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Dinçtürk E. Determination of Raman spectrum under different culture conditions: preliminary research on bacterial fish pathogens. Anim Biotechnol 2024; 35:2299733. [PMID: 38166494 DOI: 10.1080/10495398.2023.2299733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2024]
Abstract
The intensive labour and time required for conventional methods to identify bacterial fish pathogens have revealed the need to develop alternative methods. Raman spectroscopy has been used in the rapid optical identification of bacterial pathogens in recent years as an alternative method in microbiology. Strains of bacterial fish pathogens (Vibrio anguillarum, Lactococcus garvieae and Yersinia ruckeri) that often cause infectious diseases in fish were here identified and analyzed in terms of their biochemical structures in different media and at different incubation times, and the data were specified by using Raman spectroscopy. The results demonstrated that Raman spectroscopy presents species-specific Raman spectra of each disease-causing bacteria and that it would be more appropriate to choose general microbiological media over selective media for routine studies. Additionally, it was found that species-specific band regions did not differ in 24- and 48-hour cultures, but there could be a difference in peak intensity which may lead to difficult characterization of spectrum. The current study, conducted for the first time with bacterial fish pathogens under different incubation conditions, is believed to provide a basis for the routine use of Raman spectroscopy for quick pathogen identification and the precise determination of the methodology for further research.
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Affiliation(s)
- Ezgi Dinçtürk
- Fish Disease and Biotechnology Laboratory, Department of Aquaculture, Izmir Katip Celebi University, Izmir, Türkiye
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2
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Taha BA, Ahmed NM, Talreja RK, Haider AJ, Al Mashhadany Y, Al-Jubouri Q, Huddin AB, Mokhtar MHH, Rustagi S, Kaushik A, Chaudhary V, Arsad N. Synergizing Nanomaterials and Artificial Intelligence in Advanced Optical Biosensors for Precision Antimicrobial Resistance Diagnosis. ACS Synth Biol 2024; 13:1600-1620. [PMID: 38842483 DOI: 10.1021/acssynbio.4c00070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Abstract
Antimicrobial resistance (AMR) poses a critical global One Health concern, ensuing from unintentional and continuous exposure to antibiotics, as well as challenges in accurate contagion diagnostics. Addressing AMR requires a strategic approach that emphasizes early stage prevention through screening in clinical, environmental, farming, and livestock settings to identify nonvulnerable antimicrobial agents and the associated genes. Conventional AMR diagnostics, like antibiotic susceptibility testing, possess drawbacks, including high costs, time-consuming processes, and significant manpower requirements, underscoring the need for intelligent, prompt, and on-site diagnostic techniques. Nanoenabled artificial intelligence (AI)-supported smart optical biosensors present a potential solution by facilitating rapid point-of-care AMR detection with real-time, sensitive, and portable capabilities. This Review comprehensively explores various types of optical nanobiosensors, such as surface plasmon resonance sensors, whispering-gallery mode sensors, optical coherence tomography, interference reflection imaging sensors, surface-enhanced Raman spectroscopy, fluorescence spectroscopy, microring resonance sensors, and optical tweezer biosensors, for AMR diagnostics. By harnessing the unique advantages of these nanoenabled smart biosensors, a revolutionary paradigm shift in AMR diagnostics can be achieved, characterized by rapid results, high sensitivity, portability, and integration with Internet-of-Things (IoT) technologies. Moreover, nanoenabled optical biosensors enable personalized monitoring and on-site detection, significantly reducing turnaround time and eliminating the human resources needed for sample preservation and transportation. Their potential for holistic environmental surveillance further enhances monitoring capabilities in diverse settings, leading to improved modern-age healthcare practices and more effective management of antimicrobial treatments. Embracing these advanced diagnostic tools promises to bolster global healthcare capacity to combat AMR and safeguard One Health.
