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Abo Dena AS, Nejmedine Machraoui A, Mizaikoff B. Intelligent Microcontroller-Based Infrared Attenuated Total Reflection Spectroscopy for High-Throughput Screening and Discrimination of Foodborne Fungi. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 323:124936. [PMID: 39142262 DOI: 10.1016/j.saa.2024.124936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Revised: 07/31/2024] [Accepted: 08/03/2024] [Indexed: 08/16/2024]
Abstract
Food safety became one of the most critical issues owing to the large expansion of international trading and emission of various pollutants in air, water and soil. Fungal contamination of food and feed has attracted most of the attention in the last decade because of the emerging analytical tools that facilitate the detection and discrimination of fungal species in imported foodstuff, seeds, grains, plants, meats …etc. In this work, we give an insight on the application of integrated attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy and artificial-intelligence algorithms to the determination and discrimination of fungal species/strains which potentially infect plants, seeds and grains. The proposed method is based on a microcontroller which allows the PC to analyze a large number of samples via serial connection with an UART module. Penicillium chrysogenum, Aspergillus niger, Aspergillus fumigatus, Aspergillus solani, Aspergillus flavus and two different strains of Fusarium oxysporum were used as model microorganisms. The use of artificial-intelligence algorithms herein provides the advantage of automation enabling high throughput screening of large numbers of food samples in less than 5 s. In addition, the classification accuracy is enhanced by applying these machine-learning classification techniques. Principle component analysis (PCA) was used in order to extract the spectral discriminative features from the recorded fungal FTIR spectra. Three intelligent methods of classification; namely, artificial neural network (ANN), support-vector machine (SVM) and k-nearest neighbor (KNN), were used in this study in order to prove that integration of spectroscopic measurements with varying machine-learning methods give a simple analytical tool for detection and classification of foodborne pathogens. All the utilized classifiers gave an accuracy of 100 % and were able to discriminate different species and/or strains of the investigated fungi in few milliseconds.
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Affiliation(s)
- Ahmed S Abo Dena
- Pharmaceutical Chemistry Department, National Organization for Drug Control and Research (NODCAR), P.O. Box 29, Giza, Egypt; Faculty of Oral and Dental Medicine, Future University in Egypt, New Cairo, Egypt; Institute of Analytical and Bioanalytical Chemistry, Ulm University, 89081 Ulm, Germany
| | | | - Boris Mizaikoff
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, 89081 Ulm, Germany; Hahn-Schickard, 89077 Ulm, Germany.
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Fransson P, Robertson AHJ, Campbell CD. Carbon availability affects already large species-specific differences in chemical composition of ectomycorrhizal fungal mycelia in pure culture. MYCORRHIZA 2023; 33:303-319. [PMID: 37824023 PMCID: PMC10752919 DOI: 10.1007/s00572-023-01128-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 09/27/2023] [Indexed: 10/13/2023]
Abstract
Although ectomycorrhizal (ECM) contribution to soil organic matter processes receives increased attention, little is known about fundamental differences in chemical composition among species, and how that may be affected by carbon (C) availability. Here, we study how 16 species (incl. 19 isolates) grown in pure culture at three different C:N ratios (10:1, 20:1, and 40:1) vary in chemical structure, using Fourier transform infrared (FTIR) spectroscopy. We hypothesized that C availability impacts directly on chemical composition, expecting increased C availability to lead to more carbohydrates and less proteins in the mycelia. There were strong and significant effects of ECM species (R2 = 0.873 and P = 0.001) and large species-specific differences in chemical composition. Chemical composition also changed significantly with C availability, and increased C led to more polysaccharides and less proteins for many species, but not all. Understanding how chemical composition change with altered C availability is a first step towards understanding their role in organic matter accumulation and decomposition.
