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Tewes TJ, Kerst M, Pavlov S, Huth MA, Hansen U, Bockmühl DP. Unveiling the efficacy of a bulk Raman spectra-based model in predicting single cell Raman spectra of microorganisms. Heliyon 2024; 10:e27824. [PMID: 38510034 PMCID: PMC10950671 DOI: 10.1016/j.heliyon.2024.e27824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 02/29/2024] [Accepted: 03/07/2024] [Indexed: 03/22/2024] Open
Abstract
In a previous publication, we trained predictive models based on Raman bulk spectra of microorganisms placed on a silicon dioxide protected silver mirror slide to make predictions for new Raman spectra, unknown to the models, of microorganisms placed on a different substrate, namely stainless steel. Now we have combined large sections of this data and trained a convolutional neural network (CNN) to make predictions for single cell Raman spectra. We show that a database based on microbial bulk material is conditionally suited to make predictions for the same species in terms of single cells. Data of 13 different microorganisms (bacteria and yeasts) were used. Two of the 13 species could be identified 90% correctly and five other species 71%-88%. The six remaining species were correctly predicted by only 0%-49%. Especially stronger fluorescence in bulk material compared to single cells but also photodegradation of carotenoids are some effects that can complicate predictions for single cells based on bulk data. The results could be helpful in assessing universal Raman tools or databases.
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Affiliation(s)
- Thomas J. Tewes
- Faculty of Life Sciences, Rhine-Waal University of Applied Sciences, Marie-Curie-Straße 1, 47533, Kleve, Germany
| | - Mario Kerst
- Faculty of Life Sciences, Rhine-Waal University of Applied Sciences, Marie-Curie-Straße 1, 47533, Kleve, Germany
| | - Svyatoslav Pavlov
- Faculty of Life Sciences, Rhine-Waal University of Applied Sciences, Marie-Curie-Straße 1, 47533, Kleve, Germany
| | - Miriam A. Huth
- Faculty of Life Sciences, Rhine-Waal University of Applied Sciences, Marie-Curie-Straße 1, 47533, Kleve, Germany
| | - Ute Hansen
- Faculty of Communication and Environment, Rhine-Waal University of Applied Sciences, Friedrich-Heinrich-Allee, 47475, Kamp-Lintfort, Germany
| | - Dirk P. Bockmühl
- Faculty of Life Sciences, Rhine-Waal University of Applied Sciences, Marie-Curie-Straße 1, 47533, Kleve, Germany
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2
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Vaculík O, Bernatová S, Rebrošová K, Samek O, Šilhan L, Růžička F, Šerý M, Šiler M, Ježek J, Zemánek P. Rapid identification of pathogens in blood serum via Raman tweezers in combination with advanced processing methods. BIOMEDICAL OPTICS EXPRESS 2023; 14:6410-6421. [PMID: 38420303 PMCID: PMC10898560 DOI: 10.1364/boe.503628] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 10/06/2023] [Accepted: 10/21/2023] [Indexed: 03/02/2024]
Abstract
Pathogenic microbes contribute to several major global diseases that kill millions of people every year. Bloodstream infections caused by these microbes are associated with high morbidity and mortality rates, which are among the most common causes of hospitalizations. The search for the "Holy Grail" in clinical diagnostic microbiology, a reliable, accurate, low cost, real-time, and easy-to-use diagnostic method, is one of the essential issues in clinical practice. These very critical conditions can be met by Raman tweezers in combination with advanced analysis methods. Here, we present a proof-of-concept study based on Raman tweezers combined with spectral mixture analysis that allows for the identification of microbial strains directly from human blood serum without user intervention, thus eliminating the influence of a data analyst.