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Affiliation(s)
- Bakr Ahmed Taha
- Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia UKM, 43600 Bangi, Malaysia
| | - Naser M Ahmed
- Department of Laser and Optoelectronics Engineering, Dijlah University College, 00964 Baghdad, Iraq
| | - Rishi Kumar Talreja
- Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi 110029, India
| | - Adawiya J Haider
- Applied Sciences Department/Laser Science and Technology Branch, University of Technology, 00964 Baghdad, Iraq
| | - Yousif Al Mashhadany
- Department of Electrical Engineering, College of Engineering, University of Anbar, Anbar 00964, Iraq
| | - Qussay Al-Jubouri
- Department of Communication Engineering, University of Technology, 00964 Baghdad, Iraq
| | - Aqilah Baseri Huddin
- Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia UKM, 43600 Bangi, Malaysia
| | - Mohd Hadri Hafiz Mokhtar
- Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia UKM, 43600 Bangi, Malaysia
| | - Sarvesh Rustagi
- School of Applied and Life Sciences, Uttaranchal University, Dehradun, Uttrakhand 248007, India
| | - Ajeet Kaushik
- NanoBioTech Laboratory, Department of Environmental Engineering, Florida Polytechnic University, Lakeland, Florida 33805, United States
| | - Vishal Chaudhary
- Physics Department, Bhagini Nivedita College, University of Delhi, New Delhi 110045, India
| | - Norhana Arsad
- Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia UKM, 43600 Bangi, Malaysia
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Chu J, Yu X, Jiang G, Tao Y, Wu W, Han S. Bacterial imaging in tumour diagnosis. Microb Biotechnol 2024; 17:e14474. [PMID: 38808743 PMCID: PMC11135020 DOI: 10.1111/1751-7915.14474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 04/15/2024] [Accepted: 04/17/2024] [Indexed: 05/30/2024] Open
Abstract
Some bacteria, such as Escherichia coli (E. coli) and Salmonella typhimurium (S. typhimurium), have an inherent ability to locate solid tumours, making them a versatile platform that can be combined with other tools to improve the tumour diagnosis and treatment. In anti-cancer therapy, bacteria function by carrying drugs directly or expressing exogenous therapeutic genes. The application of bacterial imaging in tumour diagnosis, a novel and promising research area, can indeed provide dynamic and real-time monitoring in both pre-treatment assessment and post-treatment detection. Different imaging techniques, including optical technology, acoustic imaging, magnetic resonance imaging (MRI) and nuclear medicine imaging, allow us to observe and track tumour-associated bacteria. Optical imaging, including bioluminescence and fluorescence, provides high-sensitivity and high-resolution imaging. Acoustic imaging is a real-time and non-invasive imaging technique with good penetration depth and spatial resolution. MRI provides high spatial resolution and radiation-free imaging. Nuclear medicine imaging, including positron emission tomography (PET) and single photon emission computed tomography (SPECT) can provide information on the distribution and dynamics of bacterial population. Moreover, strategies of synthetic biology modification and nanomaterial engineering modification can improve the viability and localization ability of bacteria while maintaining their autonomy and vitality, thus aiding the visualization of gut bacteria. However, there are some challenges, such as the relatively low bacterial abundance and heterogeneously distribution within the tumour, the high dimensionality of spatial datasets and the limitations of imaging labeling tools. In summary, with the continuous development of imaging technology and nanotechnology, it is expected to further make in-depth study on tumour-associated bacteria and develop new bacterial imaging methods for tumour diagnosis.
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Affiliation(s)
- Jian Chu
- Huzhou Central HospitalAffiliated Central Hospital Huzhou UniversityHuzhouChina
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive CancerHuzhouChina
- Fifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital)HuzhouChina
| | - Xiang Yu
- Huzhou Central HospitalAffiliated Central Hospital Huzhou UniversityHuzhouChina
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive CancerHuzhouChina
- Fifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital)HuzhouChina
| | - Gaofei Jiang
- Key Lab of Organic‐Based Fertilizers of China, Jiangsu Provincial Key Lab for Solid Organic Waste UtilizationNanjing Agricultural UniversityNanjingChina
| | - Ye Tao
- Shanghai BIOZERON Biotechnology Co., Ltd.ShanghaiChina