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Affiliation(s)
- Petra Fransson
- Department of Forest Mycology and Plant Pathology, Uppsala BioCenter, Swedish University of Agricultural Sciences, PO Box 7026, SE-750 07, Uppsala, Sweden.
| | - A H Jean Robertson
- The James Hutton Institute, Craigiebuckler, Aberdeen, AB15 8QH, Scotland
| | - Colin D Campbell
- The James Hutton Institute, Craigiebuckler, Aberdeen, AB15 8QH, Scotland
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Abu-Aqil G, Tsror L, Shufan E, Adawi S, Mordechai S, Huleihel M, Salman A. Differentiation of Pectobacterium and Dickeya spp. phytopathogens using infrared spectroscopy and machine learning analysis. JOURNAL OF BIOPHOTONICS 2020; 13:e201960156. [PMID: 32030907 DOI: 10.1002/jbio.201960156] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 12/10/2019] [Accepted: 02/01/2020] [Indexed: 05/23/2023]
Abstract
Pectobacterium and Dickeya spp. are soft rot Pectobacteriaceae that cause aggressive diseases on agricultural crops leading to substantial economic losses. The accurate, rapid and low-cost detection of these pathogenic bacteria are very important for controlling their spread, reducing the consequent financial loss and for producing uninfected potato seed tubers for future generations. Currently used methods for the identification of these bacterial pathogens at the strain level are based mainly on molecular techniques, which are expensive. We used an alternative method, infrared spectroscopy, to measure 24 strains of five species of Pectobacterium and Dickeya. Measurements were then analyzed using machine learning methods to differentiate among them at the genus, species and strain levels. Our results show that it is possible to differentiate among different bacterial pathogens with a success rate of ~99% at the genus and species levels and with a success rate of over 94% at the strain level.
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Affiliation(s)
- George Abu-Aqil
- Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Leah Tsror
- Department of Plant Pathology, Institute of Plant Protection, Agricultural Research Organization, Gilat Research Center, Negev, Israel
| | - Elad Shufan
- Department of Physics, Shamoon College of Engineering, Beer-Sheva, Israel
| | - Samar Adawi
- Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Shaul Mordechai
- Department of Physics, Ben-Gurion University, Beer-Sheva, Israel
| | - Mahmoud Huleihel
- Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ahmad Salman
- Department of Physics, Shamoon College of Engineering, Beer-Sheva, Israel
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Sharaha U, Rodriguez-Diaz E, Sagi O, Riesenberg K, Salman A, Bigio IJ, Huleihel M. Fast and reliable determination of Escherichia coli susceptibility to antibiotics: Infrared microscopy in tandem with machine learning algorithms. JOURNAL OF BIOPHOTONICS 2019; 12:e201800478. [PMID: 30916881 DOI: 10.1002/jbio.201800478] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 03/12/2019] [Accepted: 03/25/2019] [Indexed: 06/09/2023]
Abstract
Antimicrobial drugs have an important role in controlling bacterial infectious diseases. However, the increasing resistance of bacteria to antibiotics has become a global health care problem. Rapid determination of antimicrobial susceptibility of clinical isolates is often crucial for the optimal antimicrobial therapy. The conventional methods used in medical centers for susceptibility testing are time-consuming (>2 days). Two bacterial culture steps are needed, the first is used to grow the bacteria from urine on agar plates to determine the species of the bacteria (~24 hours). The second culture is used to determine the susceptibility by growing colonies from the first culture for another 24 hours. Here, the main goal is to examine the potential of infrared microscopy combined with multivariate analysis, to reduce the time it takes to identify Escherichia coli susceptibility to antibiotics and to determine the optimum choice of antibiotic to which the bacteria will respond. E coli colonies of the first culture from patients with urinary tract infections (UTI) were examined for the bacterial susceptibility using Fourier-transform infrared (FTIR). Our results show that it is possible to determine the optimum choice of antibiotic with better than 89% sensitivity, in the time span of few minutes, following the first culture.
