Computer-based classification of bacteria species by analysis of their colonies Fresnel diffraction patterns

In the presented paper the optical system with converging spherical wave illumination for classification of bacteria species, is proposed. It allows for compression of the observation space, observation of Fresnel patterns, diffraction pattern scaling and low level of optical aberrations, which are not possessed by other optical configurations. Obtained experimental results have shown that colonies of specific bacteria species generate unique diffraction signatures. Analysis of Fresnel diffraction patterns of bacteria colonies can be fast and reliable method for classification and recognition of bacteria species. To determine the unique features of bacteria colonies diffraction patterns the image processing analysis was proposed. Classification can be performed by analyzing the spatial structure of diffraction patterns, which can be characterized by set of concentric rings. The characteristics of such rings depends on the bacteria species. In the paper, the influence of basic features and ring partitioning number on the bacteria classification, is analyzed. It is demonstrated that Fresnel patterns can be used for classification of following species: Salmonella enteritidis, Staplyococcus aureus, Proteus mirabilis and Citrobacter freundii. Image processing is performed by free ImageJ software, for which a special macro with human interaction, was written. LDA classification, CV method, ANOVA and PCA visualizations preceded by image data extraction were conducted using the free software R.

[1]  J. Saarela,et al.  Instrumentation for measuring fluorescence cross sections from airborne microsized particles. , 2008, Applied optics.

[2]  Katarzyna Wysocka-Król,et al.  Evaluation of Antibacterial Agents Activity , 2010 .

[3]  S. Levy,et al.  The challenge of antibiotic resistance. , 1998, Scientific American.

[4]  Michael D. Abràmoff,et al.  Image processing with ImageJ , 2004 .

[5]  P. Wyatt Differential light scattering: a physical method for identifying living bacterial cells. , 1968, Applied optics.

[6]  Weihong Tan,et al.  Ultrasensitive detection of biomolecules with fluorescent dye-doped nanoparticles. , 2004, Analytical biochemistry.

[7]  Halina Podbielska,et al.  Influence of various growth conditions on Fresnel diffraction patterns of bacteria colonies examined in the optical system with converging spherical wave illumination. , 2011, Optics express.

[8]  B V Bronk,et al.  Fluorescence from airborne microparticles: dependence on size, concentration of fluorophores, and illumination intensity. , 2001, Applied optics.

[9]  Yong-Le Pan,et al.  Angularly resolved light scattering from aerosolized spores: observations and calculations. , 2007, Optics letters.

[10]  David Sands,et al.  Emission wavelength dependence of fluorescence lifetimes of bacteriological spores and pollens. , 2006, Applied optics.

[11]  Avraham Rasooly,et al.  Spectral surface plasmon resonance biosensor for detection of staphylococcal enterotoxin B in milk. , 2002, International journal of food microbiology.

[12]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[13]  D. Rosen,et al.  Bacterial Endospore Detection Using Photoluminescence from Terbium Dipicolinate , 1999 .

[14]  Lou Reinisch,et al.  Two-dimensional multiwavelength fluorescence spectra of dipicolinic acid and calcium dipicolinate. , 2005, Applied optics.

[15]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[16]  J. Paul Robinson,et al.  High speed classification of individual bacterial cells using a model-based light scatter system and multivariate statistics. , 2008, Applied optics.

[17]  Rolph E. Anderson,et al.  Multivariate Data Analysis (7th ed. , 2009 .

[18]  Anne-Marie Nicol,et al.  Communicating the Risks of a New, Emerging Pathogen: The Case of Cryptococcus gattii , 2008, Risk analysis : an official publication of the Society for Risk Analysis.

[19]  S. Weisberg,et al.  A review of technologies for rapid detection of bacteria in recreational waters. , 2005, Journal of water and health.

[20]  S. Levy,et al.  Antibacterial resistance worldwide: causes, challenges and responses , 2004, Nature Medicine.

