1,721,049 research outputs found
Viability staining and detection of metabolic activity of sourdough lactic acid bacteria under stress conditions
No full textForty-one strains of lactic acid bacteria isolated
from wheat sourdoughs were exposed to acid, osmotic
and oxidative stresses. Live/DeadÒ BacLightTM Bacterial
Viability kit was used to assess cell viability based on
membrane integrity and the reduction of the redox dye
2-(iodophenyl)-3-(p-nitrophenyl)-5-phenyltetrazolium chlo-
ride (INT) was used to detect residual metabolic activity.
Comparison between the two different methods and plate
counts was carried out for several strains. Complete loss of
membrane integrity was observed in Lactobacillus curva-
tus strains for all treatments, while Weissella cibaria and
Leuconostoc mesenteroides presented a damaged mem-
brane only after exposure to acid stress. For most of the
strains belonging to Lb. plantarum and Lb. paraplantarum
species, a high percentage of cells conserved cell mem-
brane integrity after exposure to the different stresses,
indicating a high tolerance of all treatments. All species
were able to reduce INT after exposure to osmotic stress,
but a drastic decrease or a complete loss of cell metabolic
activity were achieved after acid and oxidative stress
treatments. Live/Dead staining is a rapid method to mon-
itor cell injury, but it does not provide a good assessment of
cell viability for all stresses. A good agreement was found
between cell viability measured by plate count and Bac-
Light staining for acid and osmotic stresses, but the latter
viability measurement method underestimated the damage
caused by oxidative stress when compared to plate count or
measurement of metabolic activity
FoodMicrobionet v4: A large, integrated, open and transparent database for food bacterial communities
No full textWith the availability of high-throughput sequencing techniques our knowledge of the structure and dynamics of food microbial communities has made a quantum leap. However, this knowledge is dispersed in a large number of papers and hard data are only partly available through powerful on-line databases and tools such as QIITA, MGnify and the Integrated Microbial Next Generation Sequencing platform, whose annotation is not optimized for foods. Here, we present the 4th iteration of FoodMicrobionet, a database of the composition of bacterial microbial communities of foods and food environments. With 180 studies and 10,151 samples belonging to 8 major food groups FoodMicrobionet 4.1.2 is arguably the largest and best annotated database on food bacterial communities. This version includes 1684 environmental samples and 8467 food samples, belonging to 16 L1 categories and 196 L6 categories of the EFSA FoodEx2 classification and is approximately 4 times larger than previous version (3.1, https://doi.org/10.1016/j.ijfoodmicro.2019.108249). As a representative case study among the many potential applications of FoodMicrobionet, we confirm that taxonomic assignment at the genus level can be performed confidently for the majority of amplicon sequence variants using the most commonly used 16S RNA gene target regions (V1-V3, V3-V4, V4), with best results with higher quality sequences and longer fragment lengths, but that care should be exercised in confirming the assignment at species level. Both FoodMicrobionet and related data and software conform to FAIR (findable, accessible, interoperable, reusable/reproducible) criteria for scientific data and software and are freely available on public repositories (GitHub, Mendeley data). Even if FoodMicrobionet does not have the sophistication of QIITA, IMNGS and MGnify, we feel that this iteration, due to its size and diversity, provides a valuable asset for both the scientific community and industrial and regulatory stakeholders
Modelling the growth of Weissella cibaria as a function of fermentation conditions
No full textAims: To investigate the effect of pH, water activity (aw) and temperature on
the growth of Weissella cibaria DBPZ1006, a lactic acid bacterium isolated from
sourdoughs.
Methods and Results: The kinetics of growth of W. cibaria DBPZ1006 was
investigated during batch fermentations as a function of pH (4Æ0–8Æ0), aw
(0Æ935–0Æ994) and temperature (10–45°C) in a rich medium. The growth curve
parameters (lag time, growth rate and asymptote) were estimated using the
dynamic model of Baranyi and Roberts (1994. A dynamic approach to predic-
ting bacterial growth in food. Int J Food Microbiol 23, 277–294). The effect of
pH, aw and temperature on maximum specific growth rate (lmax) were esti-
mated by fitting a cardinal model. lmax under optimal conditions (pH = 6Æ6,
aw = 0Æ994, T = 36Æ3°C) was estimated to be 0Æ93 h)1. Minimum and maxi-
mum estimated pH and temperature for growth were 3Æ6 and 8Æ15, and 9Æ0°C
and 47Æ8°C, respectively, while minimum aw was 0Æ918 (equivalent to 12Æ2%
w ⁄ v NaCl).