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Affiliation(s)
- Ondřej Vaculík
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno, 61264, Czech Republic
| | - Silvie Bernatová
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno, 61264, Czech Republic
| | - Katarína Rebrošová
- Department of Microbiology, Faculty of Medicine of Masaryk University and St. Anne's, University Hospital, Pekařská 53, Brno, 65691, Czech Republic
| | - Ota Samek
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, Brno, 61264, Czech Republic
| | - Lukáš Šilhan
- 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 of Masaryk University and St. Anne's, University Hospital, Pekařská 53, Brno, 65691, Czech Republic
| | - Mojmír Šerý
- 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
| | - 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
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3
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Siems K, Runzheimer K, Rebrosova K, Etzbach L, Auerhammer A, Rehm A, Schwengers O, Šiler M, Samek O, Růžička F, Moeller R. Identification of staphyloxanthin and derivates in yellow-pigmented Staphylococcus capitis subsp. capitis. Front Microbiol 2023; 14:1272734. [PMID: 37840735 PMCID: PMC10570620 DOI: 10.3389/fmicb.2023.1272734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 09/13/2023] [Indexed: 10/17/2023] Open
Abstract
Introduction Staphylococcus capitis naturally colonizes the human skin but as an opportunistic pathogen, it can also cause biofilm-associated infections and bloodstream infections in newborns. Previously, we found that two strains from the subspecies S. capitis subsp. capitis produce yellow carotenoids despite the initial species description, reporting this subspecies as non-pigmented. In Staphylococcus aureus, the golden pigment staphyloxanthin is an important virulence factor, protecting cells against reactive oxygen species and modulating membrane fluidity. Methods In this study, we used two pigmented (DSM 111179 and DSM 113836) and two non-pigmented S. capitis subsp. capitis strains (DSM 20326T and DSM 31028) to identify the pigment, determine conditions under which pigment-production occurs and investigate whether pigmented strains show increased resistance to ROS and temperature stress. Results We found that the non-pigmented strains remained colorless regardless of the type of medium, whereas intensity of pigmentation in the two pigmented strains increased under low nutrient conditions and with longer incubation times. We were able to detect and identify staphyloxanthin and its derivates in the two pigmented strains but found that methanol cell extracts from all four strains showed ROS scavenging activity regardless of staphyloxanthin production. Increased survival to cold temperatures (-20°C) was detected in the two pigmented strains only after long-term storage compared to the non-pigmented strains. Conclusion The identification of staphyloxanthin in S. capitis is of clinical relevance and could be used, in the same way as in S. aureus, as a possible target for anti-virulence drug design.
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Affiliation(s)
- Katharina Siems
- Department of Radiation Biology, Institute of Aerospace Medicine, German Aerospace Center (DLR), Cologne, Germany
| | - Katharina Runzheimer
- Department of Radiation Biology, Institute of Aerospace Medicine, German Aerospace Center (DLR), Cologne, Germany
| | - Katarina Rebrosova
- Department of Microbiology, Faculty of Medicine, Masaryk University and St. Anne’s University Hospital, Brno, Czechia
| | - Lara Etzbach
- Institute of Nutritional and Food Sciences, Food Sciences, University of Bonn, Bonn, Germany
| | - Alina Auerhammer
- Institute of Nutritional and Food Sciences, Food Sciences, University of Bonn, Bonn, Germany
| | - Anna Rehm
- Department of Algorithmic Bioinformatics, Justus Liebig University Giessen, Giessen, Germany
| | - Oliver Schwengers
- Department of Bioinformatics and Systems Biology, Justus Liebig University Giessen, Giessen, Germany
| | - Martin Šiler
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czechia
| | - Ota Samek
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czechia
| | - Filip Růžička
- Department of Microbiology, Faculty of Medicine, Masaryk University and St. Anne’s University Hospital, Brno, Czechia
| | - Ralf Moeller
- Department of Radiation Biology, Institute of Aerospace Medicine, German Aerospace Center (DLR), Cologne, Germany
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Koch SM, Freidank-Pohl C, Siontas O, Cortesao M, Mota A, Runzheimer K, Jung S, Rebrosova K, Siler M, Moeller R, Meyer V. Aspergillus niger as a cell factory for the production of pyomelanin, a molecule with UV-C radiation shielding activity. Front Microbiol 2023; 14:1233740. [PMID: 37547691 PMCID: PMC10399693 DOI: 10.3389/fmicb.2023.1233740] [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: 06/02/2023] [Accepted: 07/03/2023] [Indexed: 08/08/2023] Open
Abstract