| | - Wei Wu
- Huzhou Central HospitalAffiliated Central Hospital Huzhou UniversityHuzhouChina
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive CancerHuzhouChina
- Fifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital)HuzhouChina
| | - Shuwen Han
- Huzhou Central HospitalAffiliated Central Hospital Huzhou UniversityHuzhouChina
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive CancerHuzhouChina
- Fifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital)HuzhouChina
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Dorta D, Plazaola C, Carrasco J, Alves-Rosa MF, Coronado LM, Correa R, Zambrano M, Gutiérrez-Medina B, Sarmiento-Gómez E, Spadafora C, Gonzalez G. Mechanical Characterization of the Erythrocyte Membrane Using a Capacitor-Based Technique. MICROMACHINES 2024; 15:590. [PMID: 38793163 PMCID: PMC11122917 DOI: 10.3390/mi15050590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 04/22/2024] [Accepted: 04/24/2024] [Indexed: 05/26/2024]
Abstract
Pathological processes often change the mechanical properties of cells. Increased rigidity could be a marker of cellular malfunction. Erythrocytes are a type of cell that deforms to squeeze through tiny capillaries; changes in their rigidity can dramatically affect their functionality. Furthermore, differences in the homeostatic elasticity of the cell can be used as a tool for diagnosis and even for choosing the adequate treatment for some illnesses. More accurate types of equipment needed to study biomechanical phenomena at the single-cell level are very costly and thus out of reach for many laboratories around the world. This study presents a simple and low-cost technique to study the rigidity of red blood cells (RBCs) through the application of electric fields in a hand-made microfluidic chamber that uses a capacitor principle. As RBCs are deformed with the application of voltage, cells are observed under a light microscope. From mechanical force vs. deformation data, the elastic constant of the cells is determined. The results obtained with the capacitor-based method were compared with those obtained using optical tweezers, finding good agreement. In addition, P. falciparum-infected erythrocytes were tested with the electric field applicator. Our technique provides a simple means of testing the mechanical properties of individual cells.
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Affiliation(s)
- Doriana Dorta
- Facultad de Ciencias Naturales, Exactas y Tecnología, Universidad de Panamá, Panama City 06001-01103, Panama;
- Centro de Biología Celular y Molecular de Enfermedades, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Ciudad del Saber, Panama City 1843-01103, Panama; (J.C.); (M.F.A.-R.); (L.M.C.); (R.C.); (C.S.)
| | - Carlos Plazaola
- Facultad de Ingeniería Mecánica, Universidad Tecnológica de Panamá, Panama City 0819-07289, Panama;
| | - Jafeth Carrasco
- Centro de Biología Celular y Molecular de Enfermedades, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Ciudad del Saber, Panama City 1843-01103, Panama; (J.C.); (M.F.A.-R.); (L.M.C.); (R.C.); (C.S.)
| | - Maria F. Alves-Rosa
- Centro de Biología Celular y Molecular de Enfermedades, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Ciudad del Saber, Panama City 1843-01103, Panama; (J.C.); (M.F.A.-R.); (L.M.C.); (R.C.); (C.S.)
| | - Lorena M. Coronado
- Centro de Biología Celular y Molecular de Enfermedades, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Ciudad del Saber, Panama City 1843-01103, Panama; (J.C.); (M.F.A.-R.); (L.M.C.); (R.C.); (C.S.)
| | - Ricardo Correa
- Centro de Biología Celular y Molecular de Enfermedades, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Ciudad del Saber, Panama City 1843-01103, Panama; (J.C.); (M.F.A.-R.); (L.M.C.); (R.C.); (C.S.)
| | - Maytee Zambrano
- Facultad de Ingeniería Eléctrica, Universidad Tecnológica de Panamá, Panama City 0819-07289, Panama;
- Centro de Estudios Multidisciplinarios en Ciencias, Ingeniería y Tecnología (CEMCIT-AIP), Panama City 0819-07289, Panama
| | - Braulio Gutiérrez-Medina
- Advanced Materials Division, Instituto Potosino de Investigación Científica y Tecnológica A. C. (IPICYT), San Luis Potosí 78216, Mexico;
| | - Erick Sarmiento-Gómez
- Departamento de Ingeniería Física, División de Ciencias e Ingenierías, Campus León, Universidad de Guanajuato, Guanajuato 37320, Mexico;
| | - Carmenza Spadafora
- Centro de Biología Celular y Molecular de Enfermedades, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Ciudad del Saber, Panama City 1843-01103, Panama; (J.C.); (M.F.A.-R.); (L.M.C.); (R.C.); (C.S.)