Conclusions: Weissella cibaria DBPZ1006 is a fast-growing heterofermentative
strain, which could be used in a mixed starter culture for making bread.
Significance and Impact of the Study: This is the first study reporting the
modelling of the growth of W. cibaria, a species that is increasingly being used
as a starter in sourdough and vegetable fermentations
Enzymatyc activities of lactic acid bacteria isolated from Cornetto di Matera sourdoughs
No full textUse 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
No full textConventional 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 7 × 7 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
Selection of oxidative tolerant mutants from aerobic culture of Lactobacillus plantarum C17
No full textMetataxonomic insights in the distribution of Lactobacillaceae in foods and food environments
No full text: Members of the family Lactobacillaceae, which now includes species formerly belonging to the genera Lactobacillus and Pediococcus, but also Leuconostocaceae, are of foremost importance in food fermentations and spoilage, but also as components of animal and human microbiota and as potentially pathogenic microorganisms. Knowledge of the ecological distribution of a given species and genus is important, among other things, for the inclusion in lists of microorganisms with a Qualified Presumption of Safety or with beneficial use. The objective of this work is to use the data in FoodMicrobionet database to obtain quantitative insights (in terms of both abundance and prevalence) on the distribution of these bacteria in foods and food environments. We first explored the reliability of taxonomic assignments using the SILVA v138.1 reference database with full length and partial sequences of the 16S rRNA gene for type strain sequences. Full length 16S rRNA gene sequences allow a reasonably good classification at the genus and species level in phylogenetic trees but shorter sequences (V1-V3, V3-V4, V4) perform much worse, with type strains of many species sharing identical V4 and V3-V4 sequences. Taxonomic assignment at the genus level of 16S rRNA genes sequences and the SILVA v138.1 reference database can be done for almost all genera of the family Lactobacillaceae with a high degree of confidence for full length sequences, and with a satisfactory level of accuracy for the V1-V3 regions. Results for the V3-V4 and V4 region are still acceptable but significantly worse. Taxonomic assignment at the species level for sequences for the V1-V3, V3-V4, V4 regions of the 16S rRNA gene of members of the family Lactobacillaceae is hardly possible and, even for full length sequences, and only 49.9 % of the type strain sequences can be unambiguously assigned to species. We then used the FoodMicrobionet database to evaluate the prevalence and abundance of Lactobacillaceae in food samples and in food related environments. Generalist and specialist genera were clearly evident. The ecological distribution of several genera was confirmed and insights on the distribution and potential origin of rare genera (Dellaglioa, Holzapfelia, Schleiferilactobacillus) were obtained. We also found that combining Amplicon Sequence Variants from different studies is indeed possible, but provides little additional information, even when strict criteria are used for the filtering of sequences
SDS-PAGE patterns of whole cell proteins of Streptococcus thermophilus: impact of strain, growth phase and adaptation and relationship with stress response
No full textIn previous studies we demonstrated that a relatively large diversity of stress response patterns (acid, osmotic, oxidative, heat) exists among Streptococcus thermophilus strains. Changes in protein expression, evaluated by SDS–PAGE in 4 wild strains (CNBL7035, TH681, Y3, Sfi39) and in three Sfi39 mutants in which hrcA, ctsR and rr01 genes were inactivated showed that significant variations of proteins involved in general stress response (GSR) occur as a function of growth phase, adaptation and inactivation of stress response regulators. In this work we re-evaluate the previous results comparing two unsupervised (Hierarchical Cluster Analysis, HCA, and Principal Component Analysis, PCA) and one supervised (Partial Least Square Regression, PLSR) statistical techniques for the ability to extract information from SDS–PAGE patterns of wild type and mutant strains of S. thermophilus and to uncover relationships between protein patterns and stress tolerance. HCA and PCA are two purely descriptive techniques. The HCA showed that SDS–PAGE is an efficient tool to differentiate strains but did not shed any light on the relationships between band intensity and strain, growth phase or adaptation treatment. PCA helped to identify group of bands which covaried with the stress input factors butalso not allow to find a relationship between protein expression and stress tolerance. The PLS regression, even with the limitations due to the data set used in this study, appears as an extremely promising tools for the identification of complex relationships between design and response variables in the analysis of SDS–PAGE patterns of whole cell proteins
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