Melanins are complex pigments with various biological functions and potential applications in space exploration and biomedicine due to their radioprotective properties. Aspergillus niger, a fungus known for its high radiation resistance, is widely used in biotechnology and a candidate for melanin production. In this study, we investigated the production of fungal pyomelanin (PyoFun) in A. niger by inducing overproduction of the pigment using L-tyrosine in a recombinant ΔhmgA mutant strain (OS4.3). The PyoFun pigment was characterized using three spectroscopic methods, and its antioxidant properties were assessed using a DPPH-assay. Additionally, we evaluated the protective effect of PyoFun against non-ionizing radiation (monochromatic UV-C) and compared its efficacy to a synthetically produced control pyomelanin (PyoSyn). The results confirmed successful production of PyoFun in A. niger through inducible overproduction. Characterization using spectroscopic methods confirmed the presence of PyoFun, and the DPPH-assay demonstrated its strong antioxidant properties. Moreover, PyoFun exhibited a highly protective effect against radiation-induced stress, surpassing the protection provided by PyoSyn. The findings of this study suggest that PyoFun has significant potential as a biological shield against harmful radiation. Notably, PyoFun is synthesized extracellularly, differing it from other fungal melanins (such as L-DOPA- or DHN-melanin) that require cell lysis for pigment purification. This characteristic makes PyoFun a valuable resource for biotechnology, biomedicine, and the space industry. However, further research is needed to evaluate its protective effect in a dried form and against ionizing radiation.
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Affiliation(s)
- Stella Marie Koch
- Radiation Biology Department, Aerospace Microbiology Research Group, German Aerospace Center, Institute of Aerospace Medicine, Cologne, Germany
| | - Carsten Freidank-Pohl
- Applied and Molecular Microbiology, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany
| | - Oliver Siontas
- Applied and Molecular Microbiology, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany
| | - Marta Cortesao
- Radiation Biology Department, Aerospace Microbiology Research Group, German Aerospace Center, Institute of Aerospace Medicine, Cologne, Germany
| | - Afonso Mota
- Radiation Biology Department, Aerospace Microbiology Research Group, German Aerospace Center, Institute of Aerospace Medicine, Cologne, Germany
| | - Katharina Runzheimer
- Radiation Biology Department, Aerospace Microbiology Research Group, German Aerospace Center, Institute of Aerospace Medicine, Cologne, Germany
| | - Sascha Jung
- Applied and Molecular Microbiology, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany
| | - Katarina Rebrosova
- Department of Microbiology, Faculty of Medicine, Masaryk University (MUNI) and St. Anne's Faculty Hospital, Brno, Czechia
| | - Martin Siler
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czechia
| | - Ralf Moeller
- Radiation Biology Department, Aerospace Microbiology Research Group, German Aerospace Center, Institute of Aerospace Medicine, Cologne, Germany
| | - Vera Meyer
- Applied and Molecular Microbiology, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany
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5
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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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6
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Benešová M, Bernatová S, Mika F, Pokorná Z, Ježek J, Šiler M, Samek O, Růžička F, Rebrošová K, Zemánek P, Pilát Z. SERS-Tags: Selective Immobilization and Detection of Bacteria by Strain-Specific Antibodies and Surface-Enhanced Raman Scattering. BIOSENSORS 2023; 13:182. [PMID: 36831948 PMCID: PMC9954015 DOI: 10.3390/bios13020182] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/16/2023] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
Efficient separation and sensitive identification of pathogenic bacterial strains is essential for a prosperous modern society, with direct applications in medical diagnostics, drug discovery, biodefense, and food safety. We developed a fast and reliable method for antibody-based selective immobilization of bacteria from suspension onto a gold-plated glass surface, followed by detection using strain-specific antibodies linked to gold nanoparticles decorated with a reporter molecule. The reporter molecules are subsequently detected by surface-enhanced Raman spectroscopy (SERS). Such a multi-functionalized nanoparticle is called a SERS-tag. The presented procedure uses widely accessible and cheap materials for manufacturing and functionalization of the nanoparticles and the immobilization surfaces. Here, we exemplify the use of the produced SERS-tags for sensitive single-cell detection of opportunistic pathogen Escherichia coli, and we demonstrate the selectivity of our method using two other bacterial strains, Staphylococcus aureus and Serratia marcescens, as negative controls. We believe that the described approach has a potential to inspire the development of novel medical diagnostic tools for rapid identification of bacterial pathogens.
