Comparison of statistical methods for identification of Streptococcus thermophilus, Enterococcus faecalis, and Enterococcus faecium from randomly amplified polymorphic DNA patterns

Phenotypic and genotypic heterogeneity of Enterococcus species isolated from food in Southern Brazil

Enterococcus is an important group of lactic acid bacteria (LAB), which inhabits the gastrointestinal tract of humans and animals. These microorganisms can also be found in large groups of foods where they can play a beneficial role during food maturation processes or, conversely, can be used as a food contamination indicator. These microorganisms have an additional importance in various aspects of clinical microbiology. The aim of this study was to investigate and determine the phenotypic and genetic diversity in 55 enterococci isolated from different food sources. Phenotypic characteristics based upon substrate hydrolysis differences were used to identify different Enterococcus species. Analysis of the resultant data divided these species into eight Enterococcus phenotype groups. E. faecalis was the food isolate species with the greatest phenotypic variability. Fifty-five previously isolated Enterococcus strains were re-confirmed as belonging to this genus by PCR techniques. Randomly amplified polymorphic DNA (RAPD-PCR) was used to study the genetic variability using M13 primers and the resultant DNA fragments produced a database of different fingerprints. After statistical analyses of the RAPD-PCR profiles, 42 patterns were obtained and 6 different Enterococcus RAPD clusters (ERC) were identified. Genetic diversity was highest in ERC I, which grouped together approximately 40% of the E. faecium and E. faecalis isolates obtained from dairy products. Samples isolated from meat and vegetables offered the greatest genotype variability. Results of the present study suggest the presence of both phenotypic and genotypic variability within enterococci strains isolated from diverse sources of food common to Southern Brazil.

Use of unsupervised and supervised artificial neural networks for the identification of lactic acid bacteria on the basis of SDS-PAGE patterns of whole cell proteins

Conventional multivariate statistical techniques (hierarchical cluster analysis, linear discriminant analysis) and unsupervised (Kohonen Self Organizing Map) and supervised (Bayesian network) artificial neural networks were compared for as tools for the classification and identification of 352 SDS-PAGE patterns of whole cell proteins of lactic acid bacteria belonging to 22 species of the genera Lactobacillus, Leuconostoc, Enterococcus, Lactococcus and Streptococcus including 47 reference strains. Electrophoretic data were pre-treated using the logistic weighting function described by Piraino et al. [Piraino, P., Ricciardi, A., Lanorte, M. T., Malkhazova, I., Parente, E., 2002. A new procedure for data reduction in electrophoretic fingerprints of whole-cell proteins. Biotechnol. Lett. 24, 1477-1482]. Hierarchical cluster analysis provided a satisfactory classification of the patterns but was unable to discriminate some species (Leuconostoc, Lb. sakei/Lb. curvatus, Lb. acidophilus/Lb. helveticus, Lb. plantarum/Lb. paraplantarum, Lc. lactis/Lc. raffinolactis). A 7x7 Kohonen self-organizing map (KSOM), trained with the patterns of the reference strains, provided a satisfactory classification of the patterns and was able to discriminate more species than hierarchical cluster analysis. The map was used in predictive mode to identify unknown strains and provided results which in 85.5% of cases matched the classification obtained by hierarchical cluster analysis. Two supervised tools, linear discriminant analysis and a 23:5:2 Bayesian network were proven to be highly effective in the discrimination of SDS-PAGE patterns of Lc. lactis from those of other species. We conclude that data reduction by logistic weighting coupled to traditional multivariate statistical analysis or artificial neural networks provide an effective tool for the classification and identification of lactic acid bacteria on the basis of SDS-PAGE patterns of whole cell proteins.

