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Abedini M, Montazeri H, Lotfali E, Ghasemi R, Badieyan S, Sasanpour P. Rapid discrimination of Candida species based on optical diffraction pattern. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY. B, BIOLOGY 2023; 240:112630. [PMID: 36736030 DOI: 10.1016/j.jphotobiol.2022.112630] [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: 04/05/2021] [Revised: 10/30/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022]
Abstract
Candidiasis occurs mainly in immunocompromised patients. Rapid detection of Candida species can play a major role in the successful management of fungal infections and treatment monitoring. Detection and discrimination of five common strains of Candida species was performed using the optical elastic scattering diffraction pattern of their colonies. Using laser light with 632 nm wavelength and the designed optical system, optical diffraction patterns of C. albicans (ATCC12261), C. tropicalis (ATCC20336), C. glabrata (15545), C. guilliermondii (20216), and C. parapsilosis (22019) were recorded, processed and analyzed. The results of our study show that based on the different structure of Candida species and dissimilar structure of their colonies, the difference between acquired diffraction patterns are recognizable. In addition, through extraction of statistical feature of the diffraction pattern images and using classification techniques, the detection and discrimination could be performed in a semi-automatic way. The analysis of the colonies of five different Candida species by the optical diffraction patterns generated from the interaction of the laser with colonies' structures demonstrated that the technique had the potential to be applied for the detection and discrimination of various species.
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Affiliation(s)
- Mitra Abedini
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hojatollah Montazeri
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Ensieh Lotfali
- Department of Medical Parasitology and Mycology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| | - Reza Ghasemi
- School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Saeedesadat Badieyan
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Laser Application in Medical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Pezhman Sasanpour
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran; School of Nanoscience, Institute for Research in Fundamental Sciences (IPM), P. O. Box 19395-5531, Tehran, Iran.
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Doh IJ, Dowden B, Patsekin V, Rajwa B, Robinson JP, Bae E. Development of a Smartphone-Integrated Reflective Scatterometer for Bacterial Identification. SENSORS (BASEL, SWITZERLAND) 2022; 22:2646. [PMID: 35408260 PMCID: PMC9003293 DOI: 10.3390/s22072646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 03/21/2022] [Accepted: 03/27/2022] [Indexed: 06/14/2023]
Abstract
We present a smartphone-based bacterial colony phenotyping instrument using a reflective elastic light scattering (ELS) pattern and the resolving power of the new instrument. The reflectance-type device can acquire ELS patterns of colonies on highly opaque media as well as optically dense colonies. The novel instrument was built using a smartphone interface and a 532 nm diode laser, and these essential optical components made it a cost-effective and portable device. When a coherent and collimated light source illuminated a bacterial colony, a reflective ELS pattern was created on the screen and captured by the smartphone camera. The collected patterns whose shapes were determined by the colony morphology were then processed and analyzed to extract distinctive features for bacterial identification. For validation purposes, the reflective ELS patterns of five bacteria grown on opaque growth media were measured with the proposed instrument and utilized for the classification. Cross-validation was performed to evaluate the classification, and the result showed an accuracy above 94% for differentiating colonies of E. coli, K. pneumoniae, L. innocua, S. enteritidis, and S. aureus.
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Affiliation(s)
- Iyll-Joon Doh
- Applied Optics Laboratory, School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA;
| | - Brianna Dowden
- Basic Medical Science, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA; (B.D.); (V.P.); (J.P.R.)
| | - Valery Patsekin
- Basic Medical Science, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA; (B.D.); (V.P.); (J.P.R.)
| | - Bartek Rajwa
- Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA;
| | - J. Paul Robinson
- Basic Medical Science, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA; (B.D.); (V.P.); (J.P.R.)
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907, USA
| | - Euiwon Bae
- Applied Optics Laboratory, School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA;
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Hajipour MJ, Saei AA, Walker ED, Conley B, Omidi Y, Lee K, Mahmoudi M. Nanotechnology for Targeted Detection and Removal of Bacteria: Opportunities and Challenges. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:e2100556. [PMID: 34558234 PMCID: PMC8564466 DOI: 10.1002/advs.202100556] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 08/06/2021] [Indexed: 05/04/2023]
Abstract
The emergence of nanotechnology has created unprecedented hopes for addressing several unmet industrial and clinical issues, including the growing threat so-termed "antibiotic resistance" in medicine. Over the last decade, nanotechnologies have demonstrated promising applications in the identification, discrimination, and removal of a wide range of pathogens. Here, recent insights into the field of bacterial nanotechnology are examined that can substantially improve the fundamental understanding of nanoparticle and bacteria interactions. A wide range of developed nanotechnology-based approaches for bacterial detection and removal together with biofilm eradication are summarized. The challenging effects of nanotechnologies on beneficial bacteria in the human body and environment and the mechanisms of bacterial resistance to nanotherapeutics are also reviewed.