| | - Guadalupe Gonzalez
- Facultad de Ingeniería Eléctrica, Universidad Tecnológica de Panamá, Panama City 0819-07289, Panama;
- Centro de Estudios Multidisciplinarios en Ciencias, Ingeniería y Tecnología (CEMCIT-AIP), Panama City 0819-07289, Panama
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Ren Y, Zheng Y, Wang X, Qu S, Sun L, Song C, Ding J, Ji Y, Wang G, Zhu P, Cheng L. Rapid identification of lactic acid bacteria at species/subspecies level via ensemble learning of Ramanomes. Front Microbiol 2024; 15:1361180. [PMID: 38650881 PMCID: PMC11033474 DOI: 10.3389/fmicb.2024.1361180] [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: 12/25/2023] [Accepted: 03/28/2024] [Indexed: 04/25/2024] Open
Abstract
Rapid and accurate identification of lactic acid bacteria (LAB) species would greatly improve the screening rate for functional LAB. Although many conventional and molecular methods have proven efficient and reliable, LAB identification using these methods has generally been slow and tedious. Single-cell Raman spectroscopy (SCRS) provides the phenotypic profile of a single cell and can be performed by Raman spectroscopy (which directly detects vibrations of chemical bonds through inelastic scattering by a laser light) using an individual live cell. Recently, owing to its affordability, non-invasiveness, and label-free features, the Ramanome has emerged as a potential technique for fast bacterial detection. Here, we established a reference Ramanome database consisting of SCRS data from 1,650 cells from nine LAB species/subspecies and conducted further analysis using machine learning approaches, which have high efficiency and accuracy. We chose the ensemble meta-classifier (EMC), which is suitable for solving multi-classification problems, to perform in-depth mining and analysis of the Ramanome data. To optimize the accuracy and efficiency of the machine learning algorithm, we compared nine classifiers: LDA, SVM, RF, XGBoost, KNN, PLS-DA, CNN, LSTM, and EMC. EMC achieved the highest average prediction accuracy of 97.3% for recognizing LAB at the species/subspecies level. In summary, Ramanomes, with the integration of EMC, have promising potential for fast LAB species/subspecies identification in laboratories and may thus be further developed and sharpened for the direct identification and prediction of LAB species from fermented food.
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Affiliation(s)
- Yan Ren
- School of Life Science and Technology, Inner Mongolia University of Science and Technology, Baotou, China
- Inner Mongolia Key Laboratory for Biomass-Energy Conversion, Baotou, China
| | - Yang Zheng
- School of Life Science and Technology, Inner Mongolia University of Science and Technology, Baotou, China
| | - Xiaojing Wang
- School of Life Science and Technology, Inner Mongolia University of Science and Technology, Baotou, China
| | - Shuang Qu
- School of Life Science and Technology, Inner Mongolia University of Science and Technology, Baotou, China
| | - Lijun Sun
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China
| | - Chenyong Song
- Qingdao Single-Cell Biotechnology Co., Ltd., Qingdao, Shandong, China
| | - Jia Ding
- Qingdao Single-Cell Biotechnology Co., Ltd., Qingdao, Shandong, China
| | - Yuetong Ji
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China
- Qingdao Single-Cell Biotechnology Co., Ltd., Qingdao, Shandong, China
| | - Guoze Wang
- School of Life Science and Technology, Inner Mongolia University of Science and Technology, Baotou, China
- Inner Mongolia Key Laboratory for Biomass-Energy Conversion, Baotou, China
| | - Pengfei Zhu
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China
- Qingdao Single-Cell Biotechnology Co., Ltd., Qingdao, Shandong, China
| | - Likun Cheng
- School of Life Science and Technology, Inner Mongolia University of Science and Technology, Baotou, China
- Inner Mongolia Key Laboratory for Biomass-Energy Conversion, Baotou, China
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Lu L, Zhao Y, Li M, Wang X, Zhu J, Liao L, Wang J. Contemporary strategies and approaches for characterizing composition and enhancing biofilm penetration targeting bacterial extracellular polymeric substances. J Pharm Anal 2024; 14:100906. [PMID: 38634060 PMCID: PMC11022105 DOI: 10.1016/j.jpha.2023.11.013] [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: 08/04/2023] [Revised: 11/08/2023] [Accepted: 11/26/2023] [Indexed: 04/19/2024] Open
Abstract
Extracellular polymeric substances (EPS) constitutes crucial elements within bacterial biofilms, facilitating accelerated antimicrobial resistance and conferring defense against the host's immune cells. Developing precise and effective antibiofilm approaches and strategies, tailored to the specific characteristics of EPS composition, can offer valuable insights for the creation of novel antimicrobial drugs. This, in turn, holds the potential to mitigate the alarming issue of bacterial drug resistance. Current analysis of EPS compositions relies heavily on colorimetric approaches with a significant bias, which is likely due to the selection of a standard compound and the cross-interference of various EPS compounds. Considering the pivotal role of EPS in biofilm functionality, it is imperative for EPS research to delve deeper into the analysis of intricate compositions, moving beyond the current focus on polymeric materials. This necessitates a shift from heavy reliance on colorimetric analytic methods to more comprehensive and nuanced analytical approaches. In this study, we have provided a comprehensive summary of existing analytical methods utilized in the characterization of EPS compositions. Additionally, novel strategies aimed at targeting EPS to enhance biofilm penetration were explored, with a specific focus on highlighting the limitations associated with colorimetric methods. Furthermore, we have outlined the challenges faced in identifying additional components of EPS and propose a prospective research plan to address these challenges. This review has the potential to guide future researchers in the search for novel compounds capable of suppressing EPS, thereby inhibiting biofilm formation. This insight opens up a new avenue for exploration within this research domain.