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Affiliation(s)
- Markéta Benešová
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, 612 64 Brno, Czech Republic
| | - Silvie Bernatová
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, 612 64 Brno, Czech Republic
| | - Filip Mika
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, 612 64 Brno, Czech Republic
| | - Zuzana Pokorná
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, 612 64 Brno, Czech Republic
| | - Jan Ježek
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, 612 64 Brno, Czech Republic
| | - Martin Šiler
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, 612 64 Brno, Czech Republic
| | - Ota Samek
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, 612 64 Brno, Czech Republic
| | - Filip Růžička
- Department of Microbiology, Faculty of Medicine of Masaryk University and St. Anne’s University Hospital, Pekařská 53, 656 91 Brno, Czech Republic
| | - Katarina Rebrošová
- Department of Microbiology, Faculty of Medicine of Masaryk University and St. Anne’s University Hospital, Pekařská 53, 656 91 Brno, Czech Republic
| | - Pavel Zemánek
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, 612 64 Brno, Czech Republic
| | - Zdeněk Pilát
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Královopolská 147, 612 64 Brno, Czech Republic
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7
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Bhunia AK, Singh AK, Parker K, Applegate BM. Petri-plate, bacteria, and laser optical scattering sensor. Front Cell Infect Microbiol 2022; 12:1087074. [PMID: 36619754 PMCID: PMC9813400 DOI: 10.3389/fcimb.2022.1087074] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 12/07/2022] [Indexed: 12/24/2022] Open
Abstract
Classical microbiology has paved the path forward for the development of modern biotechnology and microbial biosensing platforms. Microbial culturing and isolation using the Petri plate revolutionized the field of microbiology. In 1887, Julius Richard Petri invented possibly the most important tool in microbiology, the Petri plate, which continues to have a profound impact not only on reliably isolating, identifying, and studying microorganisms but also manipulating a microbe to study gene expression, virulence properties, antibiotic resistance, and production of drugs, enzymes, and foods. Before the recent advances in gene sequencing, microbial identification for diagnosis relied upon the hierarchal testing of a pure culture isolate. Direct detection and identification of isolated bacterial colonies on a Petri plate with a sensing device has the potential for revolutionizing further development in microbiology including gene sequencing, pathogenicity study, antibiotic susceptibility testing , and for characterizing industrially beneficial traits. An optical scattering sensor designated BARDOT (bacterial rapid detection using optical scattering technology) that uses a red-diode laser, developed at the beginning of the 21st century at Purdue University, some 220 years after the Petri-plate discovery can identify and study bacteria directly on the plate as a diagnostic tool akin to Raman scattering and hyperspectral imaging systems for application in clinical and food microbiology laboratories.