Artificial neural network based identification of Campylobacter species by Fourier transform infrared spectroscopy

Two prototypes of artificial neural network (ANN), multilayer perceptron (MLP), and probabilistic neural network (PNN), were used to analyze infrared (IR) spectral data obtained from intact cells belonging to the species Campylobacter coli and Campylobacter jejuni. In order to establish a consistent identification and typing procedure, mid infrared spectra of these species were obtained by means of a Fourier transform infrared (FT-IR) spectroscope. FT-IR patterns belonging to 26 isolates subclassified into 4 genotypes were pre-processed (normalized, smoothed and derivatized) and grouped into training, verification and test sets. The two architectures tested (PNN, MLP) were developed and trained to identify or leave unassigned a number of IR patterns. Two window ranges (w(4), 1200 to 900 cm(-1); and w(5), 900 to 700 cm(-1)) in the mid IR spectrum were presented as input to the ANN models functioning as pattern recognition systems. No matter the ANN used all the training sets were correctly identified at subspecies level. For the test set, the four-layer MLP network was found to be specially suitable to recognize FT-IR data since it correctly identified 99.16% of unknowns using the w(4) range, and was fully successful in detecting atypical patterns from closely related Campylobacter strains and other bacterial species. The PNN network obtained lower percentages in assignation and rejection. Overall, ANNs constitute an excellent mathematical tool in microbial identification, since they are able to recognize with a high degree of confidence typical as well as atypical FT-IR fingerprints from Campylobacter spp.

Molecular characterization of lactic acid bacteria from sourdough breads produced in Sardinia (Italy) and multivariate statistical analyses of results

The objective of this work was to investigate the structure and diversity of lactic acid bacteria (LAB) communities in sourdough used for the production of traditional breads (Carasau, Moddizzosu, Spianata, Zichi) in Sardinia. 16S rDNA sequencing and Randomly Amplified Polymorphic DNA (RAPD-PCR) was applied for the identification and typing of the LAB isolated from 25 samples of sourdoughs. Multivariate statistical techniques were applied to RAPD-PCR pattern to study the biological diversity of sourdough samples. Twelve different species of LAB were identified, and most isolates were classified as facultative heterofermentative lactobacilli. Lactobacillus pentosus dominated the lactic microflora of many samples while Lactobacillus sanfranciscensis was isolated only from a limited number of samples. Although heterofermentative species represented between between 30% and 60% of the isolates in Carasau, Spianata and Zichi sourdoughs, only 2% of the isolates from Moddizzosu sourdoughs were identified as heterofermentative LAB. RAPD-PCR with a single primer followed by cluster analysis did not allow the identification of the isolates at the species level. However, a multidimensional scaling/bootstrapping approach on the RAPD-PCR patterns uncovered the diversity of the LAB communities of LAB showing differences both within and between bread types.

Improved strategy for comparing microbial assemblage fingerprints

Microbial fingerprinting techniques permit the rapid visualization of entire assemblages in single assays, allowing direct comparison of communities in different samples, where the null hypothesis of such analyses is that all samples are the same. The comparison of fingerprints relies upon the precise estimation of all amplified DNA fragment lengths, which correspond to operational taxonomic units (OTU; analogous, but not equal to, a taxon in macroorganism studies). However, computer interpolation of size standards (and consequently OTU size calling) can be imprecise between gel runs, which can lead to imprecise calculation of similarity indices between multiple assemblages. To account for OTU size calling imprecision, all fragments within a range of sizes (a window) can be combined (i.e., "binned") where the window is as wide as the imprecision of OTU size calling. However, artifacts may occur upon binning samples that may cause samples to appear less similar to each other, caused by splitting of OTU between adjacent bin windows. In this work we present an improved binning technique that accounts for OTU size calling imprecision in the comparison of multiple fingerprints. This technique comprises binning all pairwise comparisons in multiple bin window frames, where the starting size of the window (i.e., frame) is shifted by +1 bp for a total of x frames, where x bp is the width of the maximum bin window size in any binning scheme. Pairwise similarity indices between different community fingerprints are calculated for each of the x frames. To best address the null hypothesis of the community comparison, the maximum similarity value of all x frames is then used in downstream analyses to compare the communities. We believe this binning technique provides the most accurate and least biased comparison between different microbial fingerprints.