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Affiliation(s)
- Lan Lu
- Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, Sichuan Industrial Institute of Antibiotics, School of Pharmacy, Chengdu University, Chengdu, 610000, China
| | - Yuting Zhao
- Meishan Pharmaceutical Vocational College, School of Pharmacy, Meishan, Sichuan, 620200, China
| | - Mingxing Li
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Xiaobo Wang
- Hepatobiliary Surgery, Langzhong People's Hospital, Langzhong, Sichuan, 646000, China
| | - Jie Zhu
- Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, Sichuan Industrial Institute of Antibiotics, School of Pharmacy, Chengdu University, Chengdu, 610000, China
| | - Li Liao
- Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, Sichuan Industrial Institute of Antibiotics, School of Pharmacy, Chengdu University, Chengdu, 610000, China
| | - Jingya Wang
- Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, Sichuan Industrial Institute of Antibiotics, School of Pharmacy, Chengdu University, Chengdu, 610000, China
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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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8
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Frempong SB, Salbreiter M, Mostafapour S, Pistiki A, Bocklitz TW, Rösch P, Popp J. Illuminating the Tiny World: A Navigation Guide for Proper Raman Studies on Microorganisms. Molecules 2024; 29:1077. [PMID: 38474589 DOI: 10.3390/molecules29051077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/13/2024] [Accepted: 02/18/2024] [Indexed: 03/14/2024] Open
Abstract
Raman spectroscopy is an emerging method for the identification of bacteria. Nevertheless, a lot of different parameters need to be considered to establish a reliable database capable of identifying real-world samples such as medical or environmental probes. In this review, the establishment of such reliable databases with the proper design in microbiological Raman studies is demonstrated, shining a light into all the parts that require attention. Aspects such as the strain selection, sample preparation and isolation requirements, the phenotypic influence, measurement strategies, as well as the statistical approaches for discrimination of bacteria, are presented. Furthermore, the influence of these aspects on spectra quality, result accuracy, and read-out are discussed. The aim of this review is to serve as a guide for the design of microbiological Raman studies that can support the establishment of this method in different fields.