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Affiliation(s)
- Arun K. Bhunia
- Molecular Food Microbiology Laboratory, Department of Food Science, Purdue University, West Lafayette, IN, United States,Purdue University, Purdue University Interdisciplinary Life Science Program (PULSe), West Lafayette, IN, United States,Purdue Institute of Inflammation, Immunology and Infectious Disease, Purdue University, West Lafayette, IN, United States,Department of Comparative Pathobiology, Purdue University, West Lafayette, IN, United States,*Correspondence: Arun K. Bhunia,
| | - Atul K. Singh
- Molecular Food Microbiology Laboratory, Department of Food Science, Purdue University, West Lafayette, IN, United States,Clear Labs, San Carlos, CA, United States
| | - Kyle Parker
- Department of Biological Sciences, Purdue University, West Lafayette, IN, United States
| | - Bruce M. Applegate
- Molecular Food Microbiology Laboratory, Department of Food Science, Purdue University, West Lafayette, IN, United States,Purdue University, Purdue University Interdisciplinary Life Science Program (PULSe), West Lafayette, IN, United States,Purdue Institute of Inflammation, Immunology and Infectious Disease, Purdue University, West Lafayette, IN, United States,Department of Biological Sciences, Purdue University, West Lafayette, IN, United States
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8
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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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9
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Lister AP, Highmore CJ, Hanrahan N, Read J, Munro APS, Tan S, Allan RN, Faust SN, Webb JS, Mahajan S. Multi-Excitation Raman Spectroscopy for Label-Free, Strain-Level Characterization of Bacterial Pathogens in Artificial Sputum Media. Anal Chem 2022; 94:669-677. [DOI: 10.1021/acs.analchem.1c02501] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Adam P. Lister
- School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton, SO17 1BJ Southampton, United Kingdom
- National Biofilms Innovation Centre (NBIC) and Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Callum J. Highmore
- School of Biological Sciences, Faculty of Environmental and Life Sciences, University of Southampton, SO17 1BJ Southampton, United Kingdom
- Faculty of Medicine and Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Niall Hanrahan
- School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton, SO17 1BJ Southampton, United Kingdom
- National Biofilms Innovation Centre (NBIC) and Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - James Read
- School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton, SO17 1BJ Southampton, United Kingdom
- National Biofilms Innovation Centre (NBIC) and Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Alasdair P. S. Munro
- NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
- Faculty of Medicine and Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Samuel Tan
- Faculty of Medicine and Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Raymond N. Allan
- School of Biological Sciences, Faculty of Environmental and Life Sciences, University of Southampton, SO17 1BJ Southampton, United Kingdom
- NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
- School of Pharmacy, Faculty of Health and Life Sciences, De Montfort University, Leicester LE1 9BH, UK
| | - Saul N. Faust
- NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
- Faculty of Medicine and Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
- National Biofilms Innovation Centre (NBIC) and Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Jeremy S. Webb
- School of Biological Sciences, Faculty of Environmental and Life Sciences, University of Southampton, SO17 1BJ Southampton, United Kingdom
- National Biofilms Innovation Centre (NBIC) and Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Sumeet Mahajan
- School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton, SO17 1BJ Southampton, United Kingdom
- National Biofilms Innovation Centre (NBIC) and Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
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10
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Lu J, Chen J, Liu C, Zeng Y, Sun Q, Li J, Shen Z, Chen S, Zhang R. Identification of antibiotic resistance and virulence-encoding factors in Klebsiella pneumoniae by Raman spectroscopy and deep learning. Microb Biotechnol 2021; 15:1270-1280. [PMID: 34843635 PMCID: PMC8966003 DOI: 10.1111/1751-7915.13960] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 10/18/2021] [Indexed: 12/12/2022] Open
Abstract
Klebsiella pneumoniae has become the number one bacterial pathogen that causes high mortality in clinical settings worldwide. Clinical K. pneumoniae strains with carbapenem resistance and/or hypervirulent phenotypes cause higher mortality comparing with classical K. pneumoniae strains. Rapid differentiation of clinical K. pneumoniae with high resistance/hypervirulence from classical K. pneumoniae would allow us to develop rational and timely treatment plans. In this study, we developed a convolution neural network (CNN) as a prediction method using Raman spectra raw data for rapid identification of ARGs, hypervirulence‐encoding factors and resistance phenotypes from K. pneumoniae strains. A total of 71 K. pneumoniae strains were included in this study. The minimum inhibitory concentrations (MICs) of 15 commonly used antimicrobial agents on K. pneumoniae strains were determined. Seven thousand four hundred fifty‐five spectra were obtained using the InVia Reflex confocal Raman microscope and used for deep learning‐based and machine learning (ML) algorithms analyses. The quality of predictors was estimated in an independent data set. The results of antibiotic resistance and virulence‐encoding factors identification showed that the CNN model not only simplified the classification system for Raman spectroscopy but also provided significantly higher accuracy to identify K. pneumoniae with high resistance and virulence when compared with the support vector machine (SVM) and logistic regression (LR) models. By back‐testing the Raman‐CNN platform on 71 K. pneumoniae strains, we found that Raman spectroscopy allows for highly accurate and rationally designed treatment plans against bacterial infections within hours. More importantly, this method could reduce healthcare costs and antibiotics misuse, limiting the development of antimicrobial resistance and improving patient outcomes.