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Affiliation(s)
- Uraib Sharaha
- Department of Microbiology, Immunology and Genetic, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Eladio Rodriguez-Diaz
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
- Section of Gastroenterology, VA Boston Healthcare System, Boston, Massachusetts
| | - Orli Sagi
- Microbiology Laboratory, Soroka University Medical Center, Beer-Sheva, Israel
| | - Klaris Riesenberg
- Infectious Diseases Department, Soroka University Medical Center, Beer-Sheva, Israel
| | - Ahmad Salman
- Department of Physics, SCE-Shamoon College of Engineering, Beer-Sheva, Israel
| | - Irving J Bigio
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
- Department of Electrical & Computer Engineering, Boston University, Boston, Massachusetts
| | - Mahmoud Huleihel
- Department of Microbiology, Immunology and Genetic, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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Sharaha U, Rodriguez-Diaz E, Sagi O, Riesenberg K, Lapidot I, Segal Y, Bigio IJ, Huleihel M, Salman A. Detection of Extended-Spectrum β-Lactamase-Producing Escherichia coli Using Infrared Microscopy and Machine-Learning Algorithms. Anal Chem 2019; 91:2525-2530. [DOI: 10.1021/acs.analchem.8b05497] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
| | | | - Orli Sagi
- Director of Microbiology Laboratory, Soroka University Medical Center, Beer-Sheva 84105, Israel
| | | | - Itshak Lapidot
- Department of Electrical and Electronics Engineering, ACLP-Afeka Center for Language Processing, Afeka Tel-Aviv Academic College of Engineering, Tel-Aviv 69107, Israel
| | | | | | | | - Ahmad Salman
- Department of Physics, SCE - Shamoon College of Engineering, Beer-Sheva 84100, Israel
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Huleihel M, Shufan E, Tsror L, Sharaha U, Lapidot I, Mordechai S, Salman A. Differentiation of mixed soil-borne fungi in the genus level using infrared spectroscopy and multivariate analysis. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY B-BIOLOGY 2018; 180:155-165. [PMID: 29433053 DOI: 10.1016/j.jphotobiol.2018.02.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Revised: 01/24/2018] [Accepted: 02/06/2018] [Indexed: 01/31/2023]
Abstract
Early detection of soil-borne pathogens, which have a negative effect on almost all agricultural crops, is crucial for effective targeting with the most suitable antifungal agents and thus preventing and/or reducing their severity. They are responsible for severe diseases in various plants, leading in many cases to substantial economic losses. In this study, infrared (IR) spectroscopic method, which is known as sensitive, accurate and rapid, was used to discriminate between different fungi in a mixture was evaluated. Mixed and pure samples of Colletotrichum, Verticillium, Rhizoctonia, and Fusarium genera were measured using IR microscopy. Our spectral results showed that the best differentiation between pure and mixed fungi was obtained in the 675-1800 cm-1 wavenumber region. Principal components analysis (PCA), followed by linear discriminant analysis (LDA) as a linear classifier, was performed on the spectra of the measured classes. Our results showed that it is possible to differentiate between mixed-calculated categories of phytopathogens with high success rates (~100%) when the mixing percentage range is narrow (40-60) in the genus level; when the mixing percentage range is wide (10-90), the success rate exceeded 85%. Also, in the measured mixed categories of phytopathogens it is possible to differentiate between the different categories with ~100% success rate.
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Affiliation(s)
- M Huleihel
- Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel.
| | - E Shufan
- Department of Physics, SCE-Sami Shamoon College of Engineering, Beer-Sheva 84100, Israel
| | - L Tsror
- Department of Plant Pathology, Institute of Plant Protection, Agricultural Research Organization, Gilat Research Center, M.P. Negev 85250, Israel
| | - U Sharaha
- Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - I Lapidot
- Department of Electrical and Electronics Engineering, ACLP-Afeka Center for Language Processing, Afeka Tel-Aviv Academic College of Engineering, Israel
| | - S Mordechai
- Department of Physics, Ben-Gurion University, Beer-Sheva 84105, Israel
| | - A Salman
- Department of Physics, SCE-Sami Shamoon College of Engineering, Beer-Sheva 84100, Israel.