Molecular and biochemical analysis of the galactose phenotype of dairy Streptococcus thermophilus strains reveals four different fermentation profiles

Lactose-limited fermentations of 49 dairy Streptococcus thermophilus strains revealed four distinct fermentation profiles with respect to galactose consumption after lactose depletion. All the strains excreted galactose into the medium during growth on lactose, except for strain IMDOST40, which also displayed extremely high galactokinase (GalK) activity. Among this strain collection eight galactose-positive phenotypes sensu stricto were found and their fermentation characteristics and Leloir enzyme activities were measured. As the gal promoter seems to play an important role in the galactose phenotype, the galR-galK intergenic region was sequenced for all strains yielding eight different nucleotide sequences (NS1 to NS8). The gal promoter played an important role in the Gal-positive phenotype but did not determine it exclusively. Although GalT and GalE activities were detected for all Gal-positive strains, GalK activity could only be detected for two out of eight Gal-positive strains. This finding suggests that the other six S. thermophilus strains metabolize galactose via an alternative route. For each type of fermentation profile obtained, a representative strain was chosen and four complete Leloir gene clusters were sequenced. It turned out that Gal-positive strains contained more amino acid differences within their gal genes than Gal-negative strains. Finally, the biodiversity regarding lactose-galactose utilization among the different S. thermophilus strains used in this study was shown by RAPD-PCR. Five Gal-positive strains that contain nucleotide sequence NS2 in their galR-galK intergenic region were closely related.

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.

Methods used for the isolation, enumeration, characterisation and identification of Enterococcus spp

This paper reviews the methodology applied for the identification and characterisation of enterococci and covers phenotypic, genotypic and phylogenetic techniques. Although conventional phenotypic typing schemes are useful for rapid and simple identification of enterococcal species for routine applications, other methods like standardised sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE), multilocus enzyme electrophoresis (MLEE), antimicrobial susceptibility testing, serotyping, pyrolysis mass spectrometry (pyMS) and vibrational spectroscopic methods allow a more in-depth characterisation of enterococci. Many of the recently described enterococcal species exhibit deviations from hitherto so-called classical enterococci with regard to their phenotypical properties. Therefore, genotypic methods have to be used to clarify their possible assignment to the genus Enterococcus. In this review, special emphasis is given on recently developed polymerase chain reaction (PCR)-based typing methods such as random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), specific and random amplification (SARA) and modifications of PCR-ribotyping as well as pulsed-field gel electrophoresis (PFGE) and partial sequence analysis. The use of PCR and probes for genus and species identification of enterococci is also considered like the application of sequence data of conserved DNA regions (e.g., ribosomal ribonucleic acid (rRNA) genes) in the case of species identification.

Optimization of single-base-pair mismatch discrimination in oligonucleotide microarrays

The discrimination between perfect-match and single-base-pair-mismatched nucleic acid duplexes was investigated by using oligonucleotide DNA microarrays and nonequilibrium dissociation rates (melting profiles). DNA and RNA versions of two synthetic targets corresponding to the 16S rRNA sequences of Staphylococcus epidermidis (38 nucleotides) and Nitrosomonas eutropha (39 nucleotides) were hybridized to perfect-match probes (18-mer and 19-mer) and to a set of probes having all possible single-base-pair mismatches. The melting profiles of all probe-target duplexes were determined in parallel by using an imposed temperature step gradient. We derived an optimum wash temperature for each probe and target by using a simple formula to calculate a discrimination index for each temperature of the step gradient. This optimum corresponded to the output of an independent analysis using a customized neural network program. These results together provide an experimental and analytical framework for optimizing mismatch discrimination among all probes on a DNA microarray.