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Affiliation(s)
- Sandra Baaba Frempong
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Markus Salbreiter
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Sara Mostafapour
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Aikaterini Pistiki
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance-Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Thomas W Bocklitz
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance-Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Jürgen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
- InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance-Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
- Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, 07743 Jena, Germany
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Shankarnarayan SA, Charlebois DA. Machine learning to identify clinically relevant Candida yeast species. Med Mycol 2024; 62:myad134. [PMID: 38130236 DOI: 10.1093/mmy/myad134] [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: 09/19/2023] [Revised: 12/06/2023] [Accepted: 12/19/2023] [Indexed: 12/23/2023] Open
Abstract
Fungal infections, especially due to Candida species, are on the rise. Multi-drug resistant organisms such as Candida auris are difficult and time consuming to identify accurately. Machine learning is increasingly being used in health care, especially in medical imaging. In this study, we evaluated the effectiveness of six convolutional neural networks (CNNs) to identify four clinically important Candida species. Wet-mounted images were captured using bright field live-cell microscopy followed by separating single-cells, budding-cells, and cell-group images which were then subjected to different machine learning algorithms (custom CNN, VGG16, ResNet50, InceptionV3, EfficientNetB0, and EfficientNetB7) to learn and predict Candida species. Among the six algorithms tested, the InceptionV3 model performed best in predicting Candida species from microscopy images. All models performed poorly on raw images obtained directly from the microscope. The performance of all models increased when trained on single and budding cell images. The InceptionV3 model identified budding cells of C. albicans, C. auris, C. glabrata (Nakaseomyces glabrata), and C. haemulonii in 97.0%, 74.0%, 68.0%, and 66.0% cases, respectively. For single cells of C. albicans, C. auris, C. glabrata, and C. haemulonii InceptionV3 identified 97.0%, 73.0%, 69.0%, and 73.0% cases, respectively. The sensitivity and specificity of InceptionV3 were 77.1% and 92.4%, respectively. Overall, this study provides proof of the concept that microscopy images from wet-mounted slides can be used to identify Candida yeast species using machine learning quickly and accurately.
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Affiliation(s)
| | - Daniel A Charlebois
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G-2E1, Canada
- Department of Physics, Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G-2E9, Canada
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10
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Wu L, Ye T, Pan X, Hong L, Shi Y. A case of Elizabethkingia meningoseptica septicemia. Zhejiang Da Xue Xue Bao Yi Xue Ban 2023; 53:126-130. [PMID: 38105675 PMCID: PMC10945492 DOI: 10.3724/zdxbyxb-2023-0427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 10/10/2023] [Indexed: 12/19/2023]
Abstract
A 82-year-old man was admitted to hospital with fever, unresponsiveness, elevated hypersensitive C-reactive protein and neutrophile granulocyte. Ceftriaxone was administrated by intravenous dripping in the emergency room, but the effect was not satisfactory. Following his admission to the ward, cefoperazone sulbactam were given. Elizabethkingia meningoseptica was identified by blood culture and further confirmed by 16S rRNA sequencing. The lumbar puncture showed that cerebrospinal fluid pressure was 80 mmH2O (1 mmH2O=0.0098 kPa) and biochemical results were normal. After 11 days of cefoperazone sulbactam treatment, the patient was discharged with negative blood culture. The hypersensitive C-reactive protein and neutrophile granulocyte had also declined. The patient received levofloxacin tablets for anti-infection treatment for 14 d after discharge. No signs of infection were observed in three months' following up.
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Affiliation(s)
- Lihua Wu
- Department of Infectious disease, Dongyang People's Hospital, Dongyang 322100, Zhejiang Province, China.
| | - Tinghua Ye
- Clinical Laboratory, Dongyang People's Hospital, Dongyang 322100, Zhejiang Province, China
| | - Xinling Pan
- Department of Biological Laboratory, Dongyang People's Hospital, Dongyang 322100, Zhejiang Province, China
| | - Li Hong
- Department of Infectious disease, Dongyang People's Hospital, Dongyang 322100, Zhejiang Province, China
| | - Yunzhen Shi
- Department of Infectious disease, Dongyang People's Hospital, Dongyang 322100, Zhejiang Province, China.
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11
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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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12
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Liu W, Tang JW, Mou JY, Lyu JW, Di YW, Liao YL, Luo YF, Li ZK, Wu X, Wang L. Rapid discrimination of Shigella spp. and Escherichia coli via label-free surface enhanced Raman spectroscopy coupled with machine learning algorithms. Front Microbiol 2023; 14:1101357. [PMID: 36970678 PMCID: PMC10030586 DOI: 10.3389/fmicb.2023.1101357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 02/20/2023] [Indexed: 03/11/2023] Open
Abstract
Shigella and enterotoxigenic Escherichia coli (ETEC) are major bacterial pathogens of diarrheal disease that is the second leading cause of childhood mortality globally. Currently, it is well known that Shigella spp., and E. coli are very closely related with many common characteristics. Evolutionarily speaking, Shigella spp., are positioned within the phylogenetic tree of E. coli. Therefore, discrimination of Shigella spp., from E. coli is very difficult. Many methods have been developed with the aim of differentiating the two species, which include but not limited to biochemical tests, nucleic acids amplification, and mass spectrometry, etc. However, these methods suffer from high false positive rates and complicated operation procedures, which requires the development of novel methods for accurate and rapid identification of Shigella spp., and E. coli. As a low-cost and non-invasive method, surface enhanced Raman spectroscopy (SERS) is currently under intensive study for its diagnostic potential in bacterial pathogens, which is worthy of further investigation for its application in bacterial discrimination. In this study, we focused on clinically isolated E. coli strains and Shigella species (spp.), that is, S. dysenteriae, S. boydii, S. flexneri, and S. sonnei, based on which SERS spectra were generated and characteristic peaks for Shigella spp., and E. coli were identified, revealing unique molecular components in the two bacterial groups. Further comparative analysis of machine learning algorithms showed that, the Convolutional Neural Network (CNN) achieved the best performance and robustness in bacterial discrimination capacity when compared with Random Forest (RF) and Support Vector Machine (SVM) algorithms. Taken together, this study confirmed that SERS paired with machine learning could achieve high accuracy in discriminating Shigella spp., from E. coli, which facilitated its application potential for diarrheal prevention and control in clinical settings.
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Affiliation(s)
- Wei Liu
- School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Jia-Wei Tang
- School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Laboratory Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
| | - Jing-Yi Mou
- The First School of Clinical Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Jing-Wen Lyu
- Laboratory Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
| | - Yu-Wei Di
- Laboratory Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
| | - Ya-Long Liao
- Laboratory Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
| | - Yan-Fei Luo
- Laboratory Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
| | - Zheng-Kang Li
- Laboratory Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
- *Correspondence: Zheng-Kang Li,
| | - Xiang Wu
- School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Xiang Wu,
| | - Liang Wang
- Laboratory Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
- Liang Wang,
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Barani M, Fathizadeh H, Arkaban H, Kalantar-Neyestanaki D, Akbarizadeh MR, Turki Jalil A, Akhavan-Sigari R. Recent Advances in Nanotechnology for the Management of Klebsiella pneumoniae-Related Infections. BIOSENSORS 2022; 12:1155. [PMID: 36551122 PMCID: PMC9776335 DOI: 10.3390/bios12121155] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 12/04/2022] [Accepted: 12/06/2022] [Indexed: 06/17/2023]
Abstract
Klebsiella pneumoniae is an important human pathogen that causes diseases such as urinary tract infections, pneumonia, bloodstream infections, bacteremia, and sepsis. The rise of multidrug-resistant strains has severely limited the available treatments for K. pneumoniae infections. On the other hand, K. pneumoniae activity (and related infections) urgently requires improved management strategies. A growing number of medical applications are using nanotechnology, which uses materials with atomic or molecular dimensions, to diagnose, eliminate, or reduce the activity of different infections. In this review, we start with the traditional treatment and detection method for K. pneumoniae and then concentrate on selected studies (2015-2022) that investigated the application of nanoparticles separately and in combination with other techniques against K. pneumoniae.
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Affiliation(s)
- Mahmood Barani
- Student Research Committee, Kerman University of Medical Sciences, Kerman 7616913555, Iran
- Medical Mycology and Bacteriology Research Center, Kerman University of Medical Sciences, Kerman 7616913555, Iran
| | - Hadis Fathizadeh
- Department of Laboratory Sciences, Sirjan School of Medical Sciences, Sirjan 7616916338, Iran
| | - Hassan Arkaban
- Department of Chemistry, University of Isfahan, Isfahan 8174673441, Iran
| | - Davood Kalantar-Neyestanaki
- Medical Mycology and Bacteriology Research Center, Kerman University of Medical Sciences, Kerman 7616913555, Iran
- Department of Medical Microbiology (Bacteriology and Virology), Afzalipour Faculty of Medicine, Kerman University of Medical Sciences, Kerman 7616913555, Iran
| | - Majid Reza Akbarizadeh
- Department of Pediatric, Amir Al Momenin Hospital, Zabol University of Medical Sciences, Zabol 9861663335, Iran
| | - Abduladheem Turki Jalil
- Medical Laboratories Techniques Department, Al-Mustaqbal University College, Babylon, Hilla 51001, Iraq
| | - Reza Akhavan-Sigari
- Department of Neurosurgery, University Medical Center Tuebingen, 72076 Tuebingen, Germany
- Department of Health Care Management and Clinical Research, Collegium Humanum Warsaw Management University, 00014 Warsaw, Poland
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