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Sahu RK, Salman A, Mordechai S. Tracing overlapping biological signals in mid-infrared using colonic tissues as a model system. World J Gastroenterol 2017; 23:286-296. [PMID: 28127202 PMCID: PMC5236508 DOI: 10.3748/wjg.v23.i2.286] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2016] [Revised: 10/19/2016] [Accepted: 11/16/2016] [Indexed: 02/06/2023] Open
Abstract
AIM To understand the interference of carbohydrates absorbance in nucleic acids signals during diagnosis of malignancy using Fourier transform infrared (FTIR) spectroscopy.
METHODS We used formalin fixed paraffin embedded colonic tissues to obtain infrared (IR) spectra in the mid IR region using a bruker II IR microscope with a facility for varying the measurement area by varying the aperture available. Following this procedure we could measure different regions of the crypt circles containing different biochemicals. Crypts from 18 patients were measured. Circular crypts with a maximum diameter of 120 μm and a lumen of about 30 μm were selected for uniformity. The spectral data was analyzed using conventional and advanced computational methods.
RESULTS Among the various components that are observed to contribute to the diagnostic capabilities of FTIR, the carbohydrates and nucleic acids are prominent. However there are intrinsic difficulties in the diagnostic capabilities due to the overlap of major absorbance bands of nucleic acids, carbohydrates and phospholipids in the mid-IR region. The result demonstrates colonic tissues as a biological system suitable for studying interference of carbohydrates and nucleic acids under ex vivo conditions. Among the diagnostic parameters that are affected by the absorbance from nucleic acids is the RNA/DNA ratio, dependent on absorbance at 1121 cm-1 and 1020 cm-1 that is used to classify the normal and cancerous tissues especially during FTIR based diagnosis of colonic malignancies. The signals of the nucleic acids and the ratio (RNA/DNA) are likely increased due to disappearance of interfering components like carbohydrates and phosphates along with an increase in amount of RNA.
CONCLUSION The present work, proposes one mechanism for the observed changes in the nucleic acid absorbance in mid-IR during disease progression (carcinogenesis).
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Salman A, Shufan E, Lapidot I, Tsror L, Moreh R, Mordechai S, Huleihel M. Assignment of Colletotrichum coccodes isolates into vegetative compatibility groups using infrared spectroscopy: a step towards practical application. Analyst 2015; 140:3098-106. [DOI: 10.1039/c5an00213c] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
FTIR spectroscopy may provide a specific, rapid, and inexpensive method for the successful classification of Colletotrichum coccodes isolates into vegetative compatibility groups.
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Affiliation(s)
- A. Salman
- Department of Physics
- SCE – Shamoon College of Engineering
- Beer-Sheva 84100
- Israel
| | - E. Shufan
- Department of Physics
- SCE – Shamoon College of Engineering
- Beer-Sheva 84100
- Israel
| | - I. Lapidot
- Department of Electrical and Electronics Engineering ACLP-Afeka Center for Language Processing
- Afeka. Tel-Aviv Academic College of Engineering
- Israel
| | - L. Tsror
- Department of Plant Pathology
- Institute of Plant Protection
- Agricultural Research Organization
- Gilat Research Center
- M.P. Negev
| | - R. Moreh
- Department of Physics
- Ben-Gurion University of the Negev
- Beer-Sheva 84105
- Israel
| | - S. Mordechai
- Department of Physics
- Ben-Gurion University of the Negev
- Beer-Sheva 84105
- Israel
| | - M. Huleihel
- Department of Microbiology
- Immunology and Genetics
- Faculty of Health Sciences
- Ben-Gurion University of the Negev
- Beer-Sheva 84105
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Characterization of Phytophthora infestans resistance to mefenoxam using FTIR spectroscopy. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY B-BIOLOGY 2014; 141:308-14. [DOI: 10.1016/j.jphotobiol.2014.10.005] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2014] [Revised: 10/06/2014] [Accepted: 10/11/2014] [Indexed: 11/21/2022]
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Classification of Colletotrichum coccodes isolates into vegetative compatibility groups using infrared attenuated total reflectance spectroscopy and multivariate analysis. Methods 2014; 68:325-30. [DOI: 10.1016/j.ymeth.2014.02.021] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2013] [Revised: 01/18/2014] [Accepted: 02/15/2014] [Indexed: 11/21/2022] Open
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