Bacteria species identification by the statistical analysis of bacterial colonies Fresnel patterns

Suchwałko, Agnieszka; Buzalewicz, Igor; Wieliczko, Alina; Podbielska, Halina

doi:10.1364/oe.21.011322

Cited by 30 publications

(26 citation statements)

References 32 publications

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“…In addition, the proposed method can also be integrated in a portable platform for field measurements when it combines with in-line holography37. Both biological studies and biomedical applications, such as label-free species identification1738 of food pathogens, are expected to be further facilitated by the proposed aFTLS approach for measuring the 2D ALS patterns of individual bacteria.…”

Section: Discussionmentioning

confidence: 99%

Angle-resolved light scattering of individual rod-shaped bacteria based on Fourier transform light scattering

Jung

Lee

et al. 2014

Sci Rep

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Two-dimensional angle-resolved light scattering maps of individual rod-shaped bacteria are measured at the single-cell level. Using quantitative phase imaging and Fourier transform light scattering techniques, the light scattering patterns of individual bacteria in four rod-shaped species (Bacillus subtilis, Lactobacillus casei, Synechococcus elongatus, and Escherichia coli) are measured with unprecedented sensitivity in a broad angular range from −70° to 70°. The measured light scattering patterns are analyzed along the two principal axes of rod-shaped bacteria in order to systematically investigate the species-specific characteristics of anisotropic light scattering. In addition, the cellular dry mass of individual bacteria is calculated and used to demonstrate that the cell-to-cell variations in light scattering within bacterial species is related to the cellular dry mass and growth.

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Section: Discussionmentioning

confidence: 99%

Angle-resolved light scattering of individual rod-shaped bacteria based on Fourier transform light scattering

Jung

Lee

et al. 2014

Sci Rep

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“…In some restricted cases, the image processing can even provide a reliable bacteria identification, nevertheless this approach cannot be applied to a significant number of pathogens. The optical forward-scattering (OFS) 3 technique, that has been proposed as a label-free method for bacterial identification (Banada et al, , 2009Bae et al 2011b; Suchwalko et al 2013) is also based on image processing, but in this case the identification is done at the colony level and, under suitable conditions, it has been demonstrated that the colony can provide a reliable signature of the constituting bacterium at the serotype level (Rajwa et al 2006;Akova et al 2010;Buzalewicz et al, 2011). The OFS technique has been mainly investigated in the foodsafety field, however, due to its great potential its usage also in the clinical laboratory is worth to be investigated.…”

Section: Introductionmentioning

confidence: 99%

On the application of optical forward-scattering to bacterial identification in an automated clinical analysis perspective

Minoni

Signoroni

Nassini

2015

Biosensors and Bioelectronics

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The Optical Forward Scattering (OFS) technique can be used to identify pathogens by direct observation of bacteria colonies growing on a culture plate. The identification is based on the acquisition of scattering images from isolated colonies and their subsequent comparison with reference images acquired from known bacteria. The technique has been mainly studied for the identification of pathogens in the food-safety field. This paper focuses on the possibility of extending the applicability of the technique to the field of clinical laboratory automation. This scenario requires that the paradigm of image acquisition at fixed colony-dimension, well established in the food-safety applications, should be substituted by an acquisition at fixed incubation time. As a consequence, the scatterometer must be adjustable in real-time for adapting to the actual features of the bacterial colony. The paper describes an OFS system prototype qualified by the possibility to tune both the laser beam diameter and the acquisition camera field of view.Preliminary experiments on bacteria cultures from pathogens causing infections of the urinary tract show that the proposed approach is promising for the development of an Submitted to Biosensor and Bioelectronics 2 automated bacteria identification station. The new OFS approach also involves an alternative method for building a reference image database for subsequent image analysis.

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“…Despite the ability of these instrumental analytical techniques to obtain reliable and accurate results in the identification and classification of microorganisms, the use of digital images presents some advantages, since it has low-cost equipment, avoids the manipulation of the Petri plate where microorganisms are grown, and does not require the knowledge of a skillful microbiologist. In this sense, some works concerning image analysis have been proposed in the literature [18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

“…Suchwalko et al [21] identified bacteria species (Salmonella enteritidis, Staphylococcus aureus, Staphylococcus intermedius, E. coli, Proteus mirabilis, Pseudomonas aeruginosa, and Citrobacter freundii) based on their colonies' Fresnel diffraction patterns recorded in an optical system with converging spherical wave illumination. The proposed method used image processing and statistical analysis based on feature extraction, feature selection, and classification methods, reaching 98 % identification accuracy in 36 h from sample acquiring.…”

Section: Introductionmentioning

confidence: 99%

Using color histograms and SPA-LDA to classify bacteria

et al. 2014

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In this work, a new approach is proposed to verify the differentiating characteristics of five bacteria (Escherichia coli, Enterococcus faecalis, Streptococcus salivarius, Streptococcus oralis, and Staphylococcus aureus) by using digital images obtained with a simple webcam and variable selection by the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA). In this sense, color histograms in the red-green-blue (RGB), hue-saturation-value (HSV), and grayscale channels and their combinations were used as input data, and statistically evaluated by using different multivariate classifiers (Soft Independent Modeling by Class Analogy (SIMCA), Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA), Partial Least Squares Discriminant Analysis (PLS-DA) and Successive Projections Algorithm-Linear Discriminant Analysis (SPA-LDA)). The bacteria strains were cultivated in a nutritive blood agar base layer for 24 h by following the Brazilian Pharmacopoeia, maintaining the status of cell growth and the nature of nutrient solutions under the same conditions. The best result in classification was obtained by using RGB and SPA-LDA, which reached 94 and 100 % of classification accuracy in the training and test sets, respectively. This result is extremely positive from the viewpoint of routine clinical analyses, because it avoids bacterial identification based on phenotypic identification of the causative organism using Gram staining, culture, and biochemical proofs. Therefore, the proposed method presents inherent advantages, promoting a simpler, faster, and low-cost alternative for bacterial identification.

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Bacteria species identification by the statistical analysis of bacterial colonies Fresnel patterns

Cited by 30 publications

References 32 publications

Angle-resolved light scattering of individual rod-shaped bacteria based on Fourier transform light scattering

Angle-resolved light scattering of individual rod-shaped bacteria based on Fourier transform light scattering

On the application of optical forward-scattering to bacterial identification in an automated clinical analysis perspective

Using color histograms and SPA-LDA to classify bacteria

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