Isolation and partial characterization of an antibacterial substance produced by Enterococcus faecium

A strain of Enterococcus faecium isolated from Bulgarian yellow cheese "kashkaval" produced a bacteriocin-like substance named enterococcin A 2000. The antibacterial substance had a low molar mass (< 2 kDa), was relatively stable toward heat but was sensitive to selected proteolytic enzymes. It was active against Gram-positive bacteria including enterococci, such as Listeria, Bacillus and Streptococcus, and also against Gram-negative E. coli. Production of enterococcin A 2000 has a maximum near the end of the exponential phase of producer growth. The peptide was purified by ammonium sulfate precipitation, butanol extraction, followed by cation-exchange chromatography and reversed-phase chromatography. A partial sequence of purified enterococcin A 2000 indicated that this substance does not belong to the class IIa of bacteriocins presenting the consensus anti-Listeria motif YGNGV.

Single-base-pair discrimination of terminal mismatches by using oligonucleotide microarrays and neural network analyses

The effects of single-base-pair near-terminal and terminal mismatches on the dissociation temperature (T(d)) and signal intensity of short DNA duplexes were determined by using oligonucleotide microarrays and neural network (NN) analyses. Two perfect-match probes and 29 probes having a single-base-pair mismatch at positions 1 to 5 from the 5' terminus of the probe were designed to target one of two short sequences representing 16S rRNA. Nonequilibrium dissociation rates (i.e., melting profiles) of all probe-target duplexes were determined simultaneously. Analysis of variance revealed that position of the mismatch, type of mismatch, and formamide concentration significantly affected the T(d) and signal intensity. Increasing the concentration of formamide in the washing buffer decreased the T(d) and signal intensity, and it decreased the variability of the signal. Although T(d)s of probe-target duplexes with mismatches in the first or second position were not significantly different from one another, duplexes with mismatches in the third to fifth positions had significantly lower T(d)s than those with mismatches in the first or second position. The trained NNs predicted the T(d) with high accuracies (R(2) = 0.93). However, the NNs predicted the signal intensity only moderately accurately (R(2) = 0.67), presumably due to increased noise in the signal intensity at low formamide concentrations. Sensitivity analysis revealed that the concentration of formamide explained most (75%) of the variability in T(d)s, followed by position of the mismatch (19%) and type of mismatch (6%). The results suggest that position of the mismatch at or near the 5' terminus plays a greater role in determining the T(d) and signal intensity of duplexes than the type of mismatch.

Differentiation of plasmids in marine diazotroph assemblages determined by randomly amplified polymorphic DNA analysis

Nitrogen fixation by diazotrophic bacteria is a significant source of new nitrogen in salt marsh ecosystems. Recent studies have characterized the physiological and phylogenetic diversity of oxygen-utilizing diazotrophs isolated from the rhizoplanes of spatially separated intertidal macrophyte habitats. However, there is a paucity of information regarding the traits encoded by and the diversity of plasmids occurring in this key ecological functional group. Five-hundred and twenty-one isolates cultivated from the rhizoplanes of Juncus roemarianus, Spartina patens and different growth forms (short-form and tall-form) of Spartina alterniflora were screened for the presence of plasmids. One-hundred and thirty-four diazotrophs carrying plasmids that ranged in size from 2 to >100 kbp were identified. The majority of the marine bacteria contained one plasmid. Diazotrophs from the short-form S. alterniflora rhizoplane contained significantly fewer plasmids relative to isolates from tall-form S. alterniflora, J. roemarianus and S. patens. Although some plasmids exhibited homology to a nifH gene probe, the majority of the plasmids were classified as cryptic. Two oligonucleotide primers were developed to facilitate genotypic typing of the endogenously isolated marine plasmids by the randomly amplified polymorphic DNA (RAPD)-PCR technique. These primers proved to be more effective than 21 commercially available primers tested to generate RAPD-PCR patterns. Analysis of the RAPD-PCR patterns indicated as many as 71 different plasmid genotypes occurring in diazotroph bacterial assemblages within and between the four different salt marsh grass rhizoplane habitats investigated in this study.