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Affiliation(s)
- Mohammad J. Hajipour
- Department of Radiology and Precision Health ProgramMichigan State UniversityEast LansingMI48824USA
| | - Amir Ata Saei
- Division of Physiological Chemistry IDepartment of Medical Biochemistry and BiophysicsKarolinska InstitutetStockholm171 65Sweden
| | - Edward D. Walker
- Department of EntomologyMichigan State UniversityEast LansingMI48824USA
- Department of Microbiology and Molecular GeneticsMichigan State UniversityEast LansingMI48824USA
| | - Brian Conley
- Department of Chemistry and Chemical BiologyRutgersThe State University of New JerseyPiscatawayNJ08854USA
| | - Yadollah Omidi
- Department of Pharmaceutical SciencesCollege of PharmacyNova Southeastern UniversityFort LauderdaleFL33328USA
| | - Ki‐Bum Lee
- Department of Chemistry and Chemical BiologyRutgersThe State University of New JerseyPiscatawayNJ08854USA
| | - Morteza Mahmoudi
- Department of Radiology and Precision Health ProgramMichigan State UniversityEast LansingMI48824USA
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Doh IJ, Kim H, Sturgis J, Rajwa B, Robinson JP, Bae E. Optical multi-channel interrogation instrument for bacterial colony characterization. PLoS One 2021; 16:e0247721. [PMID: 33630969 PMCID: PMC7906345 DOI: 10.1371/journal.pone.0247721] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 02/11/2021] [Indexed: 11/18/2022] Open
Abstract
A single instrument that includes multiple optical channels was developed to simultaneously measure various optical and associated biophysical characteristics of a bacterial colony. The multi-channel device can provide five distinct optical features without the need to transfer the sample to multiple locations or instruments. The available measurement channels are bright-field light microscopy, 3-D colony-morphology map, 2-D spatial optical-density distribution, spectral forward-scattering pattern, and spectral optical density. The series of multiple morphological interrogations is beneficial in understanding the bio-optical features of a bacterial colony and the correlations among them, resulting in an enhanced power of phenotypic bacterial discrimination. To enable a one-shot interrogation, a confocal laser scanning module was built as an add-on to an upright microscope. Three different-wavelength diode lasers were used for the spectral analysis, and high-speed pin photodiodes and CMOS sensors were utilized as detectors to measure the spectral OD and light-scatter pattern. The proposed instrument and algorithms were evaluated with four bacterial genera, Escherichia coli, Listeria innocua, Salmonella Typhimurium, and Staphylococcus aureus; their resulting data provided a more complete picture of the optical characterization of bacterial colonies.
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Affiliation(s)
- Iyll-Joon Doh
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, United States of America
| | - Huisung Kim
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, United States of America
| | - Jennifer Sturgis
- Basic Medical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, Indiana, United States of America
| | - Bartek Rajwa
- Bindley Bioscience Center, Purdue University, West Lafayette, Indiana, United States of America
| | - J. Paul Robinson
- Basic Medical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, Indiana, United States of America
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America
| | - Euiwon Bae
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, United States of America
- * E-mail:
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Buzalewicz I, Karwańska M, Wieliczko A, Podbielska H. On the application of multi-parametric optical phenotyping of bacterial colonies for multipurpose microbiological diagnostics. Biosens Bioelectron 2020; 172:112761. [PMID: 33129071 DOI: 10.1016/j.bios.2020.112761] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 10/14/2020] [Accepted: 10/21/2020] [Indexed: 02/06/2023]
Abstract
The development of new diagnostics techniques and modalities is critical for early detection of microbial contamination. In this study, the novel integrated system for multi-parametric optical phenotyping and characterization of bacterial colonies, is presented. The system combines Mach-Zehnder interferometer with a spectral imaging system for capturing multispectral diffraction patterns and multispectral two-dimensional transmission maps of bacterial colonies, along with the simultaneous interferometric profilometry. The herein presented investigation was carried out on five representative bacteria species and nearly 3000 registered multispectral optical signatures. The interferograms were analyzed by four-step phase shift algorithm to reconstruct the colony profile to enable the obtaining of the comparable optical signatures. The dedicated image processing algorithms were used for extraction of quantitative features of these signatures. The random forest algorithm was applied for selection of the most predictive set of features, which were used in classification model based on Support-Vector Machine. Obtained results have shown that the use of multiple multispectral optical signatures provide a multi-parametric bacteria identification at an exceptionally high accuracy (99.4-100%), significantly better than in case of classification based on each of these signatures (multispectral diffraction patterns, two-dimensional transmission coefficient maps), separately. Obtained results revealed that analysis of multispectral signatures can also be applied for characterisation of physical, physicochemical and chemical properties of the bacterial colonies in the presence of the antimicrobial factors. Therefore, the proposed label-free, non-destructive optical technique has perspectives to be exploited in the multipurpose diagnostics and it can be used as a pre-screening tool in microbiological laboratories.
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Affiliation(s)
- Igor Buzalewicz
- Bio-Optics Group, Department of Biomedical Engineering, Wroclaw University of Science and Technology, 27 Wybrzeze S. Wyspianskiego St., 50-370, Wroclaw, Poland.
| | - Magdalena Karwańska
- Department of Epizootiology and Veterinary Administration with Clinic of Infectious Diseases, Wroclaw University of Environmental and Life Science, 45 Grunwaldzki Square, 50-366, Wroclaw, Poland
| | - Alina Wieliczko
- Department of Epizootiology and Veterinary Administration with Clinic of Infectious Diseases, Wroclaw University of Environmental and Life Science, 45 Grunwaldzki Square, 50-366, Wroclaw, Poland
| | - Halina Podbielska
- Bio-Optics Group, Department of Biomedical Engineering, Wroclaw University of Science and Technology, 27 Wybrzeze S. Wyspianskiego St., 50-370, Wroclaw, Poland
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