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Affiliation(s)
- Jiayue Lu
- Department of Clinical Laboratory, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jifan Chen
- Department of Ultrasound, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Congcong Liu
- Department of Clinical Laboratory, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yu Zeng
- Department of Clinical Laboratory, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qiaoling Sun
- Department of Clinical Laboratory, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiaping Li
- Department of Clinical Laboratory, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhangqi Shen
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Veterinary Medicine, China Agricultural University, Beijing, China
| | - Sheng Chen
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China
| | - Rong Zhang
- Department of Clinical Laboratory, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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11
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Uysal Ciloglu F, Saridag AM, Kilic IH, Tokmakci M, Kahraman M, Aydin O. Identification of methicillin-resistant Staphylococcus aureus bacteria using surface-enhanced Raman spectroscopy and machine learning techniques. Analyst 2021; 145:7559-7570. [PMID: 33135033 DOI: 10.1039/d0an00476f] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
To combat antibiotic resistance, it is extremely important to select the right antibiotic by performing rapid diagnosis of pathogens. Traditional techniques require complicated sample preparation and time-consuming processes which are not suitable for rapid diagnosis. To address this problem, we used surface-enhanced Raman spectroscopy combined with machine learning techniques for rapid identification of methicillin-resistant and methicillin-sensitive Gram-positive Staphylococcus aureus strains and Gram-negative Legionella pneumophila (control group). A total of 10 methicillin-resistant S. aureus (MRSA), 3 methicillin-sensitive S. aureus (MSSA) and 6 L. pneumophila isolates were used. The obtained spectra indicated high reproducibility and repeatability with a high signal to noise ratio. Principal component analysis (PCA), hierarchical cluster analysis (HCA), and various supervised classification algorithms were used to discriminate both S. aureus strains and L. pneumophila. Although there were no noteworthy differences between MRSA and MSSA spectra when viewed with the naked eye, some peak intensity ratios such as 732/958, 732/1333, and 732/1450 proved that there could be a significant indicator showing the difference between them. The k-nearest neighbors (kNN) classification algorithm showed superior classification performance with 97.8% accuracy among the traditional classifiers including support vector machine (SVM), decision tree (DT), and naïve Bayes (NB). Our results indicate that SERS combined with machine learning can be used for the detection of antibiotic-resistant and susceptible bacteria and this technique is a very promising tool for clinical applications.
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Affiliation(s)
- Fatma Uysal Ciloglu
- Department of Biomedical Engineering, Erciyes University, Kayseri 38039, Turkey.
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12
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Non-destructive Monitoring of Staphylococcus aureus Biofilm by Surface-Enhanced Raman Scattering Spectroscopy. FOOD ANAL METHOD 2020. [DOI: 10.1007/s12161-020-01792-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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13
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Jaafreh S, Valler O, Kreyenschmidt J, Günther K, Kaul P. In vitro discrimination and classification of Microbial Flora of Poultry using two dispersive Raman spectrometers (microscope and Portable Fiber-Optic systems) in tandem with chemometric analysis. Talanta 2019; 202:411-425. [PMID: 31171202 DOI: 10.1016/j.talanta.2019.04.082] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 04/27/2019] [Accepted: 04/30/2019] [Indexed: 01/08/2023]
Abstract
Discrimination and classification of eight strains related to meat spoilage and pathogenic microorganisms commonly found in poultry meat were successfully carried out using two dispersive Raman spectrometers (Microscope and Portable Fiber-Optic systems) in combination with chemometric methods. Principal components analysis (PCA) and multi-class support vector machines (MC-SVM) were applied to develop discrimination and classification models. These models were certified using validation data sets which were successfully assigned to the correct bacterial species and even to the right strain. The discrimination of bacteria down to the strain level was performed for the pre-processed spectral data using a 3-stage model based on PCA. The spectral features and differences among the species on which the discrimination was based were clarified through PCA loadings. In MC-SVM the pre-processed spectral data was subjected to PCA and utilized to build a classification model. When using the first two components, the accuracy of the MC-SVM model was 97.64% and 93.23% for the validation data collected by the Raman Microscope and the Portable Fiber-Optic Raman system, respectively. The accuracy reached 100% for the validation data by using the first eight and ten PC's from the data collected by Raman Microscope and by Portable Fiber-Optic Raman system, respectively. The results reflect the strong discriminative power and the high performance of the developed models, the suitability of the pre-processing method used in this study and that the low accuracy of the Portable Fiber-Optic Raman system does not adversely affect the discriminative power of the developed models.
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Affiliation(s)
- Sawsan Jaafreh
- Institute of Safety and Security Research, Bonn-Rhein-Sieg University of Applied Sciences, Von Liebig-Straße 20, 53359 Rheinbach, Germany.
| | - Ole Valler
- Rhine-Waal University of Applied Sciences, Marie-Curie-Straße 1, 47533 Kleve, Germany
| | | | - Klaus Günther
- Institute of Nutritional and Food Sciences, Food Chemistry, University of Bonn, Endenicher Allee 11-13, 53115 Bonn, Germany; Institute of Bio- and Geosciences (IBG-2), Research Centre Jülich, 52425 Jülich, Germany
| | - Peter Kaul
- Institute of Safety and Security Research, Bonn-Rhein-Sieg University of Applied Sciences, Von Liebig-Straße 20, 53359 Rheinbach, Germany
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14
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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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Hrubanova K, Krzyzanek V, Nebesarova J, Ruzicka F, Pilat Z, Samek O. Monitoring Candida parapsilosis and Staphylococcus epidermidis Biofilms by a Combination of Scanning Electron Microscopy and Raman Spectroscopy. SENSORS 2018; 18:s18124089. [PMID: 30469521 PMCID: PMC6308600 DOI: 10.3390/s18124089] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2018] [Revised: 11/16/2018] [Accepted: 11/20/2018] [Indexed: 02/03/2023]
Abstract
The biofilm-forming microbial species Candida parapsilosis and Staphylococcus epidermidis have been recently linked to serious infections associated with implanted medical devices. We studied microbial biofilms by high resolution scanning electron microscopy (SEM), which allowed us to visualize the biofilm structure, including the distribution of cells inside the extracellular matrix and the areas of surface adhesion. We compared classical SEM (chemically fixed samples) with cryogenic SEM, which employs physical sample preparation based on plunging the sample into various liquid cryogens, as well as high-pressure freezing (HPF). For imaging the biofilm interior, we applied the freeze-fracture technique. In this study, we show that the different means of sample preparation have a fundamental influence on the observed biofilm structure. We complemented the SEM observations with Raman spectroscopic analysis, which allowed us to assess the time-dependent chemical composition changes of the biofilm in vivo. We identified the individual spectral peaks of the biomolecules present in the biofilm and we employed principal component analysis (PCA) to follow the temporal development of the chemical composition.
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Affiliation(s)
- Kamila Hrubanova
- Institute of Scientific Instruments of the Czech Academy of Sciences, CZ-61264 Brno, Czech Republic.
| | - Vladislav Krzyzanek
- Institute of Scientific Instruments of the Czech Academy of Sciences, CZ-61264 Brno, Czech Republic.
| | - Jana Nebesarova
- Biology Centre of the Czech Academy of Sciences, CZ-37005 Ceske Budejovice, Czech Republic.
| | - Filip Ruzicka
- Department of Microbiology, Faculty of Medicine, Masaryk University and St. Anne's Faculty Hospital, CZ-65691 Brno, Czech Republic.
| | - Zdenek Pilat
- Institute of Scientific Instruments of the Czech Academy of Sciences, CZ-61264 Brno, Czech Republic.
| | - Ota Samek
- Institute of Scientific Instruments of the Czech Academy of Sciences, CZ-61264 Brno, Czech Republic.
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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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