Comparison of pattern recognition techniques for the identification of lactic acid bacteria

Disposable all-printed electronic biosensor for instantaneous detection and classification of pathogens

A novel disposable all-printed electronic biosensor is proposed for a fast detection and classification of bacteria. This biosensor is applied to classify three types of popular pathogens: Salmonella typhimurium, and the Escherichia coli strains JM109 and DH5-α. The proposed sensor consists of inter-digital silver electrodes fabricated through an inkjet material printer and silver nanowires uniformly decorated on the electrodes through the electrohydrodynamic technique on a polyamide based polyethylene terephthalate substrate. The best sensitivity of the proposed sensor is achieved at 200 µm teeth spaces of the inter-digital electrodes along the density of the silver nanowires at 30 × 10³/mm². The biosensor operates on ±2.5 V and gives the impedance value against each bacteria type in 8 min after sample injection. The sample data are measured through an impedance analyzer and analyzed through pattern recognition methods such as linear discriminate analysis, maximum likelihood, and back propagation artificial neural network to classify each type of bacteria. A perfect classification and cross-validation is achieved by using the unique fingerprints extracted from the proposed biosensor through all the applied classifiers. The overall experimental results demonstrate that the proposed disposable all-printed biosensor is applicable for the rapid detection and classification of pathogens.

Rapid identification of dairy lactic acid bacteria by M13-generated, RAPD-PCR fingerprint databases

About a thousand lactic acid bacteria (LAB) isolated from dairy products, especially cheeses, were identified and typed by species-specific PCR and RAPD-PCR, respectively. RAPD-PCR profiles, which were obtained by using the M13 sequence as a primer, allowed us to implement a large database of different fingerprints, which were analysed by BioNumerics software. Cluster analysis of the combined RAPD-PCR fingerprinting profiles enabled us to implement a library, which is a collection of library units, which in turn is a selection of representative database entries. A library unit, in this case, can be considered to be a definable taxon. The strains belonged to 11 main RAPD-PCR fingerprinting library units identified as Lactobacillus casei/paracasei, Lactobacillus plantarum, Lactobacillus rhamnosus, Lactobacillus helveticus, Lactobacillus delbrueckii, Lactobacillus fermentum, Lactobacillus brevis, Enterococcus faecium, Enterococcus faecalis, Streptococcus thermophilus and Lactococcus lactis. The possibility to routinely identify newly typed, bacterial isolates by consulting the library of the software was valued. The proposed method could be suggested to refine previous strain identifications, eliminate redundancy and dispose of a technologically useful LAB strain collection. The same approach could also be applied to identify LAB strains isolated from other food ecosystems.

Clustering files of chemical structures using the fuzzy k-means clustering method

This paper evaluates the use of the fuzzy k-means clustering method for the clustering of files of 2D chemical structures. Simulated property prediction experiments with the Starlist file of logP values demonstrate that use of the fuzzy k-means method can, in some cases, yield results that are superior to those obtained with the conventional k-means method and with Ward's clustering method. Clustering of several small sets of agrochemical compounds demonstrate the ability of the fuzzy k-means method to highlight multicluster membership and to identify outlier compounds, although the former can be difficult to interpret in some cases.

Biodiversity among Lactobacillus helveticus strains isolated from different natural whey starter cultures as revealed by classification trees

Lactobacillus helveticus is a homofermentative thermophilic lactic acid bacterium used extensively for manufacturing Swiss type and aged Italian cheese. In this study, the phenotypic and genotypic diversity of strains isolated from different natural dairy starter cultures used for Grana Padano, Parmigiano Reggiano, and Provolone cheeses was investigated by a classification tree technique. A data set was used that consists of 119 L. helveticus strains, each of which was studied for its physiological characters, as well as surface protein profiles and hybridization with a species-specific DNA probe. The methodology employed in this work allowed the strains to be grouped into terminal nodes without difficult and subjective interpretation. In particular, good discrimination was obtained between L. helveticus strains isolated, respectively, from Grana Padano and from Provolone natural whey starter cultures. The method used in this work allowed identification of the main characteristics that permit discrimination of biotypes. In order to understand what kind of genes could code for phenotypes of technological relevance, evidence that specific DNA sequences are present only in particular biotypes may be of great interest.