAL OF ANALYTICAL CHEMISTRY 2021. [DOI: 10.1016/j.cjac.2021.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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18
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Li M, He H, Huang G, Lin B, Tian H, Xia K, Yuan C, Zhan X, Zhang Y, Fu W. A Novel and Rapid Serum Detection Technology for Non-Invasive Screening of Gastric Cancer Based on Raman Spectroscopy Combined With Different Machine Learning Methods. Front Oncol 2021; 11:665176. [PMID: 34646758 PMCID: PMC8504718 DOI: 10.3389/fonc.2021.665176] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 09/06/2021] [Indexed: 12/04/2022] Open
Abstract
Gastric cancer (GC) is the fifth most common cancer in the world and a serious threat to human health. Due to its high morbidity and mortality, a simple, rapid and accurate early screening method for GC is urgently needed. In this study, the potential of Raman spectroscopy combined with different machine learning methods was explored to distinguish serum samples from GC patients and healthy controls. Serum Raman spectra were collected from 109 patients with GC (including 35 in stage I, 14 in stage II, 35 in stage III, and 25 in stage IV) and 104 healthy volunteers matched for age, presenting for a routine physical examination. We analyzed the difference in serum metabolism between GC patients and healthy people through a comparative study of the average Raman spectra of the two groups. Four machine learning methods, one-dimensional convolutional neural network, random forest, support vector machine, and K-nearest neighbor were used to explore identifying two sets of Raman spectral data. The classification model was established by using 70% of the data as a training set and 30% as a test set. Using unseen data to test the model, the RF model yielded an accuracy of 92.8%, and the sensitivity and specificity were 94.7% and 90.8%. The performance of the RF model was further confirmed by the receiver operating characteristic (ROC) curve, with an area under the curve (AUC) of 0.9199. This exploratory work shows that serum Raman spectroscopy combined with RF has great potential in the machine-assisted classification of GC, and is expected to provide a non-destructive and convenient technology for the screening of GC patients.
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Affiliation(s)
- Mengya Li
- Department of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Haiyan He
- Department of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Guorong Huang
- Department of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Bo Lin
- Department of Laboratory Medicine, Chongqing University Cancer Hospital, Chongqing, China
| | - Huiyan Tian
- Department of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Ke Xia
- Department of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Changjing Yuan
- Department of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Xinyu Zhan
- Department of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Yang Zhang
- Department of Laboratory Medicine, Chongqing University Cancer Hospital, Chongqing, China
| | - Weiling Fu
- Department of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China
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19
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Trends in the bacterial recognition patterns used in surface enhanced Raman spectroscopy. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116310] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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20
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Rousseau AN, Faure N, Rol F, Sedaghat Z, Le Galudec J, Mallard F, Josso Q. Fast Antibiotic Susceptibility Testing via Raman Microspectrometry on Single Bacteria: An MRSA Case Study. ACS OMEGA 2021; 6:16273-16279. [PMID: 34235297 PMCID: PMC8246468 DOI: 10.1021/acsomega.1c00170] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 04/05/2021] [Indexed: 05/14/2023]
Abstract
Despite recent advances in molecular diagnostics, ultrafast determination of the antibiotic susceptibility phenotype of pathogenic microorganisms is still a major challenge of in vitro diagnostics (IVD) of infectious diseases. Raman microspectroscopy has been proposed as a means to achieve this goal. Previous studies have shown that susceptibility phenotyping could be done through Raman analysis of microbial cells, either in large clusters or down to the single-cell level in the case of Gram-negative rods. Gram-positive cocci such as Staphylococcus aureus pose several challenges due to their size and their different metabolic and chemical characteristics. Using a tailored automated single-cell Raman spectrometer and a previously proposed sample preparation protocol, we acquired and analyzed 9429 S. aureus single cells belonging to three cefoxitin-resistant strains and two susceptible strains during their incubation in the presence of various concentrations of cefoxitin. We observed an effect on S. aureus spectra that is weaker than what was detected on previous bacteria/drug combinations, with a higher cell-to-cell response variability and an important impact of incubation conditions on the phenotypic resistance of a given strain. Overall, the proposed protocol was able to correlate strains' phenotype with a specific modification of the spectra using majority votes. We, hence, confirm that our previous results on single-cell Raman antibiotic susceptibility testing can be extended to the S. aureus case and further clarify potential limitations and development requirements of this approach in the move toward industrial applications.
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Affiliation(s)
| | - Nicolas Faure
- bioMérieux,
R&D Microbiology, 5 rue des Berges, 38024 Grenoble, France
| | - Fabian Rol
- Bioaster, 40 avenue Tony Garnier, 69007 Lyon, France
| | | | - Joël Le Galudec
- bioMérieux,
R&D Microbiology, 5 rue des Berges, 38024 Grenoble, France
| | - Frédéric Mallard
- bioMérieux,
R&D Microbiology, 5 rue des Berges, 38024 Grenoble, France
| | - Quentin Josso
- bioMérieux,
R&D Microbiology, 376 Chemin de l’Orme, 69280 Marcy-l’Etoile, France
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21
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Establishment of a reliable scheme for obtaining highly stable SERS signal of biological serum. Biosens Bioelectron 2021; 189:113315. [PMID: 34049082 DOI: 10.1016/j.bios.2021.113315] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 03/27/2021] [Accepted: 05/05/2021] [Indexed: 12/20/2022]
Abstract
As a rapid and non-destructive biological serum detection method, SERS technology was widely used in the screening and medical diagnosis of various diseases by combining the analysis of serum SERS spectrum and multivariate statistical algorithm. Because of the high complexity of serum components and the variability of SERS spectra, which often resulted in the phenomenon that the SERS spectrum of the same biological serum was significantly different due to the different test conditions. In this experiment, through the dilution treatment of the serum and the systematic test of the serum of all concentration gradients with lasers of wavelength of 785, 633 and 532 nm, the most suitable conditions for detecting the serum were investigated. The experimental results showed that only when the serum is diluted to low concentration (10 ppm), the SERS spectrum with high reproducibility and stability could be obtained, furthermore, the low concentration serum had weak tolerance to laser, and 532 nm laser was not suitable for serum detection. In this paper, a set of test scheme for obtaining highly stable serum SERS spectra was established by using high-performance gold nanoparticles (Au NPs) as the active substrate of SERS. Through comparative analysis of SERS spectrum of serum of normal people and cervical cancer, the reliability of the established low-concentration serum test program was verified, as well as its great potential advantages in disease screening and diagnosis.
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22
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Rammal H, Al Assaad A, Dosio F, Stella B, Maksimenko A, Mura S, Van Gulick L, Callewaert M, Desmaële D, Couvreur P, Morjani H, Beljebbar A. Investigation of squalene-doxorubicin distribution and interactions within single cancer cell using Raman microspectroscopy. NANOMEDICINE-NANOTECHNOLOGY BIOLOGY AND MEDICINE 2021; 35:102404. [PMID: 33932593 DOI: 10.1016/j.nano.2021.102404] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 03/10/2021] [Accepted: 04/08/2021] [Indexed: 11/17/2022]
Abstract
Intracellular distribution of doxorubicin (DOX) and its squalenoylated (SQ-DOX) nanoparticles (NPs) form in murine lung carcinoma M109 and human breast carcinoma MDA-MB-231 cells was investigated by Raman microspectroscopy. Pharmacological data showed that DOX induced higher cytotoxic effect than SQ-DOX NPs. Raman data were obtained using single-point measurements and imaging on the whole cell areas. These data showed that after DOX treatment at 1 μM, the spectral features of DOX were not detected in the M109 cell cytoplasm and nucleus. However, the intracellular distribution of SQ-DOX NPs was higher than DOX in the same conditions. In addition, SQ-DOX NPs were localized into both cell cytoplasm and nucleus. After 5 μM treatment, Raman bands of DOX at 1211 and 1241 cm-1 were detected in the nucleus. Moreover, the intensity ratio of these bands decreased, indicating DOX intercalation into DNA. However, after treatment with SQ-DOX NPs, the intensity of these Raman bands increased. Interestingly, with SQ-DOX NPs, the intensity of 1210/1241 cm-1 ratio was higher suggesting a lower fraction of intercalated DOX in DNA and higher amount of non-hydrolyzed SQ-DOX. Raman imaging data confirm this subcellular localization of these drugs in both M109 and MDA-MB-231 cells. These finding brings new insights to the cellular characterization of anticancer drugs at the molecular level, particularly in the field of nanomedicine.
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Affiliation(s)
- Hassan Rammal
- Translational BioSpectrocopy, BioSpecT, EA 7506, Université de Reims, Faculté de Pharmacie, Reims, France.
| | - Almar Al Assaad
- Translational BioSpectrocopy, BioSpecT, EA 7506, Université de Reims, Faculté de Pharmacie, Reims, France.
| | - Franco Dosio
- Department of Drug Science and Technology, University of Torino, Torino, Italy.
| | - Barbara Stella
- Department of Drug Science and Technology, University of Torino, Torino, Italy.
| | - Andrei Maksimenko
- Institut Galien Paris-Saclay CNRS UMR8612, Université Paris-Saclay, Faculté de Pharmacie, Châtenay-Malabry, France..
| | - Simona Mura
- Institut Galien Paris-Saclay CNRS UMR8612, Université Paris-Saclay, Faculté de Pharmacie, Châtenay-Malabry, France..
| | - Laurence Van Gulick
- Translational BioSpectrocopy, BioSpecT, EA 7506, Université de Reims, Faculté de Pharmacie, Reims, France; Institut de Chimie Moléculaire de Reims, ICMR - UMR 7312, Université de Reims, Faculté de Pharmacie, Reims, France.
| | - Maïté Callewaert
- Institut de Chimie Moléculaire de Reims, ICMR - UMR 7312, Université de Reims, Faculté de Pharmacie, Reims, France.
| | - Didier Desmaële
- Institut Galien Paris-Saclay CNRS UMR8612, Université Paris-Saclay, Faculté de Pharmacie, Châtenay-Malabry, France..
| | - Patrick Couvreur
- Institut Galien Paris-Saclay CNRS UMR8612, Université Paris-Saclay, Faculté de Pharmacie, Châtenay-Malabry, France..
| | - Hamid Morjani
- Translational BioSpectrocopy, BioSpecT, EA 7506, Université de Reims, Faculté de Pharmacie, Reims, France.
| | - Abdelilah Beljebbar
- Translational BioSpectrocopy, BioSpecT, EA 7506, Université de Reims, Faculté de Pharmacie, Reims, France.
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23
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Kudo Y, Kino S, Matsuura Y. Vacuum Ultraviolet Absorption Spectroscopy Analysis of Breath Acetone Using a Hollow Optical Fiber Gas Cell. SENSORS 2021; 21:s21020478. [PMID: 33445436 PMCID: PMC7827082 DOI: 10.3390/s21020478] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 01/06/2021] [Accepted: 01/08/2021] [Indexed: 02/02/2023]
Abstract
Human breath is a biomarker of body fat metabolism and can be used to diagnose various diseases, such as diabetes. As such, in this paper, a vacuum ultraviolet (VUV) spectroscopy system is proposed to measure the acetone in exhaled human breath. A strong absorption acetone peak at 195 nm is detected using a simple system consisting of a deuterium lamp source, a hollow-core fiber gas cell, and a fiber-coupled compact spectrometer corresponding to the VUV region. The hollow-core fiber functions both as a long-path and an extremely small-volume gas cell; it enables us to sensitively measure the trace components of exhaled breath. For breath analysis, we apply multiple regression analysis using the absorption spectra of oxygen, water, and acetone standard gas as explanatory variables to quantitate the concentration of acetone in breath. Based on human breath, we apply the standard addition method to obtain the measurement accuracy. The results suggest that the standard deviation is 0.074 ppm for healthy human breath with an acetone concentration of around 0.8 ppm and a precision of 0.026 ppm. We also monitor body fat burn based on breath acetone and confirm that breath acetone increases after exercise because it is a volatile byproduct of lipolysis.
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Elumalai S, Managó S, De Luca AC. Raman Microscopy: Progress in Research on Cancer Cell Sensing. SENSORS (BASEL, SWITZERLAND) 2020; 20:E5525. [PMID: 32992464 PMCID: PMC7582629 DOI: 10.3390/s20195525] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 09/21/2020] [Accepted: 09/24/2020] [Indexed: 02/07/2023]
Abstract
In the last decade, Raman Spectroscopy (RS) was demonstrated to be a label-free, non-invasive and non-destructive optical spectroscopy allowing the improvement in diagnostic accuracy in cancer and analytical assessment for cell sensing. This review discusses how Raman spectra can lead to a deeper molecular understanding of the biochemical changes in cancer cells in comparison to non-cancer cells, analyzing two key examples, leukemia and breast cancer. The reported Raman results provide information on cancer progression and allow the identification, classification, and follow-up after chemotherapy treatments of the cancer cells from the liquid biopsy. The key obstacles for RS applications in cancer cell diagnosis, including quality, objectivity, number of cells and velocity of the analysis, are considered. The use of multivariant analysis, such as principal component analysis (PCA) and linear discriminate analysis (LDA), for an automatic and objective assessment without any specialized knowledge of spectroscopy is presented. Raman imaging for cancer cell mapping is shown and its advantages for routine clinical pathology practice and live cell imaging, compared to single-point spectral analysis, are debated. Additionally, the combination of RS with microfluidic devices and high-throughput screening for improving the velocity and the number of cells analyzed are also discussed. Finally, the combination of the Raman microscopy (RM) with other imaging modalities, for complete visualization and characterization of the cells, is described.
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Affiliation(s)
| | | | - Anna Chiara De Luca
- Institute of Biochemistry and Cell Biology (IBBC), National Research Council of Italy (CNR), Via P. Castellino 111, 80131 Naples, Italy; (S.E.); (S.M.)
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25
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Vardaki MZ, Kourkoumelis N. Tissue Phantoms for Biomedical Applications in Raman Spectroscopy: A Review. Biomed Eng Comput Biol 2020; 11:1179597220948100. [PMID: 32884391 PMCID: PMC7440735 DOI: 10.1177/1179597220948100] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 07/16/2020] [Indexed: 12/26/2022] Open
Abstract
Raman spectroscopy is a group of analytical techniques, currently applied in several research fields, including clinical diagnostics. Tissue-mimicking optical phantoms have been established as an essential intermediate stage for medical applications with their employment from spectroscopic techniques to be constantly growing. This review outlines the types of tissue phantoms currently employed in different biomedical applications of Raman spectroscopy, focusing on their composition and optical properties. It is therefore an attempt to present an informed range of options for potential use to the researchers.
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Affiliation(s)
- Martha Z Vardaki
- Department of Medical Physics, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Nikolaos Kourkoumelis
- Department of Medical Physics, School of Health Sciences, University of Ioannina, Ioannina, Greece
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26
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Biochemical characterization of pathogenic bacterial species using Raman spectroscopy and discrimination model based on selected spectral features. Lasers Med Sci 2020; 36:289-302. [PMID: 32500291 DOI: 10.1007/s10103-020-03028-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 04/22/2020] [Indexed: 01/09/2023]
Abstract
This study aimed to evaluate the differences in the Raman spectra of nine clinical species of bacteria isolated from infections (three Gram-positive and six Gram-negative species), correlating the spectra with the chemical composition of each species and to develop a classification model through discriminant analysis to categorize each bacterial strain using the peaks with the most significant differences. Bacteria were cultured in Mueller Hinton agar and a sample of biomass was harvested and placed in an aluminum sample holder. A total of 475 spectra from 115 different strains were obtained through a dispersive Raman spectrometer (830 nm) with exposure time of 50 s. The intensities of the peaks were evaluated by one-way analysis of variance (ANOVA) and the peaks with significant differences were related to the differences in the biochemical composition of the strains. Discriminant analysis based on quadratic distance applied to the peaks with the most significant differences and partial least squares applied to the whole spectrum showed 89.5% and 90.1% of global accuracy, respectively, for classification of the spectra in all the groups. Raman spectroscopy could be a promising technique to identify spectral differences related to the biochemical content of pathogenic microorganisms and to provide a faster diagnosis of infectious diseases.
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27
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Kumar S, Gopinathan R, Chandra GK, Umapathy S, Saini DK. Rapid detection of bacterial infection and viability assessment with high specificity and sensitivity using Raman microspectroscopy. Anal Bioanal Chem 2020; 412:2505-2516. [PMID: 32072214 DOI: 10.1007/s00216-020-02474-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 01/05/2020] [Accepted: 01/30/2020] [Indexed: 01/15/2023]
Abstract
Infectious diseases caused by bacteria still pose major diagnostic challenges in spite of the availability of various molecular approaches. Irrespective of the type of infection, rapid identification of the causative pathogen with a high degree of sensitivity and specificity is essential for initiating appropriate treatment. While existing methods like PCR possess high sensitivity, they are incapable of identifying the viability status of the pathogen and those which can, like culturing, are inherently slow. To overcome these limitations, we developed a diagnostic platform based on Raman microspectroscopy, capable of detecting biochemical signatures from a single bacterium for identification as well as viability assessment. The study also establishes a decontamination protocol for handling live pathogenic bacteria which does not affect identification and viability testing, showing applicability in the analysis of sputum samples containing pathogenic mycobacterial strains. The minimal sample processing along with multivariate analysis of spectroscopic signatures provides an interface for automatic classification, allowing the prediction of unknown samples by mapping signatures onto available datasets. Also, the novelty of the current work is the demonstration of simultaneous identification and viability assessment at a single bacterial level for pathogenic bacteria. Graphical abstract.
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Affiliation(s)
- Srividya Kumar
- Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore, 560012, India
| | - Renu Gopinathan
- Department of Molecular Reproduction, Development and Genetics, Indian Institute of Science, Bangalore, 560012, India
| | - Goutam Kumar Chandra
- Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore, 560012, India.,Department of Physics, NIT Calicut, Calicut, Kerala, 673601, India
| | - Siva Umapathy
- Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore, 560012, India. .,Department of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore, 560012, India.
| | - Deepak Kumar Saini
- Department of Molecular Reproduction, Development and Genetics, Indian Institute of Science, Bangalore, 560012, India. .,Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, 560012, India. .,Centre for Infectious Diseases Research, Indian Institute of Science, Bangalore, 560012, India.
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28
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Ramanome technology platform for label-free screening and sorting of microbial cell factories at single-cell resolution. Biotechnol Adv 2019; 37:107388. [DOI: 10.1016/j.biotechadv.2019.04.010] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2018] [Revised: 04/08/2019] [Accepted: 04/23/2019] [Indexed: 01/09/2023]
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29
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Rebrošová K, Šiler M, Samek O, Růžička F, Bernatová S, Ježek J, Zemánek P, Holá V. Identification of ability to form biofilm in Candida parapsilosis and Staphylococcus epidermidis by Raman spectroscopy. Future Microbiol 2019; 14:509-517. [PMID: 31025881 DOI: 10.2217/fmb-2018-0297] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Aim: Finding rapid, reliable diagnostic methods is a big challenge in clinical microbiology. Raman spectroscopy is an optical method used for multiple applications in scientific fields including microbiology. This work reports its potential in identifying biofilm positive strains of Candida parapsilosis and Staphylococcus epidermidis. Materials & methods: We tested 54 S. epidermidis strains (23 biofilm positive, 31 negative) and 51 C. parapsilosis strains (27 biofilm positive, 24 negative) from colonies on Mueller-Hinton agar plates, using Raman spectroscopy. Results: The accuracy was 98.9% for C. parapsilosis and 96.1% for S. epidermidis. Conclusion: The method showed great potential for identifying biofilm positive bacterial and yeast strains. We suggest that Raman spectroscopy might become a useful aid in clinical diagnostics.
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Affiliation(s)
- Katarína Rebrošová
- Department of Microbiology, Faculty of Medicine, Masaryk University & St. Anne's Faculty Hospital, Pekařská 53, Brno 65691, Czech Republic
| | - Martin Šiler
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno 61264, Czech Republic
| | - Ota Samek
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno 61264, Czech Republic
| | - Filip Růžička
- Department of Microbiology, Faculty of Medicine, Masaryk University & St. Anne's Faculty Hospital, Pekařská 53, Brno 65691, Czech Republic
| | - Silvie Bernatová
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno 61264, Czech Republic
| | - Jan Ježek
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno 61264, Czech Republic
| | - Pavel Zemánek
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno 61264, Czech Republic
| | - Veronika Holá
- Department of Microbiology, Faculty of Medicine, Masaryk University & St. Anne's Faculty Hospital, Pekařská 53, Brno 65691, Czech Republic
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30
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Phenotypic antibiotic susceptibility testing of pathogenic bacteria using photonic readout methods: recent achievements and impact. Appl Microbiol Biotechnol 2018; 103:549-566. [PMID: 30443798 DOI: 10.1007/s00253-018-9505-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Revised: 11/02/2018] [Accepted: 11/05/2018] [Indexed: 12/12/2022]
Abstract
The development of antibiotic resistances in common pathogens is an increasing challenge for therapy of infections and especially severe complications like sepsis. To prevent administration of broad-spectrum and potentially non-effective antibiotics, the susceptibility spectrum of the pathogens underlying the infection has to be determined. Current phenotypic standard methods for antibiotic susceptibility testing (AST) require the isolation of pathogens from the patient and the subsequent culturing in the presence of antibiotics leading to results only after 24-72 h. Since the early initialization of an effective antibiotic therapy is crucial for positive treatment result in severe infections, faster methods of AST are urgently needed. A large number of different assay systems are currently tested for their practicability for fast detection of antibiotic resistance profiles. They can be divided into genotypic ones which detect the presence of certain genes or gene products associated with resistances and phenotypic assays which determine the effect of antibiotics on the pathogens. In this mini-review, we summarize current developments in fast phenotypic tests that use photonic approaches and critically discuss their status. We further outline steps that are required to bring these assays into clinical practice.
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31
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García-Timermans C, Rubbens P, Kerckhof FM, Buysschaert B, Khalenkow D, Waegeman W, Skirtach AG, Boon N. Label-free Raman characterization of bacteria calls for standardized procedures. J Microbiol Methods 2018; 151:69-75. [DOI: 10.1016/j.mimet.2018.05.027] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 05/10/2018] [Accepted: 05/31/2018] [Indexed: 11/25/2022]
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32
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The application of UV resonance Raman spectroscopy for the differentiation of clinically relevant Candida species. Anal Bioanal Chem 2018; 410:5839-5847. [DOI: 10.1007/s00216-018-1196-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Revised: 05/30/2018] [Accepted: 06/13/2018] [Indexed: 01/21/2023]
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33
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Cozar IB, Colniţă A, Szöke-Nagy T, Gherman AMR, Dina NE. Label-Free Detection of Bacteria Using Surface-Enhanced Raman Scattering and Principal Component Analysis. ANAL LETT 2018. [DOI: 10.1080/00032719.2018.1445747] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Affiliation(s)
- Ionuţ Bogdan Cozar
- Department of Molecular and Biomolecular Physics, National Institute of Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | - Alia Colniţă
- Department of Molecular and Biomolecular Physics, National Institute of Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | - Tiberiu Szöke-Nagy
- Department of Molecular and Biomolecular Physics, National Institute of Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
- Faculty of Biology and Geology, Babeş-Bolyai University, Cluj-Napoca, Romania
- Institute of Biological Research Cluj-Napoca, Branch of the National Institute of Research and Development for Biological Sciences Bucharest, Cluj-Napoca, Romania
| | - Ana Maria Raluca Gherman
- Department of Molecular and Biomolecular Physics, National Institute of Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
- Faculty of Physics, Babeş-Bolyai University, Cluj-Napoca, Romania
| | - Nicoleta Elena Dina
- Department of Molecular and Biomolecular Physics, National Institute of Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
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34
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Taubert M, Stöckel S, Geesink P, Girnus S, Jehmlich N, von Bergen M, Rösch P, Popp J, Küsel K. Tracking active groundwater microbes with D2O labelling to understand their ecosystem function. Environ Microbiol 2017; 20:369-384. [DOI: 10.1111/1462-2920.14010] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Accepted: 11/16/2017] [Indexed: 11/30/2022]
Affiliation(s)
- Martin Taubert
- Aquatic Geomicrobiology, Institute of Biodiversity; Friedrich Schiller University Jena, Dornburger Str. 159; 07743 Jena Germany
| | - Stephan Stöckel
- Institute of Physical Chemistry and Abbe Center of Photonics; Friedrich Schiller University Jena, Helmholtzweg 4; 07743 Jena Germany
| | - Patricia Geesink
- Aquatic Geomicrobiology, Institute of Biodiversity; Friedrich Schiller University Jena, Dornburger Str. 159; 07743 Jena Germany
| | - Sophie Girnus
- Institute of Physical Chemistry and Abbe Center of Photonics; Friedrich Schiller University Jena, Helmholtzweg 4; 07743 Jena Germany
| | - Nico Jehmlich
- Department of Molecular Systems Biology; Helmholtz Centre for Environmental Research - UFZ, Permoserstrasse 15; 04318 Leipzig Germany
| | - Martin von Bergen
- Department of Molecular Systems Biology; Helmholtz Centre for Environmental Research - UFZ, Permoserstrasse 15; 04318 Leipzig Germany
- Institute of Biochemistry, Pharmacy and Psychology; University of Leipzig, Brüderstraße 32; 04103 Leipzig Germany
- Department of Chemistry and Bioscience; University of Aalborg, Fredrik Bajers Vej 7H; 9220 Aalborg East Denmark
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics; Friedrich Schiller University Jena, Helmholtzweg 4; 07743 Jena Germany
| | - Jürgen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics; Friedrich Schiller University Jena, Helmholtzweg 4; 07743 Jena Germany
- Leibniz-Institute of Photonic Technology, Albert-Einstein-Straße 9; 07745 Jena Germany
| | - Kirsten Küsel
- Aquatic Geomicrobiology, Institute of Biodiversity; Friedrich Schiller University Jena, Dornburger Str. 159; 07743 Jena Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5E; 04103 Leipzig Germany
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35
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Tannert A, Ramoji A, Neugebauer U, Popp J. Photonic monitoring of treatment during infection and sepsis: development of new detection strategies and potential clinical applications. Anal Bioanal Chem 2017; 410:773-790. [PMID: 29214536 DOI: 10.1007/s00216-017-0713-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2017] [Revised: 10/06/2017] [Accepted: 10/17/2017] [Indexed: 01/02/2023]
Abstract
Despite the strong decline in the infection-associated mortality since the development of the first antibiotics, infectious diseases are still a major cause of death in the world. With the rising number of antibiotic-resistant pathogens, the incidence of deaths caused by infections may increase strongly in the future. Survival rates in sepsis, which occurs when body response to infections becomes uncontrolled, are still very poor if an adequate therapy is not initiated immediately. Therefore, approaches to monitor the treatment efficacy are crucially needed to adapt therapeutic strategies according to the patient's response. An increasing number of photonic technologies are being considered for diagnostic purpose and monitoring of therapeutic response; however many of these strategies have not been introduced into clinical routine, yet. Here, we review photonic strategies to monitor response to treatment in patients with infectious disease, sepsis, and septic shock. We also include some selected approaches for the development of new drugs in animal models as well as new monitoring strategies which might be applicable to evaluate treatment response in humans in the future. Figure Label-free probing of blood properties using photonics.
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Affiliation(s)
- Astrid Tannert
- Leibniz Institute of Photonic Technology, Albert-Einstein-Str. 9, 07745, Jena, Germany
- Jena Biophotonics and Imaging Laboratory, 07745, Jena, Germany
| | - Anuradha Ramoji
- Leibniz Institute of Photonic Technology, Albert-Einstein-Str. 9, 07745, Jena, Germany
- Center for Sepsis Control and Care, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany
| | - Ute Neugebauer
- Leibniz Institute of Photonic Technology, Albert-Einstein-Str. 9, 07745, Jena, Germany.
- Jena Biophotonics and Imaging Laboratory, 07745, Jena, Germany.
- Center for Sepsis Control and Care, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.
- Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany.
- InfectoGnostics Research Campus Jena, Philosophenweg 7, Jena, Germany.
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology, Albert-Einstein-Str. 9, 07745, Jena, Germany
- Jena Biophotonics and Imaging Laboratory, 07745, Jena, Germany
- Center for Sepsis Control and Care, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany
- Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany
- InfectoGnostics Research Campus Jena, Philosophenweg 7, Jena, Germany
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36
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Dalla Marta S, Novara C, Giorgis F, Bonifacio A, Sergo V. Optimization and Characterization of Paper-Made Surface Enhanced Raman Scattering (SERS) Substrates with Au and Ag NPs for Quantitative Analysis. MATERIALS 2017; 10:ma10121365. [PMID: 29182585 PMCID: PMC5744300 DOI: 10.3390/ma10121365] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 11/13/2017] [Accepted: 11/24/2017] [Indexed: 11/16/2022]
Abstract
In this work, we present a systematic study on solid Surface Enhanced Raman Scattering (SERS) substrates consisting of Au and Ag nanoparticles (NPs) loaded on filter paper with the dip-coating method. The aim of this work is to explore how a series of parameters (e.g., concentration of colloidal solution, different porosity of filter paper, and the presence of an aggregating agent) affects the analytical performance of paper-based SERS substrates. All the substrates developed in this study have been analyzed with two non-resonant probe molecules, 4-mercaptobenzoic acid (4-MBA) and adenine, in terms of (i) inter-sample repeatability, (ii) intra-sample repeatability, (iii) sensitivity, and (iv) overall SERS performance in terms of analyte quantification. Moreover, the issue of how to evaluate the repeatability for a solid SERS substrate is carefully discussed.
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Affiliation(s)
- Silvia Dalla Marta
- Department of Engineering and Architecture, University of Trieste, I-34127 Trieste, Italy.
| | - Chiara Novara
- Department of Applied Science and Technology, Politecnico of Torino, I-10129 Torino, Italy.
| | - Fabrizio Giorgis
- Department of Applied Science and Technology, Politecnico of Torino, I-10129 Torino, Italy.
| | - Alois Bonifacio
- Department of Engineering and Architecture, University of Trieste, I-34127 Trieste, Italy.
| | - Valter Sergo
- Department of Engineering and Architecture, University of Trieste, I-34127 Trieste, Italy.
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Dina NE, Colniţă A, Szöke-Nagy T, Porav AS. A Critical Review on Ultrasensitive, Spectroscopic-based Methods for High-throughput Monitoring of Bacteria during Infection Treatment. Crit Rev Anal Chem 2017; 47:499-512. [PMID: 28541711 DOI: 10.1080/10408347.2017.1332974] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The world is in the midst of a pre-emptive public health emergency, one that is just as dramatic as the global aggressive viruses-related crises (Ebola, Zika, or SARS), but not as visible. The "superbugs" and their antimicrobial resistance do not cause much public alarm or awareness, but provoke financial losses of $100 trillion annually (WHO, http://www.who.int/mediacentre/commentaries/superbugs-action-now/en/ ). This status quo review offers an overview of ultrasensitive methods for high-throughput monitoring of bacteria during infection treatment, the effects of antibiotics on bacteria at single-cell level and the challenges we will face in their detection due to the extraordinary capability of these "superbugs" to gain and constantly improve multiresistance to antibiotics. A special emphasis is put on the ultrasensitive spectroscopic-based analysis techniques, using nanotechnology or not necessarily, that are more and more promising alternatives to conventional culture-based ones. The particular case of Mycobacteria detection is discussed based on recent reported work.
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Affiliation(s)
- Nicoleta Elena Dina
- a Department of Molecular and Biomolecular Physics , National Institute of R&D of Isotopic and Molecular Technologies , Cluj-Napoca , Romania
| | - Alia Colniţă
- a Department of Molecular and Biomolecular Physics , National Institute of R&D of Isotopic and Molecular Technologies , Cluj-Napoca , Romania
| | - Tiberiu Szöke-Nagy
- a Department of Molecular and Biomolecular Physics , National Institute of R&D of Isotopic and Molecular Technologies , Cluj-Napoca , Romania.,b Faculty of Biology and Geology , Babeş-Bolyai University , Cluj-Napoca , Romania
| | - Alin Sebastian Porav
- a Department of Molecular and Biomolecular Physics , National Institute of R&D of Isotopic and Molecular Technologies , Cluj-Napoca , Romania.,b Faculty of Biology and Geology , Babeş-Bolyai University , Cluj-Napoca , Romania
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Rapid identification of staphylococci by Raman spectroscopy. Sci Rep 2017; 7:14846. [PMID: 29093473 PMCID: PMC5665888 DOI: 10.1038/s41598-017-13940-w] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Accepted: 10/03/2017] [Indexed: 12/25/2022] Open
Abstract
Clinical treatment of the infections caused by various staphylococcal species differ depending on the actual cause of infection. Therefore, it is necessary to develop a fast and reliable method for identification of staphylococci. Raman spectroscopy is an optical method used in multiple scientific fields. Recent studies showed that the method has a potential for use in microbiological research, too. Our work here shows a possibility to identify staphylococci by Raman spectroscopy. We present a method that enables almost 100% successful identification of 16 of the clinically most important staphylococcal species directly from bacterial colonies grown on a Mueller-Hinton agar plate. We obtained characteristic Raman spectra of 277 staphylococcal strains belonging to 16 species from a 24-hour culture of each strain grown on the Mueller-Hinton agar plate using the Raman instrument. The results show that it is possible to distinguish among the tested species using Raman spectroscopy and therefore it has a great potential for use in routine clinical diagnostics.
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Rebrošová K, Šiler M, Samek O, Růžička F, Bernatová S, Ježek J, Zemánek P, Holá V. Differentiation between Staphylococcus aureus and Staphylococcus epidermidis strains using Raman spectroscopy. Future Microbiol 2017; 12:881-890. [PMID: 28686040 DOI: 10.2217/fmb-2016-0224] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
AIM Raman spectroscopy is an analytical method with a broad range of applications across multiple scientific fields. We report on a possibility to differentiate between two important Gram-positive species commonly found in clinical material - Staphylococcus aureus and Staphylococcus epidermidis - using this rapid noninvasive technique. MATERIALS & METHODS For this, we tested 87 strains, 41 of S. aureus and 46 of S. epidermidis, directly from colonies grown on a Mueller-Hinton agar plate using Raman spectroscopy. DISCUSSION & CONCLUSION The method paves a way for separation of these two species even on high number of samples and therefore, it can be potentially used in clinical diagnostics.
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Affiliation(s)
- Katarína Rebrošová
- Department of Microbiology, Faculty of Medicine & St Anne's Faculty Hospital, Pekařská 53, Brno 65691, Czech Republic
| | - Martin Šiler
- ASCR, Institute of Scientific Instruments, Královopolská 147, Brno 61264, Czech Republic
| | - Ota Samek
- ASCR, Institute of Scientific Instruments, Královopolská 147, Brno 61264, Czech Republic
| | - Filip Růžička
- Department of Microbiology, Faculty of Medicine & St Anne's Faculty Hospital, Pekařská 53, Brno 65691, Czech Republic
| | - Silvie Bernatová
- ASCR, Institute of Scientific Instruments, Královopolská 147, Brno 61264, Czech Republic
| | - Jan Ježek
- ASCR, Institute of Scientific Instruments, Královopolská 147, Brno 61264, Czech Republic
| | - Pavel Zemánek
- ASCR, Institute of Scientific Instruments, Královopolská 147, Brno 61264, Czech Republic
| | - Veronika Holá
- Department of Microbiology, Faculty of Medicine & St Anne's Faculty Hospital, Pekařská 53, Brno 65691, Czech Republic
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40
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Accurate and Rapid Differentiation of Acinetobacter baumannii Strains by Raman Spectroscopy: a Comparative Study. J Clin Microbiol 2017; 55:2480-2490. [PMID: 28592553 PMCID: PMC5527427 DOI: 10.1128/jcm.01744-16] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Accepted: 04/28/2017] [Indexed: 01/11/2023] Open
Abstract
In recent years, matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) has become the standard for routine bacterial species identification due to its rapidity and low costs for consumables compared to those of traditional DNA-based methods. However, it has been observed that strains of some bacterial species, such as Acinetobacter baumannii strains, cannot be reliably identified using mass spectrometry (MS). Raman spectroscopy is a rapid technique, as fast as MALDI-TOF, and has been shown to accurately identify bacterial strains and species. In this study, we compared hierarchical clustering results for MS, genomic, and antimicrobial susceptibility test data to hierarchical clustering results from Raman spectroscopic data for 31 A. baumannii clinical isolates labeled according to their pulsed-field gel electrophoresis data for strain differentiation. In addition to performing hierarchical cluster analysis (HCA), multiple chemometric methods of analysis, including principal-component analysis (PCA) and partial least-squares discriminant analysis (PLSDA), were performed on the MS and Raman spectral data, along with a variety of spectral preprocessing techniques for best discriminative results. Finally, simple HCA algorithms were performed on all of the data sets to explore the relationships between, and natural groupings of, the strains and to compare results for the four data sets. To obtain numerical comparison values of the clustering results, the external cluster evaluation criteria of the Rand index of the HCA dendrograms were calculated. With a Rand index value of 0.88, Raman spectroscopy outperformed the other techniques, including MS (with a Rand index value of 0.58).
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41
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Cultivation-Free Raman Spectroscopic Investigations of Bacteria. Trends Microbiol 2017; 25:413-424. [DOI: 10.1016/j.tim.2017.01.002] [Citation(s) in RCA: 132] [Impact Index Per Article: 18.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Revised: 01/06/2017] [Accepted: 01/11/2017] [Indexed: 01/22/2023]
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Iwata T, Katagiri T, Matsuura Y. Real-Time Analysis of Isoprene in Breath by Using Ultraviolet-Absorption Spectroscopy with a Hollow Optical Fiber Gas Cell. SENSORS 2016; 16:s16122058. [PMID: 27929387 PMCID: PMC5191039 DOI: 10.3390/s16122058] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Revised: 11/28/2016] [Accepted: 11/30/2016] [Indexed: 12/24/2022]
Abstract
A breath analysis system based on ultraviolet-absorption spectroscopy was developed by using a hollow optical fiber as a gas cell for real-time monitoring of isoprene in breath. The hollow optical fiber functions as an ultra-small-volume gas cell with a long path. The measurement sensitivity of the system was evaluated by using nitric-oxide gas as a gas sample. The evaluation result showed that the developed system, using a laser-driven, high-intensity light source and a 3-m-long, aluminum-coated hollow optical fiber, could successfully measure nitric-oxide gas with a 50 ppb concentration. An absorption spectrum of a breath sample in the wavelength region of around 200–300 nm was measured, and the measured spectrum revealed the main absorbing components in breath as water vapor, isoprene, and ozone converted from oxygen by radiation of ultraviolet light. The concentration of isoprene in breath was estimated by multiple linear regression. The regression analysis results showed that the proposed analysis system enables real-time monitoring of isoprene during the exhaling of breath. Accordingly, it is suitable for measuring the circadian variation of isoprene.
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Affiliation(s)
- Takuro Iwata
- Graduate School of Biomedical Engineering, Tohoku University, 6-6-05 Aoba, Sendai 980-8579, Japan.
| | - Takashi Katagiri
- Graduate School of Engineering, Tohoku University, 6-6-05 Aoba, Sendai 980-8579, Japan.
| | - Yuji Matsuura
- Graduate School of Biomedical Engineering, Tohoku University, 6-6-05 Aoba, Sendai 980-8579, Japan.
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Kogermann K, Putrinš M, Tenson T. Single-cell level methods for studying the effect of antibiotics on bacteria during infection. Eur J Pharm Sci 2016; 95:2-16. [PMID: 27577009 DOI: 10.1016/j.ejps.2016.08.042] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2016] [Revised: 08/17/2016] [Accepted: 08/23/2016] [Indexed: 12/11/2022]
Abstract
Considerable evidence about phenotypic heterogeneity among bacteria during infection has accumulated during recent years. This heterogeneity has to be considered if the mechanisms of infection and antibiotic action are to be understood, so we need to implement existing and find novel methods to monitor the effects of antibiotics on bacteria at the single-cell level. This review provides an overview of methods by which this aim can be achieved. Fluorescence label-based methods and Raman scattering as a label-free approach are discussed in particular detail. Other label-free methods that can provide single-cell level information, such as impedance spectroscopy and surface plasmon resonance, are briefly summarized. The advantages and disadvantages of these different methods are discussed in light of a challenging in vivo environment.
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Affiliation(s)
- Karin Kogermann
- Institute of Pharmacy, University of Tartu, Nooruse 1, 50411 Tartu, Estonia.
| | - Marta Putrinš
- Institute of Technology, University of Tartu, Nooruse 1, 50411 Tartu, Estonia.
| | - Tanel Tenson
- Institute of Technology, University of Tartu, Nooruse 1, 50411 Tartu, Estonia.
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44
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Brownbill P, Chernyavsky I, Bottalico B, Desoye G, Hansson S, Kenna G, Knudsen LE, Markert UR, Powles-Glover N, Schneider H, Leach L. An international network (PlaNet) to evaluate a human placental testing platform for chemicals safety testing in pregnancy. Reprod Toxicol 2016; 64:191-202. [PMID: 27327413 DOI: 10.1016/j.reprotox.2016.06.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 05/23/2016] [Accepted: 06/07/2016] [Indexed: 12/14/2022]
Abstract
The human placenta is a critical life-support system that nourishes and protects a rapidly growing fetus; a unique organ, species specific in structure and function. We consider the pressing challenge of providing additional advice on the safety of prescription medicines and environmental exposures in pregnancy and how ex vivo and in vitro human placental models might be advanced to reproducible human placental test systems (HPTSs), refining a weight of evidence to the guidance given around compound risk assessment during pregnancy. The placental pharmacokinetics of xenobiotic transfer, dysregulated placental function in pregnancy-related pathologies and influx/efflux transporter polymorphisms are a few caveats that could be addressed by HPTSs, not the specific focus of current mammalian reproductive toxicology systems. An international consortium, "PlaNet", will bridge academia, industry and regulators to consider screen ability and standardisation issues surrounding these models, with proven reproducibility for introduction into industrial and clinical practice.
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Affiliation(s)
- Paul Brownbill
- Maternal and Fetal Health Research Centre, Institute of Human Development, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK; Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
| | - Igor Chernyavsky
- School of Mathematics, University of Manchester, Manchester, UK.
| | - Barbara Bottalico
- Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Lund University, Lund, Sweden,.
| | - Gernot Desoye
- Department of Obstetrics and Gynecology, Medical University of Graz, Graz, Austria.
| | - Stefan Hansson
- Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Lund University, Lund, Sweden,.
| | | | - Lisbeth E Knudsen
- Department of Public Health, Faculty Of Health Sciences, University of Copenhagen, Denmark.
| | - Udo R Markert
- Placenta-Labor Laboratory, Department of Obstetrics, Friedrich Schiller University, D-07740, Jena, Germany.
| | - Nicola Powles-Glover
- Reproductive, Development and Paediatric Centre of Excellence, AstraZeneca, Mereside, Alderley Park, Alderley Edge SK10 4TG, UK.
| | - Henning Schneider
- Department of Obstetrics and Gynecology, Inselspital, University of Bern, Switzerland.
| | - Lopa Leach
- Molecular Cell Biology & Development, School of Life Sciences, Faculty of Medicine & Health Sciences, University of Nottingham, UK.
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