[21]  Yong-Le Pan,et al.  Multivariate analysis and classification of two-dimensional angular optical scattering patterns from aggregates. , 2004, Applied optics.

[22]  S. Amyes,et al.  The rise in bacterial resistance , 2000, BMJ : British Medical Journal.

[23]  J. Paul Robinson,et al.  Optical forward-scattering for detection of Listeria monocytogenes and other Listeria species. , 2007, Biosensors & bioelectronics.

[24]  E Hirst,et al.  Simultaneous light scattering and intrinsic fluorescence measurement for the classification of airborne particles. , 2000, Applied optics.

[25]  Euiwon Bae,et al.  On the sensitivity of forward scattering patterns from bacterial colonies to media composition , 2011, Journal of biophotonics.

[26]  Dmitri Ivnitski,et al.  Biosensors for detection of pathogenic bacteria , 1999 .

[27]  L. Radziemski From LASER to LIBS, the path of technology development , 2002 .

[28]  K Christen Bioterrorism and waterborne pathogens: how big is the threat? , 2001, Environmental science & technology.

[29]  Halina Podbielska,et al.  Exploiting of optical transforms for bacteria evaluation in vitro , 2009, European Conference on Biomedical Optics.

[30]  Yong-Le Pan,et al.  Simultaneous forward- and backward-hemisphere elastic-light-scattering patterns of respirable-size aerosols. , 2006, Optics letters.

[31]  S. C. Hill,et al.  Single-shot fluorescence spectra of individual micrometer-sized bioaerosols illuminated by a 351- or a 266-nm ultraviolet laser. , 1999, Optics letters.

[32]  Weihong Tan,et al.  Using bioconjugated nanoparticles to monitor E. coli in a flow channel. , 2006, Chemistry, an Asian journal.

[33]  Robert Tibshirani,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.

[34]  R. Kirsner,et al.  Analysis of antibiotic susceptibilities of skin wound flora in hospitalized dermatology patients. The crisis of antibiotic resistance has come to the surface. , 1998, Archives of dermatology.

[35]  Alan C. Samuels,et al.  Classification of Select Category A and B Bacteria by Fourier Transform Infrared Spectroscopy , 2008, SPIE Defense + Commercial Sensing.

[36]  Yong-Le Pan,et al.  Characterizing and monitoring respiratory aerosols by light scattering. , 2003, Optics letters.

[37]  D. Rosen,et al.  Airborne bacterial endospores detected by use of an impinger containing aqueous terbium chloride. , 2006, Applied optics.

[38]  Philippe Adam,et al.  Detection of bacteria by time-resolved laser-induced breakdown spectroscopy. , 2003, Applied optics.

[39]  J. Paul Robinson,et al.  Modeling light propagation through bacterial colonies and its correlation with forward scattering patterns. , 2010, Journal of biomedical optics.

[40]  R. Leclercq,et al.  Bacterial resistance to macrolide, lincosamide, and streptogramin antibiotics by target modification , 1991, Antimicrobial Agents and Chemotherapy.

[41]  Katarzyna Wysocka-Król,et al.  Image processing guided analysis for estimation of bacteria colonies number by means of optical transforms. , 2010, Optics express.

[42]  J. Paul Robinson,et al.  Label-free detection of multiple bacterial pathogens using light-scattering sensor. , 2009, Biosensors & bioelectronics.

[43]  Paul Leonard,et al.  A generic approach for the detection of whole Listeria monocytogenes cells in contaminated samples using surface plasmon resonance. , 2004, Biosensors & bioelectronics.

[44]  Joseph Irudayaraj,et al.  A mixed self-assembled monolayer-based surface plasmon immunosensor for detection of E. coli O157:H7. , 2006, Biosensors & bioelectronics.

[45]  J. Paul Robinson,et al.  Analysis of time-resolved scattering from macroscale bacterial colonies. , 2008, Journal of biomedical optics.