Characterization ofCarnobacteriumspecies by pyrolysis mass spectrometry

Effects of Sr2 + on the preparation of Escherchia coli DH5α competent cells and plasmid transformation

Bacterial gene transformation used with Escherichia coli as a desired microorganism is one of the important techniques in genetic engineering. In this study, the preparation of E. coli DH5α competent cells treated with SrCl2 and transformation by heat-shock with pUC19 plasmid was optimized by Response Surface Methodology (RSM). Other five E. coli strains including BL21 (DE3), HB-101, JM109, TOP10 and TG1, three different sizes plasmids (pUC19, pET32a, pPIC9k) were used to verify the protocol, respectively. The transformation mechanism was explored by scanning electron microscope combined with energy dispersive spectrometer (SEM-EDS), atomic absorption spectroscopy (AAS) and Fourier-transform infrared spectroscopy (FT-IR). An equation of regression model was obtained, and the ideal parameters were Sr2 + ions of 90 mM, heat-shock time of 90 s and 9 ng of plasmid. Under this conditions, the transformation efficiency could almost reach to 106 CFU/µg DNA. A small change of the cell surface structure has been observed between E. coli DH5α strain and competent cells by abovementioned spectrum technologies, which implied that a strict regulation mechanism involved in the formation of competent cells and transformation of plasmids. An equation of regression model for the competent cells preparation and plasmid transformation could be applied in gene cloning technology

Carnobacterium maltaromaticum: identification, isolation tools, ecology and technological aspects in dairy products

Carnobacterium species constitute a genus of Lactic Acid Bacteria (LAB) present in different ecological niches. The aim of this article is to summarize the knowledge about Carnobacterium maltaromaticum species at different microbiological levels such as taxonomy, isolation and identification, ecology, technological aspects and safety in dairy products. Works published during the last decade concerning C. maltaromaticum have shown that this non-starter LAB (NSLAB) could present major interests in dairy product technology. Four reasons can be mentioned: i) it can grow in milk during the ripening period with no competition with starter LAB, ii) this species synthesizes different flavouring compounds e.g., 3-methylbutanal, iii) it can inhibit the growth of foodborne pathogens as Listeria monocytogenes due to its ability to produce bacteriocins, iv) it has never been reported to be involved in human diseases as no cases of human infection have been directly linked to the consumption of dairy products containing this species.

Carnobacterium divergens and Carnobacterium maltaromaticum as spoilers or protective cultures in meat and seafood: phenotypic and genotypic characterization

Carnobacterium, a genus of lactic acid bacteria, frequently dominate the microflora of chilled vacuum- or modified atmosphere-packed meat and seafood. In this study Carnobacterium isolates were characterized by phenotypic and molecular methods in order to investigate the association of species and intra-species groups with distinct kinds of meat and seafood. Of 120 test strains, 50 originated from meat (beef and pork products, including 44 strains isolated during this study and 6 strains obtained from culture collections) and 52 from seafoods (cod, halibut, salmon, shrimps and roe products). In addition, 9 reference strains of Carnobacterium spp from other sources than meat and fish and 9 reference strains of lactic acid bacteria belonging to other genera than Carnobacterium were included. Numerical taxonomy relying on classical biochemical reactions, carbohydrate fermentation and inhibition tests (temperature, salt, pH, chemical preservatives, antibiotics, bacteriocins), SDS-PAGE electrophoresis of whole cell proteins, plasmid profiling, intergenic spacer region (ISR) analysis and examination of amplified-fragment length polymorphism (AFLP) were employed to characterize the strains. The numerical taxonomic approach divided the carnobacteria strains into 24 groups that shared less than 89% similarity. These groups were identified as Carnobacterium divergens with one major cluster (40 strains) and 7 branches of one to four strains, Carnobacterium maltaromaticum (previous C. piscicola) with one major cluster (37 strains) and 9 branches of one to four strains and Carnobacterium mobile (three branches consisting in total of 4 strains). Branches consisting of references strains of the remaining Carnobacterium spp. were separated from clusters and branches of C. divergens, C. maltaromaticum and C. mobile. Isolates from the main clusters of C. divergens and C. maltaromaticum were found both in fresh and lightly preserved meat and seafood products. High phenotypic intra-species variability was observed for C. divergens and C. maltaromaticum but despite this heterogeneity in phenotypic traits a reliable identification to species levels was obtained by SDS-PAGE electrophoresis of whole cell proteins and by ISR based on 16S-23S rDNA intergenic spacer region polymorphism. With AFLP, two distinct clusters were observed for C. divergens but only one for C. maltaromaticum. The two C. divergens clusters were not identical to any of the clusters observed by numerical taxonomy. A limited number of C. divergens and C. maltaromaticum isolates possessed a biopreservative potential due to their production of bacteriocins with a wide inhibition spectrum. This study serves as a base-line for further investigations on the potential role of species of Carnobacterium in foods where they predominate the spoilage microflora.

Characterization of Carnobacterium divergens strain 6251 isolated from intestine of Arctic charr (Salvelinus alpinus L.)

An atypical strain of Carnobacterium divergens, strain 6251, was isolated from the small intestine of Arctic charr (Salvelinus alpinus L.), fed high dietary carbohydrate. This strain showed marked growth inhibitory effects in vitro against the fish pathogens Aeromonas salmonicida subsp. salmonicida (furunculosis), Vibrio anguillarum (vibriosis) and Vibrio viscocus (winter ulcer). The strain is a non-motile Gram-positive psychrotrophic rod that lacks both catalase and oxidase, grows at pH 9.1 (CTAS agar), but not on acetate containing media (pH < or = 5.4), on TCBS or at < or =6% sodium chloride content. Strain 6251 is facultatively anaerobic and utilises tryptone as a sole source of nutrient. Further characterisation showed the most abundant cellular fatty acid of strain 6251 to be oleic acid (18:1) (n-9) (36.0%). Sequencing of a 16S rDNA region of 578 nucleotides and AFLP microbial fingerprinting suggested that strain 6251 is not closely related to any carnobacteria known, however, DNA-DNA similarity determinations showed high similarity (96.2%) with the type strain of Carnobacterium divergens. The unique phenotypic attributes of this strain represent new information on the biodiversity and ecology of carnobacteria and especially of the species C. divergens.

The differentiation of Carnobacterium divergens using the random amplification of polymorphic DNA polymerase chain reaction technique

The potential of the randomly amplified polymorphic DNA polymerase chain reaction (RAPD-PCR) technique to differentiate Carnobacterium divergens from other members of the genus Carnobacterium was examined. A numerical analysis of the genomic profiles obtained demonstrated that it was possible to differentiate the C. divergens strains from other Carnobacterium strains using this technique. The heterogeneity observed in the representatives of the species C. piscicola adds further weight to the suggestion in other taxonomic studies that subspecies of this species exist.

Curie-point pyrolysis mass spectrometry as a tool in clinical microbiology

Pyrolysis mass spectrometry is a well established analytical tool that has received a considerable boost from the development of low cost, dedicated instruments and sophisticated statistical analyses on personal computers. Further analytical developments, especially in the area of neural networks, are pushing the technology to the forefront of methods for the discrimination and identification of microorganisms and their products. The speed and reproducibility of pyrolysis mass spectrometry and its applicability to a wide range of microorganisms make it an attractive method for epidemiological studies. For inter-strain comparisons, the method is at least as discriminatory as conventional typing systems and usually gives discrimination similar to that of nucleic acid fingerprinting techniques. There has been some success in using neural networks to make identifications across pyrolysis mass spectrometric batches. Further development of methods used to handle data from multiple PyMS analyses can be expected to extend the value of pyrolysis mass spectrometry in clinical microbiology.

Pyrolysis mass spectrometry and its applications in biotechnology

Pyrolysis mass spectrometry is a rapid and high-resolution method for the analysis of otherwise non-volatile material and has been widely applied for discriminating between closely related microbial strains. Recent advances in statistical and neural network methods based on supervised learning have now permitted exploitation of pyrolysis mass spectrometry in the quantitative analysis of many diverse samples of biotechnological interest; the technique may thus be regarded as an 'anything-sensor'.

Correction of mass spectral drift using artificial neural networks

For pyrolysis mass spectrometry (PyMS) to be used for the routine identification of microorganisms, for quantifying determinands in biological and biotechnological systems, and in the production of useful mass spectral libraries, it is paramount that newly acquired spectra be compared to those previously collected. Neural network and other multivariate calibration models have been used to relate mass spectra to the biological features of interest. As commonly observed, however, mass spectral fingerprints showed a lack of long-term reproducibility, due to instrumental drift in the mass spectrometer; when identical materials were analyzed by PyMS at dates from 4 to 20 months apart, neural network models produced at earlier times could not be used to give accurate estimates of determinand concentrations or bacterial identities. Neural networks, however, can be used to correct for pyrolysis mass spectrometer instrumental drift itself, so that neural network or other multivariate calibration models created using previously collected data can be used to give accurate estimates of determinand concentration or the nature of bacteria (or, indeed, other materials) from newly acquired pyrolysis mass spectra. This approach is not limited solely to pyrolysis mass spectrometry but is generally applicable to any analytical tool which is prone to instrumental drift, such as IR, ESR, NMR and other spectroscopies, and gas and liquid chromatography, as well as other types of mass